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Effectiveness of the SEC’s comment letters in initial public offerings
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Content
Effectiveness of the SEC’s Comment Letters in Initial Public Offerings
Pureum Kim
University of Southern California
______________________________________________________________________________
A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(BUSINESS ADMINISTRATION)
Conferred May 2017
1
Acknowledgements
I am extremely grateful to my advisor Randy Beatty for his guidance and encouragement on this
project. I also thank the other members of my committee, Mark Defond, Jerry Hoberg, and Clive
Lennox for their guidance and constructive feedback.
This paper has also benefited from discussions and comments from You-Il Park, Sangwan Kim,
Ventsi Stamenov, Satish Sahoo, Jeong Goo Kang, and seminar participants at University of
Southern California and California State University, Fullerton.
I also thank my family and friends for their unconditional support throughout my academic career.
2
Table of Contents
Acknowledgements ....................................................................................................................................... 1
Abstract ......................................................................................................................................................... 3
1. Introduction ............................................................................................................................................... 4
2. SEC Regulatory Review ........................................................................................................................... 9
3. Literature Review and Hypothesis Development ................................................................................... 10
4. Sample and Descriptive Statistics ........................................................................................................... 17
4.1. Sample Construction ........................................................................................................................ 17
4.2. Descriptive Statistics ........................................................................................................................ 19
5. Results ..................................................................................................................................................... 21
5.1. Determinants of Number Comments ............................................................................................... 21
5.2. IPO Financial Restatements ............................................................................................................. 25
5.3. Restatement of Financial Statements after IPO ............................................................................... 28
6. Conclusion .............................................................................................................................................. 30
References ................................................................................................................................................... 32
Figures ........................................................................................................................................................ 37
Appendix ..................................................................................................................................................... 38
Tables .......................................................................................................................................................... 45
3
Abstract
This study analyzes the SEC review process and assesses the SEC’s effectiveness in regulating
IPO firms’ financial disclosures. Using novel SEC review data, I examine the effect of SEC
comments on IPO prospectus’ accounting quality using restatements of IPO firm financial
statements. I find that 18.5% of all registrants have a material restatement, experiencing a 4%
revenue decline and a 64% decrease in net income. I show that an increase in one standard
deviation in accounting comments increases the likelihood of an IPO restatement by 10.3% and
the severity of restatement by 6.4%. During the review process, 68.4% of all restatements of IPO
prospectuses are identified by the SEC. These findings suggest that the SEC has the capacity to
identify and correct accounting problems but misses a substantial number of accounting issues. To
further understand the SEC’s review capability, I examine the financial restatements of the
registrants after the IPO (10-K, 10-Q). I find that the number of accounting comments is not
associated with post-IPO restatements. Overall, these results suggest that the SEC’s effectiveness
is limited to identifying and remediating some but not all accounting issues in the IPO process.
4
Effectiveness of the SEC’s Comment Letters in Initial Public Offerings
1. Introduction
Initial public offerings (IPO) are notorious for engendering substantial information
asymmetry between potential investors and the firm. Prospectus filings to the Securities and
Exchange Commission (SEC) provide an updated source of information for investors prior to the
firm becoming publicly traded. Despite the prospectus’ role in providing information to investors,
there is limited research on the SEC review process that regulates the information content of a
prospectus. This lack of understanding is problematic as lax or excessive SEC regulation may
potentially hinder the function and growth of the IPO market. Fraudulent firms may go public with
deficient disclosures or companies may refrain from going public due to excessive regulatory
scrutiny. Thus, it is critical to examine the IPO process through SEC comment letters, as they may
substantially impact information disclosures, affecting information asymmetry and the IPO market.
To fill this gap in our understanding of the SEC regulation of IPOs, this study examines the effect
of the SEC comments on IPO prospectuses. Specifically, I examine the SEC comment generating
function and its effect on the prospectus’ information content measured through accounting quality
using restatements of IPO financial statements.
Most research reviewing the SEC’s regulatory function has focused on extreme
misreporting such as SEC enforcement actions (Dechow, Sloan, and Sweeny 1996; Erickson,
Hanlon, and Maydew, 2004; Dechow, Ge, Larson, and Sloan 2011). Although the focus on
extreme failures increases our understanding of the regulatory process, it does not shed light on
the SEC’s typical review process, which is more comprehensive and focused on complete and
5
accurate disclosure. Research on the SEC’s review process is still nascent. To date, researchers
have examined the relation between receiving a comment letter and auditor characteristics, usage
of accounting estimates, failure to disclose CEO compensation, and firms’ compliance with SEC
comments (Cassell, Dreher, and Myers, 2013; Boone, Linthicum, and Poe, 2013; Robinson, Xue,
and Yu, 2011; Bozanic, Dietrich, and Johnson, 2014). These studies primarily examine the
determinants of receiving comment letters for publicly traded firms who are reviewed at least once
every three years by the SEC.
1
The studies that examine IPO comment letters are limited. Ertimur
and Nondorf (2006) studies the content of comment letters and its determinants, finding that
managerial expertise is associated with fewer SEC comments. Lowry, Michaeli, and Volkova
(2016) classifies the content of comment letters using Latent Dirichlet Allocation analysis and
finds that higher SEC scrutiny is associated with higher offering price updates and higher
underpricing. Li and Liu (2017) examine the effect of number of comment letters on offering price
and underpricing. They find that registrants that receive more comment letters lower their offering
price but have similar underpricing compared to those IPOs with fewer comment letters.
This limited research on the SEC’s review process of IPOs raises concerns for the
following reasons. First, IPOs are important for the individual firms seeking capital. A poorly
functioning IPO market may not only limit the firm’s growth opportunities but may also diminish
overall economic growth and employment opportunities (Black and Gilson, 1998; Weild, 2011).
2
Second, IPOs are arguably one of the most important events in a firm’s life, as critical corporate
mechanisms including capital structure, corporate governance, accounting, and disclosure policies
1
Section 408 of Sarbanes-Oxley Act establishes the periodicity of the review and scope of the review.
2
A well-functioning market enables firms to raise equity efficiently, allowing them to engage in positive net present
value projects, and contributing to economic growth. However, if the firms are unable to raise capital or face high cost
of capital due to poorly functioning markets, then the firm cannot invest in profitable projects, diminishing profit and
economic growth.
6
are established during this IPO stage (Alti 2006; Beatty and Zajac, 1994; Friedlan, 1994;
Venkataram, Weber, and Willenborg, 2008). It is the first time that all of the corporate mechanisms
are monitored by regulators, underwriters, auditors, law firms, significant owners, and potential
investors. Third, IPOs are inherently risky due to their lack of operating histories, developing
business models, and limited information. For instance, Bhattacharya, Borisov, and Yu (2011)
study publicly listed firms’ life cycles and find that the firms face the highest risk of bankruptcy
during the first three years after going public. Given the high bankruptcy risk, the SEC review
process may provide valuable information about the firms’ risks to investors. Under the Securities
Act of 1933, the SEC has the authority to regulate required information disclosures from firms and
has the accumulated experience of evaluating the quality of critical disclosures.
3
Despite the SEC’s regulatory power and insights, it is unclear whether the SEC comment
process is effective given the following constraints. First, the SEC’s resources are constrained.
4
The SEC must review all public firms once every three years and must monitor various types of
funds, brokers, and development of exotic trading or vehicles with a relatively limited budget of
$1.7 billion dollars in 2014. The SEC has roughly 5,100 employees overseeing a total of 35,000
entities and 515 professionals work for the Division of Corporation Finance reviewing 9,500
publicly traded firms.
5
Second, the SEC’s effectiveness may be impacted by regulatory capture
(Stigler, 1971), since many former SEC employees work for law firms and work as auditors that
serve publicly traded firms (DeHann, Kedia, Koh, and Rajgopal, 2015). Both the Government
Accounting Office and Project on Government Oversight, a nongovernmental organization (NGO),
3
Securities Act of 1933, often called “The Truth in Securities Act,” was created to ensure that investors receive
complete and accurate information about securities.
4
In February 6
th
of 2009, SEC commissioner Paredes spoke about potential limits to SEC’s enforcement due to limited
resources (http://www.sec.gov/news/speech/2009/spch020609tap.htm).
5
Information about the SEC review process can be found at http://www.sec.gov/divisions/corpfin/cffilingreview.htm.
7
have raised concerns about the revolving door.
6
In contrast to the constraining forces of regulatory
capture, the SEC’s effectiveness may also be hampered by potential regulatory overreach. In recent
cases, federal judges have criticized the SEC for aggressive enforcement and going beyond the
securities laws.
7
Hence, the SEC’s aggressiveness may adversely affect information decisions as
firms engage in excessively conservative actions such as limiting forward looking information to
avoid enforcement by the SEC.
Given the SEC’s resource constraints, possible regulatory capture and overreach, the
effectiveness of the SEC’s review process on initial public offerings is unclear. My study seeks to
understand the SEC’s impact on the IPO process.
This study examines the overall SEC review procedure from the comment generating
process to its impact on pre-IPO and post-IPO accounting quality using financial statement
restatements (registrant’s financial statements after going public). Restatements are a good proxy
for accounting quality as they clearly indicate accounting issues. Furthermore, restatements offer
a measure of severity of the accounting issues through the magnitude of the restated amounts. First,
I examine the determinants of the SEC comments. Then I study the effect of SEC comment letters
on the financial restatements during the IPO review. Finally, I examine the effect of comments on
registrants’ financial statements within two years of going public.
Examining the determinants of the SEC comments, I find that larger firms are associated
with more comments overall while highly reputable intermediaries such as Big 4 auditors and
private equity investors are associated with a 14% and 12% reduction in accounting and legal
6
The Project on Government Oversight’s data on former SEC employees can be found at http://www.pogo.org/our-
work/reports/sec-revolving-door.html. GAO report is available at http://www.gao.gov/new.items/d11654.pdf.
7
In the U.S. v. Goyal case, Chief Judge Kozinski lamented that the SEC was overreaching by forcing a case that lacked
materiality (http://cdn.ca9.uscourts.gov/datastore/opinions/2010/12/10/08-10436.pdf).
8
comments, respectively. I also find that SEC reviewers that are the least busy, measured in number
of SEC filings received by the assistant director offices, result in a 30% increase in accounting
comments. For the accounting quality analysis, I find that among 351 IPOs in my sample, 18.5%
of the registrants (65 IPOs) have a material restatement, experiencing on average a 4% drop in
revenues and a 64% decrease in net income. I find that firms receiving more accounting comments,
specifically related to consolidation, acquisition, fair value, revenue recognition, intangible and
off-balance sheet items are more likely to restate during the IPO process. An increase in one
standard deviation of subjective accounting comments increases the probability of restatement by
7.9%. I also find that the number of accounting comments is associated with the severity of the
restatement, measured in terms of the restatement magnitude of revenues or net income. An
increase in one standard deviation of accounting comments increases the probability of a severe
restatement by 6.5%.
In the post-IPO analysis, I find that accounting comments are not associated with
registrant’s financial statements after IPO (10-K, 10-Q). These results show that the SEC comment
letters influence the firm’s accounting up to the point that it becomes public and does not seem to
identify near term future restatements of financial statements.
8
To my knowledge, this is the first paper to comprehensively study the SEC IPO review
process by coding all comment letters issued during the review process and documenting the
prevalence of IPO financial statement restatements. My results increase our understanding of the
SEC’s review process, potentially benefitting IPO investors, managers, and experts in preparing
for an IPO, and can assist regulators in assessing the effectiveness of their regulatory process.
8
The lack of statistical significance may also be attributable to low power (24 post-IPO restatements).
9
Specifically, this is the first study presenting evidence that SEC accounting comments are
associated with the likelihood of an IPO financial restatement. I also find that accounting
comments are associated with the severity of the restatement. I further find that 68.4% of all
restatements of IPO prospectuses are exposed during the SEC review process. Although this study
is unable to address the question of an ideal regulatory process, it does establish that the SEC has
the capacity to identify and correct accounting problems. Finally, my study addresses the concerns
by Leuz and Wyosocki (2016) and Beyer, Cohen, Lyz, and Walther (2010) about disclosure
regulation and answers the call of Lowry, Michaely, and Volkova (2016) for a better understanding
of the IPO review process.
The paper proceeds as follows. Section 2 presents the SEC regulatory review. Section 3
discusses the relevant literature. Section 4 discusses the sample and the descriptive statistics.
Section 5 discusses the results, and Section 6 concludes.
2. SEC Regulatory Review
An IPO firm’s interaction with the SEC starts once the firm submits the initial registration
filing to the SEC. Following the Securities Act of 1933, the SEC’s Division of Corporation Finance
reviews all registration statements including IPO filings.
9
The Division is organized into eleven
industry groups (assistant director offices), where an assistant director is supported by 25 to 35
staff examiners, primarily comprised of accountants and lawyers.
10
Within 30 days of filing the
initial prospectus, the assistant director office reviews the filing and issues a comment letter. The
SEC comments can vary from clarifying questions to inquiries about accounting or disclosure
9
Unless the issuance of security does not fall within an exemption, the issuer must comply with the SEC’s disclosure
requirements.
10
More information can be found at http://www.sec.gov/divisions/corpfin/cffilingreview.htm#.VG0nh_nF98E.
10
deficiencies. By sending the comment letter to the firm, the SEC initiates a review process where
the SEC and the firm communicate through comment letters and responses to the letters.
11
Upon
receipt of the letter, the registrant must respond within ten business days or communicate an
alternative timeframe. After receiving the comment letter, the registrant can accept the SEC’s
changes, request a reconsideration of the comment, or request confidential treatment. Most
contests are resolved at the senior staff level. However, in certain situations, the SEC’s Office of
the Chief Accountant may become involved to resolve a pending issue.
12
Once the assistant
director office is satisfied with the status of the registration filing, it declares the prospectus
effective by issuing a “Completion of Review” letter, and the firm can conduct the initial public
offering.
3. Literature Review and Hypothesis Development
Academics and practitioners have long debated the purpose and the effect of securities
regulation. Proponents argue that securities regulations are essential for market efficiency and to
prevent market failures. In contrast, critics of financial regulation counter that regulators have
limited abilities and often fluctuate between lax and excessive regulation, creating regulatory
booms and busts. This section presents competing regulatory views.
Supporters of securities regulation offer the following two arguments: information
efficiency and failure of private intermediaries. In the first case, SEC regulation improves
information efficiency. Mandatory disclosure enforced by the SEC prevents the underproduction
of information, increasing the efficiency of investment decision making and monitoring of
11
The firm and the SEC reviewer can also communicate through phone using the contact information listed in the
comment letter.
12
See the reconsideration process at https://www.sec.gov/divisions/corpfin/cffilingreview.htm.
11
management. Without the production of sufficient information, financial markets can easily
become a “market for lemons” (Akerlof, 1970), where there is no separation between good and
bad quality firms, leading to market failure. Mandatory disclosure also forces a low cost provider
of corporate information, the firm itself, to provide information to the market. The centralization
of information production can reduce the cost of duplicative research by analysts and investors.
Furthermore, mandatory disclosure may impose greater accountability on the management through
timely and public disclosures, permitting enhanced monitoring of managers. Thus, SEC regulation
prevents market failures and enhances the overall information efficiency of the market.
Second, private intermediaries cannot fully substitute for securities regulation because of
cost and monitoring failures. Intermediaries are not costless. The cost of gathering data and
monitoring may be substantial, reducing the production of valuable information and decreasing
market efficiency. Furthermore, as the recent scandals demonstrate, intermediaries are susceptible
to failures despite their reputational concerns. For instance, analysts and auditors may have
contributed to the dot-com bubble (Coffee, 2003). The dot-com bubble attracted analysts such as
Henry Blodget and Jack Grubman that appeared to have aggressively promoted stocks as opposed
to analyzing the fundamentals.
13
Auditors gave less weight to financial results when issuing going
concern opinions to technology companies during the dot-com bubble (Leone, Rice, Weber, and
Willenborg, 2013). Underwriters’ certification may be short-lived as they provide only limited
assurance of the registrant’s quality up to the IPO (Rock, 2002). Furthermore, underwriters may
face a potential conflict of interest as the IPO firm may become their future client for other services
(Coffee, 2003; Lowry et al., 2017).
13
See http://www.wsj.com/articles/SB963527415634796028.
12
Competition between private intermediaries may not elicit sufficient information to ensure
an efficient market. Before the Exchange Act of 1933, NYSE competed with 33 exchanges and
required substantial disclosures. It required two years of balance sheet and income statement
information and earnings statements for the prior five years. It further required the financial
statements to be periodically updated. Yet firms did not update their disclosures and even delisted
from the NYSE (Ferrel, 2004). Most recently, the Israel Stock Exchange and Brazil Novo Mercado
proposed broader disclosures, requiring stricter corporate governance, and stronger shareholder
rights. As a result of expanded disclosure and governance requirements, many firms delisted from
these exchanges (Ferrel, 2004). In contrast, Neuer Markt boasted its reliance on voluntary
disclosure but later suffered from accounting and market manipulation scandals. Comroad, an
internet company, fabricated 98% of the revenues and severely damaged the exchange’s reputation.
Moreover, Kurt Ochner, a major investment fund, has been charged with manipulating stock prices
(Vitols and Engelhardt, 2005). United Kingdom’s Alternative Investment Market (AIM) boasted
low compliance cost, where it allowed listed firms to either comply with the rules or explain why
they were not complying. Such lax regulation has been criticized for encouraging fraud, including
listing of Langbar International, a fraud investigated by the security regulators.
14
Hence, history
and recent precedents suggest that private intermediaries may not be an alternative to securities
regulation to ensure market efficiency.
In contrast to the arguments proposed by the proponents of regulation, critics present three
reasons why the SEC may not be effective in regulating IPOs: regulatory capture, lack of qualified
regulators, and excessive regulation. First, the SEC’s effectiveness may be diminished through
14
See https://www.theguardian.com/business/2011/jun/24/langbar-international-fraud-history.
13
regulatory capture where the firms the SEC tries to regulate heavily influences the commission.
The regulatory capture theory proposed by Stigler (1971) argues that industries can capture their
regulator through successful organization. His model shows that a group with more at stake is
likely to organize and influence regulation. Regulatory capture of the SEC is even more likely
according to Laffont and Tirole’s model (1991), where complexity of information leads to a large
information asymmetry between the interest group and the regulator, resulting in a higher
likelihood of capture. The complexity of finance is inherent because of uncertain payoffs that are
influenced by many factors. In addition, the development of financial innovation and globalization
has further increased complexity. Hence, the SEC is more likely to be influenced by the financial
sector given this complexity. Regulatory capture theory is further supported by empirical evidence.
Both the Government Accounting Office and Project on Government Oversight (PGO), a non-
profit organization, have raised concerns about the revolving door. GAO (2011) pointed out that
the SEC had lax policies for controlling the revolving door and PGO found that many senior level
SEC officials joined law firms that serve public companies.
Second, the SEC may not have the necessary expertise to regulate effectively. The SEC
has been plagued by high profile enforcement lapses, where major frauds (e.g., Bernie Madoff,
Allen Stanford) flourished while lesser cases received excessive attention (Barnard, 2010). In the
SEC’s Bernie Madoff report, the Inspector General noted that such deficient enforcement stemmed
from a lack of training for entry-level lawyers, “inexperienced enforcement staff,” and a lack of
critical follow-up.
15
The report further criticized many SEC staff for lacking “training” and
familiarity with trading or securities laws. Bond and Glode (2014) propose a model of the labor
15
Report of “US SEC Exch. Communication Office of Investigation of Failure of the SEC to Uncover Bernard
Madoff’s Ponzi Scheme” is available at https://www.sec.gov/news/studies/2009/oig-509.pdf.
14
market for bankers and regulators. In their model, agents with heterogeneous abilities choose
between working as a banker or a regulator, facing a trade-off between compensation and human
capital accumulation (regulatory experience). The model shows that the bankers are more skilled
on average than the regulators as individuals with higher abilities choose banking for its higher
compensation. In a dynamic setting, those with the highest abilities work as a regulator and then
switch to banking to maximize their payoffs. This model indicates that the SEC, on average, may
have inferior talent compared to the finance sector, making regulation difficult. Bond and Glode’s
model (2014) coupled with Laffont and Tirole’s model (1991) suggest that information asymmetry
may be exacerbated by differing abilities leading to weak regulatory monitoring.
Concerns about the effectiveness of the SEC are further supported by the SEC’s limited
budget, officials being negligent during the financial crisis, and recent scandals including the
Madoff and Stanford Ponzi schemes. The SEC has also been blamed for its antiquated technology.
During the Lehman Brother’s failure, the SEC could not assess Lehman’s counterparty exposure,
as the data could not be easily processed.
16
Brummer (2014) also points out that the SEC is still
trying to grasp recent financial innovations including dark pools, Electronic Communication
Network (ECN) 144A trading platforms, and crowdfunding websites. In addition, the SEC has
been cited by the GAO (2015) for its own internal control problems.
17
The report flags deficiencies
including inaccurate inventory records, identifying and summarizing uncorrected misstatements
and issues with information security. These deficiencies suggest that the SEC is operating
inefficiently. Hence, the SEC’s effectiveness is likely to be limited by its constrained abilities
and resources.
16
SEC’s lack of technological capabilities is discussed at http://www.cnbc.com/id/102523725.
17
GAO report is available at http://www.gao.gov/products/GAO-15-387R.
15
Third, the SEC’s effectiveness may also be hampered by the SEC’s potential overreach of
authority. Recently, the legal community has become more concerned about the SEC’s
aggressiveness and potential politicization. For instance, in U.S. v. Goyal case, Chief Judge Alex
Kozinski lamented that the SEC was going beyond its authority by forcing a case that lacked
materiality.
18
In SEC v. Miller, the SEC filed a complaint against Polycom for not disclosing other
compensation that amounted to less than 0.5% of Miller’s total compensation, causing uproar in
the legal community.
19
In SEC v. Wyly, the SEC demanded disgorgements of all profits, even those
that were not related to the securities violations.
20
The district court swiftly dismissed this action
as going beyond the securities laws. With an increasing number of overreaches, the SEC’s
aggressiveness may adversely affect information disclosures as firms engage in excessively
conservative actions such as limiting forward looking information to avoid SEC enforcement.
Overall, the regulation literature offers strong competing regulatory theories and empirical
findings. Proponents of regulation argue that securities regulations promote market efficiency
while its opponents contend that regulators are constrained and may even cause harm through
regulatory overreach. Hence, the effectiveness of SEC regulation remains an empirical question.
In contrast to the effectiveness of regulation literature, the research on the SEC review
process generally finds that comment letters are associated with changes in firm behavior. Bozanic
et al. (2014) study how publicly traded firms respond to the SEC comment letters. They find that
most firms implement the SEC’s suggestions and as a result, experience a reduction in information
asymmetry, measured as lower bid-ask spreads and return volatility. Cassell et al. (2013) find that
smaller firms with smaller auditors take longer to remediate the issues raised by the SEC. These
18
U.S. V. Goyal case is available at http://cdn.ca9.uscourts.gov/datastore/opinions/2010/12/10/08-10436.pdf.
19
SEC V. Miller case is available at https://securitiesdiary.files.wordpress.com/2015/04/sec-v-miller-complaint.pdf.
20
SEC V. Wyly case is available at https://www.sec.gov/litigation/litreleases/2010/lr21607.htm.
16
two studies show that firms mostly comply with SEC comment letters. Furthermore, research has
found that SEC comment letters have an impact on recipient firms’ peers. Brown et al. (2015)
examine the effect of SEC comments on risk factor disclosures and find that peer firms also change
their disclosures after an industry leader has received an SEC comment. SEC comment letters are
heeded not only by the recipient firm but also by its competitors, showing a broad impact of
comment letters on firm disclosures.
Researchers have also examined how comment letters affect firms’ earnings management
and tax avoidance. Cunningham et al. (2016) study the association between comment letters and
earnings management. They find that firms engage in more real earnings management than
accruals management after receiving comment letters. Kubick et al. (2015) examine the
relationship between comment letters and tax avoidance. They find that firms receiving tax-related
comment letters engage in less tax avoidance. In the IPO setting, Ertimur and Nondorf (2006)
study the content of the IPO comment letters and its effect on the information environment,
measured as underpricing and bid-ask spread. They find that management expertise is related to a
lower number of comments and comment letters are not associated with underpricing or bid-ask
spreads. Lowry et al. (2016) use Latent Dirichlet Allocation analysis to classify the content of SEC
comment letters into five categories. They find that registrants receiving more valuation and
compensation-related comments experience higher offering price updates and higher underpricing.
Li and Liu (2017) examine the effect of comment letters on offering price and underpricing. They
find that registrants that receive more comment letters lower their offering price and have similar
underpricing but higher long-term returns compared to those IPOs that received fewer comment
letters. Overall, these studies suggest that SEC comment letters are associated with changes in
firms’ disclosure behavior and actions.
17
Based on the empirical findings of the SEC comment letter literature, the SEC’s IPO review
process is likely to be associated with changes in the IPO prospectus. Therefore, I hypothesize that
the SEC comment letter is associated with changes in disclosures in an IPO prospectus.
Specifically, I surmise that accounting-related comments are associated with the IPO’s accounting
quality measured by financial statement restatements.
H1: SEC accounting comments are associated with the likelihood of IPO financial
restatements.
SEC accounting comments may also reveal problems with the registrant’s accounting
choices. Specifically, numerous accounting comments may reveal the quality of the IPO financial
team, internal control issues, and other accounting functions of the firm. These managerial choices
are not temporary and may affect the accounting quality of the firm in the near term. Hence, I
hypothesize that accounting comments predict the restatement of registrants’ financial statements
after the IPO.
H2: SEC accounting comments predict restatement of registrants’ financial statements within
two years of going public.
4. Sample and Descriptive Statistics
4.1. Sample Construction
This study’s sample period spans from August 1, 2004 to April 5, 2012. The sample period
begins on August 1, 2004, as the SEC began publicly releasing comment letters starting from this
date.
21
The sample period ends on April 5, 2012 to avoid including emerging growth companies
21
Information about the release of comment letters is available at http://www.sec.gov/answers/edgarletters.htm.
18
from the Jumpstart Our Business Startups Act (JOBS ACT).
22
In order to create a comprehensive
IPO dataset, I combine six datasets: SDC, Jay Ritter’s IPO data, Loughran-McDonald IPO data,
Kenny and Patton’s IPO data, IPO Scoop’s IPO data, and Audit Analytics. I collect additional
IPOs by using PERL to crawl through S-1 filings to create a comprehensive IPO dataset.
23
This
study purposefully constrains the sample to new IPOs that have no previous exposure to the SEC
review process. Registrants without exposure to the SEC review process are less likely to be
accustomed to comment letters, which increases the identification of the effect of the SEC’s review
process on an IPO.
Table 1 shows that a total of 1,268 IPOs filed an S-1 after August 1, 2004 and became
public before April 5, 2012. Financial firms (SIC: 6000-6999) are excluded due to their unique
nature of business models and regulatory issues (252 registrants). Foreign firms are excluded to
keep the regulatory environment constant. Units, trusts, acquisition companies, reorganizations,
spin-offs, mergers, and roll-ups are excluded as their structures and business models differ from a
traditional IPO operating firm.
24
This filtering reduces the sample to 412 IPO firms.
25
This study
further excludes registrants that were either public in the past or have applied for an IPO previously
but have withdrawn (18 registrants). Finally, this study requires that the IPO firms have comment
letters on SEC EDGAR and financial and return information available on COMPUSTAT, CRSP,
22
See https://www.sec.gov/divisions/corpfin/guidance/cfjjobsactfaq-title-i-general.htm.
23
Ritter’s data base is available at http://bear.warrington.ufl.edu/ritter/ipodata.htm. Kenny and Patton’s data is
available at http://maryannfeldman.web.unc.edu/data-sources/business-creation-development/kenny-patton-ipo-
database/. IPO scoop’s data is available at http://www.iposcoop.com/.
24
IPO studies typically exclude these types of IPOs. The loss of IPOs is further magnified as many IPOs that are not
included in the datasets are included through hand collection.
25
During my sample period, there is an increase in ADRs after 2007, mainly Chinese firms listing in the US. In
addition, there is an increase of trusts and units.
19
and SDC. The final sample consists of 351 US domestic IPOs with operations that have never been
exposed to the SEC review process.
26
4.2. Descriptive Statistics
Table 2 Panel A describes my sample firm characteristics. The sample firms have average
total assets of $197.9 million (LN_TA=4.15) and average revenues of $148.5 million
(LN_REV=3.51). The average firm age when the registrant goes public is 13 years. In terms of
intermediaries, the vast majority of the IPOs engage a Big 4 auditor and a top underwriter,
consistent with the IPO literature (Beatty and Welch, 1996). For the prospectus, the average length
of MD&A Section, Risk Section, and Notes Section are 18, 18, and 36 pages respectively.
27
On
average, a registrant receives four comment letters, which amounts to 74 comments (T_COM).
The standard deviation of the number of comments is 32, almost 50% of the total comments,
suggesting high variation in both the SEC comment process and the quality of the IPOs.
Approximately one fourth of the comments are related to accounting (T_ACC). T_ACC2, the
number of accounting comments that require more judgment, comprises about a third of the total
accounting comments. Related to SEC comment generating function, the SEC office’s resources
are measured using ADO_BUSY and ADO_SLACK, as a function of the total number of filings that
each assistant director office receives during the IPO review period, representing the office’s
workload. Approximately 11% of the registrants file their S-1 filings when the SEC assistant
director office is busy (ADO_BUSY) while 5% of the firms file their prospectus when the SEC
assistant director office is the least busy (ADO_SLACK).
26
My sample is similar to Loughran and McDonald (2013) and Kenney and Patton (2010).
27
These lengths are in line with IPO practitioner’s guidelines. See A Practical Guide to Going Public, chapter 13.
20
Table 2, Panel B shows restatement amounts for the IPO financial restatements.
28
There
are 23 IPOs that have a change in revenues with an average decline in revenues of $8.78 million
(REV_CH), a 4% drop (REV_PCT). There are 60 IPOs that experience on average 64% drop in net
income (NI_CH). There are 26 firms with change in total assets and on average they experience a
1% increase in assets. The increase in assets is a result of restating asset and liability items. These
statistics indicate that there are significant and material restatements during the IPO process.
Table 2, Panel C shows the registrant’s descriptive statistics for the first two years after
going public. The table shows that the firms on average have increased their total assets to $430
million (LN_TA=5.24) while decreasing their leverage from 1.88 before to 0.42 after IPO,
consistent with initial public offering providing capital to increase the firm size and reduce
leverage. The majority of the firms retain a Big 4 auditor (82%). Finally, 4% of the registrants (24
firms) have a restatement of financial statement within two years of going public.
Table 2, Panel D shows the IPO financial statement and missed restatements by auditors.
Among the Big 4 auditors, KPMG has the highest IPO restatement rate (25%). However,
considering the number of audits, Ernst & Young has the highest IPO restatement percentage
(16.15%). It may be the case that Ernst & Young has the most complex IPOs such as high tech
firms. In terms of missed restatements, Deloitte missed 14% of the restatements, showing that
Deloitte may not be able to fully detect accounting issues of the IPO. The next tier audit firms,
BDO, McGladery, and Grant Thornton, have on average higher rates of IPO restatements
compared to Big 4 auditors. An untabulated t-test confirms that Big 4 auditors have lower rate of
IPO restatements but do not differ in missed restatements. Overall, Panel D shows evidence that
28
Some IPOs restate multiple items (revenues, net income, or total assets) while others only restate one item.
21
Big 4 auditors have lower IPO restatement rates compared to lower tier firms. Yet Deloitte,
specifically, seems to have missed a significant number of accounting issues.
Table 2, Panel E shows the IPO restatements and missed restatements by SEC assistant
director offices. The Beverage, Apparel, and Mining Assistant director office has the largest IPO
restatement rate of 36%. Among the top three offices that do the most reviews, Healthcare &
Insurance office has the highest IPO restatement rate (20.69%). Such high IPO restatement rate
may be related to the complexity of medical firms and their accounting. Consumer/ Information
Technology office has the highest missed restatement rate (14.95%). Such high missed
restatement rate may be attributable to the complexity of information technology firms and their
accounting. Also, it may be a sign of congestion, as IPOs tend to cluster by industry and time.
Overall, Panel E shows evidence that more complex industries seem to have higher rates of IPO
and missed restatements.
5. Results
5.1. Determinants of Number Comments
In this Section, I first examine the determinants of the number of SEC comments. This
analysis provides a better understanding of the SEC review process, specifically how the SEC
generates comments. I hypothesize that the number of comments is associated with firm
characteristics, intermediary skills (e.g. underwriter, law firm), length and complexity of the initial
S-1, and the SEC’s resources. Firm characteristics are revenues (LN_REV), total assets (LN_TA),
loss (LOSS), return on assets (ROA), leverage (LEV), and age (AGE). Intermediary skills are
private equity (PE), venture capital (VC), Big 4 auditor (BIG4), top legal firm
(TOP_MGN_LEGAL) and top underwriter (TOP_UDW). The complexity of the prospectus is
22
measured as the length of the MD&A Section (MDA), Risk Section (RISK), Notes Section
(NOTES), and remaining sections of the prospectus (PROS_OTHER). SEC constraint is measured
as the number of 10-Ks, S-1s, comment letters, and response letters received by the Corporation
Finance’s assistant director office during the 60 days before the filing of the initial S-1, scaled by
the number of 10-Ks, S-1s, comment letters, and response letters received during the surrounding
360 days. I create two SEC constraint variables by dividing the scaled measure into deciles.
ADO_BUSY represents a busy assistant director office, where it is equal to one if it is in the top
decile. ADO_SLACK represents a non-busy assistant director office, where it is equal to one if it
is in the bottom decile.
29
For the regression analysis, I regress the number of comments on the variables of interest
using a negative binomial regression with robust standard errors.
30
Industry and year fixed effects
are included.
31
Table 4 Column (1) shows the determinants of total comments (T_COM). The
coefficient of LN_REV is 0.066 and statistically significant at the 1% level. Calculation of the
marginal effect shows that a 1% increase in revenues results in 0.49 additional comments. This
result is consistent with SEC’s focus on revenue recognition and larger registrants. The coefficient
of LEV is 0.009 and statistically significant at the 1% level. This result is consistent with the SEC’s
closely reviewing firms that are riskier due to higher leverage. Intermediary variables, PE and
BIG4, are negative and statistically significant, at the 10% and 5% levels, respectively. Calculation
of the marginal effects shows that private equity firm investment (PE) results in nine fewer
comments while a Big 4 auditor (BIG4) results in a reduction of ten comments. These effects are
29
This measure is more comprehensive than Gunny and Hermis’ (2015) SEC office busyness measure, which only
includes number of 10-K filings.
30
Negative binomial is superior to OLS given the non-normality of count data but results do not differ.
31
Fama and French 12 Industry definition is used
(http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html).
23
economically significant as PE and BIG4 result in 12% and 14% fewer comments, respectively,
potentially decreasing the cost and time to go public.
32
Top law firm (TOP_MGN_LEGAL) and
Top underwriter (TOP_UDW) are both statistically insignificant. This result is surprising as the
law firm communicates with the SEC and drafts the responses to the SEC. Furthermore, the
underwriter coordinates the overall IPO process. The lack of statistical significance may be
attributable to the measurement of top law firm and top underwriter, which are based on market
shares. MD&A is statistically insignificant. This result is also surprising given SEC and
practitioners’ emphasis on the MD&A section. RISK and NOTES are both statistically significant
at the 5% and 1% levels, respectively. A longer Risk Section is associated with lower comments,
as the firm is fully divulging its risks. A longer Notes Section is likely to proxy for business
complexity and complex accounting, associated with higher comments. The coefficient of
ADO_BUSY is statistically insignificant. In contrast, the coefficient of ADO_SLACK is 0.254 and
statistically significant at the 5% level. Calculation of marginal effects shows that when the
assistant director office is the least busy, it issues 19 additional comments, an increase of 26% on
average. This magnitude is economically significant and shows that the SEC increases its scrutiny
of the prospectus when it has more resources.
Table 4 Column (2) shows the determinants of accounting comments. Consistent with
Table 4 Column (1), LN_REV and LEV are positive and statistically significant at the 1% and 5%
levels, respectively. These results show that larger firms and those with high leverage receive more
accounting comments. The coefficient of BIG4 is -0.247 and it is statistically significant at the 1%
level. Calculation of marginal effect shows that employing a Big 4 auditor results in five fewer
32
Reduction in comments is calculated by dividing the marginal effect by the average number of total comments.
PE: 9/74=12.3% and BIG4: 10/74=13.5%
24
accounting comments. The magnitude of reduction is 25% on average and shows that Big 4
auditors are associated with a significant decrease in the number of comments. The coefficient of
PE is statistically insignificant as private equity investors do not handle accounting issues. Both
RISK and NOTES are statistically significant at the 5% and 1% levels, respectively. The coefficient
of ADO_SLACK is 0.347 and statistically significant at the 5% level. Calculation of marginal effect
shows that an idle assistant director office results in six higher accounting comments, an increase
of 30%. This result shows that reviewers pay closer attention to accounting disclosures when they
are less busy.
Table 4 Column (3) shows the determinants of legal comments. Consistent with Columns
(1) and (2), LN_REV and LEV are positive and statistically significant at the 1% and 5% levels,
respectively. The coefficient of PE is -0.237 and statistically significant at the 1% level.
Calculation of the marginal effect shows that a firm financed (or supported) by a private equity
fund results in 13 fewer comments. The magnitude of reduction is 24% on average. This result is
consistent with private equity investors’ ensuring that the IPO goes well, as their returns are closely
tied to the success of the IPO. The coefficient of BIG4 is statistically insignificant as the auditor
does not handle non-accounting issues. The coefficient of ADO_SLACK is 0.217 and statistically
significant at the 10% level. Calculation of the marginal effect shows that the least busy office
results in 12 higher comments, an increase of 22%. This result shows that reviewers seem to pay
closer attention to legal issues when they are less busy.
Overall, Table 4 shows that SEC comments are a function of firm economics,
intermediaries, prospectus content, and SEC resource constraints. The results show that larger
firms are more likely to get more comments. Levered firms also receive more comments due to
their financial risk. Reputable intermediaries such as a Big 4 auditors result in fewer comments. In
25
addition, Table 4 suggests that the SEC is resource constrained, as the office tends to issue more
comments when it is least busy.
5.2. IPO Financial Restatements
In this Section, I examine the effect of SEC comments on financial restatements during the
IPO process. This analysis addresses the SEC’s concerns for creative accounting in IPOs.
33
I divide
the prospectus restatements that occurred during the SEC review process into two categories; those
that were discovered during the SEC review process (RES_IPO) and those that were discovered
after the registrant had gone public (MISS_RES). This classification enables me to assess the
effectiveness of the SEC’s review process by comparing the accounting issues revealed during the
review process and those that were missed and revealed later after the IPO. I hand collect
restatements by using key words (e.g. restate) and looking for changes in the audited annual
results.
34
I find 18.5% of all IPOs (65 firms) restate their financial statements during the SEC
review process. Using Audit Analytics, I find additional 30 firms that restated their IPO financial
statements after they went public (8.5%). In total, there are 95 registrants (27%) that restated their
IPO prospectus financial statements during or within two years of going public. This restatement
percentage is almost three times higher than the percentage of restatements of public firms
(estimated to be about 8-10%) and supports the SEC’s concern for IPO accounting quality and
increased scrutiny.
35
In Table 5, I examine whether the SEC review process affects the likelihood of a financial
restatement. Specifically, I run a logit regression of SEC comment measures, firm characteristics,
33
See http://www.wsj.com/articles/tailored-accounting-at-ipos-raises-flags-1420677431.
34
SEC requires registrants to include two years of audited financial statements.
35
The Audit Analytics’ report can be found at http://www.auditanalytics.com/0000/custom-reports.php.
26
and intermediaries on IPO restatements. To control for audit effort and risk, I include total accruals
(TOT_ACC), prior restatements (RES_S1) and length of the Notes Section (NOTES). RES_S1 is a
restatement that occurred before the firm filed the prospectus, which proxies for the firm’s
historical accounting quality. I also include Industry and year fixed effects. The first three columns
examine the effect of SEC comments on those IPO restatements that were discovered during the
SEC review process (RES_IPO) and the last three columns examine the IPO restatements that were
discovered after the firm had become public (MISS_RES). Table 5 Column (1) shows that the
coefficient of T_COM is 0.019 and statistically significant at the 1% level. The calculation of the
marginal effect shows that an increase in one standard deviation increases the probability of a
restatement by 7.4%. Column (2) further disaggregates T_COM to accounting comments (T_ACC)
and legal comments (T_LEGAL). The coefficient of T_ACC is 0.069 and statistically significant at
the 1% level, confirming that more accounting comments increase the likelihood of an IPO
financial restatement. The marginal effect of T_ACC is 0.0079, meaning an increase of one
standard deviation increases the likelihood of a restatement by 10.27%. These results provide
evidence that the SEC’s regulatory process affects the registrant’s accounting decisions.
I further disaggregate T_ACC into accounting issues that require significant subjective
judgment and may be used for accruals management. Specifically, T_ACC2 consists of accounting
comments related to revenue recognition, fair value, acquisition, consolidation, off-balance sheet,
and intangibles.
36
T_ACC2_OT consists of the remaining accounting comments. Column (3)
shows that the coefficient of T_ACC2 is 0.126 and statistically significant at the 1% level. The
36
The classification of T_ACC2 requiring more judgment is consistent with Ernst & Young Report documenting that
SEC staff consistently question areas related to significant judgment and estimates including, goodwill impairment
and revenue recognition. See the Ernst and Young’s SEC Comments and Trends Report
(http://www.ey.com/Publication/vwLUAssetsAL/SECCommentsTrends_CC0398_23September2014/$FILE/SECCo
mmentsTrends_CC0398_23September2014.pdf).
27
marginal effect of T_ACC2 is 0.0142, meaning an increase in one standard deviation leads to a
7.9% increase in the probability of restating the accounting numbers. T_ACC2’s effect is
economically significant and shows that the SEC is able to detect and correct accounting issues of
the registrant. Overall, I find that SEC comments are associated with higher IPO restatements,
confirming the first hypothesis (H1).
Table 5’s Column (4), Column (5), and Column (6) examine the effect of SEC comments
on IPO restatements that were discovered after the firm became public (MISS_RES). In all three
columns, the coefficients of the SEC comment measures are statistically insignificant. This result
is quite surprising because it shows that the SEC reviewers were likely unaware of the accounting
issues of the registrants. Surprisingly, the distribution of T_COM and T_ACC of those firms that
restated after the IPO are indistinguishable from those IPOs that never restated (untabulated).
Hence, the results suggest that the SEC reviewers may not have been able to detect accounting
issues during the IPO process.
37
However, interestingly, TOT_ACC, total accruals, is positive and
statistically significant at 5% level in all three columns. The marginal effect of total accruals is
0.16 and an increase of one standard deviation results in a 4.5% increase in the likelihood of a
restatement. These results suggest that the SEC might consider scrutinizing those IPOs with high
total accruals to detect accounting issues.
Table 6 examines whether SEC comments are associated with the severity of the
restatement. RES_OR is equal to two if the IPO’s restated net income or revenue and the percentage
changes in net income and revenue are in the lowest tercile (most negative). RES_OR equals one
for all other restatements and zero for non-restatements. By construction, RES_OR represents the
37
The null result may be due to the lack of power, as there are only 30 missed restatements.
28
most economically significant top or bottom line restatements. Table 6’s results are similar to those
of Table 5 and show that SEC comments are associated with a higher likelihood of a severe
restatement. The coefficients of T_COM and T_ACC are both positive and statistically significant
at the 5% and 1% levels, respectively. Calculations of the marginal effects for RES_OR=2 are
0.0033 and 0.0049, respectively. An increase in one standard deviation in total comments and
accounting comments leads to an increase in the likelihood of a severe restatement by of 10.6%
and 6.5%, respectively. Column 3 shows that the coefficient of T_ACC2 is 0.107 and statistically
significant at the 1% level. Calculation of the marginal effect for RES_OR=2 is 0.0087, meaning
an increase of one standard deviation leads to a 4.7% increase in probability of a severe restatement.
T_ACC2’s effect is economically significant and shows that the SEC is able to detect economically
significant restatements.
Overall, I find that accounting comments are likely to predict restatement of IPO financial
statements. Specifically, I find that accounting comments addressing areas that require subjective
judgment result in higher likelihood of an IPO financial restatement. Also, accounting comments
are associated with the likelihood of a severe restatement, suggesting that the SEC can identify
low accounting quality. However, the analysis of missed IPO restatements shows that the SEC
comments have no association with these restatements, suggesting that the SEC’s process was not
able to identify a significant number of accounting issues.
5.3. Restatement of Financial Statements after IPO
The previous tests have examined the effect of SEC accounting comments on financial
restatements pertaining to the IPO prospectus. This section examines the second hypothesis (H2),
the effect of SEC accounting comments on restatements of financial statements after the IPO (10-
29
K, 10-Q). Table 7 examines the likelihood that a registrant would restate within two years of
becoming public (within two years of the end of the fiscal year that the IPO went public). I use the
restatement data from Audit Analytics and supplement them with hand collected restatements from
SEC filings. I find that 24 registrants restate their financial statements after the IPO. I run a logit
model where POST_RES is equal to 1 in the fiscal year that the firm restates. Following the
restatement literature (Gillette, Jayaraman, and Zimmerman, 2016), I include additional control
variables: book-to-market (BTM), sales growth (SGR), market adjusted one year buy-and-hold
return (BH_RET), and annual return volatility (RET_VOL).
38
BTM controls for the tendency of
firms with high valuations trying to maintain the high values (Burns and Kedia, 2006). RET_VOL
and BH_RET control for the firm’s fundamental economics. I include year and industry fixed
effects and use heteroscedasticity robust errors.
Column (1) shows that the number of total comments (T_COM) does not predict future
restatements. Column (2) shows that the coefficient of T_ACC is also statistically insignificant.
The lack of statistical significance shows that the SEC accounting comments pertain to the IPO
period and do not capture the fundamental accounting quality of the firm such as the competence
of the accounting department. Alternatively, the result may be due to lack of power. However,
interestingly, the coefficient of T_LEGAL is -0.022 and statically significant at the 5% level. This
result is quite perplexing because SEC legal comments are most likely to be relevant during the
IPO process. In addition, T_LEGAL is noisy as it contains numerous bureaucratic comments
including reminders to comply with the securities laws and to submit missing exhibits. One
potential explanation is that T_LEGAL is associated with a permanent characteristic of the firm
38
I am unable to use other measures such as accrual quality or smoothness due to data limitations. In addition, I
cannot use financing variables (e.g. seasoned offering) as the firms just became public a year ago. Furthermore, I
cannot employ compensation variables due to significant loss in observations.
30
such as the business model or governance structure. Column (3) shows that T_ACC2 and
T_ACC2_OT are both statistically insignificant. In contrast, T_LEGAL is statistically significant
at the 10% level. Overall Table 7 suggests that SEC accounting comments issued during the IPO
process are not associated with future restatements, rejecting the second hypothesis (H2).
39
5.4. Robustness Tests
Using only an SDC sample does not change the results. Excluding the financial crisis
period does not affect my results. Excluding IPOs less than $10 million offering or development
stage offerings does not alter my results. Including other control variables such as distress,
exchange, or underwriter’s legal counsel does not change inferences. Using alternative definitions
of top underwriter or top law firm does not affect the results. Using two digits SIC code fixed
effects and clustering the standard errors by industry yields qualitatively similar results. For the
SEC comments, I regroup the comment categories by combining issues that do not affect 10% of
the IPOs and find no differences. Finally, combining certain categories does not change the results.
6. Conclusion
This study provides insights into the SEC review process during the initial public offering
by utilizing novel SEC comment data. I find that SEC comments are a function of firm size,
intermediaries, and congestion of SEC assistant director office. Larger firms tend to receive more
comments; however, high reputation intermediaries may decrease the number of comments. Less
busy SEC assistant director offices tend to issue more comments.
39
As noted earlier, the null result may be due to a lack of power, as there are only 30 missed restatements.
31
In the IPO restatement analysis, consistent with regulatory theory, I find that SEC comment
letters are associated with prospectus’ accounting quality. Registrants receiving more accounting
comments are more likely to restate their IPO financial statements. Furthermore, accounting
comments are associated with the severity of the restatement, showing that the SEC can detect and
correct low accounting quality. During the SEC review process, 68.4% of IPO financial
restatements are revealed, while 31.6% of the restatements are discovered after the firm goes public.
The analysis of missed restatements finds that SEC comments are not associated with these
restatements. Analyzing restatements of financial statements after IPO, I find that SEC accounting
comments are not associated with future restatements. This suggests that the effectiveness of SEC
comments is likely to be confined to the IPO process and does not appear to capture information
related to future restatements after the firm goes public. Overall, the results demonstrate that the
SEC has the capacity to identify and remediate accounting issues during the IPO process. Yet,
these results suggest that there may be room for improvement in the SEC’s IPO review process.
32
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Figures
Figure 1: SEC Review Process
When a firm decides to go public, it files an initial registration statement (e.g. S-1) with the SEC,
which contains critical information about the firm, including business model, management, and
capital structure. Following the Securities Act of 1933, SEC’s Division of Corporation Finance
reviews all Registration statements including IPO filings. The Division is organized by eleven
industry groups (assistant director offices) and is supported by staff examiners who are comprised
of 25 to 35 professionals, primarily accountants and lawyers.
40
After reviewing the initial
prospectus, the assistant director office issues a comment letter to the registrant, initiating a review
process where the SEC and the registrant communicate through comment letters and responses to
the letters. The SEC tries to give the comments within 30 days after the initial prospectus. Upon
receipt of the letter, the registrant needs to respond within ten business days or communicate an
alternative timeframe. The registrant can accept the SEC’s comments, request a reconsideration of
the content of the comment letter, or request a confidential treatment. Most contests are resolved
by a senior level staff. However, in certain situations, SEC’s chief accountant may be involved to
resolve the pending issue. Once the assistant director office is satisfied with the status of the
prospectus, the prospectus is declared effective and the registrant can conduct the initial public
offering.
40
Information about the SEC review process can be found
http://www.sec.gov/divisions/corpfin/cffilingreview.htm#.VG0nh_nF98E.
38
Appendix
Appendix A: SEC Comment Classification
1. Coding Process of Comment Letters
This section describes how I coded the information in the comment letters. Each comment
was first classified as accounting or legal comment. The SEC review process is completed by a
staff accountant and staff lawyer who handle accounting and other (legal) comments, respectively.
Accounting comments are further classified into one of 27 issues. The comments were coded based
on three types of information: header, standard or regulation mentioned in the comment, and the
content of the comment. The SEC categorizes its comments by header. For instance, SEC would
put “revenue recognition” header for comments related to revenue recognition matters. In addition,
the SEC mentions relevant standards or regulations which it bases its comment. For comments that
are difficult to classify from the comment itself, I read the registrant’s response to the comment.
When a comment reflects a variety of issues, I select the issue that is discussed the most. For
instance, if the SEC comment mainly discusses about revenue recognition and a bit about cost then
I would categorize the comment as revenue recognition. This process diminishes the concerns for
subjectivity and boosts the confidence that my coding accurately captures the information in the
comment letter. My coding scheme is congruent with practitioner reports, covering prevalent and
important SEC comments including compensation, pro forma, revenue recognition, and fair
value.
41
41
See PWC’s report on SEC comments for technology IPO firms
(https://www.pwc.com/us/en/technology/publications/assets/pwc-technology-ipo-sec-comments-letter-trends.pdf).
The ranking or order of importance of the comments are not directly comparable because the practitioner report does
not code all the comments but rather presents a general category of comments that the SEC has been focusing on.
My coding criteria for accounting compensation is similar to PWC’s SEC comment letter report
(https://www.pwc.com/us/en/hr-management/publications/assets/pwc-2013-sec-comment-letter-trends-employee-
stock-compensation.pdf).
39
Appendix A: SEC Comment Classification (continued)
2. Accounting Comment Issues
Accounts Receivable: Comments related to accounts receivable and estimation of doubtful
accounts.
Acquisition: Comments related to acquisition, including goodwill and purchase price allocations.
Reference to SFAS 141, SFAS 141R, and ASC 805.
Auditing. Comments related to auditor and audit standards.
Cash flow: Comments related to composition of cash and classification of cash flows. Reference
to SFAS 95.
Contingency: Comments related to commitment and contingencies. Reference to SFAS 5, ASC
450, and SAB Topic 5Y.
Compensation: Comments related to stock option compensation. Reference to SFAS 123R, ASC
718, and FIN 44.
Consolidation: Comments related to consolidation of subsidiaries. Reference to ASC 810.
Cost: Comments related to classification and composition of cost. Reference to SAB Topic 11
and EITF 00-10.
Debt: Comments related to valuation of debt, features of the debt including conversion and
modification of debt. Reference to ASC 470, EITF 96-19, SFAS 34, SFAS 84, EITF 00-27, EITF
02-15, APB 12, and APB 14.
Derivative: Comments related to determining derivatives and hedges. Reference to SFAS 133,
ASC 815, EITF 00-19, and EITF 00-27.
Earnings per Share: Comments related to calculation earnings per share, calculation of shares
outstanding. Reference to SFAS 128, EITF 03-6, and ASC 260.
Fair Value: Comments related to fair value calculation excluding stock option compensation.
References to SFAS 57, ASC 820, and SAB Topic 3:C.
Intangible: Comments related to the valuation of intangibles. Reference to SFAS 142 and ASC
350.
Inventory: Comments related to accounting treatment of inventory. Reference to ARB 43.
Liability: Comments related to accrued expenses, self-insurance, and reserve accounts
(warranty). Reference to ASC 460.
Material Weakness: Comments related to material weakness.
40
Appendix A: SEC Comment Classification (continued)
2. Accounting Comment Issues
Off-Balance Sheet: Comments related to off-balance sheet entities (joint venture and VIE).
Other: Comments related to other accounting issues, including short term investments, leases,
one time charges, and other income.
Plants, Properties, and Equipment: Comments related to PPE and depreciation.
Preferred Securities: Comments related to valuation and features of preferred shares
(conversion).
Pro Forma: Comments related to pro forma.
Restate: Comments related to restatements.
Revenue Recognition: Comments related to revenue recognition.
Segment: Comments related to segment disclosure.
Tax: Comments related to tax accounting (deferred tax, valuation allowance).
41
Appendix B: Descriptive Statistics of the Accounting Comments
This appendix presents the frequency and percentage of each type of accounting comment
issued by the SEC. There are 27 issues related to the accounting area. The first column designates
the area. The second column lists the issue. The third and fourth columns show the number and
percentage of registrants who received a comment about the issue, respectively. The fifth and six
columns present the number of times that the comment has been issued and the percentage
composition of the area topic, respectively. The last column shows the percentage composition of
total comments. The panel is ranked by topic from largest to smallest number of comments (fifth
column). The top three issues are shaded.
Area Issue N# of IPOs % of IPOs Total N# % of Area % of Total
ACCOUNTING COMPENSATION 309 87.78 1522 24.37 5.86
ACCOUNTING REVENUE RECOGNITION 237 67.33 952 15.24 3.66
ACCOUNTING PRO FORMA 197 55.97 617 9.88 2.37
ACCOUNTING INTANGIBLE 129 36.65 279 4.47 1.07
ACCOUNTING ACQUISITION 101 28.69 256 4.10 0.98
ACCOUNTING AUDIT 148 42.05 252 4.04 0.97
ACCOUNTING FAIR VALUE 123 34.94 231 3.70 0.89
ACCOUNTING SEGMENT 109 30.97 213 3.41 0.82
ACCOUNTING COST 127 36.08 197 3.15 0.76
ACCOUNTING TAX 100 28.41 177 2.83 0.68
ACCOUNTING EPS 89 25.28 161 2.58 0.62
ACCOUNTING DER 99 28.13 153 2.45 0.59
ACCOUNTING CLASSIFICATION 88 25.00 117 1.87 0.45
ACCOUNTING PREFERRED 65 18.47 92 1.47 0.35
ACCOUNTING MATERIAL WEAKNESS 65 18.47 87 1.39 0.33
ACCOUNTING CONTINGENCY 53 15.06 79 1.27 0.30
ACCOUNTING ACCOUNTS RECEIVABLE 57 16.19 76 1.22 0.29
ACCOUNTING EQUITY 52 14.77 72 1.15 0.28
ACCOUNTING PPE 47 13.35 70 1.12 0.27
ACCOUNTING DEBT 43 12.22 69 1.10 0.27
ACCOUNTING INVENTORY 41 11.65 62 0.99 0.24
ACCOUNTING CONSOLIDATION 35 9.94 60 0.96 0.23
ACCOUNTING RESTATE 39 11.08 59 0.94 0.23
ACCOUNTING LIABILITY 41 11.65 54 0.86 0.21
ACCOUNTING OFF-BALANCE 24 6.82 47 0.75 0.18
ACCOUNTING CASH FLOW 38 10.80 45 0.72 0.17
ACCOUNTING OTHER 137 38.92 246 3.94 0.95
42
Appendix C: Variable Definition
Firm Characteristics
LN_TA: Log of last audited year’s total assets before offering (mil), obtained from the prospectus.
LN_REV: Log of last audited year’s revenues before offering (mil), obtained from the prospectus.
LOSS: Dummy equal to 1 if the net income (NI) is less than zero, obtained from the prospectus or
COMPUSTAT.
ROA: Net income divided by total assets (NI/TA), obtained from the prospectus or COMPUSTAT.
LEV: Total liabilities divided by total assets (TL/TA), obtained from the prospectus or
COMPUSTAT.
AGE: Age of the firm, obtained from Ritter’s website or hand collection.
TOT_ACC: Total accruals, net income minus cash flow from operations (NI-CFO) divided by total
assets (TA), obtained from the prospectus or COMPUSTAT.
BTM: Book-to-Market, measured as the book value of equity divided by market value of equity,
obtained from COMPUSTAT.
SGR: Sales growth, measured as the percentage annual sales growth, obtained from COMPUSTAT.
BH_ADJ: Market adjusted annual buy-and-hold return, obtained from CRSP.
RET_STD: Annual daily return volatility, obtained from CRSP.
Intermediary
PE: Dummy equals to 1, if the firm is sponsored by a private equity firm, obtained from SDC and
prospectus.
VC: Dummy equals to 1, if the firm is sponsored by a venture capital firm, obtained from SDC and
prospectus.
BIG4: Dummy equals to 1, if the firm is audited by Deloitte, Ernst & Young, KPMG, or PWC,
obtained from Audit Analytics and prospectus.
TOP_UDW: Dummy equals to 1, if the underwriter is ranked 9 Carter-Manaster Ranking for IPO
Underwriters, obtained from Ritter’s website.
TOP_MGN_LAW: Dummy equals to 1, if the registrant employs a top ten law firm in terms of
market share, obtained from SDC.
Prospectus
RES_IPO: Dummy equals to 1, if the registrant restated IPO financial statements during the SEC
review process, obtained from the prospectus.
43
Appendix C: Variable Definition (continued)
MISS_RES: Dummy equals to 1, if the registrant restated IPO financial statements after the firm
went public, obtained from Audit Analytics.
RES_OR: Ordered restatement severity variable. It is equal to two if the IPO’s restated net
income’s or revenue’s amounts and percentages are in the lowest tercile (most negative). It is equal
to one for all other restatements and zero for non-restatements.
RES_S1: Dummy equals to 1, if the registrant restated its IPO financial statement in the initial S-
1 prospectus, obtained from the prospectus.
MDA: Number of pages of the Management Discussion and Discussion section in the initial S-1
prospectus.
RISK: Number of pages of the Risk Section in the initial S-1 prospectus.
NOTES: Number of pages of the Notes Section in the initial S-1 prospectus.
PROS_OTHER: Number of pages of the prospectus excluding MD&A, Risk, and Notes Sections.
SEC
T_COM: Number of total comments issued by the SEC, obtained from all comment letters issued
during the IPO process.
T_ACC: Number of comments related to accounting issues, obtained from all comment letters
issued during the IPO process.
T_ACC2: Number of accounting issues that require significant judgment (revenue recognition, fair
value, acquisition, consolidation, off-balance sheet, and intangibles).
T_ACC2_OT: All accounting comments (T_ACC) except for those included in T_ACC2.
T_LEGAL: All comments excluding accounting comments (T_COM-T_ACC).
ADO_BUSY: Dummy equals to one if the SEC assistant director office is in the top decile of
busyness. Busyness is measured as the number of 10-Ks, S-1s, comment letters, and response
letters received by the assistant director office during the prior 60 days to the filing of the initial
S-1, scaled by the number of 10-Ks, S-1s, comment letters, and response letters received
surrounding 360 days.
ADO_SLACK: Dummy equals to one if the SEC assistant director office is in the bottom decile of
busyness. Busyness is measured as the number of 10-Ks, S-1s, comment letters, and response
letters received by the assistant director office during the prior 60 days to the filing of the initial
S-1, scaled by the number of 10-Ks, S-1s, comment letters, and response letters received
surrounding 360 days.
44
Appendix C: Variable Definition (continued)
IPO Restatement
REV_CH: Change in revenues from the initial prospectus to the last prospectus (mil).
REV_PCT: Percent change in revenues (mil) from the initial prospectus to the last prospectus.
NI_CH: Change in net income from the initial prospectus to the last prospectus.
NI_PCT: Percent change in net income (mil) from the initial prospectus to the last prospectus.
TA_CH: Change in total assets (mil) from the initial prospectus to the last prospectus.
TA_PCT: Percent change in total assets from the initial prospectus to the last prospectus.
45
Tables
Table 1: Sample Selection
This table presents the sample used in this study. The sample period begins on August 1, 2004, as
the SEC began releasing comment letters starting from this date. The sample period ends on April
5, 2012 to avoid including emerging growth companies from the Jumpstart Our Business Startups
Act (JOBS ACT). The IPO sample is constructed by combining six datasets: SDC, Jay Ritter’s
IPO data, Loughran-McDonald IPO data, Kenny and Patton IPO data, IPO Scoop’s IPO data, and
Audit Analytics. Additional IPOs are collected by using PERL to crawl through S-1 filings.
Following the prior literature, financial firms, ADRs, units, trusts, spin-offs, mergers, roll-ups, and
blank check companies are dropped. Firms that were previously public and those without comment
letters are also removed from the sample.
Total number of IPOs with S-1 and 424 filings that filed S-1 after 8/1/2004 and
went public before 4/5/2012
1,268
Less:
Financial (252)
ADR, Foreign Incorporation, Foreign HQ, Unit, Holding Company,
Reorganization, Spin-Off, Merger, Roll-Up, Trusts, and Acquisition companies
Public before/ Withdrawn before (18)
No Comment Letters (5)
No PERMNO/GVKEY (38)
Final number of IPOs 351
(604)
46
Table 2: Summary Statistics
Panel A: IPO
VARIABLES MEAN SD 25th MED 75th
FIRM
LN_TA 4.15 1.40 3.29 4.08 4.91
LN_REV 3.51 2.14 2.66 3.97 4.95
LOSS 0.57 0.50 0.00 1.00 1.00
ROA -0.26 0.57 -0.46 -0.03 0.07
LEV 1.88 4.87 0.57 1.04 2.09
AGE 12.81 12.25 6.00 9.00 14.00
TOT_ACC -0.13 0.28 -0.21 -0.09 -0.02
INTERMEDIARY
PE 0.20 0.40 0.00 0.00 0.00
VC 0.65 0.48 0.00 1.00 1.00
BIG4 0.82 0.38 1.00 1.00 1.00
TOP_UDW 0.74 0.44 0.00 1.00 1.00
TOP_MGN_LEGAL 0.24 0.43 0.00 0.00 0.00
PROSPECTUS
RES_IPO 0.19 0.39 0.00 0.00 0.00
MISS_RES 0.10 0.30 0.00 0.00 0.00
RES_OR 0.34 0.60 0.00 0.00 1.00
RES_S1 0.06 0.24 0.00 0.00 0.00
MDA 18.07 6.76 13.00 17.00 23.00
RISK 17.61 5.77 14.00 17.00 21.00
NOTES 35.91 18.15 25.00 31.00 40.00
PROS_OTHER 97.20 25.24 80.00 94.00 110.00
SEC
T_COM 73.71 32.21 51.00 70.00 91.00
T_ACC 19.62 13.17 10.00 17.00 26.00
T_ACC2 5.39 5.29 2.00 4.00 7.00
T_ACC2_OT 14.19 9.41 7.00 12.00 20.00
T_LEGAL 53.95 25.08 36.00 49.00 68.00
ADO_BUSY 0.11 0.32 0.00 0.00 0.00
ADO_SLACK 0.05 0.21 0.00 0.00 0.00
47
Table 2: Summary Statistics (continued)
Panel B: IPO Restatement
Panel C: Post-IPO Restatement
Panel D: IPO Restatement by Auditor
VARIABLES N# OF FIRMS N# OF OBS. MEAN SD 25th MED 75th
REV_CH 23 51 -8.78 56.23 -1.71 -0.51 0.39
REV_PCT 23 51 -0.04 0.49 -0.07 -0.02 0.01
NI_CH 60 114 -2.07 6.14 -1.03 -0.25 0.13
NI_PCT 60 114 -0.64 3.49 -0.28 -0.03 0.01
TA_CH 26 43 0.32 4.58 -1.25 0.09 0.75
TA_PCT 26 43 0.01 0.07 -0.01 0.00 0.03
VARIABLES MEAN SD 25th MED 75th
POST_RES 0.04 0.20 0.00 0.00 0.00
T_COM 74.63 32.02 52.00 70.00 92.00
T_ACC 20.25 13.29 10.00 17.00 27.00
T_ACC2 5.60 5.36 2.00 4.00 7.00
T_ACC2_OT 14.60 9.56 7.00 12.00 20.00
T_LEGAL 54.24 24.90 37.00 49.00 68.00
LN_TA 5.24 1.18 4.51 5.23 5.85
LEV 0.42 0.33 0.21 0.35 0.55
BTM 0.45 0.52 0.17 0.33 0.62
ROA -0.13 0.32 -0.27 -0.02 0.08
SGR 0.46 1.35 0.00 0.20 0.41
AGE 14.54 12.47 8.00 10.00 16.00
TOT_ACC -0.10 0.15 -0.14 -0.07 -0.03
BH_ADJ 0.00 0.73 -0.43 -0.18 0.22
RET_STD 0.04 0.02 0.03 0.04 0.05
Auditor N# of IPO RES N# of MISS RES N# of Total RES N# of Audit % of IPO RES % of MISS RES % of Total RES
KPMG 7 1 8 28 25.00 3.57 28.57
PWC 10 8 18 73 13.70 10.96 24.66
DELOITTE 6 8 14 57 10.53 14.04 24.56
EY 21 7 28 130 16.15 5.38 21.54
BDO 3 0 3 7 42.86 0.00 42.86
MCGLADREY 4 0 4 10 40.00 0.00 40.00
GRANT THORNTON 4 2 6 20 20.00 10.00 30.00
OTHER 10 4 14 26 38.46 15.38 53.85
48
Table 2: Summary Statistics (continued)
Panel E: IPO Restatement by SEC Assistant Director Office
This table presents the summary statistics for the data used to analyze the effect of SEC review
process on initial public offerings. Comment related variables are measured in units. Panel A
contains the firm and IPO characteristics for 351 IPOs from August 1, 2004 to April 5, 2012. Panel
B describes the restatement amounts and percentages by the 65 IPO restatements. The restatement
amounts are collected from the prospectus. The panel presents the summary statistics conditional
on that the IPO had a change in revenue, net income, or total asset. Panel C describes the summary
statistics of the first two years of the 330 IPOs after going public based on 615 observations. Post-
IPO restatements are obtained from Audit Analytics and SEC filings. Panel D describes the IPO
and missed restatement rates by auditors. Panel E describes the IPO and missed restatement rates
by SEC assistant director offices. Variable definitions are available in Appendix C.
SEC Division Office N# of IPO RES N# of MISS RES N# of Total RES N# of Review % of IPO RES % of MISS RES % of Total RES
Beverage, Apparel, and Mining (9) 9 1 10 25 36.00 4.00 40.00
Consumer/ Information Technology (2&3) 20 16 36 107 18.69 14.95 33.64
Telecommunications (11) 9 4 13 39 23.08 10.26 33.34
Natural Resources (4) 4 1 5 17 23.53 5.88 29.41
Manufacturing & Construction (6) 6 1 7 26 23.08 3.85 26.93
Healthcare & Insurance (1) 12 2 14 58 20.69 3.45 24.14
Electronics and Machinery (10) 4 5 9 62 6.45 8.06 14.51
Transportation & Leisure (5) 1 0 1 13 7.69 0.00 7.69
Real Estate & Commodities (8) 0 0 0 4 0.00 0.00 0.00
49
Table 3: Correlation Matrix
Panel A. IPO
VARIABLES [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23] [24] [25] [26] [27]
[1] LN_TA 1.00 0.61*** -0.31***0.46*** -0.32***0.29*** 0.23*** 0.30*** -0.26***0.15** 0.22***0.16** -0.04 0.07 0.01 -0.06 0.39*** 0.03 0.40***0.28*** 0.05 0.13* 0.06 0.15** -0.01 -0.03 -0.03
[2]LN_REV 0.72*** 1.00 -0.53***0.62*** -0.19***0.38*** 0.18*** 0.30*** -0.33***0.04 0.14** 0.06 0.04 0.09 0.09 -0.01 0.43*** -0.23***0.26***-0.01 0.24*** 0.32*** 0.20*** 0.34*** 0.13* -0.01 0.02
[3] LOSS -0.30***-0.48***1.00 -0.58***0.15** -0.37***-0.32***-0.24***0.39*** 0.07 0.02 0.06 -0.03 -0.04 -0.04 -0.04 -0.05 0.30*** 0.01 0.18*** -0.13* -0.24***-0.12* -0.26***-0.04 -0.09 -0.10
[4] ROA 0.41*** 0.61*** -0.74***1.00 -0.49***0.23*** 0.54*** 0.20*** -0.22***-0.03 0.17** -0.00 0.05 0.06 0.06 0.03 0.18*** -0.28***0.10 -0.10 0.14** 0.23*** 0.13* 0.24*** 0.06 0.04 0.04
[5] LEV -0.22***-0.18***0.20*** -0.31***1.00 -0.08 -0.41***-0.08 0.01 -0.06 -0.10 -0.02 -0.05 -0.03 -0.05 -0.01 -0.09 0.08 -0.04 0.01 0.04 -0.01 0.02 -0.02 0.06 -0.02 -0.01
[6] AGE 0.23*** 0.42*** -0.30***0.35*** -0.08 1.00 0.10 0.37*** -0.42***0.03 -0.02 -0.05 0.07 -0.09 -0.02 0.00 0.01 -0.21***0.17** -0.05 0.13* 0.19*** 0.08 0.21*** 0.06 0.17** 0.01
[7] TOT_ACC 0.13* 0.14* -0.36***0.41*** -0.22***0.06 1.00 0.03 -0.01 0.03 0.08 0.04 -0.04 0.10 -0.02 0.10 -0.06 -0.08 -0.03 -0.03 0.01 0.05 -0.00 0.07 -0.02 0.03 0.00
[8] PE 0.18*** 0.13* -0.15** 0.13* -0.02 0.10 -0.02 1.00 -0.68***-0.09 0.03 -0.06 0.11* -0.10 0.04 -0.04 0.12* -0.13* 0.22***0.05 0.01 0.18*** 0.09 0.21*** -0.08 0.07 -0.01
[9] VC -0.21***-0.24***0.24*** -0.22***0.19*** -0.22***-0.14* -0.36***1.00 0.25***0.19***0.13* -0.11* 0.07 -0.04 -0.01 0.03 0.27*** -0.19*** 0.03 -0.14* -0.20***-0.05 -0.25***-0.06 -0.08 -0.11*
[10] BIG4 0.04 0.01 0.13* -0.13* 0.15** -0.05 -0.14* -0.03 0.18*** 1.00 0.27***0.11* -0.18***-0.02 -0.19*** -0.09 0.16** 0.20*** -0.05 0.13* -0.17** -0.18***-0.17** -0.16** -0.12* -0.02 -0.03
[11] TOP_UDW 0.23*** 0.16** -0.01 0.08 0.05 -0.09 0.04 0.01 0.14** 0.19***1.00 0.13* -0.09 -0.01 -0.07 -0.04 0.26*** 0.08 0.09 0.10 -0.07 -0.00 0.01 -0.01 -0.09 -0.08 -0.17**
[12] TOP_MGN_LEGAL 0.11* 0.09 0.00 0.01 0.03 0.05 -0.04 -0.08 0.12* 0.14** -0.03 1.00 -0.06 -0.01 -0.08 -0.04 0.13* 0.13* 0.02 0.09 -0.08 -0.06 -0.04 -0.06 -0.07 -0.08 -0.00
[13] RES_IPO -0.05 -0.00 0.01 -0.01 0.05 0.02 -0.05 0.04 -0.07 -0.14** -0.10 0.01 1.00 -0.15**0.77*** -0.00 -0.14* -0.11* -0.01 -0.07 0.24*** 0.35*** 0.32*** 0.30*** 0.13* 0.06 -0.01
[14] RES_MISS 0.09 0.09 -0.03 0.04 -0.06 -0.10 0.12* 0.03 0.08 0.09 0.02 0.00 0.00 1.00 0.39*** -0.08 0.07 0.00 0.01 0.04 -0.05 -0.01 0.03 -0.03 -0.07 -0.08 0.03
[15] RES_OR 0.07 0.09 -0.08 0.07 -0.06 0.04 0.07 0.08 -0.02 -0.12* 0.06 0.02 0.43*** 0.25***1.00 -0.05 -0.07 -0.11* 0.02 -0.04 0.20*** 0.28*** 0.26*** 0.25*** 0.10 -0.01 0.01
[16] RES_S1 0.03 0.02 -0.06 0.05 0.09 0.04 0.05 -0.03 -0.02 0.04 0.12* 0.05 0.00 -0.04 -0.02 1.00 0.02 -0.06 0.10 -0.02 0.09 -0.01 -0.02 -0.01 0.12* -0.02 -0.00
[17] MDA 0.42*** 0.44*** -0.03 0.15** 0.02 0.07 -0.13* 0.07 0.09 0.16** 0.29***0.10 -0.06 0.13* 0.05 0.11* 1.00 0.29*** 0.46***0.39*** -0.08 -0.02 0.07 -0.07 -0.09 -0.20*** -0.15**
[18] RISK -0.02 -0.21***0.29*** -0.32***0.12* -0.23***-0.15** -0.11* 0.30*** 0.17** 0.12* 0.05 -0.04 0.05 -0.07 0.03 0.29*** 1.00 0.07 0.53*** -0.30***-0.33***-0.19***-0.34***-0.21***-0.11* -0.23***
[19] NOTES 0.38*** 0.28*** 0.06 -0.01 -0.01 0.12* -0.08 0.06 -0.05 0.08 0.11* 0.03 -0.07 -0.01 0.06 0.05 0.51*** 0.14* 1.00 0.37*** 0.13* 0.18*** 0.19*** 0.15** 0.07 -0.15** -0.01
[20] PROS_OTHER 0.27*** 0.02 0.20*** -0.22***-0.00 -0.08 -0.13* 0.01 0.12* 0.20***0.08 0.08 0.01 0.05 -0.01 0.06 0.40*** 0.52*** 0.42***1.00 -0.12* -0.09 -0.03 -0.11* -0.11* -0.08 -0.02
[21] T_COM 0.04 0.21*** -0.14* 0.15** -0.02 0.13* 0.05 -0.00 -0.10 -0.12* -0.10 -0.08 0.09 -0.04 0.16** 0.05 -0.06 -0.31***0.08 -0.12* 1.00 0.67*** 0.50*** 0.65*** 0.92*** -0.03 0.25***
[22] T_ACC 0.14* 0.33*** -0.23***0.27*** 0.02 0.16** 0.08 0.08 -0.19***-0.19*** -0.07 -0.09 0.19*** -0.05 0.26*** -0.01 0.03 -0.36***0.19***-0.13* 0.68*** 1.00 0.79*** 0.94*** 0.33*** 0.04 0.22***
[23] T_ACC2 0.05 0.18*** -0.08 0.14** 0.05 0.15** 0.03 0.08 -0.09 -0.12* -0.03 -0.11* 0.22*** 0.05 0.23*** 0.03 0.09 -0.22***0.22***-0.05 0.47*** 0.72*** 1.00 0.53*** 0.21*** -0.01 0.16**
[24] T_ACC2_OT 0.14** 0.32*** -0.28***0.29*** -0.01 0.14** 0.10 0.07 -0.21***-0.20*** -0.08 -0.06 0.14** -0.09 0.22*** -0.01 -0.01 -0.37***0.13* -0.14** 0.65*** 0.94*** 0.47*** 1.00 0.33*** 0.05 0.21***
[25] T_LEGAL -0.03 0.10 -0.05 0.07 -0.03 0.08 0.03 -0.07 -0.03 -0.06 -0.13* -0.05 0.01 -0.01 0.09 0.06 -0.09 -0.23***-0.00 -0.11* 0.92*** 0.38*** 0.23*** 0.38*** 1.00 -0.06 0.21***
[26] ADO_BUSY 0.03 -0.00 -0.04 0.03 0.02 0.00 0.01 0.03 -0.06 -0.01 -0.05 -0.03 0.06 -0.08 -0.04 -0.06 -0.12* -0.07 -0.10* -0.07 -0.17** -0.04 -0.05 -0.02 -0.18***1.00 -0.08
[27] ADO_SLACK -0.01 0.03 -0.04 0.04 0.03 0.05 -0.01 0.04 -0.13* -0.10 -0.00 0.04 -0.00 0.00 0.01 0.05 -0.03 -0.06 0.07 0.03 0.13* 0.12* 0.06 0.12* 0.10 -0.09 1.00
50
Table 3: Correlation Matrix (continued)
Panel B. Post-IPO
This table presents Pearson (above diagonal) and Spearman (below diagonal) correlations among the key variables of interest. Panel A shows the
correlation among the variables used in the IPO analysis (Table 4, Table 5, and Table 6). T_ACC is disaggregated into accounting issues related to
significant judgment (revenue recognition, fair value, acquisition, consolidation, off-balance sheet, and intangibles), T_ACC2, and the remaining
accounting comments (T_ACC2_OT). Legal comment (T_LEGAL) is defined as non-accounting comments. Panel B shows the correlation among the
variables used in the post-IPO analysis (Table 7). Variable definitions are available in Appendix C. The statistical significance of the correlation
coefficient is based on a two-tailed test and indicated as follows: *** p<0.01, ** p<0.05, * p<0.10.
VARIABLES [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17]
[1] POST_IPO 1.00 0.04 0.02 0.01 0.02 -0.02 0.05 -0.00 0.01 -0.03 -0.06 -0.06 0.01 0.01 0.01 -0.08 -0.00
[2] LN_TA 0.00 1.00 0.14*** -0.06 0.47*** -0.04 0.20*** 0.08 0.15*** -0.38*** 0.15*** 0.12** 0.17*** 0.09* 0.18*** 0.05 -0.01
[3]LN_REV 0.00 0.22*** 1.00 -0.42*** -0.21*** 0.14*** 0.18*** -0.31*** -0.10* 0.12** 0.00 -0.02 0.06 0.01 0.08* -0.06 -0.07
[4]BTM -0.01 -0.02 -0.31*** 1.00 0.03 -0.15*** -0.02 -0.05 -0.27*** 0.19*** -0.17*** 0.06 0.08* 0.05 0.08* 0.03 0.11**
[5] ROA 0.03 0.48*** -0.11** -0.00 1.00 -0.11** 0.27*** 0.38*** 0.14*** -0.40*** 0.04 0.14*** 0.22*** 0.11** 0.23*** 0.05 0.05
[6] SGR 0.00 0.14*** 0.05 -0.29*** 0.18*** 1.00 -0.09* -0.04 0.04 0.09* 0.01 -0.04 -0.10* -0.07 -0.10* 0.00 -0.05
[7] AGE 0.04 0.15*** 0.17*** 0.01 0.33*** -0.10* 1.00 0.12** -0.01 -0.24*** 0.01 0.11** 0.17*** 0.05 0.21*** 0.06 0.06
[8] TOT_ACC 0.01 0.09* -0.21*** 0.07 0.41*** 0.09* 0.18*** 1.00 0.03 -0.29*** 0.02 -0.07 -0.06 -0.08* -0.04 -0.06 0.04
[9] BH_ADJ 0.05 0.21*** -0.03 -0.43*** 0.27*** 0.20*** 0.05 0.06 1.00 -0.07 0.05 0.02 0.01 0.01 0.00 0.02 -0.04
[10] RET_STD -0.01 -0.34*** -0.02 0.17*** -0.42*** -0.14*** -0.23*** -0.20*** -0.22*** 1.00 -0.08* -0.03 -0.11** -0.06 -0.12** 0.02 -0.00
[11] BIG4 0.00 0.12** -0.02 -0.15*** -0.00 0.01 -0.05 -0.00 0.09* -0.08* 1.00 -0.15*** -0.19*** -0.19*** -0.15*** -0.08* -0.16***
[12] T_COM -0.01 0.08* -0.01 0.07 0.14*** 0.01 0.12** 0.02 0.00 -0.01 -0.13** 1.00 0.67*** 0.49*** 0.65*** 0.91*** 0.25***
[13] T_ACC -0.02 0.17*** 0.13** 0.08 0.21*** 0.01 0.16*** -0.05 0.05 -0.12** -0.12** 0.67*** 1.00 0.78*** 0.93*** 0.32*** 0.35***
[14] T_ACC2 -0.03 0.08 0.10* 0.07 0.09* 0.05 0.13** -0.07 0.04 -0.08* -0.15*** 0.46*** 0.71*** 1.00 0.51*** 0.20*** 0.31***
[15] T_ACC2_OT -0.01 0.18*** 0.11** 0.06 0.23*** -0.00 0.16*** -0.02 0.05 -0.12** -0.10* 0.65*** 0.93*** 0.45*** 1.00 0.33*** 0.31***
[16] T_LEGAL -0.00 0.02 -0.07 0.04 0.06 0.02 0.07 0.03 -0.02 0.03 -0.10* 0.91*** 0.37*** 0.22*** 0.37*** 1.00 0.13**
[17] RES_IPO -0.02 0.03 -0.02 0.07 0.07 -0.02 0.08* 0.01 0.06 0.02 0.01 0.16*** 0.26*** 0.19*** 0.24*** 0.07 1.00
51
Table 4: Determinants of SEC Comments
(1) (2) (3)
VARIABLES T_COM T_ACC T_LEGAL
LN_REV 0.066*** 0.117*** 0.053**
[0.021] [0.026] [0.024]
LN_TA -0.013 -0.052* -0.006
[0.024] [0.030] [0.027]
LOSS 0.072 -0.050 0.123*
[0.062] [0.085] [0.069]
ROA 0.030 0.038 0.042
[0.061] [0.087] [0.065]
LEV 0.009*** 0.012** 0.008**
[0.003] [0.005] [0.004]
AGE 0.000 -0.001 0.001
[0.002] [0.003] [0.002]
PE -0.127* 0.160 -0.237***
[0.073] [0.097] [0.085]
VC 0.015 0.186** -0.030
[0.069] [0.089] [0.079]
BIG4 -0.148** -0.247*** -0.105
[0.061] [0.075] [0.071]
TOP_MGN_LEGAL -0.069 -0.101 -0.059
[0.049] [0.067] [0.057]
TOP_UDW 0.011 0.024 -0.011
[0.053] [0.078] [0.058]
MDA -0.007 -0.013** -0.005
[0.005] [0.007] [0.005]
RISK -0.012** -0.019** -0.010
[0.005] [0.008] [0.006]
NOTES 0.004*** 0.007*** 0.002
[0.001] [0.002] [0.002]
PROS_OTHER 0.000 0.003* -0.000
[0.001] [0.002] [0.001]
ADO_BUSY -0.089 0.008 -0.129
[0.076] [0.096] [0.082]
ADO_SLACK 0.254** 0.347** 0.217*
[0.103] [0.172] [0.111]
CONSTANT 4.533*** 2.747*** 4.311***
[0.226] [0.335] [0.249]
YEAR/ IND FE YES YES YES
Observations 351 351 351
WALD CHI 185.2 291.7 107.6
Prob> Chi2 0 0 0
52
Table 4: Determinants of SEC Comments (continued)
This table presents the results of a negative binomial regression, the number of comments are
regressed on firm, intermediary, and prospectus characteristics. Column (1), Column (2), and
Column (3) show the results of total comments (T_COM), accounting comments (T_ACC) and
legal comments (T_LEGAL), respectively. All variables are as defined in Appendix C. Year and
industry fixed effects are included. Heteroscedasticity robust standard errors are used and appear
in brackets. ***, **, and * denote statistical significance at the 1%, 5%, and 10% levels,
respectively.
53
Table 5: IPO Restatement
(1) (2) (3) (4) (5) (6)
DEP. VAR.
T_COM 0.019*** -0.008
[0.006] [0.006]
T_ACC 0.069*** -0.013
[0.016] [0.018]
T_ACC2 0.126*** 0.056
[0.040] [0.048]
T_ACC2_OT 0.044** -0.043
[0.022] [0.030]
T_LEGAL 0.001 0.002 -0.007 -0.006
[0.007] [0.007] [0.008] [0.008]
LN_TA -0.164 -0.156 -0.149 -0.067 -0.068 -0.043
[0.181] [0.173] [0.167] [0.332] [0.330] [0.327]
LN_REV 0.045 0.008 0.020 0.297 0.299 0.298
[0.144] [0.143] [0.144] [0.230] [0.228] [0.233]
LOSS 0.398 0.691 0.718 -0.268 -0.281 -0.228
[0.457] [0.483] [0.497] [0.545] [0.541] [0.540]
ROA 0.926 1.031 1.034 -0.542 -0.544 -0.528
[0.633] [0.643] [0.646] [0.644] [0.648] [0.670]
LEV -0.026 -0.044 -0.043 -0.088 -0.083 -0.079
[0.040] [0.093] [0.083] [0.132] [0.129] [0.132]
AGE -0.001 -0.002 -0.003 -0.033 -0.033 -0.033
[0.014] [0.013] [0.013] [0.048] [0.048] [0.049]
TOT_ACC -1.277 -1.410 -1.456 1.997** 2.010** 2.039**
[0.925] [0.962] [0.971] [0.850] [0.856] [0.839]
RES_S1 -0.252 0.169 0.173 -1.403 -1.427 -1.515
[0.650] [0.677] [0.654] [1.046] [1.078] [1.082]
PE 0.955 0.777 0.773 -0.644 -0.612 -0.689
[0.586] [0.550] [0.560] [0.751] [0.741] [0.725]
VC 0.305 0.187 0.124 0.560 0.573 0.416
[0.527] [0.515] [0.517] [0.811] [0.810] [0.790]
BIG4 -0.837** -0.674 -0.627 -0.499 -0.520 -0.394
[0.425] [0.433] [0.440] [0.518] [0.527] [0.572]
TOP_UDW -0.402 -0.474 -0.478 -0.459 -0.456 -0.473
[0.395] [0.403] [0.398] [0.547] [0.550] [0.564]
NOTES -0.006 -0.012 -0.014 0.010 0.010 0.008
[0.011] [0.009] [0.009] [0.011] [0.011] [0.012]
PROS_OTHER 0.006 0.004 0.003 0.003 0.003 0.002
[0.008] [0.007] [0.007] [0.008] [0.008] [0.009]
CONSTANT -5.707*** -5.117*** -4.838*** -0.614 -0.624 -0.318
[1.494] [1.453] [1.454] [1.700] [1.703] [1.790]
YEAR/ IND FE YES YES YES YES YES YES
Observations 351 351 351 351 351 351
WALD CHI 65.03 64.44 61.35 53.96 55.40 61.51
Prob> Chi2 0 0 0 0 0 0
RES_IPO MISS_RES
54
Table 5: IPO Restatement (continued)
This table presents the results from a logistic regression of the IPO restatement
(RES_IPO/MISS_RES) as a function of SEC comment letter, firm, intermediary, and prospectus
characteristics. RES_IPO is an indicator variable equal to 1, if the registrant restated IPO financial
statements during the SEC review process, and zero otherwise. MISS_RES is an indicator equal to
1, if the registrant restated IPO financial statements after the firm went public, and zero otherwise.
Column (1) presents the results using the total number of comments (T_COM) and Column (2)
presents the results from disaggregating the total number of comments into total number of
accounting comments (T_ACC) and legal comments (T_LEGAL). T_LEGAL is non-accounting
comments. Column (3) further disaggregates T_ACC into accounting issues subject to significant
judgment and estimates (revenue recognition, fair value, acquisition, consolidation, off-balance
sheet, and intangibles), T_ACC2, and the remaining accounting comments (T_ACC2_OT). All
variables are as defined in Appendix C. Year and industry fixed effects are included.
Heteroskedasticity robust standard errors are used and appear in brackets. ***, **, and * denote
statistical significance at the 1%, 5%, and 10% levels, respectively.
55
Table 6: Ordered IPO Restatement
(1) (2) (3)
DEP. VAR.
T_COM 0.010**
[0.004]
T_ACC 0.049***
[0.012]
T_ACC2 0.107***
[0.030]
T_ACC2_OT 0.023
[0.017]
T_LEGAL -0.005 -0.004
[0.006] [0.006]
LN_TA -0.135 -0.116 -0.111
[0.171] [0.162] [0.164]
LN_REV 0.224* 0.212* 0.224*
[0.120] [0.118] [0.120]
LOSS 0.118 0.329 0.397
[0.386] [0.384] [0.406]
ROA -0.005 0.016 0.013
[0.570] [0.549] [0.547]
LEV -0.061 -0.097 -0.098
[0.074] [0.103] [0.107]
AGE -0.016 -0.018* -0.018
[0.012] [0.011] [0.011]
TOT_ACC -0.024 -0.131 -0.072
[0.852] [0.833] [0.833]
RES_S1 -0.957 -0.695 -0.712
[0.705] [0.732] [0.726]
PE 0.486 0.228 0.157
[0.469] [0.455] [0.469]
VC 0.562 0.501 0.362
[0.490] [0.479] [0.480]
BIG4 -0.970** -0.867** -0.799**
[0.386] [0.376] [0.384]
TOP_UDW -0.326 -0.375 -0.386
[0.355] [0.353] [0.355]
NOTES -0.002 -0.005 -0.007
[0.008] [0.007] [0.007]
PROS_OTHER 0.004 0.003 0.003
[0.006] [0.006] [0.006]
CONSTANT_1 2.316*** 1.996** 1.789**
[0.876] [0.886] [0.869]
CONSTANT_2 4.205*** 3.961*** 3.772***
[0.896] [0.913] [0.893]
YEAR/ IND FE 351 351 351
Observations YES YES YES
WALD CHI 44.16 58.98 64.47
Prob> Chi2 0.02 0.00 0.00
RES_OR
56
Table 6: Ordered IPO Restatement (continued)
This table presents the results from an ordered logistic regression of the severity of restatement
(RES_OR) as a function of SEC comment letter, firm, intermediary, and prospectus characteristics.
RES_OR is an ordered restatement severity variable. It is equal to two if the IPO’s restated net
income’s or revenue’s amounts and percentages are in the lowest tercile. It is equal to one for all
other restatements and zero for non-restatements. Column (1) presents the results using total
number of comments (T_COM) and Column (2) presents the results from disaggregating the total
number of comments into total number of accounting comments (T_ACC) and legal comments
(T_LEGAL). T_LEGAL is non-accounting comments. Column (3) further disaggregates T_ACC
into accounting issues subject to significant judgment and estimates (revenue recognition, fair
value, acquisition, consolidation, off-balance sheet, and intangibles), T_ACC2, and the remaining
accounting comments (T_ACC2_OT). All variables are as defined in Appendix C. Year and
industry fixed effects are included. Heteroskedasticity robust standard errors are used and appear
in brackets. ***, **, and * denote statistical significance at the 1%, 5%, and 10% levels,
respectively.
57
Table 7: Restatement of Financial Statements after IPO
(1) (2) (3)
DEP. VAR.
T_COM -0.014
[0.009]
T_ACC 0.008
[0.019]
T_ACC2 -0.011
[0.046]
T_ACC2_OT 0.017
[0.027]
T_LEGAL -0.022** -0.022*
[0.011] [0.012]
IPO_RES 0.347 0.153 0.167
[0.543] [0.578] [0.585]
LN_TA 0.105 0.110 0.117
[0.211] [0.212] [0.218]
LEV 0.104 -0.064 -0.101
[0.770] [0.781] [0.807]
BTM 0.278 0.201 0.190
[0.609] [0.615] [0.605]
ROA -0.655 -0.791 -0.807
[1.000] [1.048] [1.050]
SGR -0.071 -0.047 -0.048
[0.105] [0.113] [0.112]
AGE 0.027* 0.027* 0.027*
[0.015] [0.014] [0.014]
TOT_ACC 0.517 0.716 0.619
[1.669] [1.783] [1.783]
BH_RET 0.221 0.198 0.194
[0.249] [0.255] [0.255]
RET_VOL 18.214 20.235 20.922
[18.464] [18.700] [19.078]
BIG4 -0.765 -0.699 -0.746
[0.479] [0.510] [0.517]
CONSTANT -3.791** -3.848** -3.891**
[1.920] [1.918] [1.910]
YEAR/ IND FE YES YES YES
Observations 615 615 615
WALD CHI 46.66 55.34 53.92
Prob> Chi2 0.001 0.001 0
POST_RES
58
Table 7: Restatement of Financial Statements after IPO (continued)
This table presents the results of a logistic regression of the restatement of financial statements
after IPO within two years (POST_RES) as a function of SEC comment letter, firm characteristics,
and accruals management related measures. POST_RES is equal to 1 in the fiscal year that the
firm restates, and zero otherwise. Column (1) presents the results using the total number of
comments (T_COM) and Column (2) presents the results of disaggregating the total number of
comments into total number of accounting comments (T_ACC) and legal comments (T_LEGAL).
T_LEGAL is non-accounting comments. Column (3) further disaggregates T_ACC into accounting
issues subject to significant judgment and estimates (revenue recognition, fair value, acquisition,
consolidation, off-balance sheet, and intangibles), T_ACC2, and the remaining accounting
comments (T_ACC2_OT). All variables are as defined in Appendix C. Year and industry fixed
effects are included. Heteroskedasticity robust standard errors are used and appear in brackets.
***, **, and * denote statistical significance at the 1%, 5%, and 10% levels, respectively.
Abstract (if available)
Abstract
This study analyzes the SEC review process and assesses the SEC’s effectiveness in regulating IPO firms’ financial disclosures. Using novel SEC review data, I examine the effect of SEC comments on IPO prospectus’ accounting quality using restatements of IPO firm financial statements. I find that 18.5% of all registrants have a material restatement, experiencing a 4% revenue decline and a 64% decrease in net income. I show that an increase in one standard deviation in accounting comments increases the likelihood of an IPO restatement by 10.3% and the severity of restatement by 6.4%. During the review process, 68.4% of all restatements of IPO prospectuses are identified by the SEC. These findings suggest that the SEC has the capacity to identify and correct accounting problems but misses a substantial number of accounting issues. To further understand the SEC’s review capability, I examine the financial restatements of the registrants after the IPO (10-K, 10-Q). I find that the number of accounting comments is not associated with post-IPO restatements. Overall, these results suggest that the SEC’s effectiveness is limited to identifying and remediating some but not all accounting issues in the IPO process.
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Asset Metadata
Creator
Kim, Pureum
(author)
Core Title
Effectiveness of the SEC’s comment letters in initial public offerings
School
Marshall School of Business
Degree
Doctor of Philosophy
Degree Program
Business Administration
Degree Conferral Date
2017-05
Publication Date
04/18/2019
Defense Date
03/20/2017
Publisher
Los Angeles, California
(original),
University of Southern California
(original),
University of Southern California. Libraries
(digital)
Tag
IPO,OAI-PMH Harvest,restatement,SEC,SEC comment letters
Format
theses
(aat)
Language
English
Contributor
Electronically uploaded by the author
(provenance)
Advisor
Beatty, Randy (
committee chair
), Jerry (
committee member
), DeFond, Mark (
committee member
), Lennox, Clive (
committee member
), (
Hoberg
)
Creator Email
eversuhoshin@gmail.com,pureum.kim@usc.edu
Permanent Link (DOI)
https://doi.org/10.25549/usctheses-oUC11255894
Unique identifier
UC11255894
Identifier
etd-KimPureum-5196.pdf (filename)
Legacy Identifier
etd-KimPureum-5196
Dmrecord
360342
Document Type
Dissertation
Format
theses (aat)
Rights
Kim, Pureum
Internet Media Type
application/pdf
Type
texts
Source
University of Southern California
(contributing entity),
University of Southern California Dissertations and Theses
(collection)
Access Conditions
The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the author, as the original true and official version of the work, but does not grant the reader permission to use the work if the desired use is covered by copyright. It is the author, as rights holder, who must provide use permission if such use is covered by copyright.
Repository Name
University of Southern California Digital Library
Repository Location
USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA
Repository Email
cisadmin@lib.usc.edu
Tags
IPO
restatement
SEC
SEC comment letters