The impact on wealth effect of acquiring firms: National
cultural distance and shareholder protection in
cross-border acquisitions
MSc International Financial Management Faculty of Economics and Business
University of Groningen
Xinna Zhang Student number: 2212137 Supervisor: Dr. Adri de Ridder Co-assessor: Dr. Victoria Purice
June 09, 2017
Abstract: The primary objective of this study is to examine the wealth effect of
acquirers as well as the influence of cultural distance and shareholder protection with a sample of 415 cross-border acquisitions around their announcement dates during the period of 2011-2015. The empirical results show that cross-border acquisitions do enhance the value for the acquirers. Furthermore, the evidence shows a positive relationship between target countries’ shareholder protection and acquirers’ wealth effect, indicating that acquirers receive greater values with the increase of shareholder protection level in target countries. However, no significant results are found regarding the relationship between national cultural distance and acquirers’ wealth effect, implying that national cultural distance may not be as important as a performance determinant as prevalent theory suggests.
Keywords: cross-border acquisitions, national cultural distance, shareholder
protection, acquirers’ wealth effect
1. Introduction
With the development of economic globalization, the multinational flow of international capital in different countries has grown increasingly active. Cross-border acquisitions have become a popular trend for modern firms expanding abroad. At present, global expansion through acquisitions has had a hundred years of history. The global economy has gone through 5 acquisition waves starting from 1890. Many giant multinational firms and important industries have condensed their competitive strengths strongly and comprehensively by devoting themselves to these acquisition waves. After a record-breaking year for global acquisition activities in 2015 with 5 US $ trillion, the total value is expected to increase to 10 US $ trillion in 2017 (J.P.Morgan, 2017). Therefore, it is essential for modern firms to adapt to an intensely competitive global environment and gain a foothold through international acquisitions in the long run.
Compared to domestic acquisitions, the major problem that cross-border acquisitions experience is the need to solve the cultural conflicts that are generated from the differences in national culture in such acquisitions. Most scholars believe that the existence of national cultural distance impedes the communication, trust, and knowledge sharing of both parties, thus negatively impacting the abnormal returns of the acquirers (Ahern et al., 2015; Morosini et al., 1998; Aybar and Ficici, 2009). However, other scholars believe that national cultural distance improves cross-border acquisition performance by providing access to the targets’ capabilities and the intangible assets embedded in the national culture (Kogut and Singh, 1988), thereby leading to a positive abnormal return for acquirers. In addition, many empirical studies also show an insignificant relationship between national cultural distance and acquirers’ wealth effect (see, e.g., Gomez-Mejia and Palich, 1997; Markides and Oyon, 1998).
Furthermore, studies also show that the equity market is significantly influenced by different levels of shareholder protection. Studies find that weak shareholder protection on the target side is expected to damage acquirers’ value, as the concentrated ownership structure in weak shareholder protection countries that increases the premiums paid, thereby decreasing acquires’ return (Starks and Wei, 2004; Bris and Cabolis, 2008). In contrast, prior studies find that cross-border acquisitions are likely to yield higher premiums when target firms are located in strong shareholder protection countries (see, e.g., Feito-Ruiz and Menendez-Requejo, 2011) in line with the agency cost theory (John et al., 2010) and bargaining power theory (La Porta et al., 1998; Anderson et al., 2009)
are used to explore the impact of the announcements on the value of the acquiring firms and the factors explaining the wealth gains for the acquirers.
Finally, the results show that, on average, cross-border acquisitions do create value for the acquirers. Furthermore, the cross-sectional results show that shareholder protection plays a significant role in the direction and magnitude of the returns from the acquirers’ announcements. The evidence shows that the target countries’ levels of shareholder protection have significant and positive influence on acquirers’ wealth effect. This indicates that the premium paid decreases with the level of shareholder protection in the target countries. However, the result is not statistically significant regarding to the impact of national cultural distance, implying national cultural distance plays a minor role in measuring acquiring firms’ performance.
This study contributes to extant studies by providing new evidence regarding the acquirers’ wealth effect around the announcement date as impacted by national cultural distance and shareholder protection during the period of 2011 to 2015, and takes further steps in exploring factors that influence cross-border acquisitions.
The remainder of this paper is organized as follows. Section 2 outlines previous empirical studies and presents the hypothesis. Section 3 describes the data and methodology. Section 4 reports and analyzes the results of this study. The final section provides the concluding remarks.
2. Literature review and hypotheses
2.1. Wealth effect on acquiring firms
The resource-based view assumes that the capabilities and intangible assets of the firm create a sustainable competitive advantage that is not easily replicated by other firms, because these capabilities and intangible assets are shaped by the interaction between the business’ histories and institutional restrictions (Collis, 1991). These firm-specific capabilities and assets are valuable wealth that other firms desire to own. Hence, cross-border acquisition arises from the desire of firms to exploit such benefits, such as the technological advantages, management and marketing skills, geographical advantages, and country-specific institutional competencies that are counted among their capabilities (Anand and Delios, 2002). In addition, Larsson and Finkelstein (1999) propose that complementary resources are constantly taken into account when firms seek to expand abroad. Thus, cross-border acquisitions imply that the potential value of the acquisition is very high. Moreover, Barney (2001) suggests that firms need diversified skills and assets to cope with the needs of a diverse world. Thus, the stronger the complementary skills and assets of both the acquirers and target firms, the greater benefit and competitiveness that can be realized after the cross-border acquisition. More importantly, internationally diversified assets can be obtained by acquirers through cross-border acquisitions. As Denis et al. (2002) state, multinational firms obtain higher value with the presence of intangible assets, which are acquired through international expansion. Hence, a positive wealth can be expected for acquirers, which is in line with the resource-based view on cross-border acquisitions.
the production, marketing and finance gradually reach the economies of scale (Sudarsanam, 2003). More importantly, acquirers can achieve synergic gains through the spreading of investment risks and improving operational flexibility by expanding internationally into various market conditions (Aybar and Ficici, 2009). DeLong (2003) states that the synergic gains through economies of scale are critical determinants of the shareholders’ value creation. As cross-border acquisitions increase the operational flexibility for acquirers, this enables them to arbitrage from institutional environment (e.g., tax regulations), to capture positive externalities (e.g., learning cost externalities), and to gain costs savings by exploiting the economies of scale under the multinational maximizing network (Doukas and Travlos, 1988). As a result, cross-border acquisitions will enhance the acquirers’ value.
However, international expansion through acquisitions also leads to great risks that can jeopardize the potential gains of the acquirers. The presences of information asymmetry and agency cost are potential risks for multinational firms when expanding abroad (Reeb et al., 1998; Goergen and Renneboog, 2004).
With respect to information asymmetry, Reeb et al. (1998) argue that foreign acquirers may lack knowledge concerning the local market, as they may have different sources and availability of information that may result in potential problems compared to local competitors. Moreover, various scholars emphasize the potential problems such as "liability of foreignness" and "double-layered acculturation" within an international context (Barkema et al., 1996; Eden and Miller, 2004). These risks are triggered by the differences in natural culture, customer preferences, business practices, and institutional environment. Thus, the challenges related with acquisition integration are increased for the acquirers (Aybar and Ficici, 2009). Meanwhile, the uncertainty of the local market will increase, which causes an increased chance of making poor investments. In addition, foreign acquirers may have fewer informed owners and managers compared to local competitors, and thus face increased risks. In view of the above discussion, it can be expected that cross-border acquisitions may result in a destruction of value for the acquirers.
private gains are likely to increase along with firm size rather than with firm performance (Goergen and Renneboog, 2004). Managers may even extract value from the acquirers’ shareholders by conducting acquisitions that force the combined business to be mainly dependent on their personal expertise (Shleifer and Vishny, 1989). Managerial hubris theory follows these lines (Roll, 1986), as it hinges on the assumption that the managers of acquirers may under or overestimate the synergies of potential acquisitions, as a result, there might be overpayment for the target firms. Consequently, cross-border acquisitions may destroy value for the acquirers.
In view of the above discussions, previous studies on cross-border acquisition that show negative abnormal returns for acquirers around the announcement date. For example, Eun et al. (1996) investigate acquirers from different countries that take over U.S. targets and observe that acquirers gain significant negative abnormal returns of – 1.20% for the event period (-5, +5) from 1979 to 1990. A similar result is found from Aw and Chatterjee (2004), who observe a sample of cross-border acquisitions. In terms of the emerging market, Aybar and Ficici (2009) examine the wealth effect of 433 cross-border acquisitions made by acquirers from different emerging markets over the period of 1991 to 2004 and they report that on average, cross-border acquisitions from emerging markets do not enhance values for acquirers, but destroy value. Besides positive and negative announcement performances of acquirers, several studies show insignificant returns in cross-border acquisitions around the announcement date. For example, Seth et al., (2000) examine 100 cross-border acquisitions of U.S. acquirers during 1981 to 1990, and the result shows that acquirers appear to neither gain nor lose on average.
H1: Cross-border acquisitions create value to acquirers around the announcement date.
2.2. The impact of national culture distance on cross-border acquisition performance The relationship between national cultural distances and acquisition performance becomes more complex and subtle as firms experience “dual cultural adaptation,” which involves national and organizational culture levels during the cross-border acquisition process (Barkema et al., 1996). In particular, as a deeper level of cultural dimension, national cultural distance is often believed to be important in explaining international acquisition performance (Chakrabarti et al., 2009). However, in cross-border acquisitions, the national cultural distance sometimes acts as obstacles that the acquiring and target firms are required to overcome together, which sometimes appears to be a potential success factor in attracting firms to conduct cross-border acquisitions. Thus, the studies on the impact of the national cultural distance on acquirers’ performances present a puzzle as some suggest a positive impact while others point to a negative impact.
reach a similar conclusion by studying 46 cross-border acquisitions of Chinese acquirers between 1985 and 2005.
depending on the level of integration between the acquiring and target firms, in which national cultural distance is a boon at low integration level but is otherwise a bane.
In summary, the national cultural distance increases the difficulty of the acquisition, impedes the post cross-border acquisition process and causes greater costs than benefits. Thus, I expect that the cross-border acquisitions with lower national cultural distances generate greater values for acquirers than others. Thus, I formulate the following hypothesis:
H2: The national cultural distance is negatively associated with the value of acquirers around the announcement date of cross-border acquisitions.
2.3. The impact of shareholder protection on cross-border acquisition performance Building on the work of La Porta et al. (1998), several studies show that the equity market is significantly influenced by different levels of shareholder protection. Thus, the shareholder protection mechanism has been gradually incorporated into cross-border acquisition studies. However, scholars have drawn contradictory conclusions on the relation between the target countries’ shareholder protection and the wealth effect of acquirers in cross-border acquisitions.
in strong protection countries (La Porta et al., 1998), thereby causing acquirers to have to pay a higher premium in order to reduce the resistance of current shareholders.
On contrary, some scholars suggest a negative relationship between target countries’ shareholder protection and acquirers’ wealth effect. In terms of the agency cost theory, John et al. (2010) assume that the agency costs will increase if the target firms are located in weak shareholder protection environments. The higher agency costs result in a value reduction of the targets, as acquirers pay less of a premium to take over the target. Hence, weak shareholder protection in the target country will decrease the valuation of the target firms and premium paid, consequently, acquirers will earn greater values compared to target firms located in strong shareholder protection countries. This finding is supported by La Porta et al. (1998) and Anderson et al. (2009), they argue that target firms have relatively greater bargaining power if they are located in strong shareholder protection environments compared to targets located in weak shareholder protection environments. As a result, acquirers are forced to pay higher premiums, implying a value destroying for acquirers.
Overall, I expect that the concentrated ownership structure in the weak shareholder protection target countries that increase the premium paid, further decreasing the returns to the acquirers. Thus, I propose the following hypothesis: H2: Shareholder protection of target firm is positively associated the value of acquirers around the announcement date of cross-border acquisitions.
3. Data and methodology
3.1. Sample selection and description
completion status, deal values, and method of payment are obtained from Zephyr. The firm level information was collected from DataStream. The country level information was obtained from the World Bank. I follow Chakrabarti et al. (2009) in the application of the following criteria in filtering the sample. I include transactions that are: 1) completed; 2) over $1 million in value; 3) end with acquirers owning 100% of the target shares after the transaction; 4) ones in which the acquirers and targets are from different countries; and 5) ones in which the acquirers are listed.
In addition, I exclude deals with multiple acquirers in order to avoid contamination of the stock returns in the horizon due to multiple transactions. I then exclude deals in which both the acquirer and target are financial services firms due to the operations of financial services firms being distinct from other types of firms. Next, I drop deals from the Bermuda Islands, Cayman Islands and Virgin Islands, to avoid the possibility of acquisitions occurring in these countries for tax reasons. Finally, I exclude the deals if the related deal specific information (e.g., deal status, deal value, and method of payment), firm level information (e.g., total assets, total debt to equity ratio, and return on assets ratio), and country-level information (e.g., national culture dimension scores of acquirer country, revised anti-director right index of target country, and GDP growth rate of target country) are not available. The final sample consists of 415 unique acquisitions with 27 acquiring countries and 43 target countries (Appendix 2).
Table 1
Sample distribution and transaction values by year and acquirer region Number of cross-border acquisitions % of cross-border acquisitions Transaction value of cross-border acquisitions (mil USD) % of transaction value
Panel A: Distribution and transaction values by year
2011 87 20.96% 34,111.00 24.96% 2012 74 17.83% 20,567.48 15.05% 2013 77 18.55% 15,650.99 11.45% 2014 96 23.13% 42,631.96 31.19% 2015 81 19.52% 23,713.97 17.35% Total 415 100.00% 136,675.40 100.00%
Panel B: Distribution and transaction values by acquirer region
Asia 38 9.16% 18,224.07 13.33%
Europe 204 49.16% 58,555.71 42.84%
North America 155 37.35% 56,600.88 41.41%
Oceania 18 4.34% 3,294.74 2.41%
Total 415 100.00% 136,675.40 100.00%
This table shows the distribution and transaction value of 415 cross-border acquisitions during the period of 2011-2015. Panel A shows the distribution and transaction value by year. Panel B shows the distribution and transaction value by the acquiring region.
region, respectively. In terms of the acquiring region distribution, Europe ranks first with 204 (49.16%) acquisitions followed by 155 (37.35%) acquisitions in North America, 38 (9.16%) acquisitions in Asia, and 18 (4.34%) acquisitions in Oceania. In terms of the deal value distribution, Europe ranks first with 58,555.71 million USD (42.84%), followed by North America with 56,600.88 million USD (41.41%), Asia at 18,224.07 million USD (13.33%), and Oceania with 3,294.74 million USD (2.41%).
3.2. Event Study
measure whether the share price would fluctuate with the occurrence of an event on the market, whether it would produce an excess rate of return, and eventually determine whether the abnormal fluctuation is caused by the event. There are two prerequisites for using the event study: (1) The capital market is an efficient market, where the stock price can be used to reflect the changes of the publicly available information in the market, and investors can make a rational judgment on the basis of the market information. Thus, it is more applicable to use the event study method to investigate the wealth effect of cross-border acquisitions when the capital market is strongly efficient. (2) There are no other major events affecting the stock price during the event window. In this study, I strictly screen the samples to guarantee the stock prices of the samples are not impacted by any significant events. Therefore, the event study is able to be used appropriately in this study.
Since this study is focusing on the "announcement effect" for a short horizon around the event period, it is necessary to determine the length of the observation interval, an event window and an estimation window. The publication day of the acquisition’s announcement is defined as the event date (Day 0) in this study.
days (-240, -41) prior to the announcement date as their estimation window while Goergen and Renneboog (2004) estimate the expected returns by using a 9-month estimation window (195 trading days) ending 6 months prior to the announcement date. In this study, 220 trading days (-240, -21) prior to the announcement date are set as the estimation window. I believe that the 220 trading days interval is long enough to capture the volatility of the company’s stock prices and to reflect the expected returns. The timing sequence is presented in Figure 1.
Figure 1
Time line for the event study
[ Estimation Window ] [ Event Window ]
Day-240 Day-21 Day-5 Day0 Day+5
The market model (Brown and Warner, 1985) is applied to measure the effects on stock price that related to the acquisition announcement. It is defined as a statistical model, which links the return of any given security to the return of the market portfolio. Mackinlay (1997) argues that the market model can better detect event effects, because the variance of the abnormal return decreases by eliminating a fraction of the returns that are associated with the variation in the market return. Therefore, the market model is employed to calculate the cumulative abnormal returns (CAR), which serves as the proxy for the acquisition premium. Below, the detailed steps for calculating CARs are shown.
Firstly, the market model is used to estimate the expected return for each firm over 220 trading days, starting at 21 days prior to the acquisition announcement date. As discussed by Mackinlay (1997), the market model assumes that there is a stable linear relationship between the firm’s stock return and market return. Thus, the expected return of stock 𝑖𝑖 is derived from the following formula:
where 𝑅𝑅𝑖𝑖𝑖𝑖 is the expected return from a particular stock 𝑖𝑖 on particular day 𝑡𝑡; 𝑅𝑅𝑚𝑚𝑖𝑖is the expected return from the market 𝑚𝑚 on particular day 𝑡𝑡 ; 𝜀𝜀𝑖𝑖𝑖𝑖is the zero mean disturbance term for stock 𝑖𝑖 at day 𝑡𝑡; 𝛼𝛼𝑖𝑖 and 𝛽𝛽𝑖𝑖 are the estimated intercept and beta of the stock in the market model for stock 𝑖𝑖.
Next, the abnormal return is calculated. This refers to the difference between the actual return and the estimated expected return. Thus, the abnormal return of stock 𝑖𝑖 on day 𝑡𝑡 is derived from the following formula:
𝐴𝐴𝑅𝑅𝑖𝑖𝑖𝑖 = 𝑅𝑅𝑖𝑖𝑖𝑖− (𝛼𝛼𝑖𝑖+ 𝛽𝛽𝑖𝑖𝑅𝑅𝑚𝑚𝑖𝑖) (2)
where 𝐴𝐴𝑅𝑅𝑖𝑖𝑖𝑖is the abnormal return for stock 𝑖𝑖 on particular day 𝑖𝑖.
Finally, the CARs are calculated to measure the stock price reaction to the acquisition’s announcement. It refers to the sum of the abnormal returns over the event window period, the CAR for stock 𝑖𝑖 on particular day 𝑖𝑖 from the event window (𝑡𝑡1, 𝑡𝑡2) is derived from the following formula:
𝐶𝐶𝐴𝐴𝑅𝑅 (𝑡𝑡1, 𝑡𝑡2) = ∑𝑖𝑖𝑖𝑖=𝑖𝑖2 1𝐴𝐴𝑅𝑅𝑖𝑖𝑖𝑖 (3)
where 𝐶𝐶𝐴𝐴𝑅𝑅 (𝑡𝑡1, 𝑡𝑡2) is the cumulative abnormal return for stock 𝑖𝑖 on particular day 𝑖𝑖 from event window (𝑡𝑡1, 𝑡𝑡2)
3.3. Multivariate Analysis
To explore whether national cultural distance and shareholder protection have an impact on acquirers’ wealth effect, multiple regression analysis is the most suitable technique to apply to this study. The regression model is estimated as follows:
𝐶𝐶𝐴𝐴𝑅𝑅 = 𝛽𝛽0+ 𝛽𝛽1(𝐶𝐶𝐶𝐶) + 𝛽𝛽2 (𝑆𝑆𝑆𝑆) + 𝛽𝛽3�𝐿𝐿𝐿𝐿𝐿𝐿(𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆)� + 𝛽𝛽4(𝑇𝑇𝐿𝐿𝑇𝑇𝑆𝑆𝑇𝑇𝑆𝑆𝑇𝑇) + 𝛽𝛽5(𝐿𝐿𝑆𝑆𝐿𝐿𝑆𝑆𝑅𝑅𝐴𝐴𝐿𝐿𝑆𝑆) + 𝛽𝛽6(𝑆𝑆𝑇𝑇𝑇𝑇𝑆𝑆𝑅𝑅𝑇𝑇𝐴𝐴𝑇𝑇𝑆𝑆𝐿𝐿𝑇𝑇𝐴𝐴𝐿𝐿) + 𝛽𝛽7(𝑅𝑅𝐿𝐿𝐴𝐴) + 𝛽𝛽8(𝑆𝑆𝑇𝑇𝐶𝐶𝐼𝐼𝑆𝑆𝑇𝑇𝑅𝑅𝐼𝐼) + 𝛽𝛽9(𝐶𝐶𝑆𝑆) + 𝛽𝛽10(𝐶𝐶𝐴𝐴𝑆𝑆𝐶𝐶) + 𝛽𝛽11(𝐿𝐿𝐶𝐶𝑆𝑆) + 𝛽𝛽12(𝐶𝐶𝑆𝑆𝐿𝐿𝑆𝑆𝐿𝐿𝐿𝐿𝑆𝑆) + 𝛽𝛽13(𝐴𝐴𝑆𝑆𝑆𝑆𝐴𝐴) +
𝛽𝛽14(𝑆𝑆𝐼𝐼𝑅𝑅𝐿𝐿𝑆𝑆𝑆𝑆) + 𝛽𝛽15(𝑇𝑇𝐿𝐿𝑅𝑅𝑇𝑇𝐶𝐶𝐴𝐴𝑅𝑅𝑆𝑆𝑅𝑅𝑆𝑆𝐶𝐶𝐴𝐴) + 𝜀𝜀 (4) where 𝐶𝐶𝐴𝐴𝑅𝑅 is the dependent variables, denoting acquirer’s cumulative abnormal
returns for the (-3, +3) event window and (-5, +5) event window. 𝐶𝐶𝐶𝐶 and 𝑆𝑆𝑆𝑆 are the
and target countries and the strength level of the shareholder protection in the target countries at the time an acquisition 𝑖𝑖 is announced, respectively. The firm level
variables, deal specific variables, country level variables and geographic regions are also incorporated in this study as control variables. For the firm level variables, 𝐿𝐿𝐿𝐿𝐿𝐿(𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆) denotes the firm size of acquirers, measured by the natural logarithm of total assets of the acquirer one year prior to the announcement; 𝑇𝑇𝐿𝐿𝑇𝑇𝑆𝑆𝑇𝑇𝑆𝑆𝑇𝑇 denotes the Tobin’s q of acquirers, measured by the ratio of market capitalization to total assets one year prior to the announcement; 𝐿𝐿𝑆𝑆𝐿𝐿𝑆𝑆𝑅𝑅𝐴𝐴𝐿𝐿𝑆𝑆 denotes the leverage of acquirers, measured by the ratio of total debt to equity one year prior to the announcement; 𝑆𝑆𝑇𝑇𝑇𝑇𝑆𝑆𝑅𝑅𝑇𝑇𝐴𝐴𝑇𝑇𝑆𝑆𝐿𝐿𝐴𝐴𝑇𝑇𝐿𝐿 denotes the internationalization level of acquirers, measured by the ratio of foreign sales to total sales one year prior to the announcement; 𝑅𝑅𝐿𝐿𝐴𝐴 denotes the return on asset (ROA) of acquirers, measured by the ratio of earnings before interest, tax, depreciation and amortization (EBITDA) to total assets one year prior to the announcement. For the deal specific variables, 𝑆𝑆𝑇𝑇𝐶𝐶𝐼𝐼𝑆𝑆𝑇𝑇𝑅𝑅𝐼𝐼 represents the industry relatedness between the acquiring and target firms, it sets to 1 if the industry of the acquirer is the same as the industry of the target firm, and 0 otherwise; 𝑅𝑅𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 denotes the relative size of the deal 𝑖𝑖, measured by the transaction value divided by the market capitalization; 𝐶𝐶𝐴𝐴𝑆𝑆𝐶𝐶 stands for the method of payment used when financing the deal 𝑖𝑖, it sets to 1 if the deal 𝑖𝑖 is paid for entirely by cash, and
0 otherwise. For the country level variables, 𝐿𝐿𝐶𝐶𝑆𝑆 denotes the GDP growth rate of the
the firm, deal, country level and geographic region variables on acquirers’ wealth effect on cross-border acquisitions. The effect of the control variables on acquisitions will be discussed in detail in the following sections.
3.3.1. Independent variables
Cultural distance: The national cultural distance is measured following Kogut and Singh's (1988) index, which is in line with previous studies. A multidimensional measure was constructed that estimates the distance between the acquiring and target countries using Hofstede’s (1980) four culture dimension scores: power distance, individualism, uncertainty avoidance and masculinity (Appendix 3):
𝐶𝐶𝐶𝐶
𝐽𝐽= ∑
(𝐼𝐼𝑖𝑖𝑖𝑖−𝐼𝐼𝑖𝑖𝑖𝑖′)2/𝑉𝑉𝑖𝑖 4 4𝑖𝑖=1 （5）
where 𝐶𝐶𝐶𝐶𝐽𝐽 denotes the cultural distance between the acquiring country 𝑗𝑗and the target country 𝑗𝑗′; 𝑆𝑆𝑖𝑖𝑖𝑖 denotes the culture dimension score 𝑖𝑖 for the acquiring country 𝑗𝑗; 𝑆𝑆𝑖𝑖𝑖𝑖′ denotes the culture dimension score 𝑖𝑖 for the corresponding target country 𝑗𝑗′, 𝐿𝐿𝑖𝑖 denotes the variance of the culture dimension score 𝑖𝑖.
Despite the limitation of Kogut and Singh index (Shenkar, 2001), it is still the most valid and reliable index to use in measuring national cultural distance, as the scores on Hofstede’s dimensions covers more than 70 countries and have been applied in many studies (see e.g., Chakrabarti, et al., 2009; Slangen, 2006; Morosini et al., 1998; Kogut and Singh, 1988)
The revised index extends to 72 countries, and ranges from 0 (weak investor protection) to 6 (strong investor protection).
3.3.2. Control Variables Firm level variables
Firm size (LOG(SIZE)):A number of scholars show that the size of acquirers influences acquisition performance (see, e.g., Feito-Ruiz and Menendez-Requejo, 2011; Moeller et al., 2004; Jensen, 1986). Feito-Ruiz and Menendez-Requejo (2011) find that cross-border acqusition by small acquirers genernates more values than larger acquirers. As explained by Moeller et al.(2004), large firms have sufficient fund and resources, thereby managers tend to overpay in acquisition deals. A similar result is found in the study of Jensen(1986), who argues that large acquirers are likely to be confronted with agency problems which can lead to empire building and hubris in conducting the acquisition. Therefore, the acquirers’ returns are expected to reduce with the increase in firm size.
Tobin’s q (TOBINSQ): Empirical studies show that the shareholders’ gains are also impacted by the acquirers’ Tobin’s q. For example, Doukas (1995) examines the relation between acquirers’ wealth effect and the Tobin’s q ratio of U.S. acquirers involving 463 cross-border acquisitions between 1975-1989. The result shows that the acquirers with high q gain substantially higher value than the acquirers with low q acquirers. Lang et al. (1989) explain that the financial markets pay back more to well-managed firms (high q firms) than poorly well-managed firms (low q firms). Moreover, the result supports the view that well-managed firms make better use of target resources to create wealth for the acquirers during takeovers.
they observe that announcement returns are positively related with the acquirers’ financial leverage. Jensen and Meckling (1976) argue that high leverage reduces future free cash flows, consequently decreasing managerial discretion, thereby reducing agencey costs by limiting manager’s ability to invest in unprofitable acquisitions.
On the other hand, Modigliani and Miller (1963) suggests that higher leverage leads to a high marginal costs which exceed the benefits of acquisitions, thereby preventing managers from invest in postive NPV projects. Therefore, a negative impact can be assumed to exist between the acquirers’ leverge positon and the acquisition performance.
Internationalization (INTERNATIONAL): The level of international experience of acquire is a salient factor in cross-border acquisitions. Harzing (2002) argues that international experience is a sustainable competitive advantage, acquirers will generate positive abnormal returns from their acquisitions if they have prior international experience. It can be explained as acquirers with overseas experience can identify the foreign investment opportunity easily and quickly. Meanwhile, the integration costs, information asymmetry, and liability of foreignness are reduced with increased international experience (Martin et al., 1998).
However, the “overconfident” theory suggests that acquirers who have abundant international experience may become over-optimistic when conducting cross-border acquisitions, as a higher premium may be paid for targets which leads to a value destruction for acquirers.
they are more efficient and have superior management skills related to processing the target assets.
Deal specific variables
Industry: Extant literatures also propose that expansion into related and unrelated industries influence the firms’ values, however, the effect is ambiguous. Recent evidence proposes that diversification plays a positive role in cross-border acquisitions. Resources can be allocated more efficiently and more risks can be reduced in diversified firms than in non-diversified firms (Feito-Ruiz and Menendez-Requejo, 2011). Furthermore, Stulz (1990) states that acquirers will gain a co-insurance effect when expanding into an unrelated industry, as their joint cash flow becomes more stable and the operating risks can be spread into different segments. With this view, diversified firms will gain more value with cross-border expansion.
On the contrary, diversification may lead to a value discount. As Denis et al. (2002) argues that diversification into unrelated industries may result in continuously increasing difficulties in integration between the different business segments. In this respect, the number of failing business segments will rise, thereby leading to an increase of agency costs. These costs of diversification may exceed the alleged synergies and result in wealth destruction for the acquirers.
Consequently, the financial pressure and integration costs will be much more than for small targets. Additionally, large deals usually take a longer time than predicted (Mulherin and Boone, 2000).
Method of Payment (CASH): The method of payment plays a key role in acquires’ wealth effect on acquisitions, however, the results are not consistent. Extant literatures indicate that full cash payment gains higher returns than any other payment method in cross-border acquisitions (Myers and Majluf, 1984; Goergen and Renneboog, 2004). The signal theory suggests that the choice of payment method influences the future cash flow and investment opportunities when performing acquisitions (Myers and Majluf, 1984). Fully financing the acquisition with cash can be viewed as a good sign as it indicates that the target has great potential value and also preempts other firms from bidding. Nevertheless, the market views the cash offer as a signal that the acquirers’ share prices will increase in the future (Myers and Majluf, 1984). In addition, the asymmetric information theory assumes that external investors do not have access to the firm’s information on stock value. Thus, the managers of acquirers prefer to use stock to finance the acquisition when they know their stock price is overvalued. Consequently, a stock offer conveys a signal to outside investors that the acquirers’ stock price is overvalued, as well as the sense that acquirers are uncertain about the target’s value. In contrast, acquirers prefer to pay for the acquisition with cash when they know their stock price is undervalued––hence, the cash offer may be a signal to outside investors that the acquirer’s stock price is undervalued (Goergen and Renneboog, 2004).
Country level variables
GDP growth rate of the target country (GDP): Hyun and Kim (2010) investigate a set of bilateral M&As for 101 countries during the period of 1989 to 2005, they find that the target country’s GDP growth rate negatively impacted acquirers’ abnormal returns. This is consist with Rossi and Volpin (2004), using a sample of cross-border acquisition announcements in 49 counties over the period of 1990 to 2002.
Degree of economic development of target country (DEVELOP): Waheed and Mathur (1995) illustrate that the target country’s economic development level significantly impacts acquirers’ abnormal returns. They find that expansion into developing countries generates higher value to acquirers. This finding is in line with Kiymaz (2004), who examines the impact of cross-border acquisitions on US acquirers of financial institutions. The result shows that acquirers earn greater values when the target is located in developing countries.
However, Kwok and Reeb (2000) suggest that when a firm located in a developed economy expands into an emerging market, the overall risks of the firm increases. This is because that there are more potential risks in emerging markets. Thus, it is assumed that when a firm located in a developed country expands into an emerging market, a negative market reaction will be generated. Conversely, when a firm located in an emerging market expands into a developed country, a positive market reaction will be observed.
Geographic region variables
level equity markets, the managerial power and motivation for value appropriation at the expense of minority shareholders will be increased, which will destroy acquirers’ value (Aybar and Ficici, 2009). Aybar and Ficici (2009) examine the wealth effect of cross-border acquisitions made by acquirers from emerging markets (including Asia), and they report that cross-border acquisitions do not enhance value for acquirers from emerging markets. On the opposite side, Boateng et al. (2008) report a positive abnormal return for Chinese acquiring firms. In terms of the European region, Goergen and Renneboog (2004) study 228 cross-border acquisitions of European acquirers from 1993 to 2000, and find that European acquirers react positively with a significant cumulative abnormal return of 0.7%. However, Aw and Chatterjee (2004) present significant and negative abnormal returns for UK acquirers in cross-border acquisitions. In terms of the North American region, Doukas and Travlos (1988) report that cross-border acquisitions are value enhancing by examining a sample of 301 US acquirers. Contradictory result is found from Denis et al. (2002), who report a value destruction effect on cross-border acquisitions for US acquirers.
4. Empirical Results
4.1. Descriptive Analysis
Table 2
Descriptive statistic
Mean Median Std. Dev.
Panel A: Dependent variables
CAR (-3, +3) 0.014 0.007 0.065
CAR (-5, +5) 0.013 0.006 0.075
Panel B: Independent variables
CD 1.008 0.448 1.129
SP 3.602 3.500 0.896
Panel C: Firm level variables
LOG(SIZE) 9.218 9.184 0.852
LEVERAGE 0.657 0.383 1.073
TOBINSQ 1.577 1.169 1.380
INTERNATIONAL 0.539 0.569 0.330
ROA 0.066 0.069 0.106
Panel D: Deal specific variables
INDUSTRY 0.508 1.000 0.501
RSIZE 0.116 0.043 0.241
CASH 0.663 1.000 0.473
Panel E: Country level variables
GDP 0.021 0.019 0.018
DEVELOP 0.896 1.000 0.305
Panel F: Geographic region variables
ASIA 0.092 0.000 0.289
EUROPE 0.492 0.000 0.501
NORTHAMERICA 0.374 0.000 0.484
OCEANIA 0.043 0.000 0.204
This table presents the means, medians, and standard deviations for each variable of 415 cross-border acquisitions during the period of 2011-2015. Panel A presents the dependent variables. Panel B presents the independent variables. The control variables at firm, deal, country, and geographic region levels are presented in Panel C, D, E, and F, respectively. All variables are defined in Appendix 1.
The correlation matrix is examined to identify any multicollinearity between the independent variables and control variables in three models. As Table 3 shows, most of the correlations are very weak, suggesting no serious multicollinearity problems.
4.2. Wealth effect for acquiring firms
Table 3 Correlation Matrix 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 1 CD 1 2 SP 0 1 3 SIZE -0.05 -0.06 1 4 TOBINSQ 0.00 -0.03 -0.29*** 1 5 LEVERAGE 0.01 0.05 0.27*** -0.19*** 1 6 INTERNATIONAL 0.01 -0.29*** 0.12** -0.02 -0.12** 1 7 ROA -0.05 -0.04 0.12** 0.20*** -0.06 0.12** 1 8 INDUSTRY 0.01 -0.01 -0.08* -0.01 -0.04 0.07 0.06 1 9 RSIZE 0.05 -0.03 -0.17*** -0.14*** 0.05 -0.14*** -0.14*** 0.02 1 10CASH -0.09* -0.04 0.15*** 0.01 -0.08* 0.12** 0.14*** 0.02 -0.19*** 1 11 GDP 0.16*** 0.00 0.03 0.02 -0.01 0.04 0.09* 0.09* 0.01 0.16*** 1 12DEVELOP -0.48*** 0.01 -0.01 -0.03 -0.09* -0.05 -0.07 -0.07 0.10** -0.01 -0.46*** 1 13 ASIA 0.34*** 0.04 0.05 -0.08 0.05 -0.01 -0.02 -0.04 0.08 0.00 0.14*** -0.11** 1 14 EUROPE 0.03 -0.28*** 0.07 0.00 0.03 0.30*** 0.01 -0.03 -0.08 -0.03 -0.09* 0.02 -0.31*** 1 15 NORTH AMERICA -0.22*** 0.25*** -0.06 0.03 -0.05 -0.29*** -0.01 0.06 -0.02 0.06 -0.02 0.07 -0.25*** -0.75*** 1 This table shows the correlations for the independent variables and control variables. The dependent variables of CAR (-3, +3) and CAR (-5, +5) are not included in this table because of the limited space. All variables are defined in Appendix 1.
Table 4
Cumulative abnormal returns (CARs) for acquirers
N Mean Std. Deviation t-value
CAR(-3,+3) 415 0.014*** 0.065 4.490
CAR(-5,+5) 415 0.013*** 0.075 3.500
This table presents cumulative abnormal returns of acquirers around the announcement date for 415 cross-border acquisitions during the period of 2011-2015 in the (-3, +3) and (-5, +5) event windows, respectively. One-sample t-test is applied to test the statistical significance of CAR (-3, +3) and CAR (-5, +5).
* Statistically significant at the 10% level. ** Statistically significant at the 5% level. *** Statistically significant at the 1% level.
the cross-border acquisitions, on average, do create value to acquirers. Thus, hypothesis 1 is supported. This result is also in line with previous studies (Kiymaz and Mukherjee, 2001; Block, 2005; Bhagat et al., 2011; Boateng et al., 2008), as confirm that acquirers do realize synergy gains, generating complementary capabilities and intangible assets from cross-border acquisitions, thereby further enhancing their values within globally maximizing context.
Table 5 presents the CARs divided into different sub-groups based on the calendar year, acquirers’ size, industry relatedness, deal relative size, method of payment, target countries’ degree of economic development and acquirers’ geographic region location.
Panel A of Table 5 presents acquirers’ CARs across the (-3, +3) and (-5, +5) event windows by the calendar year. The results show that acquirers’ CARs are positively significant in the (-3, +3) event window in 2011, 2014 and 2015 at the 10%, 1%, and 5% level, respectively. Particularly, acquirers yield the highest CAR of 1.8% in 2014 and 2015. In terms of the (-5, +5) event window, acquirers generate positive CARs in 2014 and 2015 with 1.5% and 1.7%, respectively. Although the volume of announcements on cross-border acquisitions has decreased in 2015, acquirers still received great returns.
Table 5
Cumulative abnormal returns(CARs) for acquirers by sub-groups
CAR (-3, +3) CAR (-5, +5)
N Mean Std.
Deviation t-value Mean
Std.
Deviation t-value
Panel A: By calendar year
2011 87 0.012* 0.064 1.772 0.014 0.079 1.633
2012 74 0.014 0.076 1.554 0.008 0.076 0.949
2013 77 0.010 0.059 1.512 0.009 0.066 1.135
2014 96 0.018*** 0.064 2.693 0.015* 0.077 1.880
2015 81 0.018** 0.063 2.482 0.017** 0.075 2.100
Panel B: By acquirers' size
Small acquirer size 213 0.024*** 0.079 4.381 0.018*** 0.075 3.530 Large acquirer size 202 0.005 0.044 1.452 0.007 0.075 1.391
Panel C: By industry relatedness
Unrelated Industry 377 0.015*** 0.063 4.485 0.013*** 0.073 3.564 Related Industry 38 0.013 0.084 0.922 0.007 0.093 0.493
Panel D: By deal relative size
Small deal size 316 0.006** 0.048 2.337 0.004 0.062 1.240 Large deal size 99 0.040*** 0.098 4.073 0.040*** 0.101 3.924
Panel E: By method of payment
Cash payment 275 0.007* 0.062 1.811 0.005 0.076 1.133
Other payment 140 0.029*** 0.069 5.053 0.028*** 0.070 4.712
Panel F: By target country’s degree of economic development
Developed market 369 0.018*** 0.066 5.186 0.011*** 0.076 2.854 Developing market 46 -0.014* 0.051 -1.861 0.026*** 0.056 3.020
Panel G: By acquirer region location
Asia 38 0.013 0.084 0.922 0.007 0.093 0.493
Europe 204 0.012*** 0.065 2.744 0.009 0.071 1.740
North America 155 0.008* 0.054 1.824 0.008 0.072 1.407
Oceania 18 0.010 0.041 0.996 -0.002 0.066 -0.094
This table presents the cumulative abnormal returns of acquirers by sub-groups around the announcement for 415 cross-border acquisitions during the period of 2011-2015 in the (-3, +3) and (-5, +5) event windows, respectively. One-sample t-test is applied to test the statistical significance of CAR (-3, +3) and CAR (-5, +5). * Statistically significant at the 10% level.
(-3, +3) and (-5, +5) event windows, respectively. These findings are consistent with Feito-Ruiz and Menendez-Requejo (2011), Moeller et al. (2004) and Jensen, 1986).
Panel C of Table 5 reports acquirers’ CARs classified by the industry relatedness. There are 377 deals in which the acquirers and target firms operate in different industries and 38 deals in which the acquirers expand into the same industry with the target firms. This implies that firms tend to diversify themselves into unrelated industry in international acquisitions. The results illustrate that the CARs are positively significant when acquirers expand into unrelated target industries in the (-3, +3) and (-5, +5) event windows with 1.5% and 1.3%, respectively. Feito-Ruiz and Menendez-Requejo (2011) and Stulz (1990) also report the similar results. They note that diversified firms gain a co-insurance effect with more efficient resource allocation and risk reductions.
Table 5 Panel D reports CAR (-3, +3) and CAR (-5, +5) with respect to the deal’s relative size. The sample is separated into small and large deal size by the mean value (0.116) of the relative size for all samples. The CARs for small and large deal sizes are positively significant in the (-3, +3) event window. The evidence shows that the large deal size yield more abnormal returns than small deal size in both event windows. For example, the CAR for large deal size is 4% compared to the small deal size with 0.6% CARs in the (-3, +3) event window. This finding is contradictory with previous studies (Martynova and Renneboog, 2011; Alexandridis et al., 2010; Gorton et al., 2009)
Panel F of Table 5 presents the acquirers’ CAR (-3, +3) and CAR (-5, +5) under the classifications of developing market and developed market. The result shows that 369 target firms are located in developed countries and 46 target firms are located in developing countries. It is obvious that firms are more attracted to target firms located in developed countries. The result shows that CARs are statistically significant within the two event windows. However, the results are contradictory in the (-3, +3) and (-5, +5) event windows. For example, the CAR for target firms located in developing countries yields higher wealth gains than target firms located in developed countries in the (-5, +5) event window. This finding is consistent with Waheed and Mathur (1995) and Kiymaz (2004). Yet the result present an opposite view in the (-3, +3) event window, as Kwok and Reeb (2000) argue that the potential risks increase when firms expand into developing markets, thus a lower return can be expected.
Panel G of Table 5 reports the CARs with respect to the acquirers’ geographic region location in the (-3, +3) and (-5, +5) event windows. The sample is divided into 4 different regions of Asia, Europe, North America, and Oceania. The results indicate that CARs for Europe and North America are positively significant at 1% level and 10% level in the (-3, +3) event window while showing that Europe obtains higher wealth gains with an average return of 1.2% than North America with an average return of 0.8%. However, there are no significant results found for the CARs of Asia and Oceania.
4.3. Cross-sectional results for acquirers
Table 6
Cross-sectional results for acquirers
CAR(-3,+3) CAR(-5,+5)
(1) (2) (3) (1) (2) (3)
Intercept 0.108* 0.068 0.063 0.120* 0.093 0.083
(0.059) (0.057) (0.059) (0.063) (0.062) (0.064)
Panel A: Independent variables
CD 0.002 0.002 0.004 0.004
(0.004) (0.003) (0.004) (0.004)
SP 0.010** 0.010** 0.008* 0.008*
(0.004) (0.004) (0.004) (0.004)
Panel B: Firm level variables
Log(SIZE) -0.013** -0.012** -0.012** -0.012** -0.012* -0.012* (0.006) (0.006) (0.006) (0.006) (0.006) (0.006) TOBINSQ -0.001 0.000 0.000 -0.003 -0.003 -0.003 (0.003) (0.003) (0.003) (0.004) (0.004) (0.004) LEVERAGE 0.004 0.003 0.003 0.005 0.004 0.005 (0.004) (0.004) (0.004) (0.005) 0.005 0.005 INTERNATIONAL 0.011 0.016 0.016 0.019 0.024* 0.024* (0.013) (0.013) (0.013) (0.014) (0.014) (0.014) ROA -0.009 -0.010 -0.008 0.004 0.002 0.004 (0.054) (0.053) (0.054) (0.061) (0.060) (0.060)
Panel C: Deal specific variables
INDUSTRY 0.002 0.002 0.002 0.003 0.003 0.003 (0.006) (0.006) (0.006) (0.007) (0.007) (0.007) RSIZE 0.018 0.022 0.021 0.015 0.020 0.018 (0.018) (0.017) (0.018) (0.019) (0.018) (0.018) CASH -0.006 -0.006 -0.006 -0.008 -0.008 -0.008 (0.008) (0.008) (0.007) (0.008) (0.009) (0.008)
Panel D: Country level variables
GDP 0.074 0.061 0.069 -0.056 -0.077 -0.061
(0.302) (0.305) (0.307) (0.337) (0.342) (0.341) DEVELOP 0.038** 0.034*** 0.037** 0.036** 0.028* 0.035**
(0.015) (0.013) (0.015) (0.017) (0.016) (0.017)
Panel E: Geographic region variables
ASIA -0.027 -0.024 -0.027 -0.041** -0.035* -0.041** (0.018) (0.017) (0.018) 0.020 0.019 0.020 EUROPE -0.026** -0.021* -0.022** -0.038*** -0.033** -0.035** (0.013) (0.013) (0.013) (0.014) (0.014) (0.014) NORTHAMERICA -0.023* -0.023* -0.023** -0.027* -0.026* -0.027* (0.013) (0.013) (0.013) (0.014) (0.014) (0.014) Adjusted R2 0.033 0.049 0.047 0.023 0.029 0.030 F-statistic 1.794** 2.174*** 2.073*** 1.553* 1.696** 1.660**
Year fixed effects Yes Yes Yes Yes Yes Yes
Observations 415 415 415 415 415 415
This table shows the cross-sectional regression results of 415 cross-border acquisitions over the period of 2011-2015. All variables are defined in Appendix 1. All variables use the Huber-White standard errors in order to control the heteroscedasticity problem. Values below each coefficient are standard errors in brackets.
Panel A of table 6 displays the impact of the independent variables CD and SP on the wealth effect for acquirers. Although the coefficient of CD indicates a positive sign across different models and event windows, the results are not statistically significant. Thus, hypothesis 2 is not supported. There are many plausible reasons for the insignificant result. Firstly, national culture distance is directly related to the success of the cross-border acquisitions not the shareholders’ wealth effect, which has been confirmed by many scholars and practitioners (see, e.g., Cording et al., 2008; Ellis et al., 2009). The second explanation would be that the positive and negative effects on the national cultural distance are offset in a short-term wealth effect measurement (Gomez-Mejia and Palich, 1997). The SP is positively significant across different models and event windows. For example, SP has the coefficient of 0.010 in model 2 in (-3, +3) event window and is positively related to the acquirers’ wealth effect. This indicates that acquirers pay less of a premium to the target firms if these targets are located in countries with higher shareholder protection, hence acquirers receive more values with the increase of shareholder protection level in target countries. Thus, hypothesis 3 is supported. This finding can be explained by the ownership structure statements, in which concentrated ownership structure in target country increases the premium paid (La Porta et al., 1998; Bris and Cabolis, 2008), further decreasing the returns to acquirers.
(1998), who point out that the integration costs, information asymmetry and liability of foreignness will be reduced with the increase of international experience– hence, acquirers’ are more likely to incur low premiums. However, the remaining deal level variables, TOBINSQ, LEVERAGE, and ROA, do not have any significant impact on the wealth effect in this study.
The examination of the deal specific variables on acquirers’ value creation is reported in Panel C of Table 6. However, there is no statistically support for the variables of INDUSTRY, RSIZE, and CASH.
Panel D of Table 6 shows the investigation of the country level variables on acquirers’ wealth effect. DEVELOP is the only statistically significant variables in this set, as the coefficient in all models and event windows are positive. For example, the coefficient in model 1 and the (-3, +3) event window is 3.8% at the 5% significant level, suggesting that acquirers do earn positive and significant abnormal returns when the targets are located in developed countries. This conclusion is contradictory with Waheed and Mathur (1995) and Kiymaz (2004). However, the remaining country level variable GDP does not have any significant impact on acquirers’ wealth effect in this study.
The impact of acquirers’ geographic region on acquirers’ wealth effect is presented in Panel E of Table 6. The result indicates that EUROPE and NORTHEAMERICA are negatively statistically significant within both event windows, which indicate that the acquisitions in Europe and North America point to value destruction. Similar finding is reported in previous studies (Aw and Chatterjee, 2004; Denis et al., 2002).
Table 7
Cross-sectional results for acquirers by cultural distance.
Small cultural distance Large cultural distance CAR(-3,+3) CAR(-5,+5) CAR(-3,+3) CAR(-5,+5)
Intercept 0.141** 0.142* -0.018 -0.019
(0.069) (0.082) (0.087) (0.090)
Panel A: Independent variables
SP 0.004 -0.003 0.019*** 0.022***
(0.006) (0.006) (0.006) (0.006)
Panel B:Firm level variables
LOG(SIZE) -0.011* -0.010 -0.013 -0.014 0.006 0.007 0.009 0.010 TOBINSQ 0.000 -0.001 0.002 -0.001 (0.006) (0.007) (0.003) (0.004) LEVERAGE -0.001 0.001 0.015 0.015 (0.003) (0.004) (0.010) (0.011) INTERNATIONAL 0.029 0.031 0.001 0.012 (0.018) (0.020) (0.017) (0.021) ROA -0.039 -0.071 0.062 0.115* (0.128) (0.122) (0.048) (0.061)
Panel C:Deal specific variables
INDUSTRY 0.008 0.007 -0.007 -0.008 (0.009) (0.010) (0.010) (0.012) RSIZE 0.042 0.041 0.007 0.001 (0.030) (0.029) (0.014) (0.016) CASH 0.001 0.000 -0.015 -0.021 (0.010) (0.011) (0.011) (0.013)
Panel D:Country level variables
GDP -0.448 -0.841* 0.861** 0.769*
(0.393) (0.460) (0.398) (0.407)
DEVELOP -0.018 0.018 0.071*** 0.069***
(0.015) (0.022) (0.019) (0.022)
Panel E:Georaphic region variables
ASIA -0.060* -0.044 -0.010 0.001 (0.031) (0.039) (0.028) (0.027) EUROPE -0.033* -0.055*** -0.005 0.004 (0.018) (0.019) (0.024) (0.021) NORTHAMERICA -0.021 -0.035** -0.014 0.010 (0.016) (0.018) (0.025) (0.023) Adjusted R2 0.034 0.045 0.164 0.116 F-statistic 1.506* 1.668** 2.698*** 2.132***
Year fixed effects Yes Yes Yes Yes
Observations 258 258 157 157
This table shows the cross-sectional regression results of 415 cross-border acquisitions over the period of 2011-2015 by subsets defined by the national cultural distance between the acquiring firm and target firm. For Kogut and Singh’s (1988) cultural distance index lower than the mean value (1.008) for all acquisitions are classified as small cultural distance, otherwise as large cultural distance. All variables are defined in Appendix 1. All variables use the Huber-White standard errors in order to control the heteroscedasticity problem. Values below each coefficient are standard errors in brackets.
Table 8
Cross-sectional results for acquirers by target country shareholder protection (SP)
Weak shareholder protection Strong shareholder protection CAR(-3,+3) CAR(-5,+5) CAR(-3,+3) CAR(-5,+5)
Intercept -0.012 0.060 0.248*** 0.165
(0.064) (0.070) (0.094) (0.106)
Panel A: Independent variables
CD -0.002 -0.003 0.003 0.009
(0.005) (0.005) (0.006) (0.007)
Panel B: Firm level variables
LOG(SIZE) -0.005 -0.011* -0.021** -0.010 (0.005) (0.006) (0.011) (0.011) TOBINSQ 0.000 -0.005* 0.000 0.001 (0.003) (0.003) (0.005) (0.006) LEVERAGE 0.007 0.010* -0.002 -0.004 (0.005) (0.006) (0.009) (0.009) INTERNATIONAL 0.015 0.028 -0.002 -0.013 (0.015) (0.017) (0.019) (0.021) ROA 0.075 0.116* -0.112 -0.155 (0.059) (0.067) (0.106) (0.115)
Panel C: Deal specific variables
INDUSTRY 0.003 0.006 -0.002 -0.002 (0.009) (0.010) (0.011) (0.013) RSIZE 0.036 0.023 0.012 0.014 0.031 0.030 0.016 0.018 CASH 0.002 0.002 -0.010 -0.014 (0.009) (0.010) (0.010) (0.012)
Panel D: Country level variables
GDP 0.617** 0.345 -0.343 -0.309
(0.294) (0.307) (0.383) (0.467)
DEVELOP 0.056*** 0.050*** 0.024 0.020
(0.017) (0.019) (0.022) (0.028)
Panel E: Geographic region variables
ASIA -0.036* -0.036* -0.026 -0.052 (0.019) (0.021) (0.028) (0.036) EUROPE -0.026* -0.033** -0.031 -0.049* (0.015) (0.013) (0.019) (0.026) NORTHAMERICA -0.013*** -0.005 -0.049*** -0.064*** (0.017) (0.016) (0.018) (0.025) Adjusted R2 0.039 0.079 0.158 0.109 F-statistic 1.586* 2.225*** 2.630*** 2.056**
Year fixed effects Yes Yes Yes Yes
Observations 258 258 157 157
This table shows the cross-sectional regression results of 415 cross-border acquisitions over the period of 2011-2015 by subsets defined by the level of shareholder protection in the target country. Target countries with revised anti-director rights index lower than the mean value (3.602) for all acquisitons are classified as weak shareholder protection counties, otherwise as strong shareholder porteciotn countreis. All variables are defined in Appendix 1. All variables use the Huber-White standard errors in order to control the heteroscedasticity problem. Values below each coefficient are standard errors in brackets.
the acquiring and target countries are significantly disparity, thereby acquirers with lower shareholder protection yield great gains from targets with higher shareholder protection environments, whereas acquirers are located in higher shareholder protection countries experience value destruction for taking over targets with lower shareholder protection environments.
Table 8 presents the results for the sample classified by the level of shareholder protection. However, the variable of CD are not statistically significant, further confirming that national cultural distance plays a minor role in measuring acquiring firms’ performance.
5. Conclusion
This study aims to examine the wealth effect of cross-border acquisitions on acquiring firms and the impact of the cultural distance and shareholder protection on the market reactions to acquirers, respectively. The sample consists of 415 cross-border acquisitions originating from a variety of countries across Asia, Europe, North American and Oceania over the period of 2011 - 2015.
The empirical results show that the financial markets react positively to the cross-border acquisition announcements. The cumulative abnormal returns surrounding the announcement date are positively statistically significant in the (-3, +3) and (-5, +5) event windows, suggesting that cross-border acquisition announcements are recognized as value creations for acquirers, which is in line with my expectation. After further analysis, the evidence shows that small acquirers yield significant positive abnormal returns compared to large acquirers. The analysis of the deal specific factor, indicating that acquirers experience greater wealth gains when they are more diversified, the target is relatively large and with payment for the acquisition is made fully in cash. Furthermore, the analysis of the acquirers’ geographic region shows that acquirers only experience a significant wealth effect with the cross-border acquisitions when they are located in Europe and North America.
that acquirers with strong shareholder protection environments yield greater returns from the targets with weak shareholder protection environments than targets with strong shareholder protection environments. This finding is consistent with my hypothesis and the ownership structure statements suggested by previous studies (La Porta et al., 1998; Bris and Cabolis, 2008). The result for the impact of national cultural distance on the cumulative abnormal returns is insignificant. The plausible reasons for this result would be that the national culture distance is not directly related to the shareholders’ wealth gains (Cording et al., 2008; Ellis et al., 2009) or the positive and negative influences of the national culture are offset in a short-term wealth effect measurement (Gomez-Mejia and Palich, 1997). Hence, this reveals that culture may not be as important as a performance indicator as prevalent theory assumes. Furthermore, cross-sectional analysis indicates that the acquirers’ internationalization level and the target in developed market generate positive abnormal returns for acquirers around the acquisition announcement. On the contrary, the acquirers’ size and geographic region locations of Asia, Europe, and North America are negatively associated with acquirers’ wealth around the acquisition announcement date.
This study has strong implication to managers who intend to expand internationally through acquisitions. The findings recommend that managers should target firms with significant differences in shareholder protection environments, as well as firms are located in developed countries under strong shareholder protection environments. Furthermore, highly internationalization firms should conduct more aggressive strategies and establish their own firm-specific routines in the international acquisitions, as they can identify the foreign investment opportunity easily and quickly. Although the findings show insignificant impact of national cultural distance, managers and investors who intend to gain profits by investing abroad with significant cultural span still need to deliberate thoroughly.
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