Environmental Performance and Regulation Effect of China's Atmospheric Pollutant Emissions: Evidence from Three Regions and Ten Urban Agglomerations

This paper employs the slack-based measure method and an extended Luenberger productivity indicator to estimate and decompose the atmospheric environmental performance under the constraints of energy and atmospheric pollutant emissions [i.e., the growth of the atmospheric environment total factor productivity (AETFP)] of the three regions and ten urban agglomerations (TRTAs) in China. Specifically, undesirable output is considered as both carbon and air pollutant emissions, i.e., CO2, SO2, and NOx emissions. Also, based on the proposed approach, we identify the different paths of the technical change as a crucial driver of the AETFP growth. Furthermore, using the spatial econometric model with a symmetric geographical distance weight matrix and an asymmetric economic geography weight matrix, we investigate the effect of different types of environmental regulation on the AETFP growth to verify the Porter hypothesis in China. The results show that the main drivers of China's atmospheric environment inefficiency are air pollutant emissions (SO2 and NOx), carbon emissions, and fossil energy use. Spatially, the environment inefficiency presents a decreasing trend from northern China to southern China. The improved performance of SO2 emissions made more contributions to the AETFP growth during China's 11th Five-Year Plan period (2006-2010), while NOx emissions has a marginal positive effect on the AETFP growth is marginal. Despite the differences in the technical change across regions, the technical progress offsets the negative impact of declining technical efficiency on the AETFP growth. Overall, energy-saving and emission-reduction policies and technologies in TRTAs exert a decisive influence on the AETFP growth. In particular, the spatial econometric results indicate that the market-motivated environmental regulation has a positive effect on the AETFP growth and thus conforms to the Porter hypothesis in China but does not cause the race-to-the-bottom effect among local governments, while the command-and-control oriented regulation leads to a race-to-the-bottom effect and undermines the AETFP growth.