Discussion Paper No. 121
Is Corporate Environmental Responsibility
More Valuable in
the Shaky Period? The Moderating Effect ofOwnership Type
Zhou Hui and Jun Nagayasu

March, 2021

Data Science and Service Research
Discussion Paper

Center for Data Science and Service Research

Graduate School of Economic and Management
Tohoku University27-1 Kawauchi, Aobaku

Sendai 980-8576, JAPANIs Corporate Environmental Responsibility More Valuable in
the Shaky Period? The Moderating Effect of Ownership Type*
Zhou Hui Jun Nagayasu

Abstract
Local protectionism is a severe problem in Chinese environmental governance thatoffers enterprises various levels of protection from environmental regulations according todifferent ownership types. Therefore, we examine the effectiveness of corporate environmental responsibility (CER) engagement on firm value with emphasis on the moderatingrole of ownership type. The study period is split into a period with a steady institutional
background (2006–2015) and a shaky period of environmental reforms (2016–2019) tocapture the difference in legal circumstances. We find that, first, the impact of CER on
firm value changed significantly from negative to positive over the two periods. Second,
ownership type played a moderating role that influenced CER effectiveness on firm value.
Third, given the environmental reforms, CER effectiveness for state-owned enterprises affiliated with the central government increased the most while that for private enterprises
increased the least.
JEL classification: M14, G32, H70
Keywords: Corporate environmental responsibility; Firm value; Centralization; Local
protectionism; Ownership type*This study is partially supported by the Tohoku Forum for Creativity via the thematic program, Environmental and Financial Risks. We acknowledge the helpful comments and suggestions given by Akira Hibiki,
Xintong Li, and other attendees of the online International Conference of Young Researchers Meeting on
Environmental Risks (December 2020).

Tohoku University, Graduate Program in Economics and Management, Address: 27-1 Kawauchi, Aobaku, Sendai, Miyagi 980-8576 JAPAN.Email: moyinghuifree@gmail.com, Tel: +81 22 795 6265, Fax: +81 22
795 6270.
Tohoku University, Graduate School of Economics and Management, Address: 27-1 Kawauchi, Aoba-ku,
Sendai, Miyagi 980-8576 JAPAN. Email: jun.nagayasu.d8@tohoku.ac.jp, Tel: +81 22 795 6265, Fax: +81 22
795 6270.

1

1

Introduction

With growing environmental degradation, studies are increasingly focusing on corporate environmental responsibility (CER) engagements.1 CER refers to a firm’s willingness and ability
to combine environmental considerations with its daily operations and management. The
related literature is mainly devoted to the connotation, determinants, and consequences of
CER (Porter and Kramer, 2006; Jo and Harjoto, 2012). In China, empirical studies haveanalyzed the determinants and consequences of CER. He and Chen (2009) discuss the driversof CER among Chinese corporations and find the government and the social environment
to be the most important in creating CER consciousness. Zeng et al. (2010) investigate thedeterminants and status of environmental information disclosure of Chinese listed companies.
Du et al. (2014) examine religion’s influence on polluting enterprises and find that Buddhism
is significantly positively associated with CER. Wu et al. (2020) and Li et al. (2020) evaluate
CER’s impact on firm performance using different mediating factors.
Nonetheless, previous empirical studies do have some limitations. One limitation is thatno attention has been paid to the evolution of CER’s impact. That is, most studies implicitly
assume a stable background regarding CER investments, which results in the same consequence from the same level of CER engagement. This assumption is reasonable for somedeveloped countries, whose institutional and social backgrounds are relatively mature andstable (Holtbrügge and Dögl, 2012). However, it is impractical for countries such as China,
where comprehensive environmental management reforms undertaken since 2016 have created a shaky institutional background. Nearly all listed enterprises have been investigatedfor a potential violation of environmental regulations, with some of them facing the prospectof stringent punishment (Jia and Chen, 2019). As a result, CER engagements have becomea more important signal for the market than before as more CER engagements might becorrelated with a reduced risk of punishment, a kind of “risk resistance indicator.”
The other limitation is that there is no hypothesis that explains why CER’s impact on firm
value can be either negative or positive in any country. For example, some researchers defending the trade-off hypothesis argue that CER could increase the operating costs of a company
and, thereby, reduce firm value, while others support the stakeholder theory, which indicatesthat CER has overwhelming benefits for building corporate reputation and enhancing competitive advantages (Escrig-Olmedo et al., 2017; Dixon-Fowler et al., 2017). This study, how1

As an important part of corporate social responsibility (CSR), CER focuses on environmental responsibility and corporate sustainability. Thus, in this study, using CER instead of CSR can yield a more reliableconclusion.

2

ever, hypothesizes that such mix-ups can be attributed to local protectionism—unwarranted
protection from local government to lower environmental protection requirements and createcompetitive advantages for local enterprises. We believe that when local protectionism isstrong, the corporate competitiveness generated by greater CER engagements is trivial compared to lower environmental investment and that CER engagements actually damage firm
value, and vice versa. Note that the environmental reforms undertaken in China since 2016
have strengthened environmental supervision2 and weakened local protection. We therefore
explore the role of CER’s evolutionary impact on firm value while examining the role of local
protectionism.
Thus, the purpose of this study is to examine CER’s consequences over time—whether
the impact of CER engagement on firm value changes when institutional background is different. Equally important is ascertaining whether local protectionism can be considered an
important potential factor through checking the evolution of CER’s impact and the moderating effect of ownership type. In China, firm ownership type influences firm operation andmanagement. Compared to private firms, state-owned firms do not have a strong incentive
to pursue profit and are more likely to comply with national policies. Moreover, state-owned
businesses face higher public pressure. In this study, we divide all companies in our sample
into three categories based on ownership types: firms controlled by the central government,
firms controlled by local governments, and private firms. We investigate how the effects of
CER differ with ownership type under the centralization trend in China.
Our study contributes to prior research in two ways. First, it is the pioneer to investigate
CER effectiveness under varying institutional circumstances. We use two subsample periods: a “steady period” representing a relatively steady institutional background from 2006
to 2015 and a “shaky period” representing a relatively shaky institutional background withenvironmental reform from 2016 to 2019. Second, we integrate environmental reform into an
overall trend toward centralization in Chinese administrative reform and provide a novel perspective to demonstrate how local protectionism influences CER’s impact in the two periods
and for different ownership types. Previous studies have pointed out an intrinsic connection
between the centralization trend and environmental reform, but no study has explored therelationship between CER engagements and local protectionism (Zhang et al., 2018). Our
subsample regression results strongly indicate weakened local protectionism during 2016–19.
The remainder of this paper is organized as follows. In Section 2, we discuss the varying
2

It is part of the centralization reform, which signifies greater local power to the central government andstrengthening the direct supervision powers of the central government.

3

institutional setups under which the study is conducted. Section 3 summarizes the literatureand puts forward the hypotheses. Section 4 presents the sampling variables for empiricalresearch and estimation methods. Section 5 presents the empirical results and Section 6
concludes.

2

Institutional background2.1

Environmental governance before 2016

The Chinese environmental governance system was set up in 1973, while initially concerns
like deforestation and land overuse owing to poor agricultural practices were the main environmental problems. Although the central government was the dominant player in environmental governance on both legislation and enforcement until 1989, environmental protection
had never been a priority compared to economic and social issues (He et al., 2012). Most
environmental protection regulations and laws were drafted during 1989–2015, and local environmental protection bureaus were gradually established from the province level to thecounty level, thereby creating a comprehensive administration. Since 2012, the Chinese central government has assigned a high priority to environmental protection for local cadres(Wang, 2013).
Despite these institutional developments, rapid industrialization has resulted in greater
environmental degradation (Zhang and Wen, 2008; Sands et al., 2015). For example, theaverage PM2.5 (a kind of pollution particle smaller than 2.5 mm) concentration level in 170
Chinese cities in 2014 was around 61 ± 20µg/m3 , 4 − 8 times higher than the standard set by
the World Health Organization for “good health,” and only 9.5% of the cities monitored in
China met the National Ambient Air Quality Standards (Wang et al., 2017).
Widespread lax environmental protection, or so-called local protectionism in environmental management, is to blame (Lo, 2015; Van Rooij et al., 2017) for weak protection. On
the one hand, the environmental regulatory framework had matured in a decentralized waythat adopted a “divide and rule strategy” (Yu and Wang, 2013; Ran, 2013). That is, local
environmental protection bureaus were empowered with sufficient discretion in return for nomonetary support from the central government. This means that the Ministry of Environmental Protection (MEP) delegated its regulatory powers in exchange for a spending fee. On
the other hand, under a dual leadership structure, there are two higher authorities for local
environmental protection bureaus—a high-level environmental protection branch (the vertical4

authority) and a local cadre (the horizontal authority). As fiscal and personnel powers were
controlled mostly by local governments, local environmental protection bureaus responded
more to these governments’ desire for lax enforcement (Bai et al., 2004). This lax enforcement protected local enterprises and yielded the benefits of tax revenue, private benefits,
as well as sound economic performance for the local government (Ran, 2013; Kostka, 2014).
In line with the pollution haven hypothesis, lax environmental enforcement also attracted
investments from manufacturing enterprises (Kostka, 2016). This framework directly led toineffectual supervision of enforcement by the MEP. Correspondingly, the MEP only guided
provincial and sub-provincial regulatory administrations, which are often vague and aspirational (Yang, 2017). A former Minister of MEP, Zhou Shengxian, called his department oneof the “four major embarrassing departments in the world” in 2013, admitting the distressing
situation.

2.2

Environmental governance during 2016–2019

A crystal fact is that the main source of environmental degradation and resource consumption
are industries (Przychodzen et al., 2018). To prevent factories and enterprises from bypassing regulations and laws, the central government launched comprehensive reforms in 2016.
President Xi introduced the term “New Normal” to refer to the long-lasting changes frompursuing economic growth to a more sustainable and balanced development. The reforms
had a centralized pattern in three aspects: legislation, institutional framework reform, andenforcement (Li et al., 2019). For legislation, new and amended laws were enacted by thecentral committee, such as Environmental Protection Law (revised), Atmospheric Pollution
Prevention and Control Law, Marine Environment Protection Law, Water Pollution Prevention and Control Law, and Law on the Prevention and Control of Environment Pollution
Caused by Solid Wastes. Similar regulations for the atmosphere, water, and soil protection
were also issued directly by the MEP.
Importantly, the conventional “top-down” regulatory framework, where local cadres had
the motivation and discretion to dominate environmental enforcement, was bypassed in theprocess of institutional restructuring. The MEP now has more funds to support local environmental projects directly. Further, the Ministry of Ecology and Environment was established
to replace the MEP in granting more responsibilities on environmental enforcement and supervision. There is a tighter central control over local agents’ fiscal powers and the salientdeviation from the previously dominant performance-based governance system. That is, im-5

proved environmental enforcement has replaced robust GDP growth as one of the dominating
factors for a local official’s career promotion (Li et al., 2019). The central authority also encourages markets and NGOs to supervise the locally dominated environmental enforcement.
One landmark event during these reforms was an unprecedented Environmental Inspection led by the Central Government (EICG), initiated in 2016. The EICG focused on there-evaluation of local governments’ environmental enforcement and enterprises’ illegalities.
Under the direct supervision of central government officials, the EICG inspected all provincesin five batches over two years. Although the start date of inspections in the provinces varied
for each batch, the inspection period was always one month. The Central Discipline Committee of the Communist Party of China, which is the enforcer of anti-corruption policies, wasalso involved to maximize the effectiveness of EICG. From 2018, the second round of EICG
was conducted to achieve consistent supervision. According to official reports, 1,527 people
were taken into custody and 18,199 officials were publicly named for violating environmentallaws.
In summary, it is widely recognized that local protectionism before 2016 led to lax environmental governance. The comprehensive reforms undertaken from 2016 to 2019, viewed
as a part of a centralizing trend in administrative reform, have weakened this protectionism
and overturned the lax enforcement, at least in the short term.

3

Literature review and hypothesis development

3.1

Effects of CER on firm value in the steady period

CER is one of the key factors that align a firm’s environmental protection engagementswith firm value. However, there are long-standing debates on whether the benefits of CER
activities exceed their costs in the short term. Many investigators agree with CER’s overall
positive contribution in helping to control costs, establish firm reputation, and earn credits
from customers (Porter and Van der Linde, 1995; Tantalo and Priem, 2016). The majorityof these views are based on the stakeholder theory, which implies that CER contributes tofirms’ competitive advantage by helping them build a good reputation among stakeholders(Dixon-Fowler et al., 2017). Consequently, firm value can be enhanced by managing the core
stakeholder relationships (Hamman et al., 2010).
In contrast, the trade-off hypothesis argues that CER activities weaken corporate financial
performance despite apparent gains (Elsayed and Paton, 2005). This is because CER is viewed

6

as a disadvantage that increases corporate costs and, thereby, reduces profitability (Liu et al.,2010). As CER activities consume the firm’s core resources, they contribute directly to a
relative disadvantage vis-a-vis competitors with a smaller CER engagement; hence, firms do
not have the incentive to spend more on CER (Fujii et al., 2013; Trumpp and Guenther,2017). Islam and Deegan (2008) suggest that legislative pressure and accountability are thekey elements that boost CER activities rather than mere earnestness. Darnall and Edwards Jr(2006) further list out factors that explain greater costs when adopting an environmental
management system (one is CER implementation). The trade-off hypothesis has more appeal
in developing markets, which focus more on enterprise profitability and are less sensitive to
CER engagements.
Based on the previous analyses, we support the trade-off hypothesis and propose Hypothesis 1.
Hypothesis 1: During the steady period (2016–19), CER had a significant negative
impact on firm value, ceteris paribus.

3.2

Effects of CER on firm value in the shaky period

The mechanism of CER’s effectiveness can be derived from ample theoretical research. It
is widely agreed that changing CER’s determinants from an inconsistent policy improves
the stock market’s response (Pfeffer and Salancik, 2003; Cots, 2011). CER is conceived as
the accepted ideas of social relationships and norms that align enterprises’ willingness withexternal factors (Frynas and Yamahaki, 2016). However, there is no consensus regarding
how much time is needed for reform, and enterprises need much time and repeated attempts
before successfully managing a new relationship. Due to temporary dysfunction, the stock
market also adjusts its evaluation of CER’s effectiveness (Mitchell et al., 1997). Mellahi et al.
(2016) demonstrate that, in the formation of economic outcomes, nonmarket issues (political,
social, or environmental) take effect through mediating mechanisms regarding organizationalboundary spanning and external moderating mechanisms.
From the perspective of practical evidence, the other factor that explains the mechanismof CER’s effectiveness is the increased business risk faced by enterprises since 2016. As discussed above, environmental enforcement was lax in China earlier. Many enterprises chose
low-cost methods like bribery to evade environmental supervision. However, the environmental reforms since 2016 have overturned the situation using multiple methods, including
campaign-style inspection, stricter legislation, and institutional reform. For example, EICG

7

was carried out by the central government from 2016 to 2018; the revised Marine Environment Protection Law was issued in 2017; the revised Water Pollution Prevention and Control
Law was published in 2017; the Ministry of Environment was reorganized in 2018; an environmental lawsuit system was set up in 2018 and 2019; and a Special Environmental Protection
Fund was established in 2016. The central executive branch now takes more responsibilities
in law enforcement while the local government’s discretion is limited (Tian et al., 2019). One
striking result is that enterprises that fail to comply with new regulations within a specified
time face penalties and risk permanent closure as well (Zhang et al., 2018). Correspondingly,
more CER engagements can be viewed as an appropriate “risk resistance indicator” that
boosts the stock market’s confidence.
In summary, based on the theoretical foundation and practical evidence, the Chinese
environmental reform that purportedly threatens enterprise survival will cause CER’s effectiveness to increase. Thus, we propose Hypothesis 2.
Hypothesis 2: During the shaky period (2006–15), CER’s impact on firm value significantly increased and was positive, ceteris paribus.

3.3

Distinctive effects of CER on firm value by ownership type

It is widely recognized that firm ownership type plays an important role in CSR’s impact
on firm value in China (Chen et al., 2009). Ownership type can be categorized into threegroups: state-owned enterprises controlled by the central government (SOECG), state-owned
enterprises controlled by the local government (SOELG), and private enterprises (PE) (Wanget al., 2008). State-owned enterprises (SOEs) including SOECGs and SOELGs are believed tobe managed differently than PEs (Chen et al., 2009). For example, one SOE’s managers are
officials deputed by the government and therefore, their career prospects are closely related
to the extent to which their management executes instructions from their superiors.
One result from China’s decentralized administrative structure 3 is notable—heterogeneous
enforcement across localities and enterprises (Kostka and Nahm, 2017). Heterogeneous enforcement refers to the fact that despite a uniform central management system, the ill-suitedadministrative structure eventually fails to enforce these laws and regulations coherently.
China has a complex system of formal and informal divisions of authority between the central government and various levels of local and regional governments (Lo and Fryxell, 2005).
Heberer and Schubert (2017) demonstrate that local cadres still establish low-demand local
3

The decentralized structure in the environmental executive branch is where the central government relinquishes most of its fiscal, administrative, and personnel powers to sub–national governments.

8

regulations, regardless of strict national legislation, and take advantage of their discretionary
powers to evade environmental protection responsibilities and defend local enterprises. Lax
enforcement is particularly salient in the case of SOEs because of strong political connections.
That is, SOELGs receive local protection because they are directly responsible for and aremost politically connected with local authorities, and SOECGs receive more protection because their managers often have higher administrative rankings than the local head (Wang,2016). Therefore, engaging in CER activities will not result in external credits for SOEs as
the stock market responds indifferently as well. Besides, according to the trade-off theory,the overweight cost from these engagements will result in enterprises spending the bare minimum on CER. Hence, CER effectiveness was negative particularly for SOECGs and SOELGs
during the steady period (2016–19).
From 2016, all enterprises could expect an increasingly positive CER effectiveness in the
shaky period with weakened local protectionism as CER can be viewed as a “risk resistanceindicator.” However, CER effectiveness in SOEs could be more because of “additional politicalscore” (Li and Zhang, 2010; Van Rooij et al., 2017). Becoming an advocate of central policies
is believed to be an important signal of good risk resistance capability for SOEs and politicalachievement for their managers, as the Chinese government is used to promoting new policies
by setting examples and commending them vigorously in the future. Private enterprises, on
the other hand, rarely receive equivalent credit because of fewer political connections and are
not fully trusted (Kung and Ma, 2018; Walder, 2002).
In brief, the cost of CER engagements shall surpass their benefits in the steady period
particularly for SOEs, while they gain more from the combination of weakened local protectionism and unique benefits from political advocates. Therefore, we suggest Hypothesis
3.
Hypothesis 3: For SOELGs & SOECGs, there is an increased CER impact on firm
value than for PEs. That is, CER was more valuable for SOELGs & SOECGs during the
shaky period.

9

4

Research design

4.1

Sample periods and data collection

The initial sample contains all A-listed firms 4 from 2006 to 2019.5 China is suitable for ourinvestigation of CER’s evolutionary effectiveness for three reasons. First, China is paying
more attention to environmental information disclosure in recent years, so we can obtainsuitable data related to corporate environmental responsibility (Li et al., 2020).6 Second,
China witnessed steady economic growth in the study period and provides a stable social environment beyond environmental management reform.7 Third, China has undergone comprehensive reforms on environmental governance from 2016 to 2019, which offers us the varying
institutional circumstances needed for our study purpose. Finally, we split the study period
into two distinct periods to capture the change in the institutional background.8 The period
from 2006 to 2015 is considered a relatively stable period regarding environmental management policy and enforcement, before the country started extensive environmental reforms
from 2016. Therefore, a partition into two periods allows us to investigate CER effectivenessunder different environments.
Our data set includes 1004 listed firms and 6232 observations. For the validity of theresearch, we exclude all special treatment (*ST/ST) firms9 and firms that do not have ourrequired data. Moreover, to avoid the influence of extreme values on the results, all continuous
variables are winsorized at the 1st and 99th percentiles. The data are collected from the China
Stock Market & Accounting Research Database (CSMAR), Chinese Research Data Services
Platform, and Wind Database.

4.2
4.2.1

Measurement of variables
Corporate environmental responsibility

We use content analysis to measure CER by analyzing the environmental information disclosed in CSR reports based on the CSMAR and Chinese Research Data Services Platform.
4

A-shares denote the publicly listed firms traded on Shenzhen and Shanghai Stock Exchanges. These stocks
are traded in Renminbi (RMB), China’s legal tender.
5
We choose this time period since it allows us the maximum time interval for calculating CER engagement.
6
The “Guidelines for Social Responsibility of Listed Companies” published in China in 2006 stipulates that
Chinese listed firms should routinely assess their CSR performance in accordance with the guidelines.
7
See Report on the Work of the Government 2019 (http://www.gov.cn/zhuanti/2019qglh/2019lhzfgzbg/index.htm).
8
See the official schedule for comprehensive environmental reform, Integrated Reform Plan for Promoting Ecological Progress (http://www.caeisp.org.cn/zh-hans/integrated-reform-plan-promoting-ecologicalprogress).
9
Those firms are at risk of being delisted.

10Based on Li et al. (2020), we evaluate CER on five dimensions: legal consciousness, social
evaluation, eco-friendly production, low-carbon technology, and green management. Eachdimension is measured by several indexes. The specific evaluation system is shown in Table
1. To keep the direction of all indicators consistent, firms that have not been penalized forenvironmental irregularities take the value of 1; else they take a value of 0. Firms that are
not discharging pollutants take a value of 1; else they take a value of 0. For the remaining
indicators, if the answer is yes, we assign the value of 1, else 0. These indicators are allreflections of the sampled firms’ objective facts. We weighted all the items equally to avoid
subjectivity and get a reasonable calculation of CER for all selected firms. The score of eachdimension of CER is the sum of the values of the indicators under each dimension, and thetotal CER score is the sum of the five dimensions.
[Table 1]
4.2.2

Firm value

Firm value usually reflects the company’s ability to provide satisfactory returns to all stakeholders (shareholders, creditors, managers, employees, etc.) under value-induced management and the rule of law. In this study, we use Tobin’s Q to measure firm value. Tobin’s
Q is the ratio of firm market value to its asset replacement cost, and it is widely used asa measurement of firm value in the accounting, economics, and finance literature (Mangena
et al., 2012; Gompers et al., 2003). It is a good indicator for evaluating firm value since it
can not only reflect the firm’s past value but also take into account its future performance
expectations.
4.2.3

Ownership structure of China’s listed companies

According to the listed company equity documents from CSMAR, all Chinese listed firms
can be divided into four types based on ownership structure: state-owned enterprises, private
enterprises, foreign companies, and others. Further, state-owned enterprises are divided into
three categories according to different hierarchies: city, province, and country. According to
the distinct performance mechanisms of different ownership structure companies in different
institutional backgrounds and consistent with the literature (Chen et al., 2009), we divide oursample enterprises into three categories: SOECG, SOELG, and PE. We use dummy variables
SOECG, SOELG, and PE to indicate the three kinds of enterprises.

114.2.4Control variables

In addition to CER, many determinants that can potentially affect firm value are added
into the estimation model as control variables. Referring to previous studies, we select thefollowing control variables (Fosu et al., 2016; Kuzey and Uyar, 2017). Firm size (SIZE) measured as the natural logarithm of total assets is considered an important variable that affects
performance through economies of scale or scope (Stock et al., 2002). Other factors such as
total leverage (LEVE; measured as operating leverage multiplied by financial leverage), debt
ratio (DEBT; measured as the ratio of total debt divided by total assets), liquidity (CR;measured as current assets divided by current liabilities), fixed assets ratio (FA; measured
as fixed assets divided by total assets), and firm age (AGE; measured as firm’s listing age)are also included (Fosu et al., 2016; Kuzey and Uyar, 2017). The variables’ description andmeasurements are shown in Table 2.
[Table 2]
4.2.5

Model construction

This section describes the econometric model used to examine the relationship between CERand firm value (Tobin’s Q) in different periods. To test our hypotheses, we construct thefollowing baseline regression model for all firms. We use the dummy variable Period todistinguish between the steady and shaky periods, which is referred to by Mangena et al.
(2012) and Shen et al. (2019).
Baseline model:
Tobin’sQi,t =β0 + β1 CERi,t + β2 CERi,t × Periodi,t + β3 Periodi,t(1)+ β4 Controlsi,t + Year + Industry + Province + εi,twhere i indexes the firm, t indexes the year, and Period captures the different periods
when the year of the observation is between 2016 to 2019. Period takes the value of 1,
else 0. Control is a set of control variables expected to influence firm value, like firm size,
debt ratio, total leverage, liquidity, fixed assets ratio, and firm listing age. Year captures
the time-fixed effects. Industry captures the industry-fixed effects. Province captures theprovince-fixed effects. εi,t is the error term. To determine if the impact of CER on firm value
increased during the shaky period, our model contains the interaction term CER*Period. To
see how ownership type plays a moderating effect, we perform the previous regression on theownership type subsamples.
12

5

Empirical results

5.1

Data description

Table 3 shows the descriptive statistics of all variables for the full period (2013–2018), thesteady period (Period 0, 2013–2015), and the transitional period (Period 1, 2016–2018). The
CER of the whole period ranges from 1 to 13 points, with a mean score of 6.045. No firm has a
CER level of zero, which signifies that all the A-listed firms in our study period provide CER
information in their annual reports according to our measurement. The scores also show that
the CER level of the sample firms has a wide range, with some firms obtaining a full score of
13 points. The mean of the CER level in stage 2 (6.151) is slightly higher than that of stage
1 (5.956), which indicates a slightly increasing willingness in CER engagements during the
shaky period. The mean firm value (Tobin’s Q) in stage 2 (1.923) is slightly lower than instage 1 (2.216), because the stock market value decreased slightly after 2015. Regarding thecontrol variables, the mean value of the natural logarithm of firm size is 23.128, the averagevalue of the fixed assets ratio is 23.2%, the mean value of the current ratio is 1.98, the averagedebt-to-asset ratio is 47.8%, the mean total leverage is 2.447, and the average listing age is
12.135 years. All these values are consistent with the literature (Kuzey and Uyar, 2017; Liet al., 2020).
[Table 3]
Table 4 is the correlation matrix, which exhibits the correlation between all the variables
and suggests potential collinearity. After analyzing the correlation matrix and the varianceinflation factor (VIF), we confirm that multicollinearity is not a concern for all the variables.
We also observe that CER has a significant negative impact on firm value.
[Table 4]

5.2

Baseline findings

We start our analysis by testing the impact of CER on firm value in the two periods. Table 5
reports the baseline results for the constructed models of the whole sample in the two periods.
As shown in column (4), the results are derived from two methods (ordinary least squares(OLS) and fixed-effects (FE)) and consider the existence of covariates’ effect. Regardless ofthe method adopted (columns (1) and (2) vs columns (3) and (4)) or whether covariates areincluded (columns (1) and (3) vs columns (2) and (4)), the results are similar. Specifically,
the CER coefficient is -0.032 and -0.038, respectively, and significant at the 1% level using13

both methods given the involvement of covariates, indicating that every one-point increase in
the CER score decreases the Tobin’s Q value by around 0.03, or around 1.5% in the steadyperiod, all else being equal. This result shows that CER has a significant negative impact on
Tobin’s Q in 2006–2015, which is consistent with some previous studies (Zeng et al., 2010;
Shen et al., 2019) and strongly supports Hypothesis 1. On the other hand, the CER*Period
coefficient is 0.065 and 0.062, respectively, and significant at the 1% level using both methods
given the involvement of covariates, indicating that every one-point increase in the CER scoreincreases around 0.03, or around 1.5% of the Tobin’s Q value in the shaky period, all else being
equal. This result shows that CER has an inverse positive impact on Tobin’s Q during 2016–2019 and confirms the presence of CER’s effectiveness, which strongly supports Hypothesis
2. With respect to the effect of covariates, we find that firm size (SIZE) is negatively related
to Tobin’s Q, which implies that bigger firms are relatively inefficient. Furthermore, the fixed
assets ratio, total leverage, and debt ratio are significantly negatively correlated with Tobin’s
Q. We also find that the current ratio is significantly positively correlated with firm value.
These findings are consistent with those of previous studies (Bozec et al., 2010; Li et al.,2020).
[Table 5]
We then test the moderating effect of ownership type between CER and firm value. Table
6 reports the results from the subsample regression of the two periods. Columns (1), (2) and(3) show the results from the OLS method while columns (4), (5) and (6) indicate those fromthe FE model. First, focusing on the CER coefficient, we find that CER had a more negative
impact on firm value for SOECGs and SOELGs than PEs in the steady period in bothmodels. This is consistent with our hypothesis that SOECGs and SOELGs receive stronger
local protection because of their closer connections to the local governments. When local
protection is strong, corporate competitiveness generated by greater CER engagements would
be insignificant compared to the lower environmental investment; thus, CER engagements
are a disadvantage for firm value since the corresponding added cost may exceed the valueof any added benefit and vice versa. PEs benefited less from local protectionism than theother types during the steady period and therefore gained more “compensation” from CER
engagements. Second, focusing on the interaction term CER*Period, both methods strongly
support the fact that CER’s positive impact increased the most for SOECGs and the least
for PEs during the shaky period in both models. For example, when comparing model(1) with model (3), CER’s impact increases over 30% more for SOECGs than for PEs. This14

finding further supports our hypothesis that following the environmental reforms and reduced
local protection during the shaky period, SOECGs, which suffered the most from reduced
local protection, gained the most competitive advantage from CER engagements. These
competitive advantages from CER promote firm value in two ways: first, as a “risk resistanceindicator” to credit the enterprise’s capacity for surviving and running smoothly during the
shaky period, and second, as an “additional political score” to credit the enterprise’s capacity
for advocating new policies. These findings, therefore, strongly support Hypothesis 3 andindicate the involvement of local protectionism.
[Table 6]

5.3

Endogeneity concerns

To eliminate potential endogeneity caused by simultaneity and reverse causality, we adopt
lagged explanatory variables instead of contemporaneous variables; the results are reported
in Table 7. In columns (1) and (2), we use OLS estimation with industry-fixed effects,
province-fixed effects, and year-fixed effects. In columns (3) and (4), we use the FE modelfor estimation with firm-fixed effects and year-fixed effects. We include control variables
in columns (2) and (4). We can see from the table that for L.CER (lagged CER) and
L.CER*Period (lagged CER*Period), the coefficients are similar to that of Table 5. The
same implications hold: CER had a significant negative impact on Tobin’s Q during 2006–
2015 (which strongly supports Hypothesis 1) and had significant positive incremental impact
on Tobin’s Q during 2016–2019 (which strongly supports Hypothesis 2).
[Table 7]
We also employ the instrumental variables method to alleviate the endogenous concernsof omitting correlated variables, using the average CER of all other firms in the same industry
as instrumental variables. The results are displayed in Table 8. Columns (1) and (2) exclude
control variables while columns (3) and (4) include control variables. Columns (1) and (3) are
the regression results of the first stage, and columns (2) and (4) show the regression resultsof the second stage. From Table 8, we can see that our IV CER is highly related to theoriginal CER in the two regressions, 0.980 and 0.786, respectively. Thus, CER’s impact onfirm value during the steady period and its incremental impact during the shaky period areconsistent with our baseline model. That is, the coefficients of CER are significantly negative(-0.587 and -0.300), and the coefficients of the CER*Period are significantly positive (0.204
and 0.158) in the regression results in the second stage.

15

[Table 8]

5.4

Robustness check

The robustness of the results is checked through three further analyses, which support ourtheoretical framework and propositions. First, we run separate OLS and FE model regressions
for the steady period (2006—2015) and the shaky period (2016—2019). The subsample
results are shown in Table 9, where columns (1) and (2) indicate the OLS regression results
and columns (3) and (4) indicate the FE regression results. Using simple comparison, we
find that the OLS results are consistent with the previous baseline findings; the impact of
CER on firm value is significantly negative during the steady period, while it is significantly
positive during the shaky period, and is significant at the 5% level. Although the FE model
regression results are not significant, they show a predicted sign. Therefore, the regression
results of the subsample support our findings.
[Table 9]
Second, we observe that the EICG was conducted during the environmental reforms. As
Table 10 implies, EICG was conducted in batches, and there were natural control and treatedgroups in each batch. Therefore, we can use the difference-in-difference (DID) method to
examine the average treatment effect of EICG and consider receiving treatment as a substituteof experiencing a shaky period for enterprises. Inspect is equal to 1 if firm i is under or has
finished inspection in year t, and 0 otherwise. CER*Inspect shows the incremental CER
impact after the EICG. The results from the DID method are compared with the baseline
results to assess robustness. From the results shown in Table 11, the coefficients of CER
and CER*Inspect are strongly consistent with the baseline findings in Table 5 regardless ofwhether there is an involvement of covariates. The four coefficients of CER in the first row
show that the impact of CER on firm value is significantly negative in the steady period. The
four coefficients of CER*Inspect in the second row show that the incremental CER impact onfirm value is significantly positive in the steady period. Thus, this test supports the validityof our findings.
[Tables 10 & 11]
Finally, we conduct a placebo test to exclude the effect of time-changing factors and totest whether the influence from the shaky period does exist. The argument is that, given
the assumption that the environmental reforms began in another year rather than in 2016,
if there exists any significant non-zero coefficient of CER*Period (indicating the incremental

16

impact of CER on firm value) before 2016 or any insignificant close-to-zero coefficient of
CER*Period after 2016, then our preceding time division will lose its statistical validity.
We use Period14 to represent the assumed beginning of the shaky period from the year
2014; thus, CER*Period14 captures the incremental impact of CER on firm value in theassumed shaky period. The other interaction terms such as CER*Period15, CER*Period17,
and CER*Period18 have similar meanings. The placebo results are shown in Table 12. Allfour columns’ results clear our concerns, as coefficients of CER*Period14 and CER*Period15
are both close-to-zero and coefficients of CER*Period, CER*Period17, and CER*Period18
are all significantly non-zero. Furthermore, the coefficients of CER*Period across the threeownership type groups after 2016 also support our findings from Table 6. That is, theincremental CER impact is highest for SOECGs and least for PEs. One interesting result
is that if we split the period later (2017 or 2018), the difference in CER effectiveness ismore salient as SOECGs benefit increasingly more from CER engagements than others. Thispattern might reflect the theoretical proposition that since the shaky period is composed of
an integration of many environmental reforms rather than just a sole campaign-style EICG in
2016, we should expect a shift from the shaky period to another steady period with normalized
stringent supervision in the future.
[Table 12]6Conclusion

The government and the public have been paying increasing attention to environmental degradation in recent years and demanding greater environmental accountability and disclosure
from enterprises. CER, which measures the willingness and investment of enterprises forenvironmental protection, thus assumes importance. It is explicitly demonstrated that CER
has an impact on firm value, but whether this impact is positive or negative is still debatable.
As many studies in China yield mixed results, we believe strong local protectionism could
be the potiential reason. Notice that the environmental reforms undertaken from 2016 havestrengthened environmental supervision and weakened local protection, CER’s impact in twoseperate time periods (before and after 2016) is considered in our study to test evolution of
CER’s impact. The moderating role of ownership is also studied to better reveal the existenceof local protectionism.
This study makes two main contributions. First, to the best of our knowledge, it is
the first to investigate CER effectiveness under varying institutional circumstances—that is,17whether there has been a robust change in the impact of CER on firm value before and after
the environmental reforms in 2016. The results provide strong evidence on the involvementof local protectionism in the relationship between CER and firm value. Second, according to
the findings of previous studies, firm ownership type is closely connected with the strengthof local protection, which is ample reason for us to dig deeper into local protectionism’s role.
Our results demonstrate the role of weakened local protectionism after 2016 and help us
to view the environmental reforms from a new perspective—that is, as a part of the larger
Chinese administrative reforms to combat decentralization.
We investigate the impact of CER on firm value using data from Chinese A-listed firms
from 2006–2019. We first examine whether there is a significant difference in CER’s effectiveness on firm value between the steady period and shaky period. Then, we investigate themoderating role of firm ownership types on that relationship in the two periods to check local
protectionism’s role. Our results show that, first, CER negatively affects firm value in thesteady period, but positively affects it in the shaky period. Second, we find that enterprisesthat previously received more local protection show larger increments in CER effectiveness.
Our findings are very relevant to firm management, investors, and policymakers. When
deciding on CER investment, managers should comprehensively consider the characteristicsof the company and the institutional background to optimize their results. When anticipating strict environmental enforcement and weak local protection in a few years, they should
consider greater CER engagements and information disclosure. For investors, keeping aclose eye on policies and change in public awareness is necessary when reasonably estimating firm value. Our results show that, throughout the environmental reform period, greater
CER engagements benefited SOECGs. Therefore, investors should also be more attentive to
CER. Policymakers should try to ensure strict and effective implementation of environmental policies and laws. Our results show that, to make environmental policies truly effective,
policymakers need to combat local protectionism. Moreover, when environmental protection
policies are strictly implemented, CER’s positive effect is more prominent. This will undoubtedly lead companies to more environmental protection investments and promote sustainable
development.

18

References
Bai, C.-E., Du, Y., Tao, Z. and Tong, S. Y. (2004), ‘Local protectionism and regional specialization: evidence from China’s industries’, Journal of International Economics 63(2), 397–
417.
Bozec, R., Dia, M. and Bozec, Y. (2010), ‘Governance–performance relationship:are-examination using technical efficiency measures’, British Journal of Management21(3), 684–700.
Chen, G., Firth, M. and Xu, L. (2009), ‘Does the type of ownership control matter? Evidence
from China’s listed companies’, Journal of Banking & Finance 33(1), 171–181.
Cots, E. G. (2011), ‘Stakeholder social capital: a new approach to stakeholder theory’, Business Ethics: A European Review 20(4), 328–341.
Darnall, N. and Edwards Jr, D. (2006), ‘Predicting the cost of environmental management
system adoption: the role of capabilities, resources and ownership structure’, Strategic
Management Journal 27(4), 301–320.
Dixon-Fowler, H. R., Ellstrand, A. E. and Johnson, J. L. (2017), ‘The role of board environmental committees in corporate environmental performance’, Journal of Business Ethics
140(3), 423–438.
Du, X., Jian, W., Zeng, Q. and Du, Y. (2014), ‘Corporate environmental responsibility inpolluting industries: Does religion matter?’, Journal of Business Ethics 124(3), 485–507.
Elsayed, K. and Paton, D. (2005), ‘The impact of environmental performance on firm performance: static and dynamic panel data evidence’, Structural Change and Economic Dynamics 16(3), 395–412.
Escrig-Olmedo, E., Muñoz-Torres, M. J., Fernández-Izquierdo, M. Á. and Rivera-Lirio, J. M.
(2017), ‘Measuring corporate environmental performance: A methodology for sustainable
development’, Business Strategy and the Environment 26(2), 142–162.
Fosu, S., Danso, A., Ahmad, W. and Coffie, W. (2016), ‘Information asymmetry, leverageand firm value: Do crisis and growth matter?’, International Review of Financial Analysis
46, 140–150.

19

Frynas, J. G. and Yamahaki, C. (2016), ‘Corporate social responsibility: Review and roadmapof theoretical perspectives’, Business Ethics: A European Review 25(3), 258–285.
Fujii, H., Iwata, K., Kaneko, S. and Managi, S. (2013), ‘Corporate environmental and economic performance of Japanese manufacturing firms: Empirical study for sustainable development’, Business Strategy and the Environment 22(3), 187–201.
Gompers, P., Ishii, J. and Metrick, A. (2003), ‘Corporate governance and equity prices’, The
Quarterly Journal of Economics 118(1), 107–156.
Hamman, J. R., Loewenstein, G. and Weber, R. A. (2010), ‘Self-interest through delegation:
An additional rationale for the principal-agent relationship’, American Economic Review
100(4), 1826–46.
He, G., Lu, Y., Mol, A. P. and Beckers, T. (2012), ‘Changes and challenges: China’s environmental management in transition’, Environmental Development 3, 25–38.
He, M. and Chen, J. (2009), ‘Sustainable development and corporate environmental responsibility: Evidence from Chinese corporations’, Journal of Agricultural and Environmental
Ethics 22(4), 323–339.
Heberer, T. and Schubert, G. (2017), County and township cadres as a strategic group. A new
approach to political agency in China’s local state, in ‘Critical Readings on the Communist
Party of China (4 Vols. Set)’, Brill, pp. 1141–1177.
Holtbrügge, D. and Dögl, C. (2012), ‘How international is corporate environmental responsibility? A literature review’, Journal of International Management 18(2), 180–195.
Islam, M. A. and Deegan, C. (2008), ‘Motivations for an organisation within a developing
country to report social responsibility information’, Accounting, Auditing & Accountability
Journal .
Jia, K. and Chen, S. (2019), ‘Could campaign-style enforcement improve environmental performance? Evidence from China’s central environmental protection inspection’, Journal ofEnvironmental Management 245, 282–290.
Jo, H. and Harjoto, M. A. (2012), ‘The causal effect of corporate governance on corporatesocial responsibility’, Journal of Business Ethics 106(1), 53–72.

20

Kostka, G. (2014), Barriers to the implementation of environmental policies at the local levelin China, The World Bank.
Kostka, G. (2016), ‘Command without control: The case of China’s environmental target
system’, Regulation & Governance 10(1), 58–74.
Kostka, G. and Nahm, J. (2017), ‘Central–local relations: Recentralization and environmental
governance in China’, The China Quarterly 231, 567–582.
Kung, J. K.-s. and Ma, C. (2018), ‘Friends with benefits: How political connections help tosustain private enterprise growth in China’, Economica 85(337), 41–74.
Kuzey, C. and Uyar, A. (2017), ‘Determinants of sustainability reporting and its impact onfirm value: Evidence from the emerging market of Turkey’, Journal of Cleaner Production
143, 27–39.
Li, W. and Zhang, R. (2010), ‘Corporate social responsibility, ownership structure, and political interference: Evidence from China’, Journal of Business Ethics 96(4), 631–645.
Li, X., Yang, X., Wei, Q. and Zhang, B. (2019), ‘Authoritarian environmentalism and environmental policy implementation in China’, Resources, Conservation and Recycling 145, 86–
93.
Li, Z., Liao, G. and Albitar, K. (2020), ‘Does corporate environmental responsibility engagement affect firm value? The mediating role of corporate innovation’, Business Strategy andthe Environment 29(3), 1045–1055.
Liu, X., Liu, B., Shishime, T., Yu, Q., Bi, J. and Fujitsuka, T. (2010), ‘An empirical study
on the driving mechanism of proactive corporate environmental management in China’,
Journal of Environmental Management 91(8), 1707–1717.
Lo, C. W.-H. and Fryxell, G. E. (2005), ‘Governmental and societal support for environmental
enforcement in China: an empirical study in Guangzhou’, Journal of Development Studies
41(4), 558–588.
Lo, K. (2015), ‘How authoritarian is the environmental governance of China?’, Environmental
Science & Policy 54, 152–159.
Mangena, M., Tauringana, V. and Chamisa, E. (2012), ‘Corporate boards, ownership structure and firm performance in an environment of severe political and economic crisis’, British
Journal of Management 23, S23–S41.
21

Mellahi, K., Frynas, J. G., Sun, P. and Siegel, D. (2016), ‘A review of the nonmarket strategy
literature: Toward a multi-theoretical integration’, Journal of Management 42(1), 143–173.
Mitchell, R. K., Agle, B. R. and Wood, D. J. (1997), ‘Toward a theory of stakeholder identification and salience: Defining the principle of who and what really counts’, Academy ofManagement Review 22(4), 853–886.
Pfeffer, J. and Salancik, G. R. (2003), The external control of organizations: A resource
dependence perspective, Stanford University Press.
Porter, M. E. and Kramer, M. R. (2006), ‘The link between competitive advantage andcorporate social responsibility’, Harvard Business Review 84(12), 78–92.
Porter, M. E. and Van der Linde, C. (1995), ‘Toward a new conception of the environmentcompetitiveness relationship’, Journal of Economic Perspectives 9(4), 97–118.
Przychodzen, W., Gómez-Bezares, F. and Przychodzen, J. (2018), ‘Green information technologies practices and financial performance–the empirical evidence from German publicly
traded companies’, Journal of Cleaner Production 201, 570–579.
Ran, R. (2013), ‘Perverse incentive structure and policy implementation gap in China’s local
environmental politics’, Journal of Environmental Policy & Planning 15(1), 17–39.
Sands, J., Lee, K.-H., Qian, W., Burritt, R. and Chen, J. (2015), ‘The potential for environmental management accounting development in China’, Journal of Accounting & Organizational Change .
Shen, F., Ma, Y., Wang, R., Pan, N. and Meng, Z. (2019), ‘Does environmental performance
affect financial performance? Evidence from Chinese listed companies in heavily polluting
industries’, Quality & Quantity 53(4), 1941–1958.
Stock, G. N., Greis, N. P. and Fischer, W. A. (2002), ‘Firm size and dynamic technologicalinnovation’, Technovation 22(9), 537–549.
Tantalo, C. and Priem, R. L. (2016), ‘Value creation through stakeholder synergy’, Strategic
Management Journal 37(2), 314–329.
Tian, M., Xu, G. and Zhang, L. (2019), ‘Does environmental inspection led by central government undermine Chinese heavy-polluting firms’ stock value? The buffer role of politicalconnection’, Journal of Cleaner Production 236, 117695.
22

Trumpp, C. and Guenther, T. (2017), ‘Too little or too much? Exploring U-shaped relationships between corporate environmental performance and corporate financial performance’,
Business Strategy and the Environment 26(1), 49–68.
Van Rooij, B., Zhu, Q., Na, L. and Qiliang, W. (2017), ‘Centralizing trends and pollution
law enforcement in China’, The China Quarterly 231, 583–606.
Walder, A. G. (2002), ‘Markets and income inequality in rural China: Political advantage inan expanding economy’, American Sociological Review pp. 231–253.
Wang, A. L. (2013), ‘The search for sustainable legitimacy: environmental law and bureaucracy in China’, Harv. Envtl. L. Rev. 37, 365.
Wang, Q., Wong, T.-J. and Xia, L. (2008), ‘State ownership, the institutional environment, and auditor choice: Evidence from China’, Journal of Accounting and Economics
46(1), 112–134.
Wang, S., Zhou, C., Wang, Z., Feng, K. and Hubacek, K. (2017), ‘The characteristics anddrivers of fine particulate matter (PM2.5) distribution in China’, Journal of Cleaner Production 142, 1800–1809.
Wang, Y. (2016), ‘Beyond local protectionism: China’s state–business relations in the lasttwo decades’, The China Quarterly 226, 319–341.
Wu, W., Liang, Z. and Zhang, Q. (2020), ‘Effects of corporate environmental responsibility
strength and concern on innovation performance: The moderating role of firm visibility’,
Corporate Social Responsibility and Environmental Management 27(3), 1487–1497.
Yang, D. L. (2017), ‘China’s Illiberal Regulatory State in Comparative Perspective’, Chinese
Political Science Review 2(1), 114–133.
Yu, X. and Wang, H. (2013), ‘How should the center lead China’s reforestation efforts?—Policy making games between central and local governments’, Resources, Conservation and Recycling 80, 64–84.
Zeng, S., Xu, X., Dong, Z. and Tam, V. W. (2010), ‘Towards corporate environmental information disclosure: an empirical study in China’, Journal of Cleaner Production
18(12), 1142–1148.

23

Zhang, B., Chen, X. and Guo, H. (2018), ‘Does central supervision enhance local environmental enforcement? Quasi-experimental evidence from China’, Journal of Public Economics
164, 70–90.
Zhang, K.-m. and Wen, Z.-g. (2008), ‘Review and challenges of policies of environmental
protection and sustainable development in China’, Journal of Environmental Management
88(4), 1249–1261.

24

Table 1: CER evaluation system
Dimensions
Legal consciousness
Social evaluation
Eco-friendly production
Low carbon technology
Green management

Indicators
1. Whether to follow the Global Reporting Initiative Sustainable Reporting Guidelines;
2. Whether to disclose the environment and sustainable development information;
3. Whether subjected to environmental penalties.
1. Whether received an environmental commendation;
2. Whether to have environmental advantages.
1. Whether to adopt a circular economy;
2. Whether to carry out green production;
3. Whether to discharge pollution.
1. Whether to save energy;
2. Whether to develop or apply environmentally friendly technologies.
1. Whether to have a third-party verification;
2. Whether to have an ISO 14001 certification;
3. Whether to adopt a green office.

Note: This CER evaluation system is directly referred to Li et al. (2020).

Table 2: Variable description
Variables
Tobin’s Q
CER
PeriodInspect
SIZE
LEVE
DEBT
CR
FA
AGE
SOECG
SOELG
PE
Province fixed effectIndustry fixed effectYear fixed effectFirm fixed effectDescription
Market value divided by total assets
Measured by CER evaluation system
Measured as 1 if in shaky period, otherwise 0
Measured as 1 if firm i in year t is under inspection, otherwise 0
The natural logarithm of total assets
Operating leverage multiplied by financial leverage
The total debt divided by total assets
The current assets divided by current liabilities
Fixed assets divided by total assets
The firm listing age
Measured as 1 if firm i is state-owned enterprises affiliated by the central government, otherwise 0
Measured as 1 if firm i is state-owned enterprises affiliated by the local government, otherwise 0
Measured as 1 if firm i is private enterprises, otherwise 0
Province dummies to control for common features at province level
Industry dummies to control for common features at Industrial level
Time dummies to control for common macroeconomic effectControl for common features at firm level25

Table 3: Descriptive statistics
SampleWhole

Period=0

Period=1

Variable
TobinsQ
CER
FA
CR
DEBT
LEVE
SIZE
AGE
TobinsQ
CER
FA
CR
DEBT
LEVE
SIZE
AGE
TobinsQ
CER
FA
CR
DEBT
LEVE
SIZE
AGE

N
6232
6232
6232
6232
6232
6232
6232
6232
3386
3386
3386
3386
3386
3386
3386
3386
2846
2846
2846
2846
2846
2846
2846
2846

Mean
2.082
6.045
0.232
1.980
0.478
2.447
23.12812.135
2.216
5.956
0.241
2.045
0.481
2.553
22.89910.597
1.923
6.151
0.221
1.902
0.474
2.321
23.39913.964

SD
1.407
1.898
0.184
1.887
0.197
2.935
1.482
6.696
1.476
1.774
0.185
2.078
0.202
3.250
1.464
5.922
1.303
2.032
0.181
1.626
0.190
2.503
1.457
7.093

Min
0.818
1.000
0.002
0.252
0.064
0.966
18.650
0.000
0.818
2.000
0.002
0.252
0.064
0.966
19.276
0.000
0.818
1.000
0.002
0.252
0.064
0.966
18.650
0.000

P25
1.163
5.000
0.083
1.049
0.329
1.229
22.050
7.000
1.241
5.000
0.093
1.044
0.330
1.208
21.872
5.000
1.079
5.000
0.076
1.056
0.328
1.245
22.342
8.000

Median
1.591
6.000
0.185
1.451
0.489
1.530
22.98812.000
1.703
6.000
0.194
1.437
0.493
1.509
22.77511.000
1.475
6.000
0.176
1.466
0.483
1.554
23.30115.000

P75
2.413
7.000
0.341
2.136
0.630
2.246
24.04117.000
2.587
7.000
0.356
2.142
0.640
2.251
23.77015.000
2.237
8.000
0.329
2.121
0.618
2.237
24.28820.000Max
8.322
13.0000.753
12.9840.860
21.34628.50928.000
8.322
12.0000.753
12.9840.860
21.34628.50925.000
8.322
13.0000.753
12.9840.860
21.34628.50928.000Note: Our sample contains all listed firms in the Chinese A-share market after dropping special treatment(ST) firms and observations with missing values. The whole period of the sample is 2006-2019. “Period=0” refers to subsamples in a steady period (2006-2015), “Period =1” refers to subsamples in a shaky
period (2016-2019). The total numbers of firms and observations are 1004 and 6232, respectively.

Table 4: Correlation matrix
TobinsQ
CER
Period
FA
CR
DEBT
LEVE
SIZE
AGE

TobinsQ
1-0.187***-0.104***-0.172***0.390***-0.455***-0.168***-0.473***-0.271***

CER

Period

FA

CR

DEBT

LEVE

SIZE

AGE

1
0.051***
0.097***-0.167***0.171***
0.024*
0.373***
0.070***

1-0.053***-0.038***-0.019-0.039***0.168***
0.250***

1-0.267***-0.0030.309***
0.074***-0.029**1-0.630***-0.197***-0.394***-0.194***1
0.234***
0.565***
0.229***

1
0.090***
0.067***

1
0.281***

1

Note: This table reports the correlation coefficients of each variable in our main regression. All of correlation coefficients are
below 0.8 which indicates there are no significant multi-collinearity problem.

26

Table 5: The relation between CER and firm value in two periods

CER
CER*Period
Period(1)
OLS-0.108***(-9.71)
0.067***(4.52)-0.504(-1.52)

FA
CR
DEBT
LEVE
SIZE
AGE
Constant
Industry
Province
Year
Firm
N
adj. R2

3.870***(9.47)
Yes
Yes
Yes
No
6232
0.372

(2)
OLS
-0.032***(-3.14)0.065***(4.95)-0.087(-0.25)-0.676***(-5.70)0.055***(3.57)-0.981***(-7.92)-0.025***(-6.14)-0.227***(-16.26)-0.029***(-11.47)
8.795***(17.33)
Yes
Yes
Yes
No
6232
0.496

(3)
FE
-0.045***(-3.68)0.059***(4.19)-0.992***(-3.09)2.560***(8.10)
Yes
Yes
Yes
Yes
6232
0.270

(4)
FE
-0.038***(-3.22)0.062***(4.61)-3.343***(-7.48)-0.268(-1.05)-0.034(-1.54)-0.170(-0.68)-0.031***(-7.23)-0.577***(-8.01)
0.272***(11.07)14.270***(9.17)
Yes
Yes
Yes
Yes
6232
0.319

Note: This table reports the OLS and fixed-effect (FE) regression results of research in which the dependent variable is Tobin’ Q. Our primary concern is whether the impact of CER on firm value increased inshaky period (Period =1 refers to the shaky period, 0 otherwise). The
coefficient of CER captures the relationship between CER and firm
value in a steady period. The interaction term CER*Period captures
the incremental impact of CER in a shaky period. We report the OLS
regression results with industry, province and year fixed effects included
in columns (1) and (2), FE regression results with firm and year fixed
effects included in columns (3) and (4). Besides, in columns (3) and(4), the control variables are added while there are no control variables
in columns (1) and (2). The t-statistics (in parentheses) are based onheteroscedasticity-consistent standard errors. * denotes p < 0.1, **denotes p < 0.05, *** denotes p < 0.01.

27

Table 6: The moderating effect of ownership type

CER
CER*Period
Period
FA
CR
DEBT
LEVE
SIZE
AGE
Constant
Industry
Province
Year
Firm
N
adj. R2

(1)
OLS
SOECG
-0.027*(-1.70)0.072***(3.36)
1.479***(4.63)-0.126(-0.55)0.118***(2.96)-0.716***(-2.84)-0.023***(-3.08)-0.295***(-12.63)-0.024***(-4.63)
7.094***(11.87)
Yes
Yes
Yes
No
1518
0.603

(2)
OLS
SOELG
-0.033**(-2.49)0.068***(4.06)-0.563(-1.44)-0.777***(-5.67)-0.026(-1.06)-0.791***(-5.09)-0.026***(-5.83)-0.214***(-9.69)-0.010**(-2.23)7.288***(10.08)
Yes
Yes
Yes
No
2242
0.519

(3)
OLS
PE
-0.018(-0.87)0.055**(2.08)
0.400(0.94)-0.696**(-2.47)0.033(1.43)-1.242***(-4.67)-0.045***(-3.91)-0.245***(-7.66)-0.030***(-5.98)8.793***(11.92)
Yes
Yes
Yes
No
2472
0.477

(4)
FE
SOECG
-0.064***(-3.37)0.078***(3.24)-3.157***(-3.24)0.477(1.33)
0.058(1.35)-0.211(-0.57)-0.031***(-4.20)-0.601***(-5.27)0.188***(5.00)
15.722***(6.15)
Yes
Yes
Yes
Yes
1518
0.330

(5)
FE
SOELG
-0.026(-1.60)0.054***(2.75)-2.236***(-3.80)0.277(1.09)-0.014(-0.35)0.339(1.00)-0.022***(-4.15)-0.319***(-3.97)0.147***(4.96)
8.075***(4.68)
Yes
Yes
Yes
Yes
2242
0.306

(6)
FE
PE
-0.025(-1.06)0.049*(1.95)-4.461***(-6.13)-1.244*(-1.95)-0.070**(-2.43)-0.311(-0.63)-0.046***(-4.13)-0.662***(-4.95)0.412***(8.43)
16.653***(5.94)
Yes
Yes
Yes
Yes
2472
0.375

Note: This table reports the OLS and fixed-effect (FE) regression results of ownership type subsamples in which the dependent variable is Tobin’s Q. We report the OLS results with industry, province
and year fixed effects included in columns (1), (2) and (3), FE regression results with firm and year
fixed effects included in columns (4), (5) and (6). The t-statistics (in parentheses) are based onheteroscedasticity-consistent standard errors. * denotes p < 0.1, ** denotes p < 0.05, *** denotes
p < 0.01

28

Table 7: Regression results with lagged explanatory variables

L.CER
L.CER*Period
Period(1)
OLS-0.099***(-8.32)0.058***(3.72)-0.590(-1.03)

L.FA
L.CR
L.DEBT
L.LEVE
L.SIZE
AGE
Constant
Industry
Province
Year
Firm
N
adj. R2

4.085***(6.25)
Yes
Yes
Yes
No
4826
0.393

(2)
OLS
-0.028**(-2.56)
0.054***(3.86)-0.245(-0.46)-0.554***(-4.52)0.057***(3.56)-0.875***(-6.95)-0.009(-1.53)-0.213***(-15.07)-0.024***(-8.54)8.674***(12.64)
Yes
Yes
Yes
No
4826
0.504

(3)
FE
-0.034***(-2.61)
0.056***(3.64)-1.489***(-4.40)2.975***(9.07)
Yes
Yes
Yes
Yes
4826
0.259

(4)
FE
-0.025**(-2.02)0.052***(3.49)-3.296***(-7.09)-0.152(-0.59)-0.030(-1.31)0.302(1.23)-0.014**(-2.31)-0.563***(-7.32)0.229***(9.45)
14.159***(8.60)
Yes
Yes
Yes
Yes
4826
0.297

Note: We lag some explanatory variables by one year and perform the
OLS and FE regression to alleviate the endogenous problem caused bysimultaneity or reverse causality. The t-statistics (in parentheses) arebased on heteroscedasticity-consistent standard errors. * denotes p < 0.1,** denotes p < 0.05, *** denotes p < 0.01

29

Table 8: 2SLS regression results

IV CER(1)
First
0.980***(28.12)

CER
CER*Period
PeriodControls
ProvinceYearNadj. R2

1.769***(4.90)
No
Yes
Yes
6232
0.188

(2)
Second

-0.587***(-11.64)0.204***(3.29)-0.496(-1.00)
No
Yes
Yes
6232
.

(3)
First
0.786***(21.89)1.108***(2.95)
Yes
Yes
Yes
6232
0.259

(4)
Second-0.300***(-5.89)0.158***(2.96)-0.288(-0.70)
Yes
Yes
Yes
6232
0.336

Note: To alleviate the endogenous concerns on omitted correlated
variables, we conduct the instrumental variables method, we use theaverage CER of all other firms in the same industry as the instrumental variable. We report results of the instrumental variables approach in this table, columns (1) and (2) without control variables
while columns (3) and (4) with control variables. The t-statistics(in parentheses) are based on heteroscedasticity-consistent standard
errors. * denotes p < 0.1, ** denotes p < 0.05, *** denotes p < 0.01.

30

Table 9: The relationship between CER and firm value in period subsamples

CER
FA
CR
DEBT
LEVE
SIZE
AGE
Constant
Industry
Province
Year
Firm
N
adj. R2(1)
OLS
Period=0-0.026**(-2.43)-0.559***(-3.34)0.013(0.71)-1.331***(-7.95)-0.024***(-4.09)-0.258***(-13.68)-0.026***(-6.47)9.676***(16.01)
Yes
Yes
Yes
No
3386
0.528

(2)
OLS
Period=1
0.025**(2.37)-0.697***(-4.11)0.144***(5.42)-0.449**(-2.44)-0.022***(-3.74)-0.189***(-8.98)-0.033***(-10.03)
7.828***(13.77)
Yes
Yes
Yes
No
2846
0.482

(3)
FE
Period=0-0.005(-0.34)-0.216(-0.55)-0.068**(-2.43)0.226(0.65)-0.038***(-5.42)-0.796***(-7.23)0.185***(4.59)
18.872***(8.10)
Yes
Yes
Yes
Yes
3386
0.322

(4)
FE
Period=1
0.001(0.11)
0.097(0.26)
0.024(0.63)-1.110**(-2.43)-0.020***(-3.13)-0.020(-0.14)-0.203***(-11.32)
5.847*(1.88)
Yes
Yes
Yes
Yes
2846
0.299

Note: Period =0 refers to steady period, and Period =1 refers to
shaky period. Columns (1) and (2) are OLS regression with industry, province and year fixed effects controlled. Columns (3) and(4) are FE regression with firm and year fixed effects controlled.
The t-statistics (in parentheses) are based on heteroscedasticityconsistent standard errors. * denotes p < 0.1, ** denotes p < 0.05,*** denotes p < 0.01

Table 10: Inspection time periods and inspected provinces
Inspection batches
2016.1.1-2016.2.5
2016.7.12-2016.8.19
2016.11.24-2016.12.30
2017.4.24-2017.5.28
2017.8.7–2017.9.15

Provinces subjected to EICG
Hebei
Inner Mongolia, Heilongjiang, Jiangsu, Jiangxi, Henan, Guangxi, Yunnan, and Ningxia
Beijing, Shanghai, Hubei, Guangdong, Chongqing, Shanxi, and Gansu
Shanxi, Anhui, Tianjin, Hunan, Fujian, Liaoning, and Guizhou
Jilin, Zhejiang, Shandong, Hainan, Sichuan, Xizang, Qinghai, and Xinjiang

Note: EICG is conducted in 5 batches with each lasted about one months. Several provinces are under inspection in each batch
expect for the pilot province Hebei.

31

Table 11: DID results for EICG
CER
CER*Inspect
Inspect(1)
OLS-0.110***(-10.17)0.077***(5.21)-0.587***(-4.11)

FA
CR
DEBT
LEVE
SIZE
AGE
Constant
Industry
Province
Year
Firm
N
adj. R2

3.886***(9.53)
Yes
Yes
Yes
No
6232
0.373

(2)
OLS
-0.036***(-3.72)0.080***(6.14)-0.581***(-4.70)-0.674***(-5.69)0.055***(3.57)-0.977***(-7.89)-0.025***(-6.13)-0.228***(-16.33)-0.030***(-11.52)
8.841***(17.43)
Yes
Yes
Yes
No
6232
0.497

(3)
FE
-0.049***(-4.19)0.073***(5.37)-0.533***(-4.82)2.585***(8.19)
Yes
Yes
Yes
Yes
6232
0.272

(4)
FE
-0.042***(-3.69)0.076***(5.78)-0.527***(-4.93)-0.263(-1.03)-0.034(-1.55)-0.171(-0.69)-0.031***(-7.20)-0.578***(-8.03)0.049*(1.82)
15.073***(9.59)
Yes
Yes
Yes
Yes
6232
0.321

Note: Inspect captures whether the firm is after the inspection
then. CER*Inspect captures the incremental impact of CER on firm
value after the EICG. The t-statistics (in parentheses) are based onheteroscedasticity-consistent standard errors. * denotes p < 0.1, ** denotes p < 0.05, *** denotes p < 0.01

32

Table 12: Placebo test results
CER*Period14
CER*Period15
CER*Period
CER*Period17
CER*Period18
Controls
Firm
Year
N
adj. R2(1)
Whole-0.010(-0.66)0.002(0.17)
0.062***(4.61)
0.094***(7.23)
0.088***(7.10)
Yes
Yes
Yes
6232
0.315

(2)
SOECG
-0.022(-0.83)-0.001(-0.02)0.078***(3.24)
0.127***(5.26)
0.123***(5.46)
Yes
Yes
Yes
1518
0.322

(3)
SOELG
0.024
(1.18)
0.024(1.31)
0.054***(2.75)
0.078***(3.90)
0.078***(4.36)
Yes
Yes
Yes
2242
0.301

(4)
PE
-0.040(-1.42)-0.019(-0.70)0.049*(1.95)
0.075***(3.27)
0.057**(2.36)
Yes
Yes
Yes
2472
0.374

Note: We use Period14 to represent the shaky period from 2014,
CER*Period14 captures the incremental impact of CER on firm value
in the assumed shaky period. The other interaction terms havethe similar meanings. We report all the assumed incremental impacts in this table. The t-statistics (in parentheses) are based onheteroscedasticity-consistent standard errors. * denotes p < 0.1, **denotes p < 0.05, *** denotes p < 0.01

33