Does payment method matter in cross-border acquisitions?

Does payment method matter in cross-border acquisitions? Shantanu Dutta a,⁎, Samir Saadi a,1, PengCheng Zhu b,2 a University of Ontario Institute of Technology, Faculty of Business and Information Technology, 2000 Simcoe Street North, Oshawa, ON, Canada L1H 7K4 b University of the Pacific, Eberhardt School of Business, 3601 Pacific Avenue, Stockton, CA 95211, USA a r t i c l e i n f o a b s t r a c t Available online 15 June 2012 In this study, we focus on 1300 completed deals (545 cross-border and 755 domestic deals) by Canadian acquirers between 1993 and 2002 to examine the effect of payment methods in the context of cross-border M&A deals. Our results show a significant and positive effect for stock- financed deals in the cross-border acquisitions. This result is robust to a set of commonly used control variables in the literature. In order to find a justification for such positive reactions for stock financed deals, we investigate the long-term operating performance of cross-border cash- and stock financed deals. Our results do not show any significant difference. It appears that market is overenthusiastic about the cross-border stock financed deals and overestimates the synergy gains. Market corrects for this overreaction for cross-border stock financed deals in the subsequent periods. We carry out a detailed buy-and-hold abnormal return (BHAR) analysis to evaluate the long term stock returns for these firms. Our results show that cross- border stock financed deals significantly underperform in the long-run compared to the cross- border cash financed deals. Further, we examine the role of stock payment in mitigating information asymmetry in cross-border deals and alleviating the risk arising from making acquisitions in a foreign market with lower corporate governance rating. Our results show that stock payment is viewed as a possible remedy for reducing information asymmetry and lowering corporate governance related risk in cross-border acquisitions. © 2012 Elsevier Inc. All rights reserved. JEL classifications: G14 G34 Keywords: Mergers and acquisitions Cross-border acquisitions Payment methods Short- and long-term performances 1. Introduction Mergers and acquisitions (M&As) are quite complex and are significant strategic events for the acquiring and target firms. Scores of studies have documented various aspects of M&A activity including trends in M&A activity, characteristics of the transactions, and corresponding gains or losses to shareholders. Perhaps, one of the most important issues in M&A that requires significant considerations and efforts of acquiring firms' managers is the form of payment and its appropriate mix. Once an acquiring firm's3 management is convinced about the benefits of a deal and decides to go ahead with the acquisition, they need to determine the method of payment (such as cash, stock, or mixed) and the financing structure. Extant literature shows that payment method matters to the shareholders and shareholders of acquiring firms view cash offers more positively than stock offers. Fuller, Netter, and Stegemoller (2002), among others, argue that due to information asymmetry and valuation uncertainty surrounding a stock acquisition, the market views stock financed deals less favorably than cash financed acquisitions. However, International Review of Economics and Finance 25 (2013) 91–107 ⁎ Corresponding author at: University of Ontario Institute of Technology, Faculty of Business and Information Technology, 2000 Simcoe Street North, Oshawa, ON, Canada L1H 7K4. Tel.: +1 905 721 8668x3700; fax: +1 905 721 3167. E-mail addresses: [email protected] (S. Dutta), [email protected] (S. Saadi), pzhu@pacific.edu (P. Zhu). 1 Tel.: +1 613 767 6476. 2 Tel.: +1 209 946 3904. 3 Following Moeller and Schlingemann (2005), we focus our analysis only on the acquiring firms' returns and the valuation consequences for the acquiring firms' shareholders. 1059-0560/$ – see front matter © 2012 Elsevier Inc. All rights reserved. doi:10.1016/j.iref.2012.06.005 Contents lists available at SciVerse ScienceDirect International Review of Economics and Finance j ourna l homepage: www.e lsev ie r .com/ locate / i re f there are some important advantages of stock financed deals vis-à-vis cash financed deals — such as ‘monitoring by existing shareholders of the target firm’ (Kang & Kim, 2008), ‘corporate memory retention’ (Uysal, Kedia, & Panchapagesan, 2008), and ‘alleviation of asymmetric information problem’ (Chen & Hennart, 2004). These factors are likely to play more significant roles in cross-border acquisitions. In this study we focus on the impact of payment methods in the context of cross-border acquisitions. Acquiring firms are interested in foreign targets for a number of reasons such as to achieve geographic diversification, new market penetration, lower labor costs, accelerated growth, follow customers and to tap intangible assets. Cross-border acquisitions pose significant challenges to the acquiring firms. It is more difficult to integrate and control a foreign target compared with a domestic one.4 Cash payments in M&A deals are often associated with drastic changes in the target firm's management (Dennis & Dennis, 1995), which could be detrimental to the integration process. Further, cash acquisition will also eliminate the existing shareholders of a target firm. In the case of a cross-border acquisition, it is more important to have ‘local’ shareholders monitoring the activities of the newly acquired firm (Kang & Kim, 2008). Local investors have access to soft information which is of great importance for stock valuation (Uysal et al., 2008). Therefore, in the context of cross-border acquisitions, market may react differently with respect to the method of payment. Our study examines this important issue with an extensive sample of Canadian M&A events. To the best of our knowledge, this is the first study to investigate this issue, at least in the Canadian context. In this study, we focus on 1300 completed deals (545 cross-border and 755 domestic deals) by Canadian acquirers between 1993 and 2002. We find significantly positive abnormal returns for Canadian acquiring firms' shares around the announcement date. Similar to Eckbo and Thorburn's (2000) results, however, we do not find any significant difference in acquirers' returns for payment methods. In the case of cross-border acquisitions, our results show a significant and positive effect for stock financed deals. This result is robust to a set of commonly used control variables in the literature. Still most of the cross-border deals (90%)5 by Canadian acquirers use cash as a payment method. The results are puzzling, as most of the acquiring firms do not use stock as a payment method irrespective of the positive perception of such cross-border deals around the M&A announcement dates. Do the cross-border stock financed deals really give more benefits to the acquiring firm shareholders in comparison with cash financed deals? In order to find a justification for such positive reactions for stock financed deals, we investigate the long term operating performance of cross-border cash- and stock financed deals. Our results do not show any significant difference. It appears that market is overenthusiastic about the cross-border stock financed deals and overestimated the synergy gains. Does market correct for this overreaction in the subsequent period? We carry out a detailed buy-and-hold abnormal return (BHAR) analysis to evaluate the long term stock returns for these firms. Our results show that cross-border stock financed deals significantly underperform in the long run compared with the cross-border cash financed deals. Further, we examine the role of stock payment in mitigating information asymmetry in cross-border deals and alleviating the risk arising from making acquisition in a foreign market with lower corporate governance rating. Our results show that stock payment is viewed as a possible remedy for reducing information asymmetry and lowering corporate governance related risk in cross-border acquisitions. Our study contributes to the literature in several ways. First, we examine Canadian acquiring firms and thus present out-of- sample evidence with a different developed country capital market. We take the view that differences in the size of the economy and in the capital market and regulatory environment may lead to different results. Most of the prior studies focus on USA and UK acquisition markets, where most of the M&A deals take place. However, Canadian M&A market is also considerably large and vibrant. As reported by Crosbie & Co., a Toronto-based merchant bank, total transaction values of the announced deals during 2007 was $370 billion with 1941 deals in Canadian M&A market. This was a record in Canadian M&A history with 60 transactions in excess of $1 billion. By examining Canadian acquiring firms, we present out-of-sample evidence with a different developed country capital market. Dutta and Jog (2009) identify a number of important differences between the Canadian and the U.S. M&A markets and show that market reactions to M&A announcements differ between these two markets.6 Therefore, a detailed examination of Canadian M&As is likely to present interesting insights to the investors' perception on M&A events. Second, we focus on the performance implications of the payment methods in cross-border deals. Most of the earlier studies focus on either cross-border deals or payment methods with respect to the M&A deals. Joint investigation of these two deal characteristics leads to interesting findings. Though cash financed deals are viewed positively by shareholders and market participants, stock financed deals have some unique advantages in the context of cross-border acquisitions. Third, we check for a consistency in market reactions to cross-border stock financed M&A deal announcements. We find that the market reactions to M&A announcements are significantly positive for cross-border stock financed deals. Such positive reactions could be attributed to the expectation of significant positive synergistic gains from the cross-border stock financed deals. In order to validate this view, we examine the long-term operating performance of cross-border acquisitions with respect to different types of payment methods (Moeller & Schlingemann, 2005) and find that cross-border stock financed deals do not show any significant improvement in acquirer's long- term operating performance. It appears that market is overenthusiastic about the cross-border stock financed deals around the deal announcement dates and overestimates the synergy gains. Market corrects for this overreaction for cross-border stock financed deals in the subsequent periods. Our study reinforces the importance of evaluating both short-term and long-term 4 In a recent study, Uysal et al. (2008) find that acquirer returns in geographically closer transactions (target location within 100 km) are more than twice that in geographically farther transactions. The higher return to local acquirer is not explained by related, either horizontal or vertical, industry transactions, and appears to be related to information advantages arising from geographical proximity. 5 This percentage includes pure cash- and mixed- (i.e. cash+stock) financed deals. 63% of the deals are concluded with pure cash payments. The statistics is based on the SDC Platinum database. 6 M&A studies using U.S. data generally report either negative or insignificant abnormal returns for the acquiring firms around the announcement date (Bruner, 2004). This is contrary to the notion of the synergy motive that leads to acquisition activities. In contrast, previous Canadian studies consistently report significantly positive abnormal returns around the announcement date (Eckbo & Thorburn, 2000; Yuce & Ng, 2005). 92 S. Dutta et al. / International Review of Economics and Finance 25 (2013) 91–107 performance results collectively to have a holistic view on the relevant issues. Finally, in this study we specifically examine the interaction between (i) stock payment and information asymmetry risk and (ii) stock payment and differential corporate governance rating between the acquiring and target country. These issues have not been clearly explored in the current literature. The remainder of the paper proceeds as follows. Section 2 presents the relevant literature review. Section 3 discusses the sample and methodology. Section 4 presents and discusses the empirical results. Section 5 presents summary and conclusions. 2. Literature review 2.1. Cross-border acquisitions Cross-border acquisitions may present some unique opportunities for the acquiring firms. Moeller and Schlingemann (2005) argue that through cross-border acquisitions, acquiring firms will have the access to an expanded investment opportunity set, which could increase the likelihood of realizing synergistic and efficiency gain. “The acquisitions of foreign assets can provide the acquirer with valuable opportunities like risk management, improved technology, and favorable government policies” (Moeller & Schlingemann, 2005, p. 534). Bris, Brisley, and Cabolis (2008) present a governance or agency perspective of cross- border acquisitions. Acquiring firms are likely to inflict their corporate governance practices on the target firms thus alter the level of protection that target firms provide to their shareholders. If the target firms are acquired by foreign firms coming from countries with better shareholder protection and better accounting standards, the performance of the combined firm is likely to improve. For a sample of 7330 ‘national industry years’ (spanning 39 industries in 41 countries) in the period 1990–2001, Bris et al. (2008) find that the Tobin's Q of an industry increases when firms within that industry are acquired by well governed foreign firms. However, cross-border acquisitions could pose serious challenges to the acquiring firms and may negatively affect shareholders' wealth.7 Quah and Young (2005) posit that in the cross-border acquisitions, the management of both cultural and organizational integrations (and their interactions) plays a significant role in making the acquisitions successful. Dealing with cultural differences among employees of two different cross-border entities or differences in regulatory and accounting systems needs significant resources and top management commitments (Campa & Hernando, 2006). Poor attention to these issues would impede the post- integration process and destroy synergistic gains. Moeller and Schlingemann (2005) expose few other ‘dark sides’ of cross-border acquisitions. Cross-border acquisitions are likely to result in a high degree of market integration which may cause an increase in the level of competition in the market for corporate control. Such competition would reduce acquirers' returns. Further, cross-border acquisitions may lead to an increase in ‘hubris’ (Roll, 1986) and agency problems, which could result in over-bidding and lower returns for acquirers' shareholders. Finally, in an era of electronic banking and online trading, individual portfolio diversification can be achieved at a lower cost. Therefore, investorsmight not view the cross-border acquisitions (that lead to global diversification) very favorably, which are very challenging and risky, in general. Moeller and Schlingemann (2005) examine a sample of 4430 acquisitions between 1985 and 1995 and find that U.S. firms who acquire cross-border targets relative to those that acquire domestic targets experience significantly lower announcement stock returns and operating performance. In the case of European bankmergers, Beitel and Schiereck (2001) and Cybo-Ottone andMurgia (2000) report lower stock return performance for cross-border than for domestic acquisitions. 2.2. Cash vs. stock offer Myers and Majluf (1984) contend that if the bidder believes that the firm's shares are properly valued, it may offer cash to send a positive signal to the market. As a result, the market is likely to view a cash offer as more favorable than a stock offer. Also, if the bidder is uncertain about the target's value, the bidder may not want to offer cash because the target will only accept a cash offer greater than its true value and the bidder will have overpaid (Fishman, 1989; Fuller et al., 2002). Faccio and Lang (2005) focus on the control aspect of a target firm while examining the effect of payment methods on an acquirer's returns. They argue that an acquiring firm would prefer cash payment over stock payment, if the acquirer is concerned about retaining the control in the target firm in the post-acquisition period. However, if the target size is smaller or the target firm does not have a sizeable concentrated ownership, bidders are likely to be less apprehensive about the stock payment. An alternative tax-based hypothesis exists that favors stock offers. If a bidder acquires a target with cash, target shareholders must pay taxes immediately; while in the case of stock offers, tax implications are deferred (Fuller et al., 2002). Fuller et al. (p. 1765) summarize such dynamics as follows: “If this tax option is valuable to owners, they may accept a discounted price for the firm equal to, at the most, the value of the option. This lower price will be reflected in the higher bidder returns for stock offers.” Empirical studies generally support the hypothesis that shareholders of acquiring firms view cash offers more positively than stock offers (Fuller et al., 2002; Moeller, Schlingemann, & Stulz, 2003). In a Canadian context, Eckbo and Thorburn (2000) do not 7 Raff, Ryan, and Stahler (2009) have further shown that cross-border acquisitions might not always present an optimal solution to an acquiring firm that is looking for a new market. The other two viable options are greenfield investment and joint venture. 93S. Dutta et al. / International Review of Economics and Finance 25 (2013) 91–107 find any significant difference for cash payments. Faccio and Lang (2005) examine a large sample of European M&As over the period 1997–2000 and focus on the dynamics between corporate control issues and payment methods. They find that when bidder's controlling shareholder has an intermediate level of voting power in the range of 20 to 60%, they prefer cash payments. Savor and Lu (2009) find that stock financed deals generate negative reactions around the announcement dates and also underperform significantly in the long-run. However, using a global dataset, Alexandridis, Petmezas, and Travlos (2010) show that stock financed deals are not necessarily value destroying events outside the competitive markets (such as United States, United Kingdom and Canada). 2.3. Cross-border acquisitions, payment methods and relevant hypotheses As the cross-border acquisitions are more complex in nature due to the uncertainty involved in dealing with a target in a foreign market, decisions on payment methods (i.e. cash vs. stock) may need further considerations. Some of the studies (such as Faccio & Lang, 2005) argue in favor of cash financed deals in case of cross-border acquisitions. Faccio and Lang posit that investors generally have a ‘home country bias’ in their portfolio decisions. Hence the investors of foreign target firms are likely to be less interested in acquiring firms' shares. Cross-border target firms' shareholders are likely to consider foreign shares more risky and be concerned with the access to less timely and more limited foreign firm information (Faccio & Lang, 2005). Further, as discussed above, acquiring firms that are concerned with retaining control in target firms are likely to prefer cash payments. On the other hand, a number of other studies state that stock financed deals have some distinctive advantages in cross-border acquisitions. First, as Dennis and Dennis (1995) report, target firm's existing management is often changed in the cash financed deals. Such dramatic changes in target firm management may disrupt the post-acquisition integration process severely, specially in the cross-border acquisitions. Second, in the stock financed deals local shareholders of a cross-border target firm are more likely to retain a significant level of ownership. As Kang and Kim (2008) argue, it is more important to have ‘local’ shareholders monitoring the activities of the newly acquired firm. This may translate into better synergy realization for the combined firm in the post-acquisition period. Third, information asymmetry problems are likely to be more pronounced in cross-border M&A deals in comparison to the domestic deals. Sharing part of the firm ownership with the foreign investors or shareholders of the target firms can effectively alleviate the problem of asymmetric information in cross-border acquisitions (Chen & Hennart, 2004; Reuer, Shenkar, & Ragozzino, 2004). Further, Uysal et al. (2008) argue that local investors have access to soft information which is of great importance for stock valuation. Finally, in case of cross-border acquisitions, acceptance of stock payments by the foreign shareholders may also send a signal to the market that the acquirer's stock has high liquidity and intrinsic value. Therefore, in the context of cross-border acquisitions, market may react differently with respect to different payment methods and view stock financed deals more favorably (Owers, Lin, & Rogers, 2008). Hypothesis 1. The market is likely to react more positively to the acquirers' cross-border stock financed deals than the cross- border cash financed deals. Although, this study primarily focuses on the short-term effect of cross-border M&A announcements, we take the view that in order to (i) understand the market reactions fully and (ii) check the consistency of the results, it is important to examine the effects of those deals on long-term performance. Section 2.4 presents the main arguments and relevant literature review on the long-term performance studies in the context of M&As. 2.4. Cross-border deals and long-term performance of the acquiring firms In Section 2.3 we have hypothesized that cross-border stock financed deals would be viewed more favorably by the acquiring firms' shareholders. According to the conventional wisdom, it can be argued that the market expects a higher level of synergistic gains in those deals and hence reacts more favorably around the announcement dates. Better synergistic gains are likely to be translated into better long-term operating performance. Below we present a brief literature review on long-term operating performance. 2.4.1. Long-term operating performance A smaller but growing body of literature has investigated the long-term operating performance of acquiring firms. However, previous empirical studies in this area have reported inconsistent results (Martynova, Oosting, & Renneboog, 2006). Most of the recent US based studies either report an improvement in operating performance (Heron & Lie, 2002; Linn & Switzer, 2001), or an unchanged performance (Moeller & Schlingemann, 2005).8 Results from the studies on other markets are also inconsistent. For example, using UK data, Powell and Stark (2005) report modest improvements in operating performance for acquiring firms. For continental Europe, Gugler, Mueller, Yurtoglu, and Zulehner (2003) report an insignificant increase in post-acquisition profit and Martynova et al. (2006) report an insignificant decrease in operating performance. In the similar fashion, Asian studies also present inconsistent results (Rahman & Limmack, 2004; Sharma & Ho, 2002). Rahman and Limmack (2004) show that operating performance improves significantly for Malaysian acquirers; whereas, Sharma and Ho (2002) find insignificant changes in 8 Moeller and Schlingemann (2005) report no significant change in the long-term operating performance for the overall sample. However, they find that cross- border acquisitions have a negative impact on the long-term operating performance. 94 S. Dutta et al. / International Review of Economics and Finance 25 (2013) 91–107 acquirers' post-acquisition operating performance for Australian firms. Most of the earlier studies show that there is no significant relation between method of payment and post-acquisition long-term operating performance (Healy, Palepu, & Ruback, 1992; Martynova et al., 2006; Sharma & Ho, 2002). However, Linn and Switzer (2001) and Ghosh (2001) find that post-acquisition operating performance is significantly higher for cash offer as compared to stock offer. In case of cross-border acquisitions, Moeller and Schlingemann (2005) find that long-term operating performance decreases for the combined firms. We are not aware of any study that examines the long-term operating performance of acquiring firms for cross-border stock financed deals. We take the view that if market reacts significantly positively for cross-border deals, it expects a significant improvement in operating performance in the post-acquisition period. Hypothesis 2. The acquirers' long-term operating performance is better in cross-border stock financed deals than that in the cross-border cash financed deals. Some other studies have emphasized that one should also examine the impact of long-term stock-return performance (Rau & Vermaelen, 1998). However, studies related to long-term stock return performance invite serious debates. According to market efficiency hypothesis, there should not be any long-term abnormal stock-return following any significant event (Fama, 1998). However, others argue that if market fails to fully understand the impact of some significant event in the short-term around the announcement dates, there is likely to be long-term abnormal returns (Rau & Vermaelen, 1998). Below we present a brief review of the arguments presented in the literature on long-term stock-return performance. 2.4.2. Long-term stock-return performance Following a detailed review of past influential studies, Agrawal and Jaffe (2000) have concluded that, “in our opinion, the work starting with Franks, Harris, and Titman (1991) shows strong evidence of abnormal underperformance following mergers. Except for Franks et al. (1991) itself, each paper shows at least some evidence of underperformance” (p. 50). As presented in Dutta and Jog (2009, p. 1402), most of the studies (dominated by U.S. studies and many with overlapping sample periods) report negative long-term abnormal returns. However, Fama (1998) dismissed any systematic claim of long-term abnormal returns and concluded that “consistent with the market efficiency hypothesis that the anomalies are chance results, apparent overreaction of stock prices to information is about as common as under-reaction. And post-event continuation of pre-event abnormal returns is about as frequent as post-event reversal” (p. 304).9 Notwithstanding such arguments, evidence of long-term underperformance as presented in some of the detailed and careful studies (such as that of Rau & Vermaelen, 1998) remains a puzzle. In view of market efficiency hypothesis, we propose the following hypothesis: Hypothesis 3. There will not be any long-term abnormal stock returns for the acquiring firms that have executed cross-border acquisitions, irrespective of the choice of payment methods. 2.5. Information asymmetry, corporate governance and cross-border acquisitions As briefly outlined in Section 2.3, in case of cross-border acquisitions, acquiring firms' shareholders are likely to be more concerned about information asymmetry problem compared to the domestic acquisitions. Two of the more commonly used proxies for information asymmetry are (i) geographic distance (Kang & Kim, 2008; Ragozzino, 2009), and (ii) cultural distance (Han, Kang, Salter, & Yoo, 2010; Kogut & Singh, 1988). As the geographic and cultural distances increase, the communication between acquiring and target firm shareholders becomes more complicated. This would lead to a higher level of information asymmetry. One way to mitigate such information asymmetry problem is to retain local shareholders (Kang & Kim, 2008), by using stock as a payment method (Reuer et al., 2004). Hypothesis 4. In case of higher geographic and cultural distances between the acquiring and target firms, the market is likely to react more positively to the acquirers' cross-border stock financed deals than the cross-border cash financed deals. In recent years, the finance literature has placed a significant level of emphasis on corporate governance issues and its impact on financial decisions (Jiraporn, Kim, Kim, & Kitsabunnarat, 2012). Cross-border merger and acquisition literature is not an exception. Bris et al. (2008) among others argue that “target firms usually import the corporate governance system of the acquiring company by law” (p. 224). Bris et al. (2008) find that the Tobin's Q of an industry generally increases if firms within that industry are acquired by foreign firms with better governance practices. However, notwithstanding this benefit, it can be argued that an acquiring firm assumes substantial risk if it decides to acquire a cross-border target firm operating under poor governance environment. Under such circumstances, acquiring firms' shareholders might prefer to use some sort of ‘contingent payment’ (such as stock payment) to share the risk with target shareholders. Thus, a significant difference in the country level governance environment may influence an acquiring firm's financing decision. 9 Mitchell and Stafford (2000) and Dutta and Jog (2009) report no significant change in long-term stock return performance, once the methodological biases were corrected. 95S. Dutta et al. / International Review of Economics and Finance 25 (2013) 91–107 Hypothesis 5. If the target firms' home country governance environment is weaker, the market is likely to react more positively to the acquirers' cross-border stock financed deals than the cross-border cash financed deals. 3. Data and methodology 3.1. Data This study considers all Canadian M&A deals that occurred between 1993 and 2002 and involved a Toronto Stock Exchange (TSX) listed bidding company. We obtain our dataset from the SDC Thomson Financial Database. Our data meet the following criteria: (i) the deals were completed, (ii) the acquiring firm was not from the financial industry, (iii) acquiring firms with multiple acquisitions during 1993–02 period were considered, and (iv) deals with all sizes of transaction value were considered.10 Stock return data was collected from the Canadian Financial Market Research Center (CFMRC) database. Accounting information was collected from the Stock Guide database. The sample set-up and the descriptive statistics are presented in Tables 1 and 2. Descriptive statistics of the sample show that: (i) in line with the overall Canadian merger and acquisition (M&A) activities, there is an increase in M&A deals between 1996 and 2000 but a decline in the post 2000 period, which is somehow characterized by much larger individual deal sizes. (ii) Most of the acquirers (757 out of 968 acquiring firms) are single acquirers (that is, made only one completed deal in a calendar year); the rest of the firms made more than one acquisition in a given year. (iii) Most of the deals are in minerals, manufacturing, and service industries consistent with the industrial landscape in Canada. In terms of the characteristics of the offers, we find that (Table 2) there are significantly higher numbers of (a) domestic deals (755) than cross border deals (545), (b) merger offers (1158) than tender offers (142), (c) pure cash transactions (764) than share swaps (184), (d) growth acquiring firms11 (1057) than value acquiring firms (164), and (e) unrelated acquisitions (772) than related acquisitions (527). We also find that most of the cross-border acquisitions use cash payment method. 3.2. Methodology 3.2.1. Abnormal returns around the announcement dates We follow Brown and Warner's (1985) standard-event study methodology to calculate bidder-announcement effects – abnormal returns (ARs) and cumulative abnormal returns (CARs) – around initial acquisition announcements. We use the market model, which expresses daily abnormal returns as: ARjt ¼ Rjt− �αj þ �βjRmt � � ð1Þ where Rjt and Rmt are the observed returns for security “j” and the market portfolio, respectively, in time period “t” relative to the event date of interest. We compute the security-specific parameters �αj and �βj over the estimation period t−31 to t−120 trading days.12 We exclude the 30-day time interval t−30 to t−1 days to avoid including information about the event that may affect security returns. We use a z-test to evaluate the significance of the CARs and univariate and multivariate (regression) analyses to investigate the effect of payment methods and cross-border acquisitions on the CARs surrounding an acquisition. 3.2.2. Long-term operating performance We use a firm's cash-flow to total assets as a measure of operating performance. In line with the recommendation by Ghosh (2001), we use a matching firm as a benchmark to find the adjusted operating cash flows of the acquiring firms. In order to select a matching firm we follow a two-stage procedure. First, we identify all TSX firms that have not made any acquisition in the period from 1990 to 2005. Second, we perform an OLS regression considering all acquirers, targets and matching firms. We regress the firms' return on equity on firm size and market-to-book value variables (Loughran & Vijh, 1997). Subsequently, matching firms are selected based on the nearest propensity score obtained by using the coefficients of firm size and price-to-book value factors. Once we obtain the benchmark cash flows, the matching firm adjusted cash flows are computed as follows: Matching firm adjusted cash flow return ¼ acquiring firm0s cash flow to total asset–matching firms cash� flow to total asset: ð2Þ Subsequently, we calculate the matching firm adjusted profitability for each acquiring firm for three years prior and three years subsequent to the takeover event. Traditionally, in the related literature, the mean pre-acquisition profitability is compared with the mean post-acquisition profitability to test whether or not there is a significant change in the long-term operating performance (this approach is termed as ‘change model’). 10 Out of the 1300 events considered in the study, only 88 cases have transaction values less than $1 million CDN. 11 We define a growth-acquiring firm as the acquiring firm with price-to-book value of more than 1 in the preceding year of an acquisition. 12 Some studies use a longer estimation window (e.g., t−41 to t−240 days). As the estimation window increases, the chance of encountering other external events during this estimation period also increases. Since many acquirers make multiple acquisitions, we chose to use a shorter estimation window in our analysis. 96 S. Dutta et al. / International Review of Economics and Finance 25 (2013) 91–107 However, in one of the most widely cited study on long-term operating performance, Healy et al. (1992) recommends using an ‘intercept model’ as opposed to the simple change model. In the ‘intercept model’, acquisition-induced changes in cash flow are estimated as the intercept (α) of the cross-sectional regression of post-acquisition benchmark-adjusted cash flows on pre- acquisition benchmark-adjusted cash flows. For example, a positive and significant value for the intercept would mean an improvement in operating performance in the post-acquisition period over the pre-acquisition period. Healy et al. (1992) argue that this methodology (i.e. ‘intercept model’) which accounts for possible persistence in cash flow returns is superior to a ‘change model’ that compares post- and pre-acquisition operating performances directly (Ghosh, 2001; Moeller & Schlingemann, 2005). Further, intercept model allows us to control for other variables in the regression models. In this study, we employ an ‘intercept model’ to test the impact of various deal and firm specific factors on long-term operating performance. 3.2.3. Long-term stock return performance We followed standard buy-and-hold abnormal return (BHAR) methodology13 (Barber & Lyon, 1997) in order to examine the long term performance of acquiring firms. We define the buy-and-hold abnormal return (BHAR) as the return on a buy-and-hold investment in the sample firm less the return on a buy-and-hold investment in an asset/portfolio with an appropriate expected return: BHARiτ ¼ ∏ τ t¼1 1þ Rit½ �−∏ τ t¼1 1þ E Ritð Þ½ �: ð3Þ Expected return, E(Rit), in Eq. (3), is calculated in two ways: by using (i) a reference portfolio return (such as market index return), and (ii) control firm return (such as a matching firm based on size and book to market value ratio). As reported by Barber and Lyon (1997), BHAR with reference portfolio is subject to a new listing bias, a skewness bias, and a rebalancing bias. We used Lyon, Barber, and Tsai's (1999) methodology to account for skewness bias while we calculated BHAR with the reference portfolio. The control firm approach eliminates the new listing bias (since both the sample and control firm must be listed in the identified event month), the rebalancing bias (since both the sample and control firm returns are calculated without rebalancing), and the skewness problem (since the sample and the control firms are equally likely to experience large positive returns). In the control firm approach, we used the same matching firms as identified in the BHAR analysis. However, neither the reference portfolio approach nor the control firm approach accounts for cross-dependence among acquisition eventswhich poses a serious problem to 13 We use monthly return data for three years (i.e. 36 monthly return data) starting from the closing date of the deal in the BHAR analysis. Table 1 Yearly and sectoral distribution of Canadian acquirers listed on Toronto Stock Exchange. The sample size is 1300 acquisition events over 1993–2002 period by Canadian acquirers listed on the TSX. The sample includes multiple acquirers. ‘Multiple acquirers’ refers to the acquiring firms that acquire more than one target in a calendar year. ‘Single acquirers’ acquire only one target in any calendar year. Panel A. Number of acquisitions over 1993–2002 and corresponding transaction value # of transactions # of acquirer # of single acquirer # of multiple acquirer Total transaction value (in $ mil. CDN) Avg. transaction value (in $ mil. CDN) 1993 93 70 57 13 4919.0 52.9 1994 105 82 67 15 9021.2 85.9 1995 107 78 63 15 7757.6 72.5 1996 139 100 73 27 7366.3 53.0 1997 159 127 101 26 11293.7 71.0 1998 160 109 81 28 40,006.9 250.0 1999 135 105 84 21 30,467.8 225.7 2000 150 107 85 22 54,739.8 364.9 2001 134 100 75 25 18,440.2 137.6 2002 118 90 71 19 18,922.5 160.4 Total 1300 968 757 211 20,2934.9 156.1 Panel B. Transactions by primary SIC code SIC # of transactions # of acquirer # of single acquirer # of multiple acquirer Total transaction value (in $ mil CDN) Avg. transaction value (in $ mil. CDN) 10 minerals 394 303 242 61 31723.3 80.5 20–39 manufacturing 325 239 184 55 89352.3 274.9 40 communications 154 101 71 30 53195.2 345.4 50 trades 42 35 30 5 1730.2 41.2 70–89 services 385 290 230 60 26933.9 70.0 Total 1300 968 757 211 202934.9 156.1 97S. Dutta et al. / International Review of Economics and Finance 25 (2013) 91–107 event-time based long-term performance methodologies such as BHAR. Consequently, we have adopted the correction procedure employed by Mitchell and Stafford (2000) for the adjustment of cross-sectional dependence in BHAR test statistics: σBHAR independenceð Þ σBHAR dependenceð Þ ≈ 1ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 1þ N−1ð Þρi;j q ð4Þ where, N = number of sample events, σ(BHAR) is the cross-sectional sample standard deviations of abnormal returns for the sample of ‘N’ firms and �ρi;j = average correlation of individual BHARs. In this study, we report our results based on control firm approach. 4. Results and discussions 4.1. Short-term performance of the acquiring firms in the cross-border acquisitions Table 3 (panel A) presents the results for cumulative abnormal returns (CARs) for the acquiring firms for various event windows (t−1,+1, t−2,+2, t0,+2, and t−5,+5). The CARs are highly significant and positive across the four different event-windows. Our findings differ from US results in which the CARs surrounding the announcement date are negative or insignificant. Possibly some features of the Canadian M&A market such as the larger relative size of target firms, the higher propensity of cash financed deals, and the lack of strict anti-takeover regulations help in generating positive CARs for shareholders of Canadian acquiring firms. Table 3 (panel B) presents the results for CARs for different payment methods (i.e. Cash and Stock). Results are significant for both payment methods and the differences between these methods are not significant. Our results corroborate the results of Eckbo and Thorburn's (2000) study, which does not find any significant difference in acquirers' returns for payment methods. Panel C and panel D present the results for domestic vs. cross-border acquisitions and cross-border cash financed vs. stock-finance acquisitions, respectively. These univariate results show that market favors (i) cross-border acquisitions over domestic deals and (ii) cross-border stock financed deals over cross-border cash financed deals. Table 2 Descriptive statistics of deal-specific variables for acquiring firms. The sample consists of 968 annual observations for acquiring firms between 1993 and 2002 for the firm specific variables and 638 for the governance variables between 1997 and 2002; the data for previous years is not available. For acquiring firms, only one event is considered in case of multiple acquisitions by the firm in any year. “Deal size” is the total transaction value in million Canadian dollars. “Tender or merger” is a dummy variable. If the acquisition is completed through tender offer, the values are “1” and “0” otherwise. “Target type” is a categorical variable outlining the nature of a target firm. Three categories are created: (i) public target, (ii) private target, and (iii) other (subsidiaries, joint ventures etc.). “Related/unrelated acquisition” is a dummy variable. For related acquisition, the values are “1” and “0” otherwise. It is determined based on the SIC code of acquiring firm and target firm. Two versions of this dummy variable are created based on: (i) 4-digit SIC code, and (ii) 2-digit SIC code (not reported here). “Payment type” or “Methods of payment” is a categorical variable outlining the nature of transaction payment mode. Three categories are created: (i) pure cash payment, (ii) pure stock payment, and (iii) mixed or other. “Domestic/Cross border target” represents different categories depending on target location. “Growth or value” is a dummy variable. The value is “1” if the acquiring firm's price to book value ratio is greater than 1 and “0” otherwise. “Relative size” is the ratio of transaction value and market value of the acquiring firm's equity. Total number of events is 1300 for each deal characteristics category. Number Percentage Deal size (transaction value) Less than 10 m 535 41.2% 10 to 100 m 499 38.4% More than 100 m 266 20.5% Tender or merger Tender 142 10.9% Merger 1158 89.1% Target type Public 400 30.8% Private 476 36.6% Other (sub., JV) 424 32.6% Related/unrelated target (based on 4 digit SIC) Related 527 40.5% Unrelated 772 59.4% Info. not available 1 0.1% Methods of payment Cash 764 58.8% Stock 184 14.2% Other/mixed 352 27.1% Growth or value acquirers Growth 1057 81.3% Value 164 12.6% Info. not available 79 6.1% Domestic/cross-border targets Domestic — Canada 755 58.1% Cross-border: USA 316 24.3% Cross-border: Other 229 17.6% Cross-border and payment method Cross-border: cash 342 63% Cross-border: stock 56 10% Cross-border: mixed 147 27% Relative size Less than 5% 496 38.2% 5 to 25% 398 30.6% More than 25% 259 19.9% Info. not available 147 11.3% 98 S. Dutta et al. / International Review of Economics and Finance 25 (2013) 91–107 Next, we use multivariate analysis (OLS regression) to examine the effects of payment methods and cross-border acquisitions on CARs. Table 4 presents the results of four regression models. We employ the following regression model: CAR ¼ αþ β1 � Cross� border targetþ β2 � Payment methodþ β3 � Cross� border target� Payment method þβ4 � Public target firmþ β5 � ln Market capitalizationð Þ þ β6 � ln Price to book valueð Þ þβ7 � ln Cash flow to total assetsð Þ þ β8 � ln Related=unrelated targetð Þ þ β9 � ln Relative sizeð Þ þβ10 � Tender offerþ β11 � Year dummyþ β12 � Industry dummyþ ε: ð5Þ All regression models use CAR (−1, +1) as the dependent variable. Regression models include a number of independent and control variables. ‘Cross-border target’ is a dummy variable. If the target is non-Canadian, its value is ‘1’, and else ‘0’. For ‘payment methods’, we use two dummy variables to differentiate ‘pure cash’, ‘pure stock’, and ‘mixed’ payments. ‘Public target firm’ is a dummy variable. For public target firms its value is ‘1’, and ‘0’ otherwise. ‘Market capitalization’ is the total market value of the acquiring firm's equity in the preceding year of M&A event. ‘Price-to-book value’ is the ratio of a firm's market value to book value in the prior year. ‘Cash flow to total assets’ is the ratio of the firm's operating cash flow to total assets in the prior year of acquisition. ‘Related/ unrelated target’ is a dummy variable. A related acquisition (based on 4-digit SIC code) has a value of 1 and an unrelated acquisition has a value of 0. ‘Relative size’ is the ratio of transaction value tomarket value of an acquiring firm's equity. ‘Tender offer’ is a dummy variable. If a firm completes an acquisition through a tender offer, the values are 1 and 0 otherwise. Models 1 and 2 include only ‘pure stock’ dummy variable to examine the effect of stock payments exclusively. Models 3 and 4 include both ‘pure cash’ and ‘pure stock’ dummy variables and the results are contrasted with ‘mixed’ payment dummy variable. In order to examine the effect of cross-border stock payment deals, we include interaction terms (‘cross-border target×payment method’) in Models 2 and 4. Similar to the univariate analysis, our results show that the main effects of method of payments are not statistically significant Table 3 Short-run cumulative abnormal returns: market model. The sample size is 989 for all acquiring events. We use the market model “ARjt ¼ Rjt− �α j þ �β jRmt � � ” to determine the abnormal return and adjusted abnormal return. We compute the security-specific parameters �α j and �β j over the estimation period t−31 to t−120 trading days. We exclude the 30-day time interval t−30 to t−1 days to avoid including information about the event that may affect security returns. “CAR” is the average of the summation of the abnormal returns for each stock for a specific period. Four different versions of CAR were used in the analysis. The statistical significance of the abnormal return was examined by Z-statistics introduced by Linn and McConnell (1983). Standard deviation of AR used in the test accounts for the first order correlation effect. CAR results are reported in decimals (not in percentage). All cases CAR1 (−1, +1) CAR2 (−2, +2) CAR3 (0, +2) CAR4 (−5, +5) Panel A. Cumulative abnormal returns for all M&A events Avg. CAR 0.013⁎⁎⁎ 0.016⁎⁎⁎ 0.013⁎⁎⁎ 0.012⁎⁎⁎ Z-stat 9.253 9.476 10.008 6.971 Panel B. Methods of payment and cumulative abnormal returns 1. Cash (N=596) Avg. CAR 0.013⁎⁎⁎ 0.017⁎⁎⁎ 0.014⁎⁎⁎ 0.014⁎⁎⁎ Z-stat 7.309 7.989 8.278 5.249 2. Stock (N=137) Avg. CAR 0.011⁎⁎ 0.009 −0.001 0.009⁎⁎ Z-stat 2.526 1.580 1.296 2.015 Mean diff (1 −2) 0.002 0.008 0.015 0.005 t-Stat 0.239 0.708 1.506 0.258 Panel C. Domestic and cross-border acquisitions and cumulative abnormal returns 1. Domestic (N=554) Avg. CAR 0.0086⁎⁎⁎ 0.0102⁎⁎⁎ 0.0085⁎⁎⁎ 0.0064⁎⁎⁎ Z-stat 5.948 5.736 6.253 4.937 2. Cross-border (N=435) Avg. CAR 0.0188⁎⁎ 0.0234⁎⁎⁎ 0.0178⁎⁎⁎ 0.0198⁎⁎⁎ Z-stat 7.238 7.814 8.033 4.938 Mean diff (1 −2) −0.0102⁎⁎ −0.0132⁎⁎ −0.0093⁎⁎ −0.0133 t-Stat −2.157 −2.304 −2.215 −1.609 Panel D. Cross-border cash financed and stock financed deals 1. Cross-border cash financed deals (N=279) Avg. CAR 0.0133⁎⁎⁎ 0.0189⁎⁎⁎ 0.0163⁎⁎⁎ 0.0106⁎⁎ Z-stat 4.607 5.650 5.764 2.519 2. Cross-border stock financed deals (N=40) Avg. CAR 0.0602⁎⁎⁎ 0.0634⁎⁎⁎ 0.0395⁎⁎⁎ 0.0986⁎⁎⁎ Z-stat 5.302 4.194 3.341 4.343 Mean diff (1 −2) −0.0468⁎⁎⁎ −0.0445⁎⁎⁎ −0.0009 −0.0880⁎⁎⁎ t-Stat −4.106 −3.152 −0.092 −4.252 Note. * Indicates statistical significance at 10% level. ⁎⁎ Indicates statistical significance at 5% level. ⁎⁎⁎ Indicates statistical significance at 1% level. 99S. Dutta et al. / International Review of Economics and Finance 25 (2013) 91–107 (Model 1 and Model 3). However, we find that in cross-border acquisitions, stock financed deals have significant positive effects on CARs (‘cross-border target×pure stock’ variable is significant and positive in Models 2 and 4). In other words, investors of acquiring firms clearly prefer the announcements of stock financed deals in cross-border acquisitions. The results presented above show support for Hypothesis 1. Our result is consistent with the views of a number of past studies who argue in favor of stock payments in cross-border acquisitions (Chen & Hennart, 2004; Dennis & Dennis, 1995; Kang & Kim, 2008; Reuer et al., 2004). However, our results do not support the views of Faccio and Lang (2005). We offer the following potential explanations. In their study, Faccio and Lang consider M&A deals from Western Europe. In Western Europe the ownership is more concentrated. Hence, acquisition of a target firm with concentrated ownership might pose a threat to the acquiring firm's owners in terms of maintaining control in the post-acquisition period. In our sample, most of the cross-border targets are from USA, where the corporate ownership is generally widely held. Hence, the Canadian acquirers included in our sample are likely to be less concerned with control issue in the post-acquisition period. Also, it could be simply that, other favorable factors embedded in cross-border stock deals (such asmitigation of information asymmetry, alleviation of corporate governance risk) outperform the negative views associated with such contingent payment. It is quite challenging to directly test as to why stock offers are favored by the market participants and the acquiring firms' shareholders. In the subsequent sections we attempt to explore some plausible explanations to justify such results. 4.2. Plausible explanations for the favorable reactions to cross-border stock financed deals 4.2.1. Do acquiring firm's characteristics matter? It could be possible that better performing firms use stock as a medium of payment in acquiring foreign targets. If this is true, market would bemore upbeat about the cross-border stock financed deals. We test this conjecture by using the logistic regression methodology and considering only cross-border deals. We use probability of cash payment as the dependent variable in the binary logistic regression model. The main independent variable is the acquiring firm's return on asset (ROA), which indicates the efficiency of a firm. Cordeiro and Veliyath (2003) posit that a firm's ‘ROA’ is viewed as an indicator of managerial efficiency and CEO compensation is directly related to such performance indicators. We use a number of other firm and deal specific factors as control variables in the logistic regression models. We employ the following logistic regression model to examine the differentiating characteristics of cross-border cash financed and stock financed deals. Table 4 Effect of cross-border acquisitions and payment methods on CARs. The table shows the OLS regression results that test the impact of cross-border payment type on the acquisition announcement returns. We use the CARs of the acquiring firms in the window of (−1, +1) days around the acquisition announcement as the dependent variable. “Cross border target” is a dummy variable. The value is “1” if the target is from outside Canada and “0” otherwise. Based on the “Payment type” three dummy variables are created: (i) pure cash payment, (ii) pure stock payment, and (iii) mixed or other. “Public target firm” is a dummy variable. If the target is a public firm, its value is ‘1’ and ‘0’ otherwise. “Market capitalization” is the total market value of the acquiring firm's equity in the preceding year of M&A event. “Price to book value” is a ratio of the market price to book value of acquiring firm's share. “Cash flow to total asset” is a ratio of the firm's operating cash flow to total assets. “Related/unrelated target” is a dummy variable. For a related acquisition (based on 4-digit SIC code), the values are 1 and 0 otherwise. “Relative size” is the ratio of transaction value andmarket value of the acquiring firm's equity. Total number of events is 1300 for each deal characteristic category. “Tender offer” is a dummy variable. If a firm completes an acquisition through a tender offer, the values are 1 and 0 otherwise. Dependent variable: CAR (−1, +1) Model 1 Model 2 Model 3 Model 4 β t Value β t Value β t Value β t Value (Intercept) 0.068 2.802 ⁎⁎⁎ 0.070 2.927 ⁎⁎⁎ 0.067 2.744 ⁎⁎⁎ 0.069 2.828 ⁎⁎⁎ Cross-border target 0.005 0.996 −0.002 −0.332 0.005 0.975 −0.001 −0.125 Pure stock −0.001 −0.192 −0.022 −2.507 ⁎⁎ 0.003 0.355 −0.018 −1.693 ⁎ Pure cash 0.007 1.169 0.007 0.899 Cross-border target×pure stock 0.075 4.543 ⁎⁎⁎ 0.074 4.031 ⁎⁎⁎ Cross-border target×pure cash −0.001 −0.084 Public target firm 0.001 0.299 0.001 0.348 0.001 0.255 0.001 0.306 Log (market capitalization) −0.002 −1.400 −0.003 −1.533 −0.002 −1.435 −0.003 −1.564 Price to book value 0.000 −0.307 0.000 −0.263 0.000 −0.330 0.000 −0.283 Cash flow to total assets −0.022 −0.750 −0.016 −0.544 −0.022 −0.749 −0.016 −0.541 Related/unrelated target −0.007 −1.428 −0.008 −1.599 −0.008 −1.465 −0.008 −1.632 Log (relative size) 0.006 3.205 ⁎⁎⁎ 0.005 2.973 ⁎⁎⁎ 0.006 3.403 ⁎⁎⁎ 0.006 3.166 ⁎⁎⁎ Tender offer −0.019 −2.216 ⁎⁎ −0.018 −2.113 ⁎⁎ −0.019 −2.130 ⁎⁎ −0.018 −2.005 ⁎⁎ Year dummy Yes Yes Yes Yes Industry dummy Yes Yes Yes Yes N 869 869 869 869 F 2.74 ⁎⁎⁎ 3.58 ⁎⁎⁎ 2.68 ⁎⁎⁎ 3.34 ⁎⁎⁎ R-squared 0.067 0.089 0.068 0.09 Adj. R-squared 0.042 0.064 0.043 0.063 Note. ⁎ Indicates statistical significance at 10% level. ⁎⁎ Indicates statistical significance at 5% level. ⁎⁎⁎ Indicates statistical significance at 1% level. 100 S. Dutta et al. / International Review of Economics and Finance 25 (2013) 91–107 Logit π cashð Þð Þ ¼ αþ β1 � ROAþ β2 � Cash� flow to total assetsþ β3 � Price� to� book value þ β4 � ln Market valueð Þ þ β5 � ln Relative sizeð Þ þ β6 � Public target firm þ β7 � Tender offerþþβ8 � ln Related=unrelated targetð Þ þ β9 � Year dummy þ β10 � Industry dummyþ ε ð6Þ where, π(cash) is the probability of a cross-border cash financed deal. ‘ROA’ is the acquiring firm's return on assets. Other variables, namely, ‘Cash flow to total assets’, ‘Price-to-book value’, ‘Market capitalization’, ‘Relative size’, ‘Public target firm’, ‘Tender offer’ and ‘Related/unrelated target’ are defined in the previous section and in Tables 4 and 5. In the context of favorable market reactions to cross-border stock financed deals we expect that ‘ROA’ will be negatively related to π(cash) (the probability of being a cash financed deal). We further expect that ‘Cash flow to total assets’ will have a positive relationship with π(cash). A higher value of ‘Cash flow to total assets’ variable indicates the cash richness of an acquiring firm. ‘Price-to-book value’ indicates the future investment and growth opportunity. An acquiring firm with a higher value of ‘Price- to-book value’ is more likely to use stock in making an acquisition. A higher ‘Relative size’ of the target firm would require more resources and hence acquiring firms are more likely to use stocks in acquiring a bigger target. Also, extant literature suggests that ‘Tender offers’ generally use cash as a medium of payment. Table 5 presents the logistic regression results. Model 1 presents the full model. Model 2 excludes ‘Cash flow to total assets’ andModel 3 excludes ‘ROA’. As both ‘Cash flow to total assets’ and ‘ROA’ could indicate firm's performance, we evaluate the effect of each variable separately in Models 2 and 3. From the results presented in Table 5 we find that ROA is not significant in any of the three models. That is, acquiring firm's existing performance is not a determinant of the cross-border payment method. Our results further show that cash rich acquiring firms tend to prefer cash deals (cash flow to total assets variable is marginally significant in Models 1 and 3),14 stock is the preferred payment method in relatively bigger acquisition deals, and cash deals are more prevalent in cross-border public target acquisitions. In summary, acquiring firm's characteristics do not offer any reasonable explanation for the favorable reactions to cross-border stock financed deals. Table 5 Determinants of cross-border acquisitions' payment methods. The table shows the logistic regression results that examine the differentiating characteristics of cross-border acquisitions' payment methods. π(cash) is the dependent variable that denotes the probability of a cross-border cash financed deal. ‘ROA’ is the acquiring firm's return on assets. ‘Cash flow to total assets’ is the ratio of the acquiring firm's operating cash flow to total assets in the prior year of acquisition. ‘Price-to-book value’ is the ratio of a firm's market value to book value in the prior year. ‘Market capitalization’ is the total market value of the acquiring firm's equity in the preceding year of M&A event. ‘Relative size’ is the ratio of transaction value to market value of an acquiring firm's equity. ‘Public target firm’ is a dummy variable. For public target firms its value is ‘1’, and ‘0’ otherwise. ‘Tender offer’ is a dummy variable. If a firm completes an acquisition through a tender offer, the values are 1 and 0 otherwise. ‘Related/unrelated target’ is a dummy variable. For a related acquisition (based on 4-digit SIC code), the values are 1 and 0 otherwise. Wald statistics denote the significance of each variable included in a model. Hosmer and Lameshow test refers to the ‘goodness of fit’ of the models. Dependent variable: π(cash) Model 1 Model 2 Model 3 β Wald stat β Wald stat β Wald stat (Intercept) −2.471 1.663 −2.810 2.243 −2.325 1.540 ROA −0.004 0.054 0.009 0.666 Cash flow to total assets 4.234 3.034 ⁎ 3.842 3.441 ⁎ Price to book value 0.060 0.863 0.055 0.775 0.060 1.019 Log (market capitalization) 0.067 0.221 0.080 0.333 0.081 0.338 Log (relative size) −0.423 6.466 ⁎⁎⁎ −0.463 8.166 ⁎⁎⁎ −0.415 6.275 ⁎⁎⁎ Public target firm 0.840 6.860 ⁎⁎⁎ 0.906 8.076 ⁎⁎⁎ 0.832 6.678 ⁎⁎⁎ Tender offer 1.531 1.677 1.913 2.637 1.452 1.518 Related industry/target −0.395 0.910 −0.509 1.592 −0.354 0.735 Year dummy Yes Yes Yes Industry dummy Yes Yes Yes N 348 351 350 −2 log likelihood 184.837 188.603 185.925 Cox & Snell R square 0.176 0.168 0.174 Nagelkerke R square 0.342 0.327 0.338 Hosmer and Lameshow test Chi-square 15 10 7 df (degree of freedom) 8 8 8 Sig. 0.054 0.260 0.505 Note. ** Indicates statistical significance at 5% level. ⁎ Indicates statistical significance at 10% level. ⁎⁎⁎ Indicates statistical significance at 1% level. 14 As an alternative view, cash flow to total asset could be also considered as a proxy for operating efficiency. From that perspective, significant positive results for cash flow to total assets variable imply that acquiring firms with better operating efficiency would prefer cash payments (and not stock payments) in cross- border deals. 101S. Dutta et al. / International Review of Economics and Finance 25 (2013) 91–107 4.2.2. Do cross-border stock-finance deals show better synergistic gain in the long-run? Another possible reason for more favorable reactions to cross-border stock financed deals is the ex-ante expectation of better synergistic gains for such deals. If the cross-border stock financed deals provide bettermonitoring by erstwhile target shareholders and retain more corporate memory (Chen & Hennart, 2004; Kang & Kim, 2008; Uysal et al., 2008), operating performance (or synergistic gains) should be better for these deals. In order to test this conjecture, we compare the long-term operating synergy gains (i.e. long-term operating performance) between the cash- and stock financed deals in the spirit of Moeller and Schlingemann (2005). As discussed earlier, we use the ‘intercept model’ to test the change in long-term operating performance. We employ the following regression model: MMFCTPost ¼ αþ β1 �MMFCTPre þ β2 � Cross� border targetþ β3 � Payment method þ β4 � Crossborder target� Payment methodþ β5 � Public target firm þ β6 � ln Market capitalizationð Þ þ β7 � ln Price to book valueð Þ þ β8 � ln Cash flow to total assetsð Þ þ β9 � ln Related=unrelated targetð Þ þ β10 � ln Relative sizeð Þ þ β11 � Tender offerþ β12 � Year dummy þ β13 � Industry dummyþ ε: ð7Þ Table 6 presents the OLS regression results that test the impact of various deal and firm specific factors on long-term operating performance. The dependent variable in all three regression models is MMFCTPost (Matching adjusted post average cash flow to total asset). MMFCTPost is the average of ‘matching firm adjusted cash flow to total asset’ for post acquisition period (years +1, +2 and+3). ‘Matching firm adjusted cash flow to total asset’ is the average difference in the operating performance (cash flow to total asset) between the acquiring firm and the corresponding matching firm for a given year relative to the acquisition year. Similarly, MMFCTPre refers to the pre-acquisition period operating performance of the acquiring firms. Descriptions of all other variables are presented in Table 4. Out of payment method variables, Model 1 includes only ‘pure stock’ dummy variable to examine the effect of stock payments exclusively. Models 2 and 3 include both ‘pure cash’ and ‘pure stock’ dummy variables and the results are contrasted with ‘mixed’ payment dummy variable. Models 2 and 3 differ with respect to the inclusion of ‘yearly dummy’ variables. In order to examine the effect of stock payment deals in the context of cross-border acquisitions, we include interaction terms (‘cross-border target×payment Table 6 Operating performance (cash flow to total assets) for pre- and post-merger period. The table presents the OLS regression results that test the impact of various deal and firm specific factors on long-term operating performance. The dependent variables in all three regression models is Matching adjusted post average cash flow to total asset (MMFCTPost). ‘Matching adjusted post average cash flow to total asset (MMFCTPost)’ is the average of ‘matching firm adjusted cash flow to total asset’ for post acquisition period (year +1, +2 and +3). ‘Matching firm adjusted cash flow to total asset’ is the average difference in the operating performance (cash flow to total asset) between the acquiring firm and matching firm for a given year relative to the acquisition year. The ‘Individual matching firm’ was selected based on the nearest propensity score with respect to firm size and price to book value. ‘Matching adjusted pre average cash flow to total asset (MMFCTPre)’ is the average of ‘Matching firm adjusted cash flow to total asset’ for the pre-acquisition period (year−1,−2 and−3). ‘Matching firm adjusted post and pre difference’ is the average of the difference between ‘Matching adjusted post average cash flow to total asset’ and ‘Matching adjusted pre average cash flow to total asset’. In case of multiple acquisitions by a firm in any year, only one event was considered in the analysis. All operating performance variables are expressed in decimals. Mean differences in operating performance are expressed in decimals (not in percentage). Definitions of all other independent variables are presented in Table 4. Dependent variable: MMFCTPost Model 1 Model 2 Model 3 β t Value β t Value β t Value (Intercept) 0.052 0.934 0.000 0.008 0.055 0.984 MMFCTPre 0.712 14.152 ⁎⁎⁎ 0.720 14.328 ⁎⁎⁎ 0.714 14.170 ⁎⁎⁎ Cross-border target −0.004 −0.306 −0.004 −0.167 0.007 0.265 Pure stock 0.036 1.510 0.025 0.925 0.031 1.139 Pure cash −0.017 −0.811 −0.008 −0.401 Cross-border target×pure stock 0.043 0.896 0.034 0.642 0.034 0.644 Cross-border target×pure cash 0.003 0.111 −0.015 −0.507 Public target firm −0.004 −0.416 −0.003 −0.303 −0.004 −0.458 Log (market capitalization) 0.001 0.347 0.002 0.430 0.001 0.326 Price to book value 0.010 3.961 ⁎⁎⁎ 0.010 3.815 ⁎⁎⁎ 0.010 3.896 ⁎⁎⁎ Cash flow to total assets −0.097 −1.168 −0.098 −1.184 −0.097 −1.169 Related industry/target 0.003 0.195 0.003 0.213 0.002 0.183 Log (relative size) 0.006 1.303 0.005 0.968 0.005 0.978 Tender offer 0.000 0.009 0.005 0.212 0.000 −0.013 Year dummy Yes Yes N 553 553 553 F 17.928 ⁎⁎⁎ 26.069 ⁎⁎⁎ 16.332 ⁎⁎⁎ R-squared 0.402 0.386 0.404 Adj. R-squared 0.380 0.371 0.379 Note. * Indicates statistical significance at 10% level. ** Indicates statistical significance at 5% level. ⁎⁎⁎ Indicates statistical significance at 1% level. 102 S. Dutta et al. / International Review of Economics and Finance 25 (2013) 91–107 method’) in all threemodels (i.e. Models 1, 2 and 3). Results show that there is no significant improvement in operating performance for cross-border stock financed deal. Therefore, our results do not support Hypothesis 2. In other words, there is no unique synergistic gain for cross-border stock financed deals that could justify significant positive abnormal returns for cross-border deals. It appears that acquiring firm's investors overestimate the synergy value of the cross- border stock financed deals and benefits of stock financed deals such as the continuation of monitoring by the existing target shareholders and corporate memory retention. 4.2.3. Does market correct for this overreaction in the subsequent periods? We carry out a detailed long-term stock return analysis (using BHAR methodology) to evaluate whether or not market adjusts for such overreactions around the announcement dates. Earlier studies that report long-term abnormal returns assume that the market gradually reassesses the quality of acquiring firms as the results of the acquisition become more clear (Rau & Vermaelen, 1998). Results of the BHAR analysis are presented in Table 7. Table 7 (panel A) presents the BHAR analysis for cross-border and domestic deals; Table 7 (panel B) presents the BHAR analysis for cash financed and stock financed deals; and Table 7 (panel C) presents the BHAR analysis for the cross-border cash financed and cross-border stock financed deals. Panel B shows marginally significant (at 10% level) negative long-term stock return performance for stock financed deals. More interestingly, panel C shows significant and negative abnormal returns for cross-border stock financed deals (with a 3-year BHAR value of −10.8% and an adjusted t-statistics of −2.32); whereas, the results for cross-border cash financed deals are not significant.15 It appears that market is overenthusiastic about the cross-border stock financed deals around the announcement dates. Subsequently, in the long-run, market reassesses the benefits of such deals and negatively adjusts the stock price of the acquiring firms that made cross-border stock financed deals. Our results do not support Hypothesis 3, which is grounded onmarket efficiency hypothesis (Fama, 1998). However, long-term stock return analysis reveals the consistency in market reactions for cross-border stock financed deals. In the absence of any significant improvement in long-term operating performance for such deals, market participants reassess the firm values and make negative corrections to nullify initial overreactions around the announcement dates. Table 7 Buy-and-hold abnormal returns (BHAR) for acquiring firms (with 36 monthly returns following the deal completion). “BHAR” is the buy and hold abnormal return based on the average difference in the aggregated (compounded) performance between the included stock and the benchmark over a 36-month period starting after the effective month of acquisition. We had 1018 valid cases for BHAR calculations with all cases and 229 observations with non-overlapping cases. If a firm makes acquisitions within three years of a previous acquisition, the cases were considered ‘overlapping’. Otherwise, events are considered “non- overlapping” cases. Value weight BHAR is calculated based on the market value weight of the acquiring firm at the effective date of acquisition. BHAR uses individual matching firm returns as the benchmark. Adjusted t-statistics accounts for skewness and cross-sectional dependence in stock returns. BHAR values are expressed in decimals (not in percentage). Panel A. Cross-border and domestic deals Cross-border deals (N=458) Domestic deals (N=560) Value weighted BHAR (individual matching firm as a benchmark) 0.0186 −0.041 Adj. t-stat 0.194 −0.313 Panel B. Cash and stock financed deals Cash-financed deals (N=618) Stock-financed deals (N=133) Value weighted BHAR (individual matching firm as a benchmark) 0.118 −0.100 Adj. t-stat 0.921 −1.740⁎ Panel C. Cross-border cash and stock financed deals Cross-border cash financed deals (N=296) Cross-border stock financed deals (N=45) Value weighted BHAR (individual matching firm as a benchmark) 0.154 −0.108 Adj. t-stat 1.192 −2.32⁎⁎⁎ Note. * Indicates statistical significance at 10% level. ** Indicates statistical significance at 5% level. *** Indicates statistical significance at 5% level. 15 For brevity, we report only value weighted BHAR that considers matching firm returns as a benchmark. That is, we report BHAR with control firm as a benchmark. BHAR with reference portfolio as a benchmark suffers from a number of biases (Barber & Lyon, 1997). 103S. Dutta et al. / International Review of Economics and Finance 25 (2013) 91–107 4.3. Information asymmetry, corporate governance and cross-border acquisitions Based on extant literature we argue that stock payment is likely to reduce information asymmetry in cross-border M&A deals. Further, stock financed cross-border acquisitions are likely to mitigate corporate governance related risk (please refer to Section 2.5). In this section we examine these conjectures (Hypotheses 4 and 5). Table 8 presents the results of four regression models. We employ the following regression model (for Models 2, 3, 4)16: CAR ¼ αþ β1 � Cross� border targetþ β2 � Pure stockþ β3 � Public target firmþ β4 � ln Market capð Þ þ β5 � ln Price to book valueð Þ þ β6 � ln Cash flow to total assetsð Þ þ β7 � ln Related=unrelated targetð Þ þ β8 � ln Relative sizeð Þ þ β9 � Tender offerþ β10 � Anti� director index difference þ β11 � cultural distanceþ β12 � Geographic distance þ β13 � Anti� director index difference� Pure stock þ β14 � Cultural distance� Pure stockþ β15 � Geographic distance� Pure stock þ β15 � Other country specific variablesþ β16 � Year dummyþ β17 � Industry dummyþ ε: ð8Þ Table 8 Information asymmetry, corporate governance and cross-border acquisitions. The table presents the OLS regression results that test the interaction between (i) information asymmetry and stock payment and (ii) corporate governance and stock payment. We use the CARs of the acquiring firms in the window of (−1, +1) days around the acquisition announcement as the dependent variable. Deal specific variables are defined in Table 4. Variables of interest for this table (i.e. Table 8) are: cultural distance, geographic distance, and target country anti-director index. For Cultural distance, we use Hofstede's (1980) index and combined Hofstede's four most common cultural dimensions – power distance, individualism, masculinity, and uncertainty avoidance – into the following composite index on the basis of Kogut and Singh's (1988) formula: Cultural distance ¼ P 4 j¼1 HA;j−HT;jð Þ2 4�Vj , where HA,j is the acquiring-country score for Hofstede's cultural dimension j, HT,j is the target-country score for the corresponding cultural dimension j, and Vj is the variance of the index score of cultural dimension j. We measure the geographic distance (in kilometers) between the capital cities of the target country and the acquiring country. We take the logarithm of the measure to make it close to normal distribution. In order to capture the relative position of target country's corporate governance environment, we use the ‘Anti-director index difference’. This measure is developed in the spirit of Djankov et al.'s (2008) paper to measure the investor right protection in the country. Dependent variable: CAR (−1, +1) Model 1 Model 2 Model 3 Model 4 Beta t Value Beta t Value Beta t Value Beta t Value (Intercept) 0.192 0.507 0.151 0.523 0.285 0.986 0.205 0.707 Cross-border target 0.145 0.305 0.124 0.875 0.172 1.215 0.155 1.096 Pure stock −0.018 0.102 −0.024 −2.568 ⁎⁎ −0.012 −1.380 0.253 3.249 ⁎⁎⁎ Pure cash 0.009 0.272 Cross-border target×pure stock 0.079 0.000 ⁎⁎⁎ Cross-border target×pure cash −0.001 0.911 Public target firm 0.002 0.545 0.003 0.650 0.002 0.490 0.003 0.649 Log (market capitalization) −0.002 0.249 −0.002 −1.058 −0.002 −0.876 −0.002 −1.066 Price to book value −0.001 0.406 −0.001 −0.754 −0.001 −0.782 −0.001 −0.804 Cash flow to total assets −0.017 0.599 −0.020 −0.590 −0.026 −0.768 −0.019 −0.558 Related industry/target −0.011 0.062 ⁎ −0.011 −1.846 ⁎ −0.010 −1.648 ⁎ −0.010 −1.762 ⁎ Log (relative size) 0.006 0.002 ⁎⁎⁎ 0.005 2.850 ⁎⁎⁎ 0.006 2.964 ⁎⁎⁎ 0.005 2.892 ⁎⁎⁎ Tender offer −0.017 0.071 ⁎ −0.018 −1.959 ⁎ −0.020 −2.164 ⁎⁎ −0.019 −2.014 ⁎⁎ Anti-director index difference −0.014 −0.149 −0.013 −1.289 −0.013 −1.268 −0.017 −1.753 ⁎ Cultural distance 0.001 0.724 0.001 0.369 −0.001 −0.184 0.001 0.366 Geographic distance −0.017 0.335 −0.015 −0.841 −0.019 −1.091 −0.018 −0.997 Target country GDP −0.005 0.508 −0.003 −0.445 −0.008 −1.093 −0.004 −0.612 Target country GDP growth 0.002 0.382 0.001 0.782 0.001 0.540 0.002 1.011 Target country economic freedom index −0.001 0.547 −0.001 −0.549 −0.001 −0.625 −0.002 −0.887 M&A market competition 0.000 0.415 0.000 0.797 0.000 0.654 0.000 0.900 Geographic distance×pure stock 0.011 4.126 ⁎⁎⁎ Cultural distance×pure stock 0.010 2.569 ⁎⁎ Anti-director index diff×pure stock 0.068 3.359 ⁎⁎⁎ Year dummy Yes Yes Yes Yes Industry dummy Yes Yes Yes Yes N 740 740 740 740 F 2.632 ⁎⁎⁎ 2.768 ⁎⁎⁎ 2.389 ⁎⁎⁎ 2.560 ⁎⁎⁎ R-squared 0.106 0.105 0.092 0.098 Adj. R-squared 0.066 0.067 0.053 0.059 Note. ⁎ Indicates statistical significance at 10% level. ⁎⁎ Indicates statistical significance at 5% level. ⁎⁎⁎ Indicates statistical significance at 1% level. 16 In order to test the robustness of the earlier results (as presented in Table 4), we also present Model 1 in Table 8, that includes a set of country specific variables. We find that our main results (as presented in Section 4.1) are robust to a set of target country specific variables. However, as in our sample cross- border stock financed deals are very limited in number, in the subsequent models (Models 2, 3, and 4) we excluded the interaction term ‘Cross-border target×Pure stock’. In models 2, 3, and 4 we have other interaction terms with ‘Pure stock’ variable to test Hypotheses 4 and 5. 104 S. Dutta et al. / International Review of Economics and Finance 25 (2013) 91–107 All regression models use CAR (−1, +1) as the dependent variable. M&A deal specific variables are defined in Section 4.1. We employ two proxies for information asymmetry, namely, cultural distance and geographic distance. These variables are defined below: Cultural distance: we use Hofstede's (1980) index to measure cultural distance and combined Hofstede's four most common cultural dimensions — power distance, individualism, masculinity, and uncertainty avoidance — into the following composite index on the basis of Kogut and Singh's (1988) formula: Cultural distance ¼ P 4 j¼1 HA;j−HT;jð Þ2 4�Vj , where HA,j is the acquiring-country score for Hofstede's cultural dimension j, HT,j is the target-country score for the corresponding cultural dimension j, and Vj is the variance of the index score of cultural dimension j. Geographic distance: we measure the geographic distance (in kilometers) between the capital cities of the target country and the acquiring country. We take the logarithm of the measure to make it close to normal distribution. In order to capture the relative position of target country's corporate governance environment, we use the ‘Anti-director index difference’. This measure is developed in the spirit of Djankov, La Porta, Lopez-de-Silanes, and Shleifer (2008). Djankov et al. (2008) present an index (score) to measure the investor right protection in a country. The higher the score, the better the investor right protection in a country. In this study, we use the difference of the indices between Canada and each target country (i.e. Canada index− target country index) to measure the difference in the quality of overall corporate governance environment. In order to ensure that our results are robust to other country specific variables, we have controlled for following ‘other country specific variables’ in the regression analysis: Target country GDP: we use the GDP value (in million USD) of the target country in the latest fiscal year end before the acquisition. We take the logarithm of the measure to make it close to normal distribution for the statistical analysis. The data is collected from the World Development Indicator database. Target country GDP growth rate: we use the GDP growth rate (%) of the target country in the preceding year of the acquisition. The data is collected from the World Development Indicator database. Target country economic freedom index: we take the economic freedom index of the target country in the preceding year of the acquisition. The data is collected from the Heritage Foundation (www.heritage.org/index/). M&A market competition: we measure the M&A market competition by counting the number of acquisitions announced by the firms in the same 4-SIC code acquiring industry in the past three months17 before the acquisition. The larger the number, the more competitive is the M&A market in the announcement period. In Table 8, all three models include the main effects of ‘information asymmetry’ (i.e. cultural distance and geographic distance) and ‘corporate governance’ (i.e. Anti-director index difference) variables as well as specific interaction effects. More specifically, Models 2 and 3 include the interaction effects of ‘geographic distance×Pure stock’ and ‘Cultural distance×Pure stock’ respectively. In both cases the coefficient of the interaction effects are highly significant and positive. It implies that stock payments are more favorably viewed in the M&A deals in which information asymmetry is likely to be higher. Use of stock payment is likely to retain the existing shareholders in the target firms and hence would help in alleviating information asymmetry problems between the acquiring and target firms. These results show support for Hypothesis 4. Model 4 (Table 8) includes the interaction effect ‘Anti-director index difference×Pure stock’ in order to examine the role of stock payment inmitigating the risk arising fromweak governance environment in the target firm country. The coefficient is highly significant and positive. It implies that if the target country governance is weaker, the stock payment is more favorably viewed by the market participants. This result supports Hypothesis 5. It is interesting to note that the main effect of ‘Anti-director index difference’ in Model 4 is negative and significant. It implies that, in general, market participants are ambivalent about the outcome of such cross-border deals. These findings are consistent with the main results presented in Kuipers, Miller, and Patel (2009) who find that “firms operating under stronger legal environments are more valuable” (p. 562). Hence, as the main effect of ‘Anti- director index difference’ shows (coefficient of−0.017; in model 4, Table 8), Canadian acquiring firms' shareholders are likely to react negatively to an M&A deal, if the target firm is acquired from a country with poor corporate governance environment. However, acquiring firms' investors feel more comfortable once these deals are carried out through contingent payment (such as stock payment). In case of stock payment, the existing target shareholders will also continue to bear the consequences of governance risk. 5. Summary and conclusions In this study, we focus on 1300 completed deals (545 cross-border and 755 domestic deals) by Canadian acquirers between 1993 and 2002 to examine the effect of payment methods in the context of cross-border M&A deals. Extant literature shows that market participants generally prefer cash financed deals. However, cross-border acquisitions have some interesting features that may make market participants view stock financed deals more favorably. Cross-border acquisitions pose significant challenges to 17 We also count the number in 6 month or 12 month time period. The results are similar. Thanks to the anonymous reviewer for suggestions on this robustness test. 105S. Dutta et al. / International Review of Economics and Finance 25 (2013) 91–107 the acquiring firms in terms of integrating the new business and thus realizing projected synergistic gains. Some of the important advantages of stock financed deals such as ‘monitoring by existing shareholders of the target firm’, ‘mitigating information asymmetry’, and ‘corporate memory retention’ are likely to play positive roles in cross-border acquisitions. Results presented in this study show that in the case of cross-border acquisitions, market reacts significantly and positively to stock financed deals. This result is robust to a set of commonly used control variables in the literature. In order to find a justification for such positive reactions for stock financed deals, we investigate the long term operating performance of cross- border cash and stock financed deals. Our results do not show any significant difference. It appears that market is overenthusiastic about the cross-border stock financed deals and they overestimate the synergy gains. An analysis of the long-term stock return performance shows that market makes adjustments for these deals in the long-run. Results show that cross-border stock financed deals significantly underperform in the long-run compared to the cross-border cash financed deals. In other words, though stock financed cross-border deals show initial promise, they do not live up to the expectations in the long-run. Perhaps, this explains why Canadian acquirers still predominantly use cash as a method of payments in cross-border deals. 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Dutta et al. / International Review of Economics and Finance 25 (2013) 91–107 Does payment method matter in cross-border acquisitions? 1. Introduction 2. Literature review 2.1. Cross-border acquisitions 2.2. Cash vs. stock offer 2.3. Cross-border acquisitions, payment methods and relevant hypotheses 2.4. Cross-border deals and long-term performance of the acquiring firms 2.4.1. Long-term operating performance 2.4.2. Long-term stock-return performance 2.5. Information asymmetry, corporate governance and cross-border acquisitions 3. Data and methodology 3.1. Data 3.2. Methodology 3.2.1. Abnormal returns around the announcement dates 3.2.2. Long-term operating performance 3.2.3. Long-term stock return performance 4. Results and discussions 4.1. Short-term performance of the acquiring firms in the cross-border acquisitions 4.2. Plausible explanations for the favorable reactions to cross-border stock financed deals 4.2.1. Do acquiring firm's characteristics matter? 4.2.2. Do cross-border stock-finance deals show better synergistic gain in the long-run? 4.2.3. Does market correct for this overreaction in the subsequent periods? 4.3. Information asymmetry, corporate governance and cross-border acquisitions 5. Summary and conclusions References