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The effect of market classification in cross-border mergers and acquisitions on shareholders’ value: analyses of the African market.
Bachelor Thesis
BSc Economics and Business Economics Specialization in Finance
By
Wessel Koot – 11906758 Supervisor: Dr. Solomon George Zori Abstract
This thesis studies the impact of market classification on the wealth creation for shareholders through cross-border merger and acquisition with targets from Africa and bidders from emerging and developed markets outside of Africa. The paper includes a literature review discussing different motives behind M&A and cross-border M&A. In addition the differences between motives of the bidders with different market classification are shown. To conclude motivations to target Africa are presented. Moreover, an empirical is done by means of an event study to defend or deny the hypothesis. The sample used contains 302 CBMA deals targeting African firms, 52 of deals were done by a bidder from an emerging market. The abnormal returns around the announcement date were calculated using the market model. The results are contradicting previous literature and leaning towards value destroying of shareholders value through CBMA instead of value creating close to the announcement date especially in the short run. Contrary, when the event window is extended the returns become positive, however this was not significant.
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Statement of originality
This document is written by student Wessel Koot who declares to take full responsibility for the contents of this document.
I declare that the text and work presented in this document are original and that no sources other than those mentioned in the text and its references have been used in creating it. The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.
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Table of Contents
1. Intro ...4
2. Literature review ...6
2.1 The fruitfulness of M&A ...6
2.2 Determinants of mergers and acquisitions ...7
2.2 Developed and emerging markets ...9
2.3 Cross-border motives ...10
2.4 CBMA ...11
2.4.1 Bidder developed market ...11
2.4.2 Bidder emerging market...12
2.5 Africa ...13
2.6. Hypothesis ...13
3. Data and methodology ...14
3.1 Data ...14 3.2 Methodology ...17 3.2.1 Event study ...17 3.2.2 OLS regression ...20 4. Results ...21 4.1 CAR Analyses...21
4.2 The OLS Regression ...24
5. Conclusion ...28
6. References ...30
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1. Intro
Investment through mergers and acquisitions is commonly known in the investment world, with a yearly average of 1 trillion USD worth of investments. Currently the total worth of investment out grew the average with 2 trillion USD for the last four years(Massoudi et al, 2017). With developed countries witnessing a pragmatic stock reform, technical and financial innovations a lot of capital is ready to be invested. Furthermore, with the help of the the integration of financial products and markets together with globalization it seems as if the investors have chosen foreign targets to invest in, for instance Africa. With Africa being a big target the M&A activity in Africa has risen rapidly over the last 20 years, the net foreign direct investment even almost tripled from 2004 to 2007 in the Sub-Sahara from 13 billion USD to 33 billion USD. The economic markets in Africa are relatively small compared to the sizes of the population, Africa is the home of over 50% of the world population (Alagidede, 2010).
Africa is getting more attractive due to the financial and political stability created in most countries. Mainly the political stability resulted in an increase of confidence of the investors making it more attractive to invest in Africa and increasing the value of deals in to a record of 44 billion USD(Amewu & Alagidede, 2018).
However, though the numbers seem promising, little research has been done on the value creations that comes along with these M&A deals. Previous M&A studies focused primarily on U.S domestic acquisitions with 28 out of the 30 event studies published in the strategic management journal focusing their analyses to firms in a single country withing the United States(Park, 2004). Eventually the scope of the studies extended and cross border acquisitions became of more importance. Next the focus on emerging markets was brought to light. A prior research that focused on emerging markets chose China as their emerging market and found a positive effect on value creation for the acquiring firm and the target firm(Chari, Outimet, & Tesar, 2004). However, prior research has not found any consensus about the shareholders benefit of the acquiring firm with some claiming that there are no positive ARs for the acquiring firm(Kyriazis, 2010). To tackle this problem Amewu and Alagided conducted a research that seeks to investigate the market value creation of acquiring firms shareholders up on M&A announcement in Africa’s emerging market. They includeded specific deal factors such as deal value, method of payment, merger form, cross industry and many more. Furthermore, some research suggests that geographical differences and market differences may affect the success of an M&A deal(Weber, Tarba, & Bachar, 2011). They added the comparison
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between South-Africa and the rest of Africa because the economic market of South-Africa is relatively more developed compared to the rest of Africa. Amewu & Alagidede came to the conclusion that the African market reacts positively to M&A announcements and therefor value is created for the acquiring shareholders(Amewu & Alagidede, 2018).
However their paper did not focus on the differences in geographical characteristics of the acquiring firm and focused on Africa alone. In 2014 the United Nations reported that 73% of the international investments is done by developed countries, this illustrates foreign direct investment is dominated by developed countries investing abroad(UNCTAD, 2004). Firms see potential in the emerging markets due to the high growth rates compared to the decreasing growth rates in their home country. However that does not alter the fact that investing in emerging markets could be beneficial for acquirers in emerging markets. One of the well-known motives for M&A deals is synergy, this motive is describe as 1+1=3(Marks & Mirvis, 2010). Besides, emerging markets are becoming a bigger player in the global investment market with more than 25% of the outward foreign direct investment(OFDI) is done by emerging markets(Bouchet, n.d.). Therefor this paper is written as a follow up research on the research from Amewu and Alagidede but focusses on two different acquiring markets developed and emerging. Previous literature mainly focused on cross-border mergers and acquisitions(CBMA) with the target company from an emerging market and de acquiring firm from a developed market. However, the aim of this paper is to investigate to what extent the market classification of the acquiring firms affects the shareholders’ value, when acquiring a firm in Africa. This paper has a similar lay out as Amewu and Alagidede but investigates the effect of market classification on market responses to M&A deals. The acquiring firms are from outside of Africa and labeled as developed or emerging and target firms and the targeted firms are in Africa, excluding South Africa. Furthermore the great difference in CBMA by developed and emerging countries might be explained based on the results.
To conduct this research an event study is used to measure the abnormal returns around the announcement date in the period 2000-2019. By combining the ARs the cumulative abnormal returns can be calculated and one is able to determine if value is created or not. Secondly a cross-sectional multivariate test will be done to measure deal characteristic effects with 249 developed countries and 52 emerging countries acquiring firms in Africa. Furthermore by adding control variables more insight is given in the cause of the results. Chapter one starts with a literature review containing relevant existing information from previous research about CBMA and ends with a hypotheses based on the literature. The next chapter focusses on the
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methodology and the data used in this research, following up with the results in chapter 4. Lastly chapter 5 represents the conclusion and the discussion.
2. Literature review
2.1 The fruitfulness of M&A
Acquiring firms and target firms have several reasons to engage in M&A deals all over the world. A M&A deal can arise in different ways but the basic principle is that the acquiring firms take over the control of the target firms. The acquiring firm can be seen as the buyer and the target firm as the seller. When two firms decide to join forces and to continue as one new entity instead of two separated entities it is called a merger. When a company acquires shares of another company it is called an acquisition, when a company acquires more than 50% of the shares it gains control over that company(Bauer & Matzler, 2014) This research focusses on acquisitions in which the acquiring firm acquires over 50% of the shares and takes control. Acquisitions are seen as an opportunity and when it goes according to plan it can be successful and beneficial for both firms. Previous literature presents three main reasons for M&A deals, the synergy motive, the managerial hubris and the agency problems (Devos et al, 2009). With the latter two motives destroying share holders’ value compared to the shareholders’ value-enhancing synergy motive.
First the synergy motive, the synergy motive is used by managers to justify a M&A deal. In a previous study on motives of CFOs in the USA states that the most essential motive is the synergy motive (Mukherjee et al. 2004). These synergies can be divided into two categories, financial synergies and operating synergies(Devos et al, 2009). Financial synergies are achieved by creating better and cheaper access to capital, a lower probability of bankruptcy and by a better cash flow stability(Martynova and Renneboog, 2006). Some more advantages are tax advantages and diversification. Tax advantages occur when a highly profitable firms takes over a less profitable firm resulting in less tax payments due to the compensation of profits and losses. Diversification increases through acquiring a firm by reducing the industry-specific risk of the company. Although, literature suggests that diversification can be achieved more efficient by diversifying through investing in different companies by buying shares (Goel, Nanda & Narayanan, 2004). Furthermore, diversification leads to a reduction in the risk of bankruptcy and therefor allows for cheaper access to capital. The operating synergies happen through
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economies of scale, scope and the increase of expertise and knowledge(Demarzo & Berk, 2014). The economies of scale help to reduce the costs due to spreading the fixed costs over two companies instead of one. Economies of scope occur due to firms sharing their infrastructure, products and marketing. This distribution reduces the costs as well. Lastly the valuable knowledge that firms have can be shared increasing the human capital and R&D.
Contrary, the agency problems reduce the shareholders’ value despite being an explanation for takeovers. The agency problem occurs when the managers and the shareholders do not align with their preferences. When a firm has a large amount of free cash flow a disagreement between the shareholders and the managers can arise due to different incentives. The managers may want to choose for empire building, meaning that a manager wants to increase the size of the firm. In contrary the shareholders would like to see some of the cash returning to them. Empire building is attractive for managers because they admire a prominent company due to the salary and their ego. Therefore, they are more likely to pay a premium because a failed bid hurts their reputation(Martynova and Renneboog, 2006). A previous study showed that in 75% of the mergers in which the acquiring firms shareholders lost value the CEOs increased their value(Harford and Li, 2007).
Lastly, the managerial hubris, addressing the overconfidence of managers in their overall abilities. Some research even suggest that this hubris is the essential reason for the destroyment of value in M&A(Faccio et al., 2006). The overconfident CEOs engage mergers and acquisitions opportunities with low a low chance of value creating, while paying a premium. Furthermore, they need repeated losses to finally change their believes on the capacity of their abilities(Demarzo & Berk, 2014). The research Goergen and Renneboog (2004) suggests that one third of the total takeovers in Europe experienced managerial hubris.
2.2 Determinants of mergers and acquisitions
Previous literature mentioned a lot of variables that influence the success of CBMA. Not all are relevant for the topic of this paper and do not have a significant impact on the value creation during CBMA, the most relevant that are used in this paper will be discussed based on previous literature.
The method of payment the acquiring firm uses to take over the target firm is an important indicator for the value creation for the shareholder. A firm can choose between two payment methods, through cash or through the issue of shares. A combination of both is also possible. Acquiring firms is accompanied with high value transactions, most firms do not have
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the cash available to pay for acquisition. This leads to two choices borrowing cash or issuing stock, in other words debt financing or equity financing(Faccio & Masulis, 2005). Previous literature shows that when a firm is overvalued it will choose equity financing over debt financing and when a firm is undervalued debt financing over equity financing. Given an indication towards the investors that the stock price is undervalued or overvalued. When a firm is overvalued it is expected that the firms share prices will drop making it less attractive to invest in the company(Faccio et al., 2006). As a consequence creating negative or low abnormal returns after an M&A announcement compared to using cash as a payment method(Chari et al., 2004). Furthermore making a bid through equity may result in creating another block in the ownership structure of the target company when the target company is concentrated. Additionally, the leverage of the current corporate governance structure of the acquiring firm influences the payment method. Making the bidder reluctant to use equity financing because this threatens the dominant shareholders(Faccio & Masulis, 2005).
Acquiring a firm may result in a positive return for the shareholder but previous research did not find consent. However, when not looking at all acquisitions but focusing on the private acquisitions alone results in different positive outcomes(Faccio, McConnell, and Stolin, 2006). One of the reasons could be that normally diversified shareholders can hold both stocks in the bidder and the target firm and are indifferent between positive returns of both firms. However, private firms are not listed and therefore it is impossible to hold stocks of both firms. Therefore, shareholders of the acquiring firm have an higher incentive to increase the firms share price. Secondly, private firms are not as liquid compared to public firms and therefore the bidder could get a private firm at a discount instead of paying a premium due to agency problems or managerial hubris. Furthermore, it is possible to eliminate Hubris due to private targets not being monitored by the public and therefore the acquiring firm would not damage his name when acquisition negotiations are terminated(Conn et al. 2005). Making it less likely for a CEO to pay a premium to not damage his ego. Furthermore, the ownership structure in a public firm is more complex making it harder to agree on a takeover proposal(Aybar & Ficici, 2009). On the other hand, the information about a private firm is less available for a private firm compared to a public firm. Making it harder to do research about a private firm before acquiring it increasing the risk(Capron & Shen, 2007). Nevertheless, most research suggests that acquiring a private target results in the bidders shareholders gaining more value compared to when acquiring a public firm(Fuller et al. 2002)
Furthermore, the size of the acquiring firm influences the effect of M&A on the creation of value for the shareholders. Multiple studies have shown that the deal size has a negative
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effect on the abnormal returns of the bidders(Martynova, Renneboog, 2008). The study showed that bigger firms are more likely to deal with managerial hubris and end up overpaying for poor acquisitions. In addition, Moeller et al. (2004) showed that the acquiring firm lost 25.2 million dollars in market capitalization on average after an announcement. Furthermore, the managers of smaller companies tend to have more stake in the firm that they are managing compared to bigger firms. Making it less likely for a manager of a small firm to make an acquisition with low potential. In addition, bigger firms have a higher chance of having a surplus of cash and therefore will make more acquisitions with low potential(Moeller et al., 2004).
Thirdly, deal value is of impact for the shareholders’ value of the firm because of the integration process after an acquisition. Smaller deal values go along with smaller target firms, making the integration process less of a struggle(Moeller et al., 2004).
Another key factor is the industry relatedness of the companies involved in the deal. When the merging companies operate in the same industry, they are able to increase their market power through their market share and therefore can be value creating. On contrary, firms that engage diversified industry M&A creates a negative return. US as acquiring firms in unrelated CMBA experienced a negative return due to inefficient use of capital(Dos Santos et al, 2008).
Lastly, the return on assets of the acquiring firm is an important characteristic that has an effect on the creation of value for the shareholders. However, there is no consensus between the previous researchers. Sparta (2005) has found that the abnormal returns are negatively affected by the ROA. In contrast Martiani et al (2009) found a significant positive effect on abnormal returns by the ROA.
2.2 Developed and emerging markets
A perfect definition for an emerging market does not exist. However, a distinguish is made between developed markets and emerging markets based on multiple factors, mainly economic and risk factors. Developed countries have developed economic markets and have undergone the industrialization in the past. Contrary, the emerging markets are still undergoing industrialization. These countries are developing quickly in terms of their position in the global economy and global politics. As a result, they tend to have a higher growth rate, however this growth rate goes along with a higher risk. Nevertheless, an index has been made called the MSCI ACWI index. MSCI ACWI is an independent institution providing research tools and insights and is extensively used by the biggest investment managers for over 45 years(MSCI,
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2020). The index is made based on all factors characterizing market classification and therefor useful in categorizing countries as developed or emerging markets. Some of the factors that the index uses to asses if a country is a developed market are, size, liquidity, economic development and market accessibility(MSCI, 2020). For emerging markets, the index has less criteria compared to those of a developed country. For emerging markets, the sustainability of the developed market is not part of the requirements.
2.3 Cross-border motives
Cross-border deal are increasing over the last twenty years due to the increase in globalization and integration between the markets. The cross-border deals have the same motives as mentioned before about M&A deals in general. However, some extra motives play a role in determining if a cross-border could be more of value due to economic, strategic and political perspectives.
First, the synergy values due to economics of scope and scale are greater compared to a domestic acquisition(walker, 2000). Furthermore, differences in tax systems can be exploited when the target country has a lower corporate income tax compared to the bidder’s country. Similarly, changes in exchange rate can generate a profit for the acquiring firm. This occurs when the currency of the acquiring firm appreciates compared to the target’s currency. Trying to get access to a new market can be a struggle. However cross-border M&A is seen as a fast and direct way to invest in a new market(Shimizu et al., 2004). Getting access to a new market is desired because it increases the market share and therefor market power. Besides, by acquiring a firm the acquirer takes control over the intangible assets such as knowledge, valuable personnel and patents(Georgen & Renneboog., 2004). Another factor is corporate governance, countries differ from each other in terms of corporate governance. Corporate governance consists of a system with rules that a firm has to obey, if not it can risk a penalty when controlled. The rules are formed to secure the relationship between the shareholders and the firm by means of transparency and protection for the shareholders(Martynova & Renneboog., 2008). Most target firms have a less advanced corporate system and when they are acquired by a firm with an advanced corporate system, they adopt the advanced system. As a positive consequence creating wealth.
However, cross-border acquisitions do not have beneficial effects only, “liability of foreignness” brings a long some risk. Most importantly are the cultural differences between the two countries. The M&A integration process costs are highly influenced by the degree of
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cultural differences such as religion and language(Shimizu et al, 2004). Similarly, the geographical distance between the two countries increases the transaction cost. Besides when the product has to travel through multiple countries, they are subject to the rules of the countries that they cross resulting in more costs(Moeller and Schlingemann., 2005). Lastly, the asymmetric information that arises within cross-border M&A. As a result, the acquiring firm has trouble assessing the accurate value of the target firm and potentially pays a high premium. To conclude, the literature is divided about the creation of CARs based on cross-border M&A. Finding different outcomes due to different sample periods(Moeller et al., 2004).
2.4 CBMA
Prior literature suggests that the bidder in a cross-border CBMA has a higher return compared to a non-cross-border acquisition(Chari, Outimet, & Tesar, 2004). A few reasons can be assigned to the difference in the creation of shareholders’ value. However, those reasons differ between different markets, a firm from a developed market has different incentives to do CBMA compared to a firm in an emerging market.
2.4.1 Bidder developed market
The large differences between emerging markets and developed markets has advantages and disadvantages. Prior literature suggests that the advantages outweigh the disadvantages when a firm in a developed market acquires a firm in an emerging market, resulting in higher abnormal returns(von Eije & Wiegerinck, 2010). Several factors can potentially explain the positive return for the shareholders.
First of all, the bidder firms from developed markets tend to use CBMA as a way to get access to the emerging market, this is called the entry hypothesis(Zhu et al.,2011). Second, during a M&A the bidder firm takes corporate control of the target firm thereby restructuring the corporate governance. On average the bidder firm has a more advanced structure and when the target firm reorganizes it increases their profitability(Bauer & Matzler, 2014). In addition, Chari et al. (2010) found a significant abnormal return for the shareholders when a firm from a developed market targeted a firm in an emerging market. In consent US firms taking over firms in emerging markets generated a positive return on the shareholders(Burns and Liebenberg. 2012).
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Furthermore, the economic growth in emerging markets is on average higher compared to the growth in developed markets making it attractive for developed firms to exploit these growth rates(Amewu & Alagidede, 2018). Moreover, the firms from developed markets may have valuable intangible assets such as patents, knowledge and technology. After the acquisition the emerging target can exploit these intangible assets increasing the competitive advantages of the target firm. Lastly, the access to capital in emerging markets is limited making it harder for the domestic firms to participate in NPV projects. Due to the acquisition the firm can get access to cheaper capital with the help of the bidder firm(Francis et al. 2008).
2.4.2 Bidder emerging market
Previous studies mainly focused on CBMA in which the emerging market firm acquires a firm in a developed market. Indian firms use CBMA to gain access to developed markets, because of the lack of skilled labor, knowledge and technology in their domestic country. The bidder firms from India realized a significant higher abnormal return with CBMA compared to domestic M&A(Kohli & Mann. 2011).
However, there is limited literature investigating the effect of an emerging market firm participating in a CBMA with another emerging market firm. Even though emerging markets have several reasons to invest in an emerging market. First of all, the resource dependence theory. The resource dependence theory is based on firms depending on certain resources that are constraint by their domestic environment(Salnick, 2003). A firm in need for particular resources can use CBMA as a solution to get the crucial resources that they need. With the means of M&A a firm increases their power by becoming less dependent due to controlling their vital resources. With a higher market and resource availability increasing the concentration in CBMA deals(Yang, 2015). Furthermore Yang (2015) found that firms from emerging market target firms have a lot of natural resources. Besides, due to domestic competition and market control by high market share firms acquiring market share in the home country can be unsuccessful. Making it even more attractive to look for market share gains in foreign countries. Furthermore, firms do not only gain from the availability of resources such as raw materials but they also benefit from crucial supply chains and costumers and skilled labor. Even with RDT becoming an important theoretical factor in explaining the M&A activity, the previous literature on CMBA by emerging markets firms is scarce(Deng, 2013).
On the other hand, the geography of the firms matters in CBMAs. When firms are distanced far apart, they tend to pay a premium on small targets and therefor limiting the
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creation of value(Deng, 2013). While focusing on emerging markets outside of Africa, creating a big distance between de markets can be an important factor in this study.
2.5 Africa
As mentioned in the introduction Africa is booming in terms of M&A activity. One of the reasons that makes Africa so attractive for international firms is the high GDP and the high population growth. With a GDP growth as high as 5,7% for low income countries in Sub-Saharan Africa in 2019(IMF. 2019). The middle class of Africa is currently growing, increasing the consumer market for mass-market products. Accompanied with the growth of GDP and population firms seek to capture this market full of potential by entering through M&A(Bouchet, n.d.).
Moreover, the openness of the economy accompanied with political stability is a key determinant for the level of foreign direct investment influx into a country. With African economies opening up to the world and achieving political stability foreign direct investment is attracted (Amewu & Alagidede, 2018).
Furthermore, due to the markets in Africa being relatively less developed compared to the markets in developed countries firms entering the market can move as a first mover and increase revenues(Bouchet, n.d.). Due to the limited development in the African market competition is relatively scarce when entering the market as an international firm.
Lastly, potentially the biggest reason for foreign direct investment is the significant unutilized land and other natural resources such as diamonds, oil, gold and timber. With the export of Angola consisting for 90% of oil. Similarly, Botswana is relying on their countries richness of diamonds, with diamonds accounting for 91% of their export in 2014(KPMG, 2016)(Onyeiwu & Shrestha, 2004). In addition, with the means of M&A a firm increases their power by becoming less dependent due to controlling their vital resources. With a higher market and resource availability increasing the concentration in CBMA deals(Yang, 2015).
2.6. Hypothesis
Most previous literature only covered the effect of CBMA with a developed acquirer and an emerging target. In contrast literature about CMBA between two firms in an emerging market is scarce. However, when looking at the literature available and discussed the effect of CBMA between a developed market acquiring firm and an emerging market target firm was on average
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a positive CARs for the share-holders. Regarding the announcement effect due to CBMA between two firms both for an emerging market no previous research has found significant evidence. However, acquiring firms in Africa has a lot of potential and therefor it is likely that positive CARs will be realized as well. To complete the research a last form of CBMA needs to be added. Namely, African firms acquiring firms from developed markets outside of Africa. African firms may want to acquire firms in developed market to get access to the market or to skilled labor, knowledge and technology. However, stock traders are not extensively monitoring firms in Africa creating information asymmetry. Traders will be reluctant to buy shares of a company that they do not have much information of. Therefore, African firms acquiring developed market firms outside of Africa will be less efficient.
Hypothesis 1: CBMA with a developed market acquirer outside of Africa and an emerging target in Africa have a positive effect on the shareholders’ value around the announcement date.
Hypothesis 2: CBMA with an emerging market acquirer outside of Africa and an emerging market target in Africa have a positive effect on the shareholders’ value around the announcement date.
Hypothesis 3: CMBA with an emerging market acquirer in Africa and a developed market target outside of Africa have a negative effect on the shareholders’ value around the announcement date.
3. Data and methodology
3.1 Data
Multiple databases have been used to collect all relevant data. To find the acquisition announcement dates and firms we used a dataset from Zephyr. The acquisitions had specific requirements with the first Boolean stating that the targets needed to be in Africa, excluding South Africa. Secondly, all acquisitions occurred in the period from 01-01-2000 till 31-12-2019. The time period was chosen because for the last two decades the acquisitions in Africa rose and, in some areas, direct investment even tripled. The Mergers had to be subject to multiple criteria. First of all, the Target firm had to be located in Africa, excluding South Africa.
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The reason that South Africa is excluded is mainly because it is an extreme outlier based on market regulations and efficiency, South Africa can be seen as a developed market(Park, 2004). The acquirers are based all over the world so that we can observe the differences in CAR between different market areas. The next requirement stated that the acquiror needed to be a public traded company, if it was a private company tracking the differences in stock price around the announcement date would not be possible. Lastly the acquired stake should be minimal 50% or the initial stake should be maximum 50% and the final stake a minimum of 50.1%. The last requirement makes sure that the acquiring firm acquires the majority of the shares.
Secondly a database was needed that contained the stock prices of the firms during the announcement dates. DataStream was used containing stock prices of companies worldwide and not only one world region.
Lastly the database Orbis was used to find financial and firm characteristics of the acquiring firms found in zephyr. By adding the characteristics consisted of type of deal value, method of payment, country code, industry code, market capitalization, ROA and world region. Furthermore, the acquiring countries were divided in two categories developed market and emerging market to be able to test the influence of market classification effect on share price for CBMA. The MSCI ACWI index was used to make a classification between the market forms, developed and emerging. MSCI ACWI is an independent institution providing research tools and insights and is extensively used by the biggest investment managers for over 45 years (MSCI). The index is made based on all factors characterizing market classification, table 1 contains the countries classified as developed and table 2 the countries classified as emerging. In addition a second dataset was gathered from zephyr to be able to answer the third hypothesis. Dataset consists of CMBA deals with African bidder firms acquiring developed market firms outside of Africa. The other criteria are the same as the first dataset. Unfortunately due to the lack of monitoring the African market a lot of deal characteristics and firms characteristics are missing. Even without dropping transactions with missing control variables the total sample size consisted only of 52 transactions.
TABLE 1DEVELOPED COUNTRIES
Developed countries
Americas Europe and Middle East Pacific
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TABLE 2 EMERGING COUNTRIES
Emerging Countries
Americas Europe and Middle East Asia
Argentina Czech Republic China
Brazil Greece India
Chile Hungary Indonesia
Colombia Poland Korea
Mexico Qatar Malaysia
Peru Russia Pakistan
Saudi Arabia Philippines
United Arab Emirates Taiwan Thailand
Table 3 contains the descriptive statistics of the first sample used for the analyses. When looking at the table a few values a few things stand out. First of all only 17.3% of the transactions in our sample are made by an acquiring firm from an emerging market. Moreover,
United States Belgium Hong Kong
Denmark Japan
Finland New Zealand
France Singapore Germany Ireland Israel Italy Netherlands Norway Portugal Spain Sweden Switzerland United Kingdom
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the percentages of deals that are paid for with cash only or shares only are low as well. Therefor most of the deals are done by a mix of shares and cash.
The variables value and size were rewritten as natural logarithms to make them directly interpretable. Unfortunately, due to the lack of information on firms in Africa over 100 of the transactions in the sample did not include deal size. The impact of reducing the sample size so drastically would be bigger compared to dropping the control variable. Therefore, the control variable deal size is dropped from the dataset. Secondly the outliers are reduced and the curtails of the variables. The other variables are dummy variables or already in percentages. Secondly to reduce the outliers the variables are all winsorized on the 5 and 95 percentile and observations with a negative value for size were dropped.
TABLE 3DESCRIPTIVE STATISTICS VARIABLES DATASET 1
VARIABLES N mean Standard Deviation min max
Value(Ln) 197 11.21 3.098 6.226 16.72 Shares 301 0.140 0.347 0 1 Cash 301 0.106 0.309 0 1 Emerging 301 0.173 0.379 0 1 Ind_related 301 0.385 0.487 0 1 Listed 301 0.0698 0.255 0 1 CAR1 301 -0.00633 0.0368 -0.0896 0.0657 CAR5 301 -0.0127 0.0866 -0.196 0.151 CAR15 301 0.00539 0.156 -0.284 0.362 CAR25 301 0.0132 0.223 -0.405 0.543 ROA% 270 -2.057 11.70 -26.39 14.75 Size(Ln) 290 5.811 3.522 0.457 10.71
Notes: Ind_related refers to industry related
Due to the lack of information the control variables of the second sample are dropped to keep a sufficient dataset to test.
3.2 Methodology
3.2.1 Event study
As mentioned before this empirical research is done using the event study methodology. Performing one makes one able to investigate the effect of market classification of the acquirer on CBMA in Africa, with the distinction being made between emerging and developed countries. With the help of the event study tool from Eikon the abnormal returns were calculated
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which were used to calculate the CARs. Eventually with the help of the CARs analysis by Fama, Fisher, Jensen and Roll, the founders of the event study methodology, the effect of the market classification can be segregated with multivariate analysis.
To measure the impact of an event on stock prices an event study is the most used research method. An event study is used to measure the impact that an event has on the value of the firm. It assumes the efficient market hypothesis and examines the stock market during a public event to investigate the response of the investor(Fama, 1980). When conducting an event study on M&A deals the event is the announcement of an acquisition and therefore we have a different event date for every firm. During an M&A announcement new information is brought to the market and will be processed by the market resulting in immediate price changes due to the efficient market hypothesis(Fama, 1980). The changes in stock prices are used to calculated the abnormal returns(ARs) with the help of their estimated returns based on the market index. Next the ARs are added up to calculate the Cumulative Abnormal Returns(CARs). The CARs are used to do the student t-test while using the CAR analysis, the test measures the overall effect of the CBMA on stock prices. It does not make any distinguishes between the market classification or other control variables. To investigate the impact of market classification the de multivariate analyses is needed, the multivariate analyses conducts an ordinary least square regression(OLS) with the CARs as the dependent variable. The independent variables are the remaining firm characteristics.
The method used for calculating the ARs is from the database Eikon and uses DataStream for the information about stock prices. This is a specially developed event study tool to generate CARs and ARs for specified windows. The tool first calculates the expected returns based on the average return of the stock over a certain period before the event. Within an event study a stock return market model is conducted, this is called the market model. The market model is used to calculate the expected stock return of a security based on multiple factors such as past performance and the sensitivity to market movements reflected by the stock market index(Faccio et al., 2006).Within an event study multiple windows can be used to calculate investigate different outcomes. The estimation period chosen is a period of 200 days before the event ending 50 days before the announcement. The expected returns are calculated using the market model stated below:
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𝑅𝑖𝑡 = expected return of security i, on event date t 𝑅𝑚𝑘𝑡 = daily return of market, on event date t 𝛼𝑖 = intercept security i
𝛽𝑖 = parameter security 𝜀𝑖𝑡 = residual
The abnormal returns will be calculated with the event study tool from Eikon as well. The ARs are calculated with the help of the market return and the estimated return for the chosen windows. The windows used in this paper are similar to the paper from Amewu & Alagidede. The windows: 3-day(-1,1); 11-day(-5,5); 21-day(-10,10) and 51-day(-25,25). The windows are quite large even if we are looking for short-term wealth effect due different capital markets absorbing information in different ways. Therefor information and money might travel slower resulting in a delay in the announcement effect. Secondly the window is extended quite far before the event because of information leakage. It is expected that in Africa insider’s information is shared more frequently, allowing stock price changes to occur before the event day. The formula to calculate the AR is:
𝐴𝑅 𝑖𝑡 = 𝑅𝑖𝑡 - 𝐸(𝑅)𝑖t
𝐴𝑅 𝑖𝑡 = Absolute return of security i, on event date t 𝑅𝑖𝑡 = Actual ex-post return of security i, on event date t 𝐸(𝑅)𝑖𝑡= Expected return of security i, on event date t
The calculated abnormal returns are used to calculated the cumulative abnormal returns(CARs) by adding the ARs of the event windows.
𝐶𝐴𝑅 (𝑡1,𝑡2) = ∑𝑇2𝑇1𝐴𝑅𝑖𝑡
The CARs can be negative or positive, when the CAR is positive it has had a positive effect on the share price and creates value for the shareholders. The efficient market theory states that the stocks are priced accurately and no one can beat the system. Within the efficient market theory the average CAR should therefore be zero. However, the student t-test will test the efficient market hypothesis by testing if the CARs are different from zero.
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t𝐶𝐴𝑅 (𝑡1,𝑡2) =CAR (t1,t2)
σCAR/√N
However to answer the research question of this paper a follow up with the multivariate analysis based on the OLS regression is needed.
3.2.2 OLS regression
Variables: Market classification, Method of payment, Deal value, Firm size, Target listed, Return on equity, Industry
With the help of the multivariable analysis using an OLS regression the effect of market classification on wealth creation can be measured while controlling for other variabeles. This is done by presenting the relationship between de independent variable and the dependent variable. The independent variable is the explanatory variable and shows the effect it has on the dependent variable. In this research the dependent variable is the cumulative abnormal return and the explanatory variables are the control variables, focusing on the market classification variable. The formula is as follows:
𝐶𝐴𝑅𝑖𝑡 = 𝛽0 + 𝛽1∗𝐸𝑚𝑒𝑟𝑔𝑖𝑛𝑔 + 𝛽2∗𝐶𝑎𝑠ℎ + 𝛽3∗𝑆𝑡𝑜𝑐𝑘 + 𝛽4∗Listed + 𝛽5∗deal value + 𝛽6∗𝐼𝑛𝑑𝑢𝑠𝑡𝑟𝑦 𝑅𝑒𝑙𝑎𝑡𝑒𝑑 + 𝛽7∗ROA + 𝛽8∗Firms Size + 𝜀𝑖
By making this regression one can see the effect of a change in variable values, the beta’s show how much the CAR will deviate when one of the variables increases by 1. Only 𝛽0 does not show the effect of a variable, this is the constant that presents the intercept of the regression to minimize the residual values. Explanation of the variables:
- Emerging: dummy variable that becomes 1 when acquirer is from an emerging market, otherwise it will take value 0.
- Cash: a dummy variable that takes value 1 when the acquisition is payed for with cash, otherwise it will take value 0.
- Stock: a dummy variable that takes value 1 when the acquisition is paid for with stock, otherwise it will take value 0.
- Listed: a dummy variable that takes value 1 if the target firm is a listed company, otherwise it will take value 0.
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- Deal value: takes the natural logarithm of the deal value
- Industry related: a dummy variable that takes value 1 if the acquisition is done between firms in a related industry.
- ROA: Takes the value of the return on equity of the acquiring firm
- Firm size: takes the natural logarithm of the market capitalization of the acquiring firm. When running an OLS regression the data has to meet the following requirement to full fill the role as best linear unbiased estimator(BLUE), the sample mean has to be normally distributed, no multicollinearity and no heteroscedasticity. To test for the normality we may use the Central Limit Theory. The Central limit theory states that when a sample of over 30 observations is taken from a population we may assume that the sample mean is normally distrusted. To comply with this theory we have to assume that the population where the sample is taken from is normally distributed as well. To test for multicollinearity the Variance Inflation Factor is used to calculate the degree of multicollinearity. The first step to calculate the VIF a regression is run on the variables in the sample. The second step is to calculate the VIF by the formula VIF = 1/(1-R²). The rule of thumb states that if the VIF value is 1 it is not correlated and if it is 5 it is correlated. In addition one can look at the table fo correlation between variables. Correlation is high when the value is bigger than 0.800. Lastly to test for heteroscedasticity the Breasch-Pagan test is used. Heteroscedasticity occurs when the standard errors of variables in a sample are monitored for a specific time in which they are not consistent. This is a chi test which indicates heteroscedasticity when significant.
4. Results
4.1 CAR Analyses
For the first sample with African targets, the data had to full fill the requirements of the OLS regression mentioned before. The sample size is sufficient enough to allow us to assume that our sample is normally distributed. For testing for multicollinearity the correlation between the variables was examined and the results can be seen in the appendix ,only the CAR variables are correlated but is expected since they contain similar inputs. In addition, the variance inflation factor was calculated to double check the multicollinearity. The outcome was a fairly low VIF value with a mean of 1.1, allowing us to assume there is no multicollinearity. Lastly, to test for heteroscedasticity the Breusch-Pagan test was used. The outcome was significant for heteroscedasticity with a p-value<1%. To solve this problem robust standard errors are used for
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every regression. At first the student t-test was used to check if the CARs of the M&A deals were significantly different from zero. Table 3 below shows the descriptive statistics of the CARs for the different event windows. Lastly, fixed effects were added to the regression to control for fixed industry effects and fixed time effects.
When looking at the results one can see that the CARs from the first two event windows [-1,1] and [-5,5] show significant differences from zero. The first event window shows a decrease in the returns of -0.55% and the second event window shows a decrease of -1.29%. This result contradicts the findings of Chari A, Ouimet P & Tesar L(2004) who found a positive return for the acquiring shareholders of 2.4%. However no causal relationship can be determined due to the absences of control variables. Besides no conclusions can be drawn regarding the hypothesis because no distinguish is made between acquiring firms from a developed market developed and acquiring firms from an emerging market.
TABLE 5T-TEST STATISTICS CARS SAMPLE 1
Event Window Mean Std.Error T-test p-value
CAR[-1,+1] -.0063275 .002121 -2.9832 0.0031***
CAR[-5,+5] -.0126801 .0049898 -2.5412 0.0116**
CAR[-15,15] .0053911 .008985 0.6000 0.5490
CAR[-25,25] .0132062 .0128821 1.0252 0.3061
Table 4 and 5 show the descriptive statistics of the CARs for the different event windows when controlled for the different market classifications. Table 4 for consists of the CARs of acquirers from developed markets. As one can see the results are quite similar to the results of the whole sample. However only the event window [5,+5] is significant with a decrease in returns of -1.21%. These results are again in conflict with most of the previous literature. Chari et al. (2010) found significant positive abnormal returns for the acquiring shareholders when a firm from a developed market targeted a firm in an emerging market. In addition Burns & Liebenberg (2012) stated that shareholders of US firms realized a positive abnormal return when acquiring a firm from an emerging market country. Based on these results the first hypothesis can be rejected. However the multivariate analyses is needed to give a clear conclusion about the causal relationship.
Table 5 shows the CARs of acquiring firms from an emerging country. The table shows no significant results for all the event windows. Little literature is out there investigates the effect of emerging market acquirers targeting emerging market firms. The literature mainly focused on emerging market firms acquiring developed market firms to get access to their skills
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and governance(Kohli & Mann. 2011). Based on the results the second hypothesis cannot be accepted. Again, the multivariate analyses is needed to make a clear conclusion about the relationship. However a similar pattern is shown for both markets, an increase in the returns when the event window increases. This is in consent with the paper by Amewu et all (2018). They found that when they widened the event window the CAR increased due to information leakage and the lower level of information travel.
TABLE 6T-TEST STATISTICS CARS DEVELOPED MARKET SAMPLE 1
Event Window Mean Std.Error T-test p-value
CAR[-1,+1] -.0058718 .0023199 - 2.5311 0.0120**
CAR[-5,+5] -.0122614 .0053883 -2.2755 0.0237**
CAR[-15,15] .0046604 .0096737 0.4818 0.6304
CAR[-25,25] .0124145 .0141133 0.8796 0.3799
TABLE 7T-TEST STATISTICS CARS EMERGING MARKET SAMPLE 1
Event Window Mean Std.Error T-test p-value
CAR[-1,+1] -.0085095 . 0052679 -1.6154 0.1124
CAR[-5,+5] -.0146852 .0131001 -1.1210 0.2675
CAR[-15,15] .0088901 .0238644 0.3725 0.7702
CAR[-25,25] .0169976 .031814 0.5343 0.5955
The second sample with African bidder firms the only possible test was the CAR analyses by means of the student t-test. The results are shown in table 8. Due to the lack of information about deal characteristics and firm characteristics an OLS regression was feasible. However, when looking at the output of the student t-test we can see that none of the outcomes are significant. A similar pattern is shown compared to the output of the first sample. Negative CAR for the shorter event window that becomes positive and increases when the event window is extended. Based on these results we cannot accept our third hypothesis.
TABLE 8T-TEST STATISTICS CARS SAMPLE 2
Event Window Mean Std.Error T-test p-value
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CAR[-5,+5] .01021 .0094112 1.0849 0.2831
CAR[-15,15] .0298157 .0207847 1.4345 0.1575
CAR[-25,25] .0336595 .0274873 1.2245 0.2264
4.2 The OLS Regression
To be able to make a clear conclusion about the effect of market classification on the returns of the acquiring shareholders within CBMA the OLS regression is used. Table 6 contains the results of the regressions that have been done on the whole sample while adding control variables for firm characteristics. Again we see a significant negative constant for the shorter event window [-5,+5]. Furthermore when looking at the results one can see that almost none of the variables came out as significant which is consistent with the fairly low R-squared values of the regression. Only when shares are used to finance the acquisition a positive significant effect of 7% is realized on the CARs in the event window [-15,+15]. This result is contradicting the results of Faccio et al (2006) in which they found lower returns when an acquisition was financed with shares compared to with cash. Furthermore the findings of Chari et al (2004) are in contrast as well, their findings supported the idea that equity financing negatively influences the abnormal returns.
To answer the first hypothesis the output in table 8 is used. This table shows the output of the same OLS regression while controlling for market classification. The first four columns are outputs when controlled for developed market acquirers and the last four columns when controlled for emerging market acquirers. When testing the validity of the hypothesis the constants of the regression should be examined. The first hypothesis stated that CBMA with a developing market acquirer and an emerging target in Africa have a positive effect on the share holders’ value around the announcement date. However when looking at the constants of the regressions when controlled for developed markets a negative effect can be seen instead of a positive effect. Again, when increasing the event window the constant coefficient become positive. However, these effects are not significant for every event window and we therefor are rejecting the first hypothesis. Similar to the uncontrolled regression financing the deal with equity has a significant positive effect of 7% for the [-15,+15] event window. In addition, when a target firm is a publicly traded firm the CAR is negatively affected when looking at the
[-25
25,+25] event window. Faccio et al 2006 found significant evidence of private target companies on the abnormal returns.
The second hypothesis stated that CBMA with an emerging market acquirer and an emerging market target in Africa have a positive effect on the share holders’ value around the announcement date. To test the hypothesis the OLS regression was run while controlling for emerging market acquirers, the results are shown in the last four columns of table 8. The constants show a significant negative effect on the first two event windows and a negative insignificant effect for the two longer event windows. When looking at the constants one can reject the second hypothesis as well. The firms characteristics for emerging market bidders show some significant results. Size has a positive significant impact for almost all event windows, increasing shareholders’ return with as much 3.3 percentage points when size increases by 1% for the longest event window. Contrary, return on assets has a significant negative effect on CAR for the longest event window of -1 percentage point for an increase of 1% in return on assets .
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TABLE 9REGRESSION OUTPUT TOTAL SAMPLE 1
Dependent Variable CAR
Event Window
[-1,+1]
[-5,+5]
[-15,+15]
[-25,+25]
VARIABLES
CAR1
CAR5
CAR15
CAR25
Ind_related
-0.001
-0.009
-0.013
-0.008
(0.905)
(0.421)
(0.520)
(0.766)
0.005
0.011
0.020
0.027
Shares
0.004
0.011
0.071**
0.063
(0.549)
(0.498)
(0.014)
(0.110)
0.007
0.016
0.029
0.039
Cash
-0.009
-0.007
-0.016
0.052
(0.264)
(0.732)
(0.629)
(0.317)
0.008
0.021
0.033
0.052
ROA
-0.000
-0.001*
-0.001
-0.000
(0.106)
(0.077)
(0.446)
(0.975)
0.000
0.001
0.001
0.002
Size
0.002
0.004*
0.003
0.001
(0.131)
(0.069)
(0.500)
(0.813)
0.001
0.002
0.004
0.006
Listed
0.009
0.013
0.009
-0.065
(0.352)
(0.568)
(0.813)
(0.236)
0.009
0.023
0.039
0.055
Constant
-0.015*
-0.036**
-0.015
-0.002
(0.052)
(0.049)
(0.654)
(0.973)
0.008
0.018
0.033
0.049
Observations
259
259
259
259
R-squared
0.029
0.023
0.031
0.015
Robust pval in parentheses
*** p<0.01, ** p<0.05, * p<0.1
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Dependent Variable CAR
Developed Market Emerging Market
Event Window [-1,+1] [-5,+5] [-15,+15] [-25,+25] [-1,+1] [-5,+5] [-15,+15] [-25,+25] VARIABLES CAR1 CAR5 CAR15 CAR25 CAR1 CAR5 CAR15 CAR25 Ind_related -0.001 -0.008 -0.008 -0.003 -0.008 -0.020 -0.086 -0.112 (0.877) (0.507) (0.704) (0.909) (0.639) (0.574) (0.192) (0.145) 0.005 0.012 0.022 0.029 0.017 0.036 0.065 0.076 Shares 0.004 0.008 0.073** 0.066 0.013 0.043 0.095 0.103 (0.582) (0.645) (0.016) (0.119) (0.143) (0.108) (0.437) (0.565) 0.007 0.017 0.030 0.042 0.009 0.026 0.121 0.177 Cash -0.012 -0.022 0.025 0.092 -0.002 0.030 -0.107* -0.031 (0.247) (0.399) (0.548) (0.134) (0.882) (0.434) (0.051) (0.748) 0.010 0.026 0.041 0.061 0.014 0.038 0.054 0.096 ROA -0.000 -0.001 -0.000 0.001 -0.002* -0.003* -0.007* -0.010*** (0.432) (0.307) (0.821) (0.521) (0.070) (0.075) (0.077) (0.009) 0.000 0.001 0.001 0.002 0.001 0.002 0.004 0.004 Size 0.001 0.003 0.000 -0.003 0.005** 0.013** 0.020* 0.033** (0.346) (0.236) (0.989) (0.614) (0.035) (0.030) (0.052) (0.029) 0.001 0.002 0.005 0.007 0.002 0.006 0.010 0.014 Listed 0.002 0.013 -0.035 -0.132** 0.024 0.014 0.128 0.111 (0.839) (0.599) (0.367) (0.016) (0.132) (0.799) (0.164) (0.375) 0.012 0.024 0.038 0.054 0.016 0.054 0.090 0.124 Constant -0.010 -0.023 0.000 0.031 -0.039** -0.104** -0.091 -0.173* (0.240) (0.235) (0.998) (0.557) (0.013) (0.017) (0.248) (0.074) 0.009 0.020 0.036 0.053 0.015 0.042 0.078 0.095 Observations 210 210 210 210 49 49 49 49 R-squared 0.020 0.019 0.034 0.036 0.156 0.117 0.198 0.156 Robust pval in parentheses
*** p<0.01, ** p<0.05, * p<0.1
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5. Conclusion
In this study, the effect of cross-border merger and acquisition announcements on shareholders’ value when the targeted firms are from Africa is examined. The acquiring firms are divided into two groups based on the market classification of their country, creating a developed market group and an emerging market group. This thesis contains a literature review evaluating the potential gains and losses that are arising due to M&A activity. There are several motives for M&A with different outcomes for both the shareholders and the managers. Motives for the managers that destroy the value of the shareholders are agency problems and managerial hubris. In contrary, M&A leads to synergy gains creating value for the shareholders. When a merger or acquisition is border more motives are added to the list. Motives created by cross-border mergers and acquisitions that create value for the shareholders arise from tax benefits, accessing a new market and corporate governance. Contrary, liability of foreignness such as geographical distance, cultural differences and integration costs destroy shareholders’ value. Lastly, differences in market classification creates more motives to engage in an acquisition deal, especially in Africa. African firms are an attractive target for foreign firms due to the high GDP growth, richness of natural resources and an increase in both political stability and consumer market. To study the effect of those motives and potential gains an empirical analyses was done. The analyses consist of an event study analyzing the CARs and thereafter using a multivariate analyses to check for deal specific effects by mean of the market model. The study is done on two samples, the first sample of 302 CMBA deals in which the target firm is from Africa and the bidder firm from an emerging country or developed country outside of Africa. Out of the 302 transaction 52 were done by a firm from an emerging country and 249 by a developed country. A second sample with 52 CMBA transactions by African firms acquiring developed market firms outside of Africa.
There is still no consensus in previous literature about the shareholders’ wealth creation due to firms acquiring firms in emerging markets. However, most studies recent studies state that such M&A deals generate gains for the shareholders by increasing the share price. Especially when the acquiring firm is from a developed market. Literature about emerging market firms targeting emerging market firms was really scarce. In this study the abnormal returns of stock prices around the announcement date were examined using the market model. The results were inconsistent with previous studies and showed a negative effect in the short run on shareholders’ value for both acquiring firms, emerging and developed. With a significant
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effect on the developed market bidder firm of -1.29 for event window [-5,+5] and -0.63% for the event window [-1,+1]. When the duration is extended the shareholders’ value seems to increase however this is not significant. In addition, no evidence is found that African acquirers create positive nor negative returns for the shareholders when acquiring developed firms outside of Africa .
To further investigate the effect of market classifications of the acquiring firms the multivariate analyses is used based on the OLS regression while controlling for deal specifics and firm characteristics. Unfortunately, this was not feasible for the second sample due to the lack of information. Again the results show that when a bidder is from a developed market the acquisition has a negative insignificant effect on shareholders wealth. When the acquiring firms is from an emerging market a M&A deals negatively impact shareholders’ wealth for as much as -10% for the event window [-5,+5]. Some deal characteristics and firm characteristics significantly impact the shareholders’ value as well. If the acquiring developed market firm uses equity financing as their method of payment the CAR increases by 7% for the event window [-15,+15]. Furthermore when the acquirer is from an emerging market ROA negatively affects shareholders wealth and in contrary firm size positively affects shareholders’ wealth within M&A.
Several limitations can be mentioned regarding the empirical analyses. First of all the sample size is relatively small only 300 transactions. However most problematic are the low percentage of emerging market bidders, only 52 transactions. Besides, financial information in Africa is recorded less accurately compared to other continents and countries. For instance the deal value variable has been dropped due to the high percentage of missing values. In addition most acquired firms were private firms creating less transparency. These problems can bias the OLS regression and bias the results of the research.
Further research could take in account the relative GDP growth between the target and the bidder firm and potentially increase the sample size if possible. Emerging bidders are slowly representing a larger percentage of the global M&A transactions that could potentially increasing the sample size of emerging market bidders. In addition, over the years emerging market firms will potentially be monitored more extensively making it possible to run a regression while including deal and firm characteristics as control variables.
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