The Effect of R&D Intensity on Relationship between ... · The Effect of R&D Intensity on...

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The Effect of R&D Intensity on Relationship between Corporate

Social Responsibility and Real Earnings Management: Evidence

from U.S. Firms

Amy Yueh-Fang Ho*

Department of Finance, National Chung Cheng University

[email protected]

Phone: +886-5-272-0411 ext. 34212; Fax: +886-45-272-0818

Gary A. Patterson

Kate Tiedemann College of Business, University of South Florida St. Petersburg

[email protected]

Phone: 727-873-4005; Fax: 727-873-4571

Yu-Wen Kao

Department of Finance, Providence University

[email protected]

Phone: +886-4-2632-8001; Fax: +886-4-2631-1222

May 2018

* Corresponding Author. Department of Finance, National Chung Cheng University, No.168, Sec. 1, University

Rd., Min-Hsiung Township, Chia-yi County 621, Taiwan; Phone: +886-5-272-0411 ext. 34212;

Fax: +886-45-272-0818; E-mail: [email protected]

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The Effect of R&D Intensity on Relationship between Corporate

Social Responsibility and Real Earnings Management: Evidence

from U.S. Firms

AbstractPrior studies indicate that R&D intensity and corporate social responsibility (CSR) have

a positive relationship, meaning that firms investing more in R&D can promote more CSR

related activities and develop more innovative products. However, R&D investment is also a

tool for firms to smooth their earnings, or firms may enhance their earnings by reducing R&D

expenses. Prior literature suggests a negative relationship between CSR and earnings

management. Firms involved in more CSR activities are relatively ethical and less likely to

manipulate earnings. Sustainable innovation and development play an important role for firms

to establish competitive advantages. The main purpose of this paper is not only to discuss the

relationship between CSR and real earnings management (RM) activities in U.S. firms from

2000 to 2014, but also to examine whether R&D intensity and the global financial crisis of

2007 – 2008 will affect the relation between CSR and earnings management.

To avoid the endogeneity issue, we adopt a Two-Stage Regression to test the relationship

between CSR and earnings management, and incorporate the effects of R&D intensity and the

financial crisis. We find that the relation between CSR and earnings management is negative

for the entire sample and for those firms with high R&D intensity or after the financial crisis.

Those firms with high R&D intensity are more likely to participate in CSR activities and less

likely to manipulate earnings. Nevertheless, our results show that the negative relation

between CSR and earnings management does not exist in low R&D intensive firms. In

addition, our results show that high R&D intensive firms with larger size, higher leverage, or

lower profitability are more likely to engage in earnings management activities.

Keywords: R&D intensity, Corporate social responsibility, Real earnings management,

Financial crisis

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1. Introduction

Corporate social responsibility (CSR) is increasingly important to firms on multiple

perspectives. In the European Union (EU), CSR activities strengthen the goals of the Europe

2020 growth strategy for sustainable development and a highly competitive social market

economy.1 In addition, a greater number of US firms have engaged in CSR reporting to

inform various stakeholders. According to Global Reporting Initiative database, the number of

US firms that published CSR reporting has increased from 70 firms in 2007 to more than 540

firms in 2012.2 Proponents of CSR believe such activities can benefit firms in the areas of

risk management, cost savings, access to capital, customer relationships, human resource

management, and innovation capacity.

While investors are focusing more attention on CSR issues gradually, ethics continues to

play a crucial role in the communication process between firms and stakeholders. When the

corporation pursues profit maximization, they should focus not only on internal stakeholders

but also on other stakeholders. In other words, the corporation is responsible for community,

corporate governance, diversity, employee relations, environment, human rights, and products.

Therefore, CSR is an important component of firm reputation and success.

Nearly half of U.S. chief financial officers think that CSR and sustainability are

important items in their business strategies. A recent survey of financial officers identified

three reasons for engaging in CSR including: improving external image and brand; improving

employee morale and hiring; and complying with legal or regulatory requirements.3 In the

1 Refer to the article entitled “New EU Communication on CSR: A Renewed EU Strategy 2011-2014 forCorporate Social Responsibility” at http://www.csreurope.org/csr-and-sustainability-machine-tools-sector.2 Refer to the article entitled “Top 4 Reasons U.S. Companies Report CSR”, written by Francis Quinn, andpublished on November 15, 2013 at https://www.workiva.com/blog/top-4-reasons-us-companies-report-csr.3 Refer to the article entitled “CFO Magazine Global Business Outlook Survey” and published at DukeUniversity in 2013.

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UK, CSR is seen as the business contribution to sustainable development goals.4 In addition,

sustainable development is an important issue in corporate operations. Therefore, CSR

becomes an important part of the corporate reputation and competitiveness.

Research suggests that CSR activities have positive effects on operating, financial

performance, firm valuation, and financing cost (Dhaliwal et al., 2011; El Ghoul et al., 2011;

Deng et al., 2013; Xiao et al., 2013; Cheng et al., 2014). Since the CSR could increase

transparency, it may reduce information asymmetry, attract financing from socially conscious

investors to expand the investor base, and effectively decrease external financing.

Furthermore, the mass media also emphasizes the significance of CSR. For instance, The

Economist praises the concept that corporations adopt CSR as a key strategic instrument,5

while the Financial Times identifies CSR as a risk management tool.6 CSR appears to be a

business practice used to achieve a balance between economic, social, and environmental, and

satisfy the expectations of shareholders and stakeholders at the same time. Overall, corporate

reputation is significant in today's world more than ever and an emphasis on CSR could be

profitable for firms in the long run.

In contrast with CSR which can raise the financial reporting transparency, earnings

management (EM) is a tool used for managing earnings through the choice of accounting

methods. Stockholders examine the financial statements of a company to assess the amount,

timing, and uncertainty of future cash flows. They invest in the firms based on their

4 Refer to the book entitled “Developing Corporate Social Responsibility: A European Perspective”, written byFrancesco Perrini, and published by Edward Elgar Publishing.5 Refer to the article entitled “Corporate Social Responsibility Can Be Profitable”, written by RubénHernández-Murillo and Christopher J. Martinek, and published on April 2009 athttps://www.stlouisfed.org/publications/regional-economist/april-2009/corporate-social-responsibility-can-be-profitable.6 Refer to the article entitled “Corporate social responsibility and global workforce dynamics” and published byThe Economist on June 2015 athttp://futurehrtrends.eiu.com/report-2015/corporate-social-responsibility-and-global-workforce-dynamics/.

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evaluation. Hence, the quality of the earnings reported plays an important role in the

communication process between firms and stockholders. A poor-quality financial reporting

may mislead the external stockholders who use the financial information to make investment

decisions. Research highlights two common methods of earnings management that firms use

with the intent to influence the quality of earnings. One method uses accrual-based earnings

management (AM) activities while the other approach uses real earnings management (RM)

activities. Prior literature provides a survey on earnings management (Healy and Wahlen,

1999; Kothari, 2001). Healy and Wahlen (1999) find that firms conduct AM by modifying the

level of accruals in order to meet their earnings goals. Roychowdhury (2006) indicates that

firms engage in RM activities to manipulate earnings that deviate from normal business

operations and modify future cash flows. The primary difference between the AM and RM

methods is that RM generates direct cash flow consequences since future cash flows may be

impacted by RM actions taken to manipulate current earnings.

According to prior research, there are at least two reasons for financial executives willing

to conduct RM rather than AM (Bruns and Merchant, 1990; Graham et al., 2005; Cohen et al.,

2008; Cohen and Zarowin, 2010). First, AM is easier to attract auditor or regulatory scrutiny

than real manipulation associated with product pricing, production cost, and expenditures on

research and development (R&D) or advertising. Second, it is risky for firms simply to rely

on accrual manipulation. Furthermore, Zang (2012) finds that RM and AM are negatively

correlated. Cohen et al. (2008) suggest that AM and RM are substitute methods, implying that

AM decreases while RM increases and vice versa. Graham et al (2005) and Cohen et al. (2008)

find that after the passage of Sarbanes-Oxley Act (SOX) enacted in 2002 the firms tend to

shift away from AM to RM. Besides, RM is harder to detect than AM (Graham et al., 2005).

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As a result, our study emphasizes the relationship between CSR and RM.

Prior research has documented that earnings management is associated with CSR

activities. There are two possible relationships between CSR and AM. Some literature

suggests a negative relationship between CSR and earnings management (Chih et al., 2008;

Labelle et al., 2010; Hong and Andersen, 2011) since firms associated with more involvement

of CSR activities are perceived to be relatively ethical and less likely to manage their earnings.

Nevertheless, the others studies suggest a positive relationship CSR and earnings

management (Jiang et al. 2013; Grougiou et al., 2014) since CSR practices could be used as a

strategy to mask RM activities.

Many studies on earnings management have focused on a range of internal and external

factors observed in firms. For instance, Teoh et al. (1998) explore the impact of earnings

manipulation on long-term market performance for firms issuing initial public offerings.

Jiraporn et al. (2008) examine whether corporate diversification aggravates or mitigates

earnings manipulation. Siregar and Utama (2008) explore the effect of a firm’s size, corporate

governance, and ownership structure on different types of earnings management.

Since firms operate in a business environment that is often turbulent, it is more difficult

for firms to rely on their own abilities to keep the competitive advantage in the market. Many

firms agree that CSR and innovation are important positions that may increase their

competitive advantage (McWilliams and Siegel, 2000; Porter and Kramer, 2006). Firms face a

fiercely competitive market so they will need to pursue advances in technology and

innovation through R&D to enhance their ability, withstand competitors’ imitating of

strategies, and maintain their competitive advantage (Du Plessis, 2007; Lai et al., 2015). On

the other hand, firms may increase earnings through manipulating earnings in order to attract

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investors’ attention or misinform investors. It is also a common maneuver for firms to impact

earnings by manipulating R&D expenses. Therefore, we discuss the relation among CSR, RM,

and R&D in this study.

In order to maintain the target of sustainable development, firms need to invest in R&D

continuously and participate in CSR activities to advance in their position of competitive

advantage and innovation. However, R&D expense can easily become a tool that firms use

when hoping to meet short term earnings goals, especially since the future benefits of R&D is

uncertain. Such manipulation of R&D expense may cause damage to sustainable development.

Hence, the purpose of this study is to explore whether R&D intensity impacts the relation

between CSR and RM. Our study is the first to investigate the effect of R&D intensity on the

association between CSR and earnings management in U.S. firms. Our findings would assist

investors when selecting stocks with a focus on R&D intensity associated with CSR and RM

activities.

The rest of this paper is organized as follows. In Section 2, we discuss the literature

review and hypothesis development. In Section 3, we present our sample selection and

explain the definition of key variables and the testable models. Next, we discuss our empirical

findings and results in Section 4. Finally, we provide the conclusion of this paper in Section 5.

2. Literature Review

2.1 Corporate Social Responsibility (CSR)

CSR measures strengths of a firm in several areas such as the community, corporate

governance, diversity, product, employee relations, environment, and human rights. CSR

activities have been considered a powerful public relation tool for firms to strengthen

mutually beneficial relationships with stakeholders (Kim and Choi, 2012). Porter and Kramer

(2006) identify that there are four popular reasons for firms to engage in socially responsible

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actions. First, firms may decide they have an ethical responsibility to participate in actions for

the benefit of all stakeholders that reduces the immediate profit consideration of such actions.

Second, the concept of sustainability emphasizes the need for the firm’s responsibility for the

environment and the community. Third, the social license to operate is relevant to the CSR

strategy, hence governments, communities, and other stakeholders will give firms silent or

clear permission to do their business. Finally, successful implementation of a CSR strategy

can improve the reputation of a firm.

Prior literature suggests that CSR has two external benefits in corporate goodwill and

image (Orlitzky et al., 2003; McWilliams et al., 2006; Branco and Rodrigues, 2006). Park et

al. (2014) find that CSR activities improve goodwill and build up consumer trust in

corporations. These findings imply that via consumer opinion, CSR creates important

intangible resources for the corporation. Corporate goodwill and image offer a sustainable

competitive advantage to firms (Branco and Rodrigues, 2006) and a positive effect on their

financial performance (Fombrun and Shanley, 1990; Roberts and Dowling, 2002).

2.2 Real Earnings Management (RM)

Roychowdhury (2006) shows that firms conduct RM to manipulate reported earnings

which deviate from normal business practices to meet certain earnings goals. Cohen and

Zarowin (2010) demonstrate that managers might increase sales revenue through increasing

price discounts, reduce cost of sales by increasing final inventories, and increase earnings

through reducing discretionary expenses. Hong and Andersen (2011) suggest that managers

may inflate earnings through EM to meet their performance goals in order to increase their

compensation. Cohen et al. (2008) find that firms altered their earnings manipulation from

AM to RM after the SOX legislation passed in 2002, despite AM considered harder to detect

than EM while RM is more costly for firms to implement.

Real activities manipulation may reduce overall firm value because the activities taken in

the current period to increase earnings could negatively impact future cash flows. For

example, a price discount implemented to increase sales and satisfy some short-term earnings

goals may lead customers to expect such discounts in the future. This pricing environment

infers that sales in the future may have lower profit margins.

Previous studies suggest that managers engage in a series of commonly observed RM

activities such as: 1) offering discounts for a limited time to increase sales at the end of the

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year; 2) building up excess inventories to lower reported cost of sales; and 3) decreasing R&D

expenditures (Baber et al., 1991; Dechow and Sloan, 1991; Bushee, 1998; Dernirag, 1998;

Grinyer and Collison, 1998; Roychowdhury, 2006; Gunny, 2010; Seybert, 2010; Tahinakis,

2014). The survey reported in Graham et al. (2005) finds that 80% of survey participants

would take real earnings manipulation, such as decreasing discretionary expenses on R&D,

advertising, and maintenance, and more than half of survey participants would delay a new

project to meet their earnings goals. Graham et al. (2005) indicate that many respondents tend

to reduce discretionary expenditures or capital investments rather than engage in other

manipulation methods.

2.3 Relation between CSR and RM

Prior research often suggests that firms that engage in greater CSR practices are less likely

to engage in real earnings management activities. Labelle et al. (2010) point out that ethics

plays a role in controlling earnings management. The firms with a higher level of ethics are

associated with a higher quality of financial reporting. Chih et al. (2008) find that firms with a

higher level of social responsibility engagement are less likely to manipulate earnings. Hong

and Andersen (2011) find that firms with more social responsibility have higher financial

reporting quality and less earnings management activities.

However, some prior research finds that EM is positively associated with CSR (Jiang et al.

2013; Grougiou et al., 2014). Grougiou et al. (2014) find that the managers involved in

earnings management activities also tend to engage in CSR activities. Jiang et al. (2013) find

that CSR acts as a window-dressing for non-state owned firms in China to engage in earnings

management.7 Managers use CSR activity as a powerful tool for self-defense when they do

things to injure the benefits of shareholders or other stakeholders. With this strategy, the

manager will decrease the possibility of getting stress from dissatisfied shareholders or other

stakeholders whose benefits are harmed by the exercise of earnings management.

Kim et al. (2012) provide two possible, but inconsistent explanations for the relationship

between CSR performance and EM. They offer one explanation based on “Transparent

Financial Reporting Hypothesis” which proposes that higher CSR performance would

decrease managers’ motives to manipulate earnings. Their second explanation, based on

7 According to this article, the CSR is mandatory reporting requirement in China. Sets of states (SOEs) ownedare more closely monitored so that it does not exhibit the same results between CSR performance and EM withnon-sets of states (NSOEs).

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“Opportunistic Financial Reporting Hypothesis”, supports a positive relationship between

CSR and EM. The managers may take advantage of other stakeholders’ benefit to manipulate

earnings. Kim et al. (2012) report that U.S. firms voluntarily report CSR activities according

to the transparent financial reporting hypothesis that CSR positively signals to external

stakeholders that the manager is honest.

2.4 R&D Intensity

The investment community often considers R&D as an important driver for corporate

innovation that can create the economic rents favorable for economic development. R&D

intensity measures the ratio of expenditures by a firm on its research and development to its

sales, and prior research suggests that R&D intensity is positively related to the market value

of firms (Hirschey, 1982; Cockburn and Griliches 1988; Hall, 1993). These findings suggest

that more highly R&D intensive firms that are often more innovative would also expect to be

more profitable in the future.

2.5 R&D Intensity and CSR

Prior research seems to agree increasingly that CSR and R&D are complementary

(McWilliams and Siegel, 2000; Branco and Rodrigues, 2006; Padgett and Galan, 2010;

Padgett and Moura-Leite, 2012) while they both have positive impacts on the firm’s

reputation (Chun, 2006). Innovation creates intangible capital through R&D investment and

CSR performance obtains intangible capital by enhancing firms' reputations (Branco and

Rodrigues, 2006; McWilliams et al., 2006). Chun (2006) shows that in order to innovate and

have a good reputation, firms need to be socially responsible. Thus, CSR and R&D could

provide firms with competitive advantage.

McWilliams and Siegel (2001) and Padgett and Galan (2010) suggest that firms with

higher R&D expenditure would invest more in CSR activities since they tend to be involved

in CSR activities through product innovations. Padgett and Moura-Leite (2012) find that

R&D activities which create social benefits obtain a greater positive effect on corporate

reputation than R&D by itself. Although R&D investment can create innovation, it is unable

to produce any social benefit and is more difficult for external stakeholders to perceive.

Research indicates that R&D with low social benefits has a lower effect on firms’ reputations

than R&D with high social benefits. Thus, firms engaged in related CSR activities in R&D

may derive a competitive and profitable advantage over an extended period of time.

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2.6 R&D Intensity and RM

Research has documented that R&D expenditure may lead to a firms’ growth and

competitive advantage, but managers may also cut R&D expenditure to promote short-term

earnings performance. Bushee (1998) finds that some managers manipulate R&D investment

to meet short-term earnings target; thus these managers negatively impact investors through

their shortsighted investment action in R&D. Roychowdhury (2006) finds that firms could

increase earnings through decreasing discretionary expenditures on R&D, advertisement, and

repair. Osma (2008) also explains that cutting R&D expenditure reduces short-term earnings

pressure. Dechow and Sloan (1991) observe that managers often reduce R&D expense near

the end of their tenure to increase short-term earnings.

R&D expenses are considered to be highly discretionary expenditures and may be used to

manipulate earnings. Nagy and Neal (2001) find evidence that some managers of U.S. and

Japanese firms adjust discretionary accruals and R&D spending to smooth their income.

Mande et al. (2000) show evidence where Japanese firms across several industries would

adjust R&D budgets to smooth earnings. Lev and Sougiannis (1996) and Ettlie (1998)

demonstrate that Japanese firms manipulate real earnings by increasing or decreasing R&D

expenditure or changing R&D project to meet the short-term earnings goals. Bereskin et al.

(2017) find that R&D reductions associated with earnings management result in fewer patents

and lower innovative performance. Thus strong evidence exists that managers frequently

adjust R&D expenses in an attempt to achieve short-term earnings goals.

3. Hypothesis Development

In this paper, we first discuss the relationship of CSR and RM activities engaged in the

U.S. However, prior research does not present consistent views on the relationship between

CSR and EM. In general, firms with higher CSR are perceived as more ethical, so they are

less likely to manipulate earnings base on “Transparent Financial Reporting Hypothesis”. In

this environment, firms engage more in CSR with a sense of ethical responsibility, they would

make ethically responsible business decisions and would less likely manage earnings, and

their financial reporting would generally be more transparent. Chih et al. (2008) find that the

relation between CSR and EM depends on differentiating the type of EM the firms practice

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and suggest the CSR firms tend to engage in less RM activities. Hong and Andersen (2011)

show that the more socially responsible firms have a higher level of ethics, a higher quality of

financial reporting, and less earnings manipulation. Therefore, we construct our first

hypothesis as follows:

H1: Firms with higher CSR tend to engage less in RM activities. Thus, there is a negative

relationship between CSR and RM.

Research consistently shows that CSR has a positive correlation with R&D intensity

because they are complementary, as observed by McWilliams and Siegel (2001), Branco and

Rodrigues (2006), Padgett and Galan (2010), and Padgett and Moura-Leite (2012). According

to the resource-based view (RBV) theory, firms with valuable and rare assets are difficult to

be replaced and have a competitive advantage. CSR and R&D are intangible resources, and

both of them can improve a firm’s competitive advantage if used effectively. Padgett and

Galan (2010) report that the relationship between R&D intensity and CSR is significantly

positive in manufacturing firms. Padgett and Moura-Leite (2012) find that firms participate in

related CSR activities supported by R&D investment that could provide a competitive and

profitable advantage in the long-term. Importantly, R&D investment with social benefits is

easier for external stakeholders to perceive, so such outputs can create greater positive effects

than the R&D itself.

However, firms have a motive to meet earnings goals by adjusting R&D spending

(Roychowdhury, 2006). The R&D investment expenditure is often used as an earnings

manipulation tool to conduct real earnings management. In order to achieve short-term

earnings objective, firms would reduce R&D expenditure (Dechow and Sloan, 1991; Bushee,

1998). This maneuver helps the managers mask the true performance of a firm. Dechow and

Sloan (1991) observe that managers tend to decrease R&D expense on purpose to increase

earnings near the end of their tenure. Nagy and Neal (2001) show that the firms usually adjust

the discretionary expenditures on R&D, adverting, and SG&A expenses to smooth earnings in

the U.S.

Since R&D has a positive (negative) relationship with CSR (RM), we expect that firms

with lower R&D intensity would participate in fewer CSR activities, and then firms with

lower CSR would engage in more RM activities. Therefore, we institute our second, third, and

fourth hypotheses as follows:

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H2: The relationship between R&D and CSR intensity is positive.

H3: The relationship between R&D and RM is negative.

H4: The negative relationship between CSR and RM may differ for those firms with high and

low R&D intensity.

We also discuss the relationship between CSR and RM within the broader context of the

financial crisis. After the financial crisis, firms would be more conservative and focus on

enhancing their earnings. Additionally, actions taken by firms would be more conservative

and defensive during the financial crisis, as noted by Cheney and McMillan (1990). Research

by Bansal et al. (2015) suggests that firms will cancel CSR activities during a financial crisis

since resources are scarce and there is greater economic uncertainty. Furthermore, firms may

not have enough capital to participate in both CSR and essential activities. Therefore, firms

might prefer not to engage in CSR activities during periods of great economic turmoil.

Therefore, we establish our fifth hypothesis as follows:

H5: The relationship between CSR and RM may differ before and after a financial crisis.

4. Methodology and Data

4.1 Measurements

4.1.1 Measuring Real Earnings Management (RM)

Following Dechow et al. (1998), Roychowdhury (2006), Cohen et al. (2008) and Cohen

and Zarowin (2010), we adopt three metrics to measure the level of RM: 1) the abnormal

levels of cash flow from operations (CFO); production costs (PROD); and discretionary

expenses (DISX).

Roychowdhury (2006) observes that firms manipulate earnings or avoid reporting losses

in three ways. First, firms accelerate the timing of sales through improved price discounts and

more lenient credit conditions. While price discounts and lenient credit conditions may

improve sale provisionally, the sales increase would probably disappear when the firms revert

to their regular pricing. Yet, the extra sales would enhance current earnings, presuming that

operating margins are positive. Nevertheless, price discounts and lenient credit conditions will

lead to lower cash flows from operations in the current period. Second, firms report lower

cost of goods sold through boosting production. Firms can disperse the fixed overhead cost of

goods sold to large amount of units when they produce more units. While the increase in

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marginal cost per unit does not offset to reduction in fixed costs per unit, total cost per unit

decreases. Although firms could boost their operating margins by decreasing cost of goods

sold, it will result in higher annual production cost relative to sales and lower cash flows from

operations. Third, firms that decrease DISX including the expenses in advertising, R&D, and

SG&A will not only boost earnings and increase operating profit margins but also increase

current cash flows at the risk of decreasing future cash flows if firms paid these expenses

mostly in cash.

We use cross-sectional regressions for each industry and year to estimate the normal

levels of CFO, PROD, and DISX by first creating the matching sample based on two-digit

SIC code and year.8 Equation (1) estimates the normal level of CFO in the period t for our

sample.

CFOAssets ,

= β1

Assets ,+ β

SalesAssets ,

+ βΔSales

Assets ,+ ε (1)

where is the cash flows from operations of firm i in period t; , is total

assets of firm i in period t-1; reflects net sales of firm i in period t; and Δ is

the change in net sales of firm i in period t.

The abnormal CFO (ab_CFO) is computed as actual CFO minus normal CFO.

PROD represents the sum of the costs of goods sold (COGS) and change in inventory

(ΔINV) in period t. From Equations (2) and (3), we estimate COGS which is a linear function

of contemporaneous sales and ΔINV which is a linear function of contemporaneous and

lagged change in sales.

COGSAssets ,

= β1

Assets ,+ β

SalesAssets ,

+ ε (2)

ΔINVAssets ,

= β1

Assets ,+ β

ΔSalesAssets ,

+ βΔSales ,

Assets ,+ ε (3)

where is the costs of goods sold of firm i in period t; Δ is the change in

inventory of firm i in period t; Δ , is the change in net sales of firm i in period t-1.

We use Equation (4) to estimate the normal level of PROD based on Equations (2) and

(3).

8 Total assets of matching firms are more than one million U.S. dollars. Each sample has to include at least eightmatched firms.

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PRODAssets ,

= β1

Assets ,+ β

SalesAssets ,

+ βΔSales

Assets ,+ β

ΔSales ,

Assets ,+ ε (4)

The abnormal PROD (ab_PROD) is actual PROD minus normal PROD which is

calculated from Equation (4).

Equation (5) estimates the normal level of DISX.

DISXAssets ,

= β1

Assets ,+ β

Sales ,

Assets ,+ ε (5)

where DISX is the discretionary expenditure defined as the sum of the expenses in advertising,

R&D, and SG&A of firm i in period t.

The abnormal DISX (hereafter ab_DISX) is actual DISX minus normal DISX which is

calculated from Equation (5).

After estimating Equations (1), (4), and (5), we use ab_CFO, ab_PROD, and ab_DISX

as proxies for real earnings manipulation. Firms are more likely to adopt any of the tools

mentioned above to manage earnings upward by decreasing CFO, increasing PROD, and (or)

decreasing DISX.

In addition to the aggregated measured (RM), we also follow Cohen and Zarowin (2010)

and Zang (2012) using two comprehensive metrics (RM1 and RM2) of real earnings

management activities in order to catch the total influence of RM. In Equation (6), RM is

calculated by ab_PROD minus ab_CFO and ab_DISX.9 In Equation (7), RM1 equals

ab_PROD minus ab_DISX.10 The higher the amount of RM (RM1, RM2), the more likely

the firms will manage earnings upwardly. In Equation (8), RM2 equals negative ab_CFO

minus ab_DISX.

RM = −ab_CFO + ab_PROD− ab_DISX (6)

RM1 = ab_PROD− ab_DISX (7)

RM2 = −ab_CFO − ab_DISX (8)

4.1.2 Measuring Corporate Social Responsibility (CSR)

We follow Hong and Andersen (2011), Grougiou et al. (2014), and Gao and Zhang (2015)

to compute the CSR scores retrieved from the MSCI ESG STATS database11 for each firm by

9 There might be double counting issue when low ab_CFO and high ab_PROD are combined in RM measure.10 Ab_PROD is not multiply by negative one because firms can boost earnings by increasing PROD throughoverproduction to reduce cost of goods sold.11 MSCI ESG STATS database is previously known as KLD database. KLD database was acquired byRiskMetrics Group (RMG) in 2009, and then RMG was acquired by MSCI in 2010.

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summing up total positive scores (strengths) and negative scores (concerns) across seven

issue areas including community, corporate governance, diversity, employee, environment,

product, and human right in each year based on Equations (9)-(15). The positive (negative)

total CSR score indicates that firm has more (less) strengths than concerns in CSR activities.

Appendix 1 provides more detailed information concerning the components of strengths and

concerns for each issue.

CSR_COM = COM + COM + COM + COM + COM + COM + COM

− COM + COM + COM + COM (9)

where _ is the sum of scores for the strengths and concerns of community. The

items of strengths in community area include COM (Charitable Giving), COM is

(Innovative Giving), COM (Support for Housing), COM (Support for Education),

COM (Non-US Charitable Giving), COM (Volunteer Programs), and COM (other

strength). The items of concerns in community area include (Investment

Controversies), (Negative Economic Impact), (Tax Disputes), and

(other concern).

CSR = CGOV + CGOV + CGOV + CGOV + CGOV − CGOV +

CGOV + CGOV + CGOV + CGOV + CGOV +

CGOV (10)

where _ is the sum of scores for the strengths and concerns of corporate

governance issue. The items of strengths in corporate governance area include

(Limited Compensation), (Ownership Strength), (Transparency

Strength), (Political Accountability Strength), and (other strength).

The items of concerns in corporate governance area include (High Compensation),

(Ownership Concern), (Accounting Concern),

(Transparency Concern), (Political Accountability Concern),

(Governance Structures Controversies), and (other concern).

CSR_DIV = DIV + DIV + DIV + DIV + DIV + DIV + DIV +

DIV + DIV − DIV + DIV + DIV + DIV (11)

where _ is the sum of scores for the strengths and concerns of diversity issue. The

17

items of strengths in diversity area include (CEO), (Promotion),

(Board of Directors), (Work/Life Benefits), (Women and Minority

Contracting), (Employment of the Disabled), (Gay and Lesbian Policies),

(Employment of Underrepresented Groups), and (other strength). The

items of concerns in diversity area include (Controversies),

(Non-Representation), (Board Diversity-Gender), and (other

concern).

CSR_EMP = EMP + EMP + EMP + EMP + EMP − EMP +

EMP + EMP + EMP + EMP (12)

where _ is the sum of scores for the strengths and concerns of employee relations

issue. The items of strengths in employee relations area include (Union Relations),

(Cash Profit Sharing), (Employee Involvement), (Health and

Safety Strength), and (other strength). The items of concerns in the employee

relations area include (Union Relations), (Health and Safety concern),

(Workforce Reductions), (Retirement Benefits Concern), and

(other concern).

CSR_ENV = ENV + ENV + ENV + ENV + ENV + ENV + ENV +

ENV + ENV − ENV + ENV + ENV + ENV +

ENV + ENV + ENV + ENV (13)

where _ is the sum of scores for the strengths and concerns of environment issue.

The items of strengths in environment area include (Beneficial Products and

Services), (Pollution Prevention), (Recycling), (Clean Energy),

(Communications), (Management Systems), (Environmental

Opportunities-Green Buildings), (Waste Management-Electronic Waste), and

(other strength). The items of concerns in environment area include

(Hazardous Waste), (Regulatory Problems), (Ozone Depleting

Chemicals), (Substantial Emissions), (Agricultural Chemicals),

(Climate Change), (Impact of Products and Services), and (other

concern).

18

CSR_HUM = HUM + HUM + HUM − HUM + HUM + HUM +

HUM + HUM (14)

where _ is the sum of scores for the strengths and concerns of human right issue.

The items of strengths in human right area include HUM (Indigenous Peoples Relations

Strength), HUM (Labor Rights Strength), and HUM (other strength). The items of

concerns in human right area include HUM (Burma), HUM (Labor Rights Concern),

HUM (Indigenous People Relations Concern), HUM (Human Rights Violations),

and HUM (other concern).

CSR_PRO = (PRO + PRO + PRO + PRO ) − PRO + PRO +

PRO + PRO (15)

where _ is the sum of scores strengths and concerns of product issue. The items of

strengths in product area include (Quality), (R&D or Innovation),

(Benefits to Economically Disadvantaged), and (other strength). The

items of concerns in product area include (Product Safety), (Marketing

or Contracting Concern), (Antitrust), and (other concern).

The sum of scores for seven CSR issue areas is computed as CSR based on Equation

(16).

CSR = CSR_COM + CSR_CGOV + CSR_DIV + CSR_EMP + CSR_ENV + CSR_HUM +

CSR_PRO (16)

4.1.3 Measuring the R&D Intensity

We adopt three proxies to measure the R&D intensity which has a positive relationship

with product innovations and patents (Hitt et al., 1997). First, we follow Gao and Zhang

(2015) and Baysinger et al. (1991) using R&D spending scaled by the lagged sales in

Equation (17), which is also used to measure R&D intensity in prior research (McWilliams

and Siegel, 2000; Bouquet and Deutsche, 2008; Prior et al., 2008; Padgett and Galan, 2010).

Second, we measure R&D intensity based on the expenditures in R&D scaled by the nature

logarithm of total assets in the period t-1 in Equation (18) proposed by Berrone et al. (2007).

Third, we measure R&D intensity based on the expense in R&D dividing by the total number

of employees in Equation (19) according to Padgett and Moura-Leite (2012). Note that the

measurement scaled by the number of employees is less sensitive to business cycles and

19

accounting manipulations than the other two measurements scaled by sales and assets.

RD_INT1 =R&

SALES (17)

RD_INT2 =R&

ln TA (18)

RD_INT3 =R&

NUM_Employees (19)

where RD_INT stands for R&D intensity; R&D is defined as the expense in R&D; and

NUM_Employees indicates the number of the employees.

4.1.4 Control Variables

Following the evidence discussed in the earnings management literature (Chih et al.,

2008; Cohen and Zarowin, 2010; Grougiou et al., 2014), we include the following four

financial variables: firm’s size; capital structure; growth opportunity; and profitability to

control.

First, we use the natural logarithm of total assets (SIZE) to control for firm size since

larger firms are required to disclose the information and have more scrutiny by outsiders.

Therefore, larger firms are less likely to engage in earnings management. Second, to capture

the debt effect on RM, we use the debt ratio (DAT) to measure firm’s financial leverage. Press

and Weintrop (1990) and Sweeney (1994) suggest that firms with higher leverage tend to

manipulate earnings. However, Dechow and Skinner (2000) and Ke (2001) find that firms

with higher leverage tend to engage less earnings management while Chung and Kallapur

(2003) and Chih et al. (2008) find no evidence of significant association between RM and

leverage. Third, we use the market-to-book ratio (MKBKF) to measure the growth

opportunity of firms in the future. Because growth stocks are sensitive to earnings surprises

(Skinner and Sloan, 2002) and the market responds negatively to firms that break the string of

continuous earnings increases (Barth et al., 1999), firms tend to adopt accounting policies to

boost earnings. In addition, we use ROA to capture the effect of profitability since the firms

with higher profitability are less likely to adopt accounting policies to manipulate earnings.

4.2 Regression Models

Prior research suggests that firms which engage in earnings management activities also

tend to engage in CSR activities (Grougiou et al., 2014). Yet these observations may be

capturing endogeneity between CSR and RM (Prior et al., 2008; Labelle et al., 2010). Recent

20

CSR research emphasizes the importance of controlling the endogenous problems (Hillmane

and Keim, 2001; Garcia-Castro et al., 2010; Grougiou et al., 2014). Therefore, we adopt the

Two-Stage Least Square (2SLS) regression. In the first stage of regression, the endogenous

variable CSR is regressed against exogenous variables as instrumental variables (IVs) in

Equation (20). According to Grougiou et al. (2014), we use the firm’s leverage (DAT), growth

opportunities (MKBKF), and profitability (EBIT) as IVs.

CSR = α + α DAT + α MKBKF + α EBIT + ω (20)

where CSR indicates CSR scores; DAT is total debt to the total assets ratio; MKBKF is the

market value of equity to the book value of equity; while EBIT is the earnings before interest

and taxes scaled by total assets for prior year.

IVs need to be uncorrelated with the error term (ω ) but partially or sufficiently

correlated with CSR. After running the regression based on Equation (20), we find the

estimated coefficients for IVs and further estimate CSR in Equation (21).

= α + α DAT + α MKBKF + α EBIT (21)

In the second stage of regression in Equation (22), RM is regressed on the value of

estimated CSR which is derived from the first stage regression in Equations (20) and (21). We

use the natural logarithm of total assets, debt ratio, market to book value, and ROA to control

the size, capital structure, growth opportunity, and profitability of firms, respectively. The

independent variable is CSR and the dependent variable is RM.

RM = β + β CSR + β SIZE + β DAT + β MKBKF + β ROA + ε (22)

where RM is the proxy of the real earnings management; CSR indicates CSR scores; SIZE is

the natural logarithm of total assets; DAT is total debt to the total assets ratio; MKBKF is the

market value of equity to the book value of equity; ROA is return on total asset.

According to Bates et al. (2009) and Brown and Petersen (2011) indicating that R&D

investment is related to more cash holdings, we further add the interaction terms of IVs and

D_RD1 in the first stage of robustness regression, and add cash holdings (CHE), dummy

variable of R&D intensity (D_RD1), dummy variable for a period after financial crisis

(D_ACrisis), the interaction term of CSR and D_RD1, the interaction term of CSR and

D_ACrisis, and interaction term of CHE and D_RD1 in the second stage of robustness

regression.

= α + α DAT + α MKBKF + α EBIT + α DAT ∗ D_RD1 +

21

α MKBKF ∗ D_RD1 + α DAT ∗ D_RD1 (23)

RM = β + β CSR + β SIZE + β DAT + β MKBKF + β ROA +

β CSR ∗ D_RD1 + β CHE + β D_RD1 + β CHE ∗ D_RD1 +

β D_ACrisis + β CSR ∗ D_ACrisis + ε (24)

where RM is the proxy of real earnings management; CSR indicates CSR scores; SIZE is

the natural logarithm of total assets; DAT is the total debt to total assets ratio; MKBKF is the

market value of equity to book value of equity; ROA is return on total asset; CHE is cash

holdings calculated by the cash plus short-term investments divided by total assets for prior

year; D_RM1 is the dummy variable of R&D intensity equal to one if R&D intensity is higher

than median, and zero otherwise; DAT*D_RD1 is the interaction term of DAT and D_RD1;

MKBKF*D_RD1 is the interaction term of MKBKF and D_RD1; EBIT*D_RD1 is the

interaction term of EBIT and D_RD1; CSR*D_RD1 is the interaction term of CSR and

D_RD1; CHE*D_RD1 is the interaction term of CHE and D_RD1. D_ACrisis is the dummy

variable for a period after financial crisis equal to one if the sample period is 2009-2014,

equal to zero otherwise. CSR*D_ACrisis is the interaction term of CSR and D_ACrisis.

4.3 Data Collection

In this paper, we collect the CSR scores data from the MSCI ESG STATS database which

gathers CSR activities information from 1991 and has been widely adopted to measure CSR

activities in prior research. We also collect our financial data from the Compustat database.

Then, we merge the MSCI ESG STATS and Compustat data12, and remove the observations in

the financial firms industries (SIC codes 6000-6999) and public utility institutions (SIC codes

4910-4949) from our sample since these industries have unique accounting reporting. All the

data and variables used in our study are included in Appendix 2.

Figure 1 shows the trend of RM related variables including ab_CFO, ab_PROD, ab_DIXS,

RM, RM1, and RM2. In general, RM is higher than RM1 and RM2 over time. Figure 2 shows

the trend of CSR related variables in seven issue areas. The score of environment is

consistently positive from 2000 to 2014. It means that most of firms perform well on

environmental protection. Figure 3 shows the trend of R&D expense and intensity. After the

passage of SOX in 2002, the R&D investment decreases in 2003, and then grows slightly. It

implies that the firms tend to shift away from AM to RM.

12 All the variables are winsorized at 1and 99 percentiles.

22

[Insert Figure 1 Here]



Table 1 provides the sample distribution of our sample. Our sample consists of 20471

observations from 2000 to 2014. Panel A shows the distribution over time, while Panel B

shows the distribution by industry.13 Most observations are concentrated on manufacturing

industry. Panel C shows data distribution by stock exchange listed on NYSE, NASDAQ, and

other markets. The observations are almost equally distributed between NYSE and NASDAQ.

[Insert Table 1 Here]

Table 2 provides the descriptive statistics including the values of minimum, Q1, median,

mean, Q3, maximum, and standard deviation. The mean (median) of Asset, Sales, COGS,

Inventory, AD, R&D, SG&A, CFO, PROD, DISX, EBIT, and CHE is 5067.360 (944.288),

4017.990 (865.343), 2601.820 (500.928), 3820128 (540637), 44.601 (0.000), 84.085 (3.278),

655.870 (159.065), 476.401 (87.986), 2983.948 (580.527), 784.555 (187.754), 457.463

(77.951), and 531.119 (110.579) in million, respectively. The mean (median) of Employees is

13.947 (3.360) in thousands. The mean (median) of RM, RM1, and RM2 is -0.159 (-0.121),

-0.061 (-0.073), and -0.119 (-0.076), respectively. The mean of CSR, CSR_COM,

CSR_CGOV, CSR_DIV, CSR_EMP, CSR_ENV, CSR_HUM, and CSR_PRO is -0.123, 0.050,

-0.223, 0.095, -0.119, 0.196, -0.032, and -0.090, respectively, and the median of these

variables are 0. The mean (median) of DAT, MKBKF, and ROA is 19.441% (16.915%), 3.595

(2.450), and 2.380% (4.784%), respectively.


Table 3 reports the Pearson correlation coefficients between dependent, independent,

instrumental, and control variables and variance inflation factor (VIF). All the correlation

coefficients are statistically significant except Cor (DAT, EBIT) and Cor (DAT, R&D). All

VIFs are less than 3, indicating that collinearity does not exist on our regression analysis.


13 MSCI ESG STATS database (formerly KLD) has expanded coverage to MSCI World Index (Ex-US), MSCIEmerging Market Index, MSCI Australia 200, the top 275 of the MSCI UK IMI, MSCI Canada IMI, MSCISouth Africa IMI, and MSCI Emerging Frontier Markets Africa Index. The number of whole observationsincreases in 2013. In our sample, the number of US observations decreases sharply in 2013.

23

5. Results

5.1 Test for Differences in Mean and Median for Subsamples Based on High and Low

R&D Intensity

Table 4 provides the results of comparison analysis for subsamples divided by the degree

of R&D intensity measured by R&D expenses divided by prior sales.14

The mean and median of RM, RM1 and RM2 for the firms with high R&D intensity are

significantly lower than those firms with low R&D intensity. The results imply that firms with

higher R&D investment are less likely to manipulate earnings. Consistent with our hypothesis

3, the results suggest a negative relationship between R&D and RM. The mean and median of

CSR for the firms with high R&D intensity are significantly higher than those firms with low

R&D intensity. Consistent with our hypothesis 2, the results suggest a positive relationship

between CSR and R&D. The results indicate that firms with higher R&D investment tend to

participate in more CSR activities. The mean and median of the instrumental or control

variables including DAT, EBIT, SIZE, and ROA for the firms with high R&D intensity are

significantly lower than those firms with low R&D intensity. The mean and median of the

instrumental or control variables including MKBKF, RD and CHE for the firms with high

R&D intensity are significantly higher than those firms with low R&D intensity. These traits

suggest that the high R&D intensity firms, while emphasizing CSR activities, appear to be

smaller with a less reliance on debt financing of their operations. The test results also suggest

that firms with higher R&D intensity have relatively higher stock price valuation.

Overall, our results are consistent with the second and third hypotheses suggesting a

positive (negative) relationship between R&D and CSR (RM). Firms with higher R&D

intensity exhibit higher CSR scores. Firms with lower R&D intensity, while having higher

EBIT and ROA measures, may not be as favorably perceived by investors since such firms

place less emphasis on R&D. Such firms, while larger, have higher RM measures which may

impact investor interpretation of other control variables, such as the lower cash holdings and

higher debt ratio, leading to relatively lower stock prices.


14 We alternatively use the proxies of R&D intensity based on R&D expenses divided by the logarithm of totalassets at year t-1 and R&D expenses divided by the number of employees, respectively. We obtain the sampleresults in difference tests. No matter which kinds of R&D intensity measures we use, the relations between CSRand RM are negative.

24

5.2 Test for Differences in Mean and Median for Subsamples before and after Financial

Crisis

Table 5 provides comparison results before and after the 2008 global financial crisis. The

mean and median of RM, RM1, and RM2 before the financial crisis are significantly lower

than that after the financial crisis. The mean and median of pre-crisis CSR are significantly

lower than that after the financial crisis. The means and medians of MKBKF, EBIT, ROA,

and CHE before the financial crisis are significantly higher than the post-crisis data except

DAT, SIZE and RD. Overall, after the financial crisis, firms exhibit higher CSR scores, higher

RM measures, greater size, lower market to book ratio, lower EBIT, lower ROA, and lower

cash holdings.


5.3 Empirical Results of Two-Stage Least Squares Regression Analysis

Tables 6, 7, and 8 report the results of 2SLS regressions for the entire sample and

subsamples classified by the degree of R&D intensity and three different periods: pre-, during,

and post-financial crisis, respectively.15 The value of Durbin-Watson statistic is close to 2,

indicating that there is no autocorrelation between the residuals. In Table 6, the results of the

first stage show that DAT is significantly negatively related to CSR, while MKBKF and EBIT

are significantly positively related to CSR at the 0.01 level. The results of the second stage

show that in the regression of RM on CSR, the coefficient is -0.7148 significant at the 0.01

level. This result implies that as firms engage in more CSR activities, they will, on average,

decrease their earnings management activities. Given the size of the coefficients, the change

in earnings management behavior would be notable, for an increase of one unit of CSR

activities would generally see firms decrease their earning management (RM) by 0.7148 units.

The coefficient on SIZE is 0.0367 significant at the 0.01 level and implies that as firms

increase in size, their earnings management activity would usually increase. The positive

relationship between size and earnings management may reflect a greater complexity within

the financial statements of larger firms that would reduce the potential discovery of earnings

management activities. These results are consistent with Chih et al. (2008) and Hong and

Andersen (2011) that firms with higher CSR or smaller size are less likely to manipulate

15 We also provide results of Ordinary Least Square (OLS) regression in Appendices 4, 5, and 6. The findingsshow that firms with higher CSR score are less likely to manipulate earnings. The negative relationship betweenCSR and RM are not affected by the degree of R&D intensity and the different periods of financial crisis.

25

earnings.

The test results with the dependent variable of RM1 show a similar relationship with CSR

which has a negative coefficient that is significant at the 0.01 level. This result indicates that

if firms engage in more CSR activities by 1 unit, then RM1 would be expected to decrease by

1.3475 units. The test results show a significant and positive relationship between the market

to book ratio and RM1. These findings suggest that firms with relatively higher stock price

valuations or priced to be more like a growth stock may engage in more earnings management

as measured by RM1. Thus, if the market to book value of firms increases by one unit, then

RM1 would be expected to increase by 0.0536 units. The results show that firms that have

higher CSR activities or lower market to book ratios, such as value stocks, are less likely to

manage earnings.

However, test results for the third real earnings management measure, RM2, show

somewhat different relationships. We observe that RM2 does not have a significant

relationship with CSR, yet all other variables show significant relationships at the 0.01 level.

Both size and the debt ratio are positively related to RM2, suggesting that firms that increase

in size as well as in debt are more likely to engage in earnings management. It may be that

firms with greater size and more debt may have more complex financial statements leading

management to believe they can engage in earnings management with lower risk of discovery.

Additionally, the market to book and ROA variables have negative relationships with RM2.

These results suggest that firms engage in less earnings management as they achieve higher

returns on their assets. Interestingly, the results suggest that firms with higher market to book

ratios decrease their level of earnings management, as measured by the RM2 variable. In this

scenario, growth firms may

The results show that firms which have smaller size, lower debt ratio, higher ROA, or higher

market to book ratio are less likely to manage earnings. Overall, our findings are

consistent with the first hypothesis based on the transparent financial reporting hypothesis.

The relationship between CSR and RM are negative. Higher CSR is a signal of more honest,

ethical managers and better firm reputation. In other words, ethical firms are more likely to

report earnings that are not manipulated.


Table 7 provides the results after we construct two subsamples based upon high and low

26

R&D intensity.16 We observe distinct differences between high and low R&D intensity firms

in how CSR relates to other variables. In the first stage for high R&D intensity firms, all

variables are significantly positively related to CSR at the 0.01 level. The test results suggest

that firms that commit to high levels of discretionary spending in R&D and also increase their

leverage (DAT) will engage in greater CSR activities since these firms already demonstrate

financial resources. Additionally, test results also suggest that high R&D intensity firms that

experience increases in growth opportunities (MKBKF) or profitability (EBIT) will also

engage in more CSR activities. Yet these relationships with CSR change greatly with low

R&D density firms where leverage (DAT) and profitability (EBIT) display significantly

negative relations with CSR at the 0.01 level. These low R&D intensity firms may not have

the resources to engage in such discretionary spending. Thus, CSR activities expand in these

firms when they experience decreases in leverage or greater profitability.

In the second stage for high and low R&D intensity, we observe distinct differences in

the significance of the variables used to explain the management of earnings. We observe

strong statistical significance in CSR and the other independent variables for high R&D

intensity firms whereas a complete lack of significance exists for the low R&D intensity

subsample. The test results show differences in how the earnings management metrics interact

with variables in the model. The model provides the most robust explanation with the

aggregated earnings management measure, RM. Test results suggest that high R&D intensity

firms that reduce their CSR activities also increase earnings management activities. Since

CSR activities often correspond to ethical management, these findings imply that firms where

management diminish their ethical positions related to CSR also demonstrate greater

willingness to engage in management of earnings. These results also demonstrate that high

R&D intensity firms increase earnings management activities when they grow in size,

increase leverage, or experience declines in profitability. Larger firms, with more complex

financial statements, may avoid public detection of many of their earnings management

activities. Additionally, managers in firms with increasing debt, lower profitability, or reduced

growth opportunities may choose to manage earnings to enhance the financial position of the

16 No matter which kinds of alternative R&D intensity measures are adopted, the relations between CSR andRM are still negative. Moreover, we also provide the results of 2SLS regression for subsamples with inexistentand existent R&D expense, and for subsamples with high and low R&D intensity given the existent R&Dexpense in Appendices 8 and 9, respectively. All of results remain unchanged.

27

firm.

The second stage results with the other earnings management metrics, RM1 and RM2,

provide similar, though less robust findings. Test results do not find that size and profitability

explain the RM1 metric, which does not have the cash flow component of the aggregate

measure, RM. Results also show that CSR does not explain the RM2 metric, which does not

contain production costs.

Interestingly, the second stage results show that none of the variables in the model for

firms with low R&D intensity explains earnings management activities. These findings are

consistent with our fourth hypothesis where the negative relation between CSR and RM

apparently only exists in those firms with high intensity. Overall, the results show that those

high R&D firms are less likely to manipulate earnings if they engage in greater CSR activities,

are smaller in size, have lower levels of debt, more growth opportunities (higher market to

book ratio), and greater profitability.


Table 8 presents the results when we split the sample around the global financial crisis

that took place from 2007 through 2008. In the first stage, we observe great consistency

across the sub-periods. The results suggest that firms that experience greater growth

opportunities (MKBKF) and profitability (EBIT) and less debt (DAT) will engage in more

CSR activities, regardless of the economic conditions experienced in the three sub-periods.

Such findings may reflect that firms may be more willing to engage in CSR activities when

they have stronger financial positions and opportunities, regardless of the general economic

climate. The sole exception is where firms in the post-financial crisis increase their debt levels

and also increase their CSR engagement. The post-financial period was marked with limited

access to the credit market. Thus, firms in the post-financial period that could access the

financial markets and increase their leverage would have been of above average financial

health. Such firms would have possessed the financially security to engage freely in greater

CSR activities.

Results from the second stage show that the model does little to explain earnings

management before or during the financial crisis. We observe some patterns of firms engaged

in earnings management behavior, as measured by RM2, where larger firms engage are more

prone in the pre-financial crisis period while firms with more debt during the financial crisis.

28

Yet the post-financial crisis period provides results that are remarkably similar to those of

Table 6 which spans the entire time period. These findings suggest that the post-financial data

may be driving the overall results. These results suggest that firms that reduce their CSR

activities tend to engage more earnings management, as measured by RM and RM1. Test

results for this last sub-period also show that larger firms practice earnings management, as

defined by RM and RM2. These results are consistent with Chih et al. (2008) and Hong and

Andersen (2011) that firms with lower CSR or greater size are more likely to manipulate

earnings. The results also suggest that firms with greater debt (DAT) or reduced profitability

(ROA) are more likely to manage earnings. Such findings imply that firms may engage in

earnings management behavior when they experience less optimal financial conditions.

Results with MKBKF, which captures growth opportunities, generate different result contrary

results. Firms that experience more growth opportunities appear to engage in more earnings

management activities, as measured by RM1, yet these finding reverse with the RM2 metric.

The RM1 metric captures production costs which appears to capture the positive relation

between growth opportunities of a firm, production costs, and earnings management.

Consistent with our fifth hypothesis suggesting that the relationship between CSR and

RM may differ before, during, and after the financial crisis. The results show that after the

financial crisis the relationship between CSR and RM become significantly negative.

However, there is no significantly negative relation between CSR and RM before or during

the financial crisis.


5.4 Robustness Checking with the Effect of R&D Intensity and Financial Crisis

Table 9 reports the results for robustness checking based on the 2SLS regression with

proxies of CSR and RM, interaction term of CSR and R&D intensity, interaction term of CSR

and post-financial crisis, interaction term of cash holdings and R&D intensity, and the effects

of R&D investing and the financial crisis, cash holdings, year and industry control variables.17

We find that the coefficients on CSR are significantly negative for RM1. The findings are

consistent with the results in Tables 6-8, though without CHE, D_RD1, D_ACrisis,

interaction term of CSR and R&D intensity, interaction term of CSR and post-financial crisis,

and interaction term of CHE and D_RD1. However, for RM2, the coefficients on CSR are

17 We use the 2SLS with alternative R&D intensity measures and all the results still remain unchanged.

29

significantly positive. It indicates that firms with high CSR are more likely to manipulate

earnings by adjusting cash flow from operations and discretionary expenditure upward. The

coefficients on interaction term of CSR and D_RD1 are significantly negative across the

models. Consistent with the fourth hypothesis and results in Table 7, our findings suggest that

high R&D firms involved with more CSR are less likely to manage earnings. The coefficients

on CHE are significantly negative except for RM1. The coefficients on interaction term of

CHE and D_RD1 are all significantly negative. This suggests that for firms with high cash

holdings and high R&D intensity are less likely to manipulate earnings.

The results for the other variables provide findings consistent with earlier tests. Firms that

are larger, more indebted, or have lower profits on their asset bases tend to engage in more

earnings management activities. We observe that the coefficients on SIZE are all significantly

positive while the coefficients on DAT for RM and RM2 are significantly positive. The

coefficients on MKBKF are all significantly negative while the coefficients on ROA are all

significantly negative. After we add dummy variables for year and industry, the negative

relations between CSR and RM remain unchanged for firms with high R&D investment. The

coefficients on interaction term of CSR and D_ACrisis are significantly negative. Consistent

with our fifth hypothesis and results in Table 8, our findings suggest that there is a significant

negative relationship between CSR and RM (RM2) in the post-financial crisis period.


6. Conclusion

Previous studies have focused more on examining the relationship between CSR and

earnings management. However, there is a lack of evidence explaining the impact R&D

investment has on the relation between CSR and real earnings management. We contribute to

the literature on the relation between CSR and real earnings management by providing

evidence on how this relation is affected by the change in the level of R&D intensity in U.S.

firms from 2000-2014.

We first investigate whether there are statistically significant differences in the mean and

median values of firms’ characteristics, CSR, and earnings management (RM) activities for

subsamples with high and low R&D intensity. We use 2SLS regression to solve the

endogenous problem between CSR and RM. Consistent with the first hypothesis supported by

30

Chih et al. (2008) and Hong and Andersen (2011), our results show that CSR has a negative

correlation with earnings management. Ethical firms with more involvement in CSR activities

are less likely to manage earnings. In line with the fourth hypothesis, we also find that a

negative relation between CSR and earnings management only exists for firms with high

R&D intensity.

Furthermore, we discuss the relation between CSR and earnings management for

subsamples before, during, and after the global financial crisis. Consistent with the fifth

hypothesis, we find that the negative relationship between CSR and RM only exists in the

post-financial crisis period. Our findings suggest that after the financial crisis, firms with high

CSR would be less likely to manipulate earnings. In addition, our findings indicate that large

firms are more likely to manage earnings due to higher information asymmetry. Firms with

lower returns on their assets (ROA) also tend to manage earnings, indicating that firms with

higher profitability are less likely to manipulate earnings.

In the robustness checking, we incorporate cash holdings, dummy variable of R&D

intensity, the interaction term between CSR and R&D intensity, the interaction term between

cash holdings and R&D intensity, dummy variable of after financial crisis, and the interaction

term of CSR and post-financial crisis. Overall, we find consistent evidence of the negative

relation between CSR and real earnings management (measured by RM and RM1). The main

contribution of this paper is to explore how the relation between CSR and earnings

management activity changes with R&D intensity. In sum, our findings indicate that CSR is

significantly negatively associated with earnings management, particularly for firms with high

R&D intensity after the financial crisis.

Our findings might be useful to investors for selecting stocks issued by firms in terms of

the R&D intensity associated with CSR and RM activities. Overall, innovative firms involved

with CSR activities are less likely manage earnings. As a result, their financial reporting

would be expected to be relatively reliable and transparent.

31

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35

Table 1 Data DistributionTable 1 reports data distribution of our sample from 2000 to 2014. Panel A shows the distribution over time including the periods of pre,during and post financial crisis. Panel B shows data distribution by industry. Panel C shows data distribution by stock exchange.Panel A: By Year

Year Observation % Financial crisis Observation %2000 315 1.54%

Pre financial crisis2000-2006 7865 38.42%

2001 587 2.87%

2002 594 2.90%

2003 1628 7.95%

2004 1706 8.33%

2005 1511 7.38%

2006 1524 7.44%

2007 1514 7.40% During financial crisis2007-2008 3060 14.95%

2008 1546 7.55%

2009 1603 7.83%

Post financial crisis2009-2014 9546 46.63%

2010 1704 8.32%

2011 1623 7.93%

2012 1626 7.94%

2013 1562 7.63%

2014 1428 6.98%

Total 20471 100% Total 20471 100%

36

Table 1 (Continued)

Panel B: By SIC code

Range of SIC Codes Industry Observation %0100-0999 Agriculture, Forestry and Fishing 74 0.36%1000-1499 Mining 1210 5.91%1500-1799 Construction 335 1.64%2000-3999 Manufacturing 10672 52.13%4000-4999 Transportation, Communications, Electric, Gas and Sanitary service 1408 6.88%5000-5199 Wholesale Trade 688 3.36%5200-5999 Retail Trade 1844 9.01%6000-6799 Finance, Insurance and Real Estate 0 0.00%7000-8999 Services 4172 20.38%9100-9999 Public Administration 68 0.33%

Total 20471 100%

Panel C: By Stock ExchangeStock Exchange Observation %

NYSE 9922 48%NASDAQ 9707 47%

Other 842 4%Total 20471 100%

37

Table 2 Descriptive StatisticsTable 2 presents the descriptive statistics (mean, median, standard deviation, maximum, minimum, Q1 and Q3) concerning CFO, Assets, Sales, COGS,Inv, PROD, DISX, AD, R&D, SG&A, Employees, DAT, MKBKF, ROA, EBIT, CSR_COM, CSR_CGOV, CSR_DIV, CSR_EMP, CSR_ENV,CSR_HUM, and CSR_PRO over the period 2000-2014. Assets denotes total assets. Sales denotes net sales. COGS denotes cost of goods sale. Inventorydenotes inventories. AD denotes advertisement expense. R&D denotes research and development expense. SG&A denotes selling, general andadministrative expense. CFO denotes cash flow from operations in millions of US dollars. PROD denotes the sum of the cost of goods and change ofinventory. DISX denotes the sum of the expenses in AD, R&D, and SG&A. Employees denotes the total number of employees. RM, RM1, and RM2denote real earnings management measures. CSR denotes the sum of CSR scores for seven issues. CSR_COM denotes score of the strengths andconcerns of community. CSR_CGOV denotes score of the strengths and concerns of corporate governance. CSR_DIV denotes score of the strengths andconcerns of diversity. CSR_EMP denotes score of the strengths and concerns of employee. CSR_ENV denotes score of the strengths and concerns ofenvironment. CSR_HUM denotes score of the strengths and concerns of human rights. CSR_PRO denotes score of the strengths and concerns ofproduct. DAT denotes debt ratio. MKBKF denotes market to book ratio. EBIT denotes earnings before interest and taxes. ROA denotes return on assets.CHE denotes the cash holdings calculated as the cash plus short-term investments.Variables Minimum Q1 Median Mean Q3 Maximum Std DeviationAssets (in Millions) 31.737 341.639 944.288 5067.360 2995.549 541329.000 17153.596Sales (in Millions) 0.000 296.553 865.343 4017.990 2756.700 120550.000 10176.866COGS (in Millions) 0.000 139.842 500.928 2601.820 1741.100 90709.000 6907.298Inventory (in Millions) 0.000 4.155 54.637 382.128 258.000 16479.000 1035.343AD (in Millions) 0.000 0.000 0.000 44.601 7.355 2400.000 179.740R&D (in Millions) 0.000 0.000 3.278 84.085 40.631 4850.000 300.647SG&A (in Millions) 0.000 59.320 159.065 655.870 473.000 20450.793 1668.405CFO (in Millions) -663.000 24.820 87.986 476.401 298.200 17854.637 1371.278PROD (in Millions) 0.000 162.700 580.527 2983.948 2038.638 107188.000 7733.832DISX (in Millions) 0.000 72.748 187.754 784.555 562.674 27700.793 2002.599Employees (in Thousands) 0.003 0.933 3.360 13.947 11.000 323.000 31.302RM -5.735 -0.383 -0.121 -0.159 0.088 6.894 0.498RM1 -3.435 -0.231 -0.073 -0.061 0.081 5.195 0.335RM2 -4.759 -0.232 -0.076 -0.119 0.029 1.861 0.293

38

Table 2 Descriptive Statistics (Continued)

Variables Minimum Q1 Median Mean Q3 Maximum Std DeviationCSR 11.000 -1.000 0.000 -0.123 1.000 17.000 2.075CSR_COM -2.000 0.000 0.000 0.050 0.000 4.000 0.428CSR_CGOV -3.000 -1.000 0.000 -0.223 0.000 2.000 0.639CSR_DIV -2.000 -1.000 0.000 0.095 0.000 7.000 1.086CSR_EMP -4.000 0.000 0.000 -0.119 0.000 5.000 0.796CSR_ENV -3.000 0.000 0.000 0.196 0.000 6.000 0.714CSR_HUM -3.000 0.000 0.000 -0.032 0.000 2.000 0.275CSR_PRO -4.000 0.000 0.000 -0.090 0.000 2.000 0.510DAT (%) 0.000 0.972 16.915 19.441 31.133 101.870 18.294MKBKF 0.015 1.559 2.450 3.595 4.026 45.994 3.906EBIT (in Millions) -790.681 17.541 77.951 457.463 277.903 25179.000 1384.456ROA (%) -107.286 0.794 4.784 2.380 8.602 30.091 13.710CHE (in Millions) 0.451 327.509 110.579 531.119 327.509 73670.078 1909.272

39

Table 3 Pearson Correlation MatrixRM, RM1, and RM2 denote the proxies of real earnings management. CSR denotes the sum of CSR score for seven issues. DAT denotes debt ratio.MKBKF denotes market to book ratio. EBIT denotes the earnings before interest and taxes divided by total assets at t-1. SIZE denotes the logarithm oftotal assets. ROA denotes return on assets. R&D denotes R&D expense. CHE denotes the cash holdings calculated as the cash plus short-terminvestments. VIF is variance inflation factor. The p-values are reported in parentheses. ***, **, and * represent 1%, 5%, and 10% significance level,respectively.

RM RM1 RM2 CSR DAT MKBKF EBIT SIZE ROA R&D CHERM 1 0.8491 0.9340 -0.0747 0.1571 -0.2096 -0.1863 0.1361 -0.1599 -0.0792 -0.0256

(<.0001)*** (<.0001)*** (<.0001)*** (<.0001)*** (<.0001)*** (<.0001)*** (<.0001)*** (<.0001)*** (<.0001)*** (0.0003)***RM1 1 0.6608 -0.0944 0.0802 -0.1010 -0.5288 -0.0564 -0.4543 -0.0901 -0.0730

(<.0001)*** (<.0001)*** (<.0001)*** (<.0001)*** (<.0001)*** (<.0001)*** (<.0001)*** (<.0001)*** (<.0001)***RM2 1 -0.0478 0.1917 -0.2411 -0.0143 0.2182 -0.0235 -0.0624 0.0100

(<.0001)*** (<.0001)*** (<.0001)*** (0.0414) (<.0001)*** 0.0008 (<.0001)*** (0.1522)CSR 1 -0.0152 0.0857 0.0546 0.2429 0.0796 0.3190 0.2741

(0.0298)** (<.0001)*** (<.0001)*** (<.0001)*** (<.0001)*** (<.0001)*** (<.0001)***DAT 1 0.1096 0.0068 0.3743 -0.0584 -0.0029 0.0240

(<.0001)*** (0.3330) (<.0001)*** (<.0001)*** (0.6757) (0.0006)***MKBKF 1 0.0006 -0.0821 -0.0516 0.0628 0.0309

(0.9321) (<.0001)*** (<.0001)*** (<.0001)*** (<.0001)***EBIT 1 0.2155 0.7966 0.0324 0.0444

(<.0001)*** (<.0001)*** (<.0001)*** (<.0001)***SIZE 1 0.2437 0.4069 0.4569

(<.0001)*** (<.0001)*** (<.0001)***ROA 1 0.0516 0.0807

(<.0001)*** (<.0001)***R&D 1 0.6858

(<.0001)***CHE 1

VIF 1.15361 1.30597 1.06675 2.77521 1.79396 2.87061 2.01849 2.05733

40

Table 4 Tests for Differences in Mean and Median Based on R&D IntensityRD_INT1 denotes R&D expense divided by total sales at t-1. RM, RM1, and RM2 denote real earnings management measures. CSRdenotes the sum of CSR scores in seven issues. DAT denotes debt ratio. MKBKF denotes price to book ratio. EBIT denotes the earningsbefore interest and taxes divided by total assets at t-1. SIZE denotes the logarithm of total assets. ROA denotes return on assets. RD denotesthe expense in R&D. CHE denotes the cash holdings calculated as the cash plus short-term investments divided by total assets at t-1. Thep-values are reported in parentheses. ***, **, and * represent 1%, 5%, and 10% significance level, respectively.Based on median of RD_INT1

High RD_INT1 Low RD_INT1 Mean MedianVariable Mean Median Mean Median Difference T STAT Difference Z STATRM -0.2655 -0.2174 -0.0534 -0.0538 -0.2122 -31.1800 (<.0001)*** -0.1636 -32.5226 (<.0001)***RM1 -0.0811 -0.1008 -0.0416 -0.0480 -0.0395 -8.4500 (<.0001)*** -0.0529 -14.8489 (<.0001)***RM2 -0.1963 -0.1467 -0.0410 -0.0339 -0.1553 -39.2600 (<.0001)*** -0.1129 -39.9949 (<.0001)***CSR 0.1336 0.0000 -0.3794 0.0000 0.5130 17.8200 (<.0001)*** 0.0000 14.0708 (<.0001)***DAT 15.3273 11.0260 23.5543 22.1470 -8.2270 -33.0200 (<.0001)*** -11.1210 -33.2296 (<.0001)***MKBKF 4.1623 2.8740 3.0272 2.1110 1.1351 21.0100 (<.0001)*** 0.7630 29.9600 (<.0001)***EBIT 0.0523 0.0839 0.1120 0.0990 -0.0596 -25.1400 (<.0001)*** -0.0151 -18.7942 (<.0001)***SIZE 6.7937 6.5856 7.2335 7.1041 -0.4398 -19.7700 (<.0001)*** -0.5184 -22.3304 (<.0001)***ROA 0.4231 4.6150 4.3367 4.9115 -3.9136 -20.6300 (<.0001)*** -0.2965 -9.0864 (<.0001)***RD 166.8000 39.8640 1.4019 0.0000 165.4000 40.9300 (<.0001)*** 39.8640 127.4352 (<.0001)***CHE 0.3675 0.2430 0.1404 0.0757 0.2271 44.9400 (<.0001)*** 0.1673 57.5380 (<.0001)***N 10235 10235 10236 10236

41

Table 5 Tests for Differences in Mean and Median before and after Financial CrisisRM, RM1, and RM2 denote real earnings management measures. CSR denotes the sum of CSR scores in seven issues. DAT denotes debtratio. MKBKF denotes price to book ratio. EBIT denotes the earnings before interest and taxes divided by total assets at t-1. SIZE denotesthe logarithm of total assets. ROA denotes return on assets. RD denotes the expense in R&D. CHE denotes the cash holdings calculated asthe cash plus short-term investments divided by total assets at t-1. The p-values are reported in parentheses. ***, **, and * represent 1%,5%, and 10% significance level, respectively.

Pre financial crisis After financial crisis Mean Median

Variable Mean Median Mean Median Difference T STAT Difference Z STAT

RM -0.1849 -0.1438 -0.1351 -0.0997 -0.0498 -6.6000 (<.0001)*** -0.0441 -7.1995 (<.0001)***

RM1 -0.0805 -0.0839 -0.0452 -0.0626 -0.0353 -7.0000 (<.0001)*** -0.0213 -6.6191 (<.0001)***

RM2 -0.1334 -0.0926 -0.1027 -0.0625 -0.0307 -6.9600 (<.0001)*** -0.0301 -8.5453 (<.0001)***

CSR -0.1865 0.0000 0.0543 0.0000 -0.2408 -7.8200 (<.0001)*** 0.0000 -7.6978 (<.0001)***

DAT 18.9655 17.0520 19.6439 16.6960 -0.6784 -2.4600 (0.0137)** 0.3560 -0.7681 (0.4424)

MKBKF 3.7325 2.7420 3.6672 2.3630 0.0653 1.1100 (0.2675) 0.3790 13.2115 (<.0001)***

EBIT 0.0977 0.1014 0.0712 0.0845 0.0265 10.4100 (<.0001)*** 0.0169 13.6021 (<.0001)***

SIZE 6.9411 6.7824 7.0997 6.9611 -0.1586 -6.4900 (<.0001)*** -0.1786 -6.2484 (<.0001)***

ROA 3.5555 5.1750 1.8810 4.3780 1.6744 8.7100 (<.0001)*** 0.7970 9.7084 (<.0001)***

RD 79.7848 4.5280 91.2643 2.5160 -11.4795 -2.4600 (0.0138)** 2.0120 1.4649 (0.1429)

CHE 0.2649 0.1310 0.2480 0.1450 0.0169 2.9200 (0.0035)*** -0.0140 -3.0524 (0.0023)***

N 7865 7865 9546 9546

42

Table 6 2SLS Regression for Entire SampleRM, RM1, and RM2 denote real earnings management measures. CSR denotes the sumof CSR scores in the seven issues. DAT denotes debt ratio. MKBKF denotes market tobook ratio. EBIT denotes the earnings before interest and taxes divided by total assets att-1. SIZE denotes the logarithm of total assets. ROA denotes return on assets. Thep-values are reported in parentheses. ***, **, and * represent 1%, 5%, and 10%significance level, respectively.Stage 1 Dependent Variable: CSRIntercept -0.29028

(<.0001)***DAT -0.00286

(0.0003)***MKBKF 0.046964

(<.0001)***EBIT 0.65938

(<.0001)***R-Square 0.01095Adjusted R-Square 0.0108

Dependent Variable

Stage 2 RM RM1 RM2

CSR -0.7148 -1.3475 0.0227(<.0001)*** (<.0001)*** (0.4296)

SIZE 0.0367 0.0056 0.0282(<.0001)*** (0.6832) (<.0001)***

DAT 0.0016 -0.0024 0.0026(0.0328)** (0.0828)* (<.0001)***

MKBKF 0.0058 0.0536 -0.0198(0.4657) (0.0002)*** (<.0001)***

ROA -0.0023 -0.0024 -0.0015(0.0834)* (0.3172) (<.0001)***

Intercept -0.5513 -0.4068 -0.2893(<.0001)*** (0.0007)*** (<.0001)***

R-Square 0.0132 0.0044 0.1202Adjusted R-Square 0.0129 0.0041 0.1200Durbin Watson 1.8188 1.8117 1.85681st Order Autocorrelation (ρ) 0.0906 0.0942 0.0716N 20471 20471 20471

43

Table 7 2SLS Regression for Subsamples with High and Low R&D IntensityRD_INT1 denotes the R&D expense divided by lagged total sales. RM, RM1, and RM2 denotereal earnings management measures. CSR denotes the sum of CSR scores in the seven issues.DAT denotes debt ratio. MKBKF denotes market to book ratio. EBIT denotes the earningsbefore interest and taxes divided by total assets at t-1. SIZE denotes the logarithm of total assets.ROA denotes return on assets. The p-values are reported in parentheses. ***, **, and * represent1%, 5%, and 10% significance level, respectively.

High RD_INT1 Low RD_INT1Stage 1 Dependent Variable: CSR Dependent Variable: CSRIntercept -0.2154 -0.3155

(<.0001)*** (<.0001)***DAT 0.0096 -0.0076

(<.0001)*** (<.0001)***MKBKF 0.0341 0.0438

(<.0001)*** (<.0001)***EBIT 1.1342 -0.1509

(<.0001)*** (0.3578)R-Square 0.0222 0.0101Adjusted R-Square 0.0219 0.0098

Dependent Variable Dependent VariableStage 2 RM RM1 RM2 RM RM1 RM2CSR -0.5183 -0.9244 0.0108 4.6443 4.6037 2.0969

(<.0001)*** (<.0001)*** (0.6043) (0.5176) (0.5168) (0.5182)SIZE 0.0432 0.0077 0.0323 0.0225 0.0021 0.0181

(<.0001)*** (0.5822) (<.0001)*** (0.7198) (0.9726) (0.5225)DAT 0.0117 0.0123 0.0043 0.0347 0.0346 0.0156

(<.0001)*** (<.0001)*** (<.0001)*** (0.5281) (0.5242) (0.5289)MKBKF -0.0142 0.0201 -0.0225 -0.2155 -0.2084 -0.0978

(0.0006)*** (0.0041)*** (<.0001)*** (0.4863) (0.4960) (0.4844)ROA -0.0031 -0.0025 -0.0026 -0.0019 -0.0021 -0.0005

(0.0126)** (0.2371) (<.0001)*** (0.8916) (0.8771) (0.9298)Intercept -0.6085 -0.2811 -0.3880 1.3903 1.5148 0.5538

(<.0001)*** (0.0042)*** (<.0001)*** (0.5616) (0.5226) (0.6091)R-Square 0.0351 0.0151 0.1782 0.0002 0.0002 0.0002Adjusted R-Square 0.0346 0.0146 0.1778 -0.0003 -0.0003 -0.0003Durbin Watson 1.8549 1.8545 1.8088 1.7728 1.7735 1.77231st Order Autocorrelation (ρ) 0.0725 0.0727 0.0956 0.1136 0.1132 0.1138N 10235 10235 10235 10236 10236 10236

44

Table 8 2SLS Regression pre, during, and post Financial CrisisThe sample periods of pre financial crisis, during financial crisis, and after financialcrisis are 2000-2006, 2007-2008, and 2009-2014, respectively. RM, RM1, and RM2denote real earnings management measures. CSR denotes the sum of CSR scores in theseven issues. DAT denotes debt ratio. MKBKF denotes market to book ratio. EBITdenotes the earnings before interest and taxes divided by total assets at t-1. SIZEdenotes the logarithm of total assets. ROA denotes return on assets. The p-values arereported in parentheses. ***, **, and * represent 1%, 5%, and 10% significance level,respectively.

Pre financial crisis During financial crisis Post financial crisis

Stage 1 Dependent Variable: CSR

Intercept -0.2821 -0.5338 -0.2051(<.0001)*** (<.0001)*** (<.0001)***

DAT -0.0066 -0.0101 0.0023(<.0001)*** (<.0001)*** (0.0478)**

MKBKF 0.0513 0.0632 0.0380(<.0001)*** (<.0001)*** (<.0001)***

EBIT 0.2986 0.4264 1.0652(0.0290)** (0.0425)** (<.0001)***

R-Square 0.0114 0.0163 0.0146Adjusted R-Square 0.0110 0.0153 0.0143

Dependent Variable Dependent Variable Dependent Variable

Stage 2 RM RM1 RM2 RM RM1 RM2 RM RM1 RM2

CSR -1.9851 -2.9937 -0.3556 -0.7372 -1.9625 0.4606 -0.3810 -0.8183 0.0480(0.2137) (0.2138) (0.2365) (0.1657) (0.1557) (0.1790) (<.0001)*** (<.0001)*** (0.1057)

SIZE 0.0384 0.0058 0.0287 0.0396 0.0090 0.0281 0.0324 0.0037 0.0264(0.2245) (0.9033) (<.0001)*** (0.0761)* (0.8770) (0.0503)* (<.0001)*** (0.7555) (<.0001)***

DAT -0.0086 -0.0177 0.0006 -0.0039 -0.0183 0.0071 0.0040 0.0028 0.0021(0.4198) (0.2733) (0.7565) (0.4797) (0.2045) (0.0456)** (<.0001)*** (0.0130)** (<.0001)***

MKBKF 0.0660 0.1390 -0.0046 0.0101 0.1097 -0.0536 -0.0076 0.0248 -0.0174(0.4377) (0.2787) (0.7742) (0.7693) (0.2194) (0.0155)** (0.0605)* (0.0014)*** (<.0001)***

ROA -0.0011 -0.0028 -0.0002 -0.0026 -0.0022 -0.0020 -0.0029 -0.0025 -0.0022(0.8780) (0.7876) (0.8497) (0.2962) (0.7368) (0.2274) (0.0150)** (0.2825) (<.0001)***

Intercept -0.9011 -0.8531 -0.3926 -0.7717 -1.0933 -0.0690 -0.3893 -0.1689 -0.2664(0.0644)* (0.2458) (<.0001)*** (0.0157)** (0.1876) (0.7372) (<.0001)*** (0.0519)* (<.0001)***

R-Square 0.0026 0.0010 0.0232 0.0117 0.0020 0.0120 0.0292 0.0109 0.0946Adjusted R-Square 0.0020 0.0004 0.0225 0.0100 0.0003 0.0104 0.0287 0.0104 0.0941

Durbin Watson 1.8676 1.8659 1.8868 1.9434 1.9384 1.9244 1.8497 1.8457 1.9248

1st Order Autocorrelation (ρ) 0.0658 0.0667 0.0562 0.0283 0.0308 0.0378 0.0751 0.0771 0.0375N 7865 7865 7865 3060 3060 3060 9546 9546 9546

45

Table 9 Robustness RegressionCSR denotes the sum of CSR scores in the seven issues. DAT denotes debt ratio.MKBKF denotes price to book ratio. EBIT denotes the earnings before interest andtaxes divided by total assets at t-1. D_RD1 is the dummy variable of R&D intensityequal to one if R&D intensity is higher than median, equal to zero otherwise.DAT*D_RD1 is the interaction term of DAT and D_RD1. MKBKF*D_RD1 is theinteraction term of MKBKF and D_RD1. EBIT*D_RD1 is the interaction term of EBITand D_RD1. RM, RM1, and RM2 denote real earnings management measures.D_ACrisis is the dummy variable for a period after financial crisis equal to one if thesample period is 2009-2014, equal to zero otherwise. CSR*D_ACrisis is the interactionterm of CSR and D_ACrisis. SIZE denotes the logarithm of total assets. ROA denotesreturn on assets. CSR*D_RD1 is the interaction term of CSR and D_RD1. CHE is cashholdings the cash plus short-term investments divided by total assets at t-1.CHE*D_RD1 is the interaction term of CHE and D_RD1. The p-values are reported inparentheses. ***, **, and * represent 1%, 5%, and 10% significance level, respectively.Stage 1 Dependent Variable: CSRIntercept -0.25393

(<.0001)***DAT -0.00871

(<.0001)***MKBKF 0.041693

(<.0001)***EBIT -0.28317

(0.0881)*DAT*D_RD1 0.019034

(<.0001)***MKBKF*D_RD1 -0.00472

(0.5306)EBIT*D_RD1 1.437086

(<.0001)***R-Square 0.03206Adjusted R-Square 0.03177

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Table 9 Robustness Regression (Continued)Dependent Variable Dependent Variable

Stage 2 RM RM1 RM2 RM RM1 RM2CSR -0.0218 -0.1563 0.0417 -0.0225 -0.1597 0.0428

(0.1871) (<.0001)*** (<.0001)*** (0.1686) (<.0001)*** (<.0001)***CSR*D_RD1 -0.0133 -0.0087 -0.0050 -0.0121 -0.0076 -0.0044

(<.0001)*** (0.0001)*** (0.0004)*** (<.0001)*** (0.0010)*** (0.0020)***CSR*D_ACrisis -0.0020 0.0008 -0.0017 -0.0066 -0.0028 -0.0038

(0.4623) (0.7430) (0.2853) (0.0160)** (0.2925) (0.0208)**SIZE 0.0288 0.0069 0.0190 0.0322 0.0089 0.0208

(<.0001)*** (0.0024)*** (<.0001)*** (<.0001)*** (0.0001)*** (<.0001)***DAT 0.0010 0.0004 0.0007 0.0007 0.0003 0.0005

(<.0001)*** (0.0436)** (<.0001)*** (0.0002)*** (0.1823) (<.0001)***MKBKF -0.0180 -0.0023 -0.0130 -0.0177 -0.0020 -0.0128

(<.0001)*** (0.0275)** (<.0001)*** (<.0001)*** (0.0524)* (<.0001)***ROA -0.0089 -0.0105 -0.0034 -0.0092 -0.0107 -0.0036

(<.0001)*** (<.0001)*** (<.0001)*** (<.0001)*** (<.0001)*** (<.0001)***D_RD1 -0.0818 0.0316 -0.0629 -0.1980 -0.0353 -0.1292

(<.0001)*** (0.0077)*** (<.0001)*** (<.0001)*** (0.0059)*** (<.0001)***D_ACrisis 0.0308 0.0179 0.0218 0.0204 0.0143 0.0107

(<.0001)*** (0.0031)*** (<.0001)*** (0.2035) (0.3569) (0.2632)CHE -0.0946 -0.0084 -0.0761 -0.1165 -0.0191 -0.0883

(<.0001)*** (0.6738) (<.0001)*** (<.0001)*** (0.3386) (<.0001)***CHE*D_RD1 -0.2427 -0.0674 -0.2128 -0.2154 -0.0532 -0.1976

(<.0001)*** (0.0025)*** (<.0001)*** (<.0001)*** (0.0174)** (<.0001)***Intercept -0.2022 -0.1123 -0.1262 0.0000 0.0000 0.0000

(<.0001)*** (<.0001)*** (<.0001)*** - - -Year Dummy - - - Included Included IncludedSIC Dummy - - - Included Included IncludedR-Square 0.1859 0.1317 0.2369 0.2170 0.1465 0.2609Adjusted R-Square 0.1855 0.1312 0.2365 0.2157 0.1452 0.2597Durbin Watson 1.9343 1.8766 1.9306 1.9377 1.8841 1.93121st Order Autocorrelation (ρ) 0.0328 0.0617 0.0347 0.0311 0.0580 0.0344N 20471 20471 20471 20471 20471 20471

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Figure 1 Trend of RM Related VariablesAb_CFO denotes the abnormal cash flow form operation (CFO) computed as actual CFO minus normal CFO. Ab_PROD denotes theabnormal production costs (PROD) computed as actual PROD minus normal PROD. Ab_DISX denotes the abnormal discretionaryexpenses (DISX) computed as actual DISX minus normal DISX. RM, RM1, and RM2 denote the proxies of real earnings management.

-0.25

-0.2

-0.15

-0.1

-0.05

02000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014Dollar

Year

RM

RM1

RM2

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Dollar

Year

ab_CFO

ab_PROD

ab_DISX

48

Figure 2 Trend of CSR Related VariablesCSR_COM, CSR_CGOV, CSR_DIV, CSR_EMP, CSR_ENV, CSR_HUM, and CSR_PRO denote CSR scores of community, corporategovernance, diversity, employee, environment, human rights, and product, respectively. CSR denotes the sum of CSR scores for sevenissues.

-1

-0.5

0

0.5

1

1.5

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Unit

Year

CSRCSR_COMCSR_CGOVCSR_DIVCSR_EMPCSR_ENVCSR_HUMCSR_PRO

49

Figure 3 Trend of R&D Related VariablesR&D (Millions U.S. Dollars) denotes the expense in R&D. RD_INT1 (Ratio) denotes the R&D expense divided by lagged total sales.RD_INT2 (Ratio) denotes R&D expense divided by total assets on a log scale at t-1. RD_INT3 (U.S. Dollars) denotes R&D expense dividedby total number of employees.

0.03125

0.0625

0.125

0.25

0.5

1

2

4

8

16

32

1

2

4

8

16

32

64

128

256

512

1024

2048

4096

8192

16384

32768

65536

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Ratio

Year

Dollar

R&D

RD_INT3

RD_INT1

RD_INT2

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Appendix 1 The Components of the Strengths and Concerns for CSR Issue Areas in KLD Database

Issue Areas Strengths Concerns

Community(CSR_COM)

1. Charitable Giving (COM )2. Innovative Giving (COM )3. Support for Housing (COM )4. Support for Education (COM )5. Non-US Charitable Giving (COM )6. Volunteer Programs (COM )7. Other Strength (COM )

1. Investment Controversies (COM )2. Negative Economic Impact (COM )3. Tax Disputes (COM )4. Other Concern (COM )

Corporate Governance(CSR_CGOV)

1. Limited Compensation (CGOV )2. Ownership Strength (CGOV )3. Transparency Strength (CGOV )4. Political Accountability Strength (CGOV )5. Other Strength (CGOV )

1. High Compensation (CGOV )2. Ownership Concern (CGOV )3. Accounting Concern (CGOV )4. Transparency Concern (CGOV )5. Political Accountability Concern (CGOV )6. Governance Structures Controversies (CGOV )7. Other Concern (CGOV )

Diversity(CSR_DIV)

1. CEO (DIV )2. Promotion (DIV )3. Board of Directors (DIV )4. Work/Life Benefits (DIV )5. Women & Minority Contracting (DIV )6. Employment of the Disabled (DIV )7. Gay & Lesbian Policies (DIV )8. Employment Of Underrepresented Groups (DIV )9. Other Strength (DIV )

1. Controversies (DIV )2. Non-Representation (DIV )3. Board Diversity - Gender (DIV )4. Other Concern (DIV )

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Appendix 1 (Continued)

Issue Areas Strengths Concerns

Employee Relations(CSR_EMP)

1. Union Relations (EMP )2. Cash Profit Sharing (EMP )3. Employee Involvement (EMP )4. Health and Safety Strength (EMP )5. Other Strength (EMP )

1. Union Relations (EMP )2. Health and Safety Concern (EMP )3. Workforce Reductions (EMP )4. Retirement Benefits Concern (EMP )5. Other Concern (EMP )

Environment(CSR_ENV)

1. Beneficial Products and Services (ENV )2. Pollution Prevention (ENV )3. Recycling (ENV )4. Clean Energy (ENV )5. Communications (ENV )6. Management Systems (ENV )7. Environmental Opportunities-Green Buildings (ENV )8. Waste Management - Electronic Waste (ENV )9. Other Strength (ENV )

1. Hazardous Waste (ENV )2. Regulatory Problems (ENV )3. Ozone Depleting Chemicals (ENV )4. Substantial Emissions (ENV )5. Agricultural Chemicals (ENV )6. Climate Change (ENV )7. Impact of Products and Services (ENV )8. Other Concern (ENV )

Human Rights(CSR_HUM)

1. Indigenous Peoples Relations Strength (HUM )2. Labor Rights Strength (HUM )3. Other Strength (HUM )

1. Burma (HUM )2. Labor Rights Concern (HUM )3. Indigenous Peoples Relations Concern (HUM )4. Human Rights Violations (HUM )5. Other Concern (HUM )

Product(CSR_PRO)

1. Quality (PRO )2. R&D/Innovation (PRO )3. Benefits to Economically Disadvantaged (PRO )4. Other Strength (PRO )

1. Product Safety (PRO )2. Marketing/Contracting Concern (PRO )3. Antitrust (PRO )4. Other Concern (PRO )

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Appendix 2 Description of Variables and Data Sources

Panel A RM Variables

Variable Definition Measurement methods Data Source Unit

Assets Total asset Compustat annual data item (A6)

Millions

Sales Net salesCompustat annual data item (A12)

ΔSales The change of net sales ΔSales = Sales − Sales

COGS The cost of goods sale Compustat annual data item (A41)

ΔINV The change in inventory ΔINV = INV − INV Compustat annual data item (A3)

CFO Cash flow from operationsOperating activities net cash flowminus extraordinary items anddiscontinued operations.

Compustat annual data item (A308)minus (A124)

PROD The sum of the cost of goods andchange in inventory PROD = COGS + ΔINV Compustat annual data item (A41)

and (A3)

DISX The sum of the expenses inadvertising, R&D, and SG&A. DISX = AD + R& + &

Compustat annual data itemA45(AD), A46(R&D), andA189(SG&A)

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Appendix 2 (Continued)Panel B R&D Intensity VariablesVariable Definition Measurement methods Data Source Unit

R&D Intensity(RD_INT1)

The expense in R&D divided bylagged total sales R _INT1 =

R&SALES

Compustat annual data item (A46)divided by (A12) Ratio


The expense in R&D to totalassets on a log scale R _ 2 =

R&ln TA

Compustat annual data item (A46)divided by (A6) Ratio


The expense in R&D to totalnumber of employees R _ 3 =

R&NUM_Employees

Compustat annual data item (A46)divided by (A29) Dollars

Panel C Control Variables

Variable Definition Measurement methods Data Source Unit

SIZE The nature logarithm of total assets Compustat annual data item (A6) MillionsDebt ratio(DAT) Total debt by total assets DAT =

Total debtTotal assets

Compustat annual data item (DAT) Percentage

Market tobook(MKBKF)

Market value at the end of thefiscal year divided by the bookvalue of the common equity.

MKBKF =Market value of equityBook value of equity

Compustat item (MKBKF)

ROA The return on assets ROA =NITA

Compustat annual data item(ROA) Percentage

EBITThe earnings before interest andtaxes divided by previous totalasset.

EBIT =EBITTA

Compustat annual data item(EBIT) divided by item (A6) Millions

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