EMERGING MARKET CROSS-BORDER ACQUISITION. Nicholas Seay Volz. Cameron School of Business. University of North Carolina Wilmington.

Transcription

1 EMERGING MARKET CROSS-BORDER ACQUISITION Nicholas Seay Volz A Thesis Submitted to the University of North Carolina in Partial Fulfillment of the Requirements for the Degree of Master of Business Administration Cameron School of Business University of North Carolina Wilmington 2011 Approved by Advisory Committee Cetin Ciner Pete Schuhmann Nivine Richie Chair Accepted by Dean, Graduate School

2 TABLE OF CONTENTS ABSTRACT... iii LIST OF TABLES... iv LIST OF FIGURES... v 1. INTRODUCTION BRIEF OVERVIEW OF GLOBALIZATION RELATED LITERATURE FINANCIAL CHARACTERISTICS OF ACQUIRER AND TARGET FIRMS NET PRESENT VALUE CRITERIA AND THE LIKELIHOOD OF ACQUISITION FACTORS PREDICTING WHETHER FIRMS WILL BE TARGETS OR ACQUIRERS INDUSTRY CHARACTERISTICS CULTURAL DISTANCE HYPOTHESES DATA AND METHODOLOGY RESEARCH DESIGN RESULTS CONCLUSION REFERENCES ii

3 ABSTRACT This study looks at the characteristics of cross-border acquisitions made by emerging market firms of developed market firms to determine the factors that affect the likelihood of an emerging market firm acquiring a majority or total ownership of a developed market firm. Financial and cultural characteristics of both the acquirer and target firms are used in logit regression to predict whether a majority or total ownership is purchased. The findings of this study conclude that greater liquidity of the acquirer firm increases the likelihood of an emerging market firm acquiring a majority ownership of a developed market firm. These results support the firm liquidity preference hypothesis and are consistent with findings from Vasconcellos (1993) and Gonzalez (1997) regarding firm liquidity. The findings further conclude that higher cultural distance negatively affects whether a majority or total acquisition is made. These results support the cultural distance hypothesis and are consistent with Kogut and Singh s (1988) findings regarding the effect of cultural distance on a firm s method of foreign direct investment. There is additional evidence that suggests emerging market firms are also acquiring greater ownership of both the best performing and the most distressed developed market firms. iii

4 LIST OF TABLES Table Page 1. Summary Statistics Country Distribution of Acquisitions Acquirer Firm Results Estimating Majority and Total Ownership Models Acquirer Firm Results Estimating Total Ownership Models Acquirer Firm Results Estimating Majority Ownership Model Acquired Firm Results Estimating Majority and Total Ownership Models Acquired Firm Results Estimating Total Ownership Model Acquired Firm Results Estimating Majority Ownership Model iv

5 LIST OF FIGURES Figure Page 1. Acquirer Firm Acquisition Summary Panel A: Percentage of Total Acquisition Among Each Acquiring Country Panel B: Acquirer Country Industry Focus: Industry Most Targeted by Each Acquiring Country as a Percentage of Their Individual Acquisition Total v

6 1. INTRODUCTION Over the past decade, several emerging market firms have acquired developed market firms. Lenovo Group acquired IBM s PC business for $1.75 billion. Tata Motors acquired Jaguar and Land Rover operations from Ford Motors for $2.3 billion. Vale SA acquisition of Vale Canada for $ billion. In each of these cases, an emerging market firm increased its international presence and has become a powerful global competitor. Recent business news continues to report on the rise of emerging market multinationals and their acquisition spree of developed market assets. According to a summary of business articles, the three main driving forces behind emerging market acquisitions of developed market firms are attaining expertise, resources and access to developed markets. This study examines cross-border acquisitions from emerging to developed markets through identifying the financial characteristics that affect the likelihood of a majority purchase being made. Characteristics of acquired and acquirer firms that have previously been shown to affect the likelihood of an acquisition include efficiency, size, leverage and cultural distance. Data is collected from both acquired and acquirer firms from a sample of emerging market crossborder acquisitions made by firms from Brazil, Russia, India, China and South Africa (BRICS) of developed market firms from the United States, selected Western European countries, Australia, Japan and Singapore during the years of 2000 to In this study logit regression is used to identify the financial characteristics and relative cultural distance that determine whether a majority ownership is purchased. Since emerging market firm acquisitions into developed markets is relatively new, from a global business perspective one must understand the motivations behind this flow of acquisitions. Better

7 understanding of emerging market acquisitions of developed market firms can help multinational firms understand their rising emerging market challengers. 1.1 Brief Overview of Globalization Over the past two decades the rate of globalization has accelerated helping to spread economic, social and political development throughout the world. As companies from developed economies expand internationally and engage in foreign direct investment with emerging economies, the world becomes more interconnected. Globalization is defined as the growing interdependence of countries worldwide through increasing cross-border transactions and widespread diffusion of technology (International Monetary Fund). While the internationalization of firms from developed economies is at the forefront of globalization, other key elements work with foreign direct investment and help to drive the process. These drivers of globalization include: economic liberalization through the General Agreement on Trade and Tariffs and the World Trade Organization; the spread of international governance and regulation; the spread of finance and capital through international markets; the diffusion of information and communication technologies; and the social and cultural convergence creating a global consumer with global opportunities. As firms identify their core capabilities, they strive to leverage them to create competitive advantage. Core capabilities become the focus of value generation for the firm and other activities are standardized to reduce costs and increase efficiency and profitability. The drivers of globalization help to create an environment where firms from developed-economies can move production to low-cost countries, therefore developing a competitive advantage in reduced production costs relative to their competitors who choose to keep production at home (Craig & 2

8 Douglas, 1997). For example, India has become a source of inexpensive intellectual capital while China has become a region where inexpensive products can be efficiently mass-produced. Choosing to internationalize presents the perfect opportunity for capable firms to locate production operations to developing economies where these labor costs are relatively inexpensive. Firms from developed economies who recognize these opportunities help to increase the rate of globalization by expanding their international presence and foreign direct investment, thus adding to the process of globalization. Once firms begin expanding internationally and moving production to low cost countries, foreign direct investment flows increase from developed to developing countries. Foreign subsidiaries are established through Greenfield investments and joint ventures with local companies. As economic development grows in these low cost countries, monetary inflow and government stability help to create emerging middle class structures. Domestic companies, who gain experience from past joint ventures with developed economy firms, are focus attention on growing within their domestic markets as well as expanding internationally. Factors driving the internationalization of firms include lower barriers to international trade and investment; improvement of international regulation and governance; and improvements in communication. The success of new economic powerhouses in Brazil, India and China, have created new opportunities and challenges for firms throughout the world (Eitman, Stonehill & Moffett, 2010). Firms from foreign markets will increasingly enter these powerhouse markets to seek growth, as newly developing firms from within these markets will emerge as global competitors challenging the established developed market multinationals. 3

9 Market drivers of internationalization include the convergence of global needs and wants, helping to create a global consumer where firms can standardize certain activities to become more efficient. Therefore, firms seek to develop global brands that transcend geographical boundaries. The findings of this study conclude that greater liquidity of the acquirer firm increases the likelihood of an emerging market firm acquiring a majority ownership of a developed market firm. These results support the firm liquidity preference hypothesis and are consistent with finding from Vasconcellos (1993) and Gonzalez (1997) regarding firm liquidity. The findings also conclude that higher cultural distance negatively affects whether a majority or total acquisition is made. These results support the cultural distance hypothesis and are consistent with Kogut and Singh s (1988) findings regarding the affect of cultural distance on a firm s method of foreign direct investment. There is also evidence that suggests emerging market firms are choosing to acquire a greater ownership of both the best performing and most distressed developed market firms. 2. RELATED LITERATURE The literature on mergers and acquisitions focuses on the key attributes of acquired and acquirer firms to identify characteristics associated with an acquisition. The literature can be categorized along the following six topics: (1) financial characteristics of acquirer and acquired firms, (2) net present value criteria and the likelihood of becoming an acquired firm, (3) factors predicting whether firms will be targets of acquirers, (4) industry characteristics, and (5) cultural distance. 4

10 2.1 Financial Characteristics of Acquirer and Target Firms Prior studies identify attributes of acquired and acquirer firms involved in acquisitions. Studies that analyze acquired firms during the late 1960s find that acquired firms are smaller in size and have lower price-earnings ratios relative to non-acquired firms (Monroe and Simkowitz, 1971). Additional results from Stevens (1973) are consistent with these finding regarding smaller acquired firms with lower price-earnings, yet they also conclude acquired firms have more liquidity and less leverage than non-acquired firms. Harris (1982) examines the likelihood of a firm being acquired between 1974 and 1977 and concludes that the lower the price-earnings multiple and smaller the size, the greater the likelihood of a firm being acquired. While financial variables help to predict a firm becoming a target for acquisition, the study also indicates that product market variables such as advertising and industry concentration are irrelevant. Wansley (1984) finds that acquired firms have less leverage relative to non-acquired firms. Deitrich and Sorensen (1984) focusing on acquisitions within the food and beverage, chemicals, electronics and transportation industries from the years and find that lower turnover and lower leverage increase the likelihood of a firm becoming acquired. Sorensen (2000) finds evidence suggesting acquirer firms are relatively more profitable which supports the viewpoint that acquirer firms have above average margins and look to quickly expand their sales base through acquisition. Through an empirical investigation of the factors affecting cross-border acquisitions between the United States and the United Kingdom, Vasconcellos (1990) finds that exchange rate differences between these two countries have a positive effect on the firm becoming acquired. However, further analysis by Vasconcellos (1993) of cross-border acquisitions between the United States and Japan conclude that exchange rate differences only have 5

11 significance as a predictor of trends in acquisitions, and are not causal factors. Significant determinants of acquisitions found between the United States and Japan include the cost of debt related to firm financial leverage and the stock price related to firm price-earnings. Owen (1995) finds that price-earnings ratios for target firms are relatively high. These results indicate that the market views the acquired firms as having high potential for success. 2.2 Net Present Value Criteria and the Likelihood of Acquisition Evidence from Gonzalez (1997) suggests that the financial characteristics that affect the net present value of expected cash flows are the same factors that affect cross-border acquisitions. Gonzalez (1997) develops three hypotheses involving the net present value criteria for acquired firms that include price-earnings, leverage and liquidity. According to his price-earnings hypothesis firms with higher price-earnings ratios tend to increase acquisition costs and reduce the net present value of future cash flows. The increased acquisition costs and reduction of the NPV of future cash flows decreases the likelihood of the firm being acquired and leads to the assumption that firms with higher price-earnings ratios are less likely to be acquired. His leverage hypothesis suggests firms with low leverage have underutilized debt capacity. Therefore, the opportunity exists for an acquiring firm to utilize the low leverage of the acquired firm in order to help finance the acquisition. This in turn will lower the cash outlays of the acquiring firm. As a result, this hypothesis contends that firms with lower leverage are more likely to become acquisition targets. Lastly, his liquidity ratio asserts firms with a high current ratio may have extra liquidity and the potential for increased debt capacity. This creates an opportunity for acquiring firms to 6

12 use this extra liquidity or increased debt capacity to reduce their cash outlay. Consequently, firms with higher liquidity ratios have a greater likelihood of becoming an acquisition target. Findings from Gonzalez (1997) based on cross-border mergers and acquisitions using the net present value financial hypotheses conclude that the net present value criteria affect the likelihood of a U.S. firm becoming a target for acquisition by a foreign acquirer. Vasconcellos (1993) finds that U.S firms with lower price-earnings, lower leverage, and higher liquidity are more likely to become foreign acquisition targets and these findings are consistent with the prior results on studies of cross-border mergers and acquisitions between U.S and Japanese firms. 2.3 Factors Predicting Whether Firms will be Targets or Acquirers In addition to studies showing that size, price earnings, leverage and liquidity can determine the likelihood of an acquisition, other hypotheses are frequently used in acquisition studies to analyze both acquired and acquirer firms. These studies test the firm characteristics previously tested in the Net Present Value criteria. Palepu (1986) develops hypotheses focusing on the acquired firm that include inefficient management, growth-resource imbalance, industry disturbance, firm size, asset under-valuation, and price-earnings ratio. Palepu s (1986) inefficient management hypothesis contends that firms seek to acquire targets that have relatively low financial efficiency. The idea is that efficiency can be influenced and controlled by superior management. Acquirers targeting firms that are relatively inefficient suggests that acquirer firms believe new management can lead to increased efficiency. Therefore, acquirers can replace the current management and increase efficiency. His growth-resource hypothesis contends that growth opportunities and excess debt capacity within acquired firms provide potential gains to acquiring firms. The excess liquidity or debt capacity resources of acquired firms can be more profitably invested in projects taken by the 7

13 acquirer, or the projects of the acquired firm can be more profitably financed at the acquirer s lower cost of debt. As tested by Palepu (1986) the lower the firm leverage, the more likely the firm is to become an acquisition target. Palepu s (1986) industry disturbance hypothesis contends that merger waves are the result of economic shocks due to changes in technology, market structures, and regulation. For example, the forces of globalization previously mentioned above may be partly responsible for the wave of mergers and acquisitions from emerging to developed markets used. His firm size hypothesis contends that larger firms are less likely to become acquisition targets due to the greater costs of integrating larger targets into the organizational structure of the acquiring firm. In addition, larger firms may have the ability to engage in prolonged and costly takeover defenses. His asset undervaluation hypothesis contends that firms with low market-to-book ratios are viewed as undervalued and more attractive for takeover. In addition, acquired firms will have lower market-to-book value compared to non-acquired firms. His price-earnings hypothesis contends that firms with high price-earnings ratios will experience instantaneous gains from the acquisition of low price-earnings firms as a result of a tendency for the market to value the combined firm at the higher original price-earnings ratio of the acquirer firm. Studies performed by Palepu (1986) testing the acquired firm acquisition hypotheses on a sample of acquisitions taken from the years find strong support for the firm size hypothesis. Palepu (1986) finds larger firms are less likely to become acquisition targets. The results also support the resource imbalance hypothesis related to acquired firm leverage and the price-earnings hypothesis. 8

14 Although Palepu s (1986) study testing the acquisition hypotheses is significant, a replicated study by Cudd and Duggal (2000) that adjusts each observation for industry specific characteristics finds new evidence to support the inefficient management hypothesis. Cudd and Duggal (2000) find firms with lower profitability are more likely to be acquired. The different results found between Palepu s (1986) original study and the replicated study by Cudd and Duggal (2000) suggest that industry specific characteristics exist when using a sample containing different industries and therefore should be addressed. Kumar and Rajib (2007) further build upon Paleup s (1986) hypotheses and develop additional hypotheses focusing on the acquirer firm that include capital structure, firm size and management performance. Kumar and Rajib s (2007) capital structure hypothesis contends that acquirer firms with relatively low leverage levels have the ability to use their underutilized debt capacity to finance acquisitions. Furthermore, their hypothesis states that acquired firms with high levels of leverage are unable to pursue capital-intensive projects. As a result acquirer firms with low leverage seek target firms with high leverage. Therefore, acquirer firms will have relatively lower leverage compared to acquired firms. Their firm size hypothesis for acquirer firms contends that large firms have more resources in terms of financial capabilities and are more likely to pursue acquisitions. Therefore, acquirer firms tend to be relatively large. Their management performance hypothesis contends, the stronger the past performance of acquirer firms, the more likely they are to succeed through acquisitions. Therefore, the higher the acquirer efficiency the more likely the acquirer is to pursue acquisitions. 9

15 An empirical examination by Kumar and Rajib (2007) of merging firms in India finds support for the firm size hypothesis. Kumar and Rajib (2007) further conclude that higher firm leverage increases the likelihood of the firm becoming acquired. They suggest that acquiring firms tend to be more profitable than target firms, suggesting that acquirers are profitable businesses that seek growth by external acquisitions. 2.4 Industry Characteristics Evidence suggests that unique industry specific financial characteristics exist and can have an impact on the results of financial analysis. Financial ratio averages tend to be different for each industry. Trahan and Shawky (1992) find that having multiple industries in the same sample leads to inconclusive results when predicting the likelihood of a firm becoming an acquisition target. In order to address the issue of having multiple industries within the same sample, Cudd and Duggal (2000) develop an industry adjustment formula which adjusts the financial ratios to reflect the degree to which a firm deviates from the industry. 2.5 Cultural Distance Cross-border acquisitions involve unique dimensions that must be considered when doing business internationally. Culture plays an important role in the organizational structure and management style of a firm. Multinational corporations must be aware of the different characteristics of culture when engaging in business throughout the world just as consumer needs and wants vary and business norms and practices are often derived in part by the culture of the country in which the business is centrally located. In today s global business environment transnational companies must have a global perspective to succeed. However, as companies internationalize they tend to gravitate towards familiarity before engaging in business with 10

16 cultures significantly different from their own. In other words, companies tend to take steps toward internationalization that begin with familiar territory as they gradually increase their global footprint and move towards more unfamiliar territory as experience increases. Measuring the cultural distance between each country involved in cross-border acquisition can suggest if the percent owned is influenced by the relative distance in culture. In order to measure the individual cultural distance between two countries, Hofstede (1980) has developed four cultural dimensions from which each country is given a score based on how their own culture is rated on each dimension. Hofstede s four cultural dimensions are power distance, individualism, masculinity, and uncertainty avoidance. Power distance is the extent to which the less powerful members of organizations accept and expect that power is distributed unequally. Individualism is the extent to which individuals are integrated into groups. The opposite would be collectivism. Masculinity and femininity refer to the distribution of roles between the genders. Uncertainty avoidance deals with a society s tolerance for uncertainty and ambiguity. Kogut and Singh (1988) show that cultural distance matters in choosing to internationalize. Foreign direct investment choices of whether to invest in a joint venture, wholly owned Greenfield project or acquisition are influenced by cultural distance. Kogut and Singh (1988) use Hofstede s cultural dimension to test if greater cultural distance between the country of the investing firm and the country of entry increases the likelihood a firm will choose a joint venture or wholly owned Greenfield project over an acquisition. Kogut and Singh (1988) find that cultural distance matters when choosing a method to invest and that the greater the cultural distance between the foreign firm and the United States, the less risk the foreign firm is willing to take. 11

17 3. HYPOTHESES Much research has been focused on acquisitions within developed markets, cross-border acquisitions made from developed-to-developed markets, and cross-border acquisitions made from developed to emerging markets. That is why the focus of my study is on emerging to developed cross-border acquisitions, in other words, acquisition flow in the opposite direction. As the forces of globalization have helped to redistribute and create wealth in new areas throughout the world, the emerging market economies of Brazil, Russia, India, China and South Africa have rapidly expanded. As these countries have developed and grown, emerging market multinational firms have emerged to become global competitors, acquiring developed market firms along the way. This study helps to understand the motives behind emerging-market firms acquiring developed market firms by looking into the financial characteristics of both acquired and acquirer firms and their effect on the percent of ownership sought by the acquiring firm, therefore determining what characteristics of developed market firms make them more attractive targets for complete ownership by emerging market acquirers. The five hypotheses tested in this study are as follows. Hypothesis 1. Management Efficiency Hypothesis. The management efficiency hypothesis states the higher the acquirer firm efficiency, the greater the percentage of ownership will be acquired by the emerging market firm. The hypothesis also states the lower the acquired firm efficiency, the greater the percentage of ownership will be acquired by the emerging market firm. 12

18 Hypothesis 2. Capital Structure Hypothesis. The capital structure hypothesis states the lower the acquirer firm leverage, the greater the percentage of ownership will be acquired by the emerging market firm. The capital structure hypothesis also states the lower the acquired firm leverage, the greater the percentage of ownership will be acquired by the emerging market firm. Hypothesis 3. Liquidity Preference Hypothesis. The liquidity preference hypothesis states the higher the acquirer firm liquidity, the greater the percentage of ownership will be acquired by the emerging market firm. The liquidity preference hypothesis also states greater the acquired firm liquidity, the greater the percentage of ownership will be acquired by the emerging market firm. Hypothesis 4. Firm Size Hypothesis. The firm size hypothesis states the higher the acquirer firm total assets, the greater the percentage of ownership will be acquired by the emerging market firm. The firm size hypothesis also states the lower the acquired firm total assets, the greater the percentage of ownership will be acquired by the emerging market firm. Hypothesis 5. Cultural Distance Hypothesis. The cultural distance hypothesis states the lower the cultural distance between the acquirer firm s home country and the acquired firm s home country, the greater the percentage of ownership will be acquired by the emerging market firm. 13

19 4. DATA AND METHODOLOGY The data are taken from a list of cross-border acquisitions using the Bloomberg database. The acquisitions are filtered to include acquiring firms from the emerging-markets of Brazil, India, China, Russia and South Africa and their target firms from the developed markets of Australia, Austria, Belgium, Canada, Finland, France, Germany, Ireland, Italy, Japan, Netherlands, Norway, Portugal, Singapore Spain, Sweden, Switzerland and the United States. The sample period is from 2000 to The industries include auto manufacturers, beverages, biotechnology, chemicals, coal, computers, food, iron/steel, mining, oil and gas, pharmaceuticals, retail, and software. The financial data for the year prior to the announcement date are gathered from Bloomberg. Country cultural dimension information is gathered from Geert Hofstede s website on cultural differences. The complete set of observations used in this study is separated into two samples according to acquired and acquirer firm financial data. Sample one includes 312 observations of acquirer firm data. Sample two includes 99 observations of target firm data. 14

20 Table 1. Summary Statistics CULTURE is the difference between the acquirer and target home country s cultural distances, ROE is the average 3-year return on equity one year prior to the acquisition date, CR is the 3- year average current assets divided by the current liabilities one year prior to the acquisition announcement date, DA is the 3-year average long-term debt to total assets one year prior to the acquisition announcement date, and ASSETS is the total assets one year prior to the acquisition announcement date. Panel A. Acquirer Firm Summary Statistics N MEAN MEDIAN ST DEV MIN MAX ROE ROA CR DA ASSETS , , Panel B. Acquired Firm Summary Statistics N MEAN MEDIAN ST DEV MIN MAX ROE ROA CR DA ASSETS , Table 1 Panel A presents the summary statistics for the acquirer sample. For the 11-year period from January 2000 to July 2011, the sample includes 312 acquiring firms with an average 3-year return on equity of percent and a median 3-year return on equity of percent. The acquirer sample has an average 3-year debt to assets of percent. The average total 15

21 assets one year prior to the acquisition announcement date for acquiring firms in the sample is $5,922 million. Overall the acquiring firms are profitable businesses. Table 1 Panel B presents the summary statistics for the acquired sample. The sample includes 99 acquired firms with an average 3-year return on equity of percent and a median 3-year return on equity of percent. The acquired sample has an average 3-year debt to assets of 11.5 percent. The average total assets one year prior to the acquisition announcement date for acquired firms in the sample is $1,1270 million. Overall the acquired firms in the sample are unprofitable. The average total assets for acquired firms is much lower than for the acquirer firms. Table 2. Country Distribution of Acquisitions 344 observations This table presents the total number of acquisitions made by each of the acquiring countries: Brazil, India, China, Russia and South Africa, in each of the target counties. Total Country Brazil China India Russia South Africa Australia Austria 1 1 Belgium 3 Britain Canada Denmark 1 Finland 3 France 1 3 Germany Ireland 1 1 Italy Japan

22 Table 2 cont. Netherlands 1 Norway Portugal Singapore Spain 5 Sweden 3 Switzerland United States Table 2 presents the distribution of acquisitions across different countries. The table shows that 16 emerging market acquirers come from Brazil, 60 from China, 199 from India, 26 from Russia and 43 from South Africa. The United States has the largest number of acquired firms with 134, followed by Europe with 60, and Britain with 51. The largest acquirer of United States firms is India with 103 acquisitions. Germany has the largest number of acquired firms in Europe with 14. There are 45 acquired firms from Australia and 36 from Canada. Chart 1. Acquirer Firm Acquisition Summary Panel A. Percentage of Total Acquisitions among each Acquiring Country 8% 13% 5% 17% Acquirer Country Brazil China India 58% Russia South Africa 17

23 Panel B. Acquirer Country Industry Focus: Industry Most Targeted by each Acquiring Country as a Percentage of their Individual Acquisition Total Brazil 31% food companies India 25.63% software China 50% mining South Africa 44.18% mining Russia 33.33% oil & gas Chart 1 Panel A presents the percentage of total acquisitions by each of the acquiring countries. Panel A shows that 58 percent of the acquiring firms are from India, followed by 17 percent from China, 13 percent from South Africa, 8 percent from Russia and 5 percent from Brazil. Chart 1 Panel B presents each emerging market country and the industry where the greatest percentage of their individual acquisitions come from. Panel B shows that 31 percent of Brazil s acquisitions are of food companies while percent of India s acquisitions are of software companies. 50 percent of China s acquisitions are of mining companies as well as percent of South Africa s acquisitions percent of Russia s acquisitions are of oil and gas companies. 18

24 4.1 Research Design A number of prior studies use logit regression to predict the likelihood of an acquisition. Following Paleup (1986), the model to be estimated in this study is the probability of an emerging market firm acquiring 100 percent of a developed market firm as a function of the emerging market firm return on equity, return on assets, current ratio, total debt to total assets, total assets, and cultural distance. Probability of (Ownership=1) is: 1 / (1+e Zi ) (1) Where zi is specified as: Z i = 1 ROE i + 2 CR i + 3 DA i + 4 ASSETS i + 5 CULTURE i + e i Where acquirer firm return on equity, current ratio, and long-term debt to total assets are each the 3-year average ratio prior to the acquisition announcement date. The total assets is the acquirer firm total assets one year prior to the acquisition announcement date. The cultural distance is the difference between the acquirer firm home country and the acquired firm home country MODEL (1) The first model estimated in this study is the probability of an emerging market firm acquiring total ownership of a developed market firm as a function of the emerging market firm return on equity, current ratio, long-term debt to total assets, total assets, and cultural distance. TOTDUM is a dummy variable that takes a value of 1 if the acquirer purchases 100 percent of the target, and zero otherwise. TODUM replaces OWNERSHIP. Model 1 is tested again using acquired firm data. 19

25 MODEL (2) The second model estimated in this study is the probability of an emerging market firm acquiring a majority of a developed market firm as a function of the emerging market firm return on equity, current ratio, long-term debt to total assets, total assets, and cultural distance. The model is estimated using MAJDUM as the dependent variable where MAJDUM is a dummy variable that takes the value of 1 if the acquirer purchases a majority (>50%) stake of the target, and zero otherwise. MAJDUM replaces OWNERHSIP. Model 2 is tested again using acquired firm data. To control for the effect of unique industry characteristics, Cudd and Duggal s Industry Adjustment Formula is used, allowing multiple industries to be included within the same sample set. Variable Adjustment Di = (Rij - Ni) / Sigmaj (2) Where: Rij = the financial ratio value of firm i in industry j, Nj = the industry average financial ratio value of industry j, Sigmaj = the standard deviation of Rij values within industry j, and Di = the adjusted financial ratio deviation from the industry norm for firm i. The procedure captures the dispersion of ratio values unique to each industry represented in the sample. As a consequence, the measure (Di) reflects the degree to which the ratio's deviation from the industry norm is atypical for that industry. 20

26 5. RESULTS This study finds support for the liquidity preference hypothesis and the cultural distance hypothesis. The results of the logit regression of acquirers show that the CR variable is positive and statistically significant at the 5 percent level for the majority ownership model. This suggests that as acquirer firm liquidity increases, the likelihood of an emerging market firm acquiring a majority ownership of a developed market firm increases. The results show that the CULTURE variable is negative and statistically significant at the 1 percent level for both the total and majority ownership models. This suggests that as the cultural distance between the acquirer and target country decreases, the likelihood of an emerging market firm acquiring a total or majority ownership of a developed market firm increases. The results of the logit regression of acquired firms show that the DA variable is positive and statistically significant at the 5 percent level for both the total and majority ownership models. This suggests that as target firm long-term leverage increases, the likelihood of an emerging market firm acquiring a total or majority ownership of a developed market firm increases. The results show that the ROE variable is positive and significant at the 5 percent level for the total ownership model. This suggests that as target firm efficiency increases, the likelihood of an emerging market firm acquiring total ownership of a developed market firm increases. Table 3 displays the results of the logit regression of acquirers designed to estimate the percent purchased by the acquiring firm using data sample one. Table 3 displays both the total ownership model and the majority ownership model, which each include all of the independent variables. Table 4 displays only the total ownership model with each 21

27 independent variable estimated separately. Table 5 displays only the majority ownership model with each independent variable estimated separately. Table 3. Acquirer Firm Results Estimating Majority and Total Ownership Models The following logit regressions are estimated Probability of (Ownership=1) is: 1 / (1+e Zi ) Where zi is specified as: Zi = 1ROEi + 2CRi + 3DAi + 4ASSETSi + 5CULTUREi + e i Where the dependent variable TOTDUM is created as a dummy variable that takes the value of 1 if the acquirer purchases 100 percent of the target, and zero otherwise. Where the dependent variable MAJDUM is created as a dummy variable that takes the value of 1 if the acquirer purchases a majority (>50%) stake of the target, and zero otherwise. CULTURE is the difference between the acquirer and target home country s cultural distances, ROE is the average 3-year return on equity one year prior to the acquisition date, CR is the 3- year average current assets divided by the current liabilities one year prior to the acquisition announcement date, DA is the 3-year average long-term debt to total assets one year prior to the acquisition announcement date, and ASSETS is the total assets one year prior to the acquisition announcement date. * Significance level of 10 percent. ** Significance level of 5 percent. *** Significance level of 1 percent 312 observations Model 1. Total Ownership 2. Majority Ownership INTERCEPT (.4438) (.5682) CULTURE *** *** (.0162) (.0193) ROE ** (.2920) (.2911) CR ** (.1758) (.2278) DA (.1758) (.2278) ASSETS (.1422) (.1520) Model Fit Statistics Model 1. Total Ownership Criterio Intercept and Covariates -2 Log L Model 2. Majority Ownership Criterion Intercept and Covariates -2 Log L

28 Tables 3, 4, and 5 present the results of the logit regression of acquirers. The results indicate that for both the total ownership model and the majority ownership model, the CULTURE variable is negative and statistically significant at the 1 percent level. This indicates that as the cultural distance increases, the likelihood of a total or majority ownership decreases. This suggests as the cultural distance decreases between the acquirer firm s home country and the acquired firm s home country, the likelihood of a greater percentage of ownership acquired by the emerging market firm increases. These results support the cultural distance hypothesis and are consistent with Kogut and Singh s (1988) findings regarding the effect of cultural distance on a firm s method of foreign direct investment. Table 4 presents the results of the logit regression of acquirers by estimating the total ownership model. Table 4. Acquirer Firm Results Estimating Total Ownership Model The following logit regression is estimated Probability of (TOTDUM=1) is: 1 / (1+e Zi ) Where zi is specified as: Zi = 1ROEi + 2CRi + 3DAi + 4ASSETSi + 5CULTUREi + e i Where the dependent variable TOTDUM is created as a dummy variable that takes the value of 1 if the acquirer purchases 100 percent of the target, and zero otherwise. CULTURE is the difference between the acquirer and target home country s cultural distances, ROE is the average 3-year return on equity one year prior to the acquisition date, CR is the 3- year average current assets divided by the current liabilities one year prior to the acquisition announcement date, DA is the 3-year average long-term debt to total assets one year prior to the acquisition announcement date, and ASSETS is the total assets one year prior to the acquisition announcement date. * Significance level of 10 percent. ** Significance level of 5 percent. *** Significance level of 1 percent 23

29 Table 4 cont. 312 observations model ( 1 ) ( 2 ) ( 3 ) ( 4 ) ( 5 ) INTERCEPT (.4194) (.1416) (.1281) (.1272) (.1283) CULTURE *** (.0154) ROE ** (.2899) CR.0785 (.1649) DA (.1672) ASSETS.1174 (.1310) The results of Table 4 indicate that for the total ownership model, the ROE variable is negative and statistically significant at the 5 percent level. This indicates that as the ROE increases, the likelihood of a total ownership decreases. This result suggests higher acquirer firm efficiency decreases the likelihood of an emerging market firm acquiring 100 percent of a developed market firm. These findings do not support the management efficiency hypothesis. Table 5 presents the results of the logit regression of acquirers by estimating the majority ownership model. 24

30 Table 5. Acquirer Firm Results Estimating Majority Ownership Model The following logit regression is estimated Probability of (MAJDUM=1) is: 1 / (1+e Zi ) Where zi is specified as: Zi = 1ROEi + 2CRi + 3DAi + 4ASSETSi + 5CULTUREi + e i Where the dependent variable MAJDUM is created as a dummy variable that takes the value of 1 if the acquirer purchases a majority (>50%) stake of the target, and zero otherwise. CULTURE is the difference between the acquirer and target home country s cultural distances, ROE is the average 3-year return on equity one year prior to the acquisition date, CR is the 3- year average current assets divided by the current liabilities one year prior to the acquisition announcement date, DA is the 3-year average long-term debt to total assets one year prior to the acquisition announcement date, and ASSETS is the total assets one year prior to the acquisition announcement date. * Significance level of 10 percent. ** Significance level of 5 percent. *** Significance level of 1 percent 312 observations model ( 1 ) ( 2 ) ( 3 ) ( 4 ) ( 5 ) INTERCEPT (.5289) (.1681) (.1833) (.1583) (.1629) CULTURE *** (.0186) ROE (.2962) CR.7157** (.3176) DA (.2083) ASSETS (.1374) The results of Table 5 indicate that for the majority ownership model, the CR variable is positive and significant at the 5 percent level. This indicates that as the current ratio increases, the likelihood of a majority ownership increases. This suggests higher 25

31 acquirer firm liquidity increases the likelihood of an emerging market firm acquiring a majority ownership of a developed market firm. These results support the firm liquidity preference hypothesis and are consistent with Vasconcellos (1993) and Gonzalez (1997) findings regarding acquired firm liquidity. Tables 6, 7, and 8 display the results of the logit regression of targets designed to estimate the percent purchased by the acquiring firm using data sample two. Table 6 displays both the total ownership model and the majority ownership model, which each include all of the independent variables. Table 7 displays only the total ownership model with each independent variable estimated separately. Table 8 displays only the majority ownership model with each independent variable estimated separately. Table 6. Acquired Firm Results Estimating Majority and Total Ownership Models The following logit regressions are estimated Probability of (Ownership=1) is: 1 / (1+e Zi ) Where zi is specified as: Zi = 1ROEi + 2CRi + 3DAi + 4ASSETSi + 5CULTUREi + e i Where the dependent variable TOTDUM is created as a dummy variable that takes the value of 1 if the acquirer purchases 100 percent of the target, and zero otherwise. Where the dependent variable MAJDUM is created as a dummy variable that takes the value of 1 if the acquirer purchases a majority (>50%) stake of the target, and zero otherwise. CULTURE is the difference between the acquirer and target home country s cultural distances, ROE is the average 3-year return on equity one year prior to the acquisition date, CR is the 3- year average current assets divided by the current liabilities one year prior to the acquisition announcement date, DA is the 3-year average long-term debt to total assets one year prior to the acquisition announcement date, and ASSETS is the total assets one year prior to the acquisition announcement date. * Significance level of 10 percent. ** Significance level of 5 percent. *** Significance level of 1 percent 26

32 99 observations Table 6 cont. Test 1. Total Ownership 2. Majority Ownership INTERCEPT (.6866) (.6720) CULTURE (.0230) (.0220) ROE (.1799) (.1487) CR (.1729) (.1517) DA.5406**.4579** (.2145) (.2159) ASSETS (.4984) (.4862) Model Fit Statistics Model 1. Total Ownership Criterion Intercept and Covariates -2 Log L Model 2. Majority Ownership Criterion Intercept and Covariates -2 Log L Table 6 presents the results of the logit regression of targets. The results indicate that for both the total ownership model and the majority ownership model, the DA variable is positive and statistically significant at the 5 percent level. This indicates that as the longterm debt to total assets increases, the likelihood of a total or majority ownership increases. This suggests that as the target firm leverage increases, the likelihood of a greater percentage of ownership acquired by the emerging market firm increases. These results do not support the capital structure hypothesis. Table 7 presents the results of the logit regression of targets by estimating the total ownership model. Table 7. Acquired Firm Results Estimating Total Ownership Model The following logit regression is estimated Probability of (TOTDUM=1) is: 1 / (1+e Zi ) Where zi is specified as: 27

33 Table 7 cont. Zi = 1ROEi + 2CRi + 3DAi + 4ASSETSi + 5CULTUREi + e i Where the dependent variable TOTDUM is created as a dummy variable that takes the value of 1 if the acquirer purchases 100 percent of the target, and zero otherwise. CULTURE is the difference between the acquirer and target home country s cultural distances, ROE is the average 3-year return on equity one year prior to the acquisition date, CR is the 3- year average current assets divided by the current liabilities one year prior to the acquisition announcement date, DA is the 3-year average long-term debt to total assets one year prior to the acquisition announcement date, and ASSETS is the total assets one year prior to the acquisition announcement date. * Significance level of 10 percent. ** Significance level of 5 percent. *** Significance level of 1 percent 99 observations model ( 1 ) ( 2 ) ( 3 ) ( 4 ) ( 5 ) INTERCEPT (.6219) (.2152) (.2094) (.2169) (.2626) CULTURE (.0208) ROE.3145** (.1715) CR (.1678) DA.5159*** (.1983) ASSETS.2055 (.4478) The results of Table 7 indicate that for the total ownership model, the ROE variable is positive and significant at the 5 percent level. This indicates that as the return on equity increases, the likelihood of a total ownership increases. This suggests higher target firm efficiency increases the likelihood of an emerging market firm acquiring a total ownership of a developed market firm. These results do not support the management efficiency 28

34 hypothesis. The results of Table 7 also indicate that for the total ownership model, the DA variable is positive and significant at the 1 percent level. The DA variable increases in significance for the total ownership model when only the DA variable is estimated. Table 8 presents the results of the logit regression of targets by estimating the majority ownership model. Table 8. Acquired Firm Results Estimating Majority Ownership Model The following logit regression is estimated Probability of (MAJDUM=1) is: 1 / (1+e Zi ) Where zi is specified as: Zi = 1ROEi + 2CRi + 3DAi + 4ASSETSi + 5CULTUREi + e i Where the dependent variable MAJDUM is created as a dummy variable that takes the value of 1 if the acquirer purchases a majority (>50%) stake of the target, and zero otherwise. CULTURE is the difference between the acquirer and target home country s cultural distances, ROE is the average 3-year return on equity one year prior to the acquisition date, CR is the 3- year average current assets divided by the current liabilities one year prior to the acquisition announcement date, DA is the 3-year average long-term debt to total assets one year prior to the acquisition announcement date, and ASSETS is the total assets one year prior to the acquisition announcement date. * Significance level of 10 percent. ** Significance level of 5 percent. *** Significance level of 1 percent 99 observations Model ( 1 ) ( 2 ) ( 3 ) ( 4 ) ( 5 ) INTERCEPT (.6136) (.2111) (.2043) (.2106) (.2584) CULTURE (.0204) ROE.1783 (.1443) CR (.1468) DA.4222** (.2015) ASSETS.0428 (.4425) 29

35 The results of Table 8 indicate that for the majority ownership model, the DA variable is positive and significant at the 5 percent level. There are no other significant variables indicated in Table 8. The significance of the DA variable for the majority ownership model is the same as shown in Table CONCLUSION The objective of this study is to determine the characteristics that predict the percent purchased of a developed market firm by an emerging market firm. The findings of this study conclude that both acquirer firm liquidity and the cultural distance between the acquirer and acquired firm s home countries predict the likelihood of the percent purchased. As the acquirer firm liquidity increases, the likelihood of an emerging market firm acquiring a majority ownership of a developed market firm increases. These results support the firm liquidity preference hypothesis and are consistent with findings from Vasconcellos (1993) and Gonzalez (1997) regarding acquired firm liquidity. As the cultural distance decreases between the acquirer firm s home country and the acquired firm s home country, the likelihood of a greater percentage of ownership acquired by the emerging market firm increases. These results support the cultural distance hypothesis and are consistent with Kogut and Singh s (1988) findings regarding the affect of cultural distance on a firm s method of foreign direct investment. Additional results conclude that as the long-term leverage of the target firm increases, the likelihood of an emerging market firm acquiring a majority or total ownership of a developed market firm increases. This suggests that emerging market firms prefer to acquirer greater ownership of distressed developed market firms. As the target 30