Reverse Mergers and Earnings Quality
Chen Chu
University of Texas at El Paso
cchen3@utep.edu
Giorgio Gotti
University of Texas at El Paso
ggotti@utep.edu
Kathryn Schumann
James Madison University
schumakm@jmu.edu
Last Version: March 14, 2016
Abstract
We test for differences in financial reporting quality between companies that went public
through a reverse merger (RM) vs. other public companies and IPO firms. Moreover we test
whether audit quality (Big 4), foreign incorporation, and seasoned equity offering (SEO) play a
role in the earnings quality of RM firms, above and beyond reverse mergers. The presence of a
Big 4 auditor does appear to enhance reporting quality and contribute to the survival for firms
audited by one of the Big 4 auditors. The rate of survival is significantly higher (almost twice as
much) than the rate of survival for firms that went through RM with a non-Big 4 auditor.
Furthermore, contrary to popular beliefs, we find evidence of earnings management in both U.S.
and international RM companies. Finally, we find that earnings management is pervasive at all
RM firms, especially those that need to raise capital through an SEO after the merger.
Keywords: Earnings Quality, SEC, Reverse Merger, Audit Quality
Data availability: The data are available from public sources identified in the text.
1.
Introduction
For the past two years, the PCAOB, SEC, and several members of the business press
have expressed concerns over potential accounting troubles at foreign firms that went public in
the U.S. markets through reverse mergers (RM). In a reverse merge a private operating company,
either from the U.S. or abroad, merges with a ‘shell’ US publicly listed company. Upon
consummation of the merger its shares are publicly traded in the U.S. securities markets. Since it
avoids an underwriter, this process allows companies, especially foreign companies, to go public
in the U.S. more quickly and in a less expensive way than a traditional IPO. Critics, however,
point out how this procedure allows companies to go public with less scrutiny of their financial
situations, exposing investors to a higher risk.
In the summer of 2010 the SEC began an investigation into questionable financial
statements and auditing quality of several foreign firms that went public in the U.S. market by
way of reverse mergers. The commission issued a bulletin warning investors of the increased
risks of investing in foreign reverse merger companies as some foreign companies had been
using small U.S. auditing firms. These smaller auditing firms were a concern as some of them
“may not have the resources to meet auditing obligations when all or substantially all of the
private company’s operations are in another country” and thus the auditing firms might have
missed identifying circumstances where these companies were not in compliance with relevant
accounting standards.1 Around the same time period the PCAOB also issued a research note
discussing those firms from the China region and the concerns surrounding the audit quality of
these reverse merger firms.2 According to the Washington Post, firms from China were of a
SEC Office of Education and Advocacy, “Investor Bulletin: Reverse Mergers,” June 2011
PCAOB Research Note # 2011-P1. “Activity Summary and Audit Implications for Reverse Mergers Involving Companies from the China
Region: January 1, 2007 through March 31, 2010”, March 14, 2011.
1
2
2
particular concern because more than 300 Chinese companies had accessed U.S. capital markets
through reverse mergers since 2004.3
In response to the SEC investigation and ongoing concern over accountability issues at
foreign reverse merger companies the SEC and U.S. exchanges proposed new rules that would
“toughen the standards that “reverse-merger” companies must meet to list on the Big Board, in
the wake of accounting questions at many Chinese companies that have gone public via such
transactions.4” In November of 2011 the SEC adopted new rules on listing requirements for
reverse merger companies that SEC Chairman Mary Schapiro said would “provide greater
protections for investors.”5 The new rule requires a reverse merger company to be traded in the
U.S. over-the-counter or another regulated U.S. or foreign exchange for at least one year before
it can be publicly listed on the NYSE, Nasdaq or NYSE Amex.
The new rules were designed to combat the questionable accounting quality from foreign
firms listing in the U.S. However, the intense focus on foreign firms, particularly Chinese firms,
by the business press and government agencies has ignored the accounting quality of domestic
firms as domestic firms that engage in reverse mergers are treated with relatively little suspicion.
In an effort to better understand the differences between accounting quality of foreign and
domestic firms, we analyze the earning quality of companies that went public through a reverse
merger and compare it with other public U.S. firms and with IPO firms. Moreover we test
whether audit quality (Big 4), foreign incorporation, and seasoned equity offering (SEO) play a
role in the earnings quality and long-term survivability of RM firms beyond reverse mergers.
Contrary to popular belief, a comparison of foreign and domestic firms that go public
through reverse mergers reveals very little difference between the US and non-US based RM
Steven Mufson, “Gaining by Betting Against Flimsy Chinese Firms”, The Washington Post, August 28, 2011.
WSJ, August 10, 2011
5
SEC Press Release 2011-235. ‘SEC Approves New Rules to Toughen Listing Standards for Reverse Merger Companies’ Nov. 9, 2011.
http://www.sec.gov/news/press/2011/2011-235.htm
3
4
3
companies. Rather, it appears that RM firms in general are much more likely to engage in more
earnings management than non-RM companies and it appears that the focus on foreign firms as
risky investments by the SEC and PCAOB has actually ignored a large group of firms with
questionable accounting practices. We argue that perhaps the caution that has been to readily
applied to foreign RM firms should be expanded to include RM firms as a whole.
As previously discussed, the primary concern over foreign reverse merger firms has centered on
the lack of transparency for RM firms and the quality of accounting statements by these firms.
Since prior literature has found that earnings management should be more prevalent in cases of
asymmetric information (Richardson 2000), it is unsurprising that these RM firms engage in
more earnings management in general. To further examine whether certain scenarios result in
less earnings management for these firms, we separate the sample into subsets and find that,
though RM firms are more likely to engage in more earnings management than non-RM
companies, the likelihood of earnings management varies for firms that are audited by the
Big 4 or are in the process of a SEO. We find that companies that also intend to issue equity
within the year of a reverse merger are more likely to
management earnings than a firm that is
undertaking a reverse merger alone. On the other hand, we find that the presence of Big 4 audit
quality appears to control earnings management behaviors as those RM firms that employ higher
quality auditors are less likely to manage earnings. We continue this analysis of auditor effects
by employing a hazard model to study the survival rates for firms that employ Big 4 auditors and
those that do not. Results of this analysis indicate that in addition to less earnings management,
RM firms that use Big 4 auditors are associated with significantly lower rates of failure
(delisting) in the years following the reverse merger than those firms that do not employ a Big 4
auditor during the reverse merger. The rest of the paper proceeds as follows. Section 2 reviews
the relevant literature on reverse mergers and discusses the hypotheses presented. Section 3
4
presents the research design and Section 4 discusses the data collection method, Section 5
presents the results of empirical tests and Section 6 reviews the sensitivity tests employed.
Section 7 concludes.
2. Previous Literature and Hypothesis
2.1 Background of Reverse Mergers
Normally a reverse merger is conducted as a reverse triangle merger whereby a public
shell forms a new, wholly-owned empty subsidiary and then merges this subsidiary into a private
company that wishes to go public through a reverse merger. Once the merger is completed the
private company’s shares are converted into shares of the public shell and constitute a majority
stake in the public company.6 At this point the private firm operates as a wholly-owned
subsidiary of the public company. In some cases the reverse merger is organized as a direct
merger where the shell is merged directly in with the private firm but the reverse triangle
structure has fewer transaction costs and therefore is used more often (Sjostrom 2008).
Though reverse mergers have been going on since at least the 1950’s, they have not
received much attention until recent years.7 Due to their relatively unregulated status reverse
mergers were considered risky investments. In 1999 the SEC addressed this issue for the first
time when it proposed a rule that would curb the issuance of securities to “employees” that were
actually advisors to the shell companies on Form S-8. Though ultimately never adopted, this
proposal and the concurrent attention given to the accounting and reporting requirements for
reverse merger firms by SEC comments marked the first step in regulating reverse mergers.
6
Typically the majority stake is 80 to 90 percent (Sjostrom 2008)
For example, Occidental Petroleum (OXY), which trades on the NYSE and has a little under $50 billion in market cap, was a reverse merger
from the 1950s http://practice.findlaw.com/practice-guide/reverse-merger-small-business-funding-alternative-to-ipo.html
7
5
In 2004 the SEC proposed a rule change affecting the use of Form S-8 and Form 8-K by
shell companies that was eventually adopted, with a few changes, in 2005. The new rules
clarified the definition of ‘shell companies’ as those with little to no operations and asset other
than cash, prohibited the use of Form S-8 by shell companies, required shell companies to file
additional information on Form 8-K if they changed classifications, and required shell companies
to indicate that they are shells on 10-K forms (Pavkov 2006). Today all post- RM companies that
trade on the NYSE, NASDAQ or the OTC Bulletin Boards are required to file Forms 10K and
10Q disclosures and provide audited annual financial statements. This heightened transparency
helped create a perception of lower risk for investors in RM firms than in previous decades.
However, in recent years reverse mergers have again come under increased scrutiny as
concerns about the quality of financial statements have been raised. In the summer of 2010, the
SEC began an investigation into several companies with foreign operations to determine whether
these firms were accurately reporting financial reports and using quality auditors. In the
following months the SEC and U.S. exchanges suspended or halted trading for more than 35
overseas based companies due to a “lack of current and accurate information about the firms and
their finances” including several companies that were formed by reverse mergers.8 The SEC
issued a bulletin in June 2011 that specifically stated a risk to investors from some foreign RM
companies that were using small U.S. auditing firms since “such auditing firms might not
identify circumstances where these companies may not be complying with the relevant
accounting standards.” 9
On November 9, 2011 the SEC approved new rules that were intended to tighten the
requirements for a firm to conduct a reverse merger, again citing foreign firms as the impetus for
SEC Press Release 2011-235. “SEC Approves New Rules to Toughen Listing Standards for Reverse Merger Companies” Nov. 9, 2011.
http://www.sec.gov/news/press/2011/2011-235.htm
9
SEC Office of Education and Advocacy, “Investor Bulletin: Reverse Mergers,” June 2011
8
6
the change. Under the new rules, NYSE, NYSE Amex, and Nasdaq are required to impose a oneyear ‘seasoning period’ for firms becoming public through reverse mergers where they must
trade in the OTC market or other regulated U.S. or foreign exchange following the reverse
merger, during which time they must file audited financial statements before being listed on the
major exchanges. Additionally, the company would only be eligible to list on the exchange
provided that it maintains the exchange’s requisite minimum share price for a sustained period of
time and stays at this price or above for at least 30 of the 60 days prior to listing application with
the major exchange. Various business press articles followed this rule change announcement
with additional warnings about the continued “concerns with the quality of the auditing of
Chinese firms' financial reporting as well as the limitations on the ability of regulators to enforce
the securities laws and for investors to recover losses tied to fraudulent disclosures” and how the
new rules could make it more difficult for foreign companies to enter the U.S. markets through
reverse mergers.10
What is interesting in this situation is the continued focus by the press and the SEC on
foreign firms that become public by reverse mergers. To date precious little attention has been
given to the private U.S. firms that are entering through the back door by way of reverse merger.
Media and SEC warnings have been solely centered on foreign firms but it appears that even
U.S. firms utilizing reverse mergers may be suspect for poor financial statement quality and
questionable auditing practices. To address this question, we focus this paper on the earnings
management behavior of all firms, regardless of country of origin, that enter the U.S. markets
through reverse mergers. We find that firms from the US are equally as likely to engage in
earnings management as firms from foreign countries, which begs the question of why there has
Wall Street Journal, November 10, 2011 “SEC Tightens Rules for 'Reverse Merger' Listings” and Financial Times, November 10, 2011 “SEC
tightens rules on reverse mergers”
10
7
been such a focus on foreign RM firms only? Indeed, it appears that the warnings to investors
would be better applied to all RM firms as they have a higher likelihood of engaging in earnings
management as compared to non-RM firms. There are, however, clear differences in what types
of RM firms are more likely to engage in earnings management. We find that it is not country of
origin, but rather the presence of high quality auditors and/or the intention to also issue equity at
the time of the reverse merger that drives the earnings management behaviors. Taking these
results together, we would argue that less attention should be paid to where a firm comes from in
a reverse merger, but rather who reviews their accounting practices and whether capital issuance
is a need for the firm.
2.2 Previous Academic Literature
Academic interest in reverse mergers is relatively new but increasing as more attention is
given to reverse merger firms in the media. To date the main research questions have focused on
what type of firms choose reverse mergers over IPOs and the profitability and continued
operations of these companies after the reverse merger.
There are several reasons a firm may choose a reverse merger. By far the most commonly
cited reason for choosing a reverse merger is the cost. Depending on whether or not the shell is
publicly traded, the cost of setting up a public shell can range from $50,000 to $800,000 while
IPO underwriting fees generally cost millions of dollars (Adjei et al. 2008). (Ritter 1998) finds
average gross spreads of 7.31% for IPOs (11% when registration, printing, legal, and auditing
fees are added) but (Gleason et al. 2005) find that fees in a reverse merger situation average
2.72% of transaction value. However, this cost advantage seems to disappear if the firm wishes
to raise capital through an SEO after the reverse merger is completed. Companies wishing to
8
issue equity would have less incentive to use a reverse merger as the cost of a reverse merger that
includes an SEO is approximately equal to the cost of an IPO (Arellano Ostoa and Brusco 2002).
In addition to lower cost, (Gleason et al. 2005) report several additional reasons a firm
may choose a reverse merger. The first is that the private firm may not need to raise equity
capital at the same time as they go public.11 Second, smaller firms may find reverse mergers
more accessible and faster as they due to the lower costs and the speed in which the reverse
merger can be completed.12 Lastly, since reverse mergers are combinations of companies, they
have a much higher likelihood of completion as compared to IPOs, which depend on the
receptiveness of the market. Management typically cites one of seven categories as the primary
reason for conducting a reverse merger. These categories are growth, diversification,
organizational depth, taking advantage of economies of scale, capitalizing on private firm
strengths, expanding into complementary lines of business, and the desire of the private firm to
be publicly listed.
Research has also found that there are disadvantages of a reverse merger due to the
perception of the quality of firms that use reverse mergers and the liquidity gained post-merger.
Firms that undertake reverse mergers are typically smaller, younger and more poorly performing
before the merger than those firms that undertake an IPO (Adjei et al. 2008). Since IPO
underwriters provide liquidity and marketing, reverse merger firms typically see shares much
more thinly traded post merge than firms that use an IPO. If investors wish to convert their
shares to cash in the future, this can be considered a disadvantage of a reverse merger.
Additionally, as reverse mergers do not require the support of underwriters they can be construed
a signal of low quality (Sjostrom 2008) since conducting an IPO serves as a signal of higher
11
Gleason et al. (2005) find that less than 20% of the firms in their sample accessed public capital markets within the first two years of going
public.
12
Reverse mergers generally take 1-3 months to complete compared to more than 6 months for an IPO.
9
quality and consequently lower risk (Carter and Manaster 1990). (Arellano Ostoa and Brusco
2002) present a theoretical model whereby they determine that under certain conditions there is a
separating equilibrium in which high quality firms choose IPOs and low quality firms choose
reverse mergers. These low quality firms are also not very likely to raise capital after completion
of the reverse merger.
This low quality signal seems to have support in the post-performance of RM firms.
Empirical research around reverse mergers finds that the public firms involved in the reverse
mergers are generally unprofitable prior to the merger and that, while shareholders receive
significant gains at the announcement of the merger, there is little-to-no post-merger
improvement in operations or profitably for the RM firms. In the two years following a reverse
merger these firms continue to have higher debt, lower profitability, lower trading liquidity,
higher volatility, and lower institutional ownership than conventional IPO firms and more than
40 percent are delisted or bankrupt by the end of the two year period ((Gleason et al. 2005);
(Adjei et al. 2008); (Gleason et al. 2006)).
Given that so many firms that undertake reverse mergers are less profitable and are
delisted in such a short period of time post-merger, we analyze some of the potential firm
characteristics that may impact the accounting of RM firms in this paper. Due to issues with
quality of the firm and the accounting statement transparency, RM firms are typically
characterized by a high degree of information asymmetry and a highly asymmetric information
environment has been found to encourage earnings management behavior by firms. As
(Richardson 2000)points out, when information asymmetry is high, shareholders do not have the
resources available or access to information needed for adequate monitoring of management.
This leads to earnings management by these types of firms and the level of earnings management
10
tends to increase as information asymmetry increases ((Warfield 1995);(Richardson 2000)).
Because of this relationship between information asymmetry and earnings management, we
believe that exploring the earnings management behavior of RM firms may shed some light on
the types of firms that are of higher quality and able to survive in the long term after becoming
public corporations.
As defined by (Healy and Wahlen 1998), “earnings management occurs when managers
use judgment in financial reporting and in structuring transactions to alter financial reports to
either mislead some stakeholders about the underlying economic performance of the company or
to influence contractual outcomes that depend on reported accounting numbers.” It is this
intention to mislead stakeholders that produces the detection difficulty in earnings management
research as to be successful, earnings management typically needs to be undetected by the
stakeholders. Prior research suggests that there are two alternative ways by which a firm
manages earnings: accruals and real activities manipulation ((Roychowdhury 2006); (Cohen et
al. 2008); (Zang 2011)). The earliest studies tended to focus on accrual earnings management
((Jones 1991); (Teoh et al. 1998a)), while more recent studies have found that firms also engage
in real earnings management ((Roychowdhury 2006); (Kim et al. 2011); (Cohen and Zarowin
2010)).
Accruals give a summary measure of the firms accounting choice and discretionary
accruals are those expenses that are non-obligatory, and thus could be altered to suit the needs of
a firm. As discretionary accruals cannot be observed directly from financial statements a model
must be used that form an expectation on the level of nondiscretionary accruals and the deviation
of accruals from this level. One of the most widely used models for measuring discretionary
accruals is the Jones (1991) model. There are a substantial number of studies that use the cross-
11
sectional Jones (1991) model or one of its variations to measure abnormal accruals. For example,
DeFond and Jiambalvo (1994) use the Jones model to find that debt agreements motivate
managers to manipulate accruals. Subramanyam (1996) employs the Jones model to examine the
relationship between abnormal accruals and stock market response. Becker et al. (1998) indicate
that audit quality is negatively related to the level of abnormal accruals and Cohen and Zarowin
(2010) use Jones model to study firms’ earning management behaviors around seasoned equity
offerings.
Alternatively, real earnings management involves adjusting the timing and scale of
underlying business activities to alter earnings. (Roychowdhury 2006) defines real earnings
management as “departures from normal operational practices, motivated by managers: desire to
mislead at least some stakeholders into believing certain financial reporting goals have been met
in the normal course of operations". Although real earnings management has not been studied as
long as accruals management, a survey by (Graham et al. 2005) determines that managers prefer
real activities manipulation over accruals manipulation for at least two reasons. The first is that
accrual-based earnings management is more likely to draw attention from auditors and the
second is that there is risk involved with relying on accruals management alone as real activities
cannot be adjusted at the end of the fiscal reporting period.
Real earnings management and accrual earnings management function as substitutes
(Zang 2011), though real earnings management has the potential to create larger long-term costs
on shareholders than accrual earnings management because of its negative consequences on
future cash flows ((Cohen et al. 2008); (Cohen and Zarowin 2010)). Firms that engage in real
earnings management have been found to over-invest (Cohen and Zarowin 2009) and also
employ activities such as reductions in R&D investments and SG&A activities or increases in
12
investments in unnecessary inventory that can hurt future cash flows ((Gupta et al. 2010)). In the
short-term, real activities management is less costly than accruals management since it is less
likely to draw regulator or auditor attention (Cohen et al. 2008).
In addition to the costs of earnings management, prior research also finds that auditor
quality impacts the level of earnings management by a firm. (Becker et al. 1998) find that clients
of higher quality auditors are associated with less accruals earnings management as lower quality
audits are associated with more “accounting flexibility.” Later research by Chi et al. (2011)
determines that, because of the constraints on accrual earnings management, clients of higher
quality auditors and longer tenure auditors are more likely to resort to higher cost real earnings
management behaviors.
Based on this prior research into RM firms and earnings management, in this paper we
analyze the earnings management behaviors of RM firms to determine whether or not the
country of incorporation, use of specific auditors, or need to issue additional equity have an
impact on the earnings management levels. Specifically we examine these subsets to determine
whether auditor identity impacts the likelihood of earnings management around reverse mergers,
whether firms with higher quality auditors survive longer than those with lower quality auditors,
and whether RM firms that conduct subsequent SEOs post-merger are more likely to engage in
earnings management during the reverse merger.
2.3 Hypotheses
1. Private firms that go public using reverse mergers engage in more earnings management
than other firms.
As previously discussed, firms that undertake reverse mergers are typically smaller,
younger and more poorly performing before the merger than those firms that undertake an IPO
13
and, as reverse mergers do not require the support of underwriters, they can be construed a signal
of low quality since conducting an IPO serves as a signal of higher quality and consequently
lower risk (Carter and Manaster 1990). Since firms that undertake reverse mergers are likely to
be more poorly performing and perceived as lower quality, it is likely that these firms are more
incentivized to engage in earnings management than other firms in an effort to overcome these
problems. We hypothesize that the sample of RM firms will utilize more earnings management
than our control sample of firms.
2. Firms that utilize one of the Big 4 auditors around the time of the reverse merger are
associated with less earnings management and higher survival rates than those with nonBig 4 auditors.
RM firms are typically associated with higher levels of information asymmetry than other
firms as they have less transparency of financial statements prior to going public than the typical
firm does. As prior research finds that earnings management is higher in environments of
asymmetric information (Richardson 2000), we expect to find earnings management higher for
RM firms in general. However, in Section 2.2 we discussed the results of prior research into
auditor quality and its effect on earnings management. In general research finds that higher
quality auditors are associated with less accruals earnings management ((Becker et al. 1998) but
are more incentivized to engage in real earnings management behaviors rather than accruals
((Chi et al. 2011)). This line of research is the basis for Hypothesis 2. We hypothesize that RM
firms that utilize higher quality auditors, which we define as the Big 4 auditors, will be
associated with less accruals-based earnings management than those that do not employ Big 4
auditors. In addition, as prior research has found auditor quality impacts survival rates for IPO
14
firms (Jain 2005), we expect to see a similar effect of increased survival rates for the use of
higher quality auditors in reverse mergers.
3. International private firms that go public using reverse mergers engage in more earnings
management than U.S. private firms.
In Section 2.1 we briefly outlined the history of reverse mergers and why they are
currently such a concern to the SEC. Beginning mid-2010, the SEC began intense investigation
in to questionable accounting at more than 35 overseas based companies, including many firms
that were formed via reverse merger, due to concerns with their accounting practices. In 2011 the
SEC issued warnings that specifically cautioned investors about investing in some foreign RM
companies that were using small U.S. auditing firms and enacted rule changes intended to tighten
the requirements for a reverse merger. Additionally, throughout 2011 various business press
articles continued to express concerns over the quality of auditing at Chinese firms and various
other foreign firms that enter the U.S. markets via reverse merger. This intense focus by the SEC
and the press on foreign firms is the basis for Hypothesis 3. We hypothesize that international
firms going public with reverse mergers will engage in more earnings management than private
U.S. firms that choose reverse mergers as an avenue to go public.
4. Firms that conduct an SEO within a year of entering U.S. public markets using reverse
mergers are associated with more earnings management than those that do not conduct a
SEO.
Many studies in earnings management focus on unexpected accrual behaviors during
periods when capital market incentives are high. Prior research has found that firms report
positive (income-increasing) unexpected accruals prior to SEOs, and IPOs and there is evidence
that the unexpected accruals reverse following IPOs ((Teoh et al. 1998b, 1998a);(Teoh et al.
15
1998c)). These findings form the basis for Hypothesis 4. While the decision to go public via a
reverse merger and the subsequent desire to present a firm in the best light could be a reason a
firm would choose to manage earnings; should a firm also intends to issue equity once it has
gone public, it would most likely have an even higher incentive to manage earnings. Based on
this logic, we hypothesize that firms that conduct an SEO within a year of entering the U.S.
markets via a reverse merger will engage in more earnings management than those firms that
only enter the U.S. market with a reverse merger but do not issue equity.
3. Research Design and Models
To test our first hypothesis, we examine measures of earnings quality in order to
determine if there are systematic differences in the financial reporting quality between
companies that go public via reverse mergers and other companies in the US market.
We gather the data necessary from Securities Data Corporation (SDC), Compustat, CRSP, Audit
Analytic.
We measure earnings quality as abnormal accruals calculated with Jones (1991) model:
TAit
1
Assetsi,t−1
= k1 Assets
i,t−1
+ k2
∆Salesit
Assetsi,t−1
PPE
+ k 3 Assetsit
i,t−1
+ εit
(1)
We include a dummy variable (RM) equal to 1 for companies that went public through a
reverse merger, zero otherwise. We also control for Market-to-book ratio (MTB), size of the
company (LNSIZE) and return on assets (ROA).
Following Barber and Lyon (1996) we run the main analysis of our paper using a
matched sample design. For each Reverse Merger (RM) firm we find a group of firms from the
non RM sample that is matched based on year, two digit SIC and firms’ ROA within +/- 10% of
16
the RM firm’s ROA. After removing duplicate observations we merge the RM firms sample with
the non RM sample.13
To test the main hypothesis of the paper we adopt the following model:
𝐴𝑐𝑐𝑟𝑢𝑎𝑙𝑠 = 𝛼 + 𝛽1 𝑅𝑀 + 𝛽2 𝑀𝑇𝐵 + 𝛽3 𝐿𝑁𝑆𝐼𝑍𝐸 + 𝛽4 𝑅𝑂𝐴 + 𝜀
(2)
Where Accruals are the absolute value, positive, and negative values abnormal accruals
calculated following the Jones model (Jones 1991). The variables for the model are defined in
Appendix A. RM is a dummy variable equal to 1 if the firm went public on the U.S. capital
market through a reverse merge, zero if the firm is in the control group 14. MTB is a control
variable equal to the market value of equity divided by the book value of equity. LNSIZE is equal
to the natural logarithm of total assets and is included to control for the size of the company.
ROA is the return on assets, equal to net income before extraordinary items scaled by lagged total
assets. A positive and significant for the coefficient 𝛽1will suggest a positive associating between
abnormal accruals (total, positive, negative) and firms that went public on the U.S. capital market
through reverse merge, providing evidence in support of our hypothesis 1.
To test Hypothesis 2, we examine whether audit quality (AUDITOR) play a role in the
earnings quality of RM firms both at the time of the reverse merger and in the longer term. First,
we run our main model only for the restricted sample of RM firms, introducing a dummy
variables, AUDITOR, equal to 1 if the auditor is one of the Big 4 audit firms, zero otherwise:
𝐴𝑐𝑐𝑟𝑢𝑎𝑙𝑠 = 𝛼 + 𝛽1 𝑅𝑀 + 𝛽2 𝐴𝑈𝐷𝐼𝑇𝑂𝑅 + 𝛽3 𝐴𝑈𝐷𝐼𝑇𝑂𝑅 ∗ 𝑅𝑀 + 𝛽4 𝑀𝑇𝐵 + 𝛽5 𝐿𝑁𝑆𝐼𝑍𝐸 +
𝛽6 𝑅𝑂𝐴 + 𝜀
(3)
13
We also created a performance-matched accrual model following Kothari et al. (2005) in the sensitivity section of
the paper, and our inferences do not change
14
We also test RM firms vs. all the firms in the U.S. capital market and RM firms vs. IPO firms in the sensitivity
section of the paper
17
Next we employ a Cox proportional hazard model to test whether there is a significant
difference in the survival rate between RM firms that used one of the Big 4 audit firms during the
reverse merger as compared to those that did not use a Big 4 auditor. .
Log hi(t)= β1AUDITORi +β2MTBi +β3ROAi+ β4SIZEi
(4)
With the hazard model, a negative and significant coefficient for β1 provides evidence of
a higher probability of survival for RM companies audited by a Big 4 auditor.
To test hypotheses 3 we look at whether there is a difference between U.S. and
international RM firms in term of earnings management by running model (5) for all RM firms
including the dummy variable US, equal to 1 if the sample firm is a private U.S. firm that went
public through reverse merger, zero if the firm is an international firm that went public through
reverse merge.
𝐴𝑐𝑐𝑟𝑢𝑎𝑙𝑠 = 𝛼 + 𝛽1 𝑈𝑆 + 𝛽2 𝑀𝑇𝐵 + 𝛽3 𝐿𝑁𝑆𝐼𝑍𝐸 + 𝛽4 𝑅𝑂𝐴 + 𝜀
(5)
A positive and significant estimate of 𝛽1 in model 5 would provide evidence that U.S.
RM firms are characterized by higher total, positive, negative abnormal accruals than
international RM firms.
As an additional test, we also add a control for auditor quality to determine whether the
influence of the auditor’s on earnings quality of RM firms is different whether the firm is from
the U.S. or abroad. We run the following model:
𝐴𝑐𝑐𝑟𝑢𝑎𝑙𝑠 = 𝛼 + 𝛽1 𝑈𝑆 + 𝛽2 𝐴𝑈𝐷𝐼𝑇𝑂𝑅 + 𝛽3 𝐴𝑈𝐷𝐼𝑇𝑂𝑅 ∗ 𝑈𝑆 + 𝛽4 𝑀𝑇𝐵 + 𝛽5 𝐿𝑁𝑆𝐼𝑍𝐸 +
𝛽6 𝑅𝑂𝐴 + 𝜀
(6)
As before, a positive and significant coefficient for 𝛽1 will provide evidence of a
difference in earnings quality between U.S. and international RM firms, while a significant
18
coefficient for the interaction term 𝛽3 will provide evidence of systematic differences in
auditor’s influence on earnings quality of U.S. vs. international RM firms.
To test hypothesis 4, we test whether seasoned equity offering (SEO) is a factor
contributing to explain the earnings quality of the firms and introduce a dummy variable SEO
equal to 1 if the firm issued new shares in year t or t+1, zero otherwise.
𝐴𝑐𝑐𝑟𝑢𝑎𝑙𝑠 = 𝛼 + 𝛽1 𝑆𝐸𝑂 + 𝛽2 𝑀𝑇𝐵 + 𝛽3 𝐿𝑁𝑆𝐼𝑍𝐸 + 𝛽4 𝑅𝑂𝐴 + 𝜀
(7)
Additionally, we test the joint significance of auditor quality (AUDITOR) and seasoned
equity offering (SEO) on the earnings quality of all RM firms with the following model:
𝐴𝑐𝑐𝑟𝑢𝑎𝑙𝑠 = 𝛼 + 𝛽1 𝑆𝐸𝑂 + 𝛽2 𝐴𝑈𝐷𝐼𝑇𝑂𝑅 + 𝛽3 𝑆𝐸𝑂 ∗ 𝐴𝑈𝐷𝐼𝑇𝑂𝑅 + 𝛽4 𝑀𝑇𝐵 + 𝛽5 𝐿𝑁𝑆𝐼𝑍𝐸 +
𝛽6 𝑅𝑂𝐴 + 𝜀
(8)
4. Sample Selection and Descriptive Statistics
4.1 Sample Selection
Reverse merger data cover the period from 1/1/1987 to 12/31/2010 and are obtained from
the Securities Data Corporation (SDC) database. The definition of reverse merger or reverse take
over from SDC is the following: “Reverse Takeover Flag: ‘Y’ indicates a merger in which the
acquiring company offers more than 50% of its equity as consideration offered to the target
company resulting in the target company becoming the majority owner of the new company.”
The data for SEO are also obtained from the Securities Data Corporation (SDC) database and
cover the period from 1/1/1987 to 12/31/2010. There are 12,982 observations related to SEO. If
the filing date is missing, the issue date is used as filing date. We gather accounting data for the
years from 1987 to 2010 from Compustat. The firm should have sufficient data from Compustat
to calculate the earning measures to be included in the regressions. Moreover, the sample
19
exclude regulated industries (SIC codes between 4400 and 5000) and banks and financial
institutions (SIC codes between 6000 and 7000). In addition, for production cost (necessary to
calculate our measure of real activity earning management) we require a lag of two-year data. All
variables are winsorized at the extreme 1 percent and 99 percent before regression. If the data
for Research and Development Expense (XRD) and Advertising Expense (XAD) are missing, a
zero value is assigned. For the regressions that do not employ the data on auditors, the final
sample consists of 1971 RM firms and 6344 control firms for a total of 8315 firm-year
observations. For the regressions that include auditor data, the final sample consists of 1965 RM
firms and 6338 control firms for a total of 8303 firm-year observations. Table 1 details the
process for selecting our sample.
[Insert Table 1 about here]
4.2 Descriptive Statistics
[Insert Table 2 about here]
In table 2 we present descriptive statistics for the sample of RM firms from the U.S. and
from international firms, as well as for the non-RM firms that we use as control sample
following the method from Barber and Lyon (1996). Sample and control firms are relatively
similar in terms of size; however, the percentages of firms that employ Big 4 auditors are
noticeably different between the sample and control firms. While both domestic and international
reverse merger firms employ Big 4 auditors between 64 and 67 percent of the time respectively,
the control firms employ Big 4 auditors over 80 percent of the time.
Table 3 presents the correlation table of the variables included in our regression models as
defined in Appendix A. As indicated by Table 3, discretionary accruals are positively correlated
20
with market-to-book ratio (MTB) and return on assets (ROA) and negatively correlated with the
size of the firm (LNSIZE).
[Insert Table 3 about here]
5. Results
5.1 Earnings Quality of RM Firms – Hypothesis 1
We test our first hypothesis by looking for differences in financial reporting quality
between RM and non RM firms. This test uses abnormal accruals as a proxy for financial
reporting quality, where lower abnormal accruals indicate higher financial reporting quality. We
run Model (2) and (3) for the total absolute value of abnormal accruals and separately for
positive (income-increasing) and negative (income-decreasing) accruals firms to single out
whether the abnormal accruals were used to increase or decrease income.
Table 4 reports results for the estimation of Model (2) and (3) where the first three columns
contain results utilizing Model (2) and the last three columns are results from Model (3). The
coefficient estimate for the dummy variable RM is positive and significant for both models
where the independent variable is positive (income increasing) abnormal accruals (column 2 and
5 of Table 4), and it provides evidence that reverse merger firms are characterized by lower
earnings quality (higher earnings management) than the firms in the control group. This is true
for the basic model and also when we control for audit quality including the variable AUDITOR,
that control for the fact that the firm was audited by one of the Big 4 auditors during the reverse
merger process. Moreover the negative and significant coefficient for the interaction term 𝛽3 in
column 5 (positive abnormal accruals) suggests that Big 4 auditors are able to constrain the
earnings management (income increasing) behaviors of RM firms. Results presented in Table 4
provide evidence in support of Hypotheses 1 and 2 that RM firms are characterized by more
21
earnings management than non-RM firms and that Big 4 auditors do have a monitoring effect on
these RM firms and help curb earnings management behaviors.
[Insert Table 4 about here]
5.3 Earnings Quality and Auditor quality – Hypothesis 2
As we presented above, Table 4 provides evidence in support of hypothesis 2 that there is
strong evidence of Big 4 auditor helping RM firms in constraining their earnings management
behaviors. We examine this behavior further in Table 5 with a test that examines the impact of
audit quality on earnings quality in our sample of RM firms. As shown in Table 5, the
coefficient for the dummy variable AUDITOR is again negative and significant for the absolute
value and for the income increasing abnormal accruals columns (columns 1 and 2). This result
supports the hypothesis that RM firms audited by one of the Big 4 auditors have lower total and
positive abnormal accruals than RM firms audited by a non-Big 4 auditor. Furthermore, the
positive and significant coefficient for the variable AUDITOR for the sub-sample of firms with
income decreasing abnormal accruals (column 3) suggests that Big 4 auditors are more
conservative and encourage their RM clients to book more income decreasing accruals than nonBig 4 firms.
[Insert Table 5 about here]
In addition to examining whether auditors help constrain earnings management, we also
consider whether auditors are associated with the number of failures15 in the sample that occur
after the reverse merger. We examine the sample subsets of those firms that employ Big 4
auditors and those that to not and compare the rate of failure (delisting from the stock exchange)
between the subsets. Employing a similar methodology as (Adjei et al. 2008), we find that a
15
Firms are deemed as ‘failed’ based on the definition as discussed in (Adjei et al. 2008). Firms are considered as failed if the
CRSP delisted code is between 500 and 599.
22
higher percentage of firms do not survive in the months following a reverse merger if they
employ non-Big 4 auditors as compared to those that do. As shown in figure 1, in the two year
following the reverse merger, the rate of failure for RM firms that employ non-Big 4 auditors is
approximately double than that of firms employing Big 4 auditors.
[Insert Figure 1 about here]
Furthermore we adopt a Cox proportion hazard model to assess the probability of failure
(delisting) for RM firm audited by one of the Big 4 as compared to non-Big 4 firms. Table 6
presents results for this model. The coefficient for the AUDITOR variable is negative and
significant with the hazard ratio equaling 0.557. Thus it appears that the hazard of failure for
RM firms audited by a Big 4 firm is almost half (55.7%) that of the hazard of failure for RM
firms without a Big 4 auditor. This difference is statistically significant and therefore we find
additional support for hypothesis 2.
[Insert Table 6 about here]
To assess whether investors are aware of the risk associated with investment in a RM
firm with/without a Big 4 auditor we perform a future stock performance analysis that is
presented in Table 7. In Panel A we present average compounded buy-and-hold abnormal returns
(BHARs) for reverse merge firms with/without a Big 4 auditor where returns are compounded
12, 24, and 36 months after the announcement of reverse merger. In Panel B we present the
Cumulative Abnormal Returns (CARs) for 12, 24, and 36 months after the RM announcement.
In both cases we use equal-weighted and value-weighted market returns as a benchmark. Panel C
presents BHARs for the period of 12 months starting 3 months after the fiscal year-end and Panel
D presents the CARs for the same period, again using as a benchmark to compute abnormal
returns both the equal-weighted and the value-weighted market returns. This analysis presents
23
consistent and strong evidence that investor are not aware and do not demand higher returns
from RM firms audited by a non-Big 4 auditor to compensate for the higher risk (as shown in
Table 6) deriving from investing in these firms.
[Insert Table 7 about here]
5.2 Earnings Quality and International RM Firms – Hypothesis 3
Table 4 provided evidence consistent with Hypothesis 1 that private firms going public
by reverse mergers engage in more earnings management than other firms. However, as
discussed previously, most of the concern of RM firms has been focused on international firms
only. To determine whether international RM firms are more likely to engage in earnings
management behavior, we split the RM sample into U.S. and non-U.S. subsamples.
Table 8 shows the results of Models (5) and (6) where we test whether there is a
difference in earnings quality between U.S. and international reverse merger firms, without and
with the control for auditor quality (AUDITOR). Columns 1-3 present results from Model 5 and
columns 4-6 present results from Model 6. As shown in the table, the dummy variable US is
statistically insignificant in all the models, providing compelling evidence that earnings
management behavior of RM firms is common to both U.S. and international firms. This result is
surprising as we hypothesized in hypothesis 3 that, based on the concerns of the SEC and the
business press over the accounting quality of international firms, international RM firms would
engage in more earnings management than domestic RM firms. However, as shown in Table 8,
this does not appear to be the case. Table 8 provides evidence against our Hypothesis 3 and in
disagreement with the SEC warning to investor on the riskiness of RM international companies.
Our results provide statistical evidence that all RM firms, not just international firms, are
characterized by positive abnormal accruals, thus earnings management behaviors.
24
[Insert Table 8 about here]
5.4 Earnings Quality and Seasoned Equity Offering (SEO) – Hypothesis 4
In Hypotheses 4 we postulate that firms conducting an SEO within a year of entering
U.S. public markets using reverse mergers are associated with more earnings management than
those that do not conduct a SEO. We examine this further in Tables 9 and 10. Table 9 presents
the results for Model 7 whereby we run the model on the restricted sample of RM firms and
introduce variables for the presence of Big 4 auditors and an indicator for whether or not the RM
firm issued new shares in the year t or t+1. Table 9 presents the results for Model 8 in which we
test the joint significance of auditor quality and seasoned equity offerings on the earnings quality
of all RM firms. In both models we test whether RM companies that are issuing new shares
shortly after conducting a reverse merger are engaged in more earnings management than other
RM firms. The main question of interest in this section is whether or not the motivation of
earnings management is the reverse merger process or if the motivation is actually the intention
to issue new shares in the near future. As column 2 (abnormal positive accruals) of Table 9
indicates, RM firms that issue new shares in year t or t+1 do use abnormal positive accruals to
show a more positive earnings picture to investors than other RM firms. When we control for
auditor quality in Table 10, the SEO coefficient remains positive and significant in column 3,
indicating that, even after controlling for auditor quality, we still find a positive association
between abnormal accruals and RM firms that issue new shares. Moreover, the auditor quality
variable (AUDITOR) consistently illustrate throughout the models in column 2, 3, and 4 of Table
10 that Big 4 auditors are constraining the use of income increasing abnormal accruals by their
clients.
[Insert Table 9 and 10 about here]
25
6. Sensitivity Tests
6.1 Different measure of abnormal accruals: Francis and Wang (2008)
As a robustness test, we check whether our results are dependent on the measure of
abnormal accrual adopted in the paper. We apply the model developed by (Francis and Wang
2008) and calculate an alternative measure of abnormal accruals as the deviations from the
estimated values form the following equation:
Predicted accrual=
𝑆𝑎𝑙𝑒𝑡 ∗(
𝐶𝐴𝑡−1
𝐷𝑒𝑝𝑟𝑡−1
⁄𝑆𝑎𝑙𝑒𝑠 )−𝑃𝑃𝐸𝐺𝑇𝑡 ∗(
⁄𝑃𝑃𝐸𝐺𝑇 )
𝑡−1
𝑡−1
𝑇𝑜𝑡𝑎𝑙 𝐴𝑠𝑒𝑒𝑡𝑡−1
(9)
This model estimates predicted (and abnormal) accruals using the previous year results of
the same company as benchmark. Results from this model are presented in Table 11. As
expected, our results and inferences do not change with this model. We continue to find a
positive and significant coefficient for income increasing abnormal accruals for RM firms, and a
negative and significant coefficient for the dummy variable AUDITOR for income increasing
abnormal accruals firms, providing again evidence that Big 4 auditors constrain the earnings
management behaviors of their clients.
[Insert Table 11 about here]
6.2 Different measure of abnormal accruals: Kothari et al. (2005) Performance-matched
Accruals
We re-run our main models (2) and (3) adopting an alternative measure of earnings
quality: the abnormal accruals performance matched model presented in Kothari et al. (2005),
where they define the Jones-model performance-matched discretionary accrual for a firm in year
t as the discretionary accrual in year t minus the matched firm's discretionary accrual for the
same period. The matched firm is the firm with the closest ROA in the same industry (two-digit
26
SIC). Also in this case we find a positive and significant coefficient for income increasing
abnormal accruals for RM firms and a negative and significant coefficient for the interaction
term, confirming previous evidence that Big 4 auditors constrain the earnings management
behaviors of their clients. Results for this test are available from the authors.
6.3 Full sample test
Instead of a matched sample design, as a further robustness measure we run our main
model (3) to test whether RM firms engage in more earnings management than all other non-RM
firms. In this test we compare our sample of RM firms with all others US firms with data in
Compustat and CRSP and present the results of this regression in Table 12. Our inferences and
conclusions do not change based on the results in Table 12.
[Insert Table 12 about here]
6.4 RM vs. IPO sample test
We run our main models (2) and (3) limiting the sample to RM firms and firms that went
through an IPO to check whether there is a significant difference in earnings quality between the
two sub-samples. We continue to find a positive and significant coefficient for income increasing
abnormal accruals for RM firms and a negative and significant coefficient for the interaction
term, confirming previous evidence that Big 4 auditors constrain the earnings management
behaviors of their clients. Results for this test are available from the authors.
6.5 Earnings Management through Real Activity Management
Thus far we have focused the results presented in this section on accruals-based earnings
management. However, as discussed in section 2, real earnings management is a second way in
which firms can manage earnings. We compute real earnings management following previous
literature based on the methods suggested in (Roychowdhury 2006) and test whether there is a
27
significant different in real earnings management between RM firms and non-RM firms. In
general we do not find evidence of earnings management through real activity management in
our sample and do not include these tables in this paper.
6.6 Earnings Management through Classification Shifting
As a third method of earnings management, we also follow previous literature based on
(McVay 2006) and compute classification shifting measure for the firms in our sample to search
for evidence of earnings management through classification shifting for RM firms. We do not
find any evidence of earnings management through classification shifting in our sample and
therefore do not include these tables.
7. Conclusions and Future Research
In recent years the SEC and other various government and business press entities have
issued warnings over the possibility of accounting quality problems at foreign firms that used
reverse mergers to enter the U.S. markets. In the summer of 2010 the SEC began investigating
several foreign RM firms for questionable financial statements and auditing concerns. In the
following months they issued a bulletin warning investors of the increased risks of investing in
foreign reverse merger companies as some foreign companies had been using small U.S. auditing
firms and the PCAOB issued a research note concerning Chinese RM firms and the questionable
audit quality of those firms. Following these reports, many members of the business press also
issued warnings about firms from the Chinese region.
To combat these concerns, the SEC and the U.S. exchanges have enacted new rules that
“toughen the standards that “reverse-merger” companies must meet to list on the Big Board, in
the wake of accounting questions at many Chinese companies that have gone public via such
28
transactions.16” This intense focus on foreign RM firms has generally ignored the question of
accounting quality at private domestic firms that choose to go public through the use of reverse
mergers and therefore these firms are treated with relatively little suspicion. In this paper we
specifically focus on this question and analyze the earning quality of companies that went public
through a reverse merger and compare it with other public U.S. firms and with other IPO firms.
Additionally we examine whether audit quality, foreign incorporation, and SEOs play a role in
the earnings quality of RM firms.
Inconsistent with popular beliefs, an initial comparison of foreign and domestic firms that
go public through reverse mergers reveals very little difference between the US and non-US
based RM companies as the variable indicating a foreign firm is insignificant in all tests. We do,
however, find that both international and domestic RM firms engage in more earnings
management than non-RM companies. Though the issue of foreign or domestic does not appear
to impact the likelihood of earnings management, the employment of high quality auditors does
appear to have an effect. We find that the presence of Big 4 audit quality appears to control
earnings management behaviors as those RM firms that employ higher quality auditors are less
likely to manage earnings and are more likely to survive in the U.S markets. On this issue we
also find strong evidence that RM firms audited by a Big 4 auditor are almost twice as more
likely to survive than RM firms. Even more troubling, we find investors do not demand higher
returns for the increased risk associated with the firms that do not use Big 4 auditors with a
reverse merger, indicating that perhaps they are not aware of the increased risk of failure for
using smaller auditing firms. Furthermore, whether or not a company plans to issue equity in the
U.S. through an SEO following the reverse merger also appears to affect earnings management
16
WSJ, August 10, 2011
29
behaviors. We find that companies that issue equity within year t or t+1 after the merger are
more likely to manage earnings than a firm that is conducting a reverse merger alone.
Based on this evidence, we conclude that the focus on foreign firms by the SEC may
have been too narrow. It is clear that earnings management is a concern at all RM firms,
especially those that need to raise capital through an SEO after the merger, not just foreign RM
firms. Though the presence of a Big 4 auditor does appear to lessen these earnings management
issues significantly and reduce the probability of the firms being delisted in the near future, it is
clear that caution should be applied to all RM firms regardless of their country of incorporation.
30
References List
Adjei, F., K. Cyree, and M. Walker. 2008. The determinants and survival of reverse mergers vs
IPOs. Journal of Economics and Finance 32 (2):176-194.
Arellano Ostoa, A., and S. Brusco. 2002. Understanding reverse mergers: a first approach. DEE Working Papers. Business Economics. WB.
Barber, B. M., and J. D. Lyon. 1996. Detecting abnormal operating performance: The empirical
power and specification of test statistics. Journal of Financial Economics 41 (3):359-399.
Becker, C. L., M. L. Defond, J. Jiambalvo, and K. R. Subramanyam. 1998. The Effect of Audit
Quality on Earnings Management*. Contemporary Accounting Research 15 (1):1-24.
Carter, R., and S. Manaster. 1990. Initial Public Offerings and Underwriter Reputation. The
Journal of Finance 45 (4):1045-1067.
Chi, W., L. L. Lisic, and M. Pevzner. 2011. Is Enhanced Audit Quality Associated with Greater
Real Earnings Management? Accounting Horizons 25 (2):315-335.
Cohen, D. A., A. Dey, and T. Z. Lys. 2008. Real and accrual-based earnings management in the
pre- and post-Sarbanes-Oxley periods. The Accounting Review 83 (3):757–787.
Cohen, D. A., and P. Zarowin. 2009. Earnings Management and Excess Investment: AccrualBased versus Real Activities. Working Paper, New York University.
———. 2010. Accrual-based and real earnings management activities around seasoned equity
offerings. Journal of Accounting and Economics 50 (1):2-19.
Francis, J. R., and D. Wang. 2008. The Joint Effect of Investor Protection and Big 4 Audits on
Earnings Quality around the World. Contemporary Accounting Research 25 (1):157-191.
Gleason, K. C., R. Jain, and L. Rosenthal. 2006. Alternatives for Going Public: Evidence from
Reverse Takeovers, Self-Underwritten IPOs, and Traditional IPOs. Working Paper,
Available at SSRN: http://ssrn.com/abstract=890714.
Gleason, K. C., L. Rosenthal, and R. A. Wiggins Iii. 2005. Backing into being public: an
exploratory analysis of reverse takeovers. Journal of Corporate Finance 12 (1):54-79.
Graham, J. R., C. R. Harvey, and S. Rajgopal. 2005. The economic implications of corporate
financial reporting. Journal of Accounting and Economics 40 (1–3):3-73.
Gupta, M., M. Pevzner, and C. Seethamraju. 2010. The Implications of Absorption Cost
Accounting and Production Decisions for Future Firm Performance and Valuation*.
Contemporary Accounting Research 27 (3):889-922.
31
Healy, P. M., and J. M. Wahlen. 1998. A Review of the Earnings Management Literature and its
Implications for Standard Setting. Working Paper, Available at SSRN:
http://ssrn.com/abstract=156445.
Jain, B. A., Charles L. Martin Jr. 2005. The Association Between Audit Quality and Post-IPO
Performance: A Survival Analysis Approach. Review of Accounting and Finance 4
(4):50-75.
Jones, J. J. 1991. Earnings Management During Import Relief Investigations. Journal of
Accounting Research 29 (2):193-228.
Kim, B. H., L. L. Lisic, L. A. Myers, and M. Pevzner. 2011. Debt Contracting and Real Earnings
Management. Working Paper Available at SSRN: http://ssrn.com/abstract=1701218
McVay, S. E. 2006. Earnings Management Using Classification Shifting: An Examination of
Core Earnings and Special Items. Accounting Review 81 (3):501-531.
Pavkov, A. R. 2006. Ghouls and Godsends - A Critique of Reverse Merger Policy. Berkeley
Business Law Journal 3 (475).
Richardson, V. 2000. Information Asymmetry and Earnings Management: Some Evidence.
Review of Quantitative Finance and Accounting 15:325-347.
Ritter, J. R. 1998. Initial Public Offerings. Contemporary Finance Digest 2:5– 30.
Roychowdhury, S. 2006. Earnings management through real activities manipulation. Journal of
Accounting & Economics 42 (3):335-370.
Sjostrom, W. K. J. 2008. Truth about Reverse Mergers. Entrepreneurial Business Law Journal
743 (2).
Subramanyam, K. R. 1996. The pricing of discretionary accruals. Journal of Accounting and
Economics 22 (1–3):249-281.
Teoh, S. H., I. Welch, and T. J. Wong. 1998a. Earnings Management and the Long-Run Market
Performance of Initial Public Offerings. The Journal of Finance 53 (6):1935-1974.
———. 1998b. Earnings management and the underperformance of seasoned equity offerings.
Journal of Financial Economics 50 (1):63-99.
Teoh, S. H., T. J. Wong, and G. R. Rao. 1998c. Are Accruals during Initial Public Offerings
Opportunistic? Review of Accounting Studies 3 (1):175-208.
Warfield, T. D., J.J. Wild, and K.L. Wild. 1995. Managerial Ownership, Accounting Choices and
Informativeness of Earnings. Journal of Accounting and Economics 20:61-91.
Zang, A. Y. 2011. Evidence on the Trade-Off between Real Activities Manipulation and
Accrual-Based Earnings Management. Accounting Review, Forthcoming.
32
Appendix A. Variable Descriptions
Variables
Accrual
CFO
Description
Discretionary Accruals are estimated using Jones (1991) model:
𝑇𝐴𝑖𝑡
1
∆𝑆𝑎𝑙𝑒𝑠𝑖𝑡
𝑃𝑃𝐸𝑖𝑡
= 𝑘1
+ 𝑘2
+ 𝑘3
+ 𝜀𝑖𝑡
𝐴𝑠𝑠𝑒𝑡𝑠𝑖,𝑡−1
𝐴𝑠𝑠𝑒𝑡𝑠𝑖,𝑡−1
𝐴𝑠𝑠𝑒𝑡𝑠𝑖,𝑡−1
𝐴𝑠𝑠𝑒𝑡𝑠𝑖,𝑡−1
Where TA is the total accrual, which is the difference between earnings before
extraordinary items and discontinued operations (IBC) and operating cash flows
(OANCF-XIDOC)
Abnormal cash from operations are calculated as the deviations from the estimated values
form the following industry-year regression:
𝐶𝐹𝑂𝑖𝑡
1
𝑆𝑎𝑙𝑒𝑠𝑖𝑡
∆𝑆𝑎𝑙𝑒𝑠𝑖𝑡
= 𝑘1
+ 𝑘2
+ 𝑘3
+ 𝜀𝑖𝑡
𝐴𝑠𝑠𝑒𝑡𝑠𝑖,𝑡−1
𝐴𝑠𝑠𝑒𝑡𝑠𝑖,𝑡−1
𝐴𝑠𝑠𝑒𝑡𝑠𝑖,𝑡−1
𝐴𝑠𝑠𝑒𝑡𝑠𝑖,𝑡−1
Where CFO is the cash flow from operations (OANCF- XIDOC)
PROD
Abnormal production costs are calculated deviations from the estimated values form the
following industry-year regression:
𝑃𝑅𝑂𝐷𝑖𝑡
1
𝑆𝑎𝑙𝑒𝑠𝑖𝑡
∆𝑆𝑎𝑙𝑒𝑠𝑖𝑡
∆𝑆𝑎𝑙𝑒𝑠𝑖𝑡−1
= 𝑘1
+ 𝑘2
+ 𝑘3
+𝑘4
+ 𝜀𝑖𝑡
𝐴𝑠𝑠𝑒𝑡𝑠𝑖,𝑡−1
𝐴𝑠𝑠𝑒𝑡𝑠𝑖,𝑡−1
𝐴𝑠𝑠𝑒𝑡𝑠𝑖,𝑡−1
𝐴𝑠𝑠𝑒𝑡𝑠𝑖,𝑡−1
𝐴𝑠𝑠𝑒𝑡𝑠𝑖,𝑡−1
Where PROD are the production costs that are the sum of costs of goods sold (COGS)
and change in inventory (INVT)
DISX
Abnormal discretionary expenses are calculated deviations from the estimated values
form the following industry-year regression:
𝐷𝐼𝑆𝑋𝑖𝑡
1
𝑆𝑎𝑙𝑒𝑠𝑖𝑡−1
= 𝑘1
+ 𝑘2
+ 𝜀𝑖𝑡
𝐴𝑠𝑠𝑒𝑡𝑠𝑖,𝑡−1
𝐴𝑠𝑠𝑒𝑡𝑠𝑖,𝑡−1
𝐴𝑠𝑠𝑒𝑡𝑠𝑖,𝑡−1
Where DISX are discretionary expenses, defined as the sum of advertising expenses
(XAD ), R&D expenses (XRD), and SG&A (XSGA)
MTB
Market to book, the market value of equity divided by the book value of equity
ROA
Return on assets, net income before extraordinary items, scaled by lagged assets
LNSIZE
RM
The natural logarithm of total assets
Dummy variable, coded as 1 if the firm merged with other firms through a reverse
takeover, 0 otherwise
AUDITOR
Dummy variable, coded as 1 if the firm hires one of the Big 4 auditors (EY, Deloitte,
PwC, KPMG), 0 otherwise
US
Dummy variable, coded as 1 if the reverse merger firm is from the U.S., 0 otherwise
Growth
Sales growth, which is measured as change in sales divided by sales from the previous
year
SEO
Dummy variable, coded as 1 if the firm issues new shares in year t or t+1, 0 otherwise
33
Figure 1: Firm failures (delisting) following reverse mergers based on auditor identity
Figure 1 displays the cumulative failures (delisting) of RM firms as a percentage of the total number of firms. The dashed line
represents the sample firms that employ non-Big 4 auditors and the solid line represents the sample firms that employ Big 4
auditors. Firms are classified as ‘failed’ if they are delisted from the stock market where they were traded (CRSP delisted code
between 500 and 599), as discussed in (Adjei et al. 2008).
Cumulative Failure Percentages
60%
50%
40%
30%
20%
10%
0%
0
50
100
150
200
34
250 Months
Table 1. Sample Selection Criteria
Table 1 illustrates the sample selection process. We start with the entire population of firms from Compustat for the period 19872010 and then removed financial institutions and observations with missing values and/or inadequate information.
Firm-year
Without
With
auditor
auditor
Annual Compustat (1987–2010)
Less observations from financial institutions and
regulated industries
Less observations with missing value (i.e. missing total asset or sales)
Less observations with inadequate information to perform regressions
Less observations after performance matched
Less observations with missing auditor information
Final sample (firm-year)
254,770
254,770
46,317
81,362
11,731
107,045
8,315
46,317
81,362
11,731
107,045
12
8,303
Table 2. Descriptive Statistics
Table 2 displays the mean and median values for the sample of foreign RM firms, U.S. RM firms, and control sample firms. The
control sample columns contain the mean and median values for the matched sample firms as suggested by Barber and Lyon
(1996). LNSIZE is equal to the natural logarithm of total assets. ROA is equal to the net income before extraordinary items scaled
by lagged total assets. MTB is the market-to-book ratio and equal to the market value of equity divided by the book value of
equity. Growth is the sales growth and measured as change in sales divided by sales from previous year. TA is the total accrual
equal to the difference between earnings before extraordinary items and discontinued operations (IBC) and operating cash flows
(OANCF-XIDOC). Accruals are estimated using Jones (1991) model:
𝑇𝐴𝑖𝑡
𝐴𝑠𝑠𝑒𝑡𝑠𝑖,𝑡−1
= 𝑘1
1
𝐴𝑠𝑠𝑒𝑡𝑠𝑖,𝑡−1
+ 𝑘2
∆𝑆𝑎𝑙𝑒𝑠𝑖𝑡
𝐴𝑠𝑠𝑒𝑡𝑠𝑖,𝑡−1
+ 𝑘3
𝑃𝑃𝐸𝑖𝑡
𝐴𝑠𝑠𝑒𝑡𝑠𝑖,𝑡−1
+ 𝜀𝑖𝑡
Finally, AUDITOR is a dummy variable equally to1 if the firm is audited by one of the Big 4 auditors, 0 otherwise.
LNSIZE
ROA
MTB
Growth
TA
Accruals
AUDITOR
N
Control firm
Mean
Median
5.6256
5.5705
0.0940
0.0775
3.8008
2.2294
0.3544
0.1349
-0.0281
-0.0389
0.2347
0.0525
0.8039
1.0000
6,338
International RM
Mean
Median
5.2794
4.8992
0.0863 -0.0072
0.7480
1.9958
0.9026
0.1241
0.3427 -0.0676
-0.1710 -0.0048
0.6720
1.0000
372
35
US RM
Mean Median
4.5862 4.3820
-0.2666 -0.0041
3.2193 1.7976
6.9783 0.1009
-0.1944 -0.0651
0.1719 0.0003
0.6453 1.0000
1,593
Table 3. Correlation Table with Pearson (Spearman) Correlation Coefficients above
(below) the Diagonal
Table 3 contains correlation coefficients for the variables included in our regression models and defined in Appendix A. All
variables are winsorized at the 1% and 99% percentiles before the correlation analysis. All coefficients are significant at 5%
level, with the exception of those marked with ! and #.
! Indicates significance at 10% level, and # Indicates that the coefficient is not significant.
Accruals
Accruals
CFO
PROD
DISX
MTB
LNSIZE
ROA
-0.1172
0.0103
-0.0444
0.0434
0.0062!
0.2024
CFO
0.0019#
0.0774
-0.2489
0.2155
0.3877
0.6487
PROD
-0.0009#
0.0014#
0.0759
-0.1346
0.0036#
0.1305
DISX
MTB LNSIZE ROA
-0.0287 0.0092
-0.014
0.0765
-0.0619 0.002#
0.0302 0.1273
0.037 -0.0123 -0.0108 0.0035#
-0.0265 -0.0681 -0.1492
0.0453
0.0275 0.0472
-0.4461 0.1678
0.3492
-0.2474 0.2989 0.3519
36
Table 4. Impact of Reverse Mergers (RM) on Earnings Management Behaviors of Firms
Table 4 reports regression results for Models 2 and 3. Columns1-3 are estimated using Model 2 as suggested in Jones (1991) while columns 4-6 are estimated using Model 3. To
build the matched sample we follow the method highlighted in Barber and Lyon (1996): for each Reverse Merger (RM) firm we find a group of firms from the not Reverse Merger
sample that is matching based on 1) year; 2) two digit SIC code; and 3) Firm’s ROA higher than 90% of the ROA of the RM firm’s and lower than 110% of the ROA of the RM
firm. After removing all duplicate observations we merge the RM firms sample with the matched non RM sample.
RM is a dummy variable with value equal to one if the firm went public through Reverse Merger, zero otherwise.
Abnormal Accruals (absolute value |Accrual| in column 1 and 4, positive [+] Accrual in column 2 and 5, and negative [-] Accrual in column 3 and 6) are estimated using Jones
(1991) model:
TAit
1
∆Salesit
PPEit
= k1
+ k2
+ k3
+ εit
Assetsi,t−1
Assetsi,t−1
Assetsi,t−1
Assetsi,t−1
All other variables are defined in Appendix A.
T-statistics are in brackets and ** (*) indicates statistical significance at the 1% (5%) level (two-tailed)
Variables
RM
|Accrual|
0.2022
[1.63]
[+] Accrual
0.4897
[3.00]**
[-] Accrual
0.2616
[1.34]
-0.0002
[-0.40]
-0.1294
[-5.76]**
-0.3060
[-12.20]**
1.6885
[12.11]**
8,315
0.0234
-0.0002
[-0.29]
-0.1686
[-6.16]**
-0.1853
[-6.61]**
1.8493
[11.14]**
5,059
0.0187
0.0015
[0.57]
0.0481
[1.25]
0.6876
[13.15]**
-1.3230
[-5.30]**
3,256
0.0515
AUDITOR
AUDITOR*RM
MTB
LNSIZE
ROA
Intercept
N.
Adj- R2
|Accrual|
0.5531
[2.70]**
-0.3815
[-2.59]**
-0.6536
[-2.67]**
-0.0002
[-0.27]
-0.0301
[-1.31]
-0.1350
[-5.74]**
1.4211
[9.61]**
8,303
0.009
37
[+] Accrual
1.0414
[4.21]**
-0.0685
[-0.41]
-1.1555
[-3.79]**
-0.0001
[-0.24]
-0.0725
[-2.64]**
-0.0520
[-2.06]*
1.3642
[8.25]**
5,051
0.0087
[-] Accrual
0.5376
[1.45]
1.1281
[3.85]**
-0.3951
[-0.93]
0.0008
[-0.34]
-0.0470
[-1.17]
0.4120
[7.92]**
-1.7000
[-5.68]**
3,252
0.0230
Table 5. The Impact of Audit Quality (AUDITOR) on Earnings Management Behavior of
RM Firms
Table 5 displays regressions results that show the impact of a Big 4 auditor on earnings management behavior of RM firms.
Colum 1 presents results for the absolute value of abnormal accruals, Column 2 presents results for income increasing (positive)
abnormal accruals, and Column 3 presents results for income decreasing (negative) abnormal accruals. Abnormal Accruals are
estimated using Jones (1991) model:
𝑇𝐴𝑖𝑡
1
∆𝑆𝑎𝑙𝑒𝑠𝑖𝑡
𝑃𝑃𝐸𝑖𝑡
= 𝑘1
+ 𝑘2
+ 𝑘3
+ 𝜀𝑖𝑡
𝐴𝑠𝑠𝑒𝑡𝑠𝑖,𝑡−1
𝐴𝑠𝑠𝑒𝑡𝑠𝑖,𝑡−1
𝐴𝑠𝑠𝑒𝑡𝑠𝑖,𝑡−1
𝐴𝑠𝑠𝑒𝑡𝑠𝑖,𝑡−1
AUDITOR is a dummy variable that is equal to one if the RM firm hires a Big 4 auditor and zero otherwise. MTB is the marketto-book ratio and equal to the market value of equity divided by the book value of equity. LNSIZE is equal to the natural
logarithm of total assets. ROA is equal to the net income before extraordinary items scaled by lagged total assets.
T-statistics are in brackets and ** (*) indicates statistical significance at the 1% (5%) level (two-tailed).
Variables
|Accrual|
[+] Accrual
[-] Accrual
AUDITOR
-0.4267
[-4.17]**
0.0020
[0.32]
0.0006
[0.03]
-0.5012
[-10.57]**
0.8892
[10.05]**
1,965
0.0796
-0.5645
[-3.41]**
0.0046
[0.41]
-0.0232
[-0.72]
-0.5771
[-4.53]**
1.3028
[8.30]**
980
0.0432
0.2054
[1.78]*
-0.0002
[-0.03]
-0.0303
[-1.31]
0.6458
[12.28]**
-0.4883
[-3.97]**
985
0.1425
MTB
LNSIZE
ROA
Intercept
N.
Adj- R2
38
Table 6. Cox Proportional Hazard Model
Log hi(t)= β1AUDITORi +β2MTBi +β3ROAi+ β4SIZEi
Where AUDITOR is a dummy variable that is equal to one if the RM firm hires a Big 4 auditor and zero otherwise, ROA is the
Return on Assets and it is computed as the net income before extraordinary items scaled by lagged total assets, MTB is the
market-to-book ratio and equal to the market value of equity divided by the book value of equity, and Size is equal to the total
asset of the firm.
All control variables are at the Reverse Merger year (if the data for the RM year is missing, we use the data available for the
following year).
Variables
Coefficient
p-value
Hazard Ratio
AUDITOR
MTB
ROA
SIZE
N.
Likelihood ratio
-0.5858
0.0022
-0.0256
-0.0001
334
38.5072
0.0033
0.3651
<.0001
0.1064
0.557
1.002
0.975
1.000
39
Table 7. Future Stock Performance of RM firms with Big 4/non-Big 4 Auditors
Panel A presents average compounded buy-and-hold abnormal returns (BHARs) for reverse merger firms with/without a Big 4
auditor. Returns are compounded 12, 24, and 36 months after the announcement of reverse mergers.
Panel B presents cumulative abnormal returns (CARs) for 12 month after the announcement of reverse mergers for RM firms
with/without a Big 4 auditor. We use both equal-weighted (EW) and value-weighted (VW) market returns as benchmark returns.
Panel C presents average compounded buy-and-hold abnormal returns (BHARs) for reverse merger firms with/without a Big 4
auditor. We use both equal-weighted (EW) and value-weighted (VW) market returns as benchmark returns. Returns are
cumulated for a 12 months period (beginning 3 months after the fiscal year end).
Panel D presents cumulative abnormal returns (CARs) for RM firms with/without a Big 4 auditor. We use both equal-weighted
(EW) and value-weighted (VW) market returns as benchmark returns. Returns are cumulated for a 12 months period (beginning 3
months after the fiscal year end).
Panel A: Buy-and-Hold Abnormal Returns (BHARs) 12, 24, and
36 months after RM event
Equal-Weighted
Value-Weighted
Month
BHAR
p-value
BHAR
p-value
12
non-Big 4 0.1358
0.1796
Big 4
0.1927
0.2135
diff.
-0.057
0.7599
-0.0339
0.8575
24
non-Big 4 -0.0345
0.0731
Big 4
0.1408
0.1911
diff.
-0.1754
0.4144
-0.118
0.5891
36
non-Big 4 -0.0957
0.0572
Big 4
0.1706
0.2687
diff.
-0.2663
0.3409
-0.2115
0.4548
Panel B: Cumulative Abnormal Returns (CARs) 12, 24, and 36
months after RM event
Equal-Weighted
Value-Weighted
Month
CAR
p-value
CAR
p-value
12
non-Big 4 0.2103
0.2556
Big 4
0.2447
0.2615
diff.
-0.0344
0.8114
-0.0058
0.9681
24
non-Big 4 0.2808
0.3929
Big 4
0.2894
0.345
diff.
-0.0085
0.9622
0.0478
0.7950
36
non-Big 4 0.3421
0.4947
Big 4
0.3441
0.443
diff.
-0.0020
0.9920
0.0516
0.8052
40
Panel C: Buy-and-Hold Abnormal Returns (BHARs) 3 months
after fiscal year-end
Equal-Weighted
Value-Weighted
Month
BHAR p-value
BHAR
p-value
12
non-Big 4 0.1059
0.1614
Big 4
0.0763
0.1354
diff.
0.0296
0.747
0.026
0.7786
Panel D: Cumulative Abnormal Returns (CARs) 3 months after
fiscal year-end
Month
12
non-Big 4
Big 4
diff.
Equal-Weighted
CAR
p-value
0.0445
0.0701
-0.0256 0.5237
Value-Weighted
CAR
p-value
0.0872
0.1169
-0.0297
0.4689
41
Table 8. Impact of Reverse Merger on Earnings Management Behaviors of U.S. vs.
International RM firms
Table 8 displays results for Models 3 and 4 that test for differences between earnings quality of foreign and domestic RM firms.
Results for Model 3 are displayed in columns 1-3 and results for Model 4 are displayed in columns 4-6. The variable US is a
dummy variable with value one if the reverse merger firm is from the U.S. and zero otherwise. All the other variables are defined
in Appendix A. Abnormal Accruals (absolute value |Accrual| in column 1 and 4, positive [+] Accrual in column 2 and 5, and
negative [-] Accrual in column 3 and 6) are estimated using Jones (1991) model:
TAit
1
∆Salesit
PPEit
= k1
+ k2
+ k3
+ εit
Assetsi,t−1
Assetsi,t−1
Assetsi,t−1
Assetsi,t−1
T-statistics are in brackets and ** (*) indicates statistical significance at the 1% (5%) level (two-tailed).
Variables
US
|Accrual|
-0.1492
[-1.30]
[+] Accrual
-0.1710
[-0.96]
[-] Accrual
0.1360
[1.09]
-0.0023
[-0.37]
-0.0445
[-2.49]**
-0.7038
[-13.78]**
1.0090
[7.13]**
1971
0.1082
0.0024
[0.21]
-0.0809
[-2.87]**
-0.9026
[-8.96]**
1.3649
[6.06]**
985
0.1023
0.0015
[0.22]
-0.0091
[-0.43]
0.6715
[12.92]**
-0.5573
[-3.37]**
986
0.1565
AUDITOR
AUDITOR*US
MTB
LNSIZE
ROA
Intercept
N.
Adj- R2
42
|Accrual|
-0.1949
[-1.30]
-0.39273
[-2.90]**
0.0046
[0.32]
0.0019
[0.30]
-0.0040
[-0.20]
-0.5668
[-10.39]**
1.0857
[7.37]**
1965
0.0719
[+] Accrual
-0.1539
[-0.63]
-0.57703
[-2.63]**
-0.0030
[-0.13]
0.0045
[0.41]
-0.0262
[-0.79]
-0.5728
[-4.48]**
1.4684
[6.35]**
980
0.0422
[-] Accrual
0.2503
[1.43]
0.10347
[0.65]
-0.0158
[-0.90]
0.0002
[0.03]
-0.0239
[-1.01]
0.6423
[12.16]**
-0.5626
[-3.17]**
985
0.1426
Table 9. Impact of Seasoned Equity Offering (SEO) on Earnings Management behaviors of
RM Firms
Table 9 presents results for Model 6.. The variable SEO is a dummy variable with value one if the firm issues new shares in year t
or t+1, zero otherwise. All other variables are defined in Appendix A. The dependent variable, Abnormal Accruals (absolute
value |Accrual| in column 1, positive [+] Accrual in column 2, and negative [-] Accrual in column 3) are estimated using Jones
(1991) model:
TAit
1
∆Salesit
PPEit
= k1
+ k2
+ k3
+ εit
Assetsi,t−1
Assetsi,t−1
Assetsi,t−1
Assetsi,t−1
T-statistics are in brackets and ** (*) indicates statistical significance at the 1% (5%) level (two-tailed).
Variables
SEO
MTB
LNSIZE
ROA
Intercept
N.
Adj- R2
|Accrual|
0.2727
[2.15]*
0.0003
[0.06]
-0.0406
[-2.58]**
-0.4889
[-10.79]**
0.8295
[9.42]**
2,005
0.0695
Accrual
[+] Accrual
0.6028
[3.03]**
0.0015
[0.15]
-0.0864
[-3.46]**
-0.4747
[-4.45]**
1.1727
[8.38]**
1,006
0.0419
[-] Accrual
0.1514
[1.01]
0.0006
[0.10]
-0.0134
[-0.73]
0.5656
[13.27]
-0.4275
[-4.16]**
999
0.1563
43
Table 10. Impact of Audit Quality (AUDITOR) and Seasoned Equity Offering (SEO) on
Earnings Management of RM Firms
Table 10 presents results for Model 7. The variable SEO is a dummy variable with value one if the firm issues new shares in year
t or t+1, zero otherwise. All other variables are defined in Appendix A. The dependent variable, Abnormal Accruals (absolute
value |Accrual|) is estimated using Jones (1991) model:
TAit
1
∆Salesit
PPEit
= k1
+ k2
+ k3
+ εit
Assetsi,t−1
Assetsi,t−1
Assetsi,t−1
Assetsi,t−1
T-statistics are in brackets and ** (*) indicates statistical significance at the 1% (5%) level (two-tailed).
Variables
SEO
|Accrual|
0.2727
[2.15]*
Auditor
-0.3965
[-4.45]**
0.2980
[2.36]*
-0.4058
[-4.55]**
0.0020
[0.37]
0.0007
[0.04]
-0.4964
[-14.55]**
0.9132
[10.20]**
1965
0.0765
0.0012
[0.23]
-0.0029
[-0.16]
-0.4921
[-10.92]**
0.9105
[10.18]**
1965
0.0786
SEO*Auditor
MTB
LNSIZE
ROA
Intercept
N.
Adj- R2
0.0003
[0.06]
-0.0406
[-2.58]**
-0.4889
[-10.79]**
0.8295
[9.42]**
2005
0.0695
44
0.5108
[1.90]
-0.3845
[-4.17]**
-0.2720
[-0.90]
0.0012
[0.84]
-0.0038
[0.21]
-0.4900
[-0.21]
0.9016
[0.09]
1965
0.0785
Table 11. Sensitivity Test: Impact of RM on Earnings Management (Abnormal accruals by
Francis and Wang 2008)
Table 11 utilizes as dependent variable Abnormal Accruals calculated adopting the model developed by (Francis and Wang
2008). This model calculates abnormal accruals as the deviations from the estimated values form the following equation:
Predicted accrual=
𝐶𝐴
𝑆𝑎𝑙𝑒𝑡 ∗( 𝑡−1⁄𝑆𝑎𝑙𝑒𝑠
𝑡−1
𝐷𝑒𝑝𝑟𝑡−1
)−𝑃𝑃𝐸𝐺𝑇𝑡 ∗(
⁄𝑃𝑃𝐸𝐺𝑇
𝑡−1
)
𝑇𝑜𝑡𝑎𝑙 𝐴𝑠𝑒𝑒𝑡𝑡−1
Where PPEGT is the total PPE (PPEGT) and Depr is the depreciation expenses, which is the difference between Depreciation
and Amortization (DP) and Amortization of Intangibles (AM). CA is the current accrual, defined as change in non-cash working
capital. CA=Δ[total current assets(ACT)-cash and short term investments (CHE)- treasury stock shown as current assets
(TSCA)]-Δ[total current liabilities(LCT)-total amount of debt in current liabilities(DLC)-proposed dividends (PRODV).
All other variables are defined in Appendix A.
T-statistics are in brackets and ** (*) indicates statistical significance at the 1% (5%) level (two-tailed).
RM
|Accrual|
0.0370
[7.57]**
[+] Accrual
0.05629
[6.59]**
[-] Accrual
-0.0218
[-3.98]**
0.0007
[7.20]**
-0.0216
[-79.43]**
-0.1389
[-130.76]**
0.2321
[155.42]**
109,762
0.2434
0.0012
[6.57]**
-0.0277
[-58.47]**
-0.1410
[-78.53]**
0.2707
[106.27]**
49,617
0.2235
-0.0003
[-2.28]*
0.0164
[53.60]**
0.1388
[113.10]**
-0.2005
[-116.15]**
60,143
0.2285
AUDITOR
AUDITOR*RM
MTB
LNSIZE
ROA
Intercept
N.
Adj- R2
45
|Accrual|
0.0171
[2.03]*
-0.0217
[-13.37]**
0.0259
[2.51]*
0.0008
[7.63]**
-0.0200
[-67.18]**
-0.1380
[-129.79]**
0.2422
[147.06]**
109,762
0.2447
[+] Accrual
0.0284
[2.00]*
-0.0254
[-9.15]**
0.0381
[2.15]*
0.0012
[6.84]**
-0.0258
[-49.56]**
-0.1401
[-77.94]**
0.2812
[100.94]**
49,617
0.2249
[-] Accrual
-0.0075
[-0.77]
0.0177
[9.55]**
-0.0181
[-1.53]
-0.0003
[-2.60]**
0.0152
[45.34]**
0.1381
[112.35]**
-0.2082
[-109.48]**
60,143
0.2836
Table 12. Sensitivity Test: Impact of RM on Earnings Management - RM firms vs. non-RM
firms (full sample)
Table 12 presents the result of Model 3 for the entire sample of RM firms and all other US firms with data in Compustat and
CRSP. . The dependent variable, Abnormal Accruals (absolute value |Accrual| in column 1, positive [+] Accrual in column 2, and
negative [-] Accrual in column 3) are estimated using Jones (1991) model:
TAit
1
∆Salesit
PPEit
= k1
+ k2
+ k3
+ εit
Assetsi,t−1
Assetsi,t−1
Assetsi,t−1
Assetsi,t−1
T-statistics are in brackets and ** (*) indicates statistical significance at the 1% (5%) level (two-tailed).
Variables
RM
AUDITOR
AUDITOR*RM
MTB
LNSIZE
ROA
Intercept
N.
Adj- R2
|Accrual|
0.1426
[2.57]*
-0.3523
[-31.11]**
-0.0259
[-0.38]
-0.0006
[-0.99]
0.0051
[2.46]*
-0.5280
[-117.37]**
0.7257
[66.22]**
115,194
0.1430
[+] Accrual
0.2159
[2.52]*
-0.3922
[-22.54]**
-0.1098
[-1.01]
-0.0020
[-1.96]*
-0.0148
[-4.63]**
-0.5756
[-67.97]**
0.9708
[58.76]**
61,487
0.1026
[-] Accrual
-0.0802
[-1.22]
0.2598
[19.23]**
-0.0680
[-0.86]
-0.0002
[-0.23]
-0.0305
[-12.51]**
0.5434
[117.55]**
-0.3891
[-29.10]**
53,707
0.2452
46