Abstract
Carbon dioxide (CO2) emissions are one important factor that lead to climate change, and the burning of fossil fuels for many economic activities has significantly contributed to CO2 emissions. The USA and China together accounted for 43% of global CO2 emissions in 2013. This study assesses and compares how the economy has affected the environment by analyzing data for 50 states and DC in the USA and 30 provinces in China. From a longitudinal perspective, the findings show that the economy, measured by GDP per capita, contributed to CO2 emissions. Meanwhile, the impact has become relatively decoupled. From a spatial perspective, the coastal states and provinces that have higher GDP per capita tend to have less CO2 emissions. In addition, Democratic states in the USA tend to have less CO2 emissions than Republican states, after controlling for other variables. We explain the findings by referring to the various contexts at the state/provincial level, country level, and international level. To our knowledge, this is the first study to compare the environmental impact of the economy between the US states and China’s provinces. There are many political implications of these findings for both the USA and China moving forward, especially considering the recent political climate change in the USA, along with China’s continued expansion as a major global power.
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Notes
The relative decoupling means that the growth rate of the environmental variable is positive, but less than the growth rate of the economic variable. This conservative assessment is in comparison with the absolute decoupling that the EKC holds, which means that the environmental variable is stable or decreasing while the economic variable is growing (Organization for Economic Co-operation and Development 2002).
The currency exchange rate between RMB and US dollar has changed over years. It was 8.29 in 1997 ($1 equals approximately ¥8.29) and was 6.83 in 2009.
We conduct several tests to check for violations of modeling assumptions. First, the mean VIF obtained from running an OLS regression of the saturated model is 1.01, which indicates that multicollinearity is likely not a concern. Second, we estimate the model by excluding each state/province and each year in turn and find that there are no potential influential cases. Third, we estimate the first-difference baseline model to assess whether the PW regression model estimates are spurious. The results are consistent, and the PW regression analyses are not biased.
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Hao, F., He, G. & Snipes, M. A comparative study of the economy’s environmental impact between states in the USA and provinces in China. J Environ Stud Sci 8, 132–141 (2018). https://doi.org/10.1007/s13412-018-0474-9
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DOI: https://doi.org/10.1007/s13412-018-0474-9