Board reforms and M&A performance: international evidence

Ahmad, Muhammad Farooq; Aktas, Nihat; Cumming, Douglas; Xu, Guosong Article — Published Version Board reforms and M&A performance: international evidence Journal of International Business Studies Provided in Cooperation with: Springer Nature Suggested Citation: Ahmad, Muhammad Farooq; Aktas, Nihat; Cumming, Douglas; Xu, Guosong (2024) : Board reforms and M&A performance: international evidence, Journal of International Business Studies, ISSN 1478-6990, Palgrave Macmillan, London, Vol. 55, Iss. 5, pp. 616-637, https://doi.org/10.1057/s41267-023-00674-3 This Version is available at: https://hdl.handle.net/10419/316653 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may be saved and copied for your personal and scholarly purposes. You are not to copy documents for public or commercial purposes, to exhibit the documents publicly, to make them publicly available on the internet, or to distribute or otherwise use the documents in public. If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. http://creativecommons.org/licenses/by/4.0/ Vol:.(1234567890) Journal of International Business Studies (2024) 55:616–637 https://doi.org/10.1057/s41267-023-00674-3 Board reforms andM&A performance: international evidence MuhammadFarooqAhmad1· NihatAktas2· DouglasCumming3,4· GuosongXu5 Received: 2 August 2022 / Revised: 1 November 2023 / Accepted: 9 November 2023 / Published online: 16 January 2024 © The Author(s) 2024 Abstract This research employs a difference-in-differences framework to study the impact of major board reforms on the performance of mergers and acquisitions (M&As). Using an international sample of board reforms implemented in 61 countries from 1985 to 2021, we document a drastic redistribution of wealth from target shareholders to acquirer shareholders after the board reforms in target countries. This effect is most pronounced in M&A transactions that involve the sale of controlling shares, thereby supporting the hypothesis that corporate board reforms mitigate the private benefits of control in the target firm. Furthermore, these reforms increase expected deal synergies, in that deal-level announcement returns are higher after the implementation of the reforms. When country-level institutional quality and legal protection of shareholders are greater, it reinforces the reform effects. Overall M&A activity remains unchanged following the reforms, yet financial bidders complete fewer transactions, implying a reform-induced squeeze-out of financial bidders from the M&A market in the target country. Collectively, these international results are consistent with the predictions of the private benefits of control theory and underscore the role of institutional quality and investor protection in reinforcing the effects of board reforms worldwide. Keywords Board reforms· M&A activity· Target gains· Corporate governance Introduction Board oversight is a fundamental mechanism of corporate governance, and a key responsibility of corporate directors involves supervising merger and acquisition (M&A) deals. Extant literature shows that M&A negotiations are often susceptible to agency issues.1 Thus, a key question arises: How do reforms related to board practices affect the market for corporate control in general and the distribution of wealth between acquirer and target shareholders in particular? Despite its importance, the impact of board reforms on M&A transactions remains unexplored. In an effort to fill this research gap, we focus on how board reforms affect takeover targets. Since 1990, more than 60 countries have implemented board reforms, designed to improve boards’ supervisory function. Many of these reforms require greater board independence and mandate the separation of the chair and CEO positions. To the extent that the reforms in the target country alleviate some agency problems and improve the growth potential of the target firm (Fauver etal., 2017), postreform M&As should be driven more by economic synergies, which arguably should lead to greater overall efficiency gains. Yet these reforms could also alter the distribution of Accepted by Lemma Senbet, Area Editor, 9 November 2023. This article has been with the authors for three revisions. * Douglas Cumming [email protected]; [email protected]; [email protected] Muhammad Farooq Ahmad f[email protected] Nihat Aktas [email protected] Guosong Xu [email protected] 1 SKEMA Business School, Université Côte d’Azur, Lille, France 2 WHU Otto Beisheim School ofManagement, Vallendar, Germany 3 DeSantis Distinguished Professor College ofBusiness, Florida Atlantic University, BocaRaton, USA 4 Birmingham Business School, University ofBirmingham, Birmingham, UK 5 Rotterdam School ofManagement, Erasmus University, Rotterdam, TheNetherlands 1 See, e.g., Jensen (1986), Lang et al. (1991), John and Senbet (1998), Masulis etal. (2007), and Tosun and Senbet (2020). 617Journal of International Business Studies (2024) 55:616–637 synergetic gains between target and acquirer shareholders. It thus is theoretically ambiguous, ex ante, which transacting party (acquirer or target shareholders) obtain a greater share of acquisition gains after reforms. On the one hand, board reforms may bolster the bargaining power of the target firm, particularly when it is managed efficiently. The resulting increase in target value and bargaining power implies that target shareholders benefit from a greater share of the takeover gain. On the other hand, according to the theory of private benefits of control (Dyck & Zingales, 2004; Grossman & Hart, 1988), if the controlling shareholders in the target firm lose their private benefit of control over corporate resources, the value of their potential rent extraction decreases, which could lower the reservation price for target controlling shareholders during a corporate sale.2 In that scenario, acquirer firms could gain a greater share of the deal synergies, in that they pay a lower premium in the transaction (i.e., less the amount of the benefit loss to target controlling shareholders). These competing hypotheses imply that the net effect of wealth redistribution in post-reform M&As depends on whether the decrease in target controlling shareholders’ private benefits outweighs the increase in the target value. To test these hypotheses empirically, we investigate a comprehensive set of board-related corporate governance reforms across 61 countries during 1985–2021. With a sample including both domestic and cross-border M&A deals, we document several key findings. First, target shareholders experience a significant decrease in merger gains after the reform. The economic magnitude is substantial: Over a 7-day window, target shareholders’ announcement return (Target CAR ) is 5% lower in the post-reform period. In contrast, acquirers’ abnormal returns (Acquirer CAR ) following merger announcements are 0.6% higher after the reforms come into effect in the target country. These results, obtained with quasi difference-in-differences (DiD) regressions that control for an extensive set of firm, deal, and country characteristics and fixed effects, suggest that board reforms trigger a drastic redistribution of wealth from target shareholders to acquirer shareholders. Consistent with the theory of private benefits of control, we determine that the effect on wealth redistribution is driven mainly by transactions that involve sales of block shares. Second, deal-level abnormal returns (Combined CAR ) are 1.9% higher in the post-reform period. With Combined CAR , we capture expected takeover synergies, and the result confirms the hypothesis that board reforms improve overall economic gains in M&As. Substantial literature in international business and finance establishes that country-level institutional quality and legal protection of investors affect the value of each nation’s capital markets (La Porta etal., 1997, 1998, 2000, 2002). In our research context, heterogeneity in country-level legal characteristics might influence the effectiveness of the board reforms in M&A deals. Using various measures of institutional quality and shareholder protection, we establish that better quality institutions and high investor protection reinforce the effects of board reforms on target returns. This result suggests that firm-level governance reforms are more effective in countries where legal protections are stronger. Our research contributes to investigations of the role of corporate boards in takeovers. Most studies examine the effect on acquirers and find that corporate governance is a fundamental mechanism that drives M&A profitability (e.g., Dahya etal., 2019; Masulis etal., 2007). Establishing causality remains challenging though. Using board reforms as an exogenous shock to corporate governance practices, this study sheds new light on the research domain by documenting a causal link between board oversight and merger performance. We also expand research into the direct impact of country characteristics on financial markets. As initiated by La Porta etal. (1997), an ongoing literature stream has established that legal protections of external investors affect firm value and corporate actions, such as stock liquidity (Huang etal., 2020), initial public offerings (Boulton etal., 2010), innovation (Hillier etal., 2011), and cross-listings (Diniz-Maganini etal., 2023). We build on such insights to link country-level legal characteristics to firm-level takeover outcomes across a large sample of M&As from 61 countries; as such, we also add to growing international business and M&A literature (e.g., Ahern etal., 2015; Alimov, 2015; Bhagwat etal., 2021; Brockman etal., 2013; Cannon etal., 2020; Dessaint etal., 2017; Glendening etal., 2016; Zhou etal., 2016). Theory andhypotheses Board reforms andcorporate outcomes Since 1990, various reforms designed to strengthen corporate board functions have been implemented across the world. Although the details differ, the key goal of these reforms is to increase the oversight of board directors by promoting board independence and the separation of the chair from the CEO. Research in turn has established that corporate board reforms increase firm value (Fauver etal., 2017) and firm profitability during initial public offerings (Chen etal., 2022). Bae etal. (2021) reveal that firms pay higher dividends once reforms have empowered board directors and shareholders, and similarly, Chen etal. (2020) show 2 In their study across 39 countries, Dyck and Zingales (2004) estimate the average value of private control to be 14% of the firm equity value. 618 Journal of International Business Studies (2024) 55:616–637 that managers reduce corporate cash holdings and increase R&D after reforms. According to Hu etal. (2020), board reforms are associated with reductions in stock price crash risks. Finally, Driss (2022) documents improvements in investment–stock price sensitivity. In summary, extant studies offer consistent, convincing evidence that board reforms improve corporate governance practices that eventually enhance shareholder value. Unlike these prior studies though, we explore a distinct value creation channel, namely, that due to corporate takeovers. Our findings–that reform-induced M&A synergies mainly accrue to acquirer shareholders rather than target shareholders–also differ from previous M&A literature that suggests the benefits of value creation mainly benefit target shareholders and that most acquirers of listed targets barely break even or experience negative returns (e.g., Fuller etal., 2002; Moeller etal., 2004). We explore the reasons for these differences hereafter. Corporate governance, bid competition, andM&A performance Corporate governance is a key determinant of M&A performance for acquirer and target shareholders (Dahya etal., 2019; Masulis etal., 2007). To the extent that corporate governance improves due to better board oversight in the target firm, board reforms in the target country should enhance overall takeover value, including greater economic synergies at the deal level. This increase in takeover value stems from two sources. First, better governed targets offer greater growth potential (Gompers etal., 2003) and a more transparent informational environment (Durnev etal., 2009; Sugathan & George, 2015), so the acquirer can more readily identify sources of synergetic gains.3 Second, strengthened board oversight may decrease the private benefits of control in some target firms. Following these arguments, we propose: Hypothesis 1 Overall M&A value and deal synergies increase after a board reform is implemented in the target country. Moreover, board reforms could affect the distribution of transaction gains between the acquirer and target shareholders. However, it is unclear ex ante which transaction party benefits more from the value redistribution induced by these reforms. If board reforms simultaneously enhance the target firm’s value and strengthen the target’s bargaining power, targets likely bargain for greater value from the acquisition. Meanwhile, acquirers in the post-reform era may experience lower (or comparable) returns, relative to the pre-reform period. In other words, board reforms may tilt the balance of bargaining power in favor of targets, allowing them to capture a larger share of the “acquisition pie.” This hypothesis gives rise to the following predictions: Hypothesis 2 M&A targets receive higher value (stock returns), while acquirers receive lower or comparable value, after a board reform is implemented in the target country, compared with before the reform. Yet existing literature also shows that agency issues (i.e., conflicts of interest between managers and shareholders and between controlling and minority shareholders) are prevalent in some merger negotiations (e.g., Fich etal., 2011; Hartzell etal., 2004). The private value of control is so substantial for some shareholders that they demand significant transaction premia when they negotiate a sale of their controlling block of shares (Dyck & Zingales, 2004). According to the theory of private benefits of control, when controlling target shareholders lose their private benefits due to board reforms, their reservation price decreases, so the M&A premium should decrease following board reforms.4 This alternative hypothesis, which we term the private benefits hypothesis, predicts a significant wealth transfer from target shareholders to acquirer shareholders in the post-reform period: Hypothesis 3 M&A targets receive lower value (stock returns), while acquirers receive higher value, after a board reform is implemented in the target country, compared with before the reform. Thus, whether post-reform M&A value accrues more to the acquirer or target shareholders is an empirical question. The net effect of such wealth redistribution depends on whether the drop in target controlling shareholders’ private benefits outweighs the improvement in the target value after the board reform. We explore this question. In addition, with regard to the value effect, substantial international business and finance research posits that the effectiveness of reforms 3 A more transparent informational environment would allow bidders to identify access to new products, services, technologies, and efficient management teams more readily, which are important sources of synergies (Aktas etal., 2021). 4 Theoretically, the decrease in target shareholders’ reservation price and the deal premium could be greater in a hostile bid scenario, in which the bidder speaks directly to shareholders. However, we would expect the same effect in a friendly merger negotiation because the target board – representing the controlling shareholders – has less bargaining power after the reform deprives shareholders of their private benefits. Because hostile takeovers are almost completely absent from our sample (Schwert, 2000), we do not distinguish between hostile and friendly takeovers for our empirical tests. 619Journal of International Business Studies (2024) 55:616–637 relies on the institutional quality and country-level legal protections available to external investors (e.g., La Porta etal., 1997, 1998, 2000, 2002). According to this view, enhanced institutional quality or shareholder protection increases the effects of firm-level corporate governance. Therefore, we also study the heterogeneity of reform effects in our empirical analyses. Data andsummary statistics Board reforms aroundtheworld We start with all countries that implemented major board reforms during 1985–2021. This initial sample of countries comes from Fauver etal. (2017), who use various data sources to identify these board reforms, including the World Bank, the European Corporate Governance Institute, and prior research (e.g., Kim & Lu, 2013).5 Because the last board reform in their sample took place in 2007, we expanded it by manually identifying additional major reforms using the criteria applied by Fauver etal. (2017). The updated list of board reforms expands to 61 countries; the latest reform was implemented in 2016. Most reforms involve board independence, audit committee and auditor independence, and CEO/chair separation.6 We report the reform year, reform components, and reform type for each country in Panel A of Table1. Countries implement board reforms for various reasons, but the ultimate motivation is to enhance corporate governance mechanisms that constitute an “important element in strengthening the foundation for individual countries’ long-term economic performance and in contributing to a strengthened international financial system.”7 Anecdotal evidence suggests that boardroom reforms tend to occur after major corporate frauds and scandals. For example, the Enron and WorldCom scandals in the United States accelerated adoption of the 2002 Sarbanes–Oxley Act. The Parmalat scandals in Italy led to the institution of the Corporate Governance Code by the Borsa Itialiana.8 Our identification strategy leverages the assumption that such reforms are exogenous to individual firms, which seems likely, in that individual firms cannot determine the exact timing or outcomes of a nationwide reform implementation (e.g., Bae etal., 2021; Chen etal., 2020, 2022; Driss, 2022; Fauver etal., 2017). However, board reforms could correlate with a country’s economic prospects or institutional quality, such that they would be endogenous to these country-level variables. To address this concern, in Panel B of Table1, we include economic and institutional determinants, such as GDP growth, GDP per capita, economic size, stock market development, and quality of institutions, and we check whether they predict board reforms in our sample. The regression results indicate that none of these factors significantly correlates with the timing of the board reforms, confirming our sense that the reforms are plausibly exogenous.9 Sample ofM&As We gather M&A transactions from the Refinitiv SDC database. For each of the 61 sample countries, we extract all domestic transactions and cross-border M&A deals involving acquirer and target firms from our sample countries. The M&A sample starts in 1985 and ends in 2021, 5years after the last board reform. We drop M&A transactions for which the status of the bidders or target firms is a government agency, joint ventures, or mutual funds, as well as those for which the acquisition form is buyback, exchange offers, or recapitalization. We also remove financial targets (standard industrial classification [SIC] codes 6000–6999). These data filters yield a sample of 607,293 deals across the 37-year sample period, with a total deal value of approximately $50 trillion. In columns 6 and 7 of Table1, Panel A, we find that, in terms of aggregate M&A number and deal value, the most active target countries are the United States and United Kingdom. In Fig.1, we present the volume of M&A transactions by year; in terms of M&A deal number, a first peak occurs around 1999 and 2000, coinciding with the dotcom bubble. The second wave of M&A activities appears around 2006 and 2007, just before the global financial crisis, followed by another surge in deals during the last 2years of our sample period. We find a similar pattern for M&A activity measured by deal value. These patterns signal that M&As occur in waves at the aggregate level, in both domestic and cross-border contexts (e.g., Ahmad etal., 2021; Harford, 2005; Maksimovic etal., 2013). 5 Fauver etal. (2017) provide a detailed description of the reforms implemented in each country in their “Appendix1”. 6 Reforms in five countries focus on other aspects of board practices, such as definitions of board responsibilities, elections of board members, and board disclosures: Brazil, Colombia, Czech Republic, Hungary, and Switzerland. We keep these countries in our sample for completeness, like in Fauver etal. (2017). We do not find any countries that introduce reforms that weaken corporate governance mechanisms. 7 See the statements from the 2009 Latin American Corporate Governance Roundtable. 8 For a discussion of the rationales for some board reforms, see Rockness and Rockness (2005). 9 In our robustness tests, we track the dynamic effects of board reforms to confirm their exogeneity. 620 Journal of International Business Studies (2024) 55:616–637 Table 1 Sample description Country Reform year Reform component Reform type Number of deals Deal value A B C 1 2 3 4 5 6 7 Panel A. Reform country and sample distribution Argentina 2001 0 1 0 Rule-based 1811 75.60 Australia 2004 1 1 1 Comply-or-explain 21,443 1236.24 Austria 2004 1 1 0 Comply-or-explain 2563 88.08 Belgium 2005 1 1 1 Comply-or-explain 4591 258.53 Brazil 2002 0 0 0 Rule-based 7136 549.53 Bulgaria 2007 1 1 1 Comply-or-explain 600 19.79 Canada 2004 1 1 1 Rule-based 28,841 1821.98 Chile 2001 0 1 0 Rule-based 1355 81.49 China 2001 1 1 0 Rule-based 18,619 1860.32 Colombia 2001 0 0 0 Rule-based 936 53.79 Croatia 2007 1 0 1 Comply-or-explain 438 10.78 Cyprus 2002 1 1 1 Comply-or-explain 418 21.98 Czech Rep. 2001 0 0 0 Rule-based 2334 58.94 Denmark 2001 1 0 0 Comply-or-explain 5243 223.09 Egypt 2002 1 1 0 Rule-based 449 49.29 Finland 2004 1 1 1 Comply-or-explain 6001 188.42 France 2003 0 1 0 Rule-based 26,822 1390.59 Germany 2002 1 1 0 Comply-or-explain 27,717 1530.76 Greece 2002 1 1 0 Rule-based 969 87.85 Hong Kong 2005 1 1 1 Comply-or-explain 5239 509.21 Hungary 2003 0 0 0 Comply-or-explain 1340 26.19 Iceland 2004 1 1 1 Comply-or-explain 174 16.22 India 2002 1 1 0 Rule-based 6070 257.56 Indonesia 2007 1 1 0 Rule-based 1622 78.43 Ireland 1995 1 1 1 Comply-or-explain 3094 295.10 Israel 2000 1 1 1 Rule-based 1372 157.63 Italy 2006 1 1 0 Rule-based 11,960 963.51 Japan 2002 0 1 0 Rule-based 22,300 1222.43 Kazakhstan 2005 1 0 0 Comply-or-explain 236 19.64 Kenya 1999 1 1 1 Comply-or-explain 177 5.17 Kuwait 2010 1 1 1 Comply-or-explain 145 17.71 Luxembourg 2007 1 1 1 Comply-or-explain 653 149.74 Malaysia 2001 1 1 0 Comply-or-explain 7393 155.99 Mexico 2001 1 1 0 Rule-based 2409 259.94 Netherlands 2004 1 1 1 Comply-or-explain 10,799 944.98 New Zealand 2004 1 1 1 Comply-or-explain 3559 99.44 Nigeria 2003 1 1 1 Comply-or-explain 259 26.00 Norway 2005 1 1 1 Comply-or-explain 5312 286.96 Pakistan 2002 0 1 0 Comply-or-explain 150 7.93 Peru 2005 1 1 0 Comply-or-explain 867 32.30 Philippines 2002 1 1 0 Comply-or-explain 1017 45.25 Poland 2002 1 0 0 Comply-or-explain 3623 118.90 Romania 2001 1 0 0 Comply-or-explain 1038 17.81 Russia 2002 1 0 1 Comply-or-explain 9797 268.76 Saudi Arabia 2006 1 1 1 Comply-or-explain 293 107.72 621Journal of International Business Studies (2024) 55:616–637 Panel A presents the distribution of the M&A sample by target country. The M&A sample, covering the 1985–2021 period, is from Thomson Reuters SDC database and includes domestic and cross-border deals completed by acquirers and targets from the 61 countries for which major board reform data is available. For each country, we report the reform year in column 1, the reform component in columns 2–4, the reform type in column 5, the number of deals in column 6 and the aggregate deal value (in US$ billions) in column 7. Reform component A, B, and C are binary variables identifying board reforms related to board independence, audit committee independence, and chairman and CEO separation, respectively. Panel B reports the regression analysis of reform determinants. The dependent variable is a binary variable that equals one if a major board reform is effective in a given target country in a given year, and zero otherwise. All the macroeconomic factors are defined in “Appendix1”. P values are reported within parentheses below the coefficient estimates. Robust standard errors are clustered at the country level Table 1 (continued) Country Reform year Reform component Reform type Number of deals Deal value A B C 1 2 3 4 5 6 7 Singapore 2003 1 1 0 Comply-or-explain 3983 319.18 Slovakia 2002 1 1 1 Comply-or-explain 409 3.67 South Africa 2002 1 1 1 Comply-or-explain 3584 207.71 South Korea 1999 1 1 0 Rule-based 5683 566.38 Spain 2006 1 1 0 Comply-or-explain 13,350 635.27 Sweden 2006 1 1 1 Comply-or-explain 11,437 593.87 Switzerland 2002 0 0 0 Comply-or-explain 6488 730.75 Taiwan 2002 1 1 0 Rule-based 1153 123.88 Thailand 2002 1 1 0 Comply-or-explain 1293 77.66 Tunisia 2008 1 1 1 Comply-or-explain 115 1.81 Turkey 2002 1 0 1 Comply-or-explain 1710 100.17 UAE 2016 1 1 0 Rule-based 765 58.68 Ukraine 2003 1 0 1 Comply-or-explain 1029 21.53 UK 1998 1 1 1 Comply-or-explain 65,899 4274.40 US 2003 1 1 0 Rule-based 229,347 26395.73 Total 607,293 49,892.63 Board reform Within country Cross country 1 2 Panel B. Determinants of board reforms GDP growth − 0.002 − 0.004 (0.465) (0.370) Per-capita GDP 0.011 − 0.003 (0.927) (0.919) GDP 0.002 0.012 (0.984) (0.167) Stock market development 0.002 0.011 (0.926) (0.340) Investment profile 0.002 0.006 (0.753) (0.433) Quality of institutions − 0.011 − 0.005 (0.409) (0.597) Year FE Yes Yes Country FE Yes No Adjusted R20.840 0.793 Observations 1494 1494 622 Journal of International Business Studies (2024) 55:616–637 We rely on various data sources to construct the deal-, firm-, and country-level variables for our empirical analyses. Unless explicitly mentioned otherwise, SDC is the data source for deal-related variables; CRSP, Worldscope, and Compustat Global inform the firm-level variables; and the World Bank and International Country Risk Guide (ICRG) provide the country-level variables. All values are converted into U.S. dollars, if applicable. The dependent variables in our empirical analyses are takeover gains measured by cumulative abnormal returns (CAR) at the target, acquirer, and deal levels. In the main analysis, we compute announcement CAR over a 7-day event window around the announcement day, as in Dessaint etal. (2017). In robustness checks, we also report results with 3-day and 11-day alternative event windows. To compute the abnormal return, we use a market model with parameters estimated over the estimation period (− 236, − 36) relative to the announcement day; the local market index is a proxy for the market portfolio.10 Table2 presents the summary statistics for all the variables in our main analyses;11 “Appendix1” provides their detailed definitions. According to Table2, the average Target CAR is 22.2%, and the average acquirer CAR is 1.2% for the full sample, including both private and listed targets. For the sample of only listed targets, the average acquirer CAR is negative and equal to − 1.0%. In this subsample, the positive Combined CAR (2.1%) indicates that the sample deals are synergy-driven on average.12 These statistics are consistent with prior international M&A literature (e.g., Dessaint etal., 2017). The average Offer Premium is 42.2%, consistent with the offer premium of 42% reported by Rossi and Volpin (2004) for an international sample and with the premium of 46% observed in a U.S. sample by Eckbo (2009). We also tabulate country-industry-year-level M&A activities (see Table2), which compare favorably to the deal activities reported by Bargeron etal. (2008) for a sample of domestic U.S. transactions involving listed targets. With regard to deal characteristics, such as the proportion of cross-border deals, horizontal deals, hostile deals, and cash-only payments, our sample also is comparable to prior research that relies on international M&A data (e.g., Alimov, 2015; Dessaint etal., 2017; Rossi & Volpin, 2004). The proportion of vertical deals in our sample is 13.6%.13 For a sample of U.S. deals among listed companies, Kedia etal. (2011) report that the proportion of vertical deals ranges between 9.88 and 21.28%, depending on the industry classification applied. Fig. 1 Sample distribution by year. This figure plots the sample distribution by year. The M&A sample, covering the 1985–2021 period, is from Thomson Reuters SDC database and includes domestic and cross-border deals completed by acquirers and targets from the 61 countries for which major board reform data is available. The sample includes 607,293 deals across the 37-year sample period, totaling a deal value of $49,892.64 billion. The left axis refers to the number of deals, and the right axis to the aggregate deal value in US$ billion - 500 1,00 0 1,50 0 2,00 0 2,50 0 3,00 0 3,500 - 5,000 10,000 15,000 20,000 25,000 30,000 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005200720092011 2013 2015 201720192021 Number of Deals Deal Value (in US$ billions) 10 We use the local market index, because Aktas etal. (2004) document that CARs are not affected by the choice of the market index (local versus global equity market index), on average. Our choice is also consistent with prior international M&A literature that relies on the local equity market index to compute M&A announcement returns (Ahern et al., 2015; Bhagwat et al., 2021; Dessaint et al., 2017). See also El Ghoul etal. (2023) for a discussion of how to conduct event studies in international finance research. 11 To mitigate the influence of outliers, all firm-level variables are winsorized at the top and bottom 2.5% of the distribution. We obtain similar results if we use 1% as an alternative winsorization threshold (unreported). 12 Combined CAR is the market value-weighted CAR (of the acquirer and target), using the merging parties’ market capitalization 4weeks before the announcement as the weight. 13 We follow the approach in Kedia etal. (2011) to identify vertical deals (see variable definitions in “Appendix1”). 623Journal of International Business Studies (2024) 55:616–637 Empirical results Board reforms andM&A performance To investigate the impact of board reforms on M&A performance, we adopt a quasi-DiD method. Specifically, we compare the deal announcement returns for the treated firms (in a reform country) with those for the control firms. We estimate the following ordinary least squares (OLS) regression: where the dependent variable is the (acquirer or target) firm i’s CAR; Post Target is a dummy variable that equals 1 for M&As that occur in the post-reform period in target (1) CARi, [− 3, + 3 ] =𝛼+𝛽 ⋅ Post Targeti,t+𝐙i,t+𝜂y,j+𝜓c,j+𝜀i,t, countries affected by the reforms. In all regressions, we include granular industry-year fixed effects (ηy,j) and country-industry fixed effects (ψc,j). We define the industry at the two-digit SIC level. The fixed effects control for country–industry-specific and time-varying factors, such as industry-level M&A competition, that could affect deal returns. Next, Zi,t contains firm-, deal-, and country-level characteristics, such as acquirer size, relative deal size, return on assets, market-to-book value, hostile bid, cash-only deal, cross-border deal, number of bidders, acquirer country GDP, GDP per capita, GDP growth rate, market capitalization (as a percentage of GDP), real interest rate, investment profile, and the quality of institution index. We also control for horizontal and vertical deal types because they exert Table 2 Summary statistics This table provides the descriptive statistics of the variables used in our multivariate analyses. All the variables are defined in “Appendix1” Variable name Mean St. Dev. Q1 Median Q3N Dependent variables Target CAR 0.222 0.236 0.053 0.180 0.340 11,695 Offer premium 0.422 0.491 0.152 0.335 0.577 6186 Acquirer CAR 0.012 0.090 − 0.034 0.004 0.048 48,755 Target CAR, public acquirers 0.217 0.233 0.052 0.184 0.338 4310 Acquirer CAR, public targets − 0.010 0.093 − 0.064 − 0.011 0.036 4310 Combined CAR 0.021 0.090 − 0.031 0.016 0.067 4310 Number-based M&A activity Ln(1 + M&A Volume) 2.587 1.402 1.386 2.398 3.466 12,237 M&A intensity Fin. Acq. 0.120 0.166 0.000 0.066 0.188 12,237 Value-based M&A activity Ln(1 + M&A volume) 4.892 3.060 2.638 5.252 7.135 12,237 M&A intensity fin. acq. 0.123 0.255 0.000 0.000 0.093 12,237 Firm and deal characteristics Firm size 6.484 2.331 4.984 6.502 7.976 48,755 ROA 0.018 0.179 0.003 0.051 0.093 48,755 Market-to-book 0.027 0.024 0.014 0.022 0.030 48,755 Relative deal size 0.316 0.547 0.035 0.162 0.352 48,755 Cash only 0.284 0.451 0.000 0.000 1.000 48,755 Hostile 0.004 0.063 0.000 0.000 0.000 48,755 Cross-border 0.227 0.419 0.000 0.000 0.000 48,755 Number of bidders 1.016 0.146 1.000 1.000 1.000 48,755 Horizontal 0.566 0.496 0.000 1.000 1.000 48,755 Vertical 0.136 0.343 0.000 0.000 0.000 48,755 Country characteristics GDP 29.452 1.137 28.657 29.896 30.257 48,755 GDP per capita 10.498 0.571 10.400 10.618 10.791 48,755 GDP growth 2.882 2.047 2.011 2.783 4.077 48,755 Investment profile 4.747 0.333 4.638 4.841 4.967 48,755 Quality of institutions 3.668 3.152 1.590 3.069 6.324 48,755 Real interest rate 10.775 1.649 9.667 11.542 12.000 48,755 Stock market development 13.371 1.595 13.000 13.833 14.000 48,755 630 Journal of International Business Studies (2024) 55:616–637 overpayment ex post. As an alternative approach to test for increasing efficiency in deal making, we examine overpayment and report the results in column 2 of Table4, Panel D, using the acquirer’s cash holdings to proxy for the likelihood of overpayment. Harford etal. (2012) show empirically that acquirers with more cash holdings are more prone to overpayment in M&As. In a spirit similar to that established for column 1, we focus on the interaction term Post Target × Acquirer Cash Ratio. As column 2 in Panel D shows, abnormal returns to the targets acquired by a high cash bidder are significantly lower in the post-reform years than in the pre-reform period. This result further underscores reforminduced efficiency for deal making. Additional evidence: M&A volume inthepost‑reform period In this section, we investigate the economic impact of board reforms on aggregate M&A activities in the target country. The increase in deal synergies and acquirer gains following the reform might lead to a more active takeover market, but because target shareholders have less to gain from takeovers after the reform, they also may be less likely to sell. Therefore, the net impact of board reforms on aggregate M&A activities remains unclear ex ante. By studying this question, we gain insights into the macro-level effects of board reforms on the country-level M&A landscape. To inform this discussion, we run regressions based on Eq.(1) but replace the dependent variable with target country M&A Volume, measured by deal number or transaction value completed for an industry-country-year.21 We control for country characteristics, as well as industry-year and country-industry fixed effects. Table5 presents the results. We start with overall M&A activities. Columns 1 and 2 in Table5 show that the aggregate M&A deal number or value Table 5 Board Reforms and M&A activity This table presents OLS regression results examining the effect of board reforms on M&A activity in number-based (columns 1 and 3) and value-based (columns 2 and 4). In columns 1–2, the dependent variable is M&A Volume (i.e., aggregate M&A activity in industry-target country, where the industry is defined as Fama-French 12-industry). In columns 3–4, the dependent variable measures the M&A intensity by financial acquirers. Post Target is a binary variable equal to one starting the year in which the board reform becomes effective in the target country. The inclusion of fixed effects (FEs) is indicated at the bottom of the table. Variable definitions are in “Appendix1”. P values are reported within parentheses below the coefficient estimates. Robust standard errors are clustered at the country level M&A volume M&A intensity financial acquirers Number-based Value-based Number-based Value-based 1 2 3 4 Post target 0.039 − 0.096 − 0.023 − 0.040 (0.367) (0.314) (0.008) (0.006) GDP − 0.286 − 0.155 − 0.124 − 0.118 (0.527) (0.850) (0.011) (0.019) GDP per capita 0.732 1.281 0.105 0.120 (0.139) (0.188) (0.034) (0.024) GDP growth 0.010 0.032 0.000 0.000 (0.058) (0.003) (0.681) (0.959) Stock market dev. 0.025 0.090 − 0.004 0.000 (0.265) (0.004) (0.123) (0.946) Real interest rate 0.002 0.011 0.000 0.000 (0.418) (0.006) (0.926) (0.199) Investment profile − 0.011 0.033 0.002 0.005 (0.637) (0.322) (0.391) (0.020) Quality of institutions 0.029 0.000 0.002 − 0.001 (0.288) (0.993) (0.548) (0.807) Year × Industry FE Yes Yes Yes Yes Country × Industry FE Yes Yes Yes Yes Adjusted R20.887 0.611 0.223 0.101 Observations 12,237 12,237 12,237 12,237 21 Following Dessaint etal. (2017), we measure M&A deal volume at the country-industry level, where industry is classified according to the Fama-French 12 industries. 631Journal of International Business Studies (2024) 55:616–637 Table 6 Additional results and robustness checks [− 5, + 5] year Window Excluding US acquirers Excluding UK acquirers Excluding Canadian Acq. 1 2 3 4 Panel A. Subsample analyses Post target − 0.033 − 0.058 − 0.036 − 0.063 (0.086) (0.041) (0.005) (0.000) Controls Yes Yes Yes Yes Year × Industry FE Yes Yes Yes Yes Country × Industry FE Yes Yes Yes Yes Adjusted R20.104 0.082 0.123 0.117 Observations 4877 4866 10,260 10,412 Acquisition of 100% stake Including withdrawn deals 1 2 Panel B. Different M&A data screens Post target − 0.061 − 0.032 (0.000) (0.011) Controls Yes Yes Year × Industry FE Yes Yes Country × Industry FE Yes Yes Adjusted R20.125 0.132 Number of observations 7269 12,642 3-day CARs 11-day CARs 1 2 Panel C. Alternative event window CARs Post target − 0.055 − 0.048 (0.000) (0.000) Controls Yes Yes Year × Industry FE Yes Yes Country × Industry FE Yes Yes Adjusted R20.104 0.111 Observations 11,695 11,695 Propensity score matching Placebo reform years Dynamic model Stacked DiD regression 1 2 3 4 Panel D. Propensity score matching, placebo test, dynamic model, and stacked DD regression Post Target − 0.039 0.000 − 0.041 (0.047) (0.972) (0.082) Year 1 before reform 0.006 (0.807) Year 2 before reform 0.034 (0.105) Year of reform − 0.028 (0.146) Year 1 after reform − 0.053 (0.009) 632 Journal of International Business Studies (2024) 55:616–637 remains unchanged following a board reform. Therefore, it appears that the two opposing forces (i.e., more acquirer gains and less willingness to sell due to better managed companies following reforms) cancel each other out, leading to a negligible net effect on M&A volume at the aggregate level. However, as we have argued previously, financial bidders likely get (partially) “squeezed out” of the takeover market, because the board reform deprives them of an importance source of M&A gains, namely, the improvement in the target firm’s corporate governance. We confirm this conjecture with the results in columns 3 and 4 of Table5, which show that both the number and value of deals completed by financial acquirers drop significantly after the reforms are in place. Robustness checks In this section and Table6, we report on a battery of robustness checks. First, to mitigate concerns about confounding events, we restrict our sample period to 5years before and after the reform. As column 1 of Panel A shows, the coefficient estimate of Post Target is negative and statistically significant at the 10% level. The economic effect is comparable to our main findings, as reported in Table3. Second, legal origins arguably might explain the effects of corporate governance reforms. In particular, our results might be driven by common law countries with a more developed capital market (La Porta etal., 1997). We examine this possibility by removing three largest common law countries in our sample, namely, United States, United Kingdom, and Canada. These countries also represent the most active M&A markets during our sample period. In Panel A of Table6, we affirm that the findings of lower target CAR in the post-reform period are not driven by these countries though; the effects remain statistically significant when we exclude M&As in these regions (columns 2–4). The economic magnitude of the reform effect is also similar in these subsample analyses. Third, we check if our results might be sensitive to the screening criteria. For example, our results might be driven by partial acquisitions or a sample selection bias due to our inclusion of only completed deals. Panel B of Table6 features only 100%-stake deals; its column 1 shows that the effects of board reforms are similar to the baseline results. In column 2, we include withdrawn transactions in the analysis. The results again remain robust. Fourth, we examine some alternative announcement return windows. Specifically, we use [− 1, + 1] and [− 5, + 5] event windows, centered around the deal announcement. We continue to find a negative association between board reforms and target returns (Panel D, Table6). Fifth, an important assumption of the DiD analysis is that the treated and control groups would follow parallel trends in the absence of the reform. Therefore, prior to the This table presents the coefficient estimates of OLS regressions examining the effect of board reforms on Target CAR . In all models, Target CAR is computed over a 7-day event window around the announcement date (except in Panel C). Panel A reports various subsample analyses. Column 1 limits the sample to deals announced over the [− 5, + 5] year window relative to the board reform year. The remaining three columns present the results after excluding the three most active M&A markets respectively. Panel B reports the results with alternative M&A data filters. Column 1 considers completed deals involving the acquisition of 100% stake in the target, and column 2 augments the sample with withdrawn deals. Panel C replicates the main results with Target CAR calculated over a 5-day (column 1) and 11-day (column 2) event windows. Panel D reports the estimation results of the propensity-score matching approach (column 1), the model with placebo reform years (column 2), the dynamic model (column 3), and the stacked DiD regression (column 4). Post Target is a binary variable equal to one starting the year in which the board reform becomes effective in the target country. Each model includes the same set of controls and fixed effects (FEs) as in Table3, whose coefficients are untabulated for brevity. Variable definitions are in “Appendix1”. P values are reported within parentheses below the coefficient estimates. Robust standard errors are clustered at the country level. Table 6 (continued) Propensity score matching Placebo reform years Dynamic model Stacked DiD regression 1 2 3 4 Year 2 after reform − 0.039 (0.014) Years 3 and plus after reform − 0.061 (0.000) Controls Yes Yes Yes Yes Year × Industry FE Yes Yes Yes Yes Country × Industry FE Yes Yes Yes Yes Adjusted R20.139 0.114 0.110 0.087 Observations 6679 11,695 11,695 4605 633Journal of International Business Studies (2024) 55:616–637 reform, we should not find differences in returns between treated and control firms. We adopt three strategies to test whether this parallel trends assumption holds. With propensity score matching (PSM), we create a matched sample in a Probit model22 and thereby compare the treated and control firms with similar observable characteristics. “Appendix2” reports the differences in means across samples before and after matching. In column 1 of Panel D, we use the PSM sample to run our baseline regression; the effect of board reforms remains highly significant. Then we check for parallel trends by running a placebo test, in which we randomly assign the reform year to countries and re-estimate the baseline model. As expected, the placebo estimate of Post Target is not statistically significant (column 2, Panel D). Finally, we check the dynamic effect of the reforms by expanding the statistical specification in Eq.(1), using a set of indicator variables that track reform effects from 2years before until four or more years after the reform (similar to Fauver etal., 2017). In column 3, we see that prior to the reform, target returns are similar in the treated and control countries, confirming the parallel trends. The effects of the reforms are significant only 1year after the reforms are first implemented. This evidence bolsters our confidence about using reforms as valid exogenous shocks to corporate governance that enable us to examine M&A performance. Sixth, we address another concern related to the staggered DiD analysis. Staggered DiD regressions may produce biased estimates of the average treatment effect (ATE) with typical two-way fixed effects (e.g., Callaway & Sant’Anna, 2021; Sun & Abraham, 2021), because for these varianceweighted averages, some weights might be negative. The later-treated observations could act as control units before the treatment; the earlier-treated groups can serve as controls after the treatment. To deal with this concern, we follow a remedy suggested by Baker, Larcker and Wang (2022) and Cengiz, Dube, Lindner and Zipperer (2019) and create cohort-specific data sets that include target firms from a reform country (treated targets) and all M&A targets that do not experience a reform within [− 5, + 5] years around the reform year (i.e., “clean” controls).23 After stacking all the event-specific data sets in relative time, we perform the DiD estimation on these stacked data (column 4, Panel D, Table6). The stacked DiD estimate remains statistically significant, with an economic magnitude close to that of the baseline treatment effect (Table3). Therefore, our baseline findings appear unlikely to be biased by the heterogenous treatment effects identified in prior work. Conclusions Do improvements to corporate board functions affect M&A returns? We investigate this question using board reforms across 61 countries during 1985–2021. Our quasi-DiD regressions indicate that, following the reforms in a target country, acquirers’ announcement returns increase, while target returns decrease. That is, board reforms trigger a significant wealth redistribution between acquirer and target shareholders. Moreover, deal-level announcement returns increase following the reform, suggesting that board reforms improve overall transaction synergies. As we show, reforminduced reductions in the private benefits of control over the target firm resources can explain these results, in that the main findings are driven by target firms owned by large block holders. Exploring country-level heterogeneity in institutional quality and shareholder protection, we also find that the value effects of the board reforms are more pronounced in countries where legal protection of external investors is stronger. Therefore, country-level shareholder protection reinforces the effectiveness of firm-level board reforms. Moreover, after the board reforms, financial bidders participate relatively less in the takeover market, suggesting that these reforms change the composition of the acquirer pool. Among all the reforms, those implemented under a complyor-explain approach deliver the most noticeable effects. These results are informative for researchers, practitioners, and policymakers that seek to understand the role of board practices in M&A dynamics and outcomes. Corporate board reforms have been prominent in the policy agendas of several emerging markets (Ararat etal., 2021). Our findings suggest that such reforms may influence cross-border deal flows, takeover negotiations, and, ultimately, shareholder wealth in these countries. In addition to its relevance for policymaking, our study offers crucial insights for businesses, such as multinational enterprises seeking expansion through overseas takeovers. The success of their M&A strategy critically depends on the timing of the target country’s board reforms and existing legal protections in that destination country. Moreover, the impact of board reforms on firm behaviors likely expand to contexts beyond M&A, such as foreign-market entry modes and foreign direct investment. We leave the exploration of these topics to further research. 22 The dependent variable equals 1 if the target firm is acquired after the introduction of board reform (treated) and 0 if before the reform (control). The control variables are all firm and deal characteristics from column 1 in Table3. We match each treated firm with the control with the closest score to the treated firm. We also require that the maximum difference between the propensity score of each treated firm and the control firm does not exceed 0.1% in absolute value. 23 We repeat this exercise with the [− 3; + 3] year window around the reform year, and the results remain unchanged (unreported). 634 Journal of International Business Studies (2024) 55:616–637 Appendix1: Variable definitions Dependent variables Target CAR : Cumulative abnormal return for the target firm over the 7-day event window (− 3, + 3) around the announcement date. In robustness checks, 3-day and 11-day windows are also used as alternative event windows. The abnormal return is computed using a market model with parameters estimated over the estimation period (− 236, − 36) with respect to the announcement day. The value weighted index for US firms is obtained from CRSP, while for other countries local indices are retrieved from Worldscope. Offer premium: Final offer price relative to target market price 4weeks prior to M&A announcement. Acquirer CAR : Cumulative abnormal return for the acquiring firm over the 7-day event window (− 3, + 3) around the announcement date. In robustness checks, 3-day and 7-day windows are also used as alternative event windows. Combined CAR : The value weighted 7-day CAR of acquirer and target firms whereas the weights are based on market value of each firm 4weeks prior to the announcement date. It is calculated over a 7-day window around the announcement date. In robustness checks, 3-day and 7-day windows are also used as alternative event windows. M&A volume: Variable measuring the yearly aggregate M&A activity in a given industry-target country, either in number of deals or in value (million US$). The adopted industry definition is the Fama-French (FF) 12-industry classification. The regressions use the logarithm of one plus the corresponding variable. M&A intensity financial acquirers: Variable measuring the intensity of financial acquirers’ M&A activity. It corresponds to the aggregate M&A activity by financial acquirers divided by the aggregate M&A activity in the same industry-target country in that year. The aggregate M&A activity is either measured in number or in value (million US$). Independent variables ofinterest Post Target (Acquirer): Binary variable that equals the value of one beginning in a fiscal year when major board reforms became effective in a given target (acquirer) country, and zero otherwise. Firm characteristics Blockholder: It identifies target firms with strategic block owners, relying on ownership data from Orbis. Two variables are constructed: Number, which counts the number of block holders with ownership greater than 5% (or 20%), and a dummy variable, which identifies target firms with at least one block holder in a given year. Cash ratio: It is calculated as cash and short-term investments divided by the book value of total assets. Financial acquirer: Binary variable that equals the value of one if the acquirer is a financial firm as defined in SDC, and zero otherwise. Firm size: The natural logarithm of the firm’s market value of equity 4weeks prior to the announcement date (in $ million). Market-to-Book: It is calculated as the market value of common equity divided by the book value of common equity and divided by 100. ROA: It is calculated as EBITDA divided by the book value of total assets. Deal characteristics Cash only: Binary variable that takes the value of one if the method of payment is fully cash, and zero otherwise. Cross-border: Binary variable that takes the value of one if the target and the acquirer are from different countries, and zero otherwise. Horizontal: Binary variable that takes the value of one if the target and the acquirer are from the same two-digit SIC industries, and zero otherwise. Hostile: Binary variable that takes the value of one if the deal attitude is classified as hostile in SDC, and zero otherwise. Number of bidders: Variable that measures the degree of public competition, corresponding to the number of bidders reported in SDC. The regressions use the logarithm of the corresponding variable. Relative deal size: The ratio of deal value to the market capitalization of the target firm 4 weeks prior to the announcement date. Vertical: Binary variable that identifies vertical deals following the approach in Kedia etal. (2011). To that end, we estimate the vertical coefficient variable using the industry commodity flow information in the use table of benchmark input–output (IO) Accounts for the US Economy collected by the Bureau of Economic Analysis. For a given deal, we use the IO table corresponding to the year of the deal announcement. The variable takes the value of one if the vertical coefficient is higher than the 1% cutoff point. Country characteristics Accounting standards: Disclosure Quality index created by the Center for International Financial Analysis and Research to rate the quality of 1990 annual reports on their disclosure of accounting information. We use a dummy variable equal to one if the Disclosure Quality index for the target country 635Journal of International Business Studies (2024) 55:616–637 is above median, and zero otherwise (Source: La Porta etal., 2000). Investment profile: Time-varying index measuring the government’s attitude towards investment in the bidder (target) country. The investment profile is determined by summing the three following components: (1) risk of expropriation or contract viability; (2) payment delays; and (3) repatriation of profits. Each component is scored on a scale from 0, very high risk, to 4, very low risk. The index is coded in such a way that a higher score identifies countries with better investment profile, and vice versa (Source: International Country Risk Guide). GDP: The natural logarithm of the country’s gross domestic product. GDP per capita: Per-capita gross domestic product in US$. We use the log transform of the variable. GDP growth: The annual growth rate of gross domestic product. Quality of institutions: Time-varying index measuring institutional quality of a country, which is calculated by summing the following three components: (1) corruption; (2) law and order; and (3) bureaucratic quality. The index is coded in such a way that high score identifies countries with better institutional quality (Source: International Country Risk Guide). Real interest rate: The corresponding country’s real interest rate in percentage. Shareholder protection: Anti-Director Rights (ADR) index, which captures how strongly the legal system favors minority shareholders against managers and/or dominant shareholders. We use a dummy variable equal to one if the ADR index for the target country is above median, and zero otherwise (Source: Djankov etal., 2008). Stock market development: Market capitalization of listed domestic companies as a percentage of the corresponding country GDP. Appendix2: First stage ofpropensity score matching The table reports the differences in means across samples before and after matching. Before matching After matching Treated Control t-stat of differences Treated Control t-stat of differences Pscore 0.613 0.532 32.01 0.595 0.595 0.00 Firm size 5.148 4.657 13.67 4.892 4.937 − 0.86 ROA − 0.028 − 0.018 − 3.30 − 0.021 − 0.018 − 0.61 MTB 0.023 0.023 − 0.02 0.022 0.024 − 1.62 Relative deal size 0.403 0.430 − 3.12 0.412 0.418 − 0.47 Cash only 0.595 0.457 14.94 0.557 0.542 1.00 Hostile 0.021 0.083 − 15.58 0.010 0.010 0.00 Crossborder 0.263 0.165 12.71 0.198 0.209 − 0.99 Number of bidders 0.748 0.765 − 5.69 0.749 0.742 1.49 Horizontal 0.498 0.482 1.73 0.494 0.502 − 0.53 Vertical 0.088 0.145 − 9.63 0.093 0.100 − 0.77 Acknowledgements We thank Lemma Senbet (the Editor) and two anonymous referees for their constructive comments. We are also grateful to Eric de Bodt, Jean-Gabriel Cousin, Ettore Croci, Zoran Filipovic, Edith Ginglinger, Ali Özdakak, and Laurent Weill, as well as seminar participants at Paris Dauphine University and EM Strasbourg Business School for helpful comments and suggestions. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Data used in the study are from publicly available sources. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 636 Journal of International Business Studies (2024) 55:616–637 References Ahern, K., Daminelli, D., & Fracassi, C. (2015). Lost in translation? The effect of cultural values on mergers around the world. Journal of Financial Economics, 117(1), 165–189. Ahmad, M. F., de Bodt, E., & Harford, J. (2021). International trade and the propagation of merger waves. Review of Financial Studies, 34(10), 4876–4925. Aktas, N., de Bodt, E., & Roll, R. (2004). Market response to European regulation of business combinations. Journal of Financial and Quantitative Analysis, 39(4), 731–757. Aktas, N., Boone, A., Witkowski, A., Xu, G., & Yurtoglu, B. (2021). The role of internal M&A teams in takeovers. Review of Finance, 25(4), 1047–1088. Alexandridis, G., Petmezas, D., & Travlos, N. G. (2010). Gains from mergers and acquisitions around the world: New evidence. Financial Management, 39(4), 1671–1695. Alimov, A. (2015). Labor market regulations and cross-border mergers and acquisitions. Journal of International Business Studies, 46(8), 984–1009. Anderson, R. C., & Reeb, D. M. (2003). Founding-family ownership and firm performance: Evidence from the S&P 500. Journal of Finance, 58(3), 1301–1328. Ararat, M., Claessens, S., & Yurtoglu, B. (2021). Corporate governance in emerging markets: A selective review and an agenda for future research. Emerging Markets Review, 48, 100767. Bae, K., El Ghoul, S., Guedhami, O., & Zheng, X. (2021). Board reforms and dividend policy: International evidence. Journal of Financial and Quantitative Analysis, 56(4), 1296–1320. Baker, A. C., Larcker, D. F., & Wang, C. Y. (2022). How much should we trust staggered difference-in-differences estimates? Journal of Financial Economics, 144(2), 370–395. Bargeron, L., Schlingemann, F., Stulz, R., & Zutter, C. (2008). Why do private acquirers pay so little compared to public acquirers? Journal of Financial Economics, 89(3), 375–390. Bhagwat, V., Brogaard, J., & Julio, B. (2021). A BIT goes a long way: Bilateral investment treaties and cross-border mergers. Journal of Financial Economics, 140(2), 514–538. Boulton, T., Smart, S., & Zutter, C. (2010). IPO underpricing and international corporate governance. Journal of International Business Studies, 41(2), 206–222. Bradley, M., Desai, A., & Kim, E. H. (1988). Synergistic gains from corporate acquisitions and their division between the stockholders of target and acquiring firms. Journal of Financial Economics, 21(1), 3–40. Brockman, P., Rui, O., & Zou, H. (2013). Institutions and the performance of politically connected M&As. Journal of International Business Studies, 44(8), 833–852. Cai, Y., & Sevilir, M. (2012). Board connections and M&A transactions. Journal of Financial Economics, 103(2), 327–349. Callaway, B., & Sant’Anna, P. H. (2021). Difference-in-differences with multiple time periods. Journal of Econometrics, 225(2), 200–230. Cannon, J. N., Hu, B., Lee, J. J., & Yang, D. (2020). The effect of international takeover laws on corporate resource adjustments: Market discipline and/or managerial myopia? Journal of International Business Studies, 51(9), 1443–1477. Cengiz, D., Dube, A., Lindner, A., & Zipperer, B. (2019). The effect of minimum wages on low-wage jobs. Quarterly Journal of Economics, 134(3), 1405–1454. Chen, R., Guedhami, O., Yang, Y., & Zaynutdinova, G. (2020). Corporate governance and cash holdings: Evidence from worldwide board reforms. Journal of Corporate Finance, 65, 101771. Chen, Y., Goyal, A., & Zolotoy, L. (2022). Global board reforms and the pricing of IPOs. Journal of Financial and Quantitative Analysis, 57(6), 2412–2443. Claessens, S., Djankov, S., & Lang, L. H. P. (2000). The separation of ownership and control in East Asian corporations. Journal of Financial Economics, 58(1–2), 81–112. Dahya, J., Golubov, A., Petmezas, D., & Travlos, N. (2019). Governance mandates, outside directors, and acquirer performance. Journal of Corporate Finance, 59, 218–238. de Bodt, E., Cousin, J., & Officer, M. S. (2022). Financial constraints, ownership dilution, and the method of payment in M&A transactions. Journal of Corporate Finance, 75, 102250. Dessaint, O., Golubov, A., & Volpin, P. (2017). Employment protection and takeovers. Journal of Financial Economics, 125(2), 369–388. Diniz-Maganini, N., Rasheed, A. A., Yaşar, M., & Sheng, H. H. (2023). Cross-listing and price efficiency: An institutional explanation. Journal of International Business Studies, 54(2), 233–257. Djankov, S., La Porta, R., Lopez-de Silanes, F., & Shleifer, A. (2008). The law and economics of self-dealing. Journal of Financial Economics, 88(3), 430–465. Driffield, D., Jones, C., & Crotty, J. (2013). International business research and risky investment, an analysis of FDI in conflict zones. International Business Review, 22(1), 140–155. Driss, H. (2022). Board governance and investment sensitivity to stock price: International evidence. Journal of Financial and Quantitative Analysis, 58, 3027–3057. Durnev, A., Errunza, V., & Molchanov, A. (2009). Property rights protection, corporate transparency, and growth. Journal of International Business Studies, 40(9), 1533–1562. Dyck, A., & Zingales, L. (2004). Private benefits of control: An international comparison. Journal of Finance, 59(2), 537–600. Eckbo, B. E. (2009). Bidding strategies and takeover premiums: A review. Journal of Corporate Finance, 15(1), 149–178. El Ghoul, S., Guedhami, O., Mansi, S. A., & Sy, O. (2023). Event studies in international finance research. Journal of International Business Studies, 54(2), 344–364. Faccio, M., & Lang, L. H. P. (2002). The ultimate ownership of Western European countries. Journal of Financial Economics, 65(3), 365–395. Fauver, L., Hung, M., Li, X., & Taboada, A. G. (2017). Board reforms and firm value: Worldwide evidence. Journal of Financial Economics, 125(1), 120–142. Fich, E. M., Cai, J., & Tran, A. L. (2011). Stock option grants to target CEOs during private merger negotiations. Journal of Financial Economics, 101(2), 413–430. Fuller, K., Netter, J., & Stegemoller, M. (2002). What do returns to acquiring firms tell us? Evidence from firms that make many acquisitions. Journal of Finance, 57(4), 1763–1793. Glendening, M., Khurana, I. K., & Wang, W. (2016). The market for corporate control and dividend policies: Cross-country evidence from M&A laws. Journal of International Business Studies, 47(9), 1106–1134. Gompers, P., Ishii, J., & Metrick, A. (2003). Corporate governance and equity prices. Quarterly Journal of Economics, 118(1), 107–156. Gorbenko, A. S., & Malenko, A. (2014). Strategic and financial bidders in takeover auctions. Journal of Finance, 69(6), 2513–2555. Grossman, S. J., & Hart, O. (1988). One share-one vote and the market for corporate control. Journal of Financial Economics, 20, 175–202. Harford, J. (2005). What drives merger waves? Journal of Financial Economics, 77(3), 529–560. Harford, J., Humphery-Jenner, M., & Powell, R. (2012). The sources of value destruction in acquisitions by entrenched managers. Journal of Financial Economics, 106(2), 247–261. 637Journal of International Business Studies (2024) 55:616–637 Hartzell, J. C., Ofek, E., & Yermack, D. (2004). What’s in it for me? CEOs whose firms are acquired. Review of Financial Studies, 17(1), 37–61. Hillier, D., Pindado, J., de Queiroz, V., & de la Torre, C. (2011). The impact of country-level corporate governance on research and development. Journal of International Business Studies, 42(1), 76–98. Hsu, P. H., Tian, X., & Xu, Y. (2014). Financial development and innovation: Cross-country evidence. Journal of Financial Economics, 112(1), 116–135. Hu, J., Li, S., Taboada, A., & Zhang, F. (2020). Corporate board reforms around the world and stock price crash risk. Journal of Corporate Finance, 62, 101557. Huang, T., Wu, F., Yu, J., & Zhang, B. (2020). Investor protection and the value impact of stock liquidity. Journal of International Business Studies, 51(1), 72–94. Jensen, M. C. (1986). Agency costs of free cash flow, corporate finance, and takeovers. American Economic Review, 76(2), 323–329. John, K., & Senbet, L. W. (1998). Corporate governance and board effectiveness. Journal of Banking and Finance, 22(4), 371–403. Kedia, S., Ravid, A., & Pons, V. (2011). When do vertical mergers create value? Financial Management, 40(4), 845–877. Kim, E. H., & Lu, Y. (2013). Corporate governance reforms around the world and cross-border acquisitions. Journal of Corporate Finance, 22, 236–253. La Porta, R., Lopez-de-Silanes, F., Shleifer, A., & Vishny, R. (1997). Legal determinants of external finance. Journal of Finance, 52(3), 1131–1150. La Porta, R., Lopez-de-Silanes, F., Shleifer, A., & Vishny, R. (1998). Law and finance. Journal of Political Economy, 106(6), 1131–1155. La Porta, R., Lopez-de-Silanes, F., Shleifer, A., & Vishny, R. (2000). Investor protection and corporate governance. Journal of Financial Economics, 58(1–2), 3–27. La Porta, R., Lopez-de-Silanes, F., Shleifer, A., & Vishny, R. (2002). Investor protection and corporate valuation. Journal of Finance, 57(3), 1147–1170. Lang, L. H. P., Stulz, R. M., & Walkling, R. A. (1991). A test of the free cash flow hypothesis: The case of bidder returns. Journal of Financial Economics, 29(2), 315–336. Maksimovic, V., Phillips, G., & Yang, L. (2013). Private and public merger waves. Journal of Finance, 68(5), 2177–2217. Malmendier, U., & Tate, G. (2008). Who makes acquisitions? CEO overconfidence and the market’s reaction. Journal of Financial Economics, 89(1), 20–43. Masulis, R., Wang, C., & Xie, F. (2007). Corporate governance and acquirer returns. Journal of Finance, 62(4), 1851–1889. Moeller, S. B., Schlingemann, F. P., & Stulz, M. (2004). Firm size and the gains from acquisitions. Journal of Financial Economics, 73(2), 201–228. Robinson, J., Acemoglu, D., & Johnson, S. (2005). Institutions as a fundamental cause of long-run growth. Handbook of Economic Growth, 1A, 386–472. Rockness, H., & Rockness, J. (2005). Legislated ethics: From Enron to Sarbanes–Oxley, the impact on corporate America. Journal of Business Ethics, 57(1), 31–54. Rossi, S., & Volpin, P. F. (2004). Cross-country determinants of mergers and acquisitions. Journal of Financial Economics, 74(2), 277–304. Schwartz-Ziv, M., & Volkova, E. 2023. Is blockholder diversity detrimental? Management Science, forthcoming. Schwert, G. W. (2000). Hostility in takeovers: In the eyes of the beholder? Journal of Finance, 55(6), 2599–2640. Sugathan, A., & George, R. (2015). The influence of governance infrastructure and corporate governance on profit shifting. Journal of International Business Studies, 46(8), 886–916. Sun, L., & Abraham, S. (2021). Estimating dynamic treatment effects in event studies with heterogeneous treatment effects. Journal of Econometrics, 225(2), 175–199. Tosun, O. K., & Senbet, L. W. (2020). Does internal board monitoring affect debt maturity? Review of Quantitative Finance and Accounting, 54(1), 205–245. Villalonga, B., & Amit, R. (2006). How do family ownership, control, and management affect firm value? Journal of Financial Economics, 80(2), 385–417. Zhou, C., Xie, J., & Wang, Q. (2016). Failure to complete cross-border M&As: “to” vs. “from” emerging markets. Journal of International Business Studies, 47(9), 1077–1105. Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Muhammad Farooq Ahmad is Associate Professor of Finance at SKEMA Business School. His research interests include international corporate governance, sustainable finance, mergers and acquisitions, and innovation. His work has been published in the Journal of Banking and Finance, Review of Financial Studies, and other academic outlets. Nihat Aktas is Professor of Finance holding the Chair of Mergers and Acquisitions at WHU Otto Beisheim School of Management. His research articles, mostly focusing on mergers and acquisitions, have appeared in such journals as Business and Society, Economic Journal, Journal of Corporate Finance, Journal of Financial and Quantitative Analysis, Journal of Financial Economics, Review of Finance, among others. Douglas Cumming is the DeSantis Distinguished Professor of Finance and Entrepreneurship at the College of Business, Florida Atlantic University, and a Visiting Professor of Finance at Birmingham Business School, University of Birmingham. Douglas has published 21 books and 230 articles in leading refereed academic journals (including 43 in Financial Times Top-50 journals), which have been cited over 27,000 times. Guosong Xu is Assistant Professor of Finance at Rotterdam School of Management, Erasmus University. His research interests include corporate finance, behavioral finance, and the intersections with environmental, social, and corporate governance issues. His research has been published in the Journal of Corporate Finance, Journal of Financial and Quantitative Analysis, and Review of Finance.