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This paper is the first comprehensive research to examine the effect of circular economy on environment employing two environmental degradation indicators (CO2 emissions, ecological footprint) and one environmental quality indicator (load capacity factor) for 57 Belt and Road Initiative (BRI) countries during 2000-2019. The effect of other variables such as renewable energy, industrialization, and globalization was also controlled. The study applied the cross-sectional autoregressive distributed lag method (CS-ARDL), the augmented mean group (AMG), and common correlated effects mean group (CCEMG) methods as a robustness checks. The empirical findings reveal that circular economy and renewable energy have pro-environmental effects by decreasing carbon emissions and ecological footprint and increasing the load capacity factor in BRI countries. However, industrialization and globalization have detrimental effects on the environment. The result of causality shows a bidirectional causality between renewable energy, circular economy, industrialization, and three environmental indicators, but the relationship of globalization with CO2 emissions and the load capacity factor is unidirectional and with the ecological footprint is bidirectional. All the results are confirmed by the robustness tests. The study suggests policy implications for the BRI government.

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This research analyzed the effect of tourism market diversification on Singapore's CO2 emissions by measuring the level of concentration of source countries in a foreign tourist basket of Singapore using a Herfindahl-Hirschman index. Our results indicated that the index fell over the period 1978-2020, which means the diversification of source countries of Singapore's foreign tourists increased. By applying the recent bootstrap and quantile ARDL models, we found that tourism market diversification and inward FDI act as stumbling blocks to CO2 emissions. In contrast, economic growth and primary energy consumption increase CO2 emissions. Policy implications are presented and discussed.

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COVID-19 has impacted the world economy and food system in many aspects. We conducted a comprehensive examination of global food security during the COVID-19 pandemic by considering the food security index and its four key pillars (affordability, availability, quality and safety, and natural resources and resilience) for 102 countries. In addition to the fixed effect panel data estimator, the Method of Moments Quantile regression is useful for disaggregating the impact of the COVID-19 pandemic in relation to inflation, economic growth, urbanization, and agricultural land on global food security among countries with different levels of food security. We found that COVID-19 has negatively affected food security globally, especially in countries with a low food security level. The effect of income per capita and urbanization rate on the food security index is positive and statistically significant across all quantiles. Inflation rate and agricultural land, however, adversely affect food security, and this effect is stronger for countries with lower levels of food security. The results of affordability, availability, quality, and safety, and natural resources and resilience models provide meaningful implications for governments and policymakers to build resilience in food systems and to be better prepared for future crises and disruptions in the food supply.

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This study examines the Environmental Kuznets Curve hypothesis by estimating the relationship between economic structure and economic complexity with the environmental pollution in OECD countries during 1971-2016. In that respect, this research investigates how various economic sectors affect environmental pollution differently. The results confirm the Environmental Kuznets Curve hypothesis, which implies the influential role of economic structure and complexity in socio-economic developmental phases. In addition, the results show that most of the OECD countries are on the left side of the curve, implying positive connection between economic complexity and CO2 emissions. In contrast, only 3 OECD countries (Japan, Switzerland, and Germany) are close to the turning point, indicating that their patterns are sustainable for socio-economic development. The sectoral economic results affirm the most pollutant structure of the service sector, compared with the other economic sectors. Hence, new projects should attach great attention to their environmental impacts, specifically in the service sector planning. Regarding the complexity analysis, policymakers are advised to embrace knowledge-intensive restructuring of economic sectors.

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Global warming is a serious problem facing the world today. To minimize it, scholars are trying to find the reasons behind increasing CO2 emissions. This study examines the effects of overall export product diversification, extensive margin, and intensive margin on CO2 emissions as indicators of environmental degradation in 84 developing countries for the period of 1971-2014 in the context of the environmental Kuznets curve (EKC) hypothesis using three estimators, namely, autoregressive distributed lag (ARDL) bounds test, dynamic ordinary least squares (DOLS), and fully modified ordinary least squares (FMOLS). The empirical findings reveal that EKC hypothesis is valid. The overall empirical findings from various approaches show that overall diversification, extensive margin, and intensive margin have a positive and significant effect on CO2 emissions.

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This study is among the first attempts to examine the effect of economic complexity as an indicator of sophisticated and knowledge-based production structures on CO2 emissions for 55 countries over the period of 1971-2014. The countries considered fall into three different income groups, namely high income, higher middle income, and lower middle income. The study employs the panel quantile regression methodology and tests the existence of the environmental Kuznets curve (EKC) hypothesis by including economic complexity and other control variables such as energy consumption, urbanization, and trade openness in its model. The results show that economic complexity has significant impacts on the environment. Based on the analysis, economic complexity has increased the environmental degradation in lower and higher middle-income countries, and has controlled CO2 emissions in high-income countries. Since economic complexity plays a significant role in environmental damage, it is crucial for low- and middle-income countries to adjust their current industrial and production policies to promote economic growth and at the same time protect the environment.

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This article investigates the long-run and causal linkages between economic growth, CO2 emissions, renewable and non-renewable (fossil fuels) energy consumption, the Composite Trade Intensity (CTI) as a proxy for trade openness, and the Chinn-Ito index as a proxy for financial openness for a panel of the Commonwealth of Independent States (CIS) region including Armenia, Azerbaijan, Belarus, Georgia, Kazakhstan, Kyrgyzstan, Moldova, Russia, Tajikistan, Turkmenistan, Ukraine, and Uzbekistan over the period of 1992-2015. It is the first time that CTI and the Chinn-Ito indexes are used in an economic-pollution model. Employing three panel unit root tests, panel cointegration estimation methods (DOLS and FMOLS), and two panel causality tests, the main empirical results provided evidence for the bidirectional long-run relationship between all the variables in all 12 sampled countries except for economic growth-renewable energy use linkage. The findings of causality tests indicated that there is a unidirectional short-run panel causality running from economic growth, financial openness, and trade openness to CO2 emissions and from fossil fuel energy consumption to renewable energy use.

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This empirical study examines the short- and long-run relationship between GDP as an economic growth indicator and CO2 emissions as an environmental pollution indicator in Myanmar by using annual time series data over the period of 1970-2014. It also carefully considered other proxies, such as trade openness, financial openness and urbanization, and structural breaks in the country. The fundamental objective of this study is to test the validity of environmental Kuznets curve (EKC) in the context of Myanmar. The dynamic estimates of the long- and short-term relationship among greenhouse gases (CO2, CH4, N2O), GDP, trade intensity, financial openness, and urbanization growth are built through an autoregressive distributed lag (ARDL) model. The empirical findings indicate that there is positive short- and long-run relationship between CO2 and GDP and thus, no evidence of EKC hypothesis is found for CO2 in Myanmar. Nevertheless, the existence of the EKC is observed for CH4 and N2O. On the other hand, trade and financial openness have inverse relationship with CO2 emissions. These results demonstrate that trade liberalization and financial openness will improve the environment quality in Myanmar in the long run.

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This article attempts to explore the nexus between oil consumption, economic growth and carbon dioxide (CO2) emissions in three East Asian oil importing countries (i.e. China, South Korea and Japan) over the period 1980-2013, by using the Granger causality, Johansen cointegration test, Generalised Impulse Response functions (GIRF) and variance decompositions. The empirical findings provide evidence for the existence of a long-run relationship between oil consumption and economic growth in China and Japan. The results also point to a uni-directional causality from running from oil consumption to economic growth in China and Japan, and from oil consumption to CO2 emissions in South Korea. The overall results of GIRF reveal that while economic growth in China and South Korea shows a positive response to oil consumption, this variable responses negatively to the same shock in Japan. In addition, oil consumption spikes cause a negative response of CO2 emissions in Japan and China, as well as a U-shape response in South Korea.

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The main objective of this study is to examine the environmental Kuznets curve (EKC) hypothesis by utilizing the ecological footprint as an environment indicator and GDP from tourism as the economic indicator. To achieve this goal, an environmental degradation model is established during the period of 1988-2008 for 144 countries. The results from the time series generalized method of moments (GMM) and the system panel GMM revealed that the number of countries that have a negative relationship between the ecological footprint and its determinants (GDP growth from tourism, energy consumption, trade openness, and urbanization) is more existent in the upper middle- and high-income countries. Moreover, the EKC hypothesis is more present in the upper middle- and high-income countries than the other income countries. From the outcome of this research, a number of policy recommendations were provided for the investigated countries.

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