- IPO Underpricing and family controlled firms · 2017-01-05 · - IPO Underpricing and family...

ID number/name: Audun Fagerstrøm Skattum Mats Erik Strand

BI Norwegian Business School – Thesis

- IPO Underpricing and family controlled firms –

A study of the Norwegian market

Mats Erik Strand and Audun Fagerstrøm Skattum

Campus: BI Oslo

Date of submission:

02.09.2013

Supervisor:

Siv J. Staubo

Examination code and name: GRA 19003 Final Thesis

Programme: Master of Science in Business and Economics, major in Finance

This thesis is a part of the MSc programme at BI Norwegian Business School. The school takes no responsibility for the methods used, results found and conclusions drawn.

Final Thesis GRA19003 02.09.2013

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Acknowledgement

We would like to thank our supervisor, Siv J. Staubo for her helpful guidance in

writing this thesis. For helping with the collecting of data we thank Center for

Corporate Governance Research (CCGR). We would also thank those around us

who have given us a language revision and supported us through the process.


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Abstract

This paper examines how the ownership structure and corporate governance

mechanism in family controlled firms may affect the underpricing during an IPO

process in the Norwegian market.

The result from the quantitative method shows that family controlled firms have a

lower underprice when conducting an IPO, compared to non-family controlled

firms. By testing for firm age and gross proceeds, we find that family controlled

firms do have less information asymmetry, and this causes a lower underprice.

However, we do not find any evidence saying that a lower agency conflict in

family controlled firms will influence underpricing.

Surprisingly the underwriter rank seems to affect underpricing differently

depending if the firm are controlled by a family or not.


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1 Content Acknowledgement ................................................................................................... 2

Abstract .................................................................................................................... 3

1 Introduction...................................................................................................... 6

2 Literature review .............................................................................................. 8

2.1 Asymmetric information ........................................................................... 8

2.2 Agency conflict and allocation of shares ................................................ 10

2.3 Behavioral explanations .......................................................................... 11

2.3.1 Cascades: ......................................................................................... 12

2.3.2 Investor sentiments .......................................................................... 12

2.3.3 Prospect theory ................................................................................ 12

2.4 Why take a firm Public ........................................................................... 13

2.5 Family controlled firms ........................................................................... 14

2.6 Other empirical studies on the topic. ...................................................... 17

3 Hypothesis ..................................................................................................... 17

3.1 Hypothesis 1: Family controlled firms are less underpriced than

non-family controlled firms are . ................................................................ 17

3.2 Hypothesis 2: Higher firm age will result in lower underpricing. .

................................................................................................................. 18

3.3 Hypothesis 3: Proportion of shares issued and issue size will

affect the underprice. ................................................................................... 19

3.4 Hypothesis 4: Family member as CEO will reduce agency

conflicts, resulting in lower underprice. ................................................. 20

4 Variables ........................................................................................................ 20

4.1 Dependent variable ................................................................................. 20

4.2 Independent variables ............................................................................. 21

5 Data collection ............................................................................................... 24

5.1 Criteria for Our Data ............................................................................... 25

6 Descriptive ..................................................................................................... 26


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7 Methodology .................................................................................................. 32

8 Regression analysis ........................................................................................ 35

8.1 Results hypothesis 1: ............................................................................... 35

8.2 Result hypothesis 2: ................................................................................ 37

8.3 Result hypothesis 3a ............................................................................... 38

8.4 Result Hypothesis 3b .............................................................................. 39

8.5 Result hypothesis 4: ................................................................................ 40

8.6 Result from control variable ................................................................... 40

9 Robustness test .............................................................................................. 42

10 What could be improved? .............................................................................. 42

11 Conclusion ..................................................................................................... 43

12 References ....................................................................................................... 45

13 Appendix........................................................................................................ 49

13.1 Appendix 1 – IPO and closing price. .................................................. 49

13.2 Appendix 2: Underwriter rank ............................................................ 51

13.3 Appendix 3: Residuals......................................................................... 52

13.4 Appendix 4: Correlation matrix .......................................................... 52

13.5 Appendix5: Robusteness test............................................................... 53

13.6 Appendix 6: Preliminary thesis ........................................................... 54


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1 Introduction

In this thesis we are investigating the relationship between the ownership structure

and the underpricing related to initial public offering in the Norwegian market,

more specific: the difference between family firms and non-family controlled

firms. We will look at the different factors that can affect the underpricing when

conducting an IPO and relate this to the structure of firms controlled by families.

Underpricing in an initial public offering is a well-known phenomenon and has

been subject for many research papers. As early as 1975 Roger G. Ibbotsen found

evidence of underpricing in initial public offerings, but could not explain why it

occurred. “Strangely enough, we have not solved the mystery of the empirically

observed underpriced new issue offerings.” (Ibbotsen 1975)

However, there are little research on the topic concerning family controlled firms

and valuation when they are conducting an IPO.

Even though research on underpricing and IPOs has been a popular research topic

for decades, the transformation from private to public firm have yet to become

clear. There has been a lot of research on the determinants of underpricing trying

to explain why this phenomenon occurs, but a lacking understanding on what is

the corporate governance mechanism that will have an effect under an IPO

process.

Exploring the IPO performance in family controlled firms can give investors

important insights on how to evaluate different investment objects.

In this thesis, we will focus on how the ownership structure can affect information

asymmetry and agency conflict between owners, management and underwriter.

We will also focus on theories regarding the owners desire to maintain control

over the firm.

By using data on 46 Norwegian listed firms, we have investigated how the

different causes of underpricing are related to family controlled firms.

Our main findings show that that family controlled firms with ownership larger

than 25% have a lower underprice when conducting an IPO, compared to non-

family controlled firms.

By testing for company age and gross proceeds, we find that family controlled

firms do have less information asymmetry, and this causes a lower underprice.


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However we do not find any evidence saying that a lower agency conflict in

family controlled firms will influence the underprice.

Surprisingly the underwriter rank seems to affect the underprice differently

depending on the company are controlled by a family or not. A lower ranked

underwriter cause a lower underprice for family controlled firms and vice versa

for others.

This thesis can shed light onto the control and operational differences between the

two groups of family controlled firms and non-family controlled firms, and could

be interesting for both academics and investors.

Research has shown that family controlled firms have different behavior from

non-family controlled firms and these behavioral differences complicate the

investors’ effort to evaluate the quality of family controlled firms. These

differences will also help families to seek means to best preserve the value of

stocks and assets of the firm. By putting effort in areas of corporate governance

and produce positive signals, management and owner may enhance the value of

the firm.

In this paper, we will first go through literature and research on the topic of family

firm and IPO underpricing, before we present hypothesis and data. Finally, we

will review the results from the regression and the conclusion.


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2 Literature review

The phenomena of short-term underpricing in an IPO process is a well-

documented subject and has been a topic in research for decades.

In the article “A review of IPO Activity, pricing, and Allocations”, Ritter and

Welch (2002) explain the plausible causes of short-run underpricing. They focus

on theories based on asymmetric and symmetric information, theories based on

allocation of shares, agency conflict and behavioral explanations

2.1 Asymmetric information The theory of asymmetric information has been a popular theory among

researchers and was first explained by Grossman (1976).

The issuer is more informed than the investor and tries to stand out as a good

investment object, by signaling either high or low quality. High quality issuers are

selling at a lower price and will try to recap the loss in the future. This is a game

between the issuer and investors, the issuer trying to reveal the investors

valuation, while the investor tries to identify the true value of the firm. The

investors who want to pay a high price will require something in return to show

their willingness and the issuer will present a “gift on the table” in form of a lower

price (Ritter and Welch 2002). This theory is supported by Benveniste and Spindt

(1989) and their model of information acquisition saying an investor must be

rewarded to reveal their true demand during a book building period.

Leland and Pyle (1976) argues that because of moral hazard and exaggerated

quality, lenders have difficulty revealing the true characteristics of borrowers and

see which project are of good or bad quality. However, they suggest that the

action of the lender will speak louder than words. An entrepreneur has more

information about the expected future cash flow and is signaling high quality by

investing in the project. His willingness to take up a greater share of the equity

and thus a larger welfare loss may lead to the leveling of information asymmetry.

Another approach is to assume the investors are more informed than the issuers,

for example about the market demand. Assuming investors are equally informed

could explain why they purchase at a lower price, knowing they all want to make

profit and will request those issues that are valued at a significant lower level


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relative to real value, but according to Ritter and Welch (2002) this could not

explain the phenomena of an overpriced IPO.

Rock (1986) show on the other hand that underpricing is a result of differentially

informed investors. The issuer and the underwriter possess more information

about the firms anticipated performance in the future than each investor possesses

individually, but will have less knowledge than all investors combined. Whereas

uninformed investors tend to bid randomly, and informed investors only bid on

favorable priced IPO. However, there are few informed investors in the market,

forcing the issuing firm to lower their prices to enable sales among the

uninformed investors and keeping the issued shares fully subscribed. Setting the

price down will increase the demand from uninformed investors, create

oversubscription and the need for rationing occurs. The demand from uninformed

investors continues to increase to the point where all subscriptions are made by

uninformed investors. At this point, a lower price can reduce the probability to get

an allocation, leading uninformed investors to withdraw. The uninformed

investors will on average have abnormal return equal to zero. This theory is

according to Ljungqvist (2007) similar to the theory of winner’s curse, where the

winning bid will be largely overvalued.

Loughran and Ritter (2002) explain the phenomena of underpricing as the indirect

cost of having an underwriter. The issuer puts money on the table instead of

bigger fees to the underwriter. Their survey showed that IPOs with high

underpricing often had a lower initial valuation, but was priced higher as a result

of high demand for the IPO. The investors will be less critical to high

underpricing since their initial value has increased.

However, Ritter and Welch (2002) are unsure of how this value is divided

between the issuer, underwriter and the investors.

According to Ritter and Welch (2002) all theories on asymmetric information are

based on the assumption of correlation between asymmetric information and

underpricing. They indicate that the only way this can be done is to sell bundles of

both hot and cold issue to investors. They also point out that empirical research is

showing underpricing to be higher than the cost of bundling.


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Theories on symmetric information are often based on the issuer’s fear of

litigation. With a higher price the probability that the share is overpriced increases

and the issuer will sell their shares at a lower price to avoid lawsuit from outside

shareholders in the future (Ritter and Welch 2002). Nevertheless, this will

according to Ljungqvist (2007) only be a second-order driver for underpricing.

2.2 Agency conflict and allocation of shares Even though asymmetric information and symmetric information has been a

popular theory among researchers, Ritter and Welch (2002) claims that these

theories do not count for all underpricings.

They argue that underpricing can be explained by the agency conflict between the

issuer and the underwriter, the share allocation on one side, and the behavioral

explanation on the other side.

An interesting question is “How do investors decide in which issues to request

IPO allocations, and how heavily influenced is this by perceptions of what others

are going to do?” (Ritter and Welch 2002).

Arthurs et al (2008) describes the relationship between owner managers,

underwriter and venture capitalists and how there exist a multiple agency conflict

between the parties and not only the classical conflict between

owner/management and large shareholders/small shareholders.

The management together with the underwriter will determine the issue price, but

may have different incentives for the price level and allocation of shares.

The management may use the IPO as a mean to maximize own utility level on the

expense of future shareholders and non-managing shareholders. (Ljungqvist 2007)

In addition, the connection between underwriters and investors are questioned.

Arthurs et al (2008) argue that financial banks are better off having a long-term

relationship with the institutional investors and underpricing is a method to

maintain such a good reputation. They will also benefit from being responsible for

allocation decisions. The underwriters will have different incentives than the

managers and firm owners that have hired them.

However Carter, Dark and Singh (1998) and Michaely and Shaw (1994) have

done research on the connection between underwriters reputation and

underpricing. They find evidence that high underwriter reputation is associated

with lower short-term underpricing.


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According to Ritter and Welch (2002) the theories on allocation of shares has

been a more popular explanation among researchers, particular the allocation of

shares to institutional investors and individual, due to the big size of money left

on the table. Shares in an IPO are allocated to investors willing to buy the shares

and can be done either by auction, fixed-price offer or a book-building method.

By going public the issuer are taking a step further in the direction of separation

between ownership and control, and issuers may have different incentives for how

the new ownership structure and separation of power should be carried out.

Brennan and Franks (1997) find evidence that underpriced IPO tend to be

oversubscribed. They argue that underpricing increases the demand and gives the

issuer the opportunity to discriminate the allocation of shares and often in favor of

small applicants to prevent the allocation of large blocks and prevent new large

shareholders. This strategy gives the issuer the opportunity to maintain control of

the firm after the IPO is finalized.

However Habib and Ljungqvist (2001) advance another explanation and argue

that some IPOs are less underpriced because the owners have strong incentives to

keep a high price level. Owners who sell a big proportion of their shares will have

more to lose and this gives an incentive to put a lot effort and money to avoid high

underpricing, while owners issuing a smaller proportion of shares will care less

about the underpricing.

2.3 Behavioral explanations

Researchers are concerned of how much of the first day return could be explained

by asymmetric information, agency conflict or allocations of shares. They have in

recent years focused on behavioral explanations for underpricing. The theory on

behavioral explanations is based on either the irrational investor bidding up the

price above the true value or the “smart” issuer who see opportunities when the

market is biased (Ljungqvist 2007). Ljungqvist (2007) describes four possible

theories on how behavior could affect the short term return as cascades, investor

sentiments and prospect theory and mental accounting.


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2.3.1 Cascades:

Ljungqvist (2007) explain how cascades leads to investors exclude their own

information and are basing their investment decisions mainly on investors

previous purchase. This gives market power to investors in an early stage, and

provides these investors the authority to demand a lower IPO price. To secure that

negative information from one investor reach others, the underwriter has to ensure

there is no free float of information.

2.3.2 Investor sentiments

Ljungqvist (2007) examines the theory of sentiment investors and argue that the

effect on first day return may be significant when firms go public. Because of the

difficulties of valuating IPO firms, the overoptimistic investor will tend to drive

the price up. However, this overvaluation will create losses in the long run. Ritter

(1991) have investigated the long run performance on IPOs and argues that over

optimism among investors, when a firm goes public, leads to a negative

performance over a three-year period. According to Ljungqvist (2007) the issuer

will seek to maximize the value over fundamental value and will withhold a larger

proportion of shares, creating a higher demand among sentiment investors.

Ritter and Welch (2002) describe how some investor sentiment could drive up the

prices and overvalue the firm because they are too optimistic. A “smart” issuer

will tend to issue shares or take the firm public when they sense investors are to

overoptimistic about the market. This model assumes that firms going public in a

hot market will have more underpricing than firms going public in a cold market.

Loughran and Ritter (2002) measured if the market is hot or cold after the amount

of IPO’s in a certain year.

2.3.3 Prospect theory

High underpricing will also according to Ritter and Welch (2002) lead to a higher

number of new issues, because of the encouragement from underwriters who see

the high valuation as an opportunity for the issuer to make money.

Ritter and Welch (2002) examine why issuers are willing to leave so much money

on the table and explain this by prospect theory. The issuer will easier see the

wealth gain caused by the price increase, after the IPO, than the wealth loss


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created by an issue price lower than true value. If the wealth gain outweighs the

wealth loss, issuer will be willing to leave millions of dollar on the table.

Ljungqvist (2007) goes through the empirical evidence for these theories. He

shows that research supports the theories on cascades and investor sentiment, but

is more inconclusive on the topic of prospect theory. He also points out that there

has to be done more research on the area of behavioral explanation for

underpricing.

Ritter and Welch (2002) argues in their article that the classical theories on

information asymmetry, agency conflicts and allocation of shares will have

greater explanatory power on the short term underpricing while behavioral

explanations have a greater effect on the long term underpricing.

2.4 Why take a firm Public

There are several differences between a family controlled firm both in the

structure of ownership and their motives to conduct an IPO.

Ritter and Welch (2002) describe the reasons why a firm wants to go public by the

motive to raise capital and the desire to trade at a public market place. Mainly a

firm conducts an IPO so they can raise capital, to be able to invest in positive

NPV projects, or to satisfy the owners need for capital. In a family firm, some

family members sell parts of their shares for personal reasons, while in non-family

firms owners can use the situation to get a more diversified portfolio. Ritter and

Welch (2002) also look at different theories in the life cycles of the firm and

market timing, and explain how market timing may be important for the issuing

firm. They also points out that some firms may benefit from going public when

they reach a certain stage in their life cycle due to the benefits of being a public

firm. Hsieh, Lyandres and Zhdanov (2011) link the life cycle and IPOs against to

a takeover strategy. They argue that a firm’s true value only will be revealed when

they are listed on a public stock exchange, and by conducting an IPO the firm may

easier be spotted as a takeover subject. Ritter and Welch (2002) argues that an

entrepreneur will get a higher price after an IPO because the acquirer will have

difficulties to pressure the price when they in addition have to negotiate with

outside investors. Although, according to Bancel and Mitoo (2009) an IPO may

not always be an exit for the entrepreneur. In their research they show that M&As


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are not the main cause for family controlled firms. However, these firms main

reason to go public is an attempt to rebalance the power between bankers and

creditors without the family losing control over the firm.

When a firm reach a certain stage in its lifecycle, it could be beneficial to go

public for example to expand. Publicity and also the advantage of being the first

in its industry are also vital reasons.

By going public, the owners often sell a part of the firm to new shareholders,

which could have been done by selling in the private market. Selling shares

privately to several new shareholders would make the owners able to negotiate the

price and then receive a higher price for their stocks. However Chemmanur and

Fulghieri (1999) argues that this would not be efficient since the evaluation cost

would become too high compared to the information cost of going public, and

further more making the stock price lower, compared to an IPO.

Zingales (1995) points out that the initial owner could use the IPO to be able to

restructure his position in the firm, and being able to sell out the proceeds he

wants to maximize. Many entrepreneurs seizes this opportunity to “collect the

prize” of their work and sell the firm.

However, Litz (2004) explains the importance to distinguish between family firm

and entrepreneurs and refers to later research in entrepreneurship, showing the

entrepreneur to be different in the management from the organization in family

firms.

2.5 Family controlled firms The key difference between a family controlled firm and a non-family controlled

firm is the separation of control between management and owners. In a family

controlled firm, family members will have active participation as both owners and

in the management team in contrast to non-family controlled firms where the

separation between management and owners is absent. (Chambers. 2012).

Anderson and Reeb (2003) argues that a family firm is separated from a non-

family firm by the amount of shares the founding family represents and whether

they are to be found in the board of the firm. However, it is not definite how large

share of the firm the family has to possess. In their paper, they show an example

where the controlling family had as little as 2% of the shares, and still were the


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majority owner. Bøhren (2011) states that the definition of family controlled firms

are firms where the family possesses more than 50 % of the shares. He explain

that it is difficult to set the exact line for when a firm is classified as a family

controlled firm or not. Changes of statutes often require a majority of two-third.

Nevertheless, he points out that not all shareholders turn up in the general

meetings. Therefore the family may have control with lower than 50% ownership.

This is supported by La Porta, Lopez-de-Silanes and Shleifer (1998). They argue

that a definition of a family controlled firm is a firm where a family owns 20% or

more of the shares. NHO are also seeking for å new definition of Family

controlled firms and are working for a common European definition for family

controlled firms, where a family controls 25% or more of the firm (NHO 2008)

Anderson and Reeb (2003) explain how the amount of CEO ownership affects the

firm risk and states that the amount of management which also owns a part of the

firm is greater in a Family controlled firm than in a non-family controlled firm. If

the managers have shares in the firm they will carry part of the risk when

conducting an IPO. Ljungqvist (2007) indicate that the agency cost will diminish

when the ownership is so large that it may outweigh the private benefits. The

agency conflict between owner and underwriter can also be reduced when both

management and owners have the same incentive for the price level.

Anderson and Reeb (2003) present another advantage of having owners as

managers, and explain why family firms have higher profitability than non-family

controlled firms, because the CEO position is held by one of the family members

who understand the business. They conclude that when the owner both control

and lead the firm, the agency cost will conclusively be reduced and the firm will

perform equally or superior to non-family controlled firms. This is supported by

Villalonga and Amit (2006) who conclude that family controlled firms are more

profitable than other firms are. They state that value is added when the founding

owner serves as the CEO or as the chairman of the board. However they find no

evidence of this added value when the inheritors serve as the CEO or chairman.

The value created when founding owner controlled the firm seems to deteriorate.

They also claim that the agency cost created of the conflict between the family

and minority shareholders are smaller than the conflict between management and


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shareholders in a non-family controlled firm. However, they find that the low

agency cost between family and non-family firms, will similarly to the

profitability, deteriorate when the heritage are in control.

Bøhren (2011) have done similar research in the Norwegian market. He

discovered evidence of family controlled firms being more profitable than other

firms, but this premium disappears when the numbers are adjusted for other

factors that could have an effect on the profitability.

According to Chambers (2012) the success of family controlled firms are based on

the family business ability of long-term thinking. The family’s wealth depends on

the value of the firm, and the strategy for the family is to take board decisions,

making sure the persistence of the firm through generations This could benefit in

a more stabile valuation of the firm, leading to less information asymmetry. (Litz

2004).

Bøhren (2011) explains how the family members’ income and wealth are based on

salary; dividend and the value from one single firm, and not a diversified portfolio

like other investors tend to have. The risk of not being diversified has to be

reduced within the firm through the key processes of stabile income, low level of

fixed costs and a low debt ratio. Bøhren (2011) refers to a Norwegian study done

by Svalland and Vangstein (2011) where they find evidence that family controlled

firms have a significant lower operational risk. This could be explained according

to Bøhren (2011) by the involvement in the operations by the owner.

Bøhren (2011) argues further that family controlled firms going public are rare,

but some of the largest firms on the stock exchange were in fact controlled by

families at the time they went public, and some are still family controlled after the

IPO

When a family firm requires capital and this is done trough an IPO the founder

will according to Chambers (2012) find it hard to adjust to a partial ownership.

Selling to many shares leads to the loss of control of the firm. To retain a majority

of shares within the family the proportion of shares issued and the allocation of

shares have to be carefully determined.


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2.6 Other empirical studies on the topic. Daugherty and Jithendranathan (2012) found that family firms are less

underpriced than non-family controlled firms in the US market between 1996 and

2004. They explain the difference by diverse ownership structure and argue that it

is the effectiveness of managers in the family firms who achieve less

underpricing. However, Ding and Pukthuanthong-Le (2009) found evidence by

examine the Taiwan stock market that lower underprice occurs when an outsider

as CEO managed the family firm. It is clear that the ownership structure will have

various impacts on the underpricing in different markets. In both studies the age

of firms conducting an IPO has been tested upon. They found similar results, that

firms which are older, has lower underpricing when conducting the IPO. A main

difference between these two studies is the age of the two markets. The Taiwan

market does not have so many long lasting firms, while the US market has more

history and firms with longer lasting owners. (Ding and Pukthuanthong-Le 2009)

3 Hypothesis

First, we want to test if family controlled firms are more underpriced than non-

family controlled firms are. Second, we want to test the determinants for

underpricing and relate these to the structure and mechanism in family controlled

firms.

Our hypothesis’ are based on asymmetric information and how the skewed

information between issuer and investor will lead to a higher underprice. In

addition, we will test for agency conflict and see the effect on underpricing in

family controlled firms.

3.1 Hypothesis 1: Family controlled firms are less underpriced than

non-family controlled firms are .

Family controlled firms have shown to have different structure and motive for

going public than non-family controlled firms (Chambers 2012, Bancel and Mitoo

2009).

Ritter and Welch (2002) and Rock (1986) among others, have argued on how the

information asymmetry would be the cause of underpricing. We believe that


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Chambers (2012) argument on how families have a different strategy, causing a

more long-term thinking and the reduced operational risk explained by Bøhren

(2011) will lead to a reduced information asymmetry, causing a lower underprice.

In addition, the controlling family will often use the IPO as a chance to restructure

the firm and meet its commitments to creditors, and not collect their “price” as an

entrepreneur more easily will do. (Bancel and Mitoo 2009). Often, most of the

controlling family’s wealth is within the firm, and they will try to maximize and

maintain their wealth by choosing their right strategy. Following Habib and

Ljungqvist (2001), the desire to maintain the family’s wealth and simultaneously

restructure at retain control may give the family incentive to struggle more in an

attempt to keep the underprice low.

Result presented by Daugherty and Jithendranathen (2012) showed that family

firms in the U.S. market experienced a lower underprice when they conducted an

IPO.

Some of these factors will be investigated further in the three following

hypotheses, trying to explain why family firms could be less underpriced.

3.2 Hypothesis 2: Higher firm age will result in lower underpricing .

As shown in the previous chapter the information asymmetry will be reduced by

the approach of long-term decision making. When conducting an IPO the

information and valuation process is costly. Past data are used when evaluating

the firms total value, and less past data could make the evaluation harder (Ritter

1984). This mean that the age of the firm will affect the underpricing of the firm.

Maturity of the firm when conducting an initial public offering has been in several

studies used to describe how established the firm is. Daugherty and

Jithendranathen (2012) and Ding and Pukthuanthong-Le (2009) has found in their

two separate markets that the older the firm is, the less underpricing occurs. We

also get from Rock (1986) that risk is related to underpricing, in such term that

underpricing increase with higher risk of a firm. By these negative effects on

underpricing, age could be a proxy of information asymmetry, since information

asymmetry will decrease when age increase.


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3.3 Hypothesis 3: Proportion of shares issued and issue size will

affect the underprice.

3a: Higher offer size will lead to a higher underprice.

3b: Higher proportion of shares sold by the controlling family will lead to a

higher underprice.

In an initial public offering it differ a lot of how many percent of their shares the

issuing firm offer to the public. Techniques like issuing fewer shares and use

underpricing as a tool to control the allocation of shares, gives a family the

opportunity to restructure and maintain the control of the firm. This hypothesis

support Rock (1986) theories on asymmetric information and the need to lower

the price in an attempt to both reveal the investors own valuation and attract both

informed and uninformed investors. At the same time, the controlling family want

to maintain control after the IPO (Chambers, 2012), and is willing to lower the

price in an attempt to discriminate the shares against institutional investors and

prevent large blocks (Brennan and Franks, 1997). This theory indicates that

family controlled firms will issue less shares compared to non-family controlled

firms, leading to a lower underprice when they take the firm public. The size of

the issued shares and the price will be a weighted decision between the family’s

desire to maintain control or maximize the gross proceeds. This is consistent with

Michaely and Shaw (1994) who finds that higher size of the issue is related to a

higher underprice. By separating the hypothesis into two subgroups, we are able

to examine more closely, both the effect of offer size and the signaling effect

caused by proportion of shares sold by the controlling family.

In hypothesis 3b, we want to test if the proportion of shares sold by the controlling

family will affect the investor’s perception about the long-term strategy presented

by Litz (2004) and the lower operational risk in family controlled firms explained

by Bøhren (2011), and relate these factors to the risk of investing in the firm.

According to Leland and Pyle (1976), a reduction in the entrepreneur’s ownership

will send a signal of low quality, which could lead to a higher underprice.


20

3.4 Hypothesis 4: Family member as CEO will reduce agency

conflicts, resulting in lower underprice.

This hypothesis follows Arthurs et al (2008) argument saying that the agency

conflict between both owner and manager and the agency conflict between owner,

management and underwriter could be reduced when a family member possesses

the CEO position. This reduced agency cost could according to Ritter and Welch

(2002) lead to a lower underprice when a firm goes public.

The variable fam_CEO and ult_fam tests the relationship between underpricing

and the amount of family involvement in the management. If involvement from

family ownership occurs in a firm, Anderson and Reeb (2003) argue that it is

likely to decreases agency cost. They point out that the advantaged increases

when the CEO position is held by either a family founder or a hired-hand. It is

assumed that both these variables will have a negative effect on underpricing.

4 Variables

4.1 Dependent variable

Underpricing

Underpricing (UP) serves as the only dependent variable in all of the regressions

in this thesis.

The variable is based on the same variable used by Ritter (1991), Ljungqivist

(2007) among others, and was first discovered and referred to by Ibbotson (1975).

Underpricing refers to the price per share before the listing of the firm, called the

offer price (OP), and the difference between the price or real value set by the

market the first trading day; called the Closing price (CP). Ritter (1991). The

underpricing is mathematically the percentage difference between the offer price

and the closing price, and is often referred to as the first day return.

(CP-OP)/OP

If the IPO price is lower than the closing price first trading day the issuer will find

that the firm has been sold to a lower price than real value.


21

In this thesis the underpricing will be have a positive sign while overpricing is

notated with a negative sign. A higher price increase the first trading day reflects

an equally large underpricing.

4.2 Independent variables

Firm age (Ln_age)

Firm age (Ln_age) is used as an independent variable in all of the following

regressions, and is used to test for hypothesis 2. Rock (1986) express that there is

an underlying risk which is connected with underpricing, indicating that

underpricing occurs due to different kind of risks. The less past data a firm has,

the more inaccurate or risky the price becomes to measure, giving more

information asymmetry according to Ritter (1984). A common key factor of

possessing less past data would be to be a younger firm, which has not existed for

many years. Consequentially the age of a firm would be a preferable proxy to

measure risk, which could explain how more information provide a more accurate

price. In our regression, age is defined as the natural logarithm of 1 plus (Date of

IPO minus the year it was founded).

Offer size (Ln_Offersizeis)

Offer size (Ln_Offersizeis) the independent variable used to test for hypothesis 3a

and how the gross proceeds will affect the underprice. This variable is defined as

the natural logarithm of offer price multiplied by number of shares issued (NSI),

which is the same as gross proceeds. Michaley and Shaw (1994) found that gross

proceeds are negatively correlated with underpricing. Gross proceeds is also used

by Habib and Ljungqvist (2001) and Beneviste and Spindt (1989) where offer size

was used as a measure of risk. By using gross proceeds as proxy for offer size, we

want to see how this variable will affect underpricing in the Norwegian market.

Log(NSI*IPO price)

Family dummy variables

Dummy variables for family ownership the year before conducting IPO – Fam_50

is a dummy variable used in the first regression with the value of 1 when ultimate

family ownership is over 50% and value of 0 when under 50%. By using family


22

ownership as a dummy variable, we will be able to see how a firm with ownership

above 50%, effects underpricing UP in our regression. 50% is the requirement for

a firm to be classified as a family controlled firm due to theory by Bøhren (2011)

In regression number two, the requirement for the dummy variable of family

ownership is decreased from 50%, to 25%.This variable (Fam_25) is in coherence

with research by La Porta, Lopez-de-Silanes and Shleifer (1998) and NHO

(2008). It is interesting to uncover if there could be any difference in the outcome

by using 25% and 50%in the regression. By dropping the requirement we also

assume additional number of firms in the sample.

These variables are used to test for hypothesis 1.

Ultimate ownership by families (Fam_Ult)

To do a more thorough investigation whether or not family ownership has impact

on the underpricing we have also added a variable that shows the ultimate family

ownership, as a percentage of total outstanding shares. By using ultimate

ownership as the family ownership variable, we will see how an increase in

ownership effects underpricing.. This variable is measured as the natural

logarithm of the percentage of shares owned by families in the firm.

Used as a additional variable to test for hypothesis 1.

Controlling family has CEO (Fam_Ceo)

This variable will capture if the controlling family possesses the CEO position

with one of their family members, and measure this effect against the

underpricing when the firms goes public, and is used to test hypothesis 4. This

will be a dummy variable, 1 if the controlling family has the CEO and 0 if the

CEO position is held by a CEO outside the family. This variable is based on the

theory by Andersoon and Reeb (2003), where they uncover how agency cost in a

firm tends to diminish when a family member serves as the CEO. This variable

could disclose whether or not the CEO could have an effect on underprice.

Ownership of CEO (Own_Ceo)

This variable is used to conduct a more thorough analysis of the CEOs effect on

underpricing and is a supplement to the Fam_Ceo, to determine whether there is a

reduced agency conflict in family controlled firms.


23

This variable is to measures the effect of having a CEO with a large ownership.

Estimated in percentage of shares owned by the CEO it is used in all three

regressions to detect any effect the CEO has to enhance underpricing.

Proportion of shares sold out by the controlling family (Prop_Sold)

Prop_Sold is a variable made to reveal how the proportion of shares sold by the

controlling family, affects the underpricing in all three regressions. This is

calculated as the percentage difference between the ultimate ownership the year

the IPO occur (Ot) and the ultimate ownership the year before the IPO (Ot-1).

(Ot-Ot-1)/Ot-1

This variable will capture the signaling effect, inspired by Leland and Pyle (1976),

and is used as a determinant in hypothesis 3b.

Underwriter ranking (Ln_Uw)

Ln_Uw serves as the variable for underwriter rank. This variable is used as a

control variable in all of the regressions.

There are several ways to calculate the underwriter ranking, and Carter Dark and

sing (1998) explains three possible methods; the Carter and Manaster (1991)

method, a modification of this method made by Johnson and Miller (1998) and the

Megginson and Weiss (1991) method. They find all methods to be significant

against underpricing when tested individually, but only the method described in

Carter and Manaster (1991) is found significant when they were tested

simultaneously . This method is according to Carter Dark and Sing (1998) the

most superior way to estimate the quality of underwriters, ranking underwriters

from 0-9 depending on which section they were listed on tombstone

announcements. In spite of the superiority of the Carter and Manaster method,

Carter Dark and Sing (1998) argue that this method requires more effort to

construct.

This method could be difficult to adapt to the Norwegian market, where there are

smaller syndicates and often only one underwriter per issue, resulting in a

distorted view of the quality of financial banks. We have therefore chosen to use

the method presented by Megginson and Weiss (1991). The quality of each

underwriter is measured as the percentage of the total amount brought to the

market. If the underwriter has more than one lead underwriters when conducting


24

an IPO, the average quality of the underwriters are used as a proxy (see appendix

2 for complete list).

The underwriter ranking are based on 191 IPOs in the Norwegian market between

2001 and 2010 and are divided into three subgroups. 2001-2004, 2005-2007 and

2008-2010. In contrast to research done by Megginson and Weiss (1991) and

Carter and Manaster (1991) this sample is fairly modest. Their sample consisted

of 640 and 501 IPO’s respectively, and it is uncertain that we will get a satisfying

result based on only 191 observations. However, we believe that even with a quite

constricted sample, we can retrieve enough information to attain an indication on

the variables’ influence on underpricing.

5 Data collection

The data is based on a sample of IPOs listed on Oslo stock exchange in the years

between 2001 and 2010, both from Oslo Børs and Oslo Axess.

Our primary source of data for the short term return has been different news and

equity feeds provided by Oslo stock exchange via the department of Finance at BI

in addition to Thomsen Reuters DataStream. The Offer prices could unfortunately

not to be found in any systematic database, and we had to look through different

sources to be able to create a database. Most of them were collected in the news

web provided by Oslo stock exchange, Equity Feed provided by BI (originally

from Oslo Stock exchange) and Prospectus provided by the issuing firm. (See

appendix 1 for complete list of firms). All family variables and foundation dates

are collected from the CCGR database. This database contains information on

Norwegian firms with limited liabilities. However there are some missing data on

some firms, leading to fewer observations. We have not given priority to collect

and update the family variables because these data’s are considerably intricate to

find and may vary from those already existing in the CCGR database.

In the period between 2001 and 2010, there were 211 new listings on Oslo stock

exchange. Because many of these firms are foreign or are listed due to merger or

demerger, these firms have been excluded. Our analysis is based on new listings

on Oslo Stock exchange between 2001 and 2010. From this sample there are 125

with IPO and closing prices available.


25

5.1 Criteria for Our Data Norwegian firms conducting an IPO between 2001 and 2010.

- Available information on the IPO

- IPO price

- Total number of shares

- Number of shares issued

- Closing price first trading day

- Data on Underwriter / financial bank

- Not firms already listed on the stock exchange doing a merger or demerger

- Not firms that have been listed and then delisted a few years pre the

second time listing.

- Family Data both the same year and in front of the IPO

Because of these criteria, the firms had to be older than one year in front of the

issuing data.

In addition we have removed banks and financial institutions due to the

Norwegian regulation of the financial sector and their ownership structure. There

are formal requirements of the ownership structure for financial institutions saying

that one owner is not allowed to hold more than 10% of the equity (Bøhren and

Ødegaard 2002)

When these criterias are taken into account, we are left with only 46 firms from a

total of 211. We have not specifically selected firms, but the modest number of

firms are mainly due to missing data on the family variables. Particularly the

requirement of data pre and post the IPO resulted in the loss of observations due

to the difference in reporting of Public and not public firms.


26

6 Descriptive

The annual amount of IPOs is presented in table 1 and it is clear that the sample of

family controlled firms larger than 50% are relatively small. In total there has

been 21 family controlled firms larger than 50% and 46 with family ownership

larger than 25% conducting an IPO in the years between 2001 and 2010.

According to Brooks (2011) the sample size could have an effect on the outcome

of the regression, and a smaller sample size will increase the chances of type one

and type two errors. We will therefore in addition test for Family controlled firm

with an ultimate ownership larger than 25%. This is in accordance to La Porta,

Lopez-de-Silanes and Shleifer (1998) arguments saying that family controlled

firms are firms where a family will have 20% or more of the shares, and definition

of 25% by NHO (2008). The table 1 reports that money left on the table are

larger in years with many IPOs, supporting the arguments by Ritter (1991) saying

money are left on the table in years with high numbers of IPOs are due to the over

optimism among investors, the offer price become higher than the real value.

Table 1 show overall that family controlled firms on average have a lower first

day return, however this number is saying very little on the economic impact on

the shareholders wealth loss. By comparing the money left on the table we see

that the amount is considerably lower when the firm is controlled by a family both

when the ownership is larger than 50% and 25%. This number should intuitively

be related to the level of underpricing, but it is interesting to see if family

controlled firms will follow the same pattern as non-family controlled firms and

relate the high underpricing in years with high frequencies to Loughran and Ritter

(2002) explanation on hot and cold issue.


27

Tab

le 1

show

s the

des

crip

tive

stat

istic

s for

firm

s con

duct

ing

an IP

O o

n O

slo st

ock

exch

ange

eac

h ye

ar fr

om 2

001-

2010

. The

firs

t mai

n-co

lum

n sh

ows t

he d

escr

iptiv

e fo

r all

firm

s goi

ng p

ublic

. The

nex

t mai

n-co

lum

n sh

ows t

he d

escr

iptiv

e fo

r fam

ily o

wne

rshi

p la

rger

than

50%

and

the

last

mai

n-co

lum

n sh

ows t

he d

escr

iptiv

e fo

r fam

ily o

wne

rshi

p la

rger

than

25

%

Firs

t day

pro

fit is

her

e re

ferr

ed to

as t

he sa

me

as u

nder

pric

ing.

Ye

ar20

0120

0220

0320

0420

0520

0620

0720

0820

0920

10

Nu

mb

er

of

IPO

(N

ew

issu

e)

116

422

4632

5716

321

Un

de

rpri

ce M

ean

0,08

40,

017

-0,0

230,

015

0,08

20,

054

0,04

10,

013

No

val

ue

-0,0

47

Un

de

rpri

ce M

ed

ian

0,00

00,

000

-0,0

230,

000

0,02

50,

036

0,02

20,

000

-0,0

04

Mo

ne

y le

ft o

n t

able

7964

0198

,817

4792

993,

800

-348

1350

,000

4199

285,

850

9877

55,3

0389

4612

7,32

114

8772

91,1

56-1

5369

43,2

40N

o v

alu

e-2

1949

720,

797

Au

toco

rr0,

2918

Nu

mb

er

of

IPO

Fam

ily

con

tro

l >50

%1

20

34

35

20

2

Un

de

rpri

ce F

amil

y co

ntr

ol >

50%

Me

an-0

,013

0,02

2N

o v

alu

e-0

,061

0,03

80,

034

0,02

80,

111

No

val

ue

-0,0

84

Un

de

rpri

ce n

on

-fam

ily

con

tro

l0,

101

0,00

00,

047

-0,0

110,

053

0,04

90,

021

-0,0

04N

o v

alu

e-0

,114

Mo

ne

y le

ft o

n t

able

-135

0000

,000

4792

993,

800

No

val

ue

No

val

ue

4371

786,

667

9200

00,0

0011

1332

50,0

0012

8300

0,00

0N

o v

alu

e-1

2656

25,0

00

Au

toco

rr0,

1162

Nu

mb

er

of

IPO

Fam

ily

con

tro

l >25

%2

21

99

67

40

4

Un

de

rpri

ce F

amil

y co

ntr

ol >

25%

Me

an-0

,006

0,02

20,

047

-0,0

320,

060

0,01

00,

079

-0,0

74N

o v

alu

e-0

,093

Un

de

rpri

ce n

on

-Fa

mil

y co

ntr

oll

0,12

10,

000

No

val

ue

-0,0

130,

046

0,06

80,

034

0,04

2N

o v

alu

e-0

,125

Mo

ne

y le

ft o

n t

able

-135

0000

,000

4792

993,

800

1200

000,

000

8221

73,9

0082

1661

4,28

6-6

6500

0,00

051

5600

0,00

0-4

6620

0,89

3N

o v

alu

e-1

5986

76,2

50

Au

toco

rr-0

,011

6

Me

an o

f fa

mil

y o

wn

ers

hip

50%

& 2

5%-0

,009

0,02

2N

o v

alu

e-0

,047

0,04

90,

022

0,05

30,

019

No

val

ue

-0,0

89


28

From table 1 we see that money left on table is more modest for family controlled

firms. However the level of money left on the table seems to be increasing with

the numbers of IPO and is consistent with Loughran and Ritter (2002) arguments

on the hot and cold market. Table 1 shows the autocorrelation on first day return

and there is a positive coefficient for both family controlled and non family

controlled firms. If all of the information is either private or public the

autocorrelation should be zero (Loughran and Ritter 2002). We can therefore

assume that some of the high first day return in some periods can be explained by

prospect theory. High demand and irrational investors drives the price up,

resulting in the value being higher than real value, which leads to wealth increase

for the issuer, even though there is money left on the table. This effect is even

larger for family controlled firms than others. In the years of hot issue both the

underpricing and money left on the table are higher than normal, compared to

other years. This indicates that families who are in control of firms are smart

issuer and recognizes the opportunity to take their firm public when the market is

overvalued.

0

10

20

30

40

50

60

-0.15000

-0.10000

-0.05000

0.00000

0.05000

0.10000

0.15000

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Number of IPO

Number IPO family>25

Number IPO >50%

First day return

First day return family>25%

Mean family>50&25

First day return family >50%

Graph 1 shows the annual number of new issue on Oslo stock exchange in total and divided into family controlled firm with ownership larger than 25% and 50%. The first day return for the same categories are illustrated with lines.


29

Graph 1 reports annually underpricing and show that family controlled firms tends

to have a lower first day return than non family controlled firm. This graph shows

some fluctuations in the three first years but seems to stabilize from 2004-2010.

This could be due to few observations in the first three years of both family

controlled firms and non family controlled firms.

Both family controlled firms larger than 50% and 25% have an average lower first

day return compared to non family controlled firms

Due to a low number of observations we have made an average first day return

based on both the variable family controlled firms larger than 50% and larger than

25%. This line seems to follow the line of >25% but does not show the same

effect. This could be an indicator of how the first day return on Family controlled

firms relates to the average. In Graph 1 we can see that high First day return is

followed by a high number of firms going public and a lower return leading to

fewer IPOs.

This graph support Ritter and Welch (2002) argument on behavioral explanations

and how issuers tend to see when the market are too overoptimistic and will

therefore take their firm public because of the high return in the aftermarket. It

also supports the theory on cascades saying investors will rely only on previous

investor’s action and not on their own valuation of firms. Ljungqvist (2007)

Table 2 shows the descriptive statistics of the variables. This result gives an

indication that family controlled firms are less underpriced than non-family

controlled firms and supports the hypothesis.

The mean and median are showing some differences when it comes to the result

of underpricing. The mean shows a lower short term underpricing for family

controlled firms while the median shows a slightly higher underpricing. These

differences could be caused by the number of IPOs around zero. It seems like

family controlled firms have a higher number of zero underpricing, however the

underpricing are lower for family controlled firms when there is a underpricing

higher than zero. The differences are due to the methods used to calculate mean

and median.


30

Tab

le 2

show

s des

crip

tive

stat

istic

s of t

he v

aria

bles

use

d in

the

anal

ysis

, with

diff

eren

t ow

ners

hip

clas

sific

atio

ns.

UP=

Firs

t day

und

erpr

icin

g, F

am_5

0 =

dum

my

varia

ble

for f

amily

ow

ners

hip

larg

er th

an 5

0%,

Fam

_25=

dum

my

varia

ble

for f

amily

ow

ners

hip

larg

er th

an 2

5%,

Fam

_ult=

ulti

mat

e fa

mily

ow

ners

hip

mea

sure

d in

per

cent

, Ln_

age=

firm

age

, Ln_

offe

rsiz

e= g

ross

pro

ceed

s,

Fam

_ceo

= fa

mily

mem

ber a

cts a

s CEO

, Ln_

Uw

= un

derw

riter

rank

ing,

Ow

n_C

EO=

shar

es o

wne

d by

CEO

as t

he p

erce

nt o

f tot

al sh

ares

, mon

ey_t

able

= m

oney

left

on th

e ta

ble

is th

e nu

mbe

r of s

hare

s offe

red

times

und

erpr

ice,

Fam

_ow

n= fa

mily

ow

ners

hip

afte

r IPO

as t

he p

erce

nt o

f tot

al sh

ares

.

Me

an M

ed

ian

Max

imu

m M

inim

um

Std

. De

v. M

ean

Me

dia

n M

axim

um

Min

imu

m S

td. D

ev.

Var

iab

les

UP

1,16

%2,

79 %

16,0

0 %

-42,

00 %

12,5

5 %

4,53

%0,

00 %

68,0

1 %

-23,

00 %

13,8

6 %

Firm

age

10,9

05,

0037

,00

1,00

10,5

18,

345,

5034

,00

1,00

7,54

Pro

p_s

old

-44,

60 %

-46,

88 %

9,63

%-9

8,77

%30

,32

%-1

2,82

%-3

3,05

%34

0,25

%-1

00,0

0 %

76,5

8 %

Fam

_ow

n35

,56

%36

,32

%61

,70

%1,

24 %

19,1

2 %

15,6

0 %

13,6

3 %

39,2

3 %

0,86

%10

,43

%

UW

11,7

3 %

10,9

8 %

36,6

9 %

0,07

%9,

22 %

11,0

0 %

10,4

1 %

36,6

9 %

0,08

%7,

96 %

OFF

ERSI

ZE16

2 54

1 76

3

129

000

000

50

0 50

0 00

0

10 0

00 0

00

15

3 53

6 93

1

155

662

678

86

900

003

1 28

7 80

0 00

0

6 00

0 00

0

23

4 77

0 51

1

MO

NEY

_TA

BLE

5 14

5 33

4

766

500

32 0

00 0

00

-1

7 16

0 00

0

12 2

57 4

20

14

331

021

296

325

479

191

193

-33

432

480

77

251

547

Fam

_CEO

28,5

7 %

0,00

%10

0,00

%0,

00 %

46,2

9 %

18,3

3 %

0,00

%10

0,00

%0,

00 %

39,0

2 %

Me

an M

ed

ian

Max

imu

m M

inim

um

Std

. De

v. M

ean

Me

dia

n M

axim

um

Min

imu

m S

td. D

ev.

Var

iab

les

UP

1,62

%0,

00 %

38,8

9 %

-42,

00 %

12,9

6 %

5,73

%1,

78 %

68,0

1 %

-7,6

9 %

13,9

4 %

Firm

age

9,70

6,00

37,0

0

1,

00

8,

87

8,

05

5,

00

34

,00

1,00

7,88

Pro

p_s

old

-38,

54 %

-40,

29 %

36,0

0 %

-98,

77 %

30,9

0 %

1,04

%-2

3,70

%34

0,25

%-1

00,0

0 %

91,3

3 %

Fam

_ow

n28

,68

%27

,00

%61

,70

%1,

24 %

15,6

2 %

11,8

5 %

9,70

%39

,23

%0,

86 %

9,73

%

UW

10,4

0 %

8,90

%36

,69

%0,

07 %

9,03

%11

,91

%14

,03

%21

,80

%0,

14 %

7,29

%

OFF

ERSI

ZE12

1 19

2 69

6

80 9

50 0

02

50

0 50

0 00

0

6 00

0 00

0

127

050

439

19

8 45

1 22

3

102

500

000

1

287

800

000

14

000

000

275

568

974

MO

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31

Fam

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31

Further, we see that family controlled firms tend to be on average two and a half

years almost two years older for respectively family ownership larger than 50%

and 25%, than non-family controlled firms when they are conducting an IPO. This

result supports the hypothesis 2 that family controlled firms have a higher age

when conducting an IPO.

Families controlling over 50 percent of the shares in front of an IPO will on

average reduce their number of shares by 44.5 percent while families controlling

less than 50 percent will reduce their ownership by 13 percent. We find the same

result when investigating family control larger than 25%. This contradicts the

hypothesis that families taking their firm public seek to maintain control of their

firm. However, it is not clear if families with high ownership sell off a larger part

of their shares, for their own sake, or due to the listing requirements by Oslo

Stock Exchange.

However by looking at the descriptive statistic of the ultimate ownership after

IPO, we see that families controlling more than 50 percent pre IPO controls a

higher number of shares post IPO (35 %) while families controlling less than 50

percent holds on average 15 percent of the shares after the IPO. This support the

hypothesis that families want to maintain the control after they take the firm

public. These results are interesting and support the overall theory on corporate

governance presented by Chambers (2012)

We see that the percent of family controlled firms that processes the CEO position

is 28,57% and 34,88% for family ownership larger than 50% and 25%

respectively . This supports the Anderson and Reeb (2004) arguments about the

link between ownership and management. How a stronger ownership leads to a

closer collaboration between the management and owners and support hypothesis

4, about the lower agency cost in family controlled firms

An interesting aspect concerning the underwriter ranking is that family controlled

firms use underwriters with a lower ranking than non-family controlled firms.

This is surprisingly, and contradicts the assumptions of previous literature on how

underwriter ranking will affect the underpricing (Carter and Manaster 1991,

Megginson and Weiss 1991). We have argued that family controlled firms will


32

have a lower underpricing compared to non-family controlled firms leading to the

assumption concerning the use of higher ranked underwriters.

Overall, the descriptive is more precise when investigating family ownership

larger than 25%. Together with the descriptive for family ownership larger than

50%, we see that most of our arguments are correlated with the literature

presented in the previous chapter.

The result from the descriptive statistics supports overall the hypothesis and

previous literature on the topic of IPO and family controlled firms. However, this

is only on a superficial level and we cannot base the result on mean and median,

and tells us nothing about how each variable affects the underpricing.

7 Methodology

Researchers like Daugherty and Jithendranathan (2012) and Ding and

Pukthuanthong-Le (2009) have shown that OLS is a sufficient tool and will be

efficient when investigating the connection between ownership structure and short

term underpricing. Nevertheless, we have to do several diagnostic tests and

control our variables and regression to see if our estimation fulfills the assumption

of OLS.

We set up an OLS regression to examine underpricing for our variables:

𝑈𝑛𝑑𝑒𝑟𝑝𝑟𝑖𝑐𝑖𝑛𝑔𝑖 = Family dummy𝑖 + 𝐹𝑖𝑟𝑚 𝑎𝑔𝑒𝑖 + Offersize𝑖 +

Proportion of shares sold by controlling family𝑖 + Family member as CEO𝑖 +

𝑈𝑛𝑑𝑒𝑟𝑤𝑟𝑖𝑡𝑒𝑟 𝑟𝑎𝑛𝑘𝑖 + 𝑢𝑖

We have implemented all these tests in the different regressions and made

improvements to the model where needed.

Brooks (2011) explains how heteroscedasticity and autocorrelation can still cause

unbiased coefficient, but the estimate may not longer have the minimum variance

and the assumption of OLS will not hold. We have used a Whites test to test for


33

presence of heteroscedasticity. The result are somewhat ambiguous, however they

are not any better when correcting for heteroscedasticity using white’s modified

standard error estimates.

The consequence of ignoring the presence of autocorrelation is similar to the

consequence of having heteroscedasticity and there is an uncertainty whether the

independent variables will have an effect on the dependent variable. High level of

positive autocorrelation will increase the probability of a type 1 error leading to an

incorrect rejection of a null hypothesis.

The Durbin-Watson test gives an indication of the presence of autocorrelation.

Our result shows a DW value close to 2, indicating a low level of autocorrelation.

In addition, we have tested for autocorrelation using the Breush-Godfrey test since

the DW has some limitations. This test is not showing signs of autocorrelation,

and we conclude that further improvements are not necessary.

While our model passes the previous mention assumption of OLS There are some

varying result regarding the assumption of normally distribution. The output

shows a high kurtosis and skewness to the right. This does not match the

assumption of the OLS and is supported by the Jarque-Bera test, that shows a

probability lower than 0,05 and we are therefore not able to reject the null

hypothesis of normality.

According to Brooks (2011) there is not obvious how to proceed if there is

evidence of non-normality. He argues that one could find a model that is better

fitted, but this could be demanding, and if the model has been well researched, it

could be best to continue the OLS. He also argues that there are often in financial

data some extreme residuals that causes major impact, and will be shown in the

tale, leading to higher kurtosis. By examine the residuals of the regression

(appendix 3) we see that there are some observations that could cause the outlier

and hence the skewed result. These outliers could be removed from the model to

improve the normality but we are concerned that removing outliers could lead to a

worse model due to the already low sample of observations. To improve the

model we have in addition removed the year of 2007 and 2008. We will discuss

this later in the thesis under the robustness test. The result from the normality test

is positive when removing the outliers from these years. But based on Brooks

(2011) arguments for not intervening, we choose to run the original regression

without removing outliers.


34

To improve the normality we have also transferred several of the variables to a

natural logarithm. According to Brooks (2011) this will make the variables more

fit to be used in a linear regression.

To test for the presence of multicollinearity and to see the relationship between

the explanatory variables we have run a correlation matrix. According to Brooks

(2011) the model could lose precision if some of the variables are highly

correlated whit each other, and it is therefore important to detect and remove

highly correlated explanatory variables. This method could also detect if there is

presence of endogeneity. Variables which are correlated with the error term in the

regressions, causes a statistical error, called endogeneity. When endogeneity exist

in a regression, it implies that the coefficients are biased. By comparing the

correlation between the variables (appendix 4) we see that there is correlation

between Own_Ceo and Fam_Ceo. However, these variables are not used

simultaneously, but individually in different models. This result also indicate that

there is no need for a two stage OLS as opposed to other research on the topic,

like Daugherty and Jithendranathan (2012)

Our tests indicates for the most that OLS is sufficient, however there are some

evidence that OLS are not to be the best model for our regression. On the other

hand OLS has been showed to be the best model by many researchers when

testing variables affecting the short term underprice. We have mentioned earlier

that our model has a relatively low number of observations, and Brooks (2011)

argues that the result from x^2 test and F-test may be different in small samples

and this may affect the result in the diagnostic tests. Similar research has been

done abroad but with a much larger sample (Daugherty and Jithendranathan 2012,

Ding and Pukthuanthong-Le 2009)

We therefore conclude that OLS is the best method to use when investigating the

relationship between family controlled firms and underpricing.


35

8 Regression analysis

8.1 Results hypothesis 1:

The first hypothesis we investigate is the main question in this thesis and will shed

light into whether or not a family controlled firm is less underpriced than other

firms.

The dummy variable Fam_50 which includes all firms with more than 50% family

ownership is negative and has the expected sign of the coefficient which is

consistent with hypothesis 1, but it is not significant for our sample. With 46

observations, and even fewer observations of family controlled firms with

ownership larger than 50%, it could be hard to get a significant sample.

Column two shows the Fam_25, and this is significant at a 90% level and with a

coefficient of -0,08 indicates that underpricing decreases when a firm has an

Family owner with more than 25% of the firm than firms with less than 25%.

While the ownership dummy at 50% was not significant in regression one, we see

that when setting a lower requirement of family control in the ownership dummy,

we get significant results and the same sign as the coefficient in regression one.

These results correspond to our previous arguments on the classification of family

controlled firms and how the line seems to be bigger between 25% than 50%.

To test this more thoroughly, we removed the dummy variable and replaced it

with family ownership without a dummy requirement in regression three. This

because we want to see how the ultimate ownership affect the underpricing when

conducting an IPO

Fam_ult, (row 3) ultimate ownership held by families is significant, almost at a

95% level and shows a negative coefficient (-0,05) This gives the result that a

higher degree of family ownership will lead to a lower underprice when going

public.


36

1 2 3 4 5 6

Fam_50 -0,0545 -0,0563

(-1,21) (-1,24)

Fam_25 -0,0767* -0,0694

(-1,77) (-1,65)

Fam_Ult -0,0482* -0,0495

(-1,95) (-1,96)

Ln_Age -0,0470** -0,0473** -0,0465** -0,0471** -0,0505** -0,0514**

(-2,18) (-2,18) (-2,21) (-2,21) (-2,44) (-2,46)

Ln_Offersize 0,0357* 0,0355** 0,0294* 0,0279 0,3360* 0,0328*

(2,01) (2,02) (1,68) (1,60) (1,96) (1,93)

Fam_Ceo 0,0080 0,0384 0,018

(0,17) (0,80) (0,4)

Prop_Sold -0,0166 -0,0168 -0,0226 -0,0242 -0,0363 -0,0373

(-0,58) (-0,60) (-0,80) (-0,86) (-1,20) (-1,25)

Ln_UW 0,1556 0,1499 0,0609 0,0499 0,1033 0,0897

(0,70) (0,68) (0,27) (0,22) (0,48) (0,41)

Own_Ceo 0,0004 0,0009 0,0009

(0,22) (0,43) (0,43)

N 46 46 46 46 46 46

R^2 0,2423 0,2426 0,2724 0,2640 0,2833 0,2838

R^2 (adj) 0,1257 0,1261 0,1604 0,1508 0,1731 0,1736

DW 1,6775 1,6942 1,7517 1,7763 1,7449 1,7779

50% 25% Ulitmae ownership

Ownership requirement

Table 3 shows the regression output for the sample of 46 Norwegian firms from 2001-2010, and is the estimation output for hypothesis 1, 2, 3a, 3b and 4. The three main columns represents the ownership classifications for respectively 50%, 25% and ultimate ownership Sub- columns 1, 3, and 5 shows the output of the main regression, only with different ownership classifications, while sub- columns 2, 4, and 6 shows the output of the robustness test where variable Fam_Ceo is replaced with Fam_Ceo, and the different ownership classifications . Dependent variable: UP= First day underpricing Independent variable: Fam_50 = dummy variable for family ownership larger than 50%, Fam_25= dummy variable for family ownership larger than 25%, Fam_ult= ultimate family ownership measured in percent, Ln_age= firm age, Ln_offersize= gross proceeds, Fam_ceo= family member acts as CEO, Ln_Uw= underwriter ranking, Own_CEO= shares owned by CEO as the percent of total shares. 𝐶𝑜𝑙𝑢𝑚𝑛 1: 𝑈𝑃𝑖 = Fam_50𝑖 + 𝐿𝑛_𝐴𝑔𝑒𝑖+Ln_Offersize𝑖 + Prop_sold𝑖 + Fam_Ceo𝑖 + 𝑈𝑤𝑖 + 𝑢𝑖 𝐶𝑜𝑙𝑢𝑚𝑛 2: 𝑈𝑃𝑖 = Fam_50𝑖 + 𝐿𝑛_𝐴𝑔𝑒𝑖 + Ln_Offersize𝑖 + Prop_sold𝑖 + Own_Ceo𝑖 + 𝑈𝑤𝑖 + 𝑢𝑖 𝐶𝑜𝑙𝑢𝑚𝑛 3 ∶ 𝑈𝑃𝑖 = Fam_25𝑖 + 𝐿𝑛_𝐴𝑔𝑒𝑖 + Ln_Offersize𝑖 + Prop_sold𝑖 + Fam_Ceo𝑖 + 𝑈𝑤𝑖 + 𝑢𝑖 𝐶𝑜𝑙𝑢𝑚𝑛 4: 𝑈𝑃𝑖 = Fam_25𝑖 + 𝐿𝑛_𝐴𝑔𝑒𝑖 + Ln_Offersize𝑖 + Prop_sold𝑖 + Own_Ceo𝑖 + 𝑈𝑤𝑖 + 𝑢𝑖 𝐶𝑜𝑙𝑢𝑚𝑛 5: 𝑈𝑃𝑖 = 𝐹𝑎𝑚_𝑈𝑙𝑡𝑖 + 𝐿𝑛_𝐴𝑔𝑒𝑖 + Ln_Offersize𝑖 + Prop_sold𝑖 + Fam_Ceo𝑖 + 𝑈𝑤𝑖 + 𝑢𝑖 𝐶𝑜𝑙𝑢𝑚𝑛 6: 𝑈𝑃𝑖 = 𝐹𝑎𝑚_𝑈𝑙𝑡𝑖 + 𝐿𝑛_𝐴𝑔𝑒𝑖 + Ln_Offersize𝑖 + Prop_sold𝑖 + Own_Ceo𝑖 + 𝑈𝑤𝑖 + 𝑢𝑖 t-stat in ( )

* ** *** denote the significance at 10% 5% 1% respectively


37

By comparing this result with the result from the descriptive we can draw the

connection between the spurious result of underpricing on family controlled firms

larger than 50% to a low sample. On the other side the result from the descriptive

and regression on family controlled firms larger than 25 percent is more

congruent. Significant coefficient of Fam_25 and a more unambiguous mean and

median on underpricing leads to a more clear result.

We can clearly see with all three regressions that the coefficients for ownership

structure are negative and have a negative effect on underpricing. These results

are consistent with our hypothesis, that family controlled firms are lower

underpriced.

From these three regressions we can clearly see that the family ownership variable

all have the same negative coefficient and with significance in column two and

three. In our descriptive, we also saw that the underpricing was lower in family

controlled firms, so we therefore state that hypothesis one is true. This result is

consistent with the result of Daugherty and Jithendranathan (2012), who finds that

family firms are less underpriced than non-family controlled firms, which in our

thesis is presented through Norwegian firms.

The result from the regression and the coefficient on the family variables are some

ambiguous and shows the difficulty of setting a line where a firm are to be

classified as a family controlled firm. Both from the regression and the descriptive

we see a clearer line between 25% than 50% ownership.

8.2 Result hypothesis 2: As expected we get the result that the variable Ln_Age have a negative coefficient

and are significant at a 95 % level for all six regressions. The age of the firm when

conducting an IPO is still significant when including the dummy at 50% (-

0,0470), 25% (-0,0465) and ultimate ownership (0,0505). A higher firm age when

going public will result in a lower first day return. This result corresponds to the

result presented by Daugherty and Jithendranathen (2012) and supports the overall

perception on how higher firm-age reduces the information asymmetry presented

by Ritter (1984), saying that for each year the firm has existed before conducting

an IPO the firm will possess more past data, making it easier to evaluate the firm.


38

Why there is more underpricing in younger firms is explained by lack of past data,

and will lead to a higher difference in the offering price and market price. The

descriptive shows that the median and mean age of family controlled firms are

higher than non-family controlled firms, providing us evidence that family firms

are older when conducting an IPO as mentioned earlier. By comparing these two

results, we can suggest that family firms are less underpriced due to a more

mature age when going public, leading to a reduced information asymmetry. Ding

and Pukthuanthong-Le (2009) got the same result from their study on the Taiwan

market

In an IPO process valuation is the element of risk, since it is hard for the buyers to

know exactly the market price of an issue. Rock (1986) found that underpricing is

created by risk, such that higher risk of a firm will give higher underpricing. Since

the risk of a firm is decreased by higher age of the firm, we get results which

follow the principles of Rock (1986), making our hypothesis two true.

8.3 Result hypothesis 3a

In hypothesis 3a we wanted to test if the proportion of shares issued will be

posetively correlated with underpricing and if family controlled firms will issue

less than non-family controlled firms.

The result presented in table 3 show that offer size is positively correlated with

underpricing, and all three were significant at a minimum 90% level. With a

positive coefficient in all three regressions, we can therefore accept hypothesis 3a,

that proportion of shares issued will be positively correlated with underpricing.

Our hypothesis was influenced by Rock (1986) argumentation on asymmetric

information effect on underpricing and was based on Michaely and Shaw (1994)

who found results indicating that a higher offer size gives lower underpricing. A

positive and significant coefficient is consistent with hypothesis 3a and gives an

indication that the asymmetric information will have a huge impact on the

underpricing. A higher offer size could also follow Ritter and Welchs (2002) and

Brennan and Franks (1997) argumentation on allocation of shares and control,

indicate that issuers are willing to lower the price in an attempt to retain the

control of the firm. From table 2 we see that family controlled firms on average

have a higher percent of ownership after the IPO, which is consistent with


39

Chambers (2012). These results seen in relation to family controlled firms having

on average a smaller offer size when conducting an IPO (table2), gives us

evidence to conclude that hypothesis 3 a is true.

8.4 Result Hypothesis 3b In addition, our hypothesis states that the controlling family wants to retain

control and thereby selling less of their shares under an IPO. In the descriptive,

we could not see any clear result that families in control of firms sold a lower

number of their shares. In fact they issued a higher proportion of their shares than

non family controlled firms.

From the result in table 3, we see that this is in consistent with the regression

where all three coefficient are not significant. With negative coefficients in all

three regressions we can state that the more of the shares the family keeps, the

lower underpricing it has when performing an IPO, giving the hypothesis support,

but not significant enough to reject the null hypothesis. Looking at the descriptive,

we can see clearly that families seek to maintain control after they conduct an

IPO, as mentioned earlier in the descriptive, while they still sell a bigger part of

their shares (table 2). The fact that proportion sold out is not significant could be

because the shares sold by family are on average at a very similar level. In

addition, the high degree of family ownership after the IPO has a higher signaling

effect than the proportion sold. The effect seems to be absent or small as long as

the family still owns a part of the firm after the IPO. One could argue along the

theory of asymmetric information (Rock 1986) and signaling theory in family

firms (Leland and Pyle (1976)) and ask the question why this not has an effect on

the underpricing. By looking at the descriptive, we can draw the conclusion that

there is a very low number of controlling families that reduce their ownership

entirely, and we might draw the conclusion that this effect will not be captured

since it is more or less absent. As explained the signaling-effect family ownership

has on IPO price and real value seems to be present regardless of proportion of

shares sold by the family.

This result does not support hypothesis 3b, but support the perception that

families has a higher incentive to retain control of the firm after going public.


40

8.5 Result hypothesis 4:

In the last hypothesis, we wanted to see if family controlled firms with CEO will

reduce agency conflicts, resulting in lower underprice. From the regression output

(table3) we, see that all coefficients are positive, given that when the CEO also

owns a part of the firm, the underpricing is higher. However, this result is not

significant in any of the regressions and we cannot conclude that hypothesis 4 is

true. This contradicts the theory presented in the literature review. To test this

hypothesis more thoroughly, we have chosen to replace the variable Fam_Ceo

with Own_Ceo to see the connection between ultimate CEO ownership and the

underpricing. The result from this regression (column 2, 4 and 6) are similar to

previous regression (row 1, 3 and 5) and we find none of the coefficients to be

significant. In addition, we do not see any big changes in the other coefficients

and we cannot dismiss the null hypothesis.

From the descriptive, we do not get any evidence, supporting our hypothesis, but

there is clearly a link between family control and having the CEO position as

mentioned (table 1). We based our hypothesis upon Anderson and Reeb’s (2003)

and Arthurs et al (2008) research, which stated that the link between family

ownership and involvement from the family in the management could reduce

agency cost when the CEO position was held by a family founder. The

inconclusive result from both tests may be due to a low number of observations or

a smaller effect of agency cost on underpricing in the Norwegian market than

anticipated. According to research by Villalonga and Amit (2006) will the

generation controlling the firm affect the profitability of the firm, and this could

also be a decisive consideration when dealing with underpricing and agency cost.

However because of the data we cannot distinguish which generation that controls

the firm.

Based on the output presented in table 3 we must reject the hypothesis, and we

will conclude that the controlling family in the CEO position has no effect on

underpricing.

8.6 Result from control variable The result from the control variable is slightly surprising and contradicts previous

research on the topic. Based on research made by Carter and Manaster (1991),


41

Megginson, and Weiss (1991) we had expected the underwriter ranking to have a

negative effect on underpricing. However, the coefficient of underwriter ranking

was not significant in any of the regressions (table 3). This contradicts empirical

investigations, saying that higher underwriter reputation is negative correlated

with underpricing. As explained in the descriptive, family controlled firms both

larger than 25 and 50 percent are using an underwriter with a lower rank

compared to non-family controlled firms (table 2). In addition, family controlled

firms are on average lower underpriced than non-family controlled firms (table 2).

To investigate this relationship we have separated the observations into groups of

family-controlled and non-family controlled firms and developed a simple

regression to capture the underwriter effect on underpricing. Table 4 presents the

result of the impact on underpricing by underwriter rank and the result from the

regression is surprisingly, and is showing opposite effect on the two different

groups.

We see that higher underwriter ranking lead to lower underprice for non-family

controlled firms with a coefficient of -0,06777 and -0,794151 for respectively 50

and 25 percent, while with greater underwriter ranking, family-controlled firms

receive higher underpricing. However, only the result for ownership larger than

25% is significant. Researchers have argued on how underwriters could cause

both high and low underprice and this outcome could shed light into Habib and

Ljungqvist (2001) arguments on how some owners have a higher incentive to

keep a lower underprice. Family controlled firms who tend to choose a lower

ranked underwriter and at the same time keep the underpricing at a lower level fits

Table 4 shows a simple regression to test the underwriter rankings effect on underpricing. The

output is separated in two showing the different effect of underwriter ranking on family controlled

firms and non-family controlled firms.

𝑈𝑃𝑖 = 𝑈𝑤𝑖 + 𝑢𝑖

Family controlled Non-family controlled Family controlled Non-family controlled

LN_UW 0.232447 -0.067777 0.475444* -0.794151**

N 16 46 33 29

R^2 0.073387 0.001058 0.102287 0.141054

R^2 (adj) 0.007200 -0.021645 0.073329 0.109242

DW 3.095931 1.207384 2.242288 1.329631


50 % 25 %


42

well into this share-owner category. The different effect of underwriter rank in the

two groups could also support Arthurs et al (2008) arguments on how investment

banks seek to keep a better relationship with institutional investors. They argue

further that a venture capitalist will have a shorter time horizon and might have

built a stronger relationship with a investment bank both because of the profit and

because the time horizon makes it difficult to monitor the process.

9 Robustness test

Some of the result is not consistent with the hypothesis we presented and

contradicts the overall perception on the determinants on underpricing. With the

basis of these biases and the fairly modest number of observations, we have

therefore done a robustness test to see whether or not our results hold. Part of this

test is shown in table 3 where we added a substitute to the primary variables. The

variable Own_Ceo in addition to the different classification of family control.

These variables are showing similar results as the main variable and are

contributing to a more thoroughly investigated result.

Under the chapter Method, we argued how the volatility was larger pre and during

the financial crisis of 2007-2009 and we therefore want to exclude the years that

differ from the normal. By removing the year of 2007 and 2008 (none of the IPOs

in 2009 was included in the previous regression due to our requirement), we get a

result showing normality and gives similar outcome as the previous model

(appendix 5). However the dummy variable >50 is now negative and significant,

supporting hypothesis on family control and low underpricing. Even with a lower

number of observations this robustness test together with the main regression

gives us an indication that hypothesis one is true. If we disregard years with

abnormal volatility, family controlled firms tend to have a lower underprice than

non-family controlled firms.

10 What could be improved?

As explained the Norwegian stock market is small compared to other trade

markets and the size of observations could be too low to get an accurate outcome.

However, our robustness test and use of substitute variables and the fact that some

of the outcome is consistent with previous research indicate that the conclusion


43

holds. If we are going to point on a weakness in the thesis that needs to be more

thoroughly tested it is the family variables. These numbers are based on annual

data and may deviate from the actual number at the time the IPO was conducted.

By using these numbers, we are not able to investigate if owners keep their shares

after the IPO have been conducted, or if they sell all/parts of their shares due to

higher prices in the aftermarket. A more thorough investigation of the CEO

position and which generation that are in control could lead to a more accurate

result, based on the theories by Villalonga and Amit (2006), saying that that CEO

position held by inheritors could be ruining the reduced agency cost created by

having the founder as CEO. By separating the CEO position in to different sub

groups we could investigate whether there is a difference having the CEO position

held by the founder or heirs, and we could on a more secure basis accept or

exclude the impact of reduced agency cost on the IPO underpricing in the

Norwegian market

11 Conclusion

This thesis has dealt with the theories and research on the topic of IPO and

underpricing and the mechanism that will have an effect on the short term return

when a firm goes public. Further, these theories are related to the corporate

governance in family controlled firms, trying to explain why there should be

differences between the underpricing in family controlled firms and non-family

controlled firms. The result from our investigation shows that there are differences

between the two groups of family control and how this affect the short term

underpricing. Family controlled firms tend to have a lower underpricing when

going public both for firms with family ownership larger than 25% and 50%.

However, the result seems to be more accurate when dealing with ownership

larger than 25%.

The number of issue and money left on table seems to follow the same cycles as

non-family controlled firms, and we can see that years with many IPOs are

followed with higher underpricing. We can therefor relate some of the

underpricing to hot and cold markets and the behavioral explanations of

underpricing.


44

We find the variables related to the asymmetric information, age and the offer size

to have a great impact on the underpricing in family controlled firms. A higher

age will reduce the information asymmetry and lead to a lower underpricing,

while a higher offer size lead to a higher underpricing. Comparing these results to

the structure in family controlled firms, we see that these firms tend to have a

higher age and a lower offer size when conducting an IPO. Contrary we find the

variables related to theories on agency cost and management to have no impact on

the underpricing. Even though the CEO position in family controlled firms tend to

be held by one of the members of the controlling family. Our results show that

this has no effect on the underpricing.

One interesting finding is underwriters’ impact on the underpricing. Most theories

and research are showing a negative correlation between the underwriter rank and

the underpricing. However, we find an opposite effect on underpricing in the two

groups. While non-family controlled firms’ follow most theorists view that higher

underwriter rank leads to a lower underpricing, the underpricing in family

controlled firms will react opposite to the underwriter rank. The result from our

investigation shows that higher underwriter rank leads to a higher underpricing.

This is related to the findings that family controlled firms tends to choose a lower

ranked underwriter and is in accordance with our main findings that family

controlled firms have a lower IPO underprice.

Family controlled firms who go public have some characteristic differences from

other firms that goes public, and these differences have an impact on mostly the

asymmetric information between issuer and investor. The firm age and signaling

effect have in our tests proved to cause a lower underprice. Still there are some

areas that are not clear, and would be interesting to investigate more thoroughly,

especially to see whether the controlling family have a stronger incentive to keep

a low underprice, leading to more involvement in the process and higher effort to

keep the price closer to real value.


45

12 References

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and Firm Performance: Evidence from the S&P 500”. The Journal of

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Johnson. 2008. “MANAGERIAL AGENTS WATCHING OTHER

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Bancel, Frank and Usha R. Mittoo. 2009. “Why Do European Firms Go Public?”.

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Benveniste, Lawrence M. and Paul A. Spindt. 1989. “How investment bankers

determine the offer price and allocation of new issues”. Journal of

Financial Economics 24(2): 343-361.

Brennan, M.J. and J. Franks. 1997. “Underpricing, ownership and control in initial

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Brooks, Chris. 2011. Introductory Econometrics for Finance. 2nd ed. Cambridge

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Underwriter Reputation”. Journal of Finance 45(4): 1045-1067.


46

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Chambers, Andrew. 2012. Chambers’ Corporate Governance Handbook. 5th ed.

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MARKETS WHERE TRADES HAVE DIVERSE INFORMATION”. The

Journal of Finance 31(2): 573-585.

Habib, Michel A. and Alexander P. Ljungqvist. 2001. “Underpricing and

Entrepreneurial Wealth Losses in IPOs: Theory and Evidence”. The

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47

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49

13 Appendix

13.1 Appendix 1 – IPO and closing price. Closing price are collected from Oslo Børs and Thomson Reuters Datastream, and

IPO prices are collected from equity feed from Oslo Børs, newsweb and netfond

which are all delivering official news from Oslo Børs.

Firm TICKER Year IPO Price Price Closing Underpricing

24SEVEN TECHNOLOGY GROUP ASA TFSO 2007 14,00 13,50 -0,04

ABILITY DRILLING ASA ADRL 2007 15,00 16,00 0,07

AGASTI HOLDING ASA ACTA 2001 10,00 10,00 0,00

AGILITY GROUP AS GGG 2005 18,00 23,50 0,31

AGR GROUP ASA AGR 2006 47,00 46,00 -0,02

AKER ASA AKER 2004 62,00 63,00 0,02

AKER SEAFOODS ASA AKS 2005 29,00 28,90 0,00

AKER SOLUTIONS ASA AKSO 2004 130,00 126,50 -0,03

AKVA GROUP ASA AKVA 2006 35,00 35,00 0,00

ALGETA ASA ALGETA 2007 47,00 44,00 -0,06

ALLIANSE AS ALL 2005 8,00 8,50 0,06

APL AS APL 2005 49,00 57,00 0,16

AQUA BIO TECHNOLOGY ASA ABT 2008 9,00 10,00 0,11

ARROW SEISMIC ASA ARROW 2007 70,00 70,00 0,00

AUSTEVOLL SEAFOOD ASA AUSS 2006 39,00 39,80 0,02

BADGER EXPLORER ASA BXPL 2007 32,00 33,90 0,06

BERGEN GROUP ASA BERGEN 2008 31,00 29,00 -0,06

BIOTEC PHARMACON ASA BIOTEC 2005 24,50 25,00 0,02

BIRDSTEP TECHNOLOGY ASA BIRD 2002 16,50 16,50 0,00

BORGESTAD INDUSTRIES ASA BIND 2008 46,00 46,00 0,00

BOUVET ASA BOUVET 2007 40,00 40,00 0,00

BRIDGE ENERGY ASA BRIDGE 2010 20,00 17,70 -0,12

BW GAS AS GAS 2005 82,00 77,50 -0,05

BWG HOMES ASA BWG 2006 33,00 36,80 0,12

CATCH COMMUNICATION AS CATCH 2004 20,00 19,90 -0,01

CECON ASA CECON 2007 15,00 15,00 0,00

CELLCURA ASA CELL 2010 5,00 3,85 -0,23

CERMAQ ASA CEQ 2005 44,00 44,10 0,00

CLAVIS PHARMA ASA CLAVIS 2006 45,50 46,60 0,02

CODFARMERS ASA COD 2006 26,00 25,00 -0,04

CONSEPTOR AS CNS 2004 11,50 11,40 -0,01

COSL DRILLING EUROPE AS AWO 2005 22,00 22,00 0,00

DEEP SEA SUPPLY AS DESS 2005 11,50 11,90 0,03

DEEPOCEAN AS DEEP 2005 17,00 16,60 -0,02

DET NORSKE OLJESELSKAP ASA DETNOR 2006 60,00 64,50 0,08

DET NORSKE OLJESELSKAP ASA AKX 2007 56,00 56,00 0,00

DOF SUBSEA AS DOFSUB 2005 27,00 29,50 0,09

DOLPHIN GROUP ASA DOLP 2006 17,50 20,40 0,17

DOMSTEIN ASA DOM 2001 26,00 26,00 0,00

EASTERN DRILLING AS EDRILL 2005 64,00 70,00 0,09

EIDESVIK OFFSHORE ASA EIOF 2005 45,00 50,00 0,11

EITZEN CHEMICAL ASA ECHEM 2006 28,00 28,50 0,02

ELECTROMAGNETIC GEOSERVICES ASA EMGS 2007 135,00 145,50 0,08

EQOLOGY ASA SHINE 2010 2,20 2,00 -0,09

ETMAN INTERNATIONAL ASA ETMA 2007 3,50 3,50 0,00

FAKTOR EIENDOM ASA FAKTOR 2006 35,00 33,80 -0,03

FARA ASA FARA 2005 1,35 2,01 0,49

FEDAIA AS SPITS 2006 16,00 16,10 0,01

FORNEBU UTVIKLING AS SPDE 2007 37,50 37,50 0,00

FRED. OLSEN PRODUCTION ASA FOP 2007 26,00 24,80 -0,05

GJENSIDIGE FORSIKRING ASA GJF 2010 59,00 58,75 0,00

GJENSIDIGE NOR ASA GNO 2002 241,50 247,50 0,02

GRIEG SEAFOOD ASA GSF 2007 23,00 23,50 0,02

HAVILA SHIPPING ASA HAVI 2005 40,00 41,00 0,03

IDEX ASA IDEX 2010 1,20 1,23 0,03

IMAREX ASA IMAREX 2005 81,00 103,00 0,27

INFRATEK ASA INFRA 2007 18,00 17,60 -0,02

INTELECOM GROUP AS CON 2001 12,00 12,00 0,00

INTEX RESOURCES ASA ITX 2006 12,00 11,65 -0,03

JASON SHIPPING ASA CECO 2004 35,00 35,00 0,00

KLEPP SPAREBANK KLEG 2007 110,00 123,50 0,12

KONGSBERG AUTOMOTIVE HOLDING ASA KOA 2005 46,00 47,50 0,03


50

Firm TICKER Year IPO Price Price Closing Underpricing

LERØY SEAFOOD GROUP ASA LSG 2002 32,00 32,00 0,00

MAMUT AS MAMUT 2004 7,00 6,80 -0,03

MARINE FARMS AS MAFA 2006 14,00 13,80 -0,01

MEDISTIM ASA MEDI 2004 9,50 10,30 0,08

MICROSOFT DEVELOPMENT CENTER NORWAY AS FAST 2001 13,00 12,00 -0,08

MORPOL ASA MORPOL 2010 22,00 19,70 -0,10

NATTOPHARMA ASA NATTO 2008 12,00 9,93 -0,17

NEAS AS NEAS 2007 33,00 32,00 -0,03

NEMI FORSIKRING AS NEMI 2005 28,00 29,30 0,05

NETCONNECT ASA NETCO 2010 3,20 2,66 -0,17

NEXTGENTEL HOLDING AS NEXT 2003 25,00 22,70 -0,09

NORDA ASA NORD 2005 10,00 9,90 -0,01

NORGANI HOTELS AS NORGAN 2005 56,00 56,00 0,00

NORSTAT AS MRG 2005 11,00 10,50 -0,05

NORTH ENERGY ASA NORTH 2010 26,50 26,80 0,01

NORWAY PELAGIC ASA NPEL 2008 40,00 41,00 0,03

NORWEGIAN AIR SHUTTLE ASA NAS 2003 32,00 33,50 0,05

NORWEGIAN ENERGY COMPANY ASA NOR 2007 33,00 35,00 0,06

NORWEGIAN PROPERTY ASA NPRO 2006 53,50 57,75 0,08

ODIM AS OHI 2001 40,00 39,50 -0,01

ODIM HOLDING AS ODIM 2005 30,00 31,50 0,05

OFFSHORE HEAVY TRANSPORT AS OHL 2007 36,00 50,00 0,39

OSLO AREAL AS OSLO 2005 53,00 54,00 0,02

PAN PELAGIC ASA PEL 2001 13,69 23,00 0,68

PANORO ENERGY ASA PEN 2010 12,60 9,30 -0,26

PCI BIOTECH HOLDING ASA PCIB 2008 20,00 18,00 -0,10

PETROJACK ASA JACK 2005 9,00 9,15 0,02

PETROMENA ASA PMENA 2007 15,00 15,90 0,06

POWEL AS POWEL 2005 15,00 15,00 0,00

PROMENS GROUP AS POLI 2005 21,50 21,20 -0,01

PRONOVA BIOPHARMA ASA PRON 2007 23,00 23,80 0,03

PROTECTOR FORSIKRING ASA PROTCT 2007 14,00 15,00 0,07

Q-FREE ASA QFR 2002 15,70 16,40 0,04

REM OFFSHORE ASA REM 2007 40,00 43,50 0,09

RENEWABLE ENERGY CORPORATION ASA REC 2006 95,00 117,00 0,23

REPANT ASA REPANT 2007 15,20 16,60 0,09

RESERVOIR EXPLORATION TECHNOLOGY ASA RXT 2006 49,00 52,50 0,07

RESID INVEST AS SCAN 2007 40,00 42,50 0,06

SAGA TANKERS ASA SAGA 2010 12,00 13,00 0,08

SALMAR ASA SALM 2007 36,00 39,00 0,08

SCAN GEOPHYSICAL ASA SCANG 2007 28,00 27,50 -0,02

SEVAN MARINE ASA SEVAN 2004 8,50 9,80 0,15

SPAREBANK 1 NØTTERØY - TØNSBERG NTSG 2007 110,00 115,50 0,05

SPAREBANK 1 ØSTFOLD AKERSHUS RVSB 2005 110,00 130,00 0,18

STATOIL ASA STL 2001 69,00 69,00 0,00

STATOIL FUEL & RETAIL AS SFR 2010 39,00 39,00 0,00

STREAM INVEST AS BJORGE 2004 7,00 7,00 0,00

STX EUROPE AS STXEUR 2004 100,00 98,00 -0,02

SØLVTRANS HOLDING ASA STRANS 2010 25,00 25,00 0,00

TECO MARITIME GROUP AS TECO 2004 10,00 5,80 -0,42

TELIO HOLDING ASA TELIO 2006 30,00 30,00 0,00

THIN FILM ELECTRONICS ASA THIN 2008 10,00 12,90 0,29

TRANSOCEAN NORWAY DRILLING AS AKD 2005 36,85 39,20 0,06

TRIBONA ASA NLPR 2007 56,50 57,50 0,02

TROLLTECH AS TROLL 2006 16,00 17,50 0,09

UNISON FORSIKRING AS UNISON 2005 30,00 29,80 -0,01

VISMA HOSTING HOLDING AS ACTIVE 2004 6,00 5,85 -0,03

WEGA MINING AS WEMI 2007 5,00 5,80 0,16

WILH. WILHELMSEN HOLDING ASA WWASA 2010 24,20 22,90 -0,05

WILSON ASA WILS 2005 19,50 20,10 0,03

WINTERSHALL NORGE AS WNOR 2005 42,00 44,00 0,05

YARA INTERNATIONAL ASA YAR 2004 41,00 51,00 0,24


51

13.2 Appendix 2: Underwriter rank

Manager 2001-2004 2005-2007 2008-2010

Fondsfinans 0,0057 0,0011 0,0029

Cazenove 0,0057 0,0000 0,0000

First Securities 0,0210 0,0769 0,0080

Pareto Securities 0,0514 0,1410 0,2284

DnB Markets 0,2440 0,1188 0,0000

Morgan Stanley Dean Witter 0,2141 0,0000 0,0000

ABG Sundal Collier 0,0215 0,2273 0,0876

Enskilda 0,0561 0,1649 0,0332

Handelsbanken Capital Markets 0,0048 0,0014 0,0000

DnB NOR Markets 0,0000 0,1188 0,0000

Goldman Sachs 0,0150 0,0000 0,1234

UBS Investment Bank 0,2262 0,0456 0,0000

Carnegie 0,0228 0,1468 0,0353

Alfred Berg SE 0,0000 0,0012 0,0000

Oslo Branch 0,0000 0,0012 0,0000

Terra 0,0000 0,0164 0,0008

Fearnley Fonds 0,0000 0,0180 0,0000

Nordea 0,0000 0,0159 0,0592

CAR 0,0000 0,0032 0,0009

Leman Brothers 0,0000 0,0163 0,0000

Glitnir Securities 0,0000 0,0039 0,0019

Orion Securties 0,0000 0,0000 0,0046

Arcitc Securities 0,0000 0,0000 0,0132

BDO 0,0000 0,0000 0,0007

Selmer 0,0000 0,0000 0,0268

Bofa Merill Lynch 0,0000 0,0000 0,1772

Citigroup 0,0000 0,0000 0,0539

Argo Securities 0,0000 0,0000 0,0007

RS Platou Markets 0,0000 0,0000 0,0049

Periode

Underwriter rank


52

13.3 Appendix 3: Residuals

13.4 Appendix 4: Correlation matrix

-.2

.0

.2

.4

.6

-.4

-.2

.0

.2

.4

.6

.8

5 10 15 20 25 30 35 40 45

Residual Actual Fitted

Variables Ln_Age Ln_Offersize Own_Ceo Ln_Uw Prop_Sold Fam_Ceo Fam_Ult

Ln_Age 1

Ln_Offersize 0,0198 1

Own_Ceo 0,1604 0,0287 1

Ln_Uw 0,1235 0,1481 0,0769 1

Prop_Sold 0,1191 -0,2505 -0,177 0,0446 1

Fam_Ceo 0,0507 -0,0987 0,4987 -0,0896 -0,2072 1

Fam_Ult -0,0458 0,0996 0,2572 -0,1249 -0,48 0,1961 1

Correlation Matrix


53

13.5 Appendix5: Robusteness test

50% 25% Ulitmae ownership

1 3 5

Fam_50 -0.1148*

(-1,85)

Fam_25 -0.0995*

(-1.72)

Fam_Ult -0.0704*

(-2.28)

Ln_Age -0.0683** -0.0694** -0.0762**

(-2,33) (-2,35) (-2.74)

Ln_Offersize 0.0706** 0.0588** 0.0660**

(2,79) (1,68) (2.74)

Fam_Ceo -0.0017 0,0384 0.0166

(0,03) (0,80) (0.29)

Prop_Sold -0.0144 -0.021787 -0.0474

(-0,58) (-0,60) (-1.25)

Ln_UW 0.5730* 0.4039 0.4687

(1,80) (1,28) (1.55)

Own_Ceo

N 29 29 29

R^2 0.4700 0.4602 0.505150

R^2 (adj) 0.3255 0.3129 0.370191

DW 1.7612 1.663719 1.795528



54

13.6 Appendix 6: Preliminary thesis ID number/name: Audun Fagerstrøm Skattum 0829182

Mats Erik Strand 0858077

BI Norwegian Business School –

Preliminary Thesis Report

- IPO Underpricing and family controlled firms -

Hand-in date: 15.01.2013

Campus: BI Oslo

Examination code and name:

13.6.1.1 GRA 1902 Preliminary Report

Supervisor: Siv J. Staubo

Programme:

Master of Science in Business and Economics, major in Finance


55

Content

Introduction 56

Literature review 57

Methodology 62

Data 64

Further progression 64

Temporarily time schedule 65

References 44


56

Introduction

In this thesis we are investigating the relationship between the ownership structure

and the underpricing related to initial public offering in the Norwegian market,

more specific: the difference between family firms and non-family firms. We will

look at the different factors that can affect the underpricing when conducting an

IPO and correlate this to the structure of companies controlled by families.

Underpricing in an initial public offering is a well-known phenomenon and has

been a subject for many research papers.

The underpricing can be seen as the percentage difference between the price

offered by the issuer and the price at the end of the first trading day (Ljungqvist

2007). As early as 1975 Roger G. Ibbotsen found evidence of underpricing in

initial public offerings, but could not explain why it occurred.

“Strangely enough, we have not solved the mystery of the empirically observed

underpriced new issue offerings.” (Ibbotsen 1975)

Ritter (1984) and Rock (1986) among others developed theories of why and how

underpricing occur, leading to further research trying to explain how the

ownership structure in firms affect the offer price in an IPO process.

Previous research is showing that ownership structure is significant when valuing

a firm and the impact on the profit earned by investors the first trading day. But

there are little research on the topic of family controlled firms and the valuation

when they are conducting an IPO. In spite of family controlled firms is highly

important in the world economy and counts for 37 percent of fortune 500 firms

(Padgett 2012).

Researchers have in recent years focused on the ownership structure in a family

controlled firm and how it affects the long term performance.

Exploring the IPO performance in a family controlled firm can give investors

important insights on how to evaluate different investment objects.

In this thesis we will focus on how the ownership structure will affect information asymmetry and agency conflict between owners, management and underwriter. We will also focus on theories regarding the owners desire to maintain control over the firm.


57

Literature review

The phenomena of short-term underpricing in an IPO process is a well

documented subject and has been a topic in research for decades.

In the article “A review of IPO Activity, pricing, and Allocations”, Ritter and

Welch (2002) explain the plausible causes of short-run underpricing. They focus

on theories based on asymmetric and symmetric information, and theories based

on allocation of shares.

The theory of asymmetric information has been a popular theory among

researchers and was first explained by Grossman (1976). He argued that the

superior information will be showed through the equilibrium price.

The issuer is more informed than the investor and tries to distinguish from one

another other by signaling either high or low quality. High quality issuers are

selling at a lower price and try to recap the loss in the future. The investors who

want to pay a high price will require something in return to show their willingness

and the issuer will present a “gift on the table” in form of a lower price (Ritter and

Welch 2002). This theory is supported by Benveniste and Spindt (1989) and their

model of information acquisition saying an investor must be rewarded to reveal

their true demand during a book building period.

Leland and Pyle (1976) explained that an entrepreneur has more information

about the expected future cash flow and is signaling high quality by investing in

the project.

Another approach is to assume the investors are more informed than the issuers,

for example about the market demand. Assuming investors are equally informed

could explain why they buy at a lower price since they all want to make profit and

will request those issues that are valued at a significant lower level relative to real

value, but according to Ritter and Welch (2002) this could not explain the

phenomena of an overpriced IPO.

Rock (1986) show on the other hand that underpricing is a result of differentially

informed investors. The issuer and the underwriter possess more information

about the firms’ performance in the future than each investor individually, but will

have less knowledge than all investors together. Whereas uninformed investors

tend to bid randomly, informed investors only bid on favorable priced IPO.


58

However there are few informed investors in the market and the issuing firm must set the price to a lower level to be sure that uniformed investors will buy and the issued shares will be fully subscribed. Setting the price lower will increase the demand from uninformed investors, create oversubscription and the need for rationing occurs. The demand from uninformed investors will increase to the point where all subscriptions are made by uninformed investors. At this point a lower price will reduce the probability to get an allocation leading to uninformed investors will withdraw. This theory is according to Ljungqvist (2007) similar to the theory of winners curse. The uninformed investors will on average have abnormal return equal to zero

Loughran and Ritter (2002) explain the phenomena of underpricing as the indirect

cost of having the underwriter. The issuer puts money on the table instead of

bigger fees to the underwriter. Their survey showed that IPOs with high

underpricing often had a lower initially valuation, but are priced higher as a result

of high demand for the IPO. The investors will be less critical to high

underpricing since their initial value has increased.

But Ritter and Welch (2002) are unsure how this value is divided between the

issuer, underwriter and the investors.

Theories on symmetric information are often based on the issuers’ fear of

litigation. With a higher price the probability that the share is overpriced increases

and the issuer will sell their shares at a lower price to avoid lawsuit from outside

shareholders in the future (Ritter and Welch 2002). But this will according to

Ljungqvist (2007) be a second-order driver for underpricing.

Even though asymmetric information and symmetric information has been a

popular theory among researchers, Ritter and Welch (2002) means that these

theories do not count for all underpricing.

They argue that underpricing can be explained by the agency conflict between the

issuer and the underwriter, the share allocation on one side, and the behavioral

explanation on the other side.

One interesting question is “How do investors decide in which issues to request

IPO allocations, and how heavily influenced is this by perceptions of what others

are going to do?” (Ritter and Welch 2002).


59

Arthur et al (2008) describes the relationship between owner managers,

underwriter and venture capitalists and how there exist a multiple agency conflict

between the parties.

The management together with the underwriter will determine the issue price, but

may have different incentives for the price level and allocation of shares.

The management may use the IPO as a mean to maximize own utility level on the

expense of future shareholders and non-managing shareholders. (Ljungqvist 2007)

Also the connection between underwriters and investors is questioned. Arthur et al

(2008) argue that financial banks are better off having a long term relationship

with the institutional investors and underpricing is a mean to maintain such a good

reputation. They will also benefit from being responsible for allocation decisions.

The underwriters will have different incentives than the managers and company

owners that have hired them.

However Carter, Dark and Singh (1998) and Michaely and Shaw (1994) have

done research on the connection between underwriters reputation and

underpricing. They find evidence that high underwriter reputation is associated

with lower short-term underpricing.

Brennan and Franks (1997) find evidence that underpriced IPO tend to be

oversubscribed. They argue that underpricing gives the issuer the opportunity to

discriminate the allocation of shares and often in favor of small applicants to

prevent the allocation of large blocks and prevent new large shareholders, giving

the issuer the opportunity to maintain control of the firm.

However Habib and Ljungqvist (2001) advance another explanation and argue

that some IPOs are less underpriced because the owners have strong incentives to

keep a high price level. Owners who sell a big proportion of their shares will have

incentive to put a lot effort and money to avoid high underpricing, while owners

issuing a smaller proportion will care less about the underpricing.

There are several differences between a family controlled firm both in the

structure of ownership and their motives to conduct an IPO.

Ritter and Welch (2002) describe the reasons why a firm wants to go public by the

motive to raise capital and the desire to trade at a public market place. Mainly a


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firm conducts an IPO so they can raise capital, to be able to invest in positive

NPV projects, or to satisfy the owners need for capital. In a family firm some

family members sell parts of their shares for personal reasons, while in non-family

firms owners can use the situation to get a more diversified portfolio. Ritter and

Welch (2002) also look at different theories in the life-cycles of the firm and

market-timing. When a firm gets to a certain stage in its life, it could be optimal to

go public for example to expand. Publicity and also the advantage of being the

first in its industry are also vital reasons.

By going public the owners sell a part of the company to new shareholders, which

could have been done by selling in the private market. Selling shares privately to

many new shareholders would make the owners able to negotiate the price and

then receive a higher price for their stocks. However Chemmanur and Fulghieri

(1999) argues that this would not be efficient since the evaluation cost would be

too high compared to the information cost of going public, and then making the

stock price lower, compared to an IPO.

Zingales (1995) points out that the initial owner could use the IPO to be able to

restructure his position in the firm, and also being able to sell out the proceeds he

wants to maximize. Many entrepreneurs seizes this opportunity to “collect the

prize” of their work and sells the company.

However Litz (2004) explains the importance to distinguish between family firm

and entrepreneurs and refers to later research in entrepreneurship, showing the

entrepreneur to be different in the management from the organization in family

firms.

The key difference between a family controlled firm and a non-family controlled

firm is the separation of control between management and owners. In a family

controlled firm, family members will have active participation as both owners and

in the management team (Chambers. 2012).

Anderson and Reeb (2003) argues that a family firm is separated from a non-

family firm by the amount of shares the founding family represents and whether

they are to be found in the board of the firm. However it is not definite how large

share of the company the family has to possess. In their paper they show an

example where the controlling family had as little as 2% of the shares, and still

were the majority owner.


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The amount of management which also owns a part of the firm is greater than

non-family controlled firms. If the managers also have shares in the company they

will carry part of the risk when conducting an IPO. Ljungqvist (2007) argue that

the agency cost will diminish when the ownership is so large that it will outweigh

the private benefits. The agency problem between owner and underwriter can also

be reduced when both management and owners will have same incentive for the

price level.

Anderson and Reeb (2003) present another advantage of having owners as

managers. And explain why family firms have higher profitability then non-

family firms, because the CEO position is held by one of the family members who

understand the business. They interpreted their results such as that the presence of

a family in the board and controlling the firm, makes agency problems less and

family firms equal or even better in performance than non-family firms.

According to Chambers (2012) this success is based on the family business ability

of long-term thinking. The family’s wealth depends on the value of the firm, and

the strategy for the family is to take board decisions, making sure the continuance

of the firm through generations (Litz 2004). This could benefit in a more certain

valuation of the firm, leading to less information asymmetry.

When a family firm requires capital and this is done trough an IPO the founder find

it hard to adjust to a partial ownership. To retain a majority of shares within the

family the proportion of shares issued and the allocation of shares have to be

carefully designed (Chambers 2012).

Daugherty and Jithendranathan (2012) found that family firms is less underpriced

then non-family firms in the US market between 1996 and 2004. They explain the

difference by different ownership structure and argue that it is the effectiveness of

managers in the family firms who achieve less underpricing. However Ding and

Pukthuanthong-Le (2009) found evidence of lower underprice when family firm

was managed by an outsider as CEO. It is clear that the ownership structure will

have various impacts on the underpricing in different markets


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Methodology

Our hypotheses are based on the theories and empirical work exploited in the

literature review. The main question is to see if there is a significant difference in

the short-term underpricing between family controlled firm and non family

controlled firm. Further the theory shows three directions where the ownership

structure most likely will have an effect on the underpricing of a family controlled

firm, and the study will be based on the theory of information asymmetry, agency

problem and the desire for a family to maintain control.

Hypothesis 1: Family controlled firms are less underpriced than non family

controlled firms.

To test hypothesis 1 we first have to determine which firm is a family firm and

which is not. We will first set the family variable up as a dummy variable, such

that it is equal to 1 for family firm and 0 for non-family firms. To test hypothesis

1 we do the following regression OLS:

Underpricingi = 𝜷𝟎 + 𝜷𝟏 * Familyi + εi

Hypothesis 2: Higher age will result in lower underpricing.

As shown in the previous chapter the information asymmetry will be reduced by

the approach of long-term decision making. When conducting an IPO the

information and valuation process is costly. Past data are used when evaluating

the firms total value, and less past data could make the evaluation harder (Ritter

1984). This means that the age of the firm will affect the underpricing of the

company.

Age of the firm when conducting an initial public offering has been in several

studies used to describe how “established” the firm is. Daugherty and

Jithendranathen (2012) and Ding and Pukthuanthong-Le (2009) has found in their

two separate markets that the older the firm is, the less underpricing it occurs. We

also get from Rock (1986) that risk is related to underpricing, in such term that

underpricing increase with higher risk of a firm.


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Hypothesis 3: Proportion of shares issued will affect underpricing.

In an initial public offering it differ a lot of how many percent of their shares the

issuing firm offer to the public. Techniques like issue fewer shares and use

underpricing as a tool to control the allocation of shares, gives a family the

opportunity to restructure and maintain the control of the firm. If the firm issues

less it could be a sign that they believe in the future of the firm and want to

maintain control. Habib and Ljungqvist (2001) find that proportion of shares

issued is negatively correlated with underpricing when conducting an IPO.

Whether or not this is consistent whit an IPO in a family controlled firm remains

to be observed. The family wants to maximize their value while they want at the

same time to maintain control.

Hypothesis 4: Higher proportion of family members in the management will

reduce agency conflicts, resulting in lower underprice.

In this hypothesis we will test the relationship between underpricing and the

amount of family involvement in the management. If involvement from family

ownership occurs in a firm, Anderson and Reeb (2003) argue that it is likely to

decreases agency cost. They point out that when the CEO position is held by

either a family founder or a “hired-hand”, the gain of this is the greatest.

We set up an OLS regression to examine underpricing for our variables:

Underpricingi = 𝜷𝟎 + 𝜷𝟏*Age of firmi + 𝜷𝟐* IPO volumei + 𝜷𝟑 * Amount of

fam. Ownership after IPOi + 𝜷𝟒 * Amount of fam. members in managementi

+ 𝜷𝟓*Underwriter rankingi + εi

Defining our variables:

Age - Age of the company when they conducted the IPO. This variable will be the

number of years between the firm was founded and the date of IPO.

IPO volume - Percentage issued to the public of total capital.

Amount of family ownership after IPO – The percent of shares held by the

controlling family after the IPO.

Amount of family members in the management – The number of family members

in the management team when conducting the IPO.


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We will use underwriter ranking as control variable in regression. Underwriter

ranking is not data measurable precisely, so we have to make a proxy for the

ranking. We will use the underwriter’s total capital to measure ranking as a proxy

of this, assuming that firm which gets bigger IPO deals is more prestigious.

Michealy and Shaw (1994) used this as their proxy, and found high correlation

between reputation and the size of the IPO. By measuring if the underwriter

ranking has any effect on the IPO underpricing, we want to see if the firm’s

choice of underwriter is different when having a different ownership structure.

Data

We will collect our data from the Norwegian market on the 207 firms conducting

an IPO on Oslo Stock Exchange from 2002 to 2010. Our first problem will be to

examine which firms are in the definition of family firm. By doing this we will

use information made public by the firm in prospectuses before the initial public

offering. It is important to get a representative selection of data to get significant

results. Because of the size of the Norwegian market, our definition of family

firms can be modified after collecting and investigating the data.

The data involving the IPO day, issue price and the closing price will be found on

Datastream. BI also has a database called CCGR where we will collect data

regarding the age, board members, management team and family data.

Further progression

This thesis will require a high work effort and it is important for us and our

supervisor that we maintain our deadlines. After the preliminary report we will

focus on data collection, sorting and interpretation.

When we receive the feedback on the preliminary it is important to improve these

points with regard to the presentation.


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Temporarily time schedule

1.-15. February – Most of the data which we will use have to be collected.

1. March – Complete our data analysis.

15. April – Roughly completed the interpretation of the data analysis.

15. June – Send the finished thesis to last guidance from supervisor.

1. September – Official deadline to deliver the master thesis.


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