RESUMO
Introduction: The COVID-19 pandemic has significantly impacted global economies and individual health. This study uses data from the China Family Panel Data (CFPS) in 2018 (before the pandemic) and 2020 (during the pandemic) to a) estimate the relationships between the perceived risk of unemployment and individuals' mental health, physical health, and health behaviors; and b) explore the variations of these relationships between rural and urban adults in China. Methods: Ordinary linear regression models or Logit models are employed, depending on the nature (continuous vs. discrete) of the dependent variables. Results: We find that the perceived risk of unemployment was statistically and positively associated with the risk of depression, and the association was greater for rural adults than for urban adults. Rural-urban variations were observed in various dimensions. For rural adults, the perceived risk of unemployment was statistically and negatively associated with life satisfaction, the probability of gaining weight and becoming obese, the probability of having adequate sleep, and computer-based screen time. These associations were statistically insignificant for urban adults. On the other hand, the perceived risk of unemployment was statistically and negatively associated with self-rated very-good-to-excellent health condition and health-compromising behaviors (e.g., smoking and drinking) for urban adults; but such associations were statistically insignificant for rural adults. Discussion: These findings suggest that rural and urban adults exhibited different psychological and behavioral responses to the unemployment risk during the COVID-19 pandemic. Public policies aiming to improve health and employment should be strategically designed to address the unique needs of urban and rural populations.
RESUMO
Agriculture is the world's second largest greenhouse gas (GHG) emitter due to the use of fossil fuel-based fertilizers, agricultural machinery, and the burning of biomass. Meanwhile, the Group of Twenty (G20) countries, which include the world's top three agricultural markets, have a significant impact on world agricultural development. This study is the first attempt to examine the effects of the agriculture-economic growth-renewable energy nexus on carbon dioxide (CO2) emissions within the framework of the environmental Kuznets curve (EKC) in a panel of 19 nations of the G20 countries from 1990 to 2014. To do so, panel data unit root tests, cointegration tests, and the panel fully modified ordinary least squares (FMOLS) estimator are used. The main findings are as follows: (1) Panel data unit root and cointegration tests confirm the existence of a long-run relationship among the selected variables, (2) agriculture significantly increases CO2 emissions in the full sample and the developing economies of the G20, while renewable energy consumption reduces the CO2 emissions in the full sample and the developed economies of the G20, (3) the EKC indeed exists in the full sample and developed economies, while economic growth only exerts a positive impact on CO2 emissions for developing economies, indicating that the peak of CO2 emissions for developing economies has not yet been reached, and (4) varied causality links exist among the variables across the different income levels of the G20 countries. Based on the above findings, to suppress the greenhouse effect, the G20 countries' policymakers should not only promote the development of sustainable agriculture, but also stimulate renewable energy consumption, especially in developing economies.