The influence of board independence on the value performance of US acquisitions

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The influence of board independence on the value performance

of US acquisitions

A. Schrotenboer

S1383663

Rijksuniversiteit Groningen

Faculty of Business Administration

Department of Finance

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Abstract

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1. Introduction

The managing of a company is full of agency problems. The management of the company is in the hands of professional managers who are not the owners of the firm. Their interests may therefore differ from the interests of the owners. To monitor the behaviour of managers a company has a board of directors that represents the shareholders. The board of directors has, among other things, the legal authority to monitor and change actions of management and to evaluate and reward the performance of top managers.

Board of directors can differ in their composition. For instance, in the proportion of independent directors and dependent directors. Independent and dependent directors have different roles on the board. Insiders can provide firm specific information while outsiders can objectively evaluate managers’ decisions.

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hurtful to the shareholders. Therefore, companies with boards that are dominated by independent directors, should on average make better acquisitions than companies with boards that consists mainly of dependent directors.

In order to accurately assess an acquisition directors need complete and correct information. Since it is easier to obtain information about domestic targets, cross-border targets are harder to value (Conn et al, 2005). Therefore, it is more difficult for the board of directors to recognize a bad deal when the target is a cross-border company. Since cross-border companies are harder to value, making it more difficult to recognize a bad deal, average returns for acquisitions of cross-border companies will be lower than the average returns for acquisitions of domestic companies. Because independent boards will put more effort in recognizing bad deals, and since this is easier when the target is a domestic company, the difference in the average returns between cross-border and domestic companies will be larger in companies with independent boards than in companies with dependent boards.

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2. Theoretical background

M&A theory: determinants of mergers and acquisitions

Over the years quite a few theories that explain sources of merger gains have been formulated. Based on value gains/losses to bidders and targets the various theories can be separated into three groups. The first group of theories assumes positive returns for both bidders and targets. These theories are all based on synergies. The possible synergies include: operating synergies, financial synergies, efficiency improvements and increased market power. The existence of operating synergies assumes that by combining the two firms the costs can be cut. A possible source of cost reductions is combining departments like R&D and headquarters. Financial synergies can arise when the acquirer has excess cash and the target has no means of internal financing. This way the high cost of external financing of the target can be avoided. Another possible source of financial synergies arises when either of the two companies makes a profit and the other makes a loss. By combining the results a tax saving can be reached. The combined company can also have a higher debt-capacity, which also provides tax savings through the interest tax shield. Lastly, the combined firm might achieve economies of scale in transaction and flotation costs. Efficiency improvements usually arise when an efficient acquirer takes over a less efficient target. When the target has valuable assets, but for instance an inefficient management or inefficient procedures, replacing the management and putting in place the more efficient procedures of the bidder can create value. Gaining market power can become a merger motive when competition in an industry is fierce.

The second theory that explains mergers is the hubris hypothesis (Roll, 1986). This theory assumes that the acquirer wrongly believes that the target is worth more than its actual market value and in effect the acquirer overpays. The target then receives a positive return in expense of the bidder, and both returns sum up to zero.

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because leading a larger company gives them more pay and/or power. Since transactions are solely motivated by self-interest of the firm’s management, the bidders will realize a negative return and targets a small positive or a negative return. The total return for bidders and targets will be negative.

M&A literature

A large number of papers have studied the effects of acquisitions. The majority of these papers show that target firms earn a positive return. The effect of acquisitions on the bidding firm is not so straightforward. Some papers show a positive return, while others show a negative return. However, on average the return for the bidder seems to be zero. The papers also show that the combined return for the target and the bidder is usually positive. These results indicate that the reason behind an acquisition is synergy gains. An overview of papers that examine the bidder returns of acquisitions can be found in table 1.

Table 1. Overview of average abnormal bidder returns in M&A papers.

Study Years Number of deals Bidder country Event window (days) Abnormal return Significant at 5% level Bradley and Sundaram (2004) Moeller et al. (2005) Bradley et al. (1988) Mulherin and Boone (2000) Walker (2000) 1990-2000 1980-2001 1963-1984 1990-1999 1980-1996 12476 12023 236 281 278 US US US US US (-2, +2) (-1, +1) (-5, +5) (-1, +1) (-2, +2) 1,45% 0,01% 0,97% -0,37% -0,84% Yes No Yes No No

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Hypothesis 1

H0: The average abnormal bidder return will be equal to zero.

H1: The average abnormal bidder return will be unequal to zero.

Classification of directors:

The directors will be divided into two groups: independent directors and dependent directors. This will be done according to the director classification procedure developed by Baysinger and Butler (1985). They divided directors into one of three groups: inside directors, affiliated outside directors and independent outside directors. Inside directors are current or former corporate officers and their family members. Affiliated outside directors are associated with the company in some way, but are not full-time employees of the company. Affiliated outside directors can include commercial bankers that made loans to the firm, lawyers or consultants providing services to the firm or officers of the firm’s suppliers and customers. Independent outside directors do not have other links to the company besides their directorship. For this thesis the dependent directors will be formed by merging the inside directors and the affiliated outside directors, while the group of independent directors consistsof the independent outside directors.

Board of directors’ theory

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board that has a minority of independent directors. Therefore, the average return of an acquisition will be higher for a board that consists of a majority of independent directors. Board of directors’ literature

There have been a lot of papers examining the relationship between board composition and firm performance. MacAvoy et al (1983) found an insignificant relationship between the percentage of outsiders on the board and accounting performance, Bhagat and Black (2002) used Tobin’s Q as a performance measure and found no significant relationship between this measure and the fraction of outsiders. Bhagat and Black (2002) also investigated the relationship between the proportion of outside directors and long-term stock market performance. They found the relationship to be insignificant. Hermalin and Weisbach (1991) did not find a relationship between either Tobin’s Q or EBIT and board composition. Thus, there does not seem to be a relationship between board composition and overall performance. However this does not mean that board composition is insignificant in specific situations.

Rosenstein and Wyatt (1990) investigated the announcement effect of the appointment of an extra independent director on the board. They found a significant cumulative abnormal return on the days -1 and 0. Weisbach (1988) researched if the composition of the board of directors has an influence on CEO turnover. He concluded that with poor performance, the chance of the CEO loosing his job is highest with a board consisting of at least 60% independent directors. The only paper that I could find that investigates the relationship between bidder returns in an acquisition and board composition is Byrd and Hickman (1992). They found that bidder returns are significantly higher when the firm has a board that consists of a majority of independent directors. This evidence leads to the following hypothesis:

Hypothesis 2 (board independence hypothesis)

H0: The average abnormal bidder return of firms with an independent board will be equal to the average abnormal bidder return of firms with a dependent board.

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Geographic diversification theory

There may be several reasons why the bidder abnormal returns differ between a domestic acquisition and a cross-border acquisition. The returns in a cross-border acquisition can be expected to be higher if the bidder can apply its better management techniques or know-how in the target firm, if the bidder has excess capacity while growth at home is limited, and if the bidder gets access to intangible information based assets that due to market failures or high transaction costs would otherwise be lost. Examples of these market failures are the lemons problem, when information asymmetry prevents the buyer from obtaining the full value of the assets, and difficulties in transferring information that is tacit.

The returns for cross-border acquisitions may be expected to be lower when the bidder faces the risk of loss of control, when cross-border targets are more difficult to value because of imperfect information, and if culture differences make the integration a more difficult and expensive process.

Geographic diversification literature

The evidence concerning the difference between domestic and cross-border targets is mixed. Some studies find that bidder returns are higher for cross-border targets while others find that acquiring domestic targets gives higher returns. An overview of papers examining the difference between domestic and cross-border targets can be found in table 2.

Table 2. Average abnormal bidder returns for firms which acquire domestic and cross-border targets.

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(2004) Conn et al. (2005) Lowinsky et al. (2004) Moeller and Schlingemann (2005) 1984-1998 1990-2001 1985-1995 4344 114 4430 UK Switzerlan d US (-1, +1) (-1, +1) (-1, +1) 0,68% 0,32% 1,17% 0,33% 1,26% 0,307% No No Yes

In a study concerning Swiss bidders, Lowinsky et al. (2004) find that bidder returns are higher for cross-border targets, although not significantly so. On the other hand, Moeller and Schlingemann (2005) find that for US bidders returns are significantly higher for domestic targets. Since my study focuses on US bidders hypothesis 3 becomes:

Hypothesis 3 (geographic diversification hypothesis)

H0: The average abnormal bidder return of firms that acquire a domestic company is equal to the average abnormal bidder return of firms that acquire a cross-border company.

H1: The average abnormal bidder return of firms that acquire a domestic company is higher than the average abnormal bidder return of firms that acquire a cross-border company.

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Hypothesis 4

H0: The difference between the average abnormal bidder return from acquiring a domestic target and a cross-border target will not differ between firms with an independent board and firms with a dependent board.

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3. Data

Sample selection

To compile my sample I started with a list of all the mergers and acquisition deals available in the Zephyr database that satisfied the following criteria:

o The bidder is an American firm listed on the NYSE.

o The deal wasannounced between January 1, 1995 and November 4, 2003.

o The deal has been completed.

o The bidding firm does not already own a controlling interest in the target. o After the acquisition the bidder owns 100% of the shares of the target. o The deal value and the method of payment are known.

I exclude deals in which the bidder already owns a controlling interest in the target to avoid the problem of investors already expecting an acquisition. Since on November 4, 2003 a new NYSE rule became effective, obligating companies listed on the NYSE to have a board that consists of a majority of independent directors, deals announced after that date are excluded from the sample. I included the criteria that the method of payment and deal value must be known, since investors need this information to properly assess the acquisition. These criteria give a preliminary list of 762 deals.

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Sample statistics

Table 3 shows the number of deals in the sample made every year, divided by board type. Of the 503 deals in the sample 409 are made by firms with an independent board. The fraction of deals made by firms with independent boards is higher in the years 2000 to 2003 than in the earlier years. A possible explanation for this is the increased attention for corporate governance and director independence that has developed since 2000.

Table 3. Sample bids classified by year and board type.

Year Less than 50% independent directors 50% or more independent directors Year total 1997 1998 1999 2000 2001 2002 2003 Total 3 2 2 31 11 25 20 94 10 3 4 119 42 98 133 409 13 5 6 150 53 123 153 503

An unusual property of my sample is the low number of deals in the 1990’s. Since in the late ‘90’s the economy and the stock market were booming you would expect a large number of deals to have taken place in these years. The reason that they are not well represented in my sample is that for most deals made in these years the deal value and/or deal type are not available in Zephyr.

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Table 4. Board characteristics of sample firms.

Variable Minimum Maximum Mean Median Standard

deviation

Number of directors Independent directors (%) Dependent directors (%) Independent director stock ownership (%)

Dependent director stock ownership (%) 4,0 0,0 7,1 0,0 0,0 24,0 92,8 100,0 97,4 100,0 10,1 64,0 36,0 2,1 8,3 9,0 66,7 33,3 0,2 2,2 3,2 18,8 18,8 8,1 15,4

Table 5 shows the deal characteristics of my sample bids. The majority of deals are domestic deals while the target is usually a private firm. In most deals the bidder and target are from related industries. In my study this means that the bidder and target firm have the same 2-digit SIC code. About half the deals are entirely paid for by cash. The average market values and deal values are presented in table 6.

Table 5. Deal characteristics of sample bids.

Characteristic Number of deals Percentage of deals Target firm is listed

Target and bidder from related industries All cash deal

Target is a US firm 147 307 236 395 29,2 61,0 46,9 78,5

Table 6. Market values and deal values in millions of euros.

Variable Minimum (millions) Maximum (millions) Mean (millions) Median (millions) Standard deviation Market value bidder

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4. Methodology

Defining the time frame

In this thesis the event study methodology will be used to evaluate the value performance of acquisitions. An event study estimates the value performance of an acquisition by looking at the stock market reaction to the announcement of an acquisition. The event study methodology assumes a certain time frame. This time frame consists of the announcement date, the event window and the estimation window. These components of the event study time frame will be described below:

Announcement date

The announcement date represents the trading day at which the acquisition is announced to the market. This day is known as day 0.

Event window

The event window is the period used to determine if the announcement of an acquisition leads to a deviation from the normal return. Since it is possible that information about the acquisition has leaked to the market before the official announcement date, or that the market is inefficient and does not react to information immediately, the event window will include days around the announcement day. In this thesis I will look at three different event periods. This allows to observe the market reaction more precisely. My event periods are (-10, +10), (-1, +1) and 0.

Estimation window

The estimation window is used to estimate the parameters of the normal return model, which is then used to calculate abnormal stock returns over the event period. According to MacKinlay (1997) an estimation period of 120 days is enough to determine the normal return. However, in most studies a longer estimation period is used. In my thesis I will use an estimation period of 200 days. It will run from day -210 to day -11.

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Figure 1. Time frame of an event study.

estimation window event window -210 -11 -10 0 10 Choosing a normal performance model

An event study measures the effect of an acquisition by calculating the abnormal stock return. A return can only be considered abnormal relative to a certain benchmark. This benchmark is known as the normal (or expected) return. Brown and Warner (1980, 1985) presented three models which can be used to calculate normal returns; the mean adjusted returns model, the market adjusted returns model and the market and risk adjusted returns model. Although Brown and Warner claim that the first two simpler models work as well as the market and risk adjusted model, this thesis will make use of the market and risk adjusted returns model.

Another, more recent model that can be used to calculate normal returns, is the Fama-French three-factor model. This model controls for three risk-factors common to all securities. The market return, size and the book-to-market ratio. A benefit of this model is, that by adding two factors, it reduces the variability of the abnormal returns by explaining more of the variation in the normal return. However, in practice it turns out that the gains from using a multi-factor model in an event study are limited. As MacKinley (1997) says “The reason for the limited gains is the empirical fact that the

marginal explanatory power of additional factors is small, and hence, there is little reduction in the variance of the abnormal return.” Therefore, I will not use the

Fama-French three-factor model in my thesis. Market and risk adjusted returns model

The market and risk adjusted returns model assumes that the expected return of a stock depends on the market return and the risk of the stock, which is represented by Beta. The market and risk adjusted returns model is specified as:

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E (εit = 0)

var (εit) = σ2ei

Where Rit is the return of a given security, Rmt is the return on the market portfolio and αi

and ßi are the estimated values of the true parameters through OLS regression. In my

thesis the MSCI USA total return index is used as the market index.

Calculation of abnormal returns, average abnormal returns and cumulative abnormal returns

After running the market and risk adjusted return model regression for each bidding firm in the sample, I use the obtained estimated values of the model parameters (αi, βi) to

calculate the expected value of the bidder return (E(Rit)) for each day in the event period.

The abnormal return of stock i on day t can now be calculated as the difference between the actual observed return and the forecasted expected return.

ARit = Rit – E(Rit) (2)

Where E(Rit) = E(αi)+E(βi)Rmt

To calculate the average abnormal return on day t the abnormal returns of the stocks are first added and then the average is calculated.

ARt = N 1

_∑

= n i AR 1 it (3)

The ARt shows the average abnormal return on a specific day. Its sign and magnitude

reflect the opinion of the market about whether the acquisition will be value-creating or value-destroying.

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CAR(t1, t2) =

∑

= 2 1 t t t AR_t (4)

The CAR(t1, t2) shows if the market reaction carries on for more than one day. I will test

the CAR(t1, t2) for different event periods to get a better idea about the timing of the

market reaction. Significance

Concluding that the market reacted to the acquisition announcement is only possible if the observed abnormal return is statistically different from zero. Just knowing the size and sign of the average abnormal returns is not enough. To see if the observed abnormal returns are statistically different from zero a t-test will be conducted. The test statistic is specified as the standardized value of either the average abnormal return or the cumulative abnormal return, depending on the time frame.

t t AR AR ) ( σ (5) ) , (1 2 ) ( _t _t t CAR CAR σ (6) Where var(ARt) =

∑

= N i ei N 1 2 2 1 σ (7) var (CAR(t₁,t₂))=

∑

= 2 1 ) var( t t i t AR (8)

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To test if there is a significant difference between the abnormal returns of firms with an independent board and firms with a dependent board, or between firms that acquire a domestic company and firms that acquire a cross-border company (hypothesis 2 and 3) I will conduct the following t-test:

2 2 2 1 2 1 2 1 n s n s AR AR + − (9)

Where s is the standard deviation of the average abnormal return and n is the number of events.

To test if the difference between the average abnormal bidder return from acquiring a domestic target and a cross-border target significantly differs between firms with an independent board and firms with a dependent board (hypothesis 4), I will conduct the following t-test: ))) ( ) (( )) ( ) ((( ) ( ) ( int , 2 int , , 2 , int , 2 int , , 2 , int , , int , , er dep er dep nat dep nat dep er indep er indep nat indep nat indep er dep nat dep er indep nat indep n s n s n s n s AR AR AR AR + + + − − − (10) Non-parametric test

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Since the Jarque-Bera test showed that the abnormal returns are not normally distributed, I will also use a non-parametric test to see if the results of the t-test are robust. A common non-parametric test used in event studies is the sign test. This test is not based on the magnitude of the abnormal returns, but on the sign. Under the null-hypothesis, it is equally likely that the abnormal return is positive or negative. For hypothesis 1 (the average abnormal bidder return will be equal to zero), the test value is equal to:

5 , 0 * 5 , 0 5 , 0 n n S − (11) Where S*_{= S + 0,5 if S<0,5n or S}*_{= S - 0,5 if S>0,5n}

S is the number of cases where the abnormal return is positive and n is the total number of nonzero cases.

For the board independence and the geographic diversification hypotheses, the test value is as follows: 2 0 0 1 0 0 2 1 ) 1 ( ) 1 ( n p p n p p p p − + − − (12) Where P0 = 2 1 2 2 1 1 n n p n p n + + (13)

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er dep nat dep er indep nat indep er dep nat dep er indep nat indep n p p n p p n p p n p p p p p p int , 0 0 , 0 0 int , 0 0 , 0 0 int , , int , , ) 1 ( ) 1 ( ) 1 ( ) 1 ( ) ( ) ( − + − + − + − − − − (14) Where P0 = er dep nat dep er indep nat indep er dep er dep nat dep nat dep er indep er indep nat indep nat indep n n n n p n p n p n p n int , , int , , int , int , , , int , int , , , + + + + + + (15) OLS-regression

Two regression models will be used for cross-sectional analysis. The abnormal returns at the time of the announcement bid are regressed on a set of explanatory variables including board independence, the fraction of board seats held by independent directors, chairman independence, independent director stock ownership, dependent director stock ownership, geographic diversification and some control variables. The control variables are based on the evidence of previous studies which suggest that bidder abnormal returns may be influenced by the medium of exchange, whether the bidder and target are from related industries and whether the target is a public firm. In model 1 the board composition variable is the dummy variable independent board, while in model 2 the board composition variable is the fraction independent directors. In both models the dependent variable is the announcement-date abnormal return. The explanatory variables are defined as follows:

Independent board = 1 if independent directors hold at least 50% of all board seats, and 0

otherwise

Fraction independent directors = number of independent directors divided by the total

number of directors on the board

Independent chairman = 1 if the chairman of the board is independent, and 0 otherwise Independent stock ownership = fraction of the bidding firm’s outstanding voting shares

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Dependent stock ownership = fraction of the bidding firm’s outstanding voting shares

owned by dependent directors

Cash = 1 if the bid is entirely for cash, and 0 otherwise

Related industries = 1 if the bidding and target firm are from the same two-digit SIC

code, and 0 otherwise

Public target = 1 if the target is a public firm, and 0 otherwise

Domestic target = 1 if the bidding and target firm are from the same country, and 0

otherwise

5. Results

Table 7 presents the average abnormal returns for the bidders in my sample. The deals are divided into four groups; deals made by firms with an independent board, deals made by firms with a dependent board, deals in which the target is a domestic firm and deals in which the target is a cross-border firm. For the full sample the abnormal returns are negative and significant for the intervals (-10,10) and (-1,1). The only subsamples that exhibit significant abnormal returns are the sample independent boards for all intervals and cross-border target for the intervals (-10,10) and (-1,1). Except two intervals for the subgroup dependent boards all the abnormal returns are negative, although not always significantly so. This indicates that the prime motive behind these acquisitions is either hubris or agency problems.

Table 7. Average abnormal returns in percentages.

Event window Mean T-value

Median Max Min Standard deviation

N All firms

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(-1, +1) 0 Independent boards (-10, +10) (-1, +1) 0 Dependent boards (-10, +10) (-1, +1) 0 Domestic target (-10, +10) (-1, +1) 0 Cross-border target (-10, +10) (-1, +1) 0 -0,73* -0,30 -4,34** -0,87** -0,38* 0,18 -0,07 0,07 -0,33 -0,40 -0,27 -15,07** -1,90** -0,41 -2,52 -1,81 -4,92 -2,62 -2,03 0,13 -0,13 0,21 -0,37 -1,17 -1,37 -11,66 -3,88 -1,45 0,09 -0,11 0,46 -0,08 -0,11 0,58 0,33 -0,14 0,61 0,06 -0,13 0,44 0,14 -0,08 19,18 18,95 65,08 19,18 18,95 37,32 10,96 8,37 65,08 19,18 12,84 39,14 17,22 18,95 -230,50 -76,82 -1628,26 -230,50 -76,82 -36,37 -18,74 -13,25 -129,32 -27,00 -25,16 -1628,26 -230,50 -76,82 0,12 0,05 0,82 0,13 0,05 0,14 0,05 0,03 0,15 0,06 0,04 1,57 0,23 0,08 503 503 409 409 409 94 94 94 395 395 395 108 108 108

* and ** indicate statistical significance at 5% and 1% level respectively

To test the robustness of the findings in table 7 a sign test was conducted. The results of this test can be found in table 8. None of the proportions of positive abnormal returns significantly differs from 0,5.

Table 8: Sign test for abnormal returns.

Event window N positive Proportion positive p-value

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(-1, +1) 0 Cross-border target (-10, +10) (-1, +1) 0 199 186 57 56 52 0,504 0,471 0,528 0,519 0,481 0,920 0,271 0,631 0,772 0,772

After having looked at the average abnormal returns of the full sample and the four subsamples separately, I will now look if they differ significantly from each other to determine if hypotheses 2, 3 and 4 will have to be confirmed or rejected. Table 9 shows the differences between firms with an independent and a dependent board, firms who acquire a domestic or a cross-border target and the difference between a domestic and a cross-border target for firms with an independent and a dependent board.

Table 9. Differences between average abnormal returns and proportions of positive abnormal returns.

Parametric test Non-parametric test

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As can be seen almost all the differences, except for the difference between firms with an independent board and firms with a dependent board, have the expected sign, although none of the differences is significant. This means that hypothesis 2,3 and 4 cannot be rejected. The signs of the differences in average abnormal returns and proportions of positive abnormal returns are largely in accordance with each other. The most striking feature is the difference between domestic and cross-border targets between firms with independent and dependent boards for the (-10, 10) interval. The difference in average abnormal returns between domestic and cross-border targets is almost 20% higher for firms with independent boards, yet the proportion of firms with positive abnormal returns is 6% lower. This could be caused by a small number of firms with very high/low abnormal returns in one of the subsamples.

To separate the influence of board composition and the geographical origin of the target from other factors that could influence announcement date abnormal returns two OLS-regression models were conducted. In both models the dependent variable is the risk adjusted announcement date abnormal return. The explanatory variables are board independence, the fraction of board seats held by independent directors, chairman independence, independent director stock ownership, dependent director stock ownership, the geographical origin of the target and a set of control variables. The control variables are based on past studies which indicate that bidder abnormal returns could be influenced by the medium of exchange (Travlos, 1987), whether the target and bidder are from related industries ( Morck et al., 1990) and whether the target is a public company (Chang, 1998).

Table 10 shows the coefficient estimates from two OLS-regression models. In model 1 the board composition variable is the independent board dummy while in model 2 the board composition variable is the fraction independent directors.

Table 10. OLS regression results.

Model 1 Model 2

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Intercept

Independent board (yes=1) Fraction independent directors Independent chairman (yes=1) Independent stock ownership Dependent stock ownership Cash (all cash=1)

Related industries (yes=1) Public target (yes=1) Domestic target (yes=1)

0,00 -0,01 -0,01 -0,01 -0,00 0,01 0,00 -0,00 0,00 0,15 -0,95 -0,69 -0,31 -0,46 1,57 0,41 -0,65 0,73 0,00 -0,01 -0,01 -0,01 -0,00 0,01 0,00 -0,00 0,00 0,18 -0,65 -0,67 -0,33 -0,39 1,57 0,37 -0,66 0,70 F-statistic p-value F-statistic R2 Adjusted R2 0,62 0,76 0,01 -0,01 0,56 0,81 0,01 -0,01

As shown in the table none of the explanatory variables has a significant coefficient. Also, the variables concerning board composition do not have the expected sign. In contrast to the expectations, firms with an independent board seem to have slightly lower abnormal returns than firms with a dependent board, although not significantly so. Furthermore the R2_{is very low, only one percent of the variation in the abnormal returns}

is explained by the explanatory variables and the adjusted R2_{is even negative. This}

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6. Conclusion

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On the basis of the market and risk adjusted return model, it is concluded that US acquirers on average earn negative and statistically significant returns around the announcement of an acquisition. These results mean that hypothesis 1 has to be rejected. After the full sample of firms was split into two groups, it can be seen that the returns around the announcement of firms with an independent board are lower than the returns of firms with a dependent board, although insignificantly so. This result contradicts the outcome of Byrd and Hickman (1992), who found that returns are less-negative for firms in which at least half of the directors are independent.

When the sample is divided in firms which acquire a domestic target and firms which acquire a cross-border target, firms which acquire a domestic target have higher announcement returns than firms which acquire a cross-border target. This is in line with the results of Moeller and Schlingemann (2005). Since a t-test showed that the difference is not significant, hypothesis 3 cannotbe rejected.

Examining hypothesis 4, it can be seen that the difference in the returns between domestic and cross-border targets is insignificantly larger for firms with an independent board. This is in line with hypothesis 4.

The results of the OLS-regression are in accordance with the results of the t-tests. Neither the board composition, geographic diversification, nor the control variables have a significant influence on the average abnormal returns. This is not in line with previous literature, which has found that abnormal returns can be influenced by the method of payment, whether the target is a public firm and whether the bidder and target are from related industries.

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It is possible to extent this research in at least two ways. Firstly, it could be researched if board composition does influence the long-run value gains of the acquisition. Secondly, it would be possible to research if board composition does have an influence on abnormal returns in other countries which have an one-tier board, like the UK.

The results of this thesis indicate that board independence is not as important as many people, and governments, think. It has no significant influence on the returns of one of the biggest investments that companies can possibly do, namely, acquisitions. Requirements for board independence then might not be the answer to prevent further corporate scandals.

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The influence of board independence on the value performance of US acquisitions