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Article

The Response of CSR to Economic Policy Uncertainty: Evidence from China

by
Hailiang Zou
1,*,
Ruijing Wang
1 and
Guoyou Qi
2,*
1
SILC Business School, Shanghai University, Shanghai 200444, China
2
School of Business, East China University of Science and Technology, Shanghai 200237, China
*
Authors to whom correspondence should be addressed.
Sustainability 2023, 15(17), 12978; https://0-doi-org.brum.beds.ac.uk/10.3390/su151712978
Submission received: 29 June 2023 / Revised: 11 August 2023 / Accepted: 18 August 2023 / Published: 28 August 2023
Versions Notes

Abstract

:
The dynamics and instability of economic policies exercise considerable influence on firm behaviors. This study aims to explore the impact of economic policy uncertainty on the level of CSR that firms are engaged in and the heterogeneity of this impact across firms. Using a dataset of Chinese-listed companies from 2011 to 2019, which consists of 837 different firms and 4551 firm-year observations, the results show a negative response of CSR to economic policy uncertainty in China, which is mitigated by the political connections and resource slack that firms possess. These findings underscore the importance of a predictable business environment for CSR behaviors and the capability of firms to cope with uncertainty.

1. Introduction

Owing to frequent and radical changes in economic policies, the complex, unstable and unpredictable business environment shapes firms’ behaviors to a significant extent [1]. Economic policy uncertainty (EPU) wields remarkable influence on economic activities. Along with increasing EPU, firms incur heavier costs of financing [2], and they become more cautious in making investment and financing decisions [3], and the employment in policy-sensitive sectors is hampered [4]. EPU also affects firms’ earnings management [5], and leads firms to reduce investment [6,7], hold more cash [8,9], reduce financial leverage [10], postpone and refrain from M&A transactions [11,12,13], delay strategic changes [14], postpone environmental projects [15] and employ a set of measures to manage the uncertainty of economic policies. The literature documents ample evidence on the impact of EPU on firms’ financial and market behaviors [3,16]. However, the relationship between EPU and nonfinancial decisions, such as corporate social responsibility (CSR), is underexplored. CSR has been in the spotlight of China’s entire society, due to its considerable impact on social development and firm performance.
Compared to the Western countries, the Chinese government takes more control of key resources in market, and has stronger power in intervening in the economy [4]. In the rapid market-oriented transition, economic policies are adopted by the government to shape companies’ behaviors, resulting in a high degree of dynamism and uncertainty in the economy [14]. China’s transition economy is characterized by the weakness in capital market, unclear property rights and unstable institutions, such as the lack of coherent economic policies. These features make the transaction environment uncertain. As a result, Chinese firms are exposed to the dynamics of economic policies to a much higher degree than their counterparts do in the developed economies. On the one hand, it increases the information asymmetry between firms [17], and the worsened information environment makes the prediction of future cash flow of an investment more difficult, and consequently managers become more prudent in making decisions. On the other, the increasing EPU enhances the risk in operation, and firms tend to withdraw from long-term investments to preserve liquidity. CSR in China plays an important role in societal development, and is an important force in promoting social equity, poverty alleviation and rural revitalization, mitigating the environmental impact of economic development and providing disaster relief. Additionally, the evolution of CSR is regarded to be government-driven [18]. However, many studies have shown that there is a salient gap in the CSR initiatives between Chinese firms and those in the developed countries [19]. Uncovering the reasons for this gap will provide insights into how to motivate Chinese firms to assume CSR and thus achieve better development, which will also be enlightening for decision makers in other transition economies.
In CSR studies, a set of regulations and policies were examined for the impacts on CSR [20], including environmental regulation [21], trade policy [22] and poverty alleviation policy [23]. However, in these studies, the effect of policies was examined based on a static perspective. Moreover, a stream of studies has also examined the relationship between CSR and firm risk, and CSR is regarded as a differentiation strategy creating higher profit margins, enabling firms to mitigate external shocks and thus lower systematic risk [24]. CSR initiatives also serve as an insurance by providing a reservoir of social capital, which cushions the reduction in firm value on the occasion of global financial crisis [25], corporate crisis events [26,27] and other adverse shocks [28,29]. However, how the external uncertainties shape firms’ CSR engagement has not drawn much attention from scholars.
Using a sample of Chinese-listed firms, this study examines the relationship between economic policy and CSR from a dynamic perspective, and expands the research on the impact of market environment uncertainty on nonmarket strategy. Additionally, based on the studies on risk management, the social networks and resource slack are argued to provide a resource cornerstone for firms’ capability to cope with external uncertainties. Accordingly, we further investigate the contingency role of political connections and resource slack in the relationship between EPU and CSR. The empirical results show that EPU in China has an inhibitory effect on firms’ CSR initiatives. This effect is weakened in firms that possess political connections, and in those with higher resource slack. Briefly, a stable economic environment is an important motivator for firms to invest in CSR, and their political connection and resource slack could help alleviate the impact of policy uncertainties. The findings of this study uncover an important CSR antecedent, and have implications for managers to better cope with policy instability and to fend off the negative impact of EPU.
The article is structured as follows. Section 2 presents the literature review and hypotheses development. Section 3 presents the data and research methodology. Section 4 presents the main results and robustness tests. Section 5 presents the discussion. Lastly, Section 6 is the outlook and suggestions for other studies.

2. Literature and Hypotheses

2.1. Literature Review

EPU refers to the inability of economic participants to predict whether, when and how current economic policies will change, manifested by policy instability and economic volatility [1], which has a significant impact on the labor and financial markets. When the expected income is subject to uncertainty, consumers will postpone their nonessential purchases and their consumption intentions will be dampened [30]. The decline of demands in the market leads to a downturn in economic activities [31], and dampens economic growth [1]. Policy uncertainty triggers the volatility of stock and commodity price, which adversely affects the efficiency of stock markets [32]. EPU is significantly and positively related to the interest rate on bank loans, because it exacerbates the risk of default in corporate borrowing [33]. EPU increases information asymmetry between firms, which in turn enhances the cost of financing and the instability of future cash flows for firms [17,34,35]. In China, EPU has a significant negative effect on stock price synchronicity, which is reinforced by institutional investors, high-quality auditors and analysts tracking [36]. EPU has a salient influence on China’s real estate market, and there is a positive relationship between housing price variation and EPU [37].
At the firm level, EPU has a notable impact on firm decisions and behaviors. When EPU increases, firms tend to suspend investment and recruitment activities, and even curb production [38]. Under the impact of EPU, firms become more risk averse [39]. For example, firms are prone to suspend M&A activities [11], reduce their financial leverage [10] and lower their dividend payments [40], especially for those with lower levels of cash flow. EPU has a negative impact on business investment [7]. When economic uncertainty increases, firms and investors are inclined to postpone irreversible investments in prudence [1] and hold more cash, driven by precautionary motives [8]. When EPU eases, firms unleash their production and labor demand, and the economic activities rebounds quickly.
Firms are expected to be responsible for their impacts on the environment and society and to meet the needs of various stakeholders beyond legal requirements. Economic, environmental and social responsibilities are the triple bottom line of CSR. The antecedents of CSR have been studied thoroughly in prior studies, including the institutional environment [41,42], the variety of stakeholders [43,44,45], industrial competition [46], firm traits (e.g., profitability, size) [47] and corporate governance [48]. In addition, as a key stakeholder, government exercises a significant influence on firms’ CSR initiatives [49]. Ample evidence has been furnished that firms’ green behaviors [50] and philanthropic giving [51] are shaped by government interference. There is a positive impact of executive connection with the government on their engagement in social responsibility [18,51]. And from a resource-based view, resource slack, especially the unabsorbed resource slack, is a necessary condition for assuming social responsibility [19], which also enables firms to buffer external uncertainties [52], although too much slack may lead to inefficiency [52].
When the business environment is filled with uncertainties, and the investment is irreversible, the real options theory can be applied to assess the value of an investment decision [53]. Real options theory argues that every investment decision can be regarded as the exercise of an option, which is the power to purchase real assets on favorable terms [54]. In a circumstance of high environmental uncertainty, it is valuable for firms to suspend investment and await more information to make investment decisions [14], which thus highlights strategic flexibility. This perspective has been adopted to assess the strategic value of joint ventures [55,56], technology investment [57], R&D [58] and project investments [59,60]. Cuypers and Martin apply real options theory to the investment decisions in joint ventures, by distinguishing between endogenous and exogenous uncertainties, and they argue that only the exogenous uncertainties are effective for foreign investors’ equity investment in joint ventures [55]. Based on this theory, Husted regards CSR as a real option, and analyzes its implications for risk management [61]. Furthermore, based on the resource-based view, the external social capital [62] and the internal resource structure [63] provide the foundation for firms’ risk management capability. For example, political connections are found to enable firms to hedge against policy uncertainty by helping them obtain policy information in advance of public disclosure [64]. Resource slack provides firms important latitude to address both internal and market uncertainties [63]. This study aims to test whether these characteristics can help firms handle external uncertainties.
By undertaking CSR, firms are able to build closer relationships with their stakeholders, including customers [65], employees [66], suppliers [67], government [68] and media [45], thereby gaining intangible, valuable and scarce social capital [69,70,71], which can be a source of sustainable competitive advantage [72,73] and creates value for business [74]. When uncertainty in the business environment increases, the strategic flexibility becomes more valuable, because firms may be forced to adapt their strategies to the changing environment in the future, which requires a large amount of resources. Under such circumstances, managers become risk-averse in investment. The shifts in market demand and changes in business strategies could break up the relationship between a firm and its key stakeholders, thus leading to volatility in the value of CSR investments. Based on real options theory, Cassimon et al. argue that when environmental uncertainty increases, the benefits of CSR are subject to greater uncertainty, leading firms to suspend their engagement in social responsibility [75]. However, based on a sample of companies in the European countries, the overall ESG performance is found to rise during the periods of high uncertainties, arguing that ESG practices can be used as a risk management technique by firms to manage high uncertainties [39]. The Chinese government’s intervention in economy is much more comprehensive, and the policy dynamics is more radical and far-reaching, which is difficult to resist by firms’ social strategies, and thus adversely affects firms’ long-term investments [76].

2.2. Research Hypotheses

The uncertainty in the business environment is related to the volatility of the demand in the market [77], and the rising interest rate on bank loans, due to the increasing risk of default on corporate borrowing [33]. Additionally, Chinese firms are found to curb their financial leverage in the face of rising EPU [10]. The uncertainty in the business environment negatively affects firms’ cash flows [16], which harms firm performance and increases the cost of external financing, thereby placing financial constraints on corporate investment. In the literature, many studies posit that EPU increases financing costs [33,34,78] and leads firms to refrain from long-term investment [79], which reduces productivity [38].
Based upon prior studies, we propose that in the face of rising EPU, firms’ CSR activities are hampered. Concerning one factor, EPU worsens the information environment and increases information asymmetries between market participants [17], thereby decreasing interorganizational trust and cooperation between firms. For another, it leads to unpredictable fluctuations in cash flow following an investment, thus giving rise to firm risks, which in turn increases the value of delay options. CSR investments could be costly and irreversible, and the outcomes are complex and uncertain [67], especially in the face of rising uncertainties in the business environment. Therefore, based on real option theory, faced with higher uncertainties, firms attempt to adopt conservative options to control the risks [39] and delay the investment in CSR [76,77].
First, EPU is related to the deterioration of the information environment, which makes it more difficult to build trust among economic entities, and increases the opportunities for executives to conceal negative information, resulting in high risk premiums and worsened financial environment. Accordingly, executives should make investment decisions more cautiously to survive the tough environment. Therefore, when EPU increases, the strategic flexibility is more valuable, and firms’ CSR initiatives will be hampered, because the investment in CSR is irreversible. Second, high EPU usually entails institutional changes, and corporate strategic change and organizational transformation become necessary, because some business will turn to be disadvantaged and even illegal according to the new policies. The operation, supply chain management, organizational structure, or sales channels must adapt to the environment, since organizational adaptability determines firm survival. The strategic adaptation will require a large amount of resources, while the firm profitability would be hampered. It poses a severe challenge for firms, and they should refrain from long-term-oriented and less urgent investments to meet the needs for survival. Third, firms assuming CSR aim to gain support from stakeholders [80], and the dynamics of economic policies causes instability in the relationship between a firm and the key stakeholders. For example, a firm may be forced to shift its suppliers and customers when a new regulation on trade is issued. In some cases, strategic changes are initiated by new policies, which entail layoffs to capture growth opportunities, and incur additional costs to the strategies of social responsibility. CSR involves building long-term relationships with stakeholders, which is crucial to the sustainability of business, but has a negative impact on a firm’s short-term financial performance. Therefore, firms may be reluctant to invest scarce resources in socially responsible development if the cost of the investment is higher than the expected future benefits due to the increased uncertainty. On occasions of increasing EPU, firms may delay or even refuse to maintain their engagement with social responsibility. Therefore, in a dynamic environment featured by high EPU, firms that invest heavily in social issues may be at a disadvantageous position compared to the peers that invest less in CSR.
Hypothesis (H1).
EPU is negatively associated with CSR engagement.
Political connections provide firms with more convenient and earlier access to information on policy changes and policy trends [68], because politicians take control of some interior information on economic plans [81] and have better foresights into future trends [82], which mitigate executives’ perception of uncertainty in the business environment. Previous research has shown that there is less information asymmetry between politically connected firms and the legislators [83]. Politically connected firms enjoy more favorable analyst recommendations [84], and the connection with politicians increases profitability [85]. Firms with strong ties to government can better prepare for the implementation of new policies due to their advantages in information access, and they are more capable in predicting future policy trends. Therefore, they can adapt and respond to the changes more quickly and effectively. In view of real option theory, establishing political ties helps firms overcome the disadvantage of information asymmetry, thus removing the uncertainty in the outcome of business decisions, which boosts the confidence in making investment decisions and decreases the value of delay options. Hence, for firms with political connections, their CSR initiatives are less hampered in the face of increasing EPU.
On the other hand, to implement new policies and enforce new regulations, relevant funds are provided and supportive measures are employed by government to motivate firms to launch strategic changes, which offer necessary resources to relieve the shocks to their operation [50,86]. Firms’ political connections help them obtain these supports and the preferential treatments from government. Political connections complement institutional weaknesses in the transition economy of China, through which firms obtain substantial resources and support from the government [87], and firms take advantage of government officials’ rent-seeking behaviors to obtain subsidies and funds [88]. The government is a source of uncertainty in the business environment, and the benefits that accrue to firms that build a successful linkage with the government include resources accessibility and reduced uncertainty and transaction costs [68]. Political relationships are conducive to enhancing organizational legitimacy and obtaining institutional support [89], winning access to a range of valuable resources [90]. The extent to which a company is connected to government is related to the opportunities of receiving contracts with the government and obtaining tax credit and favorable treatment, thus influencing its sustainability and competitive advantage [91]. Due to the benefits firms can attain through political connections, it is widely adopted even in the developed countries to build close relationships with government officials [68]. These advantages and benefits firms obtain through political connections could relieve firms’ perception of EPU, ease the tension of resource constraint, and thus mitigate the impact of economic policy turmoil on the persistence of CSR strategies.
Hypothesis (H2).
Political connections mitigate the negative relationship between EPU and CSR.
In addition to the external social networks, the internal slack resources also provide a buffer for the impact of environmental turbulence [52,92], and help maintain the coherence of long-term strategies [93]. Studies have shown a strong relationship between financial slack and CSR performance [79,94]. Adequate cash reserves improve a firm’s ability to withstand environmental changes and capture investment opportunities [95]. Firms with abundant financial resources have a higher degree of managerial discretion in investment during financial crises [95].
In an instable environment of economic policies, the operation of business may be subject to a high level of risk, and the explorative innovation, strategic adaptation and organizational restructuring requires and consumes a great amount of financial resources, and firms are faced with a high level of liquidity constraints. Firms with higher resource slack are less subject to the risk of liquidity crunch, and they are more capable in coping with the shock of external turbulence and can even take advantage of opportunities arising in the turbulent environment [96,97]. Additionally, due to resource constraints, investing in social issues means forgoing investment in other projects. When adequate resources are available, managers can address each problem with more appropriate solutions, but when resource constraints are tight, firms are forced to narrow their focus to the more urgent issues for survival. Resource slack could alleviate firms’ inclination to divert resources from social investment to manage environmental uncertainties. Therefore, resource slack reduces the opportunity cost of investing in social responsibility, which thereby alleviates the tendency to delay and reduce CSR engagement due to policy uncertainty. As a result, resource slack enables firms to withstand uncertainties in the external environment and maintain persistence of CSR strategies.
Hypothesis (H3).
Resource slack mitigates the negative relationship between EPU and CSR.

3. Methodology

3.1. Data and Sample

CSR data were obtained from the Rankins (RKS) CSR database, and other financial data were from the database of China Securities Market and Accounting Research (CSMAR). The sample used in this study comprises companies listed in the Shanghai and Shenzhen A-stock market for 2011–2019. The EPU index was extracted from the China EPU Index, developed and compiled by Huang and Luk [37]. To eliminate the effect of extreme values on the estimations, the variables except CSR scores were winsorized at the 1% level. Excluding the financial sector and samples with missing values of key variables, the final sample consists of 837 different firms and 4551 firm-year observations.

3.2. Measurement

CSR engagement. In this study, we used both RKS CSR ratings and Hexun CSR score datasets, which are the two most widely used databases in CSR studies from China. First, for the RKS CSR ratings, its validity and reliability have been widely verified in previous studies (e.g., [98]). RKS (http://www.rksratings.cn, accessed on 1 August 2023) is an authoritative third-party rating agency for CSR in China, and RKS CSR ratings adhere to the Social Responsibility Guidelines and the KLD Social Responsibility Rating Scheme, adapted to the Chinese context [98]. RKS ratings cover the key aspects of environmental, social and governance, including corporate governance, employee relations and human rights, environmental protection, consumer and community responsibilities. Additionally, some concerns about the operations of Chinese firms were included, such as the conflicts between majority and minority shareholders, dividend distribution and corruption. In a further test, the Hexun CSR database was used, in which CSR performance was assessed not only based on the independent CSR reports, but also from the annual financial reports. As a result, the Hexun CSR dataset encompasses a wider range of firms, including those that do not disclose CSR reports independently.
EPU. In the literature, the EPU indices were mostly constructed based upon the news contents. The EPU indices compiled by Baker et al. [4] were widely adopted in previous studies to measure EPU in China, which were constructed in terms of the content published in the South China Morning Post, a newspaper in Hong Kong [4]. Huang and Luk [37] developed and adapted the index to better fit the Chinese context, based on the articles containing at least one keyword in each of the three criteria: economy, uncertainty and policy, from 10 major newspapers published in Mainland China: People’s Daily Overseas Edition, Beijing Youth Daily, Guangzhou Daily, Jiefang Daily, Shanghai Morning Post, Southern Metropolis Daily, The Beijing News, Today Evening Post, Wen Hui Daily and Yangcheng Evening News. This index is calculated as the number of articles that meet the criteria divided by the total number of articles in the 114 most influential Chinese newspapers that contain the economic-related keywords in the same month, using the average value over the period from January 2000 to December 2011 as the benchmark 100. This index has been widely used and verified in the recent studies as a proxy for the uncertainty in Chinese economic policy [99]. Additionally, following prior studies, such as Demir and Ersan [8] and Nagar et al. [17], the annual EPU index was measured as the arithmetic average of the monthly EPU index in a given year. Furthermore, considering the uneven distribution in the enaction of new policies across months in a year, consistent with Wang et al. [76] and Demir and Ersan [8], as a robustness check, another annual EPU index was calculated as a weighted average: the monthly index in the first half of a year was weighted one-third and that in the second half was weighted two-thirds, which was denoted as EPU2.
Political connections. If the chairman (or the CEO) of the company was or is serving as a party representative, the National People’s Congress (NPC) deputy or the Chinese People’s Political Consultative Conference (CPPCC) member, a value is assigned to the variable ChairPC (or CEOPC) according to the level of the agency he/she serves in: 1 for the district or county level or below, 2 for the municipal level, 3 for the provincial level, and 4 for the national level. If it equals 0, the chairman or CEO did not serve in any of these agencies.
Resource slack. Free cash is the most easily disposable slack resources with a high degree of discretion in investment [100]. Accordingly, this study used the ratio of a firm’s free cash flow at the end of a fiscal year to the total assets to measure the level of resource slack.
Control variables. The firm-level and regional-level factors were controlled for in regressions. These variables include firm size, firm age, return on assets, market value, board size, board independence, CEO-chairman duality, state ownership and regional marketization index. Firms’ CSR activities are closely associated with firm size, firm age and profitability, which also determine firms’ adaptability to environmental dynamics. Firm size was calculated as the natural log of total assets. Firm age was measured as the number of years since the company was established. Profitability was captured via annual return on assets (ROA). The ratio of market value to total net assets reflects growth potential, which is a key influencer of firms’ social strategies. Additionally, the board of directors plays a central role in firms’ decision making, in which the characteristics were controlled for, including board size, independence and CEO–chairman duality. Board size refers to the total number of board members, and board independence was calculated as the ratio of independent board members to the board size. CEO–chairman duality, a binary variable, indicates whether a CEO chairs the board of directors. In the Chinese context, government exercises a significant influence on business, and thus state ownership was included, which was captured by whether the government (state) ultimately controls the company. Additionally, firms’ social engagement is closely related to the regional institutional development, for which the marketization index at the provincial level was adopted as a proxy. The literature shows that higher industry competition brings stronger environmental uncertainty to enterprises [101]. EPU has contributed to volatility in every sector and industry output [102,103]. In addition, the dummy variables for industries and years were controlled. The variables are described in Table 1. We used the one-year lagged value of the independent variables to better capture a causal relationship.

3.3. Estimation Method

This study examines the relationship between EPU and CSR, and the moderation of political connections and resource slack. Equation (1) tests the main effect of EPU on CSR; Equation (2) shows the moderating effect of political connection on the relationship between EPU and CSR; and Equation (3) provides the moderating effect of resource slack.
CSRi,t + 1 = β0 + β1EPUi,t + ΣβjControlsi,t + εi,t
CSRi,t + 1 = β0 + β1EPUi,t + β2PCi,t + β3EPUi,t × PCi,t + ΣβjControlsi,t + εi,t
CSRi,t + 1 = β0 + β1EPUi,t + β2Slacki,t + β3EPUi,t × Slacki,t + ΣβjControlsi,t + εi,t
where CSR represents corporate social responsibility score; EPU represents the economic policy uncertainty index; PC represents political connections of either the chairman or the CEO; Slack represents resource slack; Controls represents the control variables.

4. Findings

4.1. Baseline Regression Results

Table 2 shows the sample distribution across industries. Table 3 reports the descriptive statistics of the variables in regressions. All of the VIF values are less than 2.6, below the threshold of 10 [104], indicating that this study is free from the problem of multicollinearity. Table 4 shows the Pearson correlation coefficients between key variables in which CSR is significantly and negatively correlated with EPU, providing preliminary support for Hypothesis (H1).
The results from the Hausman test suggest the fixed effect model is preferable in this study, which could also mitigate the endogenous problems. Hypothesis (H1) suggests a negative relationship between EPU and CSR. The results of Model 1 in Table 5 show a significantly negative relationship between EPU and CSR (β = −0.141; p < 0.01). Hypothesis (H2) proposes that political connections mitigate the relationship between EPU and CSR. Models 2 and 3 report the coefficients of the interaction terms between EPU and the political connections of the chairman and CEO, showing that the interaction term coefficients are both significantly positive (β = 0.086 and p < 0.05; β = 0.129 and p < 0.05), which lends support to Hypothesis (H2). Hypothesis (H3) proposes that resource slack weakens the relationship between EPU and CSR. Model 4 reports the estimates of the moderating effect of resource slack on the relationship between EPU and CSR, and the coefficient of the interaction term between EPU and resource slack is significantly positive (β = 0.180 and p < 0.05), consistent with Hypothesis (H3).

4.2. Robustness Check

Several approaches were adopted to test the robustness and sensitivity of the results. First, despite controlling for firm traits and firm-fixed effects, there could be some unobserved factors correlated with both economic policy uncertainty and CSR, raising endogeneity concerns. Following Wang et al. [76] and Sha et al. [13], we constructed an instrumental variable (IV) model using the one-year lagged value of the US EPU index as the instrument for China’s EPU index, which has been verified to be a valid instrument in previous studies (e.g., [13]). Table 6 reports the regression results. In Model 1, the coefficient of instrumented EPU is significantly negative, and in Models 2 and 3, the instrumented EPU∗ChairPC and EPU∗CEOPC interactions are included, of which the coefficients remain positive and significant. In Model 4, the interaction term EPU∗Slack is included, of which the coefficient remains negative and significant. These results suggest that our results are robust to endogeneity concerns.
Second, consistent with Wang et al. [76] and Demir and Ersan [8], the annual EPU indices were calculated alternatively as a weighted average, denoted as EPU2. The results were shown in Table 7, where the coefficients of the explanatory variables remain stable. EPU2 is negatively associated with CSR, and the interaction terms between EPU2, political connections and resource slack are positive and significant, respectively, providing further support to our hypotheses.
Third, to provide further tests of the moderators, we used split samples according the median value of resource slack, and whether a firm possesses political connection. These results are presented in Table 8, which shows that firms with less resource slack and without political connections are more affected in CSR by EPU, lending support to our hypotheses.
Fourth, based on the classifications of corporate social responsibilities, Mattingly and Berman [105] proposed Technical Corporate Social Responsibility (TCSR) and Institutional Corporate Social Responsibility (ICSR). TCSR is defined as the CSR activities that target at the dominant stakeholders of the company, including the local community, customers, shareholders, employees and suppliers. ICSR refers to the social responsibilities regarding the secondary stakeholders, such as environmental protection managers and those who cater to special interest groups, among others. Different stakeholders may have conflicting expectations of the company and different demands on the company’s resources. Therefore, it is worthwhile to further examine whether the effect of EPU on CSR changes between the different aspects of CSR. Based on the Hexun CSR dataset, which assesses CSR performance in terms of the various fields, including shareholders, employees, suppliers, customers, society and the environment, the sum of CSR scores concerning shareholders, employees, suppliers and customers was employed as a proxy for technical CSR; the sum of CSR scores regarding society and the environment was used as a proxy for institutional CSR. The results are presented in Table 9, where EPU is in a negative relationship with the overall CSR scores, as well as with the different types of CSR activities.
Fifth, we further examined the difference in the impact of uncertainty of different policy categories on CSR. EPU results mainly from monetary, fiscal, tax and trade policies [1,14,38], and the uncertainties derived from different policy categories might induce different reactions from firms. In this study, we further examine the relationships between the uncertainty indices of the four policy categories and CSR; the results are shown in Table 10. It is shown that the uncertainty indices of fiscal, monetary and exchange rate policies are negatively associated with CSR, but not that for trade policy.
Sixth, considering the difference in the effect of EPU across industries, we performed regressions for each industry. These results are reported in Table 11. Among all the sectors, the construction industry is shown to be the most affected by EPU.

5. Discussion

From the results, our hypotheses are mainly supported. It shows a negative response of CSR to economic policy uncertainty in China, which is mitigated by the political connections and resource slack that firms possess. Further analysis reveals that the impact of EPU exists on both technical and institutional aspects of CSR. Concerning the uncertainties derived from various types of economic policies, they are generally in a negative relationship with CSR, except that for trade policy. Firms’ engagement in CSR entails an irreversible investment of resources [1], and EPU deteriorates the information environment and increases uncertainty about future cash flow, which increases the costs and reduces the prospective value of CSR engagement. Executives tend to defer and reduce CSR investments to hold the disposable resources and maintain a high level of flexibility in strategy. When the uncertainty of the business environment increases, enterprises are faced with risks such as changes in market demand, business transformation and business model change, which can only be realized by changing the structure of important stakeholders such as employees, customers and suppliers. As a result, the value of CSR investment faces greater uncertainty. When economic policy uncertainty increases, firms raise expected costs and sacrifice the environment for short-term gains.
This study contributes to the literature in multiple ways. First, the instability in economic policies has attracted wide attention from both scholars and practitioners. Previous literature has focused on the impact of EPU on cash holding [8], investment decisions [6,7,76], dividend payments [40], stock prices [32], etc. Fewer of them were concerned about the impact of EPU on firms’ nonfinancial decisions. In recent years, CSR has been in the spotlight of the Chinese government and the entire society, which is argued to be shaped by the institutional environment and relevant policies. This study suggests a negative outcome in EPU regarding firms’ engagement in social responsibility, a typical nonmarket strategy. Briefly, combined with the previous studies, EPU is found to stifle firms’ investment in both market and nonmarket issues, which highlights the significance of a stable environment for the sustainability of business. In China, as a typical transition economy, market-oriented reform and institutional changes are carried out through the issuance of new economic policies, which is much more frequent and radical than that in the developed economies, leading to a higher level of EPU and serious disruption to corporate strategy. This analysis examines the impact of EPU on the strategic value of CSR from a real options perspective, which provides insights into the outcomes of EPU.
Second, in the literature, studies have found a significant role of CSR in risk management, and proposed an insurance-like effect of CSR [24], which helps cope with the market and firm-level idiosyncratic uncertainties, such as crisis event [29] and technological innovation [74]. Compared to market- and firm-level uncertainty, EPU not only causes a fluctuation in the demands and supplies in the market place [76], but also leads to organizational and strategic changes [14], which wields holistic influence on firms, and may result in a breakup in the relationship between firms and their key stakeholders, thus raising the risk of the investment in firms’ relationship with stakeholders. This study enriches the research on the antecedents of CSR and expands our knowledge on the relationship between CSR and risk management.
Third, existent research has investigated the antecedents of CSR at various levels, including the decision maker level [48], firm level [47], institutional level [41,42] and industry level [46]. Scholars have given attention to the impact of policy and regulation on CSR from a static perspective, including environmental regulation [21], trade policy [22] and poverty alleviation policy [23], but there are fewer studies on the impact of economic policy uncertainty on CSR from a dynamic perspective. This study provides a useful attempt to fill this gap, which enriches our knowledge on firms’ CSR engagement at the macro policy level more comprehensively.
The findings of the study have some implications for policy makers and business practitioners. Although economic reforms and institutional progresses are vital for the development in China, frequent and unpredictable enactments of economic policies reduce firms’ prospective value of long-term investments, especially in the relationship with stakeholders. Effective communication over the underlying intention of new economic policy and the trends in policy would mitigate firms’ perception and judgment on uncertainties. The business relations between entities might be vulnerable to the uncertainties of economic policies, and as a result, business actors may face decoupling from their partners. Hence, providing necessary support is required to help business practitioners rebuild connections in the dynamic environment of economic policy. Political connections are adopted by firms as an informal way to access this information; however, it may foster corruption and hinder economic efficiency, and puts sand on the economic wheels. On the other hand, a certain level of free cash reserve is necessary for firms to cope with environmental turbulence, which has also been emphasized in risk management literature [68]. Especially for firms that adopt long-term oriented strategies and invest heavily in social capital, adequate resource slack is critical for them to cope with external uncertainties and maintain persistency of social strategies.

6. Conclusions

This study examines the relationship between EPU and corporate engagement with social responsibility. Using a sample of listed enterprises from the Shanghai and Shenzhen stock market from 2011 to 2019, it is found that EPU is negatively related to CSR engagement. In addition, the inhibitory effect of EPU on CSR engagement is found to be weakened in enterprises with political connections and those with higher resource slack, which are regarded to be more capable of coping with EPU.
This study is subject to some limitations. First, it was conducted in a transition economy of China, and caution should be taken in generalizing these findings to developed economies due to the difference in institutional environment. It will provide more insights to examine these findings in other contexts. Moreover, CSR was gauged based on information disclosure in this study, which might lead to bias in measuring the actual level of CSR that firms are engaged in. Third, although the news-based measure of EPU proposed by Baker et al. [4] was widely employed in the literature, it is subject to several limitations for some unreported issues and vagueness in reports. There is much room for future studies to address this problem by developing a better proxy. Fourth, firms suffered from great policy uncertainties during the hard time of COVID-19, and the business context was quite different from that in normal times. In future research, it would be valuable to study and explore how the pandemic mitigation policies exercised influence on firms.

Author Contributions

Conceptualization, H.Z.; Methodology, H.Z.; Validation, G.Q.; Investigation, H.Z.; Resources, G.Q. and R.W.; Data curation, R.W.; Writing—original draft, R.W.; Writing—review & editing, H.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Shanghai Philosophy and Social Science Planning Project (Grant No. 2019EGL014), and the National Natural Science Foundation of China (Grant Nos. 71972125, 72072055).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data is contained within the article.

Conflicts of Interest

The authors declare no conflict of interest.

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Table 1. Definition of variables.
Table 1. Definition of variables.
Variable SymbolsVariable NameVariable Definitions
CSRCorporate social responsibilityRKS CSR rating score
EPUEconomic policy uncertaintyΣ monthly EPU index/12
ChairPC/CEOPCPolitical connectionsChairPC (or CEOPC) is assigned a value from 0 to 4, according to the four levels of the agency that the chairman (or CEO) was or is serving in
SlackResource slackRatio of free cash flow to the amount of total assets
DualCEO dualityWhether a CEO chairs the board of directors
AgeAge of businessNumber of years since the company was established
SizeBusiness sizeNatural logarithm of the amount of total assets
ROAReturn on assetsRatio of a firm’s annual net income to total assets
HHIIndustry competitionHerfindahl–Hirschman index, an industry’s squared market share
MVMarket valueMarket value divided by the amount of total net assets
SOEState-owned enterpriseA binary variable, indicating whether the firm is ultimately controlled by government
BoardBoard sizeNumber of board members
IBPercentage of independent directorsProportion of independent directors in the board of directors
MarketMarketization processMarketization index issued by NERI
Table 2. Sample distribution in each industry.
Table 2. Sample distribution in each industry.
IndustryNumber of CompaniesPercentage
Agriculture, forestry, animal husbandry and fisheries91.08%
Mining333.94%
Manufacturing46855.91%
Electricity, heat, gas and water production and supply industry475.62%
Construction283.35%
Wholesale and retail trade435.14%
Transport, storage and postal services475.62%
Accommodation and catering20.24%
Information transmission, software and information technology services495.85%
Real estate505.97%
Rental and business services101.19%
Scientific research and technology services industry70.84%
Water conservancy, environment and public facilities management111.31%
Education10.12%
Health and social work40.48%
Culture, sports and recreation232.75%
Public administration, social security and social organizations50.60%
SUM837100.00%
Table 3. Descriptive statistics.
Table 3. Descriptive statistics.
VariableNMeanStd.MinMedianMaxVIF
CSR488241.043912.09915.1238.4689.00
EPU5841141.271112.736125.03136.59165.741.12
Slack5764−1.27560.321−5.18−1.317.962.26
Age584117.90945.4791.0018.0040.001.15
Size584123.20191.47218.4923.0728.641.78
ROA58410.03810.125−2.070.037.451.75
MV57301.79171.3050.701.4126.821.29
IB58400.14630.0290.080.140.332.39
Dual57480.17830.3830.000.001.001.25
Board58409.12931.9674.009.0018.002.57
SOE57170.61660.4860.001.001.001.31
HHI58410.11360.1180.020.081.001.06
Market58417.97851.793−1.148.1010.831.13
Table 4. Pairwise correlation coefficients.
Table 4. Pairwise correlation coefficients.
CSREPUSlackAgeSizeROAMVIBDualBoardSOEHHIMarket
CSR1
EPU−0.118 ***1
Slack−0.114 ***0.0141
Age0.015−0.247 ***−0.093 ***1
Size0.482 ***−0.077 ***−0.395 ***0.089 ***1
ROA0.028 *0.036 ***0.356 ***−0.031 **−0.029 **1
MV−0.139 ***0.040 ***0.360 ***−0.047 ***−0.410 ***0.116 ***1
IB0.062 ***0.080 ***0.005−0.042 ***0.0110.004−0.0121
Dual−0.091 ***−0.033 **0.103 ***−0.025 *−0.123 ***0.045 ***0.078 ***−0.062 ***1
Board0.172 ***0.059 ***−0.077 ***0.023 *0.227 ***0.011−0.143 ***0.443 ***−0.149 ***1
SOE0.161 ***0.049 ***−0.170 ***0.078 ***0.305 ***−0.038 ***−0.169 ***0.163 ***−0.280 ***0.249 ***1
HHI0.102 ***0.051 ***0.006−0.085 ***0.135 ***0.003−0.0210.073 ***−0.065 ***0.078 ***0.079 ***1
Market0.123 ***−0.172 ***0.0190.065 ***0.066 ***0.022 *−0.006−0.130 ***0.091 ***−0.092 ***−0.098 ***−0.063 ***1
Note: ***, ** and * denote significance at the 1%, 5% and 10% level, respectively.
Table 5. The baseline results and the moderation of political connection and resource slack.
Table 5. The baseline results and the moderation of political connection and resource slack.
Model 1Model 2Model 3Model 4
Dependent VariableCSRCSRCSRCSR
EPU−0.141 ***(−8.35)−0.149 ***(−8.57)−0.146 ***(−8.58)−0.141 ***(−8.39)
ChairPC 0.024(0.34) 0.001(0.00)
ChairPC × EPU 0.086 **(2.02)
CEOPC 0.000(0.00)
CEOPC × EPU 0.129 **(2.20)
Slack × EPU 0.180 **(2.33)
Slack1.439 **(2.01)1.424 **(1.99)1.467 **(2.05)1.246 *(1.73)
Age−0.052(−0.79)−0.052(−0.79)−0.053(−0.80)−0.050(−0.76)
Size2.840 ***(13.30)2.842 ***(13.28)2.847 ***(13.33)2.825 ***(13.23)
ROA3.319(1.53)3.369(1.55)3.209(1.48)3.620 *(1.66)
MV0.005(0.05)0.001(0.01)0.007(0.07)0.000(0.00)
IB11.048 *(1.78)10.843 *(1.75)11.115 *(1.79)11.157 *(1.80)
Dual−0.568 *(−1.76)−0.573 *(−1.78)−0.584 *(−1.79)−0.580 *(−1.80)
Board0.109(1.03)0.110(1.03)0.108(1.02)0.107(1.01)
SOE0.109(0.21)0.099(0.19)0.117(0.22)0.109(0.21)
HHI0.615(0.44)0.514(0.37)0.706(0.51)0.632(0.46)
Market0.147(0.99)0.147(0.99)0.153(1.03)0.152(1.02)
Cons−7.808(−1.18)−6.683(−1.01)−7.274(−1.10)−7.688(−1.16)
YearYESYESYESYES
IndYESYESYESYES
N4551455145514551
R20.20340.20430.20430.2044
F1269.581274.11275.131276.34
Note: T-statistics are reported in parentheses; ***, ** and * denote significance at the 1%, 5% and 10% level, respectively.
Table 6. Using an instrumental variable for EPU.
Table 6. Using an instrumental variable for EPU.
Model 1Model 2Model 3Model 4
VariableCSRCSRCSRCSR
EPU−0.181 ***(−5.77)−0.182 ***(−5.80)−0.183 ***(−5.81)−0.181 ***(−5.76)
ChairPC −0.024(−0.34)
ChairPC × EPU 0.046 *(1.73)
CEOPC −0.002(−0.02)
CEOPC × EPU 0.089 ***(2.21)
Slack × EPU 0.109 **(2.03)
Slack1.407 **(1.97)1.392 *(1.94)1.435 **(2.00)1.213 *(1.68)
Age−0.051(−0.76)−0.052(−0.77)−0.052(−0.78)−0.049(−0.74)
Size2.798 ***(12.96)2.800 ***(12.95)2.805 ***(12.99)2.782 ***(12.89)
ROA3.349(1.55)3.399(1.57)3.239(1.49)3.649 *(1.68)
MV0.002(0.02)−0.003(−0.03)0.003(0.03)−0.003(−0.03)
IB10.946 *(1.77)10.743 *(1.74)11.011 *(1.78)11.052 *(1.79)
Dual−0.564 *(−1.76)−0.569 *(−1.77)−0.579 *(−1.78)−0.575 *(−1.79)
Board0.107(1.01)0.107(1.01)0.106(1.00)0.105(0.99)
SOE0.097(0.18)0.087(0.16)0.106(0.20)0.097(0.18)
HHI0.575(0.41)0.474(0.34)0.667(0.48)0.590(0.43)
Market0.134(0.89)0.134(0.89)0.140(0.93)0.138(0.91)
YearYESYESYESYES
IndYESYESYESYES
N4551455145514551
R20.20380.20470.20470.2048
F16,200.9516,20016,188.9516,222.56
Note: T-statistics are reported in parentheses; ***, ** and * denote significance at the 1%, 5% and 10% level, respectively.
Table 7. Using an alternative measure of EPU.
Table 7. Using an alternative measure of EPU.
Model 1Model 2Model 3Model 4
VariableCSRCSRCSRCSR
EPU2−0.022 ***(−8.56)−0.023 ***(−8.57)−0.022 ***(−8.58)−0.022 ***(−8.40)
ChairPC −0.023(−0.33)
ChairPC × EPU2 0.106 **(2.03)
CEOPC 0.001(0.01)
CEOPC × EPU2 0.130 ***(4. 42)
Slack × EPU2 0.180 **(2.37)
Slack−0.063(−0.97)1.426 **(1.99)1.465 **(2.04)1.249 *(1.73)
Age2.739 ***(13.90)−0.052(−0.79)−0.052(−0.80)−0.052(−0.76)
Size5.669 ***(3.32)2.843 ***(13.28)2.847 ***(13.32)2.840 ***(13.24)
ROA−0.011(−0.11)3.379(1.55)3.220(1.48)3.319(1.65)
MV12.696 **(2.06)0.000(0.00)0.007(0.07)0.005(−0.02)
IB−0.559 *(−1.74)10.884 *(1.76)11.095 *(1.79)11.048 *(1.81)
Dual0.087(0.83)−0.574 *(−1.78)−0.584 *(−1.79)−0.568 *(−1.79)
Board0.071(0.13)0.109(1.03)0.109(1.02)0.109(1.00)
SOE0.768(0.57)0.099(0.19)0.119(0.22)0.109(0.20)
HHI0.154(1.04)0.501(0.36)0.729(0.53)0.615(0.47)
Market−7.652(−1.20)0.146(0.98)0.153(1.02)0.147(1.00)
Cons−0.022 ***(−8.56)−7.802(−1.19)−8.326(−1.27)−8.828(−1.34)
YearYESYESYESYES
IndYESYESYESYES
N4551455145514551
R20.20340.20430.20440.2045
F1269.581274.201275.281276.68
Note: T-statistics are reported in parentheses; ***, ** and * denote significance at the 1%, 5% and 10% level, respectively.
Table 8. Using split samples.
Table 8. Using split samples.
Lower Resource SlackHigher Resource SlackWithout Political ConnectionWith Political Connection
VariablesCSRCSRCSRCSR
EPU−0.167 ***(−5.99)−0.088 ***(−3.59)−0.124 ***(−5.08)−0.114 ***(−3.91)
Slack8.704 ***(3.96)0.782(0.63)4.348 ***(4.04)0.166(0.12)
Age−0.190 ***(−3.65)0.019(0.44)−0.050(−1.17)−0.171 ***(−3.35)
Size4.630 ***(22.99)3.476 ***(15.67)4.199 ***(23.01)4.217 ***(17.57)
ROA−4.823(−0.91)8.989 *(1.89)1.296(0.32)2.150(0.34)
MV1.102 ***(3.37)0.065(0.42)0.167(1.04)1.002 ***(3.58)
IB10.544(0.97)−8.932(−0.73)3.600(0.33)15.139(1.26)
Dual−1.184 *(−1.74)−0.927 *(−1.73)−0.572(−1.03)−1.637 **(−2.45)
Board0.423 **(2.42)0.511 ***(2.73)0.416 **(2.50)0.221(1.15)
SOE1.251 **(2.27)−0.075(−0.15)0.887 *(1.86)−0.609(−1.06)
HHI7.248 ***(3.32)−2.553(−1.24)−1.464(−0.69)5.080 **(2.45)
Market0.741 ***(5.42)0.175(1.41)0.526 ***(4.46)0.598 ***(4.10)
Cons−45.896 ***(−6.20)−34.891 ***(−5.29)−45.623 ***(−7.49)−52.288 ***(−7.08)
IndYESYESYESYES
YearYESYESYESYES
N2287226428121739
R20.3640.2380.3040.341
F40.2920.4536.8025.98
Note: T-statistics are reported in parentheses; ***, ** and * denote significance at the 1%, 5% and 10% level, respectively.
Table 9. Using an alternative measure of CSR.
Table 9. Using an alternative measure of CSR.
Model 1Model 2Model 3
VariableHexun CSRTCSRICSR
EPU−0.051 ***(−32.58)−0.031 ***(−29.67)−0.020 ***(−30.00)
Age−0.058 *(−1.95)−0.098 ***(−4.67)0.036 ***(3.09)
Size2.541 ***(20.33)1.457 ***(16.92)1.029 ***(20.15)
ROA3.036 ***(6.82)2.118 ***(7.41)0.654 ***(3.35)
MV0.039 ***(2.92)0.022 **(2.56)0.016 ***(2.81)
IB16.180 **(2.30)7.397(1.58)8.729 ***(2.95)
Dual−0.061(−0.22)0.051(0.28)−0.115(−1.00)
Board−0.046(−0.42)0.028(0.38)−0.088 *(−1.92)
SOE−0.013(−0.04)−0.503 **(−2.03)0.471 ***(3.29)
HHI−1.189(−1.07)−0.640(−0.86)−0.221(−0.47)
Market0.652 ***(7.50)0.526 ***(8.59)0.110 ***(3.17)
Cons−23.963 ***(−7.82)−14.340 ***(−4.29)−13.418 ***(−10.73)
YearYESYESYES
IndYESYESYES
N19,59219,59219,592
R20.15070.14370.1143
F3553.833021.083550.67
Note: T-statistics are reported in parentheses; ***, ** and * denote significance at the 1%, 5% and 10% level, respectively.
Table 10. Effect of uncertainty on CSR by four policy categories.
Table 10. Effect of uncertainty on CSR by four policy categories.
Model 1Model 2Model 3Model 4
VariableCSRCSRCSRCSR
MPU−0.036 ***(−8.56)
XPU −0.049 ***(−8.56)
FPU −0.052 ***(−8.56)
TPU 0.018 *(0.856)
Age−0.063(−0.97)−0.063(−0.97)−0.063(−0.97)−0.063(−0.97)
Size2.739 ***(13.90)2.739 ***(13.90)2.739 ***(13.90)2.739 ***(13.90)
ROA5.669 ***(3.32)5.669 ***(3.32)5.669 ***(3.32)5.669 ***(3.32)
MV−0.011(−0.11)−0.011(−0.11)−0.011(−0.11)−0.011(−0.11)
IB12.696 **(2.06)12.696 **(2.06)12.696 **(2.06)12.696 **(2.06)
Dual−0.559 *(−1.74)−0.559 *(−1.74)−0.559 *(−1.74)−0.559 *(−1.74)
Board0.087(0.83)0.087(0.83)0.087(0.83)0.087(0.83)
SOE0.071(0.13)0.071(0.13)0.071(0.13)0.071(0.13)
HHI0.768(0.57)0.768(0.57)0.768(0.57)0.768(0.57)
Market0.154(1.04)0.154(1.04)0.154(1.04)0.154(1.04)
Cons−22.011 ***(−4.07)−21.086 ***(−3.86)−18.959 ***(−3.39)−32.405 ***(−6.54)
YearYESYESYESYES
IndYESYESYESYES
N4615461546154615
R20.20230.20230.20230.2023
F1280.121280.121280.121280.12
Note: MPU denotes monetary policy uncertainty; XPU is exchange rate policy uncertainty; FPU refers to fiscal policy uncertainty; TPU indicates trade policy uncertainty. T-statistics are reported in parentheses; ***, ** and * denote significance at the 1%, 5% and 10% level, respectively.
Table 11. The effect of EPU on CSR in each industry (with N > 30).
Table 11. The effect of EPU on CSR in each industry (with N > 30).
Industry CodeABCDEFGIKLNRS
VariableCSRCSRCSRCSRCSRCSRCSRCSRCSRCSRCSRCSRCSR
EPU−0.063−0.070−0.148 ***−0.234 **−0.560 ***−0.184 **−0.203 ***0.075−0.0940.509−0.243 *0.117−0.433
(−0.54)(−0.76)(−7.00)(−2.57)(−2.82)(−2.40)(−2.63)(0.88)(−0.25)(1.30)(−1.70)(0.38)(−1.42)
Slack1.1584.3202.148 **2.326−14.210−2.907−1.283−2.077−1.8626.967−11.61822.739 **−56.238 **
(0.24)(1.17)(2.47)(0.48)(−1.50)(−0.77)(−0.29)(−0.97)(−0.47)(0.42)(−1.01)(2.31)(−2.57)
Age0.382 **−0.328−0.048−0.593−0.724 **−0.2410.3300.681 **0.776 **2.019 ***−0.3570.021−0.812
(2.08)(−0.82)(−0.56)(−1.42)(−2.39)(−0.88)(1.16)(2.43)(2.20)(3.65)(−0.84)(0.04)(−0.86)
Size9.309 ***6.341 ***2.658 ***3.395 ***2.228 *2.655 ***6.460 ***2.172 **3.020 ***6.853 ***0.910−0.194−1.262
(6.19)(6.05)(9.60)(3.06)(1.78)(2.71)(4.24)(2.42)(3.20)(3.82)(0.82)(−0.04)(−0.30)
ROA61.094 ***−26.068 ***2.529−8.129123.519 **24.463 **27.59513.837 *15.508−28.8531.889−22.28399.187 *
(2.75)(−3.25)(0.92)(−0.41)(2.37)(2.25)(1.13)(1.74)(0.89)(−0.57)(0.02)(−1.12)(1.75)
MV1.3152.588 **−0.243 *1.2852.6271.827−0.850−0.347 *0.0971.978 *1.463−5.854 *3.474
(1.44)(2.36)(−1.80)(1.04)(0.96)(1.62)(−0.47)(−1.75)(0.12)(1.66)(0.57)(−1.72)(1.16)
IB112.7555.213−2.24018.50413.31646.71826.8436.29520.354−215.403 ***96.84350.31836.949
(0.94)(0.16)(−0.30)(0.81)(0.35)(1.46)(0.91)(0.18)(0.82)(−2.91)(1.24)(0.44)(0.28)
Dual1.403−0.387−0.113−1.456−1.7360.171−1.6740.120−3.565 ***4.316−0.5220.4063.116
(0.55)(−0.24)(−0.30)(−0.90)(−0.72)(0.10)(−0.71)(0.08)(−3.19)(1.50)(−0.09)(0.04)(0.78)
Board−1.5020.844 *0.029−0.335−0.9140.5850.1870.284−0.4842.713 **−2.3370.776−1.479
(−0.98)(1.76)(0.21)(−0.83)(−1.06)(1.11)(0.41)(0.56)(−1.29)(2.08)(−1.38)(0.45)(−1.00)
SOE7.884 ***2.450−0.189−1.3668.167 **−1.161−2.9810.5094.387−5.016−2.628−4.503−1.021
(2.88)(0.56)(−0.30)(−0.25)(2.04)(−0.50)(−0.45)(0.28)(1.31)(−1.21)(−0.86)(−0.90)(−0.26)
HHI−7.264−8.018−0.503−12.78924.04773.187 *−2.9302.496−294.160−0.8195.533−16.42526.255
(−0.49)(−1.50)(−0.16)(−1.31)(1.53)(1.93)(−0.44)(0.86)(−0.32)(−0.03)(0.43)(−0.34)(0.21)
Market−2.612 ***0.5910.109−0.7651.6440.050−0.715−1.318 *0.6926.117 **−2.199 *1.9113.059 **
(−2.74)(0.96)(0.61)(−1.04)(1.17)(0.06)(−0.87)(−1.67)(1.02)(2.37)(−1.75)(0.86)(2.38)
Cons−159.071 ***−103.052 ***2.62621.44332.053−12.233−82.791 **−30.930−29.568−279.810 ***71.067 *28.01240.430
(−3.53)(−3.01)(0.33)(0.65)(0.67)(−0.42)(−1.99)(−0.99)(−0.25)(−5.28)(1.72)(0.21)(0.28)
N65228255925316223328020928741335938
Number of firms1137470432946454847109208
Firm FEYESYESYESYESYESYESYESYESYESYESYESYESYES
Year FEYESYESYESYESYESYESYESYESYESYESYESYESYES
R20.14350.13680.23440.26560.36780.29190.34360.43740.30220.18060.52070.38210.5096
Note: T statistics in parentheses; *** p < 0.01, ** p < 0.05, * p < 0.1; Description of industry codes: A—agriculture, forestry, animal husbandry and fisheries; B—mining; C—manufacturing; D—electricity, heat, gas and water production and supply; E—construction; F—wholesale and retail trade; G—transport, storage and postal services; I—information transmission, software and information technology services; K—real estate; L—rental and business services; N—water conservancy, environment and public facility management; R—culture, sports and recreation; S—public administration, social security and utilities.
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Zou, H.; Wang, R.; Qi, G. The Response of CSR to Economic Policy Uncertainty: Evidence from China. Sustainability 2023, 15, 12978. https://0-doi-org.brum.beds.ac.uk/10.3390/su151712978

AMA Style

Zou H, Wang R, Qi G. The Response of CSR to Economic Policy Uncertainty: Evidence from China. Sustainability. 2023; 15(17):12978. https://0-doi-org.brum.beds.ac.uk/10.3390/su151712978

Chicago/Turabian Style

Zou, Hailiang, Ruijing Wang, and Guoyou Qi. 2023. "The Response of CSR to Economic Policy Uncertainty: Evidence from China" Sustainability 15, no. 17: 12978. https://0-doi-org.brum.beds.ac.uk/10.3390/su151712978

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