National Culture and International IPO Underpricing

Julia Hui Zhu1

University of Calgary, Haskayne School of business hjzhu@ucalgary.ca

This version: October, 2011

Abstract

This paper examines how national culture affects the international underpricing of initial public

offerings (IPO). Explanations for IPO underpricing in prior theoretical and empirical research

primarily focus on asymmetric information, the changing risk composition hypothesis, the

formal certification hypothesis, the realignment of incentives hypothesis, and the prospect

theory. We argue that cultural norms and beliefs informally influence human perceptions, such

as risk tolerance, motivations, and perceived options, and thus affect behavior. Using a large

dataset of 19,420 IPOs listed in 44 countries over the period from 1980 to 2009, we find strong

evidence that issuing firms located in countries with a higher degree of uncertainty avoidance

tend to experience a lower level of underpricing. In contrast, issuing firms in countries

characterized by higher collectivism, masculinity and power distance scores tend to experience

a higher level of underpricing. Our results are robust to controlling for a country‘s legal system,

investor protection, private control benefits, regulations in bank ownership, tax advantages, and

stock market performance and with respect to alternative culture proxies and subsamples. Our

findings highlight the importance of national culture in explaining international IPO

underpricing.

Keywords: national culture; initial public offerings; underpricing

JEL Classification: G15; G32; G38

1 The author thanks Viral V. Acharya and B. Espen Eckbo for helpful comments. Address: Scurfield Hall 156, 2500 University Dr. N.W., Calgary, AB T2N 1N4, Canada. Tel.: +1-403-220-2175; fax: +1-403-770-8104. E-mail: hjzhu@ucalgary.ca.

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1. Introduction

Human perceptions and behaviors are developed and determined by their cultural

norms and beliefs (Markus and Kitayama, 1991). With the rising interest in culture analyses in

recent years, the concept of a national culture has been widely adopted in finance literature.

Growing research has focused on cultural influences not only on corporate financial decisions,

such as M&A (Ahern, Daminelli, Fracassi, 2011), corporate debt maturity (Zheng, Ghoul,

Guedhami, and Kwok, 2011), capital structure (Chui, Lloyd, and Kwok, 2002; Li, Griffin, Yue,

and Zhao, 2011), dividend policy (Fidrmuc and Jacob, 2010; Shao, Kwok, and Guedhami, 2010),

cash holdings, and the financial reporting environment (Hope, 2003; Han, Kang, Salter, Yoo,

2010), but also on the form of a country‘s financial systems (Kwok and Tadesse, 2006) and its

international investment strategies (Chui, Titman, and Wei, 2010).

In this paper, we extend the important role that national culture plays in finance to

explain the underpricing of initial public offerings (IPOs). Based on Hofstede‘s cultural

measures, managers of issuing firms in uncertainty avoidance countries have a low tolerance

for ambiguity and unknown situations and are rule-followers. As a result, these managers

prefer a conservative process when going public. Consistent with the changing risk composition

hypothesis, we expect that issuing firms located in countries with a higher uncertainty

avoidance value are less likely to be underpriced. In contrast, the managers of issuing firms

located in countries with higher scores for collectivism 2 (the opposite of individualism)

emphasize group interests and lean towards collective responsibility. They are eager to have a

successful IPO and have the incentive to reallocate shares to their family and friends. As a

2 A collectivism index is obtained by subtracting individualism from 100. A high collectivism score indicates that a society is more collectivist in nature; the ties between individuals are very strong and the family is given much more weight.

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result, they make less of an effort to negotiate the offer price with the underwriter. Consistent

with the realignment of incentives hypothesis, IPOs in higher collectivist countries tend to

experience a higher level of underpricing. Similarly, the managers of issuing firms in countries

characterized by higher masculinity emphasize personal achievement and ambition.

Consequently, they have incentives to earn post-market value and are more likely to exhibit

risk-seeking behavior. Consistent with the prospect theory, IPOs in more masculine countries

tend to experience a higher level of underpricing. Likewise, a high value of power distance

indicates that there are larger inequalities between people, suggesting a lower level of social

trust between issuers, underwriters, and investors. To the extent that IPO underpricing is

reduced by a higher level of trust (Chambers and Dimson, 2009), the power distance dimension

is likely to be positively associated with underpricing.

Using a large dataset of 19,420 IPOs listed in 44 countries over the period 1980 to 2009,

we show that the level of IPO underpricing varies significantly across countries. The average

initial return of the IPOs in our sample is 34.21%, but it varies dramatically in different

countries, where it is, for instance, 19.39% in the U.S., 22.44% in Australia, 43.02% in Japan,

69.14% in Canada, and 93.93% in China. Consistent with our hypotheses, using Hofstede‘s

cultural measures, we find strong evidence that IPOs in countries with a higher level of

uncertainty avoidance tend to experience a lower level of underpricing, whereas IPOs in

countries with higher degrees of collectivism, masculinity, and power distance tend to

experience a higher level of underpricing. Our findings are robust for the inclusion of the

country‘s legal system, investor protection, private control benefits, regulations in bank

ownership, tax advantages, and stock market performance and with respect to alternative

culture proxies, model specifications, and subsamples excluding U.S. IPOs.

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This paper contributes to the literature in several ways. First, we contribute to the

emerging culture-related finance literature by establishing the linkage between national culture

and IPO underpricing. To the best of our knowledge, this is the first study to examine how

national culture influences the level of underpricing. Prior studies have documented that

underpricing is determined by the issuing firms‘ motivation to underprice, the choice of

underwriters, and agency and asymmetric information problems existing in the issuing firms

(e.g., managers and shareholders) for the underwriters and for the investors involved in the

process of issuing IPOs. We have recently seen the creation of a national culture index

(Schwartz, 1994; Hofstede, 2001; House, et al., 2004) and have developed a deeper

understanding of cultural values. The issuing firms‘ subjective perceptions, which mainly

depend on their national cultural beliefs and norms, play an important role in their incentive to

underprice, their choice of underwriters, and their conflicts of interests with underwriters and

investors. Our investigation of the effect of cultural values on the level of underpricing shows

that the different cultural dimensions, measured by various data sources (e.g., Hofstede,

Schwartz, and GLOBE), significantly influence the level of underpricing across countries.

We also contribute to the literature by investigating the determinants that influence

international IPO underpricing (e.g., Loughran, Ritter, and Rydqvist, 1994; La Porta et al., 1997;

Ljungqvist, Jenkinson, and Wilhelm, 2003; Sherman, 2005; Engelen and van Essen, 2010;

Boulton, Smart, and Zutter, 2010). Loughran, Ritter, and Rydqvist (1994) document country-

level initial returns ranging from 4.2% to 80.3% on average; they also document less

underpricing in the 1990s than in the 1980s, due to reduced regulatory interference within most

East Asian countries in the setting of offering prices. Since then, researchers have focused on the

firm-specific characteristics, such as book-building offers (Ljungqvist, Jenkinson, and Wilhelm,

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2003; Sherman, 2005), and country-specific characteristics, such as a country‘s legal system (La

Porta et al., 1997), investor protection (Engelen and van Essen, 2010), and country-level

governance (Boulton, Smart, and Zutter, 2010), in explaining international IPO underpricing

patterns. Our study shows that our primary hypotheses holds after controlling for different

country-level governance quality controls, such as anti-director rights, anti-self dealing, anti-self

dealing public enforcement, rule of law, creditor rights, high private benefits, preemptive rights,

bounced checks, tax evasion, and legal systems.

The paper is organized as follows. Section 2 reviews the literature on national culture

and the explanations for IPO underpricing and develops hypotheses for the empirical analysis.

Section 3 describes the data and variables we use in our empirical analysis. In Section 4, we

investigate the relationship between national culture and IPO underpricing. Robustness checks

on the basis of additional country-level governance qualities, alternative cultural measures, and

subsamples are presented in Section 5. Section 6 concludes this paper.

2. Literature Review and Hypothesis Development

This study is related to the literature on IPO underpricing and its cultural consequences

in finance. In this section, we first outline the role of cultural value in finance. We then review

different explanations of IPO underpricing in the literature, followed by a discussion of the role

of national culture in explaining IPO underpricing in an international setting.

2.1 National Culture

Recently, cultural dimensions have received much attention in finance literature.

Researchers have proposed different proxies for national culture (Schwartz, 1994; Hofstede,

2001; House et al. 2004). The linkage between culture and corporate financial decisions of all

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kinds with the associated proxies for national culture are illustrated as follows (See also Reuter,

2010, for a notable survey regarding culture and finance).

On the one hand, national culture has been used to explain the country‘s choice of

financial system and international investment strategy. Kwok and Tadesse (2006) find that a

bank-based financial system is more likely to appear in countries with higher uncertainty

avoidance. Employing the Hofstede (2001) cultural index, Chui, Titman, and Wei (2010)

document that high individualism is associated with a large trading volume, high volatility, and

more profit momentum. Siegel, Licht, and Schwartz (2008a, 2008b) show that countries

characterized by higher egalitarianism scores are more likely to experience investment flows of

equity, debt, M&A, and foreign direct investments. Likewise, a recent study by Ahern,

Daminelli, and Fracassi (2011) points out that the three cultural dimensions of trust, hierarchy,

and individualism substantially influence M&A activities around world, suggesting that the

volume and the gains of cross-border mergers are reduced as the distance between bidders and

targets grows.

On the other hand, the cultural background affects corporate financial policies and

decisions in various ways. First, cultural values influence corporate capital structure. Using a

sample of 5,591 firms from 22 countries, Chui, Lloyd, and Kwok (2002) show that cultural

values, such as conservatism and mastery as defined by Schwartz (1994), are negatively related

to corporate debt ratios even after controlling for differences in economic performance, legal

systems, financial institutions, and some other well-known determinants of debt ratios.

Consistent with the important role of conservatism and mastery in capital structure, Li et al.

(2011) study over 8,000 foreign joint ventures in China across 32 countries in 2002 and find

evidence that mastery is negatively associated with the short-term debt decisions of foreign

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joint ventures. Specifically, foreign joint ventures with a higher score for mastery are more

likely to have long-term debt. More recently, using 114,723 firm-years in 40 countries over the

period from 1991 to 2006, Zheng et al. (2011) document that firms located in countries

characterized by high uncertainty avoidance, collectivism, power distance, and masculinity

tend to use more short-term than long-term debt.

Second, national culture plays an important role in corporate dividend policy. Using

three of Hofstede‘s (1980, 2001) cultural dimensions – individualism, power distance, and

uncertainty avoidance – as a proxy for national culture, Fidrmuc and Jacob (2010) report that

high individualism, low power distance, and low uncertainty avoidance are significantly

related to higher dividend payouts based on a sample of 5,797 firms across 41 countries.

Interestingly, legal institutions and culture have complementary effects on dividend payouts. In

the same vein, using different proxies for national culture, Schwartz (1994), Hofstede (2001),

House et al. (2004), and Shao, Kwok, and Guedhami (2010) show that high conservatism and

low mastery are associated with high dividend payouts for a sample including 27,462 firm-

years across 21 countries over the period from 1995 to 2007.

Third, the effect of national culture on corporate risk-taking behaviors is dramatic.

Griffin et al. (2010) combine Schwartz‘s harmony dimension and Hofstede‘s individualism and

uncertainty avoidance dimensions using firm-level data from 35 countries over the period from

1997 to 2006. They find that harmony and uncertainty avoidance are negatively associated with

firm-level riskiness, whereas individualism is positively associated with firm-level riskiness.

Furthermore, interactive studies show that the presence of earnings smoothing exacerbates the

effect of individualism on risk-taking, larger firm size weakens the effects of individualism and

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uncertainty avoidance on risk-taking, and stronger creditor rights also weakens the effect of

uncertainty avoidance on risk-taking.

Finally, culture influences corporate disclosure and the accounting earnings report.

Legal institutions have been studied widely in accounting literature. Because cultural values

behave differently across different legal regimes, legal institutions, and national cultures, as a

social institution, cultural values can have opposite influences on accounting disclosure,

earnings management, and dividend payouts (Hope, 2003; Han et al., 2010; Fidrmuc and Jacob,

2010); the role of national culture might vary depending on legal origin. Using Hofstede‘s

national culture dimensions, individualism and masculinity, Hope (2003) shows that

individualism is positively related to and masculinity negatively related to annual report

disclosure for a sample of about 1900 firms over 40 countries in the years 1993 and 1995. At the

same time, Han et al. (2010) use Hofstede‘s (1980) cultural index – individualism and

uncertainty avoidance – as proxies for national culture and find that, along with strong investor

protection, high Individualism and low uncertainty avoidance are associated with more

managers‘ earnings discretion practices for a sample of 96,409 firm-years across 32 countries

over the period from 1992 to 2003. As these studies demonstrate, culture serves an important

role in the financial reporting environment.

Overall, the concept of culture has been established as an indicator in explaining

international investment and corporate financial decisions.

2.2 IPO Underpricing

A number of studies have investigated the different theories that attempt to explain the

underpricing of IPOs. The main focus of those competing explanations falls into two categories:

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behavioral explanations and explanations using the informational asymmetry model. We first

review three aspects of the behavioral explanations–the issuing firms‘ motivation to underprice,

the issuing firms‘ choice of underwriters, and agency problems between the issuing firms and

the underwriters. Then, we outline the asymmetric information explanations which focus on

whether issuers are better informed than investors or vice versa. Finally, we go over country-

level explanations, reviewing the recent international IPO underpricing literature.

It is noteworthy that the explanations for IPO underpricing focus on the setting of the

offer price, where either the issuing firm or the underwriter plays a dramatic role in the

underpricing. First, lawsuit avoidance theory (Hughes and Thakor, 1992) demonstrates that

issuing firms are motivated to underprice in an attempt to avoid be sued later. The

underpricing of IPOs attempts to reduce their legal liability (Tinic, 1988; Hughes and Thakor,

1992). However, the evidence shows that sued IPOs have higher underpricing, suggesting that

underpricing is not an efficient way to avoid subsequent lawsuits (Drake and Vetsuypens, 1993;

Lowry and Shu, 2002; Ritter and Welch, 2002). In contrast, studying the Finnish market between

1984 and 1989, Keloharju (1993) finds no evidence that IPO underpricing is related to lawsuit

avoidance.

Second, the issuing firms‘ decisions regarding the choice of the underwriter is important

when understanding IPO underpricing. Underwriters have not only price discretion but also

quantity discretion through both their pre-IPO decisions on pricing and their aftermarket

activities (Ritter and Welch, 2002). On the one hand, issuing firms contribute by hiring

underwriters that are expected to underprice the firm‘s IPO (Loughran and Ritter, 2004). On the

other hand, the choice of the underwriter is determined by the underwriter‘s quality and

prestige (Logue et al., 2002). The prior studies (Carter and Manaster, 1990; Carter, Dark, and

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Singh, 1998) show that high-quality underwriters were less sensitive to the level of IPO

underpricing in the 1980s. However, the relationship reversed in the early 1990s (Beatty and

Welch, 1996; Cooney et al., 2001). Similarly, Loughran and Ritter (2004) report that IPO

underpricing was more likely to take place in the presence of prestigious underwriters during

the Internet bubble.

Third, the conflict of interest between underwriters and issuers prohibits the issuing

firm from selecting an appropriate underwriter. On the one hand, underpricing creates excess

demand. Utilizing the prospect theory (Kahneman and Tversky, 1979), Loughran and Ritter

(2002) point out that entrepreneurs are more tolerant of excessive underpricing if they

simultaneously learn about a higher than expected post-market valuation. In other words, the

greater the recent increase in their wealth, the less effort issuers make in their negotiations with

underwriters over the offer price. The individuals who purchase an IPO‘s shares may, in turn,

influence IPO activity, underpricing, and long-run performance (Ritter and Welch, 2002). A

good number of companies begin implementing takeover defenses as early as the IPO (Field

and Karpoff, 2002). Further, the excess demand created by IPO underpricing gives both issuers

and underwriters discretion in share allocations (Mello and Parsons, 1998; Stoughton and

Zechner, 1998). For instance, Mello and Parsons (1998) document that it is an efficient issuing

strategy to have the IPO allocates shares to atomistic investors while a private placement

company allocates shares to any blockholders. Stoughton and Zechner (1998), however, argue

that underpricing is needed as it creates an incentive to acquire a block of stock and

consequently monitor the firm‘s management, creating a positive externality for atomistic

investors. On the other hand, Loughran and Ritter (2004) propose a new agency explanation for

IPO underpricing between decision-makers and other pre-issue shareholders, the spinning

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hypothesis. They document that when the top managers of the issuing firm are seeking side

payments, they are likely to hire a lead underwriter with a history of underpricing.

Fourth, investors confront technological and valuation uncertainty regarding issuing

firms. According to the changing risk composition hypothesis (Ritter, 1984), increasing the

number of risky IPOs leads to greater average underpricing. Similarly, Ljungqvist and Wilhelm

(2003) point out that changes in the ownership structure lowers the incentive for the managers

of the issuing firm to bargain for a higher offer price. This realignment of incentives hypothesis,

however, differs from the changing risk composition hypothesis in the context of the two

market determinants of underpricing: the demand side and the supply side.

In addition to providing behavioral explanations regarding the two parties – the issuing

firm and the underwriter – involved in the setting of the offer price, the information asymmetry

model provides another explanation based on recent research. Informational asymmetry arises

from evidence that the issuer is more informed than investors. High-quality issuing firms signal

their quality by underpricing IPOs (Allen and Faulhaber, 1989; Grinblatt and Huang, 1989;

Welch, 1989). This signaling model suggests that, taking private information into consideration,

only issuing firms know the IPO‘s true value. Higher quality issuing firms attempt to use

underpricing as a strategy to distinguish themselves from lower quality firms and to attract

more investors by following in future issuing activity (Welch, 1989), favorable market responses

to future dividend announcements (Allen and Faulhaber, 1989), or analyst coverage

(Chemmanur, 1993). Daniel and Titman (1995), however, argue that IPO underpricing is not an

efficient way to signal. Consistent with this argument, Michaely and Shaw (1994) find no

evidence that the high level of IPO underpricing is followed by a seasoned offering or dividend

payments.

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The other informational asymmetry arises from evidence that investors are more

informed than the issuers. Rock (1986), in the winner‘s curse model, argues that IPO

underpricing compensates uninformed investors for the risk of trading against superior

information. Beatty and Ritter (1986) and Carter and Manaster (1990) document that the greater

the proportion of capital participating in an IPO that belongs to informed investors, the greater

is the equilibrium underpricing. If investors have scarce resources to invest in information

acquisition, they specialize in acquiring information for the most uncertain investments.

Since the formal certification hypothesis was first documented by Booth and Smith

(1986), it has been developed and has survived numerous tests, including James (1992),

Blackwell, Marr, and Spivey (1990), and Barry, Muscarella, Peavy, and Vetsuypens (1990).

Further studies also show that the presence of formal certification (e.g., investment bankers,

auditors, or venture capitalists) in a firm going public can certify the offering price of the issue

reflecting all available and relevant inside information, can help resolve informational

asymmetry in the IPO process, and can serve to lower the level of IPO underpricing (DeAngelo,

1981; Beatty and Ritter, 1986; Titman and Trueman, 1986; Johnson and Miller, 1988; Carter, 1990;

Simon, 1990; Carter and Manaster, 1990; Megginson and Weiss, 1991).

Finally, more recent studies have provided across-board patterns and evidence

explaining international IPO underpricing. Loughran, Ritter, and Rydqvist (1994) report

country-level initial returns ranging from 4.2 to 80.3% on average and find evidence that there

was less underpricing in the 1990s than in the 1980s because most East Asian countries reduced

their regulatory interference in the setting of offering prices. Furthermore, different offering

techniques when going public in the international IPO market can lead to lower underpricing.

For example, book-building offers, where the underwriters pricing an IPO rely on information

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learned from potential investors, are underpriced more often outside of the U.S. in comparison

to fixed-price offerings (Ljungqvist, Jenkinson, and Wilhelm, 2003). Sherman (2005), however,

reports lower underpricing among bookbuilt deals.

More importantly, country-specific characteristics, such as a country‘s legal system,

regulatory environment, governance, investor protection, and ownership structure, play

important roles in explaining international IPO underpricing patterns. The number of IPOs is

positively associated with investor rights, the legal origin, and the law and order tradition of a

country (La Porta et al., 1997). The level of IPO underpricing also varies with a country‘s legal

framework. Using 2920 IPOs across 21 countries from 2000 to 2005, Engelen and van Essen

(2010) find that the quality of a country‘s legal framework, as measured by its level of investor

protection, the overall quality of its legal system, and its level of legal enforcement, reduces the

level of underpricing significantly. In the same vein, Boulton, Smart, and Zutter (2010) examine

4462 IPOs across 29 countries over the period 2000 to 2004 and find that underpricing is higher

in countries with corporate governance that strengthens the position of investors relative to

insiders.

2.3 Hypothesis Development

Hofstede‘s five cultural dimensions have been largely adopted in the international

business literature (Chui and Kwok, 2008; Chui et al., 2010; Han et al., 2010; Kwok and Tadesse,

2006). On the basis of a survey sample of IBM employees in the 1970s, Hofstede (2001) first

categorized national culture into four dimensions: uncertainty avoidance, collectivism,

masculinity, and power distance. In particular, the dimension of uncertainty avoidance

measures the level of acceptance of uncertainty and ambiguity within a society. A country with

a high uncertainty avoidance score is risk averse. In contrast, the dimension of collectivism

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focuses on the degree to which a society reinforces individual versus collective achievement and

interpersonal relationships. A country with a high collectivism score has strong relationships

between individuals and relies on collective responsibility. The dimension of masculinity

captures the degree of gender differences within a society. A high masculinity score indicates

that males in that country dominate the society and have much more control and power in the

society than females. Likewise, the dimension of power distance focuses on the degree of

equality/inequality between people within a society. A high power distance suggests that a

country accepts and perpetuates inequalities between individuals. Long-term orientation is

another dimension, developed later based on the Chinese Value Survey of students, which

covered only 23 countries. Long-term orientation emphasizes a forward-looking perspective.

However, because the long-term orientation dimension has a quite different sample coverage

when compared to the other four dimensions, it is not comparable to the other four.

Figure 1 illustrates the channels through which Hofstede‘s four cultural dimensions

affect IPO underpricing. The uncertainty avoidance dimension emphasizes rule-following.

When going public, the firm becomes subject to the many increased legal, regulatory, and

reporting requirements that most countries have surrounding the sale and trading of securities.

The rule-following managers of issuing firms are willing to disclose a sizable degree of financial

and operational detail, publish this information at least quarterly, comply with security

exchange rules and regulations, and comply with all of the specific operating and reporting

requirements of the exchange on which it is traded. Moreover, Hanley and Hoberg (2011)

document that either underpricing or enhanced disclosure is an efficient way to avoid lawsuit

risk after the IPO. To the extent that enhanced disclosure reduces asymmetric information

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problems between issuers, underwriters, and investors, we posit that the uncertainty avoidance

dimension is negatively associated with the level of underpricing.

The uncertainty avoidance dimension also focuses on risk-aversion behavior. Griffint et

al. (2010) identify Hofstede‘s (1980, 2001) uncertainty avoidance dimension as one of the three

most relevant culture values influencing corporate risk-taking behavior. They find that

managers or shareholders originating from countries with a higher degree of uncertainty

avoidance tend to minimize corporate risk-taking behavior. More importantly, issuers with a

higher uncertainty avoidance dimension are less tolerant of risk when going public. Therefore,

they prefer to signal their low-risk characteristics to the market by either hiring prestigious

investment bankers and auditors (Carter and Manaster, 1990; Carter et al., 1998) or by having

venture capital backed IPOs (e.g., Megginson and Weiss, 1991). The decision issuing firms make

on the choice of underwriters facilitates the understanding of IPO underpricing. The choice of

underwriter is determined by the issue‘s size and industry and the underwriter‘s quality and

prestige (Logue et al., 2002). The certain certification hypothesis (Carter and Manaster, 1990;

Carter et al., 1998) shows that IPOs with high-quality underwriters are less sensitive to the level

of underpricing. Moreover, the changing risk composition hypothesis (Ritter, 1984) suggests

that less-risky IPOs are less frequently underpriced than riskier IPOs. Accordingly, we posit

that the issuer‘s rule-following and risk-aversion behavior leads to a lower level of

underpricing. Formally, our first hypothesis is as follows:

H1. Issuing firms located in countries with a higher degree of uncertainty avoidance tend to experience a lower level of underpricing.

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The collectivism dimension focuses on group interests and strong ties between

individuals. Managers or shareholders originating from countries with a higher degree of

individualism (opposite of collectivism) tend to promote (reduce) corporate risk-taking

activities (Griffint et al., 2010). As a result, issuers in countries with higher collectivism attempt

to set a lower price and are eager to successfully sell shares when going public. In particular,

previous studies (Ljungqvist and Wilhelm, 2003) found that the managers of issuing firms had

an incentive to reallocate shares to their family and friends during the Internet bubble period

and thus made less of an effort to negotiate a higher offer price. Consistent with the realignment

of incentives hypothesis, we predict that there is a positive relationship between the

collectivism dimension and the level of underpricing.

Moreover, individualism is correlated with the exhibition of overconfidence or self-

attribution (Chui et al., 2010). One important implication of the growing literature on

managerial overconfidence suggests that overconfident managers overestimate the returns on

their investment activities (Malmendier and Tate, 2005), are more likely to initiate M&A

activities (Malmendier and Tate, 2005; Baker et al., 2011), and become more aggressive and

overbid after the success of a previous M&A deal (Aktas, de Bodt, and Roll, 2009). To the extent

that the overconfidence of the managers of issuing firms leads them to overestimate their

knowledge and the information they possess and to underestimate risks, we expect that the

issuers in individualist (collectivist) countries tend to have higher (lower) IPO underpricing.

Thus, our second testable hypothesis is stated as follows:

H2. Issuing firms located in countries with a high value for the collectivism dimension are likely to have a higher level of underpricing.

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The masculinity dimension indicates the degree of inequality between genders. Higher

masculinity scores emphasize male success, ambition, control, and power. The managers of

issuing firms in more masculine cultures are likely to seek achievement through increasing

private assets and profits when going public. According to the prospect theory (Kahneman and

Tversky, 1979), issuing firms located in countries with a high value of masculinity will be more

tolerant of excessive underpricing and make less effort to negotiate the offer price with

underwriters if they know they will earn higher post-market values (Loughran and Ritter,

2002). Furthermore, studies on the role of gender differences in risk preferences suggest that

males have a higher tendency than females to seek risky investment activities when making

financial decisions (Powell and Ansic, 1997). To the extent that masculinity is more likely to lead

to an exaggerated belief in the ability to control events and to more risk-seeking behavior when

going public, we should observe the positive relationship between masculinity and

underpricing. Hence, our third hypothesis is as follows:

H3. Issuing firms in countries characterized by a higher degree of masculinity tend to experience a higher level of underpricing.

The power distance dimension measures the degree of differences and inequalities

between people. A large inequality in the context of social distribution suggests lower social

trust and limited upward mobility from the lowest caste to the highest caste (Bjornskov, 2008).

Reduced social trust reinforces the agency conflict of interest between issuers, underwriters,

and investors. As a result, issuing firms located in countries with high power distance scores

exhibit a reduced level of social trust and thus limit the issuing firms‘ ability to select an

appropriate underwriter due to the agency conflict of interest between the issuers and the

underwriters. Moreover, a society with a high power distance score is also characterized by

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centralized authority and is more likely to exhibit a high level of opportunism for personal gain.

Thus, high-quality issuing firms with a high value for power distance are willing to signal their

quality by setting a lower offering price as a strategy to distinguish themselves from firms with

low quality and to attract more investors (Allen and Faulhaber, 1989; Grinblatt and Huang,

1989; Welch, 1989). Consistent with Chambers and Dimson (2009), we assert the positive

relationship between power distance and underpricing. Therefore, our fourth hypothesis is as

follows:

H4. Issuing firms in countries with higher power distance scores are more associated with a higher level of underpricing.

3. Data and Variables

3.1 Data and Sample Selection

We construct our sample from three sources: (1) national culture values retrieved from

Hofstede‘s (2001) cultural indices, Schwartz‘s (1994) cultural indices, and the GLOBE database

created by House et al. (2004); (2) IPOs issued from 1980 to 2009 obtained from Thomson

Financial‘s SDC Platinum New Issues database; and (3) relevant IPO price and volume data

derived from Datastream.

We retrieved IPOs issued over the period from 1980 to 2009 from Thomson Financial‘s

SDC Platinum New Issues database, omitting countries with fewer than five IPOs and without

Hofstede‘s four cultural values. We merged these IPOs with their corresponding cultural

values, resulting in a final sample of 19,420 IPOs listed in 44 countries. Our sample captures the

most countries studied compared to previous literature (Barth, Caprio, and Levine, 2006;

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Djankov, Mcliesh, and Shleifer, 2007; Djankov et al., 2008; La Porta et al., 1998; La Porta, Lopez-

de-Silanes, and Shleifer, 2006).

3.2 Variables

This study investigates whether national culture influences IPO underpricing. Table 1

summarizes the definitions and the data sources for all of the variables used in our empirical

analyses.

An IPO is underpriced if the first-day closing price in the secondary market is higher

than the final offer price. Following this initial return definition, we calculate the key dependent

variable – IPO underpricing or the initial return – as the first-day secondary market closing

price divided by the final offer price minus 1.

Prior studies (e.g., Griffin et al., 2010) show strong empirical evidence that Hofstede‘s

uncertainty avoidance and individualism are two of the most relevant culture values

influencing corporate risk-taking. In an attempt to explain whether national culture affects IPO

underpricing, we use the widely adopted cultural values from Hofstede‘s (2001) cultural

indices—uncertainty avoidance, collectivism, masculinity, power distance, and long-term

orientation—as proxies for cultural values.

To better understand the effect of national culture on IPO underpricing, it is important

to control for other relevant firm- and country-level variables. Prior literature, Boulton, Smart,

and Zutter (2010) and Engelen and van Essen (2010), among others, considers certain firm-,

issue-, and country-level characteristics to be associated with international IPO underpricing.

Specifically, we include the firm-level variables offer size, integer offer price, bookbuilt deals,

offering technique, secondary shares, equity carve-out IPOs, privatization, underwriter

19

reputation, the involvement of a venture capitalist, high-tech firms, and stock return volatility.

We also control for country-level variables, including stock market turnover, bank ownership,

inflation, and ratio of market capitalization to GDP. The year of the IPO launch is considered in

all regressions to capture hot market effects (Ritter, 1984). Brief descriptions of all firm- and

country-level control variables are as follows.

At the firm level, following Boulton, Smart, and Zutter (2010) and Engelen and van

Essen (2010), among others, our control variables include the following: offer size, expressed as

the log of the offer proceeds (in millions of US$) to capture the size effect because a negative

relationship between offer size and underpricing has been strongly confirmed by Beatty and

Ritter (1986), Mauer and Senbet (1992), and Boulton, Smart, and Zutter (2010); integer offer

price, an indicator variable set to 1 if the final offer price is an integer; bookbuilt, an indicator

variable equals 1 if the method of pricing IPO shares uses bookbuilt offers; firm commitment, an

indicator variable set to 1 if the offering technique is provided by firm commitment offerings;

secondary shares, defined as the ratio of the number of secondary shares outstanding to the

total shares outstanding issued on the market; equity carve-out, an indicator variable equal to 1

for equity carve-out IPOs; privatization, an indicator variable equal to 1 for privatizations;

underwriter reputation, measured similarly to the methods of Megginson and Weiss (1991) and

Boulton et al. (2010) as the fraction of the total offer value underwritten by a given underwriter

for a country; venture capitalist, an indicator variable set to 1 for venture capital backed IPOs;

high-tech dummy, an indicator variable set to 1 if the IPO is a high technology firm; and stock

market volatility, an ex post measure equal to the standard deviation of the daily return over

the three months following the IPO.

20

At the country level, we control for stock market turnover, bank ownership, inflation,

and the ratio of market capitalization to GDP. In particular, stock market turnover is similar to

that measured by Boulton et al. (2010) and is reported in Beck et al. (2000); bank ownership is an

indicator variable set to 1 for countries that allow banks to own 100% of the equity of

nonfinancial firms and to 0 for countries that limit bank ownership to less than 100% or that do

not permit banks to own shares in nonfinancial firms; inflation is from the World Bank

indicators from 1980 through 2009; ratio of market capitalization to GDP is defined as the

average ratio of stock market capitalization to GDP from 1999 through 2003.

3.3 Descriptive Statistics

Table 2 summarizes the descriptive statistics for the main variables used in our sample.

The variables initial return, offer size, secondary shares, underwriter reputation, stock return

volatility, and stock market turnover are winsorized at the 1st and 99th percentiles to reduce

outlier effects. Panel A reports the mean, median, 25th percentile, 75th percentile, and standard

deviations of all firm- and country-level control variables. For each IPO over our sample period,

underpricing is approximately 34.12 (7.26%) for the average (median) IPO. The average offer

size is $20.09 million. In comparison to the previous study by Boulton, Smart, and Zutter (2010)

in their sample of 4,462 international IPOs for the period from 2000 to 2004, in our sample, 60%

(54.9%)3 of the IPOs have an integer price expressed in local currency; 57% (64.8%) of the firms

go public through a bookbuilt offering; 59% (60.9%) of the IPOs are firm commitment offerings;

14% (14.2%) of the total shares are sold by pre-IPO shareholders; 4% (4.4%) of the sample firms

go public as part of an equity carve-out; 2% (1.1%) of the sample IPOs involve privatization; 2%

3 To allow easier comparison, the numbers in parentheses are from the previous study by Boulton, Smart, and Zutter (2010).

21

(8.6%) of the market shares in a country are held by the lead underwriter; and 8% (4.1%) of the

stock return volatility is observed following the issuing, on average, respectively. In addition,

on average, 36% of our sample IPOs were for high-technology firms, 15% are backed by venture

capital firms, and 36% are issued in countries that do not restrict bank ownership. The average

stock market turnover of 0.97 suggests that the value of shares traded in a year for our sample is

slightly below the aggregate value of shares in the market. The average score in the uncertainty

avoidance dimension is 55.18, which is somewhere in the middle, indicating that the countries

represented are risk-neutral on average. For the collectivism dimension, the average score of

39.34 reflects that countries in our sample have slightly lower group interests on average. The

average score of 60.24 for masculinity suggests that our sample countries experience above

average male achievement, control, and power. The average scores of power distance and long-

term orientation are 52.92 and 52.41, suggesting that there is a moderate degree of inequality

between people and forward-looking perspectives, respectively, for our sample countries.

Panel B in Table 2 shows the distribution of the IPOs across countries, underpricing on

average, various national culture values, and alternative country characteristics for each county

in our sample. Among the 44 countries, 29.22% of the IPOs are issued by the U.S., while 10.92%

of the IPOs are issued by Japan, followed by Australia (6.84%). However, China became the

fourth largest country issuing IPOs (6.80%) during the 1980-2009 period, followed by Canada

(4.24%), Taiwan (4.12%), South Korea (3.84%), and France (3.74%). The three countries with the

highest underpricing are Chile (99.79%), Hungary (99.76%), and China (96.67%), while the three

countries with the lowest underpricing are Mexico (0.94%), Luxembourg (4.64%), and Spain

(9.67%). Interestingly, the countries‘ scores on different cultural dimensions are widely

distributed. For instance, the U.S. takes the lowest score on collectivism (9), whereas Indonesia

22

and Pakistan have the highest collectivism score (86), suggesting that people in the U.S. focus

less on group interests in general. The highest score in the masculinity dimension is attributed

to Japan (95), suggesting that Japan is the country with the highest inequality between genders.

The highest score in the uncertainty avoidance dimension belongs to Greece (112), indicating

that people in Greece are the most risk averse. In terms of power distance, Malaysia is the

country characterized by the highest inequality between people and featured the strongest

centralization of authority in our sample. Hofstede‘s long-term orientation dimension based on

the Chinese Value Survey of students was developed later than the other four dimensions and

covers only 23 countries. Therefore, this dimension has a quite different sample coverage when

compared to the other four dimensions. We only have values for the long-term orientation

dimension for 22 countries. Among our sample, China has the highest score in the long-term

orientation dimension (118), suggesting the highest forward-looking perspective is in China.

Panel C in Table 2 provides correlations among underpricing, national cultural values,

and various firm- and country-level characteristics for the sample of individual firms.

Underpricing is positively associated with all of Hofstede‘s five cultural dimensions. Among all

firm- and country-level control variables, underpricing is negatively correlated with bank

ownership (-0.05), ratio of market capitalization to GDP (-0.19), offer size (-0.13), integer offer

price (-0.08), bookbuilt (-0.12), firm commitment (-0.10), secondary shares (-0.07), equity carve-

out (-0.03), and privatization (-0.01) and is positively correlated with underwriter reputation

(0.03), venture capitalist (0.02), high-tech dummy (0.05), stock return volatility (0.09), stock

market turnover (0.04), and inflation (0). Within the Hofstede cultural measures, uncertainty

avoidance is positively correlated with collectivism (0.25), masculinity (0.46), power distance (-

0.04), and long-term orientation (0.29). However, there is a very low degree of negative

23

(positive) correlation between masculinity and collectivism (-0.06) (power distance (0.01)). It is

noteworthy that in our sample the correlation coefficient between collectivism and power

distance is 0.85, whereas the correlation coefficient between collectivism and long-term

orientation is also 0.85. Our findings suggest that including both the power distance and the

long-term orientation dimensions into the other three cultural dimensions in our regression

specifications might lead to problems with multicollinearity.

4. Empirical Analysis and Results

We start our empirical analysis with two baseline cross-sectional regression

specifications to identify the most relevant firm- and country-level controls to explain

international underpricing. We then examine our hypotheses by sequentially introducing each

of the five single cultural dimensions and multiple cultural dimensions.

4.1 Baseline Cross-sectional Regression Specifications

Prior studies, such as those by Boulton, Smart, and Zutter (2010) and Engelen and van

Essen (2010), show that both firm- and country-level characteristics have a strong influence on

the level of underpricing. To ensure that the impact of cultural values is not driven by the

relationship of the underpricing with these characteristics, we use the most relevant set of firm-

and country-level characteristics as control variables. Therefore, we regress the initial return

against the firm-level characteristics offer size, integer offer price, bookbuilt dummy, firm

commitment, secondary shares, equity carve-out dummy, privatization dummy, underwriter

reputation, venture capitalist dummy, high-tech dummy, and stock return volatility. We also

regress the initial return against the country-level characteristics stock market turnover, bank

ownership dummy, inflation and ratio of market capitalization to GDP, including the firm-level

24

varaibles. In all of the model specifications, we include time dummy variables to control for

time effects and an industry dummy.

Table 3 reports our main evidence regarding the impact of national culture on IPO

underpricing. In column (1), we include only firm-level control variables. We find that IPOs that

involve a venture capitalist and are in a high-technology industry with a higher underwriter

reputation and higher after-market volatility experience higher underpricing. In contrast, IPOs

that are bookbuilt deals with larger offer proceeds, an integer offering price, a firm-commitment

offering, and secondary shares experience significantly lower underpricing. The estimates for

equity carve-out and privatization are insignificant. In column (2), we add a set of country-level

variables. Higher underpricing is associated with a higher stock market return turnover, more

restrictions on banks‘ ownership, and a lower ratio of market capitalization to GDP. The signs

and significance of the coefficients on most firm-level control variables are consistent with those

in column (1), except that the IPOs with equity carve-out become significant and IPOs with

secondary shares become insignificant. The coefficient on inflation is insignificant. Our basic

regression results, shown in columns (1) and (2), demonstrate that the effects of firm- and

country-level control variables on IPO underpricing are consistent with prior studies (Boulton,

Smart, and Zutter, 2010; Engelen and van Essen, 2010).

4.2 Effects of Various Cultural Values on IPO Underpricing

Using the Hofstede measures as proxies for national culture, the main aim of our paper

is to examine whether cultural values influence the level of IPO underpricing across countries.

For columns (3) through (7) in Table 3, we sequentially add Hofstede‘s five cultural dimensions

(uncertainty avoidance, collectivism, masculinity, power distance, and long-term orientation).

25

We also find that the signs of the coefficients of the control variables in each of these regressions

are consistent with those in our baseline regressions.

In column (3), the coefficient of uncertainty avoidance is negative and statistically

significant at the 1% level. This evidence suggests that issuing firms in countries with a higher

degree of uncertainty avoidance tend to experience lower initial day returns. One possible

explanation of this finding is that higher uncertainty avoidance scores imply a lower degree of

risk tolerance. Issuing firms located in countries with a high uncertainty avoidance score tend to

have less tolerance for risk, try to avoid unknown situations, and prefer secure rather than risky

activities when going public. As a result, the presence of certain formal certifications, such as

prestigious investment bankers, auditors, and venture capitalists, might certify that the offering

price is set to fully reflect the firms‘ true value and might serve to lower the level of

underpricing (e.g., Megginson and Weiss, 1991). The changing risk composition hypothesis

(Ritter, 1984) also suggests that less-risky IPOs are less underpriced than are riskier IPOs.

Consistent with prior research explaining IPO underpricing, we show that IPOs in countries

with high uncertainty avoidance scores who have less risk tolerance are more likely to have

lower initial day returns.

In column (4), in contrast, the coefficient of collectivism is positive and statistically

significant at the 1% level, suggesting that issuing firms located in countries with a higher

degree of collectivism tend to experience higher initial day returns. A possible interpretation of

this finding is that high collectivism scores indicate group interests and stronger ties between

individuals. Consequently, issuing firms in a high collectivism society are willing to set a lower

price in an attempt to successfully sell their shares during the process of the IPO. In particular,

the managers of the issuing firms were more likely to reallocate shares to their family and

26

friends during the Internet bubble period. The realignment of incentives (Ljungqvist and

Wilhelm, 2003) makes managers of issuing firms expend less effort to bargain a higher offer

price. Consistent with the realignment of incentives hypothesis, we find a positive relationship

between collectivism and the initial day return.

In column (5), the coefficient of masculinity is positive and statistically significant at the

1% level, indicating that issuing firms in countries with a higher degree of masculinity tend to

have higher initial returns. A possible interpretation of this finding is that individuals in a

society characterized by high masculinity emphasize success, control, and power. Managers of

issuing firms always seek personal success by increasing their profits and assets. According to

the prospect theory (Kahneman and Tversky, 1979; Loughran and Ritter, 2002), the positive

relationship between masculinity and the initial day return is observed. Furthermore, studies on

gender differences in risk preferences suggest that males have a higher tendency than females

to seek risky investment activities when making financial decisions (Powell and Ansic, 1997).

This risk-seeking behavior characterized by high masculinity creates the positive relationship

between masculinity and the initial day return.

In column (6), the coefficient of power distance is positive and statistically significant at

the 1% level, indicating that issuing firms in countries with a higher degree of power distance

tend to have higher initial returns. One possible explanation for this finding is that higher

power distance scores indicate large differences and inequalities between people. This large

inequality in the context of social distribution, in turn, suggests lower social trust (Bjornskov,

2008). According to Chambers and Dimson (2009), IPO underpricing is negatively associated

with the level of trust. As a result, reduced social trust induced by a high power distance

suggests a positive relationship between power distance and the initial day return.

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In column (7), the coefficients of long-term orientation countries are positive and

statistically significant at the 1% level, indicating that issuing firms in countries with a higher

degree of long-term orientation tend to have higher initial returns. As Zheng et al. (2011)

suggested, the impact of the Long-term orientation dimension on corporate debt maturity is still

an empirical question due to the argument that ―high long-term debt orientation is positively

related to personal adaptability and the adaptability of tradition to new circumstances, a more

forward-looking perspective.‖ Given the reduced sample coverage (22 countries), when

compared to the other four cultural dimensions, we should be careful when interpreting this

finding despite the positive relationship between long-term orientation and the initial return.

In columns (8) and (9), we examine the impact of the combined cultural dimensions on

the initial day return. Specifically, in column (8), the signs and significance of the coefficients for

all four cultural dimensions are consistent with those from the estimations for the single

cultural dimension. However, including long-term orientation in column (9), we find that the

signs and significance of the coefficients of collectivism and power distance change when

compared to those from the estimations of the single cultural dimension. One possible

explanation is that multicollinearity among the independent variables, for example the

correlation coefficient between collectivism and long-term orientation of 0.85, may cause

coefficient estimates with unexpected signs and significance (Greene, 2003 p.57).

5. Robustness Checks

5.1 Additional Country-level Governance

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To mitigate concerns that our findings are sensitive to potential country-level

governance quality4 controls addressed in the prior literature (Smart, and Zutter, 2010; Engelen

and van Essen, 2010), we examine the robustness of our results to additional controls for

governance quality.

Traindis (2001) considers the individualism (the opposite of collectivism) dimension as

the most significant cultural difference across countries. Moreover, as discussed above, the

long-term orientation dimension is based on a different sample selection criterion than the other

four cultural dimensions (uncertainty avoidance, collectivism, masculinity, and power distance)

and causes multicollinearity in the multivariate estimation. Thus, we only consider each

additional governance control for the four single most relevant cultural dimensions in the

robustness check.

To assess the cross-country differences, we first control for the quality of a country‘s

legal system. Specifically, the set of country-level governance quality control variables includes

the following: anti-self dealing index (Djankov, La Porta, Lopez-de-Silanes, and Shleifer, 2008),

defined as the average of ex-ante and ex-post private control of self-dealing, where the former

represents the average of approval by disinterested shareholders and ax-ante disclosure, and

the latter is the average of disclosure in periodic filings and the ease of proving wrongdoing;

anti-self dealing public enforcement (La Porta et al., 2006), defined as an index of public

enforcement rating if all disclosure and approval requirements have been met, in which one

quarter point is assigned for each when (1) fines for the approving body, (2) jail sentences for

4 It is noteworthy that Chile, China, Hong Kong, Hungary, Luxembourg, Macao, Norway, Pakistan, Poland, Turkey, and Vietnam are included in our sample, which are not in the samples of Boulton, Smart, and Zutter (2010) and Engelen and van Essen (2010), although we do not have data on some control variables, such as disclosure, anti director rights, and prospectus liability for these countries.

29

the approving body (3) fines for Mr. James, and (4) jail sentence for Mr. James are present;

creditor rights (Djankov, McLiesh, and Shleifer, 2007), measured with an aggregate score

ranging from 0 (weak creditor rights) to 4 (strong creditor rights) and constructed as of January

for every year from 1978 to 2003; and rule of law (La Porta, Lopez-de-Silanes, and Shleifer,

2002), as the average for the months of April and October of the monthly index measured

between 1982 and 1995 and scaled from 0 to 6, where lower scores indicate less law and order

tradition.

Other measures of investor protection include the revised anti-director rights index

(Djankov et al. 2008), the high private benefits indicator (Dyck and Zingales, 2004), preemptive

rights (La Porta et al. 2006), tax evasion (World Economic Forum, 2003), and bounced checks

(Djankov et al., 2003a). The anti-director rights index is an aggregate index of shareholder rights

and is formed by summing the following: (1) votes by mail; (2) shares not deposited; (3)

cumulative voting; (4) oppressed minorities; (5) pre-emptive rights; and (6) capital required to

call a meeting. High private benefits is an indicator variable equal to 1 for IPOs listed in a

sample country with an above-median private benefit of control value as reported by Dyck and

Zingales (2004) and 0 otherwise. The preemptive rights variable is an indicator equal to 1 if

investors have preemptive rights in a country and 0 otherwise. Tax evasion is an assessment of

the prevalence of tax evasion, where higher scores indicate higher tax evasion, and the data

ranges from 0.94 to 8.54 for 2001. The bounced checks measure is defined as the logarithm of the

length (in calendar days) for the judicial procedure to collect on a bounced check.

Prior literature (Hope, 2003; Han et al., 2010; Fidrmuc and Jacob, 2010; Engelen and van

Essen, 2010) finds strong empirical evidence that the cultural dimensions behave differently

across legal regimes in multivariable specifications. To better isolate the influence of cultural

30

values on IPO underpricing, we consider the control variable – legal origin (La Porta et al., 1998)

– measured as the binary variables (1) English Common Law, (2) French Commercial Code, (3)

German Commercial Code, (4) Scandinavian Commercial Code, and (5) Socialist/Communist

Laws. These variables identify the legal origin of the company law or commercial code of each

country.

Table 4 presents the robustness results. In columns (1) though (10) of Panel A, by

sequentially controlling for each country-level governance quality, we find that the coefficients

of uncertainty avoidance are negative and statistically significant at the 1% level, except that the

coefficient of uncertainty avoidance is negative and significant at the 10% level after controlling

for the high private benefits indicator. Similarly, in columns (1) through (10) of Panel B, C, and

D, we find that the coefficients of collectivism, masculinity, and power distance are all positive

and significant at the 1% level. The signs and significance of the coefficients on the firm- and

country-level control variables are consistent with the results in Table 3. These results suggest

that the signs and the significance of the coefficients for all four cultural dimensions are

consistent with our hypothesis even after controlling for the governance quality variables.

Moreover, the coefficients for the anti-self dealing and high private benefits indicators are

positive and statistically significant at the 1% level in all four panels, suggesting that higher

underpricing is positively associated with IPOs in countries with anti-self dealing and above-

median private benefit of control value. In contrast, the coefficients of preemptive rights and

anti-director rights are negative and statistically significant at the 1% level in all four panels,

suggesting that higher underpricing is negatively associated with preemptive rights and anti-

director rights. However, the estimates for anti-self dealing public enforcement, rule of law,

creditor rights, bounced checks, and legal origin are inconsistent in all four panels.

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5.2 Alternative Measures of National Culture

Although Hofstede‘s five cultural dimensions are widely adopted as proxies of cultural

values, following Shao, Kwok, and Guedhami (2010), we also consider alternative sources of

data on cultural values from Schwartz (1994) and from the GLOBE database created by House

et al. (2004), as robustness checks to examine whether our main results are sensitive to the

choice of cultural values.

On the basis of a survey sample of teachers and students, Schwartz (1994) classifies

national culture into seven dimensions: conservatism vs. affective autonomy and intellectual

autonomy, mastery vs. harmony, and hierarchy vs. egalitarian commitment. Following Chui,

Lloyd, and Kwok (2002) and Shao, Kwok, and Guedhami (2010), among others, these seven

dimensions can be further categorized into two major dimensions: conservatism and mastery.

The conservatism dimension captures group interests, such as family security, public image,

and self-discipline, whereas the mastery dimension captures individual interests, such as

success, ambition, and independence. These two major cultural dimensions are the most

relevant to finance theories when examining the capital structure decisions of domestic firms

(Chui, Lloyd, and Kwok, 2002), dividend theories (Shao, Kwok, and Guedhami, 2010), and the

capital structure decisions of foreign joint ventures (Li et al., 2011). House et al. (2004) grade

national culture with nine dimensions, each with a score on value (i.e., desired practice) and a

score on belief (i.e., actual practice). According to Shao, Kwok, and Guedhami (2010), in

particular, Hofstede‘s collectivism and GLOBE‘s institutional collectivism are respective

substitutes for Schwartz‘s conservatism dimension, whereas Hofstede‘s masculinity and

GLOBE‘s assertiveness are relevant counterparts of Schwartz‗s mastery dimension. However, a

current study by Brewer and Venaik (2011) suggests that Hofstede‘s collectivism dimension is

32

more closely associated with GLOBE‘s in-group collectivism rather than with the institutional

collectivism dimension. Therefore, in our robustness tests, we use Schwartz‘s conservatism,

mastery, and hierarchy and GLOBE‘s in-group collectivism, assertiveness, and power distance

to mirror Hofstede‘s collectivism, masculinity, and power distance, respectively.

In addition to the similarity captured by the three sources of data, Hofstede, Schwartz,

and GLOBE, on national culture, all three main measures of cultural values also differentiate on

the basis of the sample selection criteria and the sample period in the survey. For instance,

Hofstede (2001) survey IBM employees in the 1970s; Schwartz (1994) survey a sample of

teachers and students; and House et al. (2004) develop their measures from responses to

questionnaires from about 17,000 managers from 951 organizations in 62 countries over a 10-

year research program. Therefore, emphasizing all three main measures of culture values

enables us to more thoroughly investigate their effects on IPO underpricing.

Table 5 presents results of the regressions of the IPO‘s initial returns using Schwartz‘s

(1994) three corresponding cultural dimensions (conservatism, mastery, and hierarchy),

GLOBE‘s three corresponding cultural dimensions (in-group collectivism, assertiveness, and

power distance), and other firm- and country-level control variables. In columns (1) through (3),

we introduce each of Schwartz‘s three cultural proxies sequentially; in columns (4) though (6),

we highlight three of GLOBE‘s cultural dimensions in each column. The coefficients of

Schwartz‘s conservative dimension in column (1) and GLOBE‘s in-group collectivism

dimension in column (4) are negative and statistically significant at the 1% level. The signs and

significance of the coefficients for Schwartz‘s conservative and GLOBE‘s in-group collectivism

dimensions are consistent with those for Hofstede‘s collectivism dimension. These results

suggest that issuing firms located in countries characterized by high collectivism (Hofstede),

33

conservatism (Schwartz), and in-group collectivism (GLOBE) are more likely to experience a

higher level of underpricing. Likewise, the coefficients of Schwartz‘s mastery dimension in

column (2) and GLOBE‘s assertiveness dimension in column (5) are positive and statistically

significant at the 1% level. The signs and significance of the coefficients of Schwartz‘s mastery

and GLOBE‘s assertiveness dimensions are consistent with those of Hofstede‘s masculinity

dimension. These results suggest that the issuing firms located in countries characterized by

high masculinity (Hofstede), mastery (Schwartz), and assertiveness (GLOBE) are more likely to

experience a higher level of underpricing. Similarly, the coefficients of Schwartz‘s hierarchy

dimension in column (2) and GLOBE‘s power distance in column (5) are positive and

statistically significant at the 1% level. The signs and significance of the coefficients of

Schwartz‘s hierarchy and GLOBE‘s power distance dimensions are consistent with those of

Hofstede‘s power distance dimension. These results suggest that issuing firms located in

countries with high power distance (Hofstede), hierarchy (Schwartz), and power distance

(GLOBE) scores are more likely to experience a higher level of underpricing. Our findings are

consistent with the evidence in Section 5.2, suggesting that our primary results are robust to

alternative measures for cultural values.

5.3 Excluding U.S. IPOs

Prior studies on international IPO underpricing, including Engelen and van Essen

(2010), among others, have raised a concern about sample bias, pointing out that the U.S.

accounts for over 50% of the worldwide IPOs. To mitigate the concern that our primary results

are driven by the U.S. subsample, we re-examine our main tests by excluding the U.S. IPOs.

Table 6 presents the results. In columns (1) through (8), the signs and significance of the

coefficients of all five single and combined cultural dimensions remain consistent with those in

34

Table 3, suggesting that the uncertainty avoidance dimension is negatively associated with IPO

underpricing, whereas the collectivism, masculinity, power distance, and long-term orientation

dimensions are positively associated with IPO underpricing. These results suggest that our

primary results are robust to alternative subsample estimation.

6. Summary and Conclusions

This paper documents a significant relation between culture values and the level of IPO

underpricing. Using the Hofstede four cultural dimensions, uncertainty avoidance, collectivism,

masculinity, and power distance, we find strong evidence that the concept of culture plays an

important role on explanation of international IPO underpricing. More importantly, IPOs in

countries with high uncertainty avoidance scores tend to experience a lower level of

underpricing whereas IPOs in countries with higher collectivism, masculinity, and power

distance tend to experience a higher level of underpricing. Our results are robust because we

control for various determinants of international IPO underpricing, including a country‘s legal

system, investor protection, private control benefits, regulations in bank ownership, tax

advantage, and stock market performance, and with respect to alternative culture proxies and

sub-period samples.

A possible explanation for our results is that different cultural dimensions emphasize

different aspects of human perceptions and behaviors. First, the uncertainty avoidance

dimension emphasizes rule-following in face of unknown situations. The managers of issuing

firms are most likely to disclose all information required by rules and regulations in the process

of IPO. This enhancing disclosure facilitates to mitigate asymmetric information between the

issuers, underwriters, and investors. Consistent with Hanley and Hoberg (2011), we find the

negative relationship between the uncertainty avoidance dimension and the level of IPO

35

underpricing. Moreover, higher uncertainty avoidance scores also imply less degree of risk

tolerance. The managers of issuing firms located in high uncertainty avoidance score society

tend to have less tolerance of risk, try to avoid any unknown situations, and attempt to signal

their low risk to the market when going public. Following certain formal certifications

hypothesis (Booth and Smith, 1986), we suggest that issuing firms in countries with higher

value of uncertainty avoidance are more likely to hire a high-quality underwriter with certain

form certifications and thus are less underpriced. Further, the changing risk composition

hypothesis (Ritter, 1984), according to which less-risky IPOs are less underpriced than riskier

IPOs, suggests the negative relationship between uncertainty avoidance and underpricing of

IPOs.

Second, the collectivism dimension focuses on group interests and has stronger ties

between individuals. Issuing firms in a high collectivism society are willing to set a lower price

in an attempt to successfully sell their shares during the process of the IPO. In particular, the

managers of the issuing firms were more likely to reallocate shares to their family and friends

during the Internet bubble period, thus, make expend less effort to bargain a higher offer price

(Ljungqvist and Wilhelm, 2003). Consistent with the realignment of incentives hypothesis, we

find a positive relationship between collectivism and IPO underpricing.

Third, the masculinity dimension emphasizes individual interests such as personal

ambition, success, and control. Issuers with higher masculinity focus on individual achievement

and exhibit risk-seeking behaviors in making financial decision (Powell and Ansic, 1997). This

risk-seeking behavior characterized by high masculinity induces the positive relationship

between the masculinity dimension and IPO underpricing. Moreover, according to the prospect

theory (Kahneman and Tversky, 1979), the managers with high masculinity are more tolerant of

36

excessive underpricing if they know that their wealth increases after the IPO (Loughran and

Ritter, 2002). Consistent above views, we find the positive relationship between the masculinity

dimension and IPO underpricing.

Finally, the power distance dimension focuses on the differences and inequalities

between people. The large inequality indicates lower social trust (Bjornskov, 2008). A reduced

social trust reinforces agency conflict of interest between issuers, underwriters, and investors.

Consistent with Chambers and Dimson (2009), IPO underpricing is mitigated by trust, we find

strong positive relationship between the power distance dimension and IPO underpricing.

Our results are consistent with the growing literature in supporting the importance of

national culture on corporate financial policies and decision makings (Chui, Lloyd, and Kwok,

2002; Li et al., 2011; Fidrmuc and Jacob, 2010; Shao, Kwok, and Guedhami, 2010; Griffin et al.,

2010; Hope, 2003; Han et al., 2010; Ahern et al., 2011; Zheng et al., 2011). Since managers or

shareholders in high uncertainty avoidance countries are willing to take a lower risk in

corporate investment activities (Griffin et al., 2010), they are less tolerant of risk, and, as we

show here, less IPO underpricings. However, the managers of issuing firms in countries with

high collectivism, masculinity, and power distance are eager to undertake IPOs successfully and

willing to reallocate shares to family and friends (Ljungqvist and Wilhelm, 2003), exhibit more

risk-seeking behavior (Powell and Ansic, 1997), and lower social trust between issuers,

underwriters, and investors (Chambers and Dimson, 2009), therefore, high underpricing of

IPOs.

37

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Figure 1 Effects of national culture on IPO underpricing

Hofstede‘s four cultural dimensions

High Uncertainty avoidance Higher Collectivism Higher Masculinity Higher Power distance

Rule-following Less risk tolerance Group interests Achievement Ambition Larger inequalities

between people

Enhancing

disclosure

as required

by security

exchange

rules and

regulations

Relatively

lower risk

IPOs

Attempt to

signal their

low risk to

the market

Lower underpricing

Eagerness to

have a

successful

IPO

Incentive to

reallocate shares

to family and

friends

Managers make less effort to

negotiate the offer price

Incentive to

earn post-

market value

Exhibit more

risk-seeking

behavior

Lower social trust

between issuers,

underwriters, and

investors

Higher underpricing Higher underpricing Higher underpricing

Formal certification hypothesis

Changing risk composition hypothesis

Changing risk composition hypothesis

Prospect theory Chambers & Dimson (2009)

Realignment of

incentives

Hanley &

Hoberg (2011)

Prestigious investment bankers and auditors, and venture capital backed IPOs

43

Table 1 Description of the variables

Variables Description Source

A: Measure of IPO Underpricing

Initial return The first-day secondary market closing price divided by the final offer price minus 1. SDC database & Datastream

B: Measures of Culture Values

Uncertainty avoidance Hofstede's culture index on Uncertain Avoidance. Hofstede (2001)

Collectivism Hofstede's culture index on Collectivism (the opposite of Individualism). Hofstede (2001)

Masculinity Hofstede's culture index on Masculinity. Hofstede (2001)

Power Distance Hofstede's culture index on Power Distance. Hofstede (2001)

Long-term Origntation

Hofstede's culture index on Long-term Orientation. Hofstede (2001)

Conservatism Schwartz's culture index on Conservatism. Schwartz (1994)

Mastery Schwartz's culture index on Mastery. Schwartz (1994)

Hierarchy Schwartz's culture index on Hierarchy. Schwartz (1994)

Collectivism GLOBE's culture index on As-is In group Collectivism. House et al. (2004)

Assertiveness GLOBE's culture index on Should-be Assertiveness. House et al. (2004)

Power Distance GLOBE's culture index on Should-be Power Distance. House et al. (2004)

C: Firm-level Control Variables

Offer size The log of the offer proceeds (in mils of US$). SDC database

Integer offer price An indicator variable equals 1 for integer-priced IPOs and 0 otherwise. SDC database

Bookbuilt An indicator variable equals 1 if the method of pricing IPO shares is bookbuilt offers and 0 otherwise.

SDC database

Firm commitment An indicator variable equals 1 for firm-commitment IPOs and 0 otherwise. SDC database

Secondary shares The fraction of shares being offered that were issued and outstanding prior to the IPO.

SDC database

Equity carve-out An indicator variable equals 1 for equity carve-out IPOs and 0 otherwise. SDC database

Privatization An indicator variable equals 1 for privatizations and 0 otherwise. SDC database

Underwritter reputation

The fraction of IPO proceeds underwritten by a particular underwriter in a particular country, similar to the method proposed by Megginson and Weiss (1991).

SDC database

44

Venture capitalist An indicator variable equals 1 for firms with a venture capitalist as an early investor and 0 otherwise.

SDC database

High-tech dummy An indicator variable equals 1 for the IPOs of technological firms and 0 otherwise SDC database

Stock return volatility An ex-post measure equal to standard deviation of daily returns over the three months following the offering.

Datastream

D: Country-level Control Variables

Stock market turnover The ratio of the total value of shares traded to aggregate market capitalization. SDC database & Beck et al. (2000)

Bank ownership An indicator variable equals 1 for countries that allow banks to own 100% of the equity of nonfinancial firms and 0 otherwise.

Barth et al. (2006)

Inflation World Bank indicators from 1980 through 2009. World Bank

Ratio of MCAP to GDP

Average of the ratio of stock market capitalization to gross domestic product for the period 1999-2003. Source: World Development Indicators at http://devdata.worldbank.org/dataonline/.

La Porta et al. (2006)

E: Additional Country-level Governance Control Variables

Antidirector rights Aggregate index of shareholder rights, the index is formed by summing: (1) vote by mail; (2) shares not deposited; (3) cumulative voting; (4) oppressed minority; (5) pre-emptive rights; (6) capital to call a meeting.

Djankov et al. (2007)

Anti-self dealing Average of ex-ante and ex-post private control of self-dealing, where the former represents the average of approval by disinterested shareholders and ax-ante disclosure and the latter is the average of disclosure in periodic filings and ease of proving wrongdoing.

La Porta et al. (2006)

Anti-self dealing public enforcement

Index of public enforcement if all disclosure and approval requirements have been met. Ranges from 0 to 1. One quarter point when each of the following sanctions is available: (1) fines for the approving body; (2) jail sentences for the approving body; (3) fines for Mr. James; and (4) jail sentence for Mr. James.

La Porta et al. (2006)

Rule of law Average of the month of April and October of the monthly index between 1982 and 1995 scaled from 0 to 6, where lower scores indicate less tradition for law and order.

La Porta et al. (2002)

Creditor rights Aggregate score ranged from 0 (weak creditor rights) to 4 (strong creditor rights) and constructed as at January for every year from 1978 to 2003.

Djankov et al. (2007)

45

High private benefits indicator

An indicator variable equals 1 for IPOs listed in a sample country with an above-median private benefit of control value as reported by Dyck and Zingales (2004) and 0 otherwise.

SDC database Dyck Zingales (2004)

Preemptive rights An indicator variable equals 1 if investors have preemptive rights in a country; 0 otherwise.

La Porta et al. (2006)

Tax evasion Assessment of the prevalence of tax evasion. Higher scores indicate higher tax evasion. The data is for 2001. Ranges from 0.94 to 8.54.

World Economic Forum (2003)

Bounced check Logarithm of the length (in calendar days) for the judicial procedure to collect on a bounced check.

Djankov et al. (2003a)

Legal origin The binary variables: (1) English Common Law; (2) French Commercial Code; (3) German Commercial Code; (4) Scandinavian Commercial Code; (5) and Socialist/Communist Laws. These variables identify the legal origin of the company law or commercial code of each country.

La Porta et al. (1998)

46

Table 2 Descriptive Statistics

This table presents descriptive statistics for the entire sample of 19,420 IPOs listed in 44 countries over the period 1980 to 2009. Panel A summarizes descriptive statistics for all firm- and country-level variables used in our main regression analysis in Table 3. Panel B presents sample distribution by country for these variables. Correlations among these variables are shown in Panel C. Variable definitions and data sources are presented in Table 1. Initial return, Offer size, Secondary shares, Underwriter reputation, Stock return volatility, and Stock market turnover are winsorized at the 1st and 99th percentile.

Panel A: Sample Summary Statistics

Variables N Mean Std. Dev. 25% 50% 75%

Initial return 19420 34.21 78.77 0.00 7.26 35.25

Uncertain avoidance 19420 55.18 22.05 46.00 46.00 69.00

Collectivism 19420 39.34 29.52 9.00 29.00 74.00

Masculinity 19420 60.24 16.26 52.00 62.00 66.00

Power distance 19420 52.92 18.48 40.00 46.00 68.00

Long-term Orientation 16499 52.41 30.65 29.00 31.00 80.00

Stock market turnover 17884 0.97 0.66 0.53 0.75 1.24

Bank ownership 17991 0.36 0.48 0.00 0.00 1.00

Inflation 19078 3.29 26.41 1.47 2.39 3.37

Ratio of MCAP to GDP 19335 1.10 0.66 0.58 1.05 1.42

Offer size 19383 3.00 1.72 1.87 3.01 4.09

Integer offer price 19420 0.60 0.49 0.00 1.00 1.00

Bookbuilt 19420 0.57 0.50 0.00 1.00 1.00

Firm commitment 19420 0.59 0.49 0.00 1.00 1.00

Secondary shares 19419 0.14 0.26 0.00 0.00 0.18

Equity carve-out 19420 0.04 0.19 0.00 0.00 0.00

Privatization 19420 0.02 0.14 0.00 0.00 0.00

Underwriter reputation 19420 0.02 0.04 0.00 0.01 0.03

Venture capitalist 19420 0.15 0.36 0.00 0.00 0.00

High-tech dummy 19420 0.36 0.48 0.00 0.00 1.00

Stock return volatility 19410 0.08 0.05 0.03 0.07 0.13

47

Panel B: Sample Distribution by Country

Cultural Dimensions Country Controls Firm-level Control Varaibles

Country N

Init

ial

retu

rn

Un

cert

ain

av

oid

an

ce

Co

llec

tiv

ism

Ma

scu

lin

ity

Po

wer

dis

tan

ce

Lo

ng

-ter

m

ori

enta

tio

n

Sto

ck m

ark

et

turn

ov

er

Ba

nk

ow

ner

ship

Infl

ati

on

Ra

tio

of

MC

AP

to G

DP

Off

er s

ize

Inte

ger

off

er

pri

ce

Bo

ok

bu

ilt

Fir

m

com

mit

men

t

Sec

on

da

ry s

ha

res

Eq

uit

y c

arv

e-o

ut

Pri

va

tiz

ati

on

Un

der

wri

ter

rep

uta

tio

n

Ven

ture

cap

ita

list

Hig

h-t

ech

du

mm

y

Sto

ck r

etu

rn

vo

lati

lity

1 Argentina 17 46.67 86 54 56 49 0.31 1 7.89 0.58 4.54 0.29 1.00 0.24 0.53 0.06 0.18 0.07 0.06 0.12 0.07

2 Australia 1,329 22.44 51 10 61 36 31 0.73 1 2.78 1.01 2.02 0.19 0.05 0.48 0.08 0.03 0.01 0.02 0.03 0.22 0.09

3 Austria 66 15.02 70 45 79 11 0.47 1 1.72 0.16 4.26 0.79 0.80 0.02 0.33 0.08 0.17 0.03 0.03 0.32 0.08

4 Belgium 92 22.93 94 25 54 65 0.53 1 2.04 0.67 2.93 0.55 0.65 0.03 0.22 0.03 0.00 0.02 0.12 0.38 0.07

5 Brazil 98 16.97 76 62 49 69 65 0.42 1 69.90 0.38 5.48 0.67 0.85 0.55 0.26 0.02 0.01 0.02 0.07 0.11 0.07

6 Canada 823 69.14 48 20 52 39 23 0.61 0 1.95 1.00 1.03 0.24 0.07 0.25 0.02 0.01 0.01 0.01 0.01 0.20 0.09

7 Switzerland 110 27.12 58 32 70 34 0.96 1 1.14 2.50 4.56 0.83 0.91 0.12 0.29 0.11 0.03 0.02 0.08 0.35 0.06

8 Chile 20 99.79 86 77 28 63 0.21 0 5.97 0.89 4.17 0.70 0.80 0.20 0.06 0.05 0.00 0.07 0.00 0.10 0.06

9 China 1,320 93.93 30 80 66 80 118 1.30 0 3.96 0.38 3.99 0.11 0.33 0.46 0.06 0.01 0.04 0.01 0.04 0.25 0.08

10 Germany 517 13.42 65 33 66 35 31 0.96 1 1.44 0.54 3.85 0.76 0.86 0.01 0.17 0.05 0.02 0.02 0.06 0.50 0.08

11 Denmark 70 33.82 23 26 16 18 0.69 1 2.14 0.57 3.41 0.79 0.57 0.04 0.16 0.06 0.03 0.03 0.06 0.44 0.07

12 Spain 69 9.67 86 49 42 57 1.52 1 3.01 0.77 5.40 0.52 0.91 0.04 0.42 0.12 0.10 0.02 0.07 0.16 0.04

13 Finland 62 34.19 59 37 26 33 0.69 1 1.57 1.77 3.35 0.53 0.94 0.06 0.38 0.13 0.10 0.04 0.03 0.55 0.07

14 France 727 11.22 86 29 43 68 0.84 1 1.58 0.88 2.19 0.50 0.69 0.05 0.24 0.03 0.06 0.01 0.06 0.44 0.08

15 United Kingdom 522 28.63 35 11 66 35 25 1.67

2.10 1.57 3.00 0.22 0.68 0.18 0.12 0.06 0.01 0.01 0.05 0.29 0.07

16 Greece 147 31.47 112 65 57 60 0.63 1 3.85 0.91 2.99 0.66 0.88 0.16 0.11 0.01 0.08 0.06 0.00 0.22 0.10

17 Hong Kong, China

706 18.12 29 75 57 68 96 0.52

4.39 3.63 2.90 0.20 0.32 0.31 0.08 0.03 0.01 0.01 0.02 0.26 0.08

18 Hungary 18 99.76 82 20 88 46 50 0.34 1 21.02 0.24 3.17 0.83 0.33 0.00 0.81 0.00 0.83 0.07 0.00 0.17 0.09

19 Indonesia 232 39.45 48 86 46 78 0.53 1 9.45 0.23 2.79 0.96 0.21 0.26 0.04 0.00 0.03 0.01 0.01 0.10 0.07

20 India 467 72.35 40 52 56 77 61 0.66 0 7.56 0.34 2.38 0.96 0.43 0.76 0.06 0.00 0.02 0.00 0.09 0.30 0.09

22 Israel 100 18.14 81 46 47 13 0.40 1 13.13 0.58 3.12 0.61 0.92 0.62 0.06 0.11 0.02 0.02 0.12 0.73 0.08

23 Italy 227 24.84 75 24 70 50 1.21 1 2.45 0.53 4.41 0.51 0.89 0.05 0.33 0.06 0.11 0.02 0.06 0.23 0.08

24 Japan 2,120 43.02 92 54 95 54 80 0.75 1 0.65 0.69 2.75 1.00 0.67 0.96 0.36 0.04 0.00 0.06 0.19 0.31 0.08

25 Korea, Rep. 745 55.27 85 82 39 60 75 2.09 0 3.25 0.54 2.69 0.99 0.07 0.65 0.03 0.00 0.01 0.05 0.07 0.46 0.09

26 Luxembourg 18 4.64 70 40 50 40 0.17

2.76 1.46 3.32 0.39 0.72 0.11 0.57 0.06 0.00 0.04 0.00 0.22 0.10

27 Macao, China 10 17.55 68 54 53 70 0.32

0.30 4.19 1.00 0.90 0.00 0.50 0.00 0.30 0.09 0.00 0.10 0.08

28 Mexico 54 0.94 82 70 69 81 0.38 0 11.19 0.22 4.01 0.31 0.76 0.19 0.22 0.02 0.04 0.05 0.00 0.15 0.08

48

29 Malaysia 700 57.15 36 74 50 104 0.52 0 2.89 1.48 1.87 0.11 0.12 0.27 0.10 0.00 0.01 0.05 0.02 0.18 0.09

30 Netherlands 100 33.55 53 20 14 38 44 1.03 1 1.89 1.32 4.87 0.67 0.86 0.15 0.34 0.08 0.05 0.02 0.06 0.52 0.07

31 Norway 121 16.82 50 31 8 31 0.98

1.83 0.40 3.41 0.83 0.77 0.07 0.18 0.04 0.03 0.02 0.13 0.32 0.07

32 New Zealand 80 14.17 49 21 58 22 30 0.35 1 2.02 0.39 2.95 0.25 0.14 0.44 0.18 0.01 0.03 0.02 0.01 0.14 0.07

33 Pakistan 39 75.93 70 86 50 55 0 0.79

9.09 0.12 1.82 0.85 0.03 0.15 0.26 0.00 0.15 0.03 0.00 0.00 0.07

34 Philippines 112 17.31 44 68 64 94 19 0.26 0 7.62 0.35 3.14 0.26 0.26 0.10 0.10 0.01 0.02 0.03 0.00 0.13 0.09

35 Poland 164 12.04 93 40 64 68 32 0.42 1 5.54 0.17 3.11 0.66 0.62 0.01 0.25 0.01 0.18 0.05 0.03 0.24 0.07

36 Portugal 26 42.97 104 73 31 63 0.53 1 3.76 0.46 5.56 0.62 0.81 0.00 0.67 0.08 0.69 0.06 0.00 0.27 0.04

37 Singapore 468 29.40 8 80 48 74 48 0.66 0 1.45 1.65 2.29 0.01 0.16 0.30 0.08 0.01 0.01 0.05 0.02 0.25 0.08

38 Sweden 110 26.57 29 29 5 31 33 1.02 1 1.57 1.13 3.88 0.85 0.65 0.09 0.33 0.09 0.06 0.02 0.10 0.52 0.07

39 Thailand 272 23.98 64 80 34 64 56 0.71 0 3.93 0.45 2.63 0.69 0.07 0.36 0.05 0.01 0.03 0.03 0.01 0.11 0.07

40 Turkey 26 52.79 85 63 45 66 1.19 1 11.78 0.35 4.74 0.27 0.73 0.04 0.48 0.08 0.19 0.05 0.00 0.12 0.08

41 Taiwan 801 18.14 69 83 45 58 87 2.15 0 1.63 1.05 2.14 0.87 0.08 0.61 0.02 0.00 0.01 0.04 0.03 0.58 0.07

42 United States 5,675 19.39 46 9 62 40 29 1.09 0 3.04 1.41 3.56 0.76 0.98 0.95 0.11 0.06 0.00 0.01 0.37 0.50 0.08

43 Vietnam 13 86.02 30 80 40 70 80 0.41

8.35

2.88 0.54 0.31 0.23 0.02 0.00 0.00 0.13 0.08 0.00 0.06

44 South Africa 27 33.15 49 35 63 49 0.39 0 6.91 1.60 3.91 0.44 0.74 0.22 0.33 0.11 0.15 0.05 0.04 0.41 0.08

49

Panel C: Correlations

Variables

Init

ial

retu

rn

Un

cert

ain

avo

idan

ce

Co

llec

tiv

ism

Mas

culi

nit

y

Po

wer

dis

tan

ce

Lo

ng

-ter

m

ori

enta

tio

n

Sto

ck m

ark

et

turn

ov

er

Ban

k o

wn

ersh

ip

Infl

atio

n

Rat

io o

f M

CA

P t

o

GD

P

Off

er s

ize

Inte

ger

off

er p

rice

Bo

ok

bu

ilt

Fir

m c

om

mit

men

t

Sec

on

dar

y s

har

es

Eq

uit

y c

arv

e-o

ut

Pri

vat

izat

ion

Un

der

wri

ter

rep

uta

tio

n

Ven

ture

cap

ital

ist

Hig

h-t

ech

du

mm

y

Uncertain avoidance -0.0421*

Collectivism 0.1474* 0.1104*

Masculinity 0.0308* 0.2959* -0.0999*

Power distance 0.1496* -0.0861* 0.7714* -0.0886*

Long-term Orientation 0.1821* 0.1652* 0.8580* 0.1983* 0.7945*

Stock market turnover 0.0324* 0.0686* 0.1030* -0.1475* -0.0637* 0.1654*

Bank ownership -0.0643* 0.6111* -0.0222* 0.3062* -0.1599* 0.0789* -0.2659*

Inflation 0.003 -0.007 0.0202* -0.0269* 0.0275* 0.005 -0.014 0.002

Ratio of MCAP to GDP -0.1179* -0.4378* -0.1776* -0.0842* -0.1026* -0.1524* -0.0845* -0.3633* -0.0189*

Offer size -0.0956* -0.0499* -0.0717* 0.0579* -0.0780* 0.0369* 0.1239* -0.0379* 0.010 -0.003

Integer offer price -0.0682* 0.3863* -0.0677* 0.1428* -0.2011* -0.0442* 0.1499* 0.0672* -0.0212* -0.1558* 0.1713*

Bookbuilt -0.1174* 0.0700* -0.4366* 0.2118* -0.3330* -0.2955* 0.0346* -0.010 -0.005 0.0998* 0.3305* 0.2295*

Firm commitment -0.0662* 0.0474* -0.2133* 0.3335* -0.2036* -0.0594* 0.0562* -0.2290* -0.0272* 0.0481* 0.0982* 0.2811* 0.3034*

Secondary shares -0.0747* 0.2505* -0.0164* 0.2043* -0.0309* 0.0536* -0.0864* 0.2975* -0.014 -0.0778* 0.1972* 0.0921* 0.1610* -0.003

Equity carve-out -0.0322* 0.005 -0.0949* 0.0266* -0.0953* -0.0710* -0.010 0.0250* 0.000 0.0386* 0.1297* 0.010 0.1276* 0.0516* 0.1286*

Privatization 0.004 0.0601* 0.0533* -0.0435* 0.0514* 0.0460* -0.0255* 0.0812* 0.0165* -0.0842* 0.1976* -0.0169* 0.0275* -0.1185* 0.3624* -0.0271*

Underwriter reputation

0.0515* 0.2746* 0.2284* 0.1526* 0.1183* 0.1769* 0.0164* 0.1488* -0.0145* -0.1285* 0.0720* 0.1256* -0.0652* -0.0283* 0.1132* 0.006 0.0575*

Venture capitalist 0.004 -0.0244* -0.2586* 0.1158* -0.1929* -0.1808* 0.1066* -0.1400* -0.009 0.0835* 0.1055* 0.1788* 0.3164* 0.2650* 0.013 -0.0159* -0.0595* -0.0216*

High-tech dummy 0.0322* 0.0262* -0.1095* -0.0282* -0.1344* -0.0703* 0.1198* -0.0817* -0.0157* 0.0436* 0.0167* 0.1329* 0.1767* 0.1503* -0.0470* 0.000 -0.0575* -0.0340* 0.3140*

Stock return volatility 0.0734* 0.001 0.006 0.004 0.0201* -0.008 0.010 -0.0166* 0.005 -0.0204* -0.1102* -0.0306* -0.0208* -0.005 -0.0467* -0.0272* -0.008 -0.004 0.0367* 0.0564*

50

Table 3 The Impact of National Culture on IPO underpricing

This table presents results of the regressions of IPO initial returns on Hofstede‘s five cultural dimensions and firm- and country-level control variables. Specification (1) only includes firm-level variables whereas specification (2) adds a set of country-level variables. Specifications (3) through (7) sequentially introduce Hofstede‘s five cultural dimensions: uncertainty avoidance, collectivism, masculinity, power distance, and long-term orientation. Specifications (8) and (9) conduct multivariate regressions. The sample period spans from 1980 to 2009. Variable definitions and data sources are reported in Table 1. Year and industry dummies are included in the regressions, but not reported in the table. The robust t-statistics in parentheses are based on standard errors that are heteroskedasticity-consistent and allow clustering at the firm level. *, **, *** indicate significance at the 10%, 5%, and 1% level, respectively.

Variables (1) (2) (3) (4) (5) (6) (7) (8) (9)

Uncertain avoidance -0.505*** -0.585*** -0.629***

(-10.19)

(-11.78) (-8.88)

Collectivism

0.235***

0.160*** -0.694***

(6.55)

(3.54) (-8.63)

Masculinity

0.803***

0.802*** 0.391***

(14.86)

(15.24) (4.68)

Power distance

0.394***

0.239*** 0.055

(7.60)

(3.63) (0.37)

Long-term Orientation

0.671***

1.035***

(15.65)

(16.60)

Stock market turnover

2.415** 6.546*** 1.638 3.500*** 4.648*** -5.315*** 9.113*** 1.581

(1.97) (5.08) (1.33) (2.88) (3.62) (-3.82) (6.62) (1.00)

Bank ownership

-28.974*** -17.164*** -25.553*** -38.675*** -23.244*** -27.184*** -19.175*** -29.599***

(-15.25) (-7.84) (-12.29) (-18.93) (-10.96) (-12.71) (-7.38) (-9.08)

Inflation

0.014 0.010 0.012 0.026 0.009 0.018 0.017 0.027

(0.61) (0.42) (0.52) (1.13) (0.38) (0.78) (0.74) (1.26)

Ratio of MCAP to GDP

-40.432*** -47.968*** -34.544*** -34.646*** -36.699*** -29.126*** -37.130*** -46.987***

(-18.89) (-19.77) (-14.62) (-16.56) (-16.84) (-10.53) (-14.66) (-13.85)

Offer size -4.080*** -5.658*** -6.898*** -5.467*** -5.686*** -5.516*** -6.646*** -6.908*** -9.019***

(-8.17) (-10.70) (-12.58) (-10.17) (-10.84) (-10.27) (-10.88) (-12.54) (-14.13)

Integer offer price -7.564*** -11.923*** -6.934*** -12.430*** -10.112*** -10.552*** -14.399*** -3.845*** -2.915*

(-5.95) (-8.39) (-4.83) (-8.77) (-7.18) (-7.42) (-9.86) (-2.59) (-1.77)

Bookbuild -15.105*** -3.740*** -0.511 0.700 -7.802*** -0.874 9.052*** 0.701 0.101

(-10.67) (-2.58) (-0.35) (0.42) (-5.28) (-0.57) (5.49) (0.40) (0.06)

51

Firm commitment -3.496** -3.630** -0.858 -2.057 -16.582*** -0.688 -7.812*** -10.501*** -10.758***

(-2.53) (-2.41) (-0.54) (-1.34) (-9.72) (-0.43) (-4.49) (-5.67) (-5.05)

Secondary shares -16.377*** -1.299 2.106 -2.961 -7.529*** -3.117 -6.967** -5.802** -2.446

(-7.10) (-0.50) (0.81) (-1.14) (-2.86) (-1.19) (-2.16) (-2.22) (-0.76)

Equity carve-out 2.336 5.819* 5.680* 6.688** 7.330** 7.062** 5.693* 8.509*** 5.321*

(0.84) (1.79) (1.74) (2.07) (2.23) (2.17) (1.84) (2.61) (1.74)

Privatization 9.486 -2.669 -0.079 -2.901 7.573 -2.909 -9.261 10.260 -2.315

(1.47) (-0.38) (-0.01) (-0.42) (1.07) (-0.42) (-1.63) (1.45) (-0.39)

Underwriter reputation 110.567*** 116.084*** 151.123*** 84.916*** 77.841*** 94.969*** 2.681 84.549*** 86.228***

(7.02) (7.21) (9.30) (5.05) (4.74) (5.84) (0.15) (4.95) (4.83)

Venture capitalist 12.512*** 15.951*** 14.498*** 17.526*** 12.772*** 16.686*** 18.094*** 12.607*** 12.760***

(7.87) (9.20) (8.35) (10.10) (7.58) (9.68) (10.32) (7.49) (7.39)

High-tech dummy 2.974** 3.727*** 4.342*** 4.311*** 6.050*** 5.051*** 7.590*** 7.957*** 9.666***

(2.09) (2.59) (3.03) (2.99) (4.23) (3.49) (4.95) (5.60) (6.41)

Stock return volatility 77.389*** 73.381*** 73.243*** 73.183*** 68.597*** 71.295*** 78.920*** 67.047*** 75.038***

(6.67) (6.12) (6.14) (6.11) (5.77) (5.96) (6.26) (5.68) (6.07)

Constant 43.991*** 117.392*** 139.227*** 87.077*** 68.616*** 67.266*** 87.173*** 43.056*** 109.996***

(4.96) (10.95) (12.45) (7.24) (6.31) (5.18) (2.62) (3.27) (3.16)

Observations 17,032 14,974 14,974 14,974 14,974 14,974 12,698 14,974 12,698

R2 0.054 0.099 0.107 0.103 0.116 0.105 0.155 0.131 0.185

52

Table 4 Robustness Check: Additional Controls for Country-level Corporate Governance

This table reports results of the regressions of IPO initial returns on Hofstede‘s (2001) four cultural dimensions (uncertainty avoidance in Panel A, collectivism in Panel B, masculinity in Panel C, and power distance in Panel D) and firm- and country-level control variables under controls for 10 additional country-level governance quality variables. We sequentially introduce these additional controls in specifications (1) through (10). In each specification, the dependent variable is the initial return. Definitions and data sources for all variables including additional controls are reported in Table 1. Year and industry dummies are included in the regressions, but not reported in the table. The robust t-statistics in parentheses are based on standard errors that are heteroskedasticity-consistent and allow clustering at the firm level. *, **, *** indicate significance at the 10%, 5%, and 1% level, respectively.

Panel A: Uncertainty Avoidance

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

Variables

An

ti-s

elf

dea

lin

g

An

ti-s

elf

dea

lin

g

pu

bli

c en

forc

emen

t

Ru

le o

f la

w

Cre

dit

or

rig

hts

Hig

h p

riv

ate

ben

efit

s in

dic

ato

r

Pre

emp

tiv

e ri

gh

ts

An

tid

irec

tor

rig

hts

Ta

x e

va

sio

n

Bo

un

ced

ch

eck

Leg

al s

yst

em

Uncertainty avoidance -0.264*** -0.508*** -0.506*** -0.486*** -0.102* -0.385*** -0.478*** -0.491*** -0.495*** -0.690***

(-4.26) (-10.23) (-10.23) (-9.07) (-1.87) (-7.72) (-9.75) (-9.78) (-10.00) (-11.71)

Additional control 52.867*** -4.609** -4.773*** 1.029 10.497*** -28.908*** -4.474*** 4.627*** -4.733*** 0.248

(7.48) (-1.98) (-3.90) (1.11) (3.44) (-14.99) (-4.67) (4.73) (-3.80) (0.04)

3.502

(0.48)

29.547***

(4.08)

Stock market turnover 7.383*** 5.757*** 7.428*** 6.380*** 2.468* 5.413*** 4.859*** 6.442*** 6.302*** 0.504

(5.69) (4.21) (5.60) (4.95) (1.89) (4.29) (3.65) (5.04) (4.93) (0.37)

Bank ownership -17.085*** -17.188*** -12.054*** -17.780*** -9.895*** -22.506*** -16.209*** -18.724*** -16.029*** -18.189***

(-7.75) (-7.85) (-4.50) (-7.85) (-4.20) (-10.06) (-7.36) (-8.38) (-7.18) (-8.15)

Inflation 0.012 0.010 0.004 0.010 0.021 0.020 0.015 0.016 0.010 0.025

(0.53) (0.44) (0.16) (0.45) (0.98) (0.89) (0.66) (0.73) (0.45) (1.10)

Ratio of MCAP to GDP -52.927*** -47.172*** -40.342*** -47.313*** -12.220*** -47.845*** -45.347*** -59.310*** -49.494*** -36.116***

(-20.73) (-19.30) (-12.96) (-19.20) (-4.62) (-19.77) (-18.58) (-17.07) (-19.72) (-14.19)

Offer size -6.686*** -6.997*** -6.975*** -6.812*** -8.980*** -7.119*** -7.499*** -6.637*** -6.933*** -7.179***

(-12.10) (-12.93) (-12.76) (-12.44) (-16.15) (-13.03) (-13.64) (-12.17) (-12.66) (-13.34)

53

Integer offer price -4.652*** -7.048*** -7.292*** -6.858*** 3.543*** -3.699*** -5.367*** -6.763*** -7.722*** -7.002***

(-3.28) (-4.90) (-5.14) (-4.78) (2.61) (-2.65) (-3.74) (-4.73) (-5.36) (-4.79)

Bookbuild 5.802*** -1.172 0.929 0.186 1.085 -3.473** -2.988* -0.054 -2.056 3.642**

(3.33) (-0.77) (0.61) (0.11) (0.76) (-2.35) (-1.85) (-0.04) (-1.36) (2.42)

Firm commitment -4.304*** -2.449 0.798 -0.948 -3.310** -16.282*** -0.204 -4.534** -3.310** -4.046**

(-2.62) (-1.45) (0.49) (-0.60) (-2.15) (-8.47) (-0.13) (-2.49) (-2.00) (-2.34)

Secondary shares 2.237 1.871 2.286 2.077 0.587 -0.843 3.458 0.177 0.464 -1.322

(0.86) (0.72) (0.88) (0.80) (0.23) (-0.32) (1.31) (0.07) (0.17) (-0.50)

Equity carve-out 6.153* 5.744* 6.058* 5.626* 6.923** 5.553* 5.709* 5.682* 5.964* 6.753**

(1.88) (1.76) (1.87) (1.73) (2.18) (1.70) (1.75) (1.74) (1.83) (2.08)

Privatization 0.426 0.884 -0.654 0.016 6.102 9.405 -1.830 3.551 3.610 5.565

(0.06) (0.13) (-0.09) (0.00) (0.83) (1.33) (-0.26) (0.50) (0.51) (0.78)

Underwriter reputation 134.027*** 152.171*** 142.474*** 147.817*** 157.870*** 153.308*** 167.845*** 136.083*** 139.401*** 113.865***

(8.15) (9.36) (8.83) (8.94) (9.99) (9.48) (10.13) (8.09) (8.47) (6.81)

Venture capitalist 13.443*** 14.167*** 15.082*** 14.587*** 14.272*** 9.471*** 14.243*** 13.623*** 14.073*** 16.210***

(7.82) (8.17) (8.73) (8.42) (8.46) (5.58) (8.20) (7.95) (8.12) (9.36)

High-tech dummy 5.728*** 4.409*** 4.915*** 4.277*** 4.604*** 5.385*** 4.008*** 4.494*** 4.648*** 4.095***

(4.00) (3.08) (3.42) (2.99) (3.35) (3.81) (2.80) (3.14) (3.24) (2.89)

Stock return volatility 71.362*** 74.143*** 70.909*** 72.850*** 70.113*** 69.552*** 75.670*** 72.391*** 72.332*** 74.254***

(6.00) (6.20) (5.93) (6.08) (5.92) (5.90) (6.35) (6.07) (6.06) (6.26)

Constant 101.344*** 142.940*** 145.140*** 212.714*** 91.384 160.940*** 161.485*** 125.670*** 162.429*** 123.316***

(3.15) (12.62) (12.91) (6.87) (0.00) (14.26) (13.45) (10.82) (12.42) (9.45)

Observations 14,950 14,974 14,974 14,963 14,216 14,974 14,974 14,974 14,974 14,974

R2 0.112 0.108 0.109 0.106 0.079 0.126 0.109 0.110 0.108 0.121

54

Panel B: Collectivism

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

Variables

An

ti-s

elf

dea

lin

g

An

ti-s

elf

dea

lin

g

pu

bli

c

enfo

rcem

ent

Ru

le o

f la

w

Cre

dit

or

rig

hts

Hig

h p

riv

ate

ben

efit

s in

dic

ato

r

Pre

emp

tiv

e ri

gh

ts

An

tid

irec

tor

rig

hts

Ta

x e

va

sio

n

Bo

un

ced

ch

eck

Leg

al s

yst

em

Collectivism 0.200*** 0.237*** 0.220*** 0.220*** 0.137*** 0.687*** 0.315*** 0.263*** 0.212*** 0.189***

(5.63) (6.57) (4.73) (6.02) (3.88) (16.26) (8.10) (7.38) (5.72) (4.15)

Additional controls 65.373*** -4.302* -0.718 2.195** 9.274*** -48.408*** -7.375*** 5.689*** -3.246** -9.206

(11.74) (-1.85) (-0.46) (2.52) (3.19) (-21.69) (-7.22) (5.94) (-2.54) (-1.39)

-29.215***

(-4.51)

-1.073

(-0.17)

Stock market turnover 5.248*** 0.872 1.819 1.603 1.100 -0.116 -1.049 1.554 1.599 -0.970

(4.11) (0.65) (1.41) (1.31) (0.93) (-0.10) (-0.82) (1.28) (1.31) (-0.69)

Bank ownership -18.897*** -25.615*** -25.011*** -26.358*** -10.464*** -23.214*** -21.779*** -26.668*** -24.960*** -24.749***

(-8.48) (-12.33) (-10.59) (-12.60) (-4.81) (-11.37) (-10.05) (-12.79) (-11.93) (-9.67)

Inflation 0.013 0.012 0.011 0.013 0.022 0.024 0.020 0.020 0.013 0.026

(0.57) (0.54) (0.49) (0.57) (0.99) (1.02) (0.87) (0.85) (0.55) (1.09)

Ratio of MCAP to GDP -45.841*** -33.711*** -33.775*** -34.410*** -7.569*** -25.983*** -28.867*** -48.034*** -36.263*** -33.944***

(-16.98) (-13.86) (-11.50) (-14.62) (-2.91) (-10.98) (-11.65) (-13.98) (-14.26) (-13.18)

Offer size -5.963*** -5.551*** -5.491*** -5.472*** -8.625*** -5.960*** -6.499*** -5.164*** -5.525*** -5.428***

(-11.05) (-10.50) (-10.19) (-10.13) (-15.79) (-11.27) (-12.24) (-9.70) (-10.31) (-10.23)

Integer offer price -6.582*** -12.569*** -12.454*** -11.984*** 2.439* -6.009*** -9.586*** -12.114*** -12.858*** -13.220***

(-4.67) (-8.82) (-8.84) (-8.40) (1.82) (-4.53) (-6.88) (-8.58) (-9.06) (-9.13)

Bookbuild 9.723*** 0.100 0.627 2.228 3.150* 5.579*** -1.584 1.901 -0.754 3.612**

(5.08) (0.06) (0.37) (1.24) (1.90) (3.31) (-0.92) (1.12) (-0.42) (1.98)

Firm commitment -4.925*** -3.545** -1.911 -2.212 -2.998** -23.751*** -0.199 -6.297*** -3.858** -7.956***

(-3.25) (-2.13) (-1.22) (-1.44) (-2.03) (-12.98) (-0.13) (-3.59) (-2.35) (-4.79)

Secondary shares -0.556 -3.214 -2.828 -2.626 -1.160 -9.751*** -1.006 -5.419** -3.882 -4.756*

(-0.22) (-1.23) (-1.07) (-1.02) (-0.45) (-3.77) (-0.38) (-2.03) (-1.45) (-1.83)

Equity carve-out 7.064** 6.755** 6.688** 6.617** 7.450** 8.094** 7.019** 6.789** 6.796** 6.532**

55

(2.16) (2.09) (2.07) (2.04) (2.36) (2.50) (2.17) (2.10) (2.10) (2.03)

Privatization -0.679 -2.019 -2.974 -2.373 5.554 13.561* -5.642 1.621 -0.316 1.370

(-0.10) (-0.29) (-0.43) (-0.34) (0.76) (1.95) (-0.81) (0.23) (-0.05) (0.19)

Underwriter reputation 89.084*** 85.441*** 85.618*** 81.830*** 133.071*** 42.412** 104.870*** 63.850*** 80.373*** 61.742***

(5.30) (5.08) (5.03) (4.87) (8.11) (2.52) (6.24) (3.71) (4.77) (3.62)

Venture capitalist 15.121*** 17.238*** 17.512*** 17.576*** 15.401*** 11.567*** 17.517*** 16.590*** 17.062*** 17.533***

(8.82) (9.97) (10.07) (10.14) (9.15) (6.98) (10.10) (9.67) (9.83) (10.11)

High-tech dummy 6.292*** 4.375*** 4.359*** 4.283*** 4.845*** 7.426*** 4.013*** 4.588*** 4.471*** 4.126***

(4.39) (3.04) (3.01) (2.98) (3.52) (5.28) (2.80) (3.18) (3.10) (2.86)

Stock return volatility 70.654*** 74.023*** 72.845*** 72.003*** 70.265*** 66.568*** 77.105*** 72.108*** 72.576*** 71.010***

(5.93) (6.17) (6.06) (5.98) (5.93) (5.70) (6.46) (6.03) (6.06) (5.94)

Constant 56.613* 90.171*** 89.920*** 172.568*** 78.946 73.677*** 115.299*** 67.497*** 106.234*** 93.934***

(1.78) (7.52) (6.62) (5.59) (0.00) (6.14) (9.39) (5.46) (7.22) (6.43)

Observations 14,950 14,974 14,974 14,963 14,216 14,974 14,974 14,974 14,974 14,974

R2 0.113 0.103 0.103 0.102 0.080 0.145 0.108 0.107 0.103 0.111

56

Panel C: Masculinity

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

Variables

An

ti-s

elf

dea

lin

g

An

ti-s

elf

dea

lin

g

pu

bli

c en

forc

emen

t

Ru

le o

f la

w

Cre

dit

or

rig

hts

Hig

h p

riv

ate

ben

efit

s

ind

ica

tor

Pre

emp

tiv

e ri

gh

ts

An

tid

irec

tor

rig

hts

Ta

x e

va

sio

n

Bo

un

ced

ch

eck

Leg

al s

yst

em

Masculinity 0.725*** 0.835*** 0.870*** 0.792*** 0.455*** 0.389*** 0.779*** 0.798*** 0.794*** 1.039***

(13.32) (14.93) (15.79) (14.61) (8.75) (5.86) (14.60) (12.83) (13.89) (14.53)

Additional controls 58.258*** 5.521** -7.491*** 3.132*** 12.902*** -23.293*** -4.256*** 0.169 -1.016 -69.429***

(10.43) (2.27) (-6.11) (3.68) (4.43) (-9.83) (-4.46) (0.16) (-0.77) (-8.98)

-65.418***

(-9.09)

-64.239***

(-7.95)

Stock market turnover 6.495*** 4.519*** 4.955*** 3.336*** 2.625** 2.816** 2.070 3.494*** 3.451*** 2.630**

(5.11) (3.40) (3.97) (2.76) (2.20) (2.35) (1.64) (2.88) (2.85) (1.96)

Bank ownership -31.412*** -38.947*** -31.522*** -39.527*** -18.202*** -35.720*** -36.888*** -38.663*** -38.272*** -45.932***

(-14.24) (-18.92) (-13.08) (-19.64) (-8.33) (-17.87) (-17.97) (-18.90) (-17.65) (-18.84)

Inflation 0.026 0.027 0.018 0.027 0.027 0.028 0.031 0.027 0.026 0.033

(1.12) (1.13) (0.77) (1.17) (1.22) (1.19) (1.34) (1.14) (1.13) (1.38)

Ratio of MCAP to GDP -44.593*** -35.422*** -22.156*** -34.192*** -8.227*** -38.971*** -32.702*** -35.102*** -35.070*** -33.041***

(-18.41) (-16.50) (-7.69) (-16.40) (-3.50) (-17.71) (-15.41) (-9.81) (-15.86) (-12.88)

Offer size -6.107*** -5.578*** -5.803*** -5.717*** -8.527*** -6.086*** -6.318*** -5.677*** -5.698*** -5.844***

(-11.62) (-10.88) (-11.07) (-10.89) (-16.22) (-11.58) (-12.08) (-10.84) (-10.91) (-11.07)

Integer offer price -5.150*** -9.867*** -10.546*** -9.613*** 2.290* -7.486*** -8.424*** -10.112*** -10.283*** -11.000***

(-3.66) (-6.95) (-7.58) (-6.83) (1.71) (-5.48) (-5.98) (-7.18) (-7.24) (-7.64)

Bookbuild 1.246 -7.149*** -5.898*** -5.145*** -2.339 -7.478*** -9.877*** -7.759*** -8.075*** -9.060***

(0.72) (-4.65) (-3.89) (-2.96) (-1.63) (-5.11) (-6.11) (-5.07) (-5.35) (-5.81)

Firm commitment -17.678*** -15.173*** -15.081*** -16.534*** -11.380*** -21.801*** -15.441*** -16.638*** -16.949*** -17.503***

(-10.40) (-8.52) (-8.75) (-9.70) (-6.76) (-12.02) (-9.02) (-9.40) (-9.93) (-10.21)

Secondary shares -4.983* -7.471*** -7.785*** -7.086*** -3.420 -6.043** -5.890** -7.560*** -7.797*** -10.787***

(-1.90) (-2.83) (-2.97) (-2.70) (-1.32) (-2.31) (-2.21) (-2.83) (-2.89) (-4.04)

57

Equity carve-out 7.640** 7.313** 8.050** 7.338** 7.691** 6.422* 7.305** 7.321** 7.373** 6.964**

(2.30) (2.22) (2.46) (2.23) (2.42) (1.96) (2.22) (2.23) (2.24) (2.16)

Privatization 8.509 6.847 7.516 8.211 10.078 10.428 5.737 7.649 8.258 11.041

(1.20) (0.96) (1.06) (1.16) (1.36) (1.48) (0.80) (1.07) (1.16) (1.55)

Underwriter reputation 81.143*** 75.315*** 60.896*** 70.902*** 124.881*** 106.019*** 96.629*** 77.549*** 75.903*** 62.835***

(4.96) (4.59) (3.73) (4.31) (7.78) (6.37) (5.79) (4.69) (4.61) (3.76)

Venture capitalist 11.156*** 13.031*** 13.429*** 13.067*** 13.120*** 10.083*** 12.550*** 12.757*** 12.712*** 12.934***

(6.65) (7.72) (8.01) (7.78) (7.92) (5.99) (7.44) (7.59) (7.55) (7.64)

High-tech dummy 7.672*** 6.067*** 7.142*** 6.074*** 5.650*** 5.810*** 5.695*** 6.043*** 6.091*** 5.827***

(5.38) (4.24) (4.97) (4.25) (4.12) (4.09) (3.98) (4.22) (4.25) (4.10)

Stock return volatility 66.826*** 67.326*** 64.533*** 66.737*** 66.133*** 68.064*** 71.039*** 68.594*** 68.456*** 69.052***

(5.65) (5.64) (5.42) (5.59) (5.59) (5.76) (5.98) (5.77) (5.76) (5.82)

Constant 38.357 62.381*** 73.708*** 143.421*** 64.327 115.438*** 92.315*** 68.427*** 74.247*** 126.392***

(1.23) (5.64) (6.78) (4.69) (0.00) (9.79) (7.86) (6.24) (5.45) (9.62)

Observations 14,950 14,974 14,974 14,963 14,216 14,974 14,974 14,974 14,974 14,974

R2 0.124 0.117 0.120 0.116 0.084 0.124 0.118 0.116 0.116 0.124

58

Panel D: Power distance

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

Variables

An

ti-s

elf

dea

lin

g

An

ti-s

elf

dea

lin

g

pu

bli

c en

forc

emen

t

Ru

le o

f la

w

Cre

dit

or

rig

hts

Hig

h p

riv

ate

ben

efit

s in

dic

ato

r

Pre

emp

tiv

e ri

gh

ts

An

tid

irec

tor

rig

hts

Ta

x e

va

sio

n

Bo

un

ced

ch

eck

Leg

al s

yst

em

Power distance 0.302*** 0.397*** 0.499*** 0.399*** 0.187*** 0.836*** 0.483*** 0.592*** 0.370*** 0.592***

(5.96) (7.62) (6.71) (7.80) (3.60) (15.35) (8.94) (11.05) (7.04) (9.72)

Additional controls 61.586*** -4.402* 3.155* 3.646*** 8.690*** -43.698*** -7.284*** 8.842*** -2.829** -17.644***

(11.18) (-1.89) (1.80) (4.35) (3.00) (-21.90) (-7.38) (8.70) (-2.27) (-2.72)

-48.223***

(-7.10)

-10.493

(-1.60)

Stock market turnover 7.416*** 3.885*** 4.666*** 4.500*** 2.718** 6.914*** 2.760** 5.780*** 4.408*** 2.935**

(5.59) (2.84) (3.63) (3.54) (2.17) (5.60) (2.12) (4.50) (3.46) (1.99)

Bank ownership -17.834*** -23.299*** -25.079*** -24.316*** -10.003*** -20.676*** -19.379*** -22.748*** -22.793*** -17.405***

(-7.95) (-10.99) (-10.44) (-11.76) (-4.55) (-10.00) (-8.82) (-10.79) (-10.65) (-7.00)

Inflation 0.011 0.009 0.011 0.010 0.020 0.017 0.016 0.019 0.009 0.023

(0.45) (0.39) (0.49) (0.43) (0.93) (0.73) (0.68) (0.79) (0.40) (0.99)

Ratio of MCAP to GDP -47.393*** -35.871*** -40.766*** -36.045*** -9.803*** -35.039*** -32.237*** -56.896*** -37.927*** -34.901***

(-18.70) (-16.06) (-12.25) (-16.63) (-4.08) (-16.11) (-14.54) (-16.76) (-16.51) (-13.49)

Offer size -5.985*** -5.602*** -5.430*** -5.555*** -8.635*** -6.135*** -6.568*** -5.010*** -5.560*** -5.371***

(-11.10) (-10.61) (-10.09) (-10.36) (-15.80) (-11.56) (-12.31) (-9.40) (-10.38) (-10.09)

Integer offer price -5.429*** -10.682*** -9.942*** -9.934*** 3.232** -2.340* -7.262*** -9.280*** -11.054*** -10.931***

(-3.83) (-7.48) (-7.06) (-6.98) (2.40) (-1.72) (-5.10) (-6.61) (-7.72) (-7.47)

Bookbuild 7.578*** -1.506 -1.059 2.192 1.889 -0.988 -3.982** 1.601 -1.941 5.706***

(4.32) (-0.96) (-0.70) (1.24) (1.28) (-0.66) (-2.46) (1.02) (-1.22) (3.53)

Firm commitment -3.854** -2.205 -0.997 -0.802 -2.608* -19.718*** 1.280 -6.099*** -2.307 -6.726***

(-2.44) (-1.28) (-0.62) (-0.51) (-1.70) (-11.02) (0.79) (-3.49) (-1.36) (-4.06)

Secondary shares -0.661 -3.374 -3.711 -2.729 -1.066 -8.389*** -1.035 -7.539*** -3.948 -6.437**

(-0.25) (-1.28) (-1.38) (-1.05) (-0.41) (-3.18) (-0.39) (-2.74) (-1.46) (-2.46)

Equity carve-out 7.240** 7.131** 7.141** 7.116** 7.522** 8.210** 7.376** 7.680** 7.152** 7.453**

59

(2.21) (2.20) (2.19) (2.19) (2.38) (2.50) (2.27) (2.35) (2.20) (2.32)

Privatization -0.799 -2.005 -2.587 -1.994 5.682 12.088* -5.591 4.043 -0.660 2.508

(-0.12) (-0.29) (-0.37) (-0.29) (0.78) (1.72) (-0.80) (0.57) (-0.10) (0.35)

Underwriter reputation 99.507*** 95.630*** 95.157*** 85.965*** 141.087*** 87.209*** 120.437*** 57.468*** 89.665*** 49.341***

(6.13) (5.89) (5.85) (5.24) (8.87) (5.42) (7.34) (3.40) (5.47) (2.93)

Venture capitalist 14.466*** 16.384*** 16.492*** 16.987*** 14.828*** 9.389*** 16.312*** 15.306*** 16.370*** 17.170***

(8.47) (9.52) (9.63) (9.87) (8.85) (5.66) (9.47) (9.05) (9.51) (9.96)

High-tech dummy 6.689*** 5.120*** 5.024*** 5.141*** 5.115*** 8.329*** 4.859*** 6.035*** 5.158*** 5.644***

(4.65) (3.54) (3.47) (3.56) (3.70) (5.89) (3.37) (4.18) (3.56) (3.92)

Stock return volatility 69.402*** 72.143*** 72.285*** 69.034*** 69.498*** 63.334*** 74.764*** 68.617*** 70.879*** 66.817***

(5.83) (6.02) (6.02) (5.75) (5.87) (5.42) (6.27) (5.76) (5.92) (5.60)

Constant 49.246 70.362*** 50.106*** 146.744*** 75.223 51.837*** 94.062*** 17.395 84.504*** 51.887***

(1.53) (5.43) (3.10) (4.61) (0.00) (4.03) (7.11) (1.25) (5.50) (3.46)

Observations 14,950 14,974 14,974 14,963 14,216 14,974 14,974 14,974 14,974 14,974

R2 0.113 0.105 0.105 0.105 0.080 0.142 0.110 0.113 0.105 0.119

60

Table 5 Robustness Check: Effects of Various Culture Values on IPO Underpricing

This table presents results of the regressions of IPO initial returns Schwartz‘s (1994) three cultural dimensions (conservatism, mastery, and hierarchy), GLOBE‘s (2004) three corresponding cultural dimensions (In group collectivism, assertiveness, and power distance), and other firm- and country-level control variables. Specifications (1) through (3) highlight mainly focus on Schwartz‘s three respective cultural dimensions. Specifications (4) through (6) emphasize GLOBE‘s three cultural counterparts. Variable definitions and data sources are reported in Table 1. Year and industry dummies are included in the regressions, but not reported in the table. The robust t-statistics in parentheses are based on standard errors that are heteroskedasticity-consistent and allow clustering at the firm level. *, **, *** indicate significance at the 10%, 5%, and 1% level, respectively.

Variables (1) (2) (3) (4) (5) (6)

Conservatism 31.423***

(8.78)

Mastery

146.194***

(22.37)

Hierarchy

60.761***

(21.85)

In-group collectivism

21.975***

(12.16)

Assertiveness

29.817***

(27.74)

Power distance

38.098***

(8.05)

Stock market turnover 6.477*** -0.204 0.328 3.563*** 8.715*** 2.810**

(4.84) (-0.16) (0.25) (2.69) (6.86) (2.13)

Bank ownership -10.449*** 3.053 2.027 -6.636*** -21.109*** -19.848***

(-4.14) (1.47) (0.94) (-2.84) (-10.76) (-9.64)

Inflation -0.034*** -0.011 -0.017** -0.032*** 0.002 -0.006

(-2.59) (-1.28) (-2.20) (-2.92) (0.32) (-0.67)

Ratio of MCAP to GDP -36.679*** -11.185*** -2.249 -19.034*** -20.985*** -37.695***

(-15.49) (-4.98) (-0.88) (-7.03) (-9.29) (-15.83)

Offer size -2.540*** -4.870*** -2.886*** -2.040*** -3.443*** -2.883***

(-5.20) (-9.56) (-5.76) (-4.11) (-6.97) (-5.62)

Integer offer price -11.627*** -8.055*** -8.870*** -10.883*** -4.984*** -8.779***

(-7.98) (-5.81) (-6.38) (-7.46) (-3.67) (-6.22)

Bookbuild -2.735* -5.356*** 3.694** -0.453 -5.267*** -3.826**

(-1.69) (-3.59) (2.43) (-0.28) (-3.56) (-2.48)

Firm commitment -0.033 -20.479*** -14.432*** 3.963** -24.184*** -3.693**

(-0.02) (-10.88) (-8.42) (2.34) (-13.27) (-2.19)

Secondary shares -5.303** -7.367*** -10.521*** -6.214** -17.662*** -5.899**

(-2.10) (-2.99) (-4.25) (-2.46) (-6.83) (-2.28)

Equity carve-out 5.398 6.915** 6.410* 5.577* 7.665** 5.912*

(1.60) (2.07) (1.93) (1.65) (2.27) (1.72)

61

Privatization -9.004 5.066 5.492 -13.252** 15.928** -4.420

(-1.32) (0.74) (0.82) (-1.96) (2.36) (-0.65)

Underwriter reputation 102.274*** 103.984*** 91.881*** 86.586*** 50.352*** 114.758***

(5.86) (6.14) (5.33) (4.91) (2.91) (6.58)

Venture capitalist 14.435*** 12.743*** 13.576*** 16.808*** 8.469*** 14.531***

(8.40) (7.47) (8.08) (9.74) (5.11) (8.50)

High-tech dummy 5.076*** 5.651*** 6.198*** 4.923*** 9.621*** 3.898***

(3.45) (3.97) (4.31) (3.34) (6.71) (2.65)

Stock return volatility 77.013*** 69.630*** 80.606*** 78.950*** 71.615*** 86.641***

(6.22) (5.74) (6.65) (6.37) (5.96) (6.95)

Constant -41.353** -520.117*** -107.950*** -32.529* -61.283*** 1.825

(-2.22) (-18.17) (-7.75) (-1.87) (-4.83) (0.09)

Observations 13,095 13,095 13,095 13,010 13,010 13,010

R2 0.102 0.142 0.137 0.107 0.161 0.103

62

Table 6 Robustness Check: Excluding U.S. IPOs

This table presents results of the regressions of IPO initial returns on Hofstede‘s five cultural dimensions and firm- and country-level control variables. Specifications (1) through (7) replicate the regressions reported in specifications (3) through (9) in Table 3 by using the sample excluding U.S. IPOs. Variable definitions and data sources are reported in Table 1. Year and industry dummies are included in the regressions, but not reported in the table. The robust t-statistics in parentheses are based on standard errors that are heteroskedasticity-consistent and allow clustering at the firm level. *, **, *** indicate significance at the 10%, 5%, and 1% level, respectively.

Variables (1) (2) (3) (4) (5) (6) (7)

Uncertainty avoidance -1.188*** -1.315*** -0.519***

(-16.64)

(-18.84) (-4.14)

Collectivism

0.736***

0.617*** -1.188***

(9.83)

(7.49) (-6.10)

Masculinity

1.051***

0.991*** -0.157

(14.16)

(14.47) (-1.31)

Power distance

0.736***

0.354*** 0.786***

(9.12)

(3.92) (3.96)

Long-term Orientation

1.078***

1.384***

(19.37)

(10.99)

Stock market turnover 11.901*** -2.901 3.485** 6.042*** -5.214** 11.531*** 8.881***

(6.64) (-1.60) (1.97) (3.41) (-2.47) (6.11) (3.69)

Bank ownership -12.883*** -27.839*** -56.993*** -30.644*** -13.529*** -4.287 -5.225

(-3.33) (-6.94) (-15.41) (-8.77) (-3.03) (-1.00) (-0.84)

Inflation -0.472 0.130 1.027** -0.120 0.136 -0.332 -1.497***

(-1.17) (0.30) (2.16) (-0.28) (0.22) (-0.81) (-2.75)

Ratio of MCAP to GDP -36.581*** -25.390*** -18.062*** -30.299*** -59.571*** -17.760*** -67.352***

(-9.14) (-5.98) (-4.33) (-7.27) (-10.67) (-4.30) (-10.02)

Offer size -8.179*** -5.300*** -5.801*** -4.472*** -8.325*** -7.729*** -10.311***

(-8.67) (-5.72) (-6.34) (-4.74) (-7.44) (-8.10) (-8.71)

Integer offer price -23.636*** -36.627*** -29.093*** -29.280*** -22.652*** -14.525*** -6.573*

(-9.07) (-13.65) (-10.74) (-10.40) (-7.11) (-4.99) (-1.95)

Bookbuild 8.994*** 7.970*** -1.418 4.450 10.581*** 4.601* 6.408**

(3.35) (2.93) (-0.50) (1.61) (3.30) (1.74) (1.98)

Firm commitment 29.948*** 17.679*** -1.429 23.237*** -5.230* 6.327** -0.578

(11.37) (6.79) (-0.49) (9.23) (-1.80) (2.13) (-0.17)

Secondary shares 14.690*** 10.515** 0.770 9.575* -13.047* 6.149 -10.205

(2.96) (2.09) (0.15) (1.89) (-1.85) (1.24) (-1.47)

Equity carve-out 11.989 17.195** 18.170** 16.534** 16.818* 16.837** 14.250

(1.49) (2.14) (2.23) (2.04) (1.87) (2.12) (1.62)

Privatization -20.103*** -31.238*** -19.374*** -31.391*** 0.830 -7.285 7.829

(-3.29) (-4.98) (-3.07) (-5.12) (0.10) (-1.19) (0.99)

Underwriter reputation 142.065*** 32.136 18.086 54.924** 16.708 67.731*** 71.222***

63

(6.31) (1.38) (0.79) (2.41) (0.70) (2.93) (2.90)

Venture capitalist 25.799*** 31.661*** 22.281*** 29.916*** 24.950*** 13.550*** 17.989***

(5.68) (7.01) (5.10) (6.58) (5.17) (3.17) (3.70)

High-tech dummy 6.847*** 8.079*** 10.039*** 9.026*** 14.976*** 12.621*** 16.214***

(2.76) (3.20) (4.01) (3.56) (5.20) (5.19) (5.71)

Stock return volatility 85.608*** 75.865*** 73.555*** 72.235*** 78.304*** 73.876*** 83.129***

(4.57) (3.99) (3.89) (3.80) (3.64) (4.04) (3.90)

Constant 219.957*** 131.183*** 136.535*** 117.689*** 16.575 66.904*** 21.646

(12.40) (6.30) (7.29) (5.75) (1.13) (3.20) (1.28)

Observations 7,864 7,864 7,864 7,864 6,014 7,864 6,014

R2 0.170 0.146 0.161 0.143 0.183 0.214 0.206