ID:JJF00292

Title:

Earnings quality and valuation in IPOs

Author:Kyoko Nagata
Hiroyuki Makino

Pages:

77-90

Is Part Of:

Japan Journal of FinanceVol. 32 / No. 1.2
Feb. 2012

Publisher

Japan Finance Association

ISSN:

2186-3792

経営財務研究第 32 巻第 1・2 合併号■大会特集論文

Earnings Quality and Valuation in IPOs ＊Kyoko Nagata（Tokyo Institute of Technology）

Hiroyuki Makino（Tokyo Institute of Technology）
Abstract

Recent literatures provide evidence that IPOs are not necessarily “underpriced” with respect
to their fair/intrinsic value. This paper examines what causes over- / under- valuation at theoffer price by focusing on the effect of earnings quality and the role of institutional investors
and underwriters in the pricing process. With an improved approach to estimate the value of
IPO ﬁrms, we ﬁnd that extent of overvaluation is positively associated with aggressive earnings
management for IPOs during “the auction regime”, when the involvement of informed partiesare limited, whereas such relationship is not observed for IPOs with book building where
institutional investors and underwriters play a greater role in the pricing process.
Keyword：Initial public offerings, Valuation, Underpricing, Earnings management, IPO pricing
process.

１

Introduction

It is well known that when companies go public, the first-day market price is generally
substantially above the offer price at which investment banker sells stocks to investors, resulting ina large ﬁrst day return. This ﬁrst day return has been one of the most controversial issues in initialpublic offerings (IPOs) literature. Based on the assumption that market price reﬂects fair value inan efﬁcient market, the increase of stock price on the ﬁrst day of trading is taken as an evidence of“underpricing”1. However, recent researches offer an alternative view of underpricing that issuers*

We gratefully acknowledge many valuable comments and suggestions from an anonymous referee,
Linyu Zhai (managing editor), Katsushi Suzuki, and Ghon Rhee. We would also like to thank theseminar participants at the 36th Japan Finance Association annual conference for their helpfulcomments. This work was supported by JSPS Grant-in-Aid for Scientiﬁc Research (C)24510182.1

1

See Ibbotson et al. (1994), Ritter and Welch(2002),and Ljungqvist (2007) for the list of theories forunderpricing.

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経営財務研究第 32 巻第 1・2 合併号

underprice IPOs not necessarily with respect to the fair value. Purnanandam and Swaminathan(2004) examine this notion empirically and ﬁnd that the U.S. IPOs are, on average,“over-priced”atthe offer price relative to the valuation based on industry peer multiples.
This study attempts to explain what causes“over-/under- pricing”relative to fair/intrinsic value
by investigating the effect of earnings quality and the role of institutional investors/underwriters in
IPO pricing process. Speciﬁcally, we hypothesize that aggressive earnings management causes“offer
price’s over-pricing”when the involvement of institutional investors and underwriters are limited
whereas such relationship does not exist when they play a greater role in the pricing process.
IPO has been often cited as a typical occasion for which managers are strongly motivated tooverstate earnings to sell stocks at an inﬂated price. Several studies document evidence consistent
with this hypothesis (Friedlan, 1994; Teoh et al., 1998a; Teoh et al., 1998b; Ducharme et al., 2004),
but more recent studies find that IPO firms, on average, manage earnings more conservatively(Fan, 2007; Ball and Shivakumar, 2008). The mixed results indicate that some managers inﬂate
earnings around IPOs while others do not; the quality of reported earnings varies across IPO
ﬁrms. Generally, aggressive earnings management deteriorates quality of earnings, which signiﬁes
valuation uncertainty about IPOs. Naturally, difference in the extent of earnings manipulation
among IPO ﬁrms is potentially an important factor to explain why some ﬁrms are more“over- /under- priced”than others with respect to their fair/intrinsic value. At the same time, the ability
and incentive to estimate and adjust for the valuation uncertainty related with earnings quality
may depend on the investor type.
With a sample of 1,288 ﬁrms that went public in JASDAQ from 1989 to 2011, we estimate fair/
intrinsic value of IPOs using price multiples of comparable ﬁrms, and ﬁnd a signiﬁcantly positive
relationship between the extent of earnings management and“over-pricing”with respect to thefair/intrinsic value during“the auction regime”, when the involvement of institutional investors
and the role of underwriters were limited2. The results also suggest that earnings quality works
as an important factor in determining offer price of IPOs with book building, where institutional
investors/underwriters play a greater role in the pricing process. These results are consistent withthe prior evidence that underpricing of book-building IPOs are signiﬁcantly greater than those of
auctions (Kaneko and Pettway, 2003; Kerins et al. 2007). The reason why auction IPOs experiencelower underpricing may be attributed to the relatively uninformed individual investors’ tendency to“over-value”the IPOs with reported earnings inﬂated through earnings management.
This study makes several contributions to the literature. First, we introduce an improved2

Kerins et al. (2007) discuss that during the auction regime, regulations and underwriter-imposed
restrictions on bidding encouraged participation by individual investors, and institutional investors
generally did not participate in the IPO market. They also refer to the underwriters’ commentson the popular press that the auction process could produce excessively high bids relative to“fairvalue.”

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経営財務研究第 32 巻第 1・2 合併号

procedure to estimate fair/intrinsic value of IPO firms, by correcting the potential biases of the
Purnanadam and Swaminathan (2004)’s methodology. In addition, this study provides evidence that
aggressive earnings management tends to cause“over-valuation”when less informed individual
investors dominate the pricing process without the involvement of institutional investors/
underwriters.
The remainder of this study is organized as follows. Section 2 discusses the research design in thecontext of the related prior literatures. Section 3 presents sample and descriptive statistics. Section
4 reports the empirical results, and section 5 presents a summary and concluding remarks.

２

Research design⑴

Choosing comparable non-IPO industry peers to estimate fair/intrinsic value of IPOs

In the ﬁrst step to estimate fair/intrinsic value using price multiple, we select an industry peerwith comparable operating characteristics for each IPO ﬁrm in our sample. Our matching approach
is similar in spirit to Purnanandam and Swaminathan (2004) who ﬁnd a non-IPO industry peerwith comparable sales and EBITDA proﬁt margin, but ours is more simple and balanced between
size and proﬁtability. Purnanadam and Swaminathan (2004) group ﬁrms in each industry into threeportfolios based on past sales and then split each sales-based portfolio into three portfolios basedon past EBITDA proﬁt margin. After matching each IPO to the appropriate industry-sales-EBITDA
proﬁt margin portfolio, they ﬁnd a matching ﬁrm that is closest in sales to the IPO ﬁrm from theassigned portfolio. One concern about Purnanandam and Swaminathan (2004)’s method is to place
too much emphasis on ﬁrm size, which sometimes results in choosing a ﬁrm that is different fromthe one we would choose with the equal emphasis on both size and proﬁtability.3 Now, suppose IPO
ﬁrm X has sales revenues of 102 and EBITDA proﬁt margin of 18%, and there are two companies
in the appropriate industry-sales-EBITDA margin portfolio; company A with sales revenues of 100
and EBITDA proﬁt margin of 10%, and company B with sales revenues of 105 and EBITDA proﬁt
margin of 20%. In this case, company B seems more comparable to ﬁrm X when both metrics are
considered. However, in fact, company A is selected with Purnanandam and Swaminathan (2004)’s
method, as company A’s sales revenues is closer to ﬁrm X than company B, although it is not clear
whether company size is a dominant factor for valuing IPO ﬁrm. To avoid this bias, we apply the3

Zheng (2007) indicates that in Purnanandam and Swaminathan (2004)’s method biases are possible
in the three areas; inclusion of new primary shares, cash holdings, and capital structure regarding
the valuation method, but does not mention the bias in choosing matching ﬁrms. As described in
the later section, we consider the possible bias related with the difference in capital structure when
we estimate fair/intrinsic value.

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経営財務研究第 32 巻第 1・2 合併号

following approach to select a matching ﬁrm for each IPO ﬁrm.
We ﬁrst consider all publicly traded ﬁrms in Japanese market whose data are available for theﬁscal year prior to the IPO year. After eliminating those ﬁrms that went public during the past
three years, we group ﬁrms into industry portfolio using the ﬁve-digit Nikkei industry code. Then,from the appropriate industry portfolio, we choose a ﬁrm that is closest in size and proﬁtability
to IPO ﬁrm. More speciﬁcally, we select industry peer with minimum total of squared deviation ofsales revenues and EBITDA proﬁt margin: ((Sales Match – Sales IPO)/ Sales IPO)2 + ((EBITDA proﬁt
margin Match – EBITDA proﬁt margin IPO)/ EBITDA margin IPO)2, where Sales Match is matching ﬁrm’s
sales revenues, and Sales IPO is IPO ﬁrm’s sales revenues; likewise EBITDA proﬁt margin Match ismatching ﬁrm’s EBITDA proﬁt margin, and EBITDA proﬁt margin IPO is IPO ﬁrm’s EBITDA proﬁt
margin. If stock price data prior to the IPO date is not available for the selected ﬁrm, then we workover the same selection process and ﬁnd a ﬁrm with the second smallest sum of squared deviationof sales revenues and EBITDA proﬁt margin4. During the matching process, we do not restrict thesame matching ﬁrm from being chosen as a matching ﬁrm for other IPO ﬁrm.

IPO valuation using comparable firm’s price multiple5⑵

We estimate fair/intrinsic value for each IPO ﬁrm based on the matching ﬁrm’s price multiples;
enterprise value to sales multiple and enterprise value to EBITDA multiple. Purnanandam andSwaminathan (2004) use price to sales and price to EBITDA, however we also include value ofdebts to avoid possible bias related with capital structure suggested by prior literatures (Kim andRitter, 1999; Zheng, 2007). Consequently, the fair/intrinsic value (Enterprise Value: EV) for IPO
ﬁrms in this study is computed as follows:
EVSALES = ((Matching ﬁrm’s stock price × shares outstanding + book value of total debts) /Matching ﬁrm’s prior ﬁscal year sales revenues) × IPO ﬁrm’s prior ﬁscal year sales
revenues,
EVEBITDA = ((Matching ﬁrm’s stock price × shares outstanding + book value of total debts) /Matching ﬁrm’s prior ﬁscal year EBITDA) × IPO ﬁrm’s prior ﬁscal year EBITDA.
Based on the computed fair/intrinsic enterprise value, we calculate the offer price P/V ratios of
IPO ﬁrms as:

4

We allow those firms being selected as matching firms that lack closing stock price of the day
immediately prior to the IPO offer date but at least have closing price 5 days before the offer date.

5

Although discounted cash ﬂow (DCF) method is widely used for valuation, we use industry peer’s
price multiple for several reasons: comparability to prior researches including Purnanandam andSwaminathan (2004) and Kim and Ritter (1999), difﬁculties to estimate future cash ﬂow and/or
appropriate discount rate for pre-IPO ﬁrms due to the information restriction, and the fact thatpractitioners mainly use price multiple for valuing IPOs (Roosenboom, 2012).

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経営財務研究第 32 巻第 1・2 合併号

P/VSALES = (Offer price × total shares outstanding at the offer date + book value of total debts) /EVSALES,
P/VEBITDA = (Offer price × total shares outstanding at the offer date + book value of total debts)/
EVEBITDA.6
By deﬁnition, if an IPO ﬁrm’s P/V is more (less) than one, the offer price of this ﬁrm is consideredas over-valued (under-valued) compared to its industry peer.

⑶Measuring earnings quality

As a measure for earnings quality, this study uses three variables; total accruals (ACC), abnormal
accruals (AAC), and sign changes between operating cash ﬂows and net income (Sign Change). ACC
is calculated as change in non-cash current assets minus change in current liabilities plus change
in debt included in current liabilities minus depreciation and amortization. Abnormal accruals are
the unexpected portion of total accruals; we estimate AAC as total accruals minus industry peer’s
total accruals (matched comparable ﬁrm’s total accruals). ACC and AAC are both scaled by total
assets. We assume that higher accruals (both ACC and AAC) represent lower earnings quality. We
use AAC as the main variable for a proxy of earnings quality, as AAC is excess amount of accruals
over“normal”amount of accruals that a comparable ﬁrm without a speciﬁc incentive to manage
earnings has and considered as better indication of the degree of earnings management.
Although accruals are widely used measure of earnings management, this study additionallyuses Sign Change as another proxy measure for earnings management. As suggested by Yoon
and Miller (2002), it is natural to ﬁnd positive (negative) operating cash ﬂows for ﬁrms reporting
positive (negative) net income under normal circumstances, therefore, it is likely that ﬁrms withnegative operating cash-ﬂows and positive net income engage in aggressive earnings management.
We use Sign Change as an indication of lower quality of earnings.

３

Sample and descriptive statistics⑴

Sample selection

An initial sample consists of firms that went public in JASDAQ between 1989 and 2011. It
enables us to investigate the difference between auction IPOs and book building IPOs because
auction-pricing method was used for ﬁrms that went public between 1989 and the end of August

6

Alternatively, as is the description of P/V ratios in Purnanandam and Swaminathan (2004), offer
price P/V ratios: P/VSALES, P/VEBITDA, P/VEarnings are expressed as, (EV/Sales)IPO/ (EV/Sales)Match, and (EV/EBITDA)IPO/ (EV/EBITDA)Match, respectively.

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経営財務研究第 32 巻第 1・2 合併号

1997 in Japan, whereas most IPO firms use book building after September 1997 when bookbuilding became available. The IPO data is collected from JASDAQ Market Annual Statistics,
Equity Issue Whitepaper provided by Shoji-homu, IPO Whitepaper provided by Research Group for
Disclosure. We exclude the ﬁrms whose ﬁnancial data in the period three years before going public
are not available on the Nikkei NEEDS ﬁnancial QUEST database. Also, banks, securities ﬁrms,
and insurance firms are excluded to avoid regulation-related distortion. Consequently, a total of
1,288 ﬁrms is identiﬁed.

⑵

Descriptive statistics

Table 1 presents the descriptive statistics. Panel A reports sales revenues, EBITDA proﬁt margin,
prior period sales growth, net income, accruals, and debt to total assets ratio (leverage). Descriptive
statistics show that matching firms have quite similar size of sales revenues, EBITDA profit
margin to IPO firms, suggesting that our matching approach in general successfully identifies
appropriate comparable ﬁrm to IPO ﬁrm. On the other hand, IPO ﬁrms tend to have higher growth,lager net income, and more reliant on debt compared to their industry peer.
Panel B reports the descriptive statistics of matching ﬁrms’ price multiples (enterprise value tosales multiple and enterprise value to EBITDA multiple) across markets where matching firms
are listed. SME boards category includes JASDAQ, HERCURES, and TSE MOTHERS; other stock
Table 1. Descriptive statistics
Panel A. Characteristics of IPO ﬁrms and matching ﬁrms
IPO ﬁrms
Mean
25%
Median75%
Sales revenues
EBITDA proﬁt margin
Sales growth
Net income
Accruals
Leverage

18324
0.117
0.165
534
‑0.015
0.634

5834
0.061
0.033
201
‑0.063
0.519

10780
0.097
0.105
320
‑0.020
0.654

20908
0.154
0.209
555
0.026
0.772

Matching ﬁrms
Mean
25%

Median

75%

6010
0.059
‑0.04788‑0.053
0.329

11239
0.093
0.017
230
‑0.024
0.496

21491
0.138
0.087
484
0.010
0.663

18238
0.108
0.026
285
‑0.020
0.511

Sale revenues and net income are in 1 million yen. Accruals are computed as change in non-cash current assets minuschange in current liabilities plus change in debt included in current liabilities minus depreciation and amortization.
Leverage is debt to total assets ratio.

Panel B. Matching ﬁrms listing market and price multiple（EV/Sales）Match（EV/EBITDA）Match
25% Median 75% N
25% Median 75% N
SME boards 0.890
1.286
2.082 584 10.466
15.290 22.848 581
Main boards 0.994
1.522
2.535 681 12.935
18.017 25.595 678
SME（stock exchanges dedicated for trading the shares of small and medium scale enterprises: SMEs）boards include
JASDAQ, HERCURES, and TSE MOTHERS; others are included in Main boards.
（EV/Sales）Match ,（EV/EBITDA）Match, are（（Matching ﬁrm s market price × shares outstanding+ total debt）/
Matching ﬁrm s prior ﬁscal year sales revenues）,（（Matching ﬁrm s market price × shares outstanding）/ Matchingﬁrm s prior ﬁscal year EBITDA）. All variables deviating from the mean by more than three times the standard
deviation are excluded in order to avoid extreme value aﬀecting the validity of results; this process decreases sample
size to 1,265 for P/V Sales, and1,259 for P/VEBITDA.

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経営財務研究第 32 巻第 1・2 合併号

exchanges are included in the main board category.7 Panel B indicates any price multiples of themain boards is higher than those of the SME boards; for example, median sales-based multipleof the main boards is 1.522 whereas that of SME boards is 1.286. This suggests that when otherthings being equal, investors tend to pay more for a ﬁrm in main boards compared to a ﬁrm listed
in SME boards. Coupled with the fact that 52%-54% of matching ﬁrms are from the main boards,
the difference in price multiple across boards may cause upward bias in the estimated fair/intrinsic
value of IPOs matched on main board listing ﬁrms.
Table 2. Median P/V ratios by calendar year and pricing method
P/V Sales
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011

25%
0.783
0.822
0.816
0.717
0.742
0.810
0.570
0.684
0.578
0.665
0.898
0.499
0.632
0.589
0.614
0.703
0.476
0.594
0.585
0.570
0.872
0.952
0.502

Auction
0.705
Book building 0.603
ALL
0.651

P/V EBITDAMedian
1.072
1.139
1.058
0.945
1.079
1.114
0.891
1.001
0.816
0.907
1.312
0.928
0.978
0.775
1.030
0.967
0.939
0.817
0.767
0.697
1.114
1.014
0.696

75%
1.678
1.675
1.363
1.559
1.379
1.520
1.171
1.393
1.155
1.403
1.712
1.466
1.409
1.170
1.450
1.614
1.251
1.212
0.991
0.837
1.337
1.323
0.987

N
42
60
66
13
48
99
123
93
91
49
59
85
79
53
55
65
58
47
40
14
5
8
13

25%
0.712
0.696
0.811
0.677
0.708
0.779
0.563
0.705
0.534
0.649
0.891
0.447
0.582
0.530
0.557
0.740
0.544
0.602
0.530
0.550
0.985
0.939
0.366

Median
0.948
0.960
0.988
0.944
1.026
1.068
0.853
0.967
0.770
0.802
1.186
0.830
0.902
0.722
1.017
1.006
0.926
0.784
0.765
0.694
1.152
1.040
0.600

75%
1.181
1.324
1.241
1.655
1.356
1.448
1.077
1.384
1.123
1.297
1.586
1.288
1.571
1.135
1.449
1.442
1.238
1.172
0.964
0.833
1.159
1.168
0.866

N
42
61
66
13
48
100
122
91
91
49
58
83
80
53
54
65
58
47
39
14
5
8
12

1.004
0.918
0.947

1.379
1.372
1.379

612
653
1265

0.689
0.562
0.628

0.935
0.885
0.904

1.246
1.299
1.278

611
648
1259

Prefers to the enterprise value consisting of oﬀer price based equity value and book value of debt and V is thefair/intrinsic value based on comparable ﬁrm multiples; Vsales is the fair/intrinsic value based on comparable
ﬁrm price to sales ratio (PSR). VEBITDA is the fair/intrinsic value based on comparable ﬁrm price to EBITDA
ratio. All variables deviating from the mean by more than three times the standard deviation are excluded inorder to avoid extreme value aﬀecting the validity of results; this process decreases sample size to 1,265 for
P/V Sales, 1,259 for P/VEBITDA.

7

More speciﬁcally, over 95% of ﬁrms in SME boards category consists of JASDAQ ﬁrms, and morethan 85% of firms in main boards category consists of Tokyo Stock Exchange and Osaka Stock
Exchange (two major Japanese stock exchanges) ﬁrms.

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経営財務研究第 32 巻第 1・2 合併号

Table 2 presents the 25th, 50th, and 75th percentiles of P/V ratios based on EV/Sales, and EV/
EBITDA multiple by calendar year and pricing method. All variables deviating from the mean bymore than three times the standard deviation are excluded in order to avoid extreme value affecting
the validity of results; this process decreases sample size to 1,265 for P/V Sales, and 1,259 for P/
VEBITDA. The median of P/V ratios in ALL are below 1, and the results of Wilcoxon rank sum test
for testing the null hypothesis that the median P/V is equal to 1 indicate P/VEBITDA is signiﬁcantly
lower than 1 (not tabulated). Nevertheless, distribution of P/V ratios both within and across years
indicate that a considerable number of IPOs are“over-valued”at the offer price; for example,
median value of 75th percentile P/V Sales and P/VEBITDA are 1.379 and 1.278. These“offer-price’s overpricing”may be caused by the lower quality of earnings. Also, both median values of P/V Sales and
P/VEBITDA of auction IPOs (1.004 and 0.935, respectively) are larger than those of book building
IPOs (0.918 and 0.885, respectively). These findings are consistent with our basic expectationthat aggressive earnings management causes“over-valuation”with respect to fair/intrinsic value
especially during the auction regime when the participation of institutional investors and the roleof underwriters were limited.

４

Empirical results

We group our empirical results into two main sections. In the first section (Table 3), we use
univariate analysis to investigate the relationship between earnings quality and“over- and underpricing”relative to fair/intrinsic value. In the second section (Tables 4-5), we apply multivariate
regressions to test the signiﬁcance of earnings quality in explaining the“over- and under- pricing”
relative to fair/intrinsic value. In this analysis, we conduct regressions separately for ﬁrms thatwent public during the auction regime and for ﬁrms that went public with book building to test
whether and how the greater involvement of institutional investors (and underwriters) in thepricing process affects the association between the quality of earnings and offer price. As indicatedin prior studies that institutional investors generally did not participate in the IPO market due
to the requirements during the auction regime whereas institutional investors are more involvedin book building IPOs (Kaneko and Pettway, 2003; Kerins et al, 2007), we expect earnings quality
variables to have significantly positive coefficients over P/V ratios during the auction regime
whereas not so for the book building IPOs.

⑴

Earnings quality and “over-/under- valuation” with respect to the fair/intrinsic value

In this section, we examine whether and how earnings quality affects“over- and under- pricing”
with respect to fair/intrinsic value. We use three variables as the proxy for earnings quality, andmake three different quintile portfolios based on these earnings quality variables. Table 3 compares
the median values of offer price P/V ratio of ﬁrms with relatively higher quality of earnings (ﬁrmswith low ACC, low AAC, or No Sign Change) and those of ﬁrms with lower quality of earnings (ﬁrmswith high ACC, high AAC, or Sign Change).
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経営財務研究第 32 巻第 1・2 合併号

Table 3. Earnings quality and P/V ratios (oﬀer price)

Panel A. P/V ratios across accruals quintile
Accruals based quintile

Diﬀerence test

Wilcoxon
Z-value

Low

2

3

4

High

High-Low

P/VSales

0.939

0.925

0.918

1.019

0.967

0.028

1.323

P/VEBITDA

0.885

0.900

0.884

0.962

0.956

0.071

1.590

Panel B. P/V ratios across abnormal accruals quintile
Abnormal accruals based quintile

Diﬀerence test

Wilcoxon
Z-value

Low

2

3

4

High

High-Low

P/VSales

0.881

0.936

1.022

0.927

0.998

0.117

2.198**

P/VEBITDA

0.843

0.914

0.962

0.883

0.956

0.113

2.730***

Panel C.

Median P/V ratios of ﬁrms with and without sign change
Diﬀerence test

No-Sign Change

Sign Change

P/VSales

0.945

0.973

0.028

1.027

P/VEBITDA

0.903

0.969

0.066

1.650*

Sign Change ̶ No-Sign Change Wilcoxon Z-value

Abnormal accruals are estimated as a residual portion of accruals after subtracting the matched pair ﬁrm s accruals.
Sign Change subsample consist of ﬁrms with negative operating cash ﬂows and positive net income, and other ﬁrms are included in
No-Sign Change subsample.
P refers to the enterprise value consisting of oﬀer price based equity value and book value of debts and V is the intrinsic value basedon comparable ﬁrm multiples; Vsales is the intrinsic value based on comparable ﬁrm enterprise value to sales ratio. VEBITDA is theintrinsic value based on comparable ﬁrm enterprise value to EBITDA ratio. All reported numbers are median values. Wilcoxon
p-value is for Wilcoxon rank sum test for the diﬀerence between ﬁrms with high accruals (or Sign Change) and ﬁrms with low
accruals (or No-Sign Change). The notations *, **, and *** denote the statistical signiﬁcance at the 10%, 5%, and 1% levels, respectively.

Panel A reports the results with the accruals based quintile portfolio. Both sales-based P/V ratio
and EBITDA-based P/V ratio of high accruals firms exceed those of low accruals firms, but thedifference is not statistically signiﬁcant. Panel B reports the results with the abnormal accrualsbased quintile portfolio. Sales-based P/V ratio and EBITDA-based P/V ratio of high abnormal
accruals firms exceed those of low abnormal accruals firms, and the difference is statisticallysignificant at the 5% and 1%, respectively. Panel C reports P/V ratios of firms with negative
operating cash flows and positive net income (Sign Change), and those of other firms (No-Sign
Change), and shows the similar tendency. Both P/V ratios of Sign Change ﬁrms are higher thanthose of No-Sign Change ﬁrms. These results are consistent with our prediction that the offer priceof IPOs with lower quality of earnings tend to be“over-valued”with respect to fair/intrinsic value.

⑵

Multivariate analysis

In this section, we conduct multivariate regression analysis to examine the impact of earnings
management on P/V ratio, while controlling for other variables factors that would affect over-/under-valuation :85

経営財務研究第 32 巻第 1・2 合併号

P/VEBITDA = α + β1Eanings Quality+ β2Growth + β3Log Sales + β4Log Age + β5DMarket+ β6Shareoffer + ε.

⑴

We use P/VEBITDA as dependent variable because prior researches mainly use EBITDA-based P/Vratios because valuations based on sales based multiples tend to be less accurate (Liu et al.,2002;
Purnanadam and Swaminathan,2004). Earnings Quality takes one of the four variables in each
regression: ACC, AAC, ACC.10, or SIGNCH. ACC is total accruals and AAC is abnormal accruals.
ACC.10 is decile rank based on total accruals. SIGNCH is an indicator variable that equals 1 if
a ﬁrm with negative operating cash ﬂows reports positive net income, and 0 otherwise. Earnings
quality variable is the key variable that captures the degree of earnings management, i.e., thelarger ACC, AAC, and ACC.10, the lower earnings quality; SIGNCH represents lower quality ofearnings. Lower quality of earnings is related with valuation uncertainty about IPO ﬁrm, and thus
could lead to over-valuation with respect to fair/intrinsic value if investors fail to require discountfor such ﬁrms. Therefore, the predicted sign is positive for auction IPOs, whereas we expect thosefor book building IPOs to be insigniﬁcant (or negative).
Log Sales is the natural logarithm of sales revenues prior to going public, which controls forthe valuation uncertainty and information asymmetry. Growth is sales growth rate prior to going
public, and Log Age is the natural logarithm of the number of months until the date of going publicfrom the initiation. Growth and Log Age are included to control for the growth premium. As IPO
ﬁrms are supposed to have higher growth potential than their industry peers, IPO ﬁrms may haveprice premium. Dmarket is an indicator variable that equals 1 if the matching firm is from mainboards, and 0 otherwise. Dmarket is included because price multiples of ﬁrms listing in main boards
tend to be higher than those of SME boards as shown in Table 2, and this may negatively affect P/
V ratios. Shareoffer is the proportion of secondary shares offered in IPOs, and this variable could
affect the issuer’s incentive for price negotiation (Habib and Ljungqvist, 2001). Year dummy is also
included to control for the market wide factor.
Table 4 shows the results. The variables of our primary interest are ACC, AAC, ACC.10 and
SIGNCH. In Panel A, which reports the results of IPOs with auction, ACC, AAC, and ACC.10 havesignificantly positive coefficients, suggesting that IPOs with lower quality of earnings are more
likely to be“over-priced”with respect to fair/intrinsic value during the auction regime. On the other
hand, when conducting same regression with firms that went public with book building, all the
coefﬁcients of earnings quality variables become insigniﬁcant (Panel B). Meanwhile, other variables
such as Growth, Log Age, D market have consistent and statistically signiﬁcant coefﬁcients in theway we expect.
Overall, regression results are consistent with our prediction and suggest that greater
participation of individual investors and less involvement of institutional investors/ underwriters
in the pricing process may cause“offer price’s over-pricing”due to the individual investors’
insufﬁcient ability to detect earnings management and to claim risk premium for IPO ﬁrms withlower quality of earnings.8
86経営財務研究第 32 巻第 1・2 合併号

Table 4. Regression of the impact of earnings management on oﬀer price
P/V ratio based on EBITDA（Dependent variable: P/VEBITDA）
Panel A. Auction（N=611）
Independent variable
ACC
AAC
ACC.10SIGNCH
GrowthLog Sales
Log Agecoeﬃcientt-value

0.494

1.730 *

coeﬃcient
0.384

t-valuecoeﬃcientt-value

0.018

2.207 **
0.047
0.275
0.065
‑0.127‑0.0950.783
2.458 **
2.415 **
‑2.738 ***‑1.984 **‑0.729‑0.0840.037
4.856‑0.689coeﬃcientt-valuecoeﬃcientt-value

0.012

1.314

Dmarket2.366 **
2.463 **
‑2.768 ***‑1.906 *

0.271
0.061
‑0.124‑0.0982.434 **
2.261 **
‑2.702 ***‑2.061 **

0.267
0.066
‑0.126‑0.0932.397 **
2.478 **
‑2.738 ***‑1.947 *Shareoﬀer
Adj.R2F-statistic‑0.0760.040
5.271‑0.628‑0.0730.048
6.147‑0.606‑0.0880.043
5.600

t-valuecoeﬃcientt-value

0.265

1.374

ACC
AAC
ACC.10SIGNCH
GrowthLog Sales
Log Age

0.189

t-value

2.830 ***

0.265
0.066
‑0.128‑0.091Panel B. Book building（N=648）
Independent variable
coeﬃcientcoeﬃcient

0.783

Dmarket

0.237
0.046
‑0.169‑0.0862.334 **
1.539
‑3.745 ***‑1.4980.246
0.047‑0.167‑0.0882.417 **
1.568
‑3.702 ***‑1.5330.240
0.047‑0.169‑0.0882.365 **
1.563
‑3.758 ***‑1.520

0.081
0.233
0.046
‑0.167‑0.0871.111
2.298 **
1.527
‑3.705 ***‑1.507

Shareoﬀer‑0.181‑1.347‑0.185‑1.379‑0.181‑1.349‑0.177‑1.320Adj.R2

0.064
7.338

F-statistic

0.066
7.534

0.066
7.510

0.065
7.434

The dependent variable P/VEBITDA is the ratio of the enterprise value consisting of oﬀer price based equity value and book value ofdebt to the intrinsic value based on comparable ﬁrm enterprise value to EBITDA multiples. ACC is total accruals and AAC isabnormal accruals, which is estimated as a residual portion of total accruals after subtracting the matched pair ﬁrm s total accruals.
ACC and AAC are both deﬂated by total assets. ACC.10 is decile rank based on total accruals. SIGNCH is an indicator variable that
equals 1 if a ﬁrm with negative operating cash ﬂows reports positive net income and 0 otherwise. Log Age is the natural logarithmof the number of months until the date of going public from the initiation. GROWTH is sales growth rate prior to going public. Log
Sales is the natural logarithm of sales revenues prior to going public. Dmarket is an indicator variable that equals 1 if the matchingﬁrm is from main boards, and 0 otherwise. Shareoﬀer is the proportion of secondary shares oﬀered in IPOs. Year dummy is also
included to control for the market wide factor (not tabulated). The notations *, **, and *** denote the statistical signiﬁcance at the 10%,5%, and 1% levels, respectively.

⑶

Tendency for aggressive earnings management and the pricing method

So far, we have the results consistent with our prediction that aggressive earnings management

8

For robustness check, we additionally conduct the same regression using the natural logarithmof offer price P/VEBITDA and percentile rank of P/VEBITDA instead of P/VEBITDA as dependent variable.
The results are consistent with the results in Table 4, and further conﬁrm our earlier ﬁndings (nottabulated).

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経営財務研究第 32 巻第 1・2 合併号

Table 5. Diﬀerence in earnings management between auction and book building IPOs.
Panel A. AccrualAuction IPOs（N=611）
Book building IPOs（N=648）

Mean

25%

Median75%‑0.015‑0.017‑0.053‑0.070‑0.017‑0.024

0.022
0.028

Wilcoxon Z-value
p-value

0.007
1.426
0.154

Diﬀerence test
Auction - Book building

Panel B. Abnormal AccrualAuction IPOs（N=611）
Book building IPOs（N=648）

Mean

25%

Median75%‑0.001
0.009‑0.053‑0.067

0.004
0.001

0.059
0.068

Wilcoxon Z-value
p-value

0.003
0.394
0.694

Diﬀerence test
Auction - Book building

Panel C. Sign Change
Sign change
Auction IPOs（N=611）
Book building IPOs（N=648）

15.22%
16.05%

Diﬀerence test
Auction - Book building
χ squared
p-value‑0.83%‑0.4040.686

Abnormal accruals is estimated as a residual portion of total accruals after subtracting
the matched pair ﬁrm s total accruals. Accruals and abnormal accruals are both deﬂated
by total assets. Sign Change subsample consist of ﬁrms with negative operating cash ﬂows
and positive net income, and other ﬁrms are included in No-Sign Change subsample.

is positively related with“over-valuation”for IPOs in the auction regime, while not so for bookbuilding IPOs. We attribute these associations to the little (signiﬁcant) involvement of institutional
investors/underwriters in the pricing process of auction (book building) IPOs. However, it may
simply reﬂect more (less) earnings management for auction (book building) IPOs. To investigate
this possibility, we examine whether the quality of earnings is lower for auction IPOs compared
to book building IPOs. The results in Table 5 show that there are no signiﬁcant difference in thequality of earnings between auction IPOs and book building IPOs. Therefore, the results in above
section are not attributed to the underlying difference in earnings quality and support our ﬁndings.

５

Summary and Conclusion

Recent literatures provide evidence that IPOs are not necessarily“underpriced”with respect
to their fair/intrinsic value, however the question of why IPOs are“overpriced”has been largely
88

経営財務研究第 32 巻第 1・2 合併号

left unexamined. This study seeks to explain what causes“offer price’s over-pricing”relative tothe fair/intrinsic value by investigating the effect of earnings quality and the role of institutional
investors in IPO pricing process. Speciﬁcally, we hypothesize that aggressive earnings management
causes“offer price’s over-pricing”when the involvement of institutional investors/underwriters
are limited whereas not so when they play a greater role in the pricing process. With an improved
approach to estimate the fair/intrinsic value of JASDAQ IPOs, we find that“offer price’s overpricing”tendency is positively associated with aggressive earnings management for IPOs during
the auction regime when relatively uninformed individual investors dominate the pricing process,whereas such relationship is not observed for IPOs with book building where institutional
investors/ underwriters play a greater role. These results are also consistent with the priorevidence that underpricing of book-building IPOs are signiﬁcantly greater than those of auctions.
The reason why IPOs during the auction regime experience lower underpricing may be attributed
to the relatively uninformed individual investors’tendency to“over-value”the IPOs with inﬂated
earnings through earnings management.
Although we have consistent results supporting our prediction, these results may potentiallysuffer from biases related with our fair/intrinsic value estimation procedure. Further studies
introducing improved methods for valuation of IPOs, especially those with better control of growth
factors will beneﬁt the ongoing arguments about whether IPOs are over-/under-valued.

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