Corporate Social Responsibility and Insider Trading: The Role of Reputational Costs

Abstract

We investigate the constraining effects of reputational concerns on insider trading by examining whether a firm’s corporate social responsibility (CSR) orientation affects executives’ insider trading activities. To the extent that CSR activities increase a firm’s reputational capital and therefore the reputational costs of informed trading, executives of CSR conscious firms are likely more constrained from insider trading. Consistent with this, we find that executives of CSR conscious firms make significantly lower profits from insider purchases than executives of non-CSR conscious firms. We also find that executives of CSR conscious firms are less likely to trade on future corporate news. Collectively, our results provide evidence suggesting that reputational costs constrain insider trading.

Keywords: corporate social responsibility, insider trading, reputation

JEL Classification: M14, D82, G10

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1. Introduction

Corporate executives have incentives and disincentives to trade on their insider

information. While they can make significant profits from informed trades, they also face

various constraints. The literature has so far focused on the constraints imposed by

regulations and firm-level policies (e.g., Seyhun, 1992; Bettis et al., 2000; Jagolinzer et

al., 2011). The constraining effects of reputational concerns, on the other hand, although

often conjectured (e.g., Manne, 1985; Piotroski and Roulstone, 2008), lack empirical

support. We fill this gap by investigating whether a firm’s reputational capital created by

its corporate social responsibility (CSR) activities constrains executives’ insider trading

behavior.

There is ample evidence that insider trading brings significant financial gains to

corporate executives (e.g., Finnerty, 1976; Ravina and Sapienza, 2010; Jagolinzer et al.,

2011). These profitable trading activities, however, are commonly perceived as a result of

insiders “unfairly” exploiting their private information at the expense of uninformed

shareholders (e.g., Schotland, 1967). This appearance of impropriety raises significant

negative sentiment against insider trading among regulators, media, and the general

public. Consequently, firms and executives often experience substantial negative

publicity when information-based trading is detected and revealed (Bettis et al., 2000).

Such negative publicity and the resulting reputational losses likely have a deterring effect

on informed trading (Manne, 1985; Piotroski and Roulstone, 2008). Ceteris paribus, we

expect that executives of firms with more reputational capital, thereby having more to

lose from negative publicity, to profit less from insider trading.

On the other hand, CSR activities, which have become an issue of growing

interest for regulators, investors, and other stakeholders in recent years, are widely

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viewed as a firm’s strategic investment in reputation building and maintenance (Fombrun

and Shanley, 1990; McWilliams et al., 2006; Linthicum et al., 2010). A recent survey of

Fortune 1000 executives reveals that reputation is the primary motivation behind CSR

initiatives (Adam Friedman Associates, 2012). The literature also suggests that CSR

activities enhance a firm’s reputation by raising brand value, customer awareness, and

investor appreciation (Brown and Dacin, 1997; Servaes and Tamayo, 2012; Rosen et al.,

1991). To the extent that CSR conscious firms have more reputational capital at stake and

therefore higher reputational costs associated with insider trading than non-CSR

conscious firms, we expect that their executives are more constrained from profiting from

informed trades.

We measure a firm’s CSR orientation by examining the social ratings data issued

by MSCI ESG STATS (MSCI hereafter; previously known as KLD) from 1991 to 2010.

Similar to the extant literature (e.g., Hong and Kostovetsky, 2012; Kim et al. 2012), we

assess a firm’s CSR performance with a summary CSR score that reflects various aspects

of social responsibility, including environment, community, employee relations, diversity,

customers, and involvement in controversial industries. Following the prior literature

(e.g., Piotroski and Roulstone, 2008; Huddart and Ke, 2007; Jagolinzer et al., 2011), we

proxy for executives’ insider trading profits using the average daily abnormal returns

from the Fama-French four-factor model estimated over the 180 days following each

trade. We examine the association between a firm’s CSR orientation and its executives’

subsequent insider trading profits.

Consistent with the prior literature (Aboody and Lev, 2000; Huddar and Ke, 2007;

Jagolinzer et al., 2011), we find that executives make profits from purchase transactions

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but not from sales. We further find that, for CSR conscious firms, i.e., firms with more

CSR strengths than concerns in the prior year, executives’ trading profits from purchases

are significantly lower than for non-CSR conscious firms. The difference in trading

profits persists after we control for firms’ book-to-market ratio, size, a variety of proxies

of information asymmetry, and insider trading restrictions. Exploring various dimensions

of the aggregate CSR score, we find that environmental consciousness is a dominant

factor that constrains executives’ insider trading profits. This is consistent with

environmental initiatives receiving the most attention from regulators and the general

public (PricewaterhhouseCoopers, 2010; Adam Friedman Associates, 2012) and thus

likely contributing more to a firm’s reputational capital compared to the other dimensions

of CSR.

To reinforce our inference that CSR constrains executives’ insider trading profits,

we conduct several inter-temporal and cross-sectional tests. First, we examine whether a

firm’s adoption of new CSR initiatives is associated a subsequent decline of executives’

insider trading profits. Our analysis indicates that, after a firm turns from non-CSR

conscious to CSR conscious, its executives’ insider trading profits decrease significantly.

Second, we examine trading profits of newly appointed executives from outside

the company. These new executives do not create the firm’s CSR orientation but are

likely constrained by it. Consistent with our primary findings, these new executives of

CSR conscious firms also make lower insider trading profits than their counterparts of

non-CSR conscious firms, supporting our main inference that insider trading is

constrained by CSR.

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Third, we investigate whether the constraining effects of CSR on insider trading

profits are more pronounced absent effective alternative constraining mechanisms. Prior

research suggests that strong corporate governance limits insider trading profits (Ravina

and Sapienza, 2010; Jagolinzer et al., 2011). We thus expect the constraining effects of

CSR to be more evident in firms with weak governance. Consistent with this, our analysis

shows that executives of CSR conscious firms make lower insider trading profits than

executives of non-CSR conscious firms only in the subsample of weakly governed firms.

We perform a number of robustness tests. First, a firm’s CSR orientation could be

endogenously determined by the characteristics of the firm. To address this issue, we use

the propensity score matching technique and match each CSR conscious firm-year with a

non-CSR conscious firm-year with the closest propensity score. Our matching model

accounts for all explanatory variables in the trading profit regression and other potential

determinants of CSR, such as free cash flows and institutional ownership. We continue to

find that executives of CSR conscious firms make significantly lower profits from insider

trading than executives of matched firms.

Second, we include additional controls for potentially omitted correlated variables.

We control for media coverage, measured by the average daily number of news articles

covering each firm in the year of the trade, as mass media can be a source of information

that reduces insider trading profits (Frankel and Li, 2004) and a source of pressure that

promotes CSR practices (Zyglidopoulos et al., 2012). We also control for top executives’

total compensation since prior research suggests that insider trading can be a form of

compensation (e.g., Manne, 1966, 2011). Our inferences are robust to including the

additional controls.

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Third, we expect the constraining effects of CSR to be less prominent on lower

level managers than on executives, as lower level managers’ informed trades are likely

less damaging to a firm’s reputation given their lower visibility. We find that, while CSR

constrains executives’ trading profits, it does not constrain the trading profits of lower

level managers.

Finally, we examine whether a firm’s CSR orientation affects the likelihood of

executives engaging in insider trading prior to future corporate news. Consistent with

insider trades being driven by superior information, we find that, for non-CSR conscious

firms, executives are more likely to buy prior to good news and/or sell prior to bad news.

In contrast, there is no such evidence for executives of CSR conscious firms, suggesting

that these executives are constrained by the CSR orientation of their firms and therefore

are less likely to trade on insider information.

Our paper contributes to the literature in at least two ways. First, we add to the

insider trading literature by examining the role of reputational concerns on insider trading.

While a number of studies have investigated how regulations and firm-specific policies

constrain insider trading, there lacks empirical support for the often conjectured

constraining effects of reputational costs. Using CSR orientation as a proxy for

reputational costs, we provide evidence on the constraining role of reputational concerns.

Second, we contribute to the CSR literature by suggesting a new channel through

which CSR initiatives might affect managerial behavior. We find that a firm’s CSR

orientation could act as an economic constraint on potentially opportunistic managerial

decisions, such as informed insider trading, via its connection with the firm’s reputational

capital.

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Some studies suggest that executives of CSR conscious firms are ethical (e.g.,

Kim et al., 2012). If so, they will likely restrain from trading on private information.

However, we believe our results are better explained by the economic constraint

perspective of CSR than ethics. Executives of CSR conscious firms, just like executives

of non-CSR conscious firms, make economically and statistically significant profits from

insider trading, inconsistent with these executives being ethical.

The remainder of this paper is organized as follows: Section 2 discusses related

studies, hypothesis, and research design. Section 3 describes the sample and main

analyses. Section 4 reports additional tests and Section 5 concludes.

2. Related Studies, Hypothesis Development and Research Design

2.1. Related studies and hypothesis development

Corporate insiders have access to a continuum of material non-public information

about their own firms. Prior studies suggest that insiders trade on (e.g., Frankel and Li,

2004; Piotroski and Roulstone, 2005) and profit from (e.g., Aboody and Lev, 2000;

Skaife et al., 2012) their superior knowledge about the firms’ prospects.1 Rozeff and

Zaman (1988) point out that insider trading profits persist even after taking into account

transaction costs.

While insiders can extract profits from informed trading, they also face a number

of constraints. Regulators impose penalties on insider trades based material non-public

1 Under the semi-strong form of market efficiency, only trades based on private information can earn profits. Therefore, these persistent trading profits suggest that insiders trade on their private information.

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information.2 However, Seyhun (1992) shows that enactment of tighter regulations does

not seem to reduce insider trading profits. Piotroski and Roulstone (2005), on the other

hand, find evidence that legal costs do constrain insider trading in the sense that insiders

attempt to reduce the risk of investigation by avoiding trades immediately prior to major

news events. Firms also voluntarily adopt policies to restrict insider trades. Bettis et al.

(2000) document that the specification of blackout periods is effective in restricting

insider trades. Jagolinzer et al. (2011) further show that a more effective approach is to

require approval from the general counsel before insider transactions.

A relatively unexplored constraint of insider trading is a firm’s reputational

concerns. Profitable insider trading is associated with a general perception that insiders

exploit uninformed shareholders for personal financial gains.3 Schotland (1967) claims

that, since such gains are “unfair,” unacceptable wrong is inflicted by insiders’ informed

trading. This perception of unfairness raises significant negative sentiment against insider

trading. The media widely embrace the view that profit from insider trading is reward

without risk and wealth generated with injury done to others. 4 Consequently, when

insider trading is detected and revealed, firms often experience substantial negative

publicity that results in reputational losses (Bettis et al., 2000). For example, in the case

of Diamond v. Oreamuno, the court noted that informed trading can “cast a cloud on the

2 The Securities Exchange Act of 1934 requires insiders to forfeit (to their company) the profit realized from round-trip transactions (e.g., a buy followed by a sale) made within six months of each other. The Insider Trading Sanctions Act of 1984 increases the maximum civil penalty for illegal insider trading to three times the amount of profit gained or losses avoided, and imposed a maximum criminal penalty of $100,000 and a maximum jail sentence of 5 years. The Securities Fraud Enforcement Act of 1988 further increases the maximum criminal penalties to $1,000,000 and the maximum jail sentence to 10 years. 3 Our paper is silent on whether insider trading enhances or harms economic efficiency. The literature is inconclusive on this topic (e.g., Manne 1996; Ausubel, 1990; Fishman and Hagerty, 1992). 4 See, for example, the article by Pulitzer-Prize-winner George Will, “Keep Your Eye on Guiliani,” on Newsweek, March 2, 1987.

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corporation’s name, injure stockholder relations and undermine public regard for the

corporation’s securities.”

CSR, on the other hand, is widely considered a strategic investment in reputation

building and maintenance (Fombrun and Shanley, 1990; McWilliams et al., 2006;

Linthicum et al., 2010). McWilliams and Siegel (2001) present a theory of the firm

perspective of CSR, stating that firms accrue reputation capital through their

commitments to the social good. Adam Friedman Associates (2012) survey CSR

executives at Fortune 1000 firms and identify reputation as the primary motivation

behind CSR initiatives. Consistent with CSR being effective at enhancing reputation, the

literature shows that CSR conscious firms experience increased brand value, more

customer awareness, and greater investor appreciation (Brown and Dacin, 1997; Servaes

and Tamayo, 2012; Rosen et al., 1991).

With more reputation capital at stake, CSR conscious firms face higher potential

reputational losses from informed trading. Such expected costs, ex ante, will constrain

executives from insider trading. The constraining effects could come through multiple

channels. For example, CSR conscious firms likely entertain a corporate culture that

values reputation. This culture would discourage individual behavior that can damage

firm reputation, such as informed insider trading.5 Furthermore, managerial wealth is tied

to the value of the firm directly through the ownership of stock or stock options and

indirectly through salaries and bonuses based on various financial and nonfinancial

performance measures. Thus, reputational losses of the firm can translate into personal

5 Organizational research suggests that corporate culture is a social control mechanism that influences individual behavior by encouraging conforming activities and discourages nonconforming activities (O’Reilly and Chatman, 1996; Sunstein 1996; Sørensen, 2002).

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costs of insider trading and thereby provide disincentives for informed trading. 6 In

addition, CSR conscious firms might adopt explicit corporate policies to constrain insider

trading and protect their reputation.7

In summary, we expect that executives of CSR conscious firms are more

constrained from insider trading due to higher reputational costs and therefore would

make lower trading profits than executives of non-CSR conscious firms. We thus form

the following hypothesis:

H1: Executives of CSR conscious firms make lower insider trading profits than

executives of non-CSR conscious firms.

2.2. Research Design

2.2.1. Measure of CSR orientation

We measure firms’ CSR orientations with the CSR ratings issued by MSCI,

which uses a combination of surveys, financial statements, and articles in the popular

press and academic journals, as well as government reports, to assess firms’ CSR

performance with approximately 100 indicators. It examines strengths and concerns in

each of following seven categories: environment, community, human rights, employee

relations, diversity, customers, and governance. Additional concerns are noted for

6 Informed insider trading may also harm executives’ personal reputation. If a firm’s CSR activities increase the personal reputation of executives who make CSR decisions, the personal reputation costs of their insider trading would increase, thereby constraining their trading. While this may be possible and is consistent with reputation constraining insider trading, we are not aware of any literature support regarding the connection between a firm’s CSR orientation and its executives’ personal reputation. 7 We do not find our measure of CSR consciousness and our proxy of the existence of firm-level black-out period restrictions on insider trading to be positively correlated. While formal insider trading policies might be a channel through which CSR conscious firms regulate insider trading, it is possible that the implicit constraining effects of corporate culture and compensation schemes reduce the benefits and therefore the likelihood of adopting costly explicit policies.

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activities in the following controversial industries: alcohol, gambling, tobacco, firearms,

military, and nuclear power.

MSCI data have been used extensively in various disciplines of business

academic research to measure the construct of CSR performance (e.g., Turban and

Greening, 1997; Berman et al., 1999; Johnson and Greening, 1999; Hong and

Kostovetsky, 2012; Kim et al., 2012; Servaes and Tamayo, 2012). Chatterji et al. (2009)

commend MSCI’s social ratings as one of the most influential and the most widely

accepted CSR measures used by academics. Szwajkowski and Figlewicz (1999) evaluate

the validity and reliability of the MSCI database, and conclude that their ratings have

substantial and discernible validity with especially strong internal discriminant validity.

Waddock (2003) further assert that the MSCI data are “the de facto research standard” for

measuring CSR in scholarly research.

Similar to prior studies (e.g., Kim et al., 2012), we construct a CSR score,

measured as the total number of strengths minus the total number of concerns in all

MSCI’s rating categories excluding the human rights dimension and the corporate

governance dimension.8 We identify a CSR conscious firm as a firm with a positive CSR

score in the prior year.9

2.2.2. Measure of insider trading profits

8 Our results are robust to including the human rights dimension and the corporate governance dimension, excluding the concern indicator variables for involvement in controversial industries, and excluding observations with a CSR score of zero. 9 Our inferences are unchanged if we also classify firms with a CSR score of zero as CSR conscious firms, or if we use the continuous CSR score to measure CSR consciousness.

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Following the extant literature (e.g., Frankel and Li, 2004; Huddart and Ke, 2007;

Jagolinzer et al., 2011), we measure executives’ insider trading profits as the average

daily abnormal return over the six months following each trade.10 The trading profits are

estimated using the following transaction-specific regression of daily returns on four

common factors:

Ri – Rf = α + β1 (Rmkt – Rf) + β2 SMB + β3 HML+ β4 UMD + ε

Ri is the daily return of firm i’s equity, Rf is the daily risk-free interest rate, and Rmkt is the

CRSP value-weighted market return. SMB, HML, and UMD are the size, book-to-market,

and momentum factors. Trading profits are equal to α (-α) for purchases (sales). We

examine differences in executive’s insider trading profits between CSR conscious firms

and non-CSR conscious firms. If CSR constrains insider trading, we would find that

executives of CSR conscious firms make lower trading profits than executives of non-

CSR conscious firms.

3. Main analyses

3.1. Sample and descriptive statistics

We gather the CSR ratings data from MSCI, a database that covers about 650

largest U.S. companies from 1991 to 2000, about 1,100 largest U.S. companies from

2001 to 2002, and about 3,000 largest U.S. companies since 2003.11 We obtain insider

trading information from the Thomson Financial Insider Filing Data (TFN), which

contains insider trading activity reported on SEC Forms 3, 4, and 5. We focus on trades

10 Defining trading profits alternatively as the dollar amount of profits, i.e., abnormal returns multiplied by the value of the trades, yields qualitatively similar results. 11 Our results are robust to using only the sample period 2003 and beyond.

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of common shares by top executives including CEO, CFO, CIO, COO, CTO, and

Presidents. Following the literature (e.g., Frankel and Li 2004), we include only open-

market transactions and require a minimum transaction price of $2 a share and 100 shares

per transaction. We delete transactions with more shares than the CRSP daily volume and

prices outside the bid-ask price range. After merging with the Compustat database to

obtain control variables, our final sample includes 56,966 insider trading transactions

corporate executives made from 1992 to 2011.

Table 1 reports descriptive statistics. The mean CSR score is -0.1741 and the

median is 0. About 28% of our sample have a positive CSR score and are therefore

classified as CSR conscious firms. The summary statistics for control variables used in

the main analysis are also reported. Variable definitions are summarized in the appendix.

Not surprisingly, our sample firms are large, due to the composition of the MSCI

database.

3.2. Univariate and regression analyses

Panel A of Table 2 reports the univariate analysis of executives’ insider trading

profits in CSR conscious firms vs. non-CSR conscious firms. We present the trading

profits following each trade across various windows, i.e. 180 days, 120 days, and 90

days. Since our results are similar using different windows, we focus on the 180-day

window in our discussions. Following prior studies (Frankel and Li, 2004; Brochet, 2010;

Jagolinzer et al., 2011), we report insider purchases and sales separately. The mean daily

trading profits from executive purchases is 0.0402% for CSR conscious firms. In

contrast, for non-CSR conscious firms, the mean daily trading profits from executive

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purchases is 0.0568%, over 40 percent more than for CSR conscious firms. The

difference is significant, both statistically and economically. The comparison of the

median profits from executive purchases between CSR conscious firms and non-CSR

conscious firms exhibits the same pattern. These results suggest that executives of CSR

conscious firms make lower insider trading profits than executives of non-CSR conscious

firms.

Consistent with the prior literature (Aboody and Lev, 2000; Huddart and Ke,

2007; Jagolinzer et al., 2011), we find that insiders do not profit from sale transactions.

The average trading profits from their sales is negative for both CSR conscious firms and

non-CSR conscious firms (-0.0150% and -0.0121%, respectively).12 This is consistent

with insider sales being driven by multiple factors, some unrelated to information. For

example, executives may sell shares due to the need for diversification or portfolio

rebalancing following option grants (Ofek and Yermack, 2000). In addition, insider sales

are more likely to trigger litigation if followed by a plunge in stock price, a potential

deterrent for insiders to profit from selling on private information (Cheng and Lo, 2006;

Chen et al., 2012). As insider trading profits are more likely to create an appearance of

impropriety, in the rest of the paper, we focus on purchases only, similar to Ravina and

Sapienza (2010).

Panel B of Table 2 reports the insider trading profit regression results based on the

following model:

Trading Profitt = α + β1 CSRt-1 + β2 BTMt-1 + β3 LogMVt-1 + β4 R&Dt-1 + β5 Losst-1 + β6 Volatilityt-1 + β7 LogAnalystt-1 + β8 Turnovert-1 + β9 Restrictt-1 + εt (1)

12 The difference is -0.0029%, statistically significant at the 10% level, which is consistent with our hypothesis. However, we acknowledge that this difference is likely not economically significant.

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The variable Trading Profitt is the estimated average daily trading profits over 180 days

following each trade. The CSRt-1 indicator variable is equal to one for CSR conscious

firms, i.e., firms with a positive aggregate CSR score in the year prior to the trade.

Following Lakonishok and Lee (2001), we control for firm risk with two proxies,

the book-to-market ratio (BTMt-1) and firm size (LogMVt-1). We also control for

information asymmetry following prior research. Aboody and Lev (2000) document

higher insider trading profits in firms with R&D activities. We define R&Dt-1 as a dummy

variable equal to one if a firm has positive R&D expenses. Following Huddart and Ke

(2007) and Brochet (2010), we also include a loss dummy (Losst-1). As in Ravina and

Sapienza (2010), Volatilityt-1 is computed as the variance of daily stock returns over the

interval (-380, -20) before each trade. We also follow Frankel and Li (2004) to include

analyst following (LogAnalystt-1). We add share turnover (Turnovert-1) to control for

differences in the intensity of investor interest between CSR conscious and non-CSR

conscious firms. Bettis et al. (2000) find that insider trading restrictions with blackout

periods reduce insider trading profits. We follow Roulstone (2003) and Brochet (2010)

and control for Restrictt-1, a dummy variable set to one if 75% or more of trades in a

fiscal year occur in a 30-day window following an earnings announcement.13 Following

Ravina and Sapienza (2010) and Cao et al. (2011), we cluster standard errors by

executive.14

13 Bettis et al. (2000) collect data on blackout periods from a survey. Roulstone (2003) and Brochet (2010) construct a proxy for blackout periods based on publicly available data on insiders’ trading patterns and we follow their approach to control for blackout periods. 14 Our results are robust to clustering standard errors by executive-year or by firm, and controlling for industry and year fixed effects.

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Panel B reports the results of model (1) for purchases. Consistent with the

univariate analysis, our results are similar across different trading windows. Therefore,

we focus on the 180-day window in our discussions here and in subsequent analyses

following prior studies (Seyhun, 1998; Huddart and Ke, 2007; Brochet, 2010; Jagolinzer

et al., 2011). We find a negative and significant coefficient on CSRt-1 (-0.0181,

p=0.0074), suggesting that executives of CSR conscious firms make significantly lower

profits in insider purchases than executives of non-CSR conscious firms, consistent with

our hypothesis.

In an untabulated analysis, we also estimate model (1) for sale transactions across

different trading windows. The coefficient on CSRt-1 is insignificant at conventional

levels. Thus, there is no evidence that trading profits (losses) from insider sales differ

between CSR conscious and non-CSR conscious firms.

3.3. Dimensions of CSR

Our CSR score is a composite index summarizing various dimensions of social

responsibility. Next, we explore which aspect drives the relation between a firm’s CSR

orientation and executives’ insider trading profits. We follow the prior literature (Turban

and Greening, 1997; Kim et al., 2012) and examine each of the following five dimensions

of CSR: environment, community, employee relations, diversity, and product. 15

Environmental issues tend to attract more attention from regulators and the general public.

Adam Friedman Associates (2012) suggests that environmental issues are a top focus for

CSR executives, dominating all the other dimensions of CSR. A similar view is

15 We do not examine the controversial industries as a separate dimension because they are noted for concerns only.

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expressed in another survey by PricewaterhhouseCoopers (2010), where over 90% of

surveyed companies had a dedicated discussion about the environment in their CSR

reports. Since investing in environmental projects is more likely to effectively accrue

reputational capital for the firm, environmental consciousness is more likely to constrain

executives’ insider trading profits than the other dimensions.

Similar to the definition of CSRt-1, we construct an indicator variable for each of

the following five dimensions, CSR_Environmentt-1, CSR_Communityt-1, CSR_Employee

Relationst-1, CSR_Diversityt-1, and CSR_Productt-1. These indicator variables are equal to

one if the CSR score in the corresponding dimension is positive, i.e., the total number of

strengths is greater than the total number of concerns in that dimension. We examine the

relation between these CSR dimensions and executives’ trading profits using the

following regression model:

Trading Profitt = α + β1 CSR_Environmentt-1 + β2 CSR_Communityt-1 + β3

CSR_Employee Relationst-1 + β4 CSR_Diversityt-1 + β5 CSR_Productt-1 + β6 BTMt-1 + β7 LogMVt-1 + β8 R&Dt-1 + β9 Losst-1 + β10 Volatilityt-1 + β11 LogAnalystt-1 + β12 Turnovert-1 + β13 Restrictt-1 + εt (2)

We present the regression results in Table 3. The coefficient on CSR_Environmentt-1 is

negative and significant (-0.0239, p=0.0315) whereas coefficients on all the other CSR

dimensions are insignificant at the 10% level. Our results suggest that the environment

dimension of CSR is a dominant constraining force limiting executives’ insider trading

profits.

3.4. Effect of new CSR initiatives

To reinforce our inference that CSR constrains insider trading, we complement

the main analyses by examining whether a firm’s adoption of new CSR policies affects

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executives’ subsequent insider trading profits. Since we do not have data on CSR

initiations, we identify likely adopters of new CSR policies based on the MSCI data, i.e.,

we select a sample of firms rising from non-CSR conscious (CSR = 0) to CSR conscious

(CSR = 1). For this subsample, we estimate the following model using executive trades

before and after their rise to CSR consciousness.

Trading Profitt = α + β1 Post + β2 BTMt-1 + β3 LogMVt-1 + β4 R&Dt-1 + β5 Losst-1 + β6 Volatilityt-1 + β7 LogAnalystt-1 + β8 Turnovert-1 + β9 Restrictt-1 + εt (3)

The indicator variable Post is equal to one for executive trades during the first year after

the firm turns CSR conscious, and zero for their trades during the most recent year before

that.16 We expect the coefficient on Post to be negative if executives’ insider trading

profits decrease after the adoption of new CSR policies.

Table 4 summarizes the estimation results of model (3). The coefficient on Post is

negative and significant (-0.0553, p=0.0067), suggesting that executives’ insider trading

profits decrease as a firm turns CSR conscious. This finding reinforces our primary

inferences, suggesting that insider trading is more constrained with enhanced CSR

consciousness.17

3.5. New executives from outside the firm

An alternative explanation for our finding of a negative relation between CSR and

executives’ insider trading profits is that executives who are less likely to exploit their

16 Executives do not trade in all years, so we examine firm-years with trades to identify rises in CSR consciousness. If we identify the rises by comparing adjacent firm-years only (i.e., we require these adjacent years to have executive trades), our sample size is reduced by half but our results are robust, i.e., the coefficient on Post is still negative and significant. 17 Using an alternative specification of a firm-year level regression that regresses changes in yearly average executives’ insider trading profits on an indicator variable for rising from non-CSR conscious to CSR conscious and changes in all control variables in model (1) yields the same inference.

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private information for trading profits are also more likely to take on more CSR. To

explore this alternative explanation, we conduct an additional analysis focusing

exclusively on newly appointed executives from the outside. These new executives do

not create the firm’s CSR orientation. Thus, under the alternative explanation, we do not

expect these new, outside executives’ trading profits to be systematically correlated with

the existing CSR orientation of their new employer. However, since they are constrained

by CSR and the reputational concerns at the new company, our hypothesis should extend

to these new executives and predict a negative association between their trading profits

and the CSR consciousness of the new employer.

We identify newly appointed executives from the outside using two alternative

approaches. The first approach relies on the TFN insider filing data. We examine all

transactions, including option exercising, of executives and lower-level officers of all

firms to track the employment history of each person. If an executive was affiliated with

another organization, as an executive or as a lower-level officer, and the gap between

his/her first trade as an executive at the current company and last trade at the other

organization is within five years, we identify the executive as recently hired from the

outside.18 The second approach relies on the Execucomp data. Execucomp provides

information on the year in which an officer joins a company for about 30 percent of

executive/company combinations. We then manually merge this subsample with the

insider trading data by executive name. Under either approach, we estimate model (1)

with the purchase transactions made by these new, outside executives only.

18 Requiring the gap between trades to be within three years, two years, or one year does not change our inferences.

19

The estimation results are reported in Table 5. Column (1) shows the results for

new executives identified using the TFN data. The coefficient on CSRt-1 is negative and

significant (-0.0508, p=0.0176), suggesting that new executives of CSR conscious firms

make lower profits from insider trading than their counterparts of non-CSR conscious

firms. Column (2) reports the results for new executives identified using Execucomp

data. Consistent with the first column, the coefficient on CSRt-1 is also significantly

negative (-0.0580, p=0.0532). These results provide further support for our main

inference that CSR acts as a constraint of insider trading.19

3.6. Corporate governance and the constraining effects of CSR

The constraining effect of reputational concerns on insider trading is likely more

pronounced in the absence of effective alternative constraining mechanisms. Ravina and

Sapienza (2010) suggest that, when corporate governance is weak, executives have more

opportunities to expropriate shareholders and to profit from informed trading. In this

case, we expect the reputational capital captured by CSR orientation to exhibit a stronger

constraining effect, i.e., the difference in insider trading profits between CSR conscious

and non-CSR conscious firms is more evident under weak corporate governance.

We partition our sample into strong- vs. weak-governance firms based on the

median of the governance index proposed by Gompers et al. (2003).20 Among the 2,649

19 A potential selection issue in the appointment of new executives is the tendency of CSR conscious firms to hire executives from other CSR conscious firms. Our inferences are unchanged if we drop new executives who used to work for CSR conscious firms. 20 Since G-index data is not available after 2006, we apply the values of 2006 to future years (i.e., 2007-2011). Our results are qualitatively the same if we drop years after 2006 from our sample. We follow Ravina and Sapienza (2010) to use Gompers et al.’s (2003) governance index but not use MSCI’s corporate governance data as our proxy for corporate governance because MSCI measures the strengths and weaknesses of governance based on the quality of a firm’s CSR/sustainability reporting, a firm’s attitude

20

observations in the weak-governance sample, 1,020 observations are from CSR conscious

firms; 847 of the 2,465 observations in the strong-governance sample are from CSR

conscious firms. We estimate model (1) for firms with strong and weak corporate

governance separately and report the regression results in Table 6. We find a negative

and significant coefficient on CSRt-1 for firms with weak corporate governance (-0.0310,

p=0.0031), suggesting that executives of CSR conscious firms make lower insider trading

profits than executives of non-CSR conscious firms when governance is weak. However,

the coefficient on CSRt-1 is insignificant (0.0130, p=0.3095) for firms with strong

corporate governance. These results are consistent with our expectation that the

constraining effects of a firm’s CSR orientation on executives’ insider trading profits is

more pronounced under weak corporate governance.

Gompers et al.’s (2003) governance index captures overall governance based on

corporate charter provisions that may not be specifically designed for monitoring insider

trading. Thus, in addition to this general measure, we also explore the impact of insider-

trading-specific governance mechanisms (i.e., insider trading policies) on the

constraining effects of CSR on insider trading profits. We search firms’ websites as of

November 2012 to collect data on whether they disclose a stand-alone insider trading

policy or caution against insider trading in the code of conduct. We focus on a subsample

of insider trades occurring in 2011, the most recent year in our sample, assuming that

firms maintain consistent insider trading policies and disclosures between 2011 and

towards public policies on environment, communities, employees, or consumers, the severity of controversies related to a firm’s executive compensation and governance practices, and the severity of controversies related to a firm’s business ethics practices (MSCI ESG STATS User Guide & ESG Ratings Definition, June 2011). These dimensions are very different from the traditional measures of corporate governance that researchers use in academic research.

21

2012.21 Such disclosures highlight their concerns over insider trading and therefore we

consider it an indicator of strong insider-trading-specific governance. About 61% (304

out of 498) of our sample make these disclosures. We find a significant difference in

executives’ trading profits between CSR conscious and non-CSR conscious firms only in

the subsample where firms do not emphasize insider trading restrictions on their

websites, i.e., firms likely with weak insider-trading-specific governance. Since these

inferences are the same as those from Table 6 on overall governance, the results are

untabulated.

4. Additional analyses

4.1. Endogeneity of CSR and propensity score matching

A firm’s CSR orientation can be endogenously determined by the characteristics

of the firm. To the extent that certain firm characteristics drive a firm’s CSR orientation

and are omitted from our prior analyses, the relation between CSR and executives’

insider trading profits could be spurious. We follow the prior literature (e.g., Armstrong

et al., 2010; Jagolinzer et al., 2011) and adopt the propensity score matching technique to

mitigate this concern. To generate the propensity score, we construct a first-stage logistic

regression model for CSRt-1 at the firm-year level as follows:

Prob(CSRt-1=1) = logit(α + β1 BTMt-1 + β2 LogMVt-1 + β3 R&Dt-1 + β4 Losst-1 + β5 Volatilityt-1 + β6 LogAnalystt-1 + β7 Turnovert-1 + β8 Restrictt-1 + β9 Free Cash Flowt-1 + β10 Institutional Ownershipt-1 + β11 Firm Aget-1 + β12 Market Sharet-1 + εt-1) (4)

21 We cannot follow Bettis et al. (2000) or Jagolinzer et al. (2011) to construct their insider-trading-specific governance variables due to data constraints. Bettis et al.’s (2000) analysis is based on a survey of companies on insider trading policies. Jagolinzer et al. (2011) conduct a comprehensive web search for detailed insider trading policies and find only 437 policies out of the universe of public firms. In our random sample, only 14 firms disclose detailed insider trading policies.

22

We include all the control variables in model (1). In addition, we control for Free Cash

Flowt-1, which measures the difference between cash flow from operations and cash flow

used in investing activities. We expect that firms with more free cash flow have more

resources to invest in CSR. Since institutional investors care about CSR (Johnson and

Greens, 1999; Kim et al., 2012), we also control for Institutional Ownershipt-1, measured

as the percentage of institutional holdings. Dhaliwal et al. (2012) suggest that older firms

are more likely to invest in CSR, so we control for Firm Aget-1. We also follow Dhaliwal

et al. (2012) and use Market Sharet-1, measured as a firm’s fraction of sales in its industry,

to capture the firm’s visibility and public pressure for CSR performance.

Panel A of Table 7 tabulates the first stage logistic regression results. The

regression is estimated with 4,273 firm-year observations in our full sample, 1,240 of

which are classified as CSR conscious firms. Consistent with our expectations, we find

that larger firms, and firms with more R&D investments, higher investor interests, and

higher institutional ownership are more likely to be CSR conscious firms.

Next, we calculate the propensity scores using predicted probabilities from the

logistic regression and match each CSR conscious firm-year to a control firm-year with

the closest propensity score, provided that the propensity score of the closest match is

within a distance of 0.1. This procedure results in 1,109 matched pairs (i.e., about 90% of

the CSR-conscious firm-year observations are matched). The mean (median) propensity

score of the CSR conscious sample is 0.3706 (0.3662), while that of the matched control

sample is 0.3542 (0.3540). As in Armstrong et al. (2010), we perform a parametric t-test

of the difference in means between the CSR conscious sample and the matched sample

and a non-parametric Kolmogorov-Smirnov test of the difference between the two

23

distributions. Neither test shows the difference to be statistically different from zero at

conventional levels.

We then compare executives’ insider trading profits in CSR conscious firms vs.

the propensity score matched control firms.22 The mean trading profits for executives of

CSR conscious firms is significantly lower than the mean trading profits for executives of

the control firms (0.0390% versus 0.0561%, p<1%).23 Comparison of the medians

shows the same pattern. These results are similar to our main results reported in Table 2.

4.2. Impact of media coverage

Zyglidopoulos et al. (2012) argue that media attention could potentially pressure

firms to be more socially responsible. Meanwhile, Frankel and Li (2004) predict that

news coverage, as a source of information, helps decrease insider trading profits. Thus,

the negative association between executives’ trading profits and CSRt-1 may be driven by

CSR conscious firms being covered more extensively by the media.

To mitigate this concern, we collect from Factiva the number of news articles

covering each firm during the fiscal year of the trades. We include all sources available

on Factiva, both voluntary disclosures and press coverage. A simple correlation analysis

indicates a positive and significant correlation between CSRt-1 and the average daily

number of news articles, Mediat, (0.1474, p<0.0001). The correlation between trading

profits and Mediat is negative but insignificant (-0.0041, p=0.6898). 22 Following Jagolinzer et al. (2011), we perform the first-stage propensity score matching procedure at the firm-year level, but conduct this insider trading test at the transaction level. 23 The propensity score matching procedure creates a pseudo “random” sample such that univariate differences in means between the treatment and control groups should be sufficient to estimate the treatment effects (Dehejia and Wahba, 2002; Dehejia, 2005). Nonetheless, our inference remains unchanged if we rerun model (1), a multivariate analysis, for the pooled sample of CSR conscious firms and the propensity score matched control firms.

24

We estimate model (1) again, including Mediat as a control variable. The results

are reported in the first column of Table 8. The coefficient on Mediat is insignificant

(0.0047, p=0.2435).24 Importantly, it does not explain away the negative association

between executives’ trading profits and CSRt-1. The coefficient on CSRt-1 remains

negative and significant (-0.0152, p=0.0319).

4.3. Insider trading as a form of compensation

Manne (1996, 2011) argues that insider trading can serve as a compensation

device. Consistent with this argument, Roulstone (2003) finds firms that restrict insider

trading pay a premium in total compensation relative to firms not restricting insider

trading. This argument suggests that executive compensation can be an omitted correlated

variable if CSR conscious firms are more likely than others to pay higher executive

compensation.

To address this issue, we include the level of executive total compensation in

model (1). We obtain executive compensation data from Execucomp. Since matching

TFN and Execucomp at the person level is a manual operation, we take the natural

logarithm of median total compensation of the top five most highly paid executives as a

firm-year level measure of compensation.25

The estimation results are reported in the second column of Table 8. We find a

positive coefficient on Compensationt (0.0152, p=0.0355), contrary to the expectation of

24 Frankel and Li (2004) find a positive correlation between media coverage and trading profits, although they predict a negative association. 25 Alternatively we use the logarithm of the average total compensation and the dollar amount of average or median compensation as robustness checks. While the coefficient on the compensation variables differs across different specifications, the coefficient on our variable of interest, CSRt-1, is consistently negative and significant at better than 5% level.

25

Manne (1996, 2011). Importantly, the coefficient on CSRt-1 remains negative and

significant (-0.0142, p=0.0576), consistent with our prior results.

4.4. CSR and lower-level managers

Given their lower visibility than executives, informed trading by lower-level

managers is likely less damaging to a firm’s reputation. Therefore, the constraining

effects of reputational concerns on insider trading are likely less pronounced for lower-

level managers. To compare with our previous results for executives, we re-estimate

model (1) for trades made by lower-level managers.

Table 9 reports the estimation results. The coefficient on CSRt-1 is not

significantly different from zero (0.0056, p=0.3382), whereas the estimation results of

model (1) for trades made by executives (Table 2 Panel B) reveal a negative and

significant coefficient on CSRt-1 (-0.0181, p=0.0074). This contrast is consistent with our

expectation that insider trading less damaging to a firm’s reputation is less constrained by

CSR.

4.5. CSR and the likelihood of news-based insider trading

In addition to trading profits, we also examine the likelihood of executives trading

on private information as an alternative measure of insider trading activity. We expect

that CSR also lowers the likelihood of executives engaging in informed purchases. We

adopt the following model in Piotroski and Roulstone (2008), which focuses on trading

26

ahead of changes in earnings and returns, and estimate it separately for CSR conscious

firms and non-CSR conscious firms:26

Prob(Purchaset=1) = logit(α + β1 Earnt+1+ β2 MARett+1 + β3 BTMt + β4 LogMVt + β5 MARett + β6 R&Dt + εt) (5)

We define an indicator variable Purchaset, equal to one if any executive purchased shares

in an open-market transaction during year t and total shares purchased by executives are

greater than or equal to total shares sold by executives. Earnt+1 is one of the two proxies

for future news, measured as the change in earnings from year t to year t+1. MARett+1 is a

second proxy for future news, measured as the twelve-month buy-and-hold market-

adjusted return over year t+1. We control for insiders’ contrarian trading tendency with

the twelve-month buy-and-hold market-adjusted return over year t (MARett). We also

control for the book-to-market ratio (BTMt), firm size (LogMVt), and R&D activities

(R&Dt).27

We report the results of regression model (5) separately for CSR conscious firms

and non-CSR conscious firms in Table 10. For non-CSR conscious firms, we find a

positive coefficient on both proxies for future news, i.e., change in earnings (0.6606,

p=0.0399) and future returns (0.1163, p=0.0901), suggesting that executives are more

likely to buy prior to good news. In contrast, neither coefficient is statistically significant

26 Examining the trading patterns before future news also mitigate a potential concern of measuring insider trading profits with post-trade abnormal returns (Ke et al, 2003; Piotroski and Roulstone, 2005) since one may argue that the post-trade price movements might have been caused by the trades themselves and thus post-trade abnormal returns may not indicate insiders profiting from superior information (e.g., Ravina and Sapienza, 2010). 27 We also include variables capturing whether executives received grants of restricted stock or options during year t and whether executives exercised options during year t as additional control variables. Untabulated results show that adding these controls reduces our sample size by more than 50%, but our inferences remain unchanged.

27

for CSR conscious firms (0.1308, p=0.8174; 0.0681, p=0.5221), suggesting that

executives of CSR conscious firms do not trade on these two types of future news. 28

5. Conclusion

Prior literature on insider trading has focused on federal level and firm-level

regulations as constraints. We examine whether reputational capital created by a firm’s

CSR activities also constrains executives’ insider trading behavior. Using MSCI’s CSR

ratings data, we find that executives of CSR conscious firms make significantly lower

profits from their purchases than executives of non-CSR conscious firms, suggesting that

CSR indeed constrains insider trading. Our inference is robust to controlling for firm risk,

information asymmetry, and insider trading restrictions. We further show that the

environmental dimension of CSR is the dominant constraint for executives’ insider

trading profits.

Complementing our main analyses, we document that the adoption of new CSR

initiatives (i.e., firms turning from non-CSR conscious to CSR conscious) is associated

with a subsequent decline in executives’ insider trading profits. Further, the negative

relation between CSR and insider trading profits also exists for newly appointed

executives from the outside, who do not initiate the firm’s CSR orientation but are likely

constrained by it. We also show that the constraining effects of CSR on executive insider

trading profits are concentrated in weakly governed firms.

28 We also follow Piotroski and Roulstone (2005) and examine whether the purchase ratio (number of shares purchased/sum of number of shares purchased and number of shares sold) is associated with future news contained in change in earnings and market returns. Results (not reported) are also consistent with executives of CSR conscious firms being more constrained from trading on future news.

28

We also conduct a number of robustness tests. We find that executives of CSR

conscious firms make lower insider trading profits compared to executives of propensity-

matched non-CSR conscious firms. Furthermore, our results are robust to controlling for

media coverage and executive compensation. We also present evidence that CSR

constrains insider trading for executives, but not for lower-level officers. Finally, we

document that executives of CSR conscious firms are less likely to purchase on

foreknowledge of future corporate news.

Collectively, our findings suggest that CSR constrains executives’ insider trading

activities. We contribute to the insider trading literature by providing empirical evidence

supporting the often conjectured constraining effects of reputational concerns on insider

trading. We also contribute to the CSR literature by suggesting an economic channel

through which CSR constrains opportunistic managerial behavior, i.e., via its connection

with a firm’s reputational capital.

29

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Appendix: Variable Definitions

Variables Definition Corporate Social Responsibility MeasuresCSR scoret-1 Total number of strengths minus total number of concerns in the following

MSCI’s rating categories: Environment, Community, Employee Relations, Diversity, Product, and involvement in the alcohol, gambling, tobacco, firearms, military, and nuclear power controversial industry sectors, measured in year t-1.

CSRt-1 An indicator variable equal to one if the CSR score in year t-1 is positive and zero otherwise.

Post An indicator variable equal to one for executive trades during the first year after the firm turns CSR conscious, and zero for their trades during the most recent year before that.

CSR_Environmentt-1 An indicator variable equal to one if the total number of strengths is greater the total number of concerns in the environmental dimension of CSR in year t-1.

CSR_Communityt-1 An indicator variable equal to one if the total number of strengths is greater the total number of concerns in the community dimension of CSR in year t-1.

CSR_Employee Relationt-1 An indicator variable equal to one if the total number of strengths is greater the total number of concerns in the employee relation dimension of CSR in year t-1.

CSR_Diversityt-1 An indicator variable equal to one if the total number of strengths is greater the total number of concerns in the diversity dimension of CSR in year t-1.

CSR_Productt-1 An indicator variable equal to one if the total number of strengths is greater the total number of concerns in the product dimension of CSR in year t-1.

Dependent Variables Trading Profitt (%) The average daily abnormal return, stated in percentage terms, over the 180 days

following each trade in year t. Computed as the intercept of the Fama-French four factor model (market return, book-to-market, size, and momentum) for purchases and negative of the intercept for sales.

Purchaset An indicator variable equal to one if any executive of the firm purchased shares in an open-market transaction during year t and total shares purchased by executives are greater than or equal to total shares sold by executives, zero otherwise.

Control Variables BTMt-1 Book-to-market ratio (book value of equity over market value of equity) at the

end of year t-1. LogMVt-1 Natural logarithm of market value of equity at the end of the year t-1. R&Dt-1 An indicator variable equal to one if a firm has positive R&D expenses in year t-

1, and zero otherwise. Losst-1 An indicator variable equal to one if a firm reports negative earnings before

extraordinary items for year t-1, and zero otherwise. Volatilityt-1 Variance of daily stock returns over the interval (-380, -20) before the trade. LogAnalystt-1 Natural logarithm of one plus the number of analysts following the firm in year t-

1. Turnovert-1 The logarithm of trading volume over the (-380, -20) interval before the trade

over shares outstanding. Restrictt-1 An indicator variable set to one if 75% or more of trades during year t-1 occur

in a 30-day window following an earnings announcement, and zero otherwise. Free Cash Flowt-1 Cash flow from operations minus cash flow used in investing activities during

year t-1, deflated by total assets at the end of year t-1. Institutional Ownershipt-1 Percentage of institutional holdings at the end of year t-1. Firm Aget-1 The number of years the firm has been listed on CRSP at the end of year t-1. Market Sharet-1 The firm’s fraction of sales in its two-digit SIC industry in year t-1. Weak Govt-1 An indicator variable equal to one for firms with the Gompers et al.’s (2003)

governance index in year t-1 above sample median and zero otherwise. ∆Et+1 The change in earnings from year t to year t+1, deflated by the total assets at the

end of year t.

35

MARett+1(t) The twelve-month buy-and-hold market-adjusted return over year t+1 (t). Mediat The average daily number of news articles in Factiva covering a firm in fiscal

year t. Compensationt Natural logarithm of the median total compensation of the top five most highly

paid executives in year t.

36

Table 1: Descriptive statistics

This table reports descriptive statistics of the sample. We merge the U.S. firms covered by MSCI with the Thomson Financial Insider Filing Data, and obtain open-market transactions of executive officers. CSR scoret-1 is the total number of strengths minus total number of concerns in the following MSCI’s rating categories: Environment, Community, Employee Relations, Diversity, Product, and involvement in the alcohol, gambling, tobacco, firearms, military, and nuclear power controversial industry sectors, measured in the year prior to the insider trade (i.e., t-1). CSRt-1 is equal to one for firms with a positive CSR score in year t-1 and zero otherwise. BTMt-1 is book value of equity over market value of equity at the end of year t-1. LogMVt-1 is the natural logarithm of market value of equity at the end of year t-1. R&Dt-1 is an indicator variable equal to one if a firm has positive R&D expenses in year t-1, and zero otherwise. Losst-1 is an indicator variable equal to one if a firm reports negative earnings before extraordinary items in year t-1, and zero otherwise. Volatilityt-1 is the variance of daily stock returns over the interval (-380, -20) before the trade. LogAnalystt-1 is the natural logarithm of one plus the number of analysts following the firm in year t-1. Turnovert-1 is the logarithm of trading volume over the (-380, -20) interval before the trade over shares outstanding.Restrictt-1 is an indicator variable set to one if 75% or more of trades during year t-1 occur in a 30-day window following an earnings announcement, and zero otherwise. N=56,966. Mean Median Std. Dev. Q1 Q3

CSR scoret-1 -0.1741 0 2.0320 -1 1 CSRt-1 0.2818 0 0.4499 0 1 BTMt-1 0.4304 0.3652 0.3382 0.2175 0.5686 LogMVt-1 7.2662 7.0345 1.4701 6.1934 8.1178 R&Dt-1 0.4312 0 0.4952 0 1 Losst-1 0.1580 0 0.3647 0 0 Volatilityt-1 0.0010 0.0007 0.0010 0.0004 0.0011 LogAnalystt-1 2.2391 2.3026 0.8315 1.7918 2.8332 Turnovert-1 0.6343 0.6687 0.8069 0.1086 1.1971 Restrictt-1 0.2570 0 0.4370 0 1

37

Table 2: CSR orientation and executives’ insider trading profit

This table reports analyses of trade-specific profits over the 180 days following executives’ insider trades. The trading profits are estimated using the following transaction specific regression of daily returns on four common factors over the 180 days after each transaction: Ri – R = α + β1(Rmkt – Rf) + β2 SMB + β3 HML + β4 UMD + ε Ri is the daily return of firm i’s equity. Rf is the daily risk-free interest rate. Rmkt is the CRSP value-weighted market return. SMB, HML, and UMD are the size, book-to-market, and momentum factors. Trading profits are equal to α (-α) for purchases (sales). Panel A: Univariate analysis This panel reports mean and median average daily trading profits of CSR conscious firms vs. non-CSR conscious firms over the 180, 120, and 90 days following the trades. Trading profits of purchases and sales are separately presented in percentage terms. t-tests (Wilcoxon tests) are used to test differences in means (medians). The trading profits numbers in bold are statistically significant at the 10% level. Purchases Sales

N

Mean (%)

Median (%)

N

Mean (%)

Median (%)

CSR conscious firms Profit (t + 180) 2930 0.0402 0.0374 13121 -0.0150 -0.0142

Profit (t + 120) 2930 0.0600 0.0573 13121 -0.0148 -0.0140

Profit (t + 90) 2930 0.0619 0.0535 13121 -0.0111 -0.0088

Non-CSR conscious firms Profit (t + 180) 8039 0.0568 0.0536 32876 -0.0121 -0.0120

Profit (t + 120) 8039 0.0810 0.0733 32876 -0.0062 -0.0102

Profit (t + 90) 8039 0.0919 0.0854 32876 -0.0057 -0.0116

Difference Profit (t + 180) -0.0166 -0.0162 -0.0029 -0.0022

Profit (t + 120) -0.0210 -0.0160 -0.0085 -0.0039

Profit (t + 90) -0.0300 -0.0319 -0.0054 0.0028

38

Panel B. Regression analysis This table reports the estimation results of the following regression: Trading Profitt = α + β1 CSRt-1 + β2 BTMt-1 + β3 LogMVt-1 + β4 R&Dt-1 + β5 Losst-1 + β6 Volatilityt-1 + β7 LogAnalystt-1 + β8 Turnovert-1 + β9 Restrictt-1 + εt Trading Profitt is the estimated average daily abnormal return over the 180 days following the trade in year t, stated in percentage terms. CSRt-1 is equal to one for firms with a positive CSR score in year t-1 and zero otherwise. BTMt-1 is book value of equity over market value of equity at the end of year t-1. LogMVt-1 is the natural logarithm of market value of equity at the end of year t-1. R&Dt-1 is an indicator variable equal to one if a firm has positive R&D expenses in year t-1, and zero otherwise. Losst-1 is an indicator variable equal to one if a firm reports negative earnings before extraordinary items in year t-1, and zero otherwise. Volatilityt-1 is the variance of daily stock returns over the interval (-380, -20) before the trade. LogAnalystt-1 is the natural logarithm of one plus the number of analysts following the firm in year t-1. Turnovert-1 is the logarithm of trading volume over the (-380, -20) interval before the trade over shares outstanding. Restrictt-

1 is an indicator variable set to one if 75% or more of trades during year t-1 occur in a 30-day window following an earnings announcement, and zero otherwise. The regressions are estimated for purchases only. Standard errors are robust standard errors clustered by person.

Profit (t + 180) Profit (t + 120) Profit (t + 90)

Estimate p-value Estimate p-value Estimate p-value

Intercept 0.0247 0.2346 0.0333 0.2020 0.0368 0.2622

CSRt-1 -0.0181 0.0074 -0.0233 0.0111 -0.0348 0.0028

BTMt-1 0.0075 0.3544 0.0012 0.9160 -0.0146 0.2871

LogMVt-1 0.0028 0.3362 0.0027 0.4926 0.0030 0.5459

R&Dt-1 0.0119 0.1069 0.0114 0.2739 0.0186 0.1455

Losst-1 0.0003 0.9718 0.0113 0.3698 0.0186 0.2073

Volatilityt-1 12.5325 <.0001 20.2777 <.0001 30.4488 <.0001

LogAnalystt-1 -0.0027 0.5807 0.0008 0.9051 0.0054 0.4718

Turnovert-1 -0.0074 0.1204 -0.0094 0.171 -0.0135 0.0998

Restrictt-1 0.0010 0.8819 0.0091 0.3154 -0.0070 0.5098

N 10969 10969 10969

R2 (%) 0.84 1.08 1.55

39

Table 3: CSR orientation and executives’ insider trading profits – Dimensions of CSR

This table reports the estimation results of the following regression to estimate the relation between CSR orientation and executives’ insider trading profits by dimensions of CSR: Trading Profitt = α + β1 CSR_Environmentt-1 + β2 CSR_Communityt-1 + β3 CSR_Employee Relationst-1 + β4

CSR_Diversityt-1 + β5 CSR_Productt-1 + β6 BTMt-1 + β7 LogMVt-1 + β8 R&Dt-1 + β9 Losst-1 + β10 Volatilityt-1

+ β11 LogAnalystt-1 + β12 Turnovert-1 + β13 Restrictt-1 + εt

Trading Profitt is the estimated average daily abnormal return over the 180 days following the trade, stated in percentage terms. For CSR_Environmentt-1, CSR_Communityt-1, CSR_Employee Relationst-1, CSR_Diversityt-1, and CSR_Productt-1, each variable is equal to one for firms with a positive CSR score in the corresponding CSR dimension (i.e., total number of strengths is greater than total number of concerns in each CSR dimension) and zero otherwise. LogMVt-1 is the natural logarithm of market value of equity at the end of year t-1. R&Dt-1 is an indicator variable equal to one if a firm has positive R&D expenses in year t-1, and zero otherwise. Losst-1 is an indicator variable equal to one if a firm reports negative earnings before extraordinary items in year t-1, and zero otherwise. Volatilityt-1 is the variance of daily stock returns over the interval (-380, -20) before the trade. LogAnalystt-1 is the natural logarithm of one plus the number of analysts following the firm in year t-1. Turnovert-1 is the logarithm of trading volume over the (-380, -20) interval before the trade over shares outstanding. Restrictt-1 is an indicator variable set to one if 75% or more of trades during year t-1 occur in a 30-day window following an earnings announcement, and zero otherwise. The regression is estimated for purchases only. Standard errors are robust standard errors clustered by person.

Estimate p-value

Intercept 0.0234 0.2803

CSR_Environmentt-1 -0.0239 0.0315

CSR_Communityt-1 -0.0034 0.6927

CSR_Employee Relationst-1 0.0009 0.9035

CSR_Diversityt-1 -0.0045 0.5476

CSR_Productt-1 -0.0162 0.1933

BTMt-1 0.0079 0.3319

LogMVt-1 0.0027 0.3716

R&Dt-1 0.0140 0.0624

Losst-1 0.0011 0.9147

Volatilityt-1 11.8863 0.0002

LogAnalystt-1 -0.0029 0.5581

Turnovert-1 -0.0072 0.1370

Restrictt-1 0.0012 0.8625

N 10969

R2 (%) 0.82

40

Table 4: New CSR initiatives and executives’ insider trading profits

This table reports the estimation results of the following regression to estimate the relation between a firm’s CSR orientation and executives’ insider trading profits for firms rising from non-CSR conscious to CSR conscious: Trading Profitt = α + β1 Post + β2 BTMt-1 + β3 LogMVt-1 + β4 R&Dt-1 + β5 Losst-1 + β6 Volatilityt-1 + β7 LogAnalystt-1 + β8 Turnovert-1 + β9 Restrictt-1 + εt Trading Profitt is the estimated average daily abnormal return over the 180 days following the trade, stated in percentage terms. Post is an indicator variable equal to one for executive trades during the first year after the firm turns CSR conscious, and zero for their trades during the most recent year before that. BTMt-1 is book value of equity over market value of equity at the end of year t-1. LogMVt-1 is the natural logarithm of market value of equity at the end of year t-1. R&Dt-1 is an indicator variable equal to one if a firm has positive R&D eFxpenses in year t-1, and zero otherwise. Losst-1 is an indicator variable equal to one if a firm reports negative earnings before extraordinary items in year t-1, and zero otherwise. Volatilityt-1 is the variance of daily stock returns over the interval (-380, -20) before the trade. LogAnalystt-1 is the natural logarithm of one plus the number of analysts following the firm in year t-1. Turnovert-1 is the logarithm of trading volume over the (-380, -20) interval before the trade over shares outstanding. Restrictt-1 is an indicator variable set to one if 75% or more of trades during year t-1 occur in a 30-day window following an earnings announcement, and zero otherwise. The regression is estimated only for firms that experience a change in CSR orientation and for insider purchases only. Standard errors are robust standard errors clustered by person.

Estimate p-value

Intercept 0.1702 0.011

Post -0.0553 0.0067

BTMt-1 0.0158 0.3932

LogMVt-1 -0.0143 0.0878

R&Dt-1 0.0088 0.6926

Losst-1 -0.0934 <.0001

Volatilityt-1 16.1670 0.0299

LogAnalystt-1 0.0060 0.5500

Turnovert-1 0.0028 0.7458

Restrictt-1 -0.0163 0.4279

N 724

R2 (%) 6.47

41

Table 5: CSR orientation and new executives’ insider trading profits

This table reports the estimation results of the following regression to estimate the relation between CSR orientation and insider trading profits of new executives hired from outside the firm: Trading Profitt = α + β1 CSRt-1 + β2 BTMt-1 + β3 LogMVt-1 + β4 R&Dt-1 + β5 Losst-1 + β6 Volatilityt-1 + β7 LogAnalystt-1 + β8 Turnovert-1 + β9 Restrictt-1 + εt Trading Profitt is the estimated average daily abnormal return over the 180 days following the trade, stated in percentage terms. CSRt-1 is equal to one for firms with a positive CSR score in year t-1 and zero otherwise. BTMt-1 is book value of equity over market value of equity at the end of year t-1. LogMVt-1 is the natural logarithm of market value of equity at the end of year t-1. R&Dt-1 is an indicator variable equal to one if a firm has positive R&D expenses in year t-1, and zero otherwise. Losst-1 is an indicator variable equal to one if a firm reports negative earnings before extraordinary items in year t-1, and zero otherwise. Volatilityt-1 is the variance of daily stock returns over the interval (-380, -20) before the trade. LogAnalystt-1 is the natural logarithm of one plus the number of analysts following the firm in year t-1. Turnovert-1 is the logarithm of trading volume over the (-380, -20) interval before the trade over shares outstanding. Restrictt-

1 is an indicator variable set to one if 75% or more of trades during year t-1 occur in a 30-day window following an earnings announcement, and zero otherwise. The regression is estimated for purchases by new executives hired from outside the firm only. We identify these two executives using two alternative approaches. The first approach (reported in column (1)) relies on the TFN insider filing data. The second approach (reported in column (2)) relies on the Execucomp data. Standard errors are robust standard errors clustered by person.

(1) (2)

Estimate p-value Estimate p-value

Intercept 0.0274 0.6557 0.1014 0.3616

CSRt-1 -0.0508 0.0176 -0.0580 0.0532

BTMt-1 0.0115 0.6841 -0.0932 0.0705

LogMVt-1 0.0152 0.0607 0.0110 0.4137

R&Dt-1 0.0360 0.1098 0.0444 0.1976

Losst-1 -0.0327 0.2791 -0.0689 0.1138

Volatilityt-1 19.0939 0.0698 47.0780 0.0043

LogAnalystt-1 -0.0351 0.0160 -0.0270 0.3720

Turnovert-1 -0.0165 0.2643 -0.0410 0.0854

Restrictt-1 -0.0322 0.1312 -0.0427 0.1527

N 720 260

R2 (%) 6.16 10.62

42

Table 6: CSR orientation and executives’ insider trading profits – Role of corporate governance

This table examines whether the association between CSR orientation and executives’ insider trading profits varies with corporate governance as captured by Gompers et al.’s (2003) governance index by running the following regression for the strong governance (governance index above sample median) and weak governance (governance index below sample median) groups separately: Trading Profitt = α + β1 CSRt-1 + β2 BTMt-1 + β3 LogMVt-1 + β4 R&Dt-1 + β5 Losst-1 + β6 Volatilityt-1 + β7 LogAnalystt-1 + β8 Turnovert-1 + β9 Restrictt-1 + εt Trading Profitt is the estimated average daily abnormal return over the 180 days following the trade, stated in percentage terms. CSRt-1 is equal to one for firms with a positive CSR score in year t-1 and zero otherwise. BTMt-1 is book value of equity over market value of equity at the end of year t-1. LogMVt-1 is the natural logarithm of market value of equity at the end of year t-1. R&Dt-1 is an indicator variable equal to one if a firm has positive R&D expenses in year t-1, and zero otherwise. Losst-1 is an indicator variable equal to one if a firm reports negative earnings before extraordinary items in year t-1, and zero otherwise. Volatilityt-1 is the variance of daily stock returns over the interval (-380, -20) before the trade. LogAnalystt-1 is the natural logarithm of one plus the number of analysts following the firm in year t-1. Turnovert-1 is the logarithm of trading volume over the (-380, -20) interval before the trade over shares outstanding. Restrictt-

1 is an indicator variable set to one if 75% or more of trades during year t-1 occur in a 30-day window following an earnings announcement, and zero otherwise. Standard errors are robust standard errors clustered by person.

Weak Governance Strong Governance

Estimate p-value Estimate p-value

Intercept 0.0424 0.3260 0.0139 0.7560

CSRt-1 -0.0310 0.0031 0.0130 0.3095

BTMt-1 0.0103 0.5118 0.0016 0.9400

LogMVt-1 0.0063 0.2584 0.0032 0.6050

R&Dt-1 0.0055 0.6349 0.0317 0.0321

Losst-1 0.0238 0.1792 -0.0093 0.6624

Volatilityt-1 13.1285 0.0662 1.6635 0.8357

LogAnalystt-1 -0.0182 0.0093 -0.0069 0.5463

Turnovert-1 0.0029 0.7410 -0.0079 0.2958

Restrictt-1 -0.0165 0.1333 0.0038 0.7893

N 2649 2465

R2 (%) 2.17 0.86

43

Table 7: CSR orientation and executives’ insider trading profits – Propensity score matching

This table reports the relation between CSR and executives’ insider trading profits when each CSR conscious firm-year is matched with a non-CSR conscious control firm-year with the closest propensity score. Panel A: Logistic regression to model CSR consciousness This panel reports the estimation results of the following first stage logistic regression to model CSR conscious firms: Prob(CSRt-1=1) = logit( α + β1 BTMt-1 + β2 LogMVt-1 + β3 R&Dt-1 + β4 Losst-1 + β5 Volatilityt-1 + β6 LogAnalystt-1 + β7 Turnovert-1 + β8 Restrictt-1 + β9 Turnovert-1 + β10 Free Cash Flowt-1 + β11 Institutional Ownershipt-1 + β12 Firm Aget-1 + β13 Market Sharet-1 + εt) CSRt-1 is equal to one for firms with a positive CSR score in year t-1 and zero otherwise. BTMt-1 is book value of equity over market value of equity at the end of year t-1. LogMVt-1 is the natural logarithm of market value of equity at the end of year t-1. R&Dt-1 is an indicator variable equal to one if a firm has positive R&D expenses in year t-1, and zero otherwise. Losst-1 is an indicator variable equal to one if a firm reports negative earnings before extraordinary items in year t-1, and zero otherwise. Volatilityt-1 is the variance of daily stock returns over the interval (-380, -20) before the trade. LogAnalystt-1 is the natural logarithm of one plus the number of analysts following the firm in year t-1. Turnovert-1 is the logarithm of trading volume over the (-380, -20) interval before the trade over shares outstanding. Restrictt-1 is an indicator variable set to one if 75% or more of trades during year t-1 occur in a 30-day window following an earnings announcement, and zero otherwise. Free Cash Flowt-1 is cash flow from operations minus cash flow used in investing in year t-1 deflated by total assets at the end of year t-1. Institutional Ownershipt-1 is the percentage of institutional holdings at the end of year t-1. Firm Aget-1 is the number of years the firm has been listed on CRSP at the end of year t-1. Market Sharet-1 is the firm’s fraction of sales in its two-digit SIC industry in year t-1.

Estimate p-value

Intercept -5.5809 0.9694

BTMt-1 0.0869 0.4364

LogMVt-1 0.2936 <.0001

R&Dt-1 0.3161 0.0256

Losst-1 -0.0088 0.9373

Volatilityt-1 17.8338 0.6434

LogAnalystt-1 -0.0340 0.5650

Turnovert-1 0.1197 0.0811

Restrictt-1 -0.0297 0.6989

Free Cash Flowt-1 -0.1591 0.5121

Institutional Ownershipt-1 0.5114 0.0080

Firm Aget-1 0.0619 0.1792

Market Sharet-1 -0.9783 0.3790

Industry fixed effects Yes

Year fixed effects Yes

N of firm-years 4273

N of CSR=1 1240

Pseudo R2 0.14249

44

Panel B: Propensity score matching results This panel reports mean and median average daily trading profits (stated in percentage terms) for executives of CSR conscious firms vs. propensity-matched non-CSR conscious firms over the 180days following the trades. t-tests (Wilcoxon tests) are used to test differences in means (medians). The trading profit numbers in bold are statistically significant at the 1% level. N Mean (%) Median (%)

CSR conscious firms 2492 0.0390 0.0370

Matched firms 2639 0.0561 0.0436

Difference -0.0171 -0.0066

45

Table 8: CSR orientation and executives’ insider trading profits – Additional control variables

This table reports the estimation results of the following regression: Trading Profitt = α + β1 CSRt-1 + β2 BTMt-1 + β3 LogMVt-1 + β4 R&Dt-1 + β5 Losst-1 + β6 Volatilityt-1 + β7 LogAnalystt-1 + β8 Turnovert-1 + β9 Restrictt-1 + β10 Additional Control + εt Trading Profitt is the estimated average daily abnormal return over the 180 days following the trade, stated in percentage terms. CSRt-1 is equal to one for firms with a positive CSR score in year t-1 and zero otherwise. BTMt-1 is book value of equity over market value of equity at the end of year t-1. LogMVt-1 is the natural logarithm of market value of equity at the end of year t-1. R&Dt-1 is an indicator variable equal to one if a firm has positive R&D expenses in year t-1, and zero otherwise. Losst-1 is an indicator variable equal to one if a firm reports negative earnings before extraordinary items in year t-1, and zero otherwise. Volatilityt-1 is the variance of daily stock returns over the interval (-380, -20) before the trade. LogAnalystt-1 is the natural logarithm of one plus the number of analysts following the firm in year t-1. Turnovert-1 is the logarithm of trading volume over the (-380, -20) interval before the trade over shares outstanding. Restrictt-

1 is an indicator variable set to one if 75% or more of trades during year t-1 occur in a 30-day window following an earnings announcement, and zero otherwise. The additional control variable is either Mediat or Compensationt. Mediat is the average daily number of news articles in Factiva covering a firm in year t. Compensationt is the natural logarithm of the median total compensation of the top five most highly paid executives in year t. The regression is estimated for purchases only. Standard errors are robust standard errors clustered by person.

(1) (2)

Estimate p-value Estimate p-value

Intercept 0.0480 0.0312 0.0173 0.6618

CSRt-1 -0.0152 0.0319 -0.0142 0.0576

BTMt-1 0.0026 0.7636 -0.0068 0.5111

LogMVt-1 -0.0030 0.4895 -0.0059 0.1907

R&Dt-1 0.0100 0.1986 0.0058 0.4809

Losst-1 -0.0035 0.7439 0.0036 0.7682

Volatilityt-1 11.6610 0.0001 11.1499 0.0111

LogAnalystt-1 -0.0025 0.6312 -0.0124 0.0217

Turnovert-1 -0.0098 0.0643 -0.0085 0.1448

Restrictt-1 -0.0004 0.9574 0.0040 0.6120

Mediat 0.0047 0.2435

Compensationt 0.0152 0.0355

N 9611 6427

R2 (%) 0.82 1.20

46

Table 9: CSR orientation and executives’ insider trading profits – Lower-level managers

This table reports the estimation results of the following regression for the trades made by lower-level managers: Trading Profitt = α + β1 CSRt-1 + β2 BTMt-1 + β3 LogMVt-1 + β4 R&Dt-1 + β5 Losst-1 + β6 Volatilityt-1 + β7 LogAnalystt-1 + β8 Turnovert-1 + β9 Restrictt-1 + εt Trading Profitt is the estimated average daily abnormal return over the 180 days following the trade, stated in percentage terms. CSRt-1 is equal to one for firms with a positive CSR score year t and zero otherwise. BTMt-1 is book value of equity over market value of equity at the end of year t-1. LogMVt-1 is the natural logarithm of market value of equity at the end of year t-1. R&Dt-1 is an indicator variable equal to one if a firm has positive R&D expenses in year t-1, and zero otherwise. Losst-1 is an indicator variable equal to one if a firm reports negative earnings before extraordinary items in year t-1, and zero otherwise. Volatilityt-1 is the variance of daily stock returns over the interval (-380, -20) before the trade. LogAnalystt-1 is the natural logarithm of one plus the number of analysts following the firm in year t-1. Turnovert-1 is the logarithm of trading volume over the (-380, -20) interval before the trade over shares outstanding. Restrictt-1 is an indicator variable set to one if 75% or more of trades during year t-1 occur in a 30-day window following an earnings announcement, and zero otherwise. The regression is estimated for purchases only. Standard errors are robust standard errors clustered by person.

Estimate p-value

Intercept 0.0787 0.0002

CSRt-1 0.0056 0.3382

BTMt-1 0.0138 0.0745

LogMVt-1 -0.0043 0.1372

R&Dt-1 -0.0015 0.8333

Losst-1 -0.0159 0.1807

Volatilityt-1 13.6621 <.0001

LogAnalystt-1 -0.0052 0.1791

Turnovert-1 0.0019 0.6863

Restrictt-1 -0.0005 0.9331

N 7085

R2 (%) 1.55

47

Table 10: CSR orientation and executives’ likelihood of trading on future news

This table reports the estimation results of the following regression: Prob(Purchaset=1) = logit(α + β1 Earnt+1+ β2 MARett+1 + β3 BTMt + β4 LogMVt + β5 MARett + β6 R&Dt + εt) Purchaset is an indicator variable equal to one if any executive of the firm purchased shares in an open-market transaction during year t and total shares purchased by executives are greater than or equal to total shares sold by executives, zero otherwise. Earnt+1 is the change in earnings from year t to year t+1, deflated by the total assets at the end of year t. MARett+1 is the buy-and-hold market-adjusted return over year t+1. BTMt is book value of equity over market value of equity at the end of year t. LogMVt is the natural logarithm of market value of equity at the end of year t. MARett is the buy-and-hold market-adjusted return over year t. R&Dt is an indicator variable equal to one if a firm has positive R&D expenses in year t, and zero otherwise. Standard errors are robust standard errors clustered by firm and year.

Non-CSR conscious firms CSR-conscious firms

Estimate p-value Estimate p-value

Intercept -0.6078 0.0017 -0.9796 0.0004

Earnt+1 0.6606 0.0399 0.1308 0.8174

MARett+1 0.1163 0.0901 0.0681 0.5221

BTMt 0.4895 <.0001 0.6862 <.0001

LogMVt -0.231 <.0001 -0.1853 <.0001

MARett -0.4156 <.0001 -0.3123 0.0107

R&Dt -0.1391 0.0398 -0.1266 0.2307

N 16371 7411

R2 (%) 3.13 2.91