Chapter 15

Mergers and Acquisitions in Frontier Markets: A Comparative Analysis

E. Vagenas-Nanos    University of Glasgow, Glasgow, United Kingdom

Abstract

This chapter examines the behavior of mergers and acquisitions (M&A) in frontier markets. There has been some M&A activity in frontier markets since 1999, with a rising trend after 2006. However, acquirers based in frontier markets fail to create superior abnormal returns for their shareholders compared to acquirers from elsewhere in the world, as they seem to lack the expertise to do so. Overpayment is unlikely to be the explanation since target firms in frontier markets receive the lowest premiums. Acquirers from developed countries achieve their highest abnormal returns when they bid for target firms in frontier markets.

Keywords

frontier markets
mergers and acquisitions
acquirer gains
target gains

1. Introduction

The ultimate aim of acquiring firms is to create value for shareholders by selecting appropriate target firms which can generate synergistic gains. To create value through mergers and acquisitions (M&A), acquirers need to pay less than the sum of the present value of the target firm and the present value of potential synergies. Nevertheless, empirical studies show that acquirers generate negative or zero abnormal returns, especially for the acquisition of public target firms (Travlos, 1987; Fuller et al., 2002). One of the reasons that have been put forward to explain bidders’ underperformance is managerial hubris (Roll, 1986). Managers affected by hubris tend to overestimate synergies or underestimate risks, overpay for target firms, and end up destroying value for their shareholders. Another potential explanation is the presence of competition in M&A markets. Severe competition among bidders to acquire target firms (especially public target firms) leads to overpayment, resulting in value-destructive acquisitions (Mandelker, 1974; Draper and Paudyal, 2006).
The vast majority of empirical studies concentrate on the United States, United Kingdom, Canada, and other developed markets which are the most competitive M&A markets in the world. Alexandridis et al. (2010) in a global M&A study find that acquirers of domestic public target firms generate positive abnormal returns in countries outside the United States, United Kingdom, and Canada, and attribute this to the fact that competition in M&A markets is lower outside these three countries.
Our study examines M&A behavior in a different type of market that has never been examined before: That is, M&A in frontier markets. Frontier (preemerging) markets are characterized by being less established than the emerging markets. They are investable stock markets but are smaller than those in emerging or developed economies. Investments in frontier markets could yield high returns due their high risk profiles. Frontier markets are highly risky due to frequent political unrest, low liquidity, poor regulation and accounting standards, and high currency risk. On the other hand, diversification benefits can be achieved as there is low correlation between frontier and developed markets.
In frontier markets, M&A could be the ideal vehicle through which firms could take advantage of upcoming opportunities in order to enhance corporate growth and increase their market power and profitability. This chapter examines M&A activity in frontier markets and compares it with acquisitions that take place in the United States, United Kingdom, and Canada (hereafter USUKCAN group), in other developed markets, and in emerging economies.
The first aim of this study is to examine the evolvement of M&A in frontier markets. Unlike the United States and the United Kingdom, where a number of merger waves have been reported through the past 150 years, evidence shows that M&A activity has only recently begun in frontier markets. We find that the first relatively large deals appeared in 1999 and that there is a growing trend from 2006 until today. We further explore the announcement performance of acquiring firms. As competition in merger markets in frontier economies is low, acquirers are unlikely to suffer from hubris or to overpay to acquire target firms. Despite that fact, upon the announcement of a takeover, we find that acquirers based in frontier markets generate small and insignificant gains which are lower than the gains obtained by acquirers in the USUKCAN group in developed and emerging economies. This is likely to be attributed to the fact that acquirers in frontier markets lack expertise in achieving superior abnormal returns upon the announcement of a takeover. Overpayment is unlikely to be the explanation for the poor acquirer performance as we further examine target short-term performance. Findings show that target firms in frontier economies provide the lowest abnormal returns as compared with the short-term performance of target firms across the globe. This indicates that target firms in frontier markets receive the lowest premiums and hence acquirers’ gains are unlikely to be hampered by potential overpayment. Finally, results indicate that acquirers from developed and emerging markets enjoy the highest abnormal returns when they acquire target firms in frontier markets.
This study contributes to the existing literature in several ways. First, to the best of our knowledge, this is the first study that examines M&A behavior in frontier markets. Second, it shows that acquirers based in frontier markets lack expertise in achieving excess abnormal returns. Third, we show that competition is an important factor in explaining target firms’ abnormal returns, as in frontier markets target firms receive the lowest abnormal returns. Finally, acquirers in developed markets achieve their highest abnormal returns when they bid for targets in frontier markets.
The remainder of the chapter is structured as follows: Section 2 discusses the data and methodology, Section 3 presents the empirical results, and Section 4 concludes.

2. Data and Methodology

2.1. Sample

The sample consists of completed M&A of listed companies from all over the world for the period between 01/01/1990 and 12/31/2014. The data are sourced from the Thomson Financial SCD global M&A database. The bidders’ nations are classified into four groups. The group of interest is frontier markets, which consist of countries like Bahrain, Bulgaria, Colombia, Croatia, Cyprus, Estonia, Jordan, Kuwait, Latvia, Lithuania, Malta, Nigeria, Oman, Qatar, Romania, Saudi Arabia, Slovakia, Slovenia, Tunisia, Ukraine, and United Arab Emirates. The second group is USUKCAN, which includes deals for which the bidder is based in the United States, United Kingdom, or Canada. The third group is developed countries such as Australia, Austria, Belgium, Denmark, Finland, France, Germany, Greece, Hong Kong, Ireland (Republic of), Italy, Japan, Luxembourg, Netherlands, New Zealand, Norway, Portugal, Singapore, Spain, Sweden, and Switzerland. We created separate groups for the USUKCAN group and the rest of the developed countries, as Alexandridis et al. (2010) show that the performance of bidders in the three most active M&A markets (United States, United Kingdom, and Canada) is different from that of bidders in the rest of the world. Finally, we create a group of emerging markets, which include countries such as Argentina, Brazil, China, Czech Republic, India, Indonesia, Israel, Malaysia, Mexico, Morocco, Peru, Philippines, Poland, Russian Federation, South Africa, South Korea, Taiwan, Thailand, Turkey, and Venezuela.
The target firms are either listed or unlisted firms and are classified in groups according to national development in the same way as bidding firms. For target firms, the group of frontier markets includes additional frontier markets such as Bangladesh, Bermuda, Bosnia, Botswana, Costa Rica, Ecuador, Ghana, Jamaica, Kazakhstan, Kenya, Kyrgyzstan, Lebanon, Mauritius, Mongolia, Namibia, Pakistan, Panama, Papua New Guinea, Serbia, Sri Lanka, Tanzania, Trinidad and Tobago, Vietnam, and Zambia. The classification of countries in the four groups is based on FTSE list classification and evidence presented in Samarakoon (2011).
For a transaction to be included in the sample, the acquirer needed to buy at least 50% of the target’s shares and the deal value had to be $1 million or more. We obtained financial data for bidding and listed target firms from Thomson Financial Datastream. The initial sample consisted of 93,160 deals. After excluding deals for which financial information was not available in Thomson Financial Datastream and deals for which the bidder belonged in the financial or utilities industry, the sample was reduced to 68,846 deals. We also excluded deals for which the relative size of the target was less than 1% of the bidder. The final sample size consists of 48,642 deals.
Table 15.1 presents descriptive statistics for the whole M&A sample. The small number of merger transactions initiated by acquirers based in frontier markets justifies the lack of attention and academic research for these markets. Out of the 48,642 deals in our sample, only 105 transactions are undertaken by acquirers based in frontier markets. That consists of 0.22% of the whole sample. The vast majority of acquisitions are performed by bidders based in the United States, United Kingdom, and Canada; more than three-fourths of total deals in our sample are undertaken by these bidders. Around 18% of the deals are completed by acquirers based in developed countries, and around 5% by acquirers based in emerging markets. In frontier markets, it is on average large acquirers that engage in M&A transactions. The average size of bidders in frontier markets ($6412.14 million) is almost 3 times more that the average size of bidders in the USUKCAN group ($1986.277 million) and almost twice the size of bidders in developed markets ($3753.46 million). This indicates that only relatively large firms take the initiative to initiate and complete M&A deals in frontier markets, whereas in the United States, United Kingdom, Canada, and other developed countries even smaller firms undertake acquisitions. The market-to-book ratio of bidders in frontier markets is on average lower (2.39) relative to bidders in USUKCAN and developed markets (3.22 and 3.06, respectively), indicating that misevaluation seems to be one of the incentives to undertake acquisitions in developed countries (Shleifer and Vishny, 2003; Rhodes-Kropf et al., 2005). Regarding the method of payment, the target’s public status, and the percentage of diversifying deals, the patterns appear to be consistent across all four country classifications. Stock financing is the least preferred method of payment of acquirers all around the world, and acquisitions of public target firms consist of only 10–15% of the total M&A transactions.

Table 15.1

Descriptive Statistics for the Sample

Frontier USUKCAN Developed Emerging
N 105 37,279 8,723 2,535
% N 0.22 76.64 17.93 5.21
MV 6,412.237 1,986.277 3,753.467 4,987.717
MTBV 2.3907 3.22 3.061487 2.179169
RS 0.3283012 1.335199 1.414637 0.2265494
Deal value 362.5122 249.4885 348.2028 269.1802
Cash 26 10,295 2,032 675
Mixed 74 21,389 5,485 1,336
Stock 5 5,595 1,206 524
% Cash 24.76 27.62 23.29 26.63
% Mixed 70.48 57.38 62.88 52.7
% Stock 4.76 15.01 13.83 20.67
Private 56 20,270 3,933 1,185
Public 11 4,840 1,331 272
Subsidiary 38 12,169 3,459 1,078
% Private 53.33 54.37 45.09 46.75
% Public 10.48 12.98 15.26 10.73
% Subsidiary 36.19 32.64 39.65 42.52
Nondiversifying 59 21,756 4,706 1,230
Diversifying 46 15,523 4,017 1,305
% Nondiversifying 56.19 58.36 53.95 48.52
% Diversifying 43.81 41.64 46.05 51.48

This table presents general descriptive statistics for the sample. Acquirers’ nations are divided into four groups (frontier, USUKCAN, developed, and emerging markets) according to each country’s development as described in the data and methodology section in the chapter. N is the number of acquisitions per development group. MV is the market value of the acquirer and is measured as the market capitalization of the acquiring firm the month prior to the acquisition. MTBV is the ratio of market to book value of the bidder as measured the month prior to the acquisition announcement. RS is the relative size of the deal, which is calculated as the ratio of the deal value to the acquirer’s market value. Deal value is the deal value of the deal as reported by Thomson Financial SCD global M&A database. Cash represents 100% cash-financed acquisitions; stock represents 100% stock-financed acquisitions; the rest are classified as mixed. Private indicates the acquisition of private target firms, public the acquisition of public target firms, and subsidiary the acquisition of subsidiary target firms. If the first two digits of the SIC code of the acquiring firm are equal to the first two digits of the SIC code of the target firm, the deal is classified as nondiversifying, otherwise as diversifying. Deals are classified as domestic if both the bidder and the target firm are based in the same country and as crossborder if the target firm is located in a country different from that of the bidder.

2.2. Methodology

To estimate acquirers’ performance, we employ a standard event study methodology and calculate cumulative abnormal returns (CARs) for a 5-day window (−2, +2) around the announcement date (Fuller et al., 2002). Bidder abnormal returns are estimated by using the modified market model as follows:

ARi,t=Ri,t−Rm,t

image
where ARi,t is the excess abnormal return of acquirer i at time t, Ri,t is the return of acquirer i at time t, and Rm,t is the market return of the respective bidder’s country index at time t. For market indices, we employ the Datastream market indices (mnemonic TOTMK) for each of the bidder countries. CARs are estimated as the sum of bidder abnormal returns for the 5-day window surrounding the announcement date as follows:

CARi=∑t=−2t=+2(Ri−Rm)

image
To examine target firms’ performance, we adopt the same methodology and estimate CARs for target firms for a 3-day window (−1, +1) around the announcement date. Fu et al. (2013) employ target CARs (−1, +1) as a proxy for acquisition premium offered to target firms. Target CARs are estimated only for public target firms.
To exclude outliers, bidder 5-day CARs and target 3-day CARs are winsorized at the 1 and 99% levels.

3. Empirical Results

3.1. Trend of M&A in Frontier Markets

The first aim of this study is to examine how M&A transactions have evolved in frontier markets. Prior evidence reports that M&A activity tends to cluster over time. Since the end of the 19th century until today, six merger waves have been reported in the United States and five in the United Kingdom. Gort (1969) argues that merger waves take place during periods of growing economic activity, and Jovanovic and Rousseau (2002) claim that M&A is the vehicle through which capital is more efficiently allocated in better projects. Shleifer and Vishny (2003) show that bidder misevaluation is one of the major motives of M&A deals.
Data in our sample indicate that M&A activity in frontier markets is quite low and consist of only 0.22% of total transactions around the world. Table 15.2 and Fig. 15.1 show that M&A activity in frontier markets started in 1999 and there has been a growing trend from the year 2006 until today. In 2008 there was a peak in merger activity in frontier markets, with 21 deals taking place during that year. In the United States, United Kingdom, Canada, and other developed countries, we observe significant merger waves in the period 1998–2000 and in the period 2006–2007.

Table 15.2

Acquisitions by Country Development Group and by Year

Frontier USUKCAN Developed Emerging
N Percentage N Percentage N Percentage N Percentage
1990 0 0 788 2.11 118 1.35 2 0.08
1991 0 0 691 1.85 112 1.28 12 0.47
1992 0 0 916 2.46 89 1.02 9 0.36
1993 0 0 1134 3.04 94 1.08 16 0.63
1994 0 0 1475 3.96 134 1.54 36 1.42
1995 0 0 1565 4.2 165 1.89 56 2.21
1996 0 0 2001 5.37 200 2.29 54 2.13
1997 0 0 2447 6.56 301 3.45 90 3.55
1998 0 0 2555 6.85 299 3.43 96 3.79
1999 1 0.95 2161 5.8 453 5.19 78 3.08
2000 1 0.95 2110 5.66 643 7.37 96 3.79
2001 3 2.86 1591 4.27 388 4.45 61 2.41
2002 2 1.9 1423 3.82 335 3.84 65 2.56
2003 3 2.86 1268 3.4 338 3.87 104 4.1
2004 2 1.9 1666 4.47 425 4.87 89 3.51
2005 4 3.81 1817 4.87 518 5.94 87 3.43
2006 11 10.48 1891 5.07 661 7.58 128 5.05
2007 9 8.57 1959 5.25 784 8.99 171 6.75
2008 21 20 1324 3.55 456 5.23 191 7.53
2009 9 8.57 982 2.63 330 3.78 157 6.19
2010 10 9.52 1245 3.34 460 5.27 183 7.22
2011 6 5.71 1183 3.17 426 4.88 183 7.22
2012 7 6.67 1058 2.84 370 4.24 161 6.35
2013 10 9.52 923 2.48 285 3.27 209 8.24
2014 6 5.71 1106 2.97 339 3.89 201 7.93

This table presents the number of acquisitions per year. Acquirers’ nations are divided into four groups (frontier, USUKCAN, developed, and emerging markets) according to each country’s development as described in the data and methodology section in the chapter.

image
Figure 15.1 Histograms of acquisitions per year.
This chart is shows the histogram of acquisitions according to acquirers’ national development, which is divided into four groups, frontier, USUKCAN, developed, and emerging markets according to country’s development as described in the data and methodology section in the chapter. The four histograms show the number of acquisitions per year. (Graphs by Acquiror Nation Development.)
This growing trend in recent takeover deals in frontier markets provides a good motivation to study the behavior of acquisitions in these countries. As competition is lower in these markets and opportunities to explore hidden synergies are likely to be greater, our next goal is to explore the benefits of domestic and foreign takeovers in frontier markets.

3.2. Acquirer Performance

There are two main factors that affect the outcome of an M&A deal. The first one is the potential synergies to be created from the deal, and the second is the amount paid to finance the transaction. If bidders fail to identify deals with positive synergy gains, or if they do identify such deals but overpay for the transaction, the outcome of the deal is expected to be negative. The payment (or overpayment) in takeover deals has been argued to be affected either by managerial overconfidence (Roll, 1986) or by high competition on acquiring a particular target firm (Schwert, 1996; Boone and Mulherin, 2007).
Travlos (1987) reports short-term losses for US acquirers that announce acquisitions of public target firms. The market for public target firms is quite competitive, and this is likely to be one of the reasons that lead acquirers to overpay and suffer losses upon the announcement of the acquisition. Another potential explanation is that managers who acquire public target firms (usually large in size) are likely to be affected by hubris and therefore overestimate potential synergies, resulting in completing nonvalue-creating deals. On the other hand, the market for private firms is less liquid and competition is lower. This is one of the reasons that Chang (1998) reports positive announcement abnormal returns for acquirers that announce the acquisition of private target firms. Alexandridis et al. (2010) examine domestic acquisition for public target firms across the globe and show that in non-USUKCAN markets where competition for the acquisition of public target firms is lower, bidders tend to enjoy positive announcement abnormal returns.
This study focuses in the case of acquisitions announced by bidders in frontier markets. Table 15.3 reports the 5-day cumulative abnormal returns for acquirers in frontier, USUKCAN, developed, and emerging markets. We further split the sample into domestic and crossborder acquisitions as well as acquisitions for public target firms (panel B) and private target firms (panel C). The overall performance of acquirers in frontier markets is 0.93% (statistically insignificant), while acquirers in the USUKCAN group generate 2.42%, in the developed markets group 3.09%, and in the emerging markets group 4.70%. The positive results reported in the first column of panel A are mainly driven by the fact that the vast majority of acquisitions in the overall sample consist of acquisitions of unlisted target firms. These findings indicate that acquirers in frontier markets fail to create more value than acquirers in developed and emerging markets. Competition is unlikely to be the explanation, as frontier markets are the least active markets for mergers. The results for the USUKCAN, developed, and emerging markets groups are consistent with the competition hypothesis (Alexandridis et al., 2010), as acquirers’ returns exhibit an upward trend as we move from the most competitive group (USUKCAN) to the least competitive group (emerging markets). Acquirers based in frontier markets seem to lack expertise in achieving superior abnormal returns through M&A. Acquirer abnormal results remain similar when we split the sample into domestic and crossborder acquisitions (second and third columns of panel A in Table 15.3).

Table 15.3

Acquirers’ Cumulative Abnormal Returns According to Acquirers’ Development Country Classification

Acquirers Panel A: all Panel B: public targets Panel C: private targets
All Domestic Crossborder All Domestic Crossborder All Domestic Crossborder
Frontier 0.93% 1.06% 0.77% 0.77% 2.51% −1.31% 0.13% −0.16% 0.55%
p-Value (0.161) (0.276) (0.386) (0.677) (0.398) (0.581) (0.890) (0.897) (0.737)
N 105 56 49 11 6 5 56 33 23
USUKCAN 2.42%*** 2.43%*** 2.38%*** 0.21% 0.09% 0.72%** 2.72% 2.82% 2.39%
p-Value (0.000) (0.000) (0.000) (0.114) (0.531) (0.014) (0.000) (0.000) (0.000)
N 37,279 28,650 8,629 4,840 3,953 887 20,270 15,699 4,571
Developed 3.09%*** 3.58%*** 2.56%*** 1.59%*** 1.85%*** 1.26%*** 3.54% 4.29% 2.63%
p-Value (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)
N 8,723 4,509 4,214 1,331 735 596 3,933 2,146 1,787
Emerging 4.70%*** 5.18%*** 3.07%*** 1.49%** 2.14%*** −0.13% 5.19% 5.67% 3.64%
p-Value (0.000) (0.000) (0.000) (0.010) (0.003) (0.886) (0.000) (0.000) (0.000)
N 2,535 1,957 578 272 194 78 1,185 903 282
Front–USUKCAN −1.49%** −1.37% −1.61%* 0.57% 2.42% −2.03% −2.59% −2.97% −1.84%
p-Value (0.025) (0.160) (0.077) (0.760) (0.414) (0.408) (0.010) (0.019) (0.270)
Front–developed −2.16%*** −2.52%** −1.79%* −0.81% 0.66% −2.57% −3.40% −4.45% −2.08%
p-Value (0.001) (0.012) (0.051) (0.664) (0.819) (0.307) (0.001) (0.001) (0.217)
Front-emerging −3.78%*** −4.13%*** −2.30%** −0.71% 0.38% −1.18% −5.06% −5.83% −3.09%
p-Value (0.000) (0.000) (0.020) (0.713) (0.898) (0.637) (0.000) (0.000) (0.084)

This table presents the cumulative abnormal returns for acquirers for the whole sample. Acquirers’ nations are divided into four groups (frontier, USUKCAN, developed, and emerging markets) according to each country’s development as described in the data and methodology section in the chapter. Deals are classified as domestic if both the bidder and the target firm are based in the same country, and as crossborder if the target firm is located in a country different from that of the bidder. Panel A shows results for the whole sample, panel B for acquisitions of public target firms, and panel C for acquisitions of private target firms. Front–USUKCAN, Front–developed, and Front–emerging indicate the difference in acquirer short-term performance between acquirers based in frontier markets and acquirers based in the USUKCAN, developed, and emerging markets groups, respectively; p-values are reported in parentheses, and the number of acquisitions for each category is reported below that.

Alexandridis et al. (2010) argue that the competition hypothesis for M&A in a global framework would be more appropriately tested for domestica acquisition of public target firms, as the market for public targets is more competitive. In panel B, we report the acquirers’ announcement effect for the acquisition of public targets. In particular, the second column of panel B shows bidder performance for domestic acquisitions. Cumulative abnormal returns for acquirers based in frontier markets are the highest (2.51%) among all four groups. Results indeed show that as we move from the least competitive markets (frontier) to the most competitive markets (USUKCAN) for public target firms, acquirer abnormal returns tend to decrease. Nevertheless, the difference between frontier markets and the rest of the markets is not statistically significant. The small number of acquisitions (six deals) is not ideal to offer fruitful conclusions. On the other hand, acquisitions for private target firms (panel C) do not appear to be as successful for domestic acquirers in frontier markets as they are for the rest of the world, which indicates that bidders based in frontier markets seem to lack expertise in undertaking successful acquisitions.
The M&A literature has documented a number of factors that affect bidder performance. Such factors include the acquirer’s size (Moeller et al., 2004); the target firm’s target status and the method of payment (Travlos, 1987; Chang, 1998; Fuller et al., 2002); the relative sizes of the target and the bidder (Asquith, 1983); the bidder’s market-to-book value (Rau and Vermaelen, 1998); domestic versus crossborder acquisition (Danbolt, 2004); and industry diversification (Doukas and Kan, 2004). To examine whether these factors affect bidder performance in frontier markets, we adopt a multivariate regression framework where cumulative abnormal returns are regressed against all of the factors.
Table 15.4 presents the multivariate analysis results. In all regression we include the following control variables: the logarithm of the acquirer’s market value as measured 1 month prior to the acquisition announcement; a dummy variable that takes the value of one if the method of financing the deal was 100% in stock and zero otherwise; a dummy variable that takes the value of one if the target firm is a listed firm and zero otherwise; the relative size of the deal, which is measured as the ratio of the deal value to the market value of the bidder; the acquirer’s market-to-book value as measured 1 month prior to the acquisition; a dummy variable that takes the value of one if the bidding and the target firms are based in the same country (domestic) and zero otherwise; and a dummy variable that takes the value of one if the first two digits of the bidder’s SIC code are not equal to the first two digits of the target firm’s SIC code (diversifying).

Table 15.4

Multivariate Regression Analysis of Acquirers’ Cumulative Abnormal Returns

Model 1 Model 2 Model 3 Model 4 Model 5
All Public Private Cash Stock
BidderFrontierDummy −0.013** 0.001 −0.021 −0.030** 0.018
p -Value (0.038) (0.953) (0.045) (0.011) (0.570)
LogMV −0.005*** −0.006*** −0.005*** −0.005*** −0.005*
p-Value (0.002) (0.000) (0.002) (0.000) (0.059)
Stock 0.011** −0.013** 0.018***
p-Value (0.038) (0.015) (0.000)
Public −0.020*** −0.000 −0.043***
p-Value (0.000) (0.867) (0.000)
RS 0.000*** −0.000 0.000*** 0.000 0.000***
p-Value (0.000) (0.401) (0.000) (0.344) (0.000)
MTBV −0.000*** 0.000*** −0.000*** −0.000*** 0.000***
p-Value (0.000) (0.003) (0.000) (0.000) (0.000)
Domestic −0.001 −0.007*** 0.003 −0.004 0.005
p-Value (0.791) (0.001) (0.302) (0.242) (0.214)
Diversifying −0.001 0.003* −0.001 −0.001 0.002
p-Value (0.422) (0.080) (0.576) (0.205) (0.722)
Constant 0.056*** 0.051*** 0.053*** 0.054*** 0.066***
p-Value (0.000) (0.000) (0.000) (0.000) (0.000)
N 44,413 5,887 23,110 12,161 6,445
Adj. R2 0.024 0.020 0.020 0.018 0.047

This table presents the regression analysis results for acquirers’ cumulative abnormal returns. The dependent variable is acquirers’ cumulative abnormal returns, and the control variables consist of the following: LogMV is the logarithm of the market value of the acquirer, which is measured as the market capitalization (MV) of the acquiring firm the month prior to the acquisition. Stock is a dummy variable that takes the value of one if the deal is financed by 100% stock, and zero otherwise. Public is a dummy variable that takes the value of one if the target firm is listed, and zero otherwise. RS is the relative size of the deal, which is calculated as the ratio of the deal value to the acquirer’s market value. MTBV is the market-to-book value ratio of the bidder as measured the month prior to the acquisition announcement. Domestic is a dummy variable that takes the value of one if the bidder and the target firm are based in the same country, and zero otherwise. Diversifying is a dummy variable that takes the value of one if the first two digits of the SIC code of the acquiring firm are not equal to the first two digits of the SIC code of the target firm, and zero otherwise. The main variable of interest is the BidderFrontierDummy variable, which is a dummy variable that takes the value of one if the acquirer is based in a frontier country and zero otherwise. Model 1 presents results for the overall sample, model 2 for acquisitions of public target firms only, model 3 for acquisitions of private target firms only, model 4 for acquisitions financed with 100% cash, and model 5 for acquisitions financed with 100% stock. Significance levels at 1, 5, and 10% are represented by ***, **, and *, respectively; p-values are reported in parentheses.

The variable of interest in all regressions in Table 15.4 is the dummy variable (BidderFrontierDummy) that takes the value of one if the bidder’s nation is classified as a frontier market and zero otherwise. In the first regression (model 1), in the overall sample, the BidderFrontierDummy variable is negative and significant, which confirms the results of the univariate analysis and indicates that acquirers in frontier markets create less value than acquirers in the rest of the world. Models 2, 3, 4, and 5 provide similar results when regressions are performed in the public, private, cash, and stock acquisitions subsamples.
Table 15.5 further examines acquirer announcement abnormal returns not only based on the acquirer’s nation category but also taking into account the target firm’s nation group. Frontier bidders that acquire targets in frontier markets generate positive but insignificant gains (1.19%). In contrast, frontier bidders that announce acquisitions of target firms in countries like the United States, United Kingdom, or Canada generate negative abnormal returns. Although frontier acquirers do not seem to be able to generate positive abnormal returns upon the announcement of M&A deals, an interesting finding comes out of Table 15.5. Acquirers for the USUKCAN, developed, and emerging markets generate their highest announcement abnormal returns when they bid for target firms in frontier markets. More specifically, USUKCAN bidders generate an average return of 4.17%, which is statistically different from the performance of acquisitions announced from USUKCAN bidders in other developed or emerging markets. The same holds for developed and emerging market bidders that generate 4.35 and 6.46%, respectively.

Table 15.5

Acquirers’ Cumulative Abnormal Returns According to Acquirers’ and Targets’ Development Country Classification

Acquirers’ Region Targets acquired in
Frontier USUKCAN Developed Emerging Frontier–USUKCAN Frontier–Developed Frontier–Emerging
Frontier 1.19% −1.62% 0.91% 0.78% 2.81%* 0.28% 0.41%
p-Value (0.164) (0.211) (0.473) (0.710) (0.065) (0.850) (0.855)
N 72 4 16 12
USUKCAN 4.17%*** 2.44%*** 1.82%*** 3.05%*** 1.73%** 2.35%*** 1.12%
p-Value (0.000) (0.000) (0.000) (0.000) (0.031) (0.004) (0.194)
N 192 32,765 3,148 980
Developed 4.35%*** 2.35%*** 3.28%*** 2.91%*** 2.01%** 1.07% 1.44%
p-Value (0.000) (0.000) (0.000) (0.000) (0.032) (0.244) (0.148)
N 141 1,773 6,145 605
Emerging 6.46%*** 2.39%*** 3.81%*** 5.06%*** 4.07%** 2.65% 1.40%
p-Value (0.000) (0.000) (0.000) (0.000) (0.027) (0.153) (0.418)
N 44 234 187 2,048

This table presents the cumulative abnormal returns for acquirers according to acquirers’ and targets’ development country classifications. Acquirers’ and targets’ nations are divided into four groups (frontier, USUKCAN, developed, and emerging markets) according to each country’s development as described in the data and methodology section in the chapter. Frontier–USUKCAN, frontier–developed, and frontier–emerging indicate the difference in acquirer short-term performance between acquirers based in frontier markets and acquirers based in the USUKCAN, developed, or emerging markets groups, respectively; p-values are reported in parentheses, and the number of acquisitions for each category is reported below that.

There are two potential explanations for these findings. Either bidders from all over the world do not overpay for target firms in frontier markets or they identify opportunities for superior synergy gains to be created. Acquirers from developed and emerging markets could deploy their strategic assets and transfer their home competitive advantage to new, virgin markets which can offer greater growth opportunities. Furthermore, managerial biases are more likely to be present in the acquisition of large public target firms in developed markets rather than in frontier markets.
The reported results in Table 15.5 are further supported by the multivariate regression results as presented in Table 15.6. In Table 15.6, we employ the same control variables as in Table 15.4, and the variables of interest are BidderFrontier–TargetFrontier, BidderUSUKCAN–TargetFrontier, BidderDeveloped–TargetFrontier, and BidderEmerging–TargetFrontier. These are dummy variables that take the value of one if the bidder is based in a frontier market and the target in the frontier, USUKCAN, developed, or emerging group, respectively, and zero otherwise. The BidderFrontier–TargetFrontier in model 1 is negative and insignificant, which indicates that frontier bidders are not generating superior abnormal returns upon the announcement of acquisitions in frontier markets. The coefficients for the other three dummy variables in models 2, 3, and 4 are positive and significant (slightly insignificant in model 3), which shows that acquirers from the USUKCAN, developed, and emerging countries groups generate positive and significant abnormal returns when bidding for target firms in frontier markets even after controlling for a number of factors that have been shown to affect bidder performance.

Table 15.6

Multivariate Regression Analysis of Acquirers’ Cumulative Abnormal Returns for Frontier Acquirers and Targets Across Different Development Country Classification

Model 1 Model 2 Model 3 Model 4
BidderFrontier–TargetFrontier −0.010
p-Value (0.185)
BidderUSUKCAN–TargetFrontier 0.005**
p-Value (0.011)
BidderDeveloped–TargetFrontier 0.015
p-Value (0.203)
BidderEmerging–TargetFrontier 0.051***
p-Value (0.005)
LogMV −0.005*** −0.005*** −0.005*** −0.005***
p-Value (0.002) (0.002) (0.002) (0.002)
Stock 0.011** 0.011** 0.011** 0.011**
p-Value (0.038) (0.038) (0.038) (0.038)
Public −0.020*** −0.020*** −0.020*** −0.020***
p-Value (0.000) (0.000) (0.000) (0.000)
RS 0.000*** 0.000*** 0.000*** 0.000***
p-Value (0.000) (0.000) (0.000) (0.000)
MTBV −0.000*** −0.000*** −0.000*** −0.000***
p-Value (0.000) (0.000) (0.000) (0.000)
Domestic −0.001 −0.001 −0.000 −0.000
p-Value (0.801) (0.822) (0.852) (0.848)
Diversifying −0.001 −0.001 −0.001 −0.001
p-Value (0.425) (0.425) (0.425) (0.444)
Constant 0.056*** 0.056*** 0.056*** 0.056***
p-Value (0.000) (0.000) (0.000) (0.000)
N 44,413 44,413 44,413 44,413
Adj. R2 0.024 0.024 0.024 0.024

This table presents the regression analysis results for frontier acquirers’ cumulative abnormal returns. The dependent variable is acquirers’ cumulative abnormal returns, and the control variables consist of the following: LogMV is the logarithm of the market value of the acquirer, which is measured as the market capitalization (MV) of the acquiring firm the month prior to the acquisition. Stock is a dummy variable that takes the value of one if the deal is financed by 100% stock and zero otherwise. Public is a dummy variable that takes the value of one if the target firms is listed and zero otherwise. RS is the relative size of the deal, which is calculated as the ratio of the deal value to the acquirer’s market value. MTBV is the market-to-book value ratio of the bidder as measure the month prior to the acquisition announcement. Domestic is a dummy variable that takes the value of one if the bidder and the target firm are based in the same country and zero otherwise. Diversifying is a dummy variable that takes the value of one if the first two digits of the SIC code of the acquiring firm are not equal to the first two digits of the SIC code of the target firm, and zero otherwise. The main variables of interest are the BidderFrontier–TargetFrontier, BidderUSUKCAN–TargetFrontier, BidderDeveloped–TargetFrontier, and BidderEmerging–TargetFrontier, which are dummy variables that take the value of one if the target firm belongs to a frontier market and the acquirer is based in a frontier, USUKCAN, developed, or emerging market country group, respectively, and zero otherwise. Significance levels at 1, 5, and 10% are represented by ***, **, and *, respectively; p-values are reported in parentheses.

3.3. Target Firm Performance

Another important question is what the gains to target firms in frontier markets are. Do shareholders of target firms in frontier markets manage to secure higher premiums from bidding firms? Based on the competition hypothesis, target firms are not expected to receive high premiums. This is depicted in the results in Table 15.7, which presents the 3-day cumulative abnormal returns for target firms. Target firms in frontier markets generate 6.76% over the 3-day window. This outcome is significantly and statistically lower than the cumulative abnormal returns generated by target firms in the USUKCAN group (19.71%) and the developed countries group (13.06%). Target firms in emerging countries enjoy positive abnormal returns of similar magnitude (6.08%) to those of target firms in frontier markets.

Table 15.7

Target Cumulative Abnormal Returns According to Targets’ Development Country Classification

All Domestic Crossborder
Frontier 6.76%** 8.21%* 6.30%
p-Value (0.049) (0.056) (0.152)
N 25 6 19
USUKCAN 19.71%*** 19.17%*** 22.09%***
p-Value (0.000) (0.000) (0.000)
N 4625 3774 851
Developed 13.06%*** 12.34%*** 14.10%***
p-Value (0.000) (0.000) (0.000)
N 1140 676 464
Emerging 6.08%*** 4.10%*** 8.92%***
p-Value (0.000) (0.000) (0.000)
N 295 174 121
Front-USUKCAN −12.95%*** −10.96%** −15.79%***
p-Value (0.001) (0.021) (0.002)
Front-developed −6.30%* −4.13% −7.80%*
p-Value (0.069) (0.272) (0.085)
Front-emerging 0.68% 4.11% −2.62%
p-Value (0.842) (0.279) (0.562)

This table presents the cumulative abnormal returns for target firms for the whole sample. Targets’ nations are divided into four groups (frontier, USUKCAN, developed, and emerging markets) according to each country’s development as described in the data and methodology section in the chapter. Deals are classified as domestic if both the bidder and the target firm are based in the same country, and as crossborder if the target firm is located in a country different from that of the bidder. Front-USUKCAN, Front-developed, and Front-emerging indicate the difference in target short-term performance between targets based in frontier markets and targets based in the USUKCAN, developed, and emerging market groups, respectively; p-values are reported in parentheses, and the number of acquisitions for each category is reported below that.

These findings indicate that competition in M&A markets plays a significant role in explaining premiums received by target firms. Target firms in the most competitive group, which is the USUKCAN group, receive the highest premiums while target firms in emerging and frontier markets receive the lowest premiums. Therefore the low acquirers’ abnormal returns are unlikely to be explained as being due to overpayment.

4. Conclusions

The vast academic literature on M&A focuses on the developed economies and in particular the United States and the United Kingdom. This chapter has aimed to shed light on M&A behavior in neglected economies such as frontier markets. We have studied the evolvement of M&A in frontier markets, the short-term bidder performance, and the acquisition premiums received by target firms.
Our results reveal that it is only since 1999 that some merger activity has been observed in frontier markets, with an increasing trend from 2006 until today. We also show that the short-term performance of acquirers in frontier markets is not any different than the performance of acquirers in the rest of the world. Frontier acquirers generate small, insignificant gains for their shareholders. Overpayment is unlikely to be the explanation for not generating superior abnormal returns, as target firms in frontier markets receive the lowest premiums. It is more likely that frontier acquirers lack expertise in creating synergy gains by selected the right target firms.
An interesting finding that emanates from this study is that the highest gains obtained for acquirers from developed countries come from acquisitions in frontier markets. Acquirers from the United States, United Kingdom, Canada, and other developed and emerging countries enjoy high positive abnormal returns when they bid for target firms in frontier markets. Acquirers from developed and emerging markets could deploy their strategic assets and transfer their home competitive advantage to new, virgin markets which can offer greater growth opportunities.

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a In crossborder acquisitions, acquirers’ abnormal returns may depict the benefits emanating from investor protection (Bris and Cabolis, 2008) or information asymmetry effects.

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