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IIMB Management Review (2015) xx, 1-12
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Market response to the internationalization strategies: Evidence from Indian cross-border acquisitions
Neelam Rania*, Surendra S. Yadavb1, P.K. Jainb 2
a Rajiv Gandhi Indian Institute of Management Shillong, Mayurbhanj Complex, Nongthymmai, Shillong 793014, Meghalaya, India
b Department of Management Studies, Indian Institute of Technology Delhi, Vishwakarma Bhawan, Shaheed Jit Singh Marg, Hauz Khas, New Delhi 110016, India
KEYWORDS
Event study; Stock market valuation; Cross-border mergers and acquisitions; India;
Shareholder value; Emerging market; Developed market
Abstract The paper provides evidence that shareholders of acquirer Indian corporations engaging in cross-border transactions experience a statistically significant positive average abnormal return on the announcement day as well as cumulative average abnormal returns over multi-day event windows. The gains are significantly positive and higher for the acquisitions of targets in developed markets. The regression analysis in the paper highlights that cross-border acquisitions of high tech sector target firms in developed markets generate better wealth. Further, relatively larger acquisitions create higher gains.
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Introduction
Internationalization is the process of increasing involvement in international operations across borders (Welch &
* Corresponding author. Tel.: +91 364 2308044 (O), +91 9958934508 (mobile); fax: +91 364 2230041. E-mail addresses: neelam.iitd@gmail.com, nr@iimshillong.in (N. Rani), ssyadav@dms.iitd.ac.in (S.S. Yadav), pkjain@dms.iitd.ac.in (P.K. Jain).
1 Tel.: +9111 26591242; fax: +9111 26862620.2 Tel.: +9111 26591199; fax: +9111 26862620.
Peer-review under responsibility of Indian Institute of Management Bangalore.
Luostarinen, 1988). Internationalization strategy has been a major dimension of the on-going strategy process of majority of emerging multinational firms. Internationalization strategies depend on the dynamism of prevailing conditions in global as well as domestic markets. Internationalization of firms from emerging economies is also motivated by learning objectives that allow these firms to overcome the initial resource hurdles arising due to technological gaps (Li, 2010). Asa result of the liberalization policy since 1991, the Indian economy witnessed dramatic growth, changes in domestic market, and firm activities specifically in relation to their expansion strategies across borders. Indian firms began to develop their existing skills in production capabilities and process R&D by acquiring technology focussed firms in advanced markets. Indian companies are venturing
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abroad in the software, biotechnology, automotive and oil sectors. Companies such as Ranbaxy Laboratories, Dr. Reddy's Laboratories, Wockhardt Ltd, and Nicholas Piramal India Ltd in the pharmaceutical sector; software companies like Tata Consultancy Services, Wipro, in the information technology sector; and Bharat Forge Limited in the automobile sector have successfully adopted internationalization strategies and have become globally competitive. India has transformed its image from being a foreign direct investment (FDI) destination to a major emerging foreign direct investor (Pradhan, 2008).
The strategies adopted by Indian companies for their internationalization are: outsourcing, geographic diversification, joint ventures, and cross-border mergers and acquisitions.
Cross—border acquisitions are an important corporate strategy that enables firms to extend their current businesses to new markets, leverage their current capabilities, and diversify into related markets. In addition, cross—border acquisitions can be an important mechanism for corporate governance convergence (Wang & Xie, 2009). The acquisition based strategy of internationalization adopted by Indian enterprises in recent years by acquiring strategic assets such as technology, known brands, access to customers, and global footprints has resulted in the emergence of new corporate players on the global scene from an emerging economy (Kumar, 2008). Acquisition is the route preferred by Indian corporates for international expansion as compared to organic routes adopted in developed markets. Kumar (2008) documents that motivation for cross-border acquisitions and outward FDI has shifted from market-seeking strategies (during 1970s and 1980s) to strategic asset-seeking strategies recently. He also reports the changing pattern in investment flow to developing countries during 1990s to developed countries in 2000s. Pradhan (2004) analyses the determinants of internationalization of Indian manufacturing firms. He suggests that the production activities of Indian firms abroad are influenced by liberalization initiatives during the 1990s to a certain extent. India's economic environment during liberalization went through many transformations such as removal of restrictions on imports, liberalization of FDI policy and launching of several trade promotion measures. The Indian pharmaceutical and IT industries chose internationalization as an important part of their strategy to succeed in this new liberalised policy regime.
The last two decades have witnessed significant internationalization of firms from emerging markets in terms of their greater participation in international trade, growing outflows of FDI, and a surge in their cross-border mergers and acquisition activity. The internationalization activity of firms from emerging economies may reflect attempts to acquire strategic assets such as new technologies and brands, and to secure access to raw materials and distribution networks. In sum, rather than exploiting existing assets, FDI may reflect attempts to acquire or augment strategic and other assets. AT Kearney's (2008) study of global mergers and acquisitions (M&A) reveals that India has been at the forefront of the M&A activity among developing countries. Indian acquirers accounted for 29 percent of M&A deals by developing market firms during 2002—2007.
In this context, the present paper aims to examine the stock price reaction to the announcements of cross-border
acquisitions and to investigate if cross-border acquisition announcements create value for the shareholders of the acquiring firm in the short-term. The objective of the present paper is to examine the short-term abnormal returns to the shareholders of acquiring companies. Internationalizing with cross-border acquisitions also helps the acquirers to increase operational efficiency and flexibility by exploiting market imperfections and expanding beyond boundaries. However, these factors influence the acquirers differently when the target firms are located in developed markets as against emerging markets (Brouthers & Brouthers, 2000; Krugman, 1991; Shrivastava, 1986). Indian acquirers are expected to experience synergies from acquiring target firms in developed markets by gaining access to the production and new technology know-how and distribution channels. Indian firms are acquiring target firms in established and mature markets to realize synergies of the low-cost base structure. It also facilitates the acquiring firms with the strong management expertise of target firms in developed markets. The target firms in emerging markets offer unique challenges to the acquirers as these markets are at a different level of economic development. Little transparency, and lack of available information tend to hamper the process of due diligence when the target firms are located in emerging markets (Bhagat, Malhotra, & Zhu, 2011; Kose, Steven, Nguyen, & Vasudevan, 2010). To explore the factors influencing the direction and magnitude of market reaction, the disaggregate analysis for returns due to announcement of cross-border acquisitions has also been attempted. The disaggregated analysis has been done in terms of targets in developed and emerging markets. The present paper observes that cross-border acquisitions create value for the shareholders of the acquiring firm. The regression analysis in the paper highlights that cross-border acquisitions of high tech sector target firms in developed markets generate better wealth. Further, relatively larger acquisitions create higher gains.
For better exposition, the paper is organized into six sections. including this section. The second section reviews the previous empirical research work related to cross-border mergers and acquisitions. The third section explains the methodology used. Data collection and sample selection related issues have been delineated in the fourth section. The major findings and concluding observations are contained in the fifth and sixth section respectively.
Review of literature
There is voluminous literature analysing the success of mergers and acquisitions activity. The purpose of this paper is to assess the success of cross-border acquisitions predominantly from the point of view of the shareholders of the acquiring companies. Accordingly, the review of empirical work is primarily focussed on studies measuring the implications of cross-border transactions on the shareholder wealth of the acquiring companies. Many studies have used the event study methodology and found a positive short-term announcement effect of the cross-border M&As on the acquiring firms' stock returns (Harris & Ravenscraft, 1991; Markides & Ittner, 1994; Morck & Yeung, 1992). Contrary to this, studies on acquirers of
domestic firms have found on an average negative or at most insignificant return for the shareholders (Healy, Palepu, & Ruback, 1992; Mitchell & Stafford, 2000; Sirower, 1997; Walker, 2000).
Several studies provide empirical support for reduced abnormal returns from cross-border deals Aw & Chatterjee, 2004; Aybar & Ficici, 2009; Campa & Hernando, 2004; Carnes, Black, & Jandik, 2001; Chatterjee & Aw, 2000 (UK firms); Conn, Cosh, Guest, & Hughes, 2005; Eckbo & Thorburn, 2000 (Canadian firms); Mangold & Lippok, 2008; and Moeller & Schlingemann, 2005). In marked contrast Cakici, Hessel, &Tandon, 1996; Harris & Ravenscraft, 1991; and Kang, 1993 have documented wealth gain for foreign firms acquiring US firms.
Doukas and Travlos (1988) investigated the multinational network hypothesis for US acquiring firms and report that, on an average, there is no significant impact on acquirers' wealth but the acquiring firm experiences significant positive returns when it is entering new markets or new industries and the expansion is into less developed economies where the firm has no existing operation.
A few studies (Conn et al. 2005; Goergen & Renneboog, 2004; Mangold & Lippok, 2008; Moeller & Schlingemann, 2005) have explored the implications of cross-border versus domestic acquisitions for acquirers.
Regional domicile hypothesis considers geographic influence on the performance of acquiring firms, and the market reaction to their strategic activities has been examined by Brouthers & Brouthers, 2000; Krugman, 1991; and Shrivastava, 1986.
Uysal, Kedia, and Panchapagesan (2008) examine the impact of geographical proximity on the acquisition decisions of US public firms from 1990 to 2003. They argue that information advantages facilitate acquisition of targets that, on average, create higher overall return.
Recently, Kose et al., (2010); Zhu (2011); Zhu, Jog, and Otchere (2011) and Bhagat et al. (2011) have examined the wealth implications of cross-border acquisitions in a multi country context. Gubbi, Aulakh, Ray, Sarkar, and Chittoor (2010); Karels, Lawrence, and Yu (2011); Zhu and Malhotra (2008) observe positive returns for cross-border acquisitions by emerging market firms.
Geographical diversification is one of the enablers of the benefits of cross-border acquisitions that enables acquiring firms to internationalize and use their strategic advantages in overseas markets. The benefits of inter-country diversification are not the same for all the international markets in which the acquiring firm acquires target firms. Regional domicile hypothesis considers geographic influence on the performance of acquiring firms. A disaggregated analysis has been conducted on the basis of geographic origin of target firms to examine the performance of the acquirers of cross-border acquisitions. The sample of cross-border acquisition has been segregated for target firms in developed markets and emerging markets.
A developed market is a country that is most developed in terms of its economy and capital markets. In this paper, developed economies are defined as those that are classified as upper-income economies by the World Bank following Ghosh, Gulde, and Wolf (2003). Further, the country has openness to foreign ownership, ease of capital movement, and efficiency of market institutions, along with high income.
In this paper, emerging markets are defined using the Morgan Stanley Capital International (MSCI) classification following Rogoff, Husain, Mody, Brooks, and Oomes (2004), which designates a country as an emerging market according to a number of factors such as GDP per capita, local government regulations, perceived investment risk, foreign ownership limits and capital controls, and other factors. The main motivation for using this classification is that it captures the notion that emerging countries have access to international capital markets. All other markets constitute the emerging market group.
Despite a considerable volume of research on corporate mergers and acquisitions, results are still inconclusive regarding the valuation effects of acquisitions on acquiring companies' share price. This paper adds value to the existing literature, as many influencing factors in cross-border acquisitions by emerging market firms are substantially different from those in the developed market. Following regional domicile hypothesis, this work contributes to the extant literature by conducting a disaggregated analysis between acquisitions of targets in developed markets and emerging markets. The present paper is related to recent work by Gubbi et al. (2010) but we focus on the geographic impact and conduct a disaggregated analysis on two groups. We have used a variety of tests to check the robustness of the statistical significance of the event study results.
Methodology
The event study methodology is used to examine short-term stock price reaction to the announcements of cross-border acquisitions.
We define the announcement day as the day when the stock exchange is informed about the board approval of the M&A deal. The dates are manually verified from the archives of corporate announcements of the stock exchange. Estimation window of 255 (-290, -36) days has been used.
The cumulative abnormal returns over alternate windows have been also calculated in order to account for:
1) early share price reactions induced by the anticipation of the stock market of an upcoming announcement before the event, and
2) potentially slow information processing after the event.
We have observed the abnormal return over (-20,-2), (-5,0), (-1,0), (0, 0), (0,+1), (0,+5), (+2,+20), (-1,+1), (-2,+2),(-5,+5),(-10,+10) and (-20,+20) to capture the leakage effect. In addition, the abnormal returns are observed during an expanded event window of (-20, +60) to understand the impact of information flow that happened over a period of time. The dates have been manually verified from the archives of corporate announcements of the Bombay Stock Exchange (BSE) to ascertain the clean period data. It has been manually checked that there is no contamination of information and confounding event during the event window.
Stock returns move in response to several firm or market-specific factors. The key issue in event studies is what portion of the price movement is actually caused by
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N. Rani et al.
the event of interest. In other words, we have to extract the impact of the one particular event on stock returns. This leads to the concept of abnormal returns. The abnormal returns of the jth stock (ARjt) is obtained by subtracting the normal or expected returns in the absence of the event (E(Rjt)), from the actual return in the event period, (Rjt):
ARjt = Rjt
The market model approach relates the return of a security to the return of the market portfolio in the following manner and the market model equation is expressed as follows:
Rjt = aj + ßjRmt + ejt, where t= - 290. - 36
where aj is a constant term for the j stock, bj is the market beta of the jth stock, Rmt is the market returns, and ejt is an error term.
The parameters of the model are estimated by using the time-series data from the estimation period that precedes each individual announcement. The estimated parameters are then used in the calculation of abnormal returns for each day in the event window. The daily excess return of firm j for the day t (ARjt) is estimated from actual returns during the event period and the estimated coefficients from the estimation period:
ARjt = Rjt - (b + ßRmt
where t= -20. + 20
The average abnormal return (AARt) for each day in the event window is calculated as follows:
AARt=„j: ar
where N is the number of firms.
The cumulative abnormal returns (CARs) are daily abnormal returns cumulated over part of the event period. Over an interval of two or more trading days beginning with day T1 and ending with day T2, the cumulative average abnormal return (CAAR) is
CAART1,T2=nE EARjt
j = 1 t=r,
The null hypotheses being tested are: H01: The abnormal return on the announcement of cross-border acquisition is zero.
H02: The cumulative average abnormal return (CAAR) for the event window period on the announcements of cross-border acquisitions is zero.
Following Campbell, Cowan, and Salotti (2010) we use two parametric and two non-parametric test statistics to test for the significance of average and cumulative average abnormal returns over the event period. The four tests are:
1. Crude dependence adjustment (CDA) test (Brown & Warner, 1980)
2. Standardized cross-sectional (SCS) test (Boehmer, Masumeci, & Poulsen, 1991)
3. Generalized sign (GSign Z) test (Cowan, 1992)
4. Rank test (Corrado, 1989)
Crude dependence adjustment test
The CDA test incorporates the sample time-series standard deviation. Brown and Warner (1980) describe the test as featuring a ''crude dependence adjustment". That is, the test compensates for potential dependence of returns across security-events by estimating the standard deviation using the time series of sample mean returns from the estimation period. The CDA test uses a single variance estimate for the entire sample. Therefore, the time series standard test does not take account of the unequal return variances across securities. This test avoids the potential problem of cross-sectional correlation of security return. To account for the dependence across firms' average residuals, in event time, Brown and Warner (1980) suggest that the standard deviation of average residuals should be estimated from the time series of the average abnormal returns over the estimation period. The estimated variance of AARt is
ß2 =E-i6-290 {AARt - AAR) ßAAR 254
where the market model parameters are estimated over the estimation period of 255 days and
aarj: i-™ AARt
the test statistics for day t in event time is AARt
The CDA test for the null hypothesis that CAAR = 0 is
(T2 - T1 + 1 föaar
Standardized cross-sectional test
The standardized cross-sectional test developed by Boehmer et al. (1991) incorporates the information from both estimation and the event period. The event period abnormal returns are first standardized by estimation period standard deviation. The cross-sectional technique is then applied to the standardized abnormal returns.
The standardized abnormal return of security j for day t (SARjt) is defined as abnormal returns of security j divided by its estimated standard deviation as in equation (10)
SARjt =
where 5AB =
Z\ (AR*)2
' + d,
k-T„ (rmk-
Total standardized abnormal return (TSAR) has been obtained by summing SARjt across the sample:
TSARt = SARjt-
For day t in the event period, the test statistic is
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Market response to the internationalization
Zt--1-
N>(ÔsARt )
1 * ( 1 N \
d2ARtSARt - nE SARjt
' = 1 \ j=1 /
This correction for serial correlation can be extended to multi-period window as:
Define the standardized cumulative abnormal return for stock j as
scart,. t,. = where
VdCART1j Tj J
VTOe AR2
Oj - 2
L ( ET= T, Rmt - LjRm I
i + ii+A_Z_
' + Oj + O / . x 2
XV= , Rmk — Rm
where L is the length of the event period in trading days, L = T2-T-i+1. Dj is the number of non-missing trading day returns in the D-day interval TDb through TDe used to estimate the parameter of the firm j.
Then the SCS test for the null hypothesis that CAAR = 0 is
£n=i scar
T1j ■T2j
R/ ^ (T1j ;T2j)
1 N ( , N \
= N—1SCARTi;T2i — N g SCj
(T,j,Ty) N - 1^1 '1i''2i N-This test statistic allows for event-induced variance. Generalized sign test
The generalized sign test compares the proportion of positive abnormal returns around an event to the proportion from a period unaffected by the event. The generalized sign test adjusts for the fraction of positive abnormal returns in the estimation period instead of assuming 0.5 (Cowan, 2007). The null and alternative hypotheses of interest are: The null hypothesis for generalized sign test is that fraction of positive returns is the same as in the estimation period.
The actual test uses the normal approximation to the binomial distribution. To implement this test, we first need to determine the proportion of stocks in the sample that should have non-negative abnormal returns under the null hypothesis of no abnormal performance. The value for the null is estimated as the average fraction of stocks with nonnegative abnormal returns in the estimation period. If abnormal returns are independent across securities, under the null hypothesis the number of non-negative values of abnormal returns has a binomial distribution with parameter p.
The generalized sign test examines whether the number of stocks with positive cumulative abnormal returns in the event window exceeds the number expected in the absence of abnormal performance. The number expected is based on the fraction of positive abnormal returns in the 255 day estimation period,
1 n 1 255
p=n£255 £ S.t
j=1 t=1
Sjt= <1
if ARjt > 0
0 otherwise
The following statistic has an approximate unit normal distribution with parameterp:
w — np
\/np (1 — P)
Where w is the number of stocks in the event window for which the cumulative abnormal return is positive.
The alternative hypothesis, for any level of abnormal performance, is that the proportion is different from that prior.
Rank test
The rank test (Corrado, 1989) procedure considers the combined estimation period and event period as a single set of returns, and assigns a rank to each daily for each firm. The rank statistic for day zero is:
N g kj°)—*]/sk
where kj0 is the rank of security-event j's day zero abnormal return in security-event j's combined 255-day estimation period and 19-day event period (in case of (+2,+20) time series, k is the expected rank defined below, and sk is the time-series standard deviation of the sample mean abnormal return ranks.
Each security-event's non-missing returns have been ranked with the lowest rank being one. Ej represents the number of non-missing returns of security j in the event period; if there is no missing return, Ej Z E Z post —pre +1 and D = length of estimation window. The mean rank across the combined estimation and event period is
O + E +1 2
The rank test statistic for the event window composed of days T1 and T2 is
Zrank = (T, — T1 + 1)J<
EO+KKt — K) /O + E
KT1 T2 = t,— t,+i ^ t= t the n securities and T2
ET= T nSji=1Kjt is the average rank across T +1 days of the event window and
CART1;T,
Kt = (1 /n)Yjj=1 Kjt is the average rank across n securities on day t of the D + E day combined estimation and event period.
Data collection and sample selection
This study is based on acquisitions which were announced by Indian corporations, listed on the Bombay Stock Exchange, during the period January 2003 to December 2008. Thomson SDC Platinum Mergers and Acquisitions Database has been used for the data. The announcement dates have been verified from the archives of corporate announcements on the Bombay Stock Exchange.
Sample selection procedure
All transactions that fulfil the following conditions have been selected:
• Companies listed on the Bombay Stock Exchange
• Mergers and acquisitions of controlling stake and above announced and completed between January 2003 and December 2008.
• Acquisitions in the financial sector are excluded from the sample. This is because of the different nature of assets and liabilities of financial firms and the different financial reporting of these companies.
• In order to remain in the sample, the shares of the acquiring company must have been traded for at least 185 days.
• To measure the effect of each acquisition properly, an acquisition that followed within a year of an earlier one are excluded from the sample. If a firm has more than one acquisition within a year, then only the first acquisition is considered.
• To avoid possible information contamination or the confounding effect, the firms that undertake any significant event within twenty days prior and after the acquisition are excluded from the sample. Table 1 contains the details of selection of the final sample.
The final sample consists of 256 cross-border acquisitions of which 218 target firms were located in developed markets, 35 target firms in emerging markets, and 3 in developing markets as per World Bank classification. Fiji, Uzbekistan and Zambia are developing markets as per World Bank classification and are included as emerging markets in this paper. Table 2 reveals the geographic distribution of the sample.
Table 1 Details of sample.
Total number of cross-border announcements 1257
{Pending, rumours, withdrawn and denial 341
of news for acquisitions
Acquisitions of business, assets, divisions 241
and minor stakes
Acquisitions by financial sector companies 43
Acquisitions by unlisted companies and 167
investor groups
Trading data not available 65
Acquisition in the same year 21
Confounding events 86
More than one type of acquisition in one 12
announcement
Multiple acquisitions in one announcement} 25
Selected for the study (1257-1001) 256
Source: Thompson SDC Database, 2003-2008.
Table 2 Geographical distribution of cross-border acqui-
sitions by Indian MNCs (2003-08).
Country Type No.
Argentina Emerging 1
Australia Developed 8
Austria Developed 2
Belgium Developed 2
Bermuda Developed 1
Brazil Emerging 4
Canada Developed 6
China Emerging 1
Colombia Emerging 1
Czech Republic Emerging 4
Denmark Developed 1
Dubai Developed 1
Fijia 1
France Developed 8
Germany Developed 20
Greece Developed 1
Hong Kong Developed 1
Ireland Developed 2
Israel Emerging 1
Italy Developed 6
Japan Developed 2
Malaysia Emerging 3
Netherlands Developed 7
Nigeria Emerging 1
Philippines Emerging 1
Poland Emerging 1
Portugal Developed 1
Romania Emerging 3
Russia Emerging 1
Sharjah Emerging 1
Singapore Developed 9
South Africa Emerging 7
South Korea Emerging 1
Spain Developed 3
Sweden Developed 4
Switzerland Developed 5
Thailand Emerging 3
UK Developed 29
USA Developed 98
Uzbekistana 1
Venezuela Emerging 1
Wrexham Developed 1
Zambiaa 1
Total 256
a Developing markets as per World Bank classification, included in emerging markets in this paper.
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Market response to the internationalization 7
Empirical results
Market response to announcements of cross-border acquisitions
Table 3 reports the abnormal returns to the acquirer shareholders on the announcement day and multi-period event windows for cross-border M&A. It contains average abnormal return, cumulative average abnormal return, and median abnormal return. Additionally, it presents proportion of positive and negative average abnormal return. It also provides the results of parametric and non-parametric tests conducted to measure statistical significance for average abnormal returns and cumulative average abnormal returns.
It is evident from the table that acquirer shareholders earn average abnormal returns of 1.60% on the announcement day for cross-border M&A; the value is significant at 1% percent. The proportion of stocks having positive return on the announcement day is more than 66%. The proportion of stocks having positive return is significant at 1%. Median abnormal returns are 1.15%.
Relevant data contained in Table 3 also shows that the acquirer shareholders experience CAAR of 2.74% and 2.64% during event windows of 11 days (-5, +5) and 5 days (-2, +2) respectively. The CAAR during pre-event window of 19 days (-20, -2) is 2.22%. The CAAR during the short -event window of two days (-1, 0) and three days (-1, +1) is 2.07% and 2.31% respectively. The maximum CAAR of almost three per cent (2.97%) is observed during pre-event window of six days (-5, 0). All these results are significant at 1%. One notable finding is that the positive CAAR along with impressive precision-weighted CAAR sustain for longer event windows of twenty one days (-10, +10) and forty one days (-20, +20). But acquisitions reduce wealth significantly during post-event window of 19 days (+2, +20). The negative abnormal returns are 2.79% (significant at 1%) for the post-event window (+2, +20). However, the positive
Average abnormal returns of cross-border acquisitions
Figure 1 AAR of cross-border M&A over event window (-20, +20).
returns of marginal 1.03% are observed during the longer event window (-20, +60). However, the results are marginally significant at 5%.
Figs. 1 and 2 display the trend of AAR and CAAR during pre and post windows (-20, +20). The graph shows that abnormal returns increase up to the tenth day postacquisition and then starts falling but remains positive during the event window.
Market response to announcements of acquisitions of target firms in developed markets
Table 4 illustrates the impact of announcements of cross-border acquisitions of target firms located in developed markets across various event windows by reporting the CAAR values and their corresponding test statistic values. The CAAR values across various pre-announcement event windows (-20, -2) and (-5, 0) are 1.65% and 2.92% respectively. The CAAR values for the window (-5, 0) is maximum and significant at 1%level. This announcement effect during the event windows (-1, 0), (0, +1), (-1, +1) (-2, +2) and (-5, +5) has been interpreted by analysing the CAAR values of 2.15%, 1.89%, 2.39%, 2.81% and 2.85% respectively. These values are highly significant at 1%
Table 3 Abnormal returns to shareholders of acquiring firms (cross-border M&A, N = 256) on announcement day and during multi-days event windows, 2003—2008.
Event window Average abnormal return Positive: Negative Parametric tests Non-parametric tests
Cumulative Median CDA t SCS Z GSign Z Rank Z
(—20,—2) 2.22% 1.65% 145:111 2.453* 2.692** 3.586** 2.525*
(—5,0) 2.97% 1.70% 159:97 5.823** 5.898** 5.344** 5.610**
(—1,0) 2.07% 1.14% 170:86 7.024** 5.972** 6.724** 6.379**
(0, 0) 1.60% 1.15% 168:88 7.704** 6.324** 6.473** 7.059**
(0,+1) 1.84% 1.12% 165:91 6.266** 5.390** 6.097** 5.508**
(0,+5) 1.38% 0.48% 138:118 2.709** 2.930** 2.708** 2.288*
(+2,+20) —2.79% —2.93% 101:155 —3.079** —3.031** — 1.936 —2.868**
(—1,+1) 2.31% 1.61% 163:93 6.403** 5.540** 5.846** 5.630**
(—2,+2) 2.64% 1.65% 163:93 5.681** 5.428** 5.846** 5.243**
(—5,+5) 2.74% 2.06% 152:104 3.978** 4.209** 4.465** 3.705**
(—10,+10) 2.06% 1.44% 145:111 2.162* 2.414* 3.586** 1.531
(—20,+20) 1.74% 1.55% 146:110 1.306 1.724 3.712** 1.29
(—20,+60) 1.03% 0.96% 142:114 1.024 1.46 2.244* 1.34
* and ** denote significance at 5% and 1%, respectively.
Cumulative average abnormal returns of cross-border acquisitions
5 « 3
3 2 et
-20-18-16-14-12-10-8 -6 -4 -2 0 2 4 6 8 10 12 14 16 18 20 Event window (days)
Figure 2 CAAR of cross-border M&A over event window (-20, +20).
- AAR of cross-border acquisitions of target firms in developed markets
2 1.5 g 1 1 0.5
"fD A « 0
-0.5 -1
OOOO^t<NOOOO^t(NO<N
Event window (days)
Figure 3 AAR over event window (-20, +20) of cross-border acquisitions in developed markets.
indicating that null hypothesis of zero CAAR has been rejected.
During the post-announcement windows (+2, +5), (+2, +10), (+2, +15) and (+2, +20), there is a consistent fall in the CAAR values indicating that the positive reaction is almost nullified by the negative reaction (the peak value of CAAR declined from 4.14% on day t(+3) to 1.23% on day t(+20)). The CAAR values of 1.81% and 1.21% for the event window (-10, +10), and (-20, +20), though positive, are not statistically significant. The graph portrayed in Fig. 3 depicts that AAR is positive for twenty days during the event window. Fig. 4 corroborates the conclusion that strong positive market reaction generates high abnormal returns and after announcement, starts falling and remains positive during the entire event window.
Market response to announcements of acquisitions of target firms in emerging markets
Table 5 illustrates the impact of announcements of cross-border acquisitions of target firms in emerging markets. The CAAR values across various pre-announcement event windows (-20, -2) and (-5, 0) are 5.52% and 1.57% respectively. The CAAR values are significant at 5% level.
CAAR of cross-border acquisitions of target firms in developed markets
Event window (days)
Figure 4 CAAR over event window (-20, +20) of cross-border acquisitions in developed markets.
This announcement effect during the event windows (-1, 0), (0, +1), (-1, +1) has been interpreted by analysing the CAAR values of 1.61%, 1.57% and 1.84%, respectively. These values are significant at 5% indicating that null hypothesis of zero CAAR has been rejected. During the post-announcement windows (+2, +20), there is a little decline in the CAAR values indicating that the positive reaction almost sustains during the event window (the peak value of CAAR declined from 7.36% on day t(+1) to 4.76% on day t(+20)). The CAAR values of 1.67%, 2.11%, 3.47%, and 4.75% for the event window (-2, +2) (-5, +5) (-10, +10) and (-20, +20), though positive, are not statistically
Table 4 Abnormal returns to shareholders of acquiring firms of cross-border acquisitions (developed markets N = 218) on announcement day and during multi-days event windows, 2003-2008.
Event window Average abnormal return Positive: Negative Parametric tests Non-parametric tests
Cumulative Median CDAt SCS Z GSign Z Rank Z
(-20,-2) 1.65% 1.09% 118:100 1.608 1.898 2.572* 1.506
(-5,0) 2.92% 1.83% 136:82 5.069** 5.079** 5.021** 4.629
(-1,0) 2.15% 1.14% 147:71 6.449** 5.653** 6.517** 5.987
(0, 0) 1.65% 1.20% 145:73 7.004** 5.822** 6.245** 6.517
(0,+1) 1.89% 1.31% 140:78 5.683** 4.987** 5.565** 5.080
(0,+5) 1.58% 0.51% 118:100 2.745** 3.087** 2.572* 2.418
(+2,+20) -2.82% -2.93% 85:133 -2.753** -2.561* -1.916 -2.266
(-1,+1) 2.39% 1.83% 139:79 5.861** 5.241** 5.429** 5.274
(-2,+2) 2.81% 1.80% 140:78 5.345** 5.334** 5.565** 4.933
(-5,+5) 2.85% 2.24% 129:89 3.659** 3.967** 4.069** 3.240'
(-10,+10) 1.81% 1.46% 124:94 1.684 1.989* 3.389** 1.101
(-20,+20) 1.21% 1.42% 121:97 0.806 1.274 2.981** 0.909
(-20,+60) 1.14% 0.92% 120:98 1.682 1.542 2.141* 1.67
* and "denote significance at 5% and 1% respectively.
Table 5 Abnormal returns to shareholders of acquiring firms of cross-border acquisitions (emerging markets N = 38) on announcement day and during multi-days event windows, 2003—2008.
Event window Average abnormal return Positive: Negative Parametric tests Non-parametric tests
Cumulative Median CDAt SCS Z GSign Z Rank Z
(—20,—2) 5.52% 3.01% 27:11 2.969** 2.113* 3.147** 3.191*
(—5,0) 3.23% 1.57% 23:15 3.089** 3.739** 1.844 3.715
(—1,0) 1.61% 1.08% 23:15 2.671** 1.940 1.844 2.328
(0, 0) 1.57% 0.59% 25:13 2.603** 2.052* 2.495* 2.245*
(0,+1) 1.34% 0.80% 23:15 3.148** 2.584** 1.844 2.863
(0,+5) 0.23% 0.04% 20:18 0.215 0.048 0.867 0.123
(+2,+20) —2.61% —3.12% 16:22 —1.406 —1.812 —0.436 —2.169*
(—1,+1) 1.84% 1.18% 24:14 2.489* 1.788 2.170* 2.080
(-2,+2) 1.67% 1.03% 23:15 1.751 1.312 1.844 1.880
(—5,+5) 2.11% 1.52% 23:15 1.492 1.391 1.844 1.971
(—10,+10) 3.47% 1.02% 21:17 1.773 1.596 1.192 1.437
(—20,+20) 4.75% 1.86% 25:13 1.737 1.543 2.495* 1.258
(—20,+60) 1.26% 0.88% 22: 16 1.564 1.628 2.12* 1.48
* and **denote significance at 5% and 1% respectively.
significant. The graph portrayed in Fig. 5 depicts that AAR is positive for 20 days during the event window. Fig. 6 corroborates the conclusion that strong positive market reaction for target firms located in emerging markets also generates positive abnormal returns and remains positive during the entire event window.
Analysis of determinants on acquiring shareholders' wealth in cross-border acquisitions
In addition to the event study, regression analysis has been carried out to examine the impact of specific bid factors on returns. There are 67 acquisitions in which the deal value is undisclosed. This reduces the sample size for final analysis. The number of observations used is lower (N = 189) in the final analysis due to availability of information and missing bid-specific values. The final sample consisted of 189 target firms, out of which 160 target firms are in developed markets and 29 in emerging markets. The following firm-specific characteristics have been used in the regression model.
Two regression models have been estimated in the paper.
Model 1:
CAARi = f + b LogMVA, + b2LogRSize,
+ b3HighTechi + e, (
Model 2:
CAARi = f + bi LogMVA, + b2LogRSizei + /33HighTechi
+ b4DeVi + e, ( )
Table 6 describes the results of ordinary least square regression. The results presented consist of impact of various determinants on the shareholders wealth of the acquiring company in cross-border acquisitions. The dependent variable is CAAR during event window (-5, +5). The range of variance inflation factor (VIF) varies from 1.07 to 3.23. The mean VIF value ( = 2.12) indicates no serious issue with the multi-collinearity among variables. Further,
Acquirer size: Relative size: High tech:
Target firms in developed markets
Size of the acquiring company has been used as Log of Market Value of the acquirer (LogMVA). Value of deal/market value of the acquirer. Log of Relative Size (LogRSize) is used "1" if the target is defined as High Tech by SDC Thomson Financial Database on M&A and "0" otherwise. The final sample consists of acquisitions 113 target firms in high tech sector and 76 in others
"1" if the target firm is in developed (Dev) market and "0" if the target firm is in emerging market.
The relative size of the deal is included as the log of the ratio of the transaction value to the market value of the acquirer following Uysal et al. (2008); Asquith, Bruner, and Mullins (1983); Jarrell and Poulsen (1989); Kang (1993); Fuller, Netter, and Stegemoller (2002).
heteroscedascticity-consistent standard errors have been used to compute t-statistics.
The coefficient of variable relative size is positive and statistically significant which implies that shareholders of Indian acquiring firms experience superior gains when
+ MODEL
10 N.Rani et al.
—•—AAR of cross-border acquisitions of target firms in emerging markets
Figure 5 CAAR over event window (-20, +20) of cross-border acquisitions of target firms in emerging markets.
CAAR of cross-border acquisitions of target firms in emerging markets
Figure 6 CAAR over event window (-20, +20) of cross-border acquisitions of target firms in emerging markets.
acquisitions are of higher deal size. This result is consistent with the findings reported by Bhagat et al. (2011).
The coefficient of the variable high-tech is positive and statistically significant which reveals that the cross-border acquisitions of target firms in high tech sector create superior wealth gains. The relatively higher gains to the firms in high tech sector imply that Indian acquiring firms have increasingly used acquisitions as a means to tap into strategic resources across borders, particularly in developed economies that are viewed as sources of innovation. Moreover, the expected gains from internalizing host country market imperfections are also discounted into higher value of the acquiring firms. Cross-border acquisitions provide synergies related to internationalization of both tangible and intangible resources.
Conclusions
The objective of this paper is to review the recent changing pattern of internationalization strategies of firms in emerging markets in general and India in particular. A shift from asset exploitation to asset-seeking has been noticed.
The present paper measures the market response to the announcement of cross-border M&A. The paper aims to investigate whether cross-border mergers and acquisitions create value and whether the value effect differs for targets in developed markets and emerging markets. This paper focusses on the value effects to shareholders of the acquiring company. An event study methodology has been used to explore the short-term shareholder wealth effects of the Indian acquirers during the period 2003 to 2008. This paper finds evidence that shareholders of acquirer Indian corporations engaging in cross-border transactions experience a statistically significant positive abnormal return on the announcement day as well as statistically cumulative abnormal returns over multi-day event windows.
The empirical findings suggest that cross-border transactions result in wealth creation for shareholders of the Indian acquirers. The gains are significantly positive for the acquisitions of targets in developed markets as well as emerging markets. Regression analysis reveals that the value creation is higher in case of acquisition of relatively larger deals involving target firms of high tech sector in developed markets.
Cross-border acquisitions may generate benefits from geographical diversifications when transactions bring value from intangible assets, global brands, information technology, and R&D based knowledge. The finding that cross-border acquisitions of target firms in developed markets and in the high-tech sector create higher value is consistent with Eun, Kolodny, and Scheraga (1996); Conn et al. (2005); Pyykko (2009); Gubbi et al., (2010); and Kohli and Mann (2012). Indian companies use the acquisition route to obtain strategic resources in an attempt to strengthen their international competitive edge. Asset-seeking acquisitions, therefore, have been increasingly used as a means for Indian acquirers to tap into strategic resources across borders, particularly in developed economies that are viewed as sources of innovation. Moreover, the expected gains from internalizing host country market imperfections are also discounted into higher value of the acquiring firms. Cross-
Table 6 Results of OLS regression model with CAAR (11 days event window) as dependent variable.
Model 1 Model 2
Intercept 3.524 (2.41) 4.637* (2.34)
LogMVA -0.05 (1.62) -0.04 (1.56)
LogRSize 1.31** (4.76) 1.19** (5.13)
HighTech 1.83 (1.98*) 1.67 (2.12*)
Dev 1.47 (2.35*)
F statistics 6.42** 6.74**
Adjusted R Square 0.14 0.15
N 189 189
* and "denote significance at 5% and 1% respectively.
border acquisitions provide synergies related to internationalization of both tangible and intangible resources. The stock market values these transactions as it takes time to develop these resources internally. Acquisitions of global brands, and access to production technology and distribution channels offer an international competitive edge to Indian acquirers.
These findings have important implications for Indian acquiring firm managers, who may view the initial increase in stock price around announcement dates as a signal for positive shareholder response. The acquisitions of strategic assets may bring significant competitive advantages to Indian acquirers, thereby enhancing global competitiveness also perceived by stock market through positive market reaction. Further, with a more complete understanding of asset-seeking motive, Indian acquiring firms may consider the strategy of acquiring strategic assets to enhance competitiveness.
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