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Economic development and environmental sustainability have recently become global priorities. This study utilizes the nonlinear autoregressive distribution lag model (NARDL) to investigate the asymmetric effects of natural resource rents on economic growth and environmental quality in China and the United States from 1970 to 2020. The findings indicate that natural resource rents exert asymmetric effects on economic growth and environmental quality in both countries; however, the impact patterns differ between the two countries. In the short term, a decrease in natural resource rents significantly increases GDP per capita in the US, while an increase in natural resource rents has no effect. Moreover, natural resource rents do not influence the ecological footprint in the US. By contrast, China's GDP per capita remains unaffected by natural resource rents, while the ecological footprint is significantly influenced by both positive and negative changes in natural resource rents, exhibiting asymmetric impacts. In the long run, an increase in natural resource rents significantly impacts both GDP per capita and the ecological footprint in the US, while a decrease only impacts the ecological footprint. By contrast, both increases and decreases in natural resource rents impact per capita GDP and the ecological footprint in China. These findings highlight the importance of tailoring country‐specific policies to facilitate sustainable economic development and enhance environmental quality. [ABSTRACT FROM AUTHOR]

This paper examines the relationship among ecological footprint (EF), electricity consumption, and GDP in China using annual data ranging from 1960 to 2019. However, factors like trade openness, urbanization, and life expectancy might increase EF as ecological distortions are mainly human-induced. This study explores the effect of these variables on the environment, which is captured by EF. Quantile Regression estimates indicate that electricity consumption and real GDP increase environmental degradation, while trade and urbanization reduce EF, allowing for a higher environmental quality. On the other hand, the spectral Granger-causality tests reveal that only urbanization and life expectancy affect environmental degradation over the whole frequency domain. In the current geopolitical scenario, relevant policy implications may be derived. [ABSTRACT FROM AUTHOR]

Tourist-related activities continuously increase the competition for water, food, land, natural resources and the associated energy consumption. The input of per capita energy consumption boosts economic growth which also increases the greenhouse effect and global warming. While extensive research efforts have been devoted to exploring the future growth of tourism-related emissions, little attention has been given to evaluating the dynamic linkages among tourism development, CO2 emissions, and economic growth in a region where tourism is a pillar industry. This exploratory study selects Hainan Island, China, where tourism significantly contributes to the economic growth of the Island as an example. Data were obtained from the official statistics during the period 1986 to 2014. During that period of time period, Hainan has seen a faster growth in foreign and domestic tourism. The study aims at validating the environmental Kuznets curve (EKC) hypothesis and investigating the relationship between tourism-related economic growth and CO2 emissions by applying a bivariate vector autoregressive (VAR) model. The results of this study showed that there is no direct evidence to support the inverted-U relationship between tourism-related economic growth and CO2 emissions in this Island area. The specific implications for future research are also discussed. [ABSTRACT FROM AUTHOR]

This study aims to investigate the relationship between CO2 emissions in China and its prospective determinants, namely economic growth, globalization, financial development, and natural resources during the period from 1980 to 2017. We present more detailed analyses across multiple econometric approaches within a multivariate system, e.g., the Bayer‐Hanck combined cointegration approach, the ARDL bounds test approach, ARDL estimates in short run and long run, robustness check by cointegration regressions (i.e., FMOLS, DOLS, CCR), and Granger causality approach in the frequency domain. Our results show that economic growth and natural resources have a positive impact on CO2 emissions in China, although globalization contributes to improving its environmental quality. Meanwhile, there is no statistical evidence that CO2 emissions in China could be affected by financial development. The causality analysis reveals that globalization, economic growth and natural resources all lead to CO2 emissions in the long run, while financial development only causes the short‐run CO2 emissions, which further demonstrate our findings. Such findings are meaningful for policymakers to achieve the sustainable development in China. [ABSTRACT FROM AUTHOR]