MSc International Financial Management
Faculty of Economics and Business University of Groningen MSc Economics & Business Department of Business Studies
Uppsala University
Chinese Acquirers’ Performance
in M&A Activities
Chunyang Zhuang Student number: 2447541 Supervisor: Prof. Dr. C. L. M. Hermes
9-1-2015
Abstract
The primary objective of this study is to analyze Chinese acquirers’ performance and the influence of cultural and institutional environments on their cumulative abnormal returns of cross-border Mergers and Acquisitions (M&As) around the announcement date. I examine 593 M&A deals (382 domestic and 211 cross-border) over the 2000 to 2013 period. The finding shows that Chinese cross-border acquirers perform better than domestic ones. In cross-border M&A, acquisitions in developing countries create more gains than those in developed countries. After conducting the cross-sectional analysis of cultural and institutional factors, I find that the greater cultural distances increase acquirers’ performance, and that firms gain (lose) more to acquire targets located in weaker (stronger) legal origin countries. But the influence of corporate governance difference cannot be verified.
Keywords: mergers and acquisitions; domestic and cross-border acquisitions; developed and developing countries acquisitions; culture; institution; event study.
Table of content
1. Introduction... 1
2. M&A activities in China ... 3
3. Literature review and hypothesis ... 4
3.1 Motives for M&A activities ... 4
3.2 Acquirers’ Performance in M&A activities ... 6
3.3 domestic and cross-border M&A ... 7
3.4 M&A in developed and developing economics... 9
3.4.1 cultural distance ... 10
3.4.2 Institutional system ... 12
4. Methodology ... 14
4.1 Data and Sample ... 14
4.2 Research Design: Market performance ... 16
5. Empirical Results and Discussion ... 17
5.1 Performance around the announcement date ... 17
5.2 Cross-sectional determinants of acquirer returns in cross-border M&A ... 20
5.2.1 Cultural distances ... 20
5.2.2 Institutional systems ... 20
5.2.3 Control variables ... 22
5.3 Descriptive analysis ... 23
5.4 Cross-sectional analysis of CAR ... 26
6. Conclusion ... 31
Appendix ... 33
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1. Introduction
Mergers and acquisitions (M&As), as one method of foreign direct investments, have become prevalent globally during the last few decades. They not only restructure a firm’s operational and financial behavior but also influence the attractiveness of the capital market. Though firms form developed countries still have dominant share of global M&A, firms from emerging countries have entered this field and increased significantly in the last two decades. It is reported that outbound cross-border acquisitions by acquirers from developing countries have arrived at $182 billion in 2008 from $37 billion in 2004 (United Nations Conference on Trade and Development—UNCTAD, 2009). China, as one of the important emerging countries in the world, witnesses and is involved this trend with the openness of the market after joining World Trade Organization (WTO).
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ones. In my study, the sample covers 593 Chinese M&A deals with 382 domestic acquisitions and 211 cross-border acquisitions (167 in developed countries and 44 in developing countries) with the time span from 2000 to 2013. I employ event study method to estimate cumulative abnormal returns around the announcement date. To exploit the influential factors behind, I also take the cross-sectional analysis to estimate cultural and institutional factors.
The finding of this study is that Chinese acquirers perform better in cross-border M&A than domestic M&A. Reasons can be market imperfections or target location (Goergen and Renneboog, 2004). In cross-border M&A, Chinese acquirers perform better if their targets are from developing countries than from developed countries, which is inconsistent with previous findings (e.g., Colombo and Turati, 2014; Focarelli and Pozzolo, 2005; Liu and Qiu, 2013). The cause of this inconsistency is that the extant studies focus on acquirers from developed countries while this study concentrates on Chinese acquirers. Thereafter, I study cultural and institutional factors. Through the cross-sectional analysis on cultural and institutional levels, the results show that greater cultural distances lead to better performance because of integration benefits (Slangen, 2006), source sharing (Morosini et al., 1998) and so on. Moreover, I also find that acquisitions to targets with weaker legal origin increase acquirers’ performance, but this result is only significant in the acquisitions in the developing markets. Besides, corporate governance difference is insignificant and shows different signs, meaning that Chinese acquirers do not have similar reaction to whether adopt targets’ investor protection rights. Thus, their performance may increase or decline.
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Since institutions are developing over time, the revised index makes the results generated later more convincing. These two novel indexes both make the results more reliable.
The remainder of the paper is organized as follows. In the next section, Chinese M&A activities is introduced, briefing the development of Chinese M&A markets. The third section presents literature reviews and hypotheses, followed by methodology in the fourth section. In the fifth section, empirical results of event study and cross-sectional regression are displayed with discussion. The last section is the conclusion.
2. M&A activities in China
Figure 1: Domestic M&A in China
Source: ZEPHYR database, last accessed on 10/11/2014
Figure 2: Cross-border M&A in China
Source: ZEPHYR database, last accessed on 10/11/2014
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The number of M&A deals in China is booming in the recent decades (Figure 1, 2). Though compared with western countries, China still lags behind in M&A activities. The data in Figure 1, 2 is collected from ZEPHYR1 in the period of 2000 to 2013. The decline of M&A deals from 2011 is due to the slowdown in economic growth. However, this situation is not only limited in China, the whole world has come across similar decline since 2011. Actually the global financial crisis started from 2007, but the remarkable slowdown of corporate finance activities started from 2011. This is because of the low growth rate in the last few years, the increasing stress to maintain a high degree of liquidity and capitalization and the acquirers’ motivations to rebalance funding patterns, reported in International Monetary Fund (IFM)2. As stated in a Mckinsey Quarterly report3 in 2008, Chinese cross-border M&A, from 2003 to 2008, rose tenfold. Besides, not only the number, but also the size increases. That is, the deals expanded geographically from Asian dominant in the past to global dispersion and in many industrial sectors. This expansion in both number and size is mainly attributed to the fact that majority of firms involved in cross-border deals are state-owned, meaning that they can enjoy cash balances and acquire foreign assets.
3. Literature review and hypothesis
3.1 Motives for M&A activities
In general, there are two main outcomes – value maximizing and value destruction - for M&A activities. It is also probably that no value changes is the third outcome, but it is rather rare due to the difficulty to equalize all benefits and costs. Regarding value maximization, M&A is predicted to create wealth for shareholders and achieve synergistic gains by combining two firms (Coase, 1937). Synergistic gains stems from resources specialization. For example, when resources are specialized as production costs, firms can gain from economics of scale and scope through operational synergy. Besides, these gains can be reflected by reverse internalization and market seeking (Seth et al., 2002). Reverse internalization means that acquirers can be motivated to gain knowledge from targets, which is different from internalization that acquirers
1 ZEPHYR: the comprehensive database of M&A deal information and rumours.
2 M report: ank unding in Central astern and South astern urope Post ehman
edited by regorio mpavido Mr. Heinz udolph Mr. Luigi Ruggerone (2013).
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spread knowledge to targets. Market seeking is for long-term profitability when home market sees slow growth.
Referring to value destruction, Seth et al.(2002) classify the destruction motive into two types, namely empire building and risk reduction. The destruction motive stems from agency conflicts, called managerialism. Managerialism seeks for empire building, that is, completing the deal by sales or growth maximization (Baumol, 1962; Marris, 1964), at the expense of maximizing shareholder value (Harford et al., 2012). Risk reduction can be achieved by cross-border acquisition. Acquirers can get rid of domestic strong governance mechanism, such as restriction for overpayment, and hence, increase the likelihood of overpayment for cross-border acquisitions.
Hubris motive, put forward by Roll (1986), suggests that when evaluating targets, managers make errors of overvaluation and undervaluation. They undertake the deals presuming that their evaluation is correct, which is different from agency motive that managers know they overpay the deal. In general, managers will drop the deal if it is valued below the market price and undertake those that are over the market price. This motive is more likely to occur in cross-border M&A due to the fact that market is not completely efficient and information asymmetry is greater in cross-border M&A than domestic M&A (Seth et al., 2000).
Multiple motives, including synergy motives, agency motives and hubris motives, may coexist. Many studies find that synergy, hubris, and agency motives coexist in some takeovers (e.g., Berkovitch and Narayanan, 1993; Nguyen et al., 2012). However, the motive they focus on may vary among firms and countries. For example, Seth et al. (2000) indicate that synergy motives contribute to the majority of US takeovers, coexisting with some takeovers stimulated by hubris and agency motives.
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motivated by market development, knowledge seeking and resource seeking. In contrast, the fact, estimated by Zhang and Wang (2007), shows that acquirers’ long-term performance decreases by assuming that synergy motive is driven by long-long-term performance achievement. Thus Zhang and Wang (2007) implicate that agency or hubris motives are driven factors for Chinese listed acquirers to increase their performance.
3.2 Acquirers’ Performance in M&A activities
Many researches have been set up to investigate the performance of acquirers and targets after M&A. Most of researches on performance in domestic M&A are confined to targets (e.g., Servaes, 1991; Kaplan and Weisbach, 1992), while for acquirers, most studies focus on overall M&A (domestic and cross-border) or domestic M&A in developed countries, such as the USA and UK. Thus, researches on acquirers’ performance in domestic M&A in emerging countries are extremely scarce. But for overall M&A, compared to targets’ performance which tends to be concluded as positive performance after M&A (e.g., Bruner, 2002; Chi et al., 2011), acquirers’ performance on M&A is inconclusive and conflicting. runer’s (2002) research result is summarized from prior studies from 1971 to 2001 and his research shows that different location, period, sample size and event window of the previous researches have different outcomes. According to his summary, in general, target shareholders earn positive market-returns, while acquirers earn zero adjusted returns, and both of them in total earn positive adjusted returns. Goergen and Renneboog’s (2004) research result (significant 0.7%) on Continental Europe and UK is remarkably similar to runer’s conclusion.
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the event window (-1,1). Consistent with this finding, Chi et al. (2011) examine Chinese acquirers’ performance in four short-term event windows (−2/2 −1/1 −2/0 and −1/0) and find that cumulative abnormal returns are all significantly positive. Boateng et al. (2008) investigate 27 M&A deals in Chinese listed firms between 2000 and 2004 and find that Chinese acquirers’ value increases after cross-border M&A, which may be attributed to the synergy benefits. In addition, Gu and Reed (2010) find that the market responds positively to overseas M&A announcement by Chinese acquirers over the 1994-2008 periods. In contrast, cumulative abnormal returns can be negative around the announcement date. Aybar and Ficici (2009) find this negative reaction to shareholder value after examining 433 M&A deals in emerging markets from 1991 to 2004. However, the focused emerging markets in their study are originated mainly from Asia (excluding mainland China) and Latin America. Thus, when studying Chinese acquirers’ performance Aybar and icici’s (2009) view should be cautiously taken into consideration due to the similar and different characteristics between Chinese acquirers and those from other developing economics. Therefore, based on the above literature, Chinese acquirers tend to gain from cross-border acquisition but possibly no or small wealth value added in overall M&A activities.
To better analyze Chinese acquirers’ performance classify the M&A deals into domestic and cross-border M&A, and M&A in developed and developing countries.
3.3 domestic and cross-border M&A
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hence gain more (Goergen and Renneboog, 2004). Concerning market imperfections, information asymmetry, for example, allows different wealth effects of domestic and border M&A (Kuipers et al., 2002). There is substantial evidence that cross-border acquirers perform better than domestic acquirers. For example, the finding that cross-border acquirers perform better after M&A than domestic acquirers is indicated by Liu and Qiu (2013) after analyzing a set of performance such as size, technology, productivity and profitability in US M&A from 1991 to 2007. Similarly, the same result is echoed by Danbolt and Maciver (2012), who find that acquirers increase more shareholder wealth in cross-border than in domestic M&A, with acquirers 1.2 percent more in cross-border M&A out of the UK. Moreover, Li and Li (2007) find that shareholders gain more in cross-border M&A than that in domestic M&A, after investigating 49 cross-border M&A and 52 domestic M&A in China from 1995 to 2005.
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institutional system, such as takeover regulation, is not as good as developed countries’ Chinese acquirers, thus, are expected to generate cross-border acquisitions that averagely have stronger institutional systems and have a tendency to perform better in cross-border M&A.
In this paper, I will employ a longer time span, from 2000 to 2013, and a larger sample size to compare the differences. As mentioned previously, Chinese firms have motives to acquire firms abroad. Resource-seeking is the most significant rationales and Chinese cross-border acquisitions in developed countries allow acquirers to learn from their targets (e.g, reverse internalization) and hence perform better around the announcement date. Thus, based on the above, I draw the following hypothesis:
H1: Chinese firms that acquire foreign firms perform better than those that acquire domestic firms around the announcement date.
3.4 M&A in developed and developing economics
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countries and acquisitions in developing countries. That is, firms who acquire targets in developing countries stay inferior (including wealth gains, operating performance, etc.) to those who acquire targets in developed countries. Liu and Qiu (2013) also points out that it is easier to complete an M&A deal in developed countries than in developing ones. Through analysis of US M&A in the time span from 1991 to 2007, they find that acquirers’ performance improves more if their targets are from OECD (developed) countries than targets are from non-OECD (developing) countries (Liu and Qiu, 2013). Secondly, abnormal returns will be relatively higher in competitive takeover market (Conn and Connell, 1990; Aybar and Ficici, 2009). Competitive takeover markets are mostly located in developed areas. That is to say, both acquirers and targets are expected to gain more in developed markets. This can be supported by the fact that M&A tend to flow to developed economies through examining the M&A wave from 1987 to 2000 (Evenett, 2003; Hur et al. 2011). Besides, Corhay and Rad (2000) find that Dutch firms perform best when they acquire US targets, followed by acquisitions to Western European targets, and acquirers have negative but insignificant abnormal returns when they acquire Eastern European targets. The reason given by them is that Europe has a weaker competition market for corporate control and hence, less M&A activities. Thirdly, as mentioned previously, Chinese acquirers’ motives concentrate on resource-seeking, market-seeking, finance-seeking and capital-seeking. Compared to developing countries, developed countries have abundant resources, efficient market, and rich capital. These characteristics in developed countries provide Chinese acquirers with more availability and possibility to achieve their intentions, including value increases, that is, better performance.
Thus, I expect that Chinese acquirers perform better if the targets are from developed countries. Therefore, in this study, I will test the below hypothesis:
H2: Chinese firms that acquire foreign firms in developed countries perform better than those that acquire foreign firms in developing countries around the announcement date.
3.4.1 cultural distance
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combination of organizational and national culture. In my paper, I only concentrate on national culture and cultural distance mentioned below is only for national cultural distance. Cultural distance is the difference between value systems and it may be an influential factor in cross-border M&A. Cultural distance influences several business disciplines (Chakrabarti et al., 2009), such as management (e.g., Kogut and Singh, 1998), organizational development (e.g., Adler and Bartholomew, 1992), accounting (e.g., Cohen et al., 1993) and so on. These disciplines are significant considerations in both M&A decisions and later performance expectations. Pautler (2003) considers management of cultural difference as central to the success of a deal.
The relationship between culture and M&A performance has already been studied by many scholars without conclusive consensus. The negative relationship in this field is somewhat less abundant. Cultural differences have been blamed for the high failure rate of both domestic and cross-border M&A (e.g. Weber, 1996) with one of reason attributed to difficulty in the merge of both national and corporate culture (Barkema et al., 1996). The costs to integrate differences, such as partner’s language value (Hau and Evangelista, 2007) and so on, give rise to the negative relationship. In line with this view, Datta and Puia (1995) examine the announcement effect of cross-border M&A and observe a negative relationship between cultural distance and shareholder wealth in the short run. However, Slangen (2006) points out that it is the integration level between two firms that determines the relationship, meaning that if two firms have great cultural distances but can integrate well, shareholder wealth can also gain. Similarly, Teerikangas and Very (2006) provide a perspective that cultural differences can either positively or negatively impact M&A performance after reviewing extant research findings.
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This finding is supported by Morosini et al.’s (1998) research with a sample of 52 M&A deals during 1987 and 1992. Chakrabarti et al. (2009) also posit that culturally distant M&A perform better than culturally proximate M&A. Secondly, cultural distance creates attraction instead of stress (Very et al., 1996). Managers of acquirers and targets are sensitive to cultural issues (Evans et al., 2011) and pay more attention to dealing with cultural differences (Goulet and Schweiger, 2006). Some evidence shows acquirers and targets learn national routines from each other (e.g., Kogut and Singh, 1988). Therefore, with the increasing integration level, gains will be achieved from cultural distance in the long run (Slangen, 2006). Thus, investors will have high valuation for the deal. Based on the literature above, I expect the M&A group who has greater cultural distances performs better than the other one.
Hypothesis 2a: Cultural distances is positively associated with Chinese acquirers’ performance around announcement date.
3.4.2 Institutional system
The institutional quality influences the disparity in M&A deals between developed and developing countries (Hur et al., 2011). The extant studies show that different legal and institutional systems result in different performance after announcement date. The effects of institutional systems on M&A have already been mentioned previously. However, the conclusion is still mixed. On one hand, acquirers are expected to perform better if their targets have a relatively stronger institutional system. Because acquirers can gain from adopting better institutional systems (Starks and Wei, 2004) or premium will be paid by acquirers due to information asymmetry and agency conflicts (Moeller and Schlingemann, 2005). These explanations are supported by their findings. However, in these two studies, the periods they focus on are 1980-1998 and 1985-1995 respectively. Since the global financial market is developing, their conclusions should be cautiously taken into consideration. Moreover, as discussed earlier, stronger and better institutional systems foster M&A process (Hur et al. 2011).
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Therefore, considering the contradictory results and following Starks and Wei (2004) and Feito-Ruiz and Menéndez-Requejo (2011), I propose two contrasting hypotheses:
Hypothesis 2b(1): A target's strength level of institutional quality is positively associated with Chinese acquirers’ performance around announcement date.
Hypothesis 2b(2): A target's strength level of institutional quality is negatively associated with Chinese acquirers’ performance around announcement date.
4. Methodology
This study consists of two steps – event study and cross-sectional analysis. In the first step, I will estimate the market performance of acquirers by employing an event study method to calculate cumulative abnormal returns, and in the second one, I will test how culture and institutional system determinants impact their market performance.
4.1 Data and Sample
Table 1: Chinese cross-border M&A Country (target) Number of
deals
Number of deals with known values
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This research will be mainly achieved through data analysis by employing data from ZEPHYR and Datastream4 with time period spanning from 2000 to 2013. The sample will include domestic and cross-border acquisitions in Chinese markets, 10 developed markets and 10 developing markets (excluding China), which are recognized by United Nations ( 20135 ). Ten developed countries are Australia, Canada, France, Germany, Italy, Japan, Netherlands, Singapore, United Kingdom and United States. Ten developing countries will be Argentina, Brazil, Chile, Colombia, Egypt, India, Indonesia, Korea Republic of, Russian Federation, and South Africa. The reason for the choice of these countries is that these countries are among the top 10 that Chinese acquirers invest in (Table 1).
In ZEPHYR, detailed information about acquirers, targets, deal value, stock price, announcement date and so on is available. I collect specific data items containing acquirer’s S N code acquirer’s name target’s name, deal value (in USD) and announcement date. Besides, I use Datastream database to collect stock returns and market returns. I focus on four event windows (from day -2 to day 2, day -1 to day 1, day -1 to day 0, day 0 to day 1, where day 0 is the announcement date) and employ the standard market model to estimate abnormal returns. The data should meet the following requirements:
(1) The M&A deals are announced without limitation to whether they are completed or not.
(2) Acquirers are public listed firms located in mainland China. (3) Targets are either listed or unlisted firms in the worldwide.
(4) The announcement date of M&A lies from 01/01/2000 to 31/12/2013. (5) Both domestic and cross-border M&A.
Starting with 13271 deals (including 474 acquisitions of listed targets and the remainder is acquisition of unlisted, delisted or unknown listed status targets) in domestic M&A, 246 deals in cross-border M&A in developed countries, and 70 deals in cross-border M&A in developing countries. I eliminate deals in which:
4 Datastream: A global financial and macroeconomic database covers key economic indicators, such as
equities, stock market indices, and so on, for 175 countries and 60 markets.
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(1) The risk returns are not available in Datastream; (2) The acquirer’s S N code are unavailable in Z PHY ; (3) The acquirers were not listed when they announced;
(4) In domestic M&A, targets are unlisted or delisted (listed targets are more exposed to the markets due to the higher disclosure level requirement, so investors can rationally evaluate targets’ performance to decide whether buy hold or sell acquirer’s stocks, making the stock returns more market-driven. Besides, acquirers possibly experience a higher percentage of positive reactions if the target is private(Aybar and Ficici, 2009).
The final observations I collect are 382 (2.878% of total deals) for domestic M&A deals, 167 (67.886% of total deals) for targets in developed countries and 44 (62.857% of total deals) in developing countries.
4.2 Research Design: Market performance
There are three methods for event study, namely market return model6, Capital Asset Pricing Model (CAPM)7, and market model. Though market return model can exclude the impacts from other M&A announcements in the estimation period, it does not control the relation between stock returns and market returns, assuming that all stocks, on average, generate the same rate of returns (Bruner, 1999). Additionally, the risk free rate in China is not determined by the market (Chi et al., 2011). Thus, CAPM is not appropriate, either.
In this study, I employ the most widely used event study model - market model. I regress the market model (Brown and Warner, 1985) as follows to estimate the alpha and beta of the sample firm:
it = αi + βi Mt + it
Where Rit is the monthly return for firm I in day t, and RMt is the daily return for the
market index in month t. Ɛit is the error term. αi and βi are the regression coefficients
for firm i and they are calculated from 260 to 41 working days before announcement date.
6 Market return model: AR
it =Rit – RMt 7 CAPM: R
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Based on this market model, the abnormal return of firm i for period t is: ARit =Rit – ( + RMt )
Where αi and βi are estimated market model coefficients.
The cumulative abnormal return (CAR) is calculated to measure the short-term stock return performance around the announcement date. CARi for firm i over any event
period is:
I use 5-day event window including CAR (-2,2), CAR(-1,1), CAR(-1,0) and CAR(0,1) to analyze the market reaction to the M&A announcements.
5. Empirical Results and Discussion
5.1 Performance around the announcement date
Acquirers cumulative abnormal returns are reported in Table 2. On average, acquirers earn significantly positive abnormal returns around the announcement date with the mean abnormal returns throughout five-day event window from day -2 to day +2 amounting to 0.52%. This is consistent with the findings by Boateng et al. (2008) and Gu and Reed (2010). However, less than half of deals show positive abnormal returns in three event windows (48.90% in CAR(-2.2), 47.89% in CAR(-1,1), 48.40% in CAR(0,1)), except CAR(-1,0), which amounts to 50.42%. The positive CARs suggest that varieties of costs associated with M&A activities are expected to be offset by potential benefits. In other words, M&A can be regarded as value-creating activities by Chinese acquirers. This value-creating effect is also in line with value maximizing outcome, attributed to synergy motives (Seth et al., 2002; Goddard et al., 2011).
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with what Bhagat et al. (2011) finds. Moreover, the means are comparably larger than those in domestic M&A in the same event window. From the two-sample t-test of
Domestic vs. Cross-border, the item Mean refers to the difference8. The results show small difference in four CARs (-0.0066, -0.0043, -0.0017 and -0.0007 respectively), even though they are all insignificant. In all, the hypothesis 1 can be proved that cross-border M&A generally performs better than domestic M&A around announcement dates. This finding is consistent with better performance in cross-border M&A indicated in previous studies (Liu and Qiu, 2013; Danbolt and Maciver, 2012; Goergen and Renneboog, 2004; Feito-Ruiz and Menéndez-Requejo, 2011).
Through the comparison of developed and developing countries, it is obvious that acquirers who acquire targets in developing and developed countries both earn averagely significantly abnormal returns. Moreover, acquirers who have targets in developing countries have higher means in each event window. For the two-sample t-test of the means, I find that the difference is significantly negative (difference = developed-developing) at 10% level in CAR(-2,2). It means that on average targets in developing countries have higher abnormal returns than targets in developed countries. Thus, Hypothesis 2 is not supported. This finding is contradicted to the findings by Hur et al. (2011), Liu and Qiu (2013) and Corhay and Rad (2000). This contradicting result might be due to the acquirers I focus on are from one of emerging markets - China. This focus is different from previous researches, which focus on developed countries (e.g., Liu and Qiu, 2013; Corhay and Rad, 2000). Different from developed countries, developing countries possess some characteristics such as weak institutional systems (Goergen, et al., 2005). These weak systems allow targets to get access to cheaper financial funds from acquirers through internal capital market. Thus targets can overcome financial constraints and generate value for themselves and their acquirers (Francis et al., 2008). In line with this view, Francis et al. (2008) examine US acquirers’ performance from late 1990s to early 2000s and find that acquirers experience significantly higher positive abnormal returns when they acquire targets from developing countries. I also hypothesize two more opportunities to increase
8Difference equals to domestic mean in simple t-test minus cross-border mean in
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acquirers’ performance in M&A. After the cross-sectional regression, the results for these two hypotheses will be analyzed in details in the following section.
Table 2: Acquirers Cumulative Abnormal Returns
The table reports acquirers cumulative abnormal returns (CAR) measured over four event windows. CARs are estimated using the market model computed from working days -260 to -41 before the announcement date, day 0. Simple t-test is used to test the significance of the actual risk returns above normal risk returns in each sample, and two-sample t-test is used to test the mean of two groups(domestic vs. cross-border; developed vs. developing)
Event Window CAR(-2,2) CAR(-1,1) CAR(-1,0) CAR(0,1)
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5.2 Cross-sectional determinants of acquirer returns in cross-border M&A 5.2.1 Cultural distances
This study mainly use Hofstede (1984, 2001) cultural dimensions to estimate cultural distances. The original four dimensions are: individualism versus collectivism(IDV), uncertainty avoidance index (UAI), power distance index (PDI) and masculinity versus femininity (MAS). Long-term orientation (LTO), a fifth dimension supported by Hofstede, was added in 1991 by Michael Harris Bond. In the 2010 edition of Cultures and Organizations, based on Michael Minkov's analysis of the World Values Survey data for 93 countries, a new dimension called Indulgence versus Restraint (IND) was added. The meanings of each dimension are shown in Table 3. The countries’ each cultural dimension index is presented in Appendix 1.
Table 3: Hofstede cultural dimensions and description
Dimension Description
Individualism (IDV) People prefer to take care of themselves.
Uncertainty Avoidance (UAI) The degree to which members in a nation feel comfortable with uncertainty.
Power Distance index(PDI) The power acceptance between institutions and organizations. Masculinity (MAS) The extent to which members prefer achievement, assertiveness and
material success.
Long-term orientation (LTO) People are comfortable to sacrifice now for long term benefits Indulgence (IND) People enjoy life and have fun with free gratification in the society.
To measure Cultural Distance (CD) index, I combine all six dimensions, computing as follows (adjusting Kogut and Singh’s method (1988) in which they combine first four dimensions):
Where HAj is the acquirer’s country score for Hofstede’s cultural dimension j HTj is
the target’s country score for Hofstede’s cultural dimension j and Vj is the variance of
the index score of cultural dimension j.
5.2.2 Institutional systems
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country institutional systems influences acquirers’ abnormal returns.
Legal Origin: A country’s legal origin determines its strategy in legislation systems
such as investor protection rights (Djankov et al., 2008). Following Feito-Ruiz and Menéndez-Requejo (2011), I classify the legal environment into four systems, namely English (common law) and German, Scandinavian and French. German, Scandinavian and French law stemming from the same civil-law tradition. In the cross-border M&A, there are 88 targets from English (common law) nations, 36 with the origin of the French commercial code and 28 from nations with German commercial code. There is no targets originating from Scandinavian family. The detailed information is presented in Table 4. The table shows that targets in developed countries are mostly originated from English common law (66.67%) and a majority of targets in developing countries are French commercial code origin(72.41%). La Porta et al.(1998) examine the origin of legal rules in 49 countries, concluding that English common-law countries have the strongest legal systems, followed by German- and Scandinavian-civil-law countries, and French-civil-law countries have the weakest ones. Thus, from one to three (Table 4), the strength level of institutional systems decreases.
Table 4: Dispersion of legal origin
one if the origin is English common law, two if the origin is the German commercial code, three if the origin is the French commercial code. (Reynolds and Flores, 1989)
origin developed(N=123) developing(N=29) number % of total number % of total
English law 82 66.67% 6 20.69%
German code 26 21.14% 2 6.90%
French code 15 12.20% 21 72.41%
Corporate governance difference: Many literatures about the relation of legal systems
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protection rights) to 6 (strong investor protection rights). Table 5 shows the components of revised anti-director rights index. Generally speaking, weak investor protection systems accompany with low scores. Chinese anti-director index equals to one (Djankov et al., 2008), meaning that China has relatively weak investor protection rights. Based on the new index, corporate governance difference (CG) is calculated as below. Thus, CG takes value from -5 to 1. It means the lower the value is, the stronger target investor protection rights will be.
CG=(Acquirer_Anti- director_Index) - (Target_Anti-director_Index),
Table 5: Description of revised anti-director rights index
Component Description
Vote by mail* The country allows shareholders to mail their proxy vote directly. Shares not deposited* Shares are not blocked before the eneral shareholders’ Meeting.
Cumulative voting* Cumulative voting or proportional representation of minorities on the board of directors is allowed.
Oppressed minority* An oppressed minorities mechanism is implemented.
Pre-emptive rights* Shareholders have preemptive rights that can only be waived by a shareholder vote.
Capital to call a meeting*
The minimum percentage of share capital that allows a shareholder to call for an Extraordinary Shareholders' Meeting is at least lower than ten percent of the world median
Anti-director rights index
Aggregate index of shareholder rights by summing (1) vote by mail; (2) shares not blocked or deposited; (3) cumulative voting; (4) oppressed minority; (5) pre-emptive rights; and (6) capital.
*: The component equals one if the law rule is in line with the description.
5.2.3 Control variables
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transaction value and market capitalization is obtained from ZEPHYR and Datastream respectively. Fuller et al. (2002) find that the larger a target relative to an acquirer, the lower the acquirer abnormal returns will be. Thus, in line with this view, a negative sign is expected. Acquirer’s size (ASIZE) is calculated as the logarithm of the total assets at the year-end prior to deal announcement (Martynova and Renneboog., 2008). Data is available in Datastream. Stated by Martynova and Renneboog (2008), acquirers’ returns are expected to decrease with firm size, because larger acquirers tend to overpay in M&A deals (Moeller et al, 2004). Thus, it is expected to have a negative coefficient. Runup is measured by acquirer CAR over the window (-60,-20) preceding the M&A announcement date (Martynova and Renneboog, 2008) in order to control possible information leakage problem because this problem would result in insider trading on non-public information. Specifically, the stock price would be already influenced prior to the announcement date (Martynova and Renneboog, 2008). The leakage problem has been studied by some researchers (e.g., He and He, 2001; Tuan et al., 1995). Due to insider trading (He and He, 2001) before the announcement date, Tuan et al., (2007) find that stock price increases before M&A announcement and falls significantly after that. Chinese market is relatively inefficient and leakage problem should be paid attention to and controlled. In line with Feito-Ruiz and Menéndez-Requejo (2011), it is expected a positive effect on CAR, indicating the leakage of insider information before the announcement date.
5.3 Descriptive analysis
24 Table 6: Descriptive statistics
CAR(0,1) CAR(-1,0) CAR(-1,1) CAR(-2,2) CD ORIGIN CG RSIZE RUNUP VALUE ASIZE
ORIGIN has higher mean and median in developing countries. Moreover, average CG between China and developed countries (-2.646) is slightly more than it between China and developing countries (-3.138), meaning that in my study developed countries averagely have lower anti-director indexes. The lower anti-director index means a weaker institutional system (La Porta et al., 1999). Interestingly, this finding is not in line with the sense that developed countries have better investor protection rights than developing countries do. One of the possible explanation for this phenomenon is that Chinese firms acquire targets located in developing and stronger investor protection rights countries. For example, Brazil, Russia and Chile, scored 5, 5, 4 respectively, are countries who have the most deals with China (Table 1). Besides, RUNUP on average displays a negative sign, implying that the stock price do not averagely increase prior to the announcement date.
Table 7: Correlation Matrix
1 2 3 4 5 6 7 1 CD 1 All(N=527) 2 ORIGIN -0.803 1 3 CG -0.802 0.808 1 4 RSIZE -0.036 0.032 0.037 1 5 RUNUP 0.009 0.021 -0.004 -0.012 1 6 VALUE -0.090 0.113 0.090 0.166 0.031 1 7 ASIZE 0.095 -0.035 -0.104 -0.085 -0.042 0.414 1 1 CD NA Domestic(N=376) 2 ORIGIN NA NA 3 CG NA NA NA 4 RSIZE NA NA NA 1 5 RUNUP NA NA NA -0.013 1 6 VALUE NA NA NA 0.197 0.090 1 7 ASIZE NA NA NA -0.104 -0.035 0.338 1 1 CD 1 Crossborder(N=152) 2 ORIGIN -0.286 1 3 CG 0.402 0.256 1 4 RSIZE -0.063 0.082 0.011 1 5 RUNUP -0.061 0.146 0.111 0.020 1 6 VALUE -0.014 0.109 0.001 0.357 -0.131 1 7 ASIZE -0.005 0.135 -0.019 -0.133 -0.071 0.592 1
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the same in domestic M&A, which increases the correlation level. In cross-border M&A, there are correlations between ORIGIN and CD (-0.286), between CD and CG (0.402), between CG and Origin (0.256).
5.4 Cross-sectional analysis of CAR
I carry out a multivariate analysis in order to test the determinants that influence acquirers’ performance around the announcement date. The dependent variable (CAR) is estimated in four event windows, namely CAR(-2,2), CAR(-1,1), CAR(-1,0) and CAR(0,1). Three independent variables, namely cultural distance, origin and corporate governance difference, are tested separately and together. The results of cross-sectional regression is reported in Table 8.
As presented in Table 8, CD plays a significantly positive role in three event windows CAR(-2,2), CAR(-1,1) and CAR(0,1) in cross-border M&A and in developing countries. For M&A in developed countries, CD is only positively significant in CAR(-1,1) and CAR(0,1) at 10% and 5% significant level. These findings show that CD is a significant determinant in M&A activities. The positive sign means greater cultural distances increase acquirer abnormal returns. Therefore, Hypothesis 2a is supported. This finding is consistent with Morosini et al.’s (1998) and Chakrabarti et al.’s (2009) findings. As mentioned previously, CD is smaller in developing countries. In line with Hypothesis 2a, the performance is supposed to be not good in developing countries. However, this is contradicted to my previous finding that firms that acquire firms from developing countries perform better than those acquire firms from developed countries. One of the possible reason is that CD is not the main influential factor and other effects might offset the effects generated by CD. This can be shown by the test that the coefficients of CD are small.
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institutional systems. This is in line with the discussion generated earlier in this paper that there is a negative relationship (e.g., Martynova and Renneboog, 2008; Hagendorff et al., 2008) between the strength level of institutional systems and CAR when firms acquire targets in developing countries. However, this negative relationship is not significant in the other two groups. But it is still noticeable that there is, in general, a positive sign in cross-border M&A, consistent with the positive result in the third group. In contrast, there is, generally, a negative sign in the second group, meaning that the strong institutional systems in developed countries might decrease acquirer abnormal returns. Therefore, with legal origin as a proxy, hypothesis 2b(2) is supported but hypothesis 2b(1), when firms acquirer targets in developing countries. This result can explain why acquirers perform better when their targets are from developing countries with the result that developing firms averagely have weaker institutional systems ( Table 6).
Corporate Governance Difference shows insignificant relations in three models (Model 1.4, 2.4, and 3.4) in each group. In general, the coefficients have a negative, albeit insignificant effect on acquirers’ CA s in cross-border M&A. The negative sign suggests that the greater value of the difference9, the poorer the acquirers’ performance will be. Based on the calculation formula, the value of the difference increases with the decrease value of anti-director rights index. This means that targets’ anti-director rights index is positively associated with acquirers’ performance. However, the insignificant results imply that the impact of investor protection rights on acquirers’ abnormal returns cannot be verified by using anti-director rights index .
Moreover, RSIZE is significantly and positively related to acquirers’ performance in cross-border M&A and acquisition into firms in developed countries in four event windows. This is contradicted to uller et al.’s (2002) finding. RUNUP is insignificant in all the regressions and inconsistent in sign. VALUE is only negatively significant in developing countries in CAR(-2,2). This is consistent with the findings by Gorton et al. (2009) and Alexandridis (2013). It means ASIZE is insignificant and, in general, positive in three groups. This is inconsistent with Martynova and enneboog’s (2008) finding that bigger acquirers have negative abnormal returns.
28 Table 8: Cross-sectional regression
This table reports the results of cross-sectional regressions for acquirers in cross-border M&As and two subsamples including targets in developed and developing countries. The dependent variables in these OLS regressions are CAR(-2,2), CAR(-1,1),CAR(-1,0),CAR(0,1). The independent variables are as follows: Cultural Distance (in model 1.2, 2.2 and 3.2), Origin (in model 1.3,2.3 and 3.3); Corporate Governance Difference (in model 1.4,2.4 and 3.4). The control variables contain Relative Size, Runup, Value and Acquirer's size. The coefficients and their associated significant p-value are reported below.
Cross-border Developed Developing
Model 1.1 Model 1.2 Model 1.3 Model 1.4 Model2.1 Model2.2 Model2.3 Model2.4 Model3.1 Model3.2 Model3.3 Model3.4 Dependent variable:Car(-2,2)
Intercept 0.0062 -0.0137 0.0034 -0.0058 0.0047 -0.0096 0.0097 -0.0169 0.0205 0.0029 -0.0313 0.0235
Cultural and institutional characteristics
CD 0.0068* 0.0065 0.0121* ORIGIN 0.0037 -0.0030 0.0228** CG -0.0045 -0.0077 0.0006
Deal and firm characteristics
RSIZE 0.7570** 0.7948** 0.7351** 0.7540** 0.7805* 0.8099* 0.7977* 0.7798* 0.5148 0.5259 0.5881 0.5109 RUNUP -0.0127 -0.0097 -0.0162 -0.0097 -0.0081 -0.0051 -0.0046 -0.0023 -0.0547 -0.0471 -0.0223 -0.0544 VALUE 0.0004 0.0002 0.0004 0.0005 0.0059 0.0055 0.0059 0.0067 -0.0153^ -0.0133 -0.0164* -0.0151^ ASIZE 0.0004 0.0006 -0.0001 0.0002 -0.0028 -0.0032 -0.0029 -0.0031 0.0081 0.0059 0.0081 0.0079 N 152 152 152 152 123 123 123 123 29 29 29 29 F-Statistic 1.2083 1.3852 1.0333 1.0706 1.3743 1.3361 1.1137 1.2973 0.4917 0.8942 1.6958 0.3779 Dependent variable:Car(-1,1) Intercept -0.0104 -0.0271 -0.0107 -0.0178 -0.0183 -0.0306 -0.0123 -0.0316 0.0152 0.0042 -0.0155 0.0135
Cultural and institutional characteristics
29 ORIGIN 0.0005 -0.0035 0.0135** CG -0.0028 -0.0048 -0.0004
Deal and firm characteristics
RSIZE 0.7402*** 0.7719*** 0.7374*** 0.7384*** 0.8119** 0.8373** 0.8321** 0.8115** 0.3182 0.3251 0.3616 0.3204 RUNUP 0.0002 0.0028 -0.0002 0.0021 0.0006 0.0032 0.0047 0.0043 -0.0017 0.0030 0.0174 -0.0019 VALUE -0.0003 -0.0004 -0.0003 -0.0002 0.0031 0.0027 0.0031 0.0036 -0.0084 -0.0071 -0.0091 -0.0085 ASIZE 0.0027 0.0028 0.0026 0.0026 0.0018 0.0014 0.0016 0.0016 0.0044 0.0030 0.0044 0.0045 N 152 152 152 152 123 123 123 123 29 29 29 29 F-Statistic 2.0496* 2.2043* 1.6308 1.7101 2.2620* 2.1528* 1.8570 1.9494* 0.2552 0.5254 0.9148 0.1962 Dependent variable:Car(-1,0) Intercept 0.0121 0.0104 0.0095 0.0119 0.0086 0.0083 0.0004 0.0060 0.0262 0.0236 0.0138 0.0312
Cultural and institutional characteristics
CD 0.0006 0.0001 0.0018 ORIGIN 0.0035 0.0047 0.0055 CG -0.0001 -0.0009 0.0011
Deal and firm characteristics
30 Dependent variable:Car(0,1) Intercept -0.0254^ -0.0453** -0.0252^ -0.0282 -0.0333^ -0.0500** -0.0252 -0.0396* -0.0018 -0.0098 -0.0301 -0.0074
Cultural and institutional characteristics
CD 0.0068** 0.0076** 0.0055** ORIGIN -0.0002 -0.0047 0.0125 CG -0.0010 -0.0022 -0.0012
Deal and firm characteristics
RSIZE 0.4589** 0.4967** 0.4603** 0.4582 0.5123* 0.5467** 0.5398** 0.5121* 0.1194 0.1245 0.1594 0.1269 RUNUP 0.0033 0.0063 0.0035 0.0040 0.0083 0.0118 0.0139 0.0100 -0.0496 -0.0461 -0.0319 -0.0500 VALUE 0.0025 0.0023 0.0025 0.0025 0.0057 0.0052 0.0057 0.0060 -0.0059 -0.0050 -0.0066 -0.0063 ASIZE 0.0026 0.0028 0.0026 0.0026 0.0018 0.0013 0.0016 0.0017 0.0046 0.0036 0.0045 0.0050 N 152 152 152 152 123 123 123 123 29 29 29 29 F-Statistic 1.7935 2.5596** 1.4258 1.4409 2.1554* 2.6340** 1.8706 1.7559 0.3190 0.4819 1.1078 0.2527 ***: significant at 1% level **: significant at 5% level *: significant at 10% level
^: significant just above 10% level(between 10% and 12%)
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6. Conclusion
This paper aims to investigate Chinese acquirers’ performance in domestic and cross-border M&A by Chinese listed acquirers, and also the comparison of performance in acquisitions into targets in developed and developing countries. With 593 Chinese M&A deals from 2000 to 2013, this study contributes to the extant researches by studying the gap of comparison of Chinese acquirers’ performance around announcement date in developed and developing countries, and has a further step to analyze the cross-border M&A on cultural and institutional level.
In general, averagely either domestic or cross-border M&A generates significantly positive cumulative abnormal returns around the announcement date. The finding shows that Chinese acquirers perform better in cross-border acquisitions with higher means in four event windows in comparison to domestic M&A. The difference in performance between cross-border acquirers and domestic acquirers becomes the largest (-0.0066) in the CAR(-2,2) (See Table 2). This is because they can access to new resources and the share of resources can increase acquirers’ value by mastering better technology, enjoying economics of scale and scope and so on. Besides, this study also finds that Chinese acquirers perform significantly better in acquisitions to targets located in developing countries in CAR(0,1), which is different from the extant research results. The interpretation for this situation is probably due to more private benefits can be gained if market is inefficient. The results from the event study contribute to the inconclusive findings that cross-border acquirers perform better than domestic acquirers (e.g., Liu and Qiu, 2013; Danbolt and Maciver, 2012).
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it is supposed that acquisitions in developed countries can create more abnormal returns, which is contradicted to my previous finding. The possible explanations might be the sample size become smaller in the second step, and although CD is one of the determinants, other factors play a more important role in determining the sign of CARs. On an institutional perspective, Chinese acquirers tend to perform better if their targets are from countries with weaker legal origin, though this relationship is only significant when targets are located in developing countries. Corporate Governance Difference is insignificant throughout four event windows.
However, this research has some limitations. Firstly, the sample size becomes smaller in the second step. The smaller sample size possibly makes the results suspicious. Since observations in developing countries are only 29, the result cannot be generalized to performance of acquisitions in developing countries. Enlarging the sample size and keeping the size unchanged may help solve the contradicting results I find. Secondly, I employ event study method. This method assumes that the capital market is efficient so that investor can react immediately when M&A is announced. However, Chinese stock market is not efficient enough. Thus results might be biased. Thirdly, this study does not have robustness check, making it suspicious to generalize a convincing conclusion.
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Appendix
Appendix 1: Cultural dimensions
Country PDI IDV MAS UAI LTO IND
Developed Countries Australia 36 90 61 51 21 71 Canada 39 80 52 48 36 68 France 68 71 43 86 63 48 Germany 35 67 66 65 83 40 Italy 50 76 70 75 61 30 Japan 54 46 95 92 88 42 Singapore 74 20 48 8 72 46 Netherlands 38 80 14 53 67 68 United Kingdom 35 89 66 35 51 69 United States 40 91 62 46 26 68 Developing Countries China 80 20 66 30 87 24 Argentina 49 46 56 86 20 62 Brazil 69 38 49 76 44 59 Chile 63 23 28 86 31 68 Colombia 67 13 64 80 13 83 Egypt 70 25 45 80 7 4 India 77 48 56 40 51 26 Indonesia 78 14 46 48 62 38 Korea Republic of 60 18 39 85 100 29 Russian Federation 93 39 36 95 81 20 South Africa 49 65 63 49 34 63
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Appendix 2 : Description of variables
Description of Variables
Cultural and institutional-level variables
Culture Distance(CD)
Cultural distance between the acquirer and target nation is measured by six cultural distance indices by adjusting Kogut and Singh's (1988) calculation formula.
Source: The Hofstede Center: http://geert-hofstede.com/
Origin The legal origin of the company law or commercial code of each country, equals one if the origin is English common law, two if the origin is the French commercial code, three if the origin is the German commercial code, and four if the origin is Scandinavian civil law (Reynolds and Flores, 1989)
Corporate governance difference (CG)
Measures the difference in investor protection between the acquirer and target nations, estimated as :
COR_DIFF=(Acquirer_Antidirector_Index)
-(Target_Antidirector_Index), where anti-director indices are obtained
from Djankov et al.(2008).
Deal level variables
Relative Size (RSIZE)
Calculated as the transaction value divided by market capitalization of the acquirers ( hagat 2011). The value of firms’ market capitalization is at the year-end prior to deal announcement.
Source: based on Datastream and ZEPHYR
Runup Acquirer CAR over the window (-60,-20) preceding the M&A announcement date (Martynova and Renneboog, 2008). Abnormal returns are calculated using the market model whose parameters are estimated over the period of 260 to 41 days before the M&A announcement.
Source: based on Datastream
Value Calculated as the logarithm of the transaction value.
Source: based on ZEPHYR.
Acquirer’s Size (ASIZE)
Calculated as the logarithm of the firm’s total assets at the year-end prior to deal announcement.
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