Economic Policy Uncertainty and Firm ESG Performance

Abstract

Against the background of the impact of multiple uncertain events, such as COVID-19, the Russia–Ukraine conflict, and China–US trade frictions, it is of great strategic significance for enterprises to achieve their own sustainable development by improving ESG (environmental, social, and internal governance) performance. Using the data of Chinese A-share listed companies from 2011 to 2020, this paper empirically explores the effect of economic policy uncertainty (EPU) on corporate ESG performance. We obtain the following results: (1) EPU can promote firms to enhance ESG performance, and in each sub-item of ESG performance, EPU has the strongest promotion effect on corporations’ environmental performance (E), followed by social responsibility performance (S), while EPU has a relatively weak promotion effect on internal governance performance (G). (2) The mechanism test results show that EPU will exacerbate the credit risk of enterprises and then promote the improvement of enterprises’ ESG performance. (3) The grouping test results show that EPU has a stronger promotion effect on the ESG performance of state-owned enterprises, high-carbon industries, low regional marketization level, and enterprises with strong regional government intervention. Against the realistic background of the frequent adjustment of economic policies, the research results provide empirical evidence for guiding enterprises to strengthen the construction of ESG systems.

1. Introduction

In the past few years, due to multiple events such as the COVID-19 pandemic, the Russia–Ukraine conflict, nuclear leakage, and China–US trade frictions, uncertainty has become an important factor affecting global economic development [1]. According to the research of Baker et al. (2016) [2], the economic policy uncertainty (EPU) of China has been high since 2012. Moreover, in response to global climate change, the world’s major economies have introduced timetables for carbon peak and carbon neutrality. In the context of intensified uncertainty and climate change conflicts, investments focusing on environment, social, and governance have gradually become an important trend in the development of China’s capital market, being favored by global investors [3]. As an investment concept and enterprise evaluation standard that focuses on non-financial performance, external investors can observe the ESG performance of target enterprises, evaluate their achievements and contributions in fulfilling social responsibilities and promoting sustainable economic development, and then judge the value attributes of individual investment behaviors [3]. Promoting ESG investment is an important method and strong guarantee for achieving the dual carbon goal. The 20th National Congress of the Communist Party of China demand to build a modern socialist country in an all-round way, where promoting green development and the harmonious coexistence between man and nature is very crucial. It can be seen that ESG investment will be a key topic of academic, industry, and government departments in the future.

EPU caused by the superposition of many uncertain factors has a huge impact on market investment and consumption, prompting enterprises and external investors to pay their attention to the high-quality development model instead of the traditional economic growth model [4]. The value concept represented by ESG investment, which comprehensively considers environmental factors, social factors, and corporate governance factors, can be integrated with macroeconomic development and national strategic arrangements [5]. Therefore, does economic policy uncertainty affect corporate ESG performance? What is the way and mechanism of influence? What are the effects of enterprises with different property rights and different carbon emission intensities?

Faced with the above questions, we choose panel data of listed enterprises in China from 2011 to 2020 and empirically test how EPU affects enterprises’ ESG performance. We can see that EPU can contribute to improving ESG performance. Secondly, considering that the decision of ESG investment is influenced by credit risk, we select credit risk as the mediating variable to test the mechanism; the results suggest that EPU will aggravate the firms’ credit risk, thus promoting the improvement of ESG performance. Finally, according to the heterogeneity of property rights, carbon emissions, the degree of marketization, and the degree of government intervention, exploring the differential influence of EPU on ESG performance is important. The research results are useful to understand how to effectively improve the ESG performance in the context of EPU, aiming to promote the development of enterprises, and also to further promote the organic combination of ESG investment and “dual carbon” for the realization of the dual carbon goals.

The remaining structure of this paper is as follows: The Section 2 presents the literature review. Section 3 presents the theoretical mechanism analysis of EPU affecting ESG performance and research hypotheses. The construction econometric model and the choice of variables and data are in Section 4. We analyze the empirical results in Section 5. The conclusions and suggestions are all displayed in Section 6.

2. Literature Review

2.1. Economic Consequences of EPU

EPU refers to the inability of economic agents to accurately judge the time, content, and potential impact of policies issued by government agencies, which makes it difficult to form stable policy expectations. The economic consequences of economic policy uncertainty include macro and micro levels. From the macro perspective, EPU is the main factor that induces macroeconomic fluctuations, which has a negative effect on the economic contribution of policy-sensitive industries [2], and which will cause an increase in product cost and labor cost. This will lead to an increase in the unemployment rate and the deterioration of business environment [6]. From a micro perspective, Wang et al. (2019) [7] believed that when EPU rises, the violation risk of enterprises also rises, which will raise the external financing threshold and further damage the financial environment, which will then reduce the credit scale. Yu et al. (2019) [8] showed that, based on the precautionary saving motive, enterprises will increase the scale of cash holdings to resist risks so as to balance the impact of EPU on business activities.

In addition, based on the real option theory, many scholars believe that EPU will inhibit the investment behavior of enterprises [9,10]. Moreover, EPU will also inhibit corporate investment through the financial friction effect [11], and EPU has a more obvious inhibitory effect on enterprise investment because of information asymmetry [12], the imbalance between capital supply and demand [13], systemic risk [14], investment peer effect [15], and other influences.

2.2. Enterprise ESG Performance

So far, many scholars’ studies on ESG performance have mainly focused on the microeconomic consequences of ESG, including the impact of ESG performance on debt financing [16], the risk of stock price crash [17], enterprise value [18], financial performance [19], and so on, but no consensus has been reached. On the one hand, actively improving ESG performance is conducive to sending positive signals to the outside world, attracting the attention of external investors, and reducing financing constraints and operational risks so as to take advantage of its value enhancement effect [20]. On the other hand, due to the scarcity of resources, it is easy for enterprises to use too many resources to undertake external environmental responsibilities, social responsibilities, and other activities in order to crowd out the main business input, thus reducing the core competitiveness of enterprises [21].

In addition, few scholars have discussed the driving factors for the improvement of enterprise ESG performance. Existing studies believe that factors such as the board’s ability to obtain external resources [22] and the establishment of social responsibility organizations [23] will promote ESG performance improvement. Moreover, when an enterprise belongs to a sensitive or heavily polluting industry, it has a stronger willingness to improve ESG performance [24]. In addition, government debt will inhibit enterprises’ ESG performance [25], while party organization governance will improve enterprises’ ESG performance [26].

3. Theoretical Analysis and Research Hypothesis

3.1. EPU and Corporate ESG Performance

EPU reflects the uncertainty regarding the timing, content, and potential impact of economic policies. When the EPU value is large, evaluating or predicting the future economic policy accurately for market players is challenging, so they have a negative attitude towards the economic prospect, which allows investors to react to the effects of uncertainty by deferring investment and saving on a precautionary basis. The consequences of EPU influencing the macro economy through the real option effect and precautionary savings or other factors have been verified in many studies [4]. When EPU based on the macro level rises, external investors will generally adopt the following two practices: first, take a wait-and-see attitude towards future investments until the impact of uncertainty on enterprise development is reduced or disappeared; and the second is to increase savings to deal with the economic consequences caused by future uncertainty. The above two mechanisms affect the strategic formulation and operation decisions of enterprises to some degree. In order to be rid of this dilemma, enterprises usually disclose more information to increase the information symmetry so as to eliminate the concerns of external investors about the future survival of enterprises and relieve the pressure of external financing [27]. Information including environment protection, social responsibility, and corporate governance can be comprehensively included in enterprises’ ESG performance. ESG performance information disclosed by a third party can effectively improve the information transparency of enterprises, which helps external investors to comprehensively understand the development status of enterprises and enhances investors’ trust in enterprises to implement investment strategies, making enterprises better achieve sustainable development in the uncertain environment of economic policies.

According to the stakeholder theory, enterprises improve ESG performance and maintain their external image by improving environmental performance, actively participating in social responsibility activities and strengthening corporate governance [28], and can obtain more responsible investment with accumulated reputation, which enhances the stability and sustainability of enterprises’ development under the uncertainty of economic policies. From an environmental and social perspective, the public and the government are both stakeholders. When economic policy uncertainty is high, enterprises often choose investment methods that are conducive to improving environmental and social benefits for obtaining the support of external stakeholders, such as increasing environmental protection investments and socially responsible investments. The measure will make consumers’ recognition of enterprises’ products rise and the government’s attitude towards enterprises change. This move could ease the market pressure on companies at a time of economic policy uncertainty and accelerate a turnaround in stock performance and sales. In conclusion, when EPU is high, improving ESG performance is helpful to achieve sustainable development in such a predicament. According to the analysis, we proposed Hypothesis 1:

Hypothesis 1: 

The increase in economic policy uncertainty will promote the improvement of enterprise ESG performance.

3.2. EPU, Firm Credit Risk, and Firm ESG Performance

For enterprises, the increase in EPU significantly leads to the risk of corporate cash flow [29], which leads to an increase in corporate financing costs and financing difficulties and exacerbates the credit risks of enterprises. At the same time, economic policy uncertainty will also impact market demand, cause turbulence in the capital market, and cause a decline in external investment, resulting in serious operational and capital problems and an increased credit risks for enterprises. The long-term high credit risk of enterprises will increase the probability of bankruptcy. In order to achieve sustainable operation, strategies to improve ESG performance will be selected, which makes enterprises increase their investments in corporate governance, corporate social responsibility, and environmental responsibility, presenting a good image to the outside world and gaining favor from investors.

For financing institutions, EPU leads to a risk of bad debts with financing institutions. For the consideration of capital recoverability, financial institutions are more willing to flow funds into corporations with complete information disclosure and stable business performance, rather than with credit risks. Based on the selection effect of financial institutions, enterprises will prefer providing better information disclosure and deny credit risks. It has been proven that enterprises’ environmental protection and social responsibility can reduce the probability of debt default and promote enterprises to improve their credit ratings [30]. Therefore, by improving ESG performance from the perspective of environment, society, and governance, enterprises can not only effectively be rid of the credit risk crisis, but also obtain ESG risk premium and excess returns when the environment is uncertain [31]. In summary, policies of EPU will result in the increasing credit risks, which will make increase enterprises’ information disclosure, thus improving ESG performance. It can be seen that economic policy uncertainty promotes ESG performance through credit risks. According to these discussions, the following hypothesis is proposed:

Hypothesis 2: 

EPU increases corporate credit risk and further promotes increasing enterprises’ ESG performance.

3.3. EPU, Heterogeneity, and Enterprise ESG Performance

The impact of EPU is different with corporations who have different property rights. Differently from non-SOEs, SOEs have a natural “political bond”, and most of the managing roles of SOEs hold corresponding administrative positions [32]. When EPU is high, SOEs are more inclined to use their own advantages to disclose more information to reflect the country’s economic policy orientation. The business activities of SOEs not only take the pursuit of interests as an important goal, but also undertake the important task of performing social functions and realizing public expectations, meaning that the government exerts more regulations and constraints on SOEs [33]. With the rise of EPU, SOE enterprises need to actively disclose relevant information according to the government’s guidance and to assist the government to serve the public and other small and medium-sized enterprises in being rid of difficulties. In contrast, the main goal of non-SOEs is to maximize corporate interests and value, and the awareness of undertaking environmental protection and social responsibility is relatively weak. In the uncertain environment of economic policy, maintaining the status quo can reduce the cost of reform. At the same time, the management will weigh the costs and benefits of information disclosure and will lack the initiative to disclose information such as environmental protection and social responsibility [34]. Therefore, in comparison with non-SOEs, when EPU rises, SOEs are willing to take the initiative to take responsibility, and the promotion effect is more obvious.

Hypothesis 3: 

In comparison with non-SOEs, the effect of EPU on ESG performance will be obvious.

A dual-carbon target is a prerequisite to explore the impact of EPU on enterprise ESG performance. ESG investment is an important guarantee to achieve the dual carbon goal, but the effect is different among different industries, especially high-carbon industries. On the one hand, in the process of implementing the dual carbon target, many economic policy uncertainties exist, which aggravate the transformation and sustainable development crisis of high-carbon enterprises. As a field with a high pollution degree in China, high-carbon industries need to shoulder more social responsibility and carbon emission reduction pressure [35]. Under the supervision of the government, the public, and other stakeholders, high-carbon industries will strengthen environmental awareness and social responsibility awareness for sustainable development. On the other hand, the field classical economics believes that external environmental regulation will increase the operating costs of enterprises, and the disclosure of environmental information and the preparation of social responsibility reports will increase the additional costs of enterprises. If the enterprise does not disclose information, it will lead to an increase in financing costs and will even affect the value of the enterprise. Therefore, high-carbon enterprises will choose to disclose more ESG information to enhance the confidence of external investors and attract more funds for their own transformation and sustainable development. According to the analysis, we presented the following hypothesis:

Hypothesis 4: 

Compared with low-carbon industries, EPU has a stronger promotion result on the improvement of ESG performance in high-carbon industries.

There is a remarkable characteristic of unbalanced development in China’s regional economy, and the level of marketization in the region is an important embodiment of the economic development level. As the basic means of resource allocation, the market can solve the problem of information asymmetry to some degree, which indicates that the level of regional marketization has a positive correlation with the information transmission effect, which contributes to reducing the behavior of market forces hiding information [36]. Moreover, based on the real option theory, market forces have the same investment opportunities in the market with symmetric information, which leads to the fact that the option value obtained by waiting for the investment opportunity cannot compensate for the opportunity cost generated by postponing the investment. Therefore, the investment decisions taken by firms are no longer changed by market information. Under the impact of EPU on the market investment environment, the higher the level of marketization in the region, the smaller the effect of information disclosure, which results in the positive signals transmitted by the improvement of ESG not working. Therefore, the original investor wait-and-see attitude will not change much. Therefore, the research hypothesis is proposed as follows:

Hypothesis 5: 

The promotion of EPU on ESG performance will be weakened because of the regional marketization level.

Regional government intervention will also affect the relationship between EPU and ESG performance. When an enterprise is in an environment with strong government intervention, the confidence of the enterprise facing with risks will be improved, the adverse impact of EPU will decline, which urge the enterprise to carry out more public welfare activities for protecting the environment and undertaking social responsibilities. But excessive government intervention will produce crowding-out effect and weaken corporate governance capacity, which results to the management and control rights of enterprises cannot play an effective role [37]. So, when EPU increases, enterprises are subject to increase ESG performance in order to obtain more political resources to relieve the influence brought by EPU. Based on the above analysis, in the institutional environment with strong regional government intervention, enterprises improve ESG performance by actively undertaking environmental protection and social responsibility to cope with the impact of economic policy uncertainty. Therefore, the research hypothesis is put forward:

Hypothesis 6: 

Regional government intervention can contribute to the effect of EPU on ESG performance.

In conclusion, the analysis framework of the impact mechanism and heterogeneity of EPU on enterprise ESG performance is seen in Figure 1.

4. Methodology

4.1. Model Construction

Aiming to investigate the impact of EPU on ESG performance, we follow Zhang et al. (2023) [38] in order to construct the following econometric model:

$${ESG}_{i,t}={\beta }_0+{\beta }_1{EPU}_{i,t}+\gamma Controls+{\lambda }_i+{\mu }_t+{\epsilon }_{i,t}$$

(1)

$$\left\{\begin{array}{l}{E}_{i,t}\\ S_{i,t}\\ G_{i,t}\end{array}\right.={\beta }_0+{\beta }_1{EPU}_{i,t}+\gamma Controls+{\lambda }_i+{\mu }_t+{\epsilon }_{i,t}$$

(2)

Hypothesis 1 will be verified by Model (1), and the explained variables of Model (2) are the three sub-segments of ESG—E, S, and G performance. The controls are a series of control variables at the enterprise level, which control both industry fixed effects (λ) and year fixed effects (μ). The sign and significance of coefficient β1 can reflect the impact of economic policy uncertainty on ESG performance and its three sub-items, which is the focus of this paper.

Aiming to verify the mediating effect of credit risk, regression models (3) and (4) are constructed as follows:

$$Z_{i,t}={\beta }_0+{\beta }_1{EPU}_{i,t}+\gamma Controls+{\lambda }_i+{\mu }_t+{\epsilon }_{i,t}$$

(3)

$$\left\{\begin{array}{c}{ESG}_{i,t}\\ E_{i,t}\\ S_{i,t}\\ G_{i,t}\end{array}\right.={\beta }_0+{\beta }_1{EPU}_{i,t}+{\beta }_2{Z}_{i,t}+\gamma Controls+{\lambda }_i+{\mu }_t+{\epsilon }_{i,t}$$

(4)

Among them, Z is the mediating variable in this paper, and, according to the mediating effect test procedure, we need to focus on the symbol and significance of β1 in Model (3) and Model (4) and of β2 in Model (4).

4.2. Variable Description

4.2.1. Explained Variable

Enterprise ESG performance. ESG emphasizes environmental management, social responsibility, and internal corporate governance. Currently, the ESG performance has been noticed by the government and by society in China. So, there are many institutions measuring the ESG index of Chinese listed companies; for example, Bloomberg and WIND. A multi-dimensional index system and third-party agency ratings are mainly used to evaluate the companies’ ESG performance. After comparing the rating agency system, this paper chooses Bloomberg ESG data with mature development and complete disclosure information, which provides corresponding ratings from three terms, namely environment, social responsibility, and internal governance. To ensure the accuracy of the consequences, all scores are processed in natural logarithms.

4.2.2. Core Explanatory Variable

Economic policy uncertainty (EPU). Based on the index of China’s EPU, constructed by Baker et al. (2016) [2], the monthly arithmetic weighted average is divided by 100 to obtain the EPU data of the corresponding year.

4.2.3. Mediating Variable

Credit risk (Z-score). Referring to the practice of Zhang and Zhao (2022) [39], we use the Z-score model constructed by financial data to measure corporate credit risk. The calculation formula is as follows:

$$Z=1.2\frac{\mathrm{Woring} \mathrm{capital}}{\mathrm{Total} \mathrm{Assets}}+1.4\frac{\mathrm{Retained} \mathrm{earnings}}{\mathrm{Total} \mathrm{Assets}}+3.3\frac{\mathit{EBIT}}{\mathrm{Total} \mathrm{Assets}}+0.6\frac{\mathrm{Enquity} \mathrm{market} \mathrm{value}}{\mathrm{Book} \mathrm{value} \mathrm{of} \mathrm{total} \mathrm{liabilities}}+0.999\frac{\mathrm{Business} \mathrm{income}}{\mathrm{Total} \mathrm{Assets}}$$

4.2.4. Control Variable

With reference to others’ studies, we choose the company’s operation and management and financial status and six indicators, including the proportion of independent directors, tangible assets ratio, the return on equity, ownership concentration, the operating income growth rate, and cash flow ratio, as control variables. At the same time, the fixed effects of year and industry are controlled.

Table 1. Indicator system of variables.

Property of Variable	Variable Name	Symbol of Variables	Definition of Variables	Source of Data
Explained variables	ESG Performance	ESG	Ln (Total Enterprise ESG Rating Score)	Bloomberg
	Environmental Performance	E	Ln (Enterprise ESG rating environment score)
	Social Responsibility Performance	S	Ln (Enterprise ESG rating social responsibility score)
	Corporate Governance Performance	G	Ln (Enterprise ESG rating corporate governance score)
Core explanatory variable	Economic Policy Uncertainty	EPU	The monthly arithmetic weighted average is divided by 100	The index constructed by Baker et al.
Mediating variable	Credit Risk	Z-score	Calculated by Z-score model	WIND database
Control variables	Proportion of Independent Directors	Indep	Number of independent directors/directors	WIND database
	Tangible Assets Ratio	Ratio	Total tangible assets/total assets
	Return on equity	Roe	Net profit/average shareholders’ equity
	Concentration of ownership	Top	Number of shares held by top five shareholders/total number of shares
	Operating income growth rate	Growth	(Current year’s operating income—last year’s operating income)/last year’s operating income
	Cash flow ratio	Cash	Net cash flow from operating activities/total assets

includes the specific variable meanings.

4.3. Data Source

In 2010, China’s Ministry of Finance, China Securities Regulatory Commission, China National Audit Office, and other departments jointly issued “Guidelines on the Application of Corporate Internal Control—Social Responsibility”, emphasizing that enterprises should actively fulfill their social responsibilities and obligations, and requiring the public disclosure of their performance of social responsibilities. So, we choose the years from 2011 to 2020 as the sample interval. China’s listed A-share enterprises are used as research samples in the following processes: (1) firstly, according to “Guidelines on Industry Classification of Listed Companies (2012 Revision)”, exclude the listed companies in the financial industry; (2) secondly, eliminate the companies whose categories are ST and PT; (3) thirdly, remove the companies that own abnormal or missing data; and (4) aiming to exclude the impact of extreme values, deal with all data with a shrinking treatment with 1% quartiles. Finally, we obtain 4550 observed values.

5. Empirical Results and Discussion

5.1. Descriptive Statistics

The descriptive result is displayed in

Table 2. Descriptive statistics.

Variable	Mean	P50	SD	Min	Max
ESG	3.102	3.067	0.269	0.215	4.106
E	2.275	2.238	0.652	0.439	4.022
S	3.212	3.127	0.355	1.255	4.346
G	3.820	3.838	0.128	1.273	4.163
Z-core	4.068	2.365	6.739	−1.646	160.855
EPU	3.563	3.041	2.334	1.139	7.918
Indep	0.377	0.364	0.058	0.3	0.6
Ratio	0.931	0.959	0.096	0.206	1
Roe	0.092	0.087	0.096	−0.982	0.396
Top	0.553	0.553	0.163	0.161	0.892
Growth	0.128	0.093	0.302	−0.659	4.330
Cash	0.059	0.057	0.064	−0.0200	0.257

. The mean value of ESG performance is 3.102, and the difference between the min value of 0.215 and the max value of 4.106 is greater than the mean and median, which indicates that the gap between different enterprises is relatively wide, suggesting that some enterprises do not pay attention to ESG. In the ESG sub-item, the difference between the max value and the min value of the environmental rating (E) is 3.583, with a high standard deviation, representing that the environmental performance of different firms is uneven, while the distribution of social responsibility (S) and corporate governance (G) is similar, with a low standard deviation. The mean value of EPU is 3.563 and the standard deviation is 2.334, indicating that the economic policy changes are large and that enterprises need to constantly adapt to external changes to seek development. The maximum value of the Z-score is 160.855, which is different by 162.5 from the min value, the mean value is 4.068, the median is 2.365, and the standard deviation is greater than the mean, showing that more than 50% of enterprises have certain credit risks and that the variation range of enterprise credit risks is obvious. Among the control variables, the standard deviation of the growth rate of the operating income is higher than the mean, indicating that the indicator in different enterprises is very different and that there may be industry heterogeneity. The dispersion degree and difference degree of other control variables are reasonable and will not be elaborated on.

Figure 2 depicts the trend in the EPU index and the distribution of enterprises’ ESG scores. It can be clearly seen from this Figure that the EPU index shows a significant upward trend, which is consistent with the changing trend in the enterprise ESG score. Hypothesis 1 is intuitively verified, and the benchmark regression model will be used to empirically test the relationship between EPU and ESG.

5.2. Results of Statistical Tests

5.2.1. Results of Baseline Regression

The results in columns (1)–(4) of

Table 3. Baseline regression results.

Variable	(1) ESG	(2) E	(3) S	(4) G
EPU	0.0269 *** (27.76)	0.0529 *** (22.61)	0.0226 *** (16.84)	0.0075 *** (14.93)
Indep	0.0955 (1.45)	0.1744 (1.08)	0.0854 (0.94)	−0.0838 ** (−2.32)
Ratio	−0.134 ** (−2.17)	−0.4899 *** (−3.27)	−0.0942 ** (−2.13)	−0.0032 (−0.16)
Roe	−0.0400 (−0.92)	−0.2588 ** (−2.41)	−0.0474 (−1.06)	−0.0197 (−0.93)
Top	0.0392 *** (15.14)	0.0436 *** (13.74)	0.2993 *** (9.27)	0.1524 *** (6.67)
Growth	−0.0184 (−1.42)	−0.0181 (−0.57)	−0.0095 (−0.54)	−0.0197 *** (−3.11)
Cash	0.1524 ** (2.42)	0.7424 *** (4.79)	0.0651 (0.76)	−0.0719 ** (−2.33)
_CONS	3.115 *** (47.06)	2.649 *** (16.57)	3.2292 *** (35.20)	3.696 *** (101.43)
IND/YEAR	Control	Control	Control	Control
R2	0.166	0.120	0.202	0.106
N	4550	4550	4550	4550

Legend: ** p < 0.05; *** p < 0.01.

sequentially report the impact of EPU on ESG performance and its three sub-items, E, S, and G performance, after controlling the main factors affecting ESG performance. Among them, the R² is small, but it is consistent with the research’ results who study economic policy uncertainty [40,41,42]. The regression results in Column (1) report the overall impact of EPU on enterprise ESG, and the coefficient of the EPU index is 0.0269, which is significant at the statistical level of 1%, indicating that with the increase in economic policy uncertainty, enterprise ESG performance improves accordingly. That is, when there is uncertainty in the external macroeconomic environment, they will concentrate on environmental, social, and governance performance and promote their sustainable development by protecting the environment, assuming social responsibilities, and strengthening corporate governance. The regression results in Columns (2)–(4) report the impact of EPU on corporate environmental (E), social (S), and governance (G) performance, respectively. The coefficients are 0.0529, 0.0226, and 0.0079, respectively. Comparing the coefficient size, we can see that the impact of EPU on corporate E, S, and G decreases in turn. That is, when external economic policy uncertainty is high, enterprises are inclined to focus on environmental protection, followed by social responsibility, and finally corporate internal governance. This is basically consistent with economic intuition; that is, when enterprises are aware of high external uncertainty, they will first focus on improving environmental performance and assume the responsibility of environmental protection in order to seek sustainable development. Secondly, they focus on social responsibility performance through undertaking social responsibility to improve the corporate image. Finally, they will enhance their own governance level through internal governance.

Considering the influence of control variables on the regression results of Columns (1)–(4), asset tangibility, ownership concentration, and cash flow ratio are significantly correlated with ESG performance, indicating that the stability of capital flow and ownership structure concentration will have a positive impact on ESG performance. But, high asset tangibility inhibits the improvement of ESG performance. The stability of capital flow provides financial support and the concentration on ownership structure provides decision-making that guarantees the improvement of ESG performance. In contrast, asset tangibility inhibits corporate ESG performance. Through the above regression analysis, Hypothesis 1 is verified, which indicates that EPU has a positive effect in helping enterprise ESG performance.

5.2.2. Results of Robustness Test

Considering endogeneity problems in the model, the influence of the measurement methods of key variables, and the lag effect on the reliability of conclusions, this paper conducts robustness test using the following methods.

(1) Endogenous treatment. As for the possible omitted variables in the models, we choose the main control variables from the aspects of enterprise individual differences, operation and management, financial status, and so on, and add industry fixed effects and year fixed effects to eliminate the effect. However, the increase in the ESG practices of enterprises may prompt government agencies to introduce more biased economic policies, thus causing fluctuations in economic policies. Therefore, the instrumental variable method is used to test the potential endogeneity problem. As one of China’s most important trading partners, American EPU is closely related to Chinese EPU. Therefore, we use the two-month lagged USEPU index as the instrumental variable [43], transform monthly data into annual data, and use the 2SLS method to conduct the endogeneity test. The consequence is shown in

Table 4. Test for endogeneity.

Variable	(1)	(2)	(3)	(4)	(5)
	The First Period EPU	The Second Period ESG	The Second Period E	The Second Period S	The Second Period G
USAEPUt-2	2.8259 *** (73.78)
EPU		0.2319 *** (16.78)	0.0459 *** (13.14)	0.0178 *** (5.99)	0.0074 *** (8.29)
Control variables	Control	Control	Control	Control	Control
IND/YEAR	Control	Control	Control	Control	Control
F-TSET	5443.85 ***	47.38 ***	31.26 ***	19.77 ***	32.86 ***
Anderson–Rubin Wald test	286.48 ***
Kleibergen–Paap rk LM statistic	1000.68 ***

Legend: *** p < 0.01.

. Column (1) shows that USAEPU and EPU are significantly positively correlated at the level of 1%, and the F value in the first stage is greater than 10, indicating that USEPU is closely correlated to EPU, which is in line with the correlation hypothesis of instrumental variables. The A-R test is significant at the level of 1%, and the K-P LM statistic is significant at the level of 1%, which indicates that there is no weak instrumental variable or insufficient identification in the model and that the selected instrumental variable is helpful. In the second stage of the test results, the EPU coefficients in Columns (2)–(5) are significantly positively correlated at the level of 1%, and the size and sign of the coefficients of the subsamples are consistent with the results in Table 3.

(2) Changing the treatment method of explanatory variables. The original monthly arithmetic weighted average treatment was changed to a monthly geometric weighted average to calculate the annual EPU. EPU calculated by the above method is regressed with enterprise ESG performance, and the results are displayed in Columns (1)–(4) of

Table 5. Results of the robustness test.

Variable	(1) ESG	(2) E	(3) S	(4) G	(5) Hua Zheng ESG	(6) ESG (T + 1)	(7) E (T + 1)	(8) S (T + 1)	(9) G (T + 1)
Changed EPU	0.6793 *** (23.00)	1.3163 *** (18.58)	0.5349 *** (13.24)	0.2752 *** (17.53)
EPU					0.3867 *** (7.83)	0.0268 *** (27.76)	0.0529 *** (19.20)	0.0202 *** (13.88)	0.0077 *** (12.32)
Control variables	Control	Control	Control	Control	Control	Control	Control	Control	Control
_CONS	2.4485 *** (31.50)	1.3641 *** (7.32)	2.7157 *** (25.55)	3.4016 *** (82.37)	3.4215 *** (10.12)	3.1153 *** (47.06)	2.7118 *** (16.19)	3.2292 *** (36.47)	3.7845 *** (99.75)
IND/YEAR	Control	Control	Control	Control	Control	Control	Control	Control	Control
R2	0.173	0.137	0.097	0.128	0.103	0.166	0.104	0.094	0.097
N	4550	4550	4550	4550	4550	3900	3900	3900	3900

Legend: *** p < 0.01.

. The results are basically in accordance with the consequences of the above benchmark regression, and the regression coefficients of the sub-items E, S, and G of ESG performance are also basically the same, which further verifies the robustness of the results in the benchmark regression model; that is, EPU improves ESG performance.

(3) Replacing key explained variables. The ESG rating of China Securities is used as the proxy variable of the explained variable. Different from the Bloomberg ESG rating, the ESG rating of enterprises is rated according to nine grades, including AAA, AA, A, BBB, BB, B, CCC, CC, and C. For the convenience of research, the ESG rating of China Securities is assigned a value of 1–9, such as AAA = 9, and so on. Limited to the lack of separate ratings for E, S, and G in China Securities’ ESG, this paper focuses on the regression of ESG. The outcomes are shown in Column (5) of Table 5, and when other variables are controlled, the coefficient of EPU is still significantly positive, which again verifies the robustness of the benchmark regression.

(4) Explained variables lagged one period. ESG investment decisions taken by enterprise management based on external economic policy uncertainty are not short-term behaviors, and the impact of EPU on ESG performance may not emerge quickly, meaning that the time lag should be considered. After referring to the method of Guo and Sun (2021) [44], the lagged term of ESG is used as the explained variable, and the results can be seen in Columns (6)–(9) of Table 5.

5.2.3. Mediating Effect Test

In the theoretical analysis section, this paper expounds that the rise of EPU easily aggravates corporate credit risk, forcing enterprises to take the initiative to enhance ESG performance, aiming to weaken the inhibition of credit risk by improving the environment, assuming social responsibility and strengthening corporate internal governance. For the sake of verifying this mechanism, on the basis of the benchmark regression, the mediating effect regression model is used to examine the relationship between variables.

Table 6. Regression results of mediating effect.

Variable	(1) Z-Score	(2) ESG	(3) E	(4) S	(5) G
EPU	−0.1617 *** (−3.84)	0.0262 *** (16.13)	0.0518 *** (12.79)	0.0195 *** (10.28)	0.0071 *** (9.07)
Z-score		−0.0036 *** (−6.66)	−0.0067 *** (−4.75)	−0.0196 ** (−2.49)	−0.0028 *** (−9.88)
Indep	3.1075 * (1.83)	0.1073 (1.63)	0.1952 (1.21)	0.0754 (0.84)	0.0176 (0.55)
Ratio	1.4924 (1.46)	−0.0099 (−0.25)	0.1062 (1.09)	−0.1126 ** (−2.08)	0.0009 (0.05)
Roe	9.6216 *** (8.55)	−0.0033 (−0.08)	−0.1942 * (−1.80)	0.0643 (1.07)	0.0067 (0.32)
Top	0.3453 *** (14.62)	0.3453 *** (14.62)	0.7763 *** (13.34)	0.2927 *** (9.04)	0.1376 *** (11.97)
Growth	−0.0206 (−1.60)	−0.0206 (−1.60)	−0.0220 (−0.69)	−0.0107 (−0.60)	−0.0213 *** (−3.40)
Cash	0.2118 *** (3.34)	0.2118 *** (3.34)	0.8469 *** (5.43)	0.0956 (1.10)	−0.0291 (−0.94)
_CONS	2.792 *** (60.46)	2.7927 *** (60.46)	1.4895 *** (13.09)	3.0433 *** (48.09)	3.7267 *** (165.85)
IND/YEAR	Control	Control	Control	Control	Control
R2	0.106	0.165	0.138	0.096	0.125
N	4550	4550	4550	4550	4550

Legend: * p < 0.1; ** p < 0.05; *** p < 0.01.

reports the mediating effect regression results with the Z-score as the credit risk indicator, and an increase in the Z-score represents a decrease in corporate credit risk. From the results of Column (1), it can be found that when the industry and time are controlled, the coefficient of EPU on the Z-score is −0.1617 and is significant at the level of 1%, indicating that the increase in EPU has a negative effect on corporate credit risk, which means that the higher the EPU is, the higher the credit risk faced by enterprises. The above conclusions are in line with the basic judgment of economics. As the implicit policy risk, when policy uncertainty rises, enterprises will face a more complex operating environment, and the increase in the external financing cost and equity risk premium will lead to more serious debt repayment pressure. In this case, enterprises may intensify their credit risks due to their failure to repay debts on schedule. Considering the influence of control variables in Regression (1), the proportion of independent directors, return on equity, equity concentration, and cash flow ratio all have a significantly positive relationship with the Z-score, indicating that an increase in cash flow stability and corporate benefits will reduce the credit risk. The EPU coefficient of Regression (1) and the Z-value coefficient of Regression (2) are both significant, and the sign direction of the product of the two is the same as that of the EPU coefficient of Regression (2), indicating that credit risk has a partial mediating effect between EPU and ESG performance. The increase in EPU brings about an increase in credit risk, forcing enterprises to improve ESG performance. The negative impact of credit risk will be weakened by improving the environment, assuming social responsibility and strengthening the internal governance of the company. So, Hypothesis 2 is verified, which indicates that credit risk is the main transmission channel through which EPU contributes to improving the ESG performance. Regressions (3)–(5), respectively, report the differences in the mediating effect of credit risk in the three sub-items of ESG, among which the EPU coefficients are significantly positive at the level of 1%, and the coefficient symbols and coefficient magnitudes are in line with the results of benchmark regression. The Z-value coefficients are all significant, the sign of the product with the EPU coefficient of Regression (1) is positive, and the mediating effect ratios are 1.1%, 14%, and 5.7%, respectively, indicating that credit risk also has a partial mediating effect on the three components of ESG and that the effect of credit risk on social responsibility (S) is greater.

5.2.4. Test of Heterogeneity

The impact of EPU on ESG performance may change depending on the nature of enterprise ownership, the industry it belongs to, the local degree of marketization, and the intensity of government intervention. In order to clarify the heterogeneous effects caused by the above characteristics, the heterogeneity regression analysis will be conducted from the four perspectives of property right nature, carbon emission intensity, regional marketization degree, and government intervention intensity.

Firstly, according to the reasoning logic of theoretical Hypothesis 3 above, the research samples are divided into SOEs and non-SOEs according to the differences in the nature of property rights. Then, the effect of property rights heterogeneity on the impact of EPU on enterprise ESG performance is examined. Based on the results of differences in ownership nature in

Table 7. Heterogeneity analysis of property rights.

Variable	(1) ESG	(2) E	(3) S	(4) G
EPU	0.0233 *** (14.83)	0.0501 *** (13.20)	0.0192 *** (8.82)	0.0063 *** (7.31)
EPU × SOE	0.0058 *** (2.91)	0.0044 *** (2.82)	0.0056 ** (2.02)	0.0026 ** (2.38)
Control Variables	Control	Control	Control	Control
_CONS	3.1278 *** (45.74)	2.6709 *** (16.15)	3.2160 *** (33.94)	3.7122 *** (98.58)
IND/YEAR	Control	Control	Control	Control
R2	0.168	0.121	0.124	0.112
N	4550	4550	4550	4550

Legend: ** p < 0.05; *** p < 0.01.

, the interaction terms of EPU and EPU*SOE are all positive, indicating that the effect of EPU on ESG performance is obvious in SOEs. Hypothesis 3 is verified.

Secondly, this paper explores the effectiveness of industry heterogeneity on the influence of EPU on ESG performance under the influence of the implementation of the “3060” dual carbon target. According to the reasoning logic of theoretical Hypothesis 4 above, the enterprises belonging to 10 industries, such as ferrous metal smelting and non-ferrous metal smelting, in the research samples are regarded as high-carbon industries [45] and the others are classified as low-carbon industries to analyze the heterogeneous impact of industrial carbon emission differences. Based on the benchmark regression, the interaction term of EPU and high-carbon industry (C) is added. The coefficient of EPU in Column (1) of

Table 8. Heterogeneity analysis of carbon dioxide emissions.

Variable	(1) ESG	(2) E	(3) S	(4) G
EPU	0.0234 *** (19.61)	0.0417 *** (14.51)	0.0206 *** (12.45)	0.0068 *** (10.31)
EPU × C	0.0098 *** (4.94)	0.0320 *** (6.63)	0.0055 ** (1.99)	0.0033 *** (2.98)
Control variables	Control	Control	Control	Control
_CONS	3.0981 *** (46.11)	2.6647 *** (16.46)	3.2188 *** (34.49)	3.6818 *** (99.44)
IND/YEAR	Control	Control	Control	Control
R2	0.172	0.129	0.122	0.114
N	4550	4550	4550	4550

Legend: ** p < 0.05; *** p < 0.01.

is positive, and the interaction between EPU and high-carbon industries is positive, indicating that EPU promotes the improvement of ESG performance in high-carbon industries. Hypothesis 4 is verified; that is, when facing EPU, high-carbon industries are willing to take measures for environmental protection, undertaking social responsibility and internal corporate governance. Columns (2)–(4) show the impact of EPU on the three sub-items of E, S, and G of ESG performance, respectively. From the sign of the regression coefficient, consistent with Column (1), the coefficient of EPU is positive, and the interaction term between EPU and high-carbon industries is positive, which also indicates that the rise of the EPU index promotes the performance of high-carbon industries in terms of environment, social responsibility, and governance.

Then, the differences in the effect of EPU on the ESG performance of sample enterprises in regions with different degrees of marketization are explored. The results are in

Table 9. Heterogeneity analysis of the degree of marketization.

Variable	(1) ESG	(2) E	(3) S	(4) G
EPU	0.0360 *** (13.75)	0.0607 *** (9.55)	0.0274 *** (7.53)	0.0106 *** (7.29)
EPU × Market	−0.0014 *** (−5.32)	−0.0015 ** (−2.27)	−0.0013 *** (−3.49)	−0.0004 *** (−2.72)
Control variables	Control	Control	Control	Control
_CONS	2.9866 *** (36.22)	2.4873 *** (16.46)	3.0485 *** (31.91)	3.6598 *** (96.07)
IND/YEAR	Control	Control	Control	Control
R2	0.175	0.123	0.131	0.113
N	4550	4550	4550	4550

Legend: ** p < 0.05; *** p < 0.01.

; the coefficient of EPU is positive, the coefficient of the product of EPU and the market is negative, and the regression coefficient is small, indicating that EPU improves the ESG performance of enterprises, while the degree of marketization has a certain inhibitory consequence on the improvement of ESG performance. Hypothesis 5 is verified. Regions with a high level of marketization do not have serious information barriers and have a high efficiency of resource allocation and information transparency. Therefore, it is not only more convenient for external investors to obtain information, but also the cost of obtaining information is relatively low, thus weakening the information disclosure willingness of enterprises’ ESG performance, which is reflected in the negative moderating effect of the degree of marketization.

Finally, we examine whether the impact of EPU on ESG performance varies depending on the degree of government intervention. Government intervention can not only restrain enterprises from blind expansion and force them to disclose ESG information, but also help enterprises to form stable policy expectations when EPU is high.

Table 10. Heterogeneity analysis of the degree of government intervention.

Variable	(1) ESG	(2) E	(3) S	(4) G
EPU	0.0158 *** (4.19)	0.0295 *** (3.24)	0.0132 ** (2.52)	0.0145 *** (6.98)
EPU × GIDA	0.0016 *** (2.98)	0.0034 *** (2.62)	0.0013 * (1.72)	−0.0009 *** (−3.10)
Control variables	Control	Control	Control	Control
_CONS	3.2049 *** (42.87)	2.8283 *** (15.66)	3.3389 *** (32.21)	3.6337 *** (88.34)
IND/YEAR	Control	Control	Control	Control
R2	0.168	0.122	0.123	0.084
N	4550	4550	4550	4550

Legend: * p < 0.1; ** p < 0.05; *** p < 0.01.

reports the effect results of EPU on ESG performance when there are differences in the degree of government intervention. The coefficients of EPU and EPU × GIDA in Columns (1)–(3) of this Table are all positive, while the coefficient in Column (4) is negative. It shows that EPU improves ESG performance, and government intervention has a promotion effect on ESG performance disclosure, meaning that Hypothesis 6 is verified. The above situation has the same effect on E and S, while government intervention is harmful corporate governance; that is, excessive government intervention has a crowding-out effect on enterprises as market subjects.

6. Conclusions and Implication

6.1. Conclusions

China’s economic policy is facing great uncertainty due to the impact of multiple events such as COVID-19, nuclear leakage, and China–US trade frictions, combined with the triple pressure of shrinking demand, supply conflicts, and weakening expectations. On the basis of considering the characteristics of EPU and enterprises’ ESG performance, this paper uses the panel data of A-share listed enterprises from 2011 to 2020 to study the effect and mechanism of EPU on enterprises’ ESG performance. The results show the following: (1) EPU has a significant promotion effect on ESG performance, and the conclusion is still valid after considering the possible endogeneity problems and a series of robustness tests. (2) The test results of the mediating effect model show that there is a transmission channel from EPU to corporate credit risk to corporate ESG performance in the process of the impact of EPU on corporate ESG performance. Economic policy uncertainty intensifies the credit risks of enterprises [46], and enterprises actively disclose ESG information to cope with the impact of possible risks [47]. (3) Heterogeneity analysis shows that EPU has a more significant positive impact on the ESG performance of enterprises in state-owned enterprises, high-carbon industries, a low degree of marketization, and regions with strong government intervention. Moreover, the impact of EPU on corporate environmental (E), social (S), and governance (G) decreases in turn.

6.2. Suggestions

The conclusions contain rich policy implications as follows: (1) For corporate internal governance, EPU can promote corporate ESG performance, which is essentially the result of the internal decision-making of management to cope with uncertain risks, that is, to seek self-development opportunities in market competition by increasing ESG investment or disclosing more ESG information. Therefore, in the fluctuating environment with frequent uncertain factors, enterprises should actively adapt to the changes in economic policies, maintain adaptive organizational structure reform, and dynamically adjust the degree of performance in E, S, and other aspects so as to transform uncertainty into development opportunities. (2) To some extent, improving ESG performance is used as a tool to deal with the risk of EPU. When the uncertainty is high, the regulatory authorities and external investors should strengthen the control and identification of the quality of ESG information disclosed by enterprises and should guard against the release of false information by enterprises. (3) Pay attention to preventing enterprise credit risks and enhancing the ability to resist risks. EPU affects ESG performance through credit risk. For the sake of reducing the credit risk of enterprises exacerbated by uncertainty, enterprises should take precautions, strengthen the awareness of risk prevention, and enhance the confidence of stakeholders by enhancing capital network relations. (4) In view of the fact that the impact of EPU on the ESG performance of enterprises varies due to the nature of enterprise ownership, the industry to which they belong, the local degree of marketization, and the intensity of government intervention, regulators should carry out differentiated management based on regions and industries and should formulate policies and regulations for enterprises in different industries based on the situation of regional development. Try to ensure the stability and predictability of economic policies, and try to encourage enterprises to disclose ESG performance information.