ESG and Corporate Performance: Evidence from Agriculture and Forestry Listed Companies

Abstract

Agriculture and forestry are fundamental industries. With the development of the ESG concept, stakeholders are increasingly concerned about the relationship between ESG and agricultural and forestry corporate performance. This paper examines 156 listed agricultural and forestry companies to explore the impact of ESG on corporate performance, both theoretically and empirically, using two-stage least squares. Heterogeneity is explored from the perspective of three sub-dimensions of ESG and industry comparison, respectively. Finally, the impact mechanism of ESG is analyzed from three perspectives: government, market, and company. Results indicate that (1) ESG and corporate performance are significantly and positively correlated, and higher ESG ratings are beneficial to corporate performance improvement. (2) Compared with E performance, S and G performance are more conducive to promoting corporate performance growth. (3) There is no significant difference in the effect of ESG on corporate performance between listed companies in agriculture and forestry. (4) Tax incentives and the regional marketization degree have a negative moderating effect, but the proportion of female executives plays a positive moderating role. These findings provide useful insights for listed companies in agriculture and forestry to improve ESG performance and, consequently, corporate performance, and also promote listed companies to play a greater leading role in green development.

1. Introduction

As the sustainability of social and economic development has become a problem of global significance, the participation of the capital market in managing the social environment has become a crucial strategy. Environment, Social, and Governance (ESG) refers to the evaluation of the sustainability of a company’s activities and their impact on societal values from the perspectives of the environment, society, and corporate governance. In 2004, the UN Global Compact introduced the notion of ESG, and governments and mainstream asset managers began to pay attention to the ESG performance of companies. The United Nations developed the Principles for Responsible Investment in 2005, which incorporated ESG considerations into investment choices and practices. By 4 March 2022, 395 investors and 507 service providers from all around the world had signed the PRI, paying attention to the ESG performance of firms, and using it as a foundation for investing. With the development of Sustainable Development Goals, global warming and the COVID-19 outbreak, the global focus on ESG has intensified, and a company’s ESG performance has become a crucial metric for assessing its environmental and social responsibility [1]. In this context, companies must examine ESG challenges [2] and investigate a more ethically responsible, sustainable business model.

China’s ESG is of worldwide significance as the world’s second-largest economy. In the past, the Chinese market focused primarily on a company’s profitability, with the government shouldering most of the responsibility for sustainable development. However, the establishment of a comprehensive ESG evaluation system in China began rather late [3]. In recent years, the Chinese government has paid increased attention to the ESG performance of corporations. In 2018 and 2022, respectively, the China Securities Regulatory Commission issued the updated Governance Code for Listed Businesses and the Guidance on Investor Relations Management of Listed Companies, mandating listed companies to increase the disclosure of ESG information. According to the 2022 Environmental Performance Index produced by Yale and Columbia universities, China ranks 160th out of 180 countries/regions. Although China’s environmental performance is still unsatisfactory, the country has made significant progress, with the EPI increasing by 11.4% over the past decade, representing the largest increase in the Asia–Pacific area. This highlights the ample opportunities for China to further improve its ESG performance. In the future, the tension between economic development and environmental protection will require companies to assume greater ESG responsibilities, prompting the international community to pay greater attention to the ESG performance of Chinese companies [2].

Agriculture and forestry are essential industries that play a crucial role in ecological civilization construction and sustainable environmental growth. As leading companies in these industries, it is worth studying the ESG performance of listed agricultural and forestry companies. Agriculture and forestry are weak. According to the 2021 Top 500 Chinese Enterprises list published by the China Company Federation and the China Entrepreneur Association, agriculture and forestry companies are rarely mentioned, indicating that their performance on the financial market is abysmal. However, the ecological environment is recognized as a public good [4], ESG activities have certain positive externalities, and companies may have to pay more costs to assume ESG responsibilities. This raises questions: Does taking on ESG responsibilities impact the corporate performance of listed agricultural and forestry companies? Will it enhance or reduce profits, and can these companies achieve a win–win situation with sustainable social economic development? If so, what are the processes of influence? Few studies have addressed these concerns, although they are worthy of discussion.

In this study, we utilize listed Chinese agricultural and forestry companies’ data from 2009 to 2021 to empirically investigate the impact of ESG on corporate performance, controlling for reverse causality. We test the robustness of our results using various methods and further investigate the heterogeneity and mechanisms of the impact to fill the research gap in this field.

The literature review and hypothesis development comprise the Section 2 of this paper. The Section 3 includes the construction and evaluation of the empirical model, while the Section 4 reports the empirical analysis results. Finally, we discuss and conclude our findings.

2. Literature Review and Hypotheses

2.1. The Relationship between ESG Performance and Corporate Performance

The relationship between ESG and corporate performance has been extensively explored in academic circles. However, the conclusions are mixed. Early studies often started from the theory of shareholder supremacy and principal–agent, suggesting that a company’s social responsibility is to increase profits [5] (pp. 173–178). These scholars argued that ESG activities have strong externalities that can result in additional costs for companies. Additionally, since most ESG information is self-reported by companies, managers may be tempted to inflate data through opportunistic behavior to improve their ESG ratings. Therefore, ESG activities may not be conducive to improving corporate performance and could even harm the interests of shareholders [6,7,8,9].

The ESG concept has gained popularity, replacing the goal of maximizing shareholder profits with maximizing stakeholder benefits. Increasing numbers of academics now believe that good ESG performance can enhance corporate performance. According to stakeholder theory, a company is a collection of multilateral contracts between essential stakeholders [10]. Stakeholders contribute the resources necessary for a company’s growth, and meeting their expectations is crucial for a company’s growth prospects. Corporate responsibility for ESG is not merely a cost, a constraint, or a charitable behavior; it can also provide an opportunity for innovation and competitive advantage [11]. A vast number of studies have shown that the non-financial information provided by ESG is highly valuable to various stakeholders. When a corporation takes on ESG responsibility, it can satisfy the needs of both internal and external stakeholders, leading to enhanced performance. Internal stakeholders include managers and staff, while external stakeholders consist of government, institutions, customers, and investors.

For internal stakeholders, companies that exhibit superior ESG performance have a higher level of governance and a more comprehensive management system [12]. As a result, they have a greater ability to organize their employees, tap into their full potential, and utilize company assets more efficiently. Essentially, they are better equipped to generate economic results [13]. Additionally, good ESG performance can enhance employee engagement, foster loyalty, and attract high-quality human resources [14].

For external stakeholders, better ESG performance can improve a company’s image and reputation, signaling trustworthy and ethical business practices to the government, investors, and the public [15]. As a result, companies with good ESG performance can earn the trust and support of external stakeholders, accumulate moral capital, and enhance their legitimacy [16]. With a strong reputation, companies can increase their market competitiveness, generate additional value, and gain extra profits. Additionally, ESG information provides valuable insights not covered by financial indicators, reducing information asymmetry between investors and companies, and encouraging operators to make decisions based on stakeholder interests. This can ease financing constraints and alleviate the contradiction between the supply and demand of funds, ultimately boosting corporate performance [17].

Numerous experts have conducted empirical studies in recent years to investigate the relationship between ESG and corporate performance. Research on corporations in the United States, Europe, and Asia demonstrates that good ESG practices can contribute to improved corporate performance [18,19,20]. Bo Wang and Maojia Yang [21] analyze data from listed companies in China and also find evidence that ESG practices enhance corporate performance. By combining stakeholder theory and competitive strategy theory, they provide detailed insights on this relationship. Furthermore, their heterogeneity analysis reveals that ESG practices have a greater value effect on companies, particularly non-state-owned and non-polluting companies in eastern China.

Based on these findings, this paper proposes the first hypothesis:

Hypothesis H1.

ESG practices have a positive impact on the corporate performance of listed agricultural and forestry companies.

2.2. Mechanisms of ESG Performance on Corporate Performance

Some scholars suggest that companies with better corporate performance may have a stronger ability to bear ESG responsibilities, indicating the possibility of reverse causality in such studies. However, many studies interpret the relationship between ESG and corporate performance as ESG having a positive effect on corporate performance, despite the potential for reversibility [22]. Therefore, it is crucial to differentiate between correlation and causation. Ting Jiang [23] proposes that moderating effect analysis is a crucial approach to establishing causality, as it investigates the richer connections between independent and dependent variables. Although endogeneity cannot be entirely controlled, moderating effect analysis can help identify the causal relationship between independent and dependent variables if such correlations cannot be explained by alternative causal links.

While existing research explore various variables, such as ownership structure [24], gender of the board of directors [1], internal and external supervision [25], and ESG investors [2], the role of mechanism analysis has not been adequately recognized in many studies [23]. A company’s ability to attract resources from diverse stakeholders is critical for its continued existence and growth. From a multi-capital perspective, the government provides social capital, the market offers monetary capital, and executives provide human capital, and all these stakeholders have a significant impact on a company’s business decisions [26]. Using stakeholder theory and examining the government, market, and company perspectives, we aim to investigate the regulatory effects of tax incentives, regional marketization degree, and the proportion of female executives to illustrate the impact of ESG on corporate performance.

There is a lack of relevant studies on the impact of tax incentives on ESG, especially within the context of agriculture and forestry firms. Tax incentives are an essential tool for the government to implement industrial policies and represent a form of “government credit.” The granting of tax incentives by the government can convey a positive signal to external stakeholders, such as banks and investors, suggesting that the company has official certification and implied guarantee with significant potential for development. This reputation effect can encourage stakeholders to invest their confidence and provide financial assistance. As a result, companies with larger tax incentives can maintain good operations in the short run, which may lead to operator inertia and speculation to some extent.

In China, ESG information mainly comes from annual reports, official company websites, and announcements. However, ESG information disclosure in China has defects, such as inconsistent standards, imperfect legal protection systems, and asymmetric information. Driven by profit, company managers may conceal or falsely report information to obtain a higher ESG rating, thereby gaining a good social reputation and various resource convenience. Some companies may also pretend to engage in ESG activities without actually allocating the necessary resources to strictly implement ESG responsibilities, known as “Greenwash” practices. These practices introduce business dangers to the corporation and may severely damage the company’s reputation if exposed, eroding stakeholders’ confidence in the ESG rating and diminishing the positive impact of ESG on corporate performance.

As a result, the following hypothesis is proposed in this paper:

Hypothesis H2.

Tax incentives have a negative moderating effect on the relationship between ESG and corporate performance of listed agricultural and forestry companies.

Despite China’s vast land size, there are significant disparities in the level of development between its many regions. The varying levels of regional marketization can lead to different effects of ESG on corporate performance. In regions with a high degree of marketization, the market mechanism is well developed, and companies have better access to resources and policy flexibility. These companies experience fewer financing constraints and have more investment and financing alternatives. Additionally, regions with high marketization tend to have better rule of law and economic development, as well as stricter government and societal oversight of corporations. Therefore, stakeholders may demand that companies in these regions assume greater ESG responsibilities [27]. In other words, good ESG performance might be viewed as a company fulfilling its responsibilities. This may limit the improvement of stakeholders’ identification with the company, which may not result in significant corporate performance growth.

On the other hand, in regions with low marketization, the level of government control is often inadequate, and the factor markets are more flawed. In such situations, the moral and financial costs of companies not assuming ESG duties are smaller. If a company can still actively undertake ESG responsibilities, it will surprise stakeholders, and the marginal effect of ESG will be more apparent [28]. This can enhance stakeholders’ recognition and support of the company and drive corporate performance growth. Moreover, a higher degree of regional marketization is associated with a lower degree of information asymmetry [29]. Stakeholders have more access to information about the company, which means ESG determined based on the company’s own disclosure plays a relatively limited role for stakeholders, particularly investors.

Therefore, this paper proposes the following hypothesis:

Hypothesis H3.

The degree of regional marketization has a negative moderating effect on the relationship between ESG and the corporate performance of listed agricultural and forestry companies.

According to the Upper Echelons Theory, executives play a central role in company organization, and their demographic features have a significant impact on the company’s decision making and corporate performance. Gender is typically considered a significant demographic feature variable. The proportion of female executives may affect the relationship between ESG and corporate performance [1]. However, many papers only discuss the impact of the proportion of female executives on corporate social responsibility [30,31] and rarely explore the moderating effect of the proportion of female executives on the relationship between ESG and corporate performance.

The Feminine Ethics of Care holds that there are gender-based distinctions in moral ethics. Compared to men, women tend to interpret morality as their sense of obligation to others and emphasize a form of caring ethics based on “connection and responsibility.” Based on this idea, the public has much higher expectations for women’s ethical standards than for men’s, which makes female executives face greater social pressure to help companies assume ESG responsibilities [32]. Furthermore, research demonstrates that female leaders are more capable of driving ESG performance improvement in their companies [33].

According to Social Role Theory, gender differences in the conventional division of labor are a significant factor in the divergent expectations of the public regarding gender roles. Compared to the “individuality” of males who work outside, women demonstrate more “altruism” in public [34]. Therefore, companies with a higher proportion of female executives may pay more attention to ESG, be more attentive to stakeholder demands, and be more willing to create more comprehensive value for stakeholders, which can strengthen the impact of ESG on corporate performance. In addition, the proportion of female executives reflects the equality of promotion possibilities between men and women, which can provide insight into the significance of gender considerations in human resource management. The more equal the gender ratio of the senior management team, the more favorable employment signals will be transmitted to the labor market, which will increase stakeholder confidence and the company’s legitimacy. This may create a favorable social environment for sustainable corporate performance growth [35].

Based on the above theories and research, this paper proposes the fourth hypothesis:

Hypothesis H4.

The proportion of female executives positively moderates the relationship between ESG and the corporate performance of listed agricultural and forestry companies.

3. Methodology and Data

3.1. Empirical Model Setting

To investigate the influence and mechanism of ESG on the corporate performance of listed agricultural and forestry companies, the following models are developed:

$$S_{i,t}=a_0+a_1{ESG}_{i,t}+a_2{\xi }_{i,t}+{\phi }_i+{\lambda }_t+{\epsilon }_{i,t}$$

(1)

$$S_{i,t}=b_0+b_1{ESG}_{i,t}+b_2{Tax}_{i,t}+b_3{ESG}_{i,t}\ast {Tax}_{i,t}+b_4{\xi }_{i,t}+{\phi }_i+{\lambda }_t+{\epsilon }_{i,t}$$

(2)

$$S_{i,t}=c_0+c_1{ESG}_{i,t}+c_2{Market}_{i,t}+c_3{ESG}_{i,t}\ast {Market}_{i,t}+c_4{\xi }_{i,t}+{\phi }_i+{\lambda }_t+{\epsilon }_{i,t}$$

(3)

$$S_{i,t}=d_0+d_1{ESG}_{i,t}+d_2{Female}_{i,t}+d_3{ESG}_{i,t}\ast {Female}_{i,t}+d_4{\xi }_{i,t}+{\phi }_i+{\lambda }_t+{\epsilon }_{i,t}$$

(4)

where $S_{i,t}$ is the corporate performance of company $i$ in year $t$. ${Tax}_{i,t}$, ${Market}_{i,t}$ and ${Female}_{i,t}$ represent tax incentives, regional marketization degree in which the company is located and the proportion of female executives, respectively. ${\xi }_{i,t}$ represents control variables, ${\phi }_i$ represents the individual effect and ${\lambda }_t$ is the time effect.

3.2. Variables

3.2.1. The Dependent Variable

The dependent variable in this study is the corporate performance of listed agricultural and forestry companies. While many studies use ROA or ROE as a proxy variable for corporate performance, this paper believes that evaluating corporate performance effectively requires consideration of many factors, and a single index may not suffice. To address this concern, this paper constructs a comprehensive performance evaluation system based on the Implementation Rules for Comprehensive Performance Evaluation of Central Companies issued by the State-owned Assets Supervision and Administration Commission of the State Council of China. The system consists of four dimensions of profitability, asset quality, debt risk, and business growth ability (see

Table 1. Comprehensive corporate performance evaluation system.

	Indicator	Attribute	Calculation Formula	Weight	Co-Weight
Profitability	Net return on assets	+	Net profit/Average balance of shareholders’ equity	0.0375	0.0764
	Total return on assets	+	(Total profit + Finance costs)/Average total assets	0.0389
Asset quality	Total asset turnover ratio	+	Operating income/Average total assets	0.0844	0.7641
	Accounts receivable turnover ratio	+	Operating revenue/Average occupancy of accounts receivable	0.6797
Debt risk	Gearing ratio	−	Total liabilities/Total assets	0.0077	0.1022
	Interest cover multiplier	+	(Net profit + Finance costs)/Financial costs	0.0945
Business growth	Operating profit growth	+	(Current year’s operating profit—Prior year’s operating profit)/ Operating profit for the previous year	0.0451	0.0573
	Capital preservation and appreciation rate	+	Owner’s equity at the end of the period/Owner’s equity at the end of last year	0.0122

). Using this system, the comprehensive score of corporate performance can be computed.

Owing to the high objectivity of the entropy method, which can minimize the weight bias arising from subjective factors [36] and generate comprehensive scores based on multiple indicators, this paper adopts the entropy method to compute the comprehensive corporate performance of the listed agricultural and forestry companies. Here, $x_{itj}(i=1,2,3,\dots 156; t=1,2,3,\dots 13; j=1,2,3,\dots 8)$ denotes the $j$th indicator for the company $i$ in year $t$.

For positive indicators:

$$x_{itj}^{\prime }=\frac{x_{itj}–\min \left(x_{itj}\right)}{\max \left(x_{itj}\right)–\min \left(x_{itj}\right)}$$

(5)

For negative indicators:

$$x_{itj}^{\prime }=\frac{\max \left(x_{itj}\right)–x_{itj}}{\max \left(x_{itj}\right)–\min \left(x_{itj}\right)}$$

(6)

The weight of indicator $j$ in year $t$ in relation to the indicator:

$$p_{itj}=\frac{x_{itj}}{\sum _{i=1}^{156}{x}_{itj}}$$

(7)

Entropy value of the indicator $j$:

$$e_{tj}=-k\sum _{i=1}^{156}{p}_{itj}\ln \left(p_{itj}\right)$$

(8)

where $k=\frac{1}{lnn}>0, e_{tj}\ge 0$.

Redundancy of information entropy:

$$g_{tj}=1–e_{tj}$$

(9)

Weighting of the indicators:

$$w_{tj}=\frac{g_{tj}}{\sum _{j=1}^8{g}_{tj}}$$

(10)

Composite score for the corporate performance:

$$S_{it}=\sum _{j=1}^8{w}_{tj}\times p_{itj}$$

(11)

Table 1 shows the weight of each indicator. The results indicate that the overall corporate performance of the listed agricultural and forestry companies is poor, with the average performance of the listed forestry companies being 0.0615 and the average performance of the listed agricultural companies being 0.0735. The average annual corporate performance of the top ten corporations is listed in

Table 2. The ranking of average corporate performance.

Ranking	Company	Industry	Average Annual Performance
1	Henan Shuanghui Investment & Development Co., Ltd. (Luohe, China)	Agriculture	0.1415
2	Guangdong Haid Group Co., Ltd. (Guangzhou, China)	Agriculture	0.1299
3	New Hope Liuhe Co., Ltd. (Beijing, China)	Agriculture	0.1220
4	Tongwei Co., Ltd. (Chengdu, China)	Agriculture	0.1136
5	Jiangxi Zhengbang Technology Co., Ltd. (Nanchang, China)	Agriculture	0.1134
6	Tangrenshen Group Co., Ltd. (Zhuzhou, China)	Agriculture	0.1130
7	Hunan Zhenghong Science and Technology Develop Co., Ltd. (Yueyang, China)	Agriculture	0.1110
8	Dehua TB New Decoration Material Co., Ltd. (Huzhou, China)	Forestry	0.1095
9	Vohringer Home Technology Co., Ltd. (Shanghai, China)	Forestry	0.1066
10	Xiamen Hexing Packaging Printing Co., Ltd. (Xiamen, China)	Forestry	0.1057

.

3.2.2. The Independent Variable

In this study, the independent variable is ESG. Over the years, the concept of ESG has gained significant popularity, leading to the development of several ESG rating systems by institutions in the United States and overseas. However, these rating systems have inconsistent evaluation criteria and cover very little data on China’s listed agricultural and forestry companies as commonly used rating systems, such as Wind, Bloomberg, and SynTao Green Finance. As such, this paper utilizes the ESG rating system of Sino-Securities Index Information Service (Shanghai, China) Co. Ltd. ESG, which has the broadest coverage and highest updating frequency among China’s rating systems. This rating system provides the most comprehensive ESG data of listed Chinese agricultural and forestry companies.

The Sino-Securities ESG rating system draws on international mainstream methodologies and experiences, while also incorporating China’s national conditions and capital market features. It employs an industry-weighted average technique for ESG evaluation and provides the market with rating results of Chinese A-share and bond issuers in the areas of environment, society, and corporate governance. Furthermore, the system has dynamic adjustments made based on the company’s specific ESG status, resulting in more credible conclusions derived from data analysis.

The Sino-Securities ESG rating system designs a three-level index evaluation system, consisting of three first-level indexes, fourteen second-level indices, twenty-six third-level indexes, and over one hundred bottom-level indexes (see

Table 3. ESG rating system of Sino-Securities.

Three Pillars	Thematic Indicators	Key Indicators
Environment	Environmental management system	Environmental management
	Green business objectives	Low carbon plans or targets, green procurement policies or plans
	Green products	Carbon footprint, sustainable products or services
	External environmental certification	Product or company receives environmental certification
	Environmental violation	Environmental violations and infringements
Social	Institutional system	Quality of social responsibility reports
	Health and safety	Targets or plans to reduce safety incidents, negative business incidents, trends in business incidents
	Social contribution	Social responsibility-related donations, employee growth rates, rural revitalization
	Quality management	Product or company receives quality certification
Governance	System building	Corporate self-ESG monitoring
	Governance structure	Connected transactions, the proportion of directors and supervisors
	Business activity	Tax transparency
	Operational risk	Asset quality, overall financial credibility, short-term debt service risk, pledge ratio of major shareholders, quality of information disclosure
	External sanction	Trading sanctions, SEC penalties, disaffiliations, investigations, and violations by listed executives

Note: The information in the table is obtained from the official website of Sino-Securities Index Information Service (Shanghai) Co., Ltd. (https://www.chindices.com/, accessed on 8 July 2022).

). This evaluation system provides ESG comprehensive evaluation scores of listed companies and categorizes them into nine grades: C, CC, CCC, B, BB, BBB, A, AA, and AAA. To quantify the C–AAA grades, this paper refers to previous research [21] and assigns 1–9 points, respectively (see

Table 4. ESG Ratings of Sino-Securities.

ESG Performance	Nine Grades	Tail Risk	Assignment
Backward	C	Serious Warning	1
	CC	Warning	2
Moderate	CCC	Needs attention	3
	B	Needs attention	4
	BB	Needs attention	5
Leading	BBB	Low risk	6
	A	Low risk	7
	AA	Low risk	8
	AAA	Low risk	9

Note: The information in the first three columns of the table comes from the official website of Sino-Securities Index Information Service (Shanghai) Co., Ltd. (https://www.chindices.com/, accessed on 8 July 2022.).

).

3.2.3. Moderating Variables

Tax incentives: Previous research typically uses income tax-related indicators to calculate the effective tax rate to represent tax incentives [37,38]. However, the annual reports of listed agricultural and forestry companies reveal that the tax incentives they receive primarily cover income tax, value-added tax, and other taxes. Therefore, this paper refers to Liu Guangqiang’s [39] approach and calculates the tax incentives of listed agricultural and forestry companies by “various tax rebates received/(various tax rebates received + various taxes paid)”.

Regional marketization degree: To measure the level of regional marketization, this paper uses Wang Xiaolu’s and others’ market-based index of China’s provinces. As many recent studies only include data until 2019, this assumes that the average annual growth rate of each province’s total marketization index is the growth rate for 2019–2020 and 2020–2021, based on the research of Ma Lianfu et al. [40]. With this assumption, we can obtain the marketization data of China by province in 2020–2021 and match them with the registration location of listed agricultural and forestry firms.

Proportion of female executives: this variable is determined by calculating the “number of female executives/number of executives”, based on employment data at the end of the year.

3.2.4. Control Variables

Many studies on related topics only consider financial indicators as control variables. However, as an important factor reflecting the level of internal management, the level of governance may also have an impact on corporate performance [41]. Therefore, this paper sets control variables from two levels: finance and governance. The financial aspect comprises capital size, company age, corporate growth, cash rate, and asset–liability ratio [42,43,44,45,46]. The internal governance aspect encompasses the nature of property right, top ten shareholders’ shareholding ratio, and executive motivation. Furthermore, the empirical research controls for temporal and individual effects [42,47,48]. For a detailed explanation of each variable, refer to

Table 5. Description of control variables.

Control Variables	Variable Name	Symbol	Variable Description
Financial aspect	Capital size	Size	The logarithm of total assets
	Company age	Age	Current date minus launch date (years)
	Corporate growth	Growth	(Current year’s total operating revenue—last year’s totaloperating revenue)/last year’s total operating revenue
	Cash ratio	Cash	Net cash flows from operating activities/total assets
	Asset–liability ratio	Lev	Total assets/total liabilities
Governance aspect	Nature of property right	Cn	State-owned = 1, non-state-owned = 0
	Top ten shareholders’ shareholding ratio	Top10	Number of shares held by top ten shareholders/total number of shares
	Executive motivation	Wage	The logarithm of the total remuneration of the top three management

.

3.3. Data Sources

Currently, there are no consistent criteria in China for defining listed agricultural and forestry companies. To select research samples, this paper refers to the Guidance on Classification of Listed Companies (2012 Revision) and the Industry Classification Results of Listed Companies in the Third Quarter of 2021, published by the China Securities Regulatory Commission, and chooses 156 listed companies. Of these, 88 are in agriculture and 68 are in forestry (

Table 6. Industry distribution of sample companies.

Industry	Industry Code (Type)	Number
Agriculture	A01 (Agriculture)	16
	A03 (Animal husbandry)	16
	A04 (Fisheries)	6
	A05 (Agriculture, forestry, and fishery services)	1
	C13 (Agri-food processing industry)	49
Forestry	A02 (Forestry)	1
	C20 (Wood processing and wood, bamboo, rattan, palm, and grass products industries)	8
	C21 (Furniture manufacturing)	23
	C22 (Paper and paper products industry)	36

). As the ESG data used in this study can extend back to 2009 at the earliest, this paper uses unbalanced panel data from 2009 to 2021 for empirical research. ESG data are obtained from the Wind database, regional marketization statistics from the China Marketization Index database, and remaining data from CSMAR. Samples of ST and *ST are eliminated from the study due to unreliable information. This paper also employs linear interpolation to fill in some missing data. All variables are winsorized at 1% and 99%.

3.4. Empirical Method Selection

This paper utilizes ordinary least squares (OLS) for empirical testing. However, since OLS does not account for individual effects, it may lead to deviation of results due to the presence of missing variables. As a result, after conducting the Hausmann test, this paper adopts the Two-way Fixed Effects (FE) model for testing. To differentiate between correlation and causality, this paper employs the two-stage least square method (2SLS) for estimation. Drawing on previous studies [47,49], this paper uses the ESG performance of the previous year and the mean ESG performance of other listed companies in the same industry as instrumental variables.

4. Results

4.1. Descriptive Statistics

Overall, corporate performance of all samples from 2009 to 2021 exhibits relatively modest growth (see Figure 1a), with a similar trend observed for both listed agriculture and forestry companies. Specifically, corporate performance grew annually from 2009 to 2011, likely due to a series of positive policies implemented by the government to stimulate economic growth following the 2008 financial crisis. However, the impact of these policies was limited and likely decreased over time. Following a period of adjustment, corporate performance steadily improved. However, there was a slight dip in corporate performance after 2019, which may be attributed to the outbreak of COVID-19.

The overall ESG performance is trending upward (see Figure 1b). Listed agriculture and forestry companies are becoming increasingly aware of their ESG responsibilities, driven by societal and economic developments. Furthermore, there is a positive correlation between ESG and corporate performance over time. Due to the delayed promotion of ESG in China and lack of attention from society in the early years, the overall ESG performance did not exhibit a clear growth pattern before 2019. However, we find that ESG performance has increased significantly in 2020 and 2021, possibly because listed companies, as industry leaders, assumed greater ESG responsibilities during the COVID-19 pandemic. Notably, forestry companies have shown a remarkable increase in ESG performance since 2015 and have established a gap with agricultural companies, but their corporate performances are not significantly superior. The underlying reasons are worth discussing.

There are discernible differences in corporate performance (Score) of different companies (see

Table 7. Descriptive statistics.

Variable Symbol	Number of Observations	Average	Median	Standard Deviation	Min	Max
Score	1247	0.0924	0.0957	0.0202	0.0425	0.1368
ESG	1247	4.0489	4.0000	1.1367	1	7
Tax	1247	0.1405	0.0196	0.2204	0.0000	0.8326
Market	1247	8.8986	9.1940	1.9616	3.5380	12.0140
Female	1247	0.1585	0.1429	0.1503	0.0000	0.6000
Cash	1247	0.0566	0.0560	0.0792	−0.1830	0.2873
Wage	1247	14.3012	14.2619	0.8128	12.6508	16.5367
Size	1247	22.0088	21.8981	1.0633	19.5751	25.1115
Growth	1247	0.1672	0.1099	0.3636	−0.6042	2.0322
Age	1247	10.1866	9.2986	6.6524	0.7918	25.0000
Lev	1247	0.4272	0.4165	0.1890	0.0650	0.9752
Cn	1247	0.3144	0.0000	0.4644	0	1
Top10	1247	56.4448	58.4600	15.8063	19.9400	85.4600

), with the highest value being 0.1368 and the lowest being 0.0425. The ESG performance has some room for improvement, as no company received the highest rating. The highest value for tax incentives (Tax) is 0.8326, while the mean value is 0.1405, indicating a significant disparity in tax incentives that may be due to differences in company composition and size. The maximum value of regional marketization degree (Market) in the province is 12.0140, whereas the minimum value is only 3.5380. Given that each company operates in a distinct market environment, it is important to investigate the impact of the marketization level. The average proportion of female executives (Female) is only 15.85%, indicating that decisions concerning company operations are primarily made by male executives. Moreover, the samples consist of both long-standing and recently listed companies. The highest value for capital size (Size) is 25.1115, the lowest value is 19.5751, and the average value is 22.0088, indicating differences in capital size across the sample.

4.2. Benchmark Regression

The coefficient of ESG exhibits a significantly positive association with corporate performance at the 1% significance level, as indicated by column 2 of

Table 8. Baseline regression analysis.

	OLS	Two-Way FE	2SLS
ESG	0.0027 ***	0.0031 ***	0.0033 **
	(0.0004)	(0.0005)	(0.0015)
Cash	0.0275 ***	0.0137 **	0.0112 *
	(0.0063)	(0.0058)	(0.0060)
Wage	0.0031 ***	0.0034 ***	0.0033 ***
	(0.0007)	(0.0012)	(0.0012)
Size	0.0028 ***	0.0033 ***	0.0031 ***
	(0.0006)	(0.0011)	(0.0012)
Top10	0.0002 ***	0.0001 **	0.0001 *
	(0.0000)	(0.0001)	(0.0001)
Age	−0.0003 ***	−0.0061 ***	−0.0052 **
	(0.0001)	(0.0023)	(0.0023)
Cn	−0.0054 ***	−0.0090 **	−0.0089 **
	(0.0012)	(0.0038)	(0.0037)
Lev	−0.0235 ***	−0.0359 ***	−0.0389 ***
	(0.0029)	(0.0037)	(0.0039)
Growth	0.0034 ***	0.0016	0.0014
	(0.0013)	(0.0011)	(0.0011)
Constant	−0.0127	0.0048	0.1320 *
	(0.0115)	(0.0262)	(0.0711)
Individual effect	No	Yes	Yes
Time effect	No	Yes	Yes
Number of observations	1247	1247	1099
R2	0.3420	0.2317	0.6560
Adj_R2	0.3372	0.1120	0.6011

Note: Both instrumental variables in the 2SLS model pass the weak instruments test and the overidentified test. *, **, and *** indicate significance at the 10%, 5%, and 1% levels, respectively.

. This confirms the validity of hypothesis H1. However, as the data utilized in this study are panel data, the OLS estimation results could be influenced by individual effects and time effects. To address this, this paper employs the Two-way FE model for estimation, which is presented in column 3 of Table 8. The result reveals a positive correlation between ESG and corporate performance at the same significance level. These findings persist even after considering reverse causality, as illustrated in column 4. A one-notch increase in the ESG rating is associated with a 0.0033 increase in corporate performance. Additionally, the coefficient of ESG in column 4 is greater than that in the first two columns, which suggests that the OLS model underestimates the impact of ESG on corporate performance due to the presence of endogenous issues.

Further, the results of the control variables in column 4 of Table 8 are analyzed. The coefficients of cash ratio (Cash), capital size (Size), executive motivation (Wage), and top ten shareholders’ shareholding ratio (Top 10) are all significantly positive, suggesting that they play a role in promoting the improvement of corporate performance. One possible explanation for this finding is that larger companies with a larger cash ratio may face fewer financing constraints, making it easier for them to engage in ESG activities. Similarly, companies with strong executive motivation and a high proportion of top ten shareholders may experience fewer principal–agent conflicts, which could lead to better corporate performance. In contrast, the coefficient of nature of property rights (Cn) is notably negative, indicating that non-state-owned agricultural and forestry companies are more conducive to performance growth. We presume that this may be because state-owned companies face more government control and jurisdiction, which can limit the market’s role in determining resource allocation. Consequently, state-owned companies may have lower utilization of social resources and capital, ultimately leading to lower corporate performance. Results also suggest that the age of the company negatively impacts corporate performance. This finding implies that companies that have been public for a longer period of time do not necessarily have better corporate performance. Therefore, the importance of other influencing factors, such as ESG, cannot be overlooked.

To clarify the influence of ESG on corporate performance of listed agricultural and forestry companies, we test the three sub-dimensions of ESG respectively. The test findings for Environment (E), Social (S), and Governance (G) are displayed in columns 2 through 4 of

Table 9. ESG sub-dimensions and industry comparisons.

	Environment	Social	Governance	Agriculture	Forestry		Difference Test
E	0.0005					E
	(0.0011)
S		0.0043 ***				S
		(0.0017)
G			0.0016 **			G
			(0.0007)
ESG				0.0037 ***	0.0024 ***	ESG	0.0025
				(0.0007)	(0.0007)		(0.0047)
ESG*Ind						ESG*Ind	0.0006
							(0.0128)
Ind						Ind	−0.1202
							(0.1462)
Cash	0.0085	0.0090	0.0109 *	0.0076	0.0200 *	Cash*Ind	0.0200
	(0.0060)	(0.0062)	(0.0060)	(0.0071)	(0.0110)		(0.0142)
Wage	0.0039 ***	0.0026 *	0.0036 ***	0.0040 ***	0.0021	Wage*Ind	0.0015
	(0.0012)	(0.0013)	(0.0012)	(0.0015)	(0.0019)		(0.0043)
Size	0.0036 ***	0.0025 *	0.0035 ***	0.0023	0.0061 ***	Size*Ind	0.0052
	(0.0012)	(0.0013)	(0.0012)	(0.0015)	(0.0017)		(0.0048)
Growth	0.0012	0.0017	0.0011	0.0022	−0.0029	Growth*Ind	−0.0008
	(0.0012)	(0.0012)	(0.0011)	(0.0014)	(0.0019)		(0.0030)
Age	−0.0050 **	−0.0061 **	−0.0046 **	−0.0055 **	−0.3703 ***	Age*Ind	0.0001
	(0.0023)	(0.0024)	(0.0022)	(0.0025)	(0.1229)		(0.0007)
Lev	−0.0407 ***	−0.0414 ***	−0.0388 ***	−0.0373 ***	−0.0389 ***	Lev*Ind	−0.0397 ***
	(0.0039)	(0.0040)	(0.0039)	(0.0051)	(0.0057)		(0.0125)
Cn	−0.0096 **	−0.0045	−0.0099 ***	−0.0110 *	−0.0041	Cn*Ind	−0.0051
	(0.0038)	(0.0044)	(0.0037)	(0.0057)	(0.0043)		(0.0057)
Top10	0.0001	0.0001 **	0.0001	0.0001	0.0001	Top10*Ind	0.0001
	(0.0001)	(0.0001)	(0.0001)	(0.0001)	(0.0001)		(0.0001)
Constant	0.0996	0.1599 **	0.0938	0.1457 *	2.4819 ***	Constant	0.0882 ***
	(0.0712)	(0.0770)	(0.0692)	(0.0813)	(0.8410)		(0.0093)
Individual effect	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Time effect	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Number of observations	1099	1099	1099	680	419	Number of observations	1099
R2	0.6449	0.6197	0.6560	0.6544	0.6977	R2	0.6190
Adj_R2	0.5882	0.5591	0.6012	0.5982	0.6317	Adj_R2	0.5578

Note: *, **, and *** indicate significance at the 10%, 5%, and 1% levels, respectively.

. Under the assumption that other factors are held constant, S and G on corporate performance are both significantly positive, however, the coefficient of E is not. The reasons may be as follows: On the one hand, the business activities of listed agricultural and forestry companies depend on the development and utilization of natural resources. Therefore, the public may think that these companies should shoulder more environmental responsibilities to offset their negative externalities. Even if these companies have good E performance, they will be viewed as completing their obligations, which will not increase corporate performance. On the other hand, due to the characteristics of the industry, all segments of society have low expectations for the S and G performance of these companies. Therefore, when their S or G performance is good, it will go beyond stakeholders’ expectations, which can boost market trust and improve corporate performance.

This paper divides the samples into two groups, listed agriculture firms and listed forestry companies, and uses 2SLS for estimation in each group. The results are presented in columns 5 and 6 of Table 9. The ESG performance of both sample groups is positively related to corporate performance at the 1% significance level, with a higher coefficient of ESG for listed agricultural companies. However, this does not necessarily demonstrate that listed agricultural companies can use ESG as a more effective incentive. To further investigate the differences between the two groups, this paper creates the following model for empirical analysis:

$$S_{i,t}=e_0+e_1{ESG}_{i,t}+e_{2}Ind+e_3{ESG}_{i,t}\ast Ind+e_4{\xi }_{i,t}\ast Ind+{\phi }_i+{\lambda }_t+{\epsilon }_{i,t}$$

(12)

where Ind is the industry dummy variable, which is 1 for forestry-listed companies and 0 for agriculture-listed companies. Results are shown in column 8 of Table 9. The coefficient of ${ESG}_{i,t}\ast Ind$ is not significant, indicating that there are no significant differences in the contribution effect of ESG on corporate performance between two groups. In addition, the result of the between-group difference test on the means of performance of agricultural and forestry-listed companies is not significant, further supporting this conclusion.

4.3. Robust Tests

To conduct robust tests, we replace the dependent variable with a single indicator, such as operating profit margin (OPM) [48] and book-to-market ratio (BM) [50]. Additionally, we reconstruct the index evaluation system of corporate performance based on the research of Wang Qian [51] and use the entropy weight method to calculate the comprehensive score (Score2) as a replacement for the dependent variable. All data are obtained from the CSMAR database. The coefficients of ESG are all positive at a 1% significance level (see

Table 10. Robust tests.

	OPM	BM	Score2
ESG	0.1173 **	0.0299 ***	0.0077 ***
	(0.0525)	(0.0096)	(0.0029)
Control variables	Yes	Yes	Yes
Individual effect	Yes	Yes	Yes
Time effect	Yes	Yes	Yes
Number of observations	1099	1099	1099
R2	0.2623	0.7520	0.7204
Adj_R2	0.1447	0.7125	0.6758

Note: **, and *** indicate significance at the 5%, and 1% levels, respectively.

), suggesting that the results are relatively robust and credible.

4.4. Mechanism Analysis

This paper investigates the moderating effects of tax incentives, regional marketization degree, and the proportion of female executives from the perspectives of government, market, and company. As shown in column 2 of

Table 11. Analysis of the mechanism.

	2SLS	2SLS	2SLS
ESG	0.0033 **	0.0038 **	0.0033 **
	(0.0014)	(0.0015)	(0.0015)
ESG*Tax	−0.0165 ***
	(0.0049)
Tax	0.0026
	(0.0041)
ESG*Market		−0.0016 ***
		(0.0006)
Market		−0.0026 **
		(0.0012)
ESG*Female			0.0084 **
			(0.0039)
Female			−0.0010
			(0.0043)
Controlling variables	Yes	Yes	Yes
Individual effect	Yes	Yes	Yes
Time effect	Yes	Yes	Yes
Number of observations	1099	1099	1099
R2	0.6514	0.6558	0.6584
Adj_R2	0.5949	0.6001	0.6031

Note: **, and *** indicate significance at the 5%, and 1% levels, respectively.

, the coefficient of ESG*Tax is −0.0165, which is significant at the 1% level, indicating that tax incentives reduce the positive effect of ESG on corporate performance of listed agricultural and forestry companies. The more tax incentives a company enjoys, the harder it is to leverage the positive role of ESG. Thus, we validate H2. Column 3 of Table 11 presents the result of the mechanism test for the regional marketization degree, which shows that the coefficient of ESG*Market is also negative and extremely significant. This finding supports H3, indicating that the degree of marketization diminishes the favorable effect of ESG on corporate performance. Even if a company operates in a highly market-oriented area with a better legal environment and more convenient resources, it may not be able to fully realize the positive function of ESG on corporate performance. The gender characteristic of executives has a significant impact on the operation and growth of a company. The mechanism test result for the proportion of female executives is displayed in column 4 of Table 11. The coefficient of ESG*Female is positive at the 5% significance level, indicating that H4 is proven. Indeed, companies with a higher proportion of female executives are better equipped to shoulder ESG responsibilities and better meet stakeholder requirements, thereby promoting the translation of ESG into economic outcomes more effectively.

In conclusion, tax incentives, regional marketization degree, and the proportion of female executives all represent important mechanisms through which ESG affects corporate performance of listed agricultural and forestry companies. In other words, the relationship between ESG and corporate performance is influenced by three typical stakeholders: the government, the market, and the executives. Although the endogeneity of empirical testing may not be controlled, the mechanism analyses in this section reveal more complex relationships between ESG and corporate performance, which serve to bolster the causal argument to some extent.

5. Discussion

At first glance, ESG responsibility may appear to be an altruistic act that incurs additional costs. However, the innate profit-seeking nature of companies necessitates self-interest. If companies can internalize ESG responsibility, it can contribute to achieving economic efficiency and social win–win goals. This paper investigates the relationship between ESG and corporate performance by analyzing relevant data from 156 listed agricultural and forestry companies in China from 2009 to 2021, guided by stakeholder theory, and controlling for reverse causality. To reflect corporate performance more comprehensively, this paper constructs an indicator system based on the document issued by the State Council of China, rather than selecting a single financial indicator commonly used in academic circles. Our findings are consistent with [29,48] and demonstrate that improved ESG performance incentivizes growth in corporate performance. Unlike other countries where top-down ESG hard regulation generates mandatory pressure, China’s ESG system is still in its exploratory stage, and companies’ ESG responsibilities are primarily voluntary. Therefore, there is uncertainty as to whether companies are motivated to improve their ESG performance in the absence of mandatory legal constraints. The findings of this paper provide evidence that even in the absence of legal compulsion, market mechanisms can still function to give firms an incentive to actively undertake ESG responsibilities to improve their ESG performance.

This paper offers new perspectives on the impact mechanism of ESG by exploring its effects from the perspective of stakeholders. We find that three crucial stakeholders—government, market, and executives—can all influence the relationship between ESG and corporate performance.

From the government’s standpoint, they expect to support disadvantaged industries through tax incentives. However, our findings show that the prevalent tax incentives in agricultural and forestry companies may not facilitate ESG’s constructive role. The more tax incentives listed companies receive, the more likely they are to become complacent, resulting in lower improvements in corporate performance despite good ESG performance. This implies that companies should not overly rely on government support for their development but also recognize the value of the market. If the government can guide companies to improve their ESG performance, it will enhance stakeholders’ confidence, which can promote the level of corporate performance.

From a market perspective, the regional degree of marketization can weaken the incentive effect of ESG on corporate performance. This is likely due to the fact that companies operating in highly marketized regions may already face implicit expectations to meet good ESG performance, making it less effective at driving economic outcomes. In other words, even companies in regions with low marketization can still leverage the incentive effect of ESG on corporate performance, giving them an advantage over those located in highly marketized regions. This suggests that ESG presents opportunities for companies with weak market resources to promote healthy competition and rejuvenate the market.

From the perspective of corporate executives, the higher the proportion of female executives, the stronger the positive effect of ESG on corporate performance. Despite the relatively low percentage of female executives, they can effectively regulate the incentive effect of ESG on corporate performance due to gender role features, social expectations, and positive signals from stakeholders. This finding sheds light on the internal management of companies.

6. Conclusions

This study aims to examine and evaluate the microeconomic impact of ESG, providing empirical evidence to more effectively promote ESG in China and other emerging nations. Results show that listed agricultural and forestry companies with superior ESG can achieve higher levels of corporate performance, leading to a potential win–win situation between companies and the sustainable growth of the economy. Increasing the ESG rating by one level can improve a comprehensive corporate performance by 0.0033, which is significant for China’s agricultural and forestry-listed companies, whose average performance is 0.0924. Moreover, S and G performances have a greater impact on corporate performance improvement than E performance. The favorable effect of ESG on performance does not differ significantly between listed agriculture and listed forestry companies, according to an industry comparison. Mechanistic analyses show that government, market, and executives all have an impact on the relationship between ESG and corporate performance, with tax incentives and the regional marketization degree having a negative moderating effect, but the proportion of female executives plays a positive moderating role.

This study provides several recommendations on how to enhance the microeconomic role of ESG. Firstly, listed agricultural and forestry companies should prioritize the needs of stakeholders and consider social and environmental benefits alongside economic benefits. Adopting ESG responsibility as a long-term strategy can be an effective approach. If these companies can fully leverage the potential of their industry characteristics, it will be beneficial in improving the level of ESG under the current evaluation system. This will communicate positive ESG signals to stakeholders and promote better corporate performance.

Secondly, a promising government and efficient factor markets must be integrated. Based on a comprehensive understanding of the industry’s development status, the government should timely adjust taxation and financial policies to support the listed agricultural and forestry companies. In addition, establishing supervisory mechanisms with clear rights and responsibilities for ESG would be a good idea. Only when the government strengthens supervision can it guide the listed agricultural and forestry companies to better assume their ESG responsibilities. In this way, companies can improve their ability to increase corporate performance by enhancing their ESG performance.

Finally, it must be emphasized that this research still has limitations. Despite our efforts to demonstrate a causal relationship between ESG and corporate performance, there are certain endogenous factors that we have not taken into account. For example, the impact of ESG may have a lag. Additionally, since the concept of ESG has only been introduced in China in recent years, ESG data for some years were generated and disclosed retrospectively after the establishment of ESG rating agencies, which may lead to errors in this study’s conclusions. In future research, we intend to employ more effective methods to address these issues.