Social, economic, and environmental drivers of renewable energy transition in WESTERN Balkans

Social, economic, and environmental drivers of renewable energy transition in WESTERN Balkans | 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 Social, economic, and environmental drivers of renewable energy transition in WESTERN Balkans Fatbardha Morina, Albina Hysaj, GÜVEN SEVİL This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8609460/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract The renewable energy transition in the Western Balkans is shaped by a complex interplay of social, economic, and environmental factors. Social dynamics such as increasing public awareness of climate change and a growing demand for cleaner, more sustainable energy play a critical role. Economic considerations, including energy security, long-term cost efficiency, and employment generation, further motivate the shift. Environmental imperatives, such as the need to reduce greenhouse gas emissions and mitigate the negative effects of fossil fuel dependency, also drive the transition. This study investigates the impact of social, economic, and environmental variables on renewable energy transition in six Western Balkan countries, Albania, Kosovo, North Macedonia, Montenegro, Bosnia and Herzegovina, and Serbia over the period 2000–2023. Employing a Random Effects panel data model, the results show that the GINI index has a statistically significant positive effect on renewable energy consumption, while GDP growth and CO 2 emissions have negative and significant effects. These results indicate that policymakers should implement strong carbon mitigation policies in order to increase renewable energy investments. 1. INTRODUCTION The nations worldwide are shifting their focus to the sustainable development practices to ensure long-term growth, environmental protection and the social inclusion. As the developed countries are making significant steps towards the achievements of the Sustainable Development Goals and the exploitation of natural sources, many developing regions such as the Western Balkan are still in the nascent stages, facing several challenges through this transition (Milutinovic and Jolovic, 2010 ). Despite the investments of the recent years in the energetical sector, the Western Balkan countries mostly depend on sources such as coal, large hydropower, and fossil fuels. The reliance on those sources makes the energy consumption expensive and unsecure; causes environmental harm and increases the climate change concerns (Đurašković et al., 2021 ; Rajić et al., 2025; Young and Macura, 2023). Moreover, the outdated infrastructure makes the process inefficient and the level of CO2 emissions high (Belis et al., 2019 ). Several constrains such as limited access to capital, political instability and regulatory uncertainty makes the transition to the usage of the clean energy challenging (Kamali Saraji and Streimikiene, 2023 ), despite the potentials of the region sourcing from high solar radiation, strong wind corridors and abundant hydro resources (IRENA, 2019 ). Apart of the other challenges, even though all the Western Balkan nations are dedicated to the EU Green Agenda for the Western Balkans (Ignjatović et al., 2024 ), the regional interconnection of the energy market is very week and there is a lack of mutual strategies to forward to the usage of clean energy (Đurašković et al., 2021 ; Filipović and Ignjatović, 2022 ).The transition to renewable energy in Western Balkan countries is not only an environmental challenge. Rather, it is highly dependent on the incorporation of the social, economic, and environmental in the Western Balkans. Analysing each category of factors and the joint effect of all of them would contribute to the identification of the main drivers of the transition process (Ćetković and Buzogány, 2016 ; Jovanović et al., 2024 ). The energy system of the Western Balkans is depended on imported energy or fossil fuels making it vulnerable to high price volatility, supply disruptions and economic pressure (Filipović and Ignjatović, 2022 ; Gjukaj et al., 2024; Golušin et al., 2013 ). The price volatility and the lack of a well-organized energy market in the region make the current energy system unsustainable. Furthermore, the necessity for a sustainable energy system is related to the continuous economic challenges of the region. The transition to renewable energy involves several fiscal, legal and economic reforms. Those reforms will overcome the financial constraints and increase the trust of the investors in this sector (Đurašković, et al., 2021 ; Vuchkova, 2020 ). In the transition process are faced significant social challenges as well. Several social constrains such as the central planning system legacy and the low public awareness regarding the benefits of renewable energy contributes to limited public participations, disconnecting the societal energy needs with the energy policies (Akar, 2016; Đurović, 2021; Young and Macura, 2023). Moreover, other social problems such as energy access inequity, infrastructure gap, affordability and the low trust in the institutions are particularly existent in the rural areas (Petrović, 2021 ). To increase the social inclusiveness in the transition process requires a strong public support that can be achieved by the participation of residents and local communities in the planning process (Jegen and Audet, 2011; Walker and Devine-Wright, 2008 ). The heavy dependence on coal and fossil fuels and the usage of outdated power plants leads to high greenhouse gas emissions and severe air pollution which negatively affects the economic productivity (Filipović and Ignjatović, 2022 ; Rajić et al., 2025). The increased consumption of sustainable energy sources such as solar, wind, biomass and hydropower, would contribute to the achievement of environmental and economic goals because of the reduced emissions and improved air quality (Brkljača et al., 2021; Đurašković et al., 2021 ; Mexhuani et al., 2022 ). The transition to the renewable energy consumption in the Western Balkans is driven by several economic, social and environmental factors. Analysing those factors and the interactions among them, is important for the policy makers to design effective, inclusive, and sustainable clean energy policies. The purpose of this study is to analyse the main social, economic, and environmental factors that contribute to the renewable energy consumption in the Western Balkans. The following section presents a review of the relevant literature, continued by the methodology used to investigate the relationship between variables, the empirical findings and their interpretation, and the conclusions drawn from the study. 2. LITERATURE REVIEW Due to the global focus on the Sustainable Development Goals, the interest of researchers in sustainability and renewable energy has earned significant interest. In recent years, even developing countries are making immense attempts to renewable energy transition and the combination of factors that would enable the transition, which is also reflected in the number of articles aiming to investigate this process. This section aims to deliver an overview of the relevant theoretical background and the empirical literature. The theoretical background subsection provides an overview of economic theories related to renewable energy transition. The empirical literature briefly reviewing the literature analysing the social, economic and environmental factors that contribute to the increased renewable energy consumption. 2.1 Theoretical Background There are numerous economic theories and hypotheses that explain the determinant factors that contribute to the process of transition to renewable energy. One of the most important theories which explains the relationship between economic growth and environmental quality through a U-shaped curve is the Environmental Kuznets Curve (Apergis and Ozturk, 2015; Dinda, 2004; Stern, 2004). The U shape indicates that when economic development is at the early stages, the environmental degradation increases because of the reliance of energy sector on fossil fuel, heavy industrialization, and lack of regulations. As economic growth reaches a significant level, the investments in improved technology, renewable infrastructure and utilization of clean energy sources would contribute to the decline of the environmental degradation (Sampene et al., 2024 ). However, the legitimacy of EKC depends on several factors such as economic liberalization, social awareness, environmental policies, and technological progress (Dasgupta et al., 2002 ). Another important theory is Ecological Modernization Theory (EMT). This theory states that the economic growth can be achieved through environmental protection and sustainability via institutional reforms, technological innovation, and modernization (Mol and Sonnenfeld, 2014 ). This theory highlights mutual role of government, society, and various market actors in the promotion of clean energy consumption, environmental regulation, and investment in renewable energy technology. It challenges the view that environmental degradation is an inevitable consequence of industrialization, arguing that the usage of the right policies and tools can lead to significant ecological improvements (Spaargaren and Mol, 1992 ). However, critics of the theory oppose that in developing countries, inequality and a lack of environmental justice requires a more critical approach that considers the social dimensions of sustainability as well (Foster, 2005 ). The Pollution Haven Hypothesis (PHH) explains the association between several macroeconomic and environmental factors. This hypothesis assumes that the developing countries with weak environmental enforcement tend to attract foreign investments in pollution-intensive industries. Based on this hypothesis, high foreign direct investments would contribute to increased emissions and environmental degradation (Santos and Forte, 2021; Shaheen et al., 2022 ). However, the foreign direct investments are influenced by several factors, such as the economic structure of the country, local policies, and so on, and they can be environmentally friendly as well (Otieno and Aduda, 2022 ). 2.2 Empirical Literature Review 2.2.1 Economic Drivers of Renewable Energy An increasing number of studies investigate the economic factors contributing to renewable energy consumption. Osińska et al. ( 2024 ) explore the factors driving the renewable energy consumption worldwide for the period 1995–2019, by classifying the countries based on the development stage, indicated by the human development index. The authors find that the key economic determinants of renewable energy consumption are GDP, foreign direct investments, and terms of trade, while the effect of foreign direct investments is stronger in low-developed countries. According to Alam and Murad ( 2020 ), the economic factors have a positive effect on renewable energy consumption in OECD countries. Their study explores the influence of economic growth, trade openness, and technological advancement in 25 OECD countries for 43 years by using the ARDL model. The authors find that all the variables positively affect renewable energy consumption in the long run, while in the short run the dynamics among them perform a mixed behaviour. Sadiq et al. ( 2023 ) analyse the impact of economic variables on the sustainable energy consumption in China for the period from 1981 to 2019. The results of the analysis reveal that economic growth, foreign direct investment, inflation, and population growth contribute to the increased renewable energy consumption in China. Additionally, Vo and Vo ( 2021 ) examine the connection among growth, environment, and energy in the ASEAN region. The results suggest that the population growth increases the renewable energy consumption, while a Granger bidirectional causality is found among economic growth, energy consumption, and CO2 emissions. Ali et al. ( 2025 ) explore the impact of several economic, social, and environmental variables on renewable energy consumption in Asia from 1995 to 2020. The authors find that economic growth and foreign direct investments positively affect the renewable energy consumption, especially at low consumption levels. Also, Eyuboglu and Uzar ( 2025 ) which explore how the socio-economic and environmental variables effect the renewable energy consumption in Italy from 1970–2022, find that economic growth has a positive influence of the renewable energy consumption, while trade openness has an adverse impact. Similarly, Han et al. ( 2022 ) examine how trade openness and urbanization affect the renewable energy in China from 1990 to 2018. Based on the empirical results, the trade openness positively affects the non-renewable energy consumption and has a moderate positive effect on the consumption of the renewable energy. Conversely Mehmood et al. ( 2022 ), which analyse the socio-economic determinants of renewable energy in the BRIC countries from 1988 until 2017, notice that economic growth negatively affects renewable energy due to the fact that citizens would prefer the consumption of fuel energy to achieve economic growth. However, trade openness is found to have a positive impact on renewable energy consumption. Also Melnyk et al. ( 2020 ) investigates the socio-economic determinants of renewable energy in 36 OECD countries from 2001–2015 by using random effect model. The authors find that increased GDP would decrease renewable energy consumption, indicating that the richer the countries the more likely they are to use non-renewable energy sources. 2.2.2 Social Drivers of Renewable Energy Several studies examine how the social factors affect the renewable energy consumption. Pellegrini-Masini et al. ( 2021 ) use survey data to analyse the effect of income, income inequality, and wealth inequality on energy consumption attitudes in European countries, proxied by the Sustainable Energy Care Index (SECI). The empirical findings suggest that economic equality, including both the income and wealth index explains 41% of the variability of the index of in national level. Income equality has an adverse effect on SECI, while wealth equality has a positive effect on SECI. Eyuboglu and Uzar ( 2025 ) determine that GINI affects renewable energy in several channels, starting from political to investment, social, environmental and public awareness. The authors find a negative significant impact of inequality on the renewable energy consumption. Moreover, Uzar (2020) explores how income inequality affects renewable energy consumption in 43 countries, including both developed and developing nations, for the period 2000–2015. The author finds that income inequality has a negative effect on renewable energy, indicating that fair income distribution is very important to the transition to renewable energy consumption. Additionally, Mehmood et al. ( 2022 ) suggest that lower inequality contributes to increased level of renewable energy consumption. Asongu and Odhiambo ( 2024 ) analyse how income inequality impacts the renewable energy consumption in 34 sub-Saharan lower and middle-income countries by utilizing quadratic Tobit regression. The authors utilize three measures of inequality: Gini, Palma, and the Atkinson Index. The findings indicate that only the Atkinson Index exhibits a U-shaped effect on renewable energy. Below the threshold, inequality negatively impacts renewable energy consumption, while above the threshold, it has a positive impact. Moreover, Acheampong et al. ( 2024 ) in their investigation, which includes 166 countries, find that an increased income inequality decreases both total energy consumption, although it increases the consumption of non-renewable energy. The authors argue that distribution would drive the total energy and renewable energy consumption whilst deducting the non-renewable energy consumption. Mahalik et al. ( 2023 ) investigate the role of income inequality on renewable energy demand in several countries in South Asia from 1996 to 2018. Through a balanced panel model and by including controlling variables such as economic growth, CO2 emissions, and government effectiveness, the authors find that government effectiveness serves as an incentive to increase the demand for renewable energy. Nevertheless, the influence of income inequality, economic growth, and CO2 emission is adverse. 2.2.3 Environmental Drivers of Renewable Energy Several studies analyse the effect of renewable energy on the CO2 emission, but the contingency of studies investigating the reverse impact is very limited. Nguyen and Kakinaka ( 2019 ) in their sample of 107 countries between 1990 and 2013, conclude that the correlation among renewable energy consumption and CO2 emissions depends on the level of country development, and there are noticed significant disparities among low-income and high-income countries. In low-income countries, high levels of CO2 emissions are associated to higher renewable energy consumption levels. Conversely, in high-income countries, the relationship among CO2 emissions and renewable energy consumption levels is negative. Also, Apergis et al. ( 2010 ) which investigate the association among CO2 emissions, renewable, and nuclear energy in 19 developed and developing nations from 1984 to 2007 conclude the existence of a significant positive connection among CO2 emissions and renewable energy, while the association among the CO2 emissions and nuclear energy is adverse. An investigation for BRICS countries conducted by Mehmood et al. ( 2022 ) between 1998–2017 reveals that CO2 emissions are positively linked with renewable energy suggesting that high CO2 emission would urge the utilization of clean energy. Also Sadorsky ( 2009 ) which analyse the drivers of renewable energy consumption in G7 countries find a positive association among CO2 emissions and renewable energy consumption, considering high emissions as e trigger of clean energy. Conversely, Eyuboglu and Uzar ( 2025 ) find that CO2 emissions negatively affect the renewable energy. Also, Perone ( 2024 ) finds a negative association among the renewable energy and CO2 emission in OECD countries. 3. DATA AND METHODOLOGY The study aims to examine the effect of social, economic and environmental factors on renewable energy transition in Western Balkans countries. It includes six countries Albania, Kosovo, North Macedonia, Montenegro, Bosnia & Herzegovina, and Serbia over the period 2000 to 2023 using annual data. To estimate the model, panel data methods are applied, specifically the Random Effects model. The Hausman test is conducted as a post estimation robustness check to determine the appropriateness of the Random Effects model. Based on the theoretical framework and insights form the existing literature the following model that is employed: $$\:RE=f(GINI,\:TRADE,\:GDP,\:POP,\:{CO}_{2})$$ where renewable energy consumption as a percentage of total final energy consumption RE is used as a proxy for renewable energy transition. The GINI index is employed to represent social factors, where a value of 0 indicates perfect equality and a value of 100 signifies perfect inequality. Economic factors are captured through three variables: TRADE , defined as the sum of exports and imports of goods and services as a percentage of gross domestic product; GDP growth, measured as the annual percentage growth rate of GDP at market prices based on constant local currency; and POP , the annual population growth rate. Environmental factors are represented by CO 2 emissions, measured in metric tons per capita. All variables are based on secondary data collected from the World Bank’s Indicators database. Table 1 Descriptive Statistics Variable Obs Mean Std. Dev. Min Max RE 131 27.773 10.773 14 54.4 GINI 123 34.43 6.005 25 65.7 CO 2 140 4.146 1.901 .089 8.099 TRADE 136 91.003 21.021 21.109 166.147 GDP 136 71.471 40.397 1 140 POP 144 − .457 .651 -3.758 .967 4. EMPIRICAL RESULTS Panel Unit Root test Among the available panel unit roots test, the Im, Pesaran and Shin, 2003 (IPS) test is considered one of the most suitable for unbalanced panel data. This test is designed to determine whether a variable is stationary in level or contains a unit root across individual cross-sectional units. Based on the results of the IPS test, it is found that RE (renewable energy consumption) and GINI index are stationary only after first differencing, indicating that they are integrated of order one, I(1). In contrast, all other variables TRADE, GDP growth, POP, and CO2 emission are stationary at level. Table 2 Panel unit root tests results. Variables IPS (2003) RE 0.5135 (0.696) D(RE) -5.231***(0.000) GINI -1.314*(0.094) D(GINI) -3.815***(0.000) TRADE -1.745**(0.040) GDP -4.432 ***(000) POP -3.754***(0.000) CO2 -2.480**(0.006) Notes : Probability values are reported in parentheses. Panel root test includes intercept and trend. ***,** and * denotes the significance at 1% and 5%, and 10% level, respectively. D(.) denotes the first difference. Another important diagnostic test involves checking for multicollinearity among independent variables. As shown in Table 3 , the pairwise correlation coefficients are all below the commonly accepted threshold of 0.8, indicating that multicollinearity is not a concern in the estimated model. Table 3 Pairwise correlations. Variables (1) (2) (3) (4) (5) (1)GINI 1.000 (2) CO 2 0.422* 1.000 (3) TRADE 0.055 0.047 1.000 (4) GDP -0.170 -0.070 -0.086 1.000 (5) POP -0.251* -0.332* -0.040 0.029 1.000 * shows significance at p < 0.05 In Table 3 are shown the results of the regression model. VARIABLES D.RE D.GINI 0.134** -0.0615 CO 2 -0.163** -0.0651 TRADE -0.00715 -0.00732 GDP -0.0166*** -0.0055 POP -0.442 -0.418 Constant 2.576** -1.022 Observations 105 Number of countries 6 R-squared 0.2753 Wald chi2(5) 67.16 Prob > chi2 0.0000 Robust standard errors in parentheses *** p < 0.01, ** p < 0.05, * p < 0.1 The regression results indicate that among the three main groups of factors social, economic, and environmental, the most statistically significant determinants of the renewable energy transition in Western Balkan countries are the GINI coefficient, GDP growth and CO2 emission. The GINI representing social factors, is statistically significant and positively associated with renewable energy transition. Among economic factors, GDP growth exhibits a statistically significant negative effect on renewable energy transition in Western Balkan countries. Specifically, a one percentage point increase in GDP growth leads to a 0.016 percentage point decline in renewable energy consumption, indicating that economic expansion in the region may still rely heavily on conventional energy sources. In contrast, trade openness and population growth also show a negative coefficient, but the effects are not statistically significant, suggesting they do not play a decisive role in influencing renewable energy use. Regarding the environmental factors, CO2 emissions in metric tons per capita are found to have a negative and statistically significant impact on renewable energy at the 5% significant level. A one percentage increase in CO2 emission is associated with a 0.163 percentage decrease in renewable energy consumption. This finding highlights the ongoing dependence of Western Balkan countries on fossil fuel and suggests that behavioral and infrastructural shifts toward renewable energy may require more time and strong policy incentives. 5. CONCLUSION Legislative and political barriers hinder the process of renewable energy transition in Western Balkan countries. Except Albania that generates energy by using renewable energy sources and hydropower, other Western Balkan countries depend on coal as traditional sources that cause high environmental pollution. Thus, the aim of this study provides important findings into the key determinants of the renewable energy transition in the Western Balkan countries over the period 2000–2023 by using annual data. In order to decide the determinants of the transition, factors are categorized into social, economic, and environmental groups. The results reveal that income inequality (GINI index), GDP growth, and CO 2 emissions are the most significant variables shaping renewable energy consumption patterns in the region. The positive and statistically significant relationship between the GINI coefficient and renewable energy transition suggests that, paradoxically, higher income inequality may coincide with increase renewable energy adoption. This may be due to policy efforts targeted at expanding energy access or addressing disparities in energy services. However, this does not imply that inequality is desirable, but rather that inclusive energy policies can play a key role in supporting the transition. Conversely, GDP growth shows a significant negative impact on renewable energy consumption, indicating that the region’s economic expansion continues to depend heavily on conventional energy sources. This underlines the need for structural economic reforms and green investment strategies that decouple the economic development from fossil fuel use. The negative and significant effect of CO 2 emissions further confirm the persistence of fossil fuel dependency in the region and the challenges it poses to clean energy development. This finding points to the necessity for stronger environmental policies and investment in cleaner technologies to reduce carbon intensity and foster a sustainable energy transition. The results emphasize that while certain social dynamics may support the shift toward renewables, economic and environmental barriers remain significant. Effective policy responses such as promoting energy are crucial for accelerating the renewable energy transition in the Wester Balkans. Declarations Funding: Not applicable Data availability: The datasets generated and/or analysed during the current study are available in the World Bank’s World Development Indicators repository, https://data.worldbank.org/ Consent to Publish declaration: Not applicable Consent to Participate declaration: Not applicable Ethics declaration: Not applicable Conflict of interest: None Author Contribution Conceptualization, F.M. and A.H.; Methodology, F.M., A.H.; G.S.; Validation F.M., A.H and F.M.; G.SFormal analysis, F.M., A.H;G.S Investigation, F.M., A.H.; Data curation F.M., A.H; Writing original draft, F.M., A.H; Writing review & editing, F.M., A.H; G.S Visualization, F.M., A.H. All authors have read and agreed to the published version of the manuscript. 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An outlook at the switch to renewable energy in emerging economies: The beneficial effect of technological innovation and green finance. Energy Policy. 2024;187:114025. https://doi.org/10.1016/j.enpol.2024.114025 . Shaheen F, Zaman K, Lodhi MS, Nassani AA, Haffar M, Abro MMQ. Do affluent nations value a clean environment and preserve it? Evaluating the N-shaped environmental Kuznets curve. Environ Sci Pollut Res. 2022;29(31):47267–85. https://doi.org/10.1007/s11356-022-19104-2 . Spaargaren G, Mol APJ. Sociology, environment, and modernity: Ecological modernization as a theory of social change. Soc Nat Resour. 1992;5(4):323–44. https://doi.org/10.1080/08941929209380797 . Vo DH, Vo AT. Renewable energy and population growth for sustainable development in the Southeast Asian countries. Energy Sustain Soc. 2021;11(1):30. https://doi.org/10.1186/s13705-021-00304-6 . Vuchkova I. (2020). TRANSFORMATION IN THE WESTERN BALKANS: THE READINESS FOR A SUSTAINABLE ENERGY LANDSCAPE . https://doi.org/10.5281/ZENODO.4393659 Walker G, Devine-Wright P. Community renewable energy: What should it mean? Energy Policy. 2008;36(2):497–500. https://doi.org/10.1016/j.enpol.2007.10.019 . Young J, Macura A. (2023a). Forging Local Energy Transition in the Most Carbon-Intensive European Region of the Western Balkans. Energies , 16 (4), 2077. https://doi.org/10.3390/en16042077 Young J, Macura A. (2023b). Forging Local Energy Transition in the Most Carbon-Intensive European Region of the Western Balkans. Energies , 16 (4), 2077. https://doi.org/10.3390/en16042077 Additional Declarations No competing interests reported. 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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-8609460","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":592325979,"identity":"21b61c2f-1cd9-497f-8b5d-90b223ba21f9","order_by":0,"name":"Fatbardha Morina","email":"","orcid":"","institution":"Epoka University","correspondingAuthor":false,"prefix":"","firstName":"Fatbardha","middleName":"","lastName":"Morina","suffix":""},{"id":592325980,"identity":"970b7bae-773b-4c5d-be75-a75997bb42ad","order_by":1,"name":"Albina Hysaj","email":"","orcid":"","institution":"Epoka University","correspondingAuthor":false,"prefix":"","firstName":"Albina","middleName":"","lastName":"Hysaj","suffix":""},{"id":592325981,"identity":"c8da8af0-3ebe-4ff9-8881-ec8d823d306f","order_by":2,"name":"GÜVEN SEVİL","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4ElEQVRIiWNgGAWjYLCChAIbEGXA8ABEHSBKi0EaREsCRAtjA2E9BodJ0CLvf/iYxAOD8/Lm7Ic3PkhsY5Dju5HA/rgCjxbDG2lpEgkGtw139qQVGwC1GEveSGBsPINPywweYwOgFsYNB3LMJIBaEjeAtOBzmWH/+c9ALefsN5x/A9ZST1CLPEMO44MEgwNAwyG2JBgQ0mIgkWYI1JKcvOHGs2KDhHMShjPPPGycideW/sMPDv6osLPdcD5544MPZTbyfMeTD3zEa8sBVL4EEBOISXn80qNgFIyCUTAKgAAAzJFU63ri/GkAAAAASUVORK5CYII=","orcid":"","institution":"Anadolu University","correspondingAuthor":true,"prefix":"","firstName":"GÜVEN","middleName":"","lastName":"SEVİL","suffix":""}],"badges":[],"createdAt":"2026-01-15 10:23:36","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8609460/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8609460/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103056501,"identity":"c3fdd336-635d-4b91-8134-9eccd8cfa762","added_by":"auto","created_at":"2026-02-20 09:12:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":549207,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8609460/v1/f5fc85d3-ea3b-4e17-820b-bf0ae2860838.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Social, economic, and environmental drivers of renewable energy transition in WESTERN Balkans","fulltext":[{"header":"1.\tINTRODUCTION","content":"\u003cp\u003eThe nations worldwide are shifting their focus to the sustainable development practices to ensure long-term growth, environmental protection and the social inclusion. As the developed countries are making significant steps towards the achievements of the Sustainable Development Goals and the exploitation of natural sources, many developing regions such as the Western Balkan are still in the nascent stages, facing several challenges through this transition (Milutinovic and Jolovic, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Despite the investments of the recent years in the energetical sector, the Western Balkan countries mostly depend on sources such as coal, large hydropower, and fossil fuels. The reliance on those sources makes the energy consumption expensive and unsecure; causes environmental harm and increases the climate change concerns (Đurašković et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Rajić et al., 2025; Young and Macura, 2023). Moreover, the outdated infrastructure makes the process inefficient and the level of CO2 emissions high (Belis et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSeveral constrains such as limited access to capital, political instability and regulatory uncertainty makes the transition to the usage of the clean energy challenging (Kamali Saraji and Streimikiene, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), despite the potentials of the region sourcing from high solar radiation, strong wind corridors and abundant hydro resources (IRENA, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Apart of the other challenges, even though all the Western Balkan nations are dedicated to the EU Green Agenda for the Western Balkans (Ignjatović et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), the regional interconnection of the energy market is very week and there is a lack of mutual strategies to forward to the usage of clean energy (Đurašković et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Filipović and Ignjatović, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).The transition to renewable energy in Western Balkan countries is not only an environmental challenge. Rather, it is highly dependent on the incorporation of the social, economic, and environmental in the Western Balkans. Analysing each category of factors and the joint effect of all of them would contribute to the identification of the main drivers of the transition process (Ćetković and Buzog\u0026aacute;ny, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Jovanović et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe energy system of the Western Balkans is depended on imported energy or fossil fuels making it vulnerable to high price volatility, supply disruptions and economic pressure (Filipović and Ignjatović, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Gjukaj et al., 2024; Golušin et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The price volatility and the lack of a well-organized energy market in the region make the current energy system unsustainable. Furthermore, the necessity for a sustainable energy system is related to the continuous economic challenges of the region. The transition to renewable energy involves several fiscal, legal and economic reforms. Those reforms will overcome the financial constraints and increase the trust of the investors in this sector (Đurašković, et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Vuchkova, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the transition process are faced significant social challenges as well. Several social constrains such as the central planning system legacy and the low public awareness regarding the benefits of renewable energy contributes to limited public participations, disconnecting the societal energy needs with the energy policies (Akar, 2016; Đurović, 2021; Young and Macura, 2023). Moreover, other social problems such as energy access inequity, infrastructure gap, affordability and the low trust in the institutions are particularly existent in the rural areas (Petrović, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). To increase the social inclusiveness in the transition process requires a strong public support that can be achieved by the participation of residents and local communities in the planning process (Jegen and Audet, 2011; Walker and Devine-Wright, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe heavy dependence on coal and fossil fuels and the usage of outdated power plants leads to high greenhouse gas emissions and severe air pollution which negatively affects the economic productivity (Filipović and Ignjatović, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Rajić et al., 2025). The increased consumption of sustainable energy sources such as solar, wind, biomass and hydropower, would contribute to the achievement of environmental and economic goals because of the reduced emissions and improved air quality (Brkljača et al., 2021; Đurašković et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Mexhuani et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe transition to the renewable energy consumption in the Western Balkans is driven by several economic, social and environmental factors. Analysing those factors and the interactions among them, is important for the policy makers to design effective, inclusive, and sustainable clean energy policies. The purpose of this study is to analyse the main social, economic, and environmental factors that contribute to the renewable energy consumption in the Western Balkans. The following section presents a review of the relevant literature, continued by the methodology used to investigate the relationship between variables, the empirical findings and their interpretation, and the conclusions drawn from the study.\u003c/p\u003e"},{"header":"2.\tLITERATURE REVIEW","content":"\u003cp\u003eDue to the global focus on the Sustainable Development Goals, the interest of researchers in sustainability and renewable energy has earned significant interest. In recent years, even developing countries are making immense attempts to renewable energy transition and the combination of factors that would enable the transition, which is also reflected in the number of articles aiming to investigate this process. This section aims to deliver an overview of the relevant theoretical background and the empirical literature. The theoretical background subsection provides an overview of economic theories related to renewable energy transition. The empirical literature briefly reviewing the literature analysing the social, economic and environmental factors that contribute to the increased renewable energy consumption.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Theoretical Background\u003c/h2\u003e \u003cp\u003eThere are numerous economic theories and hypotheses that explain the determinant factors that contribute to the process of transition to renewable energy. One of the most important theories which explains the relationship between economic growth and environmental quality through a U-shaped curve is the Environmental Kuznets Curve (Apergis and Ozturk, 2015; Dinda, 2004; Stern, 2004). The U shape indicates that when economic development is at the early stages, the environmental degradation increases because of the reliance of energy sector on fossil fuel, heavy industrialization, and lack of regulations. As economic growth reaches a significant level, the investments in improved technology, renewable infrastructure and utilization of clean energy sources would contribute to the decline of the environmental degradation (Sampene et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). However, the legitimacy of EKC depends on several factors such as economic liberalization, social awareness, environmental policies, and technological progress (Dasgupta et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2002\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAnother important theory is Ecological Modernization Theory (EMT). This theory states that the economic growth can be achieved through environmental protection and sustainability via institutional reforms, technological innovation, and modernization (Mol and Sonnenfeld, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). This theory highlights mutual role of government, society, and various market actors in the promotion of clean energy consumption, environmental regulation, and investment in renewable energy technology. It challenges the view that environmental degradation is an inevitable consequence of industrialization, arguing that the usage of the right policies and tools can lead to significant ecological improvements (Spaargaren and Mol, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e1992\u003c/span\u003e). However, critics of the theory oppose that in developing countries, inequality and a lack of environmental justice requires a more critical approach that considers the social dimensions of sustainability as well (Foster, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2005\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe Pollution Haven Hypothesis (PHH) explains the association between several macroeconomic and environmental factors. This hypothesis assumes that the developing countries with weak environmental enforcement tend to attract foreign investments in pollution-intensive industries. Based on this hypothesis, high foreign direct investments would contribute to increased emissions and environmental degradation (Santos and Forte, 2021; Shaheen et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, the foreign direct investments are influenced by several factors, such as the economic structure of the country, local policies, and so on, and they can be environmentally friendly as well (Otieno and Aduda, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Empirical Literature Review\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1 Economic Drivers of Renewable Energy\u003c/h2\u003e \u003cp\u003eAn increasing number of studies investigate the economic factors contributing to renewable energy consumption. Osińska et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) explore the factors driving the renewable energy consumption worldwide for the period 1995\u0026ndash;2019, by classifying the countries based on the development stage, indicated by the human development index. The authors find that the key economic determinants of renewable energy consumption are GDP, foreign direct investments, and terms of trade, while the effect of foreign direct investments is stronger in low-developed countries. According to Alam and Murad (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), the economic factors have a positive effect on renewable energy consumption in OECD countries. Their study explores the influence of economic growth, trade openness, and technological advancement in 25 OECD countries for 43 years by using the ARDL model. The authors find that all the variables positively affect renewable energy consumption in the long run, while in the short run the dynamics among them perform a mixed behaviour.\u003c/p\u003e \u003cp\u003eSadiq et al. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) analyse the impact of economic variables on the sustainable energy consumption in China for the period from 1981 to 2019. The results of the analysis reveal that economic growth, foreign direct investment, inflation, and population growth contribute to the increased renewable energy consumption in China. Additionally, Vo and Vo (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) examine the connection among growth, environment, and energy in the ASEAN region. The results suggest that the population growth increases the renewable energy consumption, while a Granger bidirectional causality is found among economic growth, energy consumption, and CO2 emissions.\u003c/p\u003e \u003cp\u003eAli et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) explore the impact of several economic, social, and environmental variables on renewable energy consumption in Asia from 1995 to 2020. The authors find that economic growth and foreign direct investments positively affect the renewable energy consumption, especially at low consumption levels. Also, Eyuboglu and Uzar (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) which explore how the socio-economic and environmental variables effect the renewable energy consumption in Italy from 1970\u0026ndash;2022, find that economic growth has a positive influence of the renewable energy consumption, while trade openness has an adverse impact. Similarly, Han et al. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) examine how trade openness and urbanization affect the renewable energy in China from 1990 to 2018. Based on the empirical results, the trade openness positively affects the non-renewable energy consumption and has a moderate positive effect on the consumption of the renewable energy.\u003c/p\u003e \u003cp\u003eConversely Mehmood et al. (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), which analyse the socio-economic determinants of renewable energy in the BRIC countries from 1988 until 2017, notice that economic growth negatively affects renewable energy due to the fact that citizens would prefer the consumption of fuel energy to achieve economic growth. However, trade openness is found to have a positive impact on renewable energy consumption. Also Melnyk et al. (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) investigates the socio-economic determinants of renewable energy in 36 OECD countries from 2001\u0026ndash;2015 by using random effect model. The authors find that increased GDP would decrease renewable energy consumption, indicating that the richer the countries the more likely they are to use non-renewable energy sources.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.2.2 Social Drivers of Renewable Energy\u003c/h2\u003e \u003cp\u003eSeveral studies examine how the social factors affect the renewable energy consumption. Pellegrini-Masini et al. (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) use survey data to analyse the effect of income, income inequality, and wealth inequality on energy consumption attitudes in European countries, proxied by the Sustainable Energy Care Index (SECI). The empirical findings suggest that economic equality, including both the income and wealth index explains 41% of the variability of the index of in national level. Income equality has an adverse effect on SECI, while wealth equality has a positive effect on SECI.\u003c/p\u003e \u003cp\u003eEyuboglu and Uzar (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) determine that GINI affects renewable energy in several channels, starting from political to investment, social, environmental and public awareness. The authors find a negative significant impact of inequality on the renewable energy consumption. Moreover, Uzar (2020) explores how income inequality affects renewable energy consumption in 43 countries, including both developed and developing nations, for the period 2000\u0026ndash;2015. The author finds that income inequality has a negative effect on renewable energy, indicating that fair income distribution is very important to the transition to renewable energy consumption. Additionally, Mehmood et al. (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) suggest that lower inequality contributes to increased level of renewable energy consumption.\u003c/p\u003e \u003cp\u003eAsongu and Odhiambo (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) analyse how income inequality impacts the renewable energy consumption in 34 sub-Saharan lower and middle-income countries by utilizing quadratic Tobit regression. The authors utilize three measures of inequality: Gini, Palma, and the Atkinson Index. The findings indicate that only the Atkinson Index exhibits a U-shaped effect on renewable energy. Below the threshold, inequality negatively impacts renewable energy consumption, while above the threshold, it has a positive impact. Moreover, Acheampong et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) in their investigation, which includes 166 countries, find that an increased income inequality decreases both total energy consumption, although it increases the consumption of non-renewable energy. The authors argue that distribution would drive the total energy and renewable energy consumption whilst deducting the non-renewable energy consumption.\u003c/p\u003e \u003cp\u003eMahalik et al. (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) investigate the role of income inequality on renewable energy demand in several countries in South Asia from 1996 to 2018. Through a balanced panel model and by including controlling variables such as economic growth, CO2 emissions, and government effectiveness, the authors find that government effectiveness serves as an incentive to increase the demand for renewable energy. Nevertheless, the influence of income inequality, economic growth, and CO2 emission is adverse.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.2.3 Environmental Drivers of Renewable Energy\u003c/h2\u003e \u003cp\u003eSeveral studies analyse the effect of renewable energy on the CO2 emission, but the contingency of studies investigating the reverse impact is very limited. Nguyen and Kakinaka (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) in their sample of 107 countries between 1990 and 2013, conclude that the correlation among renewable energy consumption and CO2 emissions depends on the level of country development, and there are noticed significant disparities among low-income and high-income countries. In low-income countries, high levels of CO2 emissions are associated to higher renewable energy consumption levels. Conversely, in high-income countries, the relationship among CO2 emissions and renewable energy consumption levels is negative. Also, Apergis et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) which investigate the association among CO2 emissions, renewable, and nuclear energy in 19 developed and developing nations from 1984 to 2007 conclude the existence of a significant positive connection among CO2 emissions and renewable energy, while the association among the CO2 emissions and nuclear energy is adverse.\u003c/p\u003e \u003cp\u003eAn investigation for BRICS countries conducted by Mehmood et al. (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) between 1998\u0026ndash;2017 reveals that CO2 emissions are positively linked with renewable energy suggesting that high CO2 emission would urge the utilization of clean energy. Also Sadorsky (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) which analyse the drivers of renewable energy consumption in G7 countries find a positive association among CO2 emissions and renewable energy consumption, considering high emissions as e trigger of clean energy.\u003c/p\u003e \u003cp\u003eConversely, Eyuboglu and Uzar (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) find that CO2 emissions negatively affect the renewable energy. Also, Perone (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) finds a negative association among the renewable energy and CO2 emission in OECD countries.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"3.\tDATA AND METHODOLOGY","content":"\u003cp\u003eThe study aims to examine the effect of social, economic and environmental factors on renewable energy transition in Western Balkans countries. It includes six countries Albania, Kosovo, North Macedonia, Montenegro, Bosnia \u0026amp; Herzegovina, and Serbia over the period 2000 to 2023 using annual data. To estimate the model, panel data methods are applied, specifically the Random Effects model. The Hausman test is conducted as a post estimation robustness check to determine the appropriateness of the Random Effects model. Based on the theoretical framework and insights form the existing literature the following model that is employed:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:RE=f(GINI,\\:TRADE,\\:GDP,\\:POP,\\:{CO}_{2})$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere renewable energy consumption as a percentage of total final energy consumption RE is used as a proxy for renewable energy transition. The \u003cem\u003eGINI\u003c/em\u003e index is employed to represent social factors, where a value of 0 indicates perfect equality and a value of 100 signifies perfect inequality. Economic factors are captured through three variables: \u003cem\u003eTRADE\u003c/em\u003e, defined as the sum of exports and imports of goods and services as a percentage of gross domestic product; \u003cem\u003eGDP\u003c/em\u003e growth, measured as the annual percentage growth rate of GDP at market prices based on constant local currency; and \u003cem\u003ePOP\u003c/em\u003e, the annual population growth rate. Environmental factors are represented by \u003cem\u003eCO\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e emissions, measured in metric tons per capita. All variables are based on secondary data collected from the World Bank\u0026rsquo;s Indicators database.\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\u003eDescriptive Statistics\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=\"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=\"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\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eObs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStd. Dev.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMax\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27.773\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.773\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e54.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGINI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e65.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.901\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.089\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.099\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTRADE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e91.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21.109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e166.147\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGDP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e71.471\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40.397\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePOP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.457\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.651\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-3.758\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.967\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"4.\tEMPIRICAL RESULTS","content":"\u003cp\u003e \u003cem\u003ePanel Unit Root test\u003c/em\u003e \u003c/p\u003e \u003cp\u003eAmong the available panel unit roots test, the Im, Pesaran and Shin, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2003\u003c/span\u003e (IPS) test is considered one of the most suitable for unbalanced panel data. This test is designed to determine whether a variable is stationary in level or contains a unit root across individual cross-sectional units. Based on the results of the IPS test, it is found that RE (renewable energy consumption) and GINI index are stationary only after first differencing, indicating that they are integrated of order one, I(1). In contrast, all other variables TRADE, GDP growth, POP, and CO2 emission are stationary at level.\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\u003ePanel unit root tests results.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIPS (2003)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.5135 (0.696)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD(RE)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-5.231***(0.000)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGINI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-1.314*(0.094)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD(GINI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-3.815***(0.000)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTRADE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-1.745**(0.040)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGDP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-4.432 ***(000)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePOP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-3.754***(0.000)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCO2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.480**(0.006)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e\u003cb\u003eNotes\u003c/b\u003e: Probability values are reported in parentheses. Panel root test includes intercept and trend. ***,** and * denotes the significance at 1% and 5%, and 10% level, respectively. D(.) denotes the first difference.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAnother important diagnostic test involves checking for multicollinearity among independent variables. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, the pairwise correlation coefficients are all below the commonly accepted threshold of 0.8, indicating that multicollinearity is not a concern in the estimated model.\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\u003ePairwise correlations.\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=\"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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(3)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(4)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(5)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(1)GINI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(2) CO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.422*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(3) TRADE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(4) GDP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.070\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(5) POP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.251*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.332*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.040\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cem\u003e* shows significance at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e are shown the results of the regression model.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\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\u003eVARIABLES\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eD.RE\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD.GINI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e0.134**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e-0.0615\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e-0.163**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e-0.0651\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTRADE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e-0.00715\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e-0.00732\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGDP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e-0.0166***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e-0.0055\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePOP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e-0.442\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e-0.418\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e2.576**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e-1.022\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of countries\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR-squared\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e0.2753\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWald chi2(5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e67.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProb\u0026thinsp;\u0026gt;\u0026thinsp;chi2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e0.0000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eRobust standard errors in parentheses\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c3\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e*** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, * p\u0026thinsp;\u0026lt;\u0026thinsp;0.1\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe regression results indicate that among the three main groups of factors social, economic, and environmental, the most statistically significant determinants of the renewable energy transition in Western Balkan countries are the GINI coefficient, GDP growth and CO2 emission.\u003c/p\u003e \u003cp\u003eThe GINI representing social factors, is statistically significant and positively associated with renewable energy transition.\u003c/p\u003e \u003cp\u003eAmong economic factors, GDP growth exhibits a statistically significant negative effect on renewable energy transition in Western Balkan countries. Specifically, a one percentage point increase in GDP growth leads to a 0.016 percentage point decline in renewable energy consumption, indicating that economic expansion in the region may still rely heavily on conventional energy sources. In contrast, trade openness and population growth also show a negative coefficient, but the effects are not statistically significant, suggesting they do not play a decisive role in influencing renewable energy use.\u003c/p\u003e \u003cp\u003eRegarding the environmental factors, CO2 emissions in metric tons per capita are found to have a negative and statistically significant impact on renewable energy at the 5% significant level. A one percentage increase in CO2 emission is associated with a 0.163 percentage decrease in renewable energy consumption. This finding highlights the ongoing dependence of Western Balkan countries on fossil fuel and suggests that behavioral and infrastructural shifts toward renewable energy may require more time and strong policy incentives.\u003c/p\u003e"},{"header":"5.\tCONCLUSION","content":"\u003cp\u003eLegislative and political barriers hinder the process of renewable energy transition in Western Balkan countries. Except Albania that generates energy by using renewable energy sources and hydropower, other Western Balkan countries depend on coal as traditional sources that cause high environmental pollution. Thus, the aim of this study provides important findings into the key determinants of the renewable energy transition in the Western Balkan countries over the period 2000\u0026ndash;2023 by using annual data. In order to decide the determinants of the transition, factors are categorized into social, economic, and environmental groups. The results reveal that income inequality (GINI index), GDP growth, and CO\u003csub\u003e2\u003c/sub\u003e emissions are the most significant variables shaping renewable energy consumption patterns in the region.\u003c/p\u003e \u003cp\u003eThe positive and statistically significant relationship between the GINI coefficient and renewable energy transition suggests that, paradoxically, higher income inequality may coincide with increase renewable energy adoption. This may be due to policy efforts targeted at expanding energy access or addressing disparities in energy services. However, this does not imply that inequality is desirable, but rather that inclusive energy policies can play a key role in supporting the transition.\u003c/p\u003e \u003cp\u003eConversely, GDP growth shows a significant negative impact on renewable energy consumption, indicating that the region\u0026rsquo;s economic expansion continues to depend heavily on conventional energy sources. This underlines the need for structural economic reforms and green investment strategies that decouple the economic development from fossil fuel use.\u003c/p\u003e \u003cp\u003eThe negative and significant effect of CO\u003csub\u003e2\u003c/sub\u003e emissions further confirm the persistence of fossil fuel dependency in the region and the challenges it poses to clean energy development. This finding points to the necessity for stronger environmental policies and investment in cleaner technologies to reduce carbon intensity and foster a sustainable energy transition.\u003c/p\u003e \u003cp\u003eThe results emphasize that while certain social dynamics may support the shift toward renewables, economic and environmental barriers remain significant. Effective policy responses such as promoting energy are crucial for accelerating the renewable energy transition in the Wester Balkans.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eNot applicable Data availability: The datasets generated and/or analysed during the current study are available in the World Bank\u0026rsquo;s World Development\u003c/p\u003e \u003cp\u003eIndicators repository, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://data.worldbank.org/\u003c/span\u003e\u003cspan address=\"https://data.worldbank.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003eConsent to Publish declaration: Not applicable\u003c/p\u003e \u003cp\u003eConsent to Participate declaration: Not applicable\u003c/p\u003e \u003cp\u003eEthics declaration: Not applicable\u003c/p\u003e \u003cp\u003eConflict of interest: None\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization, F.M. and A.H.; Methodology, F.M., A.H.; G.S.; Validation F.M., A.H and F.M.; G.SFormal analysis, F.M., A.H;G.S Investigation, F.M., A.H.; Data curation F.M., A.H; Writing original draft, F.M., A.H; Writing review \u0026amp; editing, F.M., A.H; G.S Visualization, F.M., A.H. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated and/or analysed during the current study are available in the World Bank\u0026rsquo;s World DevelopmentIndicators repository, [https://data.worldbank.org/](https:/data.worldbank.org)\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAcheampong AO, Boateng E, Annor CB. Do corruption, income inequality and redistribution hasten transition towards (non)renewable energy economy? Struct Change Econ Dyn. 2024;68:329\u0026ndash;54. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.strueco.2023.11.006\u003c/span\u003e\u003cspan address=\"10.1016/j.strueco.2023.11.006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlam MM, Murad MW. 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Forging Local Energy Transition in the Most Carbon-Intensive European Region of the Western Balkans. \u003cem\u003eEnergies\u003c/em\u003e, \u003cem\u003e16\u003c/em\u003e(4), 2077. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/en16042077\u003c/span\u003e\u003cspan address=\"10.3390/en16042077\" 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":"discover-sustainability","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"disu","sideBox":"Learn more about [Discover Sustainability](https://www.springer.com/43621)","snPcode":"","submissionUrl":"","title":"Discover Sustainability","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8609460/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8609460/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe renewable energy transition in the Western Balkans is shaped by a complex interplay of social, economic, and environmental factors. Social dynamics such as increasing public awareness of climate change and a growing demand for cleaner, more sustainable energy play a critical role. Economic considerations, including energy security, long-term cost efficiency, and employment generation, further motivate the shift. Environmental imperatives, such as the need to reduce greenhouse gas emissions and mitigate the negative effects of fossil fuel dependency, also drive the transition. This study investigates the impact of social, economic, and environmental variables on renewable energy transition in six Western Balkan countries, Albania, Kosovo, North Macedonia, Montenegro, Bosnia and Herzegovina, and Serbia over the period 2000\u0026ndash;2023. Employing a Random Effects panel data model, the results show that the GINI index has a statistically significant positive effect on renewable energy consumption, while GDP growth and CO\u003csub\u003e2\u003c/sub\u003e emissions have negative and significant effects. These results indicate that policymakers should implement strong carbon mitigation policies in order to increase renewable energy investments.\u003c/p\u003e","manuscriptTitle":"Social, economic, and environmental drivers of renewable energy transition in WESTERN Balkans","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-17 12:17:31","doi":"10.21203/rs.3.rs-8609460/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-06T17:40:28+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-24T10:33:08+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-17T16:22:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"330160381267077012589448667190826111152","date":"2026-02-16T17:51:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"79994890014727672588288857615649682939","date":"2026-02-14T18:47:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"237764924561696716971068468762136385275","date":"2026-02-14T17:17:35+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-11T16:50:53+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-24T06:35:59+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-24T06:33:45+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Sustainability","date":"2026-01-15T10:16:35+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-sustainability","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"disu","sideBox":"Learn more about [Discover Sustainability](https://www.springer.com/43621)","snPcode":"","submissionUrl":"","title":"Discover Sustainability","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"17023ae2-0f75-4120-a570-43f624bae9d3","owner":[],"postedDate":"February 17th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-01T13:10:13+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-17 12:17:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8609460","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8609460","identity":"rs-8609460","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}