Nonlinear Effects of Governmental and Civil Environmental Regulation on Green Total Factor Productivity in China
Nonlinear Effects of Governmental and Civil Environmental Regulation on Green Total Factor...
Lei, Xubin;Wu, Shusheng
2019-11-03 00:00:00
Hindawi Advances in Meteorology Volume 2019, Article ID 8351512, 10 pages https://doi.org/10.1155/2019/8351512 Research Article Nonlinear Effects of Governmental and Civil Environmental Regulation on Green Total Factor Productivity in China 1 2 Xubin Lei and Shusheng Wu School of Economics and Trade, Hunan University, Fenglin Road, 410079 Changsha, Hunan Province, China State Grid Hunan Electric Power Company Limited, Xinshao Dong Road, 410004 Changsha, Hunan Province, China Correspondence should be addressed to Shusheng Wu; wushushengjy@163.com Received 1 July 2019; Accepted 3 October 2019; Published 3 November 2019 Academic Editor: Herminia Garc´ ıa Mozo Copyright © 2019 Xubin Lei and Shusheng Wu. 1is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 1is paper employs metafrontier Malmquist-Luenberger index to measure green total factor productivity and then builds panel model to investigate the nonlinear effects of both governmental and civil environmental regulation on green total factor productivity in 30 provinces of China in 2007–2016, where the threshold variables are environmental awareness and regulatory foundation. 1e results show that green total factor productivity takes the characteristic of cyclical fluctuation, and the magnitude and its growth rate in the eastern region are higher than those in the midwestern region. 1e degrees of the governmental and civil environmental regulation and green total factor productivity display single environmental awareness threshold and regulatory foundation threshold. It should be noted that the sign of governmental and civil environmental regulation on green total factor productivity will transform from negative to positive, if and only if threshold variables ascend and surpass the threshold value. Under the condition of metafrontier technology, governmental environmental awareness threshold value, based on the in- vestigated corruption and malpractice cases by the procuratorates among every hundred thousand people, reaches 0.2158, and civil environmental awareness threshold value based on the per capita education level will attain 12.2330 years, and the cor- responding regulatory foundation index threshold values are 0.0163 and 0.0154. 1ese findings show clear policy implications: rather than continually promoting the level of governmental environmental regulation, civil performance, environmental awareness, and regulatory foundation should be considered. are major motivations for enterprises to improve total factor 1.Introduction productivity. In this paper, we will endeavor to explore afresh Since China’s reform and opening-up, great achievements the underlying nonlinear relationship between environmental have been achieved based on China’s rapid economic de- regulation and total factor productivity. velopment, and residents received huge bonuses from the Governmental law enforcement should be primarily reform and development in the spiritual and material aspects. through discharging standards for pollutants, levying pol- But backward production technology and lack of human lution tax, providing technical innovation subsidies, and resources lead to new growth model whose major charac- improving the pollutant emission property right transaction teristics are “high energy consumption and low energy effi- market to carry out the regulation on enterprise [1–4]. It ciency, high input and low output,” which cause extreme should be pointed out that most of researches assume that decrease in production resources and ecological environment environmental regulation is equal to government-led en- deterioration. Outline of China’s 13th five-year plan points vironmental regulation, which ignores the personal role in out key to promote sustainable environment performance is that behavior. In fact, personal utility becomes more and increasing productivity, which is also the core strategy for more important role in environmental protection in in- enterprise. Market competition and government regulation formation-based or legalization-based society, especially in 2 Advances in Meteorology China. As basic public resource, excellent environmental 1ese above research papers provide meaningful study protection becomes scarce resource, while the elasticity of perspectives to understand and analyze the correlation be- tween governmental environmental regulation and pro- demand for civil healthy living tends to be lower level. Moreover, scholars presume that environmental protection ductivity, while they seldom go to study regulatory utility of law enforcement in different areas is homogeneous, which civil environmental regulation. Ebenstein [14] found that means they hold the same law enforcement utility. Taking abominable environment triggered by the production pol- China as an example, environmental awareness and regu- lution contributes to the enhancement of the demand and latory foundation are significantly heterogeneous, which can supply of civil society to protect the environment or promote affect the above law enforcement utility [5]. Among them, the total factor productivity. Zhang et al. [15] formulated the regulatory foundation reflects the regulation resistance de- Hybrid Luenberger index to measure regional industrial termined by local economic structure. 1ese pose questions green productivity and explored whether civil environ- mental protection forces the growth of China’s industrial for us: as for region heterogeneity of environmental regu- lation and regulatory foundation, can it affect the influence green productivity or not, which shows that, compared with the intensity of environmental pollution and other passive of environmental regulation on the green total factor pro- ductivity effect and how does one resolve the dilemma of environmental protection incentives, the public are more economy growth and environmental regulation? sensitive to per capita income level, education quality, health 1e remainder of this paper is organized as follows. concern, and other rational environmental protection in- Section 2 presents the corresponding literature review and centives. But, the above scholars did not take the hetero- innovation points. Section 3 denotes methodology. Section 4 geneity of the environmental awareness and regional is data. Section 5 presents the empirical analysis results. regulatory foundation, which is not comprehensive. In order Section 6 concludes this paper and provides some con- to fill these gaps, we make the following improvements. Civil structive policy implications. environmental regulation, environmental awareness, and regulatory foundation should be taken into account as the core explanatory variables or threshold variables. 2.Literature Review 1e effective measurement of green total factor pro- Since Porter and Linde [1] put forward Porter Hypothesis, ductivity is the premise and guarantee to estimate the correlation between regulation and productivity. 1e sto- relationship between environmental regulation and pro- ductivity becomes an important and hot study topic. Based chastic frontier approach (SFA) and the data envelopment on different research methods, different research objects, analysis (DEA) are mainstream research methods. What and different research data, three distinct research state- should be highlighted is SFA hinge on model parameters, ments have been obtained [6–10]. (1) Hypothesis of cost while DEA can overcome the potential error derived from competition: Becker [6] found that industries with higher the above parameters. Since Charnes et al. [16] creatively environmental regulation cost have no statistically re- proposed linear programming to calculate efficiency or productivity, the DEA method has been far-ranging used or markable influential effect in manufacturing industries, which support the hypothesis of cost competition that en- optimized with nonparametric measurement [17–20]. Charnes et al. [16] employed new directional distance terprise innovation does not offset cost with environmental regulation. (2) Porter hypothesis: Porter and Linde [1] took function to enhance the measurement accuracy for pro- ductivity based on the unexpected output. DEA model the dynamic characteristic of technology innovation in econometric model and insisted that compensation earnings contains radial situation and nonradial situation, while both derived from technology innovation in the long term are of them hold information loss under the condition of using bigger than the competition effect. Zhang et al. [11] used separately. Epsilon based measure (EBM) effectively covers Malmquist-Luenberger index to calculate productivity and the advantages of both radial situation and nonradial situ- established econometric model to explore correlation be- ation [21]. Moreover, most researchers assume that ho- tween the strictness of environmental regulation and pro- mogeneity is normal for enterprise productivity. Oh and Lee [22] put forward metafrontier Malmquist-Luenberger ductivity and then found that positive relationships are tested in empirical analysis which support Porter Hypoth- (MML) index to propose grouping frontier to measure productivity combined with metafrontier framework [23]. esis. (3) Uncertainty hypothesis: Wang and Shen [12] adopted regulatory intension as threshold variable to analyze Reference for scholar’s research, MML index is the effective the nonlinear relationship between environmental regula- and reasonable method to measure green total factor tion and total factor productivity. Results show that an productivity. “inverted U-shaped” correlation exists. Xie et al. [13] employed a panel threshold model and a province-level 3.Methodology panel dataset during 2000–2012 to examine different types of environmental regulations and heterogeneous influence on 3.1. Econometric Model. 1e purpose of this paper is to study green productivity. Research results show that both com- potential nonlinear relationship between environmental mand-and-control regulation and market-based regulation regulation and total factor productivity, whose method is have a nonlinear relationship and can be positively related to using the cross terms of the following two aspects: envi- green productivity but with different constrains on regu- ronmental regulation with environmental awareness or lation stringency. regulation foundation to construct the threshold Advances in Meteorology 3 econometric model. What should be stated is that envi- construct comprehensive index to measure the regulation ronmental awareness contains governmental environmental foundation. Moreover, studies have shown that technology awareness, civil environmental awareness, enterprise envi- research and development strength, domestic capital stock ronmental awareness, and social environmental awareness, of R&D, and foreign direct investment have significantly while regulation foundation reflects the cost factors or influence on productivity [24–26]. Considering that the marker factors, which may influence the government on green total factor productivity may have the certain conti- how to implement environmental regulation decision- nuity, a dynamic econometric model would be adopted. making. 1en, infrastructure level, industrial structure, Taking significant volatility of economy into consideration, marketization level, and opening degree are chosen to four econometric models are established as follows: MML � α + α MML + α GER + α PER + α (GER∗ FUB) it 0 1 it− 1 2 it 3 it 4 it (1) + α QYJ + α RKM + α RD + α CRD + α FDI + ε + c + μ , 5 it 6 it 7 it 8 it 9 it t i it MML � β + β MML + β GER + β PER + β (PER∗ REL) + β QYJ it 0 1 it− 1 2 it 3 it 4 it 5 it (2) + β RKM + β RD + β CRD + β FDI + ε + c + μ , 6 it 7 it 8 it 9 it t i it MML � χ + χ MML + χ GER + χ PER + χ (GER∗ REF) + χ QYJ it 0 1 it− 1 2 it 3 it 4 it 5 it (3) + χ RKM + χ RD + χ CRD + χ FDI + ε + c + μ , 6 it 7 it 8 it 9 it t i it MML � δ + δ MML + δ GER + δ PER + δ (PER∗ REF) + δ QYJ it 0 1 it− 1 2 it 3 it 4 it 5 it (4) + δ RKM + δ RD + δ CRD + δ FDI + ε + c + μ , 6 it 7 it 8 it 9 it t i it distance function to maximize the desirable output or where i is the province, t stands for year, MML represents the green total factor productivity, GER denotes the govern- minimize the undesirable output [9, 18, 21, 29]. 1is paper mental environmental regulation, PER shows the civil en- supposes that there are N kinds of production resources, M vironmental regulation, FUB is the governmental kinds of desirable outputs, and L kinds of undesirable environmental awareness, REL stands for the civil envi- outputs for each decision-making unit (DMU). Firstly, we ronmental awareness, REF represents the regulation foun- refer to the definitions by Fare ¨ et al. [30]; environmental dation, QYJ denotes the enterprise environmental technology function is introduced as in the following pro- awareness, RKM is the social environmental awareness, RD duction set: denotes the technology research and development strength, e u e e u u P(x) � X,Υ ,Υ x≥ Xλ, y ≤Υ , y � Υ λ, λ≥ 0 ,