Environmental information disclosure and firm export: evidence from China

Abstract

In this paper, we empirically investigate how a governmental environmental information disclosure (EID) program in China affects the extensive and intensive margins of export for a panel of Chinese industrial firms. The results show that stricter enforcement of environmental disclosure discourages firms’ participation in export. However, the export volume of remaining exporting firms increases following more environmental disclosure. The results are robust to a battery of robustness checks as well as an IV estimation. Mechanism analysis reveals that firms’ propensity of innovation increases after stricter enforcement of disclosure, lending support for the Porter hypothesis.

Keywords:

• Environmental regulation
• disclosure
• export
• intensive margin
• Porter hypothesis

JEL codes:

• F12
• F18
• Q50
• Q57

Notes

1 See, for example, Harris et al. (2002), Jug and Mirza (2005), Xu (2000), Costantini and Crespi (2008) and Costantini and Mazzanti (2012) among others. In addition, some literature examines the impact of environmental regulation on other competitiveness measures, such as productivity (e.g., Jaffe et al., 1995; Berman & Bui, 2001; Telle & Larsson, 2007; Lanoie et al., 2008), innovation (e.g., Jaffe & Palmer, 1997; Brunnermeier & Cohen, 2003), and economic/financial performance (e.g., Khanna & Damon, 1999; Rassier & Earnhart, 2015).

2 Possible explanations for the different results regarding the link between environmental regulation and export volume include: First, Soest et al. (2006) argue that there is little consensus about appropriate and internationally comparable measures of the stringency of environmental regulation, resulting in different conclusions using different measurements. Second, Brunel and Levinson (2016) claim that environmental regulation is multi-dimensional and different approaches of regulation may have different impacts on firm performance, including export.

3 Detrimental effects of environmental regulation on international competitiveness are found by Van Beers and Van den Bergh (1997) and Jug and Mirza (2005) among others while beneficial effects of environmental regulation are found by Xu (2000), Costantini and Crespi (2008) and Tsurumi et al. (2015) among others. More recently, Ramzy and Zaki (2018) find that environmental regulation can stimulate innovation activities, and thus improve countries’ trade competitiveness. Using a gravity model, Helble and Majoe (2017) find that the implementation of Energy Performance of Buildings Directive (EPBD) in the EU can bring about more trade in environmental goods.

4 Since the year 2003, China has passed several laws, some aspects of which involve EID, such as the 2003 Clean Production Promotion Law, the 2004 Clean Production Audit Methods (for trial implementation), and the 2005 State Council’s Decision on Strengthening Environmental Protection among others. The Measures, however, are the first nationwide laws in China specialized in EID.

5 Note that China Pollution Source Census Office has compiled the Handbook of Pollutant Emission Intensity Coefficients of Industrial Pollution Sources, which includes various pollutants’ emission intensities of 351 4-digit industrial sectors. However, those intensities cannot be directly used in this study since the types of emitted pollutants are different across sectors and thus the calculated emission intensities are not readily comparable between industrial sectors.

6 Around 0.08% of the firms in the sample have changed the city where they reside in and 3.68% of the firms have changed their reported sectors during the period.

7 We will not use the Probit or Logit model when analyzing firm participation into export since the interaction term in (1) is of our main interest and the interpretation of estimated coefficients of interaction terms in non-linear models (such as the Probit or Logit model) is quite complicated (Ai & Norton, 2003).

8 Note that the estimated effect on firm participation into trade may be under-estimated since the firms that exit the sample are more likely to be non-exporters, as discussed later on.

9 The results will be provided upon request.

10 Specifically, these variables include cities’ GDP per capita (in logs), distance to Hong Kong (in logs), SO₂ emission per GDP (in logs), internet users as a fraction of population, average output value per firm (in logs, denoted by Log(firm size)), and mayors’ tenure. We also include in the regression punishment cases against environmental violation per GDP (in logs, denoted by Punish), dummies indicating if mayors were born in locality (denoted by Native) and if they have a PhD degree or not.

11 The 2008 ASIF data are dropped because the information on new-product production is missing in that year.

Additional information

Funding

Xian-Liang Tian is grateful for the financial support from the National Natural Science Foundation of China (Grant # 72074223), the Teaching Reform Fund and Fundamental Research Funds for the Central Universities, Zhongnan University of Economics and Law (Grant # YB202162). Yu Xia is grateful for the financial support from the 2021 Discipline Construction Project of School of Law, Hubei University (Project title: Evolution of Latin American regional governance and the Construction of the Rule of Law in China; Grant # 602017200).