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Published in: Public Choice 1-2/2021

28-07-2020

New evidence on the soft budget constraint: Chinese environmental policy effectiveness in SOE-dominated cities

Authors: Mathilde Maurel, Thomas Pernet

Published in: Public Choice | Issue 1-2/2021

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Abstract

This paper analyzes the efficiency of a set of environmental measures introduced by China’s 11th Five-Year Plan in 2006, using a rich and unique data set assembled from the Ministry of Environmental Protection and the State Environmental Protection Agency. By exploiting plausibly exogenous variation in regulatory stringency generated by the regulatory system across China’s provinces, we find evidence that pollution-intensive cities reduced their SO2 emissions substantially, whereas cities with a strong state-owned enterprise (SOE) presence did not. We interpret the results as pointing to evidence of Chinese SOEs’ ongoing soft budget constraints. The findings are robust to the inclusion of different fixed effects and other key determinants of pollution. Moreover, we investigate the main factors underlying regulatory non-compliance: the overlapping (or not) of “Two Control Zone” (Special Policy Zone, Coastal) cities wherein environmental (growth) policies are prioritized; the existence of turning points below (above) which growth and reductions in pollution substitute for (complement) each other; the size and extent of industrial concentration, which determines the possibilities of firms negotiating with the local authorities; and finally, the regulation-induced adoption of cleaner technologies by polluting firms, which enhance productivity and lower SO2 emissions.

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Appendix
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Footnotes
1
The role of Chinese banks in rescuing SOEs and dampening the transition towards a green growth pattern has been documented in Maurel et al. (2019).
 
2
SOEs are similar to large corporations because they are usually large as well.
 
3
China has adopted its own air quality standard, which is less stringent than the World Health Organization’s standard. China’s National Environmental Monitoring Center (CNEMC) collects real-time, hourly air quality data for the country’s major cities. The real-time data are available at http://​www.​cnemc.​cn/​. Major air pollutants including SO2, NO2 and PM10 are monitored. To evaluate air quality, the Chinese government defines three classes. Class I means that the yearly SO2 level is less than 0.02 mg/m3, or a daily average of less than 0.05 mg/m3. Class 2 is less restrictive. The yearly average should not exceed 0.06 mg/m3, with a daily average of about 0.15 mg/m3. Class 3 corresponds to poor air quality. The yearly average can exceed 0.10 mg/m3; the daily average is 0.25 mg/m3. By contrast, WHO recommends a daily average of less than 0.02 mg/m3. For the record, exposure to high SO2 levels poses a danger to health. According to WHO, “SO2 can affect the respiratory system and the functions of the lungs, and causes irritation of the eyes. Inflammation of the respiratory tract causes coughing, mucus secretion, aggravation of asthma, and chronic bronchitis and makes people more prone to infections of the respiratory tract”.
 
4
A city was designated as an acid rain control zone if (1) its average pH value of precipitation was equal to or less than 4.5; (2) its sulfate deposition was above the critical load; (3) its SO2 emissions were high.
 
5
Three hundred and thirty-eight small power units, 784 product lines in small cement and glass plants, 404 lines in iron and steel plants, and 1422 additional pollution sources had closed and, by May 2001, 4492 high-sulfur coal mines had ceased production in the TCZ area (He et al. 2002).
 
6
The second policy required the installation of flue gas desulfurization (FGD) equipment on new and existing coal-fired power plants. At the end of 2005, FGD equipment had been installed on 46.2 GW of coal-fired electricity generation capacity—12% of the total; see Cao et al. (2009).
 
7
Among the most polluting firms, 84.3% achieved the national target in terms of SO2 emissions (China Environment Yearbook 2001).
 
8
Dewatripont et al. (1999) and Alesina and Tabellini (2007) are among the first to argue that the features of mandated tasks largely drive bureaucrats’ performance and efforts. The missions must be embedded in a precise interpretation scheme and be linked to explicit performance measures. According to Alesina and Tabellini (2008), bureaucrats choose their effort levels according to two parameters: a concrete objective to achieve and the weight of each task in the likelihood of moving up the hierarchical leadership ladder. The performance measures may or may not be correlated with global, organizational objectives.
 
9
Another potential bias results from the fact that urban sectors affected more severely by the regulation may exit the market. If so, the regression will falsely impute a reduction in pollution to the regulation. City sector level observations in our data set allow us to probe that possibility by investigating various samples that operated throughout the entire period (stayers) or not (leavers). Our results are robust and available upon request.
 
10
We check the robustness of the results by re-sorting at different thresholds: the 60th, 70th and 80th deciles.
 
11
The methodology for sampling in two subsamples, concentrated versus non-concentrated cities, is based upon the computation of a Herfindahl index. Details are presented in Sect. 5.3.2.
 
12
In Sect. 5, we estimate Kuznets curves to verify that the richest cities pollute less.
 
13
The breakdown of provinces here follows that of Wu et al. (2017). The central provinces are Anhui Henan, Hubei, Hunan, Jiangxi and Shanxi. The coastal provinces are Beijing, Fujian, Guangdong, Hainan Hebei, Jiangsu, Shandong, Shanghai, Tianjin and Zhejiang. The northeastern provinces are Heilongjiang, Jilin and Liaoning. The northwest provinces are Gansu, Inner Mongolia, Ningxia, Qinghai, Shaanxi and Xinjiang. The southwestern parts are Chongqing, Guangxi, Guizhou, Sichuan, Yunnan and Xizang.
 
14
Which we borrowed from Chen et al. (2018).
 
15
For instance, Shanghai Province was expected to reduce its SO2 emissions by 13,000 tons over the period 2005–2010.
 
16
4.9% = 1 − exp(0.478 * 0.101678), and 0.101678 is the average \({\text{Target}}_{i}\) value for non-SOE-dominated cities (see Table 4, column 3). Assuming that SOE-dominated cities, where \({\text{Target}}_{i}\) is set equal to 0.12381 million tons, would react the same way to the target policy, SO2 emissions in those cities could also decrease by 5%.
 
17
Similar results hold for the 70th and 80th deciles; they are available upon request.
 
18
Porter’s theory has been the subject of a vast body literature, the controversy being that green projects may well underperform the market because they bypass non-green projects that offer higher returns. In accordance with Porter’s theory, meta-analysis finds that the relationship between firms’ environmental and financial performance is positive overall (Endrikat et al. 2014; Horvahova 2010; Albertini 2013). A recent study (Song et al. 2017) reports a positive relationship for A-listed companies in China. From a more theoretical perspective, Porter and van der Linde (1995a, b) argue that as consumers become more sophisticated and green market segments open up globally, the early-mover “clean” companies can gain a lasting competitive edge.
 
19
The results with city, industry and year fixed effects are available upon request.
 
20
The SPZ cities include high-technology industry development areas, economic and technological development areas, and export processing zones.
 
21
The output share of SOEs in TCZ is 25.3%, 29% in the hinterlands, and 26% in SPZs, whereas the average output share of SOEs in the total sample reaches 24%.
 
22
Similar results hold for the 70th and 80th deciles; they are available upon request.
 
23
These estimates are lower than $8000 per capita, corresponding to the average turning point globally (Grossman and Krueger 1995). The turning point indeed depends on the type of pollutant (COD, SO2, NOX, PM) used in the empirical specification. As regards SO2, it is close to our estimate: in Grossman and Krueger (1995) it is $4000, in Panayotou (1993, 1995) it is around $3000 per capita, and in Shafik and Bandyopadhyay (1992) it is $3670 per capita. Kahn and Zheng (2016) report a turning point in China set equal to US$10000; it is computed from data on particulate matter annual mean concentration (PM10).
 
24
Our data set shows that the median per capita GDP of SOE-dominated cities is higher by RMB 4000: RMB 24,730 for SOE-dominated cites and RMB 20,175 for non-SOE-dominated cities. The mean per capita GDP of non-SOE-dominated cities and SOE-dominated cities is not significantly different: RMB 28,458 for the former and RMB 28,539 for the latter.
 
25
Similar results hold for the 70th and 80th deciles; they are available upon request.
 
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Metadata
Title
New evidence on the soft budget constraint: Chinese environmental policy effectiveness in SOE-dominated cities
Authors
Mathilde Maurel
Thomas Pernet
Publication date
28-07-2020
Publisher
Springer US
Published in
Public Choice / Issue 1-2/2021
Print ISSN: 0048-5829
Electronic ISSN: 1573-7101
DOI
https://doi.org/10.1007/s11127-020-00834-1

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