Revisiting the Effect of Financial Elements on Stock Performance Using Corporate Social Responsibility Cost Growth

Abstract

The purpose of this research is to analyze the effect of financial elements (asset growth, liability growth, equity growth, revenue growth, and profit growth) on stock price performance and to analyze the growth of Corporate Social Responsibility (CSR) costs as a moderating effect. The technique analysis used is regression analysis. Samples in this analysis are manufacturing firms listed on the Indonesian Stock Exchange (IDX) for the period 2014-2018. The use of regression models for hypothesis testing must fulfill several applicable assumptions such as Normality Test, Heteroscedasticity Test, Multicollinearity Test, Autocorrelation Test, Model Fit Test, Determination Coefficient Test, and Hypothesis Test. Data analysis used two research models, namely model 1 and model 2. Model 1 is without the moderating variable, and model 2 is with the moderating variable, that is, CSR cost growth. Based on the result of the regression analysis, it can be inferred that the asset, revenue, and profit growth have a positive impact on stock price results. Liabilities and equity growth do not affect stock price performance. Operating expense growth has a significant effect on price performance. CSR cost growth can moderate the effect of growth in financial statement elements on stock price performance but is not significant.

1. Introduction

Stock market performance affects the performance of firms, and the style of ownership plays a major role in the financial performance of firms (Al-Gamrh et al., 2020). The stockholder’s view of performance will result in a short term view of performance, and its broader stakeholder perspective will make it easier for the company to thrive; thus, competitive in the long term. The business prospect in the property industry environment is motivated by the increase of the population in Indonesia, which continues to grow every year (Josef & Maartje, 2020).

Integrated reports (IRs) may bring benefit for investors because it may reduce the knowledge asymmetry on nonfinancial information effect on financial results (Akisik & Gal, 2019). The interest in CSR is continuing to increase worldwide and although different companies approach to the concept varies, more companies are implementing voluntary initiatives aimed at minimizing its negative impact on society and the environment (Hagberg et al., 2015).

Financial performance is measured in this analysis by the use of two financial performance measures: market-based and accounting-based. Also, when analyzing the relationship between CSR and financial performance, some researchers use a market-based metric in Tobin’s Q’s form. This marketbased performance indicator has also been used by a variety of researchers in the past to explore the connection between CSR and market-based performance.

This relationship is considered critical for companies from advanced economies and industrialized financial prudence. CSR activities are increasingly undertaken by a large number of firms, not only in developed countries but also in emerging countries. Emerging economies find that CSR is more favorably connected to firm assessment in nations with more deficient market establishments (Kabir & Thai, 2017; Hermuningsih et al., 2020).

2. Literature Review

2.1. Stock Performance

Tasnia et al. (2020) found that stock market performance is market capitalization as a proportion of GDP. They found a significant and positive relationship between CSR and stock price volatility, which indicates that shareholders may not prefer excess concentration on CSR because of the additional cost of investment associated with implementing CSR. Also, tax payments and stock price volatility show a significant positive association, which implies that there is a higher possibility of an increase in stock price volatility if the tax rate increases. Generally, shareholders are not interested in paying more taxes, so they may swap the market instead of paying more tax.

Stock market performance influences the firm’s performance, and the type of tenure plays a significant part in firms’ monetary and social performance (Al-Gamrh et al., 2020). Board independence is perceived to be a critical tool for corporate governance to protect the rights of marginal shareholders, arguing that board liberation is essential to appeal to overseas ventures. Furthermore, a literature review suggests that the freedom of the board increases the financial and social efficiency of the firm. The growth rate of shares of manufacturing companies listed on the Indonesia Stock Exchange has been fluctuating over the past five years due to the continuous development of the global economy (Bambang et al., 2020).

Al-Gamrh et al. (2020) examined the impact of two different types of foreign ownership. They investigated how the degree of board independence affects the aforementioned relationship between these two types of foreign investors on firm performance. Results indicated that while one type of foreign ownership affects firms’ financial and social performance negatively, another type of foreign ownership does so, positively. Further tests indicate that board independence weakens the negative relationship between firm financial and social performance with one type of foreign ownership and deteriorate the relationship between firm financial and social performance and another type of foreign ownership.

CSR and taxation share a common characteristic, which is welfare to society by involving in social and environmental activities. The characteristics are in line with the stakeholders and legitimacy theory. Stakeholder theory explains the affiliation between shareholders and the firm, while legitimacy theory legitimizes the bond between the bank and society. Stakeholders’ theory considers the welfare of society the bank is operating in and emphasizes the development of the community, which includes a broad range of stakeholders bases, such as employees, customers, and communities (Tasnia et al., 2020).

The relationship between economic activity and stock market development has been discussed in both developing and developed nations. The capital market plays an essential role in the growth of commerce and industry which ultimately affects the economy of the country to a large extent. A clear positive affiliation between stock market creation and longterm economic growth after monitoring the initial or primary stage of per capita GDP, the initial level of human capital expenditure, political uncertainty, and financial and monetary policy initiatives, as well as the exchange rate policy was noticed. capitalization. The results revealed that economic growth can be attained by increasing the size of the stock markets of a country as well as the market capitalization in emerging markets. Stock prices represent all publicly accessible information, thereby offering a detailed image of the firm’s success (Nazir et al., 2010).

Bhattacharyya and Rahman (2020) examined the impact of mandated CSR expenditure on firms’ stock returns by using actual CSR spending data, whereas the previous studies mostly focus on voluntary CSR proxied by CSR scores The findings document that mandatory CSR expenditure has a negative impact on firms’ stock returns which supports the “shareholders” expense’ view. This result holds for the firms with actual CSR expenditure equal to the mandated amount but does not hold for the firms with actual CSR expenditure greater than the mandated amount. Therefore, they provided evidence that CSR expenditure’s impact on stock returns depends on whether firms simply comply with the regulation or voluntarily chose an amount of CSR expenditure above the mandated amount

Aly et al. (2018) examined the extent to which financial performance represents one of the main determinants for tone disclosure in annual reports. The descriptive analysis in this paper showed that firms disclose more good news than bad news. Therefore, the net news disclosure, or net variances, between good/bad is positive. The empirical analysis showed a positive association between the narrative disclosure of good/ bad news and financial performance based on return on assets. The authors also find a highly significant association between the auditor, profitability, leverage, firm growth, and financial reporting of good/bad news information. Commonly, many investors determine CSR success metrics for companies, together with conventional financial performance tests, while deciding investment verdicts (Akisik & Gal, 2019).

2.2. Social Corporate Responsibility (CSR)

CSR is fiscal, legal, principled, and unrestricted potentials of entities at a given time. The European Commission, on the other hand, describes it as “a term whereby companies integrate social and environmental concerns in their business operations and their interaction with their stakeholders voluntarily” (Nyeadi et al., 2018). CSR is a social and environmental responsibility of firms and financial institutions to society. The adoption of CSR will benefit both the micro and macro performance of organizations. Macro performance defines environmental development and balancing social equality. CSR disclosure can be interpreted as a form of corporate responsibility towards social and environmental problems around the firm (Machmuddah et al., 2020).

On the other hand, micro performance describes the status improvement, the potentiality to control a quality price for the service and products, and the upgraded ability to hire qualified workers. CSR can be explained as the social responsibility of a corporation. The concept of CSR has formed not only to be confined in the companies but also for societal welfare (Tasnia et al., 2020).

Sial et al. (2018) examined the relationship between CRS and firm performance and the moderating role of earnings management on the relationship between CSR and firm performance. The results demonstrated that CSR has a positive and significant relationship with a firm’s performance; also, earnings management has a negatively moderate relationship between CSR and firm performance. These results imply that a high value of earnings management, which results in a high level of symbolic CSR, converts to low firm performance of the Chinese firms. CSR actions (only as symbolic measures) promoted by managers as a means to cover their profit management incite an adverse effect on the company’s performance. This study has highlighted the impact of two different corporate social responsibilities: substantive and symbolic (genuine CSR vs greenwashing) on firm performance.

CSR plays an influential role in risk reduction; this relationship is more influential in a high dynamism environment than in a low dynamism environment (Tasnia et al., 2020). Companies with better CSR results are better placed to access funding on the capital markets. In exchange, the easing of capital controls positively affects the willingness of establishments to make successful financial acquisitions that they would not have and on the success of the stock market. Waddock and Graves (1997) reported the results of a rigorous study of the empirical linkages between financial and social performance. Corporate social performance (CSP) is found to be positively associated with prior financial performance, supporting the theory that slack resource availability and CSP are positively related. CSP is also found to be positively associated with future financial performance, supporting the theory that good management and CSP are positively related

Ullmann (1985) stated that inconsistent findings have resulted from studies of the relationships among social disclosure, social performance, and economic performance of firms. No clear tendency could be detected. The main reasons for these inconsistencies were a lack of theory, inappropriate definition of key terms, and deficiencies in the empirical databases currently available. Suggestions are made as to how this situation can be improved. Islam et al. (2012) examined the nature of the relationship between CSR and corporate financial performance (CFP). In doing they summarized the findings of the empirical studies, drawn the conceptual framework, measured CSR by developing a measure of CSP, and finally made an investigation on the banking sector of Bangladesh. The results of the study revealed that the average return on asset ratios of the banks having high CSP is higher compared to that of the banks having low CSP, though this could not be proved statistically.

Cheng et al. (2014) investigated whether superior performance on CSR strategies leads to better access to finance. They hypothesized that better access to finance can be attributed to reduced agency costs due to enhanced stakeholder engagement and reduced informational asymmetry due to increased transparency. Using a large cross‐section of firms, they found that firms with better CSR performance face significantly lower capital constraints. They provided evidence that both better stakeholder engagement and transparency around CSR performance are important in reducing capital constraints. They showed that the relationship is driven by both the social and environmental dimension of CSR

An in-depth study of the two CSR’s critical components, environmental and communal, allows one to comprehend better the particular effect of CSR on financial presentation (Kabir & Thai, 2017). Nyeadi et al. (2018) found CSR to have a strong positive impact on firm financial performance. When CSR is decomposed further into its major components, governance performance positively impacts a firm’s financial performance with no evidence of any relationship between social components and firm performance and between environmental components and firm performance. The positive impact of CSR on firm performance is greater in big firms. At the industry level, CSR is noticed to impact positively on financial performance in the extractive industry via good governance and responsible environmental behaviors. It however has no impact on firm performance in the financial sector.

2.3. Company Performance

Universally, firms are always conscious of socially responsible behavior. This aspect has a substantial effect on the Chinese firms’ CSR conduct, as they have a local and worldwide impact. There are other considerations, together with internal variables, for instance, firm efficiency and income control with the direct effect on the firm’s CSR performance (Sial et al., 2018). Companies with better performance invest in CSR operations, and these practices develop the credibility of conscientious firms. Contrarily, companies can recommend better CSR results without undertaking CSR activities referred to as symbolic CSR (Sial et al., 2018).

Investors attach a positive value to environmental financial statements (those that have an impression on financial performance) rather than to environmental disclosures that have no clear impression on financial performance. Since CSR information was found to affect financial reports, it was suggested that an IR that combines both corporate financial information and non-financial information would favor investors (Akisik & Gal, 2019).

Environmental initiatives undertaken by companies will generate potential costs and incentives that will eventually impact the financial performance of a firm, and the benefits can be enhanced by contributing to the capital of firms that will subsequently offer comparative advantages and improve the reputation of a company (Kabir & Thai, 2017). CSR activities affect the financial performance of firms positively. Furthermore, corporate governance features like foreign ownership, the board size, and board independence strengthen the positive relationship between CSR and financial performance, but there is no such impact of state ownership. CSR activities are increasingly undertaken by a large number of firms, not only in developed countries but also in emerging countries (Kabir & Thai, 2017).

Accordingly, implementing CSR in corporate strategy would be a favorable decision, which can create a win-win condition for an organization. A recent study, find that CSR activities strengthen the corporate reputation of a bank. Moreover, Tasnia et al. (2020) find a good association between CSR and bank financial performance.

2.4. Financial Performance

Financial performance is the unit’s ability to use its resources efficiently and produce outputs that are appropriate to its goals and for its users. Also, financial performance is the financial position that exists in an enterprise at a specific time or period for a specific aspect of the enterprise’s performance or its performance as a whole. Financial performance is the extent to which activities contribute to creating value or effectiveness by using available financial resources and achieving financial goals with minimal financial costs. Hence, financial performance should be concerned with a critical matter, which is competitiveness, that is, the firm’s ability to attract investors for an extended period. The financial performance is related to the activities that yield this facility

Almagtome and Abbas (2020) tested the relevance of the value of financial performance metrics that can provide investors with useful information on the assessment of corporate performance (operating income, total revenue, and dividend, to show its relationship to market indicators, both stock prices, and total traded shares). The results of the comparison between the financial performance measures showed that the correlation between the operating income index and the stock prices as well as the total traded stocks was higher than the other performance indicators (total revenue and dividends). The results of this study support capital markets by providing a better understanding of the importance of the different financial performance measures for investors and the extent to which they reflect on stock prices.

The financial performance measures are the most critical element in the implementation of a company’s strategy because of the vital role it plays in supporting and improving the performance of companies. The main objective of the financial perspective is to increase shareholder value, profitability, and long-term financial growth (Shibani & Gherbal, 2018). Company financial performance reflects the financial condition and the achievement of a company based on its financial report over a certain period. A financial report is issued periodically to be used by investors, creditors, prospective creditors, managers, employees, government, and society for their purposes. For example, information on company performance is important to investors in considering either keeping their investment in a company or finding other alternatives (Bhattacharyya & Rahman, 2020).

The relationship between affirmation and the interests of its stakeholders can be very complicated, as there are several diverse categories of stakeholders and, thus, different approaches to participate in them (Akisik & Gal, 2019). The relationship between CSR and financial performance differs not only from region to region but from industry to industry. It is therefore essential to consider the CSR’s effect on the firm financial outcomes of individual sectors as well (Nyeadi et al., 2018).

The application of accounting metrics, as some researchers have done, captures the company’s past results. Consequently, only the consumer opinions and possible aspirations of the firms are integrated into the use of economic policies. Therefore, the use of only one metric provides only a partial view of the financial results of the company (Nyeadi et al., 2018). Empirical research on the influence of CSR practices on firm performance has shown unclear outcomes. Firms that are actively involved in CSR activities were found to experience higher financial performance than other firms (Kabir & Thai, 2017).

Predominantly based on agency theory, some studies have concluded that the use of valuable firm capital to participate in CSR results in substantial managerial advantages rather than financial benefits to owners of the firm. Other authors claim that CSR can have a beneficial effect by having greater access to valuable tools, recruiting and maintaining higherquality workers, facilitating the better promotion of goods and services, generating unintended possibilities, and adding to social credibility (Cheng et al., 2014).

Yahya et al. (2013) stated that analyzing financial statements is a bit challenging for most financiers since there are details and nuanced reviews. Therefore, choosing a precise and uncomplicated analysis to analyze a firm’s financial results is an often confusing situation for managers and financiers. This study focuses on the most significant analyses to perform on financial statements. To accomplish this study, the financial statements of two companies, Unilever Foods, and National foods have been selected to perform analysis. Results showed that vertical analysis can be a suspicious analysis as its total assets and sales fluctuate gradually. Horizontal analysis is somehow a better analysis than vertical analysis as it shows a negative or positive trend of variables. DuPont analysis is a reliable analysis but it has taken into consideration only two years. However, ratio analysis seems to be the best analysis as it gives a concise and paramount review of a firm’s performance. According to these analyses, Unilever Foods is a better corporate than National Foods.

Financial analysis is the method of evaluating the essential organizational and financial features of a firm based on accounting statistics and financial statements (Hagberg et al., 2015). Although the information in the financial statements may allow investors to assess those forms of risk, the information in the CSR information may also be helpful for the assessment of credit risk and thus returns to shareholders (Sial et al., 2018). CSR expenditure and stock return should have a good affiliation. However, some classes of stockholders will also view CSR spending as an additional tax and misuse of corporate capital, and thus CSR expenditure may hurt stock equity prices (Bhattacharyya & Rahman, 2020).

3. Data and Methodology

3.1. Population and Research Sample

The population used is the financial statements is manufacturing firms listed on the Indonesian Stock Exchange (IDX) between 2014-2018. Samples collected from the population uses a purposive sampling approach with exact parameters as follows:

1. Manufacturing companies for which CSR data is available.

2. Financial reports can be accessed

3.2. Classical Assumption Test

H1 (+), H2 (-), H3 (+) H4 (-), H5 (+), H6 (+) H7(+), H8(-), H9(+) H10(-). H11(+), H12 (+)

3.3. Data Analysis Method

The use of regression models for hypothesis testing must fulfill several applicable assumptions as follows (Ghozali, 2006).

Normality Test

Tests whether or not in a statistical model, the independent variable and the dependent variable have a regular distribution. We detect it by performing the Kolmogorov-Smirnov test. If the significance value> 0.05, the data is normal.

Heteroscedasticity Test

Tests whether, in a regression model, there is a state of constant variance error usually due to the inefficient estimation of the variance in the regression model. This test is done by using the Glejser test, by regressing the independent variable to the dependent variable, namely absolute residuals. If in this study, the significance value > 0.05, it means that the data used is free of heteroscedasticity.

Multicollinearity Test

Tests if there is a perfect relationship between one or more of the independent variables in the regression model. Suppose the independent variables are strongly correlated with each other, in that case, there is a possibility that two or more variables have a strong relationship (correlation). If the effect of each of these variables on Y is difficult to distinguish, then it is said that there is multicollinearity. The detection is done using tolerance value and VIF (Varian Inflation Factor). If the tolerance value is> 0.1 and VIF <10, there is no multicollinearity.

Autocorrelation Test

Tests if there is a correlation in the regression model between the confounding error in period t and the error in period t-1 (previous). Autocorrelation occurs when consecutive findings are linked to one another over time. The test is done by comparing the Durbin-Watson value of the regression results with the value in the DurbinWatson table. Data is said to be free from autocorrelation if the Durbin-Watson regression value is between du and 4-du.

3.4. Model Fit Test

According to Ghozali (2006), the fit model test aims to determine whether the model built is appropriate or fit in predicting the dependent variable. The model is said to be fit if the significance value is <0.05.

3.5. Determination Coefficient Test

According to Ghozali (2006), the purpose of the coefficient test is to demonstrate the significance of the independent variable’s potential to describe differences in the dependent variable. The coefficient of determination seen from the modified R2 varies from zero to one. The near-one coefficient of determination implies that the independent variable has nearly all the formations required to forecast the dependent variable.

3.6. Hypothesis Testing

The methodology used in this study is a multi-linear regression analysis to assess the effect of the financial statement components’ growth on the company’s stock value. The regression model of this study is as follows (Ghozali, 2006).

\(\begin{aligned} \mathrm{KHS} 1 &=\alpha 0+\beta 1 \mathrm{PA}+\beta 2 \mathrm{PL}+\beta 3 \mathrm{PE}+\beta 4 \mathrm{PP}+\beta 5 \mathrm{PBO} \\ &+\beta 6 \mathrm{PLA}+\mathrm{e} \end{aligned}\)

\(\begin{aligned} \mathrm{KHS} 2 &=\alpha 1+\beta 7 \mathrm{PA}+\beta 8 \mathrm{PL}+\beta 9 \mathrm{PE}+\beta 10 \mathrm{PP} \\ &+\beta 11 \mathrm{PBO}+\beta 12 \mathrm{PLA}+\beta 13 \mathrm{PA} * \text { costs CSR } \\ &+\beta 14 \mathrm{PL} * \text { costs } \mathrm{CSR}+\beta 15 \mathrm{PE} * \text { costs CSR } \\ &+\beta 16 \mathrm{PP} * \text { costs } \mathrm{CSR}+\beta 17 \mathrm{PBO} * \text { costs } \mathrm{CSRPE} \\ &+\beta \mathrm{CSRPLA} * \text { costs.PP.PBO.PLA }^{*} \operatorname{cost} \mathrm{CSR}+\mathrm{e} \end{aligned}\)

Information:

KHS = Stock Price Performance

α 0 - α1 = Intercept

β1-β19 = Coefficient

PA = Asset Growth

PL = Liability Growth

PE = Equity Growth

PP = Income Growth

PBO = Operational Expense Growth

PLA = Profit Growth

PA * cost CSR = The interaction between asset growth and CSR

PL * cost CSR = The interaction between growth in liabilities and CSR

PE * cost CSR = The interaction between growth in equity and CSR

PP * cost CSR = The interaction between revenue growth and CSR

PBO * cost CSR = Interaction between growth in operating expenses and CSR

PLA * cost CSR = The interaction between profit growth and CSR

e = Error

The criteria if the hypothesis is accepted are H1 and H2 if β1> 0, while the criteria if the hypothesis is rejected are H1 and H2 if β1 <0. This study involves an overview and explanation of the data that seeks to address the researcher’s questions, which is, the analysis and the method of simplifying the data in a way that is easier to read and understand. The approach chosen to interpret the data must be based on the analysis trend and the variables to be analyzed. The model used in this analysis is a model of causality or relation of effect, discrepancy, and contrast. The empirical method used to evaluate the theory presented in this analysis is a regression that is run by the SPSS software.

From the results obtained, the Z test will be tested. The Z test is a statistical test where hypothesis testing is approached with a normal distribution. The Z test can be used to test data with large samples. A sample size of 30 or more is considered a large sample. The Z test criteria are data with normal distribution, known variance, large sample size (> 30), and used only to compare two observations. The formula is as follows:

\(Z=\frac{R^{2}(2)-R^{2}(1)}{\sqrt{\sigma^{2}(2)\left(R^{2}(2)\right)+\sigma^{2}(1)\left(R^{2}(1)\right)}}\)

Information:

Z = Z-score

R2 (2) = Adjusted R2 in the second regression model

R2 (1) = AdjustedR2 in the first regression model

σ2 (2) = Variance of the second regression model

σ2 (1) = Variance of the first regression model.

4. Results and Discussion

4.1. Descriptive Statistics

The results of the descriptive statistical analysis of 101 companies for normal data for model 1 and 91 companies for normal data for model 2 can be seen in Table 1 and Table 2 below.

Table 1: Descriptive Statistics Model 1

Table 2: Descriptive Statistics Model 2

Based on Table 1 it is known that the average asset growth variable (PA) is 0.065097, the minimum value is -0.477920, and the maximum is 0.620340 with a standard deviation of 0.138486. Therefore, the average value of 0.065097 shows that the average growth of the company’s assets is increasing by 6.50%, increasing compared to the previous year.

The average liabilities growth variable (PL) is 0.072120, the minimum value is -0.642010, and the maximum is 1.165360 with a standard deviation of 0.254173. Based on the average value of 0.072120. Therefore, the average value of 0.07120 shows that the growth of the company’s liabilities is 7.21%, which is greater than the previous period.

The average equity growth variable (PE) is 0.114174, the minimum value is -0.491620, and the maximum is 1.777600 with a standard deviation of 0.29380733. Therefore, the average value of 0.114174 shows that the average growth of the company’s equity is which is increasing 11.41% compared to the previous year.

The average income growth variable (PP) is 0.045025, the minimum value is -0.786240, and the maximum is 0.606360 with a standard deviation of 0.17655821. Therefore, the average value of 0.045025 shows that the average growth of the company’s revenue is increasing by 4.50%, compared to the previous year.

The average variable operating expense growth (PBO) is 0.273695, the minimum value is -0.782890, and the maximum is 8.15310 with a standard deviation of 1.20452043. Therefore, the average value of 0.273695 shows that the average growth of the company’s operating expenses is 27.36%, an increase compared to the previous year.

The average profit growth variable (PLA) is -0.175240, the minimum value is -6.627876, and the maximum is 4.543120 with a standard deviation is 1,39028536. Therefore, the average value of -0.175240 shows that the average growth of the company profits is decreasing by 17.5% compared to the previous period.

The average stock price performance growth variable (KHS) is -0.036762, the minimum value was -0.395880, and the maximum was 0.334250 with a standard deviation of 0.14160899. Therefore, the average value of -0.036762 shows the average growth in the performance of the company’s stock price is decreasing by 3.67% compared to the previous period.

Based on Table 2. it is known that for the asset growth variable (PA) the average is 0.2389090, the minimum value is -0.89198, and the maximum is 13.17156 with a standard deviation of 1.40893583. So, based on the average value of 0.065097, it shows that the average growth of the company’s assets is 23.89%, growing compared to the previous year.

The average liabilities growth variable (PL) is 0.0779181, the minimum value is -0.74522, and the maximum is 1.10848 with a standard deviation of 0.24691178. Based on the average value of 0.0779181 shows that the average growth of the company’s liabilities is 7.79% greater than the previous period.

The average equity growth variable (PE) is 0.2377016, the minimum value is -3.99844, and the maximum is 8.89766 with a standard deviation of 1.17539902. So, based on the average value of 0.2377016, it shows that the average growth of the company’s equity is 23.77%, growing compared to the previous year.

The income growth variable (PP) has an average of 0.0590998, the minimum value is -0.786240, and the maximum is 0.78388 with a standard deviation of 0.19593534. So, based on the average value, it shows that the average growth in company revenue is 5.91%, growing or increasing compared to the previous year.

The variable operating expense growth (PBO) has an average of 0.3657919, the minimum value is -0.64403, and the maximum is 10.16401 with a standard deviation of 1.49319163. So, based on the average value, it shows that the average growth of the company’s operating expenses is 36.57%, an increase compared to the previous year.

The average profit growth variable (PLA) is 0.6040799, the minimum value is -5.84275, and the maximum is 39.94606 with a standard deviation of 4.96028611. So, based on the average value, it shows that the average growth in company profits is decreasing by 60.41% compared to the previous period.

The variable stock price performance growth (KHS) averaged -0.0281499, the minimum value was -0.23651, and the maximum was 11.72849 with a standard deviation of 0.12954220. Based on the average value shows the average growth in the performance of the company’s stock price is decreasing by 2.82% compared to the previous period.

The interaction between PA, PL, PE, PP, PBO, PLA with CSR growth showed that the mean of each variable is lower than the standard deviation, so this indicated the data is high variation.

4.2. Normality Test

To assess this study’s data normality, the KolmogorovSmirnov test was carried out with the following results:

Judging from Table 3 it is known that the test for initial normality can be seen from the KolmogorovSmirnov sig value of 0.000 <0.05. Therefore, it can be said that the data in this study is not normal. Then the data is removed from normal or outliers. In model 1, of the 184 data, there is 83 abnormal data such that the normal data is 101, while for model 2 of the 184 data, there is 93 abnormal data such that the normal data is 91 with the following results:

Table 3: Initial Normality Test Results Model 1 and Model 2

Based on Table 4 above it is known that the test for final normality in model 1 and model 2 has a Sig value. Kolmogorov Smirnov amounted to 0.200 and 0.200, respectively, which value is more significant than 0.05, so it can be assumed that the results are normally distributed.

Table 4: Final Normality Test Results Model 1 and Model 2

4.3. Multicollinearity Test

The Multicollinearity test is a test to assess whether or not there is a correlation between independent variables. VIF and Tolerance values assess the presence or absence of multicollinearity. If the VIF value 0.1, it is certain that there is no multicollinearity. The following are the results:

Based on Table 5 it can be seen that the test results show multicollinearity because the tolerance value is 10. This is treated by eliminating the correlation on the growth of CSR costs with the following results:

Table 5: Multicollinearity Test Results Model 1 and Model 2 (Initial)​​​​​​​

Table 6: Multicollinearity Test Results Model 1 and Model 2 (Final)​​​​​​​

4.4. Autocorrelation Test

After the multicollinearity test, we perform the autocorrelation test. To find out the existence of autocorrelation in a regression model, the Durbin Watson (DW) test is carried out. The results are as follows:

Based on Table 7 it can be seen that the autocorrelation test results of Model 1 and Model 2 are 1.796 and 2.148, which are between 1.5 and 2.5 meaning that there is no or free autocorrelation in this study.

Table 7: Autocorrelation Test Results Model 1 and Model​​​​​​​

4.5. Heteroscedasticity Test

This section discusses the heteroscedasticity test. In this study, to test heteroscedasticity, the Glejser test was used. In the Glejser test, the residual absolute value (| u |) is regressed with the independent variable. The following are the test results.

Based on Table 8 it can be seen that the results of heteroscedasticity testing for each independent variable have a significant value above 0.05 (sig> 0.05); therefore, it can be said that heteroscedasticity does not occur.

Table 8: Results of Heteroscedasticity Testing Models 1 and 2​​​​​​​

4.6. Hypothesis Test

Hypothesis 1 testing (H1-H6) to determine the effect of assets, liabilities, equity, income, expenses, and profits on stock price performance (stock returns) using linear regression. The following are the results of testing hypothesis 1 (H1-H6).

Table 9 shows that sig. F = 0.000 <0.05; therefore, the model is fit, or the independent variable can be used to predict the dependent variables. Adjusted R Square value of 0.194 means that the independent variable affects the dependent variables by 19.4% while other variables influence the remaining 80.6%.

Table 9: Hypothesis Testing Results

KHS1 = α0 + β1 PA + β2 PL + β3 PE + β4PP + β5 PBO + β6PLA + e​​​​​​​

First Hypothesis

Based on the analysis, it is known that the beta coefficient value for the asset growth variable is 0.230 (positive sign) with a t-test value of 1.893 and a significance of 0.061. As a result, the findings of this test demonstrate that asset growth has a favorable impact on stock market performance and is statistically significant at 10%. The results of this study agree with the research conducted by Handyansyah and Lestari (2016) which states that asset growth has a positive effect on stock price performance. The asset growth variable with the share price variable has a moderate and positive correlation level, which indicates that asset growth has a positive correlation with stock prices. If the growth of assets increases, the stock price will increase, and vice versa. Profitable asset growth reflects the optimal use and management of company assets which will increase the company’s share price.

Second Hypothesis

Based on the analysis, it is known that the beta coefficient value for the liabilities growth variable is 0.042 (positive sign) with a t-test value of 0.419 and a significance of 0.676. The results of this test show that the growth of liabilities has a positive effect on stock price performance, but it is not statistically significant. Therefore, the second hypothesis in this study is rejected because the beta coefficient is different from the direction of stock price performance.

Third Hypothesis

Based on the analysis, it is known that the beta coefficient value for the equity growth variable is 0.004 (positive sign), and the t-test value is 0.035, with a significance of 0.972. The results of this test show that equity growth has a positive but statistically insignificant effect on stock price performance at a 5% level. Therefore, the third hypothesis in this study is rejected because it is not statistically significant to the stock price performance.

The findings of this analysis are consistent with the analysis performed by Sudiyatno et al. (2020), which concluded that equity does not have a substantial impact on stock prices. The reason for the rejection of this hypothesis is because investors do not see high or low equity growth when they invest in the stock market; therefore, this hypothesis is rejected. Investors do not use the book value of equity as the knowledge that has to be weighed when making investment decisions when the company’s operations are profitable.

Fourth Hypothesis

Based on the analysis, it is assumed that the beta coefficient value for the income growth variable is 0.159 (positive sign), and the t-test value is 1.711, with a significance of 0.090. Therefore, the results of this test indicate that income growth has a positive effect on stock price performance and is statistically significant at a 10% level. This concurs with research conducted by Rahmadewi and Abundanti (2018), who stated that income growth has a positive impact on stock performance. The higher the profits of a company, the higher the stock market output. A company’s revenue growth which is increasing compared to the previous period indicates that the performance is getting better, so this will be good news for investors in the stock market. This good news, and encourages investors to invest in the company; this increases the performance of share prices.

Fifth Hypothesis

Based on the analysis, it is known that the beta coefficient value for the operating expenses growth variable is -0.218 (negative sign) and the t-test value is -2.335 with a significance of 0.022. Therefore, the results of this test indicate that the growth in operating expenses hurts stock price performance and is statistically significant at a 5% level. These results agree with the research of Ball (1991), and Jensen and Meckling (1976) who showed that there is a negative and significant relationship between expenses and stock performance. Therefore, the higher the operating expenses of the company means the company has to incur more expenses such that it becomes bad news for investors, thereby reducing stock performance. Thus, it can be said that there is a negative influence between the growth of expenses and the stock price performance.

Sixth Hypothesis

Based on the analysis, it is known that the beta coefficient value for the profit growth variable is 0.261 (positive sign), and the t-test value is 2.855, with a significance of 0.005. Therefore, the results of this test indicate that profit growth has a positive effect on stock price performance and is statistically significant at a 1% level. The results agree with the research of Fitri et al. (2016), Pujiarti et al. (2017), and Agustami and Syahida (2019) who stated that profit has a positive and significant effect on stock prices. The company’s profit growth shows that when a company has better and more profits compared to the previous period, it is good news for the company. This encourages investors to invest in the company which will improve its share price performance. Thus, it can be said that profit growth has a positive effect on stock price performance

Seventh Hypothesis

Based on the analysis, it is known that the t significance value for the asset growth variable x CSR cost growth is 0.075 <0.10 with a positive beta coefficient value of 0.322. Therefore, the growth in CSR cost can be a moderating variable that strengthens the effect of asset growth on stock price performance. Therefore, the seventh hypothesis in this study is supported empirically at a 10% level.

Eighth Hypothesis

Based on the analysis, it is known that the significance value of t for the liabilities growth variable x CSR cost growth is 0.127> 0.05 with a negative beta coefficient value of -0.299. Therefore, growth in CSR cost cannot be a moderating variable that strengthens the effect of growth in liabilities on the price-performance stock. Hence, the eighth hypothesis in this study is not supported empirically.

Ninth Hypothesis

Based on the analysis, it is known that the t significance value for the equity growth variable x CSR cost growth is 0.170> 0.05 with a positive beta coefficient value of 0.150. Therefore, the growth in CSR cost cannot be a moderating variable that strengthens the effect of equity growth on stock price performance. Hence, the ninth hypothesis in this study is not supported empirically

Tenth Hypothesis

Based on the analysis, it is known that the t significance value for the load growth variable x CSR cost growth is 0.081 <0.10 with a negative beta coefficient value of -0.299. Therefore, the growth in CSR cost can be a moderating variable that weakens the effect of load growth on stock price performance. Hence, the tenth hypothesis in this study is supported empirically at a 10% level. These results concur with research conducted by Ball (1991) and Jensen and Meckling (1976), who stated that there is a negative influence between the growth of expenses and performance of the company’s stock price, especially in the condition that a company has high CSR cost growth means that it will weaken the influence of the burden on the stock price performance. Higher load growth means worse performance and this will reduce the performance of the company’s stock price.

Eleventh Hypothesis

Based on the analysis, it is known that the t significance value for the revenue growth variable x CSR cost growth is 0.005 <0.10 with a positive beta coefficient value of 0.261. Therefore, the growth in CSR cost can be a moderating variable that strengthens the effect of revenue growth on stock price performance. Therefore, the eleventh hypothesis in this study is supported empirically at a 10% level.

Twelfth Hypothesis

Based on the analysis, it is known that the t significance value for the profit growth variable x CSR cost growth is 0.094 <0.10 with a positive beta coefficient value of 0.151. Therefore, t net profit growth can be a moderating variable that strengthens the effect of profit growth on stock price performance. Hence, the twelfth hypothesis in this study is supported empirically at a10% level.

5. Conclusions

Based on the results of the analysis and discussion in the previous section, it can be concluded as follows:

1. Asset growth has a positive effect on stock price performance and is statistically significant at the 10% level.

2. Liability growth does not affect because the beta coefficient has different directions on the stock price performance.

3. Equity growth does not affect because it is not statistically significant to stock price performance.

4. Income growth has a favorable influence (positive effect) on stock price performance which is statistically significant at a 10% level.

5. Operating costs growth hurts stock price performance and is statistically significant at the 5% level.

6. Profit growth has a positive effect on stock price performance and is statistically significant at a 1% level.

7. CSR cost growth can be a moderating variable that strengthens the effect of asset growth on stock price performance.

8. CSR cost growth cannot be a moderating variable that weakens the influence of the liabilities growth on stock price performance.

9. CSR cost growth cannot be a moderating variable that strengthens the effect of equity growth on stock price performance

10. CSR cost growth can be a moderating variable that weakens the effect of load growth on stock price performance.

11. CSR cost growth can be a moderating variable that strengthens the effect of revenue growth on stock price performance.

12. CSR cost growth can be a moderating variable that strengthens the effect of profit growth on stock price performance.