How does corporate social responsibility contribute to investment

J. of Multi. Fin. Manag. 40 (2017) 33–46

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Journal of Multinational Financial Management journal homepage: www.elsevier.com/locate/econbase

How does corporate social responsibility contribute to investment efficiency? Marwa Samet a,∗ , Anis Jarboui b a b

Faculty of Economics and Management, Airport Road Km 4, BP 3018, Sfax, Tunisia Higher Institute of Business Administration, Airport Road Km 4, BP 1013, Sfax, Tunisia

a r t i c l e

i n f o

Article history: Received 22 February 2017 Accepted 8 May 2017 Available online 11 May 2017 Jel classification: G310 Capital Budgeting Fixed Investment and Inventory Studies Capacity Keywords: Corporate social responsibility Investment efficiency Agency costs Information asymmetry STOXX Europe 600

a b s t r a c t This paper examines the direct and indirect link between CSR performance and investment efficiency. Our panel dataset consists of 398 European companies listed in the STOXX Europe 600 during 2009–2014. Our first result shows that firms with high CSR performance invest more efficiently. Then, we perform our analysis distinguishing two alternative situations: underinvestment and overinvestment. Focusing on under-investing firms, we highlight that CSR performance enhances their investment levels through mitigating information asymmetry. In contrast, for over-investing firms, CSR performance reduces investment excess through mitigating free cash flow problems. Overall, these findings suggest a role for CSR in indirectly ameliorating firm-level investment efficiency through helping firms address agency problems and information asymmetry problems. © 2017 Elsevier B.V. All rights reserved.

1. Introduction In perfect financial market, where investment decisions are independent from financial situation, firms should carry out all positive net present value projects and forgo all negative net present value projects (Modigliani and Miller, 1958). In order to maximize their values, companies invest until the marginal benefit equals the marginal cost of projects (Hayashi, 1982; Abel, 1983). Nevertheless, a large body of literature contradicts this assumption (Hubbard, 1998; Stein, 2003; Chen et al., 2014). Capital-market frictions may prevent managers from making better investment decisions. In this case, companies deviate from their optimal levels of investment. Prior literature suggests two main explanations as to why firms deviate from predicted investment levels: namely, agency conflicts of free cash flow (Jensen, 1986; Guariglia and Yang, 2016) and information asymmetry (Myers and Majluf, 1984; Biddle et al., 2009; Gomariz and Ballesta, 2014). Each explanation contributes to different distortion in the investment decision-making process. Whereas the free cash flow problems can lead to overinvestment problems, the existence of asymmetric information among various stakeholders is commonly related to underinvestment problems. Under agency theory, there are various control mechanisms, which help to alleviate the opportunistic behavior of managers and to mitigate asymmetric information, such as CSR activities (Waddock and Graves, 1997; Eccles et al., 2012; Lopatta et al., 2015). Thus, CSR strategies may be used to monitor both underinvestment and overinvestment problems.

∗ Corresponding author. E-mail addresses: [email protected] (M. Samet), [email protected] (A. Jarboui). http://dx.doi.org/10.1016/j.mulfin.2017.05.007 1042-444X/© 2017 Elsevier B.V. All rights reserved.

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M. Samet, A. Jarboui / J. of Multi. Fin. Manag. 40 (2017) 33–46

Several researches have explored various beneficial aspects of CSR and have found evidence that CSR is associated with higher firm value (Lin et al., 2009), lower financial constraints (Cheng et al., 2014), lower investment-cash flow sensitivity (Attig et al., 2014), improved information quality (Cho et al., 2013; Cui et al., 2015 and Lopatta et al., 2015) and reduced agency conflicts (Waddock and Graves, 1997; Harjoto and Jo, 2011 and Eccles et al., 2012). Building on this stream of research, we explore the extent to which CSR involvement may influence investment decisions. The main purpose of this study is to document the relation between corporate investment decisions and a firm’s engagement in CSR activities in European context. Specifically, we aim to examine whether, and in what ways, CSR performance influences investment efficiency. In other words, we aim to identify the channels through which CSR performance contributes to the efficient allocation of capital. While existing research examines only the direct link between CSR performance and investment efficiency (Benlemlih and Bitar, 2016), this study focuses on the direct and indirect link between CSR performance and investment efficiency. According to Baron and Kenny (1986), we develop a methodology to study how CSR performance affects firm-level investment efficiency. Does it manifest through reducing agency problems of free cash flow or through reducing asymmetric information between insiders and outsiders? We construct a panel datasets for non-financial listed companies in Europe STOXX 600, covering the period 2009–2014. Our first result shows that firms with higher CSR performance invest more efficiently. Then, we perform our analysis distinguishing two alternative situations: underinvestment and overinvestment. Focusing on under-investing firms, we highlight that CSR performance enhances their investment levels through mitigating information asymmetry problems. In contrast, for over-investing firms, CSR performance reduces investment excess through mitigating free cash flow problems. We contribute to the debate on whether CSR involvement is value-increasing by showing that high CSR performance positively affects investment efficiency. In addition, we contribute to the literature by demonstrating that one mechanism linking CSR performance and investment efficiency is a reduction of capital-market imperfections such as information asymmetry and agency problems. The remainder of the paper is organized as follows. Section 2 contains the literature review and hypothesis development. Section 3 describes in detail the research design with the sample, the models and measures of variables. Section 4 presents the empirical results. Section 5 concludes the paper. 2. Previous literature and hypotheses development 2.1. CSR performance and investment efficiency According to neo-classical theory, firms should carry out all positive net present value projects and forgo all negative net present value projects (Modigliani and Miller, 1958). In order to maximize their values, companies invest until the marginal benefit equals the marginal cost of projects (Hayashi, 1982; Abel, 1983). Nevertheless, a large body of literature contradicts this assumption (Hubbard, 1998; Stein, 2003; Chen el al. 2014). Capital-market frictions may prevent managers from undertaking all profitable investments. In this case, companies may deviate from their optimal levels of investment and thus suffer from two inefficient scenarios, underinvestment and overinvestment. The underinvestment scenario occurs when firms reject some profitable projects due to funds constraints. The overinvestment scenario occurs when self-interested managers undertake unprofitable projects in order to expropriate firms ‘resources. Given that financially constrained firms are more likely to face underinvestment problems (Hubbard, 1998; Campello et al., 2010), CSR performance may play a fundamental role in strategic investment decisions by influencing the firm s’ financial constraints. The adoption of CSR activities that leads to superior CSR performance contributes to facilitate the access to external finance (Cheng et al., 2014), hence allowing firms to undertake all desired investments (Stein, 2003). Consistent with this, El Ghoul et al. (2011, 2014) show that firms with better CSR scores exhibit cheaper equity financing. This is especially true for companies that improve their responsible employee relations, environmental policies and product strategies. Dhaliwal et al. (2011) further examine the benefit associated with the voluntary disclosure of CSR activities. They find that firms with superior social responsibility performance enjoy a reduction in the cost of equity capital, while attracting dedicated institutional investors and analyst coverage. Sharfman and Fernando (2008) point out that firms who develop a strategy that improves their environmental risk management are rewarded by the financial markets. The latter accept lower risk premiums on equity, which can result in reduced cost of capital. Similarly, Nandy and Lodh (2012) establish that more eco-friendly firms, defined as firms with higher environment score get a favorable loan contract than firms with lower environment score. Therefore, CSR can be a determinant of bank debt’s cost. Recently, El Ghoul et al. (2016a) posit that CSR performance is associated with improved access to finance, greater investment, lower default risk and longer trade credit period in countries with weaker market institutions. Attig et al. (2014) provide evidence that CSR performance lead to decrease in investment-cash flow sensitivity. The findings of this study stress the relevance of CSR in ameliorating firm-level investment efficiency. Lately, Benlemlih and Bitar (2016) highlight that the implementation of CSR activities helps to reduce investment inefficiency. More precisely, dimensions that are related to primary stakeholders such as employee relations, diversity, environment and product characteristics, are the most relevant in improving investment efficiency. Taken together, the discussion above suggests that CSR performance plays a prominent role in strategic investment decisions. Firms with higher CSR performance invest more efficiently. According to these arguments, our first hypothesis is:


Informaon asymmetry

(H2)

CSR

Investment inefficiency

(H1)

(H3)

35

Underinvestment Overinvestment

Agency Costs

Fig. 1. CSR and investment inefficiency.

H1: CSR performance reduces investment inefficiency

2.2. CSR performance, information asymmetry and investment efficiency Jensen and Meckling (1976), Myers and Majluf (1984), Myers (1984) develop a framework for the role of information asymmetry in investment decision-making process through information problems, such as adverse selection and moral hazard. Adverse selection appears when the market is less well-informed about the firm’s or the project’s quality. In this case, suppliers of capital may ratio the capital provided or raise its cost (Stiglitz and Weiss, 1981). This can oblige firms to abandon some profitable investment due to financial constraints, with the consequence of underinvestment problems. Moral hazard appears when managers deploy firm resources for their own benefit by making projects that may not be suitable for shareholders, with the consequence of overinvestment problems. Ascioglu et al. (2008) report that firms with high information asymmetry have greater investment-cash flow sensitivity, especially when they use the probability of informed trade to classify firms as constrained. Their results are consistent with Mansour (2014), who confirms that firms with more pronounced moral hazard problem are deemed to exhibit higher investment-cash flow sensitivity. Recently, Chowdhury et al. (2016) find that the implementation of SOX which is expected to improve information quality result in lower investment-cash flow sensitivity. Other studies analyze the effect of informational asymmetry on investment efficiency. Firms with high-quality financial information are found to deviate less from their optimal investment levels (McNichols and Stubben, 2008; Biddle et al., 2009; Chen et al., 2011; Gomariz and Ballesta, 2014). High levels of transparency facilitate the efficient allocation of capital through allowing managers to make better investment decisions. From the agency theory perspective, there are various control mechanisms to attenuate information risk. CSR can be used as a bonding mechanism to improve firms’ information quality. As Cho et al. (2013) suggest, CSR performance plays a positive role for investors by reducing information asymmetry and regulatory action may be appropriate to alleviate the adverse selection problem faced by less- informed investors. Attig et al. (2013) point out that CSR performance conveys important non-financial information, which can lead to lower financing costs resulting from higher credit ratings. Recent supportive evidence on the role of CSR in enhancing firms’ information quality is provided by Lopatta et al. (2015). The latter demonstrate that CSR activities can increase a company’s trust-worthiness via improving its moral standards, earnings quality and transparency. This increase in turn helps to mitigate information asymmetry. Indeed, firms with strong CSR performance induce managers to produce high quality financial report and reduce earnings management (Kim et al., 2012). Employing an extensive US sample, Cui et al. (2015) find an inverse association between information asymmetry and a firm’s engagement of CSR activities. They interpret these results as supporting the stakeholders-theory that considers CSR engagement as a vehicle to build and maintain firm reputation. This is consistent with Attig et al. (2016) and Boubakri et al. (2016), who shed light on the role of internationalization and cross-listing in influencing firms’ CSR activities. As they enter foreign markets, firms are more likely to engage in CSR investments to strengthen their reputation. In fact, multinational firms are associated with increased media attention, which positively affects CSR initiatives (El Ghoul et al., 2016b). Based on the above literature, we posit that the negative impact of CSR performance on investment inefficiency problems may be realized through reducing information asymmetry. Specifically, the existence of asymmetric information between the different firms’ stakeholders is commonly associated to underinvestment problems. Stated formally, as shown in Fig. 1, we hypothesize that: H2: Reducing information asymmetry has a mediating effect on the relationship between CSR performance and underinvestment problems

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2.3. CSR performance, agency costs and investment efficiency Agency problems arise when managers or controlling shareholders divert the firm’s resources in ways that benefit themselves but which are not in the best interests of the other shareholders, including minority shareholders (Jensen and Meckling, 1976; Shleifer and Vishny, 1997; Denis and McConnell, 2003; Hermalin, 2005; Gillan, 2006 and Djankov et al., 2008). Agency conflicts between management and shareholders, as well as between controlling shareholders and minority shareholders have been found to significantly affect firms’ investment decisions. (Myers and Majluf, 1984; Jensen, 1986; Fazzari et al., 1988; Jiang et al., 2010; Luo et al., 2015). Investment inefficiency, which can be captured by investment-cash flow sensitivity, appears to be especially severe for firms with substantial agency problems. Goergen and Renneboog (2001) analyze whether the investment-cash flow sensitivity differs for companies with varying degrees of ownership control. They illustrate that the presence of institutional blockholders contributes to reduce suboptimal investment by means of effective monitoring. Degryse and De Jong (2006) point out that the sensitivity of investment expenditures to internal funds can be attributed to overinvestment resulting from the abuse of managerial discretion. As for Andrén and Jankensgård (2015), they conclude that the investment-cash flow sensitivity for large firms increases in the abundance period, suggesting that this relationship is driven by agency problems related to free cash flow. This is in line with Pawlina and Renneboog (2005), who provide strong support for the free cash flow theory as the main source of the observed investment-cash flow sensitivity. Lately, Guariglia and Yang (2016) document, in the Chinese market, a strong evidence of investment inefficiency resulting from agency problems. Managers or Controlling shareholders expropriate firm’s resources by making entrenched and self-interested decisions. As a result, they prefer to spend the free cash flow on projects with negative net present value rather than paying dividends to shareholders, resulting in overinvestment problem. The conflict resolution hypothesis suggests that corporate social responsibility investments are made to reduce conflicts of interest among various stakeholders to maximize the shareholders’ wealth (Jensen, 2001; Calton and Payne, 2003 and Scherer et al., 2006). The adoption and implementation of CSR strategies limit the amount of free cash flow available, which can be used by self-interested mangers to undertake unprofitable projects (Jensen, 1986). The monitoring role of CSR is also supported by the good management hypothesis of Waddock and Graves (1997), who posit that investments in CSR activities improve key stakeholder relations, such as community relations and employee relations. Recently, a line of research has been developed on CSR’s role in mitigating agency problems. Borghesi et al. (2014) investigate the factors that spur firm to make socially responsible investments. They find that firms with greater free cash flow demonstrate higher levels of CSR. Harjoto and Jo (2011) prove that firms use governance mechanisms, along with CSR engagement, to resolve conflicts between mangers and non-investing stakeholders, which can lead to better firm value. Eccles et al. (2012) shed light on the organizational implications of integrating social and environmental issues into a company’s strategy. They maintain that high sustainability companies are more likely to establish a formal stakeholder engagement process that limits the likelihood of short-term opportunistic behavior. Last but not least, El Ghoul et al. (2016c) find that CSR underperformance concentrates in family firms with greater agency problems, consistent with the expropriation hypothesis. Based on this discussion, we postulate that the negative impact of CSR on financial investment inefficiency problems may be realized through mitigating agency costs of free cash flow. Specifically, the free cash flow problems are commonly related to overinvestment problems. Stated formally, as shown in Fig. 1, we hypothesize that: H3: Reducing agency costs has a mediating effect on the relationship between CSR performance and overinvestment problems. 3. Research design 3.1. Data and sample selection The sample in this study consists of European companies listed in STOXX Europe 600 index between 2009 and 2014. The sample includes 15 supersectors and 17 countries. Firms in the financial sector, such as banks and insurance companies, are discarded from the study. We drop also firms with missing data. The final panel covers 397 firms, which corresponds to 2382 firm-year observation. Table 1 summarizes the sample composition. Panel A presents the distribution of firms across sectors. Three sectors, industrials, consumer goods and consumer services represent a large portion of the total number of firms, although the remaining sectors are also populated. Panel B presents the distribution of firms across countries. Approximately 60 percent of the sample originates from United Kingdom, France, Germany and Switzerland. For our empirical analysis, we extract accounting and financial data from the DATASTREAM database. Data concerning CSR performance derive from Thomson Reuters- ASSET 4. In order to alleviate the potential effects of extreme observations, we winsorize the data at the 1th and 99th percentile levels. 3.2. Variables measures 3.2.1. Dependent variable: investment inefficiency Similar to Gomariz and Ballesta (2014), we measure investment inefficiency as deviation from the expected level of investment, Therefore, underinvestment phenomena will exist when firms invest below their optimal investment, while


37

Table 1 Sample composition. Panel A. Sample distribution across sectors ICB code

Industry

N

%

0001 1000 2000 3000 4000 5000 6000 7000 9000

Oil & Gas Basic Materials Industrials Consumer Goods Health Care Consumer Services Telecommunications Utilities Technology Total

22 41 114 63 32 64 18 23 20 397

5.54% 10.33% 28.72% 15.87% 8.06% 16.12% 4.53% 5.79% 5.04% 100%

Panel B. Sample distribution across countries Country

N

%

Country

N

%

Austria Belgium Denmark Finland France Germany Greece Ireland Italy

3 9 13 14 62 44 2 5 16

0.76% 2.27% 3.27% 3.53% 15.62% 11.08% 0.50% 1.26% 4.03%

Luxembourg Netherlands Norway Portugal Spain Sweden Switzerland UK

2 19 10 3 16 25 30 124

0.50% 4.79% 2.52% 0.76% 4.03% 6.30% 7.56% 31.23%

overinvestment phenomena will exist when firms invest above their optimal investment. We estimate the deviation from the expected investment following the model developed by Chen et al. (2011). Investmenti,t = ␤0 + ␤1 NEGi,t−1 + ˇ2 SalesGrowthi,t−1 + ˇ3 NEGi,t−1 ∗ SalesGrowthi,t−1 + ␧i,t Where Investmenti,t is the total investment of firm i in year t, defined as the net increase in tangible and intangible assets and scaled by lagged total assets. Sales growthi,t -1 is the percentage of change in sales of firm i from year t − 2 to year t. NEGi,t-1 is a dummy variable that takes value one for negative sales growth, and zero otherwise. We estimate the investment model for each industry-year. The residuals from the regression capture the deviation from the expected level of investment. We use these residuals as our main proxy for investment inefficiency. A positive residual signifies that real investment is more than expected, representing an overinvestment scenario. In contrast, a negative residual signifies that a company is making investment at a lower level than expected according to sales growth, representing an underinvestment scenario. Our dependent variable (INEFF V) is the absolute value of the residuals. Thereby a high value reflects a high level of investment inefficiency. 3.2.2. Independent variable: CSR performance For our analysis, we construct an aggregated CSR index, as Cheng et al. (2014) and Attig et al. (2016), by using the annual environmental, social and corporate governance scores obtained from Thomson Reuters-ASSET 4. In the absence of theoretical guidance about how to weight each measure, we follow the convention established by Sharfman (1996), Waddock and Graves (1997). We assign equal importance to each of the three pillars. Thus, the variable CSR is the equally weighted average of the environmental, the social and the governance score for each focal firm for every year. 3.2.3. Mediating variables 3.2.3.1. Information asymmetry. As there is no general agreement on the “best” measure of asymmetric, we choose one of the most commonly used in the literature: the spread ratio. In line with Kanagaretnam et al. (2005), Cheng et al. (2011) and Cho et al. (2013), we calculate the spread (SPREAD) by annually averaging the ratio of the daily bid-ask spread to the closing price. 3.2.3.2. Agency costs. Conflicts of interest between managers and shareholders are especially severe when the company generates substantial free cash flow (Jensen, 1986). Specifically, the availability of free cash flow under management control will induce them to invest in non value-maximizing projects, creating an over-investment problem, and consequently increasing the costs incurred by shareholders. Motivated by Chi and Lee (2010), we use the free cash flow as our proxy for potential agency costs. We employ the free cash flow measure of undistributed cash flow established by Lehn and Poulsen (1989). Thus, Free Cash Flow (FCF) is defined as operating income minus the sum of the following four components: income taxes, interest expenses on debt, common stock dividend and preferred stock dividend. We scale this free cash flow measure by the firm’s book value of assets.

38


3.2.4. Control variables Following previous researches, we include several control variables in our models. As proxy for age (AGE), we use the natural the natural logarithm of the years since firm’s inception. Institutional ownership (INS) is measured as the percentage of total shares in issue held by investment banks or institutions. We add also dummy variables to control for country, industry and year fixed effects (COUNRTY, INDUSTRY and YEAR). 3.3. Model specification Our point of departure in the multivariate analysis is the following model (1) for estimating the relationship between CSR performance and investment inefficiency: INEFF V i,t = ˛0 + ˛1 CSR i,t + ˛2 INS i,t + ˛3 AGE i,t +

9

18

˛j YEAR i,t +

˛K INDUSTRY i,t +

K =10

j=4

35

˛L COUNTRY i,t + ␧i,t

L=19

Where INEFF V is the investment inefficiency; CSR is the corporate social responsibility performance; INS represents institutional ownership; AGE represents firm age; YEAR, INDUSTRY and COUNTRY stand respectively for year, industry and country fixed effects; ␧is an error term. We perform our analysis of inefficient investment distinguishing two alternative situations: underinvestment and overinvestment. In the underinvestment scenario, we consider as dependent variable (UNDER) the negative residuals in the investment model (the negative deviations from the expected investment). Thus, high value (i.e., close to zero) indicate low underinvestment problem, that is, low inefficiency. In the overinvestment scenario, we consider as dependent variable (OVER) the positive residuals in the investment model (the positive deviations from the expected investment). Thus, high value indicates high overinvestment problem, that is, high inefficiency. According to our first hypothesis, the coefficient on CSR is expected to be negative when the dependent variable is either investment inefficiency or overinvestment, and it is expected to be positive when the dependent variable is underinvestment. In the underinvestment scenario, the mediating role of information asymmetry is tested using the mediation procedure outlined by Baron and Kenny (1986). At a first stage, the dependent variable (UNDER) is regressed on the independent variable (CSR). At the second stage, the mediator (SPREAD) is regressed on the independent variable (CSR). Finally, the dependent variable (UNDER) is regressed on the independent variable (CSR) and the mediator (SPREAD). Therefore, to test our second hypothesis, we formulate the conceptual framework as the following three models: UNDER i,t = ˛0 + ˛1 CSR i,t + ˛2 INS i,t + ˛3 AGE i,t +

9

9

˛K INDUSTRY i,t +

K =10

j=4

SPREADi,t = ˛0 + ˛1 CSR i,t + ˛2 INS i,t + ˛3 AGE i,t +

18

˛j YEAR i,t +

35

˛K INDUSTRY i,t +

K =10

j=4

UNDER i,t = ˛0 + ˛1 CSR i,t + ˛2 SPREADi,t + ˛3 INS i,t + ˛4 AGE i,t +

10


L=19

18

˛j YEAR i,t +

35


L=19

˛j YEAR i,t

j=5

+

19

˛K INDUSTRY i,t +

K =11

36


L=20

Where UNDER is the underinvestment; CSR is the corporate social responsibility performance; SPREAD is the bid-ask spread; INS represents institutional ownership; AGE represents firm age; YEAR, INDUSTRY and COUNTRY stand respectively for year, industry and country fixed effects; ␧ is an error term. In the overinvestment scenario, we propose the following three multiple regression analyses to estimate the mediating role of agency costs of free cash flow. OVER i,t = ˛0 + ˛1 CSR i,t + ˛2 INS i,t + ˛3 AGE i,t +

9

˛j YEAR i,t +

j=4

FCF i,t = ˛0 + ˛1 CSR i,t + ˛2 INS i,t + ˛3 AGE i,t +

9 j=4

˛j YEAR i,t +

18

˛K INDUSTRY i,t +

K =10 18

˛K INDUSTRY i,t +

K =10

35


L=19 35


L=19


39

Table 2 Descriptive statistics. Panel A. Summary statistics of the sample Variable

Mean

Min

Q1

Median

Q3

Max

Std.Dev

INEFF V OVER UNDER CSR FCF SPREAD INS AGE

0.087 0.113 −0.073 72.735 0.033 0.182 5.008 4.004

0.000 0.000 −0.299 6.857 −0.101 0.033 0.000 0.693

0.028 0.026 −0.095 65.650 0.009 0.077 0.000 3.296

0.058 0.065 −0.056 78.350 0.031 0.112 0.000 4.190

0.105 0.131 −0.030 86.083 0.053 0.180 8.000 4.762

0.648 0.648 0.000 96.083 0.169 1.605 67.000 6.475

0.099 0.140 0.060 18.299 0.042 0.235 7.788 0.939

Panel B. Average value of variables across countries Variable

INEFF V

CSR

FCF

SPREAD

INS

AGE

Austria Belgium Denmark Finland France Germany Greece Ireland Italy Luxembourg Netherlands Norway Portugal Spain Sweden Switzerland United Kingdom

0.039 0.065 0.103 0.067 0.067 0.080 0.103 0.071 0.085 0.061 0.090 0.115 0.064 0.068 0.093 0.095 0.102

61.414 77.903 65.660 80.534 75.732 63.641 56.265 62.743 79.491 68.092 73.711 64.094 72.996 71.970 74.676 66.704 75.803

0.011 0.015 0.058 0.010 0.024 0.022 0.034 0.014 0.012 0.018 0.036 0.021 −0.008 0.014 0.030 0.045 0.048

0.183 0.121 0.203 0.148 0.131 0.137 0.329 0.240 0.489 0.116 0.111 0.151 0.194 0.596 0.181 0.155 0.153

2.111 1.315 3.577 4.012 6.083 3.216 6.250 7.033 1.563 0.000 5.675 2.267 0.944 2.510 7.540 3.333 6.565

4.441 4.502 3.881 3.862 4.126 3.936 4.074 3.834 4.102 2.574 3.825 3.391 4.480 3.662 4.082 3.949 4.072

OVER i,t = ˛0 + ˛1 CSR i,t + ˛2 FCF i,t + ˛3 INS i,t + ˛4 AGE i,t +

10 j=5

+

36

˛j YEAR i,t +

19

˛K INDUSTRY i,t

K =11


L=20

Where OVER is the overinvestment; CSR is the corporate social responsibility performance; FCF is the free cash flow; INS represents institutional ownership; AGE represents firm age; YEAR, INDUSTRY and COUNTRY stand respectively for year, industry and country fixed effects; ␧ is an error term. 4. Results and discussion 4.1. Descriptive statistics Table 2 provides descriptive statistics for the regression variables. Panel A presents descriptive statistics for the entire sample, including the mean, minimum, first quartile, median, third quartile, maximum and standard deviation. Investment inefficiency (INEFF V) shows a mean of 0.087. Separately, in an underinvestment scenario the mean value is −0.073, while in an overinvestment scenario the mean value is 0.113. The figures are consistent with prior research (Gomariz and Ballesta, 2014). The CSR has a mean value of 72.735. The standard deviation of CSR is 18,299, implying that significant variation exists across firms regarding the CSR involvement. Specifically, the distribution ranges from 6.857 for the least socially responsible firm to 96.083 for the most socially responsible firm. Furthermore, the firms in our sample have an average a SPREAD of 0.182 and a FCF of 0.033. The institutional ownership percentage (INS) shows low ownership level (mean 5%). Panel B presents the average values of the regression variables for each of the European countries represented in our sample. The country factor plays a role for many variables. In particular, CSR index is clearly different from one country to the next. Finland shows the highest index with an average score of 80.534, followed by Italy (79,491).

40


Table 3 CSR performance and investment inefficiency. INEFF V

Constant CSR

Model 1

Model 1a

Model 1b

Model 1c

0.0758*** (7.72) −0.0002** (−2.53)

0.0781*** (8.24)

0.0717*** (7.60)

0.0620*** (6.87)

−0.0002*** (−3.28)

Environmental Social Governance

−0.0001*** (−2.97)

Year FE Industry FE Country FE

0.0003*** (2.71) −0.0047*** (−3.68) Yes Yes Yes

0.0003*** (2.79) −0.0045*** (−3.57) Yes Yes Yes

0.0003*** (2.82) −0.0047*** (−3.71) Yes Yes Yes

5.41e-05 (1.22) 0.0002** (2.25) −0.0052*** (−3.92) Yes Yes Yes

Observations R-squared

2382 0.0630

2382 0.0665

2382 0.0660

2382 0.0570

INS AGE

The dependent variable is investment inefficiency. CSR is the annual corporate social responsibility performance. Environmental is the annual environmental performance of a corporation. Social is the annual social performance of a corporation. Governance is the annual corporate governance performance. INS is institutional ownership. AGE is firm age. All the estimates have been carried out using cross-sectional time-series FGLS regression. T-statistic values are in the brackets. Statistical significance at the 10%, 5% and 1% levels is indicated in bold face and by *, ** and ***, respectively.

4.2. Regression results The results estimating Model (1), which is developed to analyze whether CSR performance either ameliorates or distorts firm-level investment efficiency, are presented in Table 3. We find a strong support for our first hypothesis: the estimated coefficient of CSR is negative and statistically significant (␣ = −0.0002, p < 5%), suggesting that CSR performance has a negative effect on investment inefficiency. This finding is consistent with our expectation: firms with high CSR performance are typically characterized by reduced investment-cash flow sensitivity, low financial constraints, better access to finance and high management quality, which contributes to alleviate the inefficiency of investment. In other words, CSR performance facilitates the efficient allocation of capital. Our evidence is in line with those reported by Benlemlih and Bitar (2016). With regard to the control variables, firm age is negatively and significantly related to investment inefficiency (␣ = −0.0047, p < 1%), indicating that older firms invest more efficiently than younger firms. In contrast, institutional ownership is positively and significantly related to investment inefficiency (␣ = 0.0003, p < 1%). This positive relation can be explained in terms of low institutional ownership levels (mean of 5%). Such institutional investors are often referred to as myopic, or transient investors, who exhibit a strong preference for current earnings (Bushee, 1998; Bushee, 2001). Given that the role of institutional investors is likely to differ depending on their characteristics (Agnes Cheng and Reitenga, 2009 and Koh, 2003), short-term oriented institutional investors have few incentives to engage in effective monitoring. In this case, the likelihood that firms deviate from their optimal level of investment increases (Attig et al., 2012). As we mentioned earlier, CSR performance reflects a balanced view of a company’s performance in three areas: the environmental, the social and the corporate governance performance. The environmental pillar reflects how well a company uses best management practices to avoid environmental risks and capitalize on environmental opportunities. It covers three categories including emission reduction, product innovation and resource reduction. The social pillar is a reflection of the company’s reputation and the health of its license to operate. It covers seven categories including product responsibility, diversity and opportunity, employment quality, health and safety, training and development, community and human rights. The corporate governance pillar reflects a company’s capacity, through its use of best management practices, to direct and control its rights and responsibilities through the creation of incentives, as well as checks and balances. It covers four categories including vision and strategy, board function, board structure and compensation policy. To better understand which dimensions have a consistent impact on investment decisions, we disaggregate the CSR performance into its components and we estimate separate models for each one. The results are reported in Table 3. We find that environmental and social performances have a negative and significant effect on investment inefficiency. However, the corporate governance performance exhibits an insignificant effect. The results reveal that the key role of CSR in improving investment efficiency is driven by both the environmental and the social dimension. As an extension to our research, we divide our sample into underinvestment scenario (negative deviation with regard to expected investment) and overinvestment scenario (positive deviation with regard to expected investment). In firms that underinvest, we test whether CSR performance may mitigate underinvestment problems through reducing information asymmetry. In firms that overinvest, we test whether CSR performance may mitigate overinvestment problems through reducing free cash flow problems.


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Table 4 CSR performance, information asymmetry and underinvestment. UNDER

SPREAD

UNDER

Model 2

Model 3

Model 4

−0.0668*** (−7.09) 0.0002*** (3.42)

0.4281*** (17.98) −0.0027*** (−24.37)


0.956e-04 (0.77) 0.0035*** (3.04) Yes Yes Yes

0.851e-04 (0.08) 0.0102 (1.21) Yes Yes Yes

−0.0660*** (−7.04) -0.761e-04 (−1.04) −0.0052** (−2.19) 0.888e-04 (0.71) 0.0037*** (3.21) Yes Yes Yes


1494 0.1208

1494 0.2343

1494 0.1217

Constant CSR SPREAD INS AGE

Models (2) and (4): The dependent variable is underinvestment. Model (3): The dependent variable is the bid-ask spread. CSR is the annual corporate social responsibility performance. SPREAD is the bid-ask spread. INS is institutional ownership. AGE is firm age. All the estimates have been carried out using cross-sectional time-series FGLS regression T-statistic values are in the brackets. Statistical significance at the 10%, 5% and 1% levels is indicated in bold face and by *, ** and ***, respectively.

Table 4 presents the results estimating the mediating role of information asymmetry in the relationship between CSR performance and underinvestment problems. Following the procedure used by Baron and Kenny (1986), three conditions must be fulfilled to prove the existence of mediation process: (i) in the first regression, the independent variable (CSR) must significantly predict the dependent variable (UNDER); (ii) in the second regressionl, the independent variable (CSR) must significantly predict the mediator (SPREAD) and (iii) in the third regression, the mediator (SPREAD) must significantly predict the dependent variable (UNDER). Partial mediation is revealed when the effect of the independent variable on the dependent variable is less in the third regression than in the first. Perfect mediation is revealed if the independent variable has no effect when the mediator is controlled. In Model (2), the estimated coefficient of CSR is positive and significant (␣ = 0.0002, p < 1%), as predicted. The result suggests that higher CSR performance reduces underinvestment problems. More precisely, CSR is a mechanism that helps companies to enhance their investments and thus move towards their optimal levels. This evidence seems to support the view that CSR performance plays an important role in improving firms ‘ability to access finance (Cheng et al., 2014) and to undertake profitable projects (Benlemlih and Bitar, 2016). Model (3) shows that the coefficient on CSR is negative and significant (␣ = − 0.0027, p < 1%), indicating that an increase in CSR performance leads to a decrease in information asymmetry. This result is in line with Cui et al. (2015), Cho et al. (2013) and Lopatta et al. (2015), who report that firm’s CSR engagement makes information environment more transparent. Model (4) shows that the coefficient on SPREAD is negative and significant (␣ = −0.0052, p < 5%), claiming that the asymmetrical distribution of information between managers and stakeholders decreases the level of investment. Specifically, when information environment is more opaque, the cost of external funds often exceeds the cost of internal funds. In this circumstance, firms are obliged to forgo some profitable projects due to their difficulties in raising external capital, with subsequent underinvestment (Guariglia et al., 2016 and Chen et al., 2011). However, the significant effect of CSR on underinvestment is tenuous (␣ = −0.761e-04, p > 10%) when the SPREAD’s effect is controlled In summary, these results meet the requirements of identifying a perfect mediation, according to Baron and Kenny (1986). Therefore, our second hypothesis (H2) that reducing information asymmetry has a mediating effect on the relationship between CSR performance and underinvestment problems is strongly supported. That is, the negative effect of CSR performance on underinvestment problems follows the path through mitigating information asymmetry. Table 5 reports the results of estimating Model (5), (6) and (7), developed to capture the mediating role of agency costs of free cash flow in the relationship between CSR performance and overinvestment. In Model (5), the coefficient on CSR is negative and statistically significant (␣ = −0.0006, p < 1%). In firms when investment is higher than expected, CSR performance decreases investment excess. Hence, high CSR involvement diminishes investment inefficiency related to overinvestment. Model (6) focuses on the effect of CSR performance on the FCF. The estimated coefficient of CSR is negative and statistically significant (␣ = −0.0001, p < 1%), meaning that CSR performance attenuates the free cash flow problems. the adoption of CSR strategies limits the amount of free cash flow available, which can be used by self-interested mangers to undertake non-value adding projects (Jensen, 1986). Model (7) examines whether the free cash flow has a significant impact on overinvestment. The estimated coefficient of FCF is positive and statistically significant (␣ = 0.2318, p < 1%), indicating that firms with greater free cash flow suffer more from overinvestment phenomena because of the abuse of managerial discretion. Specifically, managers tend to expropriate firm’s resources by making self-interested decisions. They prefer to spend the free cash flow on unprofitable projects rather than paying dividends to shareholders, which result in overinvestment. Such evidence is in line with previous empirical results (Guariglia and Yang, 2016; Pawlina and Renneboog, 2005). In addition, the inclusion of

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Table 5 CSR performance, agency costs and overinvestment. OVER

FCF

OVER

Model 5

Model 6

Model 7

0.0739*** (3.79) −0.0006*** (−5.48)

0.1247*** (12.13) −0.0001*** (−4.56)


0.0016*** (7.46) −0.0021 (−0.98) Yes Yes Yes

0.0003*** (5.23) −0.0035*** (−5.62) Yes Yes Yes

0.0653*** (3.60) −0.0013* (−1.81) 0.2318*** (4.29) 0.0017*** (8.16) −0.0024 (−1.12) Yes Yes Yes


888 0.0950

888 0.1525

888 0.0957

Constant CSR FCF INS AGE

Models (5) and (7): The dependent variable is overinvestment. Model (6): The dependent variable is the Free Cash Flow. CSR is the annual corporate social responsibility performance. FCF is the free cash flow. INS is institutional ownership. AGE is firm age. All the estimates have been carried out using cross-sectional time-series FGLS regression. T-statistic values are in the brackets. Statistical significance at the 10%, 5% and 1% levels is indicated in bold face and by *, ** and ***, respectively.

the variable FCF in Model (7) allows to keep the effect of CSR on OVER significant, but at lower level than it is the case in Model (5) (␣ = −0.0013, p < 10%). Collectively, according to Baron and Kenny (1986), these results meet the requirements of identifying a partial mediation. Therefore, our hypothesis (H3) that reducing agency costs has a mediating effect on the relationship between CSR performance and overinvestment is supported. That is, the negative effect of CSR performance on overinvestment problems follows the path through reducing free cash flow. 4.3. Robustness checks In this section, we examine whether our primary results are robust to addressing endogeneity issues, applying alternative measures, and modifying the sample composition. 4.3.1. Endogeneity issues One important concern in our analysis is potential endogeneity bias stemming from reverse causality. To address the issue of potential endogeneity, we perform an instrumental variable (IV) estimation procedure. Following Attig et al. (2013) and Benlemlih and Bitar (2016), we use two instruments to extract the exogenous component of CSR. The first instrument is CSR IND, the industry-year average of CSR. The second instrument is CSR INI, the firm-level initial value of CSR. In the first stage, we regress the CSR on the two instruments and all control variables. Results are reported in Table 6, Model (1). In the second stage, we regress the investment inefficiency on the predicted value of CSR and all control variables. We employ twostage least-squares (2SLS), limited information maximum likelihood (LIML), and generalized method of moments (GMM) estimations, respectively, in Models (2), (3), and (4). The first-stage regression results show that the coefficients on the two instruments (CSR INI and CSR IND) load positively and are statistically significant. Importantly, the second-stage regressions results show that the effect of CSR on investment inefficiency remains significantly negative, indicating that endogeneity does not drive our main results. 4.3.2. Alternative measure of CSR In Table 7, we use an alternative proxy for CSR performance. Following El Ghoul et al. (2106), the variable CSR is only the equally weighted average of the environmental and the social scores. From Model (1), we can notice that our main finding that firms with high CSR performance invest more efficiently is robust to the choice of CSR proxy. In particular, Models (1a) and (1b) show the effect of two components of CSR individually. Model (1c) shows the effect of two components simultaneously. The results reveal that the environmental dimension matters more to investment efficiency. 4.3.3. Alternative measure of investment inefficiency We re-estimate the expected level of investment following the model developed by Biddle et al. (2009). Investmenti,t = ␤0 + ␤1 SalesGrowthi,t−1 + ␧i,t


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Table 6 Corporate social responsibility and investment inefficiency: addressing endogeneity. First stage

Second stage

(1)

2 SLS (2)

LIML (3)

GMM (4)

0.1051*** (3.93) −0.0005*** (−3.99)

0.1051*** (3.93) −0.0005*** (−3.99)

0.1054*** (6.10) −0.0005*** (−3.55)


0.3351*** (20.92) 0.7524*** (66.40) 0.0085 (0.72) 0.3167** (2.27) Yes Yes Yes

0.0004* (1.71) −0.0062*** (−2.70) Yes Yes Yes

0.0004* (1.71) −0.0062*** (−2.70) Yes Yes Yes

0.0004 (1.51) −0.0060** (−2.50) Yes Yes Yes


2382 0.7450

2382 0.0629

2382 0.0629

2382 0.0627

Constant

−8.8163*** (−4.97)

CSR CSR IND CSR INI INS AGE

The table reports the results of instrumental variable (IV) regressions. We employ two instruments for CSR: (1) the industry-year average of CSR (CSR IND), and (2) the firm-level initial value of CSR (CSR INI). Model (1) presents the first stage regression. The dependent variable is CSR. Models (2)–(4) shows the results from the second stage regressions (2SLS, LIML, GMM). The dependent variable is investment inefficiency. CSR is the annual corporate social responsibility performance. INS is institutional ownership. AGE is firm age. T-statistic values are in the brackets. Statistical significance at the 10%, 5% and 1% levels is indicated in bold face and by *, ** and ***, respectively. Table 7 Corporate social responsibility and investment inefficiency: alternative measure of CSR. INEFF V

Constant CSR

Model 1

Model 1a

Model 1b

Model 1c

0.0760*** (8.02) −0.0002*** (−3.30)

0.0781*** (8.24)

0.0717*** (7.60)

0.1229 (16.00)

−0.0002*** (−3.28)


0.0003*** (2.83) −0.0046*** (−3.62) Yes Yes Yes

0.0003*** (2.79) −0.0045*** (−3.57) Yes Yes Yes

0.0003*** (2.82) −0.0047*** (−3.71) Yes Yes Yes

−0.0002*** (−3.13) −0.0001* (−1.91) 0.0003** (2.05) −0.0047*** (−3.77) Yes Yes Yes


2382 0.0675

2382 0.0665

2382 0.0660

2382 0.0675

Environmental Social INS AGE

−0.0001*** (−2.97)

The dependent variable is investment inefficiency. Models (1a) and (1b) show the effect of two components of CSR individually. Model (1c) shows the effect of two components simultaneously. CSR is the annual corporate social responsibility performance. Environmental is the annual environmental performance of a corporation. Social is the annual social performance of a corporation. INS is institutional ownership. AGE is firm age. All the estimates have been carried out using cross-sectional time-series FGLS regression. T-statistic values are in the brackets. Statistical significance at the 10%, 5% and 1% levels is indicated in bold face and by *, ** and ***, respectively.

Where Investmenti,t is the total investment of firm i in year t, defined as the net increase in tangible and intangible assets and scaled by lagged total assets. Sales growthit-1 is the percentage of change in sales of firm i from year t − 2 to year t. Our results reported in Table 8 remain unchanged. 4.3.4. Sample composition Our sample consists of European companies listed in STOXX Europe 600 index. Three countries seem to dominate the sample. Approximately 50 percent of the sample originates from United Kingdom, France and Germany. In another supplementary test, we repeat the analysis after excluding observations from these countries. The results are similar to those previously reported, as displayed in Table 9.

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Table 8 Sensitivity analyses related to the investment model (Biddle et al., 2009). Investment inefficiency

underinvestment scenario

INEFF V Model 1

UNDER Model 2

SPREAD Model 3

0.0739*** −8.4 −0.0001** (−2.25)

−0.0761*** (−9.55) 0.0001*** −8.9

0.4226*** −17.27 −0.0027*** (−24.22)


0.0003*** −2.97 −0.0049*** (−3.88) Yes Yes Yes

5.12E-05 −0.41 0.0035*** −2.92 Yes Yes Yes

-1.05E-05 (−0.01) 0.0030** −2.07 Yes Yes Yes


2382 0.0627

1487 0.1350

1487 0.2314

Constant CSR SPREAD FCF INS AGE

overinvestment scenario UNDER Model 4

OVER Model 5

FCF Model 6

OVER Model 7

0.0719*** −3.97 −0.0008*** (−6.70)

0.0747*** −4.27 −0.0002*** (−8.11)

0.0756*** −4.57 -5.39E-05 (−1.25) 0.2493*** −4.53

-1.17E-05 (−0.09) 0.0041*** −3.6 Yes Yes Yes

0.0008*** −2.98 −0.0040** (−1.96) Yes Yes Yes

0.0003*** −5.28 −0.0032*** (−5.71) Yes Yes Yes

0.0009*** −3.25 −0.0050** (−2.59) Yes Yes Yes

1487 0.1360

895 0.0917

895 0.1527

895 0.0927

−0.0001 (−1.48) −0.0079*** (−3.27)

Model (1): The dependent variable is investment inefficiency. Models (2) and (4): The dependent variable is underinvestment. Model (3): The dependent variable is the bid-ask spread. Models (5) and (7): The dependent variable is overinvestment. Model (6): The dependent variable is the Free Cash Flow. CSR is the annual corporate social responsibility performance. SPREAD is the bid-ask spread. FCF is the free cash flow. INS is institutional ownership. AGE is firm age. All the estimates have been carried out using cross-sectional time-series FGLS regression. T-statistic values are in the brackets. Statistical significance at the 10%, 5% and 1% levels is indicated in bold face and by *, ** and ***, respectively.

Table 9 Sensitivity analyses related to the sample (Without three countries).

Constant CSR

Investment inefficiency

Underinvestment scenario

INEFF V Model 1

UNDER Model 2

SPREAD Model 3

UNDER Model 4

OVER Model 5

FCF Model 6

OVER Model 7

0.0887*** −6.71 −0.0002** (−2.12)

−0.0856*** (−8.30) 0.0001*** −7.06

0.3982*** −13.97 −0.0022*** (−10.00)

−0.0851*** (−8.22) -3.15E-05 (−0.29) 0.0069** −2

0.0563** −2.13 −0.0007*** (−3.85)

0.0169 −0.76 −0.0001*** −3.81

0.0516* −1.91 −0.0003* (−1.94)

SPREAD

Overinvestment scenario

FCF INS

Yes Yes Yes

−0.0005 (−1.04) −0.0008 (−0.26) Yes Yes Yes

-5.32E-06 (−0.03) 0.0045** −2.24 Yes Yes Yes

0.0003 −0.63 −0.0078** (−2.10) Yes Yes Yes

0.0007*** −7.47 −0.0013* (−1.84) Yes Yes Yes

0.2619*** −2.62 0.0002 −0.14 −0.0083 (−0.92) Yes Yes Yes

636 0.1274

636 0.2573

636 0.1287

366 0.1029

366 0.3200

366 0.1032

6.74E-06 −0.04 0.0047**


2.58E-05 −0.09 −0.0056** (−2.51) Yes Yes Yes


1002 0.0665

AGE

Model (1): The dependent variable is investment inefficiency. Models (2) and (4): The dependent variable is underinvestment. Model (3): The dependent variable is the bid-ask spread. Models (5) and (7): The dependent variable is overinvestment. Model (6): The dependent variable is the Free Cash Flow. CSR is the annual corporate social responsibility performance. SPREAD is the bid-ask spread. FCF is the free cash flow. INS is institutional ownership. AGE is firm age. All the estimates have been carried out using cross-sectional time-series FGLS regression. T-statistic values are in the brackets. Statistical significance at the 10%, 5% and 1% levels is indicated in bold face and by *, ** and ***, respectively.

5. Conclusion Does the development of CSR strategies affect investment decisions and if so, how? This is the main question of this study. We use a representative sample of European listed firms for the period 2009–2014. In the beginning, we investigate the direct effect of CSR performance on investment inefficiency. Then, we investigate in what ways CSR performance affects investment inefficiency. Therefore, we divide our sample into underinvestment scenario and overinvestment scenario. In firms that underinvest, we test the mediating role of information asymmetry in the relationship between CSR performance and underinvestment. In firms that overinvest, we test the mediating role of agency problems of free cash flow in the relationship between CSR performance and overinvestment.


45

The results indicate that firms with higher CSR performance invest more efficiently. Consistent with our expectation, socially responsible firms are typically characterized by reduced investment-cash flow sensitivity, lower capital constraints, better access to finance, and high management quality, which contributes to alleviate the inefficiency of investment. Consequently, the development of CSR strategies would improve firms ‘sustainability and competitive position (Legnick-Hall, 1996; Whitehouse, 2006). The key premise of this study is that CSR performance not only directly affects firms’ investment policy but also affects firms’ investment policy via its complementary effect on market imperfection, as well as agency conflicts and information asymmetry. In particular, we can assert that there are two important channels through which CSR performance ameliorates firm-level investment efficiency. First, CSR performance limits the amount of free cash flow available, which can be used by self-interested mangers to undertake unprofitable projects. The monitoring role of CSR may avoid firms from overinvestment. Second, CSR performance makes information environment more transparent, thereby reducing the asymmetrical distribution of information among various stakeholders. This improved information environment contributes to increasing investment level and hence avoiding firms from underinvestment. Overall, CSR performance participates in decreasing investment inefficiency in both scenarios through helping firms address agency problems and information asymmetry problems. Our empirical results are consistent with the argument of Benlemlih and Bitar (2016). Some practical managerial implications can be derived from the results of this study. The positive association between CSR performance and investment efficiency suggests to organizations that the adoption of CSR strategies is an effective way to foster firm growth and protect the interest of different stakeholders. Therefore, companies have to integrate social and environmental concerns in their business, such as employment quality, health and safety, human right, natural resource reduction and pollution reduction, which may represent a source of competitive advantage.

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