Abstract
The studies on environmental effects of foreign trade and its spatial variations are helpful to design and implement environmental protection countermeasures. In order to eliminate the adverse effects of insufficient observation values on the accuracy of regression results and dynamic information quantity of fitting equation during empirical study, panel data of the mid-eastern provinces and cities of China from 1985 to 2007 were selected based on the adjustment of classical regression model in this paper. Panel unit root test and panel cointegration analysis method were applied to investigating the environmental effects of foreign trade and its spatial variations in the mid-eastern provinces and cities of China and its three groups divided by foreign trade dependence. The results show that all scale effects are positive, while all technical effects are negative and unable to counteract positive scale effects. Foreign trade development is regarded as an important cause for outstanding eco-environmental problems in the mid-eastern provinces and cities of China. Total effects and structural effects are significantly different among different groups because of spatial variations in environmental policies, export destinations, source of FDI, etc. Following the principle of ‘coordinating generality and considering differences comprehensively’, it is essential to issue a series of policies and countermeasures corresponding to differences in regional environmental effect of foreign trade, in order to coordinate the relationship between foreign trade development and eco-environment in each region.
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Foundation item: Under the auspices of Major State Basic Research Development Program (No. 2007FY110300), Soft Science Research Project of Chongqing Science & Technology Commission (No. CSTC2011cx-rkxA0120), Science and Technology Research Project of Chongqing (No. CSTC, 2009CB2015)
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Jin, X., Dong, S., Luo, L. et al. Environmental effects of foreign trade and its spatial variations in mid-eastern provinces and cities of China. Chin. Geogr. Sci. 22, 626–636 (2012). https://doi.org/10.1007/s11769-012-0546-9
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DOI: https://doi.org/10.1007/s11769-012-0546-9