An Empirical Analysis of the Nonlinear Relationship Between Environmental Regulation and Manufacturing Productivity

Sánchez-Vargas, Armando; Mansilla-Sanchez, Ricardo; Aguilar-Ibarra, Alonso

doi:10.1016/s1514-0326(13)60015-x

Cited by 39 publications

(15 citation statements)

References 16 publications

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“…On the other hand, appropriate intervention can avoid deteriorating environmental quality results from enterprise excessive competition. The above results coincide with the nonlinear effect from the perspective of investment, which is significantly different from previous scholars' research (Sanchez-Vargas et al, 2013;Yin et al, 2015) [26,27]. The latter tells us the government should enhance research of the optimal intensity of invest-based environmental regulation in different areas.…”

Section: Conclusion and Policy Recommendationscontrasting

confidence: 60%

“…Other scholars believe that there is nonlinear transformation between environmental regulation and environmental pollution (Sanchez-Vargas et al, 2013; Yin et al, 2015; Chakraborty and Chatterjee, 2017; Xie et al, 2017) [26][27][28][29]. Sanchez-Vargas et al (2013) found that the nonlinear effects of manufacturing productivity and environmental regulation are reflected in the size of the enterprise [26]. Wang and Shen (2016) showed an inverted "U" relationship with three thresholds between China's environmental regulation and environmental productivity based on data envelopment analysis model [15].…”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Nonlinear Effects of Environmental Regulation on Environmental Pollution

Liu

Neng-sheng

2019

Discrete Dynamics in Nature and Society

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This paper classifies environmental regulation into two types and constructs a theoretical framework to explore the influences of fee-based environmental regulation and invest-based environmental regulation on environmental pollution. It then establishes some dynamic spatial autoregressive nonlinear econometric models to test the theoretical hypothesis based on 30-area panel data from 2004 to 2016. The results illustrate that inverted “U” shape curve relationship exists between fee-based environmental regulation and environmental pollution, while a “U” shape curve relationship between invest-based environmental regulation and environmental pollution exists. In addition, the findings suggest that improving the proportion of secondary industry can directly promote the environmental quality while effectively control of foreign direct investment and fiscal decentralization is also indispensable. Thus, the government should make targeted research about the optimal intensity of fee-based environmental regulation and invest-based environmental regulation and make targeted enterprise policy for the environmental pollution reduce, which contains promoting the energy revolution and strengthening the depth and strength of opening-up step by step.

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Section: Conclusion and Policy Recommendationscontrasting

confidence: 60%

Section: Literature Reviewmentioning

confidence: 99%

Nonlinear Effects of Environmental Regulation on Environmental Pollution

Liu

Neng-sheng

2019

Discrete Dynamics in Nature and Society

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“…includes environmental practices containing PACE and ET. As in the literature (Rubashkina et al 2015;Sanchez-Vargas et al 2013;Yang et al 2012, among others), PACE is used as a proxy for stringent environmental regulations. Besides, ET is considered as the proxy for firm compliance.…”

Section: Environmental Regulation and Tfp Convergencementioning

confidence: 99%

The role of environmental regulations and innovation in TFP convergence: Evidence from manufacturing SMEs in Vietnam

Nguyen-Huu¹,

Nguyen-Khac²,

Tran-Nam³

2017

WIDER Working Paper

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This is a pioneer study investigating the relationship between environmental compliance and TFP convergence for SMEs. It examines the impacts of environmental compliance, and its combination with innovation, on TFP convergence of manufacturing SMEs. We applied the dynamic panel regression method to estimate stochastic TFP. We find evidence of a β-convergence but a σ-divergence. Impacts of environmental practices of firms-pollution abatement and control expenditure, and environmental treatment-are only significant through their interaction with innovation. The β-convergence in firms' TFP is influenced by their industrial identity, while firms' size and investment have marginal impacts.

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“…Some researchers have used a large set of indicators to determine the strength of environmental regulation policies: Sanchez-Vargas et al [59] used "the sum of investment on machinery and equipment aimed at reducing pollution at the plant level" to describe it. Kheder and Zugravu [31] employed the Z-score method to calculate the standardized values of three indicators-international environmental agreements, INGOs' members per million of population, and GDP/unit of energy used-and used them to capture countries' environmental regulation stringency.…”

Section: Data Descriptionmentioning

confidence: 99%

“…In line with China's particular situation, we do not use the method by Kheder and Zugravu [31] because NGOs do not play a leading role in environmental regulation in China. We do not include the indicator used by Sanchez-Vargas et al [59] due to data availability.…”

Section: Data Descriptionmentioning

confidence: 99%

Environmental Regulation, Economic Network and Sustainable Growth of Urban Agglomerations in China

Chong

Cheng-lin

2016

Sustainability

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Abstract:In this paper, we examine the influence of environmental regulation on sustainable economic growth from both theoretical and empirical perspectives. Our research is twofold. First, we apply a modified NEG (New Economic Geography) model to analyze how environmental regulation influences firms' location choices and cities' sustainable economic growth. Second, we test a spatial econometric model employing panel data of the three largest urban agglomerations in China from 2003 to 2013 to study the relationship between environmental regulation and sustainable economic growth as well as the spillover channels of economic activities. The results reveal a remarkable negative effect of environmental regulation on economic growth. In addition, we find no sufficient evidence to prove the existence of long-term effects of environmental regulation on economic growth in the three urban agglomerations. Furthermore, using different weight matrices to illustrate the different economic networks of the urban agglomeration, we validate the difference in spillover mechanisms across these three urban agglomerations. Specifically, the disparity in environmental regulation acts as a spillover channel for the Yangtze River Delta and the Pearl River Delta, while it is not significant for Jing-Jin-Ji.

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An Empirical Analysis of the Nonlinear Relationship Between Environmental Regulation and Manufacturing Productivity

Abstract: for their excellent research support and to Flor Brown and Lilia Dominguez for giving us access to their own data. We also thank to three anonymous referees for their useful comments. All errors are our own responsibility.

Cited by 39 publications

References 16 publications

Nonlinear Effects of Environmental Regulation on Environmental Pollution

Nonlinear Effects of Environmental Regulation on Environmental Pollution

The role of environmental regulations and innovation in TFP convergence: Evidence from manufacturing SMEs in Vietnam

Environmental Regulation, Economic Network and Sustainable Growth of Urban Agglomerations in China

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