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Military-Madrasa-Mullah Complex 263
India Quarterly, 66, 2 (2010): 133–149
A Global Threat 263
Article
A Wave of Mergers and
Acquisitions: Are Indian
Banks Going Up a Blind Alley?
Neha Kalra
Shaveta Gupta
Rajesh Bagga
Abstract
Mergersandacquisitionsarestrategicdecisionstakenformaximizationofacompany’sgrowth.But
thepointofthematteris,howfardoestheempiricalevidencesupportthisnotion?Anexamination
ofthe existing literature suggestedno conclusive evidence aboutthe impact of M&Aon corporate
performance.Therefore,thisarticleinvestigatesthemergersintheIndianBankingindustrytofindout
whetherIndianbankshaveachievedperformanceefficiencyduringthepost-mergerperiodnamelyin
theareasofprofitability,liquidity,shareholderswealthandsharepricevolatility.Basically,twomethods
areemployedtocompare pre-post merger performance,ofIndianbanksfrom 2000 to 2011. First,
pairedsamplet-testdeterminesthesignificantdifferencesinfinancialperformancebeforeandafterthe
mergeractivity,andsecond,astandardeventstudyapproachexaminestheannouncementeffectof
mergersandacquisitionsonsharepricevolatility(eventwindowof120days)andtheefficiencyofthe
Indianstockmarket.
Anoverallassessment(accountingperformancemeasuresandstockmarketreaction)ofmergers
inIndianbankingsectorindicatesabsenceofanysignificantimpactontheirfinancialperformance.The
mergerinIndianbanksonlybringssignificantimprovementinEPSandMarketvaluetobookvalueof
equity.Thestudyexposedthefactthatthestockpricesreactsignificantlytomergerannouncements
intheshortperiod(30dayspre-andpost-mergerannouncement)butnotinlongperiodwhichalso
indicatedthatIndianstockmarketisefficientinthelong-run.
Keywords
Merger, profitability,liquidity, shareholders wealth,share price volatility,Kolmogorov-Smirnovtest,
pairedt-test,eventstudymethodology
Neha KalraisAssistantProfessoratApeejayInstituteofManagementTechnicalCampus,Jalandhar,Punjab,India.
E-mail:neha_kalra_16@yahoo.co.in
Shaveta Gupta isAssistantProfessoratApeejayInstituteofManagementTechnicalCampus,Jalandhar,Punjab,
India.E-mail:shaveta_gupta@rediffmail.com
Rajesh Bagga is AssistantProfessoratApeejayInstitute of ManagementTechnicalCampus,Jalandhar,Punjab,
India.E-mail:rajesh.bagga@rediffmail.com
GlobalBusinessReview
14(2)263–282
©2013IMI
SAGEPublications
LosAngeles,London,
NewDelhi,Singapore,
WashingtonDC
DOI:10.1177/0972150913477470
http://gbr.sagepub.com
Global Business Review, 14, 2 (2013): 263–282
264 Neha Kalra, Shaveta Gupta and Rajesh Bagga
Introduction
Mergers and acquisitions (M&A) are one of the most important phenomena shaping the market. Since
the middle of 1960s, when the concentration process reached a new climax and the trade in firms became
vivid, many studies have extensively been carried out on M&As. Economists and other social scientists,
managers and business consultants took an interest in the phenomenon of changing corporate ownership
(Bouwens, 2007). In the researches that have taken place in the past few years, the focus shifted from
predicting ex ante M&A performance towards post M&A phenomena (Dauber, 2009). Mergers and
acquisitions strategy is at the forefront for organizations trying to have competitive advantage over its
competitors.
In today’s competitive and turbulent corporate world, the main objective of firms is to maximize
profits and enhance shareholders’ wealth. For this purpose, organizations have many options available
like launching new products and services, expanding its operations and focusing on cost reduction.
Internal growth can be achieved by introducing new products, however external growth can be achieved
by entering into M&As (Ghosh and Das, 2003). Mergers and acquisitions have become an important
medium to expand and gain access to resources which would enable the company to compete on a global
scale (Yadav and Kumar, 2005). However there have been instances where M&As are entered into for
non-value maximizing reasons (Malatesta, 1983; Roll, 1986).
Different theories of merger motives emphasize the exclusive role of big business in this field
(Schenk, 1994). Most of the researchers in the past have explored the path of evaluating the mergers
by evaluating share prices. Nevertheless several theories on merger consequences can be disting-
uished, ranging from efficiency theory and monopoly theory to raider theory, empire-building theory
and valuation theory. All these theories focused on shareholder’s value and the transfer of wealth
(Trautwein, 1990).
Factors affecting mergers change with the changing legal, political, economic and social environ-
ments (Kaushal, 1995). The literature has identified two common reasons, i.e., efficiency gain and stra-
tegic rationale. The theories based on synergy and efficiency argue in favour of mergers, whereas theories
based on agency cost, free cash flow conflict, and managerial incentive vote against mergers (Anand and
Singh, 2008). Soludo (2004) opined that M&As are aimed at achieving cost efficiency through econo-
mies of scale. There are obvious potential benefits from mergers. Cost savings, revenue enhancement,
risk diversification, market power and weak corporate control can motivate bank mergers and acquisi-
tions. The effect of a merger on the partners’ profitability is measured by comparing book value measures
of profitability before and after the merger (Neary, 2004). Meeks and Meeks (1981) showed that these
measures can be biased. But the cost involved in it can have an impact on these benefits. Diseconomies
of mergers stemming from the difficulties in monitoring a larger firm, problems in integration of informa-
tion technology or cultural conflicts can reduce potential merger benefits (Dunis and Klein, 2002).
Williamson (1968) was the first to stress the existence of a trade-off between such cost efficiencies and
the loss due to the decrease in industry output and the consequent price rise.
For reasons either of control or knowledge, M&As are a vehicle for selling or acquiring bundles of
resources in highly imperfect resource markets (Mahoney and Pandian, 1992; Mitchell, 1994; Wernerfelt,
1984). Acquisitions enhance performance by allowing businesses to obtain preferential access to
resources that cannot be purchased in a competitive market (Barney, 1986; Dierickx and Cool, 1989;
Peteraf, 1993). As a result, mergers can create value and enhance revenues.
Global Business Review, 14, 2 (2013): 263–282
Are Indian Banks Going Up a Blind Alley? 265
The new industrial policy adopted by the Government of India has allowed business houses to under-
take any programme of expansion either by entering into a new market or in an existing market. In this
context, it also appears that Indian business houses are increasingly resorting to M&As as a means to
growth. The present article seeks to analyze the role of such mergers in the Indian banking sector from
2000 to 2011.
Literature Review
There are various strategic and financial objectives that influence mergers. A lot many studies in both
Indian and international context have been made on the post-merger corporate financial performance.
However, most of the work has been done in the USA and the UK. And in the Indian context, only a few
studies have been carried out. Several studies have been carried out on the effects of M&As on share
prices, shareholder wealth, and the pre- and post-merger operating and financial performance of the
target and bidder firms. But there is no conclusive evidence as to whether M&A enhances efficiency.
Research on post-M&A performance is bifurcated. The methodology widely used in these studies is
Event studies and accounting studies that point towards the fact that the gains from mergers are either
small or non-existent (Kumar, 2009). Studies dealing with compatibility rely mostly on non-financial
performance indices (e.g., Buono and Bowditch, 1989; Greenwood et al., 1994; Napier, 1989).
Several studies have explored the relation between compatibility and M&A performance. Datta
(1991) reported that differences in top management styles had a negative effect on post-acquisition
performance. On the same lines, Chatterjee et al. (1992) examined the relationship between top manage-
ment teams’ perceptions of cultural differences and acquirers’ stock market gains. They found that cul-
tural similarity had a significant and positive effect on shareholder gains. An effort by Greenwood et al.
(1994) found that in a study of merger of two large firms, one firm emphasized the accountant’s technical
expertise, whereas the other stressed entrepreneurial competence.
Akhavein et al. (1997) analyzed changes in profitability and found that banking organizations signifi-
cantly improved their profit efficiency ranking after mergers. In the banking sector, Healy et al. (1992)
examined all M&As that occurred between 1982 and 1986. They found that M&As did not reduce non-
interest expenses that could have led to improved efficiency. According to Pilloff and Santomero (1997),
there is little empirical evidence of mergers achieving growth or other important performance gains.
However, Cornett and Tehranian (1992) and Kay (1993) found some evidence of superior post-merger
period because of the merged firms’ enhanced ability to attract loans.
In an attempt to explore the financial impact of mergers, Cybo-Ottone and Murgia (2000) carried out
an event study analysis of 54 M&A deals covering 13 European banking markets for the period 1988–
1997. They found positive and significant increase in the shareholder value of bidder and target banks at
the time of the deal announcement. Ghosh (2001) found that merged firms show significant improve-
ments in operating performance. Pawaskar (2001) observed that the shareholders of the acquirer compa-
nies increased their liquidity performance after the merger. Another research by Sudarsanam and Mahate
(2003) provided a useful insight into the short-run performance of a sample of 519 UK acquirers between
1983 and 1995. The authors reported significantly negative abnormal returns of 1.4 per cent (over the −1
to +1 day period) with only a third of acquirers experiencing wealth gains. These results were consistent
with Holl and Kyriazis (1997).
Global Business Review, 14, 2 (2013): 263–282
266 Neha Kalra, Shaveta Gupta and Rajesh Bagga
Ramaswamy and Waegelein (2003) found that there is improvement in post-merger operating finan-
cial performance measured by industry-adjusted return on assets. Rahman and Limmack (2004) found
that there is improvement in long-run operating cash flow performance of companies. While, a study by
Tambi (2005) stated that merger neither provides economies of scale nor synergy, an effort by Uchendu
(2005) and Kama (2007) showed that the bank consolidation which took place in Malaysia facilitated
bank’s expansion and growth. However, opposite results were shown by a study of Pazarskis et al.
(2006) that the profitability of a firm is decreased due to merger/acquisition.
Kumar and Rajib (2007a) estimated the impact on the shareholder value after the merger has been
completed using accounting measure. Using book value of asset and sales model, it was found that cor-
porate performance improves after merger. Kukalis (2007) found that the acquirer company’s pre-merger
performance partially outperformed the post-merger performance of the merged company. The results of
a study by Vanitha and Selvam (2007) also pointed that financial performance of merged companies
improves. Ramakrishnan (2008) showed that mergers in India have resulted in improved long-term post-
merger firm operating performance compared to pre-merger. As per a study by Straub (2007), opposite
views emerged that M&As often failed to add significantly to the performance of the banking sector.
Surprisingly, the majority of studies comparing pre- and post-mergers performance found that potential
efficiency derived from M&As rarely materialize (Berger et al., 1999; Piloff, 1996).
The event study methodology (Brown and Warner, 1980, 1985; Etebari et al., 1987; MacKinlay,
1997; McWilliams and Siegel, 1997; Pruitt and Peterson, 1986) has been used to estimate cumulative
average abnormal returns (CAR) in a 1-day, 2-day, 5-day, 10-day, 15-day, 20-day and 40-day window
period (cited from Anand and Singh, 2008). The basis for event study analysis is the semi-strong
version of the efficient market hypothesis (EMH). It assumes that all publicly available information
is incorporated in the stock prices immediately on announcement. But event study generally predicts
the shareholder’s present and future thinking on the merger. Further the support of the shareholders
for the merger immediately after merger announcement results in high returns which help in paying
higher dividends. This results in greater support of the shareholders on combined firm in the future
(Sharma, 2010).
However, Caves (1989) pointed out to conflicting results obtained from event studies and operating
performance studies and tried to reconcile these two sets of empirical evidence. Hence, the central ques-
tion arises as to whether these two approaches lead to significantly different conclusions.
The existing literature on M&As in India is very fragmented. Some cases are very well researched,
but a general overview of it is non-existent. Growth and decline of Indian business seems above all a
matter of internal expansion and contraction.
Need and Research Objective of the Study
Corporate M&As and the resulting effects to shareholders have been long examined in the finance litera-
ture. Not only are the empirical findings mixed, but there also exist several distinct hypotheses trying to
explain the reasons for the effects. Considering the limited research on M&As in Indian industry, the
present research study has been aimed at exploring the impact on financial performance of firms going
through mergers in Indian banking industry, in the post-reforms period viz., 2000–2011. This study also
tries to examine the announcement effects of merger using event study.
Global Business Review, 14, 2 (2013): 263–282
Are Indian Banks Going Up a Blind Alley? 267
Hypotheses of the Study
Many explanations have been given in the literature as to why M&As take place, over and above the
assumption of profit maximization. This issue is tangled with that of post-merger profitability: if the
merging partners are driven by profit maximization, then all mergers should be profitable. This, how-
ever, seems not to be the case (Mueller, 1989).
Financial measures can be used to test the hypothesis that mergers occur to discipline bad manage-
ment and could be punished by being the victim of a take-over (Ravenscraft and Scherer, 1989). The
evidence for the UK shows that until 1966 acquired firms were on average smaller, grew less, and were
less profitable than the acquirers and other firms in general (Hughes, 1993). Using US data of 95 mergers
for the period 1975–1977, Ravenscraft and Scherer (1987) found that on average, targets are less profit-
able than their industry average. However, with a larger sample drawn for the same period, Ravenscraft
and Scherer (1989) found no support for their previous findings. This result was confirmed in a study by
Matsusaka (1993) where he found that targets are on average much more profitable than their industry
average. Profit measures can also be used to test the hypothesis that mergers occur because managers
pursue growth by acquisition to divert free cash flows from the shareholders (Jensen, 1986). Hay and Liu
(1996) and Berger and Humphrey (1992) found that the probability of being an acquiring firm is signifi-
cantly and positively related to profitability. Ravenscraft and Scherer (1987, 1989) however, found that
there is no evidence of an increase in profitability after a takeover. Opposite results were obtained by
Healy et al. (1992), who look at post-merger profitability of the largest 50 mergers for the period 1979–
1984, and found that, relative to their industries, these firms’ profitability is higher. However, Pilloff
and Santomero (1997) put forth that there is little empirical evidence of mergers achieving growth or
other important performance gains. From the vast body of literature on the subject of acquisition per-
formance, an array of hypothesized sources of gains has emerged (Jensen and Ruback, 1983). However,
it must also be noted that there have been studies conducted that showed that post-merger performance
also largely depends on the industry or sector and cannot be generalized (Mantravadi and Reddy, 2008).
There is therefore conflicting evidence on the effect of mergers on financial performance of firms. Thus,
following null hypothesis has been developed to explain the existence of mergers.
H01: There is no signicant difference in the post-merger nancial performance of the merged rms relative to
the pre-merger nancial performance.
Loderer and Martin (1992) found that the cumulative abnormal return is statistically significant giv-
ing positive returns to acquiring firm shareholders. Fields et al. (2007) found that there is a positive bid-
der abnormal return for bancassurance mergers. Chakrabarti (2008) found that the average Indian
acquirer gains in value both on announcement as well as over the long-run post-takeover period and
these gains are statistically significant. Boubakri et al. (2008) suggest that M&As create value in the long
run as buy and hold abnormal returns are positive and significant. Anand and Singh (2008) found merger
announcement in the Indian banking industry has positive and significant shareholders wealth effect
both for the bidder and target banks. Kyriazis (2010) found that the cumulative abnormal return is statis-
tically significant giving positive returns to acquiring firm shareholders. Thus, following null hypotheses
have been developed to explain the announcement effects of mergers.
H02: There is insignicant (zero) share price response to merger announcements.
H03: The Indian stock market is efcient.
Global Business Review, 14, 2 (2013): 263–282
268 Neha Kalra, Shaveta Gupta and Rajesh Bagga
Database and Methodology
A list of banks involved in mergers during 2000–2011 was compiled from several sources like web sites
of the BSE, money control and SEBI. For the purpose of this study, the first date of media announcement
of the merger has been taken as the event date (day zero). Table 1 enumerates the list of the banks (10)
covered in the current study. The first possible date when the news of the merger was made public has
been used. The same has been obtained from the information available on the web sites of the respective
banks. Merger cases where at least two years of data for pre-merger period was not available were
removed from the study sample. The screening criteria described earlier were applied to such a list to
arrive at the final sample. Ahmad (2007) indicated that a longer period of study should provide a better
picture. Thus, the period 2000–2011 was chosen to measure the overall performance for merged banks
and to identify whether the merger activity works out in increasing the merged banks’ efficiency and
profitability. The study is carried out over various years under consideration using Accounting Based
Approach using different financial parameters and Event study methodology. Table 1 provides the list of
merged banks considered in the current study.
Analytical Tools Used
The current article employs two analytical tools for measuring the financial impact of merger in banking
sector using Accounting Performance measure and Event study methodology. In order to determine
the impact of merger in banking sector on the financial performance, Accounting performance
measures have been used. And, in order to test the impact of merger announcements in the banking
sector on the respective share prices, Event study methodology has been adopted. The test of normality
is employed to explore whether data is normally distributed or not in order to make use of respective
analytical tool.
Table 1. SelectedBanksintheStudy
S.No. AcquirerName TargetName DateofAnnouncement YearofMerger
1 ICICIBank BankofMadura 11-12-2000 2001
2 ICICILtd ICICIBank 25-10-2001 2002
3 BankofBaroda SouthGujaratLocalArea
BankLtd
27-2-2004 2004
4 OrientalBankof
Commerce
GlobalTrustBankLtd 26-7-2004 2004
5 IDBILtd IDBIBank 20-1-2005 2005
6 CenturionBank BankofPunjab(BOP) 20-6-2005 2006
7 ICICIBankLtd SangliBankLtd 12-9-2006 2007
8 IDBILtd UnitedWesternBankLtd 12-9-2006 2006
9 HDFCBank CenturionBankofPunjab 20-5-2008 2008
10 ICICIbank BankofRajasthan 18-5-2010 2010
Source: Authors’own.
Global Business Review, 14, 2 (2013): 263–282
Are Indian Banks Going Up a Blind Alley? 269
Accounting Performance Techniques
The long-run post-acquisition performance of bidders has also attracted a great deal of research. Much
of this has been motivated by early studies suggesting that takeovers may have a negative impact on the
long-run wealth of shareholders (Asquith, 1983; Malatesta, 1983). The accounting technique gives a
measure of the assets, revenue and liability of the two involved firms prior to and after merger. The
accounting techniques help in accessing the firm’s liability and assets for the future and thereby help in
accessing the value created by the merger. But in modern public organization the shareholders support
greatly the company’s future in long term. Hence the accounting technique alone cannot predict the
value created by the merger (Sharma, 2010).
Basically, paired sample t-test has been used to determine the significance of differences in financial
performance before and after the merger activity on the basis of variables, individual banking units
and grouped data. Pre-merger and post-merger performance ratios were estimated and the averages com-
puted for the entire set of sample firms, which have gone through mergers during the period 2000–2011.
The average ratios for each of the industry sub-samples were also computed. Average pre-merger
and post-merger financial performance ratios were compared to see if there was any statistically signifi-
cant change in operating performance due to mergers, using ‘paired two sample t-test’ at confidence level
of 0.05.
Selected Variables in the Study
Ratios provide an insight into the reasons for a company’s historical performance. In addition to provid-
ing an indication of the level and variability of historical profitability and cash flow, an analysis of the
Table 2.FinancialPerformanceVariablesusedintheStudy
Parameters VariableNames VariableDescription Source
Profitability
Parameters
ReturnonCapital
Employed(ROCE)
EBIT/CapitalEmployed Swaminathan(2002),Kumar,
2009;Usmanetal.,2010
ReturnonNetWorth
(RONW)
ProfitafterTax/NetWorth Saboo&Gopi,2009
EPS EBIT/shares Usmanetal.,2010
MVtoBVofequity Authorsown
TobinQ Authorsown
Liquidity
Parameters
CurrentRatio CurrentAssets/CurrentLiabilities Kumar&Rajib,2007
QuickRatio QuickAssets/QuickLiabilities Kumar&Rajib,2007
Leverage
Parameters
TotalDebtRatio TotalDebttoTotalAssets Kumar&Rajib,2007
InterestCoverageRatio Earningbeforeinterestand
taxes(EBIT)/Interest
Kumar&Rajib,2007;Kumar
&Bansal,2008
Debt/Equity Beena,2000
Source:Authors’own.
Global Business Review, 14, 2 (2013): 263–282
270 Neha Kalra, Shaveta Gupta and Rajesh Bagga
financial statements of target normally involves the calculation of various financial ratios (refer Table 2)
that can generally be categorized as:
• Profitability ratios that indicate the proportion of revenues retained by the company at different
levels;
• Liquidity ratios, which measure the short term financial strength of the business;
• Financial leverage ratios, which measure target company’s ability to accommodate interest bearing
debt.
Event Study Methodology
The data in the present study has also been analyzed using Event Study. The procedure for event studies
is to investigate whether there are abnormal returns around the announcement date. The announcement
effect exists only if abnormal returns are significant. This analytical approach is well accepted and has
been used widely. An Event study uses transactions data from financial markets to predict the financial
gains and losses associated with newly disseminated information. The event study methodology has, in
fact, become the standard method of measuring security price reaction to some announcement or event.
In practice, event studies have been used for two major reasons: (a) to test the null hypothesis that the
market is efficient in terms of information efficiency, and (b) within the ambit of market efficiency
hypothesis, to examine the impact of some event on the wealth of the firm’s security holders. Cable and
Holland (1999) argued that the market model compares favourably to other models proposed in the
literature. For that reason, the reference has been made only to the results from the market model.
Standard Event Study Methodology
The market model assumes a linear relationship between the return of the security to the return of the
market portfolio. The BSE 500 Sensex had been taken as the benchmark index. The stock returns had
been regressed to BSE 500 Sensex returns for a period of 240 trading days viz., 120 trading days before
and after the announcement date. The abnormal return for each of the day in the event window was the
difference between the actual stock return during that day and the expected normal return according to
the BSE 500 Sensex as per the ‘α’ and ‘β’ of the concerned stock. In brief, this approach involved the
following sequence:
Daily abnormal returns before and after the announcement (including announcement day) of the
merger has been computed as:
ARi, t = Ri, t – E(Ri, t)
Where t = day measured relative to the merger announcement day (t=0)
ARi, t = abnormal return on security ‘i’ for day ‘t’
Ri, t = raw return on security ‘i’ for day ‘t’ which was calculated as:
Ri,t =i, t i, ( t 1)
i, t
MP MP
MP
−
−
Global Business Review, 14, 2 (2013): 263–282
Are Indian Banks Going Up a Blind Alley? 271
Where MPi, t = closing price of security ‘i’ on day ‘t’
MPi, (t–1) = closing price of security ‘i’ on day ‘t–1’
E(Ri, t) = expected return on security ‘i’ during day ‘t’ which had been estimated through market
model using BSE 500 Sensex as follows:
E(Ri, t) = α1 + β1Rm + εi
Where Rm = return on the BSE 500 Sensex and α1, β1 are the parameters of the market model and εi is
assumed to indicate the abnormal returns.
Average abnormal returns for each relative day had been calculated by:
AARi =
N
i 1 i, t
1AR
N=
∑
Where N = Number of securities (banks) with abnormal returns during day‘t’.
Event Definition and Date of Announcement
For the purpose of this study, the first date of media announcement of the merger has been taken as the
event date, i.e., day zero (refer Table 1). The first possible date when the news of the merger was made
public has been used. The same has been obtained from the information available on the web sites of
Bombay Stock Exchange and the respective banks.
Window Period
Even though there is no consistency between the event windows chosen in existing studies, they can be
broadly classified as being either short-run or long-run. Short-run refers to days or months around the
announcement of the bid, while long-run refers to periods of months or years. The choice of appropriate
performance measure also varies considerably between studies (Barber and Lyon 1997; Gregory 1997;
Kennedy and Limmack 1996; Lyon et al.1999; Sudarsanam and Mahate, 2006). The event window has
been taken at maximum from –120 days to the date of announcement to 120 days. The share price data
and market index data, namely, BSE 500 have been taken from the official web site of the Bombay Stock
Exchange of India Limited.
Results and Discussions
Before carrying out the analysis, the data was checked for normality in order to pick the suitable test to
be applied. Normality is a common preliminary assumption of many parametric tests such as t-test and
ANOVA. Since the dataset for this study is more than 2000 elements, the Kolmogorov–Smirnov test is
Global Business Review, 14, 2 (2013): 263–282
272 Neha Kalra, Shaveta Gupta and Rajesh Bagga
used. The Kolmogorov–Smirnov (K–S) test which was originally proposed in the 1930s by Kolmogorov
(1933) and Smirnov (1936), is the principal goodness-of-fit test for normal and uniform datasets.
In order to fulfil the prerequisites of any further analysis, Kolmogorov–Smirnov test was carried out to
measure the normality of distribution with respect to financial performance variables of Indian banks
both pre- and post-merger as given in Table 3.
The results of the normality test depend on the P-value calculated by the test. Since the test statistics
in Table 3 are greater than the level of significance 0.05, for both pre-merger (0.745) and post-merger
(0.415), it can be inferred that the data comes from a normal distribution. Hence, considering the nature
of the data, parametric test viz., paired t-test has been applied to carry out the analysis of the merged
banks before and after merger.
The analysis has been carried out in two sections. First section discusses the results of financial
impact of banking mergers employing Accounting Performance techniques and the second section dis-
cusses the results of impact of banking merger announcements on the share prices using Event study
methodology.
Accounting Performance Results
The results employing accounting measures in order to assess the impact of mergers in Indian banking
sector on the financial performance has been carried out in three parts: impact on the financial perform-
ance of the selected Indian banks on: selected financial performance parameters (refer Table 2, and for
results see Table 4), individual banking units (refer Table 1, and for results see Table 5) and on grouped
data basis (refer Table 6).
The first part of the analysis is related to impact of mergers on the financial performance of the
selected Indian banks on the basis of financial parameters. The result of the same is depicted in Table 4.
Table 4 shows the comparison of the pre-merger and post-merger financial performance ratios for the
entire sample set of mergers witnessed by the Indian banking sector during the period 2000–2011. The
results for the profitability parameters revealed that there was a decline in the mean return on capital
employed (in tandem with Swaminathan, 2002) and Tobin’s Q during the post-merger period (21.84 per
cent and 5.83 per cent respectively), but the decline was not statistically validated (t-statistic value of
Table 3. One-SampleKolmogorov–SmirnovTest
Pre-merger Post-merger
N 10 10
NormalParametersaMean 8.2606 11.4123
Std.Deviation 7.74902 13.67028
MostExtremeDifferences Absolute 0.215 0.280
Positive 0.215 0.280
Negative –0.153 –0.205
Kolmogorov-SmirnovZ 0.680 0.884
Asymp.Sig.(2-tailed) 0.745 0.415
Source: Authors’own.
Note: a.TestdistributionisNormal.
Global Business Review, 14, 2 (2013): 263–282
Are Indian Banks Going Up a Blind Alley? 273
Table 4. Pre-mergerandPost-mergerStatisticsforPerformanceRatiosofMergingBanks
PerformanceParameters
Pre-merger
(Means)
Post-merger
(Means)
Change
(%age) t p-value
Hypothesised
Relation Results
Profitability
Parameters
ReturnonCapital
Employed
10.9639 8.5699 –21.84 1.756 0.113 NS NS
ReturnonNet
Worth
11.3982 12.1142 6.28 –0.266 0.797 NS NS
EPS 15.6199 30.4599 95.01 –4.730 0.001* NS S
MVtoBVof
equity
23.8355 40.3219 69.17 –2.580 0.030* NS S
Tobin’sQ 0.3326 0.3132 –5.83 0.429 0.678 NS NS
Liquidity
Parameters
CurrentRatio 0.6035 0.1279 –78.81 1.529 0.161 NS NS
QuickRatio 8.1298 11.1326 36.94 –2.833 0.020* NS S
Leverage
Parameters
TotalDebtRatio 0.8387 0.9391 11.97 –1.424 0.188 NS NS
Interest
CoverageRatio
1.3151 0.9456 –28.10 3.386 0.008* NS S
Debt/Equity 9.5686 9.1991 –3.86 0.285 0.782 NS NS
Source: Authors’Own.
Notes: *significantat0.05level(2-tailed)
NS=Notsignificant
S=Significant
Table 5. Pre-mergerandPost-mergerStatisticsforPerformanceRatiosofMergingBanksonIndividualBasis
Banks
Pre-merger
(Means)
Post-merger
(Means)
Pre-post
Merger
(Means)
Pre-post
Merger(SD) t p-value
Hypothesised
Relation Results
ICICIBank&Bank
ofMadura
6.4496 10.3624 –3.91286 10.35760 –1.195 0.263 NS NS
ICICILtd&ICICI
Bank
5.7235 10.7688 –5.04528 11.05935 –1.443 0.183 NS NS
OrientalBank
ofCommerce&
GlobalTrustBank
Ltd
9.7284 9.6044 0.12394 4.88365 0.080 0.938 NS NS
BankofBaroda
&SouthGujarat
LocalAreaBank
Ltd
8.3172 11.1797 –2.86254 9.75213 –0.928 0.378 NS NS
IDBILtd&IDBI
Bank
6.3601 9.7784 –3.41836 11.07963 –0.976 0.355 NS NS
CenturionBank&
BankofPunjab
10.1994 16.4756 –6.27616 12.96456 –1.531 0.160 NS NS
IDBILtd&United
WesternBankLtd
6.3065 10.4890 –4.18248 11.13199 –1.188 0.265 NS NS
(Table 5 continued)
Global Business Review, 14, 2 (2013): 263–282
274 Neha Kalra, Shaveta Gupta and Rajesh Bagga
0.113 and 0.678). However, a remarkable improvement was noticed in the mean values of both EPS and
MV to BV of equity after the merger (95.01 per cent and 69.17 per cent respectively) both of which were
statistically validated (t-statistic value of 0.001 and 0.030). The results are consistent with the earlier
studies of Haynes and Thompson (1999), Campa and Hernando (2006), Lin et al. (2006), Braggion et al.
(2010) who found that there is a positive wealth effect for merged banks after the announcement month.
A marginal rise was also noticed in the measure of return on net worth (6.28 per cent), though this change
was not found to be significant (t-statistic value of 0. 797). The results for overall profitability parameters
are in tandem with the studies of Jane and Crane (1992), Pazarskis et al. (2006), Vennet (1996), Sharma
and Ho (2002) Sufian (2004) and Usman et al. (2010).
With regard to the liquidity measures a steep fall was witnessed in the mean values of current ratio of
banks following the merger (78.81 per cent, t-statistic values of 0.161), again this change was not signifi-
cant. An improvement was also found in the means of quick ratio for banks as a result of merger (36.94
per cent, t-statistic values of 0.020), and the change has been found to be significant. The results are
consistent with the findings of a study of Leepsa and Mishra (2012).
The perusal of results for the leverage measures revealed that the mean Total Debt Ratio had margin-
ally increased during post-merger period (11.97 per cent), but the t-value of 0.188 suggested that the
difference was not statistically significant. Likewise, the mean debt-equity ratio had also declined during
the post-merger period (3.86 per cent), but the increase was not statistically significant, as indicated by
Banks
Pre-merger
(Means)
Post-merger
(Means)
Pre-post
Merger
(Means)
Pre-post
Merger(SD) t p-value
Hypothesised
Relation Results
ICICIBankLtd&
SangliBankLtd
8.4604 13.0603 –4.59989 11.93877 –1.218 0.254 NS NS
HDFCBank&
CenturionBankof
Punjab
11.0148 12.0718 –1.05701 8.57718 –0.390 0.706 NS NS
ICICIBank&Bank
ofRajasthan
10.0460 10.3329 –0.28692 7.53264 –0.120 0.907 NS NS
Source:Authors’own.
Note: NS=Notsignificant
S=Significant
(Table 5 continued)
Table 6.Pre-mergerandPost-mergerStatisticsforFinancialPerformanceofMergingBanksonGrouped
DataBasis
Descriptives Pre-merger Post-merger
Mean 8.2606 11.4123
Standard Deviation 7.74902 13.67028
Correlation 0.951
Sig. 0.000
T–1.479
p-value 0.173
Source: Authors’own.
Global Business Review, 14, 2 (2013): 263–282
Are Indian Banks Going Up a Blind Alley? 275
the t-value of 0.782. A positive effect that emerged out of this decline in the debt-equity ratio was
reflected with a decline in the means of interest coverage ratio (28.10 per cent) and also statistically
significant with t-statistics of 0.008.
The results are comparable to those obtained by Piloff (1996), Berger et al. (1999), Pawaskar (2001),
Kaur (2002), Beena (2004), Straub (2007) and Mantravadi and Reddy (2008) who found that most merg-
ers during 1995–2000 in India were focused on asset growth through restructuring, rather than focusing
on improving operational efficiencies. The results above also agree with the results of research studies in
USA and Europe on operating performance of acquiring firms—that the performance of acquiring firms
had either stagnated or declined after mergers.
The next set of analysis is on banking unit basis. Again paired t-test has been applied to identify the
impact of merger on financial performance of individual banks. The results of the same are given in
Table 5.
An in-depth analysis of the results in Table 5 indicate the comparison of the pre-merger and post-
merger financial performance for the entire sample set of merged banks witnessed by the Indian banking
sector during the period 2000–2011. The results revealed that even though there has been an improve-
ment in the performance of banks (except OBC), post their mergers, yet the t-statistics do not reflect any
significant change in the sample banks. In the entire sample set the t-statistics have appeared to be
greater than the level of significance 0.05.
Finally, the paired samples T-test for data of merged banks on grouped data basis for all the selected
banks have been carried out at different times, i.e., before and after merger.
The results in Table 6 show that overall there is no significant difference in the financial performance
between pre- and post-merger due to the test statistic 0.173 greater than the acceptable level of signifi-
cance 0.05. Hence, there is no significant difference in the post-merger bank’s performance even though
the banks have achieved improvement in their performance. This finding is consistent with the results of
a study by Rosa et al. (2003) that over the long-term, in the post-announcement period, acquiring firms
earn lower returns relative to those earned in the pre-acquisition performance but their relative perform-
ance remains exceptionally good, on average.
Thus, a detailed analysis of three sets of results: on financial parameter basis, individual banking unit
basis and grouped data basis indicate absence of any significant impact on the financial performance of
the banks due to merger. This result is consistent with the findings of several previous studies such
as Pawaskar (2001), Kaur (2002), Amel et al. (2004), Campa and Hernando (2006), Mat Nor and
Mohd Said (2004), Mantravadi and Reddy (2008), Muhammad (2010), Leepsa and Mishra (2012)
and Padmavathy and Ashok (2012). The results thus lead to acceptance of null hypothesis that there is
no significant impact of merger on the financial performance of the Indian banks.
Event Study Results
Abnormal returns are calculated using the market model. The study of Cable and Holland (1999) argued
that the market model compares favourably to other models proposed in the literature. For that
reason, reference has been made only to the results from the market model. Table 7 outcome is based on
cumulative average abnormal returns (CAAR) results of 10 banking merger announcements for trading
days –120 to +120.
Global Business Review, 14, 2 (2013): 263–282
276 Neha Kalra, Shaveta Gupta and Rajesh Bagga
Inspection of Table 7 reveals that the pre-announcement and post-announcement periods contain little
new information. The results confirm the notion that the pre-announcement and post-announcement
periods contain little new information. It can be observed that the market witnessed positive abnormal
returns in the pre-announcement periods. Since, no concrete results were identified, in order to explore
the possible association between pre- and post- returns due to merger in banking sector (refer Table 8),
paired t-test has been applied for different event windows: very short (–10 to +10 days), short (–30 to
+30 days), medium (–60 to +60 days) and long (–120 to +120 days).
It can be observed from the results of paired t-test presented in Table 8 that the market witnessed posi-
tive abnormal returns during two windows of short and very short duration (–30 to + 30 and –10 to +10
days), indicating that the impact of merger announcements on the share prices is there but in the medium
(–60 to +60 days) and long-term (–120 to +120 days) windows, insignificant results have been obtained.
The findings indicated the presence of lag in reflecting and adjusting the effects of merger announce-
ments by Indian stock market, thereby, giving chance to the investors to earn abnormal returns in the
short time period (–30 to +30 days). These findings are inconsistent with the studies of Anand and Singh
(2008), Boubakri et al. (2008) and Chakrabarti (2008). Considering the momentum of the share price
adjustment to the new information coming from merger announcements, it has been observed that there
is lagging response to the same, thus, indicating the inefficiency of the Indian stock market in the short
run. But, further analysis reveals that Indian stock market responds to the corporate news contained in
merger announcements in only two event windows: –60 to +60 days and –120 to +120 days, giving no
chance to the investors to beat the market, and hence, getting no abnormal returns. On the basis of the
results, the null hypothesis (H02) of insignificant (zero) share price response to merger announcements
Table 8. Pre-andPost-CAAR:ResultsofPairedt-test
EventWindows (p-values)
–10to+10 0.018*
–30to+30 0.010*
–60to+60 0.164
–120to+120 0.375
Source: Authors’own.
Note: *Significantat0.05level.
Table 7. CumulativeAverageAbnormalReturnsResults
MergerAnnouncements CumulativeAverageAbnormalReturnin%(p-values)
Pre-Announcement –120to–1 0.0467(0.555)
–60to–1 0.1472(0.223)
–30to–1 0.3475(0.013)*
–10to–1 0.6995(0.008)*
Post-Announcement +1to+10 –0.2703(0.210)
+1to+30 –0.1368(0.290)
+1to+60 –0.734(0.491)
+1to+120 –0.544(0.490)
Source: Authors’own.
Note: *Significantat0.05level.
Global Business Review, 14, 2 (2013): 263–282
Are Indian Banks Going Up a Blind Alley? 277
and has been rejected partially. Also from the results it can be inferred that Indian stock market pos-
sesses information efficiency as the effects are shown in longer duration of any announcements as the
investors are not given any chance to earn the abnormal returns. Thus, the null hypothesis (H03) that
Indian stock market is efficient has been rejected partially.
Further, in order to identify the impact of event or announcement with a higher signaling power in
the significant event windows identified from Table 8 (–10 to +10 and –30 to +30), Cumulative Average
Abnormal Returns surrounding merger announcements of 10 selected banks in different periods
(30 days) centred on the announcement day (announcement day = 0) are calculated. Table 9 presents
cumulative average abnormal returns around announcement day. All the analysis uses the strongest
abnormal returns of the 30-day announcement period.
A close examination of Table 9 reveals that merger announcements have the most significant abnor-
mal returns in the 30-day window, highest return being 5.7381 per cent, and as the analyzed time period
widens the CAR decreases and reaches 1.3922 per cent.
Table 9. CumulativeAverageAbnormalReturns(CAAR)aroundMergerAnnouncements
Days MeanCAAR(%) t-stat
–1to+1 5.7381 0.002*
–2to+2 5.1254 0.000*
–3to+3 4.7971 0.000*
–4to+4 4.3544 0.000*
–5to+5 4.0577 0.000*
–6to+6 3.8288 0.000*
–7to+7 3.6927 0.000*
–8to+8 3.5941 0.000*
–9to+9 3.5040 0.000*
–10to+10 3.3164 0.000*
–11to+11 3.1264 0.000*
–12to+12 3.0903 0.000*
–13to+13 3.0542 0.000*
–14to+14 3.0064 0.000*
–15to+15 2.9508 0.000*
–16to+16 2.9018 0.000*
–17to+17 2.8643 0.000*
–18to+18 2.8203 0.000*
–19to+19 2.7099 0.000*
–20to+20 2.6093 0.000*
–21to+21 2.5080 0.000*
–22to+22 2.3932 0.000*
–23to+23 2.2724 0.000*
–24to+24 2.1386 0.000*
–25to+25 1.9872 0.000*
–26to+26 1.8540 0.000*
–27to+27 1.7085 0.000*
–28to+28 1.5730 0.000*
–29to+29 1.4691 0.000*
–30to+30 1.3922 0.001*
Source: Authors’own.
Note: *Significantat0.05level.
Global Business Review, 14, 2 (2013): 263–282
278 Neha Kalra, Shaveta Gupta and Rajesh Bagga
The above results also confirm the notion that the short-time period (30 days), i.e., pre-announcement
and post-announcement contain new information having an impact on the share prices.
The-perusal of the results on the basis of accounting performance measures and event study reflect that
there is no significant impact of merger announcements on the financial performance and share prices.
However, the marginal impact has been found, that too in the shorter period of merger announcements.
Conclusion
Overall, the results suggest only minor variations in terms of impact on financial performance following
mergers, in banking sector in India. The result shows that there is significant improvement in EPS and
market value to book value of equity after the bank merge. The result from paired sample t-test illustrated
that there is no significant difference in the overall financial performance between pre-merger and post-
merger, due to the significance value greater than 0.05. The results of one sample t-test when summated
with the paired t-test revealed that the market witnessed positive abnormal returns during two windows
of –30 to + 30 and –10 to +10 days, indicating that the impact of merger announcements on the share
prices is there but only in the short-term as in the medium (–60 to +60 days) and long-term (–120 to +120
days) windows, insignificant results have been obtained. With regard to the efficiency of the Indian stock
market, it responds to the merger announcements in only two event windows: –60 to +60 days and –120
to +120 days, giving no chance to the investors to beat the market, and hence, getting no abnormal
returns, suggesting the efficiency of the market. Thus, the entire study does not signify that merger’s
waves are mere eye wash, as they have not yielded any significant financial impact on the Indian banks
nor have they resulted in value addition to the investors at large. In nutshell, Indian Banks are going up
a blind alley!
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