Short Selling and Earnings Management:
`A Controlled Experiment*
`
`
`
`Vivian W. Fang a
`University of Minnesota
`
`Allen H. Huang b
`Hong Kong University of Science and Technology
`
`Jonathan Karpoff c
`University of Washington
`
`This draft: November 16, 2014
`
`
`
`Abstract
`
`
`
`
`During 2005-2007, the SEC ordered a pilot program in which one-third of the Russell 3000 were
`arbitrarily chosen as pilot stocks and exempted from short-sale price tests. Pilot firms’ discretionary
`accruals and likelihood of marginally beating earnings targets decrease during this period, and revert to
`pre-experiment levels when the program ends. After the program starts, pilot firms are more likely to be
`caught for fraud initiated before the program, and their stock returns better incorporate earnings
`information. These results indicate that short selling, or its prospect, works to curb earnings management,
`helps to detect fraud, and improves price efficiency.
`
`JEL classifications: G14; G18; G19; M41; M48
`
`Keywords: Regulation SHO; Pilot Program; Short Selling; Earnings Management; Fraud Discovery;
`Price Efficiency
`
`______________________________
`
` *
`
` We are grateful for helpful comments from two anonymous referees, an anonymous associate editor, Kenneth
`Singleton (the editor), Vikas Agarwal, Mark Chen, John Core, Hemang Desai, Jarrad Harford, Adam Kolasinski,
`Paul Ma, Scott Richardson, Ed Swanson, Jake Thornock, Wendy Wilson, and seminar participants at Cheung Kong
`Graduate School of Business, Peking University, CEAR/GSU Finance Symposium on Corporate Control
`Mechanisms and Risk, FARS Midyear Meeting, HKUST Accounting Symposium, CFEA Conference, and UC
`Berkeley Multi-disciplinary Conference on Fraud and Misconduct. We are grateful to Russell Investments for
`providing the list of 2004 Russell 3000 index, and to Jerry Martin for providing the KKLM data on financial
`misrepresentation. Huang gratefully acknowledges financial support from a grant from the Research Grants Council
`of the HKSAR, China (Project No., HKUST691213).
` a Email: fangw@umn.edu, Carlson School of Management, University of Minnesota, Minneapolis, MN 55455,
`USA.
`b Email: allen.huang@ust.hk, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon,
`Hong Kong
`c Email: karpoff@uw.edu, Foster School of Business, University of Washington, Seattle, WA 98195, USA.
`
`
`
`Coalition for Affordable Drugs IV LLC - Exhibit 1036
`
`

`
`
`
`
`
`Short Selling and Earnings Management: A Controlled Experiment
`
`I. Introduction
`
`Previous research shows that short sellers can identify earnings manipulation and fraud before
`
`they are publicly revealed.1 But this is for earnings manipulations that already have taken place. Might
`
`short selling also constrain firms’ incentives to manipulate or misrepresent earnings in the first place?
`
`That is, does the prospect of short selling help improve the quality of firms’ financial reporting?
`
`In this paper we exploit a natural experiment that allows us to address this question. In July 2004,
`
`the Securities and Exchange Commission (SEC) adopted a new regulation governing short selling
`
`activities in the U.S. equity markets – Regulation SHO. Regulation SHO contained a Rule 202T pilot
`
`program in which every third stock ranked by trading volume within each exchange was drawn from the
`
`Russell 3000 index and designated as a pilot stock. From May 2, 2005 to August 6, 2007, pilot stocks
`
`were exempted from short-sale price tests, including the tick test for exchange-listed stocks and the bid
`
`test for Nasdaq National Market Stocks.2
`
`The pilot program creates an ideal setting to examine the effect of short selling on corporate
`
`financial reporting decisions, for three reasons. First, the exemption from short-sale price tests decreased
`
`the cost of short selling in the pilot stocks relative to the non-pilot stocks (see the SEC’s Office of
`
`Economic Analysis, 2007; Diether, Lee, and Werner, 2009). The pilot program thus eliminates the need
`
`to estimate short selling costs directly, a notoriously difficult task (see Lamont, 2012). Rather, we use the
`
`fact that the prospect of short selling increased in the pilot firms relative to the non-pilot firms, all else
`
`being equal. Second, the pilot program represents a truly exogenous shock to the cost of selling short in
`
`the affected firms. We can identify no evidence that the firms themselves lobbied for the pilot program,
`
`or that any individual firm could know it would be in the pilot group until the program was announced.
`
`
`1 See Dechow, Sloan, and Sweeney (1996), Christophe, Ferri, and Angel (2004), Efendi, Kinney, and Swanson
`(2005), Desai, Krishnamurthy, and Venkataraman (2006), and Karpoff and Lou (2010).
`2 The pilot program was originally scheduled to commence on January 3, 2005 and end on December 31, 2005
`(Securities Exchange Act Release No. 50104, July 28, 2004). However, the SEC postponed the commencement date
`to May 2, 2005 (Securities and Exchange Act Release No. 50747, November 29, 2004) and extended the end date to
`August 6, 2007 (Securities and Exchange Act Release No. 53684, April 20, 2006).
`
`
`
`1
`
`
`Coalition for Affordable Drugs IV LLC - Exhibit 1036
`
`

`
`
`
`Third, the pilot program had specific beginning and ending dates, facilitating a difference-in-differences
`
`(hereafter, DiD) analysis of the impact of short selling costs on firms’ financial reporting. The known
`
`ending date allows us to investigate whether the effects of the pilot program reversed when it ended – an
`
`important check on the internal validity of the DiD tests (e.g., see Roberts and Whited, 2012).
`
`We begin by verifying that pilot firms represent a random draw from the Russell 3000 population.
`
`In the fiscal year before the pilot program, the pilot and non-pilot firms are similar in size, growth,
`
`corporate spending, profitability, leverage, and dividend payout. Although the two groups of firms also
`
`exhibit similar levels of discretionary accruals before the program, pilot firms significantly reduce their
`
`discretionary accruals once the program starts. 3 After the program ends, pilot firms’ discretionary
`
`accruals revert to pre-program levels. The non-pilot firms, meanwhile, show no significant change in
`
`their discretionary accruals around the pilot program. Our point estimates indicate that performance-
`
`matched discretionary accruals, as a percentage of assets, are one percentage point lower for the pilot
`
`firms than for the non-pilot firms during the three-year pilot program compared to the three-year pre-pilot
`
`period. This corresponds to 7.4% of the standard deviation of discretionary accruals in our sample.
`
`We also examine the pilot program’s effect on two alternative measures of earnings management.
`
`First, we find that the likelihood of beating the analyst consensus forecast by up to one cent is 1.8
`
`percentage points lower for the pilot firms than the non-pilot firms during the pilot program. This
`
`represents 11.1% of the unconditional likelihood of meeting or just beating analysts’ forecast in our
`
`sample. Similarly, the likelihood of meeting or just beating the firm’s quarterly EPS in the same quarter
`
`of the prior year is 0.8 percentage points lower for the pilot firms, representing 14.2% of the
`
`unconditional likelihood. Second, we find that the likelihood of being classified as a misstating firm,
`
`based on the F-score of Dechow et al. (2011), is significantly lower for the pilot firms during the pilot
`
`
`3 Following the literature (e.g., Kothari, Leone, and Wasley, 2005), we measure discretionary accruals as the
`difference between actual accruals and a benchmark estimated within each industry-year. Details are provided in
`Section III.C.
`
`
`
`2
`
`
`Coalition for Affordable Drugs IV LLC - Exhibit 1036
`
`

`
`
`
`period. Combined with our results regarding discretionary accruals, these results indicate that pilot firms
`
`decrease their earnings management during the pilot program.
`
` We consider several alternative interpretations for the patterns we observe in discretionary
`
`accruals. One possibility is that pilot firms’ discretionary accruals reflect changes in their growth,
`
`investment, or equity issuance, as Grullon, Michenaud, and Weston (2014) document a significant
`
`reduction in financially constrained pilot firms’ investment and equity issuance during the pilot program.
`
`We consider several controls for firm growth and investment, both in the construction of our discretionary
`
`accruals measures and as controls in the multivariate tests. None of these controls has a material effect on
`
`our main findings. We also find that the pilot firms’ investment levels do not follow a pattern that would
`
`explain the changes in their discretionary accruals during and after the pilot program. Regarding the
`
`possible impact of equity issuance, we find that pilot firms’ discretionary accruals pattern is similar
`
`among firms that do not seek to issue equity as for the overall sample. These results indicate that the
`
`effect of the pilot program on discretionary accruals is unlikely to be explained by changes in pilot firms’
`
`growth, investment, or equity issuance surrounding the program.
`
`Another possible explanation is that managers of the pilot firms decreased their earnings
`
`management because of a general increase in investors’ attention paid to these firms. Using three
`
`measures of market attention, however, we do not find that pilot firms were subject to greater attention
`
`during the pilot program. In multivariate DiD tests, the market attention measures are not significantly
`
`related to discretionary accruals, nor do they affect our main finding in discretionary accruals.
`
`The most plausible interpretation of our results is that the pilot program reduced the cost of short
`
`selling sufficiently among the pilot firms to increase potential short sellers’ monitoring activities, and that
`
`the increased monitoring induced a decrease in these firms’ earnings management.4 We conduct three
`
`additional tests to further probe this interpretation. First, we find that, among the pilot firms during the
`
`pilot program, short selling is positively related to discretionary accruals. Second, we find that short
`
`
`4 Throughout this paper, we use “potential short sellers” or “short sellers” to refer both to investors who may take
`new short positions and investors with existing short positions.
`
`
`
`3
`
`
`Coalition for Affordable Drugs IV LLC - Exhibit 1036
`
`

`
`
`
`interest increases in months in which firms are later revealed to have engaged in financial
`
`misrepresentation during our sample period. And third, we find that, among firms that had previously
`
`initiated financial fraud, pilot firms are more likely to get caught than control firms after the pilot period
`
`started. We also find that the unconditional likelihood that pilot firms are caught for financial fraud
`
`converges monotonically toward that for non-pilot firms as we sequentially include frauds initiated after
`
`the pilot program begins. This result is consistent with both an increase in the pilot firms’ conditional
`
`likelihood of being caught for any financial frauds they commit, and our finding that pilot firms
`
`endogenously adjust by decreasing their earnings manipulations after the pilot program begins.
`
`Finally, we examine the implications of the pilot program for price efficiency through its effect
`
`on firms’ reporting practices. We show that the pilot firms’ coefficients of current returns on future
`
`earnings increase. Among firms announcing particularly negative earnings surprises, the well-
`
`documented post-earnings announcement drift disappears for pilot firms during the pilot period, while it
`
`remains significant for non-pilot firms. These results indicate that the reduction in pilot firms’ earnings
`
`management during the pilot program corresponds to an increase in the efficiency of their stock prices as
`
`their stock returns better incorporate earnings information.
`
`These findings make four contributions to the literature. First, they show that an increase in the
`
`prospect of short selling has real effects on firms’ financial reporting. This demonstrates one avenue
`
`through which trading in secondary financial markets affects firms’ decisions. 5 Second, our results
`
`highlight one important avenue through which short selling improves price discovery and makes prices
`
`more efficient. Previous research emphasizes how short selling facilitates the flow of private information
`
`into prices (e.g., Miller, 1977; Harrison and Kreps, 1978; Chang, Cheng, and Yu, 2007; Boehmer and Wu
`
`2013). Our findings indicate that the prospect of short selling also improves price efficiency by
`
`decreasing managers’ tendency to manage earnings. Third, our findings identify a new determinant of
`
`
`5 See Bond, Edmans, and Goldstein (2012) for a survey of research on the real effects of financial markets. For
`example, Karpoff and Rice (1989) and Fang, Noe, and Tice (2009) examine the effect of stock liquidity on firm
`performance; Fang, Tian, and Tice (2014) examine the effect of liquidity on innovation; and Grullon, Michenaud,
`and Weston (2014) examine the effect of short selling constraints on investment and equity issuance.
`
`
`
`4
`
`
`Coalition for Affordable Drugs IV LLC - Exhibit 1036
`
`

`
`
`
`earnings management – short-sale constraints – in addition to the factors identified in prior research (for a
`
`review, see Dechow, Ge, and Schrand, 2010). And fourth, these results contribute to the policy debate on
`
`the benefits and costs of short selling. Previous research demonstrates that short sellers frequently are
`
`good at identifying the overpriced shares of firms that have manipulated earnings, and that short sellers’
`
`trading conveys external benefits to other investors by improving market quality and by accelerating the
`
`discovery of financial misconduct. 6 Our results indicate that the prospect of short selling decreases
`
`earnings management and increases price efficiency in general, even among firms that are not charged
`
`with financial reporting violations. This indicates that short selling, or its prospect, conveys external
`
`benefits to investors by improving financial reporting quality and stock price efficiency.
`
`
`
`This paper is organized as follows. Section II describes short-sale price tests in the U.S. equity
`
`markets, how they can affect firms’ tendency to manage earnings, and related research. Section III
`
`describes the data. Section IV reports tests of the effect of Regulation SHO’s pilot program on firms’
`
`earnings management. Section V examines whether short sellers actually increased their scrutiny of the
`
`pilot stocks during the pilot program by comparing the probability of fraud detection between pilot and
`
`non-pilot firms. Section VI reports on tests that examine whether the pilot program coincided with an
`
`increase in the efficiency of pilot firms’ stock prices with respect to earnings, and Section VII concludes.
`
`
`
`II. Short-sale price tests, its effect on earnings management, and related research
`
`A. Short-sale price tests in U.S. equity markets
`
`Short-sale price tests were initially introduced to the U.S. equity markets in the 1930s, ostensibly
`
`to avoid bear raids by short sellers in declining markets. The NYSE adopted an uptick rule in 1935,
`
`which was replaced in 1938 by a stricter SEC rule, Rule 10a-1, also known as the “tick test.” The rule
`
`mandates that a short sale can only occur at a price above the most recently traded price (plus tick) or at
`
`
`6 See the references in footnote 1, and also the SEC’s Office of Economic Analysis (2007), Alexander and Peterson
`(2008), and Diether, Lee, and Werner (2009). To be sure, other studies have noted the potential dark side of short
`selling, as manipulative short selling could reduce price efficiency (e.g., Gerard and Nanda, 1993; Henry and Koski,
`2010).
`
`
`
`5
`
`
`Coalition for Affordable Drugs IV LLC - Exhibit 1036
`
`

`
`
`
`the most recently traded price if that price exceeds the last different price (zero-plus tick).7 In 1994, the
`
`NASD also adopted its own price test (the “bid test”) under Rule 3350. Rule 3350 requires a short sale to
`
`occur at a price one penny above the bid price if the bid is a downtick from the previous bid.8
`
`To facilitate research on the effects of short-sale price tests on financial markets, the SEC
`
`initiated a pilot program under the Rule 202T of Regulation SHO in July 2004. Under the pilot program,
`
`every third stock in the Russell 3000 index ranked by trading volume was selected as a pilot stock. From
`
`May 2, 2005 to August 6, 2007, pilot stocks were exempted from short-sale price tests. Subsequent to the
`
`pilot program, on July 6, 2007, the SEC eliminated short-sale price tests for all exchange-listed stocks.
`
`The decision to eliminate all short-sale price tests prompted a huge backlash from managers and
`
`politicians. In 2008, NYSE Euronext commissioned Opinion Research Corporation to conduct a study to
`
`seek corporate issuers’ views on short selling. Fully 85% of the surveyed corporate managers favored
`
`reinstituting the short-sale price tests “as soon as practical,” indicating that managers are aware of and
`
`sensitive to the impact of eliminating price tests on the potential amount of short selling in their firms.
`
`The former state banking superintendent of New York argued that the SEC’s repeal of the price tests
`
`added to market volatility, especially in down markets.9 The Wall Street Journal argued that the SEC’s
`
`Office of Economic Analysis (2007) was too biased to evaluate the short-sale price tests fairly. 10
`
`Wachtell, Lipton, Rosen & Katz, a well-known law firm, argued that the uptick rule should be reinstated
`
`immediately, and three members of Congress introduced a bill (H.R. 6517) to require the SEC to reinstate
`
`the uptick rule. Presidential candidate Sen. John McCain blamed the SEC for the recent financial turmoil
`
`by “turning our markets into a casino,” in part because of the increased prospect of short sales, and called
`
`
`7 Narrow exceptions apply, as specified in SEC’s Rule 10a-1, section (e).
`8 Rule 3350 applies to Nasdaq National Market (Nasdaq NM or NNM) securities. Securities traded in the OTC
`markets, including Nasdaq Small Cap, OTCBB, and OTC Pink Sheets, are exempted. When Nasdaq became a
`national listed exchange in August 2006, NASD Rule 3350 was replaced by Nasdaq Rule 3350 for Nasdaq Global
`Market securities (formerly Nasdaq NM securities) traded on Nasdaq, and NASD Rule 5100 for Nasdaq NM
`securities traded over-the-counter. The Nasdaq switched from fractional pricing to decimal pricing over the interval
`of March 12, 2001 – April 9, 2001. Prior to decimalization, Rule 3350 required a short sale to occur at a price 1/8th
`dollar (if before June 2, 1997) or 1/16th dollar (if after June 2, 1997) above the bid.
`9 Gretchen Morgenson, “Why the roller coaster seems wilder,” The New York Times, August 26, 2007, Page 31.
`10 “There’s a better way to prevent bear raids,” The Wall Street Journal, November 18, 2008, Page A19.
`
`
`
`6
`
`
`Coalition for Affordable Drugs IV LLC - Exhibit 1036
`
`

`
`
`
`for the SEC’s chairman to be dismissed. In response to this pressure, the SEC partially reversed course
`
`and restored a modified uptick rule on February 24, 2010. Under the new rule, price tests are triggered
`
`when a security’s price declines by 10% or more from the previous day’s closing price. This policy
`
`reversal drew sharp criticism itself, this time from hedge funds and short sellers.11
`
`
`
`B. The impact of the pilot program on earnings management
`
`The strong public reactions to changes in the uptick rule indicate that the rule is important to
`
`investors, managers, and politicians. Consistent with practitioners’ perception, most prior research
`
`indicates that short-sale price tests impose meaningful constraints on short selling, an assumption we
`
`examine further in the next section.12 In this section, we draw from prior studies to construct our main
`
`hypothesis about how changes in the cost of short selling due to the removal of short-sale price tests – and
`
`the corresponding changes in the prospect of short selling – affect a manager’s tendency to engage in
`
`earnings management.
`
`Previous research indicates that executives have incentives to distort their firms’ reported
`
`financial performance to bolster their compensation, gains through stock sales, job security, operational
`
`flexibility, or control.13 This implies that managers can earn a personal benefit from managing earnings
`
`to inflate the stock price. Prior research also demonstrates that short selling facilitates the flow of
`
`unfavorable information into stock prices, increases price efficiency, and dampens the price inflation that
`
`motivates managers to manipulate earnings in the first place (e.g., see Miller, 1977; Harrison and Kreps,
`
`1978; Chang, Cheng, and Yu, 2007; Karpoff and Lou, 2010; Boehmer and Wu, 2013). These findings
`
`indicate that managers’ benefits of manipulating earnings decrease with the prospect of short selling
`
`
`11 See “Hedge Funds Slam Short-Sale Rule,” The New York Times, February 25, 2010.
`12 See, for examples, McCormick and Reilly (1996), Angel (1997), Alexander and Peterson (1999, 2008), the SEC’s
`Office of Economic Analysis (2007), and Diether, Lee, and Werner (2009). For a contradictory finding, however,
`see Ferri, Christophe, and Angel (2004).
`13 For evidence regarding compensation motives, see Bergstresser and Philippon (2006), Burns and Kedia (2006),
`and Efendi, Srivastava, and Swanson (2007); regarding stock sale motives, see Beneish and Vargus (2002);
`regarding job security and control-related motives, see DeFond and Park (1997), Ahmed, Lobo, and Zhou (2006),
`DeFond and Jiambalvo (1994), and Sweeney (1994).
`
`
`
`7
`
`
`Coalition for Affordable Drugs IV LLC - Exhibit 1036
`
`

`
`
`
`because short sellers’ activities partially offset the price inflation that motivates managers to manipulate
`
`earnings in the first place.
`
`Although earnings management conveys benefits to managers, managers cannot manipulate
`
`earnings with impunity. Previous research shows that aggressive earnings management is associated with
`
`an increased likelihood of forced CEO turnover (see Hazarika, Karpoff, and Nahata, 2012; Karpoff, Lee,
`
`and Martin 2008), and that short sellers help to monitor managers’ reporting behavior and uncover
`
`aggressive earnings management (see, e.g., Efendi, Kinney, and Swanson, 2005; Desai, Krishnamurthy,
`
`and Venkataraman, 2006; and Karpoff and Lou, 2010). These results indicate that, for any given level of
`
`earnings management, managers’ potential cost increases with a reduction in the cost of short selling and
`
`an increase in the prospect of short sellers’ scrutiny.
`
`Regulation SHO’s pilot program, which eliminated short-sale price tests for the pilot stocks,
`
`represents an exogenously imposed reduction in the cost of short selling and an increase in the prospect of
`
`short selling in these stocks. The effect is to decrease pilot firm managers’ expected benefits and to
`
`increase their expected costs at any given level of earnings management. These effects on a manager’s
`
`choice to manage earnings are illustrated in Figure 1. Let MB0 and MC0 represent the managers’ marginal
`
`benefit and marginal cost of managing earnings before the initiation of the pilot program. In drawing
`
`these curves with their normal slopes, we assume that the benefits from artificial stock price inflation
`
`increase at a decreasing rate in the level of earnings management, while the costs from the prospect of
`
`being discovered increase at an increasing rate. The pre-program optimum amount of earnings
`
`management is EM0. Once the program starts, the marginal benefit and marginal cost of earnings
`
`management shift to MB1 and MC1, and the manager adjusts endogenously by choosing a new, lower
`
`level of earnings management, EM1. This adjustment among pilot firms implies our first hypothesis:
`
`
`
`
`
`
`
`Hypothesis 1: Earnings management in the pilot firms will decrease relative to earnings
`
`management in the non-pilot firms during the pilot program.
`
`8
`
`
`Coalition for Affordable Drugs IV LLC - Exhibit 1036
`
`

`
`
`
`C. The impact of the pilot program on fraud discovery
`
`
`
`In developing Hypothesis 1 we assume that the pilot program had a substantial enough effect on
`
`short sellers’ activities to induce a measurable change in the pilot firms’ financial reporting decisions.
`
`Previous research finds that, in general, short selling tracks firms’ discretionary accruals and that short
`
`selling helps to uncover financial misrepresentation.14 In Section I of the Internet Appendix, we report
`
`results that confirm these two findings in our sample; that is, pilot firms’ short selling is positively related
`
`to these firms’ discretionary accruals during the pilot period, and short interest increases in months in
`
`which firms are later revealed to have engaged in financial misrepresentation. These results are consistent
`
`with the view that cost reduction introduced by the pilot program did provide sufficient incentives for
`
`short sellers to increase their scrutiny of the pilot firms’ reporting behavior. In this section, we exploit the
`
`unique features of the pilot program to construct a hypothesis and test for whether the pilot program also
`
`increased pilot firms’ risk of detection for earnings manipulations that rise to the level of financial
`
`misrepresentation or fraud.15
`
`We begin by noting that there generally is a time lag between when a firm begins misrepresenting
`
`its earnings and when the misrepresentation is detected. Karpoff and Lou (2010) report that this lag
`
`varies across firms and has a median of 26 months in their sample. We therefore characterize a firm’s
`
`conditional probability of being caught as:
`
`
`
`Pr(Caught(t + n)|Fraud(t)) = δ ΣsmsSSP(t + s).
`
`(1)
`
`
`
`
`14 Desai, Krishnamurthy, and Venkataraman (2006), Cao et al. (2006), Karpoff and Lou (2010), and Hirshleifer,
`Teoh, and Yu (2011) all report that short selling tracks discretionary accruals. Desai, Krishnamurthy, and
`Venkataraman (2006) find that short selling leads the announcement of earnings restatements, and Karpoff and Lou
`(2010) find that short selling accelerates the rate at which misrepresentation is detected.
`15 Karpoff et al. (2014) point out that many instances of financial misrepresentation do not include fraud charges.
`We nonetheless use the term “fraud” to refer to any illegal misrepresentation that attracts SEC enforcement action.
`
`
`
`9
`
`
`Coalition for Affordable Drugs IV LLC - Exhibit 1036
`
`

`
`
`
`In Eq. (1), Pr(Caught(t + n)|Fraud(t)) is the firm’s probability of being caught at time t + n conditional
`
`on misrepresenting at time t, where n ≥ 0. SSP(t + s) is short selling potential at time t + s, and when t +
`
`s falls within the pilot period we expect this potential to be higher for pilot firms. ms represents the
`
`individual weight each period’s short selling potential contributes to the conditional probability of
`
`detection, and depends on the wide range of non-short-selling factors that affect a firm’s probability of
`
`being caught. We hypothesize that an increase in short selling potential will help to uncover aggressive
`
`reporting, i.e., δ > 0. This leads to our second hypothesis,
`
`
`
`Hypothesis 2: Conditional on misreporting, pilot firms are more likely than non-pilot firms to get
`
`caught after the pilot program starts.
`
` A
`
` challenge in testing Hypothesis 2 is that we do not directly observe the conditional probability
`
`of detection, but rather, only the unconditional probability that a firm both commits fraud and is detected,
`
`which can be expressed as:
`
`
`
`
`
`Pr(Caught(t + n), Fraud(t)) = Pr(Fraud(t))×Pr(Caught(t + n)|Fraud(t)).
`
`(2)
`
`To develop a test of Hypothesis 2, we exploit the time lag between the commission and detection of fraud.
`
`Since the pilot firms were selected randomly, it is reasonable to assume that, before the pilot program was
`
`announced in July 2004, the actual rate of fraud commission was equal between the pilot and non-pilot
`
`firms, i.e., Pr(Fraud(t))pilot = Pr(Fraud(t))non-pilot for t < July 2004. 16 This allows us to use the
`
`unconditional probability of detection for frauds that were initiated before the pilot program was
`
`
`16 We restrict t to the period before the announcement of the pilot program (in July 2004) to ensure that the rate of
`fraud commission is equal across the two groups of firms. Whereas short sellers arguably begin to change their
`behavior after the pilot program is implemented in May 2005, managers of pilot firms could change their reporting
`behavior in response to the prospect of short selling as early as when they learn the identity of the pilot stocks in
`July 2004.
`
`
`
`10
`
`
`Coalition for Affordable Drugs IV LLC - Exhibit 1036
`
`

`
`
`
`announced in July 2004, but detected after the program started in May 2005, to infer the conditional
`
`probability of getting caught. Specifically, Hypothesis 2 implies that
`
`Pr(Caught(post-May 2005), Fraud(pre-July 2004))pilot >
`
`Pr(Caught(Post-May 2005), Fraud(pre-July 2004))non-pilot.
`
`
`
`Once the pilot program was announced, Hypothesis 1 implies that managers of the pilot firms will
`
`start to adjust endogenously to the higher conditional probability of detection by decreasing their earnings
`
`management. That is,
`
`Pr(Fraud(t))pilot < Pr(Fraud(t))non-pilot for 𝑡 > July 2004.
`
`The pilot program therefore has two offsetting effects on the unconditional probability of detection for
`
`frauds committed after July 2004: pilot firms commit fewer frauds, but conditional on committing fraud,
`
`they are more likely to be caught. This implies that the difference between pilot and non-pilot firms in the
`
`unconditional likelihood of fraud detection will decrease as we consider frauds initiated after the July
`
`2004 announcement of the pilot program. In Section V below we also test and find support for this
`
`implication of Hypothesis 2.
`
`
`
`D. Related research
`
`Our investigation is related to the small but growing literature that exploits changes in short sale
`
`regulations to examine the economic implications of short selling. Autore, Billingsley, and Kovacs
`
`(2011), Frino, Lecce, and Lepone (2011), and Boehmer, Jones, and Zhang (2013) examine the impact of a
`
`widespread ban on short selling in U.S. equity markets in 2008, and Beber and Pagano (2013) examine
`
`the impacts of short selling bans around the world. These studies conclude that the bans decreased
`
`various measures of market quality.
`
`Using Regulation SHO’s Rule 202T pilot program, Alexander and Peterson (2008) find that order
`
`execution and market quality improved for the pilot stocks during the pilot program. Diether, Lee, and
`
`Werner (2009) and the SEC’s Office of Economic Analysis (2007) show that pilot stocks listed on both
`
`
`
`11
`
`
`Coalition for Affordable Drugs IV LLC - Exhibit 1036
`
`

`
`
`
`the NYSE and Nasdaq experienced a significant increase in short-sale trades and short sales-to-share
`
`volume ratio during the term of the pilot program. The former also shows that NYSE-listed pilot stocks
`
`experienced a higher level of order-splitting, suggesting that short sellers applied more active trading
`
`strategies. Other papers relate the pilot program to firm outcomes. Grullon, Michenaud, and Weston
`
`(2014), for example, examine the effect of the pilot program on pilot firms’ stock prices, equity issuance,
`
`and investment. Kecskés, Mansi, and Zhang (2013) study bond yields, De Angelis, Grullon, and
`
`Michenaud (2014) study equity incentives, and He and Tian (2014) study corporate innovation.
`
`In our main analyses, we use the controlled experiment created by the pilot program to examine
`
`the effect of short selling costs on firms’ earnings management decisions. This experiment is well suited
`
`for our research question, as