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Chapter 5
IP O ValuationThe International Evidence
Sanjai Bhagat, Jun Lu, and Srinivasan Rangan
5.1. Introduction
Initial public offerings (IPOs) are an economically significant contributor to the amount of capital raised by firms around the world. Over US$4.1 trillion was raised by over 36,000 firms that completed an IPO between 1998 and 2015 (Thomson SDC Global New Issues database). Further, IPO firms are also considered the drivers of innovation and employment in the economy, and hence their success is critical to economic growth.
Beginning with Loughran, Ritter, and Rydqvist (1994), several studies have documented cross- country differences in the IPO process and how these differences influence the decision to go public and subsequent pricing (Henderson, Jegadeesh, Weisbach, 2006; Kim and Weisbach, 2008; Caglio, Hanley, Westburg, 2010). While a few studies have focused on underpricing (change in price on the first day of trading) of IPOs around the world, no previous study has examined cross- country differences in determinants of the level of the IPO value.1
The valuation of IPOs occupies an important place in finance, perhaps because an IPO provides public capital market participants their first opportunity to value a set of corporate assets and growth opportunities. The valuation of IPOs is also quite relevant from an economic efficiency perspective: the IPO is the first opportunity that managers of such (usually young) companies get to observe price signals from the public capital markets. Such signals can either affirm or repudiate management’s beliefs regarding the firm’s future growth opportunities, which have obvious implications for real economic activity— for example, employment and corporate investment.
The finance literature has several hundred papers on IPO underpricing, which is the dif-ference between the market price at the end of the offer day and the offer price. However, there is little in the literature on the offer price itself. It is the offer price that is of greater interest to investors, issuing companies, regulators, and investment bankers; investors are
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IPO Valuation: The International Evidence 109
more interested in IPO valuation, which is the offer price times the number of shares out-standing. In light of this, it is especially surprising that the finance literature has devoted so much intellectual effort to understanding IPO underpricing but so little to understanding the more primitive economic variable: the offer price, or the value of the IPO.
In this chapter, we study the valuation of 6,199 IPOs during 1998– 2015 for the fol-lowing countries: Australia, Canada, China, Germany, India, Japan, the United Kingdom, and the United States. We construct a model to value IPOs. Conceptually, the value of an asset is the sum of the present value of its expected future cash flows. Estimating the expected future cash flow of most any company is nontrivial; this task is even more challenging for IPO firms given that, in general, less is known about their past performance, and there is greater uncertainty about their future prospects. Instead of directly estimating future cash flows and the cost of capital to discount these cash flows, we construct proxies for the cash flows and discount rates; these proxies involve financial and nonfinancial variables. We discuss these proxies in the following.
In a seminal article, Ohlson (1990) develops a model that expresses the market value of equity as a linear function of earnings, book value of equity, and other information. Subsequently, a sizable body of empirical research (see, for example, Penman, 1998, and Francis and Schipper, 1999) has used this model to motivate empirical investigations of the value relevance of earnings and book value of equity. Myers (1977) has suggested that the market value of a firm is positively related to its growth opportunities. Growth opportunities are especially critical for IPOs given that more, if not most, of an IPO’s value is based on them. More recently, Abel and Eberly (2005) propose a valuation model that explicitly incorporates the possibility that firms may upgrade to or adopt a new technology. In their model, the value of the firm is composed of three components: the replacement cost of the firm’s physical capital, the net present value of the firm’s expected future cash flows from assets in place, and the value of growth options associated with future technological upgrades.
There is a substantive literature in financial accounting on the value relevance of ac-counting variables in explaining cross- sectional variation in the market value of stocks; Kothari (2001) and Barth, Beaver, and Landsman (2001) review this literature. Collins, Maydew, and Weiss (1997) document the increasing importance of net income in explaining the cross- sectional variation in market value. Lev (2001) has argued that the value- relevance of book value has declined over time, since intangible assets comprise a larger fraction of the value of most firms today; this would be especially true for IPOs whose value, as noted earlier, would be drawn from their growth opportunities (intan-gible assets). Rhodes- Kropf, Robinson, and Viswanathan (2005) (RRV) draw on this lit-erature and propose a simple model that includes only book value and net income to explain the cross- sectional variation in stock market values. We adopt and extend the RRV model in our analysis.
The main variables that prior literature on accounting and finance has shown to influence IPO prices in the United States are earnings, book value, expected growth, pre- IPO insider ownership, underwriter reputation, and auditor reputation (Ohlson, 1990; Aggarwal, Bhagat, and Rangan, 2009). The accounting and finance literatures document that earnings opacity influences a range of capital market outcomes
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110 Sanjai Bhagat, Jun Lu, and Srinivasan Rangan
(Bhattacharya, Daouk, and Welker, 2003; Gelos and Wei, 2005; Jin and Myers, 2006). We expect that the impact of pre- IPO data on IPO prices will be lower in countries where earnings are more opaque. Recently, several countries, especially in the European Union, have adopted International Financial Reporting Standards (IFRS). An open question is whether the adoption of these standards has influenced the quality of accounting data in these countries and if market participants perceive differences in quality.
In a series of influential papers, La Porta et al. (1997, 2000) analyze the role of a country’s legal system in protecting investor rights. They argue that “diverse elements of countries’ financial systems as the breadth and depth of their capital markets, the pace of new security issues, corporate ownership structures, dividend policies, and the effi-ciency of investment allocation appear to be explained both conceptually and empir-ically by how well the laws in these countries protect outside investors. (2000, p. 4.)” Further, they postulate that the commercial legal codes of most countries are based on four legal traditions: the English common law, the French civil law, the German civil law, and the Scandinavian law. They find that common law countries provide the most protection to investors and that they have the deepest stock markets and most dispersed corporate ownership structures. They also document that countries develop substitute mechanisms for poor investor protection, such as mandatory dividends and greater ownership concentration. Finally, they find that investor protection is posi-tively correlated with valuation across countries. To the extent that IPO valuations are correlated with valuations of financial securities, in general, investor protection would be a determinant of IPO valuation.
In a recent paper, Cumming et al. (2016) document a positive correlation between IPO valuations and backing of such IPOs by international venture capital syndicates. Additionally, listing requirements across exchanges and countries have been found to be correlated with IPO valuation; see Carpentier et al. (2012); Johan (2010); Carpentier et al. (2012); and Cumming et al. (2016).
The remainder of the chapter is organized as follows. The next section (5.2) describes our sample and data, and section 5.3 discusses descriptive statistics of several pre- IPO financial and offering variables. Section 5.4 details our empirical results for the determinants of IPO valuation across countries. The final section (5.5) concludes with a summary.
5.2. Sample and Data
5.2.1. Sample
An initial sample of 21,577 observations for the years 1998– 2015 is obtained from the Thomson Reuters SDC Platinum New Issues database (SDC) for eight coun-tries: Australia, Canada, China, Germany, India, Japan, the United Kingdom, and the
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IPO Valuation: The International Evidence 111
United States. In Table 5.1, we report the type and number of IPOs that are excluded to arrive at our final sample, by country and for all countries combined. Our filters are similar to those applied in prior research on IPO pricing— we exclude financial firms, privatizations, unit offerings, private placements, spinoffs, rights offerings, offerings by limited partnerships, offerings that do not involve common shares (for example, loan
Table 5.1 Sample Selection Screens for International IPOs, 1998– 2015
All Australia Canada China Germany India JapanUnited Kingdom
United States
Start: 21,527 2,205 4,061 4,677 955 958 2,193 1,890 4,588
(–) Financial firms
5,757 402 2,546 327 116 126 362 574 1,304
(−) Privatizations 30 6 3 15 0 0 2 3 1
(−) Offerings of units (shares + warrants)
703 93 462 2 0 0 0 10 136
(−) Private placements
73 12 3 8 20 2 4 21 3
(−) Spinoffs 1,470 149 24 452 63 15 300 100 367
(−) Rights offerings
19 14 0 0 2 0 0 0 3
(−) Limited partnerships
69 1 11 1 0 0 0 3 53
(−) Loan stock, options, or flow through shares
31 1 30 0 0 0 0 0 0
(−) Not underwritten
4 0 0 0 0 4 0 0 0
(−) Missing SEDOL and CUSIP
395 65 10 88 63 0 20 149 0
(−) Follow- on offerings
29 3 5 9 3 1 2 3 3
(−) Multiple tranches of same IPO
2,417 120 24 1,278 261 125 126 86 397
10,534 1,342 943 2,497 427 686 1,377 941 2,321
(−) Missing prospectus or IPOs not qualifying per screens
4,335 814 657 852 205 217 850 488 252
Final Sample: 6,199 528 286 1,645 222 469 527 453 2,069
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112 Sanjai Bhagat, Jun Lu, and Srinivasan Rangan
stock), offerings that are not underwritten, offerings by firms with missing CUSIPS and SEDOLs, and follow- on offerings.2 These exclusions enable us to achieve a relatively ho-mogenous sample of underwritten offerings of common shares to new investors that result in a cash infusion to the firm or its pre- IPO shareholders. The basic unit of obser-vation on SDC is an offering tranche; while some IPOs have a single tranche, others have more than one tranche. To achieve a sample of unique IPOs (one observation per firm), we also eliminate 2,417 tranches that relate to multiple- tranche IPOs.
For each of the remaining 10,534 IPOs (except for Chinese IPOs), we attempt to ob-tain final IPO prospectuses from the following sites: www.sec.gov for US firms, www.sedar.com for Canadian firms, www.sebi.gov.in for Indian firms, and the Filings Library of the Thomson One Banker database for Australian, German, Japanese, and UK firms. For Chinese firms, we obtain pre- IPO data from the Guo Tai An (GTA) database, and not from prospectuses. When reading prospectuses, we discovered firms that would be eliminated based on the aforementioned filters. Our final “filter- compliant” sample for which we have prospectuses consists of 6,199 IPOs. China and the United States have the highest number of IPOs among the eight countries, and Canada and Germany the lowest. Figure 5.1 presents a pie chart of the country- wise shares of the number of completed IPOs.
Table 5.2 presents the time series of offering frequencies in percentages for the eight countries. In general, IPO volumes display cyclicality, with peak volumes varying across countries. IPO frequencies rose during the years 1998– 2000 before dropping in 2001— the year following the crash of the dot- com bubble. Subsequently, IPO markets
USA33%
Australia8%
Canada5%
China27%
Germany4%India
8%
Japan8%
UK7%
Australia Canada China Germany India Japan UK USA
Figure 5.1. Distribution of 6,199 IPOs in countries during 1998– 2015
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Tabl
e 5.
2 Di
strib
utio
n of
IPO
s ove
r Tim
e (1
998–
2015
)
Year
Freq
uenc
yFr
eque
ncy
%
All
All
Aust
ralia
Cana
daCh
ina
Ger
man
yIn
dia
Japa
nU
nite
d Ki
ngdo
mU
nite
d St
ates
1998
332
5%1%
6%5%
6%0%
2%3%
9%
1999
553
9%5%
6%3%
18%
0%4%
1%19
%
2000
659
11%
6%9%
6%32
%3%
9%14
%15
%
2001
182
3%1%
1%3%
5%0%
7%6%
3%
2002
148
2%2%
3%2%
1%0%
4%6%
2%
2003
193
3%5%
1%3%
0%1%
6%4%
2%
2004
414
7%10
%6%
5%1%
4%6%
15%
7%
2005
347
6%10
%6%
1%2%
10%
7%13
%6%
2006
440
7%13
%6%
3%11
%14
%9%
9%6%
2007
506
8%18
%12
%6%
11%
16%
5%7%
6%
2008
166
3%3%
6%4%
1%7%
2%1%
1%
2009
177
3%4%
4%6%
0%3%
0%0%
2%
2010
493
8%5%
8%19
%2%
10%
3%2%
3%
2011
421
7%3%
9%15
%4%
6%4%
1%3%
2012
252
4%2%
6%5%
3%3%
6%2%
3%
2013
190
3%3%
5%0%
0%4%
6%4%
4%
2014
336
5%5%
2%5%
1%6%
9%8%
5%
2015
390
6%5%
3%9%
1%12
%11
%4%
3%
6,19
952
828
61,
645
222
469
527
453
2,06
9
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114 Sanjai Bhagat, Jun Lu, and Srinivasan Rangan
around the world recovered to grow in volume from 2002 to 2007. With the advent of the financial crisis in the years 2008– 2009, IPO volume fell for all countries. Thereafter, during the most recent period, 2010– 2015, volumes returned to pre- crisis levels, but never exceeded levels attained between 2002 and 2007. The peak offering frequency year varies across countries and is as follows: Australia— 2007, Canada— 2007, China— 2010, Germany— 2000, India— 2007, Japan— 2015, United Kingdom— 2004, and United States— 1999. Figure 5.2 plots the time series of offering frequency for the eight countries combined.
5.2.2. Data Sources and Definitions
SDC is our primary data source for the following 13 offering- related variables: offer price in local currency, offer date, offering proceeds in US dollars, primary shares offered, sec-ondary shares offered, total shares offered, shares outstanding after the offering, shares outstanding before the offering, name of the auditor, names of the lead underwriters, exchange, currency in which shares are offered, and four- digit SIC code. When these variables are missing, we filled in their values from prospectuses. We verify the accuracy of these SDC- sourced variables (except for SIC codes, offering proceeds, and under-writer names) by comparing their values with those in prospectuses; whenever we find a difference, we replace SDC data with values from the prospectuses. As stated earlier, for Chinese firms, we rely on the GTA database rather than SDC for offering data.
We obtain founding years from IPO prospectuses, except for China and the United States. Founding years for Chinese firms are from the GTA database. For US firms, we obtain founding years from Professor Jay Ritter’s IPO database;3 when founding years were not available on that database, we obtain them from prospectuses. We de-fine firm age as the difference between the offering year based on the offer date and the founding year.
700
600
500
400
300
200
100
01998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
Figure 5.2. Aggregate number of IPOs for Australia, Canada, China, Germany, India, Japan, the United Kingdom, and the United States.
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IPO Valuation: The International Evidence 115
Besides age, we construct four measures that we expect to influence IPO valua-tion: auditor reputation, underwriter reputation, industry Price- Earnings (PE) ratio, and pre- IPO market returns. Consistent with a large body of auditing literature, we measure auditor reputation as a 1– 0 dummy variable based on whether or not the firm’s financials were audited by a Big- N (N largest auditors, where N varies from 4 to 8) au-ditor. To measure underwriter reputation, we employ the method of Megginson and Weiss (1991). For each underwriter j and for every year t, we define xjt as the three- year moving average (t- 3, t- 2, t- 1) of IPO proceeds. Then, for the set of underwriters I, for the year t, the Megginson- Weiss rank for underwriter j is:
UWRANKx
Max xjt
jt
j I jt
= ( )
∈
log( )
log (5.1)
This measure of underwriter reputation is market- share based and is a continuous variable on the interval [0,1]. When an IPO has multiple lead underwriters, we divide IPO proceeds by the number of underwriters.
To measure industry PE, for each IPO firm, we obtain the market capitalizations at the end of the month before the offering date for all firms in that firm’s country that had the same two- digit SIC code (industry peers). We chose two- digit SIC codes to mini-mize data loss because of industries having too few firms. For these industry peers, we obtain the income before extraordinary items for the most recent year relative to the month- end at which market capitalization is measured. We compute industry medians of PE, market capitalization divided by income before extraordinary items. Market cap-italization and income before extraordinary items are from The Center for Research on Security Prices (CRSP) and North America COMPUSTAT for US firms, Global Compustat for firms from Australia, Canada, China, Germany, Japan, and United Kingdom, and from the CMIE Prowess database for Indian firms.
To compute three- month market return before each firm’s offering date, we sum daily market returns over 63 trading days ending on the day before the offering date. Daily market returns are measured as the value- weighted market- wide return for US stocks from CRSP and as percent changes in daily market index values from CMIE prowess for Indian firms and from Global Compustat for the other six countries (Appendix 5.1 details the specific market indices used for the seven countries).
Turning to the financial statement variables, we manually collect the following eight financial statement variables for years – 1 to – 3 relative to the offering date from prospectuses, whenever available: sales, research and development (R&D) costs, income before extraordinary items, cash flows from operations, capital expenditures, long- term debt, book value of equity, and total assets. All numbers were coded in millions of the local currency. For the empirical work, we converted flow numbers such as sales into US dollars by using the average of the daily exchange rates over the fiscal year. Stock num-bers such as total assets were converted into US dollars based on the exchange rate on the last day of the fiscal year. When an exchange rate was unavailable on the last date, we
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116 Sanjai Bhagat, Jun Lu, and Srinivasan Rangan
used the most recent exchange rate before the fiscal year end date. Daily exchange rates are from www.federalreserve.gov.
All financial data items obtained are audited historical numbers.4 In general, all flow numbers were measured over 12 months; however, to minimize data loss, when a firm reported either 13 months or 11 months of data, we converted those numbers into 12- month values. If a firm reported flow numbers for more than 13 months or less than 11 months, we set those numbers to missing. Additionally, if a firm changed its fiscal year, data for the year of the fiscal year change was set to missing. For stock numbers, we collected the numbers reported on the fiscal year end date; if the only balance sheet num-bers available were reported on a date other than the fiscal year end date, we set those numbers to missing. Detailed definitions of financial statement variables are provided in Appendix 5.1.
5.3. Descriptive Statistics
Table 5.3 presents descriptive statistics for several offering variables. All variables, ex-cept for the auditor reputation dummy variable, are winsorized at the 1% and 99% levels. Because most of the variables are skewed, we discuss only median values. Our primary dependent variable is post- IPO market capitalization, measured as the product of offer price and shares outstanding on completion of the offering (MCAP). To achieve com-parability, MCAP is expressed in US dollars using exchange rates on the offer date.5 US IPOs record the highest median MCAP ($312.8 million), followed by China ($256.3 mil-lion), and then by Canada at a distant third ($50.4 million). Median offering proceeds are largest for the United States ($75.0 million), and smallest for Australia ($4.8 million). Median offer prices range from $770 for Japan to $0.32 for Australia.
Prior literature has documented that insider retention (percentage of offering retained by insiders) is a significant determinant of IPO valuation. We compute insider retention by subtracting secondary shares sold during the IPO from shares outstanding before the IPO and dividing that difference by post- IPO shares outstanding. Table 5.3 indicates that median post- IPO insider retention varies from 61% in Australia to 80% in Japan. We also report data on the frequency of secondary offerings. Secondary offerings are very frequent in Japan, with 89% of Japanese IPOs having a secondary component. At the other extreme, only 3% of Chinese IPOs have a secondary component.
A large body of evidence documents that IPOs are underpriced and that first- day prices are higher than offer prices, on average. Table 5.3 indicates that this is true of our sample as well, with two additional insights. First, the mean percentage change in price from offer to open is indeed positive for all eight countries, ranging from 1% for Japan to 182% for the United Kingdom. However, medians are negative for Australia (– 18%), Germany (– 6%) and Japan (– 8%). Second, the underpricing evidence is largely driven by the change from the offer to the first- day open. The magnitude of price changes from open to close on the first day are relatively small. Mean open- to- close percent change
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Tabl
e 5.
3 O
ffer
ing
Desc
riptiv
e St
atis
tics
Aust
ralia
Cana
daCh
ina
Ger
man
yIn
dia
Japa
nU
nite
d Ki
ngdo
mU
nite
d St
ates
Mar
ket C
ap. a
t Off
er P
rice
(Mill
ions
of U
S$)
Mea
n11
8.2
192.
643
0.0
208.
120
5.1
111.
465
.756
1.9
Med
ian
27.2
50.4
256.
310
6.5
38.0
46.7
14.6
312.
8
No.
of o
bs.
528
286
1,64
522
246
952
745
32,
069
Off
er P
roce
eds (
Mill
ions
of U
S$)
Mea
n29
.152
.099
.771
.137
.822
.852
.411
9.1
Med
ian
4.8
14.8
66.9
35.6
13.0
9.1
13.2
75.0
No.
of o
bs.
528
286
1,64
522
246
952
745
32,
069
Off
er P
rice
(US$
)
Mea
n0.
804.
622.
6519
.55
3.13
770.
040.
7313
.50
Med
ian
0.32
1.96
2.07
15.9
81.
8319
.96
0.49
13.0
0
No.
of o
bs.
528
286
1,64
522
246
952
745
32,
069
Insi
der R
eten
tion
Mea
n61
%66
%73
%67
%69
%79
%63
%73
%
Med
ian
61%
71%
75%
71%
72%
80%
66%
75%
No.
of o
bs.
528
286
1,63
922
246
952
745
32,
069
Seco
ndar
y O
ffer
ings
Freq
uenc
y12
%12
%3%
65%
17%
89%
34%
29%
No.
of o
bs.
528
286
1,64
522
246
952
745
32,
069
Firs
t- Da
y Cl
ose
(US$
)
Mea
n2.
265.
763.
9529
.20
3.94
449.
972.
4120
.03
Med
ian
0.30
2.52
3.27
12.2
82.
1819
.36
1.13
15.5
0
No.
of o
bs.
512
269
1,64
521
546
752
644
91,
987
(Contin
ued)
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Aust
ralia
Cana
daCh
ina
Ger
man
yIn
dia
Japa
nU
nite
d Ki
ngdo
mU
nite
d St
ates
Firs
t- Da
y O
pen
(US$
)
Mea
n1.
685.
343.
8220
.36
3.73
22.8
52.
2219
.00
Med
ian
0.30
2.19
3.15
12.1
52.
1415
.35
1.05
15.2
5
No.
of o
bs.
509
266
1,64
521
446
737
743
51,
970
% C
hang
e fr
om O
ffer
to F
irst-
Day
Ope
n
Mea
n7%
30%
68%
15%
18%
1%18
2%31
%
Med
ian
– 18%
6%43
%−6
%8%
−8%
199%
11%
No.
of o
bs.
509
266
1,64
521
446
737
743
51,
970
% C
hang
e fr
om F
irst D
ay O
pen
to C
lose
Mea
n−1
%−1
%4%
1%3%
0%4%
3%
Med
ian
−2%
0%2%
0%0%
0%1%
0%
No.
of o
bs.
509
265
1,64
521
446
737
743
51,
970
Age
Mea
n4.
66.
07.
311
.313
.325
.44.
012
.5
Med
ian
1.0
3.0
7.0
7.0
11.0
19.0
1.0
7.0
No.
of o
bs.
500
286
1,64
522
246
952
345
32,
069
Unde
rwrit
er R
eput
atio
n
Mea
n0.
550.
570.
740.
670.
590.
800.
580.
77
Med
ian
0.59
0.60
0.75
0.68
0.55
0.89
0.58
0.81
No.
of o
bs.
528
286
1,64
522
246
952
745
32,
069
Tabl
e 5.
3 (C
ontd
.)
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Big-
N A
udito
r
Freq
uenc
y (%
)32
%55
%3%
40%
15%
85%
42%
87%
No.
of o
bs.
528
286
1,64
522
246
925
745
32,
067
Indu
stry
PE
Mea
n18
.047
.733
.413
.021
.622
.324
.7
Med
ian
16.7
46.4
20.7
10.8
20.3
21.5
24.4
No.
of o
bs.
513
01,
577
215
457
521
446
2,06
7
Pre-
Off
erin
g 63
- Day
Ret
urn
Mea
n2.
9%2.
8%3.
3%2.
5%5.
6%3.
4%2.
5%3.
8%
Med
ian
2.1%
1.9%
3.0%
2.8%
4.7%
2.6%
1.6%
4.5%
No.
of o
bs.
528
286
1,64
522
246
952
745
32,
069
Not
e: V
aria
ble
Defin
ition
s are
in A
ppen
dix
5.1.
OUP UNCORRECTED PROOF – FIRSTPROOFS, Fri Jul 27 2018, NEWGEN
Part-1.indd 119 27-Jul-18 10:11:09 PM
120 Sanjai Bhagat, Jun Lu, and Srinivasan Rangan
ranges from – 1% for Australia and Canada to 4% for China and the United Kingdom; medians range from – 2% to 2%.
Table 5.3 also reports descriptive statistics for our three nonfinancial value drivers: age, underwriter reputation, and auditor reputation. IPO firms in Australia, Canada, and the United Kingdom are relatively young, with a median age of one to three years. Japanese and Indian IPOs have the highest median ages of 11 and 19 years, re-spectively. Chinese, German, and US firms have a median age of seven years. Median underwriter reputation values are highest for Japan and the United States (0.89, 0.81). For the other countries, median reputation values range from 0.55 for Australia to 0.75 for China. The frequency with which IPO firms employ Big- N auditors varies consid-erably across countries, ranging from a mere 3% in China to 85% in Japan and 87% in the United States. Overall, it appears that US and Japanese firms prefer high reputation auditors and underwriters. Alternately stated, the audit markets in the United States and Japan are more oligopolistic than those of other countries.
Finally, we report means and medians for pre- IPO industry PE ratios and three- month market returns. Median industry multiples, except for China, range from 10 to 25; these numbers are comparable with the median PE ratio of 24 for the S&P 500 over our sample period, 1998– 2015 (http:// www.multpl.com/ table). Median Chinese in-dustry PEs are relatively high at 44. Pre- IPO market returns are in general positive, with median returns ranging from 1.6% to 4.7%.
Table 5.4 reports, via a series of panels, the mean and median values of several finan-cial indicators over years – 3 to – 1. Again, all variables are winsorized at the 1% and 99% levels. Panel A reports that median sales increases monotonically for six of the eight countries; Australian and Canadian IPOs record average declining sales. The surprising decline for these two countries can be explained by the fact that their sample sizes increases from year – 3 to – 1 and the firms that enter the sample for the first time in year – 1 tend to have low sales.6 Panel B presents sales growth rates in year – 2 and – 1. Median sales growth rates in year – 2 range from 17% for Japanese firms to 37% for US firms. In year – 1, growth rates decline for China, Germany, India, and the United Kingdom, but rise for the remaining countries.
Panels C and D in Table 5.4 provide information on pre- IPO trends in return on assets (ROA) and loss frequency. ROA is defined as income before extraordinary items divided by ending total assets. While the median Australian, Canadian, and US firm is in the red or fails to achieve profitability for all three pre- IPO years, the median firms in the other five countries generate positive ROA in all three years. Further, median ROA trends up-ward in India and Japan. In data in Panel D, suggest that pre- IPO loss frequencies in the three Asian countries— China, India, and Japan, are relatively low, ranging from 0% to 6%. In contrast, close to two- thirds of the US and Canadian firms are unable to turn a profit in year – 1.
To gain further understanding of the profit differentials across countries, we present in Panels E and F, a decomposition of ROA into operating cash flows scaled by total assets and its complement, accruals scaled by total assets (accruals = income before ex-traordinary items−operating cash flows). The poor profitability of US and Canadian
OUP UNCORRECTED PROOF – FIRSTPROOFS, Fri Jul 27 2018, NEWGEN
Part-1.indd 120 27-Jul-18 10:11:09 PM
Table 5.4 Descriptive Statistics of Pre- IPO Financial Variables
Panel A: Sales (Millions of US$)
Means Medians No. of obs.
Year – 3 Year – 2 Year – 1 Year – 3 Year – 2 Year – 1 Year – 3 Year – 2 Year – 1
Australia 156.6 120.6 100.0 30.1 19.9 12.3 108 190 268
Canada 123.8 113.2 101.0 5.2 3.7 0.8 142 177 238
China 87.6 104.3 130.8 36.9 46.1 58.9 1,612 1,632 1,643
Germany 79.6 91.5 105.4 12.8 15.0 21.2 162 207 221
India 36.1 48.7 63.2 8.0 12.1 18.4 446 449 460
Japan 81.8 108.4 119.1 28.4 36.7 41.9 393 515 525
United Kingdom
55.6 53.9 55.8 3.0 3.1 3.5 257 304 353
United States 166.1 160.9 185.6 16.6 18.3 27.6 1,537 1,899 2,012
Panel B: Sales Growth
Means Medians No. of obs.
Year - 3 Year – 2 Year – 1 Year – 3 Year – 2 Year – 1 Year – 3 Year – 2 Year – 1
Australia 52% 40% 20% 24% 106 182
Canada 108% 86% 27% 41% 107 124
China 35% 29% 24% 21% 1,612 1,631
Germany 85% 64% 32% 31% 159 201
India 106% 105% 37% 31% 422 439
Japan 45% 49% 17% 18% 393 514
United Kingdom
90% 63% 22% 21% 235 272
United States 128% 169% 37% 44% 1,389 1,730
Panel C: Return on Assets = Income before Extraordinary Items Divided by Total Assets
Means Medians No. of obs.
Year – 3 Year – 2 Year – 1 Year – 3 Year – 2 Year – 1 Year – 3 Year – 2 Year – 1
Australia −10% −18% –31% −3% −4% 0% 4 29 221
Canada −60% −36% −24% −10% −3% −7% 52 174 234
China 14% 14% 14% 12% 13% 13% 1,599 1,619 1,642
Germany 11% −4% 0% 9% 3% 5% 27 206 219
India 6% 7% 8% 4% 5% 7% 441 449 459
Japan 6% 9% 10% 6% 7% 10% 397 517 524
United Kingdom
−22% −29% −24% 2% 2% 1% 255 301 351
United States −47% −50% −44% −10% −15% −14% 1,324 1,865 2,008
(Continued)
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Part-1.indd 121 27-Jul-18 10:11:10 PM
Panel D: Loss Frequency
Means No. of obs.
Year – 3 Year – 2 Year – 1 Year – 3 Year – 2 Year – 1
Australia 17.0% 31.5% 44.9% 100 181 264
Canada 59.2% 55.1% 65.7% 142 178 238
China 0.2% 0.0% 0.0% 1,612 1,620 1,643
Germany 27.2% 29.0% 26.7% 162 207 221
India 11.2% 7.6% 5.9% 446 449 459
Japan 10.1% 8.7% 6.1% 397 517 526
United Kingdom
44.2% 44.1% 45.6% 258 304 353
United States 65.1% 66.3% 65.4% 1,529 1,893 2,010
Panel E: Operating Cash Flows/Assets
Means Medians No. of obs.
Year – 3 Year – 2 Year – 1 Year – 3 Year – 2 Year – 1 Year – 3 Year – 2 Year – 1
Australia −10% −8% −6% 0% 0% 6% 4 27 148
Canada −32% −23% −18% −6% −2% −5% 50 171 232
China 11% 13% 12% 10% 11% 11% 1,174 1,235 1,409
Germany 10% 2% 2% 11% 8% 8% 26 190 208
India 4% 3% 3% 4% 3% 5% 398 415 428
Japan 6% 9% 9% 7% 8% 9% 26 416 465
United Kingdom
−8% −14% −10% 6% 7% 7% 249 296 338
United States −30% −33% −24% −2% −5% −4% 1,270 1,847 1,999
Panel F: Accruals / Assets; Accruals = Income before Extraordinary Items minus Operating Cash Flows before Discontinued Operations
Means Medians No. of obs.
Year – 3 Year – 2 Year – 1 Year – 3 Year – 2 Year – 1 Year – 3 Year – 2 Year – 1
Australia −1% −8% −18% −2% −5% −5% 4 27 142
Canada −24% −13% −8% −7% −5% −5% 50 171 232
China 3% 2% 2% 3% 2% 2% 1,174 1,229 1,409
Germany 1% −7% −2% 0% −3% −2% 26 190 208
India 2% 3% 4% 1% 2% 2% 398 415 428
Japan 3% 0% 2% −1% 0% 1% 26 416 465
United Kingdom
−14% −13% −14% −6% −7% −7% 249 296 338
United States −18% −17% −18% −8% −8% −10% 1,270 1,845 1,997
Table 5.4 (Contd.)
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Part-1.indd 122 27-Jul-18 10:11:10 PM
Panel G: Research & Development (R&D)/ Assets (When R&D is Non−Zero)
Means Medians No. of obs.
Year – 3 Year – 2 Year – 1 Year – 3 Year – 2 Year – 1 Year – 3 Year – 2 Year – 1
Australia 9% 8% 34% 9% 7% 22% 2 7 24
Canada 41% 34% 22% 18% 20% 16% 22 68 77
China 0 0 0
Germany 27% 15% 15% 10% 0 45 50
India 26% 18% 14% 2% 1% 1% 19 26 28
Japan 10% 28% 1% 2% 0 119 198
United Kingdom
30% 27% 30% 14% 14% 12% 64 78 81
United States 49% 48% 41% 27% 29% 26% 806 1,171 1,248
Panel H: Capital Expenditures / Assets
Means Medians No. of obs.
Year – 3 Year – 2 Year – 1 Year – 3 Year – 2 Year – 1 Year – 3 Year – 2 Year – 1
Australia 6% 7% 11% 2% 3% 4% 50 89 135
Canada 6% 11% 21% 3% 5% 11% 133 172 231
China 6% 7% 9% 5% 6% 8% 1,173 1,224 1,368
Germany 6% 9% 13% 3% 5% 8% 136 190 208
India 6% 8% 12% 3% 5% 8% 402 416 429
Japan 2% 4% 6% 2% 2% 3% 3 411 481
United Kingdom
6% 7% 9% 3% 3% 4% 250 297 339
United States 7% 8% 12% 3% 4% 7% 1,453 1,853 1,968
Panel I: Book Value of Equity (Millions of US$)
Means Medians No. of obs.
Year – 3 Year – 2 Year – 1 Year – 3 Year – 2 Year – 1 Year – 3 Year – 2 Year – 1
Australia 138.1 62.6 31.7 8.2 2.7 1.6 6 31 371
Canada 1.2 10.4 21.5 0.2 0.8 0.7 53 199 282
China 35.3 46.9 61.2 18.6 26.1 34.6 1,364 1,380 1,393
Germany 46.8 18.2 21.2 15.3 2.5 5.0 27 207 220
India 13.6 18.2 25.3 2.7 4.0 6.2 443 452 465
Japan 5.9 17.0 18.4 2.2 3.1 4.0 412 518 524
United Kingdom
10.3 6.6 5.7 0.3 0.5 0.6 266 310 433
United States 26.2 20.9 19.7 0.1 −0.1 −0.1 1,416 1,936 2,059
Table 5.4 (Contd.)
(Continued)
OUP UNCORRECTED PROOF – FIRSTPROOFS, Fri Jul 27 2018, NEWGEN
Part-1.indd 123 27-Jul-18 10:11:10 PM
124 Sanjai Bhagat, Jun Lu, and Srinivasan Rangan
firms holds up even with operating cash flows; median numbers are negative for all three years. The median IPO firm in the remaining six countries are generating posi-tive operating cash flows in all three years; however, only Japanese firms report a strictly monotonic trend.
Because accruals tend to be dominated by a large negative accrual— depreciation— we expect average pre- IPO accruals to be negative. Surprisingly, median accruals divided by assets are positive for all three years for China and India, ranging from 1% to 3%. The unusual nature of these positive accruals becomes more stark, when contrasted with the median accruals divided by assets for all US firms on COMPUSTAT for our sample period. This number is – 6%. While a portion of the pos-itive accruals can be attributed to high sales growth rates, the possibility that Chinese and Indian firms are managing their pre- IPO accruals upward remains. For the other six countries, median accruals scaled by assets are in general negative, as expected, and do not display any particular trend.
We also examine the investing patterns of IPO firms before they conduct their offerings. Panel G and H report averages for R&D deflated by assets, when R&D is non- zero, and capital expenditures deflated by assets. US and Canadian firms are the most R&D intensive, with R&D rates ranging from 26% to 29%— this partly explains the poor profitability of IPOs in these two countries. India and Japanese IPOs fall on the low end of the R&D investing spectrum, with R&D rates of only 1%– 2% of assets in the year before the IPO. With respect to median capital expenditure spending rates, Panel H indicates that IPO firms in all eight countries display an increasing trend over years – 3 to – 1.
Panel I and J report data on two balance sheet characteristics— book value of eq-uity (in millions of $) and long- term debt to assets ratio. Except for US firms that have a small negative median book value, IPO firms in general report a positive book
Panel J: Long- Term Debt by Total Assets (%)
Means Medians No. of obs.
Year - 3 Year - 2 Year - 1 Year - 3 Year - 2 Year - 1 Year - 3 Year - 2 Year - 1
Australia 11% 13% 8% 0% 2% 0% 6 30 369
Canada 13% 13% 11% 0% 1% 0% 34 153 230
China 7% 7% 7% 2% 3% 3% 1,551 1,575 1,581
Germany 11% 17% 17% 0% 9% 10% 27 204 217
India 26% 26% 26% 23% 23% 24% 441 451 465
Japan 23% 19% 17% 25% 14% 11% 6 503 515
United Kingdom
24% 20% 20% 4% 5% 3% 255 304 429
United States 20% 21% 23% 4% 6% 7% 849 1,816 1,981
Table 5.4 (Contd.)
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Part-1.indd 124 27-Jul-18 10:11:10 PM
IPO Valuation: The International Evidence 125
value of equity. In terms of leverage, Indian firms have the highest levels, 24% in the year before the offering. The median German and Japanese firm funds about 10%– 11% of their assets with long- term debt. Pre- IPO leverage is relatively low for other countries.
Figures 5.3 through 5.9 illustrate some of the key descriptive statistics.
400
300
200
100
0Australia Canada China Germany India Japan UK US
Median Market Capitalization at Offer Price (Millions of US$)Median Offer Proceeds (Millions of US$)
Figure 5.3. Median IPO market capitalization, median IPO offer proceeds (US$ millions).
20
18
16
14
12
10
8
6
4
2
0Australia Canada China Germany India Japan UK US
Figure 5.4. IPO company median age (years).
Australia Canada China Germany India Japan UK US
70
60
50
40
30
20
10
0
Figure 5.5. Median sales of IPO companies during the past 12 months (US$ millions).
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Part-1.indd 125 27-Jul-18 10:11:10 PM
Australia Canada China Germany India Japan UK US
70.00%
60.00%
50.00%
40.00%
30.00%
20.00%
10.00%
0.00%
Figure 5.7. Percentage of IPOs with an earnings loss during the past 12 months.
Australia Canada China Germany India Japan UK US
30%
25%
20%
15%
10%
5%
0%
Figure 5.8. Median R&D/ assets during the past 12 months (when R&D is non- zero).
Australia Canada China Germany India Japan UK US
50%45%40%35%30%25%20%15%10%5%0%
Figure 5.6. Median sales growth of IPO companies during the past 12 months.
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IPO Valuation: The International Evidence 127
5.4. IPO Valuation
5.4.1. Cross- Country Differences in Relation of Financial Variables to IPO Valuation
Our research objective is to examine the relation between IPO market valuations and financial variables and to document the existence and magnitude of cross- country differences in the same. To do so, we estimate a simple and parsimonious valuation model estimated for US mergers by Rhodes- Kropf, Robinson, and Viswanathan (2005; RRV hereafter). The model, which is an adaptation of the seminal work of Ohlson (1990), is specified for each country j as follows:
LOGMCAP BV LOGABSNI LOSSDUM LOGABSNI
Lj j j j j j j j
j
= + + ++
α α α αα
0 1 2 3
2
*EEVj j+ α (5.2)
where LOGMCAP is the log of market value of equity on the offer date, BV is the book value of common equity at the end of the year before the offering (year – 1), LOGABSNI is the log of the absolute value of income before extraordinary items in year – 1, LOSSDUM is a dummy variable that equals one when income before extraordinary items in year – 1 is negative and 0 otherwise, and LEV is the ratio of long- term debt to total assets as the end of year – 1.
We employ log values for market capitalization and absolute value of income be-fore extraordinary items considering the significant skewness in these variables. By interacting LOSSDUM and LOGABSNI, we allow for the valuation of income to differ based on its sign. We expect the coefficients of BV and ABSNI, α1 and α2, to be positive. Because loss firms tend to have income that is less persistent, we expect α3 to be negative. RRV interpret leverage as a proxy for cost of capital and expect that higher leverage will be associated with lower market values. Alternately, leverage can also be viewed a source of monitoring that could benefit shareholders (Jensen, 1989). Under this interpretation, the sign of the coefficient on leverage would be positive.
Australia Canada China Germany India Japan UK US
12%
10%
8%
6%
4%
2%
0%
Figure 5.9. Median capital expenditure/ assets during the past 12 months.
OUP UNCORRECTED PROOF – FIRSTPROOFS, Fri Jul 27 2018, NEWGEN
Part-1.indd 127 27-Jul-18 10:11:10 PM
128 Sanjai Bhagat, Jun Lu, and Srinivasan Rangan
We first estimate Eq. (5.1) for each country j, individually. Then, we estimate a global valuation model that combines data for all eight countries and allows us to test for differences in coefficients of value- drivers across countries. All variables, except dummy variables, are winsorized at the 1% and 99% levels. Standard errors are adjusted for heteroscedasticity and clustering across firms within each year. For the country- level models, financial variables are in local currencies; for the global valuation model, finan-cial data are expressed in US dollars.
Table 5.5, Panel A, presents the results for the RRV valuation model for IPOs in the eight countries. As expected, income before extraordinary items (LOGABSNI) is pos-itively related to IPO valuation in each of the eight countries. The economic impact of net income is largest for Chinese IPOs and smallest for Australian IPOs. Specifically, a 1% increase in net income in China is associated with a 0.82% increase in IPO valua-tion. A 1% increase in net income in Australia is associated with a mere 0.07% increase in IPO valuation. In contrast to income, book value of equity that reflects assets in place is valued significantly in only four countries: Canada, Germany, India, and the United States. We do not observe a significant relation between book value and IPO valuation for Australia, China, Japan, and the United Kingdom.
The interaction between the LOSS dummy and ABSNI measures the differential val-uation of loss firms and profitable firms. For IPOs in the United States, the valuation effect of income when it is negative is lower than when it is positive; the magnitude of this differential is, however, economically small with a coefficient of – 0.10 on the in-teraction. We find that LOSS times ABSNI and IPO value are negatively related for UK IPOs as well. However, Canadian and Japanese IPOs that have incurred a loss in earn-ings are associated with a higher valuation. We do not observe a statistically significant loss- versus- profit valuation differentials for Australia, Germany, and India. Because all Chinese firms report positive pre- IPO profits, the loss- profit interaction is not relevant for them.
The results in Panel A of Table 5.5 indicate that leverage’s effect on market capitaliza-tion varies across countries. The effect is positive and statistically significant in Canada, India, and the United Kingdom, consistent with the idea that debt provides monitoring benefits to shareholders. However, it is negative and significant in Japan, suggesting that Japanese investors interpret it as a proxy for cost of capital. Leverage is not significantly related to market values in Australia, China, Germany, and the United States.
Table 5.5, Panel B, highlights the results for the RRV valuation model augmented with investment, growth, and nonfinancial variables for the IPOs in the eight different coun-tries. The magnitudes and significance of the coefficients of the RRV model for China and Germany are similar to those reported in Panel A. While ABSNI loses statistical significance in Canada and Japan, BV becomes statistically and significantly related to market values in Australia and Japan. Further, BV is no longer significantly related to value for Canadian firms. In terms of the differential valuation of loss firms, the results change for UK firms alone; LOSS*ABSNI remains negatively related to market values, but is no longer statistically significant. Finally, leverage is no longer significantly related to market value for Canadian and Indian firms; interestingly, leverage is valued posi-tively by US investors under the augmented RRV model.
OUP UNCORRECTED PROOF – FIRSTPROOFS, Fri Jul 27 2018, NEWGEN
Part-1.indd 128 27-Jul-18 10:11:10 PM
Tabl
e 5.
5 Co
untr
y- Le
vel V
alua
tion
Regr
essi
ons
Pane
l A: R
hode
s- Kr
opf,
Robi
nson
, and
Vis
hwan
atha
n (2
005)
(RRV
) Mod
el
Aust
ralia
Cana
daCh
ina
Germ
any
Coef
.t-
stat
SLCo
ef.
t- st
atSL
Coef
.t-
stat
SLCo
ef.
t- st
atSL
Inte
rcep
t0.
1135
.18
*3.
8122
.51
*4.
1323
.23
*4.
5726
.32
*
BV0.
001.
000.
002
4.03
*0.
000.
960.
002
2.93
*
LOG
ABSN
I0.
075.
77*
0.47
4.37
*0.
8223
.60
*0.
263.
86*
LOSS
*LOG
ABSN
I0.
100.
270.
191.
89**
*0.
00- 0
.04
DTOA
0.32
−0.1
51.
003.
22*
−0.2
7−1
.06
0.05
0.11
Adju
sted
R2
47.4
%50
.9%
67.3
%29
.6%
No.
of o
bs.
218
185
1,38
121
7
Indi
aJa
pan
Unite
d Ki
ngdo
mUn
ited
Stat
es
Coef
.t-
stat
SLCo
ef.
t- st
atSL
Coef
.t-
stat
SLCo
ef.
t- st
atSL
Inte
rcep
t5.
0525
.92
*7.
3024
.06
*3.
4835
.64
*5.
0143
.36
*
BV0.
0004
7.27
*0.
001.
250.
000.
560.
004.
8*
LOG
ABSN
I0.
4710
.52
*0.
234.
26*
0.59
11.0
1*
0.41
12.0
8*
LOSS
*LOG
ABSN
I−0
.02
−0.3
30.
153.
39*
−0.1
6−2
.63
**−0
.10
−3.7
4*
DTOA
0.78
2.92
*−0
.54
−1.8
1**
*0.
453.
38*
0.03
0.29
Adju
sted
R2
75.4
%14
.0%
50.2
%31
.2%
No.
of o
bs.
459
515
345
1,92
5
Not
es: T
he d
epen
dent
var
iabl
e is
the
log
of m
arke
t cap
italiz
atio
n at
the
offe
r dat
e. S
L is
sign
ifica
nce
leve
l. * i
ndic
ates
sign
ifica
nce
at th
e 1%
leve
l, **
at t
he 5
% le
vel,
and
*** a
t the
10%
leve
l. St
anda
rd e
rror
s acc
ount
for c
lust
erin
g ac
ross
firm
s with
in a
yea
r. Va
riabl
e de
finiti
ons a
re in
App
endi
x 5.
1.
(Contin
ued)
OUP UNCORRECTED PROOF – FIRSTPROOFS, Fri Jul 27 2018, NEWGEN
Part-1.indd 129 27-Jul-18 10:11:10 PM
Pane
l B: R
RV M
odel
, Aug
men
ted
with
Inve
stm
ent,
Grow
th, N
onfin
anci
al V
aria
bles
Aust
ralia
Cana
daCh
ina
Ger
man
y
Coef
.t-
stat
SLCo
ef.
t- st
atSL
Coef
.t-
stat
SLCo
ef.
t- st
atSL
Inte
rcep
t2.
333.
21*
3.11
4.84
*1.
251.
301.
874.
48*
BV0.
001
5.39
*0.
000.
390.
00−0
.15
0.00
13.
24*
LOG
ABSN
I0.
524.
40*
−0.0
3−0
.27
0.71
22.5
9*
0.27
6.38
*
LOSS
*LOG
ABSN
I−0
.15
−1.1
90.
201.
84**
*−0
.07
−1.2
5
DTOA
−0.5
6−1
.71
0.31
0.71
0.11
0.71
0.25
1.08
LOG
_ CAP
EX0.
152.
40**
0.25
3.32
*0.
000.
170.
135.
11*
LOG
_ RD
0.01
0.27
0.00
0.06
0.04
1.83
***
LOG
_ SG
RO−0
.18
−0.6
10.
070.
270.
211.
570.
231.
65
LOG
_ IN
DPE
0.28
0.85
0.11
0.58
0.15
2.45
**
RETE
NTI
ON0.
450.
600.
080.
143.
325.
11*
1.39
5.45
*
UN
DREP
0.47
0.96
1.49
2.36
**0.
773.
16*
1.80
5.71
*
BIG
N_ A
UD
0.37
1.04
0.56
1.88
***
−0.0
6−0
.90
0.15
1.96
***
AGE
0.00
−1.1
50.
010.
76−0
.02
−1.7
5**
*0.
00−1
.31
Adju
sted
R2
69.2
%45
.7%
73.1
%65
.6%
No.
of o
bs.
6574
1,30
917
9
Tabl
e .5
.5 (
Cont
d.)
OUP UNCORRECTED PROOF – FIRSTPROOFS, Fri Jul 27 2018, NEWGEN
Part-1.indd 130 27-Jul-18 10:11:10 PM
LOG
ABSN
I0.
316.
11*
0.10
0.97
0.30
7.64
*0.
158.
63*
LOSS
*LOG
ABSN
I−0
.01
−0.11
0.16
3.07
**−0
.12
−1.3
7−0
.06
−3.7
9*
DTOA
0.13
0.50
−0.9
8−2
.55
**0.
502.
15**
0.25
4.83
*
LOG
_ CAP
EX0.
113.
97*
0.08
1.73
0.20
6.37
*0.
127.
86*
LOG
_ RD
−0.0
6−1
.52
0.03
0.93
0.03
1.21
0.00
0.25
LOG
_ SG
RO−0
.02
−0.2
90.
100.
760.
010.
060.
031.
80**
*
LOG
_ IN
DPE
0.16
2.30
**1.
014.
33*
0.12
0.64
−0.0
4−0
.30
RETE
NTI
ON1.
261.
79**
*1.
812.
72**
1.10
3.49
*2.
1410
.94
*
UN
DREP
1.93
6.59
*0.
571.
86**
*1.
759.
68*
2.24
12.2
8*
BIG
N_ A
UD
0.14
1.15
0.24
1.89
***
0.44
5.23
*0.
212.
70**
AGE
0.01
3.60
*0.
00−1
.54
0.00
−0.0
80.
000.
69
Adju
sted
R2
81.8
%29
.6%
68.4
%63
.9%
No.
of o
bs.
340
228
249
1,60
0
Not
es: T
he d
epen
dent
var
iabl
e is
the
log
of m
arke
t cap
italiz
atio
n at
the
offe
r dat
e. S
L is
sign
ifica
nce
leve
l. * i
ndic
ates
sign
ifica
nce
at th
e 1%
leve
l, **
at t
he 5
% le
vel,
and
*** a
t the
10%
leve
l. St
anda
rd e
rror
s acc
ount
for h
eter
osce
dast
icity
and
clu
ster
ing
acro
ss fi
rms w
ithin
a y
ear.
Varia
ble
defin
ition
s are
in A
ppen
dix
5.1.
Indi
aJa
pan
Uni
ted
King
dom
Uni
ted
Stat
es
Coef
.t-
stat
SLCo
ef.
t- st
atSL
Coef
.t-
stat
SLCo
ef.
t- st
atSL
Inte
rcep
t2.
958.
89*
2.55
3.64
*1.
452.
54**
1.95
4.85
*
BV0.
0002
4.33
*0.
0001
2.52
**0.
000.
050.
007.
85*
OUP UNCORRECTED PROOF – FIRSTPROOFS, Fri Jul 27 2018, NEWGEN
Part-1.indd 131 27-Jul-18 10:11:10 PM
132 Sanjai Bhagat, Jun Lu, and Srinivasan Rangan
IPOs are usually associated with growth companies. Most of the value of a growth com-pany is in its growth opportunities, and less in assets in place. We consider four proxies for growth opportunities: capital expenditures (CAPEX), R&D expenditures (RD), sales growth rate (SGRO), and industry price to earnings ratio (INDPE). Panel B, Table 5.5 indicates that capital expenditures are significantly and positively related to IPO valuation in Canada, Germany, India, the United Kingdom, and the United States. A 1% increase in cap-ital expenditure is associated with a 0.25% increase in valuation in Canada, but only 0.11% in-crease in valuation in India (estimates for Germany, UK, and US are between the preceding estimates). There is no significant relation between capital expenditure and IPO valuation in China and Japan; the relation in Australia is positive but only marginally significant.
In general, we do not find a statistically significant relation between IPO valuation and either R&D expenditures or sales growth. The exceptions are Germany for R&D and the United States for sales growth.7 We find a positive and significant relation be-tween industry price- to- earnings ratios and IPO values for Japan, a marginally signif-icant and positive relation for Germany and India, and no significant relationship for Australia, Canada, China, the United Kingdom, and the United States. Overall, capital expenditures appear to be the most important driver of value from our four indicators of growth opportunities.
5.4.2. Cross- Country Differences in Relation of Nonfinancial Variables to IPO Valuation
In addition to being high- growth firms, IPO firms are perceived as facing considerable uncertainty about future cash flows. Given the importance of future cash flows to IPO valuation, knowledgeable insiders may choose to communicate their information about future cash flows via costly and credible signals. We consider three such credible sig-nals: ownership in the IPO firm retained by key insiders during the IPO (RETENTION), choice of underwriter (UNDREP), and choice of public accounting auditor (BIGN_ AUD). Further, because younger firms are likely to have more uncertain cash flows, we include the age of the firm as a fourth measure of uncertainty.
We find a positive and statistically significant relation between insider retention and IPO valuation in China, Germany, the United Kingdom, and the United States; positive but marginally significant relationship for India and Japan; and no significant relation-ship for Australia and Canada. Underwriter reputation has a positive and statistically significant relationship for IPOs in China, Germany, India, the United Kingdom, and the United States; marginally positive relationship for Canada and Japan, and no signif-icant relationship for Australia. Auditor reputation is positively and statistically signifi-cantly related to market values in the United Kingdom; marginally positive for Canada, Germany, Japan, and the United States; and is not significant related for Australia, China, and India. Age influences valuation only in India and China, and that too in op-posite ways. In India, as expected, older firms garner higher valuations; but in China younger firms are valued relatively higher.
OUP UNCORRECTED PROOF – FIRSTPROOFS, Fri Jul 27 2018, NEWGEN
Part-1.indd 132 27-Jul-18 10:11:11 PM
IPO Valuation: The International Evidence 133
In Table 5.6, we report the results of a global valuation model that combines data for all eight countries. We include all variables from the augmented RRV model except R&D and INDPE; we exclude these two variables to minimize sample size reduction because of missing data. To formally test for differences across countries in mean valuations as well as in the coefficients of the augmented RRV model, we include country dummies for seven countries and the interactions between these dummy variables and the variables in the augmented RRV model. In terms of estimation method, we report results based on ordinary least squares (OLS) as well as quantile regression. The latter is robust to the effect of outliers in the data; therefore, in our discussion, we emphasize results that are consistent across the two estimation methods.
Because we choose the United States as the base country, the coefficients on the main independent variables measure the effect of these variables on market values for US firms. The interaction term coefficients measure the country- level differences in valuation effects relative to US firms. Our first key finding is that, for US firms, the ef-fect of most of the independent variables are significant and in the expected direction. Absolute value of net income and book value of equity are positively related to market capitalization and loss firms’ net income are valued less. Leverage is valued positively consistent with a monitoring effect. Among the growth variables, capital expenditures alone are valued positively and significantly under both estimation methods. Market valuations are increasing in our three nonfinancial signals— insider retention, under-writer reputation, and auditor reputation.
Our second finding relates to the country- level dummies. Among the seven coun-tries, the dummy on China alone is negative and significant at the 1% level— after con-trolling for firm characteristics, Chinese firms alone are valued less than US firms. The cause for this difference is an interesting subject for future research.
Our third set of findings relate to the relative differences in the effect of various value- drivers between the United States and the other seven countries. We summarize these findings:
(1) The absolute value of net income of IPO firms in Australia, China, India, and the United Kingdom is valued more than that of US firms. Negative values of income are valued more for Canadian IPOs.
(2) The book value of equity of German and Japanese firms are valued more, whereas the book value of Chinese firms is valued less, relative to that of US firms.
The cross- country differences in the valuation could be attributed to the differences in financial reporting standards. For example, the accounting and finance literatures document that earnings opacity and financial reporting standards influence a range of capital market outcomes (Bhattacharya, Daouk, and Welker, 2003; Gelos and Wei, 2005; Jin and Myers, 2006). Difference in investor sophistication across countries could also drive these differences. For example, while US IPOs are largely bought by institutional investors, in India, retail investors have significant participation. More research that disentangles these alternate explanations is needed.
OUP UNCORRECTED PROOF – FIRSTPROOFS, Fri Jul 27 2018, NEWGEN
Part-1.indd 133 27-Jul-18 10:11:11 PM
Tabl
e 5.
6 Gl
obal
Val
uatio
n Re
gres
sion
s for
Inte
rnat
iona
l IPO
s (19
98– 2
015)
OLS
Qua
ntile
Reg
ress
ion
Varia
ble
Coef
.t-
stat
SLCo
ef.
t- st
atSL
Inte
rcep
t1.
868.
06*
1.77
12.9
7*
BV0.
005.
21*
0.00
6.55
*
LOG
ABSN
I0.
158.
50*
0.18
10.7
0*
LOSS
*LOG
ABSN
I−0
.07
−4.4
4*
−0.0
8−4
.71
*
DTOA
0.21
3.74
*0.
182.
94*
LOG
_ CAP
EX0.
137.
93*
0.14
12.6
7*
LOG
_ SG
RO0.
031.
80**
*0.
041.
53
RETE
NTI
ON2.
029.
70*
2.28
13.8
2*
AGE
0.00
1.27
0.00
2.03
**
UN
DREP
2.30
11.3
*2.
1517
.06
*
BIG
N_ A
UD
0.22
2.59
**0.
131.
95**
AUS
1.02
1.52
0.53
0.88
CAN
0.63
1.55
0.88
2.03
**
CHN
−1.0
5−2
.42
*−1
.16
−3.3
6*
GER
0.01
0.01
0.45
1.17
IND
−0.5
9−1
.15
−0.3
0−0
.92
JAP
0.18
0.21
0.78
1.39
UK
−0.5
8−1
.92
*−0
.51
−1.5
8
AUS*
LOG
ABSN
I0.
151.
76**
*0.
141.
83**
*
CAN
*LOG
ABSN
I−0
.02
−0.1
7−0
.07
−1.0
2
OUP UNCORRECTED PROOF – FIRSTPROOFS, Fri Jul 27 2018, NEWGEN
Part-1.indd 134 27-Jul-18 10:11:11 PM
CHN
*LOG
ABSN
I0.
5416
.68
*0.
5311
.59
*
GER
*LOG
ABSN
I0.
030.
62−0
.05
−1.1
5
IND*
LOG
ABSN
I0.
255.
29*
0.25
6.86
*
JAP*
LOG
ABSN
I−0
.12
−1.2
3−0
.07
−1.3
7
UK*
LOG
ABSN
I0.
173.
48*
0.19
4.19
*
AUS*
BV0.
000.
590.
000.
74
CAN
*BV
0.00
1.75
***
0.00
0.71
CHN
*BV
0.00
−6.1
9*
0.00
−3.6
4*
GER
*BV
0.00
3.33
*0.
002.
91*
IND*
BV0.
002.
26**
0.00
0.34
JAP*
BV0.
004.
77*
0.00
5.77
*
UK*
BV0.
00−0
.90.
00−1
.04
AUS*
LOSS
*LOG
ABSN
I0.
101.
210.
131.
29
CAN
*LOS
S*LO
GAB
SNI
0.22
2.27
**0.
303.
98*
GER
*LOS
S*LO
GAB
SNI
0.06
0.98
0.17
1.86
***
IND*
LOSS
*LOG
ABSN
I0.
101.
440.
111.
41
JAP*
LOSS
*LOG
ABSN
I0.
391.
70.
282.
37**
UK*
LOSS
*LOG
ABSN
I−0
.01
−0.2
10.
030.
49
AUS*
DTOA
−0.0
2−0
.04
0.34
0.77
CAN
*DTO
A0.
341.
20.
521.
84**
*
CHN
*DTO
A−0
.16
−0.8
9−0
.16
−0.6
2
GER
*DTO
A−0
.02
−0.1
30.
130.
40
IND*
DTOA
0.13
0.47
−0.0
6−0
.26
(Contin
ued)
OUP UNCORRECTED PROOF – FIRSTPROOFS, Fri Jul 27 2018, NEWGEN
Part-1.indd 135 27-Jul-18 10:11:11 PM
OLS
Qua
ntile
Reg
ress
ion
Varia
ble
Coef
.t-
stat
SLCo
ef.
t- st
atSL
JAP*
DTOA
−0.9
7−2
.04
*−0
.59
−1.6
8**
*
UK*
DTOA
0.28
1.5
0.45
2.68
*
AUS*
CAPE
X0.
071.
350.
040.
69
CAN
*CAP
EX0.
040.
750.
071.
29
CHN
*CAP
EX−0
.12
−5.8
1*
−0.1
2−5
.17
*
GER
*CAP
EX0.
020.
99−0
.02
−0.6
1
IND*
CAPE
X−0
.01
−0.4
2−0
.02
−0.7
6
JAP*
CAPE
X−0
.05
−1.1
4−0
.08
−2.2
2**
UK*
CAPE
X0.
061.
360.
030.
97
AUS*
SGRO
−0.2
8−1
.59
−0.2
9−1
.34
CAN
*SG
RO0.
070.
430.
130.
69
CHN
*SG
RO0.
150.
950.
171.
62
GER
*SG
RO0.
171.
530.
151.
14
IND*
SGRO
0.01
0.08
0.01
0.14
JAP*
SGRO
0.22
1.85
***
0.28
1.88
***
UK*
SGRO
−0.0
3−0
.26
−0.0
2−0
.20
AUS*
RETE
NTI
ON−1
.31
−2.1
6**
−1.1
9−2
.09
**
CAN
*RET
ENTI
ON−1
.64
−3.1
0*
−1.5
8−3
.93
*
CHN
*RET
ENTI
ON1.
702.
56**
1.58
3.28
*
GER
*RET
ENTI
ON−0
.26
−0.7
6−0
.75
−1.6
8**
*
IND*
RETE
NTI
ON−0
.88
−1.11
−1.0
6−2
.54
*
JAP*
RETE
NTI
ON−0
.65
−0.7
1−1
.55
−2.5
8*
Tabl
e 5.
6 (C
ontd
.)
OUP UNCORRECTED PROOF – FIRSTPROOFS, Fri Jul 27 2018, NEWGEN
Part-1.indd 136 27-Jul-18 10:11:11 PM
UK*
RETE
NTI
ON−0
.86
−2.9
8*
−1.2
8−3
.97
*
AUS*
AGE
0.00
−1.0
3−0
.01
−1.0
3
CAN
*AG
E0.
00−0
.13
0.01
0.76
CHN
*AG
E−0
.02
−1.7
3**
*−0
.02
−5.1
4*
GER
*AG
E−0
.01
−1.9
7**
*−0
.01
−1.4
4
IND*
AGE
0.00
0.60
0.00
−1.1
2
JAP*
AGE
−0.0
1−2
.76
*−0
.02
−4.8
4*
UK*
AGE
0.00
−0.0
70.
010.
79
AUS*
UN
DREP
−1.3
3−2
.87
*−0
.66
−1.2
0
CAN
*UN
DREP
−0.8
1−1
.87
***
−1.6
0−3
.44
*
CHN
*UN
DREP
−1.4
5−4
.23
*−1
.26
−6.4
6*
GER
*UN
DREP
−0.2
2−0
.59
−0.3
8−1
.04
IND*
UN
DREP
−0.3
8−1
.1−0
.37
−1.3
0
JAP*
UN
DREP
−1.6
0−4
.22
*−1
.71
−6.4
4*
UK*
UN
DREP
−0.5
2−1
.74
***
−0.2
6−0
.88
AUS*
BIG
N_ A
UD
0.10
0.34
0.13
0.56
CAN
*BIG
N_ A
UD
0.45
2.94
*0.
552.
71*
CHN
*BIG
N_ A
UD
−0.2
8−2
.14
**−0
.22
−1.4
8
GER
*BIG
N_ A
UD
−0.0
4−0
.43
−0.0
3−0
.22
IND*
BIG
N_ A
UD
−0.0
1−0
.04
0.02
0.15
JAP*
BIG
N_ A
UD
0.01
0.09
0.08
0.51
UK*
BIG
N_ A
UD
0.30
2.76
*0.
181.
38
Adju
sted
R2
/ Pse
udo
R280
.7%
56.4
%
No.
of o
bs.
4,22
14,
221
Not
es: T
he d
epen
dent
var
iabl
e is
the
log
of m
arke
t cap
italiz
atio
n at
the
offe
r dat
e. S
L is
sign
ifica
nce
leve
l. * i
ndic
ates
si
gnifi
canc
e at
the
1% le
vel,
** a
t the
5%
leve
l, an
d **
* at t
he 1
0% le
vel.
Stan
dard
err
ors a
ccou
nt fo
r clu
ster
ing
acro
ss fi
rms
with
in a
yea
r. Va
riabl
e de
finiti
ons a
re in
App
endi
x 5.
1.
OUP UNCORRECTED PROOF – FIRSTPROOFS, Fri Jul 27 2018, NEWGEN
Part-1.indd 137 27-Jul-18 10:11:11 PM
138 Sanjai Bhagat, Jun Lu, and Srinivasan Rangan
Turning to the other value drivers, the results in Table 5.6 indicate that non- US investors value some of the other value drivers differently. Leverage of Japanese firms is valued less compared to that of US firms, capital expenditures of Chinese firms are valued less, and sales growth of Japanese firms is valued more. The value effects of in-sider retention and underwriter reputation differ for multiple countries compared to the United States. Auditor reputation is more significantly related to value for Canadian firms. Finally, age is less important as a value driver for Chinese and Japanese firms.
5.4.3. Intertemporal Differences in Relation of Financial and Nonfinancial Variables to IPO Valuation
Table 5.7 highlights the intertemporal differences in impact of financial and nonfinancial variables on IPO valuation. Book value is not consistently related to IPO valuation during 1998– 2015. Net income is positively and statistically significantly related to IPO valuation, and this relationship has strengthened during the years 1998– 2015. For ex-ample, a 1% increase in net income in 1998 is associated with a 0.15% increase in IPO value, whereas a 1% increase in net income is associated with a 0.53% increase in IPO value in 2015. Capital expenditure is positively and significantly related to IPO value, and this relation appears to be stable over time; for example, a 1% increase in capital expenditure in 2015 is associated with a 0.12% increase in IPO value. The relationship between insider retention and IPO value is positive and statistically significant during 1998– 2002; this relation is still positive, though statistically less significant, during 2013– 2015. Underwriter reputation is positively and significantly related to IPO value in most years with no clear time trend. The relation between Big- N public accounting firm and IPO is mostly (though, not always) positive; this relation is positive and statistically sig-nificant for the most recent subperiod, 2013– 2015.
5.5. Summary and Conclusions
The valuation of IPOs occupies an important place in finance, perhaps because an IPO provides public capital market participants their first opportunity to value a set of cor-porate assets and growth opportunities. Because the IPO is the first opportunity that managers of such young companies get to observe price signals from the public capital markets, it is a setting that is important from an economic efficiency perspective. Such signals can either affirm or repudiate management’s beliefs regarding the firm’s future growth opportunities. Thus, IPO valuation has obvious implications for real economic activity— for example, employment and corporate investment.
In this chapter, we study the valuation of 6,199 IPOs during 1998– 2015 for the following countries: Australia, Canada, China, Germany, India, Japan, the United Kingdom, and
OUP UNCORRECTED PROOF – FIRSTPROOFS, Fri Jul 27 2018, NEWGEN
Part-1.indd 138 27-Jul-18 10:11:11 PM
Tabl
e 5.
7 Gl
obal
Val
uatio
n Re
gres
sion
s ove
r Tim
e fo
r Int
erna
tiona
l IPO
s (19
98– 2
015)
Varia
ble
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
BVCo
ef.
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
t- st
at9.
191.
800.
87−1
.80
1.83
0.64
−0.4
81.
200.
07−0
.20
3.21
0.03
−2.3
9−2
.39
−3.3
8−3
.30
−2.2
6−0
.26
SL*
***
***
***
***
***
***
LOG
ABSN
ICo
ef.
0.15
0.17
0.25
0.26
0.48
0.46
0.35
0.39
0.33
0.46
0.36
0.41
0.46
0.42
0.22
0.29
0.48
0.53
t- st
at3.
623.
694.
703.
704.
136.
946.
107.
406.
887.
924.
452.
645.
484.
371.
904.
808.
966.
92
SL*
**
**
**
**
**
**
***
**
**
LOSS
*LO
GAB
SNI
Coef
.0.
01−0
.01
−0.0
4−0
.06
−0.1
70.
06−0
.11−0
.01
−0.0
50.
02−0
.06
−0.1
8−0
.31
−0.1
8−0
.01
−0.0
4−0
.18
−0.0
7
t- st
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.64
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10.
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****
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LOG
_ CAP
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0.17
0.33
0.13
0.19
0.22
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0.22
0.27
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325.
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4
SL**
****
***
*
(Contin
ued)
OUP UNCORRECTED PROOF – FIRSTPROOFS, Fri Jul 27 2018, NEWGEN
Part-1.indd 139 27-Jul-18 10:11:11 PM
Varia
ble
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
RETE
NTI
ONCo
ef.
2.13
2.04
2.50
4.94
1.47
0.64
1.26
1.25
1.25
0.75
−0.0
92.
352.
133.
191.
301.
331.
451.
58
t−st
at8.
234.
625.
134.
281.
501.
873.
352.
643.
751.
97−0
.15
5.93
2.38
5.59
1.00
1.97
2.15
1.95
SL*
**
***
**
**
***
***
***
****
*
AGE
Coef
.0.
010.
000.
000.
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.01
0.00
0.00
0.00
0.01
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−0.0
1−0
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0.00
0.00
0.01
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1−0
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t−st
at1.
70−1
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0.23
3.68
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3
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UN
DREP
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t- st
at10
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7.48
6.14
0.92
2.21
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3.99
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3.71
4.05
4.72
5.76
3.56
4.74
3.67
4.49
3.63
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BIG
N_
AUD
Coef
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130.
670.
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590.
580.
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No.
of o
bs.
201
372
347
8088
114
257
202
293
343
132
146
421
350
179
126
257
305
Adj.
R2 (%)
67.7
61.3
68.1
80.6
81.2
87.4
76.5
80.9
74.1
70.5
78.8
70.2
61.3
61.9
63.1
67.5
64.7
75.7
Not
es: T
he d
epen
dent
var
iabl
e is
the
log
of m
arke
t cap
italiz
atio
n at
the
offe
r dat
e. S
L is s
igni
fican
ce le
vel. *
indi
cate
s sig
nific
ance
at t
he 1
% le
vel, *
* at t
he 5
% le
vel, a
nd **
* at
the
10%
leve
l. Sta
ndar
d er
rors
acc
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for c
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g ac
ross
firm
s with
in a
yea
r. St
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rd e
rror
s are
adj
uste
d fo
r het
eros
ceda
stic
ity. V
aria
ble
defin
ition
s are
in A
ppen
dix
5.1.
Tabl
e 5.
7 (C
ontd
.)
OUP UNCORRECTED PROOF – FIRSTPROOFS, Fri Jul 27 2018, NEWGEN
Part-1.indd 140 27-Jul-18 10:11:11 PM
IPO Valuation: The International Evidence 141
the United States. Net income is positively related to IPO valuation in each of the eight countries. The economic impact of net income is largest for Chinese IPOs and smallest for Australian IPOs. Book value is positively and significantly related to IPO valuation in only Canada, Germany, India, and the United States. Capital expenditure is significantly and positively related to IPO valuation in only Canada, Germany, India, the United Kingdom, and the United States. We find a positive and statistically significant rela-tion between insider retention and IPO valuation only in China, Germany, the United Kingdom, and the United States; positive but marginally significant relationship for India and Japan. Underwriter reputation has a positive and statistically significant rela-tionship for IPOs only in China, Germany, India, the United Kingdom, and the United States. Net income is positively and statistically significantly related to IPO valuation during the years 1998– 2015, and this relationship has strengthened over time. Capital expenditure is positively and significantly related to IPO value during 1998– 2015, and this relation appears to be stable over time.
Appendix 5.1
Variable Definitions
Variable Definition
LOGMCAP Log of the product of shares outstanding after the IPO and offer price
BV Shareholder’s equity excluding minority interest/ non- controlling interest and redeemable common stock
LOGABSNI Log of absolute value of profit. Profit excludes extraordinary items (also labeled as exceptional items or as abnormal items), discontinued operations, and the effect of changes in accounting methods. Minority interest/ Non- controlling interest is excluded.
LOSS Dummy variable that equals 1 if a firm reported a loss in year – 1, and 0 otherwise
DTOA Ratio of long- term debt to total assets. Long- term debt is the sum of all interest- bearing debt that was reported in the non- current liabilities section of the balance sheet: notes, debt, borrowings, capital lease obligations. Because we are interested in the role of debt as a source of monitoring, we exclude loans from related parties.
LOG_ RD Log of research and development costs. Research and development (R&D) costs are obtained from the Income Statement or by searching prospectuses for the following key words: “research,” “R&D,” and “product development.” Where a firm indicated that they had incurred R&D costs but did not disclose the amount, we chose to set R&D to equal zero. If R&D is equal to zero, we reset it to equal to one- half of the smallest R&D value during 1998– 2015, for the country to which the firm belonged. This adjustment allows us to apply the log transformation.
OUP UNCORRECTED PROOF – FIRSTPROOFS, Fri Jul 27 2018, NEWGEN
Part-1.indd 141 27-Jul-18 10:11:11 PM
142 Sanjai Bhagat, Jun Lu, and Srinivasan Rangan
Variable Definition
LOG_ CAPEX Log of capital expenditures, where capital expenditures is the sum of payments for property, plant, and equipment, acquisitions, and investments in subsidiaries, joint ventures, and associates.
LOG_ SGRO Change in sales in year – 1 relative to year – 2 divided by sales in year – 2. Sales included revenues from all operating sources; we exclude financial and other non- operating income. For bio- technology firms, we include government grant income.
IND_ PE The median industry PE. To measure industry PE, for each IPO firm, we obtain the market capitalizations at the end of the month before the offering date for all firms in that firm’s country that had the same two- digit SIC code (industry- peers). We chose two- digit SIC codes to minimize data loss because of industries having too few firms. For these industry peers, we obtain the income before extraordinary items in the most recent year relative to the month- end at which market capitalization is measured. We compute industry median price- to- earnings (market capitalization divided by income before extraordinary items). Market capitalization and income before extraordinary items are from CRSP and North America COMPUSTAT for US firms, Global Compustat for firms from Australia, Canada, China, Germany, Japan, and United Kingdom, and from the CMIE Prowess database for Indian firms.
RETENTION Shares outstanding before the offering minus secondary shares sold during the offering, divided by shares outstanding before the offering
AGE Difference between offering year based on offer date and the founding year
UNDREP To measure underwriter reputation, we employ the method of Megginson and Weiss (1991). For each underwriter j and for every year t, we define xjt as the three- year moving average (t– 3, t– 2, t– 1) of IPO proceeds. Then, for the set of underwriters I, for the year t, the Megginson- Weiss rank for underwriter j is
log(x )
Max log xjt
j I jt∈ ( )
BIGN_ AUD Dummy variable that equals 1 if the firm’s auditors is one of Big- N auditors, zero otherwise.
AUS Dummy variable that equals 1 for Australian IPO, zero otherwise
CAN Dummy variable that equals 1 for Canadian IPO, zero otherwise
CHN Dummy variable that equals 1 for Chinese IPO, zero otherwise
GER Dummy variable that equals 1 for German IPO, zero otherwise
IND Dummy variable that equals 1 for Indian IPO, zero otherwise
JAP Dummy variable that equals 1 for Japanese IPO, zero otherwise
U.K. Dummy variable that equals 1 for UK IPO, zero otherwise
OUP UNCORRECTED PROOF – FIRSTPROOFS, Fri Jul 27 2018, NEWGEN
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IPO Valuation: The International Evidence 143
Variable Definition
Market Return We obtain market- wide returns for the eight countries measured as the sum of 63 daily returns ending on the date before the offer date. For US firms, we use the value- weighted market return from CRSP. For the other seven countries, daily market returns are computed as percentage changes in country level indices. The indices we used to compute market returns are:Australia S&P ASX 200Canada S&P/ TSX CompositeChina Shanghai A IndexGermany DAX 30India BSE SensexJapan Nikkei 225UK FTSE 100
Notes
1. A few papers have examined the determinants of IPO prices in the United States. They are Klein (1996); Kim and Ritter (1999); and Aggarwal, Bhagat, and Rangan (2009).
2. When a firm conducted multiple offerings during the sample period, offerings subsequent to the first offering were treated as follow- on offerings and were eliminated.
3. https:// site.warrington.ufl.edu/ ritter/ ipo- data/ . 4. That is, we do not employ voluntarily disclosed non- GAAP numbers or unaudited pro
forma numbers. 5. SDC also provides offer prices in US dollars. However, because there were (a) several errors
in SDC- based offer dates and (b) relatively fewer errors in local currency offer prices that we correct, we compute dollar- value market capitalization using corrected offer prices and exchange rates on the corrected offer dates. Daily exchanges rates are from www.federalreserve.gov.
6. Australian and Canadian IPO markets are dominated by mining firms that tend to have no operations and hence no revenues before the IPO.
7. Unfortunately, the GTA database from which we obtain financial data for Chinese firms does not report R&D spending.
References
Abel, A., and J. Eberly. 2005. “Investment, Valuation, and Growth Options.” Wharton School of the University of Pennsylvania, Working paper.
Aggarwal, R., S. Bhagat, and S. Rangan. 2009. “The Impact of Fundamentals on IPO Valuation”. Financial Management 38: 253– 284.
OUP UNCORRECTED PROOF – FIRSTPROOFS, Fri Jul 27 2018, NEWGEN
Part-1.indd 143 27-Jul-18 10:11:12 PM
144 Sanjai Bhagat, Jun Lu, and Srinivasan Rangan
Barth, M. E., W. H. Beaver, W. R. Landsman. 2001. “The Relevance of the Value- Relevance Literature for Financial Accounting Standard Setting: Another View.” Journal of Accounting and Economics 31: 77– 104.
Bhattacharya, U., H. Daouk, and M. Welker. 2003. “The World Price Of Earnings Opacity.” Accounting Review 78: 641– 678.
Caglio, C., K. Hanley, and J. Westburg. 2010. “Going Public Abroad.” Securities Exchange Commission, Working paper.
Carpentier, C., D. Cumming, and J. Suret. 2012. “The Value of Capital Market Regulation: IPOs versus Reverse Mergers.” Journal of Empirical Legal Studies 9: 56– 91.
Collins, D. W., E. L. Maydew, and I. S. Weiss. 1997. “Changes in the Value- Relevance of Earnings and Book Values over the Past 40 years.” Journal of Accounting and Economics 24: 39– 67.
Cumming, D., A. Knill, and K. Syvrud. 2016. “Do International Investors Enhance Private Firm Value? Evidence from Venture Capital.” Journal of International Business Studies 47: 347– 373.
Francis, J., and K. Schipper. 1999. “Have Financial Statements Lost Their Relevance.” Journal of Accounting Research 37: 319– 352.
Gelos, R., and S. Wei. 2005. “Transparency and International Portfolio Holdings.” Journal of Finance 60: 2987– 3020.
Henderson, B., N. Jegadeesh, and M. Weisbach. 2006. “World Markets for Raising New Capital.” Journal of Financial Economics 82: 63– 101.
Jensen, M. 1989. “Eclipse of the Public Corporation.” Harvard Business Review (September/ October): 61– 74.
Jin, L., and S. Myers. 2006. “R2 around the World: New Theory and New Tests.” Journal of Financial Economics 79: 257– 292.
Johan, S. A. 2010. “Listing Standards as a Signal of IPO Preparedness and Quality.” International Review of Law and Economics 30: 128– 144.
Kim, M., and J. Ritter. 1999. “Valuing IPOs.” Journal of Financial Economics 53: 409– 437.Kim, W., and M. Weisbach. 2008. “Motivations for Public Equity Offers: An International
Perspective.” Journal of Financial Economics 87: 281– 307.Klein. A. 1996. “Can Investors Use the Prospectus to Price Initial Public Offerings?” The Journal
of Financial Statement Analysis 2: 23– 40.Kothari, S. 2001. “Capital Markets Research in Accounting.” Journal of Accounting and
Economics 31: 105– 231.La Porta, R., F. Lopez- de- Silanes, A. Shleifer, and R. Vishny. 1997. “Legal Determinants of
External Finance.” Journal of Finance 52: 1131– 1150.La Porta, R., F. Lopez- de- Silanes, A. Shleifer, and R. Vishny. 2000. “Investor Protection and
Corporate Governance.” Journal of Financial Economics 58: 3– 27.Lev, B., 2001. Intangibles: Management, Measurement, and Reporting. Washington, DC: The
Brookings Institution.Loughran, T., J. Ritter, and K. Rydqvist. 1994. “Initial Public Offerings: International Insights.”
Pacific- Basin Finance Journal 2: 165– 199.Megginson, W., and K. Weiss. 1991. “Venture Capitalist Certification in Initial Public Offerings.”
Journal of Finance 46: 879– 903.Myers, S. 1977. “Determinants of Corporate Borrowing.” Journal of Financial Economics
5: 147– 175.
OUP UNCORRECTED PROOF – FIRSTPROOFS, Fri Jul 27 2018, NEWGEN
Part-1.indd 144 27-Jul-18 10:11:12 PM
IPO Valuation: The International Evidence 145
Ohlson J. 1990. “A Synthesis of Security Valuation Theory and the Role of Dividends, Cash Flows, and Earnings.” Contemporary Accounting Research 6: 648– 676.
Penman, S. 1998. “Combining Earnings and Book Value in Equity Valuation.” Contemporary Accounting Research 15: 291– 324.
Rhodes- Kropf, M., D. T. Robinson, and S. Viswanthan. 2005. “Valuation Waves and Merger Activity: The Empirical Evidence.” Journal of Financial Economics 77: 561– 603.
OUP UNCORRECTED PROOF – FIRSTPROOFS, Fri Jul 27 2018, NEWGEN
Part-1.indd 145 27-Jul-18 10:11:12 PM