| Literature DB >> 35754081 |
Larisa Ivascu1,2, Aura Domil3, Muddassar Sarfraz4, Oana Bogdan3, Valentin Burca3, Codruta Pavel3.
Abstract
The paper examines how environmental, social, and governance (ESG), including management incentives, influence a firm's financial performance. The study method is based on an empirical analysis of data describing firm-level information about corporate financial performance and corporate sustainability performance between 2001 and 2020, summing up 6291 observations related to 422 analyzed firms from the European Union (EU). The study findings emphasize that firm size is highly influenced by sustainable economic development and significantly conditioned by a CSR strategy and a capable management team. We also prove a long-term relationship between the measures of corporate financial performance and the scores reflecting corporate ESG performance. Our results show a co-integration relationship between corporate financial performance metrics and corporate sustainability performance scores. ESG corporate performance is highly conditioned by the level of resources affected for this purpose, directly impacting firms' cash flow.Entities:
Keywords: Corporate social responsibility; Corporate sustainability; Environmental management; European Union; Financial performance
Year: 2022 PMID: 35754081 PMCID: PMC9244352 DOI: 10.1007/s11356-022-21642-8
Source DB: PubMed Journal: Environ Sci Pollut Res Int ISSN: 0944-1344 Impact factor: 5.190
Fig. 1Sample distribution by different criteria. Source: authors’ projection
Definition of variables included in the study
| Variable | Name | Description | |
|---|---|---|---|
Corporate financial performance | Profitability | ROA | It is the return on assets reported by firms at year-end financial reporting; |
| Free cash flow | FCF | It is the logarithm of the free cash flow determined as the difference between Net Operating Profit After Taxes (NOPAT) and Net Investment in Operating Capital (NIOC), where | |
Corporate sustainability performance | ESG score | ESG | It is an aggregate score calculated for each firm yearly by Refinitiv, incorporating numerous aspects of the triple-bottom-line approach, such as environmental (emissions, innovation, resource use), social (community, human rights, product responsibility, workforce), or governance (ESG reporting, governance structures, management compensation, shareholders); |
| CSR strategy | CSR | It is an aggregate score calculated for each firm every year by Refinitiv, incorporating various aspects concerning the CSR reporting or strategies in the CSR area designed by firms to obtain corporate social responsibility | |
| Management score | MS | It is a score that looks for management efficiency in implementing firms’ strategy and how shareholders offer incentives to managers to motivate them to obtain the optimal level of corporate performance, affecting firms’ capitals, respectively financial capital, manufacturing capital, intellectual capital, social capital, human capital, or natural capital | |
| Control variables | Age | A | Number of years since the firm has first been included on the Refinitiv database; |
| Size | S | The logarithm of the total assets reported at year-end; | |
| Business cycle | BC | It is the cash operating cycle used as an alternative proxy for firms’ business model cycle, as Dickinson ( | |
| Operating efficiency | OE | It is defined as a percentile rank that reflects the Refinitiv Earnings Quality Model component, which reflects persistence on operating margins reported under optimal asset allocation | |
Source: authors’ projection
Descriptive statistics
| Statistics | ROA | FCF | ESG | Mng | CSR | Size | Eff | Cycle | Age | |
|---|---|---|---|---|---|---|---|---|---|---|
| Sample size | 6291 | 6291 | 6291 | 6088 | 6088 | 6291 | 6070 | 6223 | 6291 | |
| Mean | 4.70% | 5.498 | 52.39 | 54.20 | 47.50 | 22.50 | 57.04 | 185.7 | 17.14 | |
| Median | 4.38% | 17.77 | 53.87 | 55.61 | 50.00 | 22.50 | 58.00 | 61.57 | 17.00 | |
| Std. Deviation | 13.83% | 18.20 | 20.38 | 27.81 | 32.55 | 1.60 | 23.43 | 134.8 | 9.214 | |
| Percentiles | 25 | 1.71% | − 18.10 | 36.84 | 31.43 | 16.67 | 21.43 | 41.00 | 14.23 | 10.00 |
| 50 | 4.38% | 17.77 | 53.87 | 55.61 | 50.00 | 22.50 | 58.00 | 61.57 | 17.00 | |
| 75 | 7.68% | 19.39 | 68.74 | 78.20 | 76.34 | 23.54 | 76.00 | 112.43 | 24.00 | |
| Normality | Stat | 21.28% | 0.339 | 0.049 | 0.065 | 0.091 | 0.012 | 0.059 | 0.5 | 0.043 |
| Sig | 0.000c | 0.000c | 0.000c | 0.000c | 0.000c | 0.041c | 0.000c | 0.000c | 0.000c | |
| Collinearity | VIF | 3.343 | 1.391 | 2.270 | 1.591 | 1.012 | 1.001 | 1.116 | ||
aMultiple modes exist. The smallest value is shown
bTest distribution is normal, calculated from data
cLilliefors significance correction
Source: author’s calculation
Fig. 2Evolution in time.
Source: author’s calculation
Correlation matrix
| ROA | ESG | Size | FCF | Mng | CSR | Eff | Age | Cycle | |
|---|---|---|---|---|---|---|---|---|---|
| ROA | 1 | ||||||||
| ESG score | − 0.040** | 1 | |||||||
| Size | − 0.077** | 0.575** | 1 | ||||||
| FCF | 0.292** | − 0.011 | − 0.044** | 1 | |||||
| Management | 0.035** | 0.510** | 0.218** | 0.007 | 1 | ||||
| CSR strategy | − 0.071** | 0.739** | 0.476** | − 0.056** | 0.304** | 1 | |||
| Efficiency | 0.194** | − 0.005 | − 0.083** | 0.125** | 0.025 | 0.003 | 1 | ||
| Age | − 0.079** | 0.247** | 0.028* | 0.065** | 0.089** | 0.232** | 0.054** | 1 | |
| Cash cycle | − 0.194** | − 0.025* | − 0.017 | − 0.004 | − 0.016 | − 0.020 | − 0.009 | 0.004 | 1 |
*Significant at the 0.05 level (2-tailed); **significant at the 0.01 level (2-tailed)
Source: author’s calculation
Unit root test results
| Method | ROA | FCF | ESG score | Management | CSR strategy |
|---|---|---|---|---|---|
| Levin, Lin, and Chu | − 11.24* | − 134.0* | − 16.06* | − 16.30* | − 31.55* |
| Im, Pesaran, and Shin W-stat | − 8.431* | − 26.92* | − 4.490* | − 8.395* | − 6.468* |
| ADF-Fisher chi-square | 1277.0* | 2312.6* | 1198.1* | 1142.5* | 1190.4* |
| PP-Fisher chi-square | 1880.6* | 2708.7* | 1593.1* | 1580.3* | 1745.8* |
*Rejection of the null hypothesis of the existence of a unit root at a 1% significance level
Source: author’s calculation
Panel co-integration test results
| Alternative hypothesis: common AR coefs. (within-dimension) | ||||
| Panel v-statistic | 3.970* | − 2.042 | − 5.903* | − 8.839 |
| Panel rho-statistic | 2.648 | − 2.128* | − 0.252* | − 1.856* |
| Panel PP-statistic | − 21.93* | − 29.26* | − 22.28 | − 32.41* |
| Panel ADF-statistic | − 3.352* | − 12.35* | − 11.22 | − 16.44* |
| Alternative hypothesis: individual AR coefs. (between-dimension) | ||||
| Group rho-statistic | 8.887 | 7.354 | ||
| Group PP-statistic | − 26.49* | − 46.42* | ||
| Group ADF-statistic | − 7.134* | − 13.88* | ||
*Rejection of the null hypothesis of no co-integration at 5% significance level
Source: author’s calculation
VAR model validation
| Model validation | ||||
|---|---|---|---|---|
| Residuals diagnostic | Joint normality test | JB test | 9246.8 | 3213.5 |
| 0.000 | 0.000 | |||
| Autocorrelation test | LM-Stat | 18.14 | 15.02 | |
| 0.316 | 0.523 | |||
| White heteroscedasticity test | Chi-sq | 7506.3 | 1661.7 | |
| 0.000 | 0.000 | |||
| Model stability | The root of characteristics polynomial-maximal modulus | 0.936 | 0.933 | |
Source: author’s calculation
VAR model validation
| Variable | Model | Lag | |||||
|---|---|---|---|---|---|---|---|
| (1) | (2) | (3) | (4) | ||||
| Endogenous variables | 1 | 0.427* | 0.4742* | - | - | ||
| (0.014) | (0.014) | ||||||
| 2 | 0.341* | 0.341* | |||||
| (0.015) | (0.015) | ||||||
| 1 | - | - | 0.4008* | 0.3894* | |||
| (0.014) | (0.014) | ||||||
| 2 | 0.1293* | 0.1197* | |||||
| (0.014) | (0.014) | ||||||
| 1 | − 0.0006* | − 0.0003*** | − 0.0768* | − 0.0613* | |||
| (0.0003) | (0.0002) | (0.0390) | (0.0398) | ||||
| 2 | 0.0006* | 0.0003*** | 0.1071* | 0.1016* | |||
| (0.0003) | (0.0002) | (0.0385) | (0.0390) | ||||
| 1 | 0.0001 | 0.0000 | 0.0185 | 0.0153 | |||
| (0.0001) | (0.0001) | (0.0147) | (0.0148) | ||||
| 2 | − 0.0001 | 0.0000 | − 0.0303* | − 0.0302** | |||
| (0.0001) | (0.0001) | (0.015) | (0.0146) | ||||
| 1 | − 0.0001* | − 0.0001* | − 0.025*** | − 0.027** | |||
| (0.0001) | (0.0001) | (0.017) | (0.0172) | ||||
| 2 | 0.0000 | 0.0000 | − 0.0033 | − 0.0005 | |||
| (0.0001) | (0.0001) | (0.0169) | (0.0170) | ||||
| Exogenous variables | 0.0115* | 0.0291 | 2.9214* | 8.2259** | |||
| (0.005) | (0.019) | (0.681) | (3.950) | ||||
| - | − 0.0003** | - | 0.0943* | ||||
| (0.0001) | (0.027) | ||||||
| − 0.0014*** | − 0.447** | ||||||
| (0.001) | (0.182) | ||||||
| 0.000 | 0.000 | ||||||
| (0.000) | (0.000) | ||||||
| 0.0003* | 0.0493* | ||||||
| (0.000) | (0.010) | ||||||
| Adj. | 0.435 | 0.602 | 0.576 | 0.227 | |||
| 509.4* | 650.6* | 899.0* | 127.0* | ||||
| Akaike information criterion | − 1.599 | − 2.290 | 8.609 | 8.399 | |||
| Schwarz criterion | − 1.588 | − 2.273 | 8.621 | 8.416 | |||
1% significance level; **5% significance level; ***10% significance level
Source: author’s calculation
Granger causality F statistics
| Relation | No. of lags | |||
|---|---|---|---|---|
| ROA < – ESG | 12.13* | 4.135** | 1.960 | |
| ESG < – ROA | 7.35* | 6.537* | 4.844* | |
| ROA < – MS | 0.127 | 0.051 | 0.129 | |
| MS < – ROA | 6.727* | 3.787** | 2.255 | |
| ROA < – CSR | 16.00* | 4.220** | 1.766 | |
| CSR < – ROA | 0.739 | 2.949 | 2.805** | |
| FCF < – ESG | 2.345 | 2.003 | 1.331 | |
| ESG < – FCF | 4.207** | 5.998* | 4.559* | |
| FCF < – MS | 1.097 | 0.836 | 2.679** | |
| MS < – FCF | 4.256 | 1.788 | 1.429 | |
| FCF < – CSR | 10.62* | 3.599** | 1.993 | |
| CSR < – FCF | 0.455 | 2.549** | 1.842 |
*1% significance level; **5% significance level
Source: author’s calculation
Fig. 3Causal loop diagram. Legend: blue (lag = 1), green (lag = 2), orange (lag = 3). Note: coefficient from the figure represents the regression coefficient from Table 7. Source: author’s projection
Fig. 4VAR models’ impulse representation.
Source: author’s calculation