How does China's Western Development Strategy affect regional green economic efficiency?

Wang

2021

Front. Public Health

This paper discusses the impact of air pollution on medical expenditure in eastern, central, and western China by applying the fixed-effect model, random-effect model, and panel threshold regression model. According to theoretical and empirical analyses, there are different relationships between the two indexes in different regions of China. For eastern and central regions, it is obvious that the more serious the air pollution is, the more medical expenses there are. However, there is a non-linear single threshold effect between air pollution and health care expenditure in the western region. When air pollution is lower than this value, there is a negative correlation between them. Conversely, the health care expenditure increases with the aggravation of air pollution, but the added value is not enough to make up for the health problems caused by air pollution. The empirical results are basically consistent with the theoretical analysis, which can provide enlightenment for the government to consider the role of air pollution in medical expenditure. Policymakers should arrange the medical budget reasonably, according to its situation, to make up for the loss caused by air pollution.

Section: Resultsmentioning

confidence: 99%

Does Industrial Air Pollution Increase Health Care Expenditure? Evidence From China

Wang

2021

Front. Public Health

“…Therefore, the selection of input and output indexes will be the emphasis. According to previous studies, the factors that affect economic efficiency are sorted out [ 20 , 21 ]. Besides, based on the characteristics of China’s high-tech IDZs, five aspects are selected: economic environment, economic structure, number of talents, high-tech IDZ’s regional scale, and capital investment.…”

Section: Methodsmentioning

confidence: 99%

Analyzing the regional economic changes in a high-tech industrial development zone using machine learning algorithms

Du¹,

Ji²

2021

PLoS ONE

The aims are to improve the efficiency in analyzing the regional economic changes in China’s high-tech industrial development zones (IDZs), ensure the industrial structural integrity, and comprehensively understand the roles of capital, technology, and talents in regional economic structural changes. According to previous works, the economic efficiency and impact mechanism of China’s high-tech IDZ are analyzed profoundly. The machine learning (ML)-based Data Envelopment Analysis (DEA) and Malmquist index measurement algorithms are adopted to analyze the dynamic and static characteristics of high-tech IDZ’s economic data from 2009 to 2019. Furthermore, a high-tech IDZ economic efficiency influencing factor model is built. Based on the detailed data of a high-tech IDZ, the regional economic changes are analyzed from the following dimensions: economic environment, economic structure, number of talents, capital investment, and high-tech IDZ’s regional scale, which verifies the effectiveness of the proposed model further. Results demonstrate that the comprehensive economic efficiency of all national high-tech IDZs in China is relatively high. However, there are huge differences among different regions. The economic efficiency of the eastern region is significantly lower than the national average. The economic structure, number of talents, capital investment, and economic efficiency of the high-tech IDZs show a significant positive correlation. The economic changes in high-tech IDZs can be improved through the secondary industry, employee value, and funding input. The ML technology applied can make data processing more efficient, providing proper suggestions for developing China’s high-tech industrial parks.

“…In fact, resource and environment factors have been added into efficiency and productivity analysis framework to re-estimate China's GEE and GTFP in recent literature which draws many valuable conclusions (Du et al, 2019;Li & Wu, 2017;Long et al, 2020;Shen et al, 2019;Tang et al, 2017;Wang & Shen, 2016;Zhao et al, 2018Zhao et al, , 2020Zhou et al, 2019;Zhuo & Deng, 2020;Zhu et al, 2019). This paper found that most of the above-mentioned literature is mainly about the GEE and GTFP of China's inter-provincial industries and provinces or cities, and their research does not involve urban agglomerations and economic growth zones.…”

Section: Literature Reviewmentioning

confidence: 96%

Economic policy uncertainty and green economy efficiency: power or resistance?—Empirical evidence from Chinese major urban agglomerations

Wang

Economic Research-Ekonomska Istraživanja

2021

Policy uncertainties have always played a critical role in shaping economic outcomes, as evidenced by the recent sluggish economic growth in many countries. Green economic efficiency (GEE) is a comprehensive index to measure economic, social, and environmental development. This paper uses the slack-based measurement (SBM) directional distance function and Luenberger productivity indicator to measure the static GEE and dynamic green total factor productivity (GTFP) of China's urban agglomerations from 2003 to 2020 under constraints of resources and environment. In order to clarify the driving mechanisms of GEE and GTFP, this paper adds the factor of economic policy uncertainty (EPU). The results show that there is a positive correlation between EPU with GEE and GTFP. The possible reason is that the market mechanism plays a decisive role in improved GEE and GTFP. Therefore, policymakers should give better play to the government's macro-control role, and play the decisive role of the market mechanism in the environmental governance system to improve GEE and GTFP in a targeted manner.