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MASTER THESIS
THE IMPACT OF EXCHANGE RATE RISK ON THE LIKELIHOOD OF
DEAL COMPLETION FOR CROSS-BORDER MERGER AND
ACQUISITION DEALS
By
Huang Tianyi (S3217337)
Supervisor: Dr. H. Gonenc Co-Assessor: Dr. V. Purice Submitted for the degree of
Msc International Financial Management
Faculty of Economics and Business Rijkuniversiteit Groningen
2 Abstract
Using a sample of 1,407 cross border merger and acquisition deals for the period from 2005 to 2015, I find that currency deprecation has negative impact on the likelihood of deal completion of cross border merger and acquisition deals. Importantly, currency depreciated in 10.2% more deals in withdrawn deals than those in completed deals. I further find the negative moderating effects of cash payment, economic development and law & regulatory distance on the main relationship, indicating that the interactions of currency depreciation with these variables weaken the relationship between currency depreciation and the likelihood of deal completion. Collectively, this evidence suggests that the combination of exchange rate risk, deal characteristics such as cash payment and country level characteristics play important roles in explaining the likelihood of deal completion.
Keywords: Cross Border Merger and Acquisition; Currency Depreciation; Cash Payment; Deal
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Contents
Abstract ... 2
1. Introduction ... 4
2. Literature Review and Hypothesis Development ... 9
2.1 Factors Affecting Cross-border Merger and Acquisitions ... 12
2.1.1 Exchange Rate Risk ... 13
2.1.2 Cash Payment ... 16
2.1.3 Economic Development ... 18
2.1.4 Legal and Regulatory Distance ... 20
3. Research Methodology ... 22 3.1. Data ... 22 3.2 Variables ... 24 3.2.1 Dependent Variable ... 24 3.2.2 Independent Variable... 25 3.2.3 Cash Payment ... 25 3.2.4 Economic Development ... 26
3.2.5 Legal and Regulatory Distance ... 27
3.2.6. Control Variables... 28 3.3 Regression Model ... 30 4.Result ... 32 4.1 Descriptive Statistics ... 33 4.2 Correlation Analysis ... 35 4.3 Multivariate Analysis ... 36
4.4 Limitation and Future Development ... 40
5. Conclusion ... 41
1. Introduction
Merger and acquisition (M&A) is the transaction in ownership of the firms and the process of transferring or combining the operating units and other business organizations to the acquirer company. Merger can be described as the combination of two firms, whereas acquisition is the process during which acquirer company purchases the target company. From a strategic management perspective, M&As allow the companies to grow, shrink, or even change the nature of the business or its competitive position. Therefore, M&As have a significant presence in corporate finance.
The motive of M&As is usually to protect the increase in profitability or strength of the acquirer company. In other words, maximize the shareholder's wealth. However, that is not always the case. The company may decide to merge or acquire another firm because they improve their financial position. In terms of other diversification, companies tend to use cross-border merger and acquisition. Cross-cross-border M&A refers to the transaction between a foreign company and a domestic company in the target country. When the company seeks to expand or enter a new market, they might achieve that by merging with companies or acquiring a company in other countries. Some companies attempt to relocate their business in low tax countries to reduce tax, while other firms consider the economic scale to reduce the cost of doing business and increase operational efficiency. Particularly in manufacturing industries where material, labor, and other purchases are the large portions of the cost.
M&As have been a dominant topic of interest that has resulted in number studies over the last few decades. In 1990, the investment in M&As was 98.9 billion dollars. This number was further increased by more than nine times in the year 2000 to 905.2 billion dollars.
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However, M&A activities slowed down during the financial crisis of 2008 - 2009 but later it took an upward turn in the year 2010 when the global investment rose to approximately 340 billion U.S. dollars (UNCTAD, 2016). The cross-border merger and acquisition’s deals volume also increased from 23% in 1998 to 45% in 2007 of total volume. From acquiring firm manager's perception, the combination of two companies through merger and acquisition increases the value of the company. Companies in developed countries commonly practice this strategy on companies in developing countries. However, in terms of cross-border merger and acquisition, there are additional risk elements due to differences in country and currency. For instance, currency exchange-rate risk and the differences in financial market development could increase the risk and cost to combine two companies.
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decision might be the unexpected changes in currency from the announcement date that cost more than the penalty to withdraw the deal.
Currency depreciation is considered as currency exchange risk, it occurs when the value of a country’s currency is lowered against a fixed exchange rate system and is usually triggered by certain economic conditions. Although currency exchange risk is a common risk in most cross-border transactions, and the majority of companies choose hedging to avoid this risk. However, the amount of currency deprecation may be more than the company’s currency hedge could cover. It is an attraction for target countries with low currency to attract foreign investment or M&A, but it is an additional cost for acquirer companies during the M&A procedure. In cross border M&A, payment of the deal need to face currency transaction risk, which means when the foreign currency is used as native currency for a deal, the cost may increase unexpectedly. During the cross border M&A, both parties need to confirm the native currency of payment. When the native currency is not the same with acquirer currency, this cross border M&A will face the risk of currency changes (depreciation).
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The motivation of this thesis is from the study of Zhou et al., (2016). In their study, they investigate how the predictors of cross-border M&A completion involving emerging markets depend upon the direction of global expansion. The study is based on 15 years of data from four emerging economies, Brazil, Russia, India, and China, from 1995 to 2010, reveals fundamental differences in the predictors of inbound vs. outbound M&A completion. However, they have the limitations of only focus on cross border M&As related to four fastest-growing emerging markets, BRIC instead of other emerging markets. Also, due to lack of data availability, the study only focuses on public acquirers. They suggested future research could look into more countries and add private acquirers as well.
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countries that announced and withdrawn / completed the deal. The analysis primarily evaluates the element that under international factors, instead of domestic factors, may have an impact on the likelihood of the deal completion, such as legal and law distance, financial market development, and corporate tax rate differences.
The result supports the main relationship that currency depreciation has a negative impact on the likelihood of deal completion, which supports hypothesis H1b. The result supports that cash payment has a moderating effect on the relationship between currency changes and the likelihood of deal completion. The payment method negative and significantly weaken the main relationship. Other hypothesizes are not supported by the results. My focus in this paper is placed on four questions: (1) What is the main relationship between currency exchange rate risk and the likelihood of deal completion? (2) What is the moderating effect of Cash payment on the relationship between currency changes and the likelihood of deal completion? (3) What is the moderating effect of economic development on the relationship between currency changes and the likelihood of deal completion? (4) What are the moderating effect of law and regulatory distance on the relationship between currency changes and the likelihood of deal completion?
9 2. Literature Review and Hypothesis Development
In recent years, cross-border mergers and acquisitions have become more popular and widespread. In 2011, global FDI flows are estimated at $1.5 trillion, $526 billion of which are cross-border M&As (UNCTAD, 2012). The development of operating cross-border M&As has led to an increase in profound studies in the field, such as, culture integration (Slangen, 2006), performance and returns of cross-border M&As (Bertrand & Zitouna, 2008), payment method of cross-border M&As (Dutta et. al, 2013), determinants of target selection in cross-border M&As. There are many common motives for firms to engage in cross-border M&As. Gonzalez et al. (1997) examines 533 multinational corporations in the U.S. between 1981 and 1998. Their study indicates that one of the most important reasons for U.S. firms to acquire foreign targets overseas is to access a new market. Erel et al. (2012) finds that domestic firms are more likely to become targets when the domestic currency is depreciated. Erel et al. (2012) demonstrates an increase in cross-border mergers and acquisitions as a result of high trade between two countries, or low geographical distance in between the two countries. The high trade usually indicates that two both countries possess a similar cultural background and enhanced synergies. Uysal et al. (2008) explores geographical distance in further detail and finds firms within a 100 km radius who are looking to merge can generate higher returns than firms outside of the 100 km radius, which is reflective of the informational advantage between the two firms.
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acquisition deals in regard to finance and accounting. However, most of the studies are focused on domestic merger and acquisition at firm level and deal level factors that have potential influence in terms of domestic merger and acquisition completion. For instance, the study of (Eckbo, 2009) focuses on offer premium whereas O’Sullivan & Wong (1998) mainly focuses on management resistance. Other examples are: (i) board composition (Shivdasani & Zenner, 1997), (ii) managerial ownership (Mikkelson & Partch, 1989), (iii) bid premium (Holl & Kyriazis, 1996), (iv) stake sought (Holl & Kyriazis, 1996) and (v) payment method (Sudarsanam, 1995). Recently there has been several of studies on completion of cross-border merger and acquisition, some of which focus on developed countries, such as Dikonova et al. (2010), or use a general sample of cross-border deals Aguilera & Dencker (2008).
From a company perspective, merger and acquisitions should provide improvement for both companies. Their primary motivations are expanding the market to gain additional resource, earning additional market position or reducing competition, and increasing company value by improving technology, productivity, and quality from cross-border merger and acquisition. When there is a cross board merger and acquisition deal, currency risk and culture risk are the potential risks that could influence the deal completion that companies should concern about. Therefore, we introduce to our research topic: The currency deprecation have posive / negative effect on the likelihood of cross-border merger and acquisition deals completion.
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announced deal, are extra costs to existing costs in the pre-completion phase of merger and acquisition, such as investment in resource and time. additional cost like penalties due to break of the contract could also incur (Luo, 2005). For instance, competitor companies may realize the strategic plan and long-term deployment of the company simply by a merger and acquisition' announcement information. Additionally, the reputation and credibility of an acquirer could be damaged due to termination of a deal (Luo, 2005). It is even more costly if the company is withdrawing an announced merger and acquisition completion deal between a developed and an emerging country.
12 2.1 Factors Affecting Cross-border Merger and Acquisitions
Cross-border mergers and acquisitions face the potential risks that domestic mergers and acquisitions do not have. According to earlier literuture by Zhou et. al, (2016), when the companies face potentially unfamiliar and uncertain environments, it increases the possibilities for acquirers to misinterpret or ignore important information. When the company fails to do so before issuing public announcements, they may have to withdraw their announced mergers and acquisition deal. In this case, the geographical and cultural distance not only keeps everything else the same but also having a shorter the distance between the two countries increases the likehood of merger and acquisitions between the two countries. Additionally, mergers may occur among firms in countries which frequently trade with each other, as they have higher possibilities to have synergies and a similar cultural context. Generally, buyers are from the developed countries, but its not always the case. Also, they tend to buy companies in countries with lower accounting standards.
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acquisition and institutional differences is measured as the country-risk distance between home and host countries.
2.1.1 Exchange Rate Risk
Eiteman et. al, (1992) defined exchange rate risk as the result of changes in operating cash flow that caused by an unexpected change in exchange rates. Based on earlier studies by Adler & Dumas (1984), changes in exchange rates reflect the changes in corporate value in order to capture exchange rate risk. Transaction risk is the risk that the exchange rate will change during a short period between the time of entry and the settlement of a foreign exchange transaction. Economic risk is the risk that changes in exchange rates will change the company's long-term future cash flows and corporate value. Both transactional risks and economic risks are related to cross-border mergers and acquisition failures. In the study of Flood & Lessard (1986), they related the company's foreign exchange exposure to the underlying market conditions for inputs and output at the micro level. Similarly, Choi (1986) has also made the connection between market conditions for inputs and output at the micro level. The study of Eun & Resnick (1988) demonstrates the empirical significance of the systematic exchange rate risk.
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currency via simple regressions using a small amount of yearly US aggregate FDI remarks, which Stevens (1991) bargains are delicate to specification. However, Klein & Rosengren (1994) approve that the growth of US FDI is done by exchange rate depreciation using many different examples of US FDI disaggregated kind of FDI and source of the country.
As it is provided by Blonigen (1997), there is another way to affect inward FDI through changes in the exchange rate level. However, if the FDI of a country is driven by the acquisition of transferable assets such as technology and managerial skills within a firm, then the depreciation of the foreign currency does not necessarily result in lower nominal returns. In another word, depreciation of a country’s currency may allow the sale of such transferable assets to the foreign firms which are operating globally. According to Blonigen (1997), there is strong support for increased inward US acquisition FDI by Japanese firms in response to the depreciation of dollar compare to Japanese Yen. The study confirms the direct relationship between exchange rate and acquisition FDI on industries where firm-specific assets are likely of substantial importance. Other studies of Swenson (1994), and Kogut & Chang (1996) concluded that short-run movements in exchange rate lead to increased inward FDI and does not greatly affect merger and acquisition FDI.
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when the management of the acquirer company believes the merged company will have a greater value than the individual company. The reasons that value has changed could be both domestically and internationally. Reduce contract costs and improve productivity and efficiency within the company. Consolidation can create market forces because the merging company collects profits for the purpose of maximizing its own earnings, rather than taking collective action before acquiring an independent company. Valuation is an important factor in cross-border mergers and acquisitions. Given the incompleteness of markets in different countries, valuations between markets help to stimulate cross-border mergers and acquisitions. For example, the company's currency rises because of some external reason unrelated to the company's profitability. Companies may find the underlying targets in other countries relatively cheap, resulting in some potential takeovers that will not be profitable under the old exchange rate.
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from the international development of intangible assets and to allocate resources more efficiently (Yang & Driffield, 2012). In this paper, I consider currency depreciation as the currency exchange rate risk in currency changes.
This led to the first hypothesis:
H1: Currency depreciation in acquirer currency to native currency has a negative impact
on the cross-border merger and acquisition deal completion.
2.1.2 Cash Payment
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During the period of announcement date, until a deal is completed, many risks may occur. For instance, exchange currency changes, law and the legal distance between two countries, and leverage may change the decision of the acquirer company to withdraw the deal. The trasction of cash for the stock is fairly straightforward: target company shareholders receive a cash payment for each share purchased. This transaction is treated as a taxable sale of the shares of the target company. Additionally, Faccio & Masulis (2005) examine the choice of payment method in European M&As. They report that foreign target firms prefer cash payment to stock payment, which leads to a limitation of payment options for domestic acquiring firms. As a result, financing abilities could play an important role in making investment decisions and payment methods in the context of cross-border M&As. The acquirer uses payment method as a strategy for certain reasons. According to the earlier study by Eckbo (2009), in the period of 1979 and 2009, bidders initiating takeover bids for U.S. targets offered all call as payment around one-fourth of the cases, all stock in one- third and a mix of stock and cash is also in one-third of the takeovers. According to Faccio & Masulis, (2005), in merger and acquisition monetary decisions, bidders face the option of using cash and stock as a consideration for a transaction. Despite the importance of these implications, there have not been many studies regarding the choice of payment method.
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This led to my second hypothesis:
H2a: Cash Payment has the positive moderating effect of the currency changes on the deal
completion likelihood.
H2b: Cash Payment has negative moderating effect of the currency changes on the deal
completion likelihood.
2.1.3 Economic Development
The differences in economic development between acquirer’s country and target’s country could influence the relationship between currency changes on the likelihood of deal completion. Developed countries are characterized by an efficient government, sound financial market development, strong patent protect and law enforcement that could possible enhance multinational firms’ incentive to innovate and their ability to appropriate rent from innovation. Gao & Chao (2015) also state that most important technologies are created in only a small number of rich countries and are mainly from multinational firms. Furthermore, countries that have developed markets can lower international technology transfer costs which are especially considerable for multinational firms.
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countries, found out that M&A in service sector has positive effect on the growth of service. However, economic development distance can affect deal completion in different ways (Zhou et al, 2016). First, the higher the country-risk distance, the more likely that the country with higher risk (either target or acquirer country) may face adverse changes in its political or economic environment during the public takeover period. Such adverse changes may either reduce the potential of the announced M&A or entail losses to firms involved, which in turn reduces the likelihood of deal completion. Second, even adverse changes may not significantly affect the likelihood of M&A deals completion. This kind of changes could create new information for firms involved in the M&A to comprehend in the short public takeover period. Because of the time pressure after the M&A is announced, misunderstanding and misjudging unexpected possibilities regarding the announced M&A increases the likelihood of a firm abandoning the deal. Finally, the unexpected changes can also create great uncertainty for firms involved in the M&A concerning future market stability. Therefore, it can reduce confidence in doing business in such an unstable environment. Overall, as economic development distance enlarges, the currency tends to be depreciated in the high-risk country, which in turn decreases the likelihood of deal completion.
Therefore, my third hypothesis is as follows:
H3a: The economic development distance between acquirer and target countries have a
positive moderating effect on the relationship between currency changes and deal completion
likelihood.
H3b: The economic development distance between acquirer and target countries a negative
20 2.1.4 Legal and Regulatory Distance
Legal and regulatory distance is used to measure the differences in terms of law and regulations that are related to business operation (North, 1990). According to institutional theory, institutions that comprise the rules of a society or ‘‘humanly devised constraints that shape human interaction’’ (North, 1990). Similarly, Dikova et al. (2010) suggest that the rules of the game vary across nations, which are nation-specific rules. Some rules may be unique to jurisdiction or incompatible with other nations. In addition, nearly every jurisdiction has its own stock exchange rules, securities laws, and corporate law statutes (Keegan & Green, 2011). According to Dikova et al. (2010), when two countries differ greatly in terms of legal and regulatory environments, companies that involved in cross-border merger and acquisition may encounter complexities which cannot be fully interpreted based on their native knowledge and skills. As a result, firms may misjudge the chances of success for a merger and acquisition or overlook some important aspects related to the deal. If the parties realize such misjudgments or negligence only after the merger and acquisition are announced, they may have to abandon the deal during the public takeover period.
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risks to "economic forces that can lead to dramatic changes in the business environment, which are detrimental to foreign firms" Based on Johnson & Tellis (2008) study, some of the economic risks often encountered by foreign companies that may be economic downturns or market downturns, currency crises or sudden outbursts of inflation. There are three ways that country risk distance can affect the completion rate during the merger and acquisition.
First, the greater the country's risk profile, the more likely it is risky for both domestic and host countries. The domestic and host countries may experience adverse changes in the political and economic environment during the public takeover. Such adverse changes may reduce the potential possibility of announced mergers and acquisition deals to complete. Even causing losses to the companies involved, thereby reducing the likelihood of completion rate of the cross-border merger and acquisition. Secondly, even adverse changes do not significantly affect the outcome of mergers and acquisitions; such changes may create new information to understand for companies that involved in mergers and acquisitions during a short period of public takeovers (Zhou, et al, 2016). Because of the time pressure after the announcement of mergers and acquisitions, misunderstandings and miscalculations and the unexpected possibility of announced mergers and acquisitions increase. Therefore, the possibilities that the company will withdraw the merger and acquisition deal increases as well.
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completion rate of cross border merger and acquisition deals. In this paper, the effects of both legal distance and regulatory distance on the failure of completion rate in cross-border merger and acquisition between developed and emerging markets will be examined. The legal distance and regulatory distance measures status quo differences in the legal and regulatory environments between the home and host countries. Additionally, the country risk distance measures differences between the two countries increase the likelihood that dramatic changes may be caused by political and economic forces in the business environment.
Therefore: I propose my fourth hypothesis:
H4a: The absolute law and regulatory distance between acquirer and target countries have
positive moderating effect on the relationship between currency changes and deal completion
likelihood.
H4b: The absolute law and regulatory distance between acquirer and target countries
negative moderating effect on the relationship between currency changes and deal completion
likelihood.
3. Research Methodology 3.1. Data
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$200 million and during the ten years period from 2005 to 2015. Restriction of current deal status is limited to the deals that are announced; completed and withdrawn. Deals that were announced but withdrawn is considered as a failure of cross border merger and acquisition. Any merger and acquisition from an unknown location or recorded as multinational will be excluded. Also, the restrictions on the public, private acquirers, and targets are excluded, because private companies are the target of most of the cross-border merger and acquisition activities.
Currency data are collected primarily from WRDS – Federal Reserve Bank and when the data are not available, another database FOREX API (Based on European Central Bank) is used. Information on cross border merger and acquisition announcement, completion status, acquirer and target company; country, and specific deal information are provided by Zephyr database. The merger and acquisition deals in this study were collected from the Zephyr database, which contains detailed information on more than 500,000 merger and acquisition deals worldwide, with pan-European deals dating back to 1997. No minimum deal value is required in order for deals to be included in Zephyr. Also, merger and acquisition deals involving the public as well as private bidders are covered. Compared to the SDC Platinum database of Thomson Financial and Mergerstat, the Zephyr database covers deals of smaller value and has a better coverage of European transactions. In terms of firm level financial data, they are retrieved from Datastream due to better data availability while it is not available in Zephyr.
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the currency are primarily from WRDS – Federal Reserve Bank and when the data are not available, another database FOREX API (Based on European Central Bank) is used. The firm level financial data of the acquirer and target companies are retrieved from DataStream for better data availability than Zephyr. This provided us with a sample with 1,407 observations. In order to include the deal-level, firm-level variables, and country-level variables, all the data are merged into one table.
3.2 Variables
3.2.1 Dependent Variable
This paper considers the impact of currency exchange rate risk on the likelihood of cross border merger and acquisition deals completion. Similar to Zhou et al., (2016), deal completion is defined as 1 if the deal is completed and 0 otherwise (fail). As stated in data collection, the Zephyr database provides information including the announced merger and acquisition deals on the dates of announcement and completion / withdrawn, as well as the deal status (e.g., completed or withdrawn). Based on the study of Muehlfeld et al., (2012), the median number of days to completion is about 62, with 94% of all deals completed within a year. Within my sample, the mean number of days to completion is 62 for all deals, and 67 days to withdrawn, respectively. The deals completion rate is 92.75% in the 10 years period. Therefore, I consider the cross-border M&As that were pending or without any status until 31/12/2015, to be withdrawn and coded their completion status as 0, since it has been more than two years without an update.
I define deal status as:
Deal Status = DEAL = {Completed, x = 1
25 3.2.2 Independent Variable
In this paper currency exchange rate is measure by the exchange rate between acquirer currency and native currency (currency used in actual payments) at completed/withdrawn date minus the exchange rate at the announced date, then use the differences of currency divided by exchange rate at an announced date. The data of the currency are primarily from WRDS – Federal Reserve Bank and when the data are not available, another database FOREX API (Based on European Central Bank) is used. I define the currency risk as the acquirer currency to native currency depreciation, which the acquirer company faces the risk of paying extra for the same deal due to currency depreciation. If the acquirer currency to native currency depreciated as 1, and 0 otherwise.
I define currency risk (currency depreciation) as:
Currency Risk = CURRENCY = {Depriciated, x = 1
Otherwise, x = 0
3.2.3 Cash Payment
The cash payment is measured by using the data collected from Zephyr that the acquirer company tends to acquire the target company when the merger and acquisition deal is announced and the Cash is used as the payment method of the deals. If the deal is paid by cash completely, we say Cash = 1, and 0 otherwise.
Cash Payment = PAY = { Cash, x = 1
26 3.2.4 Economic Development
Differences in financial market development will be measured by GDP per capita instead of GDP because there are some countries with high GDP, but it’s still a developing country with emerging market. For example, China. Developed markets feature higher levels of economic development, education, economic freedom, and law enforcement which are the country characteristics that facilitate innovation and help lower technology transfer costs which are substantial for multinational firms (Chou & Gao, 2014). Therefore, GDP per capita is used in this paper to measure the economic development of the acquirer and target countries. Previous studies agreed on a positive relationship between GDP per capita and cross border merger and acquisitions. For example, Garita & Marrewijk (2007) found the richer a country is, the more investment they do in other countries. However, in terms of target countries, the relationship could be either positive or negative. Based on “high buys low” principle by Erel & Liao (2012), a negative relationship between host and home countries might also be possible. The data are from the economic freedom index which developed by the Heritage Foundation, it is used to measure the economic development distance between acquirer and target countries in our variables. Looking at the descriptive statistics in Table 2, I see that the withdrawn deals have lesser economic development distance (lesser differences in GDP per capita between acquirer and target countries) compared to the completed deals, on average. To minimize the effect of outliers, I winsorize all continuous variables in this paper at the 1st and 99th percentiles of their distributions.
I define the economic development of target or acquirer countries as:
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I define absolute economic development distance as:
𝐴𝑏𝑠𝑜𝑙𝑢𝑡𝑒 Economic Development 𝐷𝑖𝑠𝑡𝑎𝑛𝑐𝑒 = 𝐸𝐶𝑂
= |Economic Development 𝑜𝑓 𝑇𝑎𝑟𝑔𝑒𝑡 𝑐𝑜𝑢𝑛𝑡𝑟𝑦 − Economic Development 𝑜𝑓 𝐴𝑐𝑞𝑢𝑖𝑟𝑒𝑟 𝐶𝑜𝑢𝑛𝑡𝑟𝑦|
3.2.5 Legal and Regulatory Distance
According to Meyer et al., (2009) & Gubbi et al., (2010) in the management and international business studies, the economic freedom index which developed by the Heritage Foundation is used to measure the law and regulation distance between acquirer and target countries in our variables. The freedom scores of the index are separated into ten categories on the scale from 0 to 100 to examine the ease of individuals and companies to seek business actions in the country. Since I focus on the categories that related to foreign company merge and acquire another company in the different country, four categories of country’s freedom scores are used. I used the average score under the financial freedom; business freedom; fiscal freedom and investment freedom from 2014 index to proxy the legal and regulatory environment of a country. Then I measure the distance between countries in terms of law and regulation by using the absolute difference of their average freedom scores. The higher the value of the variable, the larger distance of the law and regulatory between acquirer and target countries. The law and Regulatory Distance is defined as:
𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝐿𝑎𝑤 𝑎𝑛𝑑 𝑅𝑒𝑔𝑢𝑙𝑎𝑡𝑜𝑟𝑦 𝐷𝑖𝑠𝑡𝑎𝑛𝑐𝑒
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However, in this paper we use the absolute value of Law and Regulatory distance, it is defined as:
𝐴𝑏𝑜𝑠𝑜𝑙𝑢𝑡𝑒 𝐿𝑎𝑤 𝑎𝑛𝑑 𝑅𝑒𝑔𝑢𝑙𝑎𝑡𝑜𝑟𝑦 𝐷𝑖𝑠𝑡𝑎𝑛𝑐𝑒 = 𝐿𝐴𝑊
= |𝐿𝑎𝑤 𝑎𝑛𝑑 𝑅𝑒𝑔𝑢𝑙𝑎𝑡𝑜𝑟𝑦 𝐷𝑖𝑠𝑡𝑎𝑛𝑐𝑒 𝑜𝑓 𝑇𝑎𝑟𝑔𝑒𝑡 𝑐𝑜𝑢𝑛𝑡𝑟𝑦 − 𝐿𝑎𝑤 𝑎𝑛𝑑 𝑅𝑒𝑔𝑢𝑙𝑎𝑡𝑜𝑟𝑦 𝐷𝑖𝑠𝑡𝑎𝑛𝑐𝑒 𝑜𝑓 𝐴𝑐𝑞𝑢𝑖𝑟𝑒𝑟 𝐶𝑜𝑢𝑛𝑡𝑟𝑦|
3.2.6. Control Variables
Control variables are used to test the relationship between currency changes and the likelihood of deal completion. I used the market to book ratio to control the company growth and measured as the market value of equity divided by book value of equity. The higher the market to book ratio, the better company growth. According to previous literature reviews, the R&D expenditure of the company should be coming from equity or internal resources, while debt should not be used. The ratio of R&D is calculated as R&D expenditure to book value of total assets, it is used as a firm variable for moderating effect to examine the technology asset. Companies with higher leverage are more likely becoming targets rather than acquirers. Acquirers with more debt are more likely to pay lower premiums in cross-border deals, and they prefer to use more stock in such deals. Leverage deficit also exert influence on acquirers' capital structure after cross-border deals. Over-leveraged acquirers tend to finance themselves after the deals by selling more equities in stock markets, whereas under-leveraged acquirers are more likely to increase their leverage after the deals.
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with lower leverage. Similarly, if acquirers with higher leverage have difficulties in raising additional funds to pay cash to their foreign targets in cross-border M&A offers, it will be harder for them to pay a higher acquisition premium to their targets. Acquisition premium is the extra amount acquirers offer to target firms on the top of the estimated fair value of the targets. Paying a premium is not compulsory for a company to acquire another firm, which depends on the situation of acquirers and M&As.
These findings are consistent with the studies by Leary & Roberts (2005) and Frank & Goyal (2009) and provide potential explanations for why overleveraged firms adjust their debt ratios more quickly than underleveraged firms. Therefore, leverage is controlled and calculated as the book value of total debt divided by assets. We use several firm characteristics as control variables in our regression model to examine the relationship between currency changes and deal status. tangibility ratio (tangible assets divided by assets), Cash holding ratio (the Ratio of cash and short-term equivalents to book value of total assets). Profitability of the company’s’ performance in operating terms is measured by the return of asset (the ratio of EBIDTA to book value of total assets). is used as a control variable to measure the firm’s growth and investment opportunities.
Leverage = LEV = book value of total debt / assets
Tangibility ratio = TAN=tangible assets / asset
Cash holding ratio = CASH =cash and short-term equivalents / book value of total assets
Return of asset = ROA= the ratio of EBIDTA / book value of total assets
Market to book ratio = MtoB = market value of equity / book value of equity
30 3.3 Regression Model
Base on the paper by Zhou et al., (2016), they used a probit model to measure the completion likelihood of a cross-border M&A is affected by country-, firm- and deal-level factors, as they follow the papers of Muehlfeld et al., (2007, 2012); and Dikova et al., (2010). They assumed the probability of a deal completion is a probit function of exploratory variables, such as country level; firm level; deal level and control variables. According to Firth & Bennett (1998), in a completely randomized experiment with a binary outcome, if you want to adjust for covariates to improve precision, you can use either logit (with an average marginal effect calculation) or OLS to consistently estimate the average treatment effect, even if your model’s “wrong”. However, the probit model doesn’t enjoy this robustness property. Therefore, I used OLS to estimate my Model in this thesis.
The regression model 1 estimated main relationship is as follows:
𝑌𝑖 = 𝛽0 + 𝛽1 𝐶𝑈𝑅𝑅𝐸𝑁𝐶𝑌𝑖+ 𝛽2𝑃𝐴𝑌𝑖 + 𝛽3𝐸𝐶𝑂𝑖 + 𝛽4 − 9𝜀𝑖 (1) The regression model 2 that estimated with moderating effect is as follows:
𝑌𝑖 = 𝛽0 + 𝛽1 𝐶𝑈𝑅𝑅𝐸𝑁𝐶𝑌𝑖 + 𝛽2𝑃𝐴𝑌𝑖 + 𝛽3𝐸𝐶𝑂𝑖 + 𝛽4 𝐿𝐴𝑊𝑖 + 𝛽5 𝐶𝑈𝑅𝑅𝐸𝑁𝐶𝑌𝑖 ∗ 𝑃𝐴𝑌𝑖 + 𝛽6𝐶𝑈𝑅𝑅𝐸𝑁𝐶𝑌𝑖 ∗ 𝐸𝐶𝑂𝑖+ 𝛽7𝐶𝑈𝑅𝑅𝐸𝑁𝐶𝑌𝑖 ∗ 𝐿𝐴𝑊𝑖 + 𝛽8
− 13𝜀𝑖 (2)
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32 4.Result
In this section, I empirically test the likelihood of deal completion associated with cross border merger and acquisitions following (and potentially induced by) currency depreciation: firms could withdraw an announced deal due to additional cost caused by currency depreciation. Under this hypothesis, we expect deal status to be negatively associated with currency depreciation for announced cross border M&A deals. The descriptive statistics is presented in Table 2, and correlation analysis is presented in Table 3. I test my hypothesis using my sample of cross-border merger deals from 2005 to 2015. The dependent variable in our regressions is the deal status. The independent variable is currency depreciation, which is described above (in Section 3.2.2) We control for acquirer characteristics, deal characteristics, country characteristics, and year and industry (two-digit SIC industry classification) fixed effects in the regressions. The results from OLS regressions are presented in Table 4 and Table 5. Table shows the definitions of variables I used in this paper.
Variables Names Definitions
DEAL Deal Status (dependent variable) A dummy with a value of 1 for completed, 0 failed acquisitions. CURRENCY Currency Changes A dummy with a value of 1 for currency depreciated, 0 otherwises. PAY Cash Payment A dummy with a value of 1 for Cash Payment, 0 Otherwise.
ECO Economic Development Absolute distance of Natural logarithm of GDP per Capita in US Dollar between target and acquirer countries.
LAW Law and Regulatory Distance Absolute distance of Law and Regulatory between target and acquirer countries. LEV Leverage Book value of total debt divided by assets.
CASH Cash Holding Ratio of cash and short-term equivalents to book value of total assets. TAN Tangibility Tangible assets divided by assets.
33 4.1 Descriptive Statistics
Note: the table reports descriptive statistics of the key variables used in the empirical analysis, the dependent, independent, firm-level, country level, control variables. The definition of the variables is provided in Table 1.
Table 2 represents the descriptive statics of the variables that used in the regression of analysis. In Table 2 Panel A, which included both withdrawn and completed cross border M&A deals. The dependent variables DEAL has the mean of 92.8%, medium of 100% and standard
Mean Median Maximum Minimum Std. Dev. N
DEAL 92.8% 100.0% 100.0% 0.0% 0.259 1407 CURRENCY 28.7% 0.0% 100.0% 0.0% 0.453 1407 PAY 50.8% 100.0% 100.0% 0.0% 0.500 1407 ECO 4.037 4.117 4.822 2.224 0.426 1407 LAW 8.661 6.825 49.100 0.000 8.989 1407 LEV 0.275 0.261 0.945 0.000 0.151 1407 CASH 0.122 0.089 0.702 0.001 0.111 1407 TAN 0.712 0.746 1.000 -0.001 0.222 1407 MtoB 2.613 2.339 8.919 0.160 1.625 1407 R&D 0.021 0.002 0.870 -0.004 0.044 1407 ROA 0.123 0.119 0.770 -0.479 0.085 1407
Mean Median Maximum Minimum Std. Dev. N
DEAL 0.0% 0.0% 0.0% 0.0% 0.000 102 CURRENCY 38.2% 0.0% 100.0% 0.0% 0.488 102 PAY 64.7% 100.0% 100.0% 0.0% 0.480 102 ECO 3.939 4.001 4.822 2.579 0.443 102 LAW 7.043 6.825 29.550 0.000 5.468 102 LEV 0.278 0.273 0.718 0.000 0.155 102 CASH 0.130 0.094 0.671 0.002 0.117 102 TAN 0.724 0.760 1.000 0.000 0.225 102 MtoB 2.820 2.228 8.919 0.160 1.975 102 R&D 0.025 0.004 0.214 0.000 0.044 102 ROA 0.122 0.113 0.388 -0.278 0.097 102
Mean Median Maximum Minimum Std. Dev. N
DEAL 100.0% 100.0% 100.0% 100.0% 0.000 1305 CURRENCY 28.0% 0.0% 100.0% 0.0% 0.449 1305 PAY 49.7% 0.0% 100.0% 0.0% 0.500 1305 ECO 4.045 4.117 4.822 2.224 0.424 1305 LAW 8.787 6.825 49.100 0.000 9.198 1305 LEV 0.274 0.259 0.945 0.000 0.151 1305 CASH 0.122 0.089 0.702 0.001 0.110 1305 TAN 0.711 0.741 1.000 -0.001 0.222 1305 MtoB 2.597 2.339 8.725 0.170 1.595 1305 R&D 0.021 0.002 0.870 -0.004 0.043 1305 ROA 0.123 0.120 0.770 -0.479 0.084 1305
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deviation of 0.259, respectively. Since the dependent variable is defined as “Completed = 1”, “0 = Otherwise (Withdrawn)”, I separated the descriptive statics for both withdrawn and completed deals in Panel B and Panel C for better comparison, while the dependent variable DEAL is 0 for Panel B for withdrawn deal and 1 for Panel C as completed deals. The mean of independent variable CURRENCY for withdrawn deals is 38.2% compares with the 28.0% for completed deals, this means that there are 10.2% currency depreciated during the period of announce date to withdrawn or completed date. This fits my expectation that currency depreciation will decrease the likelihood of deal completion.
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deviation 8.787, 6.825, 9.198. The possible explanation is that even though the LAW and difference of ECO of completed deals is higher than the withdrawn deals, the completed deals tend to use other payment methods instead of cash. This choice may help the company to avoid currency changes of possible depreciation of the acquirer’s currency to native currency.
4.2 Correlation Analysis
Table 3: Sample Correlation
Note: Table 3 provides the information of correlation for variables used in the regression of the empirical analysis, *, **, *** means significant at 10%, 5%, 1% level, respectively (Source: DataStream).
Table 3 presents the results for the predicted probability that a deal is completed. The first row of Table 3 shows the Pearson correlations between DEAL and various estimates of the probability that a deal will be completed. PAY estimates of the probability of a deal completion correlated strongest with DEAL (p = -0.078), while independent variable CURRENCY predicted values correlated -0.059. The PAY and CURRENCY predicted values correlated 0.056, ECO and LAW are positive and significantly associated with DEAL. However, the control variables of LEV, CASH, TAN, ROA, R&D and MtoB are not significantly associated with DEAL.
36 4.3 Multivariate Analysis
I estimate the model in Equations (1) and (2) by using a full sample with both the withdraw and completed samples combined. To show the main effects of the country, firm-, and deal-level factors on deal completion, I first estimate a main-effect Model by excluding the interaction terms of these three-level factors. Then I estimate a full Model with both the main effects and interaction terms included one by one. The estimation results are presented in the columns of Model 1, Model 2 Model 3 and Model 4 in Table 4, respectively.
To test hypothesis H1, I examine the coefficient 𝛽 which measure the impact of currency depreciation on the likelihood of deal completion. A coefficient that is positive and significant means if the currency depreciation increases by 1%, the likelihood of deal completion will increase by 𝛽%. We add firm level variables and control variables to determine the impact of individual variables on the likelihood of deal completions. For moderating effect, we use Model to measure the impact of additional country level variables on the relationship between currency changes on the likelihood of deal completions. Model 5, 6, 7 and 8 is used to test hypothesis H2a H2b, H3a H3b and H4a H4b. A positive and significant coefficient 𝛽 means the moderating variables strengthen the main relationship.
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acquirer countries, respectively. In terms of moderating effect, as I proposed H2a, H2b, H3a, H3b, and H4a, H4b. The moderating effect of PAY, ECO and LAW are estimated in Model 5 to 8.
Table 4: Multivariate Analysis (Model 1 – 4)
Note: Table 4 reports estimated coefficients used in the regression of the empirical analysis, on R&D. Definitions of variables are provided in Table 1. Models employ year and industry fixed effects. The sample period is 2005-2015. Standard errors are shown in brackets. ***, **, * mean statistical significance at 1%, 5%, 10% levels respectively (Source: DataStream).
As shown in Model 1 of Table 4, the coefficient of currency depreciation is significantly negative (𝛽1 = -0.035, p<0.5), which is consistent with the literature reviewed and in line with the prediction of hypothesis H1. Also, the estimated coefficient PAY and ECO are all statistically
Variables Model 1 Model 2 Model 3 Model 4 CURRENCY -0.035** -0.035** -0.031* -0.030* (0.015) (0.015) (0.016) (0.016) PAY -0.040*** -0.040*** -0.040*** (0.014) (0.014) (0.014) ECO 0.038** 0.032* (0.017) (0.019) LAW 0.001 (0.01) LEV -0.033 -0.042 -0.046 -0.045 (0.049) (0.049) (0.049) (0.049) CASH -0.020 -0.009 -0.014 -0.015 (0.074) (0.074) (0.073) (0.073) TAN -0.027 -0.036 -0.036 -0.041 (0.033) (0.033) (0.033) (0.034) MtoB -0.006 -0.006 -0.006 -0.006 (0.005) (0.005) (0.005) (0.005) R&D -0.116 -0.074 -0.055 -0.033 (0.182) (0.182) (0.163) (0.164) ROA 0.043 0.059 0.046 0.054 (0.085) (0.085) (0.095) (0.096) Constant 0.980*** 1.005*** 0.854*** 0.874*** (0.034) (0.035) (0.077) (0.079) F-Statistics 1.2144 2.074** 0.009** 2.341***
Year Dummies Yes Yes Yes Yes
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significant which is in line with the proposed theory. For Model 2, PAY is added as additional variable for the main regression. PAY is negative and significant at 1% level in Model 1-4, which is consistence with the literature. In Model 3, ECO is significant at 5% level and positive relationship with DEAL, this is in line with literature. Moreover, in Model 4 LAW is positive and significant at 10% level. This means that the greater economic development, the higher likelihood a cross border merger and acquisition deal can be completed. The impact of control variables mainly at firm level, variables LEV, CASH, TAN, MtoB, R&D and ROA are added in all Models.
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Table 5: Multivariate Analysis (Model 5 - 8)
Note: Table 5 reports estimated coefficients used in the regression of the empirical analysis, on R&D. Definitions of variables are provided in Table 1. Models employ year and industry fixed effects. The sample period is 2005-2015. Standard errors are shown in brackets. ***, **, * mean statistical significance at 1%, 5%, 10% levels respectively (Source: DataStream).
In Table 5, Model 5 – 8 provides evidence of firm level and country level variables has moderating effect on the main relationship between CURRENCY and DEAL. Similarly, as shown in Model 2 of Table 4, the main effects of PAY remain the same after the moderating effect of
Variables Model 5 Model 6 Model 7 Model 8 CURRENCY 0.009 0.014*** -0.013 -0.022*** (0.018) (0.163) (0.024) (0.163) PAY -0.018 -0.018 (0.015) (0.015) ECO 0.042** 0.031 (0.020) (0.021) LAW 0.002*** 0.001** (0.000) (0.01) CURRENCY*PAY -0.078** -0.078** (0.032) (0.032) CURRENCY*ECO -0.012 0.002 (0.040) (0.040) CURRENCY*LAW -0.003 -0.002 (0.002) (0.002) LEV -0.044 -0.036 -0.030 -0.044 (0.049) (0.049) (0.049) (0.049) CASH -0.009 -0.025 -0.022 -0.013 (0.073) (0.072) (0.072) (0.072) TAN -0.034 -0.028 -0.033 -0.038 (0.033) (0.033) (0.034) (0.034) MtoB -0.006 -0.006 -0.006 -0.006 (0.005) (0.005) (0.005) (0.005) R&D -0.067 -0.096 -0.081 -0.028 (0.164) (0.170) (0.172) (0.164) ROA 0.058 0.031 0.055 0.055 (0.093) (0.096) (0.094) (0.095) Constant 0.993*** 0.966*** 0.966*** 0.861*** (0.037) (0.036) (0.036) (0.090) F-Statistics 2.575*** 1.574 1.456 2.404***
Year Dummies Yes Yes Yes Yes
Industry Dummies Yes Yes Yes Yes
Adjusted R2 0.010 0.004 0.003 0.013
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M&A direction is incorporated. However, the coefficient of PAY is not significantly negative (𝛽2= -0.018, p [0.10). But Model 5 provides evidence that PAY has negative and significant moderating effect on the main relationship between CURRENCY and DEAL (H2b), which means the moderating effect of PAY weaken the relationship between CURRENCY and DEAL. This is consistent with hypothesis H2b, which fits my expectation that cash payment has negative moderating effect on currency deprecation to the likelihood of deal completion.
Other moderating effect of country level variables ECO and LAW are not significant. In Model 6, the coefficient on CURRENCY*ECO is negative and not statistically significant, means that the moderating effect of economic development weaken the main relationship, as well as law and regulatory distance (LAW) in Model 7. Therefore, the hypothesis H3a, H3b, and H4a, H4b does not hold. The coefficient of control variables is not significant, possible explanation is the control variable are all at firm level, while the main relationship is about cross border merger and acquisitions. Adding country level variable might have more impact on the relationship.
4.4 Limitation and Future Development
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expecting. The main relationship of the hypothesis is not supported by the result, this could due to the possible hedging strategy used by the company. Also, the cash payment is 50% in 1, 407 deals. The companies might have avoided potential changes in currency by different payment other than cash.
In order to get more reliable data, I collected currency exchange rate from WRDS. However, the exchange rate in WRDS is only available for Local Currency / USD, and in some specific date the data are not available as well. The suggestion for possible future work is use larger data sample and use difference source to get more available data. My findings show that the currency changes have significant negative impact on the likelihood of deal completion, this could be driven by different calculation method of currency changes, as well as different payment method. Future studies could focus on the impact of currency changes in terms of cash payment or other currency related methods. In terms of currency changes, future studies could use volatilities of the currency during specific period. For financial data collected from Compustat and DataStream, many data are missing. For country level variables, I used the location of headquarter of acquirer’s country. However, some countries headquarter shows as Bermuda or Cayman Islands where the companies used to avoid tax instead of real operating location. Future research can extend the data collection at their real headquarter location.
5. Conclusion
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to merge and acquire another company to protect of increase the profitability or strength of the acquirer company and maximize the shareholder's wealth. When the company planning to expand or enter a new market, they might achieve that by merge with companies or acquirer a company in other countries. Some companies attempt to relocate their business in low tax countries to reduce tax. While the extant literature has extensively studied the factors that impact currency changes and has focused mainly on domestic M&A deals instead of cross-border M&As deals. However, cross border merger and acquisitions also associates with the difficulties that domestic merger and acquisition doesn’t have. Specifically, currency exchange rate risk is the key factor that domestic merger and acquisition does not need to face. This thesis examines the period of time during the public takeover period of a cross-border M&A deal, from when an intended cross-border M&A is announced to the completion or withdrawn of the deal. I examine the impact of currency depreciation on the likelihood of deal completion, and the moderating effect of other variables. Such as cash payment, economic development and law & regulatory distance between target and acquirer countries.
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