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Determinants of Earnout as Optimal Payment Currency in Domestic versus Cross-Border Acquisitions and Bidders’ Gains

Leonidas Barbopoulos, Krishna Paudyal, and Sudi Sudarsanam#

Abstract: We investigate the wealth effects of a comprehensive sample of US bidders offering contingent payments, or earnouts, as consideration for their domestic versus cross-border acquisitions. Our evidence conveys that bidders of domestic versus cross-border target firms using earnouts yield similar announcement period gains to their shareholders, irrespective of several transaction- and firm-specific characteristics. We construct a logistic model to predict the ‘optimal’ use of earnouts by both bidders of domestic and cross-border target firms. We show that bidders using earnouts ‘optimally’ enjoy higher announcement period gains from bids of cross-border targets than from bids of domestic targets, consistent with our model of the choice of the optimal method of payment. Our findings also confirm that the use of earnouts in foreign bids appears much more compelling, particularly when it is used ‘optimally’, compared to the ‘optimal’ use of earnouts in domestic bids. Overall, we provide robust evidence that the use of earnouts in domestic and/or cross-border acquisitions is an effective payment mechanism that helps in significantly mitigating information asymmetry issues and valuation errors, while it enhances acquirers’ net value gains in the short-run. Keywords: Earnouts, announcement bidder gains, domestic versus cross-border acquisitions, abnormal returns, method of payment, information asymmetry, valuation errors. GEL classification: G34

This draft: 12 January 2011

# The authors gratefully acknowledge the comments and suggestions of… Please send correspondence to Leonidas Barbopoulos, School of Economics and Finance, University of St Andrews, Castlecliffe, The Scores, Fife, KY16 9AL, Scotland, UK. Tel: +44 (0) 133 446 1955, Fax: +44 (0) 133 446 2444 (leonidas.barbopoulos@st-andrews.ac.uk); Krishna Paudal, University of Leeds, Leeds University Business School, The Maurice Keyworth Building, Leeds, LS2 9JT, UK (knp@lubs.leeds.ac.uk). Sudi Sudarsanam, University of Cranfield, UK (p.s.sudarsanam@cranfield.ac.uk). Any remaining errors are ours.

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1. Introduction Recent years have witnessed tremendous increases in foreign direct investments, especially in the forms of cross-border acquisitions (hereafter CBA).1 Previous research has excessively investigated several costs and benefits2 associated with foreign3 acquisitions on the gains of shareholders of participating firms. The majority of these studies highlight that the gains from CBA are highly sensitive on the acquiring firms’ exposure into new markets or countries (Doukas and Travlos, 1988), the costs and benefits of global diversification (Denis, Denis, and Yost, 2002), several macroeconomic indicators including the home and host country’s economic conditions, exchange rate volatility, and the level of effectiveness of the foreign country’s government (Kiymaz, 2004), and on targets’ geographical region (Gregory and McCorriston, 2005). Along the same lines, whereas the mergers and acquisitions (hereafter M&A) literature reveals a paucity of empirical research on the impact of such investment opportunities on the bidding firm’s stock price performance, a number of other studies focus on the comparative performance of bidders’ gains from domestic and foreign acquisitions. Among others, Moeller and Schlingemann (2005) claim that US firms acquiring foreign targets, relative to those acquiring domestic ones, experience significantly lower announcement period stock returns (see also Eckbo and Thorburn, 2000), and significantly lower changes in operating performance. They also point out that business diversification along with several transaction- and firm-specific characteristics4

are important determinates of the distribution of bidders’ announcement returns. Nevertheless, and despite the weight of available evidence, the question of whether a precise combination of the aforementioned characteristics constitute a powerful model in shaping the distribution of bidders’ value gains from domestic versus CBA, or whether additional factors are required, still calls for further investigation.

The complexities and difficulties that confronted by foreign bidders in managing subsidiaries in a different location/country are likely to be the major source of the lower net value gains that accrued to

1 Evidence on the CBA trends over the course of several decades points out that in 2007 the value of CBA worldwide accounted for almost $1,700bn (WIPS, 2009), compared to only $39bn in 1987 (UNCTAD, 2009). In addition, UNCTAD (2000, p. 10) discusses the key differences between CBA and FDI and it concludes that CBA have contributed an increasing share of FDI flows to developed and developing countries alike. 2 Extant discussions advocate that foreign acquirers do enjoy opportunities such as technological advancement, business diversification, tax differentials, and imperfections in factor and product markets (Errunza and Senbet, 1981), which are not easily available to domestic bidders. However, foreign bidders are exposed into foreign exchange, macroeconomic, political, and other types of risks which are not frequent in the domestic market. 3 In this paper we use the term ‘cross-border’ and ‘foreign’ interchangeably. 4 Asquith et al. (1983) showed that bidders’ abnormal returns are related to the transaction’s relative size, whereas Sudarsanam and Mahate (2003) confirmed that bidders’ growth opportunities affect bidders’ gains; Moeller et al. (2004) demonstrated that the size of the bidder is an important determinant of bidders’ gains; others have also confirmed that the target firm’s status and the method of payment in M&A affect bidders’ gains (see for example, Chang, 1998; Fuller et al. 2002; Draper and Paudyal, 1999 and 2006). In terms of other transaction characteristics, Goergen and Ronneboog (2004) pointed out that bidders enjoy significant gains in friendly takeovers whereas they experience significant loses in hostile bids and Doukas and Travlos (1988) showed that bidders gain more from diversifying into new industries and foreign countries.

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foreign bidders’ shareholders when compared to domestic ones. Indeed, bidders of foreign targets are forced to manage operations in a different country, which are therefore likely to face different corporate governance mechanisms, investor protection regimes, accounting systems and economic provisions, compared to bidders that stay in the home market. Numerous studies have confirmed the inverse relationship between the net value gains that accrued to foreign bidding firms’ shareholders and the above country- or region-specific characteristics.5 Accordingly, the present paper investigates a recently developed approach in M&A that contributes in mitigating significantly certain risks associated with: (a) various information asymmetry issues at the time of the M&A announcement, and (b) the post-merger integration of participating firms. More specifically, we investigate whether contingent payments, or earnouts considerations, in both domestic and foreign target acquisitions provide a solution towards the more efficient transformation of all available inputs into the expected outputs during the post-M&A period while we also test whether such expectations are priced at the time of the M&A announcement. We also investigate, by employing a logistic regression approach, whether the ‘optimal’ use of earnouts helps in further mitigating the above issues and thus further boosting shareholders wealth. In light with the previous discussion on the possible sources of the lower net value gains accrued to foreign bidders shareholders, we propose that the earnouts should not only be forced more in foreign M&A, but even more in foreign M&A where the target firm is based in countries which present greater information asymmetries and uncertainties regarding the accurate target firm’s valuation and also the realisation of the expected synergistic gains. To address such effects in the framework of our analysis we consider a number of proxies that capture the impact of several corporate governance characteristics, investor protection regimes, and accounting systems, in the prediction of the ‘optimal’ use of earnouts in foreign M&A. Our evidence shows that bidders employing ‘optimally’6

earnouts to finance their foreign M&A bids distribute the highest gains to their shareholders while in the framework of domestic versus CBA, the ‘optimal’ use of earnouts offers higher gains to bidders of foreign target firms.

Among the transaction specific characteristics which influence the bidders’ announcement period gains, the method of payment that used to finance the M&A bid appears as the most important one, as it deals with issues related to both information asymmetry and valuation errors, both at the time of the M&A announcement and in the post-merger period. Extant literature investigates excessively the traditional methods of payment in both domestic and foreign M&A bids, such as cash and stock, on the

5 See for example Bris and Cabolis (2008). 6 We use the term ‘optimal’ to refer to the expectation or prediction of the logit model as regards earnout use conditional on several transaction-specific, merging firm- and country-specific characteristics (see section 4.3.1 below for the discussion on the classification of the ‘optimal’ use of earnouts in both domestic and foreign acquisitions).

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announcement gains of bidders’ shareholders.7 An alternative to cash and/or stock exchange offer, which may reduce information asymmetry and valuation risk to both bidders and targets, which has received very little attention in the literature, is the earnout agreement – also referred to as deferred consideration. Specifically, earnout is a contingent form of payment which is used to finance M&A and involves a two stage payment structure: (a) an initial upfront payment to target firm’s shareholders (b) a second stage payment conditional upon the target firm achieving certain and agreed performance requirements. The target firm’s performance during the post-merger period, the duration of the earnout period, the currency of settlement of the earnout portion of the consideration, and the earnout size, among others, set the earnout agreement. It is therefore considered to facilitate the valuation of the target firm over a period of time as more value-relevant information become available to both merging firms. Kohers and Ang (2000) and Cain, Denis, and Denis (2010) study on the US market, Barbopoulos and Sudarsanam (2010) study on the UK market, demonstrate that in a number of M&A bids the earnout was used as a payment currency. The authors also note that the extent of the information asymmetry problem, in addition to other transaction and firm characteristics, was a large factor dictating the usefulness of earnout. Other findings reported by Kohers and Ang (2000), Mantecon (2009), and Barbopoulos and Sudarsanam (2010), clearly confirm that certain information asymmetry problems and valuation errors are mitigated in the presence of earnout in the financing of M&A bids. In the framework of the present research, we investigate the impact of (a) earnouts financing into the gains of domestic versus foreign target firms’ acquirers8

and (b) the initial payment method in earnouts financing, such as whether earnouts are attached into only cash payments, or to only stock payment, or to only mixed payments.

By confirming earlier evidence, such as Mantecon (2009), we show that bidders using earnouts to finance domestic acquisitions versus foreign ones yield similar short-run gains to their shareholders. Informed from previous literature regarding the impact of several transaction-specific, firm-, and country-specific factors that are likely to influence the utilization of earnouts in both the domestic and foreign M&A, and by using a logistic regression approach, we estimate the probability of using earnouts versus non-earnouts, at event level, for both domestic and CBA samples. We show that bidders employing earnouts ‘optimally’ to finance foreign M&A bids yield significantly higher announcement period gains to their shareholders, compared to those employing earnouts ‘optimally’ to finance domestic M&A. Such evidence reflect that the ‘optimal’ use of eanouts in foreign acquisitions provides a

7 See for example, Myers and Majluf (1984), Travlos (1987), Eckbo et al. (1990), Chang (1998), Faccio and Masulis (2005), Draper and Paudyal (1999 and 2006), and Faccio et. al. (2006). 8 Similar research has been investigated by Mantecon (2009).

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more effective mechanisms to mitigate certain risks of adverse selection, while it also helps in efficiently managing the foreign target firm’s operations during the post-M&A period. Our paper adds significantly to our existing knowledge regarding the impact of earnouts financing on the net value gains accrued to domestic versus foreign bidders’ shareholders. In fact, the paper is extending our existing knowledge (i.e. Mantecon, 2009) by estimating the ‘correct’ use of earnouts in the payment process of domestic acquisitions and/or CBA. In the process, we further contribute by controlling for the impact of the initial payment method of the earnout financing. The ‘optimal’ use of earnouts, and also the control of the initial payment in the earnouts financing process, are both largely ignored by previous studies (i.e. Kohers and Ang, 2000; Mantecon, 2009; Barbopoulos and Sudarsanam, 2010). The remainder of this paper is organized as follows. Section 2 refers to the previous literature on the gains of domestic acquisitions, CBA, and also on the cooperative performance of domestic acquisitions and CBA. Section 3 provides a conceptual framework concerning how earnouts affects acquirers’ gains and develops some testable propositions. Section 4 describes the data and methodology, while section 5 discusses the empirical results. Finally, section 6 concludes the paper while it discusses several important implications of our findings.

2. Literature on Bidders’ Gains from Foreign Acquisitions Extant literature excessively investigates the wealth effects of foreign bidders’ shareholders by considering a large number of explanatory variables, among which several transaction-specific, firm- and country-specific factors are analyzed. Along the same lines, previous literature offers, on average, mixed evidence on whether CBA create value for acquirers’ shareholders (Doukas and Travlos, 1988; Cakici et al., 1996, Denis et al., 2002; Gregory and McCorriston, 2005). Consistent with such views and based on the views of the internalization theory, evidence suggests that (bidding) firms overpopulated by intangible, or information-based assets (i.e. R&D, brand names, managerial know-how, etc.), have the tendency to be engaged in direct international investments and yield positive abnormal returns to their shareholders (Morck and Yeung, 1992; Markides and Ittner, 1994; Anand and Kogut, 1997). Similarly, evidence suggest that foreign bidders benefit from bids of targets firms that hold R&D and other information-based assets, further supporting the ‘reverse-internalization’ hypothesis (Eun, Kolodny, and Scheraga, 1996). More recent literature claims also that the variation of the gains accrued to foreign bidders’ shareholders is further determined by different motives that distinguish foreign bids, such as synergy-seeking, managerialism, and hubris (Seth, Song, and Pettit, 2002). The same authors report evidence in light with the expectation that multiple sources of value creation exist in synergistic

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CBA, such as asset sharing, reverse internalization of valuable intangible assets, and financial diversification. In the present paper we employ several characteristics of the above discussion in the prediction process of the ‘optimal’ use of earnouts in CBA (i.e. industry dummy variables, variables that capture several firm- and transaction-specific characteristics, etc.). In a different strand of literature, a number of studies (for example, La Porta, Lopez-de-Silanes, Shliefer, and Vishny, 1998; 2000; 2002) show that country’s legal environment affects firm’s value. Similarly, several scholars show that the legal traditions and investor protection regimes of the participating firms’ countries affect the gains of bidders’ shareholders (Bris and Cabolis, 2008). Rossi and Volpin (2004) confirm also that the legal environment of the countries of the participating firms affect the choice of the method of payment that used to finance the M&A bid. In fact, the authors point out that the likelihood of using cash to finance M&A bids decreases with the level of investor protection in the bidding firm’s country. Furthermore, better investor protection is associated with the greater use of stock as the method of payment and with higher takeover premiums. In foreign bids, targets are basically from countries with weak investor protection compared to the acquirers’ countries, suggesting that CBA play a major role by improving the degree of investor protection within target firms. In light of the above evidence, we examine whether the use of earnouts in CBA is be sensitive to the legal environment of the target firm’s country of residence. Extant literature investigates also the gains of bidders’ shareholders from domestic versus foreign acquisitions while it discusses various reasons that lead to any difference in performance. The vast majority of available evidence suggests that foreign acquisitions tend to be subject to great information challenges, complexities, and difficulties, compared to domestic M&A. The majority of these studies highlight that bidders’ shareholders benefit more form CBA versus domestic acquisitions (see for example Harris and Ravenscraft, 1991; Shaked and McClain, 1991; Markides and Ittner, 1994). The same authors claim also that foreign bidders (a) tend to pay more for their targets and (b) they are more often involved in bids of R&D-intensive targets. On the other hand, Moeller and Schlingemann (2005) claim that US firms acquiring foreign targets, relative to those acquiring domestic ones, experience significantly lower announcement period stock returns, and significantly lower changes in operating performance. Others point also out that firms tend to avoid bids in favour of less commitment-intensive entry modes, particularly when national cultural differences are substantial (Johanson and Vahlne, 1977; Gatignon and Anderson, 1988). However, available findings are still mixed on whether the effects of cultural differences have a significant influence on acquisitions and other forms of FDI, both in terms

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of activity and gains to participating firms’ shareholders (Morosini et al., 1998; Brouthers and Brouthers, 2001; Shenkar, 2001).

3. Hypotheses Development and Theoretical Framework on the Method of Payment The choice of payment currency in corporate acquisitions has received much attention in theoretical finance essentially drawing upon the information economics literature. Cash as Payment Currency A bidder may choose to make a cash offer, in preference to a stock exchange offer, for a variety of reasons. A cash offer is more certain and its value does not depend on the post-acquisition performance of the acquirer. It is simple to evaluate. A cash offer thus eliminates the ‘lemon’ problem for the target shareholders (see below for a discussion of this problem). It represents a clean break for target shareholders who wish to sell out of the target company. Fishman (1989) argues that a cash offer is made by a bidder who attaches a high value to the target of its bid to signal its confidence that the target will be a high-value company under its control. On the other hand, bidders, who are not confident enough, cannot afford to pay in cash and would prefer to offer a security exchange. Thus, cash bids are pre-emptive against potential rival bidders.9 Eckbo, Giammarino and Heinkel (1990) derive, from modelling the information asymmetry between bidder and target and their negotiating games, that higher valued bidders increase the cash component of their offer.10

However, target shareholders in a cash offer experience an opportunity loss if, post-acquisition, the merger creates more value than is implied in the cash offer premium to target shareholders.

Stock Exchange Offer and Adverse Selection The valuation risk arises from information asymmetry; that is, each side speculates that the other side of the transaction has more information about the true value of the bidder or target. Information asymmetry leads to adverse selection, i.e., selection of a target whose real value is lower than what appears to be. It is also called buying a ‘lemon’ (Akerlof, 1970). The acquirer may worry about buying a ‘lemon’ as much as the target shareholders about accepting the bidder’s shares in consideration. The bidder can alleviate its own adverse selection problem by offering a share exchange rather than cash.

9 M. Fishman, ‘Preemptive bidding and the role of the medium of exchange in acquisitions’, Journal of Finance, XLIV(1), 1989, 41–57. For the UK empirical evidence in support of pre-emption, see P. Cornu and D. Isakov, ‘The deterring role of the medium of payment in takeover contests: Theory and evidence from the UK’, European Financial Management, 6(4), 2000, 423–440. 10 B. E. Eckbo, R. M. Giammarino and R. L. Heinkel, ‘Asymmetric information and the medium of exchange in takeovers: Theory and tests’, Review of Financial Studies, 3(4), 1990, 651–675.

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In his theoretical model, Hansen (1987) shows that common stock due to its contingent pricing effect reduces the target valuation risk for the bidder by forcing the target shareholders to share the overvaluation risk in the ex-post period.11

Within the same adverse selection framework, Eckbo et al. (1990) derive the result that high-value bidders, i.e., bidders whose post-acquisition value will be high, offer cash, and low-value bidders, offer equity as a way of risk sharing.

Equity derivatives, such as collars and caps, are often used to minimise the valuation risk to a bidder or the target due to short term share price movement of either firm. These are appropriate where both bidders and targets are listed companies. They offer the protection against valuation risk only in the short term.12 The ‘lemon’ problem facing the target shareholders in a share exchange extends beyond the consummation of the merger transaction. Since the offer value depends on the future performance of the post-acquisition entity, target shareholders may need protection conditional on such future performance. Contingent Value Rights (CVRs) are commitments by the acquirer to pay additional cash or securities to the target shareholders if the share price of the combined company does not exceed a specified level at some future point, e.g., a year after the acquisition is completed. CVRs are part of the acquisition currency and may be traded on the open market, thereby allowing the target shareholders to cash out early.13

Deferred Consideration Financing As discussed earlier, both bidders and target shareholders face valuation risk in negotiating a price and the payment currency in a takeover. One way of mitigating this risk is to make the consideration payable to the vendors contingent upon the future performance of the target under their own management, i.e., use the earnout mechanism. Such payments are divided into two parts, an up-front payment at the time of the deal’s announcement and another payment which is determined by a set of pre-determined performance requirements. The final payment depends on the target’s future performance and ability to meet the predetermined goals (Reuer et al., 2004). Accordingly, it is often used to finance acquisitions of private companies operating in the service or high technology sectors, e.g., advertising agencies, software development businesses. In such companies, the firm value generally depends on the intangible asset of human creativity and the flair of one or two individuals.

11 Officer et al, ibid, find evidence supportive of the Hansen model in their analysis of methods of payment by US acquirers. Where the targets are young companies at development stage (or are relatively intensive of intangible assets) and hence subject to high valuation risk, the announcement period abnormal return to acquirers is 6% (10%) compared to returns with non-development stage (less intangible intensive) targets of -6% (5%). The differences are statistically significant. Further, acquiring high risk targets with stock generates more value than acquiring them with non-stock consideration. See their Table 4. 12 B. Wasserstein, Big Deal, The Battle for Control of America’s Leading Corporations (New York: Warner Books, 1998), pp. 624–629. See also C. GaCCIa-Peri, ‘Using equity derivatives in M & A’, Corporate Finance, 187, June 2000, 27–28. 13 R. Bruner, Case Studies in Finance, Managing for Corporate Value Creation (New York: Irwin, 1994), Chapter 45.

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Retaining the target management after acquisition to ensure that the target performs as expected by the acquirer may be a key consideration.14 Valuing such companies, however, is immensely difficult. Earnout provides a solution when price negotiation between buyer and seller stalls.15

In an earnout, consideration to the vendor is made up of the following:

• an immediate payment in cash or shares of the acquirer;

• a deferred payment (usually cash) contingent upon the target-turned-subsidiary achieving certain predetermined performance levels (the performance level may be expressed in terms of sales revenue or pre-tax profits or other performance metrics).

Earnouts are indeed not free of problems. The culture shock of transformation from owning and managing an independent company to running a subsidiary under the control of a larger firm may be quite traumatic for target owner-managers. For the buyer, an earnout is a way of retaining the vendor’s talents. However, the vendor may lack motivation or may try to maximize short-term profits to the detriment of the long-term interests of the buyer.

Prior Research on Earnouts in Acquisitions

In contrast to the substantial research on cash and stock exchange offers (see Sudarsanam, 2003, ch. 16 for a review), there are very few studies of choice of earnout and its impact on shareholder wealth. Among the few studies, Kohers and Ang (2000) find that targets that give rise to high information asymmetry motivate the use of earnout and that the use of earnout results in positive event period returns for the acquirers. They also find that in case of bidders acquiring private targets and hence facing high information asymmetry, the use of earnout results in considerably higher event period value gains for the acquirer than to acquirers in cash and stock transactions. They compare the abnormal returns to earnout acquirers with those to cash and stock acquirers in a sample of US takeovers. Earnout acquirers outperform the latter in terms of 2-day abnormal returns when acquiring private targets (corporate subsidiaries): 2.2% (2.1%) for earnout acquirers compared to 1.8% (1.5%) for cash acquirers and 1.13% (2.0%) for stock acquirers. Such outperformance is even greater when the targets are associated with greater information uncertainty about their value, e.g., targets in the high-tech or

14 In some cases preventing the defection of key managers to rivals or to set up their own shop, rather than retention, may motivate an earnout. See J. Marino, ‘Resisting defection’, Mergers and Acquisitions, 43, 10, 60-61, October 2008. 15 S. J. Sherman and D. A. Janatka, ‘Engineering earn-outs to get deals done and prevent discord’, Mergers and Acquisitions, September/October 1992, 26–31.

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service sectors, consistent with the rationale that earnout reduces valuation risk to the acquirer due to information asymmetry. Along the same lines, Reuer et al. (2004) suggest that the likelihood of the use of earnout increases with uncertainty facing the bidding firm. There is also some limited evidence on the effect of the earnout on bidder returns in CBA. Datar et al. (2001) investigate the likelihood of the use of earnout in CBA and find that foreign bidders of US targets are less likely to use earnout as a method of payment than US domestic bidders. The authors argue that this result is due to the unwillingness of target firms to accept deferred payments to avoid future disputes concerning the determination of the residual consideration payable to target shareholders, arising from differences in accounting practices and corporate governance characteristics between the acquirer and target countries. Furthermore, Mantecon (2009) examines the effect of various methods of uncertainty avoidance, including all-in-stock payment, equity joint ventures, earnout and toehold investment, on returns to foreign bidders. The author suggests that while the use of earnout yields positive returns for domestic acquirers, the cross-border acquirers do not benefit from the earnout use. Consistent with this evidence, Conn et al. (2005) report that, in CBA, the method of payment (cash or stock) does not affect bidders’ shareholder value performance significantly. Hypotheses to be tested Following the above arguments and empirical evidence from the extant literature, we formulate our first hypothesis: H1: ‘Bidders financing acquisitions with earnout experience higher announcement period gains than those using only non-earnout payment currencies, irrespective of the target firm’s domicile’. Earnouts and Gains from Domestic and Cross-Border Acquisitions Information asymmetry as a source of valuation risk may not be of the same severity in the case of domestic target M&A bids as in the case of foreign target M&A bids. In fact, the vast majority of available evidence suggests that CBA tend to be subject to great information challenges, complexities, and difficulties in managing foreign operations/targets, compared to domestic M&A. Thus, in CBA the rationale for the use of earnouts as against other payment currencies, like cash and stock exchange, may be more compelling than in the case of domestic target M&A bids. Even though a stock offer increases the target shareholders’ stake in the combined business (see previous discussions in the

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present section and previous work by Hansen, 1987) and thus can motivate the target managers holding stocks in the merged entity, an earnout provides a more finely-calibrated incentive mechanism than stock since it is directly related to well defined operating performance goals. Therefore, the impact of earnouts on acquirer value gains may differ significantly between domestic and foreign company targets. If the information asymmetry problem was more severe for acquirers of foreign targets, then using earnout is much likely to benefit them more than acquirers of domestic targets using the same payment currency. Overall, earnout may mitigate such asymmetry and valuation risk, the one that is associated with foreign M&A bids. We, therefore, formulate the following hypotheses: H2: ‘Value gains to acquirers of foreign target firms using earnouts are greater than those to acquirers of domestic target firms using earnouts’. The Optimal Use of Earnouts and Gains from Domestic and Cross-Border Acquisitions We model the choice of earnouts conditional on various transaction-specific characteristics, bidder- and target-specific characteristics, as well as several country-specific characteristics, which reflect useful information regarding information asymmetry issues and valuation risk. For example, (a) target firm industries may differ in terms of technology, technological change, asset composition, operating leverage etc; (b) merging firms’ countries may also share several investor protection characteristics and corporate governance mechanisms, which may significantly contribute during the post-M&A integration of the merging firms’ operations; and (c) several transaction-specific characteristics such as the relative size of the bid and the size of the transaction as well as other firm-specific ones, such as the target firm’s status and the size of the firms involved, may significantly influence the need for earnouts. Our logit model therefore ‘predicts’ whether the use of earnouts in takeover bids is ‘optimal’ at the individual M&A bid level, both for domestic and CBA transactions. In fact, from a comparison point of view, the prediction of the actual use or non-use of earnouts in a M&A bid can be assessed and thus we may observe whether earnouts are used ‘optimally’ or ‘non-optimally’ in both domestic and CBA bids. Following several arguments that discussed excessively in many studies of the relevant literature regarding the complexities and difficulties confronted by bidders of foreign target firms, and following the above discussion which suggests that the earnouts should be forced more in CBA, compared to domestic M&A, we anticipate that (a) the use of earnouts in CBA to yield higher announcement period gains, compared to domestic M&A bids, and (b) the ‘optimal’ use of earnouts in CBA, as predicted by our logit model, to offer even more higher benefits to foreign bidders’ shareholders, compared to domestic M&A bids using earnouts ‘optimally’. We consider a large number of variables in the logit

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model that are able to capture the differences in various corporate governance characteristics. In light of such discussion, Kohers and Ang (2000) highlights that the earnout contracts increase the likelihood of retaining the target firm’s managers during the post-merger period and thus the likelihood of more successful integration of the two merging firms during the post-M&A period. Noteworthy, while a stock offer may increases the target shareholders’ stake in the final entity (see previous discussions in the present section) and thus can motivate the target managers holding stocks in the merged entity which may eliminate ceratin levels of information asymmetry (see also Hansen, 1987), an earnout contract provides a more finely-calibrated incentive mechanism than stock since it is directly related to well defined operating performance goals (see section Deferred Consideration Financing and Prior

Research on Earnouts in Acquisitions). Given the greater information asymmetry and valuation risk to bidders in CBA than in domestic acquisitions, the payoff to choosing the right payment currency and penalty for choosing the wrong currency are likely to be greater than in domestic acquisitions. While optimal use of earnouts should generate higher value gains to bidders in both domestic and CBA than its non-optimal use, the differential value gains over non-optimal use are likely to be greater in CBA than in domestic acquisitions. We, therefore formulate and test the following hypothesis: H3a: ‘The optimal use of earnouts as a payment currency yields higher shareholder gains in both domestic acquisitions and CBAs; H3b: ‘The differential gains to the optimal use of earnouts over non-optimal use are larger in CBAs than in domestic acquisitions’. In the next section we describe the data and methodology used to test the above hypotheses.

4. Data and Methodology 4.1 The Sample The sample comprises takeover bids announced by US firms between 01/01/1986 and 31/12/2008 and recorded by the Security Data Corporation (SDC). The choice of sample period is guided by the comprehensiveness of records in SDC and the availability of the financial data. SDC records 228,731 cases of M&A bids involving US acquirers within the sample period. For a bid to remain in the sample, it

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must meet the following criteria: first, the acquirer is a US company listed on the major US Stock Exchanges and has a market value of at least $1 million, measured four weeks prior to the announcement of the bid. To avoid very small bids, the transaction value also needs to be at least $1 million. To ensure that the acquirer enjoys control of the target, only acquisitions of at least 50 percent of target equity are included in the sample. We also exclude bidders with more than 50 percent ownership of the target firm’s assets before the announcement of the M&A bid. Targets of any status (listed, private, and subsidiary) and domicile (US or non-US) are included in the sample. To avoid the confounding effects of multiple bids, bids announced within 5-days surrounding another bid by the same bidder are excluded. Finally, for a bid to be included in the sample, the daily stock price, the market value and the market-to-book value of the acquirer need to be available from Datastream. Once all the above criteria have been satisfied, 15,639 bids remain in the sample. 4.2 Sample characteristics The annual distribution of takeover bids in our sample depicts the three major merger waves since the mid 1980s, mid 1990s and the mid-2000s (see Table 1). Table 1 also shows the frequency of the earnouts use. Similar to all the other methods of payment (cash, stock, and mixed), the earnouts activity is highly correlated with the overall M&A activity. Indeed, the earnouts activity spikes with the overall M&A activity and its highest point is observed during periods of the peaks of merger waves. This may be because many bidders and targets during ‘hot market’ periods may try to avoid gross mis-valuation problems by entering into earnouts contracts. For definitions of the variables in Table 1 and in the rest of the paper see Appendix 1.

(Insert Table 1 about here) Table 1 shows that almost 93% of the entire US M&A activity involves bids financed by pure cash or stock or mixed payments, i.e., non-earnouts. The remaining M&A activity involves earnouts as indicated by SDC. Cash only payments represent the dominant medium of financing (38.86%), while stock only and mixed payments represent the next active groups (26.16% and 27.72% respectively). Faccio and Masulis (2005) suggest that when an acquisition takes place with the target being a subsidiary firm, cash is preferred as the medium of exchange since corporations selling subsidiaries are often facing financial distress, or they desire to use the cash proceeds to restructure towards their core business. Focused (i.e. same industry) acquisitions account for nearly 60 percent of the sample, the rest being

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diversifying (i.e. cross-industry acquisitions). CBA i.e. US bidders acquiring non-US targets appear far less frequently (almost 11% of sample) than purely US acquisitions (almost 89%). Table 2 (Panel A) further shows that the majority of acquisitions involve private targets (48.5%), followed by subsidiaries (26.4%) with the least activity being concerned with public targets (25.1%). Panel A also conveys that the mean transaction value (= the mean of the transaction values of all bids in each group as reported by the SDC) across portfolios of bids using non-earnouts versus earnouts currencies vary significantly. From Panel A it appears that the highest mean transaction value is observed for the portfolio of bids financed with mixed payments, compared to the portfolio of bids involving earnouts, irrespective of the target firm status. Noteworthy, among only listed target bids, the ones financed with stock or mixed payments show the highest mean transaction value, compared to the ones financed with cash or earnout. The higher mean transaction value when earnouts are used, compared to cash only and stock only payments, in private and subsidiary bids, may be driven by the fact that most private and subsidiary acquisitions in the US are financed with earnouts (Kohers and Ang, 2000; Datar, Frankel, and Wolfson, 2001; Cain, Denis, and Danis, 2010). In fact, Kohers and Ang (2000) report that almost 66% (27%) of US M&A bids that financed with earnouts involve privately held (divested subsidiaries) target firms.

(Insert Table 2 about here)

Further analysis presented in Table 2 (Panel B) reveals that acquirers using earnouts are on average smaller in size than acquirers paying with cash only or stock only currencies, whereas they are similar in size with acquirers paying with mixed currencies. Similarly, bidders of privately held target firms appear much smaller than the ones of public or subsidiary targets. In addition, the average transaction value of bids involving earnouts ($116 million) is much less than the average deal value of bids financed with cash, stock, or mixed payments ($201m, $546m, and $618m respectively). Table 2 (Panel B) also shows that acquirers using earnouts have lower growth opportunities than non-earnout acquirers with lower MTBV (mean of 3.02 and median of 2.21 compared to 4.10 and 2.15 respectively). The mean (median) earnout value of the consideration in all earnout acquisitions is $28.3m ($7m) and it is smaller in private company acquisitions than in public company acquisitions and acquisitions of subsidiaries (the mean value is $23.7m, $52.2m and $41.0 respectively). This is not surprising as the mean transaction value of a private company acquisition is much smaller (see Table 2, Panel A, column All and Panel B).

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4.3 Methodology 4.3.1 The Optimal Choice between Earnout and Non-Earnout Currencies Following the previous literature (Kohers and Ang, 2000; Datar et al., 2001; Reuer et al., 2004; and Mantecon, 2009), we construct a variable that reflects whether bidders choose earnouts when it is the optimal method of financing a bid. Several transaction-specific, firm- and country-specific features may determine whether bidders and targets agree upon the optimal payment method to mitigate information asymmetries and uncertainties as to the correct value of the target. We employ a logistic regression approach and maximum likelihood regression parameters are estimated which are used to compute the likelihood of the earnouts use for each bid in our sample. We apply this test for both domestic sample and foreign one and we estimate the ‘optimal’ use of earnouts in each bid for both domestic and CBA samples. The dependent variable in the logistic model is a dummy variable that takes the value of 1 if in a M&A bid earnout is used versus 0 if only non-earnouts currencies are used and it is regressed against on a set of independent variables which are discussed bellow16

. In fact, for the domestic only sample we use the following variables in the logistic regression (common variables for both domestic and foreign sample):

• Bidder and target characteristics: the bidder age; the size of the acquiring firm; the transaction value; the relative size of the bid; and the bidder growth opportunity as measured by the market-to-book value ratio;

• Target status: dummy variables that assume a value of 1 if the target firm is a private firm; and 0 otherwise;17

• Industry focus of acquisition: a set of dummy variables that take the value of 1 (0) when the acquisition is (a) focused acquisition or share the same 2-digit SIC code (diversifying acquisition or do not share the same 2-digit SIC code).

• Target industry affiliation: 12 dummy variables, one to represent each 2-digit industry to which the target belongs (see Appendix A for the industries and their definitions).18

For the CBA only sample we use, in addition to the above variables, the following variables in the logistic regression – this is to capture various cross-country effects regarding the different levels of 16 Please see the Appendix A for an analytical description of the variables employed in the logit models. 17 In our regressions the status of both a subsidiary and a public target is captured by the intercept term. This is to avoid the singular matrix in our analysis. 18 The effect of ‘Industrials’ as a sector is captured by the intercept term in the model to avoid the singular matrix in our analysis.

16

investor protection, differences in corporate governance characteristics/mechanisms, and differences in the level of taxation between the home and the host countries:19

• Corporate governance, legal system, investor protection, and taxation characteristics: Tax differentials, Rule of law, Common law vs. civil law, Oppressed minorities mechanism, Pre-emptive rights, 1 share 1 vote, Proxy by mail, Cumulative voting, Shares not blocked before meeting, Secured creditors first, Restrictions for going into reorganization, Management does not stay, and No automatic stay on secured assets. The following discussion focuses on the impact of each of the above characteristics on the use of earnouts in foreign target M&A:

o Common law vs. civil law. Extant literature suggests that foreign bidders using

earnouts to acquire US targets are mainly from countries with common-law traditions, which maximizes further their ability to enforce such contracts if necessary (Kohers and Ang, 2000; Datar et al., 2001; Reuer, Shenkar, and Ragozzino, 2004). Such views allow us to create the expectation that US bidders acquiring foreign targets that based in countries with common-law courts (see Appendix A) are more likely to use earnouts than other means of financing (i.e. cash, stock, or mixed payments).

o Rule of law. Previous research discusses various approaches on the likely factors that affect the use of earnouts in domestic and foreign M&A. In fact, one of the major reason that decreases the use of earnouts in CBA is related to the different corporate governance systems between the participating firms’ countries of residence. For example, Datar et al. (2001) investigate the likelihood of the use of earnout in CBA and find that foreign bidders of US targets are less likely to use earnout as a method of payment than US domestic bidders acquiring domestic targets. They argue that this result is due to the unwillingness of target firms to accept deferred payments to avoid future disputes concerning the determination of the residual consideration payable to target shareholders, arising from differences in accounting practices and corporate governance characteristics between the acquirer and target countries. Others also suggest that the force of earnout contracts is much more challenging for the managers of participating firms particularly in cases where various corporate governance

19 It should also be well noted at this stage that countries under the Anglo-Saxon legal system protect the minority of investors the most and have stronger corporate governance mechanisms. Thus, earnout payment is more likely to be used in countries with the Anglo-Saxon legal system, where its process can be monitored and controlled more effectively (see also Datar et al., 2001). Moreover, Kohers and Ang (2000) suggest that “the enforcement of earnout contracts may be particularly complicated in cross-border mergers if the legal environments of the two firms are notably different.” (Page 451).

17

characteristics vary significantly between the merging firms’ countries. Whether a particular earnout contract will be forced in order to influence the value gains during the post-M&A period is therefore still under investigation. In order to measure this in the present paper we employ the rule of law (see Appendix A). In fact the rule of law captures perceptions of the extent to which agents have confidence in and abide by the rules of society, and in particular the quality of contract enforcement20

o As discussed previously, the quality of the corporate governance mechanisms provide an important determinant of the enforceability of earnout contracts, particularly in the context of foreign targets M&A (Kohers and Ang, 2000; Datar et al., 2001, Reuer et al., 2004; Mantecon, 2009). To capture the quality of the corporate governance systems across the world and also to capture the differences between the US and other corporate governance systems, we employ the following proxies: Oppressed minorities mechanism (which provides minority shareholders a judicial venue to challenge the decisions of management), pre-emptive rights (which provide shareholders the first opportunity to buy new issues of stock), one-share one-vote (in which Commercial Code of the country requires that ordinary shares carry one vote per share), proxy by mail (in which Commercial Code allows shareholders to mail their proxy vote to the firm), cumulative voting (in which Commercial Code allows shareholders to direct all of their votes for one candidate standing for election to the board of directors), shares not blocked before meeting (in which Commercial Code does not allow firms to require that shareholders deposit their shares prior to a General Shareholders Meeting), secured creditors first (in which secured creditors are ranked first in the distribution of the proceeds that result from the disposition of the assets of a bankrupt firm), management does not stay (in which an official appointed by the court, or by the creditors, is responsible for the operation of the business during reorganization), and no automatic stay on secured assets (in which the reorganization procedure does not impose an automatic stay on the assets of the firm upon filing the reorganization petition the reorganization procedure does not impose an automatic stay on the assets of the firm

, property rights, the police, and the courts, as well as the likelihood of crime and violence (this variable refers to the target firm’s country). The impact of rule of law on the prediction of earnouts has not addressed by previous studies in the relevant literature and thus our paper is the first that investigates its impact.

20 In a similar discussion, Mantecon (2009) analyzes the variable Enforceability of Contracts, which measures the level to which contracts are protected (see Djankov et al., 2003).

18

upon filing the reorganization petition) (see Appendix one for the definition of the variables).

o Tax differentials. Tax differentials between the bidding and the target firm’s country of residence may cause significant variation on the value and direction of FDI over time. In fact, Grubert and Mutti (1991), Hines and Rice (1994), and Altshuler, Grubert, and Newlon (2001) show that a 1% increase in the local tax rate reduces the FDI stock between 0.1% and 2.8%. Furthermore, Hartman (1984), Boskin and Gale (1987), Newlon (1987), and Young (1988) show that the tax elasticity of FDI is around −0.6. As a result, in the present paper we investigate whether the tax difference (see Appendix A) that observed between the US and the target firm’s country or residence has a significant impact upon the enforcement of the use of earnouts, which will further help in mitigating certain risks associated with any future change in the tax policy of participating firms’ countries and thus the synergistic gains accrued into the final entity. The impact of tax difference on the prediction of earnouts has not been addressed by previous studies in the relevant literature and thus our paper is the first that investigates its impact.

The logit models (see Tables 3a and 3b) provide the classification matrices (see Tables 4a and 4b) of actual sample payment currency versus the predicted one. Based on this, we construct two new variables which are named ‘Correct Currency Domestic’ (CC_DOM) and ‘Correct Currency CBA’ (CC_CBA) which are taking the value of 1 if the actual currency in a sample M&A bid is the same with the predicted one, and 0 if otherwise. More specifically, the variable is assigned the value of 1 if the in the M&A bid earnout is used and the logit model predicts the use of earnout. 4.3.2 Analysis of announcement period abnormal returns The commonly used methodologies for estimating announcement period abnormal returns to acquirers require long estimation period returns. Since the sample used in the paper includes frequent acquirers, these methodologies are to some extent inappropriate. Therefore, in line with a number of recent studies with similar sample features (Fuller et al. 2002; Faccio et al. 2006), the announcement period abnormal returns are estimated using the market-adjusted model:21

, , ,A i t i t m tR R R= − (1)

21 Moreover, Brown and Warner (1980) suggest that the adjustment for the firm’s systematic risk, beta, does not improve the precision of the short-term abnormal returns. Hence, the use of market adjusted return does not affect the robustness of our findings.

19

where: ARi.t is the abnormal return to bidder on day ; Ri.t is the return on firm/bidder at day , Rm,t

is the value-weighted market return index at day t. The announcement period cumulative excess return is the sum of the abnormal returns of the 5-days (t-2 to t+2) surrounding the day of the announcement of the bid, day 0. In the first instance, the announcement period abnormal returns of US acquirers are analyzed by method of payment used as well as the use of earnout (non-earnout versus earnout). Then, differentials between the gains to bidders using cash or stock or mixed payments and the gains to bidders using earnout, are computed. To assess the comparative performance of different groups of acquirers, we test for the difference in means and medians. Prior studies reviewed in section 2 and 3 above have examined a number of factors that influence acquirer’s value gains including: (1) the bidding firm’s age22, (2) the bidding firm’s size, (3) the acquisition’s transaction value, (4) the relative size of the bid, (5) the bidding firm’s growth opportunities, (6) the target firm’s listing status, (7) the earnout use as the currency of payment, and (8) whether the acquisition is focused or diversifying and whether they are same country or cross-border acquisitions23

. We estimate multivariate regression models of the abnormal returns to acquirers as a function of these variables. Further, unlike previous studies, we include the variables CC_DOM and CC_CBA defined above to test whether the use of earnout when it is optimal enhances the wealth gains to bidders. In particular, the following equation is estimated:

(2)

where, the intercept, α, measures the abnormal returns to bidders after accounting for the effects of all explanatory variables, X, simultaneously. The dependent variable, CAR, is the announcement period cumulative abnormal return of acquirers:

2

,-2

t

i i tt

CAR AR=+

=

= ∑

The vector of explanatory variables, X, includes a number of factors that are known to affect bidders’ gains. Moeller et al. (2004), among others, show that on average smaller acquirers gain more than larger acquirers from takeovers. Therefore, acquirer’s size, measured by the log of the market value four

22 Zhang (2006) shows that investors tend to have more information on firms with longer histories. That is, firms with longer trading history tend to have lower information asymmetry. Therefore, the age of the acquirer, measured by the log of the number of days between the day of bid announcement and the date of the company’s first record in Datastream, is included in the model. 23 It will be noted that these variables also appear as explanatory variables in our logistic model described earlier. Since prior literature suggests that these are related to shareholder value gains in acquisitions we include them. The output of the logistic model is included in the form of CC_DOM and CC_CBA variables.

i t i t

1

N

i i ii

CAR Xα ε=

= + +∑

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weeks prior to the announcement of bid, is included in Equation 2. Extant literature (see for example Fuller et al. 2002) shows that bidder’s gains are positively related to the relative size of the bid. Hence, the relative size of the bid, measured by the ratio of deal value to acquirer’s market capitalization, is also included in Equation 2. It is also evident from the literature that the size of the bid may affect bidder’s gains (Stutz et al. 1990). Therefore, the log of the deal value is also included in the model. Rau and Vermaelen (1998) and Sudarsanam and Mahate (2003) show that value acquirers with low market-to-book values outperform glamour acquirers with high market-to-book values. Therefore, the ratio of market-to-book value of equity four weeks prior to the announcement of the bid is used to control for the growth opportunity of acquirers in Equation 2. Although the debate on whether corporate diversification enhances or destroys shareholders’ wealth is ongoing, the literature agrees that it is likely to affect firm’s value (Ekkayokkaya and Paudyal, 2009; for a review of these studies see Sudarsanam, 2003, ch. 8). If target and bidder belong to the same industrial sector, the integration of the two firms should be easier and the synergy gains higher. Such bids should also benefit from the experience of the bidder’s managers in managing the target line of business, and hence generate higher returns. However, firms acquiring targets that operate in an unrelated business may gain from diversification causing a reduction in the volatility of cash flow of the combined firm. Therefore, to control for the potential effect of corporate diversification a dummy variable that takes a value of 1 for diversifying bids (i.e., target and acquirer do not share the same 2-digit SIC code) and 0 for focused bids is included in model 2. Other dummy variables that take the value of 1 and 0 are included to represent cross-border versus domestic bids, and private versus public or subsidiary target bids. Table 2 provides the definitions of the variables discussed above.

5. Results In this section we discuss the main findings of the paper. We begin with the discussion of the findings obtained from the logit models while we follow with the discussion of the findings from our univariate analysis. In the last part of this section we discuss the findings of the multivariate cross-section analysis. 5.1 Optimal use of earnout in both domestic and foreign acquisitions Tables 3a and 3b present the logistic models estimates of both domestic and cross-border samples respectively on the prediction of the ‘optimal’ earnouts use in our sample of interest. Our analysis conveys that older

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acquirers tend to make less use of earnouts to finance their both domestic and cross-border bids, although this is highly sensitive to each model’s specification. Furthermore we show that, irrespective the target firm’s domicile, the larger the relative size of the bid the higher the likelihood of the bidder to use earnouts (the size of the coefficients appear larger in the case of CBA, compared to domestic M&A, implying that in the case of CBA the effect of relative size is much stronger). This evidence supports evidence from previous literature, such as Kohers and Ang (2000) for the US market and Barbopoulos and Sudarsanam (2010) for the UK market. Indeed, large relative size of the bid implies that, relative to the size of the bidder, the target firm’s size is large enough or even larger than the size of the bidder, and thus the need of earnouts financing may be further compelled as an insurance of the successful completion, and also delivery of the expected synergistic gains (given that earnouts force the retention of the target firm’s managers). Bidder’s growth opportunities (as measured by the MTBV) influence negatively the earnouts choice, particularly in the case of domestic M&A, although this is very sensitive to each model’s specification. The strongest result that obtained from our logit models is that earnouts have a very high likelihood of being used in M&A bids of both domestic and foreign M&A bids of private target firms. Extant literature confirms that private target firms are more likely to be acquired using earnouts, compared to public and subsidiary targets (see also Kohers and Ang, 2000; Barbopoulos and Sudarsanam, 2010). Indeed private target firms are suffering from higher levels of information asymmetry (see also Chang, 1998; Fuller et al., 2002; Draper and Paudyal, 2006) while information regarding the private target firms’ valuation may also be limited (see Ekkayokkaya, Holmes, and Paudyal, 2009), which further increases the need of earnouts to be involved in the financing process of M&A of private targets. Furthermore, our logit model shows also a high (low) likelihood of using earnouts in diversifying M&A bids of domestic (foreign) targets.

(Insert Tables 3a and 3b about here) Tables 3a and 3b also present the logit model estimates on the impact of the target firm’s industry or sector, on the likelihood of earnouts use into both domestic and foreign M&A. Following our estimates it appears that bids of domestic target firms that operate in the high technology sector are more likely to be accompanied with earnouts currencies or contracts. This evidence clearly confirms evidence from previous literature such as Kohers and Ang (2000) and Barbopoulos and Sudarsanam (2010). Such decisions are mainly driven from the fact that the balance sheets of target firms in the high technology sector may be overpopulated by intangible assets, R&D, and human capital, which motivate the managers of the bidding firms to use earnouts to eliminate any valuation errors at the time of the M&A announcement while to retain the target firm’s managers in the post-merge period. In other words, when targets operate in ‘relatively intangible rich’ industries, which are either difficult to value or there is high uncertainty regarding the expected cash flows to be generated in the long-run, earnouts may provide a solution by mitigating these problems. Furthermore, bids of domestic target firms that operate in the consumer products sector, healthcare sector, and telecommunications sector, are also highly likely

22

to use earnouts to finance their bids. In addition, we also show that there is a high likelihood of using earnouts in foreign bids of targets that operate in the healthcare sector. Our analysis also presents a significant relationship between several country-specific variables and the likelihood of using earnouts in CBA. In fact the larger the differences of the tax rates between the bidding and the target firms’ countries, the higher the likelihood of using earnouts. In addition, we present a negative relationship between the likelihood of using earnouts and (a) the oppressed minorities mechanisms, (b) the pre-emptive rights, and (c) the management does not stay variable. Overall, our logistic models identify several variables that proxy for information asymmetry and valuation errors in both domestic M&A and CBA while our results confirm that the earnouts use is more likely when the bidder faces greater information asymmetry and valuation risks.

Defining correct currency domestic (CC_DOM) and correct currency foreign (CC_CBA) variables The logistic models for which the estimates are reported in Tables 3a and 3b provide two classification matrices of actual versus the predicted use of earnouts for both domestic and foreign samples respectively. In Tables 4a and 4b we report the matrices based on the prior probabilities of earnouts and non-earnouts use equal to the sample proportions of 7.1% (92.9%) and 8.5% (91.5%) for earnouts (non-earnouts) for both domestic and foreign samples respectively. The model correctly classifies earnouts acquisitions in 65.9% of the sample bids, and non-

earnouts acquisitions in 65.6%, of the cases for the domestic sample. In addition, our approach classifies earnouts acquisitions in 72.2% of the sample bids, and non-earnouts acquisitions in 64.4%, of the cases for the foreign sample. The overall classificatory accuracy is high 65.7% (65.1) for the domestic (foreign) sample respectively. Based on the estimates reported in the classification matrices, we identify the sample bids in which the model-predicted use of earnouts coincides with the actual use of earnouts for both domestic M&A and CBA samples respectively. The dummy variable CC_DOM and CC_CBA then assumes a value of 1. Where the model predicts use of earnouts but the actual currency is non-earnouts, CC_DOM and CC_CBA assumes a value of 0. In additions, where the model does not predict the use of earnouts but the actual currency is earnouts, CC_DOM and CC_CBA assumes a value of 0. Lastly, where the model does not predict the use of earnouts but the actual currency is non-earnouts, CC_DOM and CC_CBA assumes a value of 0.

(Insert Tables 4a and 4b about here)

Table 5 shows how the sample bids fall into the CC_DOM and CC_CBA categories. For the whole sample, 7.3% of sample bids use earnouts while 7.1% and 8.5% of domestic and foreign M&A bids respectively use earnouts. A similar percentage is obtained in the subsample of private acquisitions. In the case of domestic private [subsidiary] (public) acquisitions, correct currency is used in only 637 [14] (3) out of 6,776 [3,556] (3,616) sample bids; foreign private [subsidiary] (public) acquisitions, correct currency is used in only 100 [4] (0) out of 811 [572] (306) sample bids. Thus there seems to be a high degree of misalignment between the actual use of a payment currency and the optimal predicted currency in the subsamples of subsidiary and pubic company acquisitions.

23

(Insert Table 5 about here)

5.2 The Univariate Analysis Tables 6 to 7 present cumulative abnormal returns (hereafter CAR) that reflect the bidding firm’s performance in a 5-day event window (t-2 to t+2) centred on the bid announcement day, day 0, for all acquisitions and specific acquisition types. The analysis is divided into portfolios according to the alternative methods of financing, such as cash, stock, or mixed only, earnouts and non-earouts. Differences for each group of method of payment between the sample of domestic M&A and foreign ones are computed, and the hypotheses formulated above are tested within this univariate framework.

(Insert Table 6 about here) Table 6 reports announcement period abnormal returns to bidders of domestic versus CBA by methods of payment. We find that overall, and irrespective the impact of the various methods of payment, bidders’ gains from domestic and CBA are not quantitative and statistically different. However, when the impact of the various methods of payment is considered, it appears that bidders’ gains vary significantly. Indeed, bidders earn more from domestic M&A, compared to CBA, when financed with cash, while the opposite is observed when mixed payments are used (CBA outperform domestic M&A). The most important findings from Table 6 is that the use earnouts in the financing process of M&A bids yields similar returns to domestic and foreign bidders’ shareholders. Mantecon (2009) reports similar results for the US market and Barbopoulos and Sudarsanam (2010) for the UK market. In addition, although this finding is not adjusted for the effect for several other firm-specific, country- and transaction-specific characteristics, it does not support the hypothesis H2 (however even when we adjust the effect of several firm-specific, country- and transaction-specific features in the our multivariate cross-section analysis, we still do not support the hypothesis H2 and thus we further support previous literature).

(Insert Table 7 about here) Table 7 reports announcement period abnormal returns to bidders of domestic M&A versus CBA by the ‘optimal’ method of payment. Our findings convey that bidders of foreign target firms that use earnouts ‘optimally’ yield higher gains to their shareholders, compared to the gains generated to domestic bidders’ shareholders when they use earnouts ‘optimally’ (i.e. foreign bidders yield 2.36 higher gains to their shareholders compared to domestic bidders). Such findings clearly highlights that the ‘optimal’ use of earnouts in CBA provides an even more calibrated payment technique, even better than stock financing (differences in bidders’ gains between

24

domestic M&A and CBA are reported in table 6),24

that deals effectively with the high level of revaluation uncertainty that associated with CBA, compared to domestic M&A. Accordingly, such evidence fully support our hypothesis H3b which anticipates higher gains to foreign bidders, compared to domestic ones, when both using earnouts ‘optimally’. We also show that the strength of the differentials between the gains of shareholders of domestic bidders versus foreign ones vary significantly with the initial payment that used into earnouts agreements (i.e. whether the earnouts are attached to cash, stock, or mixed payments). In fact, we show that when cash is associated with earnouts, bidders of cross-border targets generate the higher gains to their shareholders. The explanation offered in light of this finding supports the view that cash payments direct all risks associate with adverse selection and post-merger integration failures to bidders’ shareholders, whereas the earnouts financing clearly helps in avoiding such issues. In addition, it appears that the less-strong differential between the gains of bidders’ shareholders from domestic versus CBA is obtained from M&A bids financed with the ‘optimal’ use of earnouts when stock is the initial payment method. Extant literature has confirmed that stock financing may provide a calibrated method of payment that helps in eliminating certain risks of adverse selection and post-M&A integration (see Hansen, 1987). In the context of our analysis, earnouts financing do not offer a far better insurance again potential errors neither at the time of the M&A announcement nor in the post-merger period.

5.3 The Cross-Section Analysis Tables 8a and 8b report findings from our multivariate analysis which accounts for several factors that simultaneously influence bidders’ gains during the acquisition’s announcement period.25

Results obtained from the cross-section analysis not only support the findings of our univariate analysis but also further corroborate the significant impact of the use of earnouts, and ‘optimal’ use of earnouts, on the announcement period gains accrued to bidders’ shareholders. The average acquirer generally earns a significant and large positive return around the announcement of the bid, as suggested by the positive and statistical significant intercept terms in Models 1 to 4 (Table 8a). Furthermore, the coefficients of earnout variable in the models 1 to 4 appear positive and highly statistical significant, indicating the positive gains directed to shareholders of bidders using earnouts after the effect of several transaction- and firm-specific characteristics is adjusted. These findings further corroborate the ability of acquirers to generate positive gains in the short-run when use earnouts in the payment process of M&A. Supporting the findings from previous literature such as Kohers and Ang (2000) and Barbopoulos and Sudarsanam (2010) we support our hypothesis H1 that earnouts lead to higher shareholder gains.

24 See Hansen (1987) for a more analytical discussion of the impact of stock financing on the elimination of risk of adverse selection. 25 The variables included in the model are: the age of the bidder, the size of the bidder, the transaction value of the bid, the relative size of the bid, the growth opportunity of the bidder, dummy variables that account for the presence of private targets, bids in different industries, foreign bids, earnouts use, whereas other interaction dummy variables are included to account for the interactive effect of the use of earnouts and other variables discussed above.

25

Our multivariate analysis in general, and more specifically Models 1 to 4 (Table 8a), further show that when the earnouts dummy interacts with the foreign bids dummy, bidders do generate similar gains to their shareholders from domestic M&A and CBA. Although such findings are similar to our univariate findings and support evidence from previous literature (such as Mantecon, 2009) they fail to support our hypothesis H2. However, our multivariate analysis shows that when bidders employ the correct currency to finance both domestic M&A and CBA, they yield positive and significant net value gains to their shareholders, as shown by the coefficients of CC_DOM and CC_CBA in Models 6 to 8. This result clearly supports the hypotheses H3a and findings from our univariate analysis. In addition, the coefficient of the interaction variables (a) Relative Size x EA, (b) Relative Size x CC_DOM and (c) Relative Size x CC_CBA, are positive and highly statistically significant across all Models, suggesting that in relatively large acquisitions the correct use of earnouts generates more value than when the acquisition is relatively small. Since the consequence of information asymmetry and valuation risk is more severe for bidders in larger deals, they can mitigate them and add value by choosing the earnouts when it is the ‘optimal’ currency. Overall, we provide evidence consistent with the findings reported elsewhere in the literature that the use of earnouts in M&A yields significant valuation benefits to bidding firms’ shareholders.

(Insert Tables 8a and 8b about here) Evidence reported across Models 6 to 8 of Table 8a further show that the initial payment methods where the earnouts are attached to, provide very useful information regarding the risk sharing between the two parties in the M&A, and thus affect significantly the gains of bidders in the short-run. Lastly, Table 8b shows only the gains of bidders that use earnouts ‘optimally’ to acquire either domestic or foreign target firms. Evidence reported in Table 8b clearly conveys the significant impact of the optimal use of earnouts to finance domestic versus foreign M&A bids. Models 13 to 16 (9 to 12) confirm that bidders using earnouts ‘optimally’ in CBA (domestic M&A) yield higher (lower) gains to their shareholders, compared to the ones of domestic M&A (CBA). Overall, findings reported in Table 8b confirm evidence reported in table 7 after the adjustment of several transaction- and firm-specific characteristics. Also, findings reported in Tables 8a and 8b further highlight that the ‘optimal’ use of earnouts in the context of domestic M&A versus CBA yield higher gains to foreign bidders’ shareholders, after the effect of several transaction, country, and firm-specific characteristics is adjusted.

6. Conclusion The main conclusions derived from this paper suggest that US bidders enjoy significant gains from corporate takeovers when they utilize earnouts as the acquisition payment currency, supporting evidence from previous literature. We also show that, in general, bidders using earnouts do not yield different wealth effects to their shareholders from domestic and foreign M&A, further supporting evidence by Mantecon (2009). We then compute the probability for using earnouts for each M&A bid in our sample of interest and, based on such

26

probability and some priori-probability levels that obtained from the proposition of earnouts use in our sample, we compute the ‘optimal’ use of earnouts in both domestic and foreign M&A respectively. We then show that, bidders’ gains from CBA appear significantly higher than gains from domestic M&A when bidders employ earnouts ‘optimally’ to finance their acquisitions. Such findings clearly highlights that the ‘optimal’ use of earnouts in CBA provides a well calibrated payment technique that deals effectively with the high level of revaluation uncertainty that is associated with CBA, compared to domestic M&A. In addition we show that the initial payment methods in earnouts shapes bidders’ gains significantly, further suggesting that the earnouts need appears in some cases more important than others. Overall, we show that the ‘optimal’ use of earnouts, along with several other transaction- and firm-specific characteristics, shape to a great extent the announcement period gains of US bidders that engaged into domestic versus foreign M&A.

27

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30

Appendix A: The variables

The table describes and defines the variables used in the paper and indicate the data source. SDC is Thomson-Reuters SDC M&A database and LLSV refers to La-Porta et al. With a dummy variable, a sample observation without the value of 1 has a value of 0. The various industries follow their SDC classification. Variables Age, RS, MV, and DV are log transformed in both logistic and OLS regressions. Predicted use of earnout is based on the logit model reported in tables 4a and 4b.

Variable type / name Description Source Variable type: Continued Age Number of days between day the bidder is first recorded on Datastream and bid announcement day. Datastream Market Value (MV) Acquirer’s market value of equity at four weeks prior to bid announcement, in million dollars Datastream Deal Value (DV) Bid transaction value, in millions dollars SDC Relative Size (RS) Ratio of DV to MV. Datastream; SDC

MTBV Market-to-Book Value of bidder equity at four weeks and book value of equity from the most recent accounting statement prior to bid announcement. Datastream

Rule of Law (variable name: trl_est)

Captures perceptions of the extent to which agents have confidence in and abide by the rules of society, and in particular the quality of contract enforcement, property rights, the police, and the courts, as well as the likelihood of crime and violence (this variable refers to the target firm’s country).

WGI Kaufmann et al

(2009) Tax differential Tax rate in the bidding firm’s country - Tax rate in the target firm’s country. Variable type: Dummy All Refers to the entire sample analysed in this paper. SDC Domestic Dummy =1 when both bidder and target are US firms. SDC CBA Dummy = 1 with a US bidder and non-US target. SDC Focused Dummy = 1 when bidder and target in the same 2-digit SIC industry. SDC Diversifying Dummy = 1 when bidder and target in different 2-digit SIC industries. SDC Cash Dummy = 1 when consideration is 100% cash. SDC Stock Dummy = 1 when consideration is 100% stock exchange. SDC Mixed Dummy = 1 when consideration is mixture of cash, stock, and other methods of payment excluding Earnout. SDC Earnout (EA) Dummy = 1 when consideration includes Earnout (EA) in addition to cash, stock or mixed. SDC Non-Earnout (Non-EA) Dummy = 1 with pure cash, or pure stock or mixed consideration without EA. SDC Private Dummy = 1 if target is private. SDC Public Dummy = 1 if target is publicly listed. SDC Subsidiary Dummy = 1 if target is a subsidiary firm. SDC Unlisted Dummy = 1 if target is unlisted i.e. private or subsidiary. SDC Target1 Dummy = 1 when target operates in the Industrials sector. Target2 Dummy = 1 when target operates in the Media & Entertainment industry sector. SDC Target3 Dummy = 1 when target operates in the Consumer Staples sector. SDC Target4 Dummy = 1 when target operates in the Consumer Products sector. SDC Target5 Dummy = 1 when target operates in the Financial Services sector. SDC Target6 Dummy = 1 when target operates in the Materials sector. SDC Target7 Dummy = 1 when target operates in the Retail sector. SDC Target8 Dummy = 1 when target operates in the High Technology sector. SDC Target9 Dummy = 1 when target operates in the Healthcare sector. SDC Target10 Dummy = 1 when target operates in the Energy and Power sector. SDC Target11 Dummy = 1 when target operates in the Real Estate sector. SDC Target12 Dummy = 1 when target operates in the Telecommunication sector. SDC

Common vs. Civil Dummy = 1 if the origin of the target firm is English Common Law. LLSV;

Foreign Law Encyclopaedia; Commercial Laws of the World

Oppressed minorities Mechanism (variable name: oppr_mi2)

Dummy = 1 if the Company Law or Commercial Code grants minority shareholders either a judicial venue to challenge the decisions of management or of the assembly or the right to step out of the company by requiring the company to purchase their shares when they object to certain fundamental changes, such as mergers, assets dispositions and changes in the articles of incorporation. Minority shareholders are defined as those shareholders who own 10 percent of share capital or less.

LLSV; Company Law or Commercial Code

Preemptive rights (variable name: prempt)

Dummy = 1 when the Company Law or Commercial Code grants shareholders the first opportunity to buy new issues of stock and this right can only be waved by a shareholders’ vote.

LLSV; Company Law or Commercial Code

Continued

31

The variables – Continued Variable name Description Data source

One share - one vote (variable name: c1sh_1vo)

Dummy = 1 if the Company Law or Commercial Code of the country requires that ordinary shares carry one vote per share. Equivalently, this variable equals one when the law prohibits the existence of both multiple-voting and non-voting ordinary shares and does not allow firms to set a maximum number of votes per shareholder irrespective of the number of shares she owns.

LLSV; Company Law or Commercial Code

Proxy by mail (variable name: mail_prx) Dummy = 1 if the Company Law or Commercial Code allows shareholders to mail their proxy vote to the firm.

LLSV; Company Law or Commercial Code

Shares not blocked before meeting (variable name: nshsbloc)

Dummy = 1 if the Company Law or Commercial Code does not allow firms to require that shareholders deposit their shares prior to a General Shareholders Meeting thus preventing them from selling those shares for a number of days.

LLSV; Company Law or Commercial Code

Cumulative voting or proportional representation (variable name: cumu_vot)

Dummy = 1 if the Company Law or Commercial Code allows shareholders to cast all of their votes for one candidate standing for election to the board of directors (cumulative voting) or if the Company Law or Commercial Code allows a mechanism of proportional representation in the board by which minority interests may name a proportional number of directors to the board.

LLSV; Company Law or Commercial Code

No automatic stay on secured assets (variable name: nauto_st)

Dummy = 1 if the reorganization procedure does not impose an automatic stay on the assets of the firm upon filing the reorganization petition. Automatic stay prevents secured creditors to gain possession of their security. It equals zero if such restriction does exist in the law.

LLSV; Bankruptcy and

Reorganization Laws

Secured creditors first (variable name: secu_1st)

Dummy = 1 if secured creditors are ranked first in the distribution of the proceeds that result from the disposition of the assets of a bankrupt firm. Equals zero if non-secured creditors, such as the Government and workers, are given absolute priority.

LLSV; Bankruptcy and

Reorganization Laws Management does not stay (variable name: mgt_nost)

Dummy = 1 when an official appointed by the court, or by the creditors, is responsible for the operation of the business during reorganization. Equivalently, this variable equals one if the debtor does not keep the administration of its property pending the resolution of the reorganization process.

LLSV; Bankruptcy and

Reorganization Laws Correct Currency Domestic (CC_DOM) Dummy = 1 when actual use of Earnout in domestic bids equals its predicted use. Tables 4a and 4b

Correct Currency Domestic (CC_CBA) Dummy = 1 when actual use of Earnout in domestic bids equals its predicted use. Tables 4a and 4b

32

Appendix B: Distribution of cross-border sample by target firm’s country

The table shows only the CBA activity by country name and the No of M&A bids that involved in only CBA. The last row refers to the total number of CBA in our sample of interest.

Country name No of M&A bids Argentina 11 Australia 75 Austria 5 Belgium 22 Brazil 2 Canada 365 Chile 5 Denmark 22 Finland 10 France 127 Germany 160 Greece 2 Hong Kong 15 India 15 Ireland 25 Israel 45 Italy 27 Japan 20 Malaysia 2 Mexico 1 Netherlands 51 New Zealand 14 Norway 17 Portugal 3 Singapore 8 South Africa 2 South Korea 17 Spain 13 Sweden 50 Switzerland 41 Taiwan 16 Thailand 3 United Kingdom 500 All 1,691

33

Table 1: Annual Distribution of All Merger Activities by target firm’s domicile, industry classification of the acquirer and target and methods of payment

The table presents the annual distribution of M&A bids announced by US bidders between 1986 and 2009. The distribution of the sample is presented on the basis of the target firm’s domicile, merging firms’ industry classification, and the various currencies of financing that used in the bids. Please refer to Appendix A for the definitions of the variables.

All Domestic CBA Focused Divers. EA Non-EA Cash Stock Mixed 1986 143 138 5 81 62 2 141 63 49 29 1987 153 150 3 91 62 5 148 59 58 31 1988 144 142 2 79 65 3 141 74 34 33 1989 229 214 15 136 93 9 220 91 84 45 1990 177 161 16 106 71 7 170 81 50 39 1991 222 196 26 145 77 10 212 72 72 68 1992 346 321 25 230 116 14 332 92 133 107 1993 457 428 29 290 167 21 436 148 178 110 1994 696 652 44 423 273 28 668 231 251 186 1995 733 671 62 457 276 26 707 222 291 194 1996 950 870 80 567 383 27 923 278 366 279 1997 1,251 1,142 109 734 517 55 1,196 347 461 388 1998 1,388 1,226 162 816 572 86 1,302 415 448 439 1999 1,179 1,051 128 708 471 62 1,117 348 465 304 2000 1,053 931 122 631 422 69 984 287 417 280 2001 760 663 97 459 301 60 700 271 198 231 2002 720 626 94 420 300 77 643 325 98 220 2003 684 625 59 428 256 79 605 305 101 199 2004 808 697 111 500 308 85 723 410 81 232 2005 904 778 126 540 364 80 824 482 71 271 2006 906 790 116 529 377 93 813 512 68 233 2007 835 710 125 494 341 99 736 471 45 220 2008 535 453 82 334 201 85 450 302 30 118 2009 366 313 53 220 146 54 312 191 42 79 Total 15,639 13,948 1,691 9,418 6,221 1,136 14,503 6,077 4,091 4,335

% - 89.19 10.81 60.22 39.78 7.26 92.74 38.86 26.16 27.72

34

Table 2: Summary Statistics In Panel A the sample is classified by target firm’s status, method of payment, SIC 2-digit industry classification and the target firm’s domicile. The sample comprises takeover bids announced by US bidding firms between 01/01/1986 and 31/12/2009 and recorded by the SDC. Bidders are firms listed in the main American Stock Exchanges. Variables are defined in Appendix A. N represents the number of bids; % is the number of bids in a group as a proportion of all bids; Mean of DV in $ millions is the mean of deal values of all bidders in each group. In panel B the mean and median are the group mean and median. EA value is based on subsamples involving only bids with earnout elements involved.

Panel A All EA Non-EA Cash Stock Mixed Focused Diversifying Domestic Foreign

All N 15,639 1,136 14,503 6,077 4,091 4,335 9,418 6,221 13,948 1,691 % - 7.26 92.74 38.86 26.16 27.72 60.22 39.78 89.19 10.81

Mean DV (in $m) 400.9 116.2 423.2 201.4 545.9 618.2 469.0 297.7 418.6 254.4

Private N 7,587 847 6,740 2,414 2,150 2,176 4,448 3,139 6,776 811 % 48.51 5.42 43.10 15.44 13.75 13.91 28.44 20.07 43.33 5.19

Mean DV (in $m) 81.7 79.0 82.0 70.7 69.0 107.5 83.8 78.7 81.8 81.0

Public N 3,924 16 3,908 1,146 1,634 1,128 2,615 1,309 3,616 308 % 25.09 0.10 24.99 7.33 10.45 7.21 16.72 8.37 23.12 1.97

Mean DV (in $m) 1,172.3 173.8 1,176.4 460.2 1,231.2 1,824.5 1,283.8 949.5 1,216.5 653.8

Subsidiary N 4,128 273 3,855 2,517 307 1,031 2,355 1,773 3,556 572 % 26.40 1.75 24.65 16.09 1.96 6.59 15.06 11.34 22.74 3.66

Mean DV (in $m) 254.2 228.1 256.0 209.0 237.6 376.4 291.7 204.4 249.2 285.0 Panel B

Deal Category MV (in mil $) MTBV RS DV (in mil $) EA Value (in mil $) mean median Mean median mean median mean median mean median

All 6,136.1 601.5 4.02 2.16 0.26 0.08 400.9 42.5 28.3 7.0 Domestic 5,712.9 569.9 4.02 2.10 0.26 0.08 418.6 42.5 28.7 9.0

Foreign 9,626.9 925.0 4.04 2.61 0.22 0.05 254.4 42.9 25.0 7.5 Focused 5,057.3 584.2 4.30 2.15 0.27 0.09 469.0 44.9 28.3 7.5

Diversifying 7,769.3 626.2 3.60 2.16 0.23 0.07 297.7 40.0 28.3 6.0 EA 3,487.7 339.4 3.02 2.21 0.19 0.09 116.2 26.7 28.3 7.0

Private (both EA and non-EA) 4,013.8 408.6 4.08 2.30 0.18 0.06 81.7 23.4 23.7 6.2 Public (both EA and non-EA) 11,082.0 1,379.0 3.95 1.98 0.37 0.15 1,172.3 158.9 52.2 22.5

Subsidiary (both EA and non-EA) 5,335.2 643.9 3.97 2.06 0.30 0.08 254.2 46.1 41.0 8.0 Non- EA 6,343.5 628.1 4.10 2.15 0.26 0.08 423.2 44.5

Cash (only Non-EA) 8,361.0 868.7 3.62 2.19 0.16 0.05 201.4 41.7 Stock (only Non-EA) 6,487.3 626.7 4.94 2.36 0.29 0.08 545.9 45.1 Mixed (only Non-EA) 3,379.7 393.5 3.97 1.94 0.39 0.14 618.2 49.0

35

Table 3a: Logistic regression of factors affecting the likelihood of earnout use

Maximum likelihood estimates of regression coefficients are presented for the domestic sample of interest only. The dependent variable is equal to one (=1) if earnout is used in the takeover, while it is equal to zero (=0) if some other method of payment is used. Please refer to Appendix A for variables’ definitions. The missing industry is the ‘Industrial’ one while its effect is captured by the intercept term in the model. Pseudo R-Squared is the likelihood based Pseudo R-squared. HL Goodness-of-Fit refers to the Hosmer and Lemeshow Goodness-of-Fit Test which tests the null hypothesis that there is no difference between the observed and predicted values of the response variables. a, b, c indicate significance at 1%, 5% and 10% respectively.

model 1 model 2 model 3 model 4 Intercept -3.063a -3.498a -3.260a -3.631a Log (Age) 0.012 0.038 -0.108a 0.070b Log (RS) 0.010a 0.097a 0.153a 0.073a MTBV -0.046a -0.056a -0.033b -0.049a Private 1.186a 1.161a 1.414a 1.096a Diversifying 0.124c 0.115 0.175c 0.089 Media & Entertainment -0.076 -0.171 0.140 -0.087 Consumer Staples 0.168 0.315 -0.131 0.134 Consumer Products 0.455a 0.549a 0.570a 0.329b Financial -0.885a -0.897a -0.562b -1.042a Material -0.624a -0.601b -0.794c -0.580b Retail -0.383c -0.214 -0.261 -0.611b High Technology 0.313b 0.256c 0.585a 0.237c Healthcare 0.690a 0.514a 1.075a 0.630a Energy and Power -0.673a -0.661a -0.534c -0.753a Real Estate -0.936a -0.727b -0.541 -1.460a Telecommunication 0.042 -0.054 0.538b -0.160 Cash (Initial Payment) 19.214 Stock (Initial Payment) 20.972 Mixed (Initial Payment) 19.122 Pseudo R-Squared (in %) 7.53 25.48 48.75 21.44 HL Goodness-of-Fit, Pr > Chi^2 0.094 0.062 0.293 0.155 N 13,948 13,948 13,948 13,948

36

Table 3b: Logistic regression of factors affecting the likelihood of earnout use

Maximum likelihood estimates of regression coefficients are presented for the CBA sample of interest only. The dependent variable is equal to one (=1) if earnout is used in the takeover, while it is equal to zero (=0) if some other method of payment is used. Please refer to Appendix A for variables’ definitions. The missing industry is the ‘Industrial’ one while its effect is captured by the intercept term in the model. Pseudo R-Squared is the likelihood based Pseudo R-squared. HL Goodness-of-Fit refers to the Hosmer and Lemeshow Goodness-of-Fit Test which tests the null hypothesis that there is no difference between the observed and predicted values of the response variables. a, b, c indicate significance at 1%, 5% and 10% respectively.

model 1 model 2 model 3 model 4 Intercept -2.513a -1.828c -5.360a -2.654a Log (Age) -0.038 -0.109 0.032 -0.007 Log (RS) 0.245a 0.284a 0.238a 0.206a MTBV -0.031 -0.062c -0.008 -0.041 Private 1.538a 1.387a 1.939a 1.513a Diversifying -0.309c -0.489b -0.088 -0.292c Media & Entertainment -0.433 -0.165 -0.377 -0.711 Consumer Staples 0.229 0.509 0.114 0.014 Consumer Products -0.145 -0.102 0.340 -0.395 Financial 0.024 -0.606 0.561 0.144 Material -0.071 0.172 -0.834 -0.144 Retail -0.808 -8.209 0.342 -0.760 High Technology 0.144 -0.059 0.615 0.100 Healthcare 0.687b 0.659c 0.967c 0.614c Energy and Power -0.752 -0.440 -0.616 -1.123c Real Estate 0.210 0.469 0.598 -0.351 Telecommunication 0.071 0.355 -0.106 -0.055 Cash (Initial Payment) 22.711

Stock (Initial Payment) 19.955 Mixed (Initial Payment) 18.773 Tax differentials 0.046b 0.054b 0.034 0.046b Rule of law -0.131 -0.109 -0.184 -0.108 Common vs. civil 0.494 0.674 0.454 0.355 Oppressed minorities mechanism -1.043c -1.316c -0.400 -1.083c Pre-emptive rights -0.552c -0.737c -0.331 -0.574c 1 share 1 vote 0.123 -0.664 0.727 -0.077 Proxy by mail 0.108 0.436 -0.064 -0.089 Cumulative voting 0.285 0.083 0.123 0.468 Shares not blocked before meeting -0.300 -0.384 -0.433 -0.171 Secured creditors first 0.742 0.726 1.149 0.603 Restrictions for going into reorganization 0.148 0.054 0.460 0.096 Management does not stay 0.952c 0.988 0.501 1.165c No automatic stay on secured assets -0.463 -0.483 -0.344 -0.547 Pseudo R-Squared (in %) 11.10 31.59 52.96 20.04 HL Goodness-of-Fit, Pr > Chi^2 0.903 0.070 0.755 0.640 N 1,691 1,691 1,691 1,691

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Table 4a: Classification matrix based on logistic model of earnout use

The table presents the predictions of the logistic regression (Model 1, Table 4a) for earnout use for domestic takeover bids only. The results are presented in a matrix form where the columns indicate the expected number of bids using earnout whereas the rows indicate the number of bids that actually used earnout. Please refer to Appendix A for the definitions of the variables. The matrix is based on the a priori probability of a sample observation belonging to the earnout group. This is the same as the sample proportion of earnout, i.e., 7.1% (this represents the percentage of earnout financed bids in the domestic market by US bidders). Sensitivity is a measure of classification accuracy, i.e., the model predicted group is the same as the actual group of a sample bid. It is 65.9% for the earnout group meaning that the model correctly classifies 65.9% of sample earnout bids correctly. Similarly 65.6% of non-earnout bids are correctly classified. The overall sensitivity of the model is 65.7%. Misclassification rate is referred as ‘false positive’, i.e., non-earnout observations being classified as earnout (=87.2%) and as ‘false negative’, i.e., earnout observations being classified as non-earnout (=3.8%). Expected / Classified by Model

EA Non-EA All Sensitivity %

Actual group EA 654 338 992 65.9 = (654/992) Non-EA 4,452 8,504 12,956 65.6 = (8,504/12,956)

All 5,106 8,842 13,948 65.7 = [(654+8,504)/13,948] Misclassification % 87.2 = (4,452/5,106) 3.8 = (338/8,842)

Table 4b: Classification matrix based on logistic model of earnout use

The table presents the predictions of the logistic regression (Model 1, Table 4a) for earnout use for foreign takeover bids only. The results are presented in a matrix form where the columns indicate the expected number of bids using earnout whereas the rows indicate the number of bids that actually used earnout. Please refer to Appendix A for the definitions of the variables. The matrix is based on the a priori probability of a sample observation belonging to the earnout group. This is the same as the sample proportion of earnout, i.e., 8.5% (this represents the percentage of earnout financed foreign bids by US bidders). Sensitivity is a measure of classification accuracy, i.e., the model predicted group is the same as the actual group of a sample bid. It is 72.2% for the earnout group meaning that the model correctly classifies 72.2% of sample earnout bids correctly. Similarly 64.4% of non-earnout bids are correctly classified. The overall sensitivity of the model is 65.1%. Misclassification rate is referred as ‘false positive’, i.e., non-earnout observations being classified as earnout (=84.1%) and as ‘false negative’, i.e., earnout observations being classified as non-earnout (=3.9%). Expected / Classified by Model

EA Non-EA All Sensitivity %

Actual group EA 104 40 144 72.2 = (104/144) Non-EA 550 997 1,547 64.4 = (997/1,547)

All 654 1,037 1,691 65.1 = [(104+997)/1,691] Misclassification % 84.1 = (550/654) 3.9 = (40/1,037)

38

Table 5: Descriptive statistics on the right and wrong use of earnout by sample bidders

The table presents the merger activity using earnout by target origin (domestic and CBA), target status, and whether earnout is used as predicted by the logit model. Correct Currency Domestic (CC_DOM) and Correct Currency CBA (CC_CBA) are defined by comparing the actual EA and predicted EA use at the bid in each group of M&A bids, i.e. domestic and CBA samples separately. Please see Appendix A for definitions of the variables. N is number of bids; % is number of bids in a group as a proportion of all bids using earnout.

Panel A: Domestic Panel B: CBA

EA Correct Currency Domestic (CC_DOM)

EA Correct Currency CBA (CC_CBA)

All N 992 654 144 104 % - 66 - 72

Private N 736 637 111 100 % 74 64 77 69

Public N 16 3 0 0 % 2 0 0 0

Subsidiary N 240 14 33 4 % 24 1 23 3

Table 6: Announcement Period Abnormal returns to Bidders of Domestic versus CBA bids by Methods of Payment

Announcement period, 5-day [-2, +2], abnormal returns (in percent) of all sample (Panel A), divided by the target firm’s domicile (Panels B and C), by methods of payment (cash, stock, mixed and earnout), and differentials in performance between the domestic versus cross-border bids (Panel D) are presented. Please see Appendix A for definitions of the variables. Abnormal returns (AR) are market adjusted returns (please see equation 1 in the text). Statistical significance of difference in gains between two groups of bidders is tested using the T-test of equality of means. Significance of the median is tested by using the ‘Sign’ test. Significance of the difference between the medians of two groups of bidders is tested by using the Wilcoxon Two-Sample Test. N refers to number of observations in each portfolio. a, b, c indicate significance at 1%, 5% and 10% respectively.

Panel A: All sample

All Cash Stock Mixed Earnout Non EA Mean 1.27 1.30 0.75 1.60 1.80 1.23

p-value <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 Median 0.47 0.65 -0.23 0.67 0.91 0.45 p-value <.0001 <.0001 0.0565 <.0001 <.0001 <.0001

N 15,639 6077 4091 4335 1136 14503 Panel B: Domestic Bids

Mean 1.27 1.38 0.79 1.50 1.64 1.24 p-value <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 Median 0.45 0.67 -0.22 0.61 0.87 0.44 p-value <.0001 <.0001 0.0944 <.0001 0.0002 <.0001

N 13,948 5,151 3,867 3,938 992 12,956 Panel C: Foreign Bids

Mean 1.32 0.82 0.10 2.59 2.89 1.17 p-value <.0001 <.0001 0.8828 <.0001 0.0008 <.0001 Median 0.59 0.54 -0.84 1.34 1.34 0.55 p-value <.0001 0.0014 0.2560 0.0026 0.0549 0.0004

N 1691 926 224 397 144 1,547 Panel D: Domestic bids – Cross border bids (Differentials)

Mean -0.05 0.56 0.68 -1.09 -1.25 0.07 p-value 0.8074 0.0156 0.3271 0.0295 0.1266 0.7586 Median -0.14 0.13 0.62 -0.73 -0.47 -0.11 p-value 0.1766 0.1205 0.0918 0.0108 0.2245 0.2344

39

Table 7: Announcement Period Abnormal returns to Bidders of Domestic versus CBA bids by the ‘Optimal’ Method of Payment

Differentials in performance between domestic and cross-border bids are presented on the basic of the use of the ‘optimal’ or ‘correct’ method of payment. Panel A reports differentials in performance between domestic and cross-border bids where the prediction of the optimal method of payment in the logit model is not adjusted by the nature of initial method of payment in the earnout process. Panel B reports differentials in performance between domestic and cross-border bids where the prediction of the optimal method of payment in the logit model is adjusted by the nature (cash) of the initial method of payment in the earnout process. Panel C reports differentials in performance between domestic and cross-border bids where the prediction of the optimal method of payment in the logit model is adjusted by the nature (stock) of the initial method of payment in the earnout process. Panel D reports differentials in performance between domestic and cross-border bids where the prediction of the optimal method of payment in the logit model is adjusted by the nature (mixed) of the initial method of payment in the earnout process. Please see Appendix A for definitions of the variables. Abnormal returns (AR) are market adjusted returns (please see equation 1 in the text). Statistical significance of difference in gains between two groups of bidders is tested using the T-test of equality of means. Significance of the median is tested by using the ‘Sign’ test. Significance of the difference between the medians of two groups of bidders is tested by using the Wilcoxon Two-Sample Test. N refers to number of observations in each portfolio. a, b, c indicate significance at 1%, 5% and 10% respectively.

Domestic CBA Domestic – CBA Panel A: The initial payment is not included in the logistic regression

Mean 1.27 3.63 -2.36 p-value 0.0003 0.0006 0.0150 Median 0.56 1.34 -0.78 p-value 0.0314 0.0619 0.0733

N 654 104 Panel B: Cash is the initial payment in the logistic regression

Mean 1.40 4.02 -2.62 p-value <.0001 0.0004 0.0078 Median 0.66 1.46 -0.80 p-value 0.0074 0.0594 0.0676

N 683 102 Panel C: Stock is the initial payment in the logistic regression

Mean 1.52 3.16 -1.64 p-value <.0001 0.0020 0.0754 Median 0.64 1.53 -0.89 p-value 0.0081 0.0572 0.1218

N 720 111 Panel D: Mixed is the initial payment in the logistic regression

Mean 1.54 3.72 -2.18 p-value <.0001 0.0006 0.0284 Median 0.83 1.17 -0.34 p-value 0.0031 0.1332 0.1383

N 678 100

40

Table 8a: Determinants of Announcement Period Gains to Bidders: Cross Sectional Analysis

Announcement period (5-days) market-adjusted abnormal returns for the full sample of bidders are regressed on a set of explanatory variables. Equation (2) (see text on this model) is estimated using the ordinary least squares:

(2)

The intercept (α) measures the abnormal returns generated to bidders’ shareholders after accounting for the effects of all explanatory variables. In models 1 to 4 the initial method of payment in the earnout agreement is not included in the regression. In model 6 the prediction of the optimal method of payment in the logit model is adjusted by the nature (cash) of the initial method of payment in the earnout process. In model 7 the prediction of the optimal method of payment in the logit model is adjusted by the nature (stock) of the initial method of payment in the earnout process.In model 8 the prediction of the optimal method of payment in the logit model is adjusted by the nature (mixed) of the initial method of payment in the earnout process. See Appendix A for the definitions of the variables. Age, MTBV, MV, DV and Relative Size are in logarithmic form. Standard errors are corrected for heteroscedasticity by using White’s (1980) heteroscedasticity consistent standard errors method. a,b,c indicate significance at 1, 5, and 10 percent respectively.

Dependent Variable: CAR Model 1

Model 2

Model 3

Model 4

Model 6cash

Model 7stock

Model 8mixed

Intercept 0.055a 0.045a 0.054a 0.045a 0.046a 0.046a 0.046a Age -0.002a -0.004a -0.002a -0.004a -0.004a -0.004a -0.004a MTBV 0.001 0.001 0.001 0.001 0.001 0.001 0.001 MV -0.005a -0.005a DV 0.002a 0.002a Relative Size 0.004a 0.004a 0.004a 0.004a 0.004a Private 0.009a 0.012a 0.009a 0.012a 0.012a 0.012a 0.012a Diversifying 0.002 0.002 0.002 0.002 0.002c 0.002 0.002 Foreign 0.003 0.003 0.003 0.003 0.002 0.003 0.002 Earnout (EA) 0.032a 0.035a 0.032a 0.036a Cash Init. Payment 0.001 -0.001 Stock Init. Payment -0.001 -0.001 Cor. Curren. Dom (CC_DOM) 0.039b 0.037a 0.019 Cor. Curren. CBA (CC_CBA) 0.130a 0.061b 0.120a Private × EA -0.018a -0.019a -0.018a -0.019a Diversifying × EA -0.011b -0.011b -0.011b -0.011b Foreign × EA 0.012 0.012 0.012 0.012 Relative Size × EA 0.006a 0.007a 0.006a 0.007a Private × CC_DOM -0.025c -0.020b -0.005 Diversifying × CC_DOM -0.014b -0.004 -0.008 Relative Size × CC_DOM 0.006b 0.009a 0.006b Private × CC_CBA -0.083c 0.002 -0.049 Diversifying × CC_CBA -0.065a -0.049a -0.061a Relative Size × CC_CBA 0.005 0.013b 0.016b F-stat 29.47a 25.85a 25.26a 30.51a 21.51a 20.82a 20.45a Adjusted R2 (in %) 2.21 1.79 2.21 1.73 1.89 1.83 1.80 N 15,639 15,639 15,639 15,639 15,639 15,639 15,639

1

N

i i ii

CAR Xα ε=

= + +∑

41

Table 8b: Determinants of Announcement Period Gains to Bidders: Cross Sectional Analysis

Announcement period (5-days) market-adjusted abnormal returns for only the sample of bidders that the logit model predicts that the earnout is used ‘optimally’ or ‘correctly’ as the method of payment are regressed on a set of explanatory variables. Equation (2) (see text on this model) is estimated using the ordinary least squares:

(2)

The intercept (α) measures the abnormal returns generated to bidders’ shareholders after accounting for the effects of all explanatory variables. See Appendix A for the definitions of the variables. Age, MTBV, MV, DV and Relative Size are in logarithmic form. Standard errors are corrected for heteroscedasticity by using White’s (1980) heteroscedasticity consistent standard errors method. a,b,c indicate significance at 1, 5, and 10 percent respectively.

Dependent Variable: CAR Model 9

Model 10

Model 11

Model 12

Model 13

Model 14

Model 15

Model 16

Intercept 0.134a 0.131b 0.053c 0.121a -0.049c 0.039 0.025 0.019 Age 0.003 0.001 0.004 0.002 0.003 0.001 0.004 0.002 MTBV 0.001 0.003c -0.001 0.001 0.001 0.003c -0.001 0.001 Relative Size 0.019a 0.012c 0.017a 0.020a 0.012a 0.012a 0.013a 0.011a Private -0.058 -0.066 0.013 -0.038 0.074a -0.011 -0.005 0.005 Diversifying -0.052a -0.062a -0.049a -0.060a -0.011c -0.010c -0.003 -0.006 Cor. Curren. Dom (CC_DOM) -0.183a -0.092c -0.028 -0.102b Cor. Curren. CBA (CC_CBA) 0.183a 0.092c 0.028 0.102b Private × CC_DOM 0.132b 0.055 -0.018 0.042 Diversifying × CC_DOM 0.042b 0.052b 0.046b 0.055b Relative Size × CC_DOM -0.007 0.001 -0.004 -0.009 Private × CC_CBA -0.132b -0.055 0.018 -0.042 Diversifying × CC_CBA -0.042b -0.052b -0.046b -0.055b Relative Size × CC_CBA 0.007 -0.001 0.004 0.009 F-stat 5.64a 5.48a 5.57a 4.30a 5.64a 5.48a 5.57a 4.30a Adjusted R2 (in %) 6.35 5.98 5.75 4.76 6.35 5.98 5.75 4.79 N 758 785 831 778 758 785 831 778

1

N

i i ii

CAR Xα ε=

= + +∑