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Investor Protection and the Choice of Method of Payment in European M&A Transactions.

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Faculty of Economics and Business University of Groningen

Investor Protection and the Choice of

Method of Payment in European M&A

Transactions.

Abstract

Investor protection is known to encourage the development of debt- and equity markets. We analyze a data set of 2,741 M&A transactions to investigate the role of investor protection in the method of payment decision for European bidders. We find that the existence of an effect of both bidder’s debt capacity and growth opportunities on the choice of method of payment depends on the level of creditor- and shareholder protection respectively. The results are not robust after using a binary- instead of an ordinary dependent variable. However, in the robustness test we do find a highly significant, negative effect of the level of shareholder protection.

JEL classification: G32; G34

Keywords:

Mergers and Acquisitions; Method of payment; Capital structure

Supervisor: prof. dr. Wolfgang Bessler Co-assessor: dr. Peter Smid

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5 1. Introduction

Since the end of the 1990s, global merger and acquisition (M&A) activity has increased, especially in Europe. An analysis by Institute for Mergers, Acquisitions and Alliances (2019), shows that the European M&A market reaches over 10,000 transactions for the first time in 1998. With the number of deals increasing almost every year, annual transactions amount to more than 17,000 in 2018. Besides this, acquisitions in Europe have become remarkable in terms of their size and geographical distribution. The total annual deal value sums up to more than 1,000 billion euro for the past four years in a row now. Although the number of domestic M&As is still predominant in Europe, the value and likelihood of completion of foreign deals increased significantly at the beginning of the 21st century1.

However, trends are not only visible in terms of volume and geographical distribution. Also the form of payment used to complete a transaction is subject to a clear trend. Boone et al. (2014) find that from 1990 onwards, cash payments surged significantly while stock payments decreased. Alexandridis et al., (2011) analyze the sixth merger wave, which happened from 2003 till late 2007, for the U.S. specifically and find that there were significantly more cash deals and fewer stock deals. Appendix A shows that this pattern is also visible in the European data set of this study.

Several M&A studies investigate the difference in reaction of stock prices on the method of payment. As one of the first, Travlos (1987) shows that announcement returns are significantly higher for cash deals in comparison to stock deals. While announcements of all-stock bids destroy value for bidder shareholders (Franks et al., 1991; Moeller et al., 2004), announcements of all-cash bids generate ‘normal’ returns (Travlos, 1987). More

1 This are the particular findings of Moschieri and Campa (2014) who investigate the trends in the

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6 than two decades later, Alexandridis et al. (2011) find that acquisitions, despite the method of payment, still destroy value for acquiring shareholders during the sixth merger wave from 2003 till 2007. They find no significant differences in sign and size of the abnormal returns in comparison to the fifth merger wave. In a later study however, Alexandridis et al. (2017) show that, in stark contrast with average earlier findings, this trend of value destroying acquisitions has been largely reversed since 2009. They find that, on average, next to cash deals, even stock deals gain positive returns for the first time in history.

But what are the underlying reasons firms choose to pay with cash, shares, or a mixed form? Several studies investigate this topic and try to determine which factors influence the choice of method of payment in M&As. Most of these studies focus only on bidder-, target-, and deal characteristics. However, empirical findings about the significance and sign of payment determinants of the method of payment still contradict each other. Besides this, the previous literature does not pay much attention to factors of the environment where a transaction takes place. Ismail and Krause (2010) conclude that there is still a significant gap in our understanding of the determinants of the payment method. They suggest that it would be of interest to include additional factors that are not directly related to the target, bidder or the deal itself, but the environment in which they are announced in, like country-specific factors.

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7 influencing the method of payment. Several determinants of the choice of payment method are related to asymmetric information and agency theories, which makes it interesting to investigate what moderating role investor protection can play in the choice of payment method.

Investor protection can be divided into the protection of creditors and shareholders. Therefore, this study investigates the effect of those two factors separately. However, we start by investigating the effect of two bidder characteristics related to creditors and shareholders: debt capacity and growth opportunities. Thereafter, this paper analyses the potential moderating effect of investor protection. Altogether, this leads to the following research question:

Do bidder’s debt capacity and growth opportunities affect the choice of method of payment and does investor protection has a moderating effect on these relationships?

The paper is structured as follows. The first section describes the underlying theoretical and empirical literature of this study and derives the hypotheses based on theory and previous findings. Thereafter, we discuss the methods and report the results. At last, we end the paper with a conclusion, limitations, and suggestions for future research.

2. Literature review and hypothesis development

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8 discuss the three most known capital structure theories; the trade-off theory, the pecking order theory, and the market timing theory. The different payment methods and their possible determinants are discussed in section 2.4.

2.1 Trade-off theory

The static trade-off theory states that firms have target debt levels that are reached when firms balance the tax benefits of debt against the costs of financial distress (Kraus and Litzenberger, 1973), which include bankruptcy-related agency costs of debt (Jensen and Meckling, 1976; Myers, 1977; Stulz, 1990). A tax advantage of debt financing arises because interest charges are tax deductible. In this way, financial leverage decreases a firm’s income tax liability and thus increases its after-tax earnings and firm value. Without any offsetting cost of debt, this would suggest full debt financing. However, firms issuing debt are attached to the legal obligation to pay interest. In case the firm is not able to meet its debt obligation, it is forced into bankruptcy and incurs the associated penalties (Kraus and Litzenberger, 1973).

Although trade-off theory predicts that the marginal tax benefit of debt should be equal to the marginal expected bankruptcy cost, the empirical evidence is mixed. Miller (1977) argues that bankruptcy- and agency costs are, in comparison with the tax savings, relatively small and suggest ignoring them. He finds that despite the tax advantage of debt, firms are underleveraged in practice. Using a dynamic capital structure model, Ju et al (2005) calculate optimal capital structures in a realistic presentation of the traditional trade-off model. In contrast to Miller (1977), they find that the trade-off model does not predict that firms are underleveraged.

2.2 Pecking order theory

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9 selection problems. Managers have more information about the firm’s true value and future growth opportunities than outsiders. Outside investors therefore closely observe the firm’s financing decisions, including those in M&A, to obtain information about the firm’s prospects. When managers feel the firm is undervalued, they are reluctant to issue new equity because then new shareholders would benefit at the expense of old shareholders. Only when managers think the firm is overvalued, they can issue new equity to finance an M&A. By doing this, the firm signs to the market that the firm is overvalued. This is also called the signaling hypothesis.

Many empirical studies state that equity issues, including those for financing M&As, reduce firm value. And indeed, share prices drop when equity is used to finance M&As (Franks et al., 1991; Moeller et al., 2004). Hence, the best decision for a firm to finance its investments is to first use internal funds whenever available (Myers and Majluf, 1984). This source of financing avoids adverse selection problems.

The pecking order theory ranks financing sources in terms of how much they are influenced by information asymmetry. After internal funds, which have the lowest adverse selection costs, firms should finance their investments with debt. According to Myers and Majluf (1984) a firm should never issue equity except when financing with debt becomes infeasible.

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10 (2005) show that small, high-growth firms issue most of the equity and hence agree with Frank and Goyal (2003) that this finding contradicts the pecking order theory.

After accounting for debt capacity, Lemmon and Zender (2010) conclude that the pecking order theory gives a good description of financing behavior for a large sample of firms examined over an extended time period. In contrast, Leary and Roberts (2010) find little support for the ‘modified’ pecking order theory.

A dynamic version of the pecking order theory is the time-varying adverse selection explanation. This less strict interpretation implies that firms issue equity when stock prices are high and when they happen along with low adverse selection costs. Various empirical studies support this statement and find that low information asymmetry positively influences the probability of an equity issue (Bessler et al., 2011; Bharath et al., 2009; Lemmon and Zender, 2010).

2.3 Market timing theory

Just like Myers and Majluf's (1984) signaling hypothesis, the market timing framework (Baker and Wurgler, 2002) implies overvaluation as the rationale for firms issuing equity. However, the underlying idea is slightly different. In Myers and Majluf (1984) the overvaluation is a result from investors not having full information and hence overpricing the stock relative to what inside managers know. In contrast, in Baker and Wurgler (2002) the overvaluation stems from irrational investors bidding up share prices above fundamentals on sentiment. The market timing theory relates capital structure to past market-to-book ratios. According to the theory, firms prefer equity when they perceive the relative cost of equity as low, and they prefer debt otherwise.

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2.4 Payment methods

Next to determining how to finance the acquisition, the bidder also needs to decide on the payment method. The choice of the payment method is an important risk management strategy and a critical aspect of a successful M&A deal. In M&A negotiations, the seller often wants the highest possible price for the firm and the bidder strives to pay the lowest possible price. In such a situation the deal can be finalized by satisfying both buyer and target with an appropriate payment method. The payment alternative chosen in M&A is an important decision with consequences for both bidder and target. There are three options: full cash payment, full shares payment or a mixed form.

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12 relative amount of debt, creditors have a higher risk they will not get paid. Therefore, creditors are probably more reluctant to extend credit to firms with a high leverage ratio. Thus, when firms have insufficient internally generated funds and do not have the capacity to attract enough debt, they probably have to rely on issuing equity to fund the transaction. Lemmon and Zender (2010) conclude that debt capacity concerns indeed explain the use of new external equity financing.

Research on the choice of payment method specifically also shows that bidders with a low debt capacity are more likely to use shares than cash in acquisitions (Alshwer et al., 2009; Gorbenko and Malenko, 2018). Based on the pecking order theory evidence and the empirical findings that cash deals are mainly financed with debt, we propose:

Hypothesis 1: The size of bidder’s debt capacity positively affects the probability that the method of payment is cash.

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13 Overvaluation of a firm often happens when investors obtain information about future growth opportunities of the firm. Investors react and the growth opportunities are then reflected in the higher share price. However, growth opportunities are risky and often overestimated. This means there is a chance they will never be realized and hence the market value is higher than the ‘true’ value of the firm.

Still, there are several empirical studies showing evidence for the above mentioned theoretical predictions. The underlying idea is that bidders with large growth opportunities pay acquisitions with shares because in that way they can preserve their cash reserves or debt capacity to finance future investments required for their growth (Ismail and Krause, 2010; Martin, 1996). This is in line with Myers' (1977) debt overhang hypothesis: firms with high growth opportunities avoid debt financing to minimize the scope of underinvestment problems caused by high levels of debt financing.

Using a sample of 846 corporate acquisitions from 1978-1988, Martin (1996) finds that the higher a bidder’s growth opportunities, the more likely the bidder is to use shares as a method of payment. Besides that, Jung et al. (1996) report that firms issuing equity have better growth opportunities than firms issuing debt. Additionally, Giuli (2013) shows that high growth opportunities matter in the choice of method of payment, leading to greater use of stock.

In line with the findings of Martin (1996) and Jung et al. (1996), Faccio and Masulis (2005) also find, for a European sample, that higher market-to-book ratios are associated with higher proportions of stock and lower proportions of cash used as the method of payment. Based on abovementioned theoretical predictions and empirical findings we propose:

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2.5 Investor protection

According to (Djankov et al., 2007; La Porta et al., 1997) regulation influences the terms at which investors are willing to provide firms with funds. La Porta et al. (2000) argues that the protection of shareholders and creditors by the legal system is important to understand the patterns of corporate finance in different countries around the world. When outside investors, this can be both shareholders or creditors, finance a firm, they face the risk that the returns on their investments will never materialize because controlling shareholders or managers expropriate them, or the firm defaults (La Porta et al., 2000). Therefore, investor protection is crucial, since in many countries expropriation of minority shareholders and creditors by insiders is extensive.

Investors, both creditors and shareholders, are willing to accept more risk for the same return when they are better protected from expropriation. Hence, when a regulatory environment protects outside investors against expropriation by corporate management, the costs of external capital can decrease (Martynova and Renneboog, 2009). This, in turn, makes external finance options more attractive for firms.

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15 creditors is the effectiveness of their enforcement. Consistent with these propositions, La Porta et al. (1997) find that countries with better shareholder protection have more valuable stock markets, more listed securities per capita, and a higher level of IPO activity than countries with lower shareholder protection. Besides this, countries with better creditor protection have larger credit markets.

Building on earlier findings that most cash payments in acquisitions are financed by debt (Bharadwaj and Shivdasani, 2002; Harford et al., 2009; Martynova and Renneboog, 2009), the level of debt capacity is positively related to the probability that the method of payment is cash (Faccio and Masulis, 2005), and stronger creditor rights facilitate lending (Goyal and Bae, 2009; La Porta et al., 2000; Qian and Strahan, 2007b), we expect that better creditor protection weakens the relation between the level of bidders debt capacity and the probability that the method of payment is cash. Hence, we propose:

Hypothesis 3: The level of creditor protection in the bidder country positively moderates the relation between bidder’s size of debt capacity and the probability that the method of payment is cash.

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16 target shareholders accept the share offer is the highest when the bidder country has high shareholder protection.

Based on the empirical findings that higher growth opportunities (Faccio and Masulis, 2005; Jung et al., 1996; Martin, 1996; Yang et al., 2019) and better shareholder protection (Rossi and Volpin, 2004) both decrease the probability on a cash deal, we predict that the negative relation between bidder’s growth opportunities, measured by market-to-book ratio, and the probability of cash as a method of payment is more pronounced in countries with better shareholder protection. Therefore, we propose::

Hypothesis 4: The level of shareholder protection in the bidder country negatively moderates the relation between bidder’s level of growth opportunities and the probability that the method of payment is cash.

3. Data and methods

3.1. Data set

At first, we use the Bureau van Dijk M&A database Zephyr to collect deals from 1997 till 2019. To make it into the sample the bidder, as well as the target, must be a publicly listed company in Europe. The deal should have a value of at least one million euro and should be completed. Besides this, the bidder must have an ownership stake below 50% before and above 50% after the acquisition. The method of payment is cash, shares or a mixed form of those two. we exclude deals from which the bidder or the target is in the financial- or utility industry by deleting all observations with SIC-codes between 6000 and 6999 and between 4900 and 4949 respectively.

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17 from World Bank. After merging all data in STATA, 2,471 observations remain for which all variables are available. Table 1 shows how the final data set is derived.

Table1. Process to final data set.

Step in process Number of observations left

1 Start point: Zephyr data set with M&A bids from

1997-2019. 4,705

2 Excluding financial- and utility firms. 3,299

3 Excluding firms with missing firm-level variables

extracted from Datastream and Compustat. 2,596

4 Excluding firms who do not report total assets in euros (used for variable SIZE) on Zephyr

2,471

Final data set 2,471

Appendix A shows the formal definitions of all the variables used in this study. Following Faccio and Masulis (2005), the dependent variable in this study is the method of payment of the deal (MOP) which can be either 100% cash, 100% shares or a mixed form of cash and shares. MOP is an ordinal variable and takes 0 if the method of payment is shares, 1 if the method of payment is mixed, and 2 if the method of payment is cash.

Then, to test the effect of bidder’s debt capacity on the choice of method of payment (hypothesis 1), we use the ratio of total debt to the book value of total assets the year prior to the bid, LEV. Since cash is primarily obtained by issuing new debt, highly levered bidders are constrained in their ability to issue debt and as a consequence use stock financing more frequently (Faccio and Masulis, 2005). A higher leverage ratio thus stands for lower debt capacity and vice versa.

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18 shareholder rights (SHAR) on the relation between growth opportunities and the choice of method of payment. SHAR is a measure of the revised anti-director-rights index from Djankov et al. (2007). The index ranges from zero to five and measures the level of shareholder protection in a country.

Additionally, we control for several bidder- target- and deal characteristics. To control for the level of tangible assets, we follow Faccio and Masulis (2005) and employ the variable COL which is measured as the ratio of property, plant, and equipment (PPE) to the book value of total assets in the year preceding the bid. When firms have fewer tangible assets this increases the risk for creditors that they will not get paid back in case of bankruptcy of the firm. This increases the cost of debt and hence makes shares more attractive. Therefore, we expect that COL has a negative effect on the probability that the method of payment is cash.

Next, we use the variable SIZE measured by the natural logarithm of the book value of total assets to control for the bidder’s size. Larger firms are more diversified and thus have a relatively lower probability of bankruptcy, enabling them to issue more debt (Hovakimian et al., 2001). Additionally, they are likely to have better access to debt markets, which makes attracting debt easier (Faccio and Masulis, 2005). we expect SIZE to show a positive regression coefficient.

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19 acquisitions with cash. Martin (1996) indeed finds a higher probability of cash payments for cash-rich bidders.

Then, we proxy for the effects of the relative size of the deal with the variable RSIZE which is computed as the deal value divided by the market value of the firm four weeks prior to the announcement of the bid. Hansen (1987) predicts that stock payments are more likely as the bidder’s information asymmetry with regard to the targets market value increases. This information asymmetry rises when the relative size of the target in comparison with the bidder increases. Therefore, we expect RSIZE to have a negative effect on the choice of method of payment.

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20 protection and conclude that common law countries better protect minority shareholders than do civil law countries. Although common law should not directly influence M&A payment decisions, we still include the variable as it is correlated with other proxies of investor protection and is completely exogenous.

Table 2 shows the country distribution of the bidders in the data set. Just like the data set of Faccio and Masulis (2005), most of the bidders, 48.8% in this data set, are from the United Kingdom (U.K.). According to Faccio and Masulis (2005), shareholder

concentration is much lower and borrowing capacity appears to be stronger in the U.K. and Ireland. To ensure the results of this study are not biased because around half of the offers in the data set are from the U.K. and Ireland, we carry out the same analysis on the data set excluding the U.K. and Ireland to see if the results differ. Table 3 displays the

Table 2. Country distribution.

The table displays the country distribution of the bidders by method of payment, and shows the level of creditor- (CRER) and shareholder (SHAR) protection in the bidder country. Besides, it shows the number of private targets, cross-border deals, and intra-industry deals by method of payment.

Shares Mixed Cash Total % of total CRER SHAR

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21 descriptive statistics for the full sample in panel A, and the means for all variables by method of payment and for continental Europe and the U.K. and Ireland separately in

Table 3. Descriptive statistics.

Panel A shows the descriptive statistics. Panel B displays the descriptive statistics by method of payment and by subsample. The dependent variable is the method of payment (MOP). Independent- and control variables include: leverage ratio (LEV), strength of creditor rights in bidder country (CRER), interaction between leverage ratio and strength of creditor rights in bidder country (LEVCRER), level of intangible assets (COL), bidder size (SIZE), profitability (PROF), cash ratio (CASH), relative size of the target (RSIZE), deal value in euros (VAL), natural logarithm of gross domestic product (GDP). Additionally, the dummy variables indicate 1 if: the target is a private company (PRIVATE), the deal is in the same industry (INTRAINDUSTRY), the deal is cross border (CROSS) or the legal origin in the bidder country is common law (COMMON). In panel B, ***, **, and * indicate a significant difference in means between (1) shares- and cash payments and (2) European continental bidders and the U.K.-Ireland at the 1%, 5%, and 10% level respectively.

Panel A: descriptive statistics whole sample

Mean Median Min Max Std. Dev. Obs.

LEV 0.21 0.18 0.00 1.00 0.18 2,471 MB 1.95 1.12 0.02 55.90 3.70 2,471 CRER 2.70 3.00 0.00 4.00 1.45 2,471 SHAR 4.16 5.00 2.00 5.00 0.96 2,471 COL 0.19 0.14 0.00 0.95 0.18 2,471 SIZE 5.69 5.87 -2.82 11.59 2.70 2,471 PROF 0.05 0.08 -1.03 0.39 0.20 2,471 CASH 0.17 0.11 0.00 1.00 0.17 2,471 RSIZE 0.47 0.06 0.00 19.37 1.86 2,471 INTRAINDUSTRY 0.28 0.00 0.00 1.00 0.45 2,471 CROSS 0.51 1.00 0.00 1.00 0.50 2,471 GDP 10.58 10.64 8.91 11.54 0.31 2,471 PRIVATE 0.84 1.00 0.00 1.00 0.37 2,471 COMMON 0.50 1.00 0.00 1.00 0.50 2,471 VAL 385.45 19.78 1.00 189,951.10 4,288.40 2,471

Panel B: means per MOP and for split sample

Shares Mixed Cash Continental Europe only U.K. & Ireland

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22 panel B. Our two main independent variables, LEV and MB, have a mean of 0.21 and 1.95 respectively which is both lower than those in the study of Faccio and Masulis (2005). Besides that, it becomes clear that many of the variables have significantly different means for the U.K. and Ireland in comparison with continental Europe.

In addition, Appendix B shows the correlation matrix for all the variables. SHAR, CRER and COMMON are highly correlated (more than 70%) because they all reflect to some degree the underlying quality of investor protection in a country. However, they measure different institutional characteristics.

3.2. Methods

We run ordered logit regressions to estimate the effect of the explanatory variables on the probability that the method of payment is cash. We use ordered logistic regression because the dependent variable, MOP, can take on the three different ordinal values 0 (shares), 1 (mixed) or 2 (cash). The first model to determine the effect of bidder’s debt capacity on the probability that the method of payment (MOP) is cash (hypothesis 1) is:

𝑀𝑂𝑃 = 𝛼 + 𝛽1𝐿𝐸𝑉𝑖𝑡−1+ 𝛽2𝐶𝑂𝐿𝑖𝑡−1+ 𝛽3𝑆𝐼𝑍𝐸𝑖𝑡−1+ 𝛽4𝑃𝑅𝑂𝐹𝑖𝑡−1+ 𝛽5𝐶𝐴𝑆𝐻𝑖𝑡−1+ 𝛽6𝑅𝑆𝐼𝑍𝐸𝑖𝑡 + 𝛽7𝑉𝐴𝐿𝑖𝑡+ 𝛽8𝑃𝑅𝐼𝑉𝐴𝑇𝐸𝑖𝑡+ 𝛽9𝐼𝑁𝑇𝑅𝐴𝐼𝑁𝐷𝑈𝑆𝑇𝑅𝑌𝑖𝑡+

𝛽10𝐶𝑅𝑂𝑆𝑆𝑖𝑡+ 𝛽11𝐺𝐷𝑃𝑐𝑡+ 𝛽12𝐶𝑂𝑀𝑀𝑂𝑁𝑐 + 𝜀𝑖𝑡 (1) To test the effect of bidder’s market-to-book ratio (hypothesis 2), we use the same model as in equation (1), but replace LEV with the market-to-book ratio, MB:

𝑀𝑂𝑃 = 𝛼 + 𝛽1𝑀𝐵𝑖𝑡−1+ 𝛽2𝐶𝑂𝐿𝑖𝑡−1+ 𝛽3𝑆𝐼𝑍𝐸𝑖𝑡−1+ 𝛽4𝑃𝑅𝑂𝐹𝑖𝑡−1+ 𝛽5𝐶𝐴𝑆𝐻𝑖𝑡−1+ 𝛽6𝑅𝑆𝐼𝑍𝐸𝑖𝑡 + 𝛽7𝑉𝐴𝐿𝑖𝑡+ 𝛽8𝑃𝑅𝐼𝑉𝐴𝑇𝐸𝑖𝑡+ 𝛽9𝐼𝑁𝑇𝑅𝐴𝐼𝑁𝐷𝑈𝑆𝑇𝑅𝑌𝑖𝑡+

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23 𝑀𝑂𝑃 = 𝛼 + 𝛽1𝐿𝐸𝑉𝑖𝑡−1+ 𝛽2𝐶𝑅𝐸𝑅𝑐+ 𝛽3(𝐿𝐸𝑉𝑖𝑡−1× 𝐶𝑅𝐸𝑅𝑐) + 𝛽4𝐶𝑂𝐿𝑖𝑡−1+

𝛽5𝑆𝐼𝑍𝐸𝑖𝑡−1+ 𝛽6𝑃𝑅𝑂𝐹𝑖𝑡−1+ 𝛽7𝐶𝐴𝑆𝐻𝑖𝑡−1+ 𝛽8𝑅𝑆𝐼𝑍𝐸𝑖𝑡+ 𝛽9𝑉𝐴𝐿𝑖𝑡 + 𝛽10𝑃𝑅𝐼𝑉𝐴𝑇𝐸𝑖𝑡+ 𝛽11𝐼𝑁𝑇𝑅𝐴𝐼𝑁𝐷𝑈𝑆𝑇𝑅𝑌𝑖𝑡+ 𝛽12𝐶𝑅𝑂𝑆𝑆𝑖𝑡+ 𝛽13𝐺𝐷𝑃𝑐𝑡+

𝛽14𝐶𝑂𝑀𝑀𝑂𝑁𝑐+ 𝜀𝑖𝑡 (3)

At last, we test the moderating effect of shareholder protection on the relation between bidder’s market-to-book ratio and the probability the method of payment is cash, we use the following model:

𝑀𝑂𝑃 = 𝛼 + 𝛽1𝑀𝐵𝑖𝑡−1+ 𝛽2𝑆𝐻𝐴𝑅𝑐 + 𝛽3(𝑀𝐵𝑖𝑡−1× 𝑆𝐻𝐴𝑅𝑐) + 𝛽4𝐶𝑂𝐿𝑖𝑡−1+ 𝛽5𝑆𝐼𝑍𝐸𝑖𝑡−1+ 𝛽6𝑃𝑅𝑂𝐹𝑖𝑡−1+ 𝛽7𝐶𝐴𝑆𝐻𝑖𝑡−1+ 𝛽8𝑅𝑆𝐼𝑍𝐸𝑖𝑡+ 𝛽9𝑉𝐴𝐿𝑖𝑡+ 𝛽10𝑃𝑅𝐼𝑉𝐴𝑇𝐸𝑖𝑡+ 𝛽11𝐼𝑁𝑇𝑅𝐴𝐼𝑁𝐷𝑈𝑆𝑇𝑅𝑌𝑖𝑡+ 𝛽12𝐶𝑅𝑂𝑆𝑆𝑖𝑡+ 𝛽13𝐺𝐷𝑃𝑐𝑡+

𝛽14𝐶𝑂𝑀𝑀𝑂𝑁𝑐+ 𝜀𝑖𝑡 (4)

4. Results

Model I of Table 4 estimates the effect of bidder’s debt capacity on the choice of method of payment. Next to the coefficients, we show the change in odds in square brackets for an increase of one standard deviation for every discrete variable and an increase of one unit for ordinal variables2. Change in odds of dummy variables are for an increase from zero to one. The change in odds represents the percentage of change in the odds that the method of payment is cash. For example, an increase in the odds that the method of payment is cash from 4:1 to 6:1, stands for a change in odds of +50%.

The coefficient of the leverage ratio is statistically insignificant. Which suggest there is no overall effect of bidder’s debt capacity on the probability that the method of payment is cash. This result contradicts both the results of Faccio and Masulis (2005) and Harford et al. (2009) who find a significant negative and positive effect respectively. A

2 The change in odds is calculated as 𝑒𝑥𝑝(𝛽𝑘∗𝛿)−1. Where 𝛽𝑘 presents the coefficient of every

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24 possible explanation is that the bidder’s optimal capital structure has a lower leverage ratio than the bidder’s maximum debt capacity (Turnbull, 1979). Hence, bidders

Table 4. Regression results.

This table shows the results for the logistic regression analysis for the debt capacity hypothesis (I) and the creditor rights hypothesis (II). The dependent variable is the method of payment (MOP). Independent- and control variables include: leverage ratio (LEV), strength of creditor rights in bidder country (CRER), interaction between leverage ratio and strength of creditor rights in bidder country (LEVCRER), level of intangible assets (COL), bidder size (SIZE), profitability (PROF), cash ratio (CASH), relative size of the target (RSIZE), deal value in euros (VAL), natural logarithm of gross domestic product (GDP). Additionally, the dummy variables indicate 1 if: the target is a private company (PRIVATE), the deal is in the same industry (INTRAINDUSTRY), the deal is cross border (CROSS) or the legal origin in the bidder country is common law (COMMON). Additionally, year- and industry dummies are included for the year of the bid and the three-digit SIC-codes respectively. Z-statistics are in parentheses. *, ** and *** indicate statistical significance at the 10%, 5%, and 1% level, respectively.

Dependent

variable: MOP (I)

Change in odds (II) Change in odds (III) Change in odds LEV -0.328 (0.890) [-5.8%] -1.633** (-2.330) [-25.7%] CRER 0.062 0.750 [6.4%] -0.030 (-0.330) [-3.0%] LEVCRER 0.506** (2.000) [65.9%] COL 0.499 (0.960) [9.6%] 0.402 0.770 [7.6%] 0.456 (0.860) [8.7%] SIZE 0.354*** (9.710) [160.1%] 0.352*** 9.640 [158.4%] 0.352*** (9.610) [158.7%] PROF 1.882*** (4.870) [46.5%] 1.915*** 4.950 [47.5%] 1.883*** (4.870) [46.5%] CASH -0.716** (2.070) [-11.5%] -0.679** -1.990 [-10.9%] -0.721** (-2.090) [-11.5%] RSIZE -0.116*** (3.000) [-19.3%] -0.116*** -3.030 [-19.4%] -0.119*** (-3.020) [-19.9%] VAL -0.000* (1.930) [-47.7%] -0.000* -1.910 [-47.7%] -0.000* (-1.930) [-48.2%] PRIVATE 0.861*** (5.140) [136.5%] 0.849*** 5.050 [133.7%] 0.842*** (5.020) [132.0%] INTRA INDUSTRY 0.200 (1.390) [22.1%] 0.211 1.460 [23.5%] 0.193 (1.340) [21.3%] CROSS 0.986*** (7.340) [168.2%] 0.980*** 7.300 [166.5%] 0.991*** (7.360) [169.3%] GDP -0.049 (0.150) [-1.5%] -0.028 -0.080 [-0.9%] -0.027 (-0.080) [-0.9%] COMMON 1.434*** (8.950) [319.7%] 1.288*** 4.900 [262.5%] 1.297*** (4.940) [265.8%] Year and industry

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25 can pay with shares to stay close to their optimal capital ratio, although they are still able to attract the needed amount of debt.

Model II estimates the direct effect of creditor rights. The coefficient of CRER is statistically insignificant. This means there is no overall effect of the strength of creditor rights on the choice of method of payment. This is in contrast with the prediction that creditor rights facilitate lending and hence make cash payments with debt financing easier3.

In model III, which contains the interaction term, the coefficient of LEV is negative and statistically significant at the 5% level. As a higher leverage ratio indicates a smaller size of debt capacity, this means that in absence of creditor rights in the bidder country (CRER=0), which is the case for 196 deals in the data set4, the size of bidder’s debt capacity has a significant positive impact on the probability that the method of payment is cash.

The interaction term LEVCRER in the last column is positive and statistically significant at the 5% level. As the main effect of LEV in model I is insignificant, the interaction effect of LEVCRER implies that the existence of an effect of LEV depends on the level of creditor protection in the bidder country5.

The first column of Table 5 reports the regression results for the effect of bidder’s growth opportunities on the choice of method of payment. The market-to-book ratio coefficient is insignificant which suggests there is no overall effect of bidder’s growth opportunities on the method of payment. In the second model, the shareholder rights coefficient is insignificant as well which implicates there is no overall effect of the level of shareholder protection on the choice of method of payment either. Model III however, reports a statistically significant negative coefficient for MB which implicates that in the

3 Goyal and Bae, 2009; La Porta et al., 2000; Qian and Strahan, 2007a. 4 Appendix C gives a tabulation of the creditor- and shareholder rights.

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26 absence of shareholder rights (SHAR=0), bidder’s growth opportunities negatively impact the probability that the method of payment is cash. However, in this study there Table 5. Regression results.

This table shows the results for the logistic regression analysis for the market-to-book ratio hypothesis (I) and the shareholder rights hypothesis(II). The dependent variable is the method of payment (MOP). Independent- and control variables include: bidder’s market-to-book ratio (MB), strength of shareholder rights in the bidder country (SHAR), interaction between market-to book ratio and shareholder rights (MBSHAR), level of intangible assets (COL), bidder size (SIZE), profitability (PROF), cash ratio (CASH), relative size of the target (RSIZE), deal value in euros (VAL), natural logarithm of gross domestic product (GDP). Additionally, the dummy variables indicate 1 if: the target is a private company (PRIVATE), the deal is in the same industry (INTRA INDUSTRY), the deal is cross border (CROSS) or the legal origin in the bidder country is common law (COMMON). Additionally, year- and industry dummies are included for the year of the bid and the three-digit SIC-codes respectively. Z-statistics are in parentheses. *, ** and *** indicate statistical significance at the 10%, 5%, and 1% level, respectively.

Dependent

variable: MOP (I)

Change in odds (II) Change in odds (III) Change in odds MB -0.001 (-0.030) [-0.2%] -0.076** (-2.150) [-24.6%] SHAR -0.245 -1.43 [-21.7%] -0.304* (-1.800) [-26.2%] MBSHAR 0.018* (1.690) [1.8%] COL 0.380 (0.710) [7.2%] 0.481 0.920 [9.2%] 0.406 (0.760) [7.7%] SIZE 0.364*** (9.610) [167.3%] 0.349*** 9.660 [156.7%] 0.364*** (9.680) [167.1%] PROF 1.857*** (4.770) [45.8%] 1.911*** 4.900 [47.4%] 1.907*** (4.720) [47.2%] CASH -0.621* (-1.820) [-10.0%] -0.706** -2.050 [-11.3%] -0.638* (-1.850) [-10.3%] RSIZE -0.107*** (-2.950) [-18.1%] -0.116*** -3.050 [-19.3%] -0.107*** (-2.990) [-18.0%] VAL 0.000* (-1.950) [-47.4%] 0.000* -1.930 [-47.5%] 0.000* (-1.950) [-47.6%] PRIVATE 0.843*** (4.970) [132.4%] 0.863*** 5.150 [137.0%] 0.851*** (5.000) [134.2%] INTRA INDUSTRY 0.213 (1.480) [23.8%] 0.197 1.370 [21.8%] 0.219 (1.530) [24.5%] CROSS 0.955*** (7.070) [159.9%] 0.968*** 7.210 [163.2%] 0.943*** (7.020) [156.8%] GDP -0.013 (-0.040) [-0.4%] -0.076 -0.220 [-2.4%] -0.042 (-0.130) [-1.3%] COMMON 1.440*** (8.970) [322.0%] 1.847*** 5.970 [533.9%] 1.876*** (6.060) [552.4%] Year- and industry

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27 are no observations that have a value of 0 for shareholder rights, so this estimate is actually, from an economic perspective, not interpretable.

The interaction term MBSHAR is positive and statistically significant at the 10% level. Since the main effect of MB in model (I) is insignificant, the interaction effect of MBSHAR indicates that the existence of an effect of MB on the probability that the method of payment is cash, depends on the level of shareholder protection in the bidder country6. Furthermore, in both Tables 4 and 5 the estimates of the control variables SIZE, PROF, PRIVATE, CROSS, and COMMON are, as expected, positive and statistically significant for all models. Larger firms are more diversified and thus have a lower probability of default. They also have lower flotation costs and often have better access to debt markets, which makes debt financing more readily available (Faccio and Masulis, 2005). Firms with high profitability are more likely to fulfill timely their debt obligations, which lowers the cost of debt and thus makes it easier to finance with debt and pay with cash. In cross border deals, sellers are likely to view bidder share value as more uncertain (Faccio and Masulis, 2005), which increases the probability of a cash payment. At last, firms in common law countries are known to have better access to debt markets (La Porta et al., 1997; Faccio and Masulis, 2005), which makes debt financing and hence paying by cash easier.

Other significant, but negative, coefficients in all models of Table 4 and 5 are CASH, RSIZE, and VAL. The negative effect of the level of cash holdings is in contrast to the prediction of the pecking order theory which states that internally generated funds like cash should be used first to finance an investment. The negative effect of CASH can be due to the opportunity cost of holding cash hypothesis which states that financially

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28 constrained firms with high growth opportunities save cash to finance their future projects. The negative effect of the target’s relative size on the probability that the method of payment is cash support’s Hansen's (1987) asymmetric information prediction that stock financing is more likely when the bidder’s information asymmetry with regard to the target’s market value rises. In case the absolute value of the deal increases, the chance that internal funds are insufficient and the firm does not have enough debt capacity is higher, which makes stock financing and hence share payments more likely. We do not find any significant result for the variables COL, INTRA INDUSTRY, and GDP.

Table 6 reports the regression coefficients of the models we run for the data set excluding the U.K. and Ireland. The U.K. and Ireland are the only common law countries in the sample and account for almost half of the observations. Since common law countries are known to better protect minority shareholders and have better developed debt markets (La Porta et al., 1997), we run regressions without the U.K. and Ireland to see if the results of the main analysis change.

In the first model, where we test the effect of bidder’s debt capacity on the probability that the method of payment is cash, the coefficient LEV is negative and significant at the 5% level. This is in contrast to the results of the main analysis, where we do not find a significant effect of the leverage ratio. Since a higher bidder’s leverage ratio indicates a lower size of debt capacity, continental European bidders with lower debt capacity are less likely to choose cash as the method of payment. This is in line with the results of Alshwer et al. (2009) and Gorbenko and Malenko (2018) who also find that bidders with a lower debt capacity are less likely to choose cash as the method of payment in M&A. However, the result is contrary to Harford et al. (2009) who report the opposite.

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29 regression for the whole data set is statistically significant, the effect of LEVCRER becomes insignificant after excluding the U.K. and Ireland. This indicates that for continental European bidders, there is no moderating effect of the level of creditor rights on the relation between the bidder’s leverage ratio and the probability that the method of payment is cash. As a robustness check, we run the main regression models again but exchange the ordinal variable MOP with the binary variable MOP2 which indicates 0 if the method of payment is shares and 1 for cash. This means the ordered logistic regression changes to a normal logistic regression with a binary outcome. Table 8 reports the estimates of this robustness check. Both the coefficients of LEVCRER and MBSHAR become insignificant when we use MOP2 as the dependent variable.

Table 6. Regression results continental European bidders.

This table reports the regression results for the data set with only continental European bidders (excluding the U.K. and Ireland). To save space, coefficients of control variables are not reported. Year- and industry dummies are included for the year of the bid and the three-digit SIC-codes respectively. Z-statistics are in parentheses. *, ** and *** indicate statistical significance at the 10%, 5%, and 1% level, respectively.

Panel A

(I) (II) (III)

LEV -1.275** (-2.450) -2.079** -2.220 CRER 0.127 1.280 0.034 0.270 LEVCRER 0.505 1.050

Control variables Yes Yes Yes

Year and industry dummies Obs. Pseudo R2 Yes 1,229 0.328 Yes 1,229 0.326 Yes 1,229 0.327 Panel B

(I) (II) (III)

MB -0.022 (-1.110) -0.048 (-0.630) SHAR -0.285 (-1.470) -0.316 (-1.590) MBSHAR 0.008 (0.240)

Control variables Yes Yes Yes

Year and industry dummies Obs.

Pseudo R2

Yes

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30 Thus, the main results of the moderating effects of creditor- and shareholder protection cannot be judged as robust. However, remarkable is that in model II of panel B, the shareholder rights estimate is negative and highly significant at the 1% level. This indicates that the better shareholder protection in the bidder country, the lower the probability that the method of payment is cash. This is in line with the idea that target shareholders are more likely to accept shares as payment when the risk of expropriation is the lowest.

4 Conclusion

Within the M&A literature, ample research exists on the impact of bidder-, target, and deal characteristics on the choice of method of payment. However, the country

Table 8. Robustness check.

This table reports the regression results for the robustness check. MOP2 is used as the dependent variable which equals 0 for shares payments and 1 for cash payments. To save space, coefficients of control variables are not reported. Year- and industry dummies are included for the year of the bid and the three-digit SIC-codes respectively. Z-statistics are in parentheses. *, ** and *** indicate statistical significance at the 10%, 5%, and 1% level, respectively.

Panel A

(I) (II) (III)

LEV -0.569 (-0.960) -0.694 (-0.680) CRER 0.086 (0.750) 0.073 (0.510) LEVCRER 0.057 (0.140)

Control variables Yes Yes Yes

Year and industry dummies Obs. Pseudo R2 Yes 2,039 0.537 Yes 2,039 0.537 Yes 2,039 0.538 Panel B

(I) (II) (III)

MB -0.013 (-0.340) -0.027 (-0.320) SHAR -0.563*** (-3.000) -0.568*** (-2.950) MBSHAR 0.003 (0.130)

Control variables Yes Yes Yes

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31 environment in which the deals take place is often not taken into consideration. Therefore, this study investigates the role of creditor- and shareholder protection in the method of payment decision of European bidders.

We first estimate the effect of two bidder characteristics related to investor protection: debt capacity and growth opportunities. By analyzing a data set of 2,741 completed M&A transactions of European, bidders, we find that nor debt capacity nor growth opportunities has an overall effect on the choice of method of payment. But, after excluding the U.K. and Ireland, debt capacity seems to have a significant positive effect on the probability that the method of payment is cash for continental European bidders. This is in line with the results of Alshwer et al. (2009) and Gorbenko and Malenko (2018). The main finding stays however, that for European bidders, the existence of an effect of debt capacity and growth opportunities on the choice of method of payment, depends on the level of creditor- and shareholder protection in the bidder country respectively.

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36 Appendix B: overview and definitions of variables

This Table shows all the variables used in the regressions.

Variable Definition

Dependent variable

MOP Method of payment of the deal. Ordinary variable which equals 0 for all share deals, 1 for mixed payments, and 2 for all cash deals. MOP2 Dummy variable of method of payment which equals 0 for all share

deals and 1 for all cash deals. Independent variables

Firm specific

LEV Leverage ratio of the bidder. Calculated as total debt divided by the book value of total assets the year prior to the bid.

MB Market-to-book ratio of the bidder. Calculated by the bidders market value divided by the book value of total assets the year prior to the bid.

COL Percentage of tangible assets of the bidder. Calculated as Plant Property Equipment (PPE) divided by the book value of total assets the year prior to the bid.

SIZE Size of the bidder. Calculated as the natural logarithm (ln) of the book value of total assets in euros the year prior to the bid.

CASH Cash ratio of the bidder. Calculated as cash and cash equivalents divided by book value of total assets the year prior to the bid. PROF Profitability ratio of the bidder. Calculated as earnings before

interest and taxes (EBIT) divided by book value of total assets. Transaction specific

RSIZE Relative size of the deal. Calculated as the deal value divided by the bidders market value four weeks prior to the bid.

SIC Dummy variable which equals 1 if the bidder and target are in the same industry and 0 otherwise. We use three-digit SIC codes to classify the firms to the industries.

CROSS Dummy variable which equals 1 if the deal is cross border: if the target is from another country than the bidder.

PRIVATE Dummy variable which equals 1 if the target is a private company and 0 if it is a listed company.

Country specific

CRER Level of creditor protection in bidder country. We use the updated Creditor Protection Score (CPS) from Djankov et al. (2007) which ranges from 0 till 4.

SHAR Level of shareholder protection in bidder country. We use the revised anti-director rights index (ADRI) of Spamann (2010) which ranges from 0 till 6.

GDP Natural logarithm (ln) of the bidder’s country’s GDP per capita the year prior to the bid.

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37 Appendix C: correlation matrix.

This Table shows the correlations of the independent and control variables used for the regression analyses. It includes: leverage ratio (LEV), level of tangible assets (COL), natural logarithm of total assets (SIZE), market-to-book ratio (MB), profitability (PROF), cash to total assets (CASH), relative size of the deal (RSIZE), natural logarithm of GDP per capita (GDP), creditor rights index (CRER), shareholders rights index (SHAR). Additionally, the dummy variables indicate 1 if: the deal is in the same industry (SIC), the deal is cross border (CROSS) or the deal is after the financial crisis of 2008 (POST). The industries are classified by the three-digit SIC codes and countries are classified with the three-digit ISO country codes.

LEV MB CRER SHAR COL SIZE PROF CASH RSIZE VAL PRIVATE INDUSTRY CROSS INTRA GDP COMMON

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38 Appendix D. Tabulation of creditor rights- and

shareholder rights index.

Level of CRER Obs. %

0 196 8% 1 554 22% 2 250 10% 3 265 11% 4 1,206 49% Total 2,471 100%

Level of SHAR Obs. %

2 105 4% 2.5 112 5% 3 165 7% 3.5 769 31% 4 8 0% 5 1,312 53% Total 2,471 100%

Appendix E. Regression coefficients for LEV (Panel A) and MB (Panel B) of equation (1) and (2) respectively for different levels of creditor- and shareholder protection. The last row (‘average’) of each panel gives the LEV and MB regression coefficients for the original regressions in model I

in Table 4 and 5 respectively. *, ** and *** indicate

statistical significance at the 10%, 5%, and 1% level, respectively.

Panel A

CRER LEV obs.

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