Abstract
In this study, drawing on firm life cycle theory, we focus on the corporate performance of Environmental, Social, and Governance (ESG) engagement via financial stress and consider the moderate effect of transparency, financial slack, and environmental uncertainty. The industry-year fixed effects panel regression analysis is executed based on the data including 11,742 firm-year observations for 1,486 Chinese A-share listed companies from 2010 to 2020. The results show that ESG performance can significantly improve corporate performance at all life cycle stages, especially when the corporate is in the growth stage. Moreover, the mechanism analysis shows that the financial risk mediates the relation between ESG performance and corporate performance for the corporates in the growth and maturity stages. The association between ESG and corporate performance is more pronounced when corporate information disclosure quality is high. Moreover, financial slack moderates and undermine the association between ESG and corporate performance in the maturity stages. Similarly, for the maturity and decline stages of corporate, environmental uncertainty moderates and undermines the association between ESG and corporate performance. Besides offering scientific evidence for the role of ESG ratings in relieving financial pressure and promoting corporate performance in growth and maturity stages, the results can also inform the regulators and/or investors of the benefit of engaging in corporates sustainability transition, which has implications for both the success of the regulatory regime and the advancement of long-term investment philosophy.
1 Introduction
The economic outcome of corporates’ Environmental, Social, and Governance performance (ESGP) has become one of the hottest research aspects in the current global management and financial fields (; Yu et al., 2018; ; Skarmeas and Leonidou, 2013; ; ). Through ESG practice, corporates involve environmental, social, and governance factors into their management and operation processes. By improving ESGP, companies can effectively alleviate information asymmetry (Siew et al., 2016; ), build their reputation (), gain support from stakeholders (Weber, 2014; ), and promote corporate performance (; ). However, scholars who take the opposite view on corporate ESG construction argue that corporate investment in ESG activities may not make profits in the short term but instead restrict the flexibility of the corporate operating capital (Skarmeas and Leonidou, 2013), then expanding the exposure to financial risks, and ultimately damages the interests of shareholders (). Besides, as a corporate strategy, the role of ESG in different life cycle stages of a firm has received inadequate attention in the literature.
Firm life cycle theory suggests that the firm is like a living organism, which also goes through different stages such as birth, growth, maturity, and decline (; ; ). Prior studies show that corporates have disparate operating environments and financial conditions to differ across the life cycle stages, corporates require to adopt corresponding business strategies (; ), and strategies of ESG practices and ESG disclosure are no exception. Corporates need to dynamically adjust the relationship between input of ESG practices and financial outcomes according to their firm life cycle, therefore they can adapt to the current trend of sustainable development transformation, meanwhile meet the cash flow requirements for their development strategy. This study attempts to fill this gap in the literature by investigating the relationship between ESGP, financial risk, and corporate performance throughout the three stages of the life cycle.
Corporations in the growth stage are in the face of more market competition pressure, and have fewer resources at their disposal and not fully standardized management systems (), and their main development goal is to improve profitability. In contrast, corporates that are entering the maturity stage are usually relatively well positioned in the market and have the willingness and ability to engage in ESG activities more than only pursue profit. Conversely, corporates entering a decline stage have less organizational flexibility (), and shareholders will focus more on safeguarding their interests and less on the stakeholders’ interests. It is more relevant to study the relationship between ESGP and corporate performance at the dynamic level than at the static level, i.e., whether ESG activities will cause financial stress in different life cycle stage; does ESGP always enhance the performance of corporates at different life cycles?
Therefore, based on the theory of firm life cycle, this study explores the differences between ESGP, financial risks, and corporate performance in different life cycles and the reasons for their existence. The industry-year fixed effects panel regression analysis is executed based on the data including 11,742 firm-year observations for 1,486 Chinese A-share listed companies from 2010 to 2020. To control for heteroscedasticity, we correct the standard errors for the clustering of residuals at the firm level. Besides, considering the endogeneity that may bias our results, we adopt lagged regression and an instrumental variable (IV) approach that uses two-stage least squares (2SLS) regression analysis. The rest of the paper is organized as follows: Section 2 is the literature review and research hypothesis; Section 3 is the research design; Section 4 is the empirical analysis and hypothesis testing; Section 5 is the research conclusion and discussion of this study.
2 Literature review and hypotheses development
2.1 ESG and corporate performance
The existing literature has not reached a consensus regarding the relationship between ESG and corporate performance; in general, the current academic community believes that adverse ESG events in corporates will harm their performance (). Through ESG disclosure, companies can effectively enhance the transparency, reduce the degree of corporate information asymmetry, and further enhance investors’ long-term investment interests in companies (). According to the signal theory, the active disclosure of information by listed companies reflects their ability of operation, which clearly sending positive signals to the capital market. Also, through ESG information disclosure, corporates can effectively built their reputation among relevant stakeholder groups, and release their strategic intentions for sustainable development to the outside world (). In addition, ESG activities can also improve the organizational and management capabilities of corporates. Companies with better ESGP are also more attractive to employees, and employees have a higher sense of identity and belonging to that company (Weber, 2014; ). The research of Zhu and Tan, (2022) shows that ESG rating can significantly improve the green innovation ability of corporates by reducing financing constraints and improving managers’ environmental awareness (; ). Therefore, this leads us to the first hypotheses as follows:
Hypothesis 1:There is a negative relationship between ESGP and corporate performance.
2.2 ESG and corporate financial risk
The impact of ESG on corporate financial risks can be mainly explained via corporate governance and financing capacity. On one hand, the ESG governance concept can promote the dispersion of corporate stock equity and gender balance in management, and diversifying corporate equity can effectively improve the risk-taking level of the company (), and an excellent organizational structure can ensure scientific corporate decision-making. Meanwhile, management diversification can also improve corporate risk management. Companies led by male CEOs are usually willing to invest in projects with higher risks (), while a higher proportion of female board members can effectively promote the inhibitory effect of ESGP on corporate financial risks (Shakil, 2021). In addition, ESG disclosure by corporates can effectively reduce the risk of financial irregularities (Yuan et al., 2022). Corporates that attach importance to ESG activities can also reduce possible business contingencies, such as a lower probability of being prosecuted (), a stronger adaptive capacity, and lower chance to face stock price crash (; ; ).
On the other hand, improving their ESGP, corporates can effectively enhance their attractiveness in the capital market. Higher ESGP would lead to lower both corporate equity financing costs () and debt financing cost (). Due to the environmental protection and green financial concept, banks are more inclined to issue loans to corporates that disclose CSR information (Xu et al., 2021; ), the quality of non-financial information disclosed by corporates is positively correlated with the actual value of corporates. Also, considering the legitimacy of corporates (), especially in European and American capital markets, institutional investors are keener to invest in companies with better CSR performance (; ). Moreover, corporates’ participation in ESG activities is positively related to the issuance of green bonds and their own credit ratings (). The less attention a corporate pays to ecological protection, the lower its credit rating will be, and the higher its debt financing cost will be (Zerbib, 2019). This leads us to the second hypothesis:
Hypothesis 2:Financial risk mediates the relation between ESGP and corporate performance.
2.3 ESG, financial risk, corporate performance, and firm life cycle
The firm life cycle theory holds that for corporates in different life cycle stages, their environment, structure, strategy formulation, and decision-making methods are different (; ; ). With their continuous development, corporates’ earning capacity gradually decreases, while the probability of business changes gradually increases (). There are more than 20 definitions and determinants standards of firm life cycle now (; ), scholars such as believe that using three-level (growth, maturity, and decline) or four-level (start-up, growth, maturity, and decline) classification criteria can more accurately measure the life cycle of a corporate (). For the listed corporates, the start-up stage is usually combined with the growth stage, and therefore they go through only three stages: growth, maturity, and decline. Considering the distribution hypothesis problems caused by using the single indicator method and comprehensive indicator method, as well as the possible errors caused by profitability indicators (Spence, 1981; Wernerfelt, 1985; ), adopts operating cash flow, investment cash flow, and financing cash flow to comprehensively judge the firm life cycle perspective (). As a vital issue in corporates’ current long-term development strategy, ESG also requires a detailed analysis of different life cycles ().
There are few studies on the ESGP of growing companies. Although growing corporates have the advantages of higher development flexibility and faster operating income growth, meanwhile, their low market negotiation ability and low policy influence also limit their development. Due to the lack of a sound management mechanism and resources, corporations in the growth and growth stages focus more on solving current development problems and rarely take the initiative to fulfill corporate social responsibility (). On the other hand, Desa and Basu’s research shows that obtaining financing is critical for corporates in the growth stage to grow and develop (). Corporates in the growth stage have a higher degree of information asymmetry in the capital market due to their novel technology or profitability model, making it more difficult to raise external financing (Vogt, 1994), and making ESG disclosures can enhance investors’ interest in the Corporates, which in turn can lead to a relatively stable financial position.
Corporates at maturity stage have the characteristics of large production scale and diversified business scope, and have already occupied a certain position in the market (; ). Compared with growth stage companies, mature companies are usually under more pressure from society and need to improve their legitimacy by disclosing non-financial information (; ). At the same time, mature companies are more willing to invest capital in ESG activities to obtain long-term benefits in the future. Research by also shows that firm size is positively correlated with firm ESGP (). However, according to the free cash flow theory, mature companies are prone to over-investment when their financial conditions are relatively relaxed (; Triantis, 1994; Saravia, 2014), and the ESG disclosure of corporates may alleviate the agency problem faced by mature corporates.
Corporates in the decline stage usually experience a decrease in sales and a decline in market share. Due to the lack of new profit growth points, corporate cash flow shrinks. Compared with companies in the growth and mature stages, companies in decline stage are more likely to face financial distress (). However, to find new profitability, companies in decline stage are urgently required to invest a lot of money to develop new products and conduct operational promotion (). The expanding capital demands on the expenditure side of corporates and the obstacles faced by the financing side will make them more cautious in choosing investment targets. ESG activities will bring greater capital pressure on them, and corporates facing increasing survival pressure may not be able to undertake social responsibilities.
In general, we believe that corporates have different business objectives and encounter different risks at different life cycle stages, the impact of ESG in different life cycle stages has not been fully discussed. Therefore, the following hypotheses are proposed in this paper:
Hypothesis 3a:For corporates at the growth stage, financial risk cannot mediate the relation between ESGP and corporate performance.
Hypothesis 3b:For corporates at the maturity stage, financial risk mediates the relation between ESGP and corporate performance.
Hypothesis 3c:For corporates at the decline stage, financial risk cannot mediate the relation between ESGP and corporate performance.
3 Research design
3.1 Data collection
Based on data availability, this study uses the annual panel data of Chinese A-share listed companies from 2010 to 2020 as the study sample. Except for the Huazheng ESG data from the Wind database, we obtain all other financial data from China Stock Market & Accounting Research database (CSMAR). To ensure the validity of data, samples are screened according to the following principles: (1) samples of corporates with irregular transactions were excluded; (2) samples of corporates in the financial industry and real estate industry are excluded; (3) samples of corporates with asset-liability ratio greater than 1 were excluded; (4) samples with missing values on regression variables were excluded. Therefore, a total of 11,742 firm-year observations for 1,486 firms were finally obtained. In addition, to reduce the influence of outliers on the empirical results, all continuous variables in the paper are winsorized at the 1% and 99% quantiles.
3.2 Measurements
3.2.1 Corporate performance
Table 1 shows the definition of all variables in this study. Following previous study, we use Tobin’s Q ratio as the proxy to measure corporate performance (Uotila et al., 2009; ). Tobin’s Q ratio reflects the investor-to-business comprehensive evaluation of development prospects. Since stock market value changes are forward-looking and relatively difficult to be controlled by managers, Tobin’s Q index, based on market expectations, is robust in measuring corporate performance.
TABLE 1
| Type | Variable name | Notation | Measure | Source |
|---|---|---|---|---|
| Dependent | Corporate performance | Tobin’s Q | Market capitalization divided by book value | CSMAR |
| Independent | ESG Performance | ESG | Huazheng ESG rating indicators | Wind |
| Mediator | Corporate financial risk | Z-Score | Altman-Z indicator | CSMAR |
| Moderator | Information disclosure quality | DQ | List corporate information disclosure rating from Chinese Stock Exchange | CSMAR |
| Financial slack | FS | The equity liability ratio divided by the current ratio | Authors’ own calculations (AOC) | |
| Environmental uncertainty | EU | Standard deviation of the sales revenue of the sample corporates in the past five years after excluding the normal growth part and industry adjustment | AOC | |
| Control | Size of firm | Size | The logarithm of the company’s total assets | CSMAR |
| Corporate ownership | SOE | State-owned Corporates (SOE = 1); Non-state-owned Corporates (SOE = 0) | CSMAR | |
| Age of firm | Age | Take the logarithm of the current year minus the year the company went public and then add 1 | CSMAR | |
| Leverage | Lev | Total company liabilities divided by total company assets | CSMAR | |
| Growth of corporate | Grow | Operating income growth rate | CSMAR | |
| Institutional investor shareholding | INST | Institutional investors’ shareholding in total shares | CSMAR | |
| Ownership concentration | TTH | Shareholding ratio of top ten shareholders | CSMAR |
Definition of variable.
3.2.2 ESGP
In this study, we use the Huazheng ESG rating index to measure the ESGP of Chinese list corporates. Huazheng ESG rating system is one of the widely used ESG rating systems during academic research and for investing in China. Compared with other Chinese ESG rating systems, the Huazheng ESG rating has the advantages of wide coverage, early rating time, and high update frequency. By collecting data from various sources such as social responsibility reports, ESG reports, regulatory websites, and media information, Huazheng has divided the ESGP of Chinese corporates into 9 grades from C to AAA, and we assigned the 9 grades of C ∼ AAA as 1–9 in order in the empirical test of this study.
3.2.3 Corporate financial risk
We use the Altman Z-Score (Z-Score) calculated based on accounting data proposed by Altman (1,698)as a proxy to quantify the corporate financial risk (). The Z-Score are widely used in the assessment of corporate financial risk of listed companies (; ). The smaller the Z-score of the sample firms, the greater the financial risk of the firms, and conversely the smaller the financial risk. The Z-Score model for public firms is as follows:
Z = 1.2 (Working capital/Total assets) +1.4 (Retained earnings/Total assets) +3.3 (EBIT/Total assets) +0.6 (Market value of equity/Book value of total liabilities) +0.999 (Sales/Total assets).
3.2.4 Firm life cycle
In this study, we use cash flow patterns developed by , which utilize three cash flow types (operating, investing, financing) as a proxy to divide the firm life cycle into 5 stages, which are introduction, growth, mature, shake-out, and decline. Three cash flow types can take a positive or negative sign which results in 8 possible combinations, and each cash flow combinations represent the corporate status. For example, when a corporate with a negative operating cash flow, positive investment cash flow, and positive financing cash flow, that means the corporate relies on borrowing money to maintain production and operation, and its financial condition may have deteriorated, which belongs to the decline stage. In addition, considering that China’s A-share listed companies have passed the introduction stage, following previous research, this paper incorporated the introduction stage into the growth stage, meanwhile incorporating the shake-out stage into the decline stage, thus dividing the listed companies into three stages: growth stage, mature stage, and decline stage. The cash flow characteristics of each stage are shown in Table 2.
TABLE 2
| Predicted sign | Growth | Mature | Decline | |||||
|---|---|---|---|---|---|---|---|---|
| Introduction | Growth | Mature | Shake-out | Shake-out | Shake-out | Decline | Decline | |
| Cash flow of operating activities | - | + | + | - | + | + | - | - |
| Cash flow of investing activities | - | - | - | - | + | + | + | + |
| Cash flow of financing activities | + | + | - | - | + | - | + | - |
Cash flow patterns of firm at different life cycle stages.
3.2.5 Control variables
The link between ESG and corporate performance may be influenced by several other variables that we need to control for. Following previous research, we included several control variables, which are related to corporate characteristics, financial status, and corporate governance, including (1) Size of firm (Size); (2) The nature of the corporate (SOE); (3) Age of firm (Age); (4) Leverage (Lev); (5) Growth of business (Grow); (6) Institutional investor shareholding ratio (INST); (7) Equity concentration (TTH). In addition, year-fixed effects and industry-fixed effects are added to the model.
3.3 Research methodology
To test the mediation effect of financial risk on the relationship between ESGP and corporate performance, this study refers to the approach provided by , the following steps establishing the mediation test:
Firstly, we conduct the regression model between ESG and corporate performance below:
Secondly, we conduct the regression model between ESG and financial risk below:
Thirdly, we conduct the regression model between ESG、financial risk, and corporate performance below:
Moreover, for test moderate effect, we conduct the modified regression model below:Among these formulas, the subscript t represents the year, i represents the corporate. This study focuses on the coefficient , which reflects the impact of ESG on corporate performance. Besides, when coefficient is significant, the indirect mediation effect is equal to the product of coefficient , and the direct mediation effect is the coefficient . We estimate the model using ordinary least squares (OLS) with industry and year fixed effects, represents the year effects, represents the industry effects. To control for heteroscedasticity, we correct the standard errors for the clustering of residuals at the firm level.
4 Empirical result and discussion
4.1 Estimation method
We carry out F-test, unit root test (Fisher test), Wald and Wooldridge test on panel data respectively, and the results in Tables 3, 4 show that the data of sample has strong individual effect, autocorrelation, and heteroscedasticity. After the Hausman test on the data, we choose to use the fixed effect model to estimate the data, and use the company level clustering robust standard error to reduce the impact of the variance of the disturbance term on the empirical results.
TABLE 3
| Test | Statistic | p-value |
|---|---|---|
| Hausman test | chi2 (19) = 397.90 | 0.0000 |
| Wald test | chi2 (1,488) = 1.4e+37 | 0.0000 |
| Wooldridge test | F (1,1408) = 1,002.983 | 0.0000 |
Autocorrelation and heteroscedasticity test.
TABLE 4
| Variable | Chi-square statistic | p-value |
|---|---|---|
| Tobin’s Q | 36.3778*** | 0.0000 |
| ESG | 31.8982*** | 0.0000 |
| Z-Score | 28.8776*** | 0.0000 |
| TA | 35.2597*** | 0.0000 |
| Age | 54.8585*** | 0.0000 |
| Grow | 51.1199*** | 0.0000 |
| Lev | 32.7320*** | 0.0000 |
| INST | 40.4302*** | 0.0000 |
| TTH | 27.2771*** | 0.0000 |
Stability test.
4.2 Descriptive statistics
Table 5 reports the descriptive statistical results of the main variables. The Tobin’s Q mean value of the sample corporates is 2.295, the variance is 1.884, and the median is 1.747, indicating that the overall value level of the sample corporates in the financial market is high. The average ESG rating of the sample corporates is 6.299, the standard deviation is 1.057, and the median is 6, which proves that the ESG rating of the sample corporates is between BB-AA. At the same time, we divide the samples into three groups: growth stage, maturity stage, and decline stage according to the division standard of corporate life cycle stages, and test the significance of the mean difference between the groups on the main variables. As shown in Table 6, the ESG rating of corporates in the maturity stage is the highest, followed by the growth stage and the decline stage. Financial risk is significantly higher for corporates in the growth stage relative to corporates in the maturity and decline stages. In addition, corporates in the maturity and decline stages have higher corporate performance relative to corporates in the growth stage.
TABLE 5
| Variable | N | Mean | Sd | Min | P50 | Max |
|---|---|---|---|---|---|---|
| Tobin’s Q | 11742 | 2.295 | 1.884 | 0.233 | 1.747 | 10.49 |
| ESG | 11742 | 6.299 | 1.057 | 3 | 6 | 9 |
| Z-Score | 11742 | 5.369 | 5.915 | 0.148 | 3.459 | 37.27 |
| TA | 11742 | 21.97 | 1.074 | 19.95 | 21.86 | 25.13 |
| Age | 11742 | 2.761 | 0.385 | 1.486 | 2.808 | 3.466 |
| Grow | 11742 | 0.198 | 0.402 | −0.499 | 0.129 | 2.499 |
| Lev | 11742 | 0.391 | 0.193 | 0.0490 | 0.383 | 0.840 |
| Soe | 11742 | 0.225 | 0.417 | 0 | 0 | 1 |
| TTH | 11742 | 58.42 | 14.15 | 24.22 | 59.73 | 86.74 |
| INST | 11742 | 39.11 | 24.59 | 0.183 | 39.76 | 87.18 |
Descriptive statistics.
TABLE 6
| Variable | Firm life-cycle stages | T-statistic | ||||
|---|---|---|---|---|---|---|
| Growth (5,492) | Mature (4,209) | Decline (1996) | Growth-mature | Mature-decline | Decline-growth | |
| Tobin’s Q | 2.205 | 2.379 | 2.315 | −4.566*** | 1.2299 | 2.289** |
| ESG | 6.301 | 6.365 | 6.161 | −2.975*** | 6.8903*** | −5.135*** |
| Z-Score | 4.255 | 6.361 | 6.172 | 18.677*** | 1.0284 | 14.083*** |
Descriptive statistics at different life cycle stages.
4.3 Analysis of main regression results
4.3.1 ESG and corporate performance
Table 7 shows the regression results between ESGP and corporate performance. Column (1) in Table 7 uses the full sample data for the regression formula, and columns (2), (3) and (4) use the data of three sub-samples: growth stage, maturity stage and decline stage. It can be seen from Table 7 that the regression coefficient between ESGP and corporate performance is 0.150 under the full sample data, and it is significant at 1% level. Thus, this result rejects Hypothesis 1, which shows that ESGP is positively relate to corporate performance, which is consistent with previous research (G ; Yu et al., 2018; ). In addition, the regression results of the models in columns (2) (3) and (4) show that the regression coefficients of ESGP and corporate performance of corporates in different life cycles are positive, and significant at 1% level. By further distinguishing the regression results of samples in different life cycle stages, it can be found that there is a significant positive correlation between ESGP and corporate performance in both growth, maturity, and decline stages of the firm, and the positive promotion of ESGP in the growth stage are the largest. Although growth corporates face high financing constraints and weak customer base (; Wu et al., 2008), they are usually more innovative and flexible. Investors are more willing to provide financial support to growing corporates to make profits as soon as possible (Saravia, 2014). The ESGP of corporates in the growth stage enhances investors’ confidence in them (), and the positive effect of ESGP on the financing ability of corporates is further amplified, which is consistent with the previous study results of .
TABLE 7
| Variable | All | Growth | Mature | Decline |
|---|---|---|---|---|
| (1) | (2) | (3) | (4) | |
| Tobin’s Q | Tobin’s Q | Tobin’s Q | Tobin’s Q | |
| ESG | 0.150*** | 0.167*** | 0.122*** | 0.105*** |
| (0.022) | (0.025) | (0.031) | (0.033) | |
| Constant | 15.988*** | 14.754*** | 14.614*** | 20.126*** |
| (0.766) | (0.748) | (1.128) | (1.249) | |
| Industry | Yes | Yes | Yes | Yes |
| Year | Yes | Yes | Yes | Yes |
| R-square | 0.448 | 0.481 | 0.421 | 0.518 |
| Adjusted R2 | 0.446 | 0.477 | 0.416 | 0.509 |
| N | 11742 | 5,492 | 4,209 | 1996 |
| Empirical p-value | ||||
| Growth-Mature | 0.007*** | |||
| Mature-Decline | 0.347 | |||
| Decline-Growth | 0.068* | |||
Basic regression results.
Note: (1) * * *, * * and * are significant at the level of 1%, 5% and 10% respectively, and the T value in brackets (based on the clustering robust standard error at the company level); (2) “Empirical p-value” is used to test the significance of the difference in ESG variable coefficients between sub sample groups, and is obtained by bootstrap 2000 times.
4.3.2 The mediation effect of corporate financial risk
We refer to method to test the intermediary mechanism of corporate financial risk. Table 8 shows the regression results using the full sample data. The regression results in column (2) show that the regression coefficient of ESGP on corporate financial risk (Z-score) is 0.325, which is significantly positive at the 1% level, indicating that ESGP significantly reduces corporate financial risk. At the same time, in the regression results in column (3), the regression coefficient between corporate financial risk (Z-score) and corporate performance is significantly positive at 1% level, which indicates that reducing corporate financial risk has a positive effect on corporate performance. Since the regression coefficients of ; ,; are significant, it can be judged that there is a mediating effect of financial risk in the process of affecting corporate performance by ESGP according to the stepwise test mechanism. ESGP improves corporate financial performance by reducing corporate financial risk, and the original Hypothesis 2 is accepted. To ensure the robustness of the mediating effect, whether the product of ; is equal to 0 is tested by using the Sobel (1982) method as well as the Bootstrap sampling method (1,000 times of sampling) (Sobel, 1982; ). Both the direct and indirect effect are significantly different from 0, which is consistent with the above results.
TABLE 8
| (1) | (2) | (3) | |
|---|---|---|---|
| Tobin’s Q | Z-Score | Tobin’s Q | |
| ESG | 0.150*** | 0.336*** | 0.086*** |
| (0.022) | (0.073) | (0.017) | |
| Z-Score | 0.189*** | ||
| (0.008) | |||
| Constant | 15.988*** | 28.261*** | 10.648*** |
| (0.766) | (2.527) | (0.634) | |
| Industry | Yes | Yes | Yes |
| Year | Yes | Yes | Yes |
| R-square | 0.448 | 0.427 | 0.650 |
| Adjusted R2 | 0.446 | 0.425 | 0.649 |
| N | 11742 | 11742 | 11742 |
| Sobel test (Z) | 7.338*** | ||
| Bootstrap (1,000) | 7.76*** | ||
The mediation effect of corporate financial risk.
4.3.3 The mediation effect of corporate financial risk in different life cycles
In this section, we test whether corporate financial risk can play a mediating role in the process of affecting corporate performance by ESGP under different life cycles. Table 9 presents the results of mediation test, only the coefficient of ESG and Z-Score in columns (8) is not significant. This shows that the mediating effect of corporate financial risk is only exist for the corporates at the growth and maturity stages, meanwhile, the results of the Sobel test and Bootstrap test also verify this conclusion, therefore Hypotheses 3b, Hypotheses 3C are accepted and Hypothesis 3a is rejected. The reason for this phenomenon may be that corporates in the decline stage are usually less competitive in the market (), and their reduced profitability leads to a deterioration of their financial situation (), and investing the ESG project with poor short-term return rate of expenditure may elevate the financial pressure on corporates (; ). Also, corporates in the decline stage usually do not conform to the investment propensity of institutional investors because of low efficiency, and the contribution of ESGP to the enhancement of their financing ability is diminished (; ).
TABLE 9
| Growth | Mature | Decline | |||||||
|---|---|---|---|---|---|---|---|---|---|
| (1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | (9) | |
| Tobin’s Q | Z-Score | Tobin’s Q | Tobin’s Q | Z-Score | Tobin’s Q | Tobin’s Q | Z-Score | Tobin’s Q | |
| ESG | 0.167*** | 0.221*** | 0.114*** | 0.122*** | 0.456*** | 0.039 | 0.105*** | 0.133 | 0.084*** |
| (0.025) | (0.058) | (0.020) | (0.031) | (0.120) | (0.024) | (0.033) | (0.134) | (0.026) | |
| Z-Score | 0.239*** | 0.183*** | 0.156*** | ||||||
| (0.012) | (0.009) | (0.012) | |||||||
| Constant | 14.754*** | 20.942*** | 9.754*** | 14.614*** | 28.924*** | 9.308*** | 20.126*** | 39.934*** | 13.908*** |
| (0.748) | (1.984) | (0.602) | (1.128) | (3.683) | (0.977) | (1.249) | (4.730) | (1.061) | |
| Controls | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Industry | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Year | 0.481 | 0.422 | 0.677 | 0.421 | 0.446 | 0.645 | 0.518 | 0.467 | 0.689 |
| R2 | 0.477 | 0.418 | 0.674 | 0.416 | 0.441 | 0.642 | 0.509 | 0.456 | 0.683 |
| R2_A | 5,492 | 5,492 | 5,492 | 4,209 | 4,209 | 4,209 | 1996 | 1996 | 1996 |
| Sobel test(Z) | 4.264*** | 5.804*** | 1.225 | ||||||
| Bootstrap (1,000) | 4.22*** | 5.66*** | 0.202 | ||||||
The mediation effect of corporate financial risk in different life cycles stages.
4.3.4 Endogenous check
Further, we use lagged regression as well as an instrumental variable (IV) approach to avoid the bias from endogeneity.
Firstly, we regress independent variables by using one-, three-, and five-period lagged ESG variables to test the impact of changes in ESGP on a corporate’s future performance. Test results in Table 10 shows that there is a significant positive relationship between ESG lagged variables still and corporate performance, which is consistent with the benchmark regression. It indicates that corporate performance is affected by past ESGP and ESGP has a long-term contributory effect.
TABLE 10
| (1) | (2) | (3) | |
|---|---|---|---|
| Tobin’s Q | Tobin’s Q | Tobin’s Q | |
| L.ESG | 0.120*** | ||
| (0.022) | |||
| L3.ESG | 0.106*** | ||
| (0.026) | |||
| L5.ESG | 0.069** | ||
| (0.031) | |||
| _cons | 13.617*** | 14.357*** | 15.083*** |
| (0.784) | (0.876) | (1.017) | |
| Controls | Yes | Yes | Yes |
| industry | Yes | Yes | Yes |
| year | Yes | Yes | Yes |
| r2 | 0.438 | 0.456 | 0.419 |
| r2_a | 0.436 | 0.453 | 0.415 |
| N | 9,930 | 7,138 | 4,941 |
Lagged effect results.
Secondly, high-performance corporate may have more disposable capital to invest in ESG activities, thereby causing a two-way causal problem. This paper according to the research by , and uses the mean of ESG ratings of all listed firms within the province where the corporate is incorporated (ESG_IV1) and the mean of ESG ratings of firms in the same industry (ESG_IV2) as instrumental variables. The reasons for selecting both as instrumental variables are that: First, firms in close geographical proximity may be influenced by the same policies and regulations and develop similar ESG management preferences due to their similar economic, political, and competitive environments, however, the means of ESG rating of corporates across the province are not related to individual corporate performance; Second, corporates in the same industry have strong similarities in production and operation, and the industry own attributes affect the attitude of corporates in that industry toward ESG, but the means of ESG rating of all corporates in the industry are not related to the performance of individual corporate. Therefore, we use the two-stage least squares (2SLS) to test the instrumental variables ESG_IV1 and ESG_IV2. In Table 11, column (1) shows the first-stage regression results, and column (2) shows the second-stage regression results, which indicates that the hypothesis that instrumental variables are unidentified and weak instrumental variables can be rejected, and the instrumental variables are exogenous. Meanwhile, the regression results of the second stage show that ESGP is significantly positively correlated with corporate performance, which is consistent with the above conclusions.
TABLE 11
| First stage | Second stage | |
|---|---|---|
| ESG | Tobin’s Q | |
| ESG | 0.157** | |
| (0.068) | ||
| ESG_IV1 | 0.861*** | |
| (0.075) | ||
| ESG_IV2 | 0.788*** | |
| (0.046) | ||
| _cons | −10.786 | 15.994*** |
| (0.675) | (0.765) | |
| Controls | Yes | Yes |
| Industry | Yes | Yes |
| Year | Yes | Yes |
| R-square | 0.218 | 0.448 |
| Adjusted R2 | 0.215 | 0.436 |
| Kleibergen-Paap rk LM (χ2) | 150.04*** | |
| Cragg-Donald Wald F (χ2) | 244.77 | |
| Hansen J statistic (χ2) | 0.2075 | |
| N | 11928 | 11928 |
Test results of IV.
4.3.5 Robustness check
We conduct two additional tests to improve the robustness of the obtained results. First, considering that there may be a misestimate in using a single indicator to reflect corporate performance, this part uses two corporate financial performance indicators: return on assets (ROA) and return on net assets (ROE), to replace Tobin’s Q as the measurement of corporate performance. The results in Table 12 show that the coefficients of ESG on ROA and ROE are significantly positive at the 1% level, indicating that ESGP can still improve corporate performance.
TABLE 12
| All | Growth | Mature | Decline | All | Growth | Mature | Decline | |
|---|---|---|---|---|---|---|---|---|
| (1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | |
| ROA | ROA | ROA | ROA | ROE | ROE | ROE | ROE | |
| ESG | 0.009*** | 0.007*** | 0.008*** | 0.010*** | 0.017*** | 0.014*** | 0.014*** | 0.021*** |
| (0.001) | (0.001) | (0.001) | (0.002) | (0.002) | (0.003) | (0.003) | (0.004) | |
| Constant | −0.239*** | −0.138*** | −0.279*** | −0.424*** | −0.616*** | −0.403*** | −0.701*** | −0.882*** |
| (0.027) | (0.022) | (0.031) | (0.049) | (0.049) | (0.056) | (0.069) | (0.122) | |
| Controls | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Industry | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Year | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| R2 | 0.251 | 0.212 | 0.327 | 0.242 | 0.175 | 0.133 | 0.233 | 0.201 |
| R2_A | 0.248 | 0.206 | 0.321 | 0.227 | 0.172 | 0.126 | 0.226 | 0.185 |
| N | 12235 | 5,686 | 4,335 | 2,152 | 12235 | 5,686 | 4,335 | 2,152 |
Replacement of independent variables.
Second, to avoid the controversy of using a single agency to compile the index, we use the Rankins ESG rating (ESG_H) to measure the company’s ESGP. This rating system is widely used for CSR rating and ESG rating in China. It uses the nine-level evaluation index of C-AAA to measure the ESGP of Chinese A-share listed companies. We assign the rating results as 1-9 in turn. Table 13 reports the regression results between ESG_H and corporate performance at different firm life stages. Except for the recession stage (only 84 samples), the ESG_H coefficients of the regression of the whole sample and the sub-samples of the growth stage and the mature stage are significantly positive at least at the 5% level, which is consistent with the above conclusions too.
TABLE 13
| All | Growth | Mature | Decline | |
|---|---|---|---|---|
| (1) | (2) | (3) | (4) | |
| Tobin’s Q | Tobin’s Q | Tobin’s Q | Tobin’s Q | |
| ESG_H | 0.333*** | 0.550*** | 0.334** | −0.382 |
| (0.118) | (0.199) | (0.155) | (0.312) | |
| _cons | 17.024*** | 18.596*** | 16.179*** | 16.021*** |
| (2.532) | (3.321) | (3.778) | (5.290) | |
| Controls | Yes | Yes | Yes | Yes |
| Industry | Yes | Yes | Yes | Yes |
| Year | Yes | Yes | Yes | Yes |
| R2 | 0.390 | 0.514 | 0.359 | 0.564 |
| R2_A | 0.359 | 0.437 | 0.299 | 0.435 |
| N | 555 | 192 | 279 | 84 |
Replacement of dependent variables.
5 Additional test
5.1 Analysis of non-linear relationship between ESG and corporate performance
To further explore the non-linear relationship between ESGP and corporate performance, this part adds the quadratic term (ESG2) of ESGP to formula (1) for regression. The Table 14 shows that the regression using the full sample data reveals that after adding the quadratic term, ESGP is still significantly positively correlated at 1% level. The coefficient on ESG2 is significantly positive at the 1% level, which indicates that there is a U-shaped relationship between ESG and corporate performance implying there is an extreme value for the promotion of corporate performance by ESG. When the ESG rating exceeds this extreme value, corporate performance increases more with the improvement of ESG rating. At the same time, columns (2), (3) and (4) show the regression results using different life cycle sub samples. The coefficients on ESG and ESG2 are least significant at the 5% level, which also proves that there is a non-linear relationship between ESGP and corporate performance at any stage of the firm life cycle.
TABLE 14
| All | All | Growth | Mature | Decline | |
|---|---|---|---|---|---|
| (1) | (2) | (3) | (4) | (5) | |
| Tobin’s Q | Tobin’s Q | Tobin’s Q | Tobin’s Q | Tobin’s Q | |
| ESG | 0.150*** | 0.157*** | 0.170*** | 0.126*** | 0.127*** |
| (0.022) | (0.023) | (0.025) | (0.031) | (0.039) | |
| ESG2 | 0.054*** | 0.060*** | 0.050*** | 0.047** | |
| (0.012) | (0.014) | (0.017) | (0.021) | ||
| Constant | 15.988*** | 16.176*** | 15.066*** | 14.794*** | 20.078*** |
| (0.766) | (0.760) | (0.744) | (1.118) | (1.234) | |
| Controls | Yes | Yes | Yes | Yes | Yes |
| Industry | Yes | Yes | Yes | Yes | Yes |
| Year | Yes | Yes | Yes | Yes | Yes |
| R2 | 0.448 | 0.450 | 0.483 | 0.423 | 0.520 |
| R2_A | 0.446 | 0.448 | 0.479 | 0.417 | 0.510 |
| N | 11742 | 11742 | 5,492 | 4,209 | 1996 |
Non-linear test results.
5.2 The moderate effect of corporate information disclosure quality
At present, Chinese corporates’ ESG ratings greatly rely on the corporates’ ESG and CSR reports disclosed by corporates themselves, meanwhile the China Securities Regulatory Commission (CSRC) has not yet issued a unified ESG information disclosure standard. Therefore, the quality of corporate information disclosure will greatly affect the trust of stakeholders in the ESG rating of corporates which then impacts the investment interest of investors. To test the moderate effect of the quality of corporate information disclosure, we use the four-grade rating index of the Shanghai Stock Exchange and Shenzhen Stock Exchange on the quality of information disclosure of listed companies as the proxy variable (DQ) of the quality of corporate information disclosure (A = excellent, B = good, C = pass, D = fail). Also, considering the heterogeneity of the firm life cycle, data of three sub samples of growth, maturity, and decline are used for regression. The results in Table 15 show that the higher the degree of truthful, accurate, complete, timely, and fair disclosure of information by listed companies, the more acceptable the ESGP by relevant stakeholders. Adequate corporate information transparency represents good internal management () and it also compensates for the disadvantaged position of investors due to information asymmetry (). The higher the degree of investors’ trust in corporate ESG disclosure, the greater the improvement of ESGP on corporate performance.
TABLE 15
| All | Growth | Mature | Decline | |
|---|---|---|---|---|
| (1) | (2) | (3) | (4) | |
| Tobin’s Q | Tobin’s Q | Tobin’s Q | Tobin’s Q | |
| ESG | 0.147*** | 0.156*** | 0.115*** | 0.126*** |
| (0.022) | (0.024) | (0.032) | (0.038) | |
| DQ | 0.163*** | 0.170*** | 0.154*** | 0.157** |
| (0.035) | (0.041) | (0.054) | (0.063) | |
| ESG*DQ | 0.152*** | 0.145*** | 0.152*** | 0.138*** |
| (0.026) | (0.034) | (0.038) | (0.040) | |
| Constant | 16.105*** | 14.916*** | 14.768*** | 20.036*** |
| (0.754) | (0.736) | (1.116) | (1.222) | |
| Controls | Yes | Yes | Yes | Yes |
| Industry | Yes | Yes | Yes | Yes |
| Year | Yes | Yes | Yes | Yes |
| R2 | 0.454 | 0.486 | 0.426 | 0.523 |
| R2_A | 0.452 | 0.482 | 0.421 | 0.512 |
| N | 11742 | 5,492 | 4,209 | 1996 |
The moderate effect of corporate information disclosure quality.
5.3 The moderate effect of corporate financial slack
Previous research has found that in the face of the complex and changeable external business environment, corporates often adopt conservative financial policies and retain certain excess financial resources to deal with risks (). We use the equity liability ratio divided by the current ratio to measure the financial slack (Xiaofang, 2017). The degree of financial slack of a corporate reflects its financial flexibility, which is the ability of a corporate to meet its capital needs with low risk. Table 16 shows that the coefficient of the interaction term (ESG*FS) between ESG and financial slack in the full sample regression is significantly negative, which indicates that the impact of corporate financial slack on the relationship between ESG and corporate performance has a significant negative moderate effect. In other words, for corporates with low financial freedom and weak ability to meet their own capital needs, ESG has a greater role in promoting corporate performance. ESG can effectively improve the ability of corporates with low financial freedom to raise funds from outside, thus reducing the dependence of corporates on internal financing. Further distinguishing between different life cycle stages, for the mature corporates, financial slack has a significant negative moderate effect which might imply that although mature corporates have a strong ability to obtain capital (), excessive levels of corporate financial flexibility lead to slack management and increased agency costs (Triantis, 2000). However, at the growth and decline stages, the situation of high financing constraints and poor financial liquidity, corporates be compelled to execute relatively conservative financial policies to keep redundant financial resources which can buffer the risks caused by sudden changes in the external environment.
TABLE 16
| All | Growth | Mature | Decline | |
|---|---|---|---|---|
| (1) | (2) | (3) | (4) | |
| Tobin’s Q | Tobin’s Q | Tobin’s Q | Tobin’s Q | |
| ESG | 0.163*** | 0.178*** | 0.132*** | 0.110*** |
| (0.022) | (0.026) | (0.031) | (0.034) | |
| FS | 0.097*** | 0.083*** | 0.076** | 0.127*** |
| (0.020) | (0.021) | (0.030) | (0.046) | |
| ESG* FS | −0.035*** | −0.022 | −0.057*** | −0.013 |
| (0.012) | (0.014) | (0.015) | (0.020) | |
| Constant | 17.004*** | 15.250*** | 15.275*** | 21.209*** |
| (0.831) | (0.770) | (1.190) | (1.327) | |
| Controls | Yes | Yes | Yes | Yes |
| Industry | Yes | Yes | Yes | Yes |
| Year | Yes | Yes | Yes | Yes |
| R2 | 0.442 | 0.477 | 0.417 | 0.512 |
| R2_A | 0.440 | 0.473 | 0.411 | 0.502 |
| N | 11917 | 5,526 | 4,247 | 2090 |
The moderate effect of corporate financial slack.
5.4 The moderate effect of environmental uncertainty
Previous studies have shown that business strategies are closely related to the market environment in which the corporate is operate (Ward and Lewandowska, 2008). When the business environment is order and stable, the corporate is usually better able to confirm the current market situation and make correct business decisions. Otherwise, the corporate will pay more adaptation cost. We use the fluctuation of corporate sales as the proxy of environmental uncertainty (EU), which is the standard deviation of the sales revenue of the sample corporates in the past five years after excluding the normal growth part and industry adjustment (; Shen and Yu Peng, 2012). The higher the EU value, the stronger the environmental uncertainty faced by the corporate. Table 17 shows that environmental uncertainty has a significant weakening and restraining effect on the impact of ESG on corporate performance. For corporates with low operating environment uncertainty, ESG has a greater role in promoting corporate performance. This indicates that when the business environment is uncertain, the competition among corporates is more intense, which makes them reduce their investment in ESG, loosening the close connection between the corporate and relevant stakeholders, which eventually affects the corporate performance. On the contrary, when the business environment is stable, the competitive pressure on the corporate is less, and has the spare power to invest in the ESG field to improve the corporate image. For growth stage corporates, due to the higher flexibility in business strategies, corporate can better adjust the direction of operation in complex business environments.
TABLE 17
| All | Growth | Mature | Decline | |
|---|---|---|---|---|
| (1) | (2) | (3) | (4) | |
| Tobin’s Q | Tobin’s Q | Tobin’s Q | Tobin’s Q | |
| ESG | 0.136*** | 0.143*** | 0.096*** | 0.123*** |
| (0.023) | (0.026) | (0.032) | (0.037) | |
| EU | 0.013 | 0.015 | 0.011 | −0.002 |
| (0.026) | (0.028) | (0.044) | (0.038) | |
| ESG*EU | −0.044** | −0.037 | −0.071** | −0.038* |
| (0.019) | (0.031) | (0.032) | (0.021) | |
| Constant | 17.008*** | 14.466*** | 15.833*** | 21.585*** |
| (0.807) | (0.776) | (1.075) | (1.479) | |
| Controls | Yes | Yes | Yes | Yes |
| Industry | Yes | Yes | Yes | Yes |
| Year | Yes | Yes | Yes | Yes |
| R2 | 0.452 | 0.488 | 0.420 | 0.531 |
| R2_A | 0.450 | 0.482 | 0.412 | 0.519 |
| N | 8,709 | 3,958 | 3,078 | 1,627 |
The moderate effect of environmental uncertainty.
6 Conclusion
Under the comprehensive green and low-carbon transformation, Chinese corporates’ promotion of ESG construction is one of the most vital ways to achieve high-quality and sustainable development. Based on firm life-cycle perspective, and using the data of 1,486 Chinese A-share listed companies from 2010 to 2020, we analyze the dynamic relationship among ESGP, corporate financial risk, and corporate performance at different life cycle stages, and consider the moderating effect of internal and external factors. The results of the study passed the robustness test (substitution variable method) and endogenous test (lagged regression and IV method).
Overall, this finding provides several contributions to the literature. First, this study diverse the economic consequences of ESGP literature with firm life cycle theory, which provides new evidence to support ESGP on promoting corporate performance in both growth, mature, and decline stages. But we also find that, for the corporate at the decline stage, investing in ESG activities or ESG practices might take up internal resources and increase financial pressure. Second, this study focuses on the economic consequences of Chinese corporates’ ESGP, which enriches the research on ESGP in developing countries. Third, this paper also analyzes the heterogeneity of corporate ESGP with different internal and external conditions, including the extent of information disclosure quality, financial slack, and environmental uncertainty, which extend the strands of ESG literature.
This study also offers several practical implications. First, this study provides evidence of shift in business managers’ view of ESG, establishes ESG awareness in the early stage of development, and then realizes “profit with meaning”. Second, the regulatory authorities should strengthen the guidance on the ESG practice and information disclosure of corporates. While further improving the ESG disclosure system of listed companies, regulators should also launch the ESG information disclosure management opinions of SMEs, thereby cultivating the concept of sustainable development at the initial stage of corporate construction. Third, investors should establish a sustainable investment philosophy as early as possible, compared with financial return, the performance for corporate fulfillment of consumer, environmental and social responsibilities is supposed to have a greater proportion of impact on the investment decisions making. Especially for the growth corporates with a high information asymmetry, ESGP could show the potential for the development of corporates in the capital market.
This study also has some limitations. First, this paper uses the Huazheng ESG rating to measure the ESG performance of corporates, although this study has conducted robustness tests with Rankins ESG rating, there still exists rating divergence from different rating agencies on the same corporate. In future research, we will further consider the moderating effect of ESG rating divergence on ESG rating. Second, considering the difficulties of data collection, this paper chooses China’s A-share listed companies as the research samples, the empirical results may nevertheless be affected by selection bias. Therefore, it is necessary to expand the study samples to SMEs, and further explore the ESG cognition, performance, and economic consequences of SMEs.
Statements
Data availability statement
The data analyzed in this study is subject to the following licenses/restrictions: This data that support the findings of this study are available from the corresponding author upon reasonable request. Requests to access these datasets should be directed to Shang Gao, 1908765975@qq.com.
Author contributions
SG: Conceptualization, Methodology, Writing—Original Draft FM: Supervision, Funding acquisition WW: Data Curation WC: Software.
Funding
This research is financially supported by National Natural Science Foundation of China (Grant. 71972013) and Educational Commission of Guangdong Province, China (Grant. 2022WCXTD022).
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
References
1
AdizesI. (1990). Corporate lifecycles: How and why corporations grow and die and what to do about it. Hoboken, New Jersey, U.S: Prentice-Hall.
2
AdizesI. (1979). Organizational passages-Diagnosing and treating lifecycle problems of organizations. Organ. Dyn.8 (1), 3–25. 10.1016/0090-2616(79)90001-9
3
AliS.JiangJ.AhmadM.UsmanO.AhmedZ. (2022). A path towards carbon mitigation amidst economic policy uncertainty in BRICS: An advanced panel analysis. Environ. Sci. Pollut. Res.29 (41), 62579–62591. 10.1007/s11356-022-20004-8
4
AliS.ZhangJ.UsmanM.KhanF. U.IkramA.AnwarB. (2019). Sub-national institutional contingencies and corporate social responsibility performance: Evidence from China. Sustainability11 (19), 5478. 10.3390/su11195478
5
AltmanE. I. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. J. Finance23 (4), 589–609. 10.1111/j.1540-6261.1968.tb00843.x
6
AnderssonM.BaltzopoulosA.LööfH. (2012). R&D strategies and entrepreneurial spawning. Res. Policy41 (1), 54–68. 10.1016/j.respol.2011.08.005
7
AngJ.SmedemaA. (2011). Financial flexibility: Do firms prepare for recession?J. Corp. Finance17 (3), 774–787. 10.1016/j.jcorpfin.2011.02.001
8
AnthonyJ. H.RameshK. (1992). Association between accounting performance measures and stock prices: A test of the life cycle hypothesis. J. Account. Econ.15 (2–3), 203–227. 10.1016/0165-4101(92)90018-w
9
AtifM.LiuB.NadarajahS. (2022). The effect of corporate environmental, social and governance disclosure on cash holdings: Life-cycle perspective. Bus. Strategy Environ.31, 2193–2212. 10.1002/bse.3016
10
BaronR. M.KennyD. A. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. J. Personality Soc. Psychol.51 (6), 1173–1182. 10.1037/0022-3514.51.6.1173
11
BasuA.ParkerS. C. (2001). Family finance and new business start-ups. Oxf. Bull. Econ. Statistics63 (3), 333–358. 10.1111/1468-0084.00224
12
BenlemlihM.BitarM. (2018). Corporate social responsibility and investment efficiency. J. Bus. Ethics148 (3), 647–671. 10.1007/s10551-016-3020-2
13
BroadstockD. C.ChanK.ChengL. T. W.WangX. (2021). The role of ESG performance during times of financial crisis: Evidence from COVID-19 in China. Finance Res. Lett.38, 101716. 10.1016/j.frl.2020.101716
14
BrodyP.EhrlichD. (1998). Can big companies become successful venture capitalists?New York: The McKinsey Quarterly, McKinsey & Company, Inc., 50.
15
BrunaM. G.LopreviteS.RaucciD.RiccaB.RupoD. (2022). Investigating the marginal impact of ESG results on corporate financial performance. Finance Res. Lett.47, 102828. 10.1016/j.frl.2022.102828
16
CuiJ.JoH.NaH. (2018). Does corporate social responsibility affect information asymmetry?J. Bus. Ethics148 (3), 549–572. 10.1007/s10551-015-3003-8
17
CuiY.LiuB. (2018). Manufacturing servitisation and duration of exports in China. World Econ.41 (6), 1695–1721. 10.1111/twec.12614
18
CummingD.JohanS. (2010). Venture capital investment duration. J. Small Bus. Manag.48 (2), 228–257. 10.1111/j.1540-627x.2010.00293.x
19
DahlquistM.RobertssonG. (2001). Direct foreign ownership, institutional investors, and firm characteristics. J. Financial Econ.59 (3), 413–440. 10.1016/s0304-405x(00)00092-1
20
DesaG.BasuS. (2013). Optimization or bricolage? Overcoming resource constraints in global social entrepreneurship. Strategic Entrepreneursh. J.7 (1), 26–49. 10.1002/sej.1150
21
DickinsonV. (2011). Cash flow patterns as a proxy for firm life cycle. Account. Rev.86, 1969–1994. 10.2139/ssrn.1268509
22
DorfleitnerG.HalbritterG.NguyenM. (2015). Measuring the level and risk of corporate responsibility - an empirical comparison of different ESG rating approaches. J. Asset Manag.16 (7), 450–466. 10.1057/jam.2015.31
23
DrazinR.KazanjianR. K. (1990). A reanalysis of miller and friesen's life cycle data. Strat. Mgmt. J.11 (4), 319–325. 10.1002/smj.4250110407
24
DrempeticS.KleinC.ZwergelB. (2020). The influence of firm size on the ESG score: Corporate sustainability ratings under review. J. Bus. Ethics167 (2), 333–360. 10.1007/s10551-019-04164-1
25
EdwardsC. D. (1955). Conglomerate bigness as a source of power”, business Concentration and price policy. New Jersey, United States: Princeton University Press, 331–359.
26
El GhoulS.GuedhamiO.KwokC. C. Y.MishraD. R. (2011). Does corporate social responsibility affect the cost of capital?J. Bank. Finance35 (9), 2388–2406. 10.1016/j.jbankfin.2011.02.007
27
FaccioM.MarchicaM.-T.MuraR. (2016). CEO gender, corporate risk-taking, and the efficiency of capital allocation. J. Corp. Finance39, 193–209. 10.1016/j.jcorpfin.2016.02.008
28
FaccioM.MarchicaM.-T.MuraR. (2011). Large shareholder diversification and corporate risk-taking. Rev. Financ. Stud.24 (11), 3601–3641. 10.1093/rfs/hhr065
29
FlammerC. (2021). Corporate green bonds. J. Financial Econ.142 (2), 499–516. 10.1016/j.jfineco.2021.01.010
30
ForkerJ. J. (1992). Corporate governance and disclosure quality. Account. Bus. Res.22 (86), 111–124. 10.1080/00014788.1992.9729426
31
FriedeG.BuschT.BassenA. (2015). ESG and financial performance: Aggregated evidence from more than 2000 empirical studies. J. Sustain. Finance Invest.5, 210–233. 10.1080/20430795.2015.1118917
32
FuW.AbbassK.NiaziA. A. K.ZhangH.BasitA.QaziT. F. (2022). Assessment of sustainable green financial environment: The underlying structure of monetary seismic aftershocks of the COVID-19 pandemic. Environ. Sci. Pollut. Res.2022, 0123456789. 10.1007/s11356-022-20178-1
33
GangH.XiaoC.XiaoY.YanW.BaiR.DingR.et al (2019). Proteomic analysis of the reduction and resistance mechanisms of Shewanella oneidensis MR-1 under long-term hexavalent chromium stress. Environ. Int.127, 94–102. 10.1016/j.envint.2019.03.016
34
GangiF.MelesA.MonferràS.MustilliM. (2020). Does corporate social responsibility help the survivorship of SMEs and large firms?Glob. Finance J.43, 100402. 10.1016/j.gfj.2018.01.006
35
GaoY.HanK.-S. (2020). Managerial overconfidence, CSR and firm value. Asia-Pacific J. Account. Econ.29, 1600–1618. 10.1080/16081625.2020.1830558
36
GhoshD.OlsenL. (2009). Environmental uncertainty and managers' use of discretionary accruals. Account. Organ. Soc.34 (2), 188–205. 10.1016/j.aos.2008.07.001
37
GravesS. B.WaddockS. A. (1994). Institutional owners and corporate social performance. Acad. Manag. J.37 (4), 1034–1046. 10.2307/256611
38
GuoF.ZouB.ZhangX.BoQ.LiK. (2020). Financial slack and firm performance of SMMEs in China: Moderating effects of government subsidies and market-supporting institutions. Int. J. Prod. Econ.223, 107530. 10.1016/j.ijpe.2019.107530
39
HongH.KacperczykM. (2009). The price of sin: The effects of social norms on markets. J. Financial Econ.93 (1), 15–36. 10.1016/j.jfineco.2008.09.001
40
HongH.LiskovichI. (2015). Crime, punishment and the halo effect of corporate social responsibility. National Bureau of Economic Research. 10.2139/ssrn.2492202
41
HorváthováE. (2010). Does environmental performance affect financial performance? A meta-analysis. Ecol. Econ.70 (1), 52–59. 10.1016/j.ecolecon.2010.04.004
42
HoskissonR. E.HittM. A.HillC. W. L. (1993). Managerial incentives and investment in R&D in large multiproduct firmsOrganization Science. Organ. Sci.4 (2), 325–341. 10.1287/orsc.4.2.325
43
HuangD. Z. X. (2021). Environmental, social and governance (ESG) activity and firm performance: A review and consolidation. Acc. Finance61 (1), 335–360. 10.1111/acfi.12569
44
HussainY.AbbassK.UsmanM.RehanM.AsifM. (2022). Exploring the mediating role of environmental strategy, green innovations, and transformational leadership: The impact of corporate social responsibility on environmental performance. Environ. Sci. Pollut. Res.29 (51), 76864–76880. 10.1007/s11356-022-20922-7
45
JawaharI. M.MclaughlinG. L. (2001). Toward a descriptive stakeholder theory: An organizational life cycle approach. Amr26 (3), 397–414. 10.5465/amr.2001.4845803
46
JeffreyS.RosenbergS.McCabeB. (2019). Corporate social responsibility behaviors and corporate reputation. Srj15 (3), 395–408. 10.1108/srj-11-2017-0255
47
JensenM. C. (1986). Agency costs of free cash flow, corporate finance, and takeovers. Am. Econ. Rev.76 (2), 323–329.
48
KimE.-H.LyonT. P. (2015). Greenwash vs. brownwash: Exaggeration and undue modesty in corporate sustainability disclosure. Organ. Sci.26 (3), 705–723. 10.1287/orsc.2014.0949
49
KrügerF. (2015). Corporate storytelling: Theorie und empirie narrativer public relations in der unternehmenskommunikation. Berlin, Germany: Springer-Verlag.
50
LaevenL.LevineR. (2009). Bank governance, regulation and risk taking. J. Financial Econ.93 (2), 259–275. 10.1016/j.jfineco.2008.09.003
51
LevB.ZarowinP. (1999). The boundaries of financial reporting and how to extend them. J. Account. Res.37 (2), 353–385. 10.2307/2491413
52
LinsK. V.ServaesH.TamayoA. (2017). Social capital, trust, and firm performance: The value of corporate social responsibility during the financial crisis. J. Finance72 (4), 1785–1824. 10.1111/jofi.12505
53
LodererC.StulzR.WaelchliU. (2017). Firm rigidities and the decline in growth opportunities. Manag. Sci.63 (9), 3000–3020. 10.1287/mnsc.2016.2478
54
LuoW.GuoX.ZhongS.WangJ. (2019). Environmental information disclosure quality, media attention and debt financing costs: Evidence from Chinese heavy polluting listed companies. J. Clean. Prod.231, 268–277. 10.1016/j.jclepro.2019.05.237
55
MahoneyL.RobertsR. W. (2007). Corporate social performance, financial performance and institutional ownership in Canadian firms. Account. Forum31, 233–253. 10.1016/j.accfor.2007.05.001
56
MallinckrodtB.AbrahamW. T.WeiM.RussellD. W. (2006). Advances in testing the statistical significance of mediation effects. J. Couns. Psychol.53 (3), 372–378. 10.1037/0022-0167.53.3.372
57
MillerD.FriesenP. H. (1984). A longitudinal study of the corporate life cycle. Manag. Sci.30 (10), 1161–1183. 10.1287/mnsc.30.10.1161
58
MourdoukoutasP.StefanidisA. (2021). Why companies succeed or fail: Corporate cycles and firm function in tandem. J. Bus. Strategy. 10.1108/jbs-09-2021-0164
59
RaimoN.CaragnanoA.ZitoM.VitollaF.MarianiM. (2021). Extending the benefits of ESG disclosure: The effect on the cost of debt financing. Corp. Soc. Responsib. Env.28 (4), 1412–1421. 10.1002/csr.2134
60
RetolazaJ. L.RuizM.San-JoseL. (2009). CSR in business start-ups: An application method for stakeholder engagement. Corp. Soc. Responsib. Environ. Mgmt16 (6), 324–336. 10.1002/csr.191
61
RoeM. J. (2021). Corporate purpose and corporate competition. Wash. UL Rev.99, 223. 10.2139/ssrn.3817788
62
SaraviaJ. A. (2014). The lifecycle of the firm, corporate governance and investment performance. Corp. Ownersh. Control11 (2), 224–238. 10.22495/cocv11i2c1p6
63
ShakilM. H. (2021). Environmental, social and governance performance and financial risk: Moderating role of ESG controversies and board gender diversity. Resour. Policy72, 102144. 10.1016/j.resourpol.2021.102144
64
ShenH.Yu PengW. L. (2012). State ownership, environmental uncertainty and investment efficiency. Econ. Res.07, 114–127.
65
SiewR. Y. J.BalatbatM. C. A.CarmichaelD. G. (2016). The impact of ESG disclosures and institutional ownership on market information asymmetry. Asia-Pacific J. Account. Econ.23 (4), 432–448. 10.1080/16081625.2016.1170100
66
SkarmeasD.LeonidouC. N. (2013). When consumers doubt, watch out! the role of CSR skepticism. J. Bus. Res.66 (10), 1831–1838. 10.1016/j.jbusres.2013.02.004
67
SobelM. E. (1982). Asymptotic confidence intervals for indirect effects in structural equation models. Sociol. Methodol.13, 290–312. 10.2307/270723
68
SpenceA. M. (1981). The learning curve and competition. Bell J. Econ.12, 49–70. 10.2307/3003508
69
TriantisG. G. (1994). A free-cash-flow theory of secured debt and creditor priorities. Va. Law Rev.80, 2155–2168. 10.2307/1073555
70
TriantisG. G. (2000). Financial slack policy and the laws of secured transactions. J. Leg. Stud.29 (1), 35–69. 10.1086/468063
71
UotilaJ.MaulaM.KeilT.ZahraS. A. (2009). Exploration, exploitation, and financial performance: Analysis of S&P 500 corporations. Strat. Mgmt. J.30 (2), 221–231. 10.1002/smj.738
72
VogtS. C. (1994). The cash flow/investment relationship: Evidence from U.S. Manufacturing firms. Financ. Manag.23, 3–20. 10.2307/3665735
73
WardS.LewandowskaA. (2008). Is the marketing concept always necessary? The effectiveness of customer, competitor and societal strategies in business environment types. Eur. J. Mark.42, 222. 10.1108/03090560810840989
74
WeberO. (2014). Environmental, social and governance reporting in China. Bus. Strat. Env.23 (5), 303–317. 10.1002/bse.1785
75
WernerfeltB. (1985). The dynamics of prices and market shares over the product life cycle. Manag. Sci.31 (8), 928–939. 10.1287/mnsc.31.8.928
76
WuJ.SongJ.ZengC. (2008). An empirical evidence of small business financing in China. Manag. Res. News31 (12), 959–975. 10.1108/01409170810920666
77
XiaofangB. (2017). Government Subsidies,Financial slack and ambidextrous innovation. Account. Res.01, 46–52+95.
78
XuH.XuX.YuJ. (2021). The impact of mandatory CSR disclosure on the cost of debt financing: Evidence from China. Emerg. Mark. Finance Trade57 (8), 2191–2205. 10.1080/1540496x.2019.1657401
79
YuE. P.-Y.GuoC. Q.LuuB. V. (2018). Environmental, social and governance transparency and firm value. Bus. Strat. Env.27 (7), 987–1004. 10.1002/bse.2047
80
YuanX.LiZ.XuJ.ShangL. (2022). ESG disclosure and corporate financial irregularities - evidence from Chinese listed firms. J. Clean. Prod.332, 129992. 10.1016/j.jclepro.2021.129992
81
ZerbibO. D. (2019). The effect of pro-environmental preferences on bond prices: Evidence from green bonds. J. Bank. Finance98, 39–60. 10.1016/j.jbankfin.2018.10.012
82
ZhuZ.TanY. (2022). Can green industrial policy promote green innovation in heavily polluting enterprises? Evidence from China. Econ. Analysis Policy74, 59–75. 10.1016/j.eap.2022.01.012
Summary
Keywords
ESG, CSR, firm life cycle, financial risk, corporate performance
Citation
Gao S, Meng F, Wang W and Chen W (2023) Does ESG always improve corporate performance? Evidence from firm life cycle perspective. Front. Environ. Sci. 11:1105077. doi: 10.3389/fenvs.2023.1105077
Received
23 November 2022
Accepted
18 January 2023
Published
30 January 2023
Volume
11 - 2023
Edited by
Shigeyuki Hamori, Kobe University, Japan
Reviewed by
Shahid Ali, Nanjing University of Information Science and Technology, China
Uzma Bashir, National University of Modern Languages, Pakistan
Updates
Copyright
© 2023 Gao, Meng, Wang and Chen.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Shang Gao, 1908765975@qq.com; Fanchen Meng, meng@bit.edu.cn
This article was submitted to Environmental Economics and Management, a section of the journal Frontiers in Environmental Science
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