The impact of country governance standards on
mergers and acquisitions synergy in Europe
Niels Smakman S3030172 Master thesis Finance University of Groningen
Faculty of Economics and Business Supervisor: Dr. R.M. van Dalen Date: January 9, 2018
Word count: 11,966
Keywords: market for corporate control, management discipline, country governance, cross-border mergers and acquisitions, European market
ABSTRACT
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1. Introduction
Recently in the Netherlands, the Dutch painting and coatings giant Akzo Nobel came in a takeover fight with PPG, a rival from the United States (U.S.)1. PPG wanted to pay roughly 20 euros more per share than the shares were trading at the time. Finally, PPG’s attempt is cutoff by rejections of Akzo Nobel’s management, legal defeats and coverage by Dutch politicians. Nowadays, Akzo’s management made newly value creating long-term goals in order to convince their shareholders that it was the right decision at the time. Is this a valuable event which helps to align the interests between managers and shareholders? This paper tries to provide evidence.
Since the 1990’s the M&A market in Europe is at a rapid rate driven by intra-European M&As (Martynova and Renneboog, 2006). Where the number of M&As in 1990 was 4,401, in 2000 it reached a record of 18,367 and in 2015 it was still at a high level of 17,512 M&As per year2. The introduction of the Euro and the development of the new single European market are important reasons for the intra-European M&A market to grow (Martynova and Renneboog, 2006). The Euro reduced the home biasness of investors as a result of the eliminated currency risk. Therefore, the European capital market became more liquid. The single European market causes the interests in cross-border European M&As to survive the increased level of foreign competition.
Additionally, there are major corporate governance changes in Italy, France and Germany. These are corporate law reforms to strengthen the internal corporate governance standards. The law reforms give more power to shareholders, tighten disclosure requirements and toughen public enforcements (Enriques and Volpin, 2007). Laws differ significantly between European countries (La Porta et al., 1998). Therefore investor protection and corporate ownership differs as well. As a result, these differences affect the valuations of firms in Europe due to the fact of differences in risks and agency costs between firms.
3 in quality of country governance standards create more acquisition synergy in Europe? The hypothesis is that larger differences lead to more space for valuable management improvements. It is caused through the reflection of the better governance standards of one firm to the poorer governance standards of the other firm. The U.S. market is traditionally characterized by this mechanism whereas the continental European market is not (Cuervo, 2002). As indicated, the takeover market in Europe reached an all-time high record. Additionally, enforcements of the laws and laws governing investor protection differ significantly in the European countries (La Porta et al. 2000). Furthermore, as aforementioned, there are corporate governance changes due to corporate law reforms in the last decade (Enriques and Volpin, 2007). Therefore, it is interesting to conduct research based on a sample of European firms to see whether the mechanism of corporate control also works in Europe. With a recent sample period ranging from 2000 to 2015 and the use of the World Governance Index (WGI), this paper contributes to the literature. The sample consists of 129 M&As of European acquirer and target firms.
In this study the short- and the long-term acquisition synergies are considered. For the short-term the event study methodology of MacKinlay (1997) is used to obtain the abnormal returns as proxy for acquisition synergy. With the Cumulative Abnormal Returns (CARs) as dependent variable and a proxy for differences in corporate governance standards as explanatory variable, an Ordinary Least Squares (OLS) regression analysis is performed. The proxy for the quality of corporate governance is created by the following five indicators of the WGI: control of corruption, government effectiveness, regulatory quality, rule of law and voice and accountability. It is assumed that corporate governance standards correlate with country governance. The absolute difference in country governance standards between the two different countries is used as explanatory variable in the regression analysis to analyze the cross-border M&As.
The results show that the 11-day Cumulative Average Abnormal Return (CAAR) is 0.16% for the acquirer firms, 12.54% for the target firms and 2.21% for the weighted portfolio. These outcomes are in line with other studies. The regression for the short-term analysis indicates that a larger absolute difference is negatively associated with the acquisition synergy.
4 acquirer-better portfolio outperformed the target portfolio with a CAAR of -8.47% compared to -12.35%.
Looking at the results for both the short- and long-term, larger differences in quality of country governance standards are negatively associated with acquisition synergy. However, in the long-term, the acquirer-better governance portfolio performed better than the target-better governance portfolio. This partly supports the theoretical undergrounding of the mechanism of the market for corporate control. Although, the better governance standards of the acquirer firm are reflected on the target firm, it still does not create value in the long-term.
The paper structure is as follows. In section 2 the relevant literature is discussed. The section is mainly about corporate governance and M&As. Also, the existing literature outcomes are discussed. Section 3 is about the methodology and section 4 provides a data description. In section 5 the results are discussed. The outcomes of the event studies, the regression results and the long-term performance are provided. Section 6 concludes and discusses the results.
2. Literature
The main topic of the paper is the association between corporate governance and synergy created by M&As. This section starts with a literature overview concerning corporate governance and M&As in the first subsection. The second subsection provides an overview of the existing empirical evidence. The last subsection discusses the determinants of acquisition synergy.
2.1 Corporate governance and M&As
Corporate governance is defined as the degree to which shareholders, the outside investors, can protect themselves against dispossession by inside managers (La Porta et al., 1998). Traditionally in finance there exists an agency problem where the interests of the agents (managers) and shareholders are not in line. This problem exists because agents who make important decisions for the firm do not bear the risks of that decisions. The agents do not bear a substantial share of the wealth effects, thus there is a separation of ownership and control (Fama and Jensen, 1983). A mechanism to align the interests or to solve the agency problem, is the threat of a takeover (Lel and Miller, 2015). The better shareholders can align the interests, the higher the firm value is. Companies with a poorly functioning management are lower valued and are seen as an interesting investment opportunity for a bidder company. As a result, managers see it as a threat to lose their job when they manage a company poorly. An acquisition will be valuable by replacing the poor management by a more efficient management. In the literature, this is defined as the mechanism of corporate control (Lel and Miller, 2015).
5 have no incentives to share the created wealth with the shareholders in the form of dividends. On the other side, shareholders are not willing to finance if they have no rights. Shareholder rights, like the right to vote, creates a pressure (incentive) on the incumbent management to do their job as well as possible. Jiraporn and Gleason (2007) argue that agency conflicts are caused by separation in ownership and control. Firms with fewer shareholder rights are likely to face higher agency costs. The higher agency costs are caused by managers who take advantage of the weaker shareholder rights. Managers increase their perks consumption, when they place their own private interests ahead of the interests of shareholders. In that sense managers decrease their efficiency of doing their job to the best of their abilities.
Gompers, Ishii and Metrick (2003) conducted research about the relation between corporate governance and stock returns using a governance index consisting of 24 anti-takeover provisions. More anti-takeover provisions mean less shareholder rights, because anti-takeover provisions are in the advantage of the sitting management. The researchers found a negative relation in their sample of on average 1,500 U.S. firms per year in the period 1990-1999. It is argued that an improvement of corporate governance, more shareholder rights (less anti-takeover provisions) and therefore less managerial power, caused a decrease in agency costs. As a result, the shareholder wealth increases. Gompers, Ishii and Metrick (2003) also found that differences in corporate governance standards between companies are not properly reflected in the market prices. Linking that finding to the takeover market, Wang and Xie (2008) used the governance index and found that larger differences in corporate governance lead to more acquisition synergy. As aforementioned, this works as a mechanism for corporate control.
Looking at the result of prior research, there is clear evidence that the rights of shareholders are an appropriate proxy for measuring corporate governance standards. La Porta et al. (2000) showed that laws governing investor protection and the quality of enforcements of the laws differ significantly in Europe. Chung, Elder and Kim (2010) looked at the association between stock market liquidity and quality of corporate governance. Better governance standards lead to higher stock market liquidity. Higher stock market liquidity results in a lower cost of equity capital and therefore to a higher firm valuation. Firms in countries with more stringent and fairer disclosure rules and better protection of minority shareholders are in that sense likely to be valued higher. Therefore, it is argued that laws, regulations and enforcements on country level also are an appropriate proxy for quality of corporate governance.
6 Vishny, 1986; Adams and Ferreira, 2009). However, this study focuses on differences in country governance standards.
In the literature two main corporate governance systems are mentioned: the large shareholder control systems in the continental European countries and the market control systems in the Anglo-Saxon countries, like the United Kingdom (U.K.) and the U.S. (Cuervo, 2002). The large shareholder system is mainly characterized by concentrated ownership. Control is exercised by large shareholders and there is no active market for corporate control. On the other hand, in the market control system, there exists a developed market for corporate control where capital markets are very liquid and ownership is widely spread (Cuervo, 2002). In the large shareholder system anti-takeover protections protect the incumbent managers and the large shareholders use their power to benefit privately at the expense of minority shareholders (La Porta, 2000). However, codes of good governance and laws and regulations should prevent the rights of minority shareholders (Cuervo, 2002). According to Cuervo (2002), in continental European countries the laws are applied formally but not in the spirit of the law. In these countries takeovers plans are comprehensively analyzed to see what the impact is on competition. The market of corporate control is characterized by surprise effects and directly influences the strategy and governance of poor managed companies. This suggests that the market of corporate control will not work in such circumstances. It is argued that it is better to extend the mechanism of the market of corporate control than extending the use of codes of good governance in the European continental countries to solve the agency problem (Cuervo, 2002).
In this study the analysis focuses on whether the mechanism of market control works in Europe. Because there are differences in law and governance between countries, it is expected that this has an impact on cross-border acquisitions. Although there are many similarities between cross-border and domestic acquisitions, there are specific differences and unique risks (Shimizu et al, 2004). Differences and unique risks are for example in culture, preferences of customers and in government regulations. These additional risks or barriers may influence the degree of realizing the long-term objectives of firms.
7 reflected on that of the target which creates value (the positive spillover by law hypothesis). The second scenario is when there is a partial takeover: the bidder takes over a part of the target company. In that scenario it is indicated that when the acquirer firm has higher governance standards it will apply these standards to the target firm which will create value (spillover by control hypothesis). In the third scenario, the target firm has better governance standards than the acquirer firm. In that scenario it is explained that the acquirer firm will voluntary bootstrap the targets governance standards. The acquirer firm applies the better standards to their own governance which will be reflected in a share price increase (the bootstrapping hypothesis). In either scenario, when the acquirer firm or the target firm has better governance standards relatively, a M&A is more valuable. Therefore, there is evidence that the absolute difference in quality of corporate governance is positively associated with acquisition synergy. Martynova and Renneboog (2008) found no evidence to support the negative spillover hypothesis. The negative spillover hypothesis is that the poorer governance of the acquirer firm will be imposed on that of the target firm which will result in lower acquisition gains.
Based on the efficient markets hypothesis, possible acquisition synergies are immediately reflected in the market prices. However, it is possible that newly obtained information about synergies becomes available in the longer term. Agrawal, Jaffe and Mandelker (1992) found evidence that acquiring firms suffer losses of about 10% over the five years after the announcement date. This evidence suggests that markets overestimate potential synergies in the short-term. Based on these contradictions in the short- and long-term, and the changing governance environment in Europe, it is interesting to test both the short- and long-term performance of M&As in Europe. This results in the following research question: do cross-border M&As with larger absolute differences in quality of country governance standards create more acquisition synergy in Europe? Based on the research question the following hypotheses are formulated for the short- and long-term:
Hypotheses
H0a: Absolute differences in country governance standards are positively related to more cross-border M&As synergy in the short-term.
H0b: Absolute differences in country governance standards are positively related to more cross-border M&As synergy in the long-term.
2.2 Empirical evidence
8 As aforementioned in the previous subsection, Gompers Ishii and Metrick (2003) found evidence that corporate governance is strongly correlated with stock price returns. In their sample of 1,500 U.S. firms in the period 1990-1999, they found that on average half of the companies with the strongest corporate governance index earn 8.5% more than the other half of the sample with a lower corporate governance index.
Masulis, Wang and Xie (2007) conducted research in the U.S. using a sample of 3,333 acquirer companies. They found evidence that more anti-takeover provisions (less shareholder rights) lead to lower CARs around the announcement date of the acquisitions.
Wang and Xie (2008) found that deals with larger differences in corporate governance between acquirers and targets lead to higher abnormal returns around the announcement date. They used a sample of 396 U.S. M&As in the period 1990-2004. Target firms which are exposed to better governance standards due to acquisitions face on average a positive abnormal return of 21.52%. Acquirer firms, however, face a negative impact. On average, those firms lose -2.91% in the 11 days around the deal announcement date. However, by looking at a weighed portfolio of both firms, there is still a positive acquisition effect of 0.97%.
Bris and Cabolis (2008) conducted a worldwide study on cross-border mergers in the period 1989-2002 with a sample of 506 deals. They used the differences in shareholder protection, creditor protection, accounting standards and level of corruption of the country as proxies for corporate governance. Their findings are that in cross-border M&As, target companies face a higher announcement effect when the acquirer has better governance standards. Additionally, they made a comparison with matching domestic acquisitions and found that cross-border targets also face higher announcement returns compared to domestic targets.
Martynova and Renneboog (2008) looked at a sample of 2,419 M&As in Europe, with 737 cross-border deals in the period 1993-2001. They used a corporate governance index which includes different measures like shareholder rights, minority shareholder rights and creditor shareholder rights as proxy for the quality of the corporate governance of the target and bidder firms. The outcome is that the larger the absolute difference in quality of corporate governance between the bidder and the target is, the higher the acquisition synergy is at the announcement date. They explained it in the three scenarios as aforementioned in the previous subsection.
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2.3 Determinants of acquisition synergy
The existing literature found evidence for many explanatory determinants explaining acquisition synergy. The most used determinants in other studies are also applied in this study. Firm-specific characteristics are Tobin’s Q, leverage, Return On Assets (ROA) and firm size. Deal-specific characteristics include the way the deal is financed and whether the merger or acquisition is related or not. Furthermore, variables to control for common borders, crisis years and Anglo-Saxon countries are included. This subsection explains how these variables have influence on acquisition synergy. In appendix 2 a table is provided with exact definitions of all variables.
Tobin’s Q
Tobin’s Q is defined as the market value of assets over the replacement costs, the book value of the total assets (Lang, Stulz and Walking, 1989). Firms with a higher Tobin’s Q are more likely to find net present value projects and can therefore use their free cash flows more productively. It is therefore expected that the Tobin’s Q of the acquiring firm is positively related to the CARs in the short-term. Looking at this from the opposite perspective, firms with a lower Tobin’s Q are not likely to use their free cash flows productively. Those firms should rather pay out the free cash flows to the investors instead of doing an acquisition. Lang, Stulz and Walkling (1989) also argued that management performance is an important determinant for Tobin’s Q. Financial markets value firms which exploit their assets more productively (better management) higher than firms which do not. This is part of the market of corporate control mechanism. Therefore a positive sign is expected for the Tobin’s Q variable.
Leverage
Leverage can have a positive impact on the firm performance, when debt holders exert pressure on the incumbent managers to use the resources in a more productive way (Jensen and Meckling, 1976). Maloney, McCormick and Mitchell (1993) found evidence that leverage is positively associated with acquisition performance in the short-term. They also argued that due to the higher leverage the agency costs are reduced as a result of the increased power of the debt holders. However, Harrison, Hart and Oler (2014) found that too high leverage is associated with poor post-acquisitions performance. The post-acquisition management is then not familiar with the higher leverage. The management will pass over positive net present value projects because they are focusing on reducing risks. Hence there is no clear evidence whether there is a positive or negative effect in the short-term.
Firm performance
10 They found no association of the ROA of the target on both the acquirer and target abnormal returns. Hence, it is assumed that the ROA is positively associated with acquisition synergy, initiated by the target returns.
Firm size
Moeller, Schlingemann and Stulz (2004) found evidence that firm size (in terms of market capitalization) is negatively associated with acquisition performance. The main reason for this finding is the “managerial hubris”. Managers of the acquiring firms often think that they can manage the assets of the target more efficiently and overpay for the target assets (Roll, 1986). Managers prefer to make an acquisition rather than pay out the excess cash when there are no internal investment opportunities. Also, empire-building and agency costs are less an issue for smaller companies. Managers of smaller firms own a bigger stake in the company than managers of bigger firms which reduces the agency costs (Jensen, 1986). Hence, a negative sign is expected for the firm size variable.
Related acquisition
Companies that buy related assets could have costs benefits due to economics of scale and they can therefore have acquisition synergies. However, Campa and Kedia (2004) found evidence that companies that make a thoughtful decision to diversify could create firm value. Wang and Xie (2009) found evidence of a negative but insignificant association between acquisition synergy and the relatedness of the deal. An earlier study of Markides and Ittner (1994) found a positive association (in their sample of 276 U.S. international acquisitions in the period 1975-1988) between the relatedness of the industry and wealth creation. Hence in this study a positive association is expected between relatedness and acquisition synergy due to the economics of scale effect.
All cash deal
Wang and Xie (2009) found evidence that deals totally financed with cash lead to more acquisition synergy than deals partly financed with other sources like equity. It is reasoned that firms with poor returns issue equity, which they use as currency to pay for the newly assets (Travlos, 1987). According to the signal hypothesis, this is a signal to the market that their assets are overvalued which will lower the market price of the acquirer firm (Myers and Majluf, 1984). This study expects therefore a positive sign is for the all cash deal variable.
Crisis years 2007 and 2008
11 Common border
The study of Martynova and Renneboog (2008) controlled the regression to explain cross-border acquisition synergy with a common cross-border dummy variable. They found a positive significant association with the bidder abnormal returns and common borders. Narrower geographical and cultural factors make it easier to combine the companies. Hence, the variable is added in this study and a positive sign is expected.
United Kingdom country
There are roughly two corporate governance systems to distinguish as aforementioned in the literary framework (Cuervo, 2002). The United Kingdom is typically an Anglo-Saxon country which differs substantially compared to the large shareholder corporate governance system. The regressions are controlled for these differences.
3. Methodology
In this section the methodology is described. Firstly, the event study for short-term abnormal performance is discussed in subsection 3.1. Additionally, the different statistical tests to examine whether the null hypotheses that the CARS are significantly different from zero are described. Afterwards in subsection 3.2 the regression models to indicate the influence of the quality of corporate governance on acquisition performance are discussed. In the last subsection the Fama and French model for measuring the long-term abnormal performance is examined.
3.1 Event study methodology for short-term abnormal performance
To calculate the abnormal returns around the announcement date, the event study methodology of MacKinlay (1997) is used. It is a method for measuring the short-term impact of a certain event on the firm value. There are basically two models: the market model and the mean return model. The market model is a more comprehensive model which is improved over the mean return model because the variance of the abnormal returns is reduced. Therefore, in this study the market model is preferred. Using the market model, first the daily normal returns for firm i and period t (Rit) and the market return for country stock market m at period t (Rmt) are calculated as
𝑅𝑖𝑡, 𝑚𝑡 = 𝑎𝑝𝑡0
𝑎𝑝𝑡−1 -1 (1)
where apt0 is the adjusted closed price at day zero and apt-1 is the adjusted closed price at the day before day zero. To estimate the parameters of the market model the stock returns are regressed against the returns of the market in the estimation period. Using the market model, the expected return, 𝑅𝑖𝑡(𝐸), of firm i at period t is calculated as
12 where Rmt is the market return at period t, 𝛼𝑖 is the intercept, 𝛽𝑖 is the slope and 𝜀𝑖𝑡 is the error term. When the expected returns are calculated, the abnormal returns, ARit are calculated as follows
𝐴𝑅𝑖𝑡 = 𝑅𝑖𝑡− 𝑅𝑖𝑡(𝐸) (3)
The time line of the event study is displayed in figure 1 below. Date zero is the announcement date on which an acquisition is disclosed. In the figure the event window is established from day -5 till day 5. However, as is common practice, the event window also is established from day -1 till day 1 around the announcement day (MacKinlay, 1997). Furthermore, a one-day event window at the announcement day is considered. As is explained, the estimation period is needed to estimate the parameters of the market model. The parameters are needed to calculate the normal stock returns in the event window. A number of 250 days is appropriate to estimate the normal returns in the event window (MacKinlay, 1997). Estimation periods which are too long could disturb the model because possible other major effects are taken into account, whereas periods which are too short lead to less forecast power of the model. In both cases the estimated normal returns in the event window are not realistic.
t-5 t0 t5
(250 days estimation period) (Event period)
Figure 1. Time line for the event study
The CARs which are calculated in the event study need to be tested on whether they are on average significantly different from zero. The daily returns of the firms in this study are from different markets with a wide range of trading frequencies. Because some target firms in the sample are low frequent traded stocks, which are characterized by numerous zero returns and larger non-zero returns, the normality assumption is certainly violated (Cowan and Sergeant, 1996). The parametric t-test requires the normality assumption and is therefore inappropriate. Hence, nonparametric tests which have no distribution restrictions are required (Corrado, 1989). In event studies, the Cowan sign test and the Corrado rank test are often used (MacKinlay, 1997). Both tests are discussed in the following paragraphs.
The Cowan sign test counts the number of firms with positive CARs and examines whether they exceed the number expected in absence of abnormal returns in the event window (Cowan, 1992). A 100-day estimation period before the event period is used to estimate the number of expected firms in absence of abnormal returns. This test works with the following procedure: first an approximation of the binomial distribution, 𝑝̂, is calculated as
13 where N is the number of events, n is the number of positive ARs per estimation window, t is the estimation window from day -105 to day -6, i is a firm and Sit is 1 if ARit > 0 and zero otherwise. After calculating 𝑝̂, the test-statistic is calculated as
𝑡 − 𝑠𝑡𝑎𝑡𝑖𝑠𝑡𝑖𝑐 = 𝑤−𝑛𝑝̂
𝑛𝑝̂ (1−𝑝̂)2 (5)
where w is the number of stocks in the event window for which the stocks have a positive CAR. The test-statistic follows the t-distribution and can be estimated for different event windows (Cowan, 1992).
The Corrado rank test is also a non-parametric test, but the test is only powerful for a one-day event window (Cowan, 1992). For this test all the abnormal returns for each company are ranked from day -244 to day +5, denoted as Kit. After ranking the abnormal returns the standard deviation of the average ranks of each day, 𝑆𝐾 is calculated as
𝑆𝐾 = √ 1 250 ∑ (∑ (𝐾𝑖𝑡− 𝐾̅) 𝑁 𝑖=1 )2 𝑡−244 𝑡+5 (6)
Where 𝐾𝑖𝑡 is the average rank of the abnormal return on each day, 𝐾̅ is the average of all ranks, and N is the number of events. After calculating the 𝑆𝐾 the test-statistic is calculated as
𝑡 − 𝑠𝑡𝑎𝑡𝑖𝑠𝑡𝑖𝑐 = 1 𝑁∑ ( 𝐾𝑖𝑡− 𝐾̅ 𝑆𝐾 ) 𝑁 𝑖=1 (7)
where the test-statistic follows the t-distribution.
3.2 Measuring the impact of corporate governance standards on acquisition synergy
Using the event study methodology of MacKinlay (1997) and an OLS regression the impact of corporate governance on acquisition synergy is analyzed. The key explanatory variable is discussed in section 3.2.1, section 3.2.2 gives an explanation of the OLS regression model. Section 3.2.3 explains the interaction regression models which are used for further analysis.
3.2.1 Key explanatory variable and the relation of corporate governance to acquisition synergy
To measure the effect of corporate governance on acquisition synergy, an appropriate variable is needed to measure the quality of corporate governance. As mentioned in the literary framework, shareholder rights are an important determinant of the quality of corporate governance and those rights are highly influenced by the governance standards of a country. The proxy for shareholder rights is already used in studies such as Gompers, Ishii and Metrick (2003), Martynova and Renneboog (2008) and Wang and Xie (2008). Although this variable is already used in those studies, it is not widely available for European companies. Therefore, the corporate governance is measured using the WGI3 and referred to as Laws, Regulations and
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14 Enforcements (LRE) on country basis. Hence, the key explanatory variable in this study is the absolute difference in LRE between the acquirer country and the target country. This variable is appropriate as proxy for measuring the quality of corporate governance and is widely available for each country in the sample. The WGI consists of yearly data for the period 2000-2015. For each country, indicators are estimated for six governance dimensions, namely: control of corruption, government effectiveness, political stability and absence of violence/terrorism, regulatory quality, rule of law and voice and accountability.
The indicators combine the views to a large extent of companies, citizen and expert survey respondents in the countries. The indicators are based over 30 different data sources produced by different survey institutes, think tanks, non-governmental organizations, international organizations, and private sector firms4. All six indicators are scaled on a range from -2.5 to 2.5 where a higher score implies better governance quality. This methodology is inspired by the research of Gompers, Ishii and Metrick (2003) who also created an index. Their index is based on 24 anti-takeover provisions, where a higher index corresponds to more managerial power and weaker shareholder rights. As explained in the literary framework, the absolute difference in quality of country governance standards between the acquirer and target company is the outcome variable which is used in the models to see whether it influences the acquisition synergy. The hypothesis is that the synergy effects increase when the absolute difference in country governance standards (∆𝐿𝑅𝐸) increases.
3.2.2 Regression models
To analyze whether more acquisition synergy is created in the short-term when there is a larger absolute difference in quality of corporate governance the following OLS regression models are applied:
𝑀𝑜𝑑𝑒𝑙 1: 𝐶𝐴𝑅𝑃 𝑖 = 𝛼0+ 𝛽1∆𝐿𝑅𝐸 𝑖+ 𝛽2𝑋𝑑 𝑖+ 𝜀𝑖 𝑀𝑜𝑑𝑒𝑙 2: 𝐶𝐴𝑅𝑇 𝑖= 𝛼0+ 𝛽1∆𝐿𝑅𝐸 𝑖+ 𝛽2𝑋𝑑 𝑖+ 𝜀𝑖 𝑀𝑜𝑑𝑒𝑙 3: 𝐶𝐴𝑅𝐴 𝑖 = 𝛼0+ 𝛽1∆𝐿𝑅𝐸 𝑖+ 𝛽2𝑋𝑑 𝑖+ 𝜀𝑖
In the regressions, the i stands for a specific deal. The P, T and A stands for Portfolio, Target and Acquirer CAR, respectively. These are the dependent variables which are measures of the CARs around the announcement day of the acquisition in different event windows. The portfolio CAR is a measure for acquisition synergy. The variable is created by a weighted portfolio of the bidder and target firms’ market capitalization using the methodology of Bradley, Desai and Kim (1988). In all three models the key explanatory variable is the absolute difference in quality of country governance standards between the acquirer country and the target country. The variable is indicated as ∆𝐿𝑅𝐸, the absolute difference in Laws, Regulations and Enforcements.
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15 For the ∆𝐿𝑅𝐸 the β1 is the parameter of interest. With the parameter β2, the regressions are controlled using different firm- and deal-specific characteristic variables. In the models, ε denotes the error term and α is the intercept.
To control for heteroscedasticity, the regression should be controlled for clustering (Cameron and Miller, 2010). It is possible that the error terms are uncorrelated with no use of clusters, but are correlated within clusters. By using cluster robust standard errors, the regression results are controlled for non-normality and heteroscedasticity. Clusters are made by deals which are announced in the same month. For example in April 2000 there were four deals announced and in May 2004 and June 2007 there were three deals announced. The results are also robust for acquiring country clustering.
To ensure that there is no multicollinearity in the model, which means that control variables are highly correlated, the Variance Inflation Factors (VIFs) and the correlations coefficient are analyzed. VIFs higher than the threshold ten should be removed (O’brien, 2007). When it appears that two variables are highly correlated or a variable has a VIF higher than ten, the variable is removed as control variable. The correlation and VIF estimates are provided in the tables of the appendixes 3 and 4 respectively.
3.2.3 Models for further analysis
To see whether the results differ when the acquirer firm has better governance standards compared to the target or not, further analysis is required. As Brambor, Clark and Golder (2005) describe, the use of interaction variables makes it possible to test conditional hypotheses. The use of interaction variables in the regression is a tool to do the additional analysis. The models are as follows:
𝑀𝑜𝑑𝑒𝑙 4: 𝐶𝐴𝑅𝑃,𝑇,𝐴 𝑖 = 𝛼0+ 𝛽1∆𝐿𝑅𝐸 𝑖+ 𝛽2𝐴𝑖 + 𝛽3(∆𝐿𝑅𝐸 𝑖 ∗ 𝐴𝑖) + 𝛽4𝑋𝑑 𝑖+ 𝜀𝑖 𝑀𝑜𝑑𝑒𝑙 5: 𝐶𝐴𝑅𝑃,𝑇,𝐴 𝑖 = 𝛼0+ 𝛽1∆𝐿𝑅𝐸 𝑖+ 𝛽2𝑇𝑖 + 𝛽3(∆𝐿𝑅𝐸 𝑖 ∗ 𝑇𝑖) + 𝛽4𝑋𝑑 𝑖+ 𝜀𝑖 In the models the i stands for a specific deal, the A stands for the Acquirer firm has better governance standards relatively and the T stands for the Target firm has better governance standards relatively. The parameter 𝛽2 indicates a possible intercept effect. The estimate shows whether there is a fixed higher or lower effect on the CARs when the acquirer or target firm has better governance standards respectively. The parameter 𝛽3 indicates a possible slope effect. The estimate shows whether there is a more increasing governance effect on the CARs when the acquirer or target firm has better governance standards respectively. Furthermore, the models are the same as the models 1, 2 and 3.
3.3 Long-term abnormal performance measurement
16 𝑅𝑖𝑡 − 𝑅𝑟𝑓𝑡 = 𝐴𝑅𝑖 + 𝛽𝑖1(𝑅𝑚𝑡− 𝑅𝑟𝑓𝑡) + 𝛽𝑖2𝐻𝑀𝐿𝑡+ 𝛽𝑖3𝑆𝑀𝐵𝑡 + εit (8) In the model the monthly excess returns (𝑅𝑖𝑡− 𝑅𝑟𝑓𝑡) of company i at time t are regressed against the three factors of Fama and French and the difference is the abnormal return of company i (𝐴𝑅𝑖). The three factors in the Fama and French model are the excess return on the market (market return minus the risk free rate , 𝑅𝑚𝑡− 𝑅𝑟𝑓𝑡), the book-to-market size return (High-Minus-Low, HMLt) and the size factor return (Small-Minus-Big, SMBt). The error term of the model is indicated as εit. The three factors are collected from the Kenneth R. French website5. The website provides a dataset with average factors for all countries in western Europe, including the United Kingdom. Akgul (2013) found evidence that the factors between western European countries correlate from 90% to 95%, except for Ireland which correlates 81% (which is also high). Therefore the average factors are appropriate to use. The main advantage of using the three-factor model for calculating the normal expected returns is that it does not require data from related sample firms (Barber and Lyon, 1997).
To analyze whether differences in country corporate governance exercise influence over the value created, different portfolios are formed:
• A portfolio (50%) with the smallest absolute differences in quality of governance; • A portfolio (50%) with the largest absolute difference in quality of governance; • A portfolio where the acquirer firms have better governance to the target firms; • A portfolio where the target firms have better governance to the acquirer firms.
The null hypothesis which states that the mean monthly abnormal return is equal to zero can be tested by using the mean intercept (the 𝐴𝐴𝑅𝑖𝑡) (Barber and Lyon, 1997). The test-statistic is calculated as
𝑡 − 𝑠𝑡𝑎𝑡𝑖𝑠𝑡𝑖𝑐 = 𝐴𝐴𝑅
𝜎𝐴𝐴𝑅 * √𝑛 (9)
Where AAR is the Average Abnormal Return, 𝜎𝐴𝐴𝑅 is the cross-sectional sample standard deviation of the ARs and n stands for the number of firms.
4. Data
The data regarding the M&As in Europe is collected from the database Zephyr constructed by Bureau van Dijk. Zephyr is a popular database which is used in many studies about M&As. The coverage is worldwide, and the database contains information over 140,000 transactions. The database is updated each year with new deals that have taken place. The firm-specific data, the stock prices, and the benchmark indexes are obtained from Thomson Reuters DataStream. Based on the hypotheses and prior research, the following search criteria are applied:
5 Seen on October 11, 2017
17 1. The acquisition is completed;
2. The bidder controls less than 50% of the shares of the target prior to the announcement and owns more than 50% of the target after the transaction;
3. The time period is 2000-2015;
4. Listed European acquirer and listed/delisted target companies; 5. The deals are cross-border;
6. Deals are with a deal value of a million or higher and at least 1% of the acquirers’ market capitalization, measured in the year before the announcement date.
The first and second search criteria are obtained from the studies of Wang and Xie (2008) and Martynova and Renneboog (2008). It ensures that the transaction results in a change in control and that the transaction is completed. It is questioned whether the change in control is leading to an improvement in corporate governance. As mentioned in the introduction, this research is about the recent governance changes in the European countries. Those points are reflected in the third and fourth search criteria. The fifth search criterium states that cross-border deals are required, because it is hypothesized that indirectly country governance differences reflects corporate governance differences which lead to more acquisition synergy. The sixth search criterion is borrowed from the study of Moeller, Schlingermann and Stulz (2004). That study argues that firms which takeover such relatively small targets result in negligible acquisition synergy effects. Therefore those takeovers are removed from the sample.
Using the selection criteria, the sample consists of 316 cross-border M&As. However not all firm-specific data is available for all deals. After removing deals due to data availability, the sample consists of 142 M&As and after removing deals where the acquiring firm takes over less than one percent of its own market capitalization the final sample consists of 129 M&As.
Table 1. Correlation diagram of the six measures of the country governance dimensions in the sample
1 2 3 4 5 6
Δ control of corruption 1 1.00
Δ government effectiveness 2 0.82 1.00
Δ political stability and absence of violence/terrorism 3 0.23 0.22 1.00
Δ regulatory quality 4 0.74 0.50 0.13 1.00
Δ rule of law 5 0.91 0.88 0.19 0.64 1.00
Δ voice and accountability 6 0.76 0.64 0.36 0.61 0.67 1.00
Correlation diagram of the six dimensions of the absolute differences (Δ) between the acquirer country governance standards and the target country governance standards. The bold text indicates the low correlation of the political stability and absence of violence/terrorism with the other 5 dimensions.
18 violence/terrorism dimension is considered as inappropriate to measure quality of corporate governance standards. Therefore the dimension is excluded.
Table 2. Summary statistics of the control variables used in the study
Variable Mean Median SD Minimum Maximum
Δ control of Corruption 0.60 0.44 0.52 0.00 2.24
Δ government effectiveness 0.42 0.24 0.44 0.00 1.82
Δ regulatory quality 0.36 0.28 0.30 0.00 1.16
Δ rule of law 0.40 0.27 0.40 0.00 1.71
Δ voice and accountability 0.21 0.18 0.17 0.00 0.80
ΔLRE 0.38 0.25 0.34 0.01 1.42
Tobin's Q (A) 1.17 0.76 1.59 0.04 10.69
Tobin's Q (T) 1.69 0.70 4.59 0.02 44.99
Leverage (A) 0.65 0.18 1.51 -1.09 8.12
Leverage (T) 0.94 0.13 3.79 -1.90 33.70
Log market cap (A) 6.47 6.58 0.86 4.03 8.01
Log market cap (T) 5.58 5.49 0.84 3.57 7.22
ROA (A) 0.83 0.77 0.60 0.02 2.79
ROA (T) 2.59 0.93 16.31 0.01 185.70
All cash deal 0.64 1.00 0.48 0.00 1.00
Related acquisition 0.62 1.00 0.49 0.00 1.00
Crisis dummy 2007-8 0.19 0.00 0.40 0.00 1.00
Common border 0.35 0.00 0.48 0.00 1.00
United Kingdom (T) 0.09 0.00 0.28 0.00 1.00
United Kingdom (A) 0.20 0.00 0.40 0.00 1.00
The table provides the summary statistics of the explanatory and control variables used in this study. Δ stands for the absolute differences of the country governance indicators between the country of the target firm and the acquirer firm. A stands for Acquirer firm and T stands for Target firm. Furthermore, ΔLRE stands for absolute differences in Laws, Regulations and Enforcements between the acquirer
country and target country, the log market cap stands for the logarithm of the market capitalization and ROA stands for Return On Assets.
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Table 3. Governance dimensions by country
Number Control of corruption Government effectiveness
Regulatory quality Rule of law Voice and
accountability
Country Acquirer Target Mean SD Mean SD Mean SD Mean SD Mean SD
Denmark 4 5 2.43 0.10 2.11 0.16 1.81 0.08 1.94 0.07 1.62 0.09 Finland 6 3 2.36 0.14 2.14 0.13 1.79 0.11 1.97 0.06 1.59 0.08 Sweden 11 8 2.24 0.09 1.96 0.10 1.68 0.16 1.91 0.08 1.60 0.07 Switzerland 12 6 2.13 0.06 1.98 0.12 1.67 0.10 1.86 0.08 1.58 0.08 Norway 4 6 2.12 0.14 1.90 0.08 1.44 0.17 1.93 0.06 1.63 0.09 Netherlands 7 14 2.11 0.11 1.86 0.14 1.78 0.10 1.79 0.08 1.58 0.07 Luxembourg 0 2 2.00 0.15 1.75 0.14 1.75 0.09 1.82 0.05 1.54 0.07 Germany 17 14 1.81 0.09 1.61 0.12 1.55 0.06 1.67 0.08 1.39 0.05 United Kingdom 11 26 1.81 0.21 1.68 0.14 1.75 0.09 1.70 0.08 1.34 0.09 Austria 4 1 1.79 0.29 1.76 0.17 1.53 0.09 1.86 0.05 1.40 0.06 Ireland 5 0 1.58 0.14 1.54 0.11 1.71 0.13 1.68 0.11 1.38 0.10 Belgium 9 4 1.45 0.12 1.66 0.19 1.29 0.07 1.35 0.08 1.39 0.03 France 17 20 1.37 0.08 1.55 0.14 1.17 0.11 1.42 0.07 1.24 0.11 Spain 8 1 1.05 0.27 1.25 0.35 1.13 0.19 1.12 0.12 1.13 0.11 Portugal 0 2 1.03 0.11 1.07 0.11 0.99 0.21 1.11 0.11 1.22 0.15 Poland 2 7 0.39 0.16 0.58 0.13 0.87 0.12 0.60 0.16 0.98 0.09 Italy 12 5 0.24 0.26 0.50 0.18 0.88 0.13 0.46 0.16 1.01 0.07 Slovak Republic 0 2 0.22 0.15 0.80 0.12 0.98 0.16 0.46 0.10 0.92 0.04 Greece 0 3 0.14 0.32 0.58 0.17 0.73 0.21 0.65 0.21 0.87 0.18
20 Appendix 6 provides the distribution of the number of M&As per year. The descriptive statistics of the market capitalization of the acquirer and target companies prior to the M&As are presented. The mean target size to the acquirer size ratio is 0.37 and the median is 0.17. These statistics are in line with the study of Wang and Xie (2008). Acquirer firms are much greater than the target firms in the sample. There are two periods with relatively more cross-border deals which have a clear explanation. The years 2000-2001 were the end of the fifth takeover wave (Martynova and Renneboog, 2008). There are 22 deals in that part of the sample. In the years 2007 and 2008, the world hit one of the greatest economic recessions of all time. The sample includes 25 deals in the crisis period. As aforementioned the regressions controls for the crisis years.
Table 3 provides for every country in the sample the five governance indicators over the period 2000-2015. There are major differences in governance standards between the northern countries and the countries from the south and east of Europe. The countries Italy, Greece, Poland, Portugal, Slovak Republic and Spain have lower governance standards. Also the standard deviations of these countries are higher compared to the others. In the southern countries the governance standards decreased after the financial crisis years 2007 and 2008. In the eastern countries like Poland and Slovak Republic there are on average some improvements observed. Poland and Slovak Republic had in 2000, governance standards of 0.72 and 0.50 on average, while it improved in 2015 to 0.84 and 0.70 respectively. In the southern countries the opposite effect is observed, their governance standards decreased.
5. Results
In this section the outcomes of the study are discussed. In subsection 5.1 the outcomes of the event study for the short-term analysis are discussed. Subsection 5.2 provides the regression results and subsection 5.3 presents the long-term performance of the acquisitions.
5.1 Short-term performance
21
Table 4. Summary statistics of the CARs of the event studies
CARP (-5, 5) CARP (-1, 1) CARP (0) CARA (-5, 5) CARA (-1, 1) CARA (0) CART (-5, 5) CART (-1, 1) CART (0) All Mean 2.21% 1.32% 0.77% 0.02% 0.16% -0.45% 12.54%*** 10.57%*** 8.92%*** Median 1.33% 0.83% 0.23% -0.39% 0.01% -0.29% 7.26% 2.99% 1.78% Standard deviation 7.64% 5.49% 4.35% 7.11% 4.90% 3.42% 21.49% 19.81% 19.33% Minimum -23.35% -14.50% -13.01% -30.87% -14.22% -13.91% -37.67% -17.96% -8.36% Maximum 28.91% 24.76% 22.01% 26.34% 18.72% 11.81% 123.13% 126.48% 127.32% Number 129 129 129 129 129 129 129 129 129 Acquirer-better Mean 1.96% 1.60% 0.89% 0.09%* 0.57% -0.10% 10.07%*** 8.42%*** 6.39%** Median 0.97% 0.94% 0.44% -0.71% 0.24% 0.01% 3.39% 2.43% 0.69% Standard deviation 8.34% 6.45% 4.93% 7.89% 5.52% 3.65% 18.28% 15.22% 14.11% Minimum -23.35% -14.50% -13.01% -30.87% -14.22% -13.91% -37.67% -17.96% -8.36% Maximum 28.91% 24.76% 22.01% 26.34% 18.72% 7.84% 67.28% 67.99% 66.17% Number 65 65 65 65 65 65 65 65 65 Target-better Mean 2.46%* 1.04% 0.65% -0.05%* -0.26% -0.80%** 15.04%*** 12.75%*** 11.48%*** Median 1.70% 0.71% 0.04% 1.06% -0.55% -0.61% 10.37% 4.38% 3.01% Standard deviation 6.92% 4.35% 3.71% 6.27% 4.17% 3.16% 24.20% 23.50% 23.31% Minimum -19.26% -9.39% -9.61% -25.26% -14.01% -10.28% -25.43% -7.73% -3.40% Maximum 25.12% 17.54% 18.70% 16.44% 11.32% 11.81% 123.13% 126.48% 127.32% Number 64 64 64 64 64 64 64 64 64
The table contains the summary statistics of event studies of the cross-border mergers and acquisitions in Europe in the period 2000-2015. In the first column All means the entire sample, Acquirer-better stands for the acquirer companies have better governance standards than the target companies and Target-better stands for the target companies have Target-better governance standards than the acquirer companies. Furthermore, CAR stands for Cumulative Abnormal Returns for the Portfolio (P), Acquirer firm (A) and Target firm (T) with an 11-day, 3-day and 1-day event window. ***, **, * denotes the significance levels 1%, 5% and 10% respectively using the non-parametric Cowan sign tests. The CARP (0), CARA (0) and CART (0) for all nine portfolios are significant at a 1%
22 companies. They found a 2.91% loss for the acquirers and a 21.52% gain for the targets on average.
Looking at the subsamples, it seems that when the target company has better governance standards relative to the acquirer company, the portfolio performance is better. The 11-day portfolio CAAR is 2.46% compared to 1.96% where the acquirer firms have better governance standards. However, that result is not consistent. For the 3-day and the 1-day window the acquirer-better portfolio slightly outperformed the target-better portfolio. Furthermore, the results are not statistical significant. Only the target portfolio CAAR of 2.46% is significant at a 10% significance level.
There is more evidence for the 11-day CAARs when the acquirers and targets are separated. When the acquirer firms have better governance relatively, the CAAR is 10.07% compared to 15.04% when the target firms have better governance. In the 3-day event window, the CAAR is 8.42% compared to 12.75% and on the event day the AAR is 6.39% compared to 11.48%. Therefore, there is consistent evidence that when the target firms have better governance standards relatively, the target firms face higher CARs on average. All target CAARs are significant at the 1% significance level.
Looking at the subsamples of the acquirer CAARs, the differences are smaller. For the 11-day, 3-day and 1-day event window, when the acquirer firms have better governance, the CAARs are 0.09%, 0.57% and -0.10% compared to -0.05%, -0.26% and -0.80% when the target firms have better governance. Hence, when the acquirer firms have better governance standards, the acquirer firms face higher CARs on average. However, the results are not all significant.
5.2 Regression analysis
Table 5 presents the outcomes of the regression analysis for model 1, 2 and 3 as described in the methodology framework. The models are regressed for the 11-day and 3-day event windows. By looking at the portfolio CARs there is a significant negative association between the absolute difference in country governance and the acquisition synergy of a cross-border merger or acquisition. When the ΔLRE variable increases by 1 unit, the 11-day CAR of the portfolio decreases by 0.04 (4%). The result is significant at the 10% significance level. The question is what drives these results. Does it come from the acquirer firm, the target firm or from both firms? The regression analysis indicate that there is a significant negative association between the absolute difference in corporate governance standards and the target 11-day CARs. There is no significant association found between the absolute difference variable and the acquirer 11-day CARs. Therefore, this indicates that an absolute difference in governance has an effect on the announcement returns of the target, but not on that of the acquirer firm.
23
Table 5. Regression analysis CARP (-5,5) CARP (-1,1) CARA (-5,5) CARA (-1,1) CART (-5,5) CART (-1,1) Intercept 0.057 0.040 -0.043 0.012 0.047 0.095 (0.056) (0.043) (0.060) (0.039) (0.175) (0.154) ΔLRE -0.040* -0.023* -0.024 -0.015 -0.103* -0.109** (0.020) (0.013) (0.025) (0.013) (0.056) (0.050) Tobin's Q (A) 0.002 0.000 0.002 0.001 -0.002 0.002 (0.004) (0.007) (0.005) (0.007) (0.011) (0.009) Leverage (A) -0.004 -0.004 -0.004 -0.004 0.022 0.035 (0.005) (0.004) (0.005) (0.004) (0.022) (0.026) Leverage (T) 0.001 0.000 0.000 0.000 0.004 0.003 (0.002) (0.001) (0.002) (0.001) (0.003) (0.003)
Log market cap (A) -0.031*** -0.010 0.002 -0.007 0.068* 0.059*
(0.010) (0.008) (0.011) (0.009) (0.038) (0.033)
Log market cap (T) 0.034** 0.007 0.008 0.008 -0.084** -0.083**
(0.014) (0.009) (0.011) (0.008) (0.037) (0.034)
Return on assets (A) -0.008 -0.003 -0.017 -0.007 0.040 0.030
(0.013) (0.010) (0.011) (0.008) (0.034) (0.029)
All cash deal 0.009 0.008 0.011 0.007 0.001 -0.009
(0.014) (0.012) (0.013) (0.011) (0.044) (0.039) Related acquisition -0.022* 0.006 -0.017 -0.005 0.033 0.039 (0.012) (0.009) (0.011) (0.008) (0.042) (0.037) Crisis 2007 and 2008 0.045** 0.010 0.021 0.016* 0.071 0.062 (0.019) (0.008) (0.016) (0.009) (0.050) (0.049) Common border 0.007 0.012 0.012 -0.001 0.094* 0.095** (0.017) (0.010) (0.016) (0.009) (0.049) (0.045)
United Kingdom (A) -0.021 0.007 -0.005 -0.002 0.097*** 0.055
(0.017) (0.012) (0.016) (0.013) (0.036) (0.033) United Kingdom (T) -0.030 -0.011 -0.002 -0.026 0.113 0.082 (0.021) (0.030) (0.028) (0.019) (0.069) (0.070) Number of Obs. 129 129 129 129 129 129 Adjusted R2 11.13% -1.77% -1.10% -2.11% 7.07% 10.13%
The table provides the regression outcomes for analyzing the short-term acquisition performance of the 129 cross-border mergers and acquisitions in Europe in the period 2000-2015. The dependent variables are the Cumulative Abnormal Returns (CARs) for the Portfolio (P), Acquirer firm (A) and Target firm (T) with an 11-day and 3-day event window. Furthermore, ΔLRE stands for the absolute difference in
Laws, Regulations and Enforcements between the acquirer country and target country. For each variable the coefficients and the standard errors are provided. The standard errors are displayed in parentheses. The standard errors are adjusted for heteroscedasticity and time clustering. ***, **, * denotes the significance levels 1%, 5% and 10% respectively.
24 CAR of the portfolio increases by 0.034 (3.4%). A related acquisition has a significant negative impact. The 11-day CAR of the portfolio decreases by 0.022 (2.2%). Therefore a diversifying cross-border M&A creates more value in Europe. This supports the hypothesis of Campa and Kedia (2002). Firms choose to diversify, they have good reasons to make the deal. Furthermore, the crisis years had a positive impact on the 11-days acquisitions synergy of the portfolio. At a 5% significance level, the portfolio CARs in the crisis were 0.045 (4.5%) higher.
As expected the Tobin’s Q has a positive effect on acquisition synergy. When the Tobin’s Q of the acquirer firm increases by one unit, the 11-day CAR of the portfolio increases by 0.002 (0.2%). However, the coefficient is not significant. Therefore, no inferences can be made. For the other variables, which are not yet discussed in this section, hold the same. Due to multicollinearity problems in the regressions, the Tobin’s Q and the ROA variables of the target companies are removed.
For further analysis, table 6 shows whether the effect is influenced by the better governance standards of the acquirer firms relative to the target firms, or whether the effect is influenced by the better governance standards of the target firms relative to the acquirer firms. None of the six regressions find a significant effect. This means that no inferences can be made whether there are extra effects when the target or acquirer firm has better governance standards relatively. Additionally, the ΔLRE variables are not significant in the six regressions. However, those coefficients still have a negative sign which is consistent with the outcomes of the models 1, 2 and 3. Looking at the VIF table in appendix 4, the coefficients of the Abetter*ΔLRE and Tbetter*ΔLRE variables, range between the 4.707 and 6.681. These high VIFs indicate some multicollinearity issues, which probably causes the ΔLRE variable to be insignificant.
5.3 Long-term performance
For the long-term analysis, the effects of different portfolios are measured over the post five years after the announcement date of the takeover. The analysis holds only for the acquirer firms, because most target firms are taken over fully and therefore they ceased to exist. Table 7 provides the results. Because of the recentness of this study, not for all firms is the post five-year data available. Therefore the number of firms in the portfolios of the five-years one to five reduce. Because Poland is not included into the Fama and French factor data, the two observations for Poland are removed from the sample.
25
Table 6. CARP -5,5 CARA -5,5 and CART -5,5 interaction analysis
Acquirer-better Target-better
CARP CARA CART CARP CARA CART
Intercept 0.049 -0.046 0.055 0.058 -0.039 -0.023 (0.059) (0.063) (0.188) (0.057) (0.062) (0.181) ΔLRE -0.026 -0.018 -0.122 -0.051 -0.030 -0.074 (0.029) (0.032) (0.088) (0.032) (0.041) (0.071) Acquirer-better 0.009 0.007 -0.078 (0.019) (0.021) (0.069) Target- better -0.009 -0.007 0.078 (0.019) (0.021) (0.069) Acquirer-better* ΔLRE -0.025 -0.012 0.049 (0.044) (0.055) (0.114) Target-better*ΔLRE 0.025 0.012 -0.049 (0.044) (0.055) (0.114) Tobin's Q (A) 0.002 0.002 -0.001 0.002 0.002 -0.001 (0.004) (0.005) (0.012) (0.004) (0.005) (0.012) Leverage (A) -0.004 -0.004 0.023 -0.004 -0.004 0.023 (0.005) (0.005) (0.021) (0.005) (0.005) (0.021) Leverage (T) 0.001 0.000 0.003 0.001 0.000 0.003 (0.002) (0.002) (0.003) (0.002) (0.002) (0.003)
Log market cap (A) -0.030*** 0.002 0.074* -0.030*** 0.002 0.074*
(0.010) (0.011) (0.039) (0.010) (0.011) (0.039)
Log market cap (T) 0.034** 0.009 -0.088** 0.034** 0.009 -0.088**
(0.014) (0.011) (0.037) (0.014) (0.011) (0.037)
Return on assets (A) -0.008 -0.017 0.047 -0.008 -0.017 0.047
(0.013) (0.011) (0.037) (0.013) (0.011) (0.037)
All cash deal 0.010 0.011 0.006 0.010 0.011 0.006
(0.014) (0.014) (0.046) (0.014) (0.014) (0.046) Related acquisition -0.022* -0.017 0.033 -0.022* -0.017 0.033 (0.012) (0.011) (0.043) (0.012) (0.011) (0.043) Crisis 2007 and 2008 0.044** 0.021 0.066 0.044** 0.021 0.066 (0.020) (0.017) (0.050) (0.020) (0.017) (0.050) Common border 0.006 0.011 0.105* 0.006 0.011 0.105* (0.017) (0.016) (0.054) (0.017) (0.016) (0.054)
United Kingdom (A) -0.021 -0.005 0.086 -0.021 -0.005 0.086
(0.018) (0.016) (0.035) (0.018) (0.016) (0.035)
United Kingdom (T) -0.028 -0.001 0.107** -0.028 -0.001 0.107**
(0.021) (0.029) (0.077) (0.021) (0.029) (0.077)
Number of Obs. 129 129 129 129 129 129
Adjusted R2 9.86% -2.77% 7.49% 9.86% -2.77% 7.49%
The regression analysis with interaction effects, when the acquirer firm has better governance or the target firm has better governance relatively. The dependent variables are the Cumulative Abnormal Returns (CARs) for the Portfolio (P), Acquirer firm (A) and Target firm (T) with an 11-day event window. Furthermore, ΔLRE stands for the absolute difference in Laws, Regulations and Enforcements
26
are provided. The standard errors are displayed in parentheses. The standard errors are adjusted for heteroscedasticity and time clustering. ***, **, * denotes the significance levels 1%, 5% and 10% respectively.
than the small-difference portfolio, -16.70% compared to -5.27% respectively. This evidence is consistent with the outcomes in the short-term where there also is significant evidence that a larger difference in quality of corporate governance is associated with lower announcement returns. The portfolio in which the acquirer firms have better governance standards relative to the target firms performed better than the portfolio where the target has better governance standards, -8.47% compared to -12.35% respectively.
Table 7. Long-term performance
Year CAAR entire sample No. CAAR small- difference
No. CAAR large- difference No. CAAR acquirer- better No. CAAR target- better No. 1 -7.83%*** 127 -4.05%*** 64 -11.67%*** 63 -5.16%*** 64 -10.55%*** 63 2 -12.86%*** 124 -6.44%*** 62 -18.34%*** 62 -11.24%*** 62 -14.48%*** 62 3 -15.74%*** 112 -9.14%*** 56 -22.34%*** 56 -11.51%*** 53 -19.54%*** 59 4 -12.03%*** 104 -9.67%*** 52 -14.17%*** 52 -6.45%*** 50 -17.20%*** 54 5 -10.49%*** 102 -5.27%*** 51 -16.70%*** 51 -8.47%*** 49 -12.35%*** 53 Long-term performance of the acquiring firms calculated using the Fama and French three factor
model. CAAR stands for Cumulative Average Abnormal Return. For the analysis the sample is divided into portfolios of firms with small (50%) and large (50%) absolute differences in quality of country governance standards. Also, the sample is divided into portfolios where the acquirer firm has relatively better governance standards compared to that of the target. ***, **, * denotes the significance levels 1%, 5% and 10% respectively.
6. Conclusion
27 Europe with the assumption that corporate governance standards correlates with country governance standards.
Martynova and Renneboog (2008) stated that when in a takeover the better corporate governance standards of the acquirer company are imposed on those of the target, it will result in higher announcement returns. That is the positive spillover by law hypothesis with a fully and partially takeover. In this study, as the regression analysis shows in table 5, there is no evidence to support that hypothesis in the short-term. The better the governance standards of the acquirer firm relative to the target, the lower the announcement returns are. When the target firm has better governance than the acquirer firm, stated by the bootstrapping hypothesis of Martynova and Renneboog (2008), the acquirer firms also face significant positive announcement returns. That hypothesis is also not supported in this research by the analysis of the interaction regressions, as table 6 shows.
By looking at the long-term results, the portfolio of the entire sample faces a CAAR of -10.49% after five years. Generally, this means that cross-border M&A’s are not valuable. The result is in line with Agrawal and Jaffe (1992) as they also found a five-year CAAR post-acquisition performance of -10.26%. To analyze whether larger differences in governance standards lead to more acquisition synergy (a smaller loss) in the long-term, the sample is split in a large-difference and small-difference portfolio. The low-difference portfolio outperformed the high-difference portfolio. After five years the CAAR of the small-difference portfolio is -5.27% whereas that of the large-difference portfolio is -16.70%. This result is in line with the short-term regression analysis which shows that a larger difference leads to less acquisition synergy. To see whether the better acquirer governance standards or the better target governance standards influences the portfolio differently, the sample is also split into two other portfolios. The acquirer-better portfolio outperformed the target-better portfolio. After five years the acquirer-better portfolio faces a CAAR of -8.47% and the target portfolio a CAAR of -12.35%. Based on the sample used in this study it suggests that acquirer companies are able to limit the acquisition loss in some amount when they have better governance standards.
28 not face the additional risks as Shimizu et al. (2004) argued. Therefore, when limiting cross-border risks, there is more chance the mechanism of the market for corporate control to work. Discussion and further research
This study contributed new insights to the literature. However, comparability is questionable. Martynova and Renneboog (2008) also focus their research on Europe, but their timeframe is different. They used the timeframe 1993-2001, including the fifth takeover wave. This study uses the timeframe 2000-2015, including the years of one of the tremendous financial crises the world has ever faced (Essen, Engelen and Carney, 2013). Also, Martynova and Renneboog (2008) used different proxies to measure the quality of corporate governance. They used shareholder rights, minority shareholder protection and creditor rights as proxies instead of a country governance index in this study. Due to that differences, it is not surprising that the results deviate.
Cuervo (2002) made a plea for a better functioning market for corporate control in Europe to solve the traditional agency problem more properly. Cuervo (2002) argued that the European market is a large shareholder-oriented system which makes the market less liquid. Also, the surprise effects of takeovers are banished, because laws and regulations are too formally applied. This was also the case with Akzo Nobel’s takeover fight with PPG, a cooling down period, law protections and political influences cutoff the deal. Too much rules and submissions for approval in Europe eliminates surprise effects. However, the takeover threat had improved the governance of Akzo Nobel in some amount. Therefore, the takeover threat worked as the mechanism of the market for corporate control, it helped to align the interests of the managers and shareholders.
This study finds no evidence of a well-functioning market for corporate control in cross-border M&As in the European market. Larger differences are chances to create value, but as Shimizu et al. (2004) mentioned it also forms risks. These kinds of risks may influence the degree of realizing the long-term objectives of firms. The risks probably caused the negative association of larger differences in governance standards and acquisition synergies in the short- and long-term. Maybe the outcome forms an incentive to stimulate further convergence of the European Union in order to reduce the mentioned risks. With reduced risks, cross-border M&As will be more attractive and therefore the market for corporate control will function better.
