Total retail goods consumption, industry structure, urban population growth and pollution intensity: an application of panel data analysis for China.

There has been a growing concern regarding the regulation of environmental pollution in the face of a growing population, global warming, and climate change. Governments around the world have devised various mechanisms and policy strategies to ameliorate the worsening condition of natural environment around the world. Similar to the developed world, in China, the government is also aware of deteriorating environmental conditions. Hence, the existing abatement instruments include pollution discharge fees and several other policy strategies. This research is conducted to investigate the association between pollution intensity and its determinants, i.e., pollutant discharge fees and urban population, third industry structure, and total retail goods consumption. The secondary data of 29 provinces is used for empirical analysis. The principal component analysis is used to develop a single index called pollution intensity, and panel autoregressive distributed lags model (ARDL), or pooled mean group (PMG) analysis, is employed to find long-run and short-run relationship. The empirical findings show that pollution discharge fees negatively affects pollution intensity. Total retail good consumption and urban population increase pollution intensity. However, third industry structure helps to control pollution intensity. These results suggest reforms in the existing environmental regulations policy by targeting more pollutant intensive provinces.