Hitotsubashi University
Institute of Innovation Research

Initial Public Offering and Financing of Biotechnology
Start-ups: Evidence from Japan

Yuji Honjo
Sadao Nagaoka

IIR Working Paper WP#15-20

Sep. 2015

Institute of Innovation Research
Hitotsubashi University
Tokyo, Japan
http://www.iir.hit-u.ac.jp

Initial public oﬀering and ﬁnancing of biotechnology
start-ups: evidence from Japan∗
Yuji Honjo† and Sadao Nagaoka‡

Abstract:

This paper explores the initial public oﬀering (IPO) and ﬁnancing of

biotechnology start-ups in Japan. Using a unique data set, we ﬁnd that biotechnology start-ups initially backed by venture capital (VC) ﬁrms and those originatingfrom universities are more likely to go public within a shorter period. Moreover,
we examine whether two investment methods used by VC ﬁrms—staged ﬁnancing
and syndication—aﬀect the market value of equity at the IPO. The results revealthat these methods do not create a higher value of biotechnology start-ups at the
IPO. Furthermore, we provide evidence that the timing of IPOs does not depend on
market conditions in the biotechnology industry, whereas the market value of equity
tends to depend on market conditions.
JEL Classifications: G32; M13; L65
Keywords: Biotechnology; Initial public oﬀering; Market value; Staged ﬁnancing;
Start-up; Syndication∗

This study is part of an extended project of a research program entitled “Research on Science
Sources of Innovations and Economic Impacts of Science” supported by the Japan Science andTechnology Agency. We are grateful to the participants of the workshop held at Hitotsubashi
University and Nagoya University. In particular, we thank Takanori Adachi, Yoshiaki Ishii, Daisuke
Miyakawa, and the members of our research project for their valuable comments and suggestions.
Moreover, we would like to express our appreciation to the directors of biotechnology start-ups andventure capitalists who agree to participate in our interviews. Needless to say, any remaining errors
are the authors’ own.
†
Y. Honjo (corresponding author)
742-1 Higashinakano, Hachioji, Tokyo 192-0393, Japan
Faculty of Commerce, Chuo University
e-mail: yhonjo@tamacc.chuo-u.ac.jp‡
S. Nagaoka
Faculty of Economics, Tokyo Keizai University

1

1.

Introduction

The emergence of new technologies is believed to spur future economic growth.
Among the new technologies, biotechnology has created a paradigm shift in thepharmaceutical and agricultural ﬁelds. For instance, in accordance with the recent
development of biotechnology, the major drug discovery approach seems to haveshifted from chemical-based to biotechnology-based ones.1 Such a paradigm shift
may have a considerable impact on industrial organization in the pharmaceuticalindustry. Indeed, until recently, large pharmaceutical companies have been central
to drug discovery, including the so-called “blockbuster.”2 However, the division oflabor between biotechnology start-ups, universities, and pharmaceutical companies
has become more important because the drug discovery process is highly uncertain and includes multiple stages. Compared with large pharmaceutical companies,
small, young ﬁrms and universities as a whole can undertake more discovery projects
and therefore are expected to play an important role in providing new drug candidates and drug discovery technologies. Large pharmaceutical companies may often
use alliances with universities and biotechnology start-ups for drug discovery. At thesame time, the division of labor enables large pharmaceutical companies to reduce
the high risk in the early-stages of drug development by aligning with biotechnology
start-ups, although the risks are ultimately born in private equity markets.
As biotechnology start-ups require a large amount of research and development(R&D) investment, they must often rely on external ﬁnance. However, biotechnology start-ups cannot always obtain suﬃcient funds from loans because of uncertainty
1

Among the best-selling drugs of 2013, for example, seven drugs derived from biotechnology—
R
RR)) [Rank 2], inﬂiximab (Remicade⃝) [Rank 1], etanercept (Enbrel⃝adalimumab (Humira⃝
RR) [Rank 7], and trastuzumab) [Rank 6], bevacizumab (Avastin⃝[Rank 3], rituximab (Rituxan⃝R) [Rank 9]—are ranked in the top 10 for worldwide sales. For more details, see the(Herceptin⃝
website of Free Daily Pharma Industry Newsletter.
http://www.ﬁercepharma.com/special-reports/top-10-pharma-companies-2013-revenue [accessedon February 17, 2015].
2
The large pharmaceutical companies in Japan, such as Takeda Pharmaceutical, have developed
R). As Kneller (2003) stated, drug
some chemical blockbusters; for example, candesartan (Blopress⃝
discovery in the Japanese pharmaceutical companies has occurred predominantly in-house.

2and information asymmetries between entrepreneurs and creditors. To facilitate equity ﬁnancing of R&D, biotechnology start-ups tend to pursue greater access toequity markets. Although not all do this, some biotechnology start-ups go public; that is, they issue an initial public oﬀering (IPO). In particular, biotechnology
start-ups that require a signiﬁcant amount of funds for R&D are compelled to go
public for conducting R&D activities. The fate of their R&D activities is criticallydependent on whether such biotechnology start-ups can go public. In this case, wehave a saying: “public or perish.”This paper explores the IPO and ﬁnancing of biotechnology start-ups in Japan.
Despite the important role of small and young ﬁrms, biotechnology start-ups appear to be inactive in the Japanese economy. In this respect, the investigation of
biotechnology start-ups would be of great interest in promoting the development of
the biotechnology industry. To our understanding, however, there is a scarcity ofdata suitable for empirical studies. In this paper, we construct a unique data set of
213 ﬁrms that were founded in the most recent twenty-year period (1995–2014).
This paper aims to investigate the market values of equity for biotechnology
start-ups at the IPO. This is because most initial investors, including venture capital (VC) ﬁrms, presumably pay much attention to these issues. However, manybiotechnology start-ups remain privately held. Before doing so, therefore, we examine the types of biotechnology start-ups that go public. Using a survival analysis
approach, we ﬁnd that biotechnology start-ups initially backed by VC ﬁrms andthose originating from universities are more likely to go public within a shorter
period. With respect to the market values of equity, the results reveal that two
investment methods often regarded to be value enhancing—staged ﬁnancing andsyndication—do not create a higher value of biotechnology start-ups at the IPO.
Furthermore, we provide evidence that the timing of IPOs does not depend on market conditions in the biotechnology industry, whereas the market value of equity
tends to depend on market conditions.

3

The remainder of this paper is organized as follows. The following section introduces the research background, including a review of the relevant literature. Section
3 describes the method used in this paper. Section 4 explains the data used in
our analysis, and Section 5 presents the estimation results. In the ﬁnal section, we
provide some concluding remarks.

2.

Research background

2.1.

IPOs of biotechnology start-ups

For high-tech start-ups, ﬁnancing becomes a critical factor in expanding their businesses. Even if a ﬁrm has growth potential, external suppliers of capital—such as
banks and investors—do not always provide suﬃcient capital to the ﬁrm. This isbecause these suppliers cannot completely understand new technologies the ﬁrm isdeveloping; that is, information asymmetries arise between entrepreneurs and external suppliers of capital. In particular, younger ﬁrms face more diﬃculties in raisingfunds from external suppliers of capital as they have limited operating histories andlack complementary assets, including know-how and relationships that take many
years to develop.
High-tech start-ups, including biotechnology start-ups, tend to require externalﬁnancing for a large amount of R&D investment. However, banks are often reluctant
to lend money to high-tech start-ups because R&D investment is likely to become
sunk costs and high-tech start-ups have few tangible assets to provide suﬃcient collateral. Moreover, many start-ups do not generate cash ﬂow during their start-up
period; thus, debt-ﬁnancing interest payments become a burden on their businesses.
In this respect, high-tech start-ups are more likely to rely on equity ﬁnancing rather
than debt ﬁnancing, such as bank loans.
It is often argued that venture capitalists play a critical role in providing funds tohigh-tech start-ups. As Gompers (1995) emphasized, venture capitalists concentrate4

investments in younger ﬁrms and high-tech industries where informational asymmetries are signiﬁcant and monitoring is valuable. The role of venture capitalists may
be important for high-tech start-ups, especially in countries such as Japan, where
private ﬁnancings that raise funds from individual investors are less common.3 At
the same time, venture capitalists seek exit strategies for their investments and,without doubt, an IPO is one of their most typical exit strategies. While an IPO
is simply one of the millstones for biotechnology start-ups in the process of technology and product development, investors—including venture capitalists—expect
larger capital gains from an IPO. More importantly, because mergers and acquisitions (M&A) are less pronounced as a strategic exit in Japan, venture capitalists
are more likely to rely on an IPO as an exit strategy. Therefore, to recoup theirinvestments and proceed to invest in another high-tech start-up, venture capitalists
expect the start-ups to conduct an IPO in a relatively short timeframe.
Many studies have emphasized the role of VC on the IPO process. Megginson
and Weiss (1991), for example, found that VC-backed ﬁrms are signiﬁcantly younger,
have greater median book values of assets, and have a larger percentage of equity inthe capital structure than their non-VC-backed counterparts. Helwege and Packer(2009) argued that ﬁrms controlled by VC and private equity specialists are signiﬁcantly more likely to go public and that these ﬁrms value the IPO as an important
exit strategy for outside equity. Therefore, it is plausible that the likelihood of an
IPO depends on the presence of VC.
Regarding the IPO of biotechnology ﬁrms, Lerner (1994b) examined the timing of IPOs and private ﬁnancings by venture capitalists.4 Using a sample of 350
privately held VC-backed biotechnology ﬁrms in the US between 1978 and 1992,
3

In fact, as shown later, more than 20% of IPO ﬁrms in our data set relied on VC ﬁrms for theirinitial ﬁnancing.
4
Although they did not focus on biotechnology ﬁrms, Pagano et al. (1998) estimated the determinants of IPOs using a database of private ﬁrms in Italy and found that the likelihood of an IPO
is increasing in ﬁrm size and the industry’s market-to-book ratio. More recently, several empiricalstudies have examined the likelihood of an IPO using data on ﬁrms in Japan (e.g., Honjo, 2012;
Miyakawa and Takizawa, 2013).

5

Lerner showed that these ﬁrms go public when equity values are high, and that they
employ private ﬁnancings when equity values are lower. The results indicated thatthe likelihood of an IPO for biotechnology start-ups depends on market conditions.
However, ﬁnancing is often critical for most biotechnology start-ups because theymust continue to support R&D activities that require a large amount of investment.
In particular, biotechnology start-ups that face ﬁnancial diﬃculties in conducting
R&D activities cannot aﬀord to wait for a market recovery, even though they hopethat market conditions steadily improve. Therefore, there is the possibility thatbiotechnology start-ups tend to go public, regardless of market conditions. Rather,biotechnology start-ups may prefer to go public within a shorter period to expand
their equity ﬁnancing of R&D activities. At the same time, this may result in therecovery of investments for initial investors.
As mentioned earlier, this paper explores the IPO of biotechnology start-ups inJapan. Whereas Lerner’s (1994b) results indicate the impact of market conditions on
the likelihood of an IPO, biotechnology start-ups may go public, regardless of market
conditions, to secure ﬁnancing for their R&D activities. Venture capitalists—someof whom play a critical role as initial investors in Japan where private ﬁnancings
through individual investors (the so-called “business angels”) are less common—also
hope to quickly recoup their investments.5 Therefore, we predict that biotechnology
start-ups that are initially ﬁnanced by VC ﬁrms are more likely to go public withina shorter period.
2.2.

IPO values of biotechnology start-ups

Most, but not all, high-tech start-ups expect to raise funds from capital markets
through an IPO. High-tech start-ups often require ﬁnancing because of a large
5

For instance, using data provided by the Global Entrepreneurship Monitor, Honjo (2015) foundthat among 32 countries, Japan has the lowest level for new business investment by individuals, asmeasured by the ratio of individuals who have personally provided funds for a new business started
by someone else in the three years.

6amount of capital for R&D activities. By analyzing data on Italian ﬁrms, Pagano etal. (1998) estimated the eﬀects of an IPO on ﬁrm performance based on accounting
measures, such as the return on assets (ROA) and capital expenditures.6 However,
we cannot say that current proﬁtability is a better index of short-term performancefor biotechnology start-ups. This is because most biotechnology start-ups remainin the R&D phase, even after going public, and they do not gain suﬃcient sales
and yield positive proﬁts. Meanwhile, initial investors would probably pay more
attention to recouping their investments. Regarding the success of an IPO, Deeds
et al. (1997) addressed the amount of capital raised by the ﬁrm. If access to capitalis the major goal of going public, the amount of capital raised from the market will
generate interest among initial investors, including venture capitalists.
To date, several studies have examined the IPO value, which indicates the market value of equity at the IPO, and the determinants of the IPO value. By analyzing
data on 92 publicly-held ﬁrms in the US biotechnology industry, Deeds et al. (1997)
deﬁned the IPO value as the total value of capital raised from the IPO minus theunderwriter’s fees and estimated the eﬀects of location, the number of products, andcitations on the IPO value. Based on 36 ﬁrms in the Korean biotechnology industry,
Lee and Lee (2008) also used a similar variable for the IPO value and found theeﬀects of R&D investment, sales, and proﬁts on the IPO value. Whereas these studies provided interesting results, their results may simply reﬂect the characteristics
of biotechnology ﬁrms with a large capital size. Initial investors, including venture
capitalists, often invest a large amount of capital leading up to the IPO. Even if thevalue of a ﬁrm is evaluated as high at the IPO, there is the possibility that this value
does not generate suﬃcient returns for investors. From the viewpoint of investors,
therefore, more attention should be paid to the return on investment; that is, weshould address how the IPO yields a return from the invested capital prior to the6

As for IPOs in Japan, Miyakawa and Takizawa (2013) investigated ﬁrm performance measured
by total factor productivity and ROA, using a diﬀerence-in-diﬀerence approach.

7

IPO.
This paper investigates the IPO value of biotechnology start-ups. When measuring this value, we use not only the market value of equity at the IPO but alsoa relative measure for the IPO value from the perspective of investment eﬃciency.
Furthermore, some biotechnology start-ups reduce their equity prior to the IPO toeliminate any accumulated deﬁcits. As total equity at the time of the IPO does
not include capital reductions, it is inappropriate to capture the amount of total
investment, which is used as the denominator when we assess the IPO value. In thispaper, therefore, we propose a new proxy for ﬁrm performance at the IPO, taking
into account capital reductions.7
2.3.

Investment methods of VC firms

VC ﬁrms must address information uncertainty associated with investment decisions
and information asymmetries between entrepreneurs and venture capitalists, which
often generate agency and monitoring costs. To reduce information uncertainty
and asymmetries, venture capitalists often utilize staged capital infusion; namely,“staged ﬁnancing.” As Gompers (1995) argued, staged capital infusion enables venture capitalists to reevaluate the ﬁrm’s project and to reduce potential losses frombad decisions. Gompers also provided evidence on the positive relationship between
total VC ﬁnancing and the number of ﬁnancing rounds.8
In addition to staged ﬁnancing, syndication is a widely-used method for theinvestment strategy of VC ﬁrms. VC ﬁrms utilize syndication when they jointly
invest in a ﬁrm, while undertaking staged ﬁnancing. As Lerner (1994a) argued,
syndication is a mechanism through which venture capitalists resolve the informa7

Nelson (2003) also proposed an index for the percent price premium at the IPO, which indicatesthe assessment of investor optimism. Meanwhile, the cumulative average market-adjusted returnand average buy-and-hold return for the post-IPO have often been used. In this paper, however, wehighlight performance at the IPO, rather than after the IPO, and do not employ these measures.
Further investigation of these measures will be part of our future studies.
8
Hand (2007) found that equity returns between ﬁnancing rounds are reliably negatively related
to ﬁrm size and positively related to book-to-market ratios.

8tional uncertainty about potential investments. Lerner emphasized that syndication
leads to a superior selection of investments, which is referred to as the “selection
hypothesis,” and provided support for this hypothesis using data on VC investmentsin the biotechnology industry. Because it is more eﬃcient to undertake the projects
approved by two or more reviewers (investors) during the staged ﬁnancing process,syndication may enhance the market value of equity at the IPO. Lerner also examined the choice of syndication partners in ﬁrst, second, and later rounds, and foundthat in the ﬁrst round, established venture capitalists tend to syndicate with one
another; however, later rounds involve less established venture organizations. This
indicates that syndication in the ﬁrst round of ﬁnancing leads to better decisions
about whether to invest because informational asymmetries are more severe. Therefore, this stage plays a more signiﬁcant role in increasing the market value of the
ﬁrm compared with syndication in the later rounds of ﬁnancing. In this respect, we
can say that the eﬀects of syndication diﬀer between the ﬁrst and later rounds ofﬁnancing.
In contrast, Brander et al. (2002) argued that returns to syndicated investments
are lower than those to standalone investments.9 If the assessment by a venture
capitalist yields a high expected value, the venture capitalist accepts the project asthere is little need for syndication. Similarly, there is little need for staged capital infusion in this case. Therefore, it is possible that staged capital infusion andsyndication induce a negative signal about the project. Meanwhile, VC ﬁrms havea strong incentive to participate in syndicated investment in ﬁrms with a higher
probability of issuing an IPO. This is because investing in IPO ﬁrms enables VC
ﬁrms to enhance their reputation in the market. As a result, VC ﬁrms are reluctant
to miss any investment opportunities in IPOs and, hence, they have an incentive to
9

Brander et al. (2002) proposed the additional role of syndication, which is referred to as the“value-added hypothesis,” because venture capitalists can add value to the ﬁrms in which they
invest, and addressed the value-added hypothesis over the selection hypothesis as a possible rationale
for syndication.

9

participate in syndicated IPO investments, regardless of the expected value of the
projects.
In this paper, we highlight these investment methods of venture capitalists. As
discussed above, it is unclear whether these methods really generate a higher value
for an IPO. Furthermore, it is well recognized that Japan has the characteristics of abank-centered capital market (e.g., Black and Gilson, 1998). In fact, many VC ﬁrms
in Japan originated as subsidiaries of ﬁnancial institutions, including banks and security companies, where some managers are on temporary assignment. These VC
ﬁrms have an incentive to safely manage the assets provided by their parent companies rather than to take large risks, thereby resulting in an increase in the number
of VC ﬁrms that imitate such investment behavior. This paper examines whether
these investment methods add values to the Japanese biotechnology start-ups.

3.

Method

3.1.

IPO duration

First, using a survival analysis approach, we investigate the types of ﬁrms thatgo public within a shorter period. Consider the probability of ﬁrm i’s IPO at t,
which indicates the duration from the foundation date to the IPO date (hereafter,“IPO duration”). Let Ti∗ denote the IPO duration of ﬁrm i. However, we cannot
observe Ti∗ for all ﬁrms because many ﬁrms have not yet gone public during theobservation period. Furthermore, while some ﬁrms go public during the observation
period, others exit the market before going public because of liquidation throughbankruptcy. More precisely, Ti∗ is observable if a ﬁrm goes public until censoring
time, denoted by Ci , and the ﬁrm does not exit the market before going public;
otherwise, Ti∗ is not observable. We can deﬁne observable time, Ti , such that Ti ={}min Ti∗ , T̃i , Ci where T̃i is a competing event other than an IPO.
The probability of ﬁrm i’s IPO is captured by a hazard, h(t; Zit ), which is a10

function of a vector of covariates (variables), Zit . Based on this hazard, we consider
a proportional hazards model proposed by Cox (1972) to identify the determinantsof an event. However, some ﬁrms exit the market before going public becauseof liquidations. Without considering these exits, we would produce results witha selection bias. Therefore, we regard exits as competing risks and estimate thedeterminants of IPOs other than exits.10
Instead of the standard proportional hazards model, we employ a competingrisks regression and deﬁne the sub-hazard, h̄(t; Zit ).11 The speciﬁcation, which issimilar to the proportional hazards model, is write as follows:12h̄(t; Zit ) = h̄0 (t) exp (αZit )(1)

where h̄0 (t) is the baseline sub-hazard and α is the parameter to be estimated. By
maximizing the log-pseudo-likelihood function proposed by Fine and Gray (1999),
we obtain the parameter estimates, α̂, which indicate whether the covariate shortensthe duration of an IPO.
Note that the IPO duration denoted by t indicates ﬁrm age at the IPO. According
to their foundation years, ﬁrms face diﬀerent market conditions; therefore, we control
for market conditions in the estimation.
3.2.

IPO values

Next, we investigate ﬁrm performance measured by the market value of equity at the
IPO, based on a cross-sectional analysis. As we cannot observe the market values forprivately-held ﬁrms, we estimate the determinants of the IPO values only for ﬁrms
10

In practice, several ﬁrms acquired by public ﬁrms might achieve a successful exit strategy.
Unfortunately, we could not identify which ﬁrm achieved a successful exit in the data set; thus, we
treat exits other than IPOs as competing risks. However, as M&A are less pronounced as an exit
strategy in Japan, it is considered that successful exits are rare.
11
Meanwhile, Giot and Schwienbacher (2007) examined the time-to-exit through an IPO, a tradesale, and a liquidation for VC-backed ﬁrms, using a sample of investment rounds. In their estimation,
a competing-risks regression was used to allow for a joint analysis of exit type and exit timing.
12
For more details on the competing-risks regression, see, for example, Fine and Gray (1999).

11

that have gone public during the observation period. In the data set, although manyﬁrms are privately held, some ﬁrms conduct an IPO. If we ﬁnd a positive eﬀect of
VC ﬁrms on the IPO value, then this ﬁnding may indicate that the ﬁrm backed by
VC ﬁrms has a higher probability of issuing an IPO. Therefore, we employ a sample
selection model, while taking into account the sample selection bias,.
Let Yi denote the market value of equity for ﬁrm i at the IPO. We assume that
this market value is a linear function of a vector of variables, Xi . Hence, we write
this as follows:
Yi = β0 + β1 Xi + ui

(2)

where β0 and β1 are parameters to be estimated; ui is an error term; and ui ∼N (0, σ 2 ). For Equation (2), however, Yi can be observed if
γ0 + γ1 Wi + vi > 0(3)where Wi is a vector of variables; γ0 and γ1 are parameters to be estimated; vi is anerror term; vi ∼ N (0, 12 ); ui and vi have correlation ρ; and λ = ρσ. Otherwise, Yicannot be observed.
A two-step estimation method proposed by Heckman (1979)—often called the“Heckman selection model”—is used to obtain the parameter estimates: β̂0 , β̂1 , γ̂0 ,and γ̂1 .13 In Equation (2), we regress Yi on Xi , while estimating parameters ρ andσ. Among the parameter estimates, β̂1 indicates whether the variable aﬀects themarket value of equity for biotechnology start-ups.

4.

Data

4.1.

Data source

When examining start-up ﬁrms in Japan, we often face diﬃculties in obtaining data
and developing cases suitable for our studies. For instance, although the Nikkei Economic Electronic Databank System–Financial Quest (NEEDS–FQ), which has often
13

We employed the maximum likelihood estimation, instead of the Heckman two-step estimation.

12

been used as a data source for Japanese ﬁrms, covers all listed ﬁrms in Japan, the itdoes not suﬃciently cover small and young ﬁrms. Moreover, the database provided
by a credit investigation company, such as Teikoku Data Bank, does not include
an industrial classiﬁcation for biotechnology and, therefore, it is quite diﬃcult tocollect data on biotechnology ﬁrms. How we construct a data set of biotechnology
start-ups under these constraints is critical in conducting research on biotechnology
start-ups in Japan.
To construct the data set of biotechnology start-ups, we obtained a list of ﬁrms
from the Japan Bioindustry Association (JBA), which is a general incorporated
foundation that promotes the development of the biotechnology industry and thatsurveys biotechnology ﬁrms in Japan.14 However, since the JBA does not usually
survey the ﬁnancing of biotechnology ﬁrms, especially from venture capitalists, wecannot identify how biotechnology ﬁrms are ﬁnanced and which ones are backed by
VC ﬁrms from this data source. For this reason, we collected data on the ﬁnancingof biotechnology ﬁrms from a database provided by Japan Venture Research (JVR),
which is a research and consulting company that surveys not only venture capitalists
but also new ventures backed by VC ﬁrms or other corporations. As a result, by
matching ﬁrms listed in the JBA and JVR databases, we constructed a data set of
biotechnology start-ups.15 In addition to these data sources, the listing prospectus,
annual securities report, and website of each ﬁrm were used to collect data on the
ﬁrm’s proﬁle. Moreover, Kabushiki Kokai Hakusho (White Paper on Initial Public
Oﬀerings) edited by Disclosure Jitsumu Kenkyukai was used to collect data on thetiming and capital increases of IPOs. Furthermore, the NEEDS–FQ was used tocollect data on stock prices, equity values, and stock market indices.
To determine the observation period, we describe the trend in the number of
14

For more details on the surveys of the JBA, see, for example, Honjo et al. (2014).
We constructed our data set mainly from the JVR database because the required ﬁnancial
data for our analysis were available in the JVR database. A few ﬁrms listed in the JVR databasewere regarded in the JBA database as no longer engaged in biotechnology; thus, these ﬁrms were
excluded from the data set.
15

13

ﬁrms in the biotechnology industry of Japan in Figure 1.16 We found that the
number of ﬁrms increased after the mid-1990s, reached its peak in the 2000s, anddecreased in recent years. Several ﬁrms founded over a long period of time are included in the JVR database. Therefore, we set 20 years as the “start-up” stage andexcluded ﬁrms that exceeded 20 years from the data set.17 More precisely, the data
set comprises biotechnology ﬁrms founded during the period 1995–2014, which is
the observation period in this paper. As shown in Figure 1, this period covers theboom times for new entrants in the biotechnology industry of Japan.
As an additional data screening step, ﬁrms of which primary businesses are regarded as contract research organizations (CRO) or site management organizations(SMO) are excluded from the data set. In addition, a few foreign ﬁrms of whichhead oﬃces are located outside Japan are excluded from the data set. As a result,
we deﬁne a biotechnology start-up as a ﬁrm founded during the period 1995–2014
in the biotechnology industry of Japan, except for CRO and SMO.
4.2.

Descriptive statistics

The data set comprises 213 biotechnology start-ups in Japan. Among them, 33 ﬁrms
(33/213 ≃ 15%) have experienced an IPO, while 180 ﬁrms have not (to December2014).18
For the 33 IPO ﬁrms, Figure 2 displays the trend in the number of IPOs ineach market. As shown in Figure 2, all of the IPO ﬁrms were not listed in the
16

Figure 1 indicates the number of ﬁrms, based on the JBA survey, regardless of age. Moreover,
our constructed data set does not include ﬁrms if it was unclear whether the ﬁrms were backed by
VC ﬁrms. Therefore, the number of ﬁrms in Figure 1 is larger than that in our data set.
17
In general, the period of 20 years seems rather long as a start-up stage. However, since it often
takes a long period to develop new drugs, we employed 20 years as the observation period. Notethat the deﬁnition of biotechnology start-ups in the JBA survey is not completely consistent with
our deﬁnition, as the JBA survey excludes young but large-sized ﬁrms.
18
Although three of the 33 ﬁrms (LTT Bio-Pharma, ECI, and Mebiopharma) were privately heldin December 2014 by going private, we regarded these three ﬁrms as IPOs in the analysis. Further,since data on the number of ﬁnancing rounds, which will be discussed later, were not obtainable forone ﬁrm (Mebiopharma) in the JVR database, we employed 32 ﬁrms in the analysis of IPO values.

14established stock exchanges, such as the Tokyo Stock Exchange (TSE), but in theemerging markets—JASDAQ, MOTHERS, Centrex, and Tokyo Pro Market (formerly, Tokyo AIM)—which provide access to the funding of young and emerging
small- and medium-sized ﬁrms. This is mainly because there are no criteria forﬁnancial performance, such as proﬁts, in some of the emerging markets. Indeed,without these emerging markets, some of the IPO ﬁrms would not be able to go
public as they have negative proﬁts.19 In this respect, we can say that the emerging
markets in Japan are helpful in promoting the IPO of biotechnology start-ups.
Surprisingly, IPOs in the biotechnology industry of Japan are consistently foundin Figure 2. New emerging markets, such as MOTHERS and Centrex, have been created since the late 1990s and two university-origin start-ups (Anges MG and Trans
Genic) went public in 2002. Since then, biotechnology start-ups have continued toissue an IPO in the emerging markets. More importantly, the economic recession
triggered by the Lehman Brothers collapse in 2008 resulted in depressed stock markets in Japan. According to Kabushiki Kokai Hakusho, the number of IPOs in allof Japan’s stock markets considerably decreased after the Lehman Brothers collapse
and this number in all industries was down to fewer than 20 in 2009. Nevertheless,
as Figure 2 demonstrates, a dramatic change in the number of IPOs in the biotechnology industry is not found in and after 2009. In this respect, it is plausible that
the IPO of biotechnology start-ups is independent of market conditions.
Table 1 presents the trend in the number of biotechnology start-ups founded ineach year. While the number of biotechnology start-ups (A + B) increases from thelate 1990s to the early 2000s, it decreases after the late 2000s. This trend is consistent with the distribution shown in Figure 1. In this respect, the low level of new
entrants in recent years, which indicates stagnant entrepreneurship, is of increasing
concern in developing the biotechnology industry of Japan. Meanwhile, while theAmong the 32 IPO ﬁrms in the data set, 22 ﬁrms (22/32 ≃ 69%) had negative operating proﬁts
in their post-IPO accounting year, although the ﬁnancial statements of one IPO ﬁrm (Ribomic),
which went public in September 2014, could be obtained.
19

15

number of biotechnology-startups (A + B) founded in the late 1990s is lower, theratio of IPO ﬁrms (A/(A + B)) seems higher. Some biotechnology start-ups foundedin the late 1990s may be able to go public because of the boost in the emerging
markets and the policies promoting start-ups from universities.20
Table 2 presents the summary statistics of IPO duration, which capture ﬁrm age
measured by the number of months from the foundation date to the IPO date. The
IPO duration for the 33 IPO ﬁrms, on average, takes 84 months (7 years), although
this value is restricted to biotechnology start-ups that have already gone public. Table 2 also presents the summary statistics of IPO duration for each ﬁve-year period,
according to the foundation years of ﬁrms. While the ratio of IPO ﬁrms founded in
the late 1990s is higher, as shown in Table 1, the IPO duration does not seem todiﬀer according to the foundation year of ﬁrms.
Tables 3 and 4 describe the distribution of biotechnology start-ups by dividing
the data set into IPO ﬁrms (public ﬁrms) and non-IPO ﬁrms (private ﬁrms). Table
3 presents the number of biotechnology start-ups that raised equity from VC ﬁrms
when they were founded (hereafter, “initially VC-backed start-ups”). The ratio of
initially VC-backed start-ups accounts for more than 20%(≃ 7/33) of IPO ﬁrms inthe data set. According to Table 3, while the ratio of initially VC-backed start-ups
seems low (17/213 ≃ 8%), the ratio of IPO ﬁrms for initially VC-backed start-ups(7/17 ≃ 41%) is much higher than that for others (26/196 ≃ 13%). There is a
traditional view that VC ﬁrms rarely invest in high-technology ﬁrms in Japan (e.g.,
Black and Gilson, 1998). However, we provide evidence that VC ﬁrms play a rolein providing funds to biotechnology start-ups, especially as initial investors, partly
because equity ﬁnancing from individual investors is less common in Japan.
Table 4 presents the number of biotechnology start-ups that originated fromtechnologies developed in universities or persons associated with universities (here20

In 2001, the Ministry of Economy, Trade and Industry in Japan proposed a policy entitled,“The 1000 University-launched Ventures Plan,” to promote an industry–academia–government collaboration.

16

after, “university-origin start-ups”). While development in science spreads rapidly
at the international level, as argued by Goto (2000), universities still play a vitalrole in their respective countries as a local source of scientiﬁc knowledge. In thedata set, university-origin start-ups account for approximately 39%(≃ 83/213) ofbiotechnology start-ups, suggesting that universities play a role in providing thetechnological seeds for biotechnology start-ups in Japan. Moreover, the ratio of IPO
ﬁrms for such university-origin start-ups (23/83 ≃ 28%) is higher than that for others (10/130 ≃ 8%). Tables 3 and 4 may also indicate that the likelihood of an IPO
depends on the initial conditions for new ﬁrm creation.
Table 5 describes the market value of equity for IPO ﬁrms in the data set. The
mean of the IPO value that indicates the market value of equity at the IPO is approximately 29 billion yen (the median is approximately 14 billion yen). In Table
5, we present equity ﬁnancing that includes not only total paid-in capital (paid-in
capital plus additional paid-in capital) but also capital reduction. Although capital
reduction decreases equity, it should be included in equity ﬁnancing prior to the
IPO. In other words, Table 5 provides “gross” equity ﬁnancing prior to the IPO
by returning capital reduction to equity ﬁnancing. Moreover, because ﬁrms usually
issue new equity when they go public, we also provide the “IPO capital increase,”
which indicates the capital increase at the IPO. Table 5 shows that the mean ofequity ﬁnancing prior to the IPO is approximately 3.6 billion yen (the median isapproximately 1.8 billion yen) and the mean of the IPO capital increase is approximately 2.4 billion yen (the median is approximately 2.1 billion yen). Furthermore,
Table 5 presents the ratio of the IPO value divided by equity ﬁnancing prior to the
IPO and divided by the total equity invested that is measured as the sum of equity
ﬁnancing prior to the IPO and the capital increase at the IPO. The latter ratio
proposed in this paper (A/(B + C)) is a useful proxy to capture investment eﬃciency at the IPO, which may reﬂect ﬁrm performance and is similar to the conceptof the market-to-book ratio or average Tobin’s q. As a result, we ﬁnd that a Y=117

investment in a biotechnology start-up that goes public provides an average returnof Y=7.15 beyond the total equity invested (the median is Y
=3.05).
Table 6 describes the numbers of ﬁnancing rounds and VC ﬁrms for IPO ﬁrms.21
We ﬁnd that biotechnology start-ups in Japan, on average, have experienced approximately ﬁve ﬁnancing rounds and have been ﬁnanced by approximately 14 VC ﬁrms
prior to the IPO. Moreover, Table 6 indicates the number of VC ﬁrms from the foundation date through the ﬁrst round of ﬁnancing (hereafter, “ﬁrst-round VC ﬁrms”),
since the eﬀects of syndication on the IPO values diﬀer between the ﬁrst and laterrounds of ﬁnancing. As shown in Table 6, biotechnology start-ups in Japan, on average, have been ﬁnanced by approximately three ﬁrst-round VC ﬁrms. Additionally,
Table 7 presents the market value and ﬁnancing of equity for IPO ﬁrms, according to
the number of ﬁnancing rounds and ﬁrst-round VC ﬁrms, respectively. Surprisingly,
the mean and median of the IPO values are higher for biotechnology start-ups withfewer ﬁnancing rounds. Likewise, they are higher for those with fewer ﬁrst-round
VC ﬁrms. These ﬁndings indicate that the IPO values may actually decrease withthe frequency of these investment methods, in contrast to previous arguments instudies by Lerner (1994a) and Gompers (1995). We will further investigate whether
these methods decrease the IPO values using the regression analysis.
4.3.

Variables

In this section, we explain the variables (covariates) used in the estimation regressions for the IPO duration and the IPO value. First, we discuss the determinantsof the IPO duration, which is observable for all ﬁrms in the data set. We examine whether initial involvement aﬀects the IPO duration of biotechnology start-ups.
As previously mentioned, it is hypothesized that biotechnology start-ups initially21
According to the JVR database, a capital increase through a third-party allocation is deﬁned
as a ﬁnancing round. Note that a capital increase through the allocation of VC ﬁrms and othercorporations is counted, whereas a capital increase only through the allocation of individuals andsole proprietorships is not counted as a ﬁnancing round. In addition, multiple capital increases
within three months are regarded as one ﬁnancing round.

18

backed by VC ﬁrms are more likely to go public within a shorter period. We use
a dummy variable for the initial ﬁnancing of VC ﬁrms (V C ST ) to represent theinitial involvement.22
A dummy variable for university origin (U N IV ) is also included in the estimation regression. As is well-known, scientiﬁc knowledge is the most important assetof biotechnology start-ups and, as shown in Table 4, approximately 39% of biotechnology start-ups in the data set originate from universities. We examine whether
biotechnology start-ups originating from universities are more likely to go public
within a shorter period.
Additionally, a dummy variable for spin-oﬀs (SP IN OF F ) is used to measure
whether the ﬁrm is a spin-oﬀ and examine the eﬀects of a parent company on thelikelihood of an IPO.23 Using this variable, we examine whether the IPO of biotechnology start-ups depends on initial involvement. These variables are obtained fromthe JVR database.
Moreover, the likelihood of an IPO may depend on market conditions, such as“hot issue” markets, when shareholders, including VC ﬁrms, expect higher capitalgains. The literature on ﬁnance has argued that the IPO market exhibits dramatic
swings in issuance that are often referred to as hot and cold markets (e.g., Ibbotson
and Jaﬀe, 1975; Ritter, 1984; Helwege and Liang, 2004). To measure market conditions, we use a variable for the JASDAQ index (JIN DEX), which is a market
capitalization-weighted index provided by the TSE that is based on all domestic

22

How the timing of the ﬁnancing of VC ﬁrms aﬀects the IPO duration would provide morecomprehensive evidence on the role of VC ﬁrms. However, we could not obtain data from the JVR
database on each individual ﬁnancing of VC ﬁrms for IPO ﬁrms and non-IPO ﬁrms, except for the
initial ﬁnancing.
23
In the JVR database, Takara Bio was not regarded as a spin-oﬀ. However, since this ﬁrm wasfounded when Takara Shuzo became Takara Holdings, which is the major shareholder of Takara Bio,
we regarded this ﬁrm as a spin-oﬀ. Meanwhile, spin-oﬀs sometimes discriminated from spin-outs,
which are not capitalized by their parent companies. As we did not completely distinguish between
them and the sample size was not suﬃciently large, we included spin-outs in the deﬁnition of thevariable.

19

common stocks listed on JASDAQ.24 JASDAQ is one of the major emerging markets in Japan and indeed, as shown in Figure 2, some biotechnology start-ups arelisted on JASDAQ.25 The values of this variable diﬀer across ﬁrms, according to themonth and year when the ﬁrms were founded. While this variable is time variant,the others are time invariant in the estimation regression of IPO duration.
Furthermore, as shown in Table 1, the ratio of IPO ﬁrms to total ﬁrms may diﬀer
according to the foundation year. Therefore, the cohort dummies for the foundation
year (C95 99 and C00 04) are included in the estimation regression.26 Finally, theindustry dummies (DRU G and HEALT H) are included in the estimation regression.
Next, we discuss the determinants of the IPO values, which are observable only
for the IPO ﬁrms in the data set. We examine whether investment methods signiﬁcantly aﬀect the IPO value of biotechnology start-ups. As Gompers (1995) stated,
the number of ﬁnancing rounds, in addition to the size of each investment and total
ﬁnancing provided, is an important measure of the staged investment structure of
VC ﬁrms. In this paper, we use a proxy for staged ﬁnancing, which is measured by
the number of ﬁnancing rounds (N ROU N D). Data on the number of ﬁnancing
rounds are obtained from the JVR database.
In addition to staged ﬁnancing, we capture syndication as an investment method.
24

The JASDAQ index was calculated as 100 on December 28, 1991. This index was 55.25 at theend of January 1995 and 104.95 at the end of December 2014. According to the TSE, the numberof constituents was 841 at the end of December 2014. Although the TSE provides other indices for
emerging markets, such as the J-stock index, only the JASDAQ index was obtainable during theperiod 1995–2014.
25
Lerner (1994b) constructed a biotechnology equity index using publicly traded biotechnology
ﬁrms. Among publicly traded biotechnology ﬁrms in Japan, three ﬁrms (Medical and Biological
Laboratories, Kainos Laboratories, and Precision System Science) were founded before January
1995. Although we could construct the index using these ﬁrms, this index did not cover all of theobservation period from January 1995 to December 2014 because the earliest of the three ﬁrms
(Kainos Laboratories) went public in December 1995. Instead of this index, therefore, we used the
JASDAQ index in this paper.
26
Although we may be able to deﬁne the cohort dummy for ﬁrms founded during the period
2005–2009 (the reference category is the period 2010–2014), as shown in Table 1, none of the ﬁrms
founded during the period 2010–2014 went public. Therefore, we treated the cohort dummy forﬁrms founded during the period 2005–2014 as the reference category.

20

Although venture capitalists often invest in a ﬁrm through multiple funds and ﬁnancing rounds, it is not easy to measure the degree of syndication. Meanwhile, as
discussed, since the eﬀects of ﬁrst-round syndication may diﬀer from those of laterround syndication, we measure the ﬁrst round of ﬁnancing separate from the laterrounds of ﬁnancing. In this paper, we use the variable for syndication in the ﬁrst
round of ﬁnancing based on the number of ﬁrst-round VC ﬁrms (N V CF ).27 The
use of this variable may mitigate causality issues caused by the fact that VC ﬁrms
have an incentive to participate in investments in pre-IPO ﬁrms to better their reputations. Additionally, we deﬁne the variable for syndication in the later rounds ofﬁnancing by the number of later-round VC ﬁrms (N V CL). This variable is used toinvestigate the eﬀects of later-round syndication, compared with those of ﬁrst-roundsyndication. Data on the number of VC ﬁrms are obtained from the JVR database.
Moreover, the IPO duration is also included in the estimation regression to identify whether this variable has a signiﬁcant impact on the IPO value. We deﬁne thevariable for the IPO duration (IP O DU R) as the logarithm of the months from thefoundation date to the IPO date. Furthermore, we use the variable for the JASDAQ
index (JIN DEX) to control for market conditions in the estimation egression of
the IPO value. Note that this variable is measured at the time of the ﬁrm’s IPO in
the estimation regression of the IPO value, while it is measured as time variant in
the estimation regression of the IPO duration.
Table 8 summarizes the deﬁnitions of the variables and Table 9 shows the summary statistics of the variables used in our analysis.

27

More precisely, we deﬁned this variable as the logarithm of the number of VC ﬁrms plus one
because only a few ﬁrms were not backed by VC ﬁrms through the ﬁrst round of ﬁnancing.

21

5.

Estimation results

5.1.

Results for the IPO duration

In Table 10, we present the estimation results for the IPO duration using thecompeting-risks regression. While 33 ﬁrms among 213 ﬁrms in the data set haveexperienced an IPO during the observation period, 36 ﬁrms have exited the market
before going public, mainly because of liquidation, and these cases are regarded ascompeting risks in this paper. When considering exits other than IPOs as competingrisks, we estimate the determinants of the IPO duration using the competing risks
regression. Table 10 provides both the estimated coeﬃcients and sub-hazard ratios.
While the variables for initial VC ﬁnancing (V C ST ), university origin (U N IV ),spin-oﬀ (SP IN OF F ), market conditions (JIN DEX), cohort dummies (C95 99
and C00 04), and industry dummies (DRU G and HEALT H) are used in column(i), we omit the industry dummies in column (ii) because they are insigniﬁcant.28
As shown in Table 10, the coeﬃcients of V C ST are positive at the 1% significance level and the sub-hazard ratio for initially VC-backed start-ups is approximately three times higher than that for other counterparts. The results reveal thatbiotechnology start-ups initially backed by VC ﬁrms are more likely to go public
within a shorter period, which is consistent with Lee and Lee (2008). Although
information asymmetries are severe when biotechnology start-ups start their businesses, some VC ﬁrms commit to start-up ﬁnancing in the biotechnology industryof Japan. In general, venture capitalists are required to not only screen and judge
viable businesses but also recoup their investments in the ﬁrms. The ﬁndings suggestthat VC ﬁrms that have committed to start-up ﬁnancing are more likely to induce
the IPO of biotechnology start-ups within a shorter period.
The coeﬃcients of U N IV are also positive at the 1% signiﬁcance level and the28

We also estimated the determinants of exits using the standard proportional hazards modeland the competing risks regression when considering IPOs as competing risks. However, we did notﬁnd any signiﬁcant results for these variables.

22sub-hazard ratio for university-origin start-ups is approximately six times higher
than that for other counterparts. We ﬁnd that the likelihood of an IPO for universityorigin start-ups diﬀers from that of other counterparts in the biotechnology industryof Japan. The results reveal that biotechnology start-ups originating from universities are more likely to go public within a shorter period. The ﬁndings suggest that
university-origin start-ups have more incentive to access equity markets quickly,
presumably to sustain ﬁnancing for their R&D activities. This may also imply that
universities tend to select and commercialize technologies that they expect can begiven a highly positive evaluation in equity markets.
In addition, the coeﬃcients of SP IN OF F are positive at the 5% signiﬁcancelevel. We ﬁnd that the likelihood of an IPO for spin-oﬀ start-ups diﬀers from that ofother counterparts in the biotechnology industry. The results reveal that spin-oﬀs
in the biotechnology industry are more likely to go public within a shorter period.
These ﬁndings indicate that the IPO of biotechnology start-ups depends on initial
involvement.
Moreover, the coeﬃcients of JIN DEX are insigniﬁcant, indicating that the IPO
duration is not signiﬁcantly aﬀected by market conditions. The results suggest thatthe timing of IPOs does not depend on market conditions. Our ﬁndings are inconsistent with Lerner (1994b) who found that a higher level of the equity index
increases the probability of an IPO. For biotechnology start-ups, ﬁnancing is often
critical for R&D activities. At the same time, many biotechnology start-ups havenegative proﬁts; therefore, these ﬁrms cannot rely on internal ﬁnancing for R&D
activities. Even if a ﬁrm predicts that the market value of equity will be evaluatedlower, the ﬁrm may be forced to access capital markets for R&D. Additionally, VC
ﬁrms have an incentive to recoup their investments sooner, unless they are cash-rich.
The ﬁndings suggest that biotechnology start-ups cannot aﬀord to wait for a higher
market value to continue their R&D activities.
Furthermore, the coeﬃcients of C95 99 are positive at the 1% signiﬁcance level,23

while those of C00 04 are insigniﬁcant. The results indicate that biotechnology
start-ups founded in the late 1990s are more likely to go public within a shorter period. In the early periods of the rise in emerging markets, the IPO of biotechnology
start-ups may be readily acceptable due to the policies promoting start-ups fromuniversities.
5.2.

Results for the IPO value

In Table 11, we present the estimation results for the IPO value, which is deﬁned
as the logarithm of the market value of equity (M V ), using the Heckman selection
model.29 While the variables for initial VC ﬁnancing (V C ST ), university origin(U N IV ), spin-oﬀ (SP IN OF F ), and cohort dummies (C95 99 and C00 04) areused for the selection equation, the variables for staged ﬁnancing (N ROU N D) andﬁrst-round syndication (N V CF ), in addition to market conditions (JIN DEX), areused to investigate whether investment methods aﬀect the IPO value. For comparison, the variable for later-round syndication (N V CL) is used instead of N V CF .
Moreover, the variable for the IPO duration (IP O DU R) is used to investigate
whether the IPO value depends on the IPO duration. First, to identify the eﬀects
of initial VC ﬁnancing on the IPO value, we use V C ST in column (i). Because
N ROU N D, N V CF , N V CL, and IP O DU R are correlated with one another,
we use each of these variables in columns (ii) to (v), respectively.30 In Table 12,
we present the estimation results for the relative IPO value, which is deﬁned as theratio of the IPO value to total equity invested (R M V ).
As shown in Tables 11 and 12, the coeﬃcients of V C ST are positive but insigniﬁcant. We ﬁnd little evidence that the IPO value of biotechnology start-ups
depend on the initial involvement of VC ﬁrms. While biotechnology start-ups ini29
We also used an ordinary least squares method and the results were similar to those using the
Heckman selection model. Therefore, we report only the results using the Heckman selection model.
30
For instance, the correlation coeﬃcients between N ROU N D and N V CL, between
N ROU N D and IP O DU R, and between N V CL and IP O DU R were 0.684, 0.700, and 0.476,
respectively.

24tially backed by VC ﬁrms are more likely to go public within a shorter period, they
are not highly evaluated in the market.
With respect to staged ﬁnancing, the coeﬃcients of N ROU N D are negativeand signiﬁcant in Tables 11 and 12. The results reveal that the number of ﬁnancing
rounds has a negative impact not only on the IPO value but also on the relative IPO
value. We ﬁnd little evidence that the returns to more staged ﬁnancing are higher
than those to less staged ﬁnancing, which is inconsistent with Gompers (1995). The
ﬁndings suggest that staged capital infusion does not create any additional value.
In contrast, there is the possibility that staged capital infusion induces a negative
signal about the value of a project.
With respect to syndication, the coeﬃcients of N V CF are insigniﬁcant in Table
11, while they are negative in Table 12. We do not ﬁnd that the number of VC ﬁrms
has a positive eﬀect on the IPO value or the relative IPO value. This indicates thatsyndication does not increase the market value of equity, even though it induces alarge amount of capital. We ﬁnd little evidence that the returns of more syndicatedinvestments are higher than those of less syndicated investments, which is inconsistent with Lerner (1994a). In contrast, the coeﬃcients of N V CL are negative andsigniﬁcant in Tables 11 and 12. When syndication is measured by the number of VC
ﬁrms in the later rounds of ﬁnancing, we ﬁnd a negative eﬀect of syndication on the
IPO value. The results indicate that syndication in the later rounds of ﬁnancing,rather than in the ﬁrst round of ﬁnancing, has a more negative impact on the IPO
value; thus suggesting that as Lerner emphasized, the eﬀects of syndication diﬀer
between the ﬁrst and later rounds of ﬁnancing. Several studies have found imitativeand herd behavior for Japanese ﬁrms and banks (e.g., Lieberman and Asaba, 2006;
Uchida and Nakagawa, 2007). In the later rounds of ﬁnancing for pre-IPO ﬁrms, VC
ﬁrms have more incentive to participate in investments to better their reputations.
As a result, they simply herd together. Given that syndication in the later-rounds
is due to herd behavior, such syndication through staged ﬁnancing does not provide

25opportunities to improve ﬁrm values, and this may rather impede the enhancementof market values at the IPO.
In column (v) of Tables 11 and 12, the coeﬃcients of IP O DU R are negative andsigniﬁcant, which indicates that the IPO duration has a negative eﬀect on the IPO
value. The results show that IPOs with a shorter period are highly evaluated in themarket among biotechnology start-ups. While Lee and Lee (2008) found that there
is no special relationship between IPO time and IPO value in the stock market, we
ﬁnd a negative relationship between them. Our ﬁndings suggest that a delayed IPO
does not guarantee a higher value, which implies that start-ups in the biotechnology
industry should go public quickly. As the period in which new technologies canmake large proﬁts is restricted because of the patent protection period, IPOs witha longer period may not be highly evaluated in the market.
Furthermore, the coeﬃcients of JIN DEX are positive in Tables 11 and 12, although JIN DEX does not have a suﬃciently signiﬁcant eﬀect on the relative IPO
value in Table 12. We ﬁnd that the market value of equity tends to depend on market conditions at the IPO. The results indicate that the stock market boom leads toa higher market value of equity in the biotechnology industry of Japan.31 As shownin Table 10, while the timing of IPOs for biotechnology start-ups does not dependon market conditions, the market value of equity at the IPO tends to depend on
market conditions.

6.

Conclusions

This paper explored the IPO and ﬁnancing of biotechnology start-ups in Japan.
Using a unique data set, we found that biotechnology start-ups initially backed by
VC ﬁrms and those originating from universities are more likely to go public within ashorter period. We also examined whether the two investment methods used by VC
31

As a typical case, the stock prices of biotechnology ﬁrms rose sharply after the announcementof the 2012 Nobel Prize in Physiology or Medicine by John B. Gurdon and Shinya Yamanaka.

26

ﬁrms aﬀect the market value of equity at the IPO. The results revealed that staged
ﬁnancing and syndication do not create a higher value of biotechnology start-ups
at the IPO. Furthermore, we provided evidence that the timing of IPOs does notdepend on market conditions in the biotechnology industry, whereas the market
value of equity tends to depend on market conditions.
This paper makes several contributions to the literature. The results indicatethat the return on investment for biotechnology start-ups in Japan is approximately
seven times greater, on average, than the invested amount when the start-ups issue
an IPO. Moreover, our ﬁndings suggest that biotechnology start-ups with capitalraised by staged ﬁnancing are negatively evaluated in the market and syndication
does not result in higher values, indicating that the investment methods do notcreate a higher value of biotechnology start-ups at the IPO. Furthermore, we employ
an analytical method to examine the IPO duration and estimate the determinantsof the IPO duration, while taking into account competing risks alternative to the
IPO. In addition, we propose that the relative IPO value, instead of simply using
the market value of equity, is a more suitable proxy to evaluate the IPO value andprovide more reliable results for the determinants of the IPO values.
This paper also includes several implications. Biotechnology start-ups—speciﬁcally, initially VC-backed ones—are more likely to go public within a shorter period,
regardless of market conditions. This is partly because the access to equity markets
through an IPO becomes imperative for biotechnology start-ups to secure ﬁnancing
for their R&D activities. At the same time, this indicates that VC ﬁrms promote
the ﬁrms’ IPOs to recoup their investments sooner. However, we provide empiricalevidence on the negative impact of investment methods on the market values at the
IPO in the biotechnology industry of Japan. Even though venture capitalists can
reduce their investment risks through various investment methods, such methods
can actually constrain the eﬃcient investment in high-tech start-ups. Whereas VC
ﬁrms are often expected to provide hands-on management support, they may give27

priority to recovering their investments rather than adding value to biotechnology
start-ups. In fact, some VC ﬁrms, instead of individual investors, provide the initial
capital for the R&D activities of biotechnology start-ups in the early stages in Japan.
In this respect, complementary ﬁnancial support systems for R&D activities are
required to prevent biotechnology start-ups from going public under unfavorable
market conditions.32 Meanwhile, as already discussed, Japan has the characteristics
of a bank-centered capital market. VC ﬁrms in Japan may have less incentive to takelarge risks, thereby resulting in an increase in the number of VC ﬁrms that imitate
investment behavior.33 In this respect, it is hoped that the risk capital of VC ﬁrms
will have better success in its ability to add value to biotechnology start-ups.

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31

Table 1. Distribution of biotechnology start-ups: foundation year
Foundation year
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
Total (over time)

IPO (A)
1
1
1
1
5
2
5
3
5
4
3
1
0
1
0
0
0
0
0
0
33

Non-IPO (B)
2
0
1
2
8
17
16
17
20
22
12
19
10
2
4
8
8
4
6
2
180

Total (A + B)
3
1
2
3
13
19
21
20
25
26
15
20
10
3
4
8
8
4
6
2
213

Ratio (A/(A + B))
0.333
1.000
0.500
0.333
0.385
0.105
0.238
0.150
0.200
0.154
0.200
0.050
0.000
0.333
0.000
0.000
0.000
0.000
0.000
0.000
0.155

Notes: “IPO” and “Non-IPO” represent biotechnology start-ups that have experienced or
not experienced an IPO by December 2014, respectively.

32

Table 2. Summary statistics of IPO durationClass
IPO duration(Foundation year)
1995–1999
2000–2004
2005–2009
All

Mean

S.D.

25%

Median

75%

N

88.1
85.9
74.6
84.8

35.9
41.4
19.1
36.8

59.0
43.0
79.0
57.0

96.0
104.0
82.0
88.0

106.0
124.0
83.0
116.0

9
19
5
33

Notes: “IPO duration” represents the number of months from the foundation date to the
IPO date. S.D. indicates standard deviation. N indicates the number of ﬁrms.

Table 3. Distribution of biotechnology start-ups: IPO/Non-IPO and initially
VC-backed
IPO/Non-IPO Initially VC-backed (A)IPO (C)
7
Non-IPO (D)10Total (C + D)
17
χ2 = 9.308 (p < 0.01)

Others (B)
26
170
196

Total (A + B)
33
180
213

Notes: “Initially VC-backed” represents biotechnology start-ups that raised equity from VC
ﬁrms when they were founded. “IPO” and “Non-IPO” represent biotechnology start-ups
that have experienced or not experienced an IPO by December 2014, respectively.

33

Table 4. Distribution of biotechnology start-ups: IPO/Non-IPO and university
origin
IPO/Non-IPO University-origin (A)IPO (C)23
Non-IPO (D)60
Total (C + D)83
χ2 = 15.505 (p < 0.01)

Others (B)
10
120
130

Total (A + B)
33
180
213

Notes: “Initially VC-backed” represents biotechnology start-ups that raised equity from VC
ﬁrms when they were founded. “University-origin” represents biotechnology start-ups thatoriginated from universities. “IPO” and “Non-IPO” represent biotechnology start-ups thathave experienced or not experienced an IPO by December 2014, respectively.

Table 5. Market value and ﬁnancing of equity for IPO ﬁrms
Variable
IPO value (A)Equity ﬁnancing (B)IPO capital increase (C)A/B
A/(B + C)

Mean28, 6213, 601
2, 359
57.83
7.15

S.D.
38, 029
5, 003
1, 873182.6610.33

25%
8, 032
837
819
1.77
1.28

Median13, 978
1, 751
2, 100
6.16
3.05

75%
23, 660
4, 6872, 942
23.03
7.08

N
32
32
32
32
32

Notes: “IPO value” represents the market value of equity (million yen), based on the ﬁrstday closing price. “Equity ﬁnancing” represents invested equity deﬁned as the sum of paid-in
capital, additional paid-in capital, and capital reduction (million yen) prior to the IPO. “IPO
capital increase” represents the capital increase (million yen) at the IPO.

34

Table 6. Number of ﬁnancing rounds and VC ﬁrms
Variable
Number of ﬁnancing rounds
Number of VC ﬁrms
Number of ﬁrst-round VC ﬁrms

Mean
4.88
14.31
3.31

S.D.
2.61
8.44
3.59

25%
3.00
9.00
1.00

Median
5.00
12.50
2.00

75%
6.50
19.00
4.50

N
32
32
32

Notes: S.D. indicates standard deviation. N indicates the number of ﬁrms.

Table 7. Market value and ﬁnancing of equity for IPO ﬁrms by the numbers ofrounds and ﬁrst-round VC ﬁrms.
Variable / Type Mean
S.D.
25%
Median
IPO value(Number of ﬁnancing rounds)
1–3 rounds
48, 80 44, 485 14, 644 32, 804
4–7 rounds
20, 038 33, 608
7, 455 10, 467
8+ rounds
11, 036
8, 7655, 817
8, 794(Number of ﬁrst-round VC ﬁrms)
0–3 VC ﬁrms 35, 667 45, 569
7, 140 16, 026
4–7 VC ﬁrms 10, 296
4, 661
7, 34910, 418+ VC ﬁrms
30, 039 22, 651 13, 545 26, 220
IPO value/(Equity ﬁnancing + IPO capital increase)(Number of ﬁnancing rounds)
1–3 rounds
10.31
9.71
1.76
7.16
4–7 rounds
6.36
11.51
1.74
2.51
8+ rounds
1.87
1.87
0.82
1.06
(Number of ﬁrst-round VC ﬁrms)
0–3 VC ﬁrms
9.47
12.46
1.28
4.29
4–7 VC ﬁrms
3.52
2.49
1.83
2.26
8+ VC ﬁrms
2.85
2.98
1.17
1.47

75%

N

78, 877
17, 40816, 25511
17
4

41, 152
12, 965
46, 532

20
8
4

17.94
6.05
2.93

11
17
6

13.17
6.25
4.53

20
8
4

Notes: “IPO value” represents the market value of equity (million yen), based on the ﬁrstday closing price. “Equity ﬁnancing” represents total equity invested, deﬁned as the sum ofpaid-in capital, additional paid-in capital, and capital reduction (million yen) prior to the
IPO. “IPO capital increase” represents the capital increase (million yen) at the IPO.

35

Table 8. Variable deﬁnitions
Variable(All ﬁrms)
Initial VC ﬁnancing

SymbolV C ST

University origin

U N IV

Spin-oﬀ
Market conditions

SP IN OF F
JIN DEX

Cohort dummies

C95 99
C00 04

Industry dummies

I DRU GI HEALT H(Only for IPO ﬁrms)
IPO valueMV

Relative IPO value

R MV

Staged ﬁnancing

N ROU N D

Syndication

N V CFN V CLIPO duration

IP O DU R

Deﬁnition
Dummy variable for the ﬁrm ﬁnanced by a VC
ﬁrm when the ﬁrm was founded.
Dummy variable for the ﬁrm related to a university when the ﬁrm started a business fulﬁlling any of the following conditions: (1) the ﬁrm
was founded, based on technologies originatingfrom a university, (2) the ﬁrm conducted joint
research with a university within one year, (3)the ﬁrm was founded with support of a university, (4) the ﬁrm or a trusted organization itself
proclaimed university origin.
Dummy variables for the subsidiary ﬁrm.
JASDAQ index based on the month-end closing
price, normalized by its value in January 1991(= 100).
Dummy variable for the ﬁrm founded during theperiod 1995–1999.
Dummy variable for the ﬁrm founded during theperiod 2000–2004.
Dummy variable for the ﬁrm in drug discovery.
Dummy variable for the ﬁrm in medical andhealth care, except for drug discovery.
Logarithm of the market value of equity (millionyen), based on the ﬁrst-day closing price.
Logarithm of the ratio of the market value of equity, based on the ﬁrst-day closing price, divided
by the sum of paid-in capital, additional paid-in
capital, and capital reduction prior to the IPO
plus capital increase at the IPO.
Logarithm of the number of ﬁnancing rounds by
VC ﬁrms and corporations prior to the IPO.
Logarithm of the number of VC ﬁrms investingin the ﬁrm from the foundation date through theﬁrst round of ﬁnancing plus one.
Logarithm of the number of VC ﬁrms investingin the ﬁrm after the ﬁrst round of ﬁnancing prior
to the IPO plus one.
Logarithm of the number of months from thefoundation date to the IPO date.

Note: All the dummy variables take the value of one if the stated condition holds, and zerootherwise.

36

Table 9. Summary statistics of variables
Variable(All ﬁrms)
V C STU N IVSP IN OF F
JIN DEXC95 99
C00 04I DRU GI HEALT H(IPO ﬁrms)
MV
R MV
V C STN ROU N D
N V CFN V CLIP O DU R
JIN DEX

Mean

S.D.

25%

Median

75%

N

0.080
0.390
0.066
72.063
0.103
0.521
0.385
0.183

—–
—–
—–
23.807
—–
—–
—–
—–

—–
—–
—–
50.490
—–
—–
—–
—–

—–
—–
—–
65.020
—–
—–
—–
—–

—–
—–
—–
95.490
—–
—–
—–
—–

213
213
213
24, 927
213
213
213
213

9.654
1.282
0.219
1.428
1.178
2.102
4.309
68.713

1.065
1.145
—–
0.604
0.757
1.016
0.542
20.298

8.989
0.242
—–
1.099
0.693
1.386
4.034
50.825

9.544
1.114
—–
1.609
1.099
2.350
4.448
66.77510.184
1.957
—–
1.869
1.701
2.917
4.758
86.830

32
32
32
32
32
32
32
32

Notes: S.D. indicates standard deviation. N indicates the number of ﬁrms. For all ﬁrms,
JIN DEX is time variant and the others are time invariant.

37

Table 10. Estimation results for the IPO duration

VariableV C STi
U N IViSP IN OF FiJIN DEXit
C95 99i
C00 04i
I DRU GiI HEALT Hi
Number of ﬁrms
Number of IPOs
Number of competing events
Log pseudo-likelihood
Wald χ2

(i)
Coef.
SHR
∗∗∗
1.164
3.203∗∗∗(0.417)(1.331)1.770∗∗∗ 5.869∗∗∗(0.448)(2.629)1.936∗∗
6.928∗∗(0.756)(5.240)−0.0040.996(0.006)(0.006)
1.841∗∗∗ 6.303∗∗∗(0.610)(3.844)0.504
1.655(0.528)(0.874)0.293
1.340(0.407)(0.546)−0.1170.889(0.555)(0.494)
213
33
36
−149
56.7∗∗∗

(ii)
Coef.
SHR
∗∗∗
1.117
3.056∗∗∗(0.388)(1.185)1.803∗∗∗ 6.067∗∗∗(0.432)(2.623)
1.928∗∗
6.878∗∗(0.755)(5.195)−0.0050.995(0.006)(0.006)1.720∗∗∗ 5.582∗∗∗(0.553)(3.087)0.506
1.659(0.521)(0.864)

213
33
36
−150
47.0∗∗∗

Note: Figures in parentheses are standard errors adjusted for 213 ﬁrms. “Coef.” represents
estimated coeﬃcients and “SHR” represents the sub-hazard ratio. ***, **, and * indicate
the 1%, 5%, and 10% signiﬁcance levels, respectively.

38

Table 11. Estimation results for the IPO value (M V )VariableV C STi

(i)
Coef.
0.604
(0.455)N ROU N Di

(ii)
Coef.

(iii)
Coef.

(iv)
Coef.

−0.741∗∗∗(0.256)N V CFi

0.117(0.225)N V CLi−0.433∗∗∗(0.147)0.025∗∗∗(0.009)7.795∗∗∗(0.984)0.023∗∗∗(0.008)9.131∗∗∗(0.822)0.022∗∗∗(0.008)8.376∗∗∗(0.833)0.020∗∗∗(0.008)9.416∗∗∗(0.816)−0.828∗∗∗(0.281)0.026∗∗∗(0.008)11.483∗∗∗(1.267)0.927∗∗(0.363)1.010∗∗∗(0.260)1.117∗∗(0.460)1.546∗∗∗(0.409)0.698∗∗(0.301)−2.344∗∗∗(0.330)
0.020
0.899
0.018
212
32
−112
8.33∗∗

0.931∗∗(0.386)1.010∗∗∗(0.261)
1.117∗∗(0.460)1.541∗∗∗(0.416)
0.696∗∗(0.304)−2.343∗∗∗(0.333)−0.0160.820−0.01321232−109
15.9∗∗∗

0.989∗∗∗(0.355)1.015∗∗∗(0.258)1.128∗∗(0.449)1.466∗∗∗(0.425)0.670∗∗(0.297)−2.325∗∗∗(0.329)−0.3200.951−0.304212
32−113
6.96∗∗

0.981∗∗∗(0.365)0.996∗∗∗(0.201)
1.098∗∗(0.458)1.512∗∗∗(0.417)0.702∗∗(0.299)−2.339∗∗∗(0.330)−0.2120.830−0.176212
32−109
17.0∗∗∗

0.939∗∗(0.371)1.007∗∗∗(0.261)1.111∗∗(0.460)1.535∗∗∗(0.413)0.690∗∗(0.303)−2.338∗∗∗(0.333)−0.0570.819−0.047212
32−109
16.7∗∗∗IP O DU Ri
JIN DEXi
Constant term
(Selection)
V C STi
U N IViSP IN OF Fi
C95 99i
C00 04i
Constant termρσλNumber of ﬁrms
Number of IPOs
Log likelihood
Wald χ2(v)
Coef.

Note: Figures in parentheses are standard errors. “Coef.” represents estimated coeﬃcients.
***, **, and * indicate the 1%, 5%, and 10% signiﬁcance levels, respectively.

39

Table 12. Estimation results for the relative IPO value (R M V )VariableV C STi

(i)
Coef.
0.090
(0.539)N ROU N Di

(ii)
Coef.

(iii)
Coef.

(iv)
Coef.

−0.681∗∗(0.274)−0.184(0.247)N V CFiN V CLi−0.542∗∗∗(0.153)0.015(0.010)0.988∗∗(0.897)0.015(0.009)1.931∗(1.061)

0.015(0.009)1.180(0.941)

0.011(0.009)2.438∗∗(1.026)−0.667∗∗(0.325)0.018∗∗(0.009)3.459∗∗(1.454)

0.948∗∗∗(0.358)1.088∗∗∗(0.252)0.963∗∗(0.499)1.406∗∗∗(0.446)
0.634∗∗(0.294)−2.312∗∗∗(0.330)−0.5631.125−0.633
212
32
−115
2.43

1.032∗∗∗(0.344)
1.048∗∗∗(0.251)0.835(0.545)1.392∗∗∗(0.444)0.612∗∗(0.297)−2.272∗∗∗(0.338)−0.5551.018−0.565212
32−113
8.56∗∗

0.960∗∗∗(0.344)1.070∗∗∗(0.253)0.997∗∗(0.471)1.416∗∗∗(0.428)0.641∗∗(0.291)−2.313∗∗∗(0.327)−0.5361.103−0.591
212
32
−115
3.04

1.044∗∗∗(0.338)1.040∗∗∗(0.249)0.748(0.547)1.410∗∗∗(0.429)0.700∗∗(0.285)−2.318∗∗∗(0.328)−0.6440.992−0.639212
32−110
16.0∗∗

0.983∗∗∗(0.347)1.048∗∗∗(0.254)0.919∗(0.500)1.447∗∗∗(0.422)
0.633∗∗(0.295)−2.299∗∗∗(0.330)−0.4631.016−0.471212
32−114
7.00∗∗IP O DU Ri
JIN DEXi
Constant term
(Selection)
V C STi
U N IViSP IN OF Fi
C95 99i
C00 04i
Constant termρσλNumber of ﬁrms
Number of IPOs
Log likelihood
Wald χ2(v)
Coef.

Note: Figures in parentheses are standard errors. “Coef.” represents estimated coeﬃcients.
***, **, and * indicate the 1%, 5%, and 10% signiﬁcance levels, respectively.

40

Figure 1. Number of firms in the biotechnology industry of Japan
Source: Japan Biotechnology Association 2014-nen Bio Venture Tokei Doko Chosa Hokokusho(2014 Survey on Bio-Ventures)Figure 2. Number of IPOs in the biotechnology industry of Japan
Source: Disclosure Jitsumu Kenkyukai (ed.), Kabusihi Kokai Hakusho (White Paper on Initial
Public Offerings)
Note: JASDAQ includes NEO and JASDAQ Growth. Tokyo Pro indicates “Tokyo Pro Market”
and includes the former Tokyo AIM.