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Centralizing Trends and Pollution Law Enforcement in China

Published online by Cambridge University Press:  10 August 2017

Benjamin van Rooij*
Affiliation:
UC Irvine, School of Law.
Qiaoqiao Zhu
Affiliation:
Australia National University.
Wang Qiliang
Affiliation:
Yunnan University.
*
Email: bvanrooij@law.uci.edu (corresponding author).
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Abstract

This article analyses centralizing trends that may be able to reduce the negative influence of local protectionism on environmental law enforcement in China. The article finds that as centralizing trends unfolded, enforcement over time has become stricter and more frequent, however with only minor effects in reducing pollution. Moreover it finds a situation of uneven enforcement with richer and more urbanized areas having much stronger and more frequent enforcement than inland areas. Centralizing trends may thus have spurred stronger enforcement, but concurrently allowed for an uneven enforcement. At the same time, the article finds a continued local influence, keeping enforcement too weak to have much effect in reducing pollution and allowing for local interests to shape enforcement into unequal outcomes.

摘要

文章旨在分析中央集权化的趋势是否有可能减少地方保护主义对于中国环境执法所产生的负面影响。研究发现, 随着中央集权化趋势所呈现出来的执法实践正变得更加严格和频繁, 但是对于减少污染所起到的作用甚微。此外, 研究发现, 执法存在不均衡的情形, 即相对于内陆地区, 较富裕、城市化程度较高的地区执法强度更高、更频繁。因此, 中央集权化的趋势有可能刺激出较强的执法, 但同时也可能催生出不均衡的执法实践。与此同时, 研究发现, 地方性的影响仍然持续存在, 使得执法太弱而无法对减少污染产生显著作用, 并且使得地方性的利益塑造出不同等的执法后果。

Information

Type
Special Section on Central–Local Relations and Environmental Governance in China
Copyright
Copyright © SOAS University of London 2017 
Figure 0

Table 1: Development of Administrative Sanctions, Fines, Fines per Case, and Relocations and Closures of Polluting Firms in China 1999–2013 (China's Annual Environmental Statistic Yearbooks (1999–2013))

Figure 1

Table 2: Fixed-effect Regression with Pollution as Dependent Variable and GDP Output and Enforcement as Independent Variables Using Data from Each Province from the Following Years: Administrative Sanctions (1999–2011), Average Fines per Case (2001–2006) and Forced Relocations and Closures of Polluting Firms (1999–2008). (Annual Statistic Reports on the Environment in China (1999–2011))Dependent Variable: Pollution

Figure 2

Table 3: Regional Variation in Sanction/Pollution (1999–2011), Average Fines per Case (2001–2006) and Forced Relocations and Closures per Pollution (1999–2008). (Annual Statistic Reports on the Environment in China (1999–2011))

Figure 3

Table 4: Number of EPB Staff 1999–2013 (China's Annual Environmental Statistic Yearbooks (1999–2013))

Figure 4

Table 5: Fixed-effect Regression with Three Enforcement Measures as Dependent Variables and Non-Industrial GDP, Per Capita Income, Staff, Letters, Visits as Independent Variables Using Data from Each Province from the Following Years: Administrative Sanctions (1999–2011), Average Fines per Case (2001–2006) and Forced Relocations and Closures of Polluting Firms (1999–2008). (Annual Statistic Reports on the Environment in China (1999–2011))Dependent Variable: Enforcement intensity (enforcement/pollution)

Figure 5

Table 6: Number of Environmental Complaint (Letters and Visits), Total Complaints per Main Six Types of Pollutants, and Total Complaints per Industrial GDP 1999–2010 (China's Annual Environmental Statistic Yearbooks (1999–2010))

Figure 6

Table 7: Interaction Per Capita Income and Pollution Fixed-Effect Regression with Three Enforcement Measures as Dependent Variables and Non-Industrial GDP, Per Capita Income, Staff, Letters, Visits, and Interaction between Per Capita Income and Pollution as Independent Variables Using Data from Each Province from the Following Years: Administrative Sanctions (1999–2011), Average Dependent variable: Enforcement Intensity