An Economic Model for Identifying Drivers of Employment Growth in the Russian Arctic Regions

An Economic Model for Identifying Drivers of Employment Growth in the Russian Arctic Regions | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article An Economic Model for Identifying Drivers of Employment Growth in the Russian Arctic Regions Vladimir Myakshin This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9307352/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract In the context of the demographic stagnation and migration trends existing in the regions of the Russian Arctic, the task of enhancing the local employment systems involves identifying the economic sectors with high potential to create jobs (drivers of employment growth). This explains the relevance of this study which seeks to identify key drivers of employment in the Russian Arctic regions and proposes a hypothesis that a region’s core industry with a positive value of competitive effect (i.e. the industry enjoying favorable conditions for growth) represents a driver of employment growth. For the purposes of analyzing the employment patterns in the regions of the Russian Arctic, the study uses a methodological framework that employs shift-share analysis, a tool for measuring the effect of sets of factors (national growth effect, industrial mix effect, competitive effect) on regions’ employment dynamics, and the coefficient of localization, a measure of competitiveness and potential of an economic sector to generate jobs. The study has as its key outcome the shift share analysis-based algorithm for identifying job-generating sectors and proposes a classification of economic sectors that uses as key criterion the ratio between competitive effect and coefficient of localization. The economic sectors under analysis are classified into actual drivers of employment growth, potential drivers of employment growth, and sectors with potential to drive employment in the future. The proposed methodological approach has been validated using the case study of the economies of the Russian Arctic regions and relying on the data of the Federal State Statistics Service. Based on the proposed criteria, the economic sectors under study were analyzed for the potential to increase employment and classified accordingly. The scholarly and practical importance of the study consists in the proposed criterial framework making it possible to identify the economic sectors that are crucial to employment growth in the Russian Arctic and facilitating evidence-based employment planning. Further research on the topic might involve creating a model that would factor in the multiplier effect of inter-industry relations. regions of the Russian Arctic regional employment pattern shift-share components economic activities core sectors regional employment policy Figures Figure 1 Introduction An area’s employment rate represents an important criterion for measuring the effectiveness of its socio-economic policy. When developing the latter, the effect of any structural change should be considered also from the perspective of employment, adding to the relevance of studies into employment patterns in the regions comprising the Russian Arctic. The dual nature of employment as a phenomenon reflecting the relationship between economic and social processes (where formal employment plays the role as a resource while being the fundamental pillar of the performance potential) explains why the indicators of employment are increasingly used as basic measures of performance. From an indicator measuring the availability of labor resources, employment has evolved into a crucial factor to consider when shaping local economic policies. Together with intensity of inter-sectoral mobility of labor, the employment patterns represent a crucial factor in the social and economic growth in the Russian Artic. This study explores the sectoral employment patterns of the Russian Arctic regions from the perspective of the local economic activities that have potential to generate jobs. Previous research on the topic has employed a variety of methods to analyze and evaluate structural employment change and among them the analogy and comparison method for analyzing national and sector-specific occupational patterns [ 1 ]; the method allowing to measure change in (combined) sectoral and territorial composition of output [ 2 ]; the index method for evaluating structural change [3; 4]; statistical methods [5; 6; 7]; shift-share analysis [ 8 ]; and econometric methods of analysis [ 9 ]. Our analysis of the scientific literature [10; 11] shows that the most productive method for evaluating structural change is shift-share analysis. Employed extensively by both domestic and international researchers, this method offers increased flexibility, allowing to embrace the economic systems of all levels and a wide array of economic indicators. While the domestic structural change studies employ mostly the indicators that reflect scale or effectiveness of a particular economic sector (i.e. figures of employment, added value, turnover, profit, shipped output, and works and services performed), the researchers abroad tend to rely more on the employment indicators, which is due to their having easier access to official statistical databases. For a more comprehensive evaluation of the competitiveness and potential of the economic sector (ESs) to create jobs, the scope of indicators for measuring structural change should be added with the coefficient of localization (k L ), the latter allowing to calculate the share an ES has in the area’s growth and the relative concentration of employment across sectors at local and national levels, while also allowing to classify ESs under study based on their competitiveness and potential to increase employment [ 12 ]. The recent economic studies into structural change cover a fairly wide range of employment issues. Some studies explore structural employment change in relation to certain aspects of economic growth, proposing a structured approach to evaluating and measuring the quality of economic growth based on the indicators of structural change quality and intensity [ 13 ], others factor in the intersectoral relationships to provide quantified evaluations of the impact a structural change has on economic growth [ 14 ]; employ macroeconomic methods to demonstrate relationship between structural change and economic growth rate [ 15 ]; and offer analytic descriptions of structural change as an important factor of economic growth [ 16 ]. And yet, none of these studies address ESs as capable of increasing their potential to become core contributors to regions’ economic growth. In [ 17 ], the authors propose a toolkit for structured analysis of regional economies from the perspective of employment, exploring the effect of efforts to enhance the economic pattern on the actual employment figures but giving no attention to the role each particular ES plays towards increasing the employment figures. One important avenue is to measure the impact being sustained by regional employment patterns from a diversity of factors. The study presented in [ 18 ] compares exposures to national and regional factors to identify causal relationships within structural employment change. In [10; 19], the authors discuss the role the regional and sectoral factors play in stimulating change within employment patterns, while the study presented in [ 20 ] offers a case study of a municipal district to quantify structural employment change. These papers, however, fail to look at the potential the ESs under study offer towards higher employment rates. The studies presented in [21; 22] employ coefficients of localization to identify core (overall and locally significant) and non-core sectors in a regional economy. By comparing these sectors’ growth rates at regional and national levels, the authors group them into ‘strong’, ‘lagging’, ‘showing constrained growth’ and ‘depressed’ and, based on that, offer a number of possible action plans for industries showing different levels of competitiveness. But again, these studies fail to take into account how multiple factors and particular ESs can influence employment patterns. While the topic of structural change has drawn considerable attention in literature, its dynamics at regional level remains poorly explored, and there are very few studies aiming to identify ESs with the best potential to facilitate employment growth. In this paper we present the results of our study into the economic activities’ potential to create jobs in the Russian Arctic regions. We propose a classification of ESs that uses as underlying criterion the ratio between the coefficient of localization and the value of Regional Shift. The core sectors identified as showing high competitiveness at regional level (i.e. those with highest positive Regional Shift value) are defined as drivers of employment growth. Theory and methods In order to identify the sectors with ample potential to create jobs, the study uses a methodological framework that combines shift-share analysis [ 8 ] with the coefficient of localization 12]. Shift-share analysis allows to break down the regional variable (represented in this study by sectoral distribution of employment) into three differential components: National Share (NS), Industrial Mix (IM), and Regional Shift (RS). A change within employment pattern is represented by sum total of the three components: SS = NS + IM + RS (1) Depending on the object of analysis, each of the three components can be quantified for a particular ES or entire region (as the sum total of ESs). Since regions are parts of national systems, their development depends, to some extent, on macroeconomic factors. At the same time, as economic studies [ 23 ] note, the general growth trends may show differences at national and regional levels. As know, regions with nearly identical sectoral patterns often show different performance, and the same holds true for the performance of ESs in different regions. One method for identifying the performance variation across regional growth models is offered by shift-share analysis. All its versions rely on the same conceptual framework that uses sets of equations to express economic growth (or recession) as a function of three groups of factors (national, sectoral and regional). This study uses the traditional version of shift-share analysis developed by Daniel Creamer and formalized by Edgar S. Dunn [ 24 ], known also as the comparative static analysis [ 25 ]. It is essential that each of the shift-share components is interpreted correctly. The National Share shows to what extent a region’s employment level would increase if it grew at the same rate as the country’s overall employment. A region with no competitive advantages (i.e. disadvantaged region) is assumed to have its sectoral employment growing at a rate identical to that at national level. The Industrial Mix reflects the variation in sectoral distribution of the country and its regions. If a region shows positive cumulative IM value (calculated as the sum total of the IM values for ESs), its sectoral distribution is dominated by ESs that show higher-than-anticipated growth rate at national level. The National Share and Regional Shift depend on exogenous factors and national growth rate and do not depend on regions’ socio-economic setting. Together, these two components define the possible employment growth rate of a region, provided that the growth rates shown by this region’s ESs match those at the national level and that this region has a sectoral distribution which is identical to that at the national level. Since endogenous factors are unique in each particular region, the RS component can be viewed as a measure of competitiveness (comparative advantages) of a region with relation to its ESs. However, further research is needed to identify the region-specific factors that are responsible for RS value and to propose measures for mitigating their negative impact or enhancing positive effect. The disparity in RS values for different ESs within one region, and the interregional variation in the ES performance, is due to the combined effect of multiple factors (resource availability, institutional factors, infrastructural factors, etc.), multiplier effect, and local socio-economic policy. While being an essential part of measuring the effect of region-specific factors on sectoral employment, the analysis of structural change components is, however, not sufficient, for shift-share analysis is not without drawbacks and therefore can’t give a full picture of the impacts the particular ESs have on regions’ employment dynamics. Shift-share analysis does not allow the researcher to identify the factors that crucial to cause-and-effect relationships in each different region, but still it represents a fairly simple and useful tool for measuring the effect the three groups of factors (national, sectoral, regional) have on regional employment rates. Nor does shift-share analysis factor in the multiplier effect of the ESs or how employment rates change under the influence of their interplay; nor does it take into account the manufacturing ties, often leading to a region’s sectoral distribution being underanalyzed. One example is shipbuilding industry: the failure to factor in the direct and indirect links with shipbuilding in the prior estimations of the Manufacturing Output growth rate, has resulted in an RS value that was lower than the actual one and required to be adjusted upward. This point requires further research. Prior research [ 26 ] found that the numerical values of the three shift-share components are contingent also on the level of disaggregation. The higher the disaggregation level, the lower the value of RS (disaggregation trap). This defines the RS as dependent on the choice of the level of detail in sectoral classification. A priori there is no recommended level of disaggregation of data. Besides, disaggregating of data to a level required by the researcher may not even be possible due to limited access to the statistical data. To avoid disaggregation traps when analyzing the significance variance of the RS component, the researcher should stick in their analysis solely to one classification level (disaggregation). It should be noted that the independence (identity) of the values obtained with a particular economic model, from the disaggregation level may be an indication of this model’s insensitivity (immunity) to new data. Since shift-share analysis does not allow to factor in any of changes that may occur within a region’s industrial composition (sectoral distribution) over time, it seems expedient to use this method in combination with statistical methods for more accurate evaluation of the employment growth potential of ESs [ 27 ]. Given the interrelation between the regional industrial composition and the RS values, our further calculations required the introduction of one more criterion. This additional criterion classifies an ES as “ranking among core sectors of the region” and uses as measure the coefficients of localization (k L ) calculated for each ES under analysis. The coefficient of localization measures the relative concentration of a given industry in the economy of a given region (core sector industries have k L ≥ 1; if 0.90 < k L < 1, the industry is considered promising). There is a linear dependence between the degree of concentration of an ES in regional economy and its k L (the higher the k L , the higher the degree of concentration). The calculation of the coefficient of localization involves comparative analysis of the composition of employment at regional and national levels. The RS-to-k L ratio shows whether an ES, for the growth of which there exist favorable conditions in the region, is actually core in this given region. Table 1 The interpretations of the Regional Shift (RS) + Coefficient of Localization (k L ) of the ESs comprising the sectoral composition of regional economy Group RS + k L Interpretation Group 1 k L ≥ 1 RS > 0 The region has as core ESs those that enjoy favorable conditions existing for their growth (i.e. the region makes good use of its competitive advantages). Group 2 k L 0 The region does not have as core ESs those that enjoy favorable conditions existing for their growth (i.e. the region underuses its competitive advantages). Group 3 k L ≥ 1 RS < 0 The region has as core ESs those that suffer a lack of favorable conditions for growth (i.e. competitive advantages are missing). This can be due to these ESs being of high social or economic significance (education, healthcare, social services), otherwise the region’s policy with regard to these ESs should be deemed requiring extra funding to compensate for the lack of favorable conditions for these ESs to enjoy better growth. Group 4 k L < 1 RS < 0 The region does not have as core ESs those that suffer a lack favorable conditions for growth. Since these ESs receive less attention as least competitive, the region’s policy regarding them can be considered appropriate. *Authors’ own dataset. Thus, the criterion proposed for identifying drivers of employment growth is as follows: an ES will be considered as having a high potential to create jobs if its RS value is positive or high (as evidenced by presence in the region of competitive advantages), in which case the ES classifies also as the region’s core (its share in the sectoral composition of national economy is lower than its share in the regional economy). Consequently, these are the industries with high potential to create jobs that can be called the drivers of employment in the economies of the Russian Arctic regions. The algorithm for evaluating the potential of an ES to stimulate employment growth involves the following stages: - shift-share analysis-based identification of ESs whose growth is facilitated by regional factors (|RS| > |NS| + |IM|); - determination of the degree to which the region’s economy specializes on the ESs under analysis; k L -based quantification of relative concentration of employment in the ESs under analysis; - RS-to-k L ratio-based classification of ESs; and - identification of the drivers of employment growth based on the proposed criteria. The proposed methodological approach has been validated using the case study of the economies of the Russian Arctic regions. From the perspective of employment growth, an ES will be considered promising if it is core and if its RS value (as an indicator of presence in the region of competitive environment conducive to growth) is positive and exceeds IM and NS values. Results and discussion For the purposes of this study we made use of the data of the Russian Federal State Statistics Service that featured key socio-economic performance figures for the regions comprising the Arctic Zone of the Russian Federation. The task of identifying the sectors with high potential to create jobs involved also the analysis of structural change components. Once the structural change components have been quantified, it became possible to measure the effect of regional factors on the growth experienced by the ESs operating in the Russian Arctic regions (Table 2 ). Table 2 The sectors comprising the economies of the Russian Arctic regions: Regional Shift, 2010–2022 Economic sector Region of the Russian Arctic Murmansk Region Nenets Autonomous Area (NAA) Chukotka Autonomous Area Yamal-Nenets Autonomous Area Republic of Karelia Republic of Sakha (Yakutia) Komi Republic Arkhangelsk Region, excl. of NAA Krasnoyarsk Territory 1* -0.22 -0.16 0.27 0.87 -3.72 3.87 -8.46 0.93 -8.42 2* 2.73 -1.10 0.10 23.67 -1.59 2.12 -15.15 0.07 -3.10 3* -4.00 0.33 0.02 -1.16 -3.93 2.97 1.02 -3.53 7.85 4* 1.09 -0.25 -0.33 1.45 -1.16 0.08 -1.19 -2.31 -2.41 5* -2.65 0.11 0.08 -0.18 0.14 0.45 -1.27 -0.27 -0.13 6* -7.90 0.72 -0.22 -0.28 -1.17 19.45 -18.71 -4.82 6.18 7* -31.09 -0.31 -0.71 -3.01 -9.81 -0.82 -10.52 -22.91 -22.66 8* -12.45 -0.31 -0.90 -15.52 -12.29 -3.71 -15.80 -5.86 -21.53 9* -3.08 0.00 0.10 -0.02 1.45 0.89 0.58 -1.71 -4.33 10* -3.64 -0.11 -0.35 -1.05 -3.20 -2.17 -4.50 -4.29 -5.30 11* -5.40 -0.11 -0.22 2.39 0.92 0.40 -2.46 -1.10 -2.38 12* -0.66 0.04 0.04 3.23 -4.91 2.85 -5.96 -3.09 3.19 13* -4.11 -0.15 -0.24 1.12 -4.28 4.46 -4.09 -6.88 -1.14 14* -11.21 -0.56 -1.08 -0.48 -2.75 -4.43 -19.13 -6.45 7.86 * 1 - Agriculture, Forestry, Hunting, Fishing and Fish Farming; 2 - Mining; 3 - Manufacturing; 4 - Electricity, Gas and Steam Supply, Air Conditioning; 5 - Water Supply and Removal, Waste Management, Pollution Response; 6 - Construction; 7 - Retail and Wholesale Trade, Repair of Motor Vehicles and Motorcycles; 8 - Transportation and Warehousing; 9 - Hospitality and Catering; 10 - Information and Communication; 11 - Real Estate; 12 - Education; 13 - Healthcare and Social Services; 14 - Other. **Source: Authors’ own dataset. Let us analyze the job-generating potential of the ESs with positive RS values. A high negative value of RS does not necessarily imply that favorable environment is missing in the region or that the local socio-economic policy has been performing poorly: a decrease in the number of the employed in a particular ES may be due to wider use of labor-saving technologies [ 28 ]. The Nenets Autonomous Area and the Republic of Sakha appear to have created an environment conducive to growth of employment in Construction. The Chukotka Autonomous Area and the Republic of Karelia have experienced employment growth in Real Estate, while the conditions in the Yamal-Nenets Autonomous Area, Chukotka Autonomous Area, Republic of Sakha and Murmansk Region have been favorable for Mining. Here, the value of RS exceeds that of IM. For Manufacturing (NAA, Krasnoyarsk Territory, Chukotka Autonomous Area, Republic of Sakha), Electricity Supply, Education (YNAA), Healthcare (Republic of Sakha, YNAA) and Water Supply (Republic of Karelia, Sakha, Chukotka Autonomous Area, NAA), the positive effect of the regional factors compensates for the negative impact from the national and the sectoral ones, resulting in a slight increase (or preventing further decrease) in employment (|RS| > |NS| + |IM|). In the Republic of Sakha, Komi Republic and the Nenets Autonomous Area, the employment growth in Hospitality and Catering has been predominantly due to the positive industrial mix effect (|IM| > RS). The same holds true for Construction in the Krasnoyarsk Territory and Mining in the Chukotka Autonomous Area, Republic of Sakha, and Arkhangelsk Region. Hospitality, Construction, and Mining have a high potential for employment growth, and the policies pursued in the said regions have been effective. Our further analysis of the negative effect of regional environment on the ESs with no favorable conditions for growth has enabled the following conclusions. 15.1% of the ESs with negative RS values have been able to achieve progress mainly due to favorable Industrial Mix effect. These ESs have a lower potential for employment growth than the ESs in all other groups, with the regional factors existing for them not contributing to their growth. Still, there are industries in this group that have experienced some employment growth thanks to the industrial mix effect (|IM| > |RS| + |NS|). 47.7% of the ESs under analysis have been found to be affected negatively by the regional component, its negative effect overshadowing the positive influence of IM (|IM| < |RS| + |NS|). The sectors that have suffered most from this negative impact are Trade, Transportation and Warehousing. For the remaining 37.2% of the ESs under analysis, all shift-share components are negative. Judgements as to the effectiveness of a region’s policy and measures to include depend on which of the components is most dominant. If a reduction in employment has been mostly due to national and sectoral factors and the regional component measures a minimum negative, then the region’s employment policy should be considered relatively effective. When this factor combination is the case, a properly designed regional employment policy can lead to a decrease in negative IM and NS trends preventing growth in sectoral employment. Our analysis of the negative exposure experienced by the Russian Arctic regions from either one of the three components has enabled the following conclusions. In the Arkhangelsk Region, the reduction in the number of the employed in Manufacturing has been due to the maximum negative effect of sectoral factors, with the regional ones causing only a minor negative exposure, allowing to describe this region’s policy as relatively effective. In the Murmansk Region, Yamal-Nenets Autonomous Area and Republic of Karelia, the Manufacturing sector has experienced the maximum negative exposure from regional factors, indicating low effectiveness of the economic policies pursued in these regions. Given the nation-wide scale of the negative trends in sectoral employment, in six of the regions under analysis (the exceptions being Yamal-Nenets Autonomous Area, the Republic of Sakha, and the Krasnoyarsk Territory) the negative impact from regional factors has been the gravest for Healthcare. In five of the nine regions (the exceptions being the Republic of Sakha, Chukotka Autonomous Area, Yamal-Nenets Autonomous Area, and Arkhangelsk Region), the reduction in the number of the employed in Agriculture, Forestry, Hunting, Fishing and Fish Farming results from poorly performing policies. Here, the negative effect of regional factors has been much stronger than that of other groups of factors, increasing the urgency for a proper action plan to keep these sectors afloat. In order to identify the sectors that can drive employment growth, we extended our analysis to include the industries of specialization. To this end, for each of the sectors operating in the regions of the RF Arctic Zone we calculated coefficients of localization (Table 3 ). Table 3 The economic sectors operating in the regions of the Russian Arctic: Coefficient of localization, 2022 Economic sector Region of the Russian Arctic Murmansk Region Nenets Autonomous Area (NAA) Chukotka Autonomous Area Yamal-Nenets Autonomous Area Republic of Karelia Republic of Sakha (Yakutia) Komi Republic Arkhangelsk Region, excl. of NAA Krasnoyarsk Territory 1** 0.45 0.56 0.76 0.20 0.72 0.90 0.69 0.77 1.03* 2** 3.36* 13.91* 11.32* 13.96* 1.73* 6.60* 3.57* 0.44 1.27* 3** 0.80 0.20 0.11 0.19 0.86 0.28 0.66 1.30* 0.93 4** 2.52* 2.33* 5.96* 2.19* 1.43* 2.50* 1.92* 1.23* 1.39* 5** 1.54* 0.97 0.30 0.46 0.99 0.61 1.26* 0.78 0.97 6** 0.64 1.28* 0.58 1.74* 0.88 1.24* 0.71 0.64 0.92 7** 0.60 0.31 0.53 0.38 0.87 0.59 0.70 0.80 0.88 8** 1.19* 1.31* 0.96 1.40* 1.07* 1.11* 1.30* 1.18* 1.07* 9** 1.03* 0.61 0.68 1.00* 1.21* 0.50 0.87 1.10* 0.70 10** 0.80 0.70 0.65 0.70 0.78 0.87 0.61 0.59 0.71 11** 0.98 0.37 0.57 0.90 1.03* 0.57 1.05* 1.02* 0.89 12** 1.20* 1.29* 1.20* 0.88 1.22* 1.72* 1.40* 1.30* 1.19* 13** 1.32* 0.87 1.00* 0.70 1.27* 1.25* 1.43* 1.29* 1.15* 14** 1.26* 0.95 1.05* 0.87 1.06* 0.94 1.08* 0.99 1.07* * Core industry ** Please see the list of economic sectors under Table 2 . *** Authors’ own dataset. As can be seen from Table 3 , the regions comprising the RF Arctic Zone show nearly identical sectoral distribution patterns. This is due to these regions lying in the same geographical zone and climatic conditions. And yet, their employment patterns show some differences: in NAA, YNAA and Chukotka, the growth rates of the dominant industries are lower than nationwide, while in other regions (Republic of Karelia, Komi Republic, and Murmansk Region) the dominant industries outperform the growth at the national level. In the Arkhangelsk Region, Republic of Sakha and Krasnoyarsk Territory, the ESs with k L ≥ 1 (core industries) account for 50% of the total number of ESs. Nearly all the regions comprising the RF Arctic Zone (the exception being the Arkhangelsk Region) have among their core industries Mining, indicating an increase in their economies’ raw-material orientation and contradicting the objectives of the national strategy for regional development. The regions with highest concentration of Mining include the Yamal-Nenets Autonomous Area (k L = 13.96), Nenets Autonomous Area (k L = 13.91) and Chukotka Autonomous Area (k L = 11.32). Further, as our analysis of the data presented in Table 3 shows, in all the regions of the RF Arctic Zone the employment in Electricity Supply significantly exceeds the national figure, allowing us to classify this sector as core. The highest concentration of Electricity Supply is found in Chukotka Autonomous Area (k L = 5.96) and the lowest one in the Arkhangelsk Region (k L = 1.23). In the remaining regions, this sector’s coefficient of localization ranges between 1.4 and 2.5. Another economic sector identified as core in all the regions of the Russian Arctic (with the exception of the Chukotka Autonomous Area) is Transportation and Warehousing. This is due to these regions lying far from the central part of the country and the challenging operation and maintenance of the local infrastructures, roads and waterways. The concentration of Transportation and Warehousing does not exceed 1.4. Other sectors identified as core in the regions under analysis include Education (except for the Yamal-Nenets Autonomous Area) and Healthcare (except for the Nenets and Yamal-Nenets Autonomous Areas), indicating a sufficient level of development of their social services sectors, even though the concentration of Education and Healthcare stands here at fairly low levels (k L under 1.4). Other Sectors classify as core in five regions of the Russian Arctic (their concentration low) and can be described as having a good potential in four (k L ranging between 0.90 and 1.00), evidencing good dynamic in management and institutional development. Four Russian Arctic regions have been found to have among their core sectors Hospitality and Catering. This is due to the rotation team method of labor provision (YNAA) and the multiplier effect of tourism (Republic of Karelia, Murmansk Region, and Arkhangelsk Regions). To identify the economic sectors with most favorable effect on the employment rates in the economies of the Russian Arctic regions, our analysis further involved the calculation of the RS-to-k L ratios. Based on the classification criteria presented in Table 1 , the ESs under analysis have been classified into four groups representing the sectoral patterns of the regions of the Russian Arctic (Table 4 ). Table 4 The classification groups of economic sectors comprising the economies of the Russian Arctic regions, 2022 Economic sector Region of the Russian Arctic Murmansk Region Nenets Autonomous Area Chukotka Autonomous Area Yamal-Nenets Autonomous Area Arkhangelsk Region excl. of NAA Krasnoyarsk Territory Republic of Karelia Republic of Sakha (Yakutia) Komi Republic 1* 4 4 2 2 2 3 4 2 4 2* 1 3 1 1 2 3 3 1 3 3* 4 2 2 4 3 2 4 2 2 4* 1 3 3 1 3 3 3 1 3 5* 3 2 2 4 4 4 2 2 3 6* 4 1 4 3 4 2 4 1 4 7* 4 4 4 4 4 4 4 4 4 8* 3 3 4 3 3 3 3 3 3 9* 3 2 2 3 3 4 1 2 2 10* 4 4 4 4 4 4 4 4 4 11* 4 4 4 2 3 4 1 2 3 12* 3 1 1 2 3 1 3 1 3 13* 3 4 4 2 3 3 3 1 3 14* 3 4 3 4 4 1 3 4 3 * Please see the list of economic sectors under Table 2 . ** Authors’ own dataset. The ESs identified as drivers of employment growth, i.e. those with positive RS values, comprise Groups 1 and 2. Group 1 (the actual drivers of employment growth) consists of the ESs for which the regional component of structural change has been positive, suggesting there exist some favorable local factors that give these sectors a competitive advantage and that this competitive advantage is taken due account of in the regional employment policy (the ESs in Group 1 are currently core in the regions under analysis) (RS > 0, k L ≥ 1). It follows from Table 5 that the employment growth is driven in the Russian Arctic regions predominantly by Mining and Electricity (Republic of Sakha, Murmansk Region, Yamal-Nenets Autonomous Area, Chukotka Autonomous Area), Education (Republic of Sakha, Krasnoyarsk Territory, Chukotka Autonomous Area, Nenets Autonomous Area), Construction (Nenets Autonomous Area, Republic of Sakha), Real Estate and Hospitality & Catering (Republic of Karelia), Healthcare and Social Services (Republic of Sakha), and Other Sectors (Krasnoyarsk Territory). Group 2 (the potential drivers of employment growth) consists of the ESs for which the regional component has been positive (RS > 0) but the factors conducive to their further growth are not being taken full advantage of in the regional employment policy. The ESs in this group are not currently core (k L < 1). Manufacturing represents a potential driver of employment in five regions of the Russian Arctic; Agriculture, Forestry, Hunting, Fishing and Fish Farming, Hospitality and Catering, and Water Supply in four; Real Estate in two; and Education, Healthcare and Mining in one. Notably, some of the economic sectors in Group 2 – Real Estate in the Yamal-Nenets Autonomous Area; Construction and Manufacturing in Krasnoyarsk Territory; Agriculture, Forestry, Hunting, Fishing and Fish Farming in the Republic of Sakha; and Water Supply in the Republic of Karelia and Nenets Autonomous Area – have good potential to become core in the regions under study and reclassify as Group 1, provided there is an adequate action plan to support them. Group 3 and Group 4 include ESs that cannot be described as driving the employment growth at this stage of the Russian Arctic regions’ economic development (RS < 0; the regional conditions are rather hindering than promoting further development) but are seen as capable of creating jobs in the long run. As the regions under study progress in their development and the market achieves a more robust level of self-regulation, there can arise factors conducive to better growth within the ESs in Group 3 and 4. Group 3 consists of economic sectors that are core in regional economies (k L ≥ 1) even in the absence of competitive advantages for their growth. The ESs in this group have a lower potential to create jobs than the other groups, showing growth mostly when under favorable conditions. Also, the ESs of Group 3 classify as highly significant for regional development from social (Healthcare, Education) and economic (Transportation and Warehousing, Electricity, Gas and Steam) perspectives, requiring from regions extra funds to support their development. There are sectors in this group that have shown an increase in their employment size as a result of increased competitiveness. These include Construction (Yamal-Nenets Autonomous Area), Transportation and Warehousing (Yamal-Nenets Autonomous Area, Republics of Karelia, Sakha (Yakutia), Arkhangelsk Region), and Hospitality and Catering (Arkhangelsk Region, Yamal-Nenets Autonomous Area). Provided there’s a proper regional strategy for stimulating growth within these sectors, they may be likely to reclassify to a higher group. Group 4 includes the non-core sectors (k L < 1) of the economies of the regions under study. While the employment size of the ESs in this group is being affected negatively by the regional factors (RS < 0), some of them, provided there is a favorable IM effect that can neutralize the negative exposure from the regional factors, can be regarded as potentially capable of increasing the employment and therefore likely to reclassify as promising areas of specializations. These include Hospitality & Catering, Water Supply (Krasnoyarsk Territory), Information and Communications (Republic of Sakha, NAA), Construction (Republic of Karelia), Other Sectors (Republic of Sakha, Arkhangelsk Region, NAA, YNAA). It is essential that these economic sectors receive regional support to neutralize the negative effect of adverse factors. Table 5 The classification groups of drivers of employment growth in the Russian Arctic regions based on the Regional Shift (RS)-to-Coefficient of Localization (kL) ratios, 2022 Driver of employment growth? Classification group RS-to-kL ratio Economic sectors Regions of the Russian Arctic Murmansk NAA Chukotka YNAA Karelia Sakha Komi Arkhangelsk Krasnoyarsk Yes Actual driver of employment growth Group 1 RS > 0 k L ≥ 1 2, 3 2, 12 2, 13 2, 4 9, 11 2, 4, 6, 12, 13 4, 6 12, 14 Potential driver of employment growth Group 2 RS > 0 k L < 1 3, 5, 9 1, 5, 9 1, 11, 12, 13 5 1, 3, 5, 9, 11 3, 5, 9 1, 2 3, 6 No Sector with potential to increase employment in the future Group 3 RS < 0 k L ≥ 1 5, 8, 9, 12, 13, 14 2, 4, 8 3, 14 6, 8, 9 2, 4, 6, 8, 12, 13, 14 8 2, 8, 11, 12, 13, 14 3, 4, 8, 9, 11, 12, 13 1, 2, 4, 8, 13 Group 4 RS < 0 k L < 1 1, 3, 6, 7, 10, 11 1, 7, 10, 11, 13, 14 6, 7, 8, 10, 11, 13 3, 5, 7, 10, 14 1, 3, 6, 7, 10 7, 10, 14 1, 7, 10 5, 6, 7, 4, 14 5, 7, 9, 10, 11 * Please see the list of economic sectors under Table 2 . ** Authors’ own dataset. One parameter to factor in when determining the potential of an economic sector (ES) to create jobs is the variation over time in the employment volume of the sectors comprising the economy of a given area, necessitating the use of the statistical methods in structural change analysis. The extent to which an ES can affect employment levels is contingent on the concentration of the number of people employed in this ES. This necessitates the introduction into our analysis of three additional criteria allowing to identify ES as a key driver of employment, if: 1) its share in the regional employment pattern measures (close to) highest; 2) it has its share growing at a faster pace mainly thanks to its increasing number of the employed; and 3) its contribution to the variations within the regional employment pattern is significant or (close to) highest. From the standpoint of mathematical logic, one can distinguish two fundamental approaches to measuring the variations in the employment volume of a given ES, allowing the use of two indicator systems: Absolute indicators. These represent the difference in the elements within the aggregates under analysis and include the ES’s employment volume variation, calculated as the difference of the employment volume in the current year and that in the reference year; and the structural change mass, calculated as the difference in the ES’s shares in the regional employment pattern in the current and the reference years; Relative indicators. These express relations among the elements of the aggregates under analysis and include the rate of the employment growth and increment within particular ESs and economy at large, calculated as the ratio between the number of the employed in current year and that in reference year and as the ratio between the difference of the employed in sector i in current and reference years and the total number of the employed in the reference year, respectively; the contribution of the ES to variations in the number of the employed, calculated as the ratio between the absolute value of structural change mass in sector i and the sum total of the absolute values of structural changes across the region’s entire set of the ESs; and the share of the sector i employment volume in the regional employment pattern. The indicators that build on the first approach (i.e. the absolute indicators) carry less information. This is due to the fact that they can only be measured for absolute parts of the aggregates being compared, i.e. the elements in use must be homogeneous and commensurate, and, secondly, the value of absolute indicators depends on that of the variable under study (in our case, the ES’s number of the employed). Therefore, in order to expand the analytical capacity of the indicator system in use, the absolute indicators should be supplemented with relative ones. The system of statistical indicators for measuring the extent to which ESs can affect the variations within regional employment patterns, which is based on the proposed criteria, is presented in Table 6 . Table 6 – The system of statistical indicators for measuring the extent to which ESs affect variations within regional employment patterns. (Author’s own development) Criterion Indicator Formalized mathematical expression Calculation method Economic meaning Informational value of indicator (Сlose to) highest share in the regional employment pattern Share of the ES’s employment volume in the total number of the employed in regional economy \(\:{F}_{i}=\frac{{Ч}_{i}}{\sum\:_{i=1}^{n}{Ч}_{i}}100\:\%\) Ratio of the ES’s employment volume to the total number of the employed in regional economy Describes the region’s sectoral employment Allows share-based ranking of the ES in the region’s employment scorecard Outrunning growth of the ES’s share in the regional employment pattern Structural change mass in the ES employment volume \(\:{m}_{i}={F}_{ti}-{F}_{oi}\) Difference between the share in the employment volume of current year and that of reference year Describes the variation in the share of the ES’s number of the employed in the region’s total employment Shows the dynamics of the share of the ES’s number of the employed in the regional employment pattern Significant contribution of the ES to variations within regional employment pattern Contribution of the ES to variations within regional employment pattern \(\:V=\frac{\left|{m}_{i}\right|}{\sum\:_{i=1}^{n}\left|{m}_{i}\right|}\) Ratio of the absolute value of structural change mass in the ES employment volume to the sum total of the absolute values of structural change across the region’s entire set of the ESs Describes the share of the ES’s employment volume absolute variation in the sum total of the absolute variation within the regional employment pattern Shows the extent of the ES’s impact on the regional employment pattern The results of our analysis into the 2010–2022 dynamics of the Russian Arctic regions’ sectoral employment are presented in Table 7 . The regions that experienced employment growth during the said period are two – the Yamal-Nenets Autonomous Area, which shows a 7.3% increase, contributed mostly by the sectors of Mining (4.6%), Hospitality and Catering (23.9%), and Real Estate (36.1%); and the Republic of Sakha (Yakutia), which shows a 6.0% increase, contributed mostly by the sectors of Construction (60.2%), Mining (14.9%), and Other (10.0%). Seven regions suffered a decrease in their number of the employed, with the largest decline seen in the Komi Republic (a 21.9% decline), where the most affected industries include Forestry, Hunting, Fishing and Fish Farming (a 51.8% decline), Other (a 20.4% decline), Construction (a 40.0% decline); Murmansk Region (a 18.4% decrease), where the most affected industries include Trade (a 41.7% decline), Other (a 11.9% decline), Transportation and Warehousing (a 18.2% decline); and the Republic of Karelia (a 14.8% decline), its most affected industries including Agriculture, Forestry, Hunting, Fishing and Fish Farming (a 43.7% decline), Transportation and Warehousing (a 26.6% decline), and Education (a 25.5% decline). Our analysis of the Russian Arctic regions’ employment dynamics enables the following conclusions. Hospitality and Catering has shown growth in eight of the nine regions (the exception being Murmansk), which may have been caused by the expanding tourism, on the one hand, and the wider use of rotational shiftwork, on the other hand, evidencing that these eight regions have been successful keeping their tertiary sector in line with global trends. Mining has shown growth in five regions (Arkhangelsk Region, Murmansk Region, Yamal-Nenets Autonomous Area, Chukotka Autonomous Area, and the Republic of Sakha), reaching higher sustainability also in Krasnoyarsk Territory. Its growth, however, is accompanied by reducing levels of employment in Manufacturing (the exceptions being the Nenets Autonomous Area and the Republic of Sakha), evidencing a structural disparity in the economies of the Russian Arctic regions as a result of their strong focus on extractive industries. Construction has shown growth in five regions – thanks to the successful implementation in the Russian Arctic of a number of major national projects – and a slight decrease in four (with the exception of the Komi Republic). One of the key reasons for the reduction in the Russian Arctic regions’ volume of employment is shortage of personnel, which, in turn, is contributed by harsh natural and climatic conditions, remoteness from the central parts of Russia, underdeveloped infrastructure, and challenges faced by social services sector. Here, the decline in sectoral employment results not only from the decline in total employment but also from the specific nature of particular industries. One example is Trade (except in the Republic of Sakha), where digital transformation in business management, commerce, and information and communications (except in the Yamal-Nenets Autonomous Area) has led to wider use of online mode of operations. Another example is Education. In almost all the regions of the Russian Arctic (the exception being the Yamal-Nenets Autonomous Area), this sector faces a negative demographic trend (declining numbers of students) and teachers’ conscious choice to work extra hours to earn income through private tutoring. Likewise, the staff shortage has been exacerbated in Healthcare – by the internal processes designed to optimize this sector. Table 7 – The 2010–2022 dynamics in the Russian Arctic regions’ sectoral employment. (Authors’ own calculations) Economic sector Komi Republic Republic of Karelia Nenets Autonomous Area (NAA) Arkhangelsk Region, excl. of NAA Murmansk Region Yamal-Nenets Autonomous Area Krasnoyarsk Territory Republic of Sakha (Yakutia) Chukotka Autonomous Area 2010 2022 ∆Чi 2010 2022 ∆Чi 2010 2022 ∆Чi 2010 2022 ∆Чi 2010 2022 ∆Чi 2010 2022 ∆Чi 2010 2022 ∆Чi 2010 2022 ∆Чi 2010 2022 ∆Чi employees (K) employees (K) employees (K) employees (K) employees (K) employees (K) employees (K) employees (K) employees (K) employees (K) employees (K) employees (K) employees (K) employees (K) employees (K) employees (K) employees (K) employees (K) employees (K) employees (K) employees (K) employees (K) employees (K) employees (K) employees (K) employees (K) employees (K) Agriculture, Forestry, Hunting, Fishing and Fish Farming 33 15.9 -17.10 21.3 12 -9.30 1.7 1.1 -0.60 30.3 23.3 -7.00 13.3 9.6 -3.70 6 5.3 -0.70 132.5 89.4 -43.10 33.5 28.6 -4.90 1.8 1.6 -0.20 Mining 33.7 22.1 -11.60 8.4 7.7 -0.70 7.6 7.3 -0.30 3.1 3.5 0.40 14.9 19.2 4.30 66.7 97.4 30.70 29.4 29.4 0.00 49.1 56.4 7.30 5.7 6.4 0.70 Manufacturing 34.7 34 -0.70 37.7 31.9 -5.80 0.6 0.9 0.30 96 87.7 -8.30 44.3 38.1 -6.20 12.8 11 -1.80 182.2 181 -1.20 17.6 19.7 2.10 0.5 0.5 0.00 Electricity, Gas and Steam Supply, Air Conditioning 18 15.5 -2.50 10.2 8.3 -1.90 2 1.6 -0.40 16.4 12.9 -3.50 19.1 18.8 -0.30 20 20 0.00 48 42.1 -5.90 30 27.9 -2.10 5.1 4.4 -0.70 Water Supply and Removal, Waste Management, Pollution Response 6.2 4.6 -1.60 2.6 2.6 0.00 0.2 0.3 0.10 4.2 3.7 -0.50 8.3 5.2 -3.10 2.2 1.9 -0.30 14.2 13.3 -0.90 2.8 3.1 0.30 0.02 0.1 0.08 Construction 40.2 24.1 -16.10 21.2 21.4 0.20 2.8 3.7 0.90 31.2 28.4 -2.80 26.2 20 -6.20 62.9 66.7 3.80 103.7 116.6 12.90 36.2 58 21.80 1.9 1.8 -0.10 Retail and Wholesale Trade, Repair of Motor Vehicles and Motorcycles 55.6 48.2 -7.40 50 43 -7.00 2 1.8 -0.20 89.3 71.4 -17.90 65.7 38.3 -27.40 30.5 29.2 -1.30 236.1 226.7 -9.40 53.8 56 2.20 3.8 3.3 -0.50 Transportation and Warehousing 48.4 38.8 -9.60 31.2 22.9 -8.30 3.2 3.3 0.10 45.8 45.8 0.00 40.2 32.9 -7.30 55.6 47.2 -8.40 125.2 119.7 -5.50 43.8 45.7 1.90 3.1 2.6 -0.50 Hospitality and Catering 6.3 8.4 2.10 5.6 8.4 2.80 0.4 0.5 0.10 12.5 13.8 1.30 9.9 9.2 -0.70 8.8 10.9 2.10 23.8 25.2 1.40 4.6 6.6 2.00 0.4 0.6 0.20 Information and Communication 7.9 5.1 -2.80 6.5 4.7 -1.80 0.5 0.5 0.00 8.8 6.4 -2.40 8.1 6.2 -1.90 6.3 6.6 0.30 22.8 22.4 -0.40 10.1 10.1 0.00 0.7 0.5 -0.20 Real Estate 12.2 10.1 -2.10 6 7.1 1.10 0.4 0.3 -0.10 13.5 12.8 -0.70 13.7 8.7 -5.00 7.2 9.8 2.60 33.6 32.2 -1.40 7 7.6 0.60 0.7 0.5 -0.20 Education 49.3 38.3 -11.00 32.2 24 -8.20 3.3 3 -0.30 54.9 46.2 -8.70 34.6 30.4 -4.20 26.7 27.2 0.50 131.9 121.6 -10.30 69 64.8 -4.20 3.3 3 -0.30 Healthcare and Social Services 37.8 32.8 -5.00 25.8 20.9 -4.90 1.9 1.7 -0.20 46.7 38.7 -8.00 33 28.1 -4.90 17.4 18.1 0.70 102.8 99.2 -3.60 36 39.6 3.60 2.4 2.1 -0.30 Other 89.1 70.9 -18.20 52.1 49.9 -2.20 5.8 5.3 -0.50 90.4 84.9 -5.50 86.6 76.3 -10.30 64.6 64.8 0.20 251.7 262.2 10.50 88.7 85.2 -3.50 7.3 6.3 -1.00 Total employment: 472.40 368.80 -103.60 310.80 264.80 -46.00 32.40 31.30 -1.10 543.10 479.50 -63.60 417.90 341.00 -76.90 387.70 416.10 28.40 1 437.90 1 381.00 -56.90 482.20 509.30 27.10 36.72 33.70 -3.02 Agriculture, Forestry, Hunting, Fishing and Fish Farming has experienced a reduction in its number of the employed in all the regions of the Russian Arctic, evidencing further increase in technological effectiveness as primary production is losing its share. Using the first of our proposed criteria, we have identified the economic sectors with the highest share in the regional employment pattern (i.e. the sectors that rank first, second and third in the sectors scorecard) (Table 8 ). One such sector, ranking in top positions in all the Russian Arctic regions, is Other. In seven of the nine regions (the exceptions being the Nenets Autonomous Area and the Yamal-Nenets Autonomous Area), the sector with significant (between 16.00% and 9.79%) share in the regional employment pattern is Trade. Five regions (Republic of Karelia, Komi Republic, Arkhangelsk, Murmansk, and Krasnoyarsk Territory) have among their highest-scoring sectors Manufacturing (18.90% to 9.22% share), four Mining (Nenets Autonomous Area – 23.32%, Yamal-Nenets Autonomous Area – 23.41%, Chukotka Autonomous District – 18.99%, Republic of Sakha – 11.07%), and three (Nenets Autonomous Area, Yamal-Nenets Autonomous Area, and Republic of Sakha) Construction (16.03% to 11.39% share). Transportation and Warehousing occupies middle-ranking positions (4–6) in the sector scorecards of almost all the Russian Arctic regions (with the exception of the Komi Republic), its share varying between 11.34% (Yamal-Nenets Autonomous Area) and 7.72% (Chukotka Autonomous Area). The percentage of people employed in Agriculture, Forestry, Hunting, Fishing and Fish Farming varies between 6.47% (Krasnoyarsk Territory) and 1.27% (Yamal-Nenets Autonomous Area), in Electricity and Steam Supply from 13.06% (Chukotka Autonomous Area) to 2.6% (Arkhangelsk Region), and in Healthcare from 8.89% (Komi Republic) to 4.35% (Yamal-Nenets Autonomous Area). Table 8 – The percentage of people employed in sectors comprising the economies of the Russian Arctic regions, 2022. (Authors’ own calculations) Republic of Karelia Komi Republic Nenets Autonomous Area Arkhangelsk Region, excl. of NAA Murmansk Region Yamal-Nenets Autonomous Area Krasnoyarsk Territory Republic of Sakha (Yakutia) Chukotka Autonomous Area Percentage of employed, F, % F-ranking Percentage of employed, F, % F-ranking Percentage of employed, F, % F-ranking Percentage of employed, F, % F-ranking Percentage of employed, F, % F-ranking Percentage of employed, F, % F-ranking Percentage of employed, F, % F-ranking Percentage of employed, F, % F-ranking Percentage of employed, F, % F-ranking Agriculture, Forestry, Hunting, Fishing and Fish Farming 4.53% 8 4.31% 9 3.51% 9 4.86% 8 2.82% 10 1.27% 13 6.47% 8 5.62% 8 4.75% 9 Mining 2.91% 11 5.99% 8 23.32% 1 0.73% 14 5.63% 8 23.41% 1 2.13% 11 11.07% 4 18.99% 1 Manufacturing 12.05% 3 9.22% 5 2.88% 10 18.29% 1 11.17% 3 2.64% 9 13.11% 3 3.87% 10 1.48% 11 Electricity, Gas and Steam Supply, Air Conditioning 3.13% 10 4.20% 10 5.11% 8 2.69% 10 5.51% 9 4.81% 7 3.05% 9 5.48% 9 13.06% 3 Water Supply and Removal, Waste Management, Pollution Response 0.98% 14 1.25% 14 0.96% 13 0.77% 13 1.52% 14 0.46% 14 0.96% 14 0.61% 14 0.30% 14 Construction 8.08% 6 6.53% 7 11.82% 3 5.92% 7 5.87% 7 16.03% 2 8.44% 6 11.39% 3 5.34% 8 Retail and Wholesale Trade, Repair of Motor Vehicles and Motorcycles 16.24% 2 13.07% 2 5.75% 6 14.89% 3 11.23% 2 7.02% 5 16.42% 2 11.00% 5 9.79% 4 Transportation & Warehousing 8.65% 5 10.52% 3 10.54% 4 9.55% 5 9.65% 4 11.34% 4 8.67% 5 8.97% 6 7.72% 6 Hospitality & Catering 3.17% 9 2.28% 12 1.60% 11 2.88% 9 2.70% 11 2.62% 10 1.82% 12 1.30% 13 1.78% 10 Information & Communication 1.77% 13 1.38% 13 1.60% 11 1.33% 12 1.82% 13 1.59% 12 1.62% 13 1.98% 11 1.48% 11 Real Estate 2.68% 12 2.74% 11 0.96% 13 2.67% 11 2.55% 12 2.36% 11 2.33% 10 1.49% 12 1.48% 11 Education 9.06% 4 10.39% 4 9.58% 5 9.64% 4 8.91% 5 6.54% 6 8.81% 4 12.72% 2 8.90% 5 Healthcare and Social Services 7.89% 7 8.89% 6 5.43% 7 8.07% 6 8.24% 6 4.35% 8 7.18% 7 7.78% 7 6.23% 7 Other 18.84% 1 19.22% 1 16.93% 2 17.71% 2 22.38% 1 15.57% 3 18.99% 1 16.73% 1 18.69% 2 Total 100.00% - 100.00% - 100.00% - 100.00% - 100.00% - 100.00% - 100.00% - 100.00% - 100.00% - The sectors in the last (12–14) positions of the sector scorecards are defined as enjoying the lowest share in the regional employment patterns. The percentage of people employed in Water Supply and Removal, Waste Management & Pollution Response stands at 1.50%, in Information and Communications at 2.00% (due to the specific nature of this sector), in Real Estate and Hospitality & Catering at 3.00% (with the exception of the Republic of Karelia). Let us analyze the sectoral employment dynamics based on the structural change mass over 2010–2022 (Table 9 ). The structural change mass (m i ) is positive if the rate of variation within the number of the employed in sector i exceeds that measured for the aggregate employment of a region’s sectoral composition. Hospitality & Catering has shown a positive structural change mass in all the regions of the Russian Arctic. Mining has done so in seven regions of the nine (the exceptions being the Komi Republic and the Nenets Autonomous Area; Construction in six (the exceptions being the Komi Republic, Yamal-Nenets Autonomous Area, and Murmansk Region); Other, and Real Estate in five. In the Yamal-Nenets Autonomous Area, Chukotka Autonomous Area, and Murmansk Region, the structural change mass has been highest for Mining (6.20%, 3.47% and 2.07%, respectively); in the Republic of Sakha and the Nenets Autonomous Area for Construction (3.88% and 3.18%, respectively); in the Republic of Karelia and Krasnoyarsk Territory for Other (2.08% and 1.48%, respectively); in the Komi Republic for Manufacturing (1.87%); and in the Arkhangelsk Region for Transportation and Warehousing (1.12%). All the regions of the Russian Arctic have shown a decrease in the number of the employed in Agriculture, Hunting, Fishing and Fish Farming (amounting to more than 2.00% in the Krasnoyarsk Territory, Republic of Karelia, and Komi Republic) and Trade (with the exception of the Komi Republic and the Krasnoyarsk Territory), these two sectors suffering the highest reduction in the Murmansk Region (-4.49%); a reduction of 1.00% was measured for Electricity (except in the Komi Republic and the Murmansk Region) and Information & Communication (except in the Nenets Autonomous Area and the Krasnoyarsk Territory); Education has seen the highest reduction in the number of he employed in the Republic of Karelia (by 1.30%) and the Republic of Sakha (by 1.59%). Any variation in the number of people employed in a region’s economy depends, on the one hand, on the employment dynamics within sector i and, on the other hand, on the dynamics in the region’s total employment. Our analysis of the influence a region’s total employment has on the dynamics of employment in sector i enables a conclusion that there exists a relation between the extent of influence and the direction of the variation. Where total employment and sectoral employment show changes that are co-directional (i.e. they both show growth or decline), the share of sector i is unlikely to show any pronounced variation. From this perspective, if a decrease in the number of people employed in sector i is concurrent with a decrease in the region’s total employment, then the resultant dynamics are likely to reach a plateau or even show a slight increase. Likewise, an increase in the number of the employed in sector i can be partly made up by an increase in total employment, resulting in a slight decrease in structural change mass. Conversely, if a variation in region’s sector i employment is counter-directional with that in region’s total employment (i.e. one shows increase and the other decrease), then the employment dynamics of sector i will be intensified by the overall increase (decrease) in the region’s total employment. If a variation in sector i employment occurs amid some minor fluctuations (both in magnitude and direction) in the region’s total employment, then the structural change mass will be determined by the nature of the variation within sector i . For the purpose of identifying the ESs that gain share in the regional economy mostly through increase in their employment, we have performed a factor analysis of structural change mass. By looking into how the share of sector i changes in response to variations in its employment volume, it became possible to identify those ESs that owe their share gain to technological or institutional progress, with the variation in the region’s total employment causing only a minor influence. As can be seen from Table 10 , these ESs include Hospitality & Catering (in all the Russian Arctic regions except Murmansk), Mining (in 5 regions – Arkhangelsk, Murmansk, Chukotka Autonomous Area, Yamal-Nenets Autonomous Area, Republic of Sakha), Construction (in 3 regions – Nenets Autonomous Area, Krasnoyarsk Territory, Republic of Sakha), Water Supply (in 3 regions – Nenets Autonomous Area, Chukotka Autonomous Area, Republic of Sakha), Real Estate (in 3 regions – Yamal-Nenets Autonomous Area, Republic of Sakha, Republic of Karelia), Manufacturing (in 2 regions – Nenets Autonomous Area, and Republic of Sakha), Transportation and Warehousing (in NAO), Healthcare (in the Republic of Sakha), and Other (in the Krasnoyarsk Territory). For the remaining ESs, the share gain (i.e. the positive value of structural change mass) results mainly from the decrease in region’s total employment. Table 9 – The 2010–2022 dynamics in the employment volumes of the sectors comprising the economies of the Russian Arctic regions. (Authors’ own calculations) Sectoral employment: structural change mass, % Republic of Karelia Komi Republic Nenets Autonomous Area Arkhangelsk Region, excl. of NAA Murmansk Region Yamal-Nenets Autonomous Area Krasnoyarsk Territory Republic of Sakha (Yakutia) Chukotka Autonomous Area m, % ∆m, % m, % ∆m, % m, % ∆m, % m, % ∆m, % m, % ∆m, % m, % ∆m, % m, % ∆m, % m, % ∆m, % m, % ∆m, % Agriculture, Forestry, Hunting, Fishing and Fish Farming -2.32 -2.99 -2.67 -3.62 -1.73 -1.85 -0.72 -1.29 -0.37 -0.89 -0.27 -0.18 -2.74 -3.00 -1.33 -1.02 -0.15 -0.54* Mining 0.21 -0.23 -1.14 -2.46 -0.13 -0.93 0.16 0.07* 2.07 1.03* 6.20 7.92* 0.08 0.00 0.89 1.51* 3.47 1.91 Manufacturing -0.08 -1.87 1.87 -0.15 1.02 0.93* 0.61 -1.53 0.57 -1.48 -0.66 -0.46 0.44 -0.08 0.22 0.44* 0.12 0.00 Electricity, Gas and Steam Supply, Air Conditioning -0.15 -0.61 0.39 -0.53 -1.06 -1.23 -0.33 -0.64 0.94 -0.07 -0.35 0.00 -0.29 -0.41 -0.74 -0.44 -0.83 -1.91 Water Supply and Removal, Waste Management, Pollution Response 0.15 0.00 -0.07 -0.34 0.34 0.31 0.00 -0.09 -0.46 -0.74 -0.11 -0.08 -0.02 -0.06 0.03 0.06* 0.24 0.22* Construction 1.26 0.06 -1.98 -3.41 3.18 2.78* 0.18 -0.52 -0.40 -1.48 -0.19 0.98 1.23 0.90* 3.88 4.52* 0.17 -0.27 Retail and Wholesale Trade, Repair of Motor Vehicles and Motorcycles 0.15 -2.25 1.30 -1.57 -0.42 -0.62 -1.55 -3.30 -4.49 -6.56 -0.85 -0.34 0.00 -0.65 -0.16 0.46 -0.56 -1.36 Transportation & Warehousing -1.39 -2.67 0.28 -2.03 0.67 0.31* 1.12 0.00 0.03 -1.75 -3.00 -2.17 -0.04 -0.38 -0.11 0.39 -0.73 -1.36 Hospitality & Catering 1.37 0.90* 0.94 0.44* 0.36 0.31* 0.58 0.24* 0.33 -0.17 0.35 0.54* 0.17 0.10* 0.34 0.41* 0.69 0.54* Information & Communication -0.32 -0.58 -0.29 -0.59 0.05 0.00 -0.29 -0.44 -0.12 -0.45 -0.04 0.08 0.04 -0.03 -0.11 0.00 -0.42 -0.54 Real Estate 0.75 0.35 0.16 -0.44 -0.28 -0.31 0.18 -0.13 -0.73 -1.20 0.50 0.67* -0.01 -0.10 0.04 0.12* -0.42 -0.54 Education -1.30 -2.64 -0.05 -2.33 -0.60 -0.93 -0.47 -1.60 0.64 -1.01 -0.35 0.13 -0.37 -0.72 -1.59 -0.87 -0.08 -0.82 Healthcare & Social Services -0.41 -1.58 0.89 -1.06 -0.43 -0.62 -0.53 -1.47 0.34 -1.17 -0.14 0.18 0.03 -0.25 0.31 0.75* -0.30 -0.82 Other 2.08 -0.71 0.36 -3.85 -0.97 -1.54 1.06 -1.01 1.65 -2.46 -1.09 0.05 1.48 0.73* -1.67 -0.73 -1.19 -2.72 Total 0.00 -14.80 0.00 -21.93 0.00 -3.40 0.00 -11.71 0.00 -18.40 0.00 7.33 0.00 -3.96 0.00 5.62 0.00 -8.22 m – sectoral employment structural change mass. ∆m – variation in the share of ES in response to variation in its employment volume. *ESs with a share gain resulting from their increasing levels of employment. In the following stage of the analysis, we measured the share each ES had in the overall dynamics of the Russian Arctic regions’ employment patterns (Table 10 ). In the Krasnoyarsk Territory, Komi Republic, and Republic of Karelia, the major contributors (number one in sector scorecards) were Agriculture, Forestry, Hunting, Fishing and Fish Farming (39.48%, 21.58% and 19.46%, respectively); in the Yamal-Nenets Autonomous Area and Chukotka Autonomous Area – Mining (43.99% and 36.97%, respectively); in the Republic of Sakha and Nenets Autonomous Area – Construction (33.98% and 28.25%, respectively); and in Murmansk and Arkhangelsk – Wholesale and Retail Trade (34.17% and 19.95%, respectively). In almost all the regions of the Russian Arctic (with the exception of the Nenets Autonomous Area and Komi Republic), the employment patterns were influenced significantly (positions 2 and 3 in sector scorecards) by Other, with a share from 21.34% (in Krasnodar Territory) to 12.64% (in Chukotka Autonomous Area). Transportation and Warehousing accounted for major variations in the Yamal-Nenets Autonomous Area, Arkhangelsk Region, and Komi Republic (21.25%, 14.38% and 11.66%, respectively); Construction in Krasnoyarsk Territory and Komi Republic (17.73% and 15.94%, respectively); Electricity, Gas and Steam Supply in Nenets Autonomous Area and Chukotka Autonomous Area (9.43% and 8.87%, respectively); Mining in Murmansk Region (15.72%); Manufacturing in Komi Republic (15.12%); Education in the Republic of Sakha (13.89%); and Agriculture, Forestry, Hunting, Fishing and Fish Farming in the Nenets Autonomous Area (15.39%). The ESs ranking first, second and third in the sector scorecard are defined as drivers of employment patterns. Together, they account for a share ranging from 78.55% (in Krasnodar Territory) to 47.96% (in Arkhangelsk Region). The influence on the regional employment volume from the employment dynamics within Mining (in all regions except the Republic of Karelia and Chukotka Autonomous Area), Electricity, Gas and Steam Supply (in all regions except the Republic of Karelia), Hospitality & Catering (in all regions except the Yamal-Nenets Autonomous Area and Murmansk Region), Education (in all regions except Komi Republic and Chukotka Autonomous Area), and Healthcare (in all regions except Murmansk, Yamal-Nenets Autonomous Area, and Krasnoyarsk Territory) was found to be medium. These sectors rank 4 to 9 in the sector scorecards. Table 10 – The share of the ESs under analysis in the variation within regional employment patterns, 2022 Republic of Karelia Komi Republic Nenets Autonomous Area Arkhangelsk Region, excl. of NAA Murmansk Region Yamal-Nenets Autonomous Area Krasnoyarsk Territory Republic of Sakha (Yakutia) Chukotka Autonomous Area Share in employment pattern variation, % Share ranking Share in employment pattern variation, % Share ranking Share in employment pattern variation, % Share ranking Share in employment pattern variation, % Share ranking Share in employment pattern variation, % Share ranking Share in employment pattern variation, % Share ranking Share in employment pattern variation, % Share ranking Share in employment pattern variation, % Share ranking Share in employment pattern variation, % Share ranking Agriculture, Forestry, Hunting, Fishing and Fish Farming 19.46 1 21.58 1 15.39 2 9.25 4 2.80 10 1.94 10 39.48 1 11.66 4 1.64 12 Mining 1.72 10 9.21 5 1.19 13 2.05 13 15.72 2 43.99 1 1.21 8 7.81 5 36.97 1 Manufacturing 0.70 14 15.12 3 9.09 4 7.89 5 4.36 7 4.67 5 6.27 4 1.91 9 1.30 13 Electricity, Gas and Steam Supply, Air Conditioning 1.24 12 3.17 8 9.43 3 4.23 9 7.17 4 2.50 7 4.17 6 6.51 6 8.87 3 Water Supply and Removal, Waste Management, Pollution Response 1.22 13 0.53 13 3.03 11 0.02 14 3.51 8 0.79 13 0.35 12 0.25 14 2.58 10 Construction 10.57 6 15.94 2 28.25 1 2.29 12 3.08 9 1.38 11 17.73 3 33.98 1 1.78 11 Retail and Wholesale Trade, Repair of Motor Vehicles and Motorcycles 1.27 11 10.49 4 3.75 9 19.95 1 34.17 1 6.02 4 0.06 14 1.42 10 5.93 6 Transportation & Warehousing 11.66 3 2.22 11 5.92 6 14.38 2 0.22 14 21.25 2 0.57 9 0.97 12 7.75 4 Hospitality & Catering 11.49 4 7.62 6 3.22 10 7.41 6 2.50 12 2.48 9 2.44 7 2.99 7 7.37 5 Information & Communication 2.65 9 2.34 10 0.48 14 3.67 10 0.91 13 0.28 14 0.52 10 0.98 11 4.51 7 Real Estate 6.29 7 1.26 12 2.45 12 2.36 11 5.53 5 3.53 6 0.07 13 0.36 13 4.51 7 Education 10.87 5 0.41 14 5.34 7 6.09 8 4.84 6 2.48 8 5.30 5 13.89 3 0.90 14 Healthcare and Social Services 3.42 8 7.20 7 3.85 8 6.78 7 2.62 11 0.98 12 0.49 11 2.71 8 3.25 9 Other 17.45 2 2.93 9 8.60 5 13.63 3 12.58 3 7.72 3 21.34 2 14.59 2 12.64 2 Total 100.00 - 100.00 - 100.00 - 100.00 - 100.00 - 100.00 - 100.00 - 100.00 - 100.00 - The influence on the regional employment volume from the employment dynamics within Water Supply (in all regions except Arkhangelsk), Information & Communication (in all regions except Chukotka Autonomous Area), and Real Estate (in all regions except the Yamal-Nenets Autonomous Area, Chukotka Autonomous Area, Murmansk Region, and Republic of Karelia) ca be described as minor. These sectors rank 10 to 14 in the sector scorecards. For the purpose of evaluating the potential of the ESs under study to affect employment patterns in the Russian Arctic regions, let us consider if they meet our selected criteria (Table 11 ). The ESs that meet all the three criteria, and hence can be defined as drivers of employment growth, are three: Construction (Republic of Sakha, Nenets Autonomous Area), Mining (Yamal-Nenets Autonomous Area, Chukotka Autonomous Regions), and Other (Republic of Karelia, Arkhangelsk, Murmansk, and Krasnodar Territory). Meeting two of the three criteria, and hence defined as causing a significant effect on the employment patterns, are Manufacturing (Komi Republic, Arkhangelsk, Krasnodar Territory); Wholesale and Retail Trade (Komi Republic, Arkhangelsk, Murmansk); Transportation and Warehousing (Arkhangelsk Region); Education (Republic of Sakha); Electricity Supply (Chukotka Autonomous Area); Mining (Murmansk Region); and Other (Yamal-Nenets Autonomous Area, Chukotka Autonomous District, Republic of Sakha). Table 11 – The evaluation of the extent to which the ESs under analysis affected employment patterns in the economies of the Russian Arctic regions, 2022 Criterion Republic of Karelia Komi Republic Nenets Autonomous Area (NAA) Arkhangelsk Region, excl. of NAA Murmansk Region Yamal-Nenets Autonomous Area Krasnoyarsk Territory Republic of Sakha (Yakutia) Chukotka Autonomous Area Share of ES in regional employment pattern (positions 1–3 in sector scorecards) 3, 7, 14 7, 8, 14 2, 6, 14 3, 7, 14 3, 7, 14 2, 6, 14 3, 7, 14 6, 12, 14 2, 5, 14 Structural change mass in employment by sector (positions 1–3 in sector scorecards) 6, 9, 14 3, 7, 9 3, 6, 8 3, 8, 14 2, 4, 14 2, 9, 11 3, 6, 14 2, 6, 9 2, 5, 9 Contribution of ES to changes in regional employment pattern (positions 1–3 in sector scorecards) 1, 8, 14 1, 3, 6 1, 4, 6 7, 8, 14 2, 7, 14 2, 8, 14 1, 6, 14 6, 12, 14 2, 4, 14 * Please see the list of economic sectors under Table 2 . **Source: Authors’ own calculations. Of vital importance for stimulating growth within the economic sectors under study is the support from regional governments. By identifying the ESs that are capable of driving the employment growth, it is possible to achieve a more effective system of employment in the Russian Arctic regions. The results of our analyses into the ESs’ potential to increase employment (Table 6 ) and cause changes in the regional employment patterns (Table 11 ) have enabled the conclusion as follows: a sector will be identified as promising for the employment growth in the economy of a Russian Arctic region if it enjoys favorable conditions in the region and has a crucial role in the dynamics of the regional employment pattern. Figure 1 presents the economic model for identifying the key drivers of employment growth within the socio-economic ecosystems of the Russian Arctic. The model involves three stages: Stage I. Evaluation of the potential of ESs to generate employment: - develop criteria for evaluating the potential of ESs to generate employment; - evaluate extent to which ESs are influenced by national, sectoral, and regional factors (employ shift-share analysis); - identify ESs whose growth is facilitated mostly by regional factors (i.e. Regional Share is positive and assumes (close to) highest possible value; - identify key industries of regional specialization, based on the analysis of their competitiveness and potential to generate employment (employ the method of localization coefficients); - classify ESs according to the ratio between localization coefficients and Regional Share values; - group ESs into “actual drivers of employment growth”, “potential drivers of employment growth”, and “sectors that can drive employment in the future”. Stage II. Evaluation of the extent to which ESs affect regional employment pattern: - develop criteria for assessing the ability of ESs to cause variations in the regional employment pattern; - measure the share of ESs in the regional employment pattern; - measure the structural change mass from each ES; - measure the contribution of ESs to variations within regional employment pattern; - identify ESs with a major role in the dynamics of the regional employment pattern. Stage III. Identification of the sectors that are crucial to the regional employment growth. The proposed model has been tested on the economies of the Russian Arctic regions and enabled to identify key avenues for increasing the employment levels in the said regions. The support being provided to the sectors with high potential to create jobs in the economies of the Russian Arctic regions seeks to create an effectively performing employment system. In this connection, a region’s development strategy should target sectors that can drive employment growth also in non-primary industries. Conclusion Intended to contribute to the task of identifying the economic sectors with high potential to create jobs in the regions of the Russian Arctic, our study has among its outcomes the comparative evaluation of the impact the three groups of factors have on the employment in the economies of the Russian Arctic regions; core industries identified and their concentration in the regions under study measured; the classification of ESs which uses as a key criterion the ratio between the Regional Shift value and the degree to which a region specializes on the industries comprising its sectoral pattern; the algorithm allowing to evaluate ESs for potential to increase employment; the criteria for identifying the ESs that are crucial to employment growth; and the evaluation of the regions’ policies with respect to utilization of competitive advantages offered by their economic sectors. The study has produced a classification of ESs that factors in the local conditions of sectoral growth, allowing to identify the economic sectors with high potential for increasing the size and rate of regional employment growth. The scholarly and practical importance of the proposed classification has been validated using the case study of the economies of the Russian Arctic regions. By classifying the economic sectors under analysis into groups, the study has identified key drivers of employment in the regions of the Arctic Zone – the industries with high job-generating potential. Our analysis of changes in the Russian Arctic regions’ employment patterns over 2010–2022 has found that they have been driven by the economic sectors with positive RS values and employment size increasing at the rate higher than that at national level. The results obtained fully support our stated hypothesis. The theoretical and methodological significance of the study consists in the proposed criterial framework making it possible to identify the economic sectors that are crucial to employment growth in the regions of the Russian Arctic, based on the quantified ratio between the RS value and the coefficient of localization. The proposed methodological approach and the findings of this study can be used in regional decision-making to guide employment planning and analysis of local competitiveness. Declarations Author Contribution V.M. wrote the main manuscript text References Kashepov AV The sectoral and occupational distribution of employment // Social Studies and Labor Research. 2020. №1. P.19–30. 10.34022/2658-3712-2020-38-1-19-30 Vasiliev VV (2021) The structural changes in the economy of the contemporary North // North and Market: Shaping the Economic Order. № 4. P. 56–70. 10.37614/2220-802X.4.2021.74.005 Aralbayeva GG, Afanasyev VN (2011) Forecasting the structural changes in the sectoral pattern of Orenburg’s economy based on a system of econometric equations // The Bulletin of Orenburg State University. № 13(132):23–29 Elkhina IA (2014) The structural changes and differences in the economic systems of Russia // The Bulletin of Saratov State University Economics and Social Studies. №4. P. 38–41 Kazinets LS (1981) Economic growth rates and structural changes: Statistics and planning / L.S. Kazinets. Ekonomika Publ., Moscow, p 184 Serova NA, Skufyina TP (2023) № 1. 108–119. 10.37614/2220-802X.1.2023.79.007 . An analysis of structural evolution of manufacturing in the regions of the Russian Arctic // North and Market: Shaping the Economic Order Stroeva GN The structural changes in the employment pattern of Khabarovsk Territory// Research Proceedings of the Pacific National University. 2014. №. 4(5). P. 1392–1398 McLean M, Voytek KP (1992) Understanding your economy: Using analysis to guide local strategic planning. Planners, American Planning Association Skrobotov AA (2021) Structural changes in co-integration models // Applied Econometrics. № 3. P. 117–141. 10.22394/1993-7601-2021-63-117-141 Zabelina IA, Klevakina EA, Denisenko IS (2017) Structural changes in regional employment patterns: Case study of the Eastern areas of the New Silk Road // The Bulletin of Tomsk State University. Economics. № 39. P. 80–98. 10.17223/19988648/39/6 Melnikova LV. A spatial analysis of the 2004–2019 structural change dynamics in the economies of Russian regions // Region: Economics and Social Studies. 2021. №. 3. P. 54–79. 10.15372/REG20210303 Blakely E, Leigh NG (2017) Planning local economic development: theory and practice. SAGE, Los Angeles, p 508 Kuznetsov SG (2020) The structural employment change and quality of economic growth // Research Proceedings of RAS Institute for National Economic Forecasting. M.: MAKS Press, P. 504–520. 10.47711/2076-318-2020-504-520 Uzyakov RM (2020) The metrics of structural change and why inter-industry relations are essential to consider // The Issues of Forecasting. №. 2 (179). P. 25–35 Spasskaya OV (2003) The macroeconomic methods for measuring structural change // Research Proceedings of RAS Institute for National Economic Forecasting. M.: MAKS Press, P. 20–39 Akberdina VV (2008) The Structural changes in the economy of the Sverdlovsk Region: Challenges and trends // Regional Economy. №. 2. P. 149–161 Friedman YA, Blam YS, Rechko GN Enhancing the regions’ sectoral patterns for better employment performance // The Bulletin of Russian Humanities Research Foundation. 2003. №. 1. P. 77–92 Sarycheva TV The sectoral distribution and dynamics of employment in Russia // Regional Economy and Management: E-Journal. 2016. № 4 (48). P. 253–269 Karlina TV (2011) Analyzing the structural change in a cyclical growth economy to identify the nuclei of local economic clusters // The Bulletin of the Perm University. Series: Economics. №. 4. P. 18–29 Milyaeva LG A quantitative analysis of structural changes in employment: Case study of a municipal district // The Bulletin of Altai Science. 2012. № 3 – 2. С. 142–147 Byuraeva YG (2021) The employment pattern of the Republic of Buryatia: Trends and shifts /. Reg Stud 8:68–80. № 110.14530/reg.2021.1.68 Bakumenko LP, Sarycheva TV Statistical approaches to analyzing regional employment markets // The Bulletin of Volga State University of Technology. Series: Economics and Management. № 1. P. 72–85 Luukkanen J (2015) Structural change in Chinese economy: Impacts on energy use and CO2 emissions in the period 2013–2030 // Technological Forecasting and Social Change. 94:303–317 Dunn Edgar S (1960) Jr. A Statistical and Analytical Technique for Regional Analysis // Papers in Regional Science. 6(1):98–112 Dawson J (1982) Shift-share Analysis: A Bibliographic Review of Technique and Application. Vance Bibliographies. Monticello, Ill. Vance Bibliographies, p 33 Shi CY, Yang Y (2008) A review of shift-share analysis and its application in tourism // International Journal of Management Perspectives. Т. 1. №. 1. С. 21–30 LaFaive M, Hohman J (2009) 31 August The Michigan Economic Development Corporation: A Review and Analysis ( http://www.mackinac.org/10896 ). Mackinac Center. Retrieved 5 December 2013 Myakshin V (2024) The regional shifts in public employment: Russian Arctic // Structural Change and Economic Dynamics. Vol. 69. pp. 488–494. 10.1016/j.strueco.2024.03.004 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 22 Apr, 2026 Reviewers agreed at journal 21 Apr, 2026 Reviewers invited by journal 20 Apr, 2026 Editor assigned by journal 04 Apr, 2026 Submission checks completed at journal 04 Apr, 2026 First submitted to journal 02 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9307352","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":628033510,"identity":"fe0b7e9b-3088-4871-a772-61b190535cc1","order_by":0,"name":"Vladimir Myakshin","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAt0lEQVRIiWNgGAWjYHACNoYEBhsQw4AkLWmkamFgOEyCFt32488ePNxxPrF/dvPGxzwM9xIbCGkxO5NjbpB45nbijDvHig1nMBQToeUGD5tEYtvtxIYbOWYSHxgSiNHC/gyo5Vzi/Bs55j8SiNPCYAbUciBxA9AWBuJsOZMD0pJsvPFGWrHkDIMEY8Jajh9/JvmzzU523o3kjZ95KhJkCWqBAUeISuJjk4HBngS1o2AUjIJRMNIAAOTYQXkMmTg9AAAAAElFTkSuQmCC","orcid":"","institution":"FSBSI Federal Center for Integrated Arctic Research of the Russian Academy of Sciences","correspondingAuthor":true,"prefix":"","firstName":"Vladimir","middleName":"","lastName":"Myakshin","suffix":""}],"badges":[],"createdAt":"2026-04-03 00:08:33","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9307352/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9307352/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108071970,"identity":"2a12742d-5d7d-450e-aaf3-076c2acf5e8a","added_by":"auto","created_at":"2026-04-29 06:10:52","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":38596,"visible":true,"origin":"","legend":"\u003cp\u003eThe economic model enabling to identify key drivers of employment growth within the socio-economic ecosystems of the Russian Arctic\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-9307352/v1/71474f6eb45aa1ccefd74b0d.png"},{"id":108181988,"identity":"d778375a-7533-4c0c-b7cb-f36541619735","added_by":"auto","created_at":"2026-04-30 08:59:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1294484,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9307352/v1/29489112-9ea5-43a1-b9d9-3d3f996ef903.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eAn Economic Model for Identifying Drivers of Employment Growth in the Russian Arctic Regions\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAn area\u0026rsquo;s employment rate represents an important criterion for measuring the effectiveness of its socio-economic policy. When developing the latter, the effect of any structural change should be considered also from the perspective of employment, adding to the relevance of studies into employment patterns in the regions comprising the Russian Arctic.\u003c/p\u003e \u003cp\u003eThe dual nature of employment as a phenomenon reflecting the relationship between economic and social processes (where formal employment plays the role as a resource while being the fundamental pillar of the performance potential) explains why the indicators of employment are increasingly used as basic measures of performance. From an indicator measuring the availability of labor resources, employment has evolved into a crucial factor to consider when shaping local economic policies. Together with intensity of inter-sectoral mobility of labor, the employment patterns represent a crucial factor in the social and economic growth in the Russian Artic.\u003c/p\u003e \u003cp\u003eThis study explores the sectoral employment patterns of the Russian Arctic regions from the perspective of the local economic activities that have potential to generate jobs.\u003c/p\u003e \u003cp\u003ePrevious research on the topic has employed a variety of methods to analyze and evaluate structural employment change and among them the analogy and comparison method for analyzing national and sector-specific occupational patterns [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]; the method allowing to measure change in (combined) sectoral and territorial composition of output [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]; the index method for evaluating structural change [3; 4]; statistical methods [5; 6; 7]; shift-share analysis [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]; and econometric methods of analysis [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur analysis of the scientific literature [10; 11] shows that the most productive method for evaluating structural change is shift-share analysis. Employed extensively by both domestic and international researchers, this method offers increased flexibility, allowing to embrace the economic systems of all levels and a wide array of economic indicators.\u003c/p\u003e \u003cp\u003eWhile the domestic structural change studies employ mostly the indicators that reflect scale or effectiveness of a particular economic sector (i.e. figures of employment, added value, turnover, profit, shipped output, and works and services performed), the researchers abroad tend to rely more on the employment indicators, which is due to their having easier access to official statistical databases.\u003c/p\u003e \u003cp\u003eFor a more comprehensive evaluation of the competitiveness and potential of the economic sector (ESs) to create jobs, the scope of indicators for measuring structural change should be added with the coefficient of localization (k\u003csub\u003eL\u003c/sub\u003e), the latter allowing to calculate the share an ES has in the area\u0026rsquo;s growth and the relative concentration of employment across sectors at local and national levels, while also allowing to classify ESs under study based on their competitiveness and potential to increase employment [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe recent economic studies into structural change cover a fairly wide range of employment issues.\u003c/p\u003e \u003cp\u003eSome studies explore structural employment change in relation to certain aspects of economic growth, proposing a structured approach to evaluating and measuring the quality of economic growth based on the indicators of structural change quality and intensity [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], others factor in the intersectoral relationships to provide quantified evaluations of the impact a structural change has on economic growth [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]; employ macroeconomic methods to demonstrate relationship between structural change and economic growth rate [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]; and offer analytic descriptions of structural change as an important factor of economic growth [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. And yet, none of these studies address ESs as capable of increasing their potential to become core contributors to regions\u0026rsquo; economic growth.\u003c/p\u003e \u003cp\u003eIn [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], the authors propose a toolkit for structured analysis of regional economies from the perspective of employment, exploring the effect of efforts to enhance the economic pattern on the actual employment figures but giving no attention to the role each particular ES plays towards increasing the employment figures.\u003c/p\u003e \u003cp\u003eOne important avenue is to measure the impact being sustained by regional employment patterns from a diversity of factors. The study presented in [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] compares exposures to national and regional factors to identify causal relationships within structural employment change. In [10; 19], the authors discuss the role the regional and sectoral factors play in stimulating change within employment patterns, while the study presented in [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] offers a case study of a municipal district to quantify structural employment change. These papers, however, fail to look at the potential the ESs under study offer towards higher employment rates.\u003c/p\u003e \u003cp\u003eThe studies presented in [21; 22] employ coefficients of localization to identify core (overall and locally significant) and non-core sectors in a regional economy. By comparing these sectors\u0026rsquo; growth rates at regional and national levels, the authors group them into \u0026lsquo;strong\u0026rsquo;, \u0026lsquo;lagging\u0026rsquo;, \u0026lsquo;showing constrained growth\u0026rsquo; and \u0026lsquo;depressed\u0026rsquo; and, based on that, offer a number of possible action plans for industries showing different levels of competitiveness. But again, these studies fail to take into account how multiple factors and particular ESs can influence employment patterns.\u003c/p\u003e \u003cp\u003eWhile the topic of structural change has drawn considerable attention in literature, its dynamics at regional level remains poorly explored, and there are very few studies aiming to identify ESs with the best potential to facilitate employment growth.\u003c/p\u003e \u003cp\u003eIn this paper we present the results of our study into the economic activities\u0026rsquo; potential to create jobs in the Russian Arctic regions. We propose a classification of ESs that uses as underlying criterion the ratio between the coefficient of localization and the value of Regional Shift. The core sectors identified as showing high competitiveness at regional level (i.e. those with highest positive Regional Shift value) are defined as drivers of employment growth.\u003c/p\u003e"},{"header":"Theory and methods","content":"\u003cp\u003eIn order to identify the sectors with ample potential to create jobs, the study uses a methodological framework that combines shift-share analysis [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] with the coefficient of localization 12].\u003c/p\u003e \u003cp\u003eShift-share analysis allows to break down the regional variable (represented in this study by sectoral distribution of employment) into three differential components: National Share (NS), Industrial Mix (IM), and Regional Shift (RS).\u003c/p\u003e \u003cp\u003eA change within employment pattern is represented by sum total of the three components:\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSS\u0026thinsp;=\u0026thinsp;NS\u0026thinsp;+\u0026thinsp;IM\u0026thinsp;+\u0026thinsp;RS (1)\u003c/h2\u003e \u003cp\u003eDepending on the object of analysis, each of the three components can be quantified for a particular ES or entire region (as the sum total of ESs).\u003c/p\u003e \u003cp\u003eSince regions are parts of national systems, their development depends, to some extent, on macroeconomic factors. At the same time, as economic studies [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] note, the general growth trends may show differences at national and regional levels. As know, regions with nearly identical sectoral patterns often show different performance, and the same holds true for the performance of ESs in different regions.\u003c/p\u003e \u003cp\u003eOne method for identifying the performance variation across regional growth models is offered by shift-share analysis. All its versions rely on the same conceptual framework that uses sets of equations to express economic growth (or recession) as a function of three groups of factors (national, sectoral and regional). This study uses the traditional version of shift-share analysis developed by Daniel Creamer and formalized by Edgar S. Dunn [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], known also as the comparative static analysis [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIt is essential that each of the shift-share components is interpreted correctly.\u003c/p\u003e \u003cp\u003eThe National Share shows to what extent a region\u0026rsquo;s employment level would increase if it grew at the same rate as the country\u0026rsquo;s overall employment. A region with no competitive advantages (i.e. disadvantaged region) is assumed to have its sectoral employment growing at a rate identical to that at national level.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe Industrial Mix reflects the variation in sectoral distribution of the country and its regions. If a region shows positive cumulative IM value (calculated as the sum total of the IM values for ESs), its sectoral distribution is dominated by ESs that show higher-than-anticipated growth rate at national level.\u003c/p\u003e\u003cp\u003eThe National Share and Regional Shift depend on exogenous factors and national growth rate and do not depend on regions\u0026rsquo; socio-economic setting. Together, these two components define the possible employment growth rate of a region, provided that the growth rates shown by this region\u0026rsquo;s ESs match those at the national level and that this region has a sectoral distribution which is identical to that at the national level.\u003c/p\u003e\u003cp\u003eSince endogenous factors are unique in each particular region, the RS component can be viewed as a measure of competitiveness (comparative advantages) of a region with relation to its ESs.\u003c/p\u003e\u003cp\u003eHowever, further research is needed to identify the region-specific factors that are responsible for RS value and to propose measures for mitigating their negative impact or enhancing positive effect.\u003c/p\u003e\u003cp\u003eThe disparity in RS values for different ESs within one region, and the interregional variation in the ES performance, is due to the combined effect of multiple factors (resource availability, institutional factors, infrastructural factors, etc.), multiplier effect, and local socio-economic policy.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhile being an essential part of measuring the effect of region-specific factors on sectoral employment, the analysis of structural change components is, however, not sufficient, for shift-share analysis is not without drawbacks and therefore can\u0026rsquo;t give a full picture of the impacts the particular ESs have on regions\u0026rsquo; employment dynamics.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eShift-share analysis does not allow the researcher to identify the factors that crucial to cause-and-effect relationships in each different region, but still it represents a fairly simple and useful tool for measuring the effect the three groups of factors (national, sectoral, regional) have on regional employment rates.\u003c/p\u003e\u003cp\u003eNor does shift-share analysis factor in the multiplier effect of the ESs or how employment rates change under the influence of their interplay; nor does it take into account the manufacturing ties, often leading to a region\u0026rsquo;s sectoral distribution being underanalyzed. One example is shipbuilding industry: the failure to factor in the direct and indirect links with shipbuilding in the prior estimations of the Manufacturing Output growth rate, has resulted in an RS value that was lower than the actual one and required to be adjusted upward. This point requires further research.\u003c/p\u003e\u003cp\u003ePrior research [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] found that the numerical values of the three shift-share components are contingent also on the level of disaggregation. The higher the disaggregation level, the lower the value of RS (disaggregation trap). This defines the RS as dependent on the choice of the level of detail in sectoral classification. A priori there is no recommended level of disaggregation of data. Besides, disaggregating of data to a level required by the researcher may not even be possible due to limited access to the statistical data. To avoid disaggregation traps when analyzing the significance variance of the RS component, the researcher should stick in their analysis solely to one classification level (disaggregation). It should be noted that the independence (identity) of the values obtained with a particular economic model, from the disaggregation level may be an indication of this model\u0026rsquo;s insensitivity (immunity) to new data.\u003c/p\u003e\u003cp\u003eSince shift-share analysis does not allow to factor in any of changes that may occur within a region\u0026rsquo;s industrial composition (sectoral distribution) over time, it seems expedient to use this method in combination with statistical methods for more accurate evaluation of the employment growth potential of ESs [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eGiven the interrelation between the regional industrial composition and the RS values, our further calculations required the introduction of one more criterion.\u003c/p\u003e\u003cp\u003eThis additional criterion classifies an ES as \u0026ldquo;ranking among core sectors of the region\u0026rdquo; and uses as measure the coefficients of localization (k\u003csub\u003eL\u003c/sub\u003e) calculated for each ES under analysis. The coefficient of localization measures the relative concentration of a given industry in the economy of a given region (core sector industries have k\u003csub\u003eL\u003c/sub\u003e \u0026ge; 1; if 0.90\u0026thinsp;\u0026lt;\u0026thinsp;k\u003csub\u003eL\u003c/sub\u003e \u0026lt; 1, the industry is considered promising). There is a linear dependence between the degree of concentration of an ES in regional economy and its k\u003csub\u003eL\u003c/sub\u003e (the higher the k\u003csub\u003eL\u003c/sub\u003e, the higher the degree of concentration). The calculation of the coefficient of localization involves comparative analysis of the composition of employment at regional and national levels.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThe RS-to-k\u003csub\u003eL\u003c/sub\u003e ratio shows whether an ES, for the growth of which there exist favorable conditions in the region, is actually core in this given region.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe interpretations of the \u003cem\u003eRegional Shift (RS) + Coefficient of Localization (k\u003c/em\u003e\u003csub\u003e\u003cem\u003eL\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e of the ESs comprising the sectoral composition of regional economy\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRS\u0026thinsp;+\u0026thinsp;k\u003csub\u003eL\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eInterpretation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ek\u003csub\u003eL\u003c/sub\u003e \u0026ge; 1\u003c/p\u003e \u003cp\u003eRS\u0026thinsp;\u0026gt;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThe region has as core ESs those that enjoy favorable conditions existing for their growth (i.e. the region makes good use of its competitive advantages).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ek\u003csub\u003eL\u003c/sub\u003e \u0026lt; 1\u003c/p\u003e \u003cp\u003eRS\u0026thinsp;\u0026gt;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThe region does not have as core ESs those that enjoy favorable conditions existing for their growth (i.e. the region underuses its competitive advantages).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ek\u003csub\u003eL\u003c/sub\u003e \u0026ge; 1\u003c/p\u003e \u003cp\u003eRS\u0026thinsp;\u0026lt;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThe region has as core ESs those that suffer a lack of favorable conditions for growth (i.e. competitive advantages are missing). This can be due to these ESs being of high social or economic significance (education, healthcare, social services), otherwise the region\u0026rsquo;s policy with regard to these ESs should be deemed requiring extra funding to compensate for the lack of favorable conditions for these ESs to enjoy better growth.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ek\u003csub\u003eL\u003c/sub\u003e \u0026lt; 1\u003c/p\u003e \u003cp\u003eRS\u0026thinsp;\u0026lt;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThe region does not have as core ESs those that suffer a lack favorable conditions for growth. Since these ESs receive less attention as least competitive, the region\u0026rsquo;s policy regarding them can be considered appropriate.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e*Authors\u0026rsquo; own dataset.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThus, the criterion proposed for identifying drivers of employment growth is as follows: an ES will be considered as having a high potential to create jobs if its RS value is positive or high (as evidenced by presence in the region of competitive advantages), in which case the ES classifies also as the region\u0026rsquo;s core (its share in the sectoral composition of national economy is lower than its share in the regional economy).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eConsequently, these are the industries with high potential to create jobs that can be called the drivers of employment in the economies of the Russian Arctic regions.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe algorithm for evaluating the potential of an ES to stimulate employment growth involves the following stages:\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e- shift-share analysis-based identification of ESs whose growth is facilitated by regional factors (|RS| \u0026gt; |NS| + |IM|);\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e- determination of the degree to which the region\u0026rsquo;s economy specializes on the ESs under analysis; k\u003csub\u003eL\u003c/sub\u003e-based quantification of relative concentration of employment in the ESs under analysis;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e- RS-to-k\u003csub\u003eL\u003c/sub\u003e ratio-based classification of ESs; and\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e- identification of the drivers of employment growth based on the proposed criteria.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe proposed methodological approach has been validated using the case study of the economies of the Russian Arctic regions.\u003c/p\u003e \u003cp\u003eFrom the perspective of employment growth, an ES will be considered promising if it is core and if its RS value (as an indicator of presence in the region of competitive environment conducive to growth) is positive and exceeds IM and NS values.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Results and discussion","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eFor the purposes of this study we made use of the data of the Russian Federal State Statistics Service that featured key socio-economic performance figures for the regions comprising the Arctic Zone of the Russian Federation.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe task of identifying the sectors with high potential to create jobs involved also the analysis of structural change components.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eOnce the structural change components have been quantified, it became possible to measure the effect of regional factors on the growth experienced by the ESs operating in the Russian Arctic regions (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe sectors comprising the economies of the Russian Arctic regions: Regional Shift, 2010\u0026ndash;2022\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEconomic sector\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"9\" nameend=\"c10\" namest=\"c2\"\u003e \u003cp\u003eRegion of the Russian Arctic\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMurmansk Region\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNenets Autonomous Area (NAA)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eChukotka Autonomous Area\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYamal-Nenets Autonomous Area\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRepublic of Karelia\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRepublic of Sakha (Yakutia)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eKomi Republic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eArkhangelsk Region, excl. of NAA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eKrasnoyarsk Territory\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-3.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-8.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-8.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-1.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-15.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-3.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-4.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-1.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-3.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-3.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e7.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-1.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-1.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-2.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-2.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-1.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-7.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e19.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-18.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-4.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e6.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-31.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-3.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-9.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-10.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-22.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-22.66\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-12.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-15.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-12.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-3.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-15.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-5.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-21.53\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-3.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-1.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-4.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-3.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-3.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-2.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-4.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-4.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-5.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-5.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-2.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-2.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-4.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-5.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-3.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-4.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-4.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-4.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-6.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-1.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-11.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-2.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-4.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-19.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-6.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e7.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e* 1 - Agriculture, Forestry, Hunting, Fishing and Fish Farming; 2 - Mining; 3 - Manufacturing; 4 - Electricity, Gas and Steam Supply, Air Conditioning; 5 - Water Supply and Removal, Waste Management, Pollution Response; 6 - Construction; 7 - Retail and Wholesale Trade, Repair of Motor Vehicles and Motorcycles; 8 - Transportation and Warehousing; 9 - Hospitality and Catering; 10 - Information and Communication; 11 - Real Estate; 12 - Education; 13 - Healthcare and Social Services; 14 - Other.\u003c/p\u003e \u003cp\u003e**Source: Authors\u0026rsquo; own dataset.\u003c/p\u003e \u003cp\u003eLet us analyze the job-generating potential of the ESs with positive RS values.\u003c/p\u003e \u003cp\u003eA high negative value of RS does not necessarily imply that favorable environment is missing in the region or that the local socio-economic policy has been performing poorly: a decrease in the number of the employed in a particular ES may be due to wider use of labor-saving technologies [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe Nenets Autonomous Area and the Republic of Sakha appear to have created an environment conducive to growth of employment in Construction. The Chukotka Autonomous Area and the Republic of Karelia have experienced employment growth in Real Estate, while the conditions in the Yamal-Nenets Autonomous Area, Chukotka Autonomous Area, Republic of Sakha and Murmansk Region have been favorable for Mining. Here, the value of RS exceeds that of IM.\u003c/p\u003e \u003cp\u003eFor Manufacturing (NAA, Krasnoyarsk Territory, Chukotka Autonomous Area, Republic of Sakha), Electricity Supply, Education (YNAA), Healthcare (Republic of Sakha, YNAA) and Water Supply (Republic of Karelia, Sakha, Chukotka Autonomous Area, NAA), the positive effect of the regional factors compensates for the negative impact from the national and the sectoral ones, resulting in a slight increase (or preventing further decrease) in employment (|RS| \u0026gt; |NS| + |IM|).\u003c/p\u003e \u003cp\u003eIn the Republic of Sakha, Komi Republic and the Nenets Autonomous Area, the employment growth in Hospitality and Catering has been predominantly due to the positive industrial mix effect (|IM| \u0026gt; RS). The same holds true for Construction in the Krasnoyarsk Territory and Mining in the Chukotka Autonomous Area, Republic of Sakha, and Arkhangelsk Region.\u003c/p\u003e \u003cp\u003eHospitality, Construction, and Mining have a high potential for employment growth, and the policies pursued in the said regions have been effective.\u003c/p\u003e \u003cp\u003eOur further analysis of the negative effect of regional environment on the ESs with no favorable conditions for growth has enabled the following conclusions.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e15.1% of the ESs with negative RS values have been able to achieve progress mainly due to favorable Industrial Mix effect. These ESs have a lower potential for employment growth than the ESs in all other groups, with the regional factors existing for them not contributing to their growth. Still, there are industries in this group that have experienced some employment growth thanks to the industrial mix effect (|IM| \u0026gt; |RS| + |NS|).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e47.7% of the ESs under analysis have been found to be affected negatively by the regional component, its negative effect overshadowing the positive influence of IM (|IM| \u0026lt; |RS| + |NS|). The sectors that have suffered most from this negative impact are Trade, Transportation and Warehousing.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eFor the remaining 37.2% of the ESs under analysis, all shift-share components are negative.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003eJudgements as to the effectiveness of a region\u0026rsquo;s policy and measures to include depend on which of the components is most dominant. If a reduction in employment has been mostly due to national and sectoral factors and the regional component measures a minimum negative, then the region\u0026rsquo;s employment policy should be considered relatively effective. When this factor combination is the case, a properly designed regional employment policy can lead to a decrease in negative IM and NS trends preventing growth in sectoral employment.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eOur analysis of the negative exposure experienced by the Russian Arctic regions from either one of the three components has enabled the following conclusions. In the Arkhangelsk Region, the reduction in the number of the employed in Manufacturing has been due to the maximum negative effect of sectoral factors, with the regional ones causing only a minor negative exposure, allowing to describe this region\u0026rsquo;s policy as relatively effective. In the Murmansk Region, Yamal-Nenets Autonomous Area and Republic of Karelia, the Manufacturing sector has experienced the maximum negative exposure from regional factors, indicating low effectiveness of the economic policies pursued in these regions.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eGiven the nation-wide scale of the negative trends in sectoral employment, in six of the regions under analysis (the exceptions being Yamal-Nenets Autonomous Area, the Republic of Sakha, and the Krasnoyarsk Territory) the negative impact from regional factors has been the gravest for Healthcare.\u003c/p\u003e \u003cp\u003eIn five of the nine regions (the exceptions being the Republic of Sakha, Chukotka Autonomous Area, Yamal-Nenets Autonomous Area, and Arkhangelsk Region), the reduction in the number of the employed in Agriculture, Forestry, Hunting, Fishing and Fish Farming results from poorly performing policies. Here, the negative effect of regional factors has been much stronger than that of other groups of factors, increasing the urgency for a proper action plan to keep these sectors afloat.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eIn order to identify the sectors that can drive employment growth, we extended our analysis to include the industries of specialization.\u003c/p\u003e\u003cp\u003eTo this end, for each of the sectors operating in the regions of the RF Arctic Zone we calculated coefficients of localization (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe economic sectors operating in the regions of the Russian Arctic: Coefficient of localization, 2022\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEconomic sector\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"9\" nameend=\"c10\" namest=\"c2\"\u003e \u003cp\u003eRegion of the Russian Arctic\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMurmansk Region\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNenets Autonomous Area (NAA)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eChukotka Autonomous Area\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYamal-Nenets Autonomous Area\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRepublic of Karelia\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRepublic of Sakha (Yakutia)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eKomi Republic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eArkhangelsk Region, excl. of NAA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eKrasnoyarsk Territory\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.03*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.36*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.91*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.32*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13.96*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.73*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e6.60*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e3.57*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.27*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.30*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.52*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.33*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.96*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.19*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.43*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.50*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.92*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.23*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.39*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.54*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.26*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.28*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.74*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.24*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.19*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.31*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.40*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.07*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.11*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.30*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.18*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.07*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.03*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.00*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.21*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.10*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.03*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.05*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.02*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.20*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.29*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.20*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.22*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.72*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.40*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.30*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.19*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.32*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.00*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.27*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.25*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.43*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.29*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.15*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.26*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.05*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.06*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.08*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.07*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003e* Core industry\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e** Please see the list of economic sectors under Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e*** Authors\u0026rsquo; own dataset.\u003c/p\u003e \u003cp\u003eAs can be seen from Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, the regions comprising the RF Arctic Zone show nearly identical sectoral distribution patterns. This is due to these regions lying in the same geographical zone and climatic conditions. And yet, their employment patterns show some differences: in NAA, YNAA and Chukotka, the growth rates of the dominant industries are lower than nationwide, while in other regions (Republic of Karelia, Komi Republic, and Murmansk Region) the dominant industries outperform the growth at the national level. In the Arkhangelsk Region, Republic of Sakha and Krasnoyarsk Territory, the ESs with k\u003csub\u003eL\u003c/sub\u003e \u0026ge; 1 (core industries) account for 50% of the total number of ESs.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eNearly all the regions comprising the RF Arctic Zone (the exception being the Arkhangelsk Region) have among their core industries Mining, indicating an increase in their economies\u0026rsquo; raw-material orientation and contradicting the objectives of the national strategy for regional development. The regions with highest concentration of Mining include the Yamal-Nenets Autonomous Area (k\u003csub\u003eL\u003c/sub\u003e = 13.96), Nenets Autonomous Area (k\u003csub\u003eL\u003c/sub\u003e = 13.91) and Chukotka Autonomous Area (k\u003csub\u003eL\u003c/sub\u003e = 11.32).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eFurther, as our analysis of the data presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows, in all the regions of the RF Arctic Zone the employment in Electricity Supply significantly exceeds the national figure, allowing us to classify this sector as core. The highest concentration of Electricity Supply is found in Chukotka Autonomous Area (k\u003csub\u003eL\u003c/sub\u003e = 5.96) and the lowest one in the Arkhangelsk Region (k\u003csub\u003eL\u003c/sub\u003e = 1.23). In the remaining regions, this sector\u0026rsquo;s coefficient of localization ranges between 1.4 and 2.5.\u003c/p\u003e \u003cp\u003eAnother economic sector identified as core in all the regions of the Russian Arctic (with the exception of the Chukotka Autonomous Area) is Transportation and Warehousing. This is due to these regions lying far from the central part of the country and the challenging operation and maintenance of the local infrastructures, roads and waterways. The concentration of Transportation and Warehousing does not exceed 1.4. Other sectors identified as core in the regions under analysis include Education (except for the Yamal-Nenets Autonomous Area) and Healthcare (except for the Nenets and Yamal-Nenets Autonomous Areas), indicating a sufficient level of development of their social services sectors, even though the concentration of Education and Healthcare stands here at fairly low levels (k\u003csub\u003eL\u003c/sub\u003e under 1.4).\u003c/p\u003e \u003cp\u003eOther Sectors classify as core in five regions of the Russian Arctic (their concentration low) and can be described as having a good potential in four (k\u003csub\u003eL\u003c/sub\u003e ranging between 0.90 and 1.00), evidencing good dynamic in management and institutional development.\u003c/p\u003e \u003cp\u003eFour Russian Arctic regions have been found to have among their core sectors Hospitality and Catering. This is due to the rotation team method of labor provision (YNAA) and the multiplier effect of tourism (Republic of Karelia, Murmansk Region, and Arkhangelsk Regions).\u003c/p\u003e \u003cp\u003eTo identify the economic sectors with most favorable effect on the employment rates in the economies of the Russian Arctic regions, our analysis further involved the calculation of the RS-to-k\u003csub\u003eL\u003c/sub\u003e ratios.\u003c/p\u003e \u003cp\u003eBased on the classification criteria presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the ESs under analysis have been classified into four groups representing the sectoral patterns of the regions of the Russian Arctic (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe classification groups of economic sectors comprising the economies of the Russian Arctic regions, 2022\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEconomic sector\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"9\" nameend=\"c10\" namest=\"c2\"\u003e \u003cp\u003eRegion of the Russian Arctic\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMurmansk Region\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNenets Autonomous Area\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eChukotka Autonomous Area\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYamal-Nenets Autonomous Area\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eArkhangelsk Region excl. of NAA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eKrasnoyarsk Territory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eRepublic of Karelia\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eRepublic of Sakha (Yakutia)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eKomi Republic\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e*\u003c/b\u003e Please see the list of economic sectors under Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e** Authors\u0026rsquo; own dataset.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe ESs identified as drivers of employment growth, i.e. those with positive RS values, comprise Groups 1 and 2.\u003c/p\u003e\u003cp\u003eGroup 1 (the actual drivers of employment growth) consists of the ESs for which the regional component of structural change has been positive, suggesting there exist some favorable local factors that give these sectors a competitive advantage and that this competitive advantage is taken due account of in the regional employment policy (the ESs in Group 1 are currently core in the regions under analysis) (RS\u0026thinsp;\u0026gt;\u0026thinsp;0, k\u003csub\u003eL\u003c/sub\u003e \u0026ge; 1).\u003c/p\u003e\u003cp\u003eIt follows from Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e that the employment growth is driven in the Russian Arctic regions predominantly by Mining and Electricity (Republic of Sakha, Murmansk Region, Yamal-Nenets Autonomous Area, Chukotka Autonomous Area), Education (Republic of Sakha, Krasnoyarsk Territory, Chukotka Autonomous Area, Nenets Autonomous Area), Construction (Nenets Autonomous Area, Republic of Sakha), Real Estate and Hospitality \u0026amp; Catering (Republic of Karelia), Healthcare and Social Services (Republic of Sakha), and Other Sectors (Krasnoyarsk Territory).\u003c/p\u003e\u003cp\u003eGroup 2 (the potential drivers of employment growth) consists of the ESs for which the regional component has been positive (RS\u0026thinsp;\u0026gt;\u0026thinsp;0) but the factors conducive to their further growth are not being taken full advantage of in the regional employment policy. The ESs in this group are not currently core (k\u003csub\u003eL\u003c/sub\u003e \u0026lt; 1).\u003c/p\u003e\u003cp\u003eManufacturing represents a potential driver of employment in five regions of the Russian Arctic; Agriculture, Forestry, Hunting, Fishing and Fish Farming, Hospitality and Catering, and Water Supply in four; Real Estate in two; and Education, Healthcare and Mining in one.\u003c/p\u003e\u003cp\u003eNotably, some of the economic sectors in Group 2 \u0026ndash; Real Estate in the Yamal-Nenets Autonomous Area; Construction and Manufacturing in Krasnoyarsk Territory; Agriculture, Forestry, Hunting, Fishing and Fish Farming in the Republic of Sakha; and Water Supply in the Republic of Karelia and Nenets Autonomous Area \u0026ndash; have good potential to become core in the regions under study and reclassify as Group 1, provided there is an adequate action plan to support them.\u003c/p\u003e\u003cp\u003eGroup 3 and Group 4 include ESs that cannot be described as driving the employment growth at this stage of the Russian Arctic regions\u0026rsquo; economic development (RS\u0026thinsp;\u0026lt;\u0026thinsp;0; the regional conditions are rather hindering than promoting further development) but are seen as capable of creating jobs in the long run. As the regions under study progress in their development and the market achieves a more robust level of self-regulation, there can arise factors conducive to better growth within the ESs in Group 3 and 4.\u003c/p\u003e\u003cp\u003eGroup 3 consists of economic sectors that are core in regional economies (k\u003csub\u003eL\u003c/sub\u003e \u0026ge; 1) even in the absence of competitive advantages for their growth. The ESs in this group have a lower potential to create jobs than the other groups, showing growth mostly when under favorable conditions. Also, the ESs of Group 3 classify as highly significant for regional development from social (Healthcare, Education) and economic (Transportation and Warehousing, Electricity, Gas and Steam) perspectives, requiring from regions extra funds to support their development. There are sectors in this group that have shown an increase in their employment size as a result of increased competitiveness. These include Construction (Yamal-Nenets Autonomous Area), Transportation and Warehousing (Yamal-Nenets Autonomous Area, Republics of Karelia, Sakha (Yakutia), Arkhangelsk Region), and Hospitality and Catering (Arkhangelsk Region, Yamal-Nenets Autonomous Area). Provided there\u0026rsquo;s a proper regional strategy for stimulating growth within these sectors, they may be likely to reclassify to a higher group.\u003c/p\u003e\u003cp\u003eGroup 4 includes the non-core sectors (k\u003csub\u003eL\u003c/sub\u003e \u0026lt; 1) of the economies of the regions under study. While the employment size of the ESs in this group is being affected negatively by the regional factors (RS\u0026thinsp;\u0026lt;\u0026thinsp;0), some of them, provided there is a favorable IM effect that can neutralize the negative exposure from the regional factors, can be regarded as potentially capable of increasing the employment and therefore likely to reclassify as promising areas of specializations. These include Hospitality \u0026amp; Catering, Water Supply (Krasnoyarsk Territory), Information and Communications (Republic of Sakha, NAA), Construction (Republic of Karelia), Other Sectors (Republic of Sakha, Arkhangelsk Region, NAA, YNAA). It is essential that these economic sectors receive regional support to neutralize the negative effect of adverse factors.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe classification groups of drivers of employment growth in the Russian Arctic regions based on the Regional Shift (RS)-to-Coefficient of Localization (kL) ratios, 2022\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDriver of employment growth?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eClassification group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eRS-to-kL ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c12\" namest=\"c4\"\u003e \u003cp\u003eEconomic sectors\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c12\" namest=\"c4\"\u003e \u003cp\u003eRegions of the Russian Arctic\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMurmansk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eChukotka\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYNAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eKarelia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eSakha\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eKomi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eArkhangelsk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eKrasnoyarsk\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eActual driver of employment growth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGroup 1\u003c/p\u003e \u003cp\u003eRS\u0026thinsp;\u0026gt;\u0026thinsp;0\u003c/p\u003e \u003cp\u003ek\u003csub\u003eL\u003c/sub\u003e \u0026ge; 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2, 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2, 12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2, 13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2, 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9, 11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2, 4, 6, 12, 13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e4, 6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e12, 14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePotential driver of employment growth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGroup 2\u003c/p\u003e \u003cp\u003eRS\u0026thinsp;\u0026gt;\u0026thinsp;0\u003c/p\u003e \u003cp\u003ek\u003csub\u003eL\u003c/sub\u003e \u0026lt; 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3, 5, 9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1, 5, 9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1, 11, 12, 13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1, 3, 5, 9, 11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3, 5, 9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1, 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e3, 6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSector with potential to increase employment in the future\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGroup 3\u003c/p\u003e \u003cp\u003eRS\u0026thinsp;\u0026lt;\u0026thinsp;0\u003c/p\u003e \u003cp\u003ek\u003csub\u003eL\u003c/sub\u003e \u0026ge; 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5, 8, 9, 12, 13, 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2, 4, 8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3, 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6, 8, 9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2, 4, 6, 8, 12, 13, 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2, 8, 11, 12, 13, 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3, 4, 8, 9, 11, 12, 13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1, 2, 4, 8, 13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGroup 4\u003c/p\u003e \u003cp\u003eRS\u0026thinsp;\u0026lt;\u0026thinsp;0\u003c/p\u003e \u003cp\u003ek\u003csub\u003eL\u003c/sub\u003e \u0026lt; 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1, 3, 6, 7, 10, 11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1, 7, 10, 11, 13, 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6, 7, 8, 10, 11, 13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3, 5, 7, 10, 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1, 3, 6, 7, 10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e7, 10, 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1, 7, 10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e5, 6, 7, 4, 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e5, 7, 9, 10, 11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e* Please see the list of economic sectors under Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e** Authors\u0026rsquo; own dataset.\u003c/p\u003e \u003cp\u003eOne parameter to factor in when determining the potential of an economic sector (ES) to create jobs is the variation over time in the employment volume of the sectors comprising the economy of a given area, necessitating the use of the statistical methods in structural change analysis.\u003c/p\u003e \u003cp\u003eThe extent to which an ES can affect employment levels is contingent on the concentration of the number of people employed in this ES. This necessitates the introduction into our analysis of three additional criteria allowing to identify ES as a key driver of employment, if:\u003c/p\u003e \u003cp\u003e1) its share in the regional employment pattern measures (close to) highest;\u003c/p\u003e \u003cp\u003e2) it has its share growing at a faster pace mainly thanks to its increasing number of the employed; and\u003c/p\u003e \u003cp\u003e3) its contribution to the variations within the regional employment pattern is significant or (close to) highest.\u003c/p\u003e \u003cp\u003eFrom the standpoint of mathematical logic, one can distinguish two fundamental approaches to measuring the variations in the employment volume of a given ES, allowing the use of two indicator systems:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eAbsolute indicators. These represent the difference in the elements within the aggregates under analysis and include the ES\u0026rsquo;s employment volume variation, calculated as the difference of the employment volume in the current year and that in the reference year; and the structural change mass, calculated as the difference in the ES\u0026rsquo;s shares in the regional employment pattern in the current and the reference years;\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eRelative indicators. These express relations among the elements of the aggregates under analysis and include the rate of the employment growth and increment within particular ESs and economy at large, calculated as the ratio between the number of the employed in current year and that in reference year and as the ratio between the difference of the employed in sector \u003cem\u003ei\u003c/em\u003e in current and reference years and the total number of the employed in the reference year, respectively; the contribution of the ES to variations in the number of the employed, calculated as the ratio between the absolute value of structural change mass in sector \u003cem\u003ei\u003c/em\u003e and the sum total of the absolute values of structural changes across the region\u0026rsquo;s entire set of the ESs; and the share of the sector \u003cem\u003ei\u003c/em\u003e employment volume in the regional employment pattern.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe indicators that build on the first approach (i.e. the absolute indicators) carry less information. This is due to the fact that they can only be measured for absolute parts of the aggregates being compared, i.e. the elements in use must be homogeneous and commensurate, and, secondly, the value of absolute indicators depends on that of the variable under study (in our case, the ES\u0026rsquo;s number of the employed).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003eTherefore, in order to expand the analytical capacity of the indicator system in use, the absolute indicators should be supplemented with relative ones. The system of statistical indicators for measuring the extent to which ESs can affect the variations within regional employment patterns, which is based on the proposed criteria, is presented in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u0026ndash; The system of statistical indicators for measuring the extent to which ESs affect variations within regional employment patterns. (Author\u0026rsquo;s own development)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCriterion\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndicator\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFormalized mathematical expression\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCalculation method\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEconomic meaning\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eInformational value of indicator\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Сlose to) highest share in the regional employment pattern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eShare of the ES\u0026rsquo;s employment volume in the total number of the employed in regional economy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{F}_{i}=\\frac{{Ч}_{i}}{\\sum\\:_{i=1}^{n}{Ч}_{i}}100\\:\\%\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRatio of the ES\u0026rsquo;s employment volume to the total number of the employed in regional economy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDescribes the region\u0026rsquo;s sectoral employment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAllows share-based ranking of the ES in the region\u0026rsquo;s employment scorecard\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutrunning growth of the ES\u0026rsquo;s share in the regional employment pattern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStructural change mass in the ES employment volume\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{m}_{i}={F}_{ti}-{F}_{oi}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDifference between the share in the employment volume of current year and that of reference year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDescribes the variation in the share of the ES\u0026rsquo;s number of the employed in the region\u0026rsquo;s total employment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eShows the dynamics of the share of the ES\u0026rsquo;s number of the employed in the regional employment pattern\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSignificant contribution of the ES to variations within regional employment pattern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eContribution of the ES to variations within regional employment pattern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:V=\\frac{\\left|{m}_{i}\\right|}{\\sum\\:_{i=1}^{n}\\left|{m}_{i}\\right|}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRatio of the absolute value of structural change mass in the ES employment volume to the sum total of the absolute values of structural change across the region\u0026rsquo;s entire set of the ESs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDescribes the share of the ES\u0026rsquo;s employment volume absolute variation in the sum total of the absolute variation within the regional employment pattern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eShows the extent of the ES\u0026rsquo;s impact on the regional employment pattern\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe results of our analysis into the 2010\u0026ndash;2022 dynamics of the Russian Arctic regions\u0026rsquo; sectoral employment are presented in Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eThe regions that experienced employment growth during the said period are two \u0026ndash; the Yamal-Nenets Autonomous Area, which shows a 7.3% increase, contributed mostly by the sectors of Mining (4.6%), Hospitality and Catering (23.9%), and Real Estate (36.1%); and the Republic of Sakha (Yakutia), which shows a 6.0% increase, contributed mostly by the sectors of Construction (60.2%), Mining (14.9%), and Other (10.0%).\u003c/p\u003e \u003cp\u003eSeven regions suffered a decrease in their number of the employed, with the largest decline seen in the Komi Republic (a 21.9% decline), where the most affected industries include Forestry, Hunting, Fishing and Fish Farming (a 51.8% decline), Other (a 20.4% decline), Construction (a 40.0% decline); Murmansk Region (a 18.4% decrease), where the most affected industries include Trade (a 41.7% decline), Other (a 11.9% decline), Transportation and Warehousing (a 18.2% decline); and the Republic of Karelia (a 14.8% decline), its most affected industries including Agriculture, Forestry, Hunting, Fishing and Fish Farming (a 43.7% decline), Transportation and Warehousing (a 26.6% decline), and Education (a 25.5% decline).\u003c/p\u003e \u003cp\u003eOur analysis of the Russian Arctic regions\u0026rsquo; employment dynamics enables the following conclusions.\u003c/p\u003e \u003cp\u003eHospitality and Catering has shown growth in eight of the nine regions (the exception being Murmansk), which may have been caused by the expanding tourism, on the one hand, and the wider use of rotational shiftwork, on the other hand, evidencing that these eight regions have been successful keeping their tertiary sector in line with global trends.\u003c/p\u003e \u003cp\u003eMining has shown growth in five regions (Arkhangelsk Region, Murmansk Region, Yamal-Nenets Autonomous Area, Chukotka Autonomous Area, and the Republic of Sakha), reaching higher sustainability also in Krasnoyarsk Territory. Its growth, however, is accompanied by reducing levels of employment in Manufacturing (the exceptions being the Nenets Autonomous Area and the Republic of Sakha), evidencing a structural disparity in the economies of the Russian Arctic regions as a result of their strong focus on extractive industries.\u003c/p\u003e \u003cp\u003eConstruction has shown growth in five regions \u0026ndash; thanks to the successful implementation in the Russian Arctic of a number of major national projects \u0026ndash; and a slight decrease in four (with the exception of the Komi Republic).\u003c/p\u003e \u003cp\u003eOne of the key reasons for the reduction in the Russian Arctic regions\u0026rsquo; volume of employment is shortage of personnel, which, in turn, is contributed by harsh natural and climatic conditions, remoteness from the central parts of Russia, underdeveloped infrastructure, and challenges faced by social services sector. Here, the decline in sectoral employment results not only from the decline in total employment but also from the specific nature of particular industries. One example is Trade (except in the Republic of Sakha), where digital transformation in business management, commerce, and information and communications (except in the Yamal-Nenets Autonomous Area) has led to wider use of online mode of operations. Another example is Education. In almost all the regions of the Russian Arctic (the exception being the Yamal-Nenets Autonomous Area), this sector faces a negative demographic trend (declining numbers of students) and teachers\u0026rsquo; conscious choice to work extra hours to earn income through private tutoring. Likewise, the staff shortage has been exacerbated in Healthcare \u0026ndash; by the internal processes designed to optimize this sector.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u0026ndash; The 2010\u0026ndash;2022 dynamics in the Russian Arctic regions\u0026rsquo; sectoral employment. (Authors\u0026rsquo; own calculations)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"28\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c18\" colnum=\"18\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c19\" colnum=\"19\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c20\" colnum=\"20\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c21\" colnum=\"21\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c22\" colnum=\"22\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c23\" colnum=\"23\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c24\" colnum=\"24\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c25\" colnum=\"25\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c26\" colnum=\"26\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c27\" colnum=\"27\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c28\" colnum=\"28\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"3\"\u003e \u003cp\u003eEconomic sector\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eKomi Republic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eRepublic of Karelia\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003eNenets Autonomous Area (NAA)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c13\" namest=\"c11\"\u003e \u003cp\u003eArkhangelsk Region, excl. of NAA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c16\" namest=\"c14\"\u003e \u003cp\u003eMurmansk Region\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c19\" namest=\"c17\"\u003e \u003cp\u003eYamal-Nenets Autonomous Area\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c22\" namest=\"c20\"\u003e \u003cp\u003eKrasnoyarsk Territory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c25\" namest=\"c23\"\u003e \u003cp\u003eRepublic of Sakha (Yakutia)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c28\" namest=\"c26\"\u003e \u003cp\u003eChukotka Autonomous Area\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2010\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e∆Чi\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2010\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e∆Чi\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2010\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e∆Чi\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2010\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003e∆Чi\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003e2010\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e \u003cp\u003e∆Чi\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c17\"\u003e \u003cp\u003e2010\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c18\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c19\"\u003e \u003cp\u003e∆Чi\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c20\"\u003e \u003cp\u003e2010\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c21\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c22\"\u003e \u003cp\u003e∆Чi\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c23\"\u003e \u003cp\u003e2010\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c24\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c25\"\u003e \u003cp\u003e∆Чi\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c26\"\u003e \u003cp\u003e2010\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c27\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c28\"\u003e \u003cp\u003e∆Чi\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eemployees (K)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eemployees (K)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eemployees (K)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eemployees (K)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eemployees (K)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eemployees (K)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eemployees (K)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eemployees (K)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eemployees (K)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eemployees (K)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eemployees (K)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003eemployees (K)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003eemployees (K)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003eemployees (K)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e \u003cp\u003eemployees (K)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c17\"\u003e \u003cp\u003eemployees (K)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c18\"\u003e \u003cp\u003eemployees (K)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c19\"\u003e \u003cp\u003eemployees (K)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c20\"\u003e \u003cp\u003eemployees (K)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c21\"\u003e \u003cp\u003eemployees (K)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c22\"\u003e \u003cp\u003eemployees (K)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c23\"\u003e \u003cp\u003eemployees (K)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c24\"\u003e \u003cp\u003eemployees (K)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c25\"\u003e \u003cp\u003eemployees (K)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c26\"\u003e \u003cp\u003eemployees (K)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c27\"\u003e \u003cp\u003eemployees (K)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c28\"\u003e \u003cp\u003eemployees (K)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAgriculture, Forestry, Hunting, Fishing and Fish Farming\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-17.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-9.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e30.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e23.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e-7.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e13.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e-3.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c19\"\u003e \u003cp\u003e-0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e132.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e89.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c22\"\u003e \u003cp\u003e-43.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e33.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e28.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c25\"\u003e \u003cp\u003e-4.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c26\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c28\"\u003e \u003cp\u003e-0.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMining\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-11.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e14.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e19.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e4.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e66.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e97.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c19\"\u003e \u003cp\u003e30.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e29.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e29.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c22\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e49.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e56.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c25\"\u003e \u003cp\u003e7.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c26\"\u003e \u003cp\u003e5.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c28\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eManufacturing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e37.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-5.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e87.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e-8.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e44.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e38.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e-6.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e12.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c19\"\u003e \u003cp\u003e-1.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e182.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c22\"\u003e \u003cp\u003e-1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e17.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e19.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c25\"\u003e \u003cp\u003e2.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c26\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c28\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElectricity, Gas and Steam Supply, Air Conditioning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-2.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-1.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e16.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e12.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e-3.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e19.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e18.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e-0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c19\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e42.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c22\"\u003e \u003cp\u003e-5.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e27.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c25\"\u003e \u003cp\u003e-2.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c26\"\u003e \u003cp\u003e5.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c28\"\u003e \u003cp\u003e-0.70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWater Supply and Removal, Waste Management, Pollution Response\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e-0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e8.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e-3.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c19\"\u003e \u003cp\u003e-0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e14.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e13.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c22\"\u003e \u003cp\u003e-0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c25\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c26\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c28\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstruction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-16.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e31.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e28.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e-2.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e26.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e-6.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e62.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e66.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c19\"\u003e \u003cp\u003e3.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e103.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e116.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c22\"\u003e \u003cp\u003e12.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e36.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c25\"\u003e \u003cp\u003e21.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c26\"\u003e \u003cp\u003e1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c28\"\u003e \u003cp\u003e-0.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRetail and Wholesale Trade, Repair of Motor Vehicles and Motorcycles\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-7.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-7.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e89.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e71.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e-17.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e65.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e38.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e-27.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e30.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e29.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c19\"\u003e \u003cp\u003e-1.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e236.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e226.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c22\"\u003e \u003cp\u003e-9.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e53.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c25\"\u003e \u003cp\u003e2.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c26\"\u003e \u003cp\u003e3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c28\"\u003e \u003cp\u003e-0.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTransportation and Warehousing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-9.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-8.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e45.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e45.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e40.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e32.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e-7.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e55.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e47.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c19\"\u003e \u003cp\u003e-8.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e125.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e119.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c22\"\u003e \u003cp\u003e-5.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e43.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e45.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c25\"\u003e \u003cp\u003e1.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c26\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c28\"\u003e \u003cp\u003e-0.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospitality and Catering\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e12.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e13.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e1.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e9.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e9.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e-0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e8.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e10.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c19\"\u003e \u003cp\u003e2.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e23.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e25.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c22\"\u003e \u003cp\u003e1.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e6.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c25\"\u003e \u003cp\u003e2.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c26\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c28\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInformation and Communication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-2.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-1.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e8.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e-2.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e8.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e-1.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e6.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c19\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e22.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e22.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c22\"\u003e \u003cp\u003e-0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e10.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e10.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c25\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c26\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c28\"\u003e \u003cp\u003e-0.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReal Estate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-2.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e13.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e12.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e-0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e13.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e8.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e-5.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e7.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e9.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c19\"\u003e \u003cp\u003e2.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e33.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e32.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c22\"\u003e \u003cp\u003e-1.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e7.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c25\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c26\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c28\"\u003e \u003cp\u003e-0.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-11.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-8.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e54.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e46.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e-8.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e34.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e30.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e-4.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e26.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e27.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c19\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e131.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e121.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c22\"\u003e \u003cp\u003e-10.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e64.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c25\"\u003e \u003cp\u003e-4.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c26\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c28\"\u003e \u003cp\u003e-0.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealthcare and Social Services\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-5.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-4.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e46.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e38.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e-8.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e28.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e-4.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e17.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e18.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c19\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e102.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e99.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c22\"\u003e \u003cp\u003e-3.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e39.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c25\"\u003e \u003cp\u003e3.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c26\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c28\"\u003e \u003cp\u003e-0.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e89.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-18.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e49.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-2.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e90.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e84.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e-5.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e86.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e76.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e-10.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e64.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e64.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c19\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e251.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e262.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c22\"\u003e \u003cp\u003e10.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e88.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e85.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c25\"\u003e \u003cp\u003e-3.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c26\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c28\"\u003e \u003cp\u003e-1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal employment:\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e472.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e368.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-103.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e310.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e264.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-46.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e32.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e31.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e543.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e479.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e-63.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e417.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e341.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e-76.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e387.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e416.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c19\"\u003e \u003cp\u003e28.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e1 437.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e1 381.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c22\"\u003e \u003cp\u003e-56.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e482.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e509.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c25\"\u003e \u003cp\u003e27.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c26\"\u003e \u003cp\u003e36.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e33.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c28\"\u003e \u003cp\u003e-3.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAgriculture, Forestry, Hunting, Fishing and Fish Farming has experienced a reduction in its number of the employed in all the regions of the Russian Arctic, evidencing further increase in technological effectiveness as primary production is losing its share.\u003c/p\u003e \u003cp\u003eUsing the first of our proposed criteria, we have identified the economic sectors with the highest share in the regional employment pattern (i.e. the sectors that rank first, second and third in the sectors scorecard) (Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOne such sector, ranking in top positions in all the Russian Arctic regions, is Other. In seven of the nine regions (the exceptions being the Nenets Autonomous Area and the Yamal-Nenets Autonomous Area), the sector with significant (between 16.00% and 9.79%) share in the regional employment pattern is Trade. Five regions (Republic of Karelia, Komi Republic, Arkhangelsk, Murmansk, and Krasnoyarsk Territory) have among their highest-scoring sectors Manufacturing (18.90% to 9.22% share), four Mining (Nenets Autonomous Area \u0026ndash; 23.32%, Yamal-Nenets Autonomous Area \u0026ndash; 23.41%, Chukotka Autonomous District \u0026ndash; 18.99%, Republic of Sakha \u0026ndash; 11.07%), and three (Nenets Autonomous Area, Yamal-Nenets Autonomous Area, and Republic of Sakha) Construction (16.03% to 11.39% share).\u003c/p\u003e \u003cp\u003eTransportation and Warehousing occupies middle-ranking positions (4\u0026ndash;6) in the sector scorecards of almost all the Russian Arctic regions (with the exception of the Komi Republic), its share varying between 11.34% (Yamal-Nenets Autonomous Area) and 7.72% (Chukotka Autonomous Area).\u003c/p\u003e \u003cp\u003eThe percentage of people employed in Agriculture, Forestry, Hunting, Fishing and Fish Farming varies between 6.47% (Krasnoyarsk Territory) and 1.27% (Yamal-Nenets Autonomous Area), in Electricity and Steam Supply from 13.06% (Chukotka Autonomous Area) to 2.6% (Arkhangelsk Region), and in Healthcare from 8.89% (Komi Republic) to 4.35% (Yamal-Nenets Autonomous Area).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u0026ndash; The percentage of people employed in sectors comprising the economies of the Russian Arctic regions, 2022. (Authors\u0026rsquo; own calculations)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"19\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c18\" colnum=\"18\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c19\" colnum=\"19\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eRepublic of Karelia\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eKomi Republic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eNenets Autonomous Area\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eArkhangelsk Region, excl. of NAA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003eMurmansk Region\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003eYamal-Nenets Autonomous Area\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e \u003cp\u003eKrasnoyarsk Territory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003eRepublic of Sakha (Yakutia)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003eChukotka Autonomous Area\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePercentage of employed, F, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF-ranking\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercentage of employed, F, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF-ranking\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePercentage of employed, F, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eF-ranking\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePercentage of employed, F, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eF-ranking\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003ePercentage of employed, F, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eF-ranking\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003ePercentage of employed, F, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003eF-ranking\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003ePercentage of employed, F, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003eF-ranking\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e \u003cp\u003ePercentage of employed, F, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c17\"\u003e \u003cp\u003eF-ranking\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c18\"\u003e \u003cp\u003ePercentage of employed, F, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c19\"\u003e \u003cp\u003eF-ranking\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAgriculture, Forestry, Hunting, Fishing and Fish Farming\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.53%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.31%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.51%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e4.86%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2.82%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1.27%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e6.47%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e5.62%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e4.75%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMining\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.91%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.99%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e23.32%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.73%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e5.63%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e23.41%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e2.13%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e11.07%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e18.99%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eManufacturing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12.05%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.22%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.88%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e18.29%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e11.17%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e2.64%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e13.11%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e3.87%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e1.48%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElectricity, Gas and Steam Supply, Air Conditioning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.13%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.11%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2.69%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e5.51%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e4.81%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e3.05%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e5.48%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e13.06%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWater Supply and Removal, Waste Management, Pollution Response\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.98%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.25%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.96%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.77%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.52%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.46%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.96%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e0.61%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e0.30%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstruction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.08%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.53%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11.82%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e5.92%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e5.87%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e16.03%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e8.44%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e11.39%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e5.34%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRetail and Wholesale Trade, Repair of Motor Vehicles and Motorcycles\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16.24%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.07%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.75%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e14.89%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e11.23%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e7.02%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e16.42%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e11.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e9.79%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTransportation \u0026amp; Warehousing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.65%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.52%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10.54%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e9.55%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e9.65%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e11.34%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e8.67%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e8.97%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e7.72%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospitality \u0026amp; Catering\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.17%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.28%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.60%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2.88%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2.70%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e2.62%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e1.82%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e1.30%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e1.78%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInformation \u0026amp; Communication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.77%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.38%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.60%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.33%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.82%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1.59%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e1.62%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e1.98%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e1.48%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReal Estate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.68%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.74%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.96%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2.67%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2.55%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e2.36%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e2.33%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e1.49%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e1.48%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9.06%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.39%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.58%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e9.64%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e8.91%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e6.54%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e8.81%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e12.72%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e8.90%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealthcare and Social Services\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.89%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.89%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.43%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e8.07%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e8.24%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e4.35%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e7.18%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e7.78%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e6.23%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18.84%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19.22%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e16.93%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e17.71%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e22.38%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e15.57%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e18.99%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e16.73%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e18.69%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e100.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e100.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e100.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e100.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e100.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e100.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e100.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e100.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e100.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe sectors in the last (12\u0026ndash;14) positions of the sector scorecards are defined as enjoying the lowest share in the regional employment patterns.\u003c/p\u003e \u003cp\u003eThe percentage of people employed in Water Supply and Removal, Waste Management \u0026amp; Pollution Response stands at 1.50%, in Information and Communications at 2.00% (due to the specific nature of this sector), in Real Estate and Hospitality \u0026amp; Catering at 3.00% (with the exception of the Republic of Karelia).\u003c/p\u003e \u003cp\u003eLet us analyze the sectoral employment dynamics based on the structural change mass over 2010\u0026ndash;2022 (Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe structural change mass (m\u003csub\u003ei\u003c/sub\u003e) is positive if the rate of variation within the number of the employed in sector \u003cem\u003ei\u003c/em\u003e exceeds that measured for the aggregate employment of a region\u0026rsquo;s sectoral composition.\u003c/p\u003e \u003cp\u003eHospitality \u0026amp; Catering has shown a positive structural change mass in all the regions of the Russian Arctic. Mining has done so in seven regions of the nine (the exceptions being the Komi Republic and the Nenets Autonomous Area; Construction in six (the exceptions being the Komi Republic, Yamal-Nenets Autonomous Area, and Murmansk Region); Other, and Real Estate in five.\u003c/p\u003e \u003cp\u003eIn the Yamal-Nenets Autonomous Area, Chukotka Autonomous Area, and Murmansk Region, the structural change mass has been highest for Mining (6.20%, 3.47% and 2.07%, respectively); in the Republic of Sakha and the Nenets Autonomous Area for Construction (3.88% and 3.18%, respectively); in the Republic of Karelia and Krasnoyarsk Territory for Other (2.08% and 1.48%, respectively); in the Komi Republic for Manufacturing (1.87%); and in the Arkhangelsk Region for Transportation and Warehousing (1.12%).\u003c/p\u003e \u003cp\u003eAll the regions of the Russian Arctic have shown a decrease in the number of the employed in Agriculture, Hunting, Fishing and Fish Farming (amounting to more than 2.00% in the Krasnoyarsk Territory, Republic of Karelia, and Komi Republic) and Trade (with the exception of the Komi Republic and the Krasnoyarsk Territory), these two sectors suffering the highest reduction in the Murmansk Region (-4.49%); a reduction of 1.00% was measured for Electricity (except in the Komi Republic and the Murmansk Region) and Information \u0026amp; Communication (except in the Nenets Autonomous Area and the Krasnoyarsk Territory); Education has seen the highest reduction in the number of he employed in the Republic of Karelia (by 1.30%) and the Republic of Sakha (by 1.59%).\u003c/p\u003e \u003cp\u003eAny variation in the number of people employed in a region\u0026rsquo;s economy depends, on the one hand, on the employment dynamics within sector \u003cem\u003ei\u003c/em\u003e and, on the other hand, on the dynamics in the region\u0026rsquo;s total employment. Our analysis of the influence a region\u0026rsquo;s total employment has on the dynamics of employment in sector \u003cem\u003ei\u003c/em\u003e enables a conclusion that there exists a relation between the extent of influence and the direction of the variation. Where total employment and sectoral employment show changes that are co-directional (i.e. they both show growth or decline), the share of sector \u003cem\u003ei\u003c/em\u003e is unlikely to show any pronounced variation. From this perspective, if a decrease in the number of people employed in sector \u003cem\u003ei\u003c/em\u003e is concurrent with a decrease in the region\u0026rsquo;s total employment, then the resultant dynamics are likely to reach a plateau or even show a slight increase. Likewise, an increase in the number of the employed in sector \u003cem\u003ei\u003c/em\u003e can be partly made up by an increase in total employment, resulting in a slight decrease in structural change mass. Conversely, if a variation in region\u0026rsquo;s sector \u003cem\u003ei\u003c/em\u003e employment is counter-directional with that in region\u0026rsquo;s total employment (i.e. one shows increase and the other decrease), then the employment dynamics of sector \u003cem\u003ei\u003c/em\u003e will be intensified by the overall increase (decrease) in the region\u0026rsquo;s total employment. If a variation in sector \u003cem\u003ei\u003c/em\u003e employment occurs amid some minor fluctuations (both in magnitude and direction) in the region\u0026rsquo;s total employment, then the structural change mass will be determined by the nature of the variation within sector \u003cem\u003ei\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eFor the purpose of identifying the ESs that gain share in the regional economy mostly through increase in their employment, we have performed a factor analysis of structural change mass.\u003c/p\u003e \u003cp\u003eBy looking into how the share of sector \u003cem\u003ei\u003c/em\u003e changes in response to variations in its employment volume, it became possible to identify those ESs that owe their share gain to technological or institutional progress, with the variation in the region\u0026rsquo;s total employment causing only a minor influence.\u003c/p\u003e \u003cp\u003eAs can be seen from Table\u0026nbsp;\u003cspan refid=\"Tab10\" class=\"InternalRef\"\u003e10\u003c/span\u003e, these ESs include Hospitality \u0026amp; Catering (in all the Russian Arctic regions except Murmansk), Mining (in 5 regions \u0026ndash; Arkhangelsk, Murmansk, Chukotka Autonomous Area, Yamal-Nenets Autonomous Area, Republic of Sakha), Construction (in 3 regions \u0026ndash; Nenets Autonomous Area, Krasnoyarsk Territory, Republic of Sakha), Water Supply (in 3 regions \u0026ndash; Nenets Autonomous Area, Chukotka Autonomous Area, Republic of Sakha), Real Estate (in 3 regions \u0026ndash; Yamal-Nenets Autonomous Area, Republic of Sakha, Republic of Karelia), Manufacturing (in 2 regions \u0026ndash; Nenets Autonomous Area, and Republic of Sakha), Transportation and Warehousing (in NAO), Healthcare (in the Republic of Sakha), and Other (in the Krasnoyarsk Territory).\u003c/p\u003e \u003cp\u003eFor the remaining ESs, the share gain (i.e. the positive value of structural change mass) results mainly from the decrease in region\u0026rsquo;s total employment.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u0026ndash; The 2010\u0026ndash;2022 dynamics in the employment volumes of the sectors comprising the economies of the Russian Arctic regions. (Authors\u0026rsquo; own calculations)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"19\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c18\" colnum=\"18\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c19\" colnum=\"19\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"18\" nameend=\"c19\" namest=\"c2\"\u003e \u003cp\u003eSectoral employment: structural change mass, %\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eRepublic of Karelia\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eKomi Republic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eNenets Autonomous Area\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eArkhangelsk Region, excl. of NAA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003eMurmansk Region\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003eYamal-Nenets Autonomous Area\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e \u003cp\u003eKrasnoyarsk Territory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003eRepublic of Sakha (Yakutia)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003eChukotka Autonomous Area\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003em, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e∆m, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003em, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e∆m, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003em, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e∆m, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003em, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e∆m, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003em, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e∆m, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003em, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003e∆m, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003em, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003e∆m, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e \u003cp\u003em, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c17\"\u003e \u003cp\u003e∆m, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c18\"\u003e \u003cp\u003em, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c19\"\u003e \u003cp\u003e∆m, %\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAgriculture, Forestry, Hunting, Fishing and Fish Farming\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-2.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-2.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-3.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-1.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-1.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-1.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e-0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e-0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e-0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e-2.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e-3.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e-1.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e-1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e-0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c19\"\u003e \u003cp\u003e-0.54*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMining\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-2.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.07*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.03*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e6.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e7.92*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e1.51*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e3.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c19\"\u003e \u003cp\u003e1.91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eManufacturing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-1.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.93*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-1.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e-1.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e-0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e-0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e-0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e0.44*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c19\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElectricity, Gas and Steam Supply, Air Conditioning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-1.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e-0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e-0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e-0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e-0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e-0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e-0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e-0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c19\"\u003e \u003cp\u003e-1.91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWater Supply and Removal, Waste Management, Pollution Response\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e-0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e-0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e-0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e-0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e-0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e0.06*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c19\"\u003e \u003cp\u003e0.22*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstruction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-3.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.78*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e-1.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e-0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e1.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e0.90*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e3.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e4.52*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c19\"\u003e \u003cp\u003e-0.27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRetail and Wholesale Trade, Repair of Motor Vehicles and Motorcycles\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-2.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-1.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-1.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-3.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-4.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e-6.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e-0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e-0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e-0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e-0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e-0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c19\"\u003e \u003cp\u003e-1.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTransportation \u0026amp; Warehousing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-1.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-2.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-2.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.31*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e-1.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e-3.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e-2.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e-0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e-0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e-0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e-0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c19\"\u003e \u003cp\u003e-1.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospitality \u0026amp; Catering\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.90*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.44*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.31*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.24*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e-0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.54*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e0.10*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e0.41*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c19\"\u003e \u003cp\u003e0.54*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInformation \u0026amp; Communication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e-0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e-0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e-0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e-0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e-0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c19\"\u003e \u003cp\u003e-0.54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReal Estate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e-1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.67*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e-0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e0.12*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e-0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c19\"\u003e \u003cp\u003e-0.54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-1.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-2.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-2.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-1.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e-1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e-0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e-0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e-0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e-1.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e-0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e-0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c19\"\u003e \u003cp\u003e-0.82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealthcare \u0026amp; Social Services\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-1.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-1.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e-1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e-0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e-0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e0.75*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e-0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c19\"\u003e \u003cp\u003e-0.82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-3.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-1.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e-2.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e-1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e1.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e0.73*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e-1.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e-0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e-1.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c19\"\u003e \u003cp\u003e-2.72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-14.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-21.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-3.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-11.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e-18.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e7.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e-3.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e5.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c19\"\u003e \u003cp\u003e-8.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003em \u0026ndash; sectoral employment structural change mass.\u003c/p\u003e \u003cp\u003e∆m \u0026ndash; variation in the share of ES in response to variation in its employment volume.\u003c/p\u003e \u003cp\u003e*ESs with a share gain resulting from their increasing levels of employment.\u003c/p\u003e \u003cp\u003eIn the following stage of the analysis, we measured the share each ES had in the overall dynamics of the Russian Arctic regions\u0026rsquo; employment patterns (Table\u0026nbsp;\u003cspan refid=\"Tab10\" class=\"InternalRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the Krasnoyarsk Territory, Komi Republic, and Republic of Karelia, the major contributors (number one in sector scorecards) were Agriculture, Forestry, Hunting, Fishing and Fish Farming (39.48%, 21.58% and 19.46%, respectively); in the Yamal-Nenets Autonomous Area and Chukotka Autonomous Area \u0026ndash; Mining (43.99% and 36.97%, respectively); in the Republic of Sakha and Nenets Autonomous Area \u0026ndash; Construction (33.98% and 28.25%, respectively); and in Murmansk and Arkhangelsk \u0026ndash; Wholesale and Retail Trade (34.17% and 19.95%, respectively).\u003c/p\u003e \u003cp\u003eIn almost all the regions of the Russian Arctic (with the exception of the Nenets Autonomous Area and Komi Republic), the employment patterns were influenced significantly (positions 2 and 3 in sector scorecards) by Other, with a share from 21.34% (in Krasnodar Territory) to 12.64% (in Chukotka Autonomous Area). Transportation and Warehousing accounted for major variations in the Yamal-Nenets Autonomous Area, Arkhangelsk Region, and Komi Republic (21.25%, 14.38% and 11.66%, respectively); Construction in Krasnoyarsk Territory and Komi Republic (17.73% and 15.94%, respectively); Electricity, Gas and Steam Supply in Nenets Autonomous Area and Chukotka Autonomous Area (9.43% and 8.87%, respectively); Mining in Murmansk Region (15.72%); Manufacturing in Komi Republic (15.12%); Education in the Republic of Sakha (13.89%); and Agriculture, Forestry, Hunting, Fishing and Fish Farming in the Nenets Autonomous Area (15.39%).\u003c/p\u003e \u003cp\u003eThe ESs ranking first, second and third in the sector scorecard are defined as drivers of employment patterns. Together, they account for a share ranging from 78.55% (in Krasnodar Territory) to 47.96% (in Arkhangelsk Region).\u003c/p\u003e \u003cp\u003eThe influence on the regional employment volume from the employment dynamics within Mining (in all regions except the Republic of Karelia and Chukotka Autonomous Area), Electricity, Gas and Steam Supply (in all regions except the Republic of Karelia), Hospitality \u0026amp; Catering (in all regions except the Yamal-Nenets Autonomous Area and Murmansk Region), Education (in all regions except Komi Republic and Chukotka Autonomous Area), and Healthcare (in all regions except Murmansk, Yamal-Nenets Autonomous Area, and Krasnoyarsk Territory) was found to be medium. These sectors rank 4 to 9 in the sector scorecards.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab10\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 10\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u0026ndash; The share of the ESs under analysis in the variation within regional employment patterns, 2022\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"19\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c18\" colnum=\"18\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c19\" colnum=\"19\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eRepublic of Karelia\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eKomi Republic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eNenets Autonomous Area\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eArkhangelsk Region, excl. of NAA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003eMurmansk Region\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003eYamal-Nenets Autonomous Area\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e \u003cp\u003eKrasnoyarsk Territory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003eRepublic of Sakha (Yakutia)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003eChukotka Autonomous Area\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eShare in employment pattern variation, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eShare ranking\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eShare in employment pattern variation, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eShare ranking\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eShare in employment pattern variation, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eShare ranking\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eShare in employment pattern variation, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eShare ranking\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eShare in employment pattern variation, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eShare ranking\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eShare in employment pattern variation, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003eShare ranking\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003eShare in employment pattern variation, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003eShare ranking\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e \u003cp\u003eShare in employment pattern variation, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c17\"\u003e \u003cp\u003eShare ranking\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c18\"\u003e \u003cp\u003eShare in employment pattern variation, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c19\"\u003e \u003cp\u003eShare ranking\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAgriculture, Forestry, Hunting, Fishing and Fish Farming\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e15.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e9.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e39.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e11.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e1.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMining\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e15.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e43.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e1.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e7.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e36.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eManufacturing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e7.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e4.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e4.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e6.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e1.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e1.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElectricity, Gas and Steam Supply, Air Conditioning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e4.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e7.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e2.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e4.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e6.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e8.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWater Supply and Removal, Waste Management, Pollution Response\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e2.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstruction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e28.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e17.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e33.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e1.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRetail and Wholesale Trade, Repair of Motor Vehicles and Motorcycles\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e19.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e34.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e6.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e1.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e5.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTransportation \u0026amp; Warehousing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e14.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e21.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e7.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospitality \u0026amp; Catering\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e7.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e2.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e2.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e2.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e7.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInformation \u0026amp; Communication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e3.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e4.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReal Estate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e5.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e3.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e4.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e6.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e4.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e2.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e5.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e13.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealthcare and Social Services\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e6.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e2.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e3.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e13.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e12.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e7.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e21.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e14.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e12.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe influence on the regional employment volume from the employment dynamics within Water Supply (in all regions except Arkhangelsk), Information \u0026amp; Communication (in all regions except Chukotka Autonomous Area), and Real Estate (in all regions except the Yamal-Nenets Autonomous Area, Chukotka Autonomous Area, Murmansk Region, and Republic of Karelia) ca be described as minor. These sectors rank 10 to 14 in the sector scorecards.\u003c/p\u003e \u003cp\u003eFor the purpose of evaluating the potential of the ESs under study to affect employment patterns in the Russian Arctic regions, let us consider if they meet our selected criteria (Table\u0026nbsp;\u003cspan refid=\"Tab11\" class=\"InternalRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe ESs that meet all the three criteria, and hence can be defined as drivers of employment growth, are three: Construction (Republic of Sakha, Nenets Autonomous Area), Mining (Yamal-Nenets Autonomous Area, Chukotka Autonomous Regions), and Other (Republic of Karelia, Arkhangelsk, Murmansk, and Krasnodar Territory).\u003c/p\u003e \u003cp\u003eMeeting two of the three criteria, and hence defined as causing a significant effect on the employment patterns, are Manufacturing (Komi Republic, Arkhangelsk, Krasnodar Territory); Wholesale and Retail Trade (Komi Republic, Arkhangelsk, Murmansk); Transportation and Warehousing (Arkhangelsk Region); Education (Republic of Sakha); Electricity Supply (Chukotka Autonomous Area); Mining (Murmansk Region); and Other (Yamal-Nenets Autonomous Area, Chukotka Autonomous District, Republic of Sakha).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab11\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 11\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u0026ndash; The evaluation of the extent to which the ESs under analysis affected employment patterns in the economies of the Russian Arctic regions, 2022\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCriterion\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRepublic of Karelia\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKomi Republic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNenets Autonomous Area (NAA)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eArkhangelsk Region, excl. of NAA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMurmansk Region\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYamal-Nenets Autonomous Area\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eKrasnoyarsk Territory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eRepublic of Sakha (Yakutia)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eChukotka Autonomous Area\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShare of ES in regional employment pattern (positions 1\u0026ndash;3 in sector scorecards)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3, 7, 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7, 8, 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2, 6, 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3, 7, 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3, 7, 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2, 6, 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3, 7, 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6, 12, 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2, 5, 14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStructural change mass in employment by sector (positions 1\u0026ndash;3 in sector scorecards)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6, 9, 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3, 7, 9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3, 6, 8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3, 8, 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2, 4, 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2, 9, 11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3, 6, 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2, 6, 9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2, 5, 9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eContribution of ES to changes in regional employment pattern (positions 1\u0026ndash;3 in sector scorecards)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1, 8, 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1, 3, 6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1, 4, 6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7, 8, 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2, 7, 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2, 8, 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1, 6, 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6, 12, 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2, 4, 14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e* Please see the list of economic sectors under Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e**Source: Authors\u0026rsquo; own calculations.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003eOf vital importance for stimulating growth within the economic sectors under study is the support from regional governments. By identifying the ESs that are capable of driving the employment growth, it is possible to achieve a more effective system of employment in the Russian Arctic regions.\u003c/p\u003e \u003cp\u003eThe results of our analyses into the ESs\u0026rsquo; potential to increase employment (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e) and cause changes in the regional employment patterns (Table\u0026nbsp;\u003cspan refid=\"Tab11\" class=\"InternalRef\"\u003e11\u003c/span\u003e) have enabled the conclusion as follows: a sector will be identified as promising for the employment growth in the economy of a Russian Arctic region if it enjoys favorable conditions in the region and has a crucial role in the dynamics of the regional employment pattern.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the economic model for identifying the key drivers of employment growth within the socio-economic ecosystems of the Russian Arctic.\u003c/p\u003e \u003cp\u003eThe model involves three stages:\u003c/p\u003e \u003cp\u003eStage I. Evaluation of the potential of ESs to generate employment:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e- develop criteria for evaluating the potential of ESs to generate employment;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e- evaluate extent to which ESs are influenced by national, sectoral, and regional factors (employ shift-share analysis);\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e- identify ESs whose growth is facilitated mostly by regional factors (i.e. Regional Share is positive and assumes (close to) highest possible value;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e- identify key industries of regional specialization, based on the analysis of their competitiveness and potential to generate employment (employ the method of localization coefficients);\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e- classify ESs according to the ratio between localization coefficients and Regional Share values;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e- group ESs into \u0026ldquo;actual drivers of employment growth\u0026rdquo;, \u0026ldquo;potential drivers of employment growth\u0026rdquo;, and \u0026ldquo;sectors that can drive employment in the future\u0026rdquo;.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eStage II. Evaluation of the extent to which ESs affect regional employment pattern:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e- develop criteria for assessing the ability of ESs to cause variations in the regional employment pattern;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e- measure the share of ESs in the regional employment pattern;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e- measure the structural change mass from each ES;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e- measure the contribution of ESs to variations within regional employment pattern;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e- identify ESs with a major role in the dynamics of the regional employment pattern.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eStage III. Identification of the sectors that are crucial to the regional employment growth.\u003c/p\u003e \u003cp\u003eThe proposed model has been tested on the economies of the Russian Arctic regions and enabled to identify key avenues for increasing the employment levels in the said regions.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe support being provided to the sectors with high potential to create jobs in the economies of the Russian Arctic regions seeks to create an effectively performing employment system. In this connection, a region\u0026rsquo;s development strategy should target sectors that can drive employment growth also in non-primary industries.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIntended to contribute to the task of identifying the economic sectors with high potential to create jobs in the regions of the Russian Arctic, our study has among its outcomes the comparative evaluation of the impact the three groups of factors have on the employment in the economies of the Russian Arctic regions; core industries identified and their concentration in the regions under study measured; the classification of ESs which uses as a key criterion the ratio between the Regional Shift value and the degree to which a region specializes on the industries comprising its sectoral pattern; the algorithm allowing to evaluate ESs for potential to increase employment; the criteria for identifying the ESs that are crucial to employment growth; and the evaluation of the regions\u0026rsquo; policies with respect to utilization of competitive advantages offered by their economic sectors.\u003c/p\u003e \u003cp\u003eThe study has produced a classification of ESs that factors in the local conditions of sectoral growth, allowing to identify the economic sectors with high potential for increasing the size and rate of regional employment growth.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe scholarly and practical importance of the proposed classification has been validated using the case study of the economies of the Russian Arctic regions.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eBy classifying the economic sectors under analysis into groups, the study has identified key drivers of employment in the regions of the Arctic Zone \u0026ndash; the industries with high job-generating potential.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eOur analysis of changes in the Russian Arctic regions\u0026rsquo; employment patterns over 2010\u0026ndash;2022 has found that they have been driven by the economic sectors with positive RS values and employment size increasing at the rate higher than that at national level. The results obtained fully support our stated hypothesis.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThe theoretical and methodological significance of the study consists in the proposed criterial framework making it possible to identify the economic sectors that are crucial to employment growth in the regions of the Russian Arctic, based on the quantified ratio between the RS value and the coefficient of localization.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe proposed methodological approach and the findings of this study can be used in regional decision-making to guide employment planning and analysis of local competitiveness.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eV.M. wrote the main manuscript text\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eKashepov AV The sectoral and occupational distribution of employment // Social Studies and Labor Research. 2020. №1. P.19\u0026ndash;30. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.34022/2658-3712-2020-38-1-19-30\u003c/span\u003e\u003cspan address=\"10.34022/2658-3712-2020-38-1-19-30\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVasiliev VV (2021) The structural changes in the economy of the contemporary North // North and Market: Shaping the Economic Order. № 4. P. 56\u0026ndash;70. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.37614/2220-802X.4.2021.74.005\u003c/span\u003e\u003cspan address=\"10.37614/2220-802X.4.2021.74.005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAralbayeva GG, Afanasyev VN (2011) Forecasting the structural changes in the sectoral pattern of Orenburg\u0026rsquo;s economy based on a system of econometric equations // The Bulletin of Orenburg State University. № 13(132):23\u0026ndash;29\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eElkhina IA (2014) The structural changes and differences in the economic systems of Russia // The Bulletin of Saratov State University Economics and Social Studies. №4. P. 38\u0026ndash;41\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKazinets LS (1981) Economic growth rates and structural changes: Statistics and planning / L.S. Kazinets. Ekonomika Publ., Moscow, p 184\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSerova NA, Skufyina TP (2023) № 1. 108\u0026ndash;119. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.37614/2220-802X.1.2023.79.007\u003c/span\u003e\u003cspan address=\"10.37614/2220-802X.1.2023.79.007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. An analysis of structural evolution of manufacturing in the regions of the Russian Arctic // North and Market: Shaping the Economic Order\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStroeva GN The structural changes in the employment pattern of Khabarovsk Territory// Research Proceedings of the Pacific National University. 2014. №. 4(5). P. 1392\u0026ndash;1398\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcLean M, Voytek KP (1992) Understanding your economy: Using analysis to guide local strategic planning. Planners, American Planning Association\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSkrobotov AA (2021) Structural changes in co-integration models // Applied Econometrics. № 3. P. 117\u0026ndash;141. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.22394/1993-7601-2021-63-117-141\u003c/span\u003e\u003cspan address=\"10.22394/1993-7601-2021-63-117-141\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZabelina IA, Klevakina EA, Denisenko IS (2017) Structural changes in regional employment patterns: Case study of the Eastern areas of the New Silk Road // The Bulletin of Tomsk State University. Economics. № 39. P. 80\u0026ndash;98. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.17223/19988648/39/6\u003c/span\u003e\u003cspan address=\"10.17223/19988648/39/6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMelnikova LV. A spatial analysis of the 2004\u0026ndash;2019 structural change dynamics in the economies of Russian regions // Region: Economics and Social Studies. 2021. №. 3. P. 54\u0026ndash;79. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.15372/REG20210303\u003c/span\u003e\u003cspan address=\"10.15372/REG20210303\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBlakely E, Leigh NG (2017) Planning local economic development: theory and practice. SAGE, Los Angeles, p 508\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKuznetsov SG (2020) The structural employment change and quality of economic growth // Research Proceedings of RAS Institute for National Economic Forecasting. M.: MAKS Press, P. 504\u0026ndash;520. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.47711/2076-318-2020-504-520\u003c/span\u003e\u003cspan address=\"10.47711/2076-318-2020-504-520\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUzyakov RM (2020) The metrics of structural change and why inter-industry relations are essential to consider // The Issues of Forecasting. №. 2 (179). P. 25\u0026ndash;35\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSpasskaya OV (2003) The macroeconomic methods for measuring structural change // Research Proceedings of RAS Institute for National Economic Forecasting. M.: MAKS Press, P. 20\u0026ndash;39\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAkberdina VV (2008) The Structural changes in the economy of the Sverdlovsk Region: Challenges and trends // Regional Economy. №. 2. P. 149\u0026ndash;161\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFriedman YA, Blam YS, Rechko GN Enhancing the regions\u0026rsquo; sectoral patterns for better employment performance // The Bulletin of Russian Humanities Research Foundation. 2003. №. 1. P. 77\u0026ndash;92\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSarycheva TV The sectoral distribution and dynamics of employment in Russia // Regional Economy and Management: E-Journal. 2016. № 4 (48). P. 253\u0026ndash;269\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKarlina TV (2011) Analyzing the structural change in a cyclical growth economy to identify the nuclei of local economic clusters // The Bulletin of the Perm University. Series: Economics. №. 4. P. 18\u0026ndash;29\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMilyaeva LG A quantitative analysis of structural changes in employment: Case study of a municipal district // The Bulletin of Altai Science. 2012. № 3\u0026thinsp;\u0026ndash;\u0026thinsp;2. С. 142\u0026ndash;147\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eByuraeva YG (2021) The employment pattern of the Republic of Buryatia: Trends and shifts /. Reg Stud 8:68\u0026ndash;80. № 110.14530/reg.2021.1.68\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBakumenko LP, Sarycheva TV Statistical approaches to analyzing regional employment markets // The Bulletin of Volga State University of Technology. Series: Economics and Management. № 1. P. 72\u0026ndash;85\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLuukkanen J (2015) Structural change in Chinese economy: Impacts on energy use and CO2 emissions in the period 2013\u0026ndash;2030 // Technological Forecasting and Social Change. 94:303\u0026ndash;317\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDunn Edgar S (1960) Jr. A Statistical and Analytical Technique for Regional Analysis // Papers in Regional Science. 6(1):98\u0026ndash;112\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDawson J (1982) Shift-share Analysis: A Bibliographic Review of Technique and Application. Vance Bibliographies. Monticello, Ill. Vance Bibliographies, p 33\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShi CY, Yang Y (2008) A review of shift-share analysis and its application in tourism // International Journal of Management Perspectives. Т. 1. №. 1. С. 21\u0026ndash;30\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLaFaive M, Hohman J (2009) 31 August The Michigan Economic Development Corporation: A Review and Analysis (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.mackinac.org/10896\u003c/span\u003e\u003cspan address=\"http://www.mackinac.org/10896\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Mackinac Center. Retrieved 5 December 2013\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMyakshin V (2024) The regional shifts in public employment: Russian Arctic // Structural Change and Economic Dynamics. Vol. 69. pp. 488\u0026ndash;494. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.strueco.2024.03.004\u003c/span\u003e\u003cspan address=\"10.1016/j.strueco.2024.03.004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"the-annals-of-regional-science","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"arsc","sideBox":"Learn more about [The Annals of Regional Science](https://link.springer.com/journal/168)","snPcode":"168","submissionUrl":"https://submission.springernature.com/new-submission/168/3","title":"The Annals of Regional Science","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"regions of the Russian Arctic, regional employment pattern, shift-share components, economic activities, core sectors, regional employment policy","lastPublishedDoi":"10.21203/rs.3.rs-9307352/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9307352/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn the context of the demographic stagnation and migration trends existing in the regions of the Russian Arctic, the task of enhancing the local employment systems involves identifying the economic sectors with high potential to create jobs (drivers of employment growth). This explains the relevance of this study which seeks to identify key drivers of employment in the Russian Arctic regions and proposes a hypothesis that a region\u0026rsquo;s core industry with a positive value of competitive effect (i.e. the industry enjoying favorable conditions for growth) represents a driver of employment growth. For the purposes of analyzing the employment patterns in the regions of the Russian Arctic, the study uses a methodological framework that employs shift-share analysis, a tool for measuring the effect of sets of factors (national growth effect, industrial mix effect, competitive effect) on regions\u0026rsquo; employment dynamics, and the coefficient of localization, a measure of competitiveness and potential of an economic sector to generate jobs. The study has as its key outcome the shift share analysis-based algorithm for identifying job-generating sectors and proposes a classification of economic sectors that uses as key criterion the ratio between competitive effect and coefficient of localization. The economic sectors under analysis are classified into actual drivers of employment growth, potential drivers of employment growth, and sectors with potential to drive employment in the future. The proposed methodological approach has been validated using the case study of the economies of the Russian Arctic regions and relying on the data of the Federal State Statistics Service. Based on the proposed criteria, the economic sectors under study were analyzed for the potential to increase employment and classified accordingly. The scholarly and practical importance of the study consists in the proposed criterial framework making it possible to identify the economic sectors that are crucial to employment growth in the Russian Arctic and facilitating evidence-based employment planning. Further research on the topic might involve creating a model that would factor in the multiplier effect of inter-industry relations.\u003c/p\u003e","manuscriptTitle":"An Economic Model for Identifying Drivers of Employment Growth in the Russian Arctic Regions","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-29 06:10:15","doi":"10.21203/rs.3.rs-9307352/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-04-23T00:02:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"5576802098510689038046416685627874431","date":"2026-04-21T05:00:47+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-20T07:08:08+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-04T04:22:31+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-04T04:22:26+00:00","index":"","fulltext":""},{"type":"submitted","content":"The Annals of Regional Science","date":"2026-04-02T23:59:59+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"the-annals-of-regional-science","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"arsc","sideBox":"Learn more about [The Annals of Regional Science](https://link.springer.com/journal/168)","snPcode":"168","submissionUrl":"https://submission.springernature.com/new-submission/168/3","title":"The Annals of Regional Science","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"dcaf191e-daa6-42e0-bdba-353373022ea3","owner":[],"postedDate":"April 29th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-29T06:10:15+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-29 06:10:15","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9307352","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9307352","identity":"rs-9307352","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}