RETAINED WEALTH AND FAMILY FIRM IPO
Hung-bin Ding
Loyola College in Maryland
Kuntara Pukthuanthong-Le
San Diego State University
ABSTRACT
Most IPO firms are new and difficult to value. Investors can become informed by obtaining
information about the issuing companies. However, overcoming information asymmetry is
costly. Signaling is an effective approach for an issuer to communicate with its aftermarket
investors. We argue that the uniqueness of family firms have impact on how investors interpret
the signals. In this research, we investigated the effect of IPO signals in family firm IPOs. Our
sample includes 84 family IPO firms and 84 comparable non-family IPO firms. The family firms
in our sample have been constantly named as top 250 largest corporations in Taiwan over the
period of 1997-2004. The results of analysis suggest that family businesses are unique in the
relationship between IPO signals and underpricing. Practices of signaling such as the
appointment of non-family directors and partnering with prestigious underwriters significantly
reduce underpricing. In addition, family owners’ intent to retain large percentage of share in the
long run is an indication of original shareholders’ level of confidence in their own companies.
Such confidence helps reduce after market investors’ uncertainty and thus underpricing.
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INTRODUCTION
Do equity investors view family firms as a unique target of investment? One of the
central assumptions of family business research is that family-controlled or family-owned firms
systematically demonstrate distinctive behavioral patterns. Such uniqueness is largely viewed as
the results of business owners making efforts to balance the family interests and to maintain
sustainable business operations in the same time. A growing number of empirical studies have
identified many areas of such behavioral differences (e.g. Ram & Holliday, 1993; Tsui-Auch &
Lee, 2003; Craig & Dibrell, 2006).
Since family firms demonstrate distinctive behavioral patterns, shouldn’t they receive
unique treatment from investors? Consultants have long been working with their family business
clients to seek means to best preserve the value of stocks and assets of companies. The
discussions of shareholder rights are closely associated with the extensive studies on family
business succession (Davis & Harveston, 1998; Lee, Lim, & Lim, 2003; Chrisman, Chua, &
Sharma, 1998; Sharma & Rao, 2000; Sharma & Irving, 2005). Along the line of succession
research, changes in tax laws and other regulations also motivate researchers to look into the
impact of these changes on incumbent owners’ ability to transfer wealth and the control of
companies to the inheriting generations. Recently, the interests in the performance of family
firms in the capital market are on the rise. More family firm owners have come to realize that
going public is essential for long-term growth and to survive (Chemmanur, He, & Nandy, 2006;
Pagano, Panetta, & Zingales, 1998). In the United States, despite higher ROA before going
public, the equity prices of family firms tend to be lower than those of non-family firms
(Astrachan & McConaughy, 2001). Similar results were found in a study on the long-term stock
performance of family firms in Germany and Spain (Jaskiewicz, Gonzalez, Menendez, &
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Schiereck, 2005). Same article also reports that family involvement has positive contribution to
the equity price (Jaskiewicz et al., 2005). However, evidences from Standard & Poor’s 500
companies suggest that family firms perform better than non-family firms in the capital market
(Anderson & Reeb, 2003; Villalonga & Amit, 2006).
Despite the recent progresses, studies on long-term performance give us little information
about how investors view family firms when they make investment decisions. In addition,
strategic management researchers have suggested relationships between share price and a
number of factors. For example, the percentage of shares controlled by individual investors has
positive contribution to share price volatility (Hansen & Hill, 1991). A research on Japanese and
American public companies asserts that lay-off announcements significantly bring down stock
prices (Lee, 1997). Before the bust of Dot-Com, changing the name of a company to Dot-Com
significantly boasts the price of a name changer’s stock (Lee, 2001; Cooper, Dimitrov, & Rau,
2001). The results of a study on 181 multinational corporations (MNCs) uncover that the
performance indicators such as stock price reflect the confluence of multiple competitive
advantage-building activities including the emphasis on market orientation, entrepreneurship,
and innovativeness etc. (Hult & Ketchen Jr., 2001).
Observations on the extent of underpricing in family business IPO allow us to focus on
the investor effects on IPO by ruling out most of the contributing factors of long-term stock
performance. In the United States, IPO underpricing refers to the difference between the offer
price and the closing price on the IPO day. Since issuing shares are allocated mainly to the most
influential or institutional investors, the offer price reflects the information possessed by the most
informed investors. On the other hand, the closing price on the IPO day reflects private
information from small or retail investors, who rarely receive an allocation of issuing shares.
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This price difference is viewed a “money left on the table” since the original equity owners have
sold their shares to institutional or individual investors at a pre-market price, which is lower than
the first-day closing price. Overall, the first-day return phenomenon is explained by asymmetric
information between issuers and other two major stakeholders of IPO, underwriters and
investors. Issuers can close the gap of information asymmetry by working closely with
underwriters or by signaling to the market.
In this research, we focus on the impact of market signal on family firm IPO
performances. Since we are interested in the interactions between issuers and investors, we tested
our hypotheses in an auction IPO market to minimize underwriters’ effect in underpricing. This
study extends current literature in two ways. First, it highlights the extrinsic uniqueness of family
firms. Second, we reconceptualize the insider-outsider dichotomy in the corporate governance
literature by highlighting the importance of non-family board members in IPO performance. This
article is structured as follows. We will review the theories of IPO underpricing and present our
hypothesis development in the next two sections. The third section offers a description of data
collection and methodology. The results of our analysis are presented in the fourth section,
followed by discussion and conclusion.
IPO STAKEHOLDERS AND UNDERPRICING
The issuing company, underwriter, and investors are the three major stakeholders in an
equity offering deal. Underpricing occurs when investors after the issuance are willing to
purchase the issuers’ stock at a price higher than the offer price. The issuers would be able to
completely retain the wealth created from IPO if investors believe the offer price reflects the fair
value of the stocks. However, multinational surveys on initial returns of IPO suggest that the
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offer prices are usually set below the fair market price (Lounghran, Ritter, & Rydqvist, 1994;
Ljungqvist, 2006: 9-10).
Underwriter Effects in Bookbuilding and Auction IPO
The IPO stocks are priced and introduced to the market following two broadly defined
mechanisms. The first one is bookbuilding. This mechanism requires one or a coalition of
investment bankers to underwrite the offering. In addition to preparing paper works for
regulatory scrutiny, underwriters are responsible for allocating IPO shares to their favorite
institutional investors. Interactions between underwriters and institutional investors reduce the
risk of undersubscription for issuers (Sherman, 2005.) However, underwriters are also given
great discretion to set an offer price. The second IPO mechanism is auction. In an auction IPO,
the stocks are sold to bidders before being traded in the public market. An investment banker is
usually hired by the issuer to manage the offering process and to guarantee sufficient interests in
the IPO (Sherman, 2005). However, instead of allocating IPO shares to institutional investors,
underwriters of auction IPOs are responsible for selling equities to winning bidders in pre-market
auctions. The offer prices reflect the result of pre-market auctions.
There are extensive discussions and debates about the effects of underwriters in IPO
underpricing (see Ljungqvist, 2006 for a comprehensive review). The great discretion of
underwriters in bookbuilding motivates many researchers to investigate why underwriters
underprice their clients’ equities. One of the arguments is information asymmetry between
issuing companies and underwriters (Rock, 1986; Beatty & Ritter, 1986). An issuing company
may be too optimistic when presenting its operation data and financial outlook to its underwriter.
Of course underwriter will verify the accuracy of information provided by the issuing firm. The
more transparent the latter’s operation is, the more underwriter trusts the reports and assessments
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from the issuer. When information asymmetry is not a major concern, the underwriters are likely
to price the equity offering close to the expected market value. Nonetheless, underwriters will
not be able to fully trust the assessment and self-evaluation provided by their IPO clients if the
business operation and financial reporting of the latter are less transparent. The underwriter can
elect to ignore the problem with the quality of data provided by the issuing companies and
determine the offer prices accordingly. However, doing so will increase the underwriter’s risk to
overprice an IPO. Lowering the offer price allows underwriters to avoid potential overpricing.
Such information asymmetry motivates underwriters to price the equity below an optimal price
to avoid undersubscription. In other words, underwriters discount the offer price to offset risk
derived from business (Certo, Covin, Daily, & Dalton, 2001).
An IPO underwriter is also an agent to the issuing company. Agency problems occur
when an underwriter obtains economic gains by not maximizing its issuing company’s gains
from IPO. The agency problem arises because underwriters are investment banks. Besides public
offering deals, these banks usually offer different types of banking services. If selling a public
offering equity at a low price to selected clients helps retaining these major clients for the
investment bankers, underwriters may have strong incentive to introduce the IPO deal at a low
offer price (Ritter and Welch, 2002; Loughran and Ritter, 2002).
The balance of bargaining power between underwriters and issuing companies also
affects underpricing. Underwriters are prone to press the issuing companies to underprice the
equity to attract investors (Beatty & Ritter, 1986). Large underwriters usually price their IPO
equities lower than their smaller competitors (Beatty & Welch, 1996). Moderately underpriced
equities are found to generate more investors’ interests (Nanda & Yun, 1997). Because of large
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underwriters’ marketing power to reach investors, issuing companies may be willing to accept a
low offer price for more investor interests and more after-market trading (Ljungqvist, 2006).
Underwriters receive underwriting fees from equity offering firms for the service
provided in researching, valuing the deal and finding institutional investors to bid for the equity
offering. An underwriter also receives a commission or remaining equity from the sales of the
IPO equities. If the underwriters are forced to charge a low underwriting fee for their services,
underwriters are likely to intentionally price the IPO deal low to attract more buyers to bid for
the stocks. For example, Taiwan stock exchange adopted a hybrid approach of IPO sales. In the
Taiwanese market, underwriters are used to auction off the IPO equities. Underwriters are also
required by law to buy unsold equities from an IPO deal. In addition, the hyper competitive
underwriting market allows issuing companies to bargain a low underwriting fee against
underwriters. To recover from the cost of underwriting a deal, underwriters often use a low
introduction price to attract bidders and to lower the liability in case there is large quantity of
equity remaining unsold (Chen, Fok, & Wang, 2006).
In the United States, stringent rules of disclosure expose the underwriters to great legal
liabilities. A recent study estimates that about six percent of underwriters were sued for violating
disclosure rules from 1988 to 1995 (Lowry & Shu, 2002). In addition to financial damage,
lawsuits can have negative impact on an investment bankers’ reputation (Ljungqvist, 2006).
Intentionally setting the IPO offer price below the fair price is an insurance measure for
underwriters to avoid litigation (Tinic, 1988).
Although some theorists believe that auction mechanism reduces the impact of
underwriters and thus IPO underpricing (Sherman, 2005), Lounghran, Ritter, & Rydqvist’s
(1994) cross country survey indicates that underpricing exists in both auction and bookbuilding
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markets. To give a fair assessment of IPO equity, auction bidders need firm-specific information
such as business operation, major clients, competition, and management, etc. Information
production is not free. High information production would limit the number of potential bidders
and cause IPO undersubscription. If the cost of information production is low, the number of
potential bidders increases. Since the equity bidding is expected to be highly competitive,
potential investors may decide to withdraw from the bidding thus increases the variance of
auction participation (Sherman, 2005). The upshot of information production cost is that auction
mechanism can create even higher underpricing than bookbuilding (Sherman, 2005).
Investors and Underpricing
Most IPO firms are new and difficult to value. Unlike trading existing stocks in the
market, investors face a great uncertainty to determine the fair price of the stocks. Investors can
become informed by obtaining information about the issuing companies. The information
gathering efforts reduce the uncertainty of IPO valuation. However, overcoming information
asymmetry is costly. Informed investors would not buy the IPO stock in the aftermarket if the
difference between the fair price and offer price is not big enough to compensate the information
gathering cost. Underpricing thus offers needed compensation to attract informed investors
(Ritter, 1984; Beatty & Ritter, 1986). There is a positive correlation between the cost of
information and the extent of underpricing (Beatty & Ritter, 1986). On the other hand,
uninformed investors contribute to underpricing by buying the IPO stock at prices higher than
informed investors. Uninformed investors who pay below fair price will not be able to buy any
stock from the market. However, uninformed investors are likely to pay too much for IPO stocks
(Rock, 1986). Underpricing will exist even if most of the investors are well-informed about the
value of IPO stock.
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Recent behavioral finance literature highlighted many contributing factors of market
sentiment. For example, investors may develop overconfidence in their knowledge of investment
target (Odean, 1998). In addition, self-attribution bias leads investors to believe that unfavorable
outcome of investment is bad luck and attribute favorable outcome to their knowledge of market
(Daniel, Hirshleifer, & Subrahmanyam, 1998). Although underpricing caused by market
sentiment necessarily upset original shareholders of issuing companies, these shareholder are
able to regain their loss from selling their retained shares in the high price aftermarket (Derrien,
2005).
Despite the potential to make up the lost wealth in the aftermarket, the equity owners may
opt not to sell their shares to the aftermarket investors. This is particular salient in family
business IPOs when family owners intend to retain control of the firm long after IPO. In
addition, overpriced stocks in the early stage of IPO are likely to underperform in the long run
and thus increase the risk for shareholders (Ritter, 1991).
Underwriters and investors both have strong influence to the extent of IPO underpricing.
As underpricing transfers issuers’ wealth to pre-market institutional investors or auction winners,
issuers are motivated to reduce the cost of information gathering for underwriters and investors.
Issuers may neutralize the underwriter-driven underpricing by working closely with underwriters
to reduce the information asymmetry. However, bridging the gap of information asymmetry
between issuers and aftermarket investors is a great challenge. The number of aftermarket
investors is usually far greater than that of underwriters. Working closely with all investors is
simply not possible since the cost of communication will be very high. Additionally, it is not
aftermarket investors’ best interest to overload themselves with excessive information. Therefore
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sending positive signals to aftermarket become an important measure to close the information
gap between issuers and investors (Beatty & Ritter, 1986; Filatochev & Bishop, 2002).
INVESTORS AND FAMILY FIRM IPO
Signaling is particularly important to family business IPO deals. There have been
extensive studies on the behavioral difference between family and non-family firms (Brochaus,
1994; Litz, 1995; Zahra, Hayton & Salvato; 2004) and the implications of such uniqueness to
firm performances (Alvesson & Lindkvist, 1993; Ainsworth & Cox, 2003; Anderson & Reeb,
2003; Villalonga & Amit, 2006.)
The uniqueness of family firm behaviors is, by definition, a result of overlapping between
emotion-based human family and exchange-based business organization (Litz, 1995; Chrisman,
Chua, & Sharma, 1998). A recent study suggests that this overlapping enables the efficiency
enhancing practices such as commitment to long term objectives and human capital development
(Bertrand & Schoar, 2006). In addition, family ties provide a trust network when the business
environment lacks strong legal structure (Oxfeld, 1993; Rose, 2000; Burkart, Panunzi, &
Shleifer, 2003). However, family firms may be over- committed to family value (Bertrand &
Schoar, 2006). Strong family ties may become the culprit of nepotism (Barnett, 1960). Research
on family business governance has also pointed out an agency problem between family
shareholders and non-family shareholders in family firms (Morck & Yeung 2003). Such agency
problem arises when a family-controlled corporate board makes decisions in favor of family
shareholders’ interests. Investors may be able to learn if such agency problem is a concern from
the track record when considering buying a family business stock in the aftermarket. However,
with few exceptions of celebrity companies, there is very little track record information about the
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corporate governance quality of IPO stocks. As the appointment independent directors is viewed
as a signal of good governance practice in IPO (Certo et al., 2001), increasing the influence of
non-family directors on the board may reduces the uncertainty associated with investing family
IPO. Therefore:
Hypothesis 1
Giving non-family directors more seats on the corporate board reduces underpricing of a family
firm IPO.
For an IPO firm, the degree of IPO underpricing is likely to be associated with its level of
pre-IPO insider ownership. The higher the pre-IPO percentage of insider ownership, the higher
the cost imposed on insiders from the decline of firm value (Jensen and Meckling, 1976).
Entrepreneurs will suffer substantial economic losses if the firm’s future performance is poor. A
higher percentage of insider ownership signals to the market that the firm is of high quality. As
insiders are supposed to know the true value of company, their willingness to retain large amount
of shares after IPO indicates their confidence in the future prospect of the firm (Leland & Pyle,
1977; Downes & Heinkel 1982; Clarkson, Dontoh, Richardson, Sefcik, 1991; How & Low,
1994). In short, insiders’ retained stock post ante is an indication of original shareholders’ level
of confidence to their own companies. Such confidence helps reduces aftermarket investors’
uncertainty (Certo et al., 2001).
An extension of Leland and Pyle’s (1977) model is that family insiders may intentionally
send a signal of their firm’s quality by retaining a high level of pre-IPO ownership. Allen and
Faulhaber (1989), Grinblatt and Hwang (1989) and Welch (1989) model a separating equilibrium
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where high quality firms have high underpricing and pre-IPO insider ownership. They explain
that good quality firms are willing to underprice their IPOs because they expect to raise more
money after the IPO. In contrast, low-quality firms do not expect to access the capital markets
for further rounds of financing; therefore, they are not willing to underprice but rather take the
money from their IPO and “run”. An implication of this separating equilibrium is the positive
relation between underpricing and post-IPO market valuation. Moreover, underpricing is
positively related to the probability of issuing second equity offerings (SEOs) and the size of
SEOs. Based on a survey of insiders’ retained stock 1 year post-IPO, Habib and Ljungqvist
(2001) explain that the underpricing of IPO is high for IPO firm whose owners sell the fewer
shares at the IPO or retain their ownership after the IPO and thus are more tolerant of
underpricing. Taken together, we hypothesize that the expected large long-term insiders’ equity
stakes decrease underpricing.
Hypothesis 2
The expected long-term family ownership decreases underpricing.
Underwriters assist issuers to satisfy legal requirements of IPO by closely monitoring
issuers’ pre-IPO activities. The quality of their works in IPO preparation has significant impact
on their reputation. The need to uphold reputation motivates underwriters to work diligently
during the IPO process. However, some underwriters are more capable than others in identifying
the fair price of IPO stocks by, for example, uncovering hidden assets or other variable factors in
the issuer. These more capable investment bankers enjoy higher prestige than their peers in the
underwriting industry. Partnering with these high prestige underwriters sends a positive signal
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about the quality of the firm to the market (Beatty & Ritter, 1986). Since family firms are more
likely to have hidden variables than non-family firms due to the closed link between family life
and business operations, hiring a prestigious underwriter may have a stronger effect in reducing
family firm IPO uncertainty than in non-family IPOs.
Hypothesis 3
Using prestigious underwriters lower the underpricing of family and non-family firm IPOs, but
this effect is greater in family firms.
RESEARCH DESIGN AND VARIABLE DEFINITION
Empirical Models and Key Variables
We examine the association of underpricing with various family ownership and IPO
variables using the following regression model (time subscript omitted):
1. Family IPOs
Underpricing k =
B 0 +B 1 (% of outside directors) + B 2 (% of family ownership at IPO) + B 3 (%
of family ownership 3-yr post-IPO) + B 4 (potential successor dummy) +
B 5 (underwriter’s ranking) + B 6 + ( IPO volume) + B 7 (high-tech dummy) +
B 8 (log of proceed) + B 9 (firm age) + B 10 (bubble period dummy) + E
(1)
2. Non-family IPOs
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Underpricing k = A 0 + A 1 (underwriter’s ranking) + A 2 + ( IPO volume) + A 3 (high-tech
dummy) + A 4 (log of proceed) + A 5 (firm age) + A 6 (bubble period
dummy) + E
(2)
where Underpricingk is the extent of IPO underpricing for firm k, measured as the percentage
return from the offer price to the closing price on the fifteenth calendar day after the IPO.
Note that our definition of underpricing is consistent with existing international IPO
studies that generally measure IPO initial returns over a period of several weeks (e.g., Loughran,
Ritter, and Rydqvist., 1994; Ljungqvist, Jenkinson, and Wilhelm, 2003; Ritter, 2003). The
reason for the use of longer return windows is twofold. The price movements in the Taiwanese
market during the initial days of trading are restricted by exchange regulation, delaying the
emergence of an equilibrium price.1 Hsu and Hung (2005) report a daily price limit of +/-7% is
imposed on securities traded in Taiwan’s stock markets; therefore, a stock price could continue
to hit the limit several days after the IPO date. Lin, Lee, and Liu (2003) measure initial return
using the closing price on the 20th trading date. They argue that the first closing market price or
the “non-hit” price in the post-IPO market does not hit either the upper or lower price limit. To
compute IPO underpricing using the first closing price ignores any adjustments in the market
value of the IPO shares after the “non-hit” price is observed. We estimate equation (1) on sample
of 84 family IPOs and on sample of 84 non-family firms.
Indepedent variables
The first independent variable is the percentage of outside directors (% of outside
directors), which is defined as number of directors who are not members of controlling family
This argument also applies to France and Japan where “circuit breakers” are installed to limit post-IPO daily price
fluctuations within a certain preset limit.
1
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per total number of directors. Managerial entrenchment is less likely to occur with the presence
of outside directors. In addition, the outsiders may bring expertise to complement the abilities of
incumbent board members (Filatochev & Bishop, 2002). We thus expect IPOs with higher % of
outside directors display lower underpricing.
The second and third independent variables are the percentage of family ownership at the
IPO and the expected percentage of long-term family ownership. The first variable is measured
as the percentage of shares owned by original family business owner before the trading date. The
second variable is such percentage measured for 36th month after the date of IPO or from the
IPO date until the third year after the IPO. For the second variable, we apply the same
methodology used by Purnanandam and Swaminathan (2004) regressing underpricing on
forecasted book value to market value ratio where market value is known after the IPO.
The third independent variable is underwriter prestige. We hypothesize that IPOs that
have high family control should benefit more from working with more prestigious underwriters
who can provide expertise and strategic guidance in helping them harvest the fruits of their labor
through an IPO. Underwriter prestige (Underwriter prestige) is constructed based on the US$
proceeds of the IPOs each underwriter underwrote during our sample period. We followed the
approach developed by Carter and Manaster (1990) to rate underwriter prestige. The Carter and
Manaster measure is constructed from the placements of IPO underwriters in the prospectus,
which lists all the investment banking firms that comprise the underwriting syndicate of an IPO
issue with more prestigious underwriters listed higher. This measure, however, is limited to U.S.
underwriters. Following the idea that more prestigious investment banks generally underwrite
more IPOs, most of which tend to be larger offerings, we construct a discrete measure of
underwriter ranking from 0 (least prestigious) to 9 (most prestigious) by classifying each lead
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investment bank for our sample IPOs into one of 10 categories according to the total proceeds of
the IPOs the investment bank underwrote during our 1987– 2004 sample period.2 Note that our
measure is consistent with that used by Megginson and Weiss (1991) who gauge underwriter
quality with the average market share of the underwriter.
Control Variables
We derive control variables from the extant IPO literature. These variables reflect the
extent of information asymmetries in the IPO process and the degree of uncertainty over issue
value. Specifically, we include six firm-level underpricing determinants, which we discuss
below.
The first control variable is the natural logarithm of issue proceeds (Log of proceeds),
one of the most commonly used for underpricing determinants. Larger firms are generally
considered less risky than smaller firms. Hence, the size of the issue (in U.S. dollars) is expected
to be negatively correlated with underpricing (Beatty and Ritter, 1986).
The second control variable is the existence of potential successor (Successor dummy).
A family firm would be coded 1 when a successor from the family is either placed in the top
management team or the corporate board, coded zero for otherwise. Having a potential successor
from family implies that family wants to retain ownership for a long-term; therefore, they may
want to price the IPO correctly and thus decrease underpricing. In addition, the presence of
potential successor reduces the uncertainty derived from succession planning (Davis &
Harveston, 1998; Lee, Lim, & Lim, 2003).
2
Specifically, we assign a discrete integer to each lead underwriter as follows: 9 if its total proceeds are no less than
$20 billion; 8 if proceeds are between $10 and $20 billion; 7 if proceeds are between $5 and $10 billion; 6 if
proceeds are between $2 and $5 billion; 5 if proceeds are between $1 and $2 billion; 4 if proceeds are between $0.5
and $1 billion; 3 if proceeds are between $0.2 and $0.5 billion; 2 if proceeds are between $0.1 and $0.2 billion; 1 if
proceeds are below $0.1 billion; and 0 if the lead underwriter is not ranked among the top 500 by the SDC.
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The third control variable is IPO volume (IPO volume). The extant IPO literature has
long recognized that cycles exist in both the volume and the average initial returns of IPOs. 3 For
example, Ibbotson and Jaffe (1975) and Lowry and Schwert (2002) find a strong pattern of
negative associations between current IPO underpricing and prior IPO volume. To control for
cyclical patterns in the IPO market, we construct an IPO volume variable for every IPO, which is
defined as the total number of domestic IPOs issued over the 12-month period ending in the
month in which the IPO was issued.
The fourth control variable is high-tech dummy (High-tech dummy). To the extent that
information asymmetry tends to be similar within industries, industry effects provide some
control for cross-sectional variation in information asymmetry (Ljungqvist et al., 2003). As a
result, we include high-tech dummy in our regressions. High-tech firms are identified following
the classification methods in Loughran and Ritter (2004) and Cliff and Denis (2004) and
expected to have higher underpricing than other IPOs.4
The fifth control variable is bubble period dummy (Bubble period dummy), which is
equal to one if the IPO was issued in 1999 or 2000, and zero otherwise. Bubble period dummy
controls for time-series variation in underpricing (Loughran and Ritter, 2004).
Lastly, we control for firm age (Firm age). We calculate a company’s age as the
difference in years between its founding date and its IPO date. We hand-fill gaps in SDC’s
coverage of company founding dates, and manually check all firms that according to SDC were
zero to three years old at the time of their IPO, because Loughran and Ritter (2004) note that
Periods of high average initial returns and rising volume are commonly referred to as “hot issues” markets.
Loughran and Ritter (2004) and Cliff and Denis (2004) categorize firms with the following SIC codes as high-tech
firms: 2833, 2834, 2835, 2836, 3571, 3572, 3575, 3577, 3578, 3661, 3663, 3669, 3674, 3812, 3823, 3825, 3826,
2827, 3829, 3841, 3845, 4812, 4813, 4899, 7370, 7371, 7372, 7373, 7374, 7375, 7377, 7378, 7379.
3
4
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SDC frequently reports the most recent incorporation date rather than the founding date.5
According to existing studies, we expect this variable to be negatively related to underpricing
since younger firms at time of IPO are more risky and have high information asymmetry.
SAMPLE AND DESCRIPTIVE STATISTICS
Sample Selection
Business Groups in Taiwan, published annually by China Credit Information Service,
profiles the largest 250 Taiwan-based business groups in terms of total assets. This guide
identifies family-owned firms and publishes the family trees of the controlling families in the
corporate profiles. We identify 98 family firms whose profiles have constantly appeared on
Business Groups in Taiwan from 1997 to 2004. Among these firms, we chose IPO firms issued
between 1987 and 2004 that have been constantly named as top 250 largest corporations in
Taiwan. We are able to obtain the IPO performance data of these 98 family firms from the
Securities Data Corporation’s (SDC) Global New Issues database. The corporate governance
data is obtained from Taiwan Economic Journal (TEJ).
We then match these 98 IPO firms against DataStream by requiring them to have closing
stock prices available in DataStream on the fifteenth and thirtieth calendar day after the IPO. Our
close examination of the SDC database reveals several data problems. We find errors in IPO
issue dates for the majority of our sample. For example, the SDC often mistakenly provides
announcement or subscription dates as issue dates. Over 50 percent of IPOs in Taiwan have this
problem. To overcome this data problem, we manually cross-reference each of our sample IPOs
A detailed discussion of some of the errors in the SDC database can be found on Alexander Ljungqvist’s website at
http://pages.stern.nyu.edu/~aljungqvist.htm.
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with Bloomberg to identify and correct the erroneous issue dates. Our final sample consists of
84 family IPOs and 84 non-family firms.6
Non-Family Matching Firms
We also create a list of 84 non-family Taiwanese firms to test the second hypothesis.
Following the process developed by Kim and Ritter (1999) and Purnanandum and Swaminathan
(2004), we identify a matching non-family firm for each family firm in our sample that had
comparable IPO date, size, and liquidity as IPOs in the most recent fiscal year. Total offer value
captures size and cash and equivalent captures liquidity. The first-day IPO market capitalization
is not used in matching because it would not be available to an investor or underwriter before the
offering date. To choose a particular matching firm, we first explore the Taiwanese IPO data in
SDC and stock prices in Datastream. We identify non-family firms sharing the same four-digit
SIC code as its family firm counterpart and then shorten the list by excluding firms whose IPO
dated three years before or after the IPO date of comparable family firm. Setting a limit to the
date of IPO allows us to estimate the IPO performance of non-family firms under similar market
conditions. From these firms, REITs, closed-end funds, ADRs, and firms with share prices less
than five dollars are excluded. This screening criteria is normally used in the extant IPO
literature. Then, we searched for firms whose total offer value is between 75% and 125% of the
family IPO’s total offer value. If we have more than one firm left on the list of potential
candidates, we choose the one whose cash and equivalents is closest to the family firm in the
most recent fiscal year. If there is no qualified candidate, we relax the criteria to widen our
search. Each family IPOs gets a unique matching firm that is closet in total offer value and cash
& equivalent.
6
Among 84 family IPOs, one of them went public in 1987, 8 in 1991, 9 in 1992, 6 in 1993, 8 in 1994, 10 in 1995,
11 in 1996, 4 in 1997, 6 in 1998, 7 in 1999, 5 in 2000, 4 in 2001, 4 in 2002, and 1 IPO in 2004.
19
Descriptive Statistics
Table 1 provides mean and median among all variables for family and non-family IPOs.
We also provide p-value of t-statistics (Wilcoxon signed rank test) of mean (median) differences.
The results illustrate that the average 15-day returns of family IPOs is 18.94%, which is lower
than that of non-family IPOs, 22.35%. Along the same line, the average 30-day return of family
IPOs is 25.79%, which is lower than that of non-family firms, 35.85%. The differences in mean
and median are significant at 1% level. Family firms have mean (median) % of outside directors
as of 40.28% (36.99%). The mean (median) % of family ownership at the IPO is 17.86%
(17.43%) and the mean (median) % of family ownership 3 year post-IPO is 13.56% (11.54%).
On average, 43% of family firms have potential successor but at the median level, none of them
has. The information of family ownership, percentage of outside directors, and potential
successor is available only for family firms.
Underwriters of family firms are less prestigious and do fewer international deals than
those of non-family firms. The mean (median) of underwriter prestige of family firms is 3.42
(3.00) whereas that of non-family firms is 4.29 (4.00). Underwriter reputation is a dummy
variable equals to one if underwriters do both international and domestic deals and zero if
underwriters do only domestic deals. We apply this measure in the robustness test section. On
average, 16% of investment bankers associating with family IPOs do international and domestic
deals; whereas, 21% of those partnering with non-family IPOs do both types of deals. In term of
offer size, family firms have lower logged proceed than non-family. The mean (median) size of
family firms is 16.67 (16.61), which is not significantly different from that of non-family firms,
16.73 for mean and 16.64 for median. Family firms went public when average (median) 40 (41)
20
IPO firms went public, which is about the same as 40 (40) mean (median) of other IPOs that
went public at the same time when non-family firms did.
In addition, on average 14% of family firms went public during dot-com bubble, which is
significantly lower than 38.5% of non-family firms going public during this period. Along the
same line, both mean (32%) and median (0%) of non-family firms in our sample are high-tech
firms, which is significantly lower than mean (57%) and median (100%) of family firms.
Further, family firms are older than non-family firms when they went public. Finally, family
firms have significantly lower liquidity with the average of US$ 6.8 million and median of
US$1.5 million in cash and equivalents than non-family firms that have the average of US$14.4
million and median of US$2.5 million. Taken together, most of non-family firms in our sample
are more high-tech, younger, and more liquid than family firms.
*** Insert Table 1 about here ***
Table 2 provides Pearson correlation coefficients among variables for family and nonfamily IPOs. The numbers above diagonal are for family firms and those below diagonal are for
non-family firms. The results of correlation coefficients do not show a sign of multicollinearity
problem. % of outside directors, % of family ownership at IPO, % of family ownership 3 year
after IPO, and potential successor dummy are not highly correlated. The second and third
variables are not highly correlated because the latter, % of family ownership at 3 year post IPO
is measured after the first trading day. IPO volume, underwriter ranking, underwriter reputation,
and firm age are positively correlated with 15-day and 30-day returns of non-family firms but
negative correlated for family firms. Logged proceed is positively (negatively) correlated with
15-day (30-day) returns of family firms while it is positively correlated with 15-day and 30-day
returns of non-family firms.
21
*** Insert Table 2 about here ***
Results of Analysis
Table 3 illustrates regression results of underpricing on various IPO and family
ownership variables. Having outsider on board significantly reduces underpricing for 15-day
returns of family firms. The higher the percentage of outside directors, the lower 15-day
underpricing supporting our first hypothesis..
In addition, the expected percentage of family ownership 3 year post-IPO is negatively
related to 15-day underpricing. IPOs that have high expected family ownership 3 year post-IPO
indicate original shareholder’s confidence in the firm. Such confidence lowers the amount of
market uncertainty and thus underpricing. This is in contrast to the effect of family ownership at
the IPO. The higher the percentage of family ownership at the IPO, the more insider
entrenchment increasing information asymmetry and underpricing. This result supports our
second hypothesis.
Next, the existence of potential successor does not affect the magnitude of family IPO
underpricing. Finally, partnering with high-ranked underwriters reduced the extent of
underpricing in family IPOs. On the other hand, partnering with highly ranked underwriter
significantly increased the underpricing of non-family firms. The difference of underwriter
ranking coefficients between family vs. non-family firms is significant at 1 % with p-value of
0.009. This result supports the our last hypothesis in which we predict the underwriter prestige
negatively affects underpricing of family firm IPOs. The negative relation between underwriter
ranking and underpricing of family firms supports Carter and Manaster (1990)’s and Carter et al.
(1998)’s finding positing that underpricing is negatively related to underwriter prestige because
22
prestigious underwriters are more likely to underwrite high quality issues with a lower level of
uncertainty. Moreover, prestigious underwriters should provide certification to an issuer; thus
lowering the probability of having a lawsuit and decreasing underpricing. On the other hand, the
positive relation between underwriter ranking and underpricing of non-family firms is consistent
with Cliff and Denis (2004)’s finding of a positive association between underpricing and analyst
coverage by prestigious underwriters.
For non-family firms, the variation of their underpricing can be explained by high-tech
dummy, logged proceeds, firm age and bubble period dummy. Non-family IPOs that are hightech, have small offer size, young, and went public during bubble period are more underpriced
than vice versa. These factors do not explain the variation of family firm underpricing and pvalue of the differences in the coefficients of these factors between family vs. non-family firms
are significant.
Overall, percentage of outside director, percentage of family ownership, and underwriter
ranking explain the variation of family firms underpricing. For non-family firms, underwriter
ranking has an adverse effect on their underpricing, which is also affected by IPO characteristics.
Robustness checks
In this section, we perform a battery of sensitivity analyses to check the robustness of our
findings and the results are shown in Table 4. First, we apply 30-day underpricing as a dependent
variable. The results remains consistent with those in Table 4 supporting our three hypotheses.
Potential successor that does not explain the variation of family firms 15-day underpricing explain
the variation of 30-day underpricing. Potential successor may want to retain long-term ownership and
want to price the offer correctly thus reduces underpricing. Moreover, the presence of successor may
reduce uncertainty derived from succession planning. Percentage of outside directors, percentage of
family ownership 3-year after IPO, and underwriter ranking negatively affect 30-day underpricing.
23
Second, potential cross-sectional correlation where the error terms of equations (1) and (2)
were correlated would lead to an underestimation of the standard errors and an overstatement of the
significance of the coefficient estimates. We note that the extant IPO literature treats IPO
underpricing levels (i.e., initial returns) across firms as independent observations. Nonetheless, to
ensure that our results are not affected by this potential problem, we repeat the regression analysis of
equation (1) and (2) using Newey-West heteroskedasticity and autocorrelation corrected standard
errors. As shown in column fourth to sixth of Table 4, although the Newey-West standard error is
higher (by construction) than the White heteroskedasticity-consistent standard error in Table 3, the
results remain intact with those in Table 3.
Third, we replace underwriter ranking by underwriter reputation using binary underwriter
reputation dummy. We define a high-quality underwriter as one that underwrites both domestic and
international IPOs while low-quality underwriters only underwrite domestic IPOs. We argue that
underwriters with international exposure have more experience and a better reputation than
underwriters who are only domestically active. We find that our results are consistent with those in
Table 3. % of outside director, % of family ownership 3-year after IPO, and underwriter ranking
have negative coefficients; whereas, percentage of family ownership at the IPO has positive
coefficient. The only coefficient in this regression that is different from that in Table 3 is high-tech
dummy, which is positively significant for family IPOs.
Fourth, we find another set of non-family comparable firms matched by industry, market
capitalization, and profit margin. Market capitalization captures size; while, profit margin or profit
divided by sales captures profitability. This matching method is consistent with Kim and Ritter
(1999) and Purnanandum and Swaminathan (2004), who matched IPO firms by size and
profitability. The essence of our findings remains the same with those in Table 3.
24
Finally, to ensure that our results are robust across different time periods, we perform a
robustness test in which we divide our IPO sample into two halves, i.e. January 1987 to
December 1995 and January 1996 to December 2004, and test whether we have similar findings
in each sub-period. Although the magnitude and significance of coefficients in the 1996-2004
regression are lower than those in the 1987-1995 regression, our findings are little affected as our
sub-period results are quantitatively and qualitatively consistent with the results for the full
sample.
How are the Interaction Effects different between Family IPOs vs. Non-family IPOs?
In this section, we explore the difference in the interactions effects between family IPOs
vs. non-family IPOs. In particular, we focus on the interaction effects of the existence of
potential successor, % of family ownership at the IPO, % of family ownership 3 year post IPO,
underwriter ranking, age, and high-tech dummy with other variables. We first develop theoretical
predictions on how these factors affect the other factors-underpricing relation differently
between family and non-family IPOs.
To investigate whether the effect of various variables on underpricing varies with each
other, we estimate the following regression models:
1. Family IPOs
Underpricing k =
B 0 +B 1 (% of outside directors) + B 2 (% of outside directors)*Interaction
term + B 3 (% of family ownership at IPO) + B 4 (% of family ownership at
IPO)*Interaction term + B 5 (% of family ownership 3-yr post-IPO) + B 6 (%
of family ownership 3-yr post-IPO)*Interaction term + B 7 (potential
25
successor dummy) +B 8 (potential successor dummy)*Interaction term +
B 9 (underwriter’s ranking) + B 10 (underwriter’s ranking)*Interaction term
+B 11 (high-tech dummy) + B 12 (high-tech dummy)*Interaction term + B 13 (
IPO volume) + B 14 (log of proceed) + B 15 (firm age) + B 16 (bubble period
dummy) + E
(3)
where interaction term is % of family ownership at IPO, % of family ownership 3-yr postIPO, potential successor dummy, underwriter’s ranking, high-tech dummy, or age.
2. Non-family IPOs
Underpricing k = A 0 + A 1 (underwriter’s ranking) + A 2 (underwriter’s ranking) *Interaction
term + A 3 (high-tech dummy) + A 4 (high-tech dummy) *Interaction term
+ A 5 ( IPO volume) + A 6 (log of proceed) + A 7 (firm age) + A 8 (bubble
period dummy) + E
(4)
where interaction term is underwriter’s ranking, high-tech dummy, or age.
The regression results for equations (3) and (4) are summarized in Table 5. Several findings
emerge. First, although the existence of a potential successor alone is not adequate to affect
underpricing, its interaction with % of outside directors, % of family ownership 3-year post-IPO, and
underwriter ranking empower the negative impacts of these three factors on underpricing. In Model
1, Table 5, the coefficient of % of outside directors changes from -0.118 in Table 3 to -0.489 in Table
5. The coefficient of % of family ownership 3-yr post-IPO changes from -1.473 in Table 3 to -1.991
in Table 5. The coefficients of underwriter ranking alone and of its interaction with potential
successor dummy are -2.275 and -2.717, which are significant at 5% and 1%, respectively. This
implies that IPOs that have high % of outside directors, % of family ownership 3 year post-IPO, or
26
are associated with prestigious underwriter and have a presence of potential successor are less
underpriced than IPOs that have these three factors but do not have a presence of potential successor.
A decrease in information asymmetry and uncertain may be a result of a potential successor
presence, which reduces succession planning.
Second, in contrast to the interaction effects of potential successor, % of family ownership at the
IPO does not have any interaction effect. Although IPOs that have high family ownership at the IPOs
are more underpriced, having high family ownership at the IPO does not significantly affect a
decrease in underpricing from having high % of outside directors, % of family ownership 3-year
post-IPO, and high ranked underwriters. The coefficients of % of outside directors, % of family
ownership 3-year after IPO, and underwriter ranking remain significantly negative but their
interactions with % of family ownership at the IPO are insignificant. This implies a good signal from
a decrease in information asymmetry from having high % of outside directors and family ownership
3-year post-IPO overpowers a bad signal of management entrenchment from having high % family
ownership at the IPO.
Third, similar to the effect of % of family ownership at the IPO, % of family ownership 3-year
post-IPO does not interact with % of outside directors and % of family ownership at the IPO
significantly enough to have any effect on underpricing. However, IPOs that have high % family
ownership 3-year post-IPO and that are partnering with prestigious investment banks have
significantly lower underpricing than such IPOs associated with less prestigious investment bankers.
The coefficients of % family ownership 3-year post-IPO*underwriter ranking are -4.139 and -1.755
in Model (3) and (4), respectively and they are significant at 1%. Prestigious underwriter really
strengthens a decrease in underpricing from having high % of family ownership 3-year post-IPO.
This indicates the important role of high ranked underwriters in helping family firms reduce
underpricing.
27
Fourth, being high-tech reduces a decrease in underpricing from having high % of outside
directors, % of family ownership 3-yr post-IPO, and high ranked underwriter. In Model 6, Table 4,
family column, the coefficient of these interaction terms are 0.225, 0.811, and 1.276 and they are
significant at 5%, 5%, and 10%, respectively. That means high-tech IPOs have the coefficients of %
of outside directors, % of family ownership, and underwriter ranking equal to -2.286 (from 2.511+0.225), -4.805 (from -5.616+0.811), and -0.663 (from-1.939+1.276).
These coefficients
remain negative but the magnitude is less than that of non-tech IPOs. Therefore, family IPOs that
have high % of outside directors and expected family ownership 3 year post IPO, and are partnering
with prestigious underwriters do not benefit much from reduced underpricing if they are high-tech.
On the other hand, high-tech IPOs that have high IPO ownership at the IPO are more
underpriced than high-tech IPOs that have low ownership but the difference is not significant. In
contrast to family firms that prestigious underwriters help reduce the magnitude of underpricing, the
prestige of underpricing increases underpricing of non-family firms. The underwriter’s role for nonfamily firms is consistent with Cliff and Denis (2004), who find that a positive association between
underpricing and analyst coverage by prestigious underwriters and Beatty and Welch (1996), who
observe the relationship between underwriter prestige and underpricing switching from negative to
positive during the 1990s. Beatty and Welch (1996) and Cliff and Denis (2004) explain prestigious
underwriters take higher quality firms public, thus the presence of prestigious underwriters is
positively related to IPO underpricing. In contrast, the underwriter’s role for family firms can be
explained by Carter and Manaster (1990) and Carter et al. (1998) positing that underpricing is
negatively related to underwriter prestige because prestigious underwriters are more likely to
underwrite high quality issues with a lower level of uncertainty. Moreover, prestigious underwriters
should provide certification to an issuer; thus lowering the probability of having a lawsuit and
decreasing underpricing. Being high-tech weakens the negative impact of underwriter’s prestige on
28
underpricing of family firms whereas it strengthens the positive impact of underwriter’s prestige on
underpricing of non-family firms.
Lastly, there is no interaction effect of age and other variables on underpricing. The signs and
significance of other coefficients remain intact with those in Table 3. Taken together, the presence of
potential successor helps family firms that have high % of outside directors and % of family
ownership 3-year post IPO reduce the magnitude of underpricing. In contrast, being high-tech
counteracts family firms’ benefits of reduced underpricing from having high % of outside directors
and % of family ownership 3-year post IPO, and partnering with high ranked underwriter. Being
high-tech hurts non-family firms as it increases positive impact of high ranked investment bankers on
underpricing.
DISCUSSION
The central message of our research is that adoption of monitoring mechanisms and
family owner commitment signal investors about the quality of an IPO firm thus decrease the
underpricing family firm IPO. This finding is in agreement with recent studies on the impact of
corporate governance practices on family business performances (Schulze, Lubatkin, Dino, &
Buchholtz, 2001; Andersen & Reeb, 2004; Andersen, Mansi, & Reeb, 2004). In addition, we
identify two notable uniqueness of family firms. First, outside directors who are not owners or
employees of a firm play a major role in the reduction of IPO underpricing. When we
specifically test the impact of non-family director appointment on family firm IPO performance,
the results suggest that the appointment of non-family directors, not necessarily non-employee,
significantly reduce underpricing in family IPOs. This result implies that family firms may avoid
engaging in time consuming and sometimes expensive search process to find and hire director
candidates who are not currently on the payroll of the company. The second uniqueness is that
29
teaming up with prestigious underwriters significantly reduces underpricing. Surprisingly, this
effect is opposite in non-family firm IPOs. This result suggests that the beneficiaries of
underwriter prestige are unique to the family firms. Non-family firms partnering with prestigious
underwriter for lower IPO underpricing may be sacrificing bargaining power against their
underwriters for little gains.
Although the impact of external environment has been well studied by strategic
management and family business researchers in the past, family business literature has been
more inclined to focus on intrinsic uniqueness such as how a family firm react to external
challenges. However it is not unusual that the label of family-owned business invokes distinctive
perceptions for external stakeholders. Based on a survey of family and non-family managers in
family firms, Poza, Alfred, & Maheshwari (1997) report that these two groups demonstrate
different perceptions about the managerial practices, cultures, and succession processes. The
results of our analysis show that investors react to IPO signals differently when evaluating family
firm IPO deals. It would be helpful for future researchers to identify more sources of such
extrinsic uniqueness and the impact of these extrinsic factors on the strategy formulation and
implementation of family firms. The results of such research would highlight when and how
family and non-family firms adopt different strategies to address competitive challenges. The
findings of these studies would also help family firm managers develop effective strategies.
Our research also contributes to an on-going debate of IPO underpricing research.
Several earlier studies find that underwriter reputation tends to reduce underpricing (Carter and
Manaster, 1990; Carter, Dark and Singh, 1998). In contrast, studies based on more recent years
find a significant positive association between underwriter reputation and IPO underpricing
(Cliff and Denis, 2004; Loughran and Ritter, 2004). Current explanations for such shift put
30
strong emphasis on the role of underwriters. For example, Cliff and Denis (2004) argue that
underpricing is used by issuers to compensate prestigious investment banks for expected postIPO research coverage from highly ranked analysts. In addition, Loughran and Ritter (2004)
propose a spinning explanation of underpricing which suggest issuers’ intent to allocate hot IPOs
to “friends and family” and other insiders in recent years creates strong incentives for issuers to
seek underwriters with a reputation for severe underpricing. Our analysis presents an investorside explanation. Researchers are likely to observe a negative correlation between underwriter
prestige and underpricing if there is a surge of family firm IPO during the time span of
observation. On the other hand, the observed relationship between underwriter prestige and
underpricing may not be much less profound when few family firms go IPO during the period of
observation. Historical research reports that legal environments have profound impact on the
ownership structure of family firms in France, Spain, and U.K. (Colli, Fernandez Perez, & Rose,
2003). Changes in wealth transfer regulation often motivate incumbent family business owners
to take necessarily measures, including offering stocks to the public, to retain desirable level of
family wealth. Further investigation is needed to link the shift of prestige-underpricing
relationship to the prevalence of family firms in an IPO market.
The practical implication of our research is that the conventional wisdom of signaling
still holds. Practices to improve quality of corporate governance and owner commitment help
investors to better evaluate the quality of the IPO deal. Similarly, family business owners and
institutional shareholders such as venture capitalists can minimize underpricing by adopting the
corporate governance practices we suggested in this paper, non-family directors, prestigious
underwriter, and long-term share holding.
31
CONCLUSION
IPO has become an important measure to sustain long-term growth of family firms.
Signaling help prospective investors of family firm IPOs to better evaluate the value of the firm.
The findings from this study indicate that the appointment of non-family outside directors, use of
prestigious underwriters, and expected long-term share holding are viewed by the investors as
positive signals thus reduce the extent of underpricing. Our study also suggests that investors’
perception toward family firms and non-family firms are different. Further research on the
sources of effects of family firm extrinsic uniqueness would enhance our understandings in
family firm strategy and the impact of underwriter prestige on IPO underpricing.
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39
Appendix: Variable before the IPO Definitions
Panel A: Independent Variables
Variables
Source
TEJ
% of outside
directors
% of family
ownership at IPO
% of family
ownership 3-year postIPO
Underwriter ranking
Underwriter reputation
TEJ
Percentage of total shares owned by members of a family before the first trading day
TEJ
Percentage of total shares owned by members of a family 36 months after the first trading day
SDC
SDC
Loughran and Ritter (2004)’s adjusted Carter-Manaster underwriter reputation ranking
A dummy variable equal to one if the lead underwriter underwrites both domestic and
international IPOs and zero if it underwrites only domestic IPOs
Panel B: IPO Variables
Variables
Source
Underpricing (15 days)
SDC
TEJ
Potential successor
dummy
IPO volume
SDC
High- tech dummy
Log of proceeds
Firm age
Bubble period dummy
Cash and equivalents
Definition
Percentage of number of non-family outside directions by total number of directors
SDC
SDC
SDC and
prospectus
SDC and
prospectus
Definition
100[(closing price 15 days after the IPO date - offer price)/offer price]
Coded 1 if at least one family member from the younger generation or a founder’s sibling is
placed in the corporate board or is a member of top management team.
The total number of domestic IPOs issued over the 12-month period ending in the month in
which the IPO was issued
A dummy variable equal to one if the IPO is high-tech and zero if it is non high-tech. Hightech firms are identified following the classification methods in Loughran and Ritter (2004)
and Cliff and Denis (2004).
The money raised, after fees and expenses or shares offered in IPO multiplied by offer price
after fees and expenses, ($ millions)
Number of years the firm was founded before the IPO
A dummy variable equal to one if the IPO went public in 1999 or 2000 and zero for
otherwise.
The amount of cash and equivalents in the most recent fiscal year before firm going public
40
Table 1: Descriptive Statistics of IPO Underpricing
There are 84 family and 84 non-family Taiwanese IPOs from January 1, 1987 through December 31,
2004. The matching firm is a non-family firm that was in the same industry, went public within three
years of the family IPO and had comparable total offer value and cash & equivalents in its most recent
fiscal year. All variables are described in the Appendix. White’s heteroskedasticity-adjusted t-statistic
provides a test for the difference in means and the Wilcoxon Signed Rank test provides a test for the
difference in medians. .
Family-controlled IPOs
Variables
30-day returns (%)
15-day returns (%)
% of outside directors
% of family ownership at IPO
% of family ownership
3-year post-IPO
Potential successor dummy (%)
Underwriter ranking
Underwriter reputation
Log of proceeds
IPO volume
Bubble period dummy (%)
High-tech dummy (%)
Firm age (years)
Cash and equivalent (thousand US$)
Number of IPOs
Non-family controlled IPOs
Mean
Median
Mean
Median
25.79
18.94
40.28
17.86
18.61
8.15
36.99
17.43
35.85
22.35
NA
NA
22.48
13.56
NA
NA
13.56
11.54
NA
NA
42.86
4.29
16.11
16.67
40.39
14.29
0.32
28.29
6,824.68
84
0.00
4.00
0.00
16.61
41.00
0.00
0.00
27.00
1,485.60
NA
3.42
21.11
16.73
40.38
38.46
0.57
17.96
14,447.91
84
NA
3.00
0.00
16.64
40.00
0.00
1.00
17.50
2,480.50
Difference
T-stat
(P-value)
WilcoxonTest
(P-value)
0.007
0.003
0.005
0.002
0.003
0.009
0.212
0.351
0.076
0.019
0.095
0.158
0.002
0.117
0.439
0.217
0.115
0.001
0.078
0.246
41
Table 2: Correlation Coefficients of Family and Non-Family Controlled IPOs
There are 84 family and 84 non-family IPOs from January 1, 1987 through December 31, 2004. The non-family IPOs are matching firms that was in the same industry,
went public within three years of the family’s IPO date, had comparable log of proceeds and cash and equivalent in its most recent fiscal year. Descriptions of all variables
are in the Appendix. Pearson correlation coefficients for family (non-family) IPOs are reported above (below) the diagonal. P-value for t-test significance of each
correlation coefficient is reported under each correlation coefficient.
Variables
30-day
returns
(%)
30-day returns (%)
15-day returns (%)
% of outside
directors
% of family
ownership at IPO
% of family
ownership 3-year
post IPO
Potential successor
dummy (%)
Underwriter ranking
Underwriter
reputation
IPO Volume
High-tech dummy
(%)
Log of proceeds
Firm age (years)
Bubble period
dummy (%)
15-day
returns
(%)
% of
outside
directors
0.926
0.000
0.058
0.598
0.020
0.857
0.963
0.000
% of
family
ownership
at IPO
-0.010
0.930
-0.088
0.428
-0.081
0.464
% of
family
ownership
3-year
post IPO
-0.113
0.306
-0.154
0.163
-0.102
0.355
0.283
0.000
Potential
successor
dummy
(%)
Underwriter
ranking
Underwriter
reputation
IPO
Volume
Hightech
dummy
(%)
Log of
proceeds
Firm
age
(years)
Bubble
period
dummy
(%)
-0.115
0.298
-0.185
0.092
0.050
0.651
0.117
0.289
0.071
-0.011
0.920
-0.032
0.771
0.074
0.505
-0.110
0.318
-0.076
-0.026
0.877
-0.024
0.889
-0.176
0.298
0.132
0.437
0.184
-0.084
0.448
-0.182
0.097
-0.016
0.888
0.182
0.098
0.115
0.052
0.641
0.148
0.180
-0.170
0.122
-0.053
0.635
-0.066
-0.053
0.632
0.033
0.765
0.054
0.625
0.071
0.522
0.150
-0.052
0.637
-0.066
0.553
0.250
0.022
-0.031
0.777
-0.023
0.094
0.397
0.114
0.301
-0.166
0.131
-0.067
0.544
-0.040
0.519
0.495
0.275
0.299
0.549
0.175
0.835
0.721
0.026
0.817
-0.079
0.644
0.212
0.207
0.137
0.215
0.055
0.619
-0.173
0.115
0.125
0.257
0.062
0.578
-0.119
0.281
0.099
0.369
0.147
0.181
-0.147
0.181
-0.113
0.307
0.219
-0.123
0.184
-0.283
-0.040
0.434
0.662
-0.021
0.847
0.511
-0.063
0.566
-0.040
0.721
0.307
-0.041
0.708
-0.372
0.001
0.170
0.121
0.887
-0.203
0.064
0.133
0.228
0.029
0.790
-0.186
0.091
0.504
0.010
0.447
0.025
0.296
0.342
0.332
0.284
0.057
0.786
0.207
0.321
0.545
0.005
0.365
0.073
-0.442
0.027
0.212
0.066
0.755
0.254
0.221
0.594
0.002
0.296
0.151
-0.415
0.039
0.227
-0.092
0.661
0.202
0.332
0.262
0.206
0.170
0.417
-0.344
0.092
-0.013
0.939
0.085
0.618
0.239
0.155
-0.233
0.164
0.228
0.176
0.067
0.750
0.363
0.074
-0.264
0.203
-0.384
0.058
0.426
0.034
-0.290
0.160
-0.068
0.747
-0.001
0.995
-0.513
0.009
-0.157
0.453
42
Table 3
Determinants of IPO Underpricing
This table presents regressions of 15-day underpricing of 84 family and non-family IPOs that was in the same industry,
went public from January 1, 1987 to December 31, 2004. The non-family IPOs are matching firms that went public within
three years of the family’s IPO date, had comparable log of proceeds and cash and equivalent in its most recent fiscal year.
Descriptions of all variables are in the Appendix. White’s heteroscedasticity-adjusted t-statistic is shown under each
coefficient. P (Diff) is the p-value from a t-test for the difference between corresponding coefficients of family and nonfamily firms. *** Indicates statistical significance at the 1% level. ** Indicates statistical significance at the 5% level. *
Indicates statistical significance at the 10% level.
Explanatory
Variable
Constant
% of outside directors
% of family ownership at the IPO
% of family ownership from IPO date
to 3rd year after the IPO
Potential successor dummy
Underwriter ranking
IPO volume
High-tech dummy
Log of proceeds
Firm age
Bubble period dummy
Adjusted R-squared
15-day Underpricing
Family
Non-family
P(Diff)
32.487
0.389
-1.578***
-2.804
3.595***
2.985
-3.252**
-2.007
-1.188
-1.164
-2.792**
-2.394
-87.547**
-2.490
0.017
4.890**
2.167
0.009
-0.393
-0.910
2.272
0.549
1.116
1.420
1.209
1.346
2.340
0.478
15.82%
-2.249
-0.312
3.311***
3.391
-8.412**
-2.224
-2.606**
-2.411
4.511**
2.308
34.86%
0.315
0.003
0.026
0.001
0.017
43
Table 4
Robustness Tests of Various Variables on IPO Underpricing
This table presents regressions of 15-day underpricing of 84 family and non-family IPOs that went public from January 1, 1987 to December 31, 2004. The non-family
IPOs are matching firms that was in the same industry, went public within three years of the family’s IPO date, had comparable log of proceeds and cash and equivalent
in its most recent fiscal year. Descriptions of all variables are in the Appendix. White’s heteroskedasticity-adjusted t-statistic is shown under each coefficient. P (Diff) is
the p-value from a t-test for the difference between corresponding coefficients of family and non-family firms. *** Indicates statistical significance at the 1% level. **
Indicates statistical significance at the 5% level. * Indicates statistical significance at the 10%.
Independent
Variables
Constant
% of
outside
directors
% of family
ownership
at the IPO
% of family
ownership
from IPO
date to 3rd
year after
the IPO
Potential
successor
dummy
30-day underpricing as a dependent
variable
Newey West standard errors
Underwriter reputation dummy as
underwriter ranking
Family
Nonfamily
P
(Diff)
Family
Nonfamily
P
(Diff)
Family
Nonfamily
P
(Diff)
19.0874
-75.041**
0.021
32.487
-87.547**
0.019
24.585
-78.252**
0.023
1.273
-2.355
1.471
-2.340
1.264
-2.190
Non-family IPOs matched by
Industry, market capitalization,
and profit margin
NonP
Family
(Diff)
family
34.631
0.015
83.474***
0.551
-2.844
1.004***
-3.728
Include only 1987-1995
Family
Nonfamily
P
(Diff)
F
21.849
-70.946**
0.028
3
1.330
-2.063
-1.118***
-1.578**
-1.248***
-2.835
-2.725
-3.135
2.873**
3.595***
6.009**
2.427**
6.663**
2.586
2.795
2.683
2.404
2.566
-3.473***
-2.879
-3.252*
-1.914
-3.115***
-3.078
-2.685**
-2.082
-3.031***
-3.359
0
-0.946**
-1.
-2.381
-2
3.
2
-2.
-2
-2.909*
-1.188
-0.308
-1.457
-1.949
-1.342
-1.572
-1.195
2.194***
-3.689
8.001***
-0.394
0.315
-0.671
0.307
0.364
1.168***
Underwriter
ranking
-3.155***
2.318***
-3.111
2.768
IPO volume
-2.572
0.576
-1.665
0.083
High-tech
dummy
2.605
1.994**
0.735
2.416
Log of
proceeds
1.644
-6.631**
0.667
-2.065
0.008
0.337
0.003
0.030
-2.792**
4.890**
-2.063
2.670
-0.393
2.249
-0.790
0.264
2.272
3.311***
0.619
4.061
1.116
-8.412*
1.128
-1.779
0.010
0.285
0.003
0.03
-3.858***
1.984**
-3.833
2.512
-0.648
0.871
-1.643
0.074
2.207*
1.468***
1.904
3.012
1.668
-5.545*
0.534
-1.931
0.009
0.399
0.003
0.028
<0.0
01
3.266
0.526
3.851
0.981
-7.998
0.877
-1.671
0.349
0.003
0.034
-2.328
-0
-1.363
-1
-4.314***
2.215
-3.382
1.402
-2.301
0.614
-1.454
0.056
1.764
1.642**
0.770
2.742
1.529
-4.729
0.609
-1.601
44
0.011
-3
-1
0.429
-0
-0
0.003
2
0.03
-1
1
-1
Firm age
Bubble
period
dummy
Adjusted Rsquared
-2.399**
-2.207*
-2.243
-1.962
5.082
2.855***
0.304
16.49%
0.001
1.209
-2.606**
1.026
-2.718
2.340
4.510**
3.476
0.439
38.12%
15.82%
0.017
0.001
-2.822*
-2.873**
-1.745
-2.138
3.911
2.990***
2.562
0.365
34.50%
16.00%
0.02
0.001
1.478
-1.339**
1.332
-2.236
4.907
4.002***
3.715
0.519
34.81%
19.98%
0.021
0.001
-3.177
-2.499**
-1.729
-2.045
1.368
2.243***
2.960
0.452
3.074
2
30.25%
19.99%
43.16%
15
0.024
45
0.001
1
1
0.019
2.
Table 5
Interaction Effect of Various Variables on IPO Underpricing
This table presents regressions of 15-day underpricing of 84 family and non-family IPOs that was in the same industry, went public from January 1, 1987 to December
31, 2004. The non-family IPOs are matching firms that went public within three years of the family’s IPO date, had comparable log of proceeds and cash and equivalent
in its most recent fiscal year. Descriptions of all variables are in the Appendix. White’s heteroskedasticity-adjusted t-statistic is shown under each coefficient. P (Diff) is
the p-value from a t-test for the difference between corresponding coefficients of family and non-family firms. *** Indicates statistical significance at the 1% level. **
Indicates statistical significance at the 5% level. * Indicates statistical significance at the 10%.
Interaction terms
Potential
successor
At IPO
ownership
Model specification
(1)
(2)
Family
ownership 3 yr
post IPO
(3)
Independent variables
Family
Family
Family
Family
Constant
64.027**
-36.895**
4.698
-39.791*
-34.156
2.151
2.067
-1.038
-2.598**
1.106
-2.381**
-3.401***
1.407
-2.116
-3.520
-1.864
2.511***
-2.836
-0.489***
0.223
-0.063
-2.765
1.106
5.474***
3.028
% of outside directors
% of outside
directors*interaction term
% of family ownership at the
IPO
High-tech dummy
(5)
Nonfamily
Age
(5)
Nonfamily
P(Diff)
Family
0.005
68.258
-84.086
1.519
-1.349
Underwriter ranking
P(Diff)
Family
0.006
83.470*
-2.537
1.769
0.903***
-2.926
0.225**
-0.026
0.336
-0.732
2.417
-0.624
1.262
2.574**
4.987**
4.339**
6.442***
3.257***
2.200
2.279
2.684
3.559
3.261
-3.014**
% of family ownership at the
IPO *interaction term
2.462
-0.266
0.454
0.181
-0.013
1.294
-0.309
0.212
-0.114
% of family ownership from
IPO to 3 yr post IPO
1.816
-3.478**
-2.005
-2.555***
0.333
0.531
-2.726
-2.420
1.678
5.616***
-2.901
-3.070
% of family ownership from
IPO to 3 yr
post IPO * interaction term
-1.991**
0.055
0.811**
0.192
-2.135
0.076
2.305
0.506
1.630
1.755***
-3.051
Potential successor dummy
2.134
-11.729
-0.014
-2.706
-1.568*
-2.027
0.336
-1.352
-1.399
-1.186
-1.776
-0.144
Potential successor dummy *
0.339
-0.717
-0.811
-0.257
-1.065
interaction term
0.611
-0.898
-1.193
-1.183
-0.710
(4)
Nonfamily
50.156**
-2.598
P(Diff)
0.043
46
Underwriter ranking
Underwriter ranking *
interaction term
High-tech dummy
High-tech dummy *
interaction term
IPO volume
-2.275**
-3.138***
-2.526**
-1.939**
1.106*
-2.096
-3.039
-2.473
-2.152
1.910
-2.717***
-1.010
-0.115
1.276*
0.642**
-3.235
-0.066
-0.662
1.928
2.563
9.888***
5.345***
0.792
2.968**
1.199**
3.623
3.280
0.847
2.180
2.230
-1.055
0.073
-0.402
2.536
-2.682**
7.042***
-2.406
3.928
-0.082
0.885
-0.640
1.276
15.559***
1.766***
3.110
-4.139***
0.094
-3.888
1.588
5.665*
2.167
1.199**
1.381
1.615
1.827
1.652
2.230
Log of proceeds
3.597
-2.506**
-3.896*
-3.585
-6.495**
1.607
-2.594
-1.937
-0.860
-2.378
Firm age
-3.048**
-2.079*
0.544
-2.661
-3.937
-2.116
-1.802
0.391
-1.428
-1.599
1.229
5.454
5.729
5.563
0.163
0.360
1.315
1.324
1.302
0.177
13.42%
12.23%
12.92%
21.84%
32.54%
Bubble period dummy
Adjusted R-squared
<0.001
0.025
0.003
0.061
0.042
0.207
0.159
<0.001
20.610**
-2.150
3.106**
2.617
0.238
7.896***
0.962***
2.292
2.866
3.288
-0.569
0.081
-0.928
0.094
-0.213
0.119
-1.380
0.563
4.842**
0.125
0.047
2.419
0.199
1.153
0.230
0.011
-1.941**
-5.495**
2.346
0.167
1.517
-4.945**
1.101
-2.587
0.821
-4.823*
0.532
-1.976
11.609
-18.716
0.387
-0.936
26.40%
43.09%
0.002
0.002
0.082
0.093
-2.515
-2.378
-0.270
-2.937**
-0.702
-2.599
1.971
3.163**
0.244
2.177
13.01%
32.54%
0.012
0.164
0.059
0.008
0.052
0.046
47
48