Exploring the impacts of institutional quality, globalization, and urbanization on environmental pollution in Somalia: a disaggregate analysis of globalization

Exploring the impacts of institutional quality, globalization, and urbanization on environmental pollution in Somalia: a disaggregate analysis of globalization | 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 Article Exploring the impacts of institutional quality, globalization, and urbanization on environmental pollution in Somalia: a disaggregate analysis of globalization Hassan Abdikadir Hussein, Abdimalik Ali Warsame, Abdikafi Hassan Abdi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3913734/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Environmental pollution and its implications are widespread issues that require a comprehensive understanding of effective strategies that mitigate emissions. Given the unique challenges faced by Somalia, including social, political, and environmental challenges, it is crucial to assess the effects of social and political globalization, urbanization, and institutional quality on greenhouse gas (GHG) emissions. Hence, the study aims to examine the relationship between these variables and the environmental deterioration in Somalia. The study utilizes the autoregressive distributed lag (ARDL) bound test, fully modified ordinary least squares (FMOLS) method, and causality tests. The empirical results of the bound test indicate that institutional quality and social globalization have a significant negative impact on environmental pollution in Somalia in the long run. On the contrary, economic growth impedes environmental quality in Somalia in the long run. However, the remaining explanatory variables are inconsequential in the long run. To find robust results, we perform the fully modified ordinary least squares (FMOLS) as a robust analysis. The findings revealed that social globalization and institutional quality improve environmental quality by reducing GHG emissions whereas urbanization significantly hampers it. Based on the empirical evidence, the study offers several policy implications. Earth and environmental sciences/Environmental sciences Earth and environmental sciences/Environmental social sciences GHG emissions globalization Institutional quality Urbanization Somalia Figures Figure 1 Figure 2 Figure 3 1. Introduction The linkage between globalization, institutional quality, and environmental sustainability has emerged as a pivotal theme in contemporary ecological discourse. Greenhouse gas (GHG) emissions have grown since the initiation of the industrial age, which has had an upsurge in radiative force on the climate and a tendency to warm the surface and cause climatic changes (Abdi, 2023 ; Canadell et al., 2021 ) At the heart of this dialogue is the recognition of how social and political globalization, through the transnational flow of ideas, cultural values, and political ideologies, can reshape environmental governance across the globe (Dauvergne, 2013 ). While social globalization facilitates the diffusion of environmental consciousness and green technologies, political globalization often promises the proliferation of international treaties and collaborative governance frameworks (A Jahanger et al., 2023 ). The effectiveness of these processes is supported by the quality of institutional frameworks, which are crucial for converting international agreements into concrete environmental results (Bekun et al., 2021 ). Robust institutions are identified as a cornerstone for effective environmental policy-making and for the enforcement of measures aimed at reducing GHG emissions (Uzar, 2020 ; Warsame, Sheik-Ali, et al., 2022 ). Thus, it is remarkable to identify the interaction between globalization, institutional quality, and GHG emissions in developing countries to implement effective environmental policies that mitigate their ecological footprints. Empirical studies suggest that globalization has a variety of effects on the environment, depending on the channel via which it enters. The globalization process has an impact on environmental quality as it alters variables including energy, employment, technology, foreign direct investment (FDI), and industrialization (Pata & Caglar, 2021 ). It is widely agreed that the process of globalization has effectively reduced the income gap existed between emerging and developed nations through investments in capital and technologies (Atif Jahanger et al., 2022b ). However, this has come at the expense of environmental deterioration. The positive impacts of globalization are examined to its effect on ecological quality, specifically in terms of reducing environmental pollution (Atif Jahanger et al., 2022a ). Many researchers claim that the process of globalization has a detrimental effect since it amplifies the total pollution level via the heightened breakdown resulting from increased CO 2 emissions(Warsame et al., 2023; Chien et al., 202 ;Suki et al., 2020 ). CO 2 emissions resulting from globalization are identified as a primary factor contributing to deforestation, natural resource depletion, climate change, and global warming (H. Khan et al., 2022a ) During the process of globalization, the industrial sector engages in the production of goods to cater to international demand, resulting in heightened consumption of resources and the emission of pollutants into the atmosphere (Pata & Yilanci, 2020 ;Pata & Yilanci, 2020 ). The engagement in increased production and consumption activities has the potential to directly contribute to the escalation of environmental deterioration (Pata & Caglar, 2021 ) . The significance of globalization lies in the facilitation of technological transfer and collaboration across nations in addressing the issue of climate change (Ansari et al., 2021 ). Since the use of non-renewable energy sources is closely linked to the pace of economic expansion, the increasing global demand for goods and services has necessitated a rise in energy consumption (H. Khan et al., 2022a ; Abdi, 2023 ). Notably, environmental regulations in developing countries often attract pollution-intensive industries from advanced nations, leading to environmental deterioration in the receiving regions(Wenlong et al., 2023 ; Shahbaz et al., 2015 ) .This phenomenon contributes to emissions, where shifts in production locations due to varying environmental standards result in the redistribution of emissions from one country to another. On the contrary, globalization encourages knowledge transfer to developing nations and the adoption of cleaner production methods, which positively impacts the environment. International relationships between multinational corporations and countries have aided in the diffusion of technological advances into emerging economies, aiding in some manner in ecosystem preservation (Adebayo et al., 2022 ). The spread of expertise and eco-friendly technology not only enhances environmental quality but also improves labor efficiency and capital productivity, streamlining manufacturing and reducing emissions (Mansoor & Tahir, 2021 ; Wen et al., 2021 ). Conversely, numerous studies have extensively investigated the impact of institutional strength as a determining factor in improving environmental quality. Environmental issues in developing nations often correlate with weak institutional frameworks, especially in the political realm, leading to ineffective enforcement of environmental laws (H. Khan et al., 2022b ). The studies have thoroughly investigated the role of institutional factors such as governance effectiveness, democracy, legal systems, political stability, and regulatory quality in impacting environmental challenges, particularly in terms of emissions (Wenlong et al., 2023 ;Warsame, Sheik-ali, et al., 2022 ). It has been demonstrated that robust institutions can avert market inefficiencies, create impactful regulations, and formulate effective environmental strategies, all of which contribute positively to environmental health (Wenlong et al., 2023 ). On the flip side, subpar institutional quality often results in inefficient resource management and environmental deterioration (Atif Jahanger et al., 2022a ). Overall, the effectiveness of institutions is crucial to environmental outcomes, highlighting the necessity for robust legislative and institutional mechanisms to reduce environmental harm and foster sustainable global practices (Azam et al., 2021 ). Several researchers have suggested that strong institutional structures can suppress environmental degradation (Cao et al., 2022 ; Sheraz et al., 2022 ). However, the evidence Teng et al., ( 2021 )and Islam, ( 2021 )reveals that institutional quality increases environmental deterioration. Regarding this, the literature on the institutional quality-environment nexus remains inconclusive, which necessitates further investigation, particularly in countries with deficient government institutions such as Somalia. Research on industrialized nations has dominated global inquiries into elevated atmospheric carbon effects, but recent concerns have expanded the focus to include developing economies as well (Abdi, 2023 ). In Somalia,Warsame & Hassan Abdi, ( 2023 ) discovered that sustained environmental pollution and degradation negatively impact the agricultural sector, a significant contributor to the nation's export earnings. Amidst the continuing discourse on the effects of globalization and institutional quality on environmental degradation, the current study examines the connection between quality institutions, social and political globalization, urbanization and GHG emissions in Somalia by using time-series data from 1990–2018. To the best of the authors’ knowledge, there is no previous effort to analyze the connection between these variables within a single framework in the context of Somalia. Hence, this study contributes to the literature as follows. The few prior studies related to the subject in the context of Somalia have used the aggregated variable of globalizationWarsame et al., ( 2023b ) which does not capture the actual effects of globalization on the environment since the various components of globalization affect environmental quality differently. Additionally, the study utilizes advanced estimation methods, including the autoregressive distributed lag (ARDL) model, fully modified ordinary least squares (FMOLS), and causality tests. These techniques are applied to derive more thorough policy suggestions based on the linkage between globalization, institutional quality, and GHG emissions in the context of Somalia. The structure of this paper is outlined as follows. Section two represents a review of the literature. Section three delineates the econometric methods employed and the data sources utilized. The findings and discussions are presented in section four, while the concluding section offers a summary and outlines the pertinent policy implications. 2. Literature review 2.1 Globalization and Environmental Pollution The dimensions of globalization (economic, political, and social), economic growth, and institutional quality are key factors that have a significant influence on environmental degradation. Globalization refers to the rising economic connectedness between nations, encompassing the facilitation of free trade, the exchange of information, international capital movements, and the expanding mobility of labor. (Fischer, 2003 ). Considering its relation to industrialization and urban growth, this process has global environmental concerns (Veen-Groot & Nijkamp, 1999 ). Globalization is categorized into three primary dimensions: social, economic, and political globalization. These dimensions are quantified and represented as an index developed by the KOF Swiss Economic Institute (Dreher, 2006 ). Similarly, According to Dreher, ( 2006 ), globalization describes the process of creating networks of connections among actors at intra- or multi-continental distances, mediated through a variety of flows including people, information and ideas, capital, and goods. Economic globalization encompasses the movement of capital and services, the long-distance transportation of goods, as well as the exchange of ideas and information that accompany market transactions. Social globalization refers to the dissemination of information, ideas, and images. Political globalization refers to the spread of institutional policies. Hence, the relationship between globalization and the environment has resulted in escalating levels of apprehension. Gaining a comprehensive understanding of this enduring link is crucial for decision-makers who are committed to attaining sustainable development. To further such development, it is imperative to consider environmental, social, and economic issues. Even though the link between globalization and the environment has garnered a lot of attention in recent years, most in the empirical literature (Kihombo et al., 2021 ). Several studies in the current literature have examined generic aspects without delving into the particular channels and causal relationships between the two variables. For instance, several studies emphasized the impact of the economic components of globalization, particularly those relating to trade. Most of thesestudies have identified that economic globalization enhances environmental quality in developing countries (Kihombo et al., 2021 ; Sasana et al., 2018 , Ahmad et al. 2021, Jahanger et al., 2022; Xiaoman et al., 2021). Additionally, Kihombo et al., ( 2021 ) assessed the effect of financial globalization on the environmental quality measured by (ecological footprint) in West and Middle East countries from 1990 to 2017. They reported that financial globalization reduces the ecological footprint. Similarly, Ahmed et al., ( 2021 ) explored the effect of economic globalization on the ecological footprint in Japan for the period from 1971 to 2016. The empirical results uncovered that economic globalization enhances ecological sustainability in Japan. On the other hand, ample studies confirmed the adverse effects of economic globalization on environmental quality(Ahmed et al., 2021 ;Destek, 2020 ; Yilanci, 2020 ). Moreover, Yurtkuran, ( 2021 ) examined the effects of economic globalization on CO 2 emissions in Turkey using the bootstrap ARDL approach between 1970 and 2017. The empirical results highlighted that economic globalization has detrimental effects on Turkey's environmental quality. Additionally, Destek, ( 2020 ) examined different dimensions of globalization on environmental pollution in Central and Eastern European Countries from 1995 to 2015. It was observed that economic globalization raises environmental degradation. Social globalization refers to the sharing of ideas and information between and through different countries as well as the cross-border movement of cultures and openness of media. Social globalization can have a positive or negative effect on the environment. Internet and social media encourage people to consume more, which can be a problem for the environment (Bu et al., 2016 ). Moreover, the irrational development of the internet and the massive use of related devices lead to an increase in power consumption, which may negatively impact the environment (Chen, X.; 2019). Salahuddin et al., ( 2016 ) concluded that internet usage is harmful to environmental quality. On the other hand, social globalization enhances environmental quality through international social integration which might generate more environmental technology spillovers that lead to better environmental quality (Atif Jahanger et al., 2022a ; Mehmood, 2021 ) Political globalization measures the degree of the country’s international political engagement (Heshmati, 2006 ). The nexus between political globalization and environmental quality indicated blended results. Some studies reported that political globalization hinders environmental quality(Sasana et al., 2018 ; Shahbaz et al., 2015 ; Mehmood, 2021 ). While other studies stated that political globalization promotes environmental quality (Akif, 2021 ; Lenz & Fajdetić, 2021 ). 2.2 Institutional Quality and Environmental Pollution The connection between institutional quality and environmental pollution has gained substantial attention in the realm of sustainability and development. As environmental challenges such as climate change, pollution, and habitat loss continue to escalate, understanding how quality institutions influence environmental outcomes has become crucial (Ahmad et al., 2023 ). Institutional quality encompasses the effectiveness, transparency, accountability, and governance practices of institutions within a country (Amin et al., 2023 ). Moreover, Institutional quality implies the set of norms that govern relationships in social, political, and economic conditions that indicate human behavior (Hussain et al., 2020 ). Effective institutions can shape environmental quality through regulation, policy formulation, and the enforcement of environmental standards. Weak institutions, on the other hand, may hinder efforts to protect the environment. This literature review examines the existing research on the relationship between institutional quality and CO 2 emissions to better understand how institutional factors shape environmental outcomes. One fundamental aspect of institutional quality is the ability of governments to enact and enforce environmental regulations. Ample studies reported that institutional quality enhances environmental quality such as Ahmad et al., ( 2022 ) in emerging countries, (Kwakwa, 2023 ) in African countries, (Atif Jahanger et al., 2022b ) in 69 developing countries, ( Ahmed et al., 2020 ) in Pakistan (Danish & Ulucak, 2020 ) Asia-Pacific Economic Cooperation (APEC) countries. In the same vein, Islam, ( 2021 ) assessed the impact of institutional quality on CO 2 emission in Bangladesh over the period 1972–2016 by utilizing the ARDL technique. They found that institutional quality raises environmental quality. Similarly, according to Salman et al. (2019), effective local institutions have a significant role in fostering economic growth and reducing environmental deterioration. Moreover, Warsame et al., ( 2022 ) investigated the effect of institutional quality on environmental degradation in Somalia using data spanning 1990–2017. The empirical result indicated that institutional quality enhances environmental quality. Hussain & Dogan, ( 2021 ) investigated the nexus between institutional quality and environmental degradation in BRICS nations by employing data from 1992 to 2016. They reported that institutional quality reduces environmental degradation. Conversely, Numerous studies have shown that environmental quality is hampered by institutional quality (Khan et al., 2022, Wu, 2017 ). Amin et al., ( 2023 ) stated that institutional quality contributesto environmental degradation in South Asian countries. Azam et al., ( 2021 ) assessed the effect of institutional quality on environmental degradation in 66 developing countries using Generalized Method of Moments (GMM) for the period 1991–2017. The empirical findings on the institutional quality-environmental pollution nexus produced inconsistent results because of the various environmental quality measures. 2.1 Urbanization and Environmental Pollution Urbanization has become an essential global trend that has changed the globe's environment and has had enormous impacts on social, economic, and environmental conditions. The effects of urbanization on environmental quality have become a major issue as more people shift to urban areas. The impacts of urbanization on environmental quality revealed conflicting conclusions because of the differences in economic prosperity between the countries. Studies concentrated on developing nations found that urbanization degrades environmental quality (Ansari et al., 2021 , Rahman & Vu, 2020 , Khan et al., 2019 ). Doğan et al., ( 2019 ) revealed that the rate of urbanization undermines the environmental quality in lower- and higher-income countries. Similarly, Islam, ( 2021 ) reported that urbanization raises CO 2 in Bangladesh. A recent study by Abdi, ( 2023 ) found that urbanization contributes to the deterioration of environmental quality in 41 nations in Sub-Saharan Africa. Conversely, Danish et al., (2020) explored the role of urbanization on environmental quality in BRICS for the period 1992–2016. They revealed that urbanization improves environmental quality. Similarly, Gasimli et al., ( 2019 ) assessed the nexus between urbanization and environmental degradation in Sri lank. They demonstrated that urbanization decreases carbon emissions. 3. Materials and method 3.1 Data sources and descriptions The current study investigates the impact of social, and political globalization, urbanization, and institutional quality on greenhouse gas emissions in Somalia using balanced secondary data from 1990 to 2018. The sample period is determined by the availability of the data. The World Bank, KOF, and SESRIC are the sources of the data. Among the factors sampled for the study are environmental degradation measured by GHG emissions, globalization dimensions, institutional quality, and economic growth. Natural logarithm transformations of each variable were applied to remove heteroskedasticity. Economic growth and urbanization are hypothesized to have a significant contribution to the rise in environmental degradation. According to Warsame et al., (2023) indicate that economic growth raises environmental pollution. Thus, to account for these effects on environmental degradation, economic growth is utilized as a control variable. The data and its sources are shown in Table 1, and the trends of the sampled variables are presented in Figure 1. Table 1: Data sources and description Variable Code Description Source Environmental degradation GHG Greenhouse gas emissions World Bank Real Gross Domestic Product RGDP Real gross domestic product SESRIC Urbanization UR Percent of urban population to the total population World Bank Institutional Quality IQ Combination of Political and Civil Rights. Freedom House Globalization GL Kof Globalization index KOF 3.2 Econometric methodology To achieve the objective of the study, the ARDL approach is utilized. The ARDL approach performs better than other cointegration techniques in many aspects. Firstly, small sample sizes may be employed with the ARDL as it does not require long time-series data. Secondly, the ARDL has the flexibility of regressing whether the variable is stationary at level I (0), first difference I (1), or the combination of both. Thirdly, unlike other methods. The variables' long- and short-term cointegrations are simultaneously regressed (Pesaran et al., 2001). Following the previous undertakings of Warsame et al., (2023), and Usman et al., (2021), we specify the model specification of the study as follows: Whereas α 1-7 is the coefficient of short-tun, and α 0 is the intercept β 1-7 indicate the coefficient of long-run variables, ∆ is the function of the first difference, p denoted the number of lags and the ECT is the error correction term and Ɛ t is the error term. It is crucial to ascertain the dependent and independent variables' long-term cointegration. Thus, we apply the ordinary least square (OLS) approach to regress equation (2). Using the Wald F-statistic, the alternative hypothesis—which asserts that there is cointegration between the variables—is compared to the null hypothesis, which maintains that there is no cointegration among the variables in Somalia. The hypothesis is formulated as follows: 4. Empirical findings and discussion 4.1 Descriptive statistics Summary statistics of the sampled variables are reported in Table 2. Mean values of greenhouse gases (10), institutional quality (1.9), globalization (3.25), political globalization (3.3), economic growth (21.7), social globalization (2.9), and urbanization (3.5) are observed. Economic growth is established to have the highest maximum values compared to other parameters. Similarly, economic growth is recorded to have the highest standard deviation value which implies that its values are scatter compared to other sampled variables. Greenhouse gases, institutional quality, and political globalization are negatively skewed whereas the rest of the parameters are positively skewed. In contrast, the correlations of the interested variables are also presented in Table 2. All the parameters are positively associated with greenhouse gases except institutional quality which has a negative correlation with greenhouse gases. Table 2: preliminary analysis of the data 4.2 Unit root test All the sampled parameters have passed the unit root test and confirmed that they are stationary at the combination of level I(0) and first difference I (1). We contend the existence of long-run cointegration between the dependent variable (GHG) and the explanatory variables – institutional quality, globalization, political globalization, economic growth, social globalization, and urbanization. We have also performed the unit root test of the structural break as presented in Table 3. It underscored that the variables are stationary the combination of of both levels – level and first difference. Table 3: unit root test The bound test result is displayed in Table 4. The bound F-statistics is greater than the upper bound critical value at the 1% significance level, hence, confirming that the explanatory variables are cointegrated with the dependent variable in the long run. Furthermore, the long-run coefficients of the sampled parameters are also reported in Table 4. It was observed that institutional quality, economic growth, and social globalization significantly affect environmental pollution in Somalia in the long run whereas the rest of the sampled explanatory variables are inconsequential in the long run. Interpretively, a 1% increase in institutional quality enhances environmental quality by about 1.01% in the long run in Somalia. Similarly, social globalization improves environmental quality in Somalia in the long run. A 1% increase in social globalization is associated with environmental pollution to decrease by about 0.83% in the long run. On the contrary, economic growth hampers environmental quality in Somalia in the long run. A 1% increase in economic growth impedes environmental quality by about 0.65% in Somalia in the long run. Table 4: Long-run coefficients results After examining the long-run coefficients of the parameters, we subsequently estimate the short-run dynamic effects of the sampled parameters. Its result is displayed in Table 5. It was observed that economic growth, social globalization, and urbanization significantly affect environmental pollution in the short run, but other regressors are statistically insignificant. A 1% increase in economic growth leads to environmental pollution increasing 0.11% in the short run. Moreover, Social globalization improves environmental quality by about 0.33% in the short run for a 1% increase in social globalization. In the same vein, a 1% increase in urbanization leads to an environmental quality increase of about 0.49% in the short run. More importantly, the ECT is significant and has a negative coefficient which implies that the model makes convergence. Further, the diagnostic results of the model such as the serial correlation, heteroskedasticity, reset test, and normality test, are presented in Table 6. It was observed that the model is free from all the diagnostic problems. The goodness fit of the model also revealed that the model is better as shown by the adjusted R-squared. The independent variables explain that 84% of the variations happen in environmental pollution in Somalia. Moreover, the model of the study is reliable as shown in figure 2 and 3-Cusum and Cusum square tests respectively. Table 5: Short-run coefficient results 4.3 Granger Causality The results of the Pairwise Granger causality are reported in Table 7. Several unidirectional causalities from environmental pollution to social globalization and from institutional quality to globalization, urbanization, and political globalization are observed. It was also established from a unidirectional causality from urbanization to globalization. Finally, economic growth Granger causes social globalization. Table 7: Pairwise Granger Causality Tests 4.4 Robust analysis To find robust results, we perform the fully modified ordinary least squares (FMOLS) as a robust analysis. Its result reported in Table 8 revealed that institutional quality, social globalization, and urbanization are statistically significant. Both social globalization and institutional quality improve environmental quality by reducing GHG emissions whereas urbanization significantly hampers environmental quality by increasing GHG emissions. Table 8: Fully Modified Least Squares (FMOLS) Discussion of the result Social globalization enables the transfer of knowledge, ideas, and information between different countries. It provides individuals in Somalia with the ability to obtain information regarding sustainable practices, environmental preservation, and renewable technology from various parts of the globe. Enhanced consciousness can result in shifts in attitudes and behaviors regarding the environment, fostering endeavors to preserve and achieve sustainable progress. This result aligns with the recent study conducted by Rong et al., (2024), which concluded that social globalization enhances environmental quality in China. Extensive studies have demonstrated that social globalization promotes environmental quality such as Lenz & Fajdetić, (2021) for EU, Jahanger et al., (2022) 74 developing countries. Mehmood, (2021) in Singapore. Moreover, Social globalization has an insignificant impact on environmental quality in panel data from 180 countries (Farooq et al., 2022). This finding contradicts numerous earlier studies that have indicated that social globalization adversely impacts environmental quality such as Deng et al., (2022) for a global sample of 107 countries, and Akif, (2021) for Central and Eastern European Countries. The institutional quality in Somalia has had significant effects on the country's levels of environmental pollution in the long run. In promoting sustainable environmental practices, it is crucial to create high-quality institutions that demonstrate effective governance structures, strong regulatory frameworks, and rigorous enforcement mechanisms. In scenarios when institutions exhibit fragility or suffer from corruption and incompetence, the enforcement of environmental standards may be deficient or ignored, resulting in escalated levels of pollution. On the other hand, robust institutions can create and enforce environmental regulations, oversee adherence to these regulations, and offer rewards for adopting sustainable methods. Institutions that place environmental protection as a top priority may encourage environmental education and awareness, enable the implementation of clean technology, and promote responsible resource management. Hence, enhancing the quality of institutions is crucial in mitigating environmental degradation in Somalia and securing a sustainable future for its ecosystems and communities. Our finding supports the study carried out by (Kwakwa, 2023) in African countries, (Atif Jahanger et al., 2022b) in 69 developing countries, ( Ahmed et al., (2020) in Pakistan, and Danish & Ulucak, (2020) Asia-Pacific Economic Cooperation (APEC) countries. However, this result contradicts other studies such as Amin et al., (2023) in south Asian countries and Azam et al., (2021) in 66 developing countries. Conclusion Environmental pollution and its associated consequences are worldwide issues that demand a thorough comprehension of effective measures for reduction in emissions. In the specific context of Somalia, a country struggling with distinctive social, political, and environmental obstacles, assessing the impact of social and political globalization, urbanization, and institutional quality on GHG emissions is extremely important. Therefore, the study aims to investigate the relationship between these variables and environmental degradation in Somalia. This enhances the understanding of the environmental issues faced by the country and provides helpful insights on possible strategies for attaining sustainable development. The study utilizes the autoregressive distributed lag (ARDL) model, fully modified ordinary least squares (FMOLS) methods, and causality tests. The empirical results of the bound test indicate that institutional quality, economic growth, and social globalization have had a significant impact on environmental pollution in Somalia in the long run. However, the remaining explanatory variables included in the sample are inconsequential in the long run. It was observed that economic growth, social globalization, and urbanization significantly affect environmental pollution in the short run, but other regressors are statistically insignificant. To find robust results, we perform the fully modified ordinary least squares (FMOLS). The findings revealed that institutional quality, social globalization, and urbanization are statistically significant. Both social globalization and institutional quality improve environmental quality by reducing GHG emissions whereas urbanization significantly hampers environmental quality by increasing GHG emissions. Based on the empirical evidence, the study offers several policy implications. In order the social globalization to enhance sustainable development, it requires setting policies that prioritize sustainability and safeguarding the environment. This entails the establishment and implementation of regulations to mitigate pollution, improve sustainable resource management, and protect ecosystems. In addition, promoting international collaboration and alliances can allow the sharing of knowledge, transfer of technology, and provision of financial assistance for sustainable development initiatives. Engaging in partnerships with other countries and international organizations can bolster Somalia's ability to effectively tackle environmental issues. Moreover, allocating resources to education and awareness initiatives can enhance environmental awareness among the populace, fostering conscientious purchasing habits and sustainable ways of living. Furthermore, the policy considerations of enhancing institutional quality to mitigate environmental deterioration in Somalia are significant. Improving institutional quality entails bolstering governance frameworks, fostering openness, and fighting corruption. Firstly, it is essential to build efficient structures and regulatory organizations for environmental governance. These entities should possess sufficient authority and capability to implement environmental legislation, oversee adherence, and levy sanctions for infractions. In addition, fostering transparency and accountability in decision-making processes about the management of natural resources can serve as a deterrent to corruption and guarantee the implementation of sustainable practices. Considering the empirical results, we suggest that future research should examine the effects of disaggregated globalization on various environmental indicators and different countries. It is important to note that this study focused solely on Somalia and used GHG emissions as a proxy of the environmental indicator. 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Effect of foreign direct investment on CO 2 emission with the role of globalization, institutional quality with pooled mean group panel ARDL. Environmental Science and Pollution Research , 28 , 5271–5282. Usman, O., Rafindadi, A. A., & Sarkodie, S. A. (2021). Conflicts and ecological footprint in MENA countries: implications for sustainable terrestrial ecosystem. Environmental Science and Pollution Research , 28 (42), 59988–59999. https://doi.org/10.1007/s11356-021-14931-1 Uzar, U. (2020). Political economy of renewable energy: does institutional quality make a difference in renewable energy consumption? Renewable Energy , 155 , 591–603. Van Veen-Groot, D. B., & Nijkamp, P. (1999). Globalisation, transport and the environment: New perspectives for ecological economics. Ecological Economics , 31 (3), 331–346. https://doi.org/10.1016/S0921-8009(99)00099-3 Warsame, A. A., Abdi, A. H., Amir, A. Y., & Azman-Saini, W. N. W. (2023a). Towards sustainable environment in Somalia: The role of conflicts, urbanization, and globalization on environmental degradation and emissions. Journal of Cleaner Production , 406 , 136856. https://doi.org/https://doi.org/10.1016/j.jclepro.2023.136856 Warsame, A. A., Abdi, A. H., Amir, A. Y., & Azman-Saini, W. N. W. (2023b). Towards sustainable environment in Somalia: The role of conflicts, urbanization, and globalization on environmental degradation and emissions. Journal of Cleaner Production , 406 (December 2022), 136856. https://doi.org/10.1016/j.jclepro.2023.136856 Warsame, A. A., & Hassan Abdi, A. (2023). Towards sustainable crop production in Somalia: Examining the role of environmental pollution and degradation. Cogent Food & Agriculture , 9 (1). https://doi.org/10.1080/23311932.2022.2161776 Warsame, A. A., Sheik-ali, I. A., Mohamed, J., & Asumadu, S. (2022). Renewables and institutional quality mitigate environmental degradation in Somalia. Renewable Energy , 194 , 1184–1191. https://doi.org/10.1016/j.renene.2022.05.109 Warsame, A. A., Sheik-Ali, I. A., Mohamed, J., & Sarkodie, S. A. (2022). Renewables and institutional quality mitigate environmental degradation in Somalia. Renewable Energy , 194 , 1184–1191. Wen, L., Chatalova, L., Gao, X., & Zhang, A. (2021). Reduction of carbon emissions through resource-saving and environment-friendly regional economic integration: Evidence from Wuhan metropolitan area, China. Technological Forecasting and Social Change , 166 , 120590. Wenlong, Z., Tien, N. H., Sibghatullah, A., Asih, D., Soelton, M., & Ramli, Y. (2023). Impact of energy efficiency, technology innovation, institutional quality, and trade openness on greenhouse gas emissions in ten Asian economies. Environmental Science and Pollution Research , 30 (15), 43024–43039. Wu, W.-L. (2017). Institutional Quality and Air Pollution: International Evidence. International Journal of Business and Economics , 16 (1), 49–74. Yilanci, V. (2020). Does economic globalization have predictive power for ecological footprint in MENA counties ? A panel causality test with a Fourier function . 2004 . Yurtkuran, S. (2021). The effect of agriculture, renewable energy production, and globalization on CO2 emissions in Turkey: A bootstrap ARDL approach. Renewable Energy , 171 , 1236–1245. https://doi.org/10.1016/j.renene.2021.03.009 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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-3913734","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":273549462,"identity":"f2913ab9-f379-4fa3-8aa9-8bbceaa9afa3","order_by":0,"name":"Hassan Abdikadir Hussein","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/UlEQVRIiWNgGAWjYHACxgMMDGxy/OwNDEAGM1AggbAeoEo+Y8meA6RpkUvccAOskggt/NMOPzjwsc0sccPN5w8P3aixZuBnzzFg/FGBW4vE7TSDgzPb0oxn3s4xOJxzLJ1BsueNATPPGTzW3E4wOMy77Zhs3+0chsM5bIcZDG7kGDAztuHWIX87/QNQy3/GhpvHHxzO+XeYwR6ohfEnHi0GIPfwbmNTnHCDweBwbhvQFokcAwZePFoMb+cUHJz5jw0YyEC9uX3pPBJnnhUcxucXudvpGx98OAOKyuOPP+d8s5bjb0/e+BBfiGEAHhBxgAQNo2AUjIJRMAqwAAAWjVwC2EDOTwAAAABJRU5ErkJggg==","orcid":"","institution":"SIMAD University","correspondingAuthor":true,"prefix":"","firstName":"Hassan","middleName":"Abdikadir","lastName":"Hussein","suffix":""},{"id":273549463,"identity":"133bb54a-05e5-4f23-b805-47ea8afb63d5","order_by":1,"name":"Abdimalik Ali Warsame","email":"","orcid":"","institution":"SIMAD University","correspondingAuthor":false,"prefix":"","firstName":"Abdimalik","middleName":"Ali","lastName":"Warsame","suffix":""},{"id":273549464,"identity":"132076b8-3e66-4123-a59a-1417c6d9e73a","order_by":2,"name":"Abdikafi Hassan Abdi","email":"","orcid":"","institution":"SIMAD University","correspondingAuthor":false,"prefix":"","firstName":"Abdikafi","middleName":"Hassan","lastName":"Abdi","suffix":""}],"badges":[],"createdAt":"2024-01-31 12:01:37","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3913734/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3913734/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":51315471,"identity":"7af9bf45-e09f-4b1f-9493-fe1f22eeadd2","added_by":"auto","created_at":"2024-02-19 12:33:00","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":91545,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTrend of variables\u003c/strong\u003e: (\u003cstrong\u003ea\u003c/strong\u003e) GHG\u003csub\u003e.\u003c/sub\u003e (\u003cstrong\u003eb\u003c/strong\u003e) SOGL. (\u003cstrong\u003ec\u003c/strong\u003e) POGL\u003cstrong\u003e. \u003c/strong\u003e(\u003cstrong\u003ed\u003c/strong\u003e) GLO. (\u003cstrong\u003ee\u003c/strong\u003e) IQ. (\u003cstrong\u003ef\u003c/strong\u003e)URB. (\u003cstrong\u003eg\u003c/strong\u003e) RGDP.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-3913734/v1/9c0b60046daccd7ec5e8fe44.png"},{"id":51315473,"identity":"3d23fc90-7744-453e-b4d1-f57c889ff0af","added_by":"auto","created_at":"2024-02-19 12:33:00","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":38992,"visible":true,"origin":"","legend":"\u003cp\u003eCUSUM test\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-3913734/v1/84e0797bce0a87cc3104daaa.png"},{"id":51315823,"identity":"b0229487-9cf9-4115-aa41-1f9bc01dbbe4","added_by":"auto","created_at":"2024-02-19 12:41:00","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":43311,"visible":true,"origin":"","legend":"\u003cp\u003eCUSUM square test\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-3913734/v1/0452ba9ed857f1bd69a0c60c.png"},{"id":70460840,"identity":"0d5c2e93-65c3-4854-b047-3c7048c9ae87","added_by":"auto","created_at":"2024-12-03 11:32:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":857110,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3913734/v1/ba73e008-e702-4150-a779-8ba1a7552297.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Exploring the impacts of institutional quality, globalization, and urbanization on environmental pollution in Somalia: a disaggregate analysis of globalization","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe linkage between globalization, institutional quality, and environmental sustainability has emerged as a pivotal theme in contemporary ecological discourse. Greenhouse gas (GHG) emissions have grown since the initiation of the industrial age, which has had an upsurge in radiative force on the climate and a tendency to warm the surface and cause climatic changes (Abdi, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Canadell et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) At the heart of this dialogue is the recognition of how social and political globalization, through the transnational flow of ideas, cultural values, and political ideologies, can reshape environmental governance across the globe (Dauvergne, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). While social globalization facilitates the diffusion of environmental consciousness and green technologies, political globalization often promises the proliferation of international treaties and collaborative governance frameworks (A Jahanger et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The effectiveness of these processes is supported by the quality of institutional frameworks, which are crucial for converting international agreements into concrete environmental results (Bekun et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Robust institutions are identified as a cornerstone for effective environmental policy-making and for the enforcement of measures aimed at reducing GHG emissions (Uzar, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Warsame, Sheik-Ali, et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Thus, it is remarkable to identify the interaction between globalization, institutional quality, and GHG emissions in developing countries to implement effective environmental policies that mitigate their ecological footprints.\u003c/p\u003e \u003cp\u003eEmpirical studies suggest that globalization has a variety of effects on the environment, depending on the channel via which it enters. The globalization process has an impact on environmental quality as it alters variables including energy, employment, technology, foreign direct investment (FDI), and industrialization (Pata \u0026amp; Caglar, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). It is widely agreed that the process of globalization has effectively reduced the income gap existed between emerging and developed nations through investments in capital and technologies (Atif Jahanger et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022b\u003c/span\u003e). However, this has come at the expense of environmental deterioration. The positive impacts of globalization are examined to its effect on ecological quality, specifically in terms of reducing environmental pollution (Atif Jahanger et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2022a\u003c/span\u003e). Many researchers claim that the process of globalization has a detrimental effect since it amplifies the total pollution level via the heightened breakdown resulting from increased CO\u003csub\u003e2\u003c/sub\u003e emissions(Warsame et al., 2023; Chien et al., 202 ;Suki et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). CO\u003csub\u003e2\u003c/sub\u003e emissions resulting from globalization are identified as a primary factor contributing to deforestation, natural resource depletion, climate change, and global warming (H. Khan et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2022a\u003c/span\u003e) During the process of globalization, the industrial sector engages in the production of goods to cater to international demand, resulting in heightened consumption of resources and the emission of pollutants into the atmosphere (Pata \u0026amp; Yilanci, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2020\u003c/span\u003e;Pata \u0026amp; Yilanci, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The engagement in increased production and consumption activities has the potential to directly contribute to the escalation of environmental deterioration (Pata \u0026amp; Caglar, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) .\u003c/p\u003e \u003cp\u003eThe significance of globalization lies in the facilitation of technological transfer and collaboration across nations in addressing the issue of climate change (Ansari et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Since the use of non-renewable energy sources is closely linked to the pace of economic expansion, the increasing global demand for goods and services has necessitated a rise in energy consumption (H. Khan et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2022a\u003c/span\u003e; Abdi, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Notably, environmental regulations in developing countries often attract pollution-intensive industries from advanced nations, leading to environmental deterioration in the receiving regions(Wenlong et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Shahbaz et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) .This phenomenon contributes to emissions, where shifts in production locations due to varying environmental standards result in the redistribution of emissions from one country to another. On the contrary, globalization encourages knowledge transfer to developing nations and the adoption of cleaner production methods, which positively impacts the environment. International relationships between multinational corporations and countries have aided in the diffusion of technological advances into emerging economies, aiding in some manner in ecosystem preservation (Adebayo et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The spread of expertise and eco-friendly technology not only enhances environmental quality but also improves labor efficiency and capital productivity, streamlining manufacturing and reducing emissions (Mansoor \u0026amp; Tahir, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Wen et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eConversely, numerous studies have extensively investigated the impact of institutional strength as a determining factor in improving environmental quality. Environmental issues in developing nations often correlate with weak institutional frameworks, especially in the political realm, leading to ineffective enforcement of environmental laws (H. Khan et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2022b\u003c/span\u003e). The studies have thoroughly investigated the role of institutional factors such as governance effectiveness, democracy, legal systems, political stability, and regulatory quality in impacting environmental challenges, particularly in terms of emissions (Wenlong et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2023\u003c/span\u003e;Warsame, Sheik-ali, et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). It has been demonstrated that robust institutions can avert market inefficiencies, create impactful regulations, and formulate effective environmental strategies, all of which contribute positively to environmental health (Wenlong et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). On the flip side, subpar institutional quality often results in inefficient resource management and environmental deterioration (Atif Jahanger et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2022a\u003c/span\u003e). Overall, the effectiveness of institutions is crucial to environmental outcomes, highlighting the necessity for robust legislative and institutional mechanisms to reduce environmental harm and foster sustainable global practices (Azam et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Several researchers have suggested that strong institutional structures can suppress environmental degradation (Cao et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Sheraz et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, the evidence Teng et al., (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)and Islam, (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)reveals that institutional quality increases environmental deterioration. Regarding this, the literature on the institutional quality-environment nexus remains inconclusive, which necessitates further investigation, particularly in countries with deficient government institutions such as Somalia.\u003c/p\u003e \u003cp\u003eResearch on industrialized nations has dominated global inquiries into elevated atmospheric carbon effects, but recent concerns have expanded the focus to include developing economies as well (Abdi, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In Somalia,Warsame \u0026amp; Hassan Abdi, (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) discovered that sustained environmental pollution and degradation negatively impact the agricultural sector, a significant contributor to the nation's export earnings. Amidst the continuing discourse on the effects of globalization and institutional quality on environmental degradation, the current study examines the connection between quality institutions, social and political globalization, urbanization and GHG emissions in Somalia by using time-series data from 1990\u0026ndash;2018. To the best of the authors\u0026rsquo; knowledge, there is no previous effort to analyze the connection between these variables within a single framework in the context of Somalia. Hence, this study contributes to the literature as follows. The few prior studies related to the subject in the context of Somalia have used the aggregated variable of globalizationWarsame et al., (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2023b\u003c/span\u003e) which does not capture the actual effects of globalization on the environment since the various components of globalization affect environmental quality differently. Additionally, the study utilizes advanced estimation methods, including the autoregressive distributed lag (ARDL) model, fully modified ordinary least squares (FMOLS), and causality tests. These techniques are applied to derive more thorough policy suggestions based on the linkage between globalization, institutional quality, and GHG emissions in the context of Somalia.\u003c/p\u003e \u003cp\u003eThe structure of this paper is outlined as follows. Section two represents a review of the literature. Section three delineates the econometric methods employed and the data sources utilized. The findings and discussions are presented in section four, while the concluding section offers a summary and outlines the pertinent policy implications.\u003c/p\u003e"},{"header":"2. Literature review","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Globalization and Environmental Pollution\u003c/h2\u003e \u003cp\u003eThe dimensions of globalization (economic, political, and social), economic growth, and institutional quality are key factors that have a significant influence on environmental degradation. Globalization refers to the rising economic connectedness between nations, encompassing the facilitation of free trade, the exchange of information, international capital movements, and the expanding mobility of labor. (Fischer, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Considering its relation to industrialization and urban growth, this process has global environmental concerns (Veen-Groot \u0026amp; Nijkamp, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). Globalization is categorized into three primary dimensions: social, economic, and political globalization. These dimensions are quantified and represented as an index developed by the KOF Swiss Economic Institute (Dreher, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSimilarly, According to Dreher, (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), globalization describes the process of creating networks of connections among actors at intra- or multi-continental distances, mediated through a variety of flows including people, information and ideas, capital, and goods. Economic globalization encompasses the movement of capital and services, the long-distance transportation of goods, as well as the exchange of ideas and information that accompany market transactions. Social globalization refers to the dissemination of information, ideas, and images. Political globalization refers to the spread of institutional policies.\u003c/p\u003e \u003cp\u003eHence, the relationship between globalization and the environment has resulted in escalating levels of apprehension. Gaining a comprehensive understanding of this enduring link is crucial for decision-makers who are committed to attaining sustainable development. To further such development, it is imperative to consider environmental, social, and economic issues. Even though the link between globalization and the environment has garnered a lot of attention in recent years, most in the empirical literature (Kihombo et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSeveral studies in the current literature have examined generic aspects without delving into the particular channels and causal relationships between the two variables. For instance, several studies emphasized the impact of the economic components of globalization, particularly those relating to trade. Most of thesestudies have identified that economic globalization enhances environmental quality in developing countries (Kihombo et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Sasana et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2018\u003c/span\u003e, Ahmad et al. 2021, Jahanger et al., 2022; Xiaoman et al., 2021). Additionally, Kihombo et al., (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) assessed the effect of financial globalization on the environmental quality measured by (ecological footprint) in West and Middle East countries from 1990 to 2017. They reported that financial globalization reduces the ecological footprint. Similarly, Ahmed et al., (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) explored the effect of economic globalization on the ecological footprint in Japan for the period from 1971 to 2016. The empirical results uncovered that economic globalization enhances ecological sustainability in Japan.\u003c/p\u003e \u003cp\u003eOn the other hand, ample studies confirmed the adverse effects of economic globalization on environmental quality(Ahmed et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e;Destek, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Yilanci, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Moreover, Yurtkuran, (\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) examined the effects of economic globalization on CO\u003csub\u003e2\u003c/sub\u003e emissions in Turkey using the bootstrap ARDL approach between 1970 and 2017. The empirical results highlighted that economic globalization has detrimental effects on Turkey's environmental quality. Additionally, Destek, (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) examined different dimensions of globalization on environmental pollution in Central and Eastern European Countries from 1995 to 2015. It was observed that economic globalization raises environmental degradation.\u003c/p\u003e \u003cp\u003eSocial globalization refers to the sharing of ideas and information between and through different countries as well as the cross-border movement of cultures and openness of media. Social globalization can have a positive or negative effect on the environment. Internet and social media encourage people to consume more, which can be a problem for the environment (Bu et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Moreover, the irrational development of the internet and the massive use of related devices lead to an increase in power consumption, which may negatively impact the environment (Chen, X.; 2019). Salahuddin et al., (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) concluded that internet usage is harmful to environmental quality. On the other hand, social globalization enhances environmental quality through international social integration which might generate more environmental technology spillovers that lead to better environmental quality (Atif Jahanger et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2022a\u003c/span\u003e; Mehmood, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e \u003cp\u003ePolitical globalization measures the degree of the country\u0026rsquo;s international political engagement (Heshmati, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). The nexus between political globalization and environmental quality indicated blended results. Some studies reported that political globalization hinders environmental quality(Sasana et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Shahbaz et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Mehmood, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). While other studies stated that political globalization promotes environmental quality (Akif, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Lenz \u0026amp; Fajdetić, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Institutional Quality and Environmental Pollution\u003c/h2\u003e \u003cp\u003eThe connection between institutional quality and environmental pollution has gained substantial attention in the realm of sustainability and development. As environmental challenges such as climate change, pollution, and habitat loss continue to escalate, understanding how quality institutions influence environmental outcomes has become crucial (Ahmad et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Institutional quality encompasses the effectiveness, transparency, accountability, and governance practices of institutions within a country (Amin et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Moreover, Institutional quality implies the set of norms that govern relationships in social, political, and economic conditions that indicate human behavior (Hussain et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Effective institutions can shape environmental quality through regulation, policy formulation, and the enforcement of environmental standards. Weak institutions, on the other hand, may hinder efforts to protect the environment. This literature review examines the existing research on the relationship between institutional quality and CO\u003csub\u003e2\u003c/sub\u003e emissions to better understand how institutional factors shape environmental outcomes.\u003c/p\u003e \u003cp\u003eOne fundamental aspect of institutional quality is the ability of governments to enact and enforce environmental regulations. Ample studies reported that institutional quality enhances environmental quality such as Ahmad et al., (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) in emerging countries, (Kwakwa, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) in African countries, (Atif Jahanger et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022b\u003c/span\u003e) in 69 developing countries, ( Ahmed et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) in Pakistan (Danish \u0026amp; Ulucak, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) Asia-Pacific Economic Cooperation (APEC) countries. In the same vein, Islam, (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) assessed the impact of institutional quality on CO\u003csub\u003e2\u003c/sub\u003e emission in Bangladesh over the period 1972\u0026ndash;2016 by utilizing the ARDL technique. They found that institutional quality raises environmental quality. Similarly, according to Salman et al. (2019), effective local institutions have a significant role in fostering economic growth and reducing environmental deterioration. Moreover, Warsame et al., (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) investigated the effect of institutional quality on environmental degradation in Somalia using data spanning 1990\u0026ndash;2017. The empirical result indicated that institutional quality enhances environmental quality. Hussain \u0026amp; Dogan, (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) investigated the nexus between institutional quality and environmental degradation in BRICS nations by employing data from 1992 to 2016. They reported that institutional quality reduces environmental degradation.\u003c/p\u003e \u003cp\u003eConversely, Numerous studies have shown that environmental quality is hampered by institutional quality (Khan et al., 2022, Wu, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Amin et al., (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) stated that institutional quality contributesto environmental degradation in South Asian countries. Azam et al., (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) assessed the effect of institutional quality on environmental degradation in 66 developing countries using Generalized Method of Moments (GMM) for the period 1991\u0026ndash;2017. The empirical findings on the institutional quality-environmental pollution nexus produced inconsistent results because of the various environmental quality measures.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Urbanization and Environmental Pollution\u003c/h2\u003e \u003cp\u003eUrbanization has become an essential global trend that has changed the globe's environment and has had enormous impacts on social, economic, and environmental conditions. The effects of urbanization on environmental quality have become a major issue as more people shift to urban areas.\u003c/p\u003e \u003cp\u003eThe impacts of urbanization on environmental quality revealed conflicting conclusions because of the differences in economic prosperity between the countries. Studies concentrated on developing nations found that urbanization degrades environmental quality (Ansari et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Rahman \u0026amp; Vu, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, Khan et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Doğan et al., (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) revealed that the rate of urbanization undermines the environmental quality in lower- and higher-income countries. Similarly, Islam, (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) reported that urbanization raises CO\u003csub\u003e2\u003c/sub\u003e in Bangladesh. A recent study by Abdi, (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) found that urbanization contributes to the deterioration of environmental quality in 41 nations in Sub-Saharan Africa.\u003c/p\u003e \u003cp\u003eConversely, Danish et al., (2020) explored the role of urbanization on environmental quality in BRICS for the period 1992\u0026ndash;2016. They revealed that urbanization improves environmental quality. Similarly, Gasimli et al., (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) assessed the nexus between urbanization and environmental degradation in Sri lank. They demonstrated that urbanization decreases carbon emissions.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Materials and method","content":"\u003cp\u003e\u003cstrong\u003e3.1 Data sources and\u0026nbsp;descriptions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe current study investigates the impact of social, and political globalization, urbanization, and institutional quality on greenhouse gas emissions in Somalia using balanced secondary data from 1990 to 2018. The sample period is determined by the availability of the data. The World Bank, KOF, and SESRIC are the sources of the data. Among the factors sampled for the study are environmental degradation measured by GHG emissions, globalization dimensions, institutional quality, and economic growth. Natural logarithm transformations of each variable were applied to remove heteroskedasticity. Economic growth and urbanization are hypothesized to have a significant contribution to the rise in environmental degradation.\u0026nbsp;According to\u0026nbsp;Warsame et al., (2023)\u0026nbsp;indicate that economic growth raises environmental pollution. Thus, to account for these effects on environmental degradation, economic growth is utilized as a control variable. The data and its sources are shown in Table 1, and the trends of the sampled variables are presented in Figure 1.\u003c/p\u003e\n\u003cp\u003eTable 1: Data sources and description\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCode\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDescription\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSource\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eEnvironmental degradation\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eGHG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eGreenhouse gas emissions\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eWorld Bank\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eReal Gross Domestic Product\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eRGDP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eReal gross domestic product\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eSESRIC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eUrbanization\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eUR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003ePercent of urban population to the total population\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eWorld Bank\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eInstitutional Quality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eIQ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eCombination of Political and Civil Rights.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eFreedom House\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eGlobalization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eGL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eKof Globalization index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eKOF\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 Econometric methodology\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo achieve the objective of the study, the ARDL approach is utilized. The ARDL approach performs better than other cointegration techniques in many aspects. Firstly, small sample sizes may be employed with the ARDL as it does not require long time-series data. Secondly, the ARDL has the flexibility of regressing whether the variable is stationary at level I (0), first difference I (1), or the combination of both. Thirdly, unlike other methods. The variables\u0026apos; long- and short-term cointegrations are simultaneously regressed (Pesaran et al., 2001). Following the previous undertakings of \u0026nbsp;Warsame et al., (2023), and Usman et al., (2021), we specify the model specification of the study as follows:\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\"\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eWhereas \u0026alpha;\u003csub\u003e1-7\u003c/sub\u003e is the coefficient of short-tun, and \u0026alpha;\u003csub\u003e0\u003c/sub\u003e is the intercept \u0026beta;\u003csub\u003e1-7\u003c/sub\u003eindicate the coefficient of long-run variables, ∆ is the function of the first difference, p denoted the number of lags and\u0026nbsp;the ECT\u0026nbsp;is the error correction term and\u0026nbsp;Ɛ\u003csub\u003et\u003c/sub\u003e is the error term. It is crucial to ascertain the dependent and independent variables\u0026apos; long-term cointegration. Thus, we apply the ordinary least square (OLS) approach to regress equation (2).\u003c/p\u003e\n\u003cp\u003eUsing the Wald F-statistic, the alternative hypothesis\u0026mdash;which asserts that there is cointegration between the variables\u0026mdash;is compared to the null hypothesis, which maintains that there is no cointegration among the variables in Somalia. The hypothesis is formulated as follows:\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\"\u003e\u003c/p\u003e"},{"header":"4. Empirical findings and discussion","content":"\u003cp\u003e\u003cstrong\u003e4.1 Descriptive statistics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSummary statistics of the sampled variables are reported in Table 2. Mean values of greenhouse gases (10), institutional quality (1.9), globalization (3.25), political globalization (3.3), economic growth (21.7), social globalization (2.9), and urbanization (3.5) are observed. Economic growth is established to have the highest maximum values compared to other parameters. Similarly, economic growth is recorded to have the highest standard deviation value which implies that its values are scatter compared to other sampled variables. Greenhouse gases, institutional quality, and political globalization are negatively skewed whereas the rest of the parameters are positively skewed. In contrast, the correlations of the interested variables are also presented in Table 2. All the parameters are positively associated with greenhouse gases except institutional quality which has a negative correlation with greenhouse gases. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2: preliminary analysis of the data\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\"\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.2 Unit root test\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the sampled parameters have passed the unit root test and confirmed that they are stationary at the combination of level I(0) and first difference I (1). We contend the existence of long-run cointegration between the dependent variable (GHG) and the explanatory variables – institutional quality, globalization, political globalization, economic growth, social globalization, and urbanization. We have also performed the unit root test of the structural break as presented in Table 3. It underscored that the variables are stationary the combination of of both levels – level and first difference.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Table 3: unit root test\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\"\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eThe bound test result is displayed in Table 4. The bound F-statistics is greater than the upper bound critical value at the 1% significance level, hence, confirming that the explanatory variables are cointegrated with the dependent variable in the long run.\u003c/p\u003e\n\u003cp\u003eFurthermore, the long-run coefficients of the sampled parameters are also reported in Table 4. It was observed that institutional quality, economic growth, and social globalization significantly affect environmental pollution in Somalia in the long run whereas the rest of the sampled explanatory variables are inconsequential in the long run. Interpretively, a 1% increase in institutional quality enhances environmental quality by about 1.01% in the long run in Somalia. Similarly, social globalization improves environmental quality in Somalia in the long run. A 1% increase in social globalization is associated with environmental pollution to decrease by about 0.83% in the long run. On the contrary, economic growth hampers environmental quality in Somalia in the long run. A 1% increase in economic growth impedes environmental quality by about 0.65% in Somalia in the long run. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 4: Long-run coefficients results\u003c/p\u003e\n\u003cp\u003e\u003cimg 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KcVvM8g6y0h10yU78pRsZtZpjqkvQil9hGtRlyV9HiM8c9YlnrFPDiW5qi6iTFQ3sg8Zyon1ANsi101nbXuYporSflsOeNOMPqeK1caU4fxUkTxlaebmt99+a8JQGGWicxcuXGhj9rl8+XIzohR37tyZvHz5sj0qQ7v58uVLe/SV06dPt982kxcvXkymxr49+gpx7969a4+OkmeQP3z4MLl+/Xp7tA/yZUQ97bSOnAPO37x5sz36yi7ONiPrLCNm7/s4efJko78lOCeY4cj1VQJb/fbt22aWa1t48uRJMxMaOXfuXCO3rpmeZ8+eTa5cudIe7UNd0Mbfv3/fHGu2tKTXArsSbQt5aFe1ejWLc2ybvqlkTc8zvcj0JmHolPmjR4+aT5S0D51n6tSYeZjVEH3+/Lk4QMDJiUsSQ8plWYSpfjn8MsZ9BnUTYCmu9HzERaexD+wDnXKG5U06iK7OOncoAtnnTm7bKclINrbLdlJHyBd7LH1D/5B7rNMh+gvUYxxwlAYAYwPH6NSpU+3RPpKHnJ8MsmQ5LoMjj0MJQ2UaQb61gZdZDsfiMFHB6lBolFpfv337dtMoh6CGXFMwnWekasw6+PTpU/ttcejwmElhRoW2wgh1ltmu40Ltc16wEcwgYyfi7DDl4viwP4zvGmjVZpA5T1mb7miuA2Y6sLV9tpMOGKcJmSFfOvR5ZJedpW1gXt1eRR+Es0V7oI4WbXOmzrE4TDQgGiwGEUdJo0Gm0YcqlR0gsyswI8OIdm9vr/nEOA6diR0jODfa+I2dwFnU82r0rtkR0rDsHtOU4Lxtxv7sEh3rECcGeSFfHHZsNXo3C6rHeWZNTB2cUW38xrHVJIRZHce2JMfUJMZwKEzxR7QfodZxyOvexf0LZvygt8zA0ukwsMA4MvIfOhM7RpjJ0GyGOva87wl5qCMmLTJh5qQEMkRuuw62EL2pLd+QDudIDiaznJJf6RddXeCkamaUoF+Z8smxZ0QWg7ahNqAtJ9s8kNoEjs1hmpW89suUPPRtIAWNSJXemBKM1mTYCYs42OfPny9ummWpjo59KHQolJP34+BAbfrPs9ngXuoQiePcLAwdOZeup59fbzvoa9Rf9DnDcu6QvS7YzJKeMtM0dP8Z4GTFwAwpoNMcj3XmiftGJ9mrGJH+de0NQ/554A84povurYub8c3qGI3DlGFUidLyvypKhlLQuZBunvV3szswWovGvbR8g8MzpPPGwSFdHu3R2ZQcdxnerg6kpN9D7uM4uXbtWtGpI45zQ+HZ6WBxQkGdUd6zRH1l+en/D421Y54FLZ8p5CU3nKiSTnfRlbYkS5yAXZvB58cY2qgt5Gh26RtbTrLzLv0u9U+cG6q7mhgo/djBLJFp41oLXIr/LSFu37595P9Y8L8lSrdEXE4rONf1GFPl7TxnzKzwv1eG6hO6PnVq2qOv/4emBOcod2o425ivkCfnI21sS5tKbuN8R4ZdcD7KDHnwrLntcxzlVZIfMsv/qwZyWbsAsinRJwvyxLqSbS7paK63LvrKGCM8S9SxIc+GXka5ctzVlkttH5B1rDvp/xhswthZuTehTkZBjSvGoWQoRoz73//+d+hYodTIiSul7TPOxsxC1tlSZ5KNmwxZ6ZzIel/S75xmTIYxts3cHiUfPTN2QGkVSk4P5DYfO6pcVzF01cM2UpJnDKoPyTLrVU5fcgZymj7d3DaHCeKz5+dSu806HNtzSV6leotlqN3EYNbDCf5MBb41MPUMW/ZYxhhjjDlGRruHqQscpekIs3Gc+vY2GWOMMcYMZescJmDD4sOHDxvHadc2IxpjjDFm+WylwwT63yH83xH91HaW/yFijDHGGCO2bg+TMcYYY8yy2doZJmOMMcaYZWGHyRhjjDGmgh0mY4wxxpgKdpiMMcYYYyrYYTLGGGOMqbAWh4l/IMnP+vMLM2clv1FeIf+7AK5TSpdfhtpFKa//JcFuE3WKl7oOAZ2ZJQ/pS3qG3qqcMf5fMWQ3633rmbuItiC/mT/KPYfSW/x3gSivobYs29sS8XyXbKn7mG6biM9W61+wAVEOMfT1jVwj2w/1qQpD69QsCP9WYJXo/UGEvvcM9RHfnVOCd0cRMso39N1FegdV6f1Vun7pnNlueOdWfAdZPi6B7uldXXo3lI5LqJ3kNJQTdTsfbzo8D881yz3X2jtlkgYkNx1Dl5yJ36b3mA0FXY0yyccleL9clKnefyb5lXSaY70XUFDvMY3qdhvgOWJ/kI8zXTLPMhOkzzKGrPND7ItZDmvT3FjBs6AG1qVUotSBzdI4ZRD60Esqd9Ho7jKlOqcj6NPnbLzQnS6DRtnSv1wm18lGeEiHtwmosyQMdZh4NmTV13bzs5Onry5EzYZsI+hOlr062C47RnxJv8ij+FKdqiNXuaVrA3FZp8cGz5/1CR0cqucCOZR0t6+v4Rw6H+lrL2Z5rG0P01SR2m+zcePGjSbvb7/91saUefnyZfttdpgOffXq1WSqdG1MGd3Drk7r7yLoBvp39uzZNmafK1euTN6+fdseHYX/NB9hCv3atWvt0WHQp5L+MsU/NZiTCxcutDH7XL58efLmzZv2aHN5/fr1ETnUoI3V2nouk1chXb9+vT0qQz3evHmzPdodnj171uhqBF1Gp9+/f9/GHIb4kq5GG/7x48cjy6zSU5V78uTJRn9LcG7MPHnyZHLp0qX2aJ9z5841zzvLO0ypn6y7LK89fvx4MnWmjtgdoPwcz7Vh6LYTMx/HtumbSpfjEdd2Y4VrXffHH39sPlfF06dPm8+a0YWpd984V2Y3+PTpU3H/zZkzZxqHYAgYwPv37xeNH20gOghcT3z+/Lk40Dh9+vQodLD0vDVmzYP8htQDzm12PHcB7Cy6mkGnuxx+7GCuB8rBGTh//nwbs++olpAOU8bVq1cbuy4nApvO66rm0Y1NAlmcOnWqPdpHz9TliA7l3r17zbtQ+/RV8sxgM8zqOBaHCSOnjoDGRGfy33//Nc4IjUmoQcdGugpo+KWOqYSMT5fCmu2CkfQi4CxhAC9evHhkYyadB6PUrs4jOk/mKNgRRuK0XQ2uSnQ5DbtAl1MzKy9evGicH3Xid+7caZyGPrkDM6fko46w9dj0IQPTTWZZth/Z5VlPyZMZPr5rIiFek/6SAZNnk9bPsThMjKhxjjB2OEpqhCjPshq4MceNDBo6zogRx0kGEQO4DZ3HcYEccTY10GLpvqsD6VpiMsNAV1mCisvGOPksGSF3OnTqQ516HuBi09UGsPmkN/sDojyLhE3AuUS+LLNJv+OAnjxsH2EQhizR+y9fvjTntDRnVsOxLckx4kMR+tCo8N27d81nJv6kU2HoT74jlNO11p7RjMPYp5TN6sGwab8Nnxg9zZpqdiTqLuBU8V2OlSmDoylnU0uaXXYCmbu9zg97oEoDWfSbDp1AXTALhY7LCcCBQpeVlzZAWvDP4Ltnr7UFQDor/Y42AXlL9sibvVDM5FnPV8uxOUxD0KiQ0U2JOHIBvs+z+fvWrVvN55BOiv0SKKbZLnBgovMio8UsRqmzwNjlzbQ1VCagpzJ4CsDIke8YREbqJUeekal18DBxBB6h096F5bg8eESfAR0tdczodN60XIJyS/pfAmc/bqlgZq+kp9jrMfxooQucEvQt7xfSDNuQWR76mll/hNC1RM91GXyxVGdWy0Y7TCgms1B0GvPMHNXAqKBsdE40bKaX+2BUxL3UfsVjxgd1Gp0XdRLoBnUuYyhwnGc1eOw7GNJJCUaOGOa81ERnIyd/DNBhR2dxCHQOXU5Qhrqhjkp7HXdlOU6DRwXZKHQ0b4qXvNDtPqizoT9swD5jQ3OZXc7W2GdC+CGSZouFHMQhz1ZajgPsA3Yi2ht958ceJXCK6SdL5ZklM21ca4FLxf83Ma3gI//Hgv9JUbol0hHfdbs6n5mOZDrzTBX7yP+ymBroJn3pf4ToGlND08aYXQE9irrCcdbdSEnvOM76liFNbCPAMXopOK6Vs2kgq/gMQ+hqu7ks2iPpuuqDcnYd9CXKgeOsZxlkXLJ1Wc6y2V06ybl4baXfBjvKc8S+Ypbn6tNLZB91vKv9UIdcs0v3zfIpexNLRIZPQZUf41AyGlyOy8TzMWRl4hqldDmUjIYa9JC0ZneIejyk01BahSH605VOhpHQ1TFtKrpvhfh8eq4sz2wfYueCXYjnCLHTyoxNXqsi2tesY7KXile6Uoh1pXqqkcvYBmdJ9D2XZJ71k+M+hwliG8j9G3TFm9Vygj9T4RtjjDHGmA42eg+TMcYYY8wmYIfJGGOMMaaCHSZjjDHGmAp2mIwxxhhjKthhMsYYY4ypYIfJGGOMMaaCHSZjjDHGmAp2mIwxxhhjKthhMsYYY4ypsBaHiZcH8gZt3tA8C/Ht26UQX1CYKaXn5blDyG/+VsgvQc1vuFcw2we6q/od+iJo9EV5hrx8Fv0s6SjXm6WcTYLn0b3rDfqzoDaWieUSSrYgts95rr1NRFkMtYN9dRfLyyGXn+3pNhGfLfcPJdQXKnTVRSy3q9+M5YzNLoyVlTtMKNF3A986nuGtLXt7e813PjkmPH/+vIkrlStFi+kV7t2715zrUmwZAcrIef/888/JxYsXDxkOveH+9u3bzb0ordkuMGpPnz49qN/Lly9XnSaM3K1btw7yPHjwoNeooZPoZ0Z5VA7HfeVsErSVjx8/Hty74oYgZ5MORnmFOhmVq/YX2zVpePM757EFjx8/nnnAti2gq2fOnDmQ15s3bzo7alGru1heDNTF3bt321T7+sub/XUe2029bgM8R7QL9A9dfQtwDj1FBqSnT6HN57qgvl6/ft2kefjw4eTGjRtHBgRcW+UQkPFY7MKomQp7LXApvdxxFvSyTV5YGKGsXKZedtiHXjSZX5So+No9ll7mSV6/5HN7KenL1PD16grns86iI6WXblK2dDeWSf7StYfo6XGjdpshLsslw7P1PSPtLYO8Y3yWM/LddJmtAmSNbCKqm6xXYt66I1+Ue+naUGobY4PnzHqIfpWeV5T6Cem6QC5ZNrmuyFPqb/rq1CyHte1hmipS+205nDt3rvn89OlT88no8dWrVwezT10wKwRxtITnzwh0qtCT69evt7FlXr582X4zuwB6he6ePXu2jdnnypUrk7dv37ZHh0GfpoZrcuHChTZmH2amGN1n0MWSXn3+/Ln5zNeeGsvOa28KL168aO4zQ9y7d+/ao6MgO0bUjKxLbZHzN2/ebI++kkfXcZYDPnz4UG3b28izZ88aXY2gT+j0+/fv25jDzFt35Lt27Vp7NJmcPHmyaQclODdmnjx50sxgRuiTeN6urSLE57asfgy9BmxGtBvkQe4x36lTpxp9LpHLN8vl2DZ9owhyWuIeDSlOjS9fvjSfp0+fbj6ZGoUhRhHHCOdKYFSgZIjNboNDXprqZkmCafMSODqlAQK6GvUOaANy4kEDgEjJAHcZ5U2B5ZyS8Sau5DQKli7pILLDI3KHIpBr7sAEMu6qq20HPUFXM+h0l9M9b93lfHynLrHr0lcGINRxqfwxgWOE4xLRM3U5otDVbjU4ypQGU9J/5CpY1ttrt6+Y1XEsDhNKoA6FSr9//z5zko0jQ2OqgdKxXkwZcpDwuEudVAkZECmvjGnJEJvdhk5gVkpOTwk6Dzr5rs4D3UanHz161MaMh66OoQ/y4Piw94vvGkTV9h5pFrA0WMLWMHvM+Vo520jXTEQf89QdA92Sw0pnj9OE/KlLnLSxz/TNIx+gn0O/h04K4NSSHrnla6q/UxsB91+r51gcJkbUOEcYMhwlVTQzPH0NHAVCOVAUwjzGwJhNAAM4pPNAx2kn6D2dv+JY3ts2NDLXMgW2gSV2luj6OhnOl2yBHFINxmrlmPlhqa5Ll6kb6oBlVunyLkI/hz4z2EcG6KJWSqTzQrOiyE39XQT7QX8o3WbzeGkm3CyXY1uSY5aHip4FNTxCNpAoS9d6eUazBhrZS9FKxhTFRLlzqP3KxJg+NPMRdQr0S844GyKdZ6CBjqLnca/ItkG7VNukE2aGQsvmGXUaJcirTlzLnn17cMz8lGZiZTtlq1lmVV3tqv1EH9WecaDQ67xHCdBXxWm7ifonPtmXpqU60mITCLs4i7pOjs1hmpWuNV7BND4MURg8d5RUKG/JKKO0UnDyEPjetcfCjBMcmOi8yIlmhqI0e0EHkTfTivPnzxedd5bqpHcYO+mVAjAC5XvXaJ0lawYa2cBuGsyA5WUEIG6e2bFSWfr59VDyKH2bQF+j/mo2Eh0tOTPodNeer1nrjg68VBYzhtHOCmaa+vZCbTq0PXQp90mSWZ4t6oL0DJpYqusjb5DH6S9t5McubPqPQcbOaBymGhqJMu3eByMbOjONOIG8NACUdxUjn9r/7DHHD/oQnRc5SegG+pI7EDrqrh8JMHJEn/KMJZ2EnPN5QDfZ0xB1d1NhBox7zRDXNTumjiYPeqiL7CDSpuhohjqO1B/1iDO7jSCjqL/SEXQ0O5WSRZdTPmvd1ZbjSmy6w1+D/3uUnRM5iEOfDacHJ6e290hL1TFdtkeitMHfLJFp41oLXIr/HyGminLk/1jw/yfyLU0b9pG8fUw7qiZ96f98cD3OUWYJ5Z0qfRtzGM6XzhHXlYfy4v8mMeOD+ov1y3HW3Qz6ir4Ijrt0RPTpOecIYyK3cb7X2kJuo8gjHgNy7Grf+oyylw2J97JLIK8od45r9hRZRXnxvavu+uoUucfzsvFdNnhM8BxRD4c+l3S6pI/obYxX2lhf0ucYp3RmtaxcwjQWKlIBZZBjooAC0IhrcYSoJF2oUS4zLyEreH6OrrANxmHXiXqc9UA6g75GZMRK50qQLuso1yI+GuYxofsn5I5V8snyjHkIsf30tTnJWB1KDGOV37KItrRLx7riCV1OEbLO9ZdRGQrbZA/7nksyj7rHcXTmM9FmKJQo6bhZPSf4MxW2McYYY4zpYGv2MBljjDHGrAo7TMYYY4wxFewwGWOMMcZUsMNkjDHGGFPBDpMxxhhjTAU7TMYYY4wxFewwGWOMMcZUsMNkjDHGGFNhLQ4T773hhZCzvElZebqCXi7ZBe/xKuXTS1VF7ToKXe+YK6WNoeudP2YzQUdVd/O8AxA9KdV7fjlq1kPgen3nx4jkQai1WRHzEEptKJ4nlOoqynxX3uc4qw6V7F+tnrhGfk8ixGt32cttI+pYSSYl4ou+u+Q0pB7jtWfpW838rNxhQom+m+Mt4bzAkH9Cvre31xzzyTHh6tWrzYtyuxo2CnTx4sWDN7/HwEsTOS/l7ruOAvd/7969Q/lEV16uDfM8uzkeMF5Pnz49qEPezD60o1XH8+TJkyZvfgEneqdyCfmlpDKKOs9xl6EcC7RP3pSvZ1JcH+pAlOf27dtHXmSMrHPbfvnyZXt2H+qCl5vqPPIeWpdjhefjhcR6ZkAOfXz58uWIzet7uTP1U3oxL/Wqa1M32MuhDsRYQbbRXtDn1J6ZOuIFucrDC7mz0zSkHknDS5U5//Dhw+al86WBhVkyU4GvBS7Fe3JmRe/MmTbqNmYfvacnQ1ztsbiPfC+6Ttc9xnf35HvpukfK6ivTbBbUFXUZ4b1Ptfqj3snb9b4t6CtD+fO1x6w7ahMZ4nI7iZTeS0YdxHjK7itD7S7S1Ua3BZ4r64qeuaZ7We+6oBzZ3ZiH7/ka1Nm2yhpo61lXkQHP3QXyyOdVR5LnkHokTZZtrhOzGta2h2mqKO231aHR61SZms8url+/3oRZYMZA5d66dav5rHHu3Lnm89OnT82n2VyY0kZH88wQsxRv375tj47CqI6RJTMhd+/ebWMPUxv5ff78ufnM12Ymte/am8yLFy+a+88Q9+7du/boMIzOb9682R59Jc+0MSvSB+0t2xtkS1zXtccOz5VtWtanEtK9GugwusjMR4brlOzphQsX2m/bBzPJly5dao/2wd5PnZbO9v7s2bPGnkSkl+/fv2+Oh9Qjco2y5Xq0qyH1bRbj2DZ9U8lycJheZMqRMGQaV9PCTEVGWKZD+VbVUCkXxaRRDLlPGfbTp083n2ZzoZMtLYExfc7UdxePHj1qdK5vGQM9YMpcOt611FYytF3Gd9NhKa5kwIljGaJE7ggEbT12TnTyOKmSJ/YjQxstwX1tIyVnXTZKA7cSci4ly64lU+Kjjvc5rdRHXnLeNtCvU6dOtUf7SN/l/GRoy9iTDPZAA6N56pG6yUvSZjUci8NEBdNIgUaq9VpG6Q8ePGjiM9FAsj6OsxSVS0qVPfhlw74WqI3MaBzcM88562yWWT/zdqQ46exPAuln3pMAzE6i4wR0lHQC/UBPcL62hWU5epr5y22IDkvyhOiEyi6U6mGXYEYDm1qbeZAcCQwOsgOanaU+yIuDi34PGVSOkXl1e14nsq8e0XvJe6yDqzFxLA4TjQ8FoLOhkWpUyXR8l1I9bzd5kg+uXbvWfG4aKDDKi5EnbPtIa5dRh3D+/PnGWKGfOEY49PFXK3nmBP1npjJ26OgJ7QHd0SifODnouwozc7kN4TzFzkOj6yhzHCr9UENyJi4vo2wr6CY6WXN08owGsqYDlm4jU2RWc7oAOWvwi34zYHQnvhh99Yid0MZv9TdmtRzbkhxTk3J+ZuHOnTvNZx6Nnzx5svnsWj6hMWM8c5i1QWsmomt6FIODAhOyoTfbCbqnDgXHCL3m1zN9sA8uL01JbzCOGEo6+E0dGKwDBh/IYwjM8sX9XtSH5IlTIGdqF2Z7sWnM1M+7TIP+aq8XDmtcTsYJAs34R/uJnDUwUAfftTxl6tTqERnL7sjeyNE1q+HYHKZ5QUE0OxUbK/F9+4tozBhPzoNmrKRwQ+B6XLdrg93QDZRm82AUXXJwcZDnWeZd1FnGUKLns+jnJsHMWGyfgrghs2Ys7fTtHZsVZj7ynsdtBX1d1p4WOZ0K+uELdrTPfo5Vb4fAszGbk+299L1rME29lJb+sRWlmc9Z6lETBma1jM5hgq5ZJv2CY1VTweo4a9PcZnww80AnkPWGTrv0yy3QaJpfhEUoI+6pKcGIsOvXlsyGsiwyZj1jZoxnyBBXmzXDWaItz9Lp8qulrnrSEmdeftpGmPVZ1FlnULjozKYGrX0bzsdMntEEZtO6BtOAfuZBALYCu5NnPmetR83kxaV/swKmo4S1wKXi/5eYjp6P/B+L6eilSRdRXP7fFOQlfqqgbcw+Sl/KA13lxXwZ/ueGzk2Vu439CnGlMs24oJ6jPnGcdTQj3UB/QHqUj0knKDPrrSAtYRvIbZzvUQ4lkItkF1E5tDHkE9saeeJ1hNrldz3/G2eb6NKbkmwg6y4gq746kj5HO4j8oz6XdH4bybLLcimBnKJcOM79BuWUUD1SR7FOS23CrIaVW2Y1SgUqmgqPcSgZihPj/ve//x06VogKGeNjgwWuE8/HEJVcRrUv9BncfN8EK+54ifqaOxp1BFnXso5H/YKsi6WORGly3rETnz0/twy95JztQgxR5rnNldqb0tQ6sG2gZsMkd9VFlFeWeU3/1AaiXBUXwy7IHfqeWTqYZRr1N9bF0HpUu4nBrIcT/JkK3BhjjDHGdDDKPUzGGGOMMevEDpMxxhhjTAU7TMYYY4wxFewwGWOMMcZUsMNkjDHGGFPBDpMxxhhjTAU7TMYYY4wxFewwGWOMMcZUsMNkjDHGGFNhLQ4TLxjkZYK///57GzMb5I2Bl5N2wYs2c/rai1AF6XLevnvmBZM5PaF0vVI6vRTUbD7ogeqNl8MOIeuiXkgaQZdr5Wa9HKrPm0B8vqH6HuU2JI/SZ5CnyiGs4oXcYyHKYqj+ZP2twTVqZQ9JMyZi2yy17xJRrl19WSy31AepT62VY5bLyh0mlOi7775rj2ZDSsHbWxQePnw4uXfvXpviKzLMENMTrly50pzrMr7qDFHSnPfGjRtFZST9xYsXJ8+fPz+ShzdZcz42IJ0DnoHvY34b/S5B/T99+vSgDi9fvtzp3Ah0Df1Vnj///LPRl6gTMoQ6z5v8S7qGPqkcwqJvo18XyODjx48H9624Pnj+S5cuNen39vaaN+d3DVqQJe1Mco5QP7w1XtemLOzQLjpNyOL+/fsHsgDk1gf1pHogXL169UDWGdlP5N2lm0PSjA2eJ9qF3L5LUBdnzpw5yPPmzZsjbZ40r1+/bs7TV9AHRbmrT1Xfg+2gTyzZDrNkpgJfC1wqvmhwCLxsUC8cjPDywoheRthXvl4QmctT3tJ1hF4OKkhP6INyS/dTu0+zeVBn+cWavLS0rx5LedCjqGdZ5/J5MUZ94dlLbYS4/DLSSH5+2nrp+Ynraktd1+4qa5tB1vmZJZ8uWXC+pIfkyfEcD6nTWpqxwTPlfgF5Yhe64PnzedUFn0CaLKd4HrhuVx9oVsvaJFzrYEqoodUgTVagEihaVr6heYXKmLfxk3dWOZjjo8sIogfZYEbIk3WE9H11jx5G3QSOx6gvtN1SuyKOc0MpyR650o76ysntHLj2vO12rHTJqM8OEZ9lB9RFLI90NXs2JM0YKfVnyKykd6LLZpTKEpSV2xHHuRxde9f0e90c26Zvphg1Pc8UJNObhDileffu3eaTeNKU0HT9rVu3ms8+bt682Xy+f/+++VRelliGwhLBVMEnFy5caGPMNvPp06fingum1Zk274JlNKbopWOaUr9+/XrzmWE6nWUTliwiX758aabk1T7Gsv+Dpbj8LEAcyxBDwD6UZPzgwYNmiUj2ocS0Q2naqewJn7TzXWu3JRlJJufOnWs+M+horjv0d9opT86fP9/GTBp9Rc5dOg1D0owRZHHq1Kn2aB/JTP1LBhliNzK06bdv37ZHh6ENvHz5sj36Slyii3z+/Ln9ZlbBsThMKAHGDOgEtL5Ow8IYRogH9neQVk6WoEODrLwlTp482Xwqjz6jEehDhoY9UWY3oOOfBzqq6Wj8wNlBZ7r2rOEssQcBB6u0D2E6amzaAUH78TadLoM+FNq5BidyOoFysQUMkPiOLAgxDSBr7Aky5Tx2pc/B2iWePXvWyKbk0Hbx4sWLxkmVw4ktxGlgEMp31YNsJAxJM0bm1e1Z927hSKnfi9ekvyR+7HIcI8fiMMmYYRDpBNQIaVglpSINDQ/IkxXImE2EmRT0FoeHz1JnoWN0HAcLxyl2/rSNOCtC26Hj2uYNnjy/NhxjJ3A6JSeN3jU7Qprnz58fSiO0cZbzpY5nF0FGyGCWH5yQ/smTJ4dmOt69e9d8opsMRKW/OKiS8ZA0poxmV5EZgwZNMADyRKc1GKBOmYmGrllDsxyObUmOqUmM4VAYDcn4gWaaTp8+3XwOmYqUUinPLHlBM1RdSzF0YihwDjYOuwejQy2xYeDQXRydPIPKOc188Ilh7JqeF8yuDF3WGiMs32gJRx27Ol+BXDVDQlpky8yJoN2pnXJeHc+jR4+auF0EO4T+lZZ4+mBWszSQVSeuepD+MhslhqQxR0HvJTN+iQdxQCCdJmBD0H3agPKY1XBsDtO8oCg4TWrAHIOUqg8ZXXnh+qx1UAJlRCmZLcijWcAYoMCaDeM+ObYSbz444NHJ1V4hZjpKnQVLdV1Ls3RM6ACGLKKp9D7GskepBvuFSgMF4mbZMwjqdGvoerRN8uR2h7PQNdgZO+hN1N+8dQHQ11mdJcqddSlpyDL2vEvdmwB6hX7lgbb0r2uWB/mXnhv5Yme60EC9C67Lygv2xayWjXaYSo1exI5FU+55H0MEpWK5gylhGVI+tTRYcoBEXP6QUq5iWpl72Oallk2GEZ1GbITokOP85Lqm49WPCLoo6Uet80eP+4wnMDgY8iOH4+TatWtF55A4zg0FGSJ/7TNUZ5TbOvUVHSQNWjLb4pBmeP6ov3nJDSdqVscHWXU5mNQHMs52kzhtbB6SZqzwo4480Ga5uG+WB3uR5Sn91sC/hJah8wBM4IjRj3WdN0tk2rjWApeaOjbtUfknlvq5sJgq35GfafKduPzzyakj1MTnMkHlkqaErlM6P+3gjsSrPEJ8JqHz+ZzuvZSHOM7FZzWbAfWPjgiOS3oWIX3MA7HuKYPjCMcxT0lvuW4ud1PJbZzvuS1FOE97E2ovsQzgmHi1lVLboZyYT2Vlu7EL8NwlslwjyK9ki2Ie9DCWXdLpIWnGCs8R9YnjkswiyCO2AY5jf5D1Vrod0wid66tHs1xWrrlqIApULkoR41AyNawYBzk+niuRyyZQxhByPkLNwJfyEGJDUsdXC0Pv06yfqMfZQKl+c/1l3c1GL54rnYesY336uInE+8/3ng0+7VppFbocnCyXkk3ItqCrrG2lJM8YVB+SpfQvp4tBdSWyjpcYkmasxOfKOqjnznoX5ZHbvNpEDCWIR7/NejnBn6nwjTHGGGNMB6Pb9G2MMcYYs27sMBljjDHGVLDDZIwxxhhTwQ6TMcYYY0wFO0zGGGOMMRXsMBljjDHGVLDDZIwxxhhTwQ6TMcYYY0yFtThMvC+Hdxn1vestozwx5PdA5Rem6l1sMS6H/F6jXEYOfrebAXRXOvHDDz+0sf2gr1GXau8xQ9dK+jZrOZtEbI9974aMxDbZlSfKpKs+hqTZJaiLWeRAWslviB0kfU03h6QZE1HHct/SR19d5L6vS/bx2rP0rWYBmv/3vULia0FKr36ooX8VX3sdSoZ/4R/j42sCSq9I4N/VEyK69/w6ALNb8AqJqBv5uItZXmMiXSvlmaWcTYJ2E9tOPi7Bs8pOSCbZbuQ2STvP9TEkzS6BLJDJUBmQXnZSNrhkN0Hn++p2SJqxkWXSJ6NIX11knVe/lW0AedUnco40fX2kWQ5re7FPVIJZUEPro6uTyY6UlK/UaFHAkgKXyjG7RckYoRM1fR6q75SN7nW1kXnazXGjtpYhrq9TKXUM8fn5nsvVtVTukDS7BM+NTLB7JRuXQVZZ59D3kuzUWdfqdNtkzzPlfgSZ1fqKWl2U4rM+I8csS85Tb2a1rG0P01SR2m/j4uPHj1s1hWxmg6ludPfs2bNtzD5XrlyZvH37tj06CtPqQ2HZ6eXLl+3RYWYpZ5N48eLFZGr426OvEPfu3bv26Ch3795tv+3z4cOHyfXr19ujyeTTp09HbAl1Q5zKHZJmV0B/pnb+kAxrIKtS+gsXLrTf9qFt3Lt3bzLt0I+cE0PSjJEnT55MLl261B7tc+7cucnUaelss0PqgjTZ1lAuaMkPOUZZkod2lfOZ5XNsm76pZO1PiGvls6wDzwqdHNy5c6f5jJSUjbXj169fd3ZmZvuh8y05zGfOnGl0o4svX75Mbty4caDXXU43beC3335rj/avFxlazqbBQKPUpoh78+ZNe9QPsinJmE6pBNcUQ9LsAsvoRLHPOK6Z+/fvT27fvt3rAAxJM0bQr1OnTrVH+0jW79+/bz4zQ+uiy+H6/Plz++0wfQMus1yOxWGigjUCpBOgUeF507AePHjQxC8DlFodDYFjQpfivnr16lB6RkZ9naLZfhbpYPf29hq9JuCso1MRRt+MUmuGtFbOJtJl9IeCjXj8+HFjJ+KGVs1A9W1CHpLGDANnSXYxDmb5ji29efNm8102c9Y0Y2RR3e6DvhB5D5URAyjVzyrvy+xzLA4TI2qcIwwinYCmF2lYpZEMzKsM6migNm2JcVZ6BeJQRmNmIU+bo/Ponzpx9JklvdrIu1bONiJHkvaHnWCGLXYgdMIMZmiXkgNxcYlkSBrTD3LTYBadu3jx4oEd1tImunny5MkmzcOHD2dOYw6DrFi+REZyLpllBi3NCc3Aqp/SJIRZHce2JMeSBsZwXdBQZ/HcBUYWUE5jFuHWrVsHy1GaQcEoKoA6+TirkonlbCM4kXIktVwZ9x4x6KGTIDCbJFlF53NIGtMPcpOzrnqIy03qoDUIJT1x7F8TQ9KYw6Cj0l3k/+zZs+JgnzpR3NOnT5vPsc/ebTrH5jCtGxoqzLrkh0LSwD0i2m5wYKLzor1CzEiUZj1ZqtOeuHlgz4GMogIwuuT72Dv2y5cvF9sMcZybBXW6XTALwoCojyFpxgz6GvV32QO83Fn3MWQZe8x7ydQn5D1F0vc8E7QIlMnACv3tgxk8s3o23mHSxrqujXQwtPEtMss0i8Ew44PRWnRe5CThuFD/ufNnKpwl5FlgFMjs0KIsq5xVcu3ataatZYjj3FCQO/I/f/58G3MYOQYaEJUYkmbsoK9RfzUjFEGW89ox2Uw5A9QH9ZJtKXGsHsCQNGPlxx9/PPIrWfqo2rYPMbQuGJSxEqOZvi7UP9bSmQWZNq61wKX4fxJiqgRH/o8F/1uidEtTJWzi8/+eAOKnDbA9+gpll8oijhDvBXSNTFe82R2mjvah/43CcdbdiPSYdIL0sYwSWS/nLWdT4F6jnPgenyXD+enIvT36+r+TYhlC52L6zJA0uwR6M0R3crqSHgJpiBecj8cwJM1Y4Tlin8RxqS8qkWWcwQ5QXkn30ecYr7S5TzPLZ+WaqwaiIKMY41AyNawYF5FS5JDJ1yNExewqpyuUFNbsHlGvsk6oQ4l6RhqlJ5C/Bumy0ZunnE0i3n++d7VFyVMOTgyxQxKyFX2d05A0u0JNrqoj6Z70OYYuOWa7XWJImrESnyvLSM8dZV2rCyCuz8kv9WFmPZzgz1TgxhhjjDGmg53Z9G2MMcYYMy92mIwxxhhjKthhMsYYY4ypYIfJGGOMMaaCHSZjjDHGmAp2mIwxxhhjKthhMsYYY4ypYIfJGGOMMaaCHSZjjDHGmAprd5h46WB8q7ZCfrmpMccBL2qVTs7zxvdff/21CX10pfn9998PtYlZXxK9ifzwww8Hz1OTS4RnJ08X8e38XKOEztfSbRvIeZZnJb1klHU+toccVJ9D0mwrUQ+HttfYJsifyX1kSYZD0pgV0LwgZU3onUX5nVJ6d1F+p44x6wS9zO/Tyu9260N5+t731pWG6+idasD5Wa+/afA8atN6/9WQNq60hBLER1nx3i3e2xXhnV1jlt28yMZmeXRB+ijLfNyly7Om2UayPufjEtRLTKP3qgrOcSzd1bvnooyHpDGrYW0OE42HSu1SKOKPy8ANNS7zgBJ3PbPZLLLBQS+G6iRGi/TRkGX60pQ6F9KuUjdXSclhoXOotQWeF1mQFzllSvHqMGLZxO1au5NeIb8heiO5ZbIsM+Srdc5D0owZni23WWTf99JcZJrbhOpA8aW6yzo/JI1ZDWtZkmOq8vHjx5Opkk0uXLjQxh6G+OvXr7dH64NlkFevXrVHy4Vp03v37rVHZtO5e/du+22fDx8+DNZJliVevnzZHpXpSoOeXLp0qT36ytmzZ9tv44N7L8muq/2L3377rQldfPr0aTLtlNqjfbgWce/evWtjJpMvX76033YDdGhqz2eyoS9evJhMO9726CvERVlmyHft2rX2qMyQNGPmyZMnR9rsuXPnJlMHqKmLEsg0109u4+TNcZQLWvIbksashrU4TM+ePWs+z58/33wOJa71dq3T0gmhQNrzQMjr95yP5UihKe/GjRvNd52L14jr08ojSMc1Y9lxPZpzMuwXL15szu/KHoptAL16/fp1e9QPaWMnT6ee6UvT5Vxw/cuXL7dH4wbdxwGtkTuCEnRKJT5+/Nh+m0w+f/580O52oe0NkVsGeZXyEffmzZv26Chd+SJD0owZdPDUqVPt0T563vfv3zefmTwgAzk4cngg9zUCnRZD0pjlsxaHSZVbG11G5HwwalJgtoaOB+SoMHP16NGjyYMHD5o0KDIzRtHTvnLlymRvb685zyfpAQXmGMdG15BSc/2nT582cYy4lAe4LveCI0jZysu1mbECnpU4IJ7vtRkIsxmgY+gVeqH67ILzjDT7OochaTLoL3pTMrJjA2eFNkm7ie1yHiSPIZtc1e7UDksbbHeZrk63D+qvNBsaGZJmzMwjty7oQ27fvn1gG+7fv3+k/8oMSWNWw0b+WwGMIcYuOxg4N3RkKAoKRho4c+bMQVricXCyp61jHJm+KX+gg8O4ysHLo3wZYIijZhS/NLtgxoOcG+qY+mQGssswYTjfvn3buwwyJE2JW7duHej3mKEtY+CRJ+2SWZ9FOxzkwoAFB0yOE3Gxk0be0UGVfag5wKaf0rJSZkgas+9Y0hZif0Sf8/z584PZUdJoeVmzUEPSmNWwFodJhmuooWQ6uLS2jqLEvQoqt7ZWzkwRHV80sH2QvrYUwn3cvHmzPTLbAoZexl6GrGs/h2ai0CsFUGdO5zwkTYYZGZbjYoc/VpgR0sBD8uxashgKctHMEeVLhrVO+scff2ycVzM/cdmziyFpdh36QlZFSqsO6LH0m7bDLBT9YbQHQ9KY5bMWh0kjv0UN5bygUCgWM1R0VLX9DCixpv5JSx6zm2gfWgn0REZLARj98R2jNiRNBAeLGZltNHyreibkxQ9KzGwwKCwNYokrDRiZydj15ThAj7ELeRVDshwyy8NWjpKzlKFMBlzoeBdD0pjlsBaHiU4BBdMG6y40+0NjLW0QRTGYep9187iQ40TZUu4uuBdmAGyMd5dF9W1WcJbobDQjs23QmcKQDqX0a7gSyAyG7PXil027MCuM3g5xTpmZL/1CmLjSrL2X475Smq1kQmDILA/9ypAfQACOFVsD+mzCkDRmOaxtD5MUBGWR4RQ0cOLVMcXZnQgGNCpGn9MT9xKxHymmpROMSs1xPM8UP8YV54pr6RcjpNG9k6dEaTr6uGbWzHDoeOOmYOo669sqkbNUmnEaI7Td2H5pN+y5YPAxdKapq40B9YPNYOkydz60X87F5U7uhY5lVzqVaM+6oB7Q76hjfJ+ljnYV+ijtpxVMCNT2x6KXmmWO5HYuHUZnu8ocksYsmWnlrZW9vf3/UpoD8Zmpt34oDf+cS/A9nps2/CNlEydi/NQQt7H7TDvGQ3mmBuNQeuL4JF2+BvdIeTlOKC+B/GYzyXVIyDqpuo/1m+F81NMSOU3W8xjGqjO5nRByu1Mbju0UYnsk0B4jklcuL5JlWquTbaCmw7JFWRbRRmVZC8rO9ZQZkmbbkNwIWR+lg9RBqW5iiHLnuNbuh6Qxy+cEf6bCN8YYY4wxHWzkvxUwxhhjjNkk7DAZY4wxxlSww2SMMcYYU8EOkzHGGGNMBTtMxhhjjDEV7DAZY4wxxlSww2SMMcYYU8EOkzHGGGNMBTtMxhhjjDEV7DAZY4wxxlSww2SMMcYYU8EOkzHGGGNMBTtMxhhjjDEV7DAZY4wxxlSww2SMMcYYU8EOkzHGGGNMBTtMxhhjjDEV7DAZY4wxxlSww2SMMcYYU8EOkzHGGGNMBTtMxhhjjDEV7DAZY4wxxlSww2SMMcYYU8EOkzHGGGNMBTtMxhhjjDEV7DAZY4wxxlSww2SMMcYYU2FjHaa//vprcuLEid6wyXz//feT33//vT06yg8//FB8phhIswn88ccfzf38+uuvbczsLKOMTaems7NQSi8ZKpT0i7iYpiudMcaY2dhYh+ns2bOT//77b7K3t9cc88mxwtWrV5vOgE5qk1Cn9ueff7YxZV6+fHmQJj+bwocPH5rzx82FCxea+7l7924bMzvLKGMMPH/+/FAdEqjnhw8ftinqlBxlnJ6LFy8e6AqfN27cOOIMffr06cj1r1+/3p41xhgzL6NdksPhgPfv3zefm4Icg2Xw448/tt/mg850ntmFZcxsbcrs2DrByS85J48ePRrsKP7000/N53fffdd8iqdPn05u377d6BfwiRN2//795licPn26/WaMMWaZjNZh0szSqVOnms9NI3d4Jb58+dJ+OwzPxtLVorMxzEDMijrsRVhGGbsIzu2lS5cmly9fbmO+wmzjmTNn2qN9zp8/38xexVlWZpiMMcYsn413mE6ePNl+OwwOCcsfGnFH2D/UtYdDe4dII2L6SJyh0fmcRsTz88zqRGaZNdPzELQ/SHtpAKeJ7/F5SZfzAGU9fvx48urVq4PzLDEC6fQdeEaliWXPUgbgXCkdIc5MdV1jTPAMN2/ebI+6oc7evn17MENVWtL9+PFj++0w0fF+8+bNIXkuqovGGGNa/ttwph0H61tHwu3bt9sUh8nnlP/hw4dtzH//TR2t/6YOV3u0z97eXpNOcF5l5fhYlvLFOOXhOn0obynE8rogTXzW/Ewcc41IzMP9ca1ILjPeo8qSTAV54rMOKQOuXr166J4lN8qvXWMsRDn0gSwEzxqfHVRXyEVIrlGm5BUl3TfGGDMfo1mSm3YY9CAHgeUJRtBxhoTZimkHPPntt9/amP19JeS9d+/eoaWLTJ7JYgmEssjD9QT7iuJI/8GDB80G9Lh8Fq8/hGmHd+jZOO6aTcjEZxqySRw53Llzp/l+7ty55rOPvj1ZujbP3rexuFQGM03MQrE3RyA30lFnYug1NpW8jFYCva3pDM8+dXwanUTvkcvnz5+bc3GWNeohckSXqHNjjDGLMdo9THQM09H7IUfo9evXkytXrjTfI+poZ90gzjLQrVu32qMydPqlPSd0bPNSWmYsgQxwkuhAhyxZsTzDfUWHZCjxecgfO++8zNZFLOPdu3fNZ9ezznuNTQJ5s8+oD56LJUw9J0EOTq5X6ltONfLRRvA+kC9lj1F+xhizSYzWYQI2yELX5ukxE2cc4j4lQtzng8Ok2RvOxRmnDI6jZqHkPM2LOm+cGn7uHmf6lsU6rrFK2JNUc345LydIQY4i37tmDTVDp9lCY4wxq2XUDpN+EaTlNGaXSg6DRtdDlqBmheU4NtquEv6FQuxQ9S8VInSsdLQvXrxoY8ogHxwrOvM/K/8ragg4NZTz5MmTNmYYmnkZMvMx7zWOmyHLcfOCA0l912YLJd+hs5bGGGPKbLzDpNmj/HNpOgKWLmKnwawMo+74s3YchNy54DjRAUfnSkt5OBP6ZVHX6D7mY8mOa5ZmP/iFWpwNWjZcM16XfU/5//Bo6Uswc8G+FmQVlyjjr6lY2sxE54rnj0tF1FFeEqyVQQeOs0ndRHnyPNTtkGtsMjxDbTluHpAPOoo+40hGNBMpkCHyjfvEjDHGzMl/G8q0c21+4dMXSFNi6hQcShd/RSSmHc6hNPoVEuRrUx6U4kB583mu0UW+R0LpPmvol2WEfL38jPm5Yl5duyZ3XYP0iouygKFlQLyHfK7vGpsOz1XTz67zyKBLpvHXdJmS3I0xxiyHE/yZGlZjjDHGGNPBqPcwGWOMMcasAztMxhhjjDEV7DAZY4wxxlSww2SMMcYYU8EOkzHGGGNMBTtMxhhjjDEV7DAZY4wxxlSww2SMMcYYU8EOkzHGGGNMhdE4TLzrrOtdYvFt/l2QP74vbRXw7i7uIb7LrsTQdLOAbJZZXgnej8Z964Wuph/ppMKs7xVEX0vypp5juX2U8htjjJmdUThMvHCUF9mW4Nzly5ebt/g/f/686DTgoPB2/uvXr7cxq4GX+3IfvNi2j6HphkKn+Gd4se0qoPPmRa5mGOgc+kg9K7x8+bI9W4c6RefJx4uKBU4XLzZWmbdv3y46TXLKjTHGLIeNd5g0q/Tw4cPmM/PmzZuDt8KfO3eu+JZ8nKhlOSfzMOvMwqzQcfLm/1WCs7lqp2zbOHXqVPttOHJ0cISo1wjnXr16NXn69GkbM2n0+rvvvmsGDoLvV65ccX0ZY8wS2XiHCQfo7t277dHsMDNy69at9mj90Hl9+PChPVodzFqtmnVcY1v48uVL+202cH5wfksOvso8efJk8ylwjhg4iGvXrq1F54wxZpfYeIep1kmzHPfu3bvm+/v375vOI8JofJ6lOO3XiYERvsARIo32k2iEH/dKce7evXvNSF9l6FxMJyhD6Qh5z1bcu5Lz9kHaXK5mMhQ0Cxbju/aMQZRPfCbFSR4i30OU5Tby+fPnZglTzztkllEyqy3dlZyx6CDZsTXGmOUzmk3fXTD7xOiaTun+/fuHRubzLsXRudPZ7e3tNcsifMKLFy8OHAUcIWauLl261KRhVE983GvFtdnHwowBaQgsG+Z0IOdK6ViCxNHShl3Onzlz5uAczzoUHEbyAfdD56p9VCz9cB06aZwYZjh0D8TLGcqwr4Y0pBe6Tl4epAwc11huzLet8Jx6ZuhzQOHJkydNfQBp0RPqXSBzZPvgwYM2xhhjzLoYvcMEdPZ0SnGUTeePg6HRdpwRybMfGZwROi5ttpVzgHOm70DHpdkrOSA1R6CUjnt9/Phx48wIrkU6rqfzWprUnq1ZwdGK+18gyujRo0eH9orNuy9K5Qnkyd4byV/P3uWMbQPoRZSDZo26npk6xsHCAQeWojmm3qO+Ug56jhzjrGCeWTXGGLNctsJhKkHnH/c+MRukET8zUpq5yeSOq4/Spt7aLIKI6VhKBGafSjCzNa/zEmEWDMeFZwQ+T58+3XwHOud5nbEuJE/N1sUwz1LpmPnxxx+bX2v2IZ3C2SLgwDLzFMFhQn6aFaROb9682Z41xhizCrbSYWIUHzsQOUca8fOpfU+LwD6VdYDjpxkKZhvm/Xk/z43jhQMGOGrRaaET1qwaMxh0xIsy7+Zn8xUczi4YGFCnqjdjjDGrYTQO08ePHwfP3jCKn7cDwalgyag2E7BMNLOkmaYSWlIE7amaB2ba8oxFhGUeroPztIxZLf2i69mzZ83nLoPcu2aCpHdZTuh91zIvAwNmBbv26XX9qs4YY8zsjGqGKe5R6oIZmDt37rRH++A8xVE6+0P6lp7Ym5T3jrD0ETfgdlG6x9JMTUxHZ8meKTaCx6VCOkQC12ZWiWdgtinOjmlPDGmGwIwS5fBseUmR5+NecJZA9913DfbOROdSnTgb2HFw9WxZnjxnPN4mkAFOp+QGOKLIqs+Rl95FeXNc2uSNbNEX6hIZ9+FZPmOMWQLTznHj4TZjeP78eXvmMNPO47+HDx+2R4fZ29ur5o/E9ITpKL+Jp/wYT5g6BEfiiRMxPoeYrquMfC/E6/v//d//HTqn++yD65TSXb169VBZug6f8ZqEKOcYTzrKiech5yfNNpNlmXVOdZrlQLq+fNKRmg7vmryNMWbVnODP1KBuBYy6h8xCGWOMMcbMwlY5TMYYY4wxq8AOkzHGmLXyzz//tN/K9J1fZV5Y1bX//fff9luZRcpeJC8sUvbff/89+fbbb9uj7cYOkzFmI1il0YdFOoVF8kJfmkU60kXu6zjP1zrYvvOrzAuL5P/mm2/ab0dZ5L5hkfs6zrK3CTtMZqOpGWXoS7OIUV8kLyxyfltHo33nV2n0oe/8KvPCqjrSRe7ruM8bMzZG6zCt0qjDIvlXlXdbO1HoSjPE6PalWcSoL5IXauc9GjXGmPGw0Q7Tzz//PPnll1/ao8Os0qjDIvkXybuNnSgset4YY4w5TrwkZ4wxxhhTYWtfvmuMMcYYsyzsMBljjDHGVLDDZIwxxhhTwQ6TMcYYY0wFO0zGGGOMMRXsMBljjDHGVLDDZIwxxhhTwQ6TMcYYY0wFO0zGGGOMMRXsMBljjDHG9DKZ/H8XUoOwahIg7gAAAABJRU5ErkJggg==\"\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eAfter examining the long-run coefficients of the parameters, we subsequently estimate the short-run dynamic effects of the sampled parameters. Its result is displayed in Table 5. It was observed that economic growth, social globalization, and urbanization significantly affect environmental pollution in the short run, but other regressors are statistically insignificant. A 1% increase in economic growth leads to environmental pollution increasing 0.11% in the short run. Moreover, Social globalization improves environmental quality by about 0.33% in the short run for a 1% increase in social globalization. In the same vein, a 1% increase in urbanization leads to an environmental quality increase of about 0.49% in the short run. More importantly, the ECT is significant and has a negative coefficient which implies that the model makes convergence. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFurther, the diagnostic results of the model such as the serial correlation, heteroskedasticity, reset test, and normality test, are presented in Table 6. It was observed that the model is free from all the diagnostic problems. The goodness fit of the model also revealed that the model is better as shown by the adjusted R-squared. The independent variables explain that 84% of the variations happen in environmental pollution in Somalia. Moreover, the model of the study is reliable as shown in figure 2 and 3-Cusum and Cusum square tests respectively.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 5: Short-run coefficient results\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\"\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.3 Granger Causality\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe results of the Pairwise Granger causality are reported in Table 7. Several unidirectional causalities from environmental pollution to social globalization and from institutional quality to globalization, urbanization, and political globalization are observed. It was also established from a unidirectional causality from urbanization to globalization. Finally, economic growth Granger causes social globalization.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 7: Pairwise Granger Causality Tests\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cimg 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\"\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.4 Robust analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo find robust results, we perform the fully modified ordinary least squares (FMOLS) as a robust analysis. Its result reported in Table 8 revealed that institutional quality, social globalization, and urbanization are statistically significant. Both social globalization and institutional quality improve environmental quality by reducing GHG emissions whereas urbanization significantly hampers environmental quality by increasing GHG emissions.\u003c/p\u003e\n\u003cp\u003eTable 8: Fully Modified Least Squares (FMOLS)\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\"\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":" Discussion of the result","content":"\u003cp\u003eSocial globalization enables the transfer of knowledge, ideas, and information between different countries. It provides individuals in Somalia with the ability to obtain information regarding sustainable practices, environmental preservation, and renewable technology from various parts of the globe. Enhanced consciousness can result in shifts in attitudes and behaviors regarding the environment, fostering endeavors to preserve and achieve sustainable progress. This result aligns with the recent study conducted by\u0026nbsp;Rong et al., (2024), which concluded that social globalization enhances environmental quality in China. Extensive studies have demonstrated that social globalization promotes environmental quality such as\u0026nbsp;Lenz \u0026amp; Fajdetić, (2021)\u0026nbsp;for EU, \u0026nbsp;Jahanger et al., (2022)\u0026nbsp;74 developing countries.\u0026nbsp;Mehmood, (2021)\u0026nbsp;in Singapore.\u0026nbsp;Moreover, Social globalization has an insignificant impact on environmental quality in panel data from 180 countries\u0026nbsp;(Farooq et al., 2022).\u0026nbsp;This finding contradicts numerous earlier studies that have indicated that social globalization adversely impacts environmental quality such as\u0026nbsp;Deng et al., (2022)\u0026nbsp;for a global sample of 107 countries, and\u0026nbsp;Akif, (2021)\u0026nbsp;for Central and Eastern European Countries.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe institutional quality in Somalia has had significant effects on the country's levels of environmental pollution in the long run. In promoting sustainable environmental practices, it is crucial to create high-quality institutions that demonstrate effective governance structures, strong regulatory frameworks, and rigorous enforcement mechanisms. In scenarios when institutions exhibit fragility or suffer from corruption and incompetence, the enforcement of environmental standards may be deficient or ignored, resulting in escalated levels of pollution. On the other hand, robust institutions can create and enforce environmental regulations, oversee adherence to these regulations, and offer rewards for adopting sustainable methods. Institutions that place environmental protection as a top priority may encourage environmental education and awareness, enable the implementation of clean technology, and promote responsible resource management. Hence, enhancing the quality of institutions is crucial in mitigating environmental degradation in Somalia and securing a sustainable future for its ecosystems and communities. Our finding supports the study carried out by (Kwakwa, 2023) in African countries, (Atif Jahanger et al., 2022b) in 69 developing countries, ( Ahmed et al., (2020) in Pakistan, and Danish \u0026amp; Ulucak, (2020) Asia-Pacific Economic Cooperation (APEC) countries. However, this result contradicts other studies such as Amin et al., (2023) in south Asian countries and Azam et al., (2021) in 66 developing countries.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eEnvironmental pollution and its associated consequences are worldwide issues that demand a thorough comprehension of effective measures for reduction in emissions. In the specific context of Somalia, a country struggling with distinctive social, political, and environmental obstacles, assessing the impact of social and political globalization, urbanization, and institutional quality on GHG emissions is extremely important. Therefore, the study aims to investigate the relationship between these variables and environmental degradation in Somalia. This enhances the understanding of the environmental issues faced by the country and provides helpful insights on possible strategies for attaining sustainable development. The study utilizes the autoregressive distributed lag (ARDL) model, fully modified ordinary least squares (FMOLS) methods, and causality tests.\u003c/p\u003e \u003cp\u003eThe empirical results of the bound test indicate that institutional quality, economic growth, and social globalization have had a significant impact on environmental pollution in Somalia in the long run. However, the remaining explanatory variables included in the sample are inconsequential in the long run. It was observed that economic growth, social globalization, and urbanization significantly affect environmental pollution in the short run, but other regressors are statistically insignificant. To find robust results, we perform the fully modified ordinary least squares (FMOLS). The findings revealed that institutional quality, social globalization, and urbanization are statistically significant. Both social globalization and institutional quality improve environmental quality by reducing GHG emissions whereas urbanization significantly hampers environmental quality by increasing GHG emissions.\u003c/p\u003e \u003cp\u003eBased on the empirical evidence, the study offers several policy implications. In order the social globalization to enhance sustainable development, it requires setting policies that prioritize sustainability and safeguarding the environment. This entails the establishment and implementation of regulations to mitigate pollution, improve sustainable resource management, and protect ecosystems. In addition, promoting international collaboration and alliances can allow the sharing of knowledge, transfer of technology, and provision of financial assistance for sustainable development initiatives. Engaging in partnerships with other countries and international organizations can bolster Somalia's ability to effectively tackle environmental issues. Moreover, allocating resources to education and awareness initiatives can enhance environmental awareness among the populace, fostering conscientious purchasing habits and sustainable ways of living. Furthermore, the policy considerations of enhancing institutional quality to mitigate environmental deterioration in Somalia are significant. Improving institutional quality entails bolstering governance frameworks, fostering openness, and fighting corruption. Firstly, it is essential to build efficient structures and regulatory organizations for environmental governance. These entities should possess sufficient authority and capability to implement environmental legislation, oversee adherence, and levy sanctions for infractions. In addition, fostering transparency and accountability in decision-making processes about the management of natural resources can serve as a deterrent to corruption and guarantee the implementation of sustainable practices.\u003c/p\u003e \u003cp\u003eConsidering the empirical results, we suggest that future research should examine the effects of disaggregated globalization on various environmental indicators and different countries. It is important to note that this study focused solely on Somalia and used GHG emissions as a proxy of the environmental indicator.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003e1) Hassan Abdikadir Hussein writes an original research draft and conceptualization 2) Abdimalik Ali Warsame collects the data and analyzes the data3) Abdikafi Hassan Abdi writes the research introduction\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAbdi, A. H. (2023). Toward a sustainable development in sub-Saharan Africa: do economic complexity and renewable energy improve environmental quality? \u003cem\u003eEnvironmental Science and Pollution Research\u003c/em\u003e, \u003cem\u003e30\u003c/em\u003e(19), 55782\u0026ndash;55798. https://doi.org/10.1007/s11356-023-26364-z\u003c/li\u003e\n \u003cli\u003eAdebayo, T. S., Rjoub, H., Akinsola, G. D., \u0026amp; Oladipupo, S. D. (2022). 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The effect of agriculture, renewable energy production, and globalization on CO2 emissions in Turkey: A bootstrap ARDL approach. \u003cem\u003eRenewable Energy\u003c/em\u003e, \u003cem\u003e171\u003c/em\u003e, 1236\u0026ndash;1245. https://doi.org/10.1016/j.renene.2021.03.009\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"GHG emissions, globalization, Institutional quality, Urbanization, Somalia","lastPublishedDoi":"10.21203/rs.3.rs-3913734/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3913734/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eEnvironmental pollution and its implications are widespread issues that require a comprehensive understanding of effective strategies that mitigate emissions. Given the unique challenges faced by Somalia, including social, political, and environmental challenges, it is crucial to assess the effects of social and political globalization, urbanization, and institutional quality on greenhouse gas (GHG) emissions. Hence, the study aims to examine the relationship between these variables and the environmental deterioration in Somalia. The study utilizes the autoregressive distributed lag (ARDL) bound test, fully modified ordinary least squares (FMOLS) method, and causality tests. The empirical results of the bound test indicate that institutional quality and social globalization have a significant negative impact on environmental pollution in Somalia in the long run. On the contrary, economic growth impedes environmental quality in Somalia in the long run. However, the remaining explanatory variables are inconsequential in the long run. To find robust results, we perform the fully modified ordinary least squares (FMOLS) as a robust analysis. The findings revealed that social globalization and institutional quality improve environmental quality by reducing GHG emissions whereas urbanization significantly hampers it. Based on the empirical evidence, the study offers several policy implications.\u003c/p\u003e","manuscriptTitle":"Exploring the impacts of institutional quality, globalization, and urbanization on environmental pollution in Somalia: a disaggregate analysis of globalization","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-19 12:32:56","doi":"10.21203/rs.3.rs-3913734/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c3015fde-8396-4d0a-9f55-7cac993e1161","owner":[],"postedDate":"February 19th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":28826493,"name":"Earth and environmental sciences/Environmental sciences"},{"id":28826494,"name":"Earth and environmental sciences/Environmental social sciences"}],"tags":[],"updatedAt":"2024-12-03T11:24:01+00:00","versionOfRecord":[],"versionCreatedAt":"2024-02-19 12:32:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3913734","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3913734","identity":"rs-3913734","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}