Emerging Market Bidder Returns and the Choice of Payment Method in Mergers and Acquisitions: Evidence from India

Abstract

Consistent with other evidence on short-run effects of mergers and acquisitions (M&A) announcements on acquiring firm’s shareholder wealth in emerging markets, our study reveals that M&A deals in India, irrespective of the payment method, are not value destroying. Cash deals and stock deals create shareholder wealth on deal announcements. We offer ‘pseudo-cash deal hypothesis’ to explain this phenomenon. We also observe that bigger the relative size of the deal, greater is the abnormal return on deal announcements. We observe that acquirers with high promoter holdings are highly reluctant to offer stock when they acquire a majority stake. However, bigger deals, deals for listed target firms, and deals in the information technology sector, command stock offers.

JEL Classification: G34, G14

Keywords

Mergers and acquisitions payment method bidder returns promoter holdings emerging markets

1. Introduction

The extant empirical research on shareholder wealth effects suggests that M&A deals are value-destroying for bidder’s shareholders (Dodd, 1980; Jensen & Ruback, 1983). The empirical research on the short-term announcement effects of mergers and acquisitions (M&A) deals suggests that cash deal bidders earn non-negative abnormal returns; whereas, the stock deal bidders earn negative abnormal returns (Draper & Paudyal, 1999; Travlos, 1987; Trifts, 1991; Wansley, Lane, & Yang, 1987). This evidence on shareholder wealth effects is largely based on M&A deals in developed countries such as the USA, the UK and Canada (Alexandridis, Petmezas, & Travlos, 2010).

Consistent with other evidence in emerging markets (Alexandridis et al., 2010) on short-run effects of M&A announcements on acquiring firm’s shareholder wealth, our research reveals that M&A deals, in an emerging market like India, are not value destroying. Our analysis of short-run effects of M&A announcements on acquiring firm’s shareholder wealth reveals that bidders making cash offers earn significant positive abnormal returns, and bidders offering stock payment witness non-negative returns on deal announcements. Alexandridis et al. (2010) attribute positive abnormal returns observed in the emerging markets to the lack of competition in the market for corporate control in these countries. However, by considering an augmented sample which also includes privately held targets, we offer an alternate explanation for this observation of non-negative abnormal returns for stock deals.

We assert that these stock deals are in fact, pseudo-cash deals, and hence they do not signal any negative information on announcements. We argue that overvaluation does not drive stock offers in India, nor does it explain abnormal returns on deal announcements. The stock deals in India could have been the cash deals in the absence of certain institutional voids.

An emerging market like India, offers a distinct institutional context, for studying the bidder returns and the choice of payment method in M&A transactions. The distinctiveness of the institutional context stems from the presence of two significant forces, namely high insider ownership in Indian firms and lack of debt funding.

On one hand, high promoter¹ holdings are a classic feature of Indian firms’ ownership structure. The average promoter holdings of companies in India’s leading equity index, Nifty, stood close to 54 per cent in December 2007 and 48 per cent in June 2011 (Sivam, 2011). Our sample suggests that the average promoter holdings in a firm were more than 50 per cent (see Table 1). This feature implies that ceteris paribus high insider ownership is likely to be associated with cash offers (Amihud, Lev, & Travlos, 1990).

On the other hand, the Reserve Bank of India (RBI), the Indian central bank, prohibits Indian banks from lending to Indian companies for undertaking domestic acquisitions (barring few exceptions), thus creating an institutional void. Further, the Indian corporate debt market is underdeveloped (Saraogi, 2011) and cannot be reliably accessed for raising debt to fund M&A deals. The latter feature implies that even though firms with high insider ownership prefer to offer cash, their choice is more complex due to the institutional void (i.e., the absence of debt funding).

Our inquiry into the choice of method of payment in M&A deals by Indian acquirers suggests that cash has been the preferred method of financing these deals by Indian acquirers, and this can be attributed to high promoter holdings in Indian firms. The cross-sectional analysis reveals that the insider managers are more sensitive to stake dilution when they acquire a majority stake in a target firm, and therefore acquirers with higher promoter stake are more likely to offer cash in such deals. Deals with characteristics like higher percentage of stake acquired, bigger deal size and publicly listed targets are likely to command stock offers. Deals undertaken in information technology sector are also more likely to use stock as the payment method. Cross-border deals are highly likely to be cash deals.

The contribution of our study is fourfold. First, we observe that M&A deals in India, cash as well as stock deals, are not value destroying. Second, we propose a novel explanation to support the non-negative abnormal returns observed on announcement of stock deals. We hypothesise that these stock deals are ‘pseudo-cash deals’. Third, we observe that despite being value-creating, the stock offers are likely to attract lower abnormal returns than the cash offers. Fourth, we understand the determinants of the choice of payment method for bidding firms in an emerging economy with institutional voids and the presence of structural features with conflicting implications.

In the next section, we summarise the theoretical and empirical background on the choice of payment method and bidder returns, and we briefly describe our hypotheses. We present the methods and the data in Section 3. In Section 4, we discuss the results, and we present our conclusions in Section 5.

Table 1.
Summary Statistics for the Event Study Sample

Variables Cash Deals
Stock Deals

N Mean Median Std. Dev. N Mean Median Std. Dev.

Deal Size (US$ million) 379 111.195 9.210 706.896 61 245.162 22.881 539.187

Relative size 371 0.187 0.039 0.552 57 1.643 0.107 5.026

Relatedness 379 0.549 1 0.498 61 0.525 1 0.504

Liquidity 372 0.030 0.001 0.080 59 0.011 0.001 0.027

Promoter Holdings 321 0.503 0.510 0.179 49 0.530 0.544 0.197

Non-promoter holdings 328 0.501 0.490 0.190 50 0.473 0.455 0.204

Per cent acquired 362 0.504 0.490 0.321 60 0.793 1 0.305

Per cent owned 364 0.633 0.630 0.310 61 0.992 1 0.064

Debt-to-equity 372 0.721 0.498 0.954 58 1.093 0.375 3.283

Int. on Borrowings 350 0.140 0.083 0.373 53 0.128 0.090 0.162

Int. on Borrowings Dummy 350 0.494 0 0.501 53 0.547 1 0.503

Target Listing 379 0.319 0 0.467 61 0.590 1 0.496

Cross-border 379 0.351 0 0.478 61 0.066 0 0.250

Business Group 379 0.694 1 0.461 61 0.738 1 0.444

Operating Profit Acquirer 329 0.317 0.208 0.628 48 0.970 0.194 4.991

Merger dummy 379 0.187 0 0.391 61 0.689 1 0.467

Variables	Cash Deals	Stock Deals
Deal Size (US$ million)	379	111.195	9.210	706.896	61	245.162	22.881	539.187
Relative size	371	0.187	0.039	0.552	57	1.643	0.107	5.026
Relatedness	379	0.549	1	0.498	61	0.525	1	0.504
Liquidity	372	0.030	0.001	0.080	59	0.011	0.001	0.027
Promoter Holdings	321	0.503	0.510	0.179	49	0.530	0.544	0.197
Non-promoter holdings	328	0.501	0.490	0.190	50	0.473	0.455	0.204
Per cent acquired	362	0.504	0.490	0.321	60	0.793	1	0.305
Per cent owned	364	0.633	0.630	0.310	61	0.992	1	0.064
Debt-to-equity	372	0.721	0.498	0.954	58	1.093	0.375	3.283
Int. on Borrowings	350	0.140	0.083	0.373	53	0.128	0.090	0.162
Int. on Borrowings Dummy	350	0.494	0	0.501	53	0.547	1	0.503
Target Listing	379	0.319	0	0.467	61	0.590	1	0.496
Cross-border	379	0.351	0	0.478	61	0.066	0	0.250
Business Group	379	0.694	1	0.461	61	0.738	1	0.444
Operating Profit Acquirer	329	0.317	0.208	0.628	48	0.970	0.194	4.991
Merger dummy	379	0.187	0	0.391	61	0.689	1	0.467

Source: The authors.

Note: This table shows the summary statistics of the deal and firm characteristics of the M&A events in the event study sample classified by the method of payment. The sample period is from 1995 to 2015.

2. Theoretical Background and Hypotheses

The information asymmetry models (Asquith & Mullins, 1986; Leland & Pyle, 1977; Ross, 1977; Tessema, 1989; Travlos, 1987) suggest that the choice of cash as the payment method in the presence of asymmetric information signals better prospects for the firm and that stock signals opportunistic behaviour due to overvaluation. However, new evidence on short-run bidder returns shows that stock offers do not always destroy value. Chang (1998) and Draper and Paudyal (2006) show that for privately held targets, bidders experience positive abnormal returns in case of stock offers. Chatterjee and Kuenzi (2001) suggest that in the presence of investment opportunities use of stock should not signal negative information, however, they find little empirical support for this hypothesis. Alexandridis et al. (2010) observe that stock bidders in countries other than the USA, the UK and Canada had non-negative returns on deal announcements, perhaps due to lack of competition in the market for corporate control. Thus, in the presence of certain deal or firm characteristics, the implications of signalling hypothesis may not hold. However, ceteris paribus, in the presence of information asymmetries, cash offers would signal high-quality investment and thus command a positive investor reaction. Similarly, in the presence of information asymmetries, stock offers would receive a negative investor reaction.

Hypothesis 1: We expect positive abnormal returns on cash deal announcements, negative abnormal returns on stock deal announcements.

Managerial ownership hypothesis (Amihud et al., 1990; Faccio & Masulis, 2005; Ghosh & Ruland, 1998; Martin, 1996; Yook, Gangopadhyay, & McCabe, 1999) implies that there is a direct link between the extent of equity ownership by top managers in an acquiring firm and the method of payment. Bidding firms with higher managerial ownership tend to offer cash since these managers are unwilling to dilute their control and vice versa. Likewise, with respect to institutional ownership or block holders, Martin (1996) shows that the proportion of institutional owners is negatively related with the possibility of stock offer. As mentioned earlier, firms in India have high promoter holdings, that is, in general the firms have high ownership concentration. Such bidders are not likely to dilute substantial stake in stock deals if the acquisition is for smaller stakes. But the stake dilution is likely to be higher if the stakes acquired, in exchange for equity, are higher. Thus, we conjecture that the impact of managerial ownership would be profound if the bidder is acquiring a majority stake that is more than 50 per cent, in a target firm. We capture this effect by using a variable, which observes the promoter holdings only when the percentage acquired is more than 50 (Promoter Holdings Acq50).

Hypothesis 2: Bidding firms with high managerial ownership are more likely to offer cash for majority stake acquisitions.

Jensen and Meckling (1976) have argued that equity ownership of managers reduces the agency conflicts. The higher equity ownership of managers facilitates alignment of interests of managers and the shareholders. This implies that higher managerial ownership in bidding firms should have a positive impact on the announcement returns. However, the high concentration of ownership in the form of high promoter holdings calls for addressing this aspect through the lens of principal–principal agency conflicts (Young, Peng, Ahlstrom, Bruton, & Jiang, 2008).

As a consequence of high promoter holdings in majority of the Indian firms, two sets of principals emerge, that is, promoters who are often the managers and the other set of shareholders who have a substantial yet minority stake in the firm. In such a setting, there is a greater probability that the promoters ignore the interests of the minority shareholders, thereby, giving rise to principal–principal agency conflicts (Dharwadkar, George, & Brandes, 2000; Morck, Wolfenzon, & Yeung, 2005; Young et al., 2008). Corporate actions like M&A deals provide an important opportunity to understand the presence and extent of these conflicts. We posit that M&A deals by bidders with high ownership concentration with promoters should not be received positively due to the possible conflict of interest between the two sets of principals of bidding firms.

Hypothesis 3: Deals announced by bidders with high promoter holdings would be received negatively.

The ‘free cash flow’ hypothesis implies that bidding firms with an excess free cash flow (Jensen, 1986) on their books or underutilised debt capacity would prefer to offer cash over stock. Martin (1996) and Zhang (2001) show empirical support for this hypothesis. In the presence of high promoter holdings and lack of debt funding, internally generated cash is likely to be the only source of funds for making cash offers. Hence, the availability of liquid cash prior to undertaking an M&A deal is likely to motivate bidders to offer cash. We test this hypothesis by using a liquidity measure (Liquidity) estimated as cash and marketable securities scaled by the total assets of the acquirer.

Hypothesis 4: Higher pre-announcement liquidity would make cash offers more likely.

‘Investment opportunity’ hypothesis implies that firms with prospects of better investment opportunities would keep their unused debt capacity and excess cash flows intact, so that they can use their internally generated funds or raise debt to make investments when required. This encourages such firms to offer stock over cash. Martin (1996) empirically observes this phenomenon. Similar to Martin (1996), we hypothesise that firms with opportunities to invest in positive net present value (NPV) projects, as suggested by their past sales growth, would prefer to offer stock.

Chatterjee and Kuenzi (2001) suggest that in the presence of investment opportunities use of stock should not signal negative information; however, they find little empirical support for this hypothesis. Since the primary motivation for such firms for offering stock is not its overvaluation, we hypothesise that stock offers by acquirers with potential for better investment opportunities would be received positively by investors.

Hypothesis 5: Firms with greater investment opportunities would offer stock.

Hypothesis 6: Deals announced by a bidder with greater investment opportunities would be received positively.

The target company’s ‘listing status’ has also contradictory implications for the choice of payment method. If the target is a private company, then Faccio and Masulis (2005) suggest that concern for dilution of ownership in favour of another block holder, that is, a private company’s shareholder with concentrated ownership, might discourage bidders to offer stock. Contrary to this, Draper and Paudyal (2006) find empirical support for the direct relationship between a target companies’ listing status and stock offer. They argue that since the information asymmetries in case of unlisted targets are high, the bidder would offer stock to make use of the contingent pricing effect. Since, Indian bidders have high ownership concentration which is likely to make them averse to stock offers due to the dilution of stake, we believe that the argument proffered by Faccio and Masulis (2005) is more likely to hold in the given context. Further, if a target firm is unlisted, then the shareholders of such a company might see a takeover as an exit opportunity if they are offered cash.

Hypothesis 7: Bidders would offer cash to acquire privately held targets.

3.1. Mergers and Acquisitions Announcement Effects

We study if the choice of the payment method leads to value creation, destruction or retention of bidder wealth. For this, we use the event study methodology as prescribed by Brown and Warner (1985), MacKinlay (1997), and Kothari and Warner (2007).

To study the announcement effects of M&A deals on the bidder stock returns, we use the standard market model (model 1) to calculate the expected returns; subsequent to which we calculate abnormal returns (model 2) and cumulative abnormal returns (model 3) abbreviated as AR and CAR, respectively.

E (R_{i t}) = α + β R_{m t} ​

(1)

A R_{i t} = R_{i t} - E (R_{i t}) ​

(2)

C A R_{i}^{T} = \sum_{t = t_{1}}^{t_{2}} A R_{i t} ​

(3)

where E(R_it) is the expected return of a bidding firm for an event i, R_mt is the return on market portfolio for day t, and R_it is the actual return of the bidder for the event i. AR_it is the abnormal return for the event i on the day t; it is the difference between the actual returns and the estimated returns from our market model.

The length of the estimation period for the model 1 is 200 days, prior to the t – 7 day (t is the event day), that is, the estimation period is from t – 207 to t – 8 days (Brown & Warner, 1985; Kothari & Warner, 2007; MacKinlay, 1997). The variable $C A R_{i}^{T} $ is the cumulative abnormal return for an event window T. We have calculated the CAR for different event windows that is different combinations of days before and after a deal announcement. In this part, we test the null hypothesis that the mean CAR is zero.

3.2. Determinants of the Announcement Effects and the Payment Method

We study the factors that explain announcement returns and investigate if the payment method is one of the factors that could explain the short-term shareholder wealth effects. Thus, we employ a cross-sectional ordinary least square (OLS) regression analysis, with robust standard errors, to study the effects of event specific factors and acquirer characteristics on the abnormal returns around the announcements. Our cross-sectional OLS regression model is as follows:

\begin{matrix} C A R_{i}^{T} = α + β_{1} F i n_{i} + β_{2} \Pr o m o t e r H o l d i n g s_{i} + β_{3} Re l a t e d n e s s_{i} \\ + β_{4} P e r c e n t a c q .26 D u m m y_{i} + β_{5} Re ​ l a t i v e s i z e_{i} \\ + β_{6} D e b t - t o - e q u i t y_{i} + β_{7} I n t . t o B o r r o w i n g s D u m m y_{i} \\ + β_{8} \Pr i c e - t o - b o o k r a t i o_{i} + β_{9} 5 Y R C A G R Re ​ v e n u e_{i} \\ + β_{10} I n d u s t r y C o n t r o l s_{i} + β_{11} Re ​ c e s s i o n Y r . D u m m y_{i} + e_{i} \end{matrix}

(4)

where $C A R_{i}^{T} $ is the cumulative abnormal return for observation i calculated over the event window T; $C A R_{i}^{T} $ is the same as CAR (t₁,t₂), where period t₁ to t₂ are represented by an event window T. Fin_i is the method of financing, defined as a binary variable, assuming value one if it is a stock offer and zero if it is a cash offer. Promoter Holdings_i is the percentage of promoter holdings in the bidding firm.

Relatedness_i is the industry relatedness dummy variable, assuming value zero if it is a bidding firm and the target are in the same industry as per three-digit SIC code; one otherwise. Percent acq.26 Dummy_i is a dummy variable based on the percentage of stake acquired in a deal; it assumes value one if the per cent acquired exceeds 26 per cent; otherwise it takes value zero. We have also used the continuous variable per cent acquired as a control variable in place of the dummy variable for this deal characteristic. Relative size_i is the relative size of the transaction measured as the ratio of the value of a transaction over the market value of its acquirer. Debt – to – equity_i is the debt–equity ratio of the bidding firm.

Int.to Borrowings Dummy_i is a dummy variable, which assumes the value one if the acquirer’s cost of debt, as measured by the interest expense by total borrowings, before the deal announcement, is more than the median cost of debt. 5 YR CAGR Revenue_i, is the variable that measures investment opportunities and is the compound annual growth rate of sales of an acquirer for five years prior to the acquisition.

Industry Controls_i are the dummy variables for relevant industries (textiles and IT & Software), assuming value one if a particular acquirer belongs to that industry; zero otherwise. Recession Yr.Dummy_i is a dummy variable to control for recession years (2007, 2008 and 2009). Model III in the OLS regression table (Table 4) with recession years control has 2007 and 2008 as recession years; model 4 and model 6 have 2008 and 2009 as recession years and model 5 has 2007, 2008 and 2009 as recession years. The OLS regression results with robustness tests (Table 5) and the logistic regression results (Table 7) have 2008 and 2009 as recession years. We have considered appropriate transformations for different variables used in the regression models.

To study the determinants of the payment method that is stock offer versus cash offer, we use the following logistic regression:

\begin{array}{l} \begin{matrix} F i n_{i} = α + β_{1} \Pr o m o t e r H o l d i n g s A c q 50_{i} \\ + β_{2} L i q u i d i t y_{i} + β_{3} Re l a t e d n e s s_{i} \\ + β_{4} P e r c e n t a c q u i r e d_{i} + β_{5} T ​ \arg ​ e t L i s t i n g_{i} \\ + β_{6} D e a l S i z e_{i} + β_{7} C r o s s B o r d e r_{i} \\ + β_{8} D e b t - t o - e q u i t y_{i} + β_{9} 5 Y R C A G R Re ​ v e n u e_{i} \end{matrix} \\ \begin{matrix} + β_{10} B u ​ \sin ​ e s s G r o u p_{i} + β_{11} O p e r a t i n g \Pr ​ o f i t A c q u i r e r_{i} \\ + β_{12} I n d u s t r y C o n t r o l s_{i} + β_{13} Re ​ c e s s i o n Y r . D u m m y_{i} + e_{i} \end{matrix} \end{array}

(5)

Fin_i, the dependent variable, is the method of payment, defined as the binary variable, assuming the value one if it is a stock offer, and zero if it is a cash offer. Promoter Holdings Acq50_i is the percentage of promoter holdings if the percentage of stake acquired is 50 per cent or more. This variable assumes value zero for the observations where the percentage of stake acquired is less than 50. Liquidity_i is the ratio of cash and marketable securities over total assets of an acquirer.

Target Listing_i is the dummy target’s listing status, which assumes value one if the target company is listed; otherwise it takes value zero. Deal Size_i is the log-transformed transaction value of a deal, and Cross Border_i is a dummy variable which assumes value one if a deal is a cross-border deal; otherwise it takes value zero. Business Group_i is a dummy variable to identify the business group affiliated bidders; it assumes value 1 if an acquirer is a business group affiliated firm; otherwise it takes value 0. Operating Profit Acquirer_i is acquirer’s operating profit measured as the EBITDA margin.

3.3. Data

Our data set for event study analysis comprises M&A deals of publicly listed Indian acquirers from 1995 to 2015. However, for multivariate analysis of the announcement effects and the choice of payment method, the sample period is from 2001 to 2015. The data on M&A deals in India are taken from Thomson Reuters’ Thomson One database. We have taken bidder’s company financial information and the data on stock prices from the Prowess database of the Centre for Monitoring Indian Economy (CMIE).

We have considered domestic and cross-border completed deals done by Indian acquirers. We have excluded the following types of deals: the acquisition of assets, buybacks, bankruptcy acquisitions and divestiture. We also exclude those deals where acquirer is an investor group and where the value of the transaction is unavailable. For a deal to be included in our data set, we must have all the required data with respect to relevant variables used in the study. We have used ‘Grubbs method’ for detection of outliers.

All the deals included in our data set are either cash or stock financed. We have not taken the mixed deals or the other alternate form of payments such as earn-outs, warrants and so on. We have excluded the deals with confounding corporate events (namely dividend announcements, results announcements or other deal announcements), happening seven days before or after the first deal announcement.

3.4. Characteristics of the Sample

Our event study sample comprises 379 cash deals and 61 stock deals (Table 1). Although, only approximately 14 per cent of the deals in the event study sample are stock deals; the average size of the stock deals (US$245.16 million) is larger than that of cash deals ( US$111.19 million). Therefore, despite the small number of stock deals, the high average value of these deals makes these deals economically significant and calls for inquiry into the factors leading up to the choice of payment.

Cash deal bidders have better liquidity position, that is, they are cash rich and acquire lesser stake in a target company compared to the stock deal bidders. Stock deal bidders acquire more listed targets than unlisted and are more levered than the cash deal bidders. Similar characteristics are observed in the sample used for the OLS (Table 2) and the logistic regressions. The summary statistics for the sample used for the logistic regression is not reported here for the sake of brevity.

Table 2.
Summary Statistics of the OLS Regression Data

Variable N Mean Median Std. Dev.

CAR14 282 0.011 0.005 0.051

Deal Size (US$ million) 282 154.004 10.770 823.403

Relative size 282 0.226 0.052 0.632

Fin. 282 0.113 0 0.318

Liquidity 281 0.028 0.001 0.065

Promoter Holdings 282 0.487 0.500 0.194

Non-promoter holdings 281 0.506 0.493 0.189

Institutional Holdings 282 0.222 0.219 0.161

Per cent acquired 282 0.535 0.500 0.324

Per cent owned 282 0.690 0.701 0.305

Per cent acq. 26 Dummy 282 0.734 1 0.443

Per cent acq. 50 Dummy 282 0.507 1 0.501

Debt-to-equity 282 0.693 0.515 0.668

Int. on Borrowings 266 0.078 0.075 0.035

Int. on Borrowings Dummy 282 0.511 1 0.501

Relatedness 282 0.560 1 0.497

Target Listing 282 0.355 0 0.479

Cross-border 282 0.337 0 0.473

Business Group 282 0.745 1 0.437

5-year CAGR Revenue 282 0.208 0.187 0.163

Operating Profit Acquirer 275 0.216 0.190 0.124

Price-to-book ratio 282 2.659 2.065 2.039

IT Software Ind. 282 0.060 0 0.238

Textiles Ind. 282 0.082 0 0.274

Variable	N	Mean	Median	Std. Dev.
CAR14	282	0.011	0.005	0.051
Deal Size (US$ million)	282	154.004	10.770	823.403
Relative size	282	0.226	0.052	0.632
Fin.	282	0.113	0	0.318
Liquidity	281	0.028	0.001	0.065
Promoter Holdings	282	0.487	0.500	0.194
Non-promoter holdings	281	0.506	0.493	0.189
Institutional Holdings	282	0.222	0.219	0.161
Per cent acquired	282	0.535	0.500	0.324
Per cent owned	282	0.690	0.701	0.305
Per cent acq. 26 Dummy	282	0.734	1	0.443
Per cent acq. 50 Dummy	282	0.507	1	0.501
Debt-to-equity	282	0.693	0.515	0.668
Int. on Borrowings	266	0.078	0.075	0.035
Int. on Borrowings Dummy	282	0.511	1	0.501
Relatedness	282	0.560	1	0.497
Target Listing	282	0.355	0	0.479
Cross-border	282	0.337	0	0.473
Business Group	282	0.745	1	0.437
5-year CAGR Revenue	282	0.208	0.187	0.163
Operating Profit Acquirer	275	0.216	0.190	0.124
Price-to-book ratio	282	2.659	2.065	2.039
IT Software Ind.	282	0.060	0	0.238
Textiles Ind.	282	0.082	0	0.274

Source: The authors.

Note: This table shows the summary statistics of the deals included in the OLS regression sample. The sample period is from 2001 to 2015.

4. Results and Discussion

4.1. Bidder Returns on Mergers and Acquisitions Announcements: Event Study

We present a summary of significant CARs in Table 3, categorised as per the method of payment. We observe that cash deals display positive abnormal returns across different event windows. These effects are more evident in the days prior to deal announcements, suggesting the likely presence of information leakage prior to the official announcements. The CARs for event windows comprising the days following deal announcements are not significant, therefore, we have not reported these values in this summary table; however, this result is an evidence of post-announcement market efficiency.

Table 3.
Event Study Analysis: Summary of Abnormal Returns to Bidders’ Shareholders

Method of Payment No. of Obs. Day 0 Day −1 to 0 Day −3 to 0 Day −5 to 0 Day −7 to 0 Day 0 to 1 Day −1 to 1 Day −3 to 3 Day −2 to 0 Day −2 to +1 Day −3 to +1 Day −3 to −1

Cash deals 379 Mean 0.0060 0.0113 0.0109 0.0097 0.0092 0.0078 0.0132 0.0093 0.0100 0.0118 0.0127 0.0049

p-value 0.0010 0.0000 0.0006 0.0071 0.0212 0.0029 0.0000 0.0238 0.0003 0.0004 0.0005 0.0539

Cash deals with negative CARs 46.7% 43.0% 44.1% 45.1% 45.1% 44.3% 42.7% 49.9% 40.9% 43.0% 43.3% 49.1%

Stock deals 61 Mean 0.0093 0.0073 0.0193 0.0202 0.0281 0.0080 0.0060 0.0331 0.0170 0.0156 0.0179 0.0099

p-value 0.0508 0.2842 0.0285 0.0713 0.0437 0.3850 0.5927 0.0393 0.0129 0.1556 0.1462 0.1778

Stock deals with negative CARs 44.3% 47.5% 44.3% 44.3% 39.3% 49.2% 52.5% 44.3% 44.3% 49.2% 41.0% 50.8%

Cash– stock 379 & 61 Diff of Means −0.0033 0.0040 −0.0084 −0.0105 −0.0189 −0.0002 0.0072 −0.0238 −0.0070 −0.0038 −0.0052 −0.0050

H_a: diff ! = 0 p-values 0.4969 0.5479 0.3278 0.2869 0.0967 0.9842 0.4104 0.0469 0.3444 0.6840 0.6141 0.4672

Method of Payment	No. of Obs.		Day 0	Day −1 to 0	Day −3 to 0	Day −5 to 0	Day −7 to 0	Day 0 to 1	Day −1 to 1	Day −3 to 3	Day −2 to 0	Day −2 to +1	Day −3 to +1	Day −3 to −1
Cash deals	379	Mean	0.0060	0.0113	0.0109	0.0097	0.0092	0.0078	0.0132	0.0093	0.0100	0.0118	0.0127	0.0049
		p-value	0.0010	0.0000	0.0006	0.0071	0.0212	0.0029	0.0000	0.0238	0.0003	0.0004	0.0005	0.0539
Cash deals with negative CARs			46.7%	43.0%	44.1%	45.1%	45.1%	44.3%	42.7%	49.9%	40.9%	43.0%	43.3%	49.1%
Stock deals	61	Mean	0.0093	0.0073	0.0193	0.0202	0.0281	0.0080	0.0060	0.0331	0.0170	0.0156	0.0179	0.0099
		p-value	0.0508	0.2842	0.0285	0.0713	0.0437	0.3850	0.5927	0.0393	0.0129	0.1556	0.1462	0.1778
Stock deals with negative CARs			44.3%	47.5%	44.3%	44.3%	39.3%	49.2%	52.5%	44.3%	44.3%	49.2%	41.0%	50.8%
Cash– stock	379 & 61	Diff of Means	−0.0033	0.0040	−0.0084	−0.0105	−0.0189	−0.0002	0.0072	−0.0238	−0.0070	−0.0038	−0.0052	−0.0050
H_a: diff ! = 0		p-values	0.4969	0.5479	0.3278	0.2869	0.0967	0.9842	0.4104	0.0469	0.3444	0.6840	0.6141	0.4672

Source: The authors.

Notes: This table displays the CAR of the acquirers over different event windows based on the method of payment. We have estimated the expected returns based on the standard market model and have calculated the abnormal returns as the difference between the actual returns and the expected returns. In this table, we have reported results only for those event windows where CARs are significantly different from zero, either for the cash deals or for the stock deals.

The stock deals in our sample present non-negative returns for most of the event windows. This is an anomaly and is in contradiction to the empirical evidence on stock deals for developed countries that is predominantly the USA, the UK and Canada (Draper & Paudyal, 1999; Travlos, 1987; Trifts, 1991). In the discussion further, we have attempted to explain how these positive abnormal returns are justified in an emerging market like India.

In India, as per RBI regulations, banks are prohibited from funding domestic M&A deals, and the Indian debt capital market is also not yet very developed (Reserve Bank of India, 2007), which implies that bidders seeking funds for doing onshore acquisitions will have to rely on internally generated funds. The cash rich companies would offer cash payment, but the companies that are cash poor would offer stock payment. It also implies that some of the stock deals could be ‘pseudo-cash’ deals, that is, there is unused debt capacity on their balance sheet, yet they are unable to access debt due to its limited availability. Thus, we can infer that the use of the stock payment might not be viewed as a signal of overvaluation. Stock deals could then possibly receive non-negative reaction from market. This also suggests that overvaluation of acquirer’s stock might not be able to explain the abnormal returns or the payment method choice in Indian context. We substantiate these arguments with a further analysis of stock deals in Section 4.3.

4.2. The Results of Cross-sectional Regression Analysis

The regression analysis is done on a sample of 282 deals, of which 11 per cent deals are stock deals. Table 4 presents OLS regression results that help us understand the factors that affect deal announcements. All the models in the table have cumulative abnormal return observed over three days (from day –2 to day 0) as the dependent variable.

Method of payment, represented as Fin (0 for cash payment and 1 for stock), is a significant explanatory variable influencing the cumulative abnormal return. The results on this variable suggest that when a stock deal is announced, we expect lower abnormal returns on the announcement, and when a cash deal is announced, we expect higher abnormal returns. Partially, this result is in agreement with the predictions of the informational asymmetry theory and Hypothesis 1. However, it is important to note that, although the announcement effects on stock deals are predicted to be lower compared to the cash deals, yet we observe that they are non-negative, which is contrary to the predictions of the information asymmetry hypothesis.

Table 4.
Cross-sectional OLS Regression Results

Variables Model 1 Model 2 Model 3 Model 4 Model 5 Model 6

Fin. −0.0172 −0.0177 −0.0164 −0.0172 −0.0177 −0.0182

[0.031] [0.026] [0.041] [0.032] [0.026] [0.022]

Promoter Holdings 0.0175 0.0169 0.0171 0.0173 0.0169 0.0168

[0.249] [0.267] [0.260] [0.256] [0.268] [0.277]

Relatedness −0.0054 −0.0049 −0.0050 −0.0050 −0.0049 −0.0055

[0.363] [0.436] [0.424] [0.425] [0.438] [0.384]

Per cent acq. 26 Dummy 0.0201* 0.0200* 0.0197* 0.0197* 0.0200*

[0.002] [0.002] [0.002] [0.003] [0.002]

Per cent acquired 0.0277

[0.023]

Relative size 0.0032 0.0032 0.0030 0.0033 0.0032 0.0034

[0.035] [0.032] [0.046] [0.031] [0.036] [0.027]

Debt-to-equity 0.0042 0.0058 0.0045 0.0055 0.0057 0.0052

[0.616] [0.495] [0.592] [0.514] [0.504] [0.534]

Int. on Borrowings Dummy −0.0065 −0.0064 −0.0071 −0.0062 −0.0065 −0.0064

[0.262] [0.270] [0.232] [0.288] [0.264] [0.271]

Price-to-book ratio −0.0043 −0.0048 −0.0067 −0.0045 −0.0049 −0.0045

[0.459] [0.426] [0.268] [0.450] [0.420] [0.446]

5-year CAGR Revenue 0.0234 0.0231 0.0211 0.0264 0.0228 0.0265

[0.274] [0.280] [0.322] [0.234] [0.306] [0.233]

IT Software Ind. 0.0034 0.0039 0.0040 0.0034 0.0033

[0.818] [0.794] [0.789] [0.819] [0.825]

Textiles Ind. −0.0058 −0.0057 −0.0064 −0.0058 −0.0076

[0.636] [0.643] [0.602] [0.640] [0.548]

Recession Year-diff.rec.yrs 0.0087 −0.0063 0.0006 −0.0074

[0.287] [0.477] [0.938] [0.394]

N 282 282 282 282 282 282

Adj. R² 0.0730 0.0670 0.0680 0.0660 0.0640 0.0540

F 3.2590 2.8080 2.7140 2.6160 2.5680 2.4690

p-Value 0.0009 0.0018 0.0018 0.0026 0.0031 0.0045

Variables	Model 1	Model 2	Model 3	Model 4	Model 5	Model 6
Fin.	−0.0172**	−0.0177**	−0.0164**	−0.0172**	−0.0177**	−0.0182**
	[0.031]	[0.026]	[0.041]	[0.032]	[0.026]	[0.022]
Promoter Holdings	0.0175	0.0169	0.0171	0.0173	0.0169	0.0168
	[0.249]	[0.267]	[0.260]	[0.256]	[0.268]	[0.277]
Relatedness	−0.0054	−0.0049	−0.0050	−0.0050	−0.0049	−0.0055
	[0.363]	[0.436]	[0.424]	[0.425]	[0.438]	[0.384]
Per cent acq. 26 Dummy	0.0201***	0.0200***	0.0197***	0.0197***	0.0200***
	[0.002]	[0.002]	[0.002]	[0.003]	[0.002]
Per cent acquired						0.0277**
						[0.023]
Relative size	0.0032**	0.0032**	0.0030**	0.0033**	0.0032**	0.0034**
	[0.035]	[0.032]	[0.046]	[0.031]	[0.036]	[0.027]
Debt-to-equity	0.0042	0.0058	0.0045	0.0055	0.0057	0.0052
	[0.616]	[0.495]	[0.592]	[0.514]	[0.504]	[0.534]
Int. on Borrowings Dummy	−0.0065	−0.0064	−0.0071	−0.0062	−0.0065	−0.0064
	[0.262]	[0.270]	[0.232]	[0.288]	[0.264]	[0.271]
Price-to-book ratio	−0.0043	−0.0048	−0.0067	−0.0045	−0.0049	−0.0045
	[0.459]	[0.426]	[0.268]	[0.450]	[0.420]	[0.446]
5-year CAGR Revenue	0.0234	0.0231	0.0211	0.0264	0.0228	0.0265
	[0.274]	[0.280]	[0.322]	[0.234]	[0.306]	[0.233]
IT Software Ind.		0.0034	0.0039	0.0040	0.0034	0.0033
		[0.818]	[0.794]	[0.789]	[0.819]	[0.825]
Textiles Ind.		−0.0058	−0.0057	−0.0064	−0.0058	−0.0076
		[0.636]	[0.643]	[0.602]	[0.640]	[0.548]
Recession Year-diff.rec.yrs			0.0087	−0.0063	0.0006	−0.0074
			[0.287]	[0.477]	[0.938]	[0.394]
N	282	282	282	282	282	282
Adj. R²	0.0730	0.0670	0.0680	0.0660	0.0640	0.0540
F	3.2590	2.8080	2.7140	2.6160	2.5680	2.4690
p-Value	0.0009	0.0018	0.0018	0.0026	0.0031	0.0045

Source: The authors.

Notes: This table presents the results of the cross-sectional OLS regression (with robust standard errors) used to determine the factors affecting abnormal returns around M&A deal announcements. The dependent variable is cumulative abnormal return observed over three days, from day −2 to day 0 for all the models. The VIFs of the following models are in the acceptable range. The p-values are in brackets.

Promoter holdings show a positive relation with the abnormal returns, which implies that bidders with high ownership concentration could be regarded as better governed companies, as this facilitates alignment of the objectives of the owners and managers. Jensen and Meckling (1976) have argued that equity ownership of managers reduces the agency conflicts, and our results are consistent with this view. The market does not consider the deals done by bidders with high promoter stakes as value destroying, which contradicts our predictions based on the principal–principal agency conflicts (Hypothesis 3). However, the coefficient of this variable is not significant, which implies that the returns are not significantly affected by this variable.

Industry relatedness (Faccio & Masulis, 2005) does not explain the abnormal returns around deal announcements. If the deals are those where acquirers buy a substantial stake that is more than 26 per cent then such deals are received positively by the stock market. Similarly, deals, where the relative deal size is high, are received positively, too. We must note that bidder overvaluation and investment opportunity hypothesis (Hypothesis 6) fail to explain announcement returns. Our results are robust when we use different event windows for estimating CAR (Table 5).

4.3. Pseudo-Cash Deal Hypothesis

We hypothesise that the announcements of stock deals would not lead to negative investor reaction if stock payments are induced by debt-sourcing limitations faced by acquirers and not due to overvaluation reasons.

First, as observed in Table 1, stock deals are on an average larger in value terms as compared to cash deals. Also, as we discuss in the next section, the bidding firms tend to offer stock in larger deals (Table 7). Thus, it is only fair to assume that due to lack of debt funding from all possible sources, bidding firms have to offer stock payment if the size of the acquisition is large. Thus, the difference in the size characteristic of stock and cash deals, lends support to our hypothesis that the stock deals are more likely to be pseudo-cash deals.

Second, to be able to rule out the overvaluation as the motivation for stock payment, we check if there is any relationship between the high market-to-book ratio (i.e., overvaluation) of the acquirers and negative abnormal returns demonstrated by some of the stock deals in our sample. In Table 4, we do not find any significant relationship between the valuation factor and abnormal returns, when we control for relevant deal and firm characteristics.

Table 5.
Cross-sectional OLS Regression Results: Robustness Tests

Variables Model 1 Model 2 Model 3

Dependent Variable CAR Day −1 to 1 CAR Day −2 to 1 CAR Day −1 to 0

Fin. −0.0254 −0.0271 −0.0155

[0.024] [0.015] [0.034]

Promoter Holdings −0.0017 0.0048 0.0106

[0.932] [0.810] [0.459]

Relatedness −0.0053 −0.0068 −0.0037

[0.445] [0.354] [0.512]

Per cent acq. 26 Dummy 0.0158 0.0210* 0.0146

[0.031] [0.008] [0.013]

Relative size 0.0018 0.0026 0.0023*

[0.291] [0.149] [0.082]

Debt-to-equity 0.0123 0.0110 0.0066

[0.184] [0.257] [0.406]

Int. on Borrowings Dummy −0.0082 −0.0120* −0.0022

[0.211] [0.080] [0.681]

Price-to-book ratio −0.0113* −0.0110* −0.0048

[0.082] [0.093] [0.414]

5-year CAGR Revenue 0.0068 0.0156 0.0165

[0.781] [0.539] [0.398]

IT Software Ind. 0.0199 0.0154 0.0083

[0.277] [0.463] [0.479]

Textiles Ind. −0.0016 −0.0140 0.0064

[0.897] [0.270] [0.581]

Recession Year −0.0089 −0.0047 −0.0094

[0.372] [0.668] [0.198]

N 282 282 282

Adj. R² 0.0440 0.0600 0.0440

F 2.0850 2.5070 1.9480

p-value 0.0181 0.0039 0.0292

Variables	Model 1	Model 2	Model 3
Dependent Variable	CAR Day −1 to 1	CAR Day −2 to 1	CAR Day −1 to 0
Fin.	−0.0254**	−0.0271**	−0.0155**
	[0.024]	[0.015]	[0.034]
Promoter Holdings	−0.0017	0.0048	0.0106
	[0.932]	[0.810]	[0.459]
Relatedness	−0.0053	−0.0068	−0.0037
	[0.445]	[0.354]	[0.512]
Per cent acq. 26 Dummy	0.0158**	0.0210***	0.0146**
	[0.031]	[0.008]	[0.013]
Relative size	0.0018	0.0026	0.0023*
	[0.291]	[0.149]	[0.082]
Debt-to-equity	0.0123	0.0110	0.0066
	[0.184]	[0.257]	[0.406]
Int. on Borrowings Dummy	−0.0082	−0.0120*	−0.0022
	[0.211]	[0.080]	[0.681]
Price-to-book ratio	−0.0113*	−0.0110*	−0.0048
	[0.082]	[0.093]	[0.414]
5-year CAGR Revenue	0.0068	0.0156	0.0165
	[0.781]	[0.539]	[0.398]
IT Software Ind.	0.0199	0.0154	0.0083
	[0.277]	[0.463]	[0.479]
Textiles Ind.	−0.0016	−0.0140	0.0064
	[0.897]	[0.270]	[0.581]
Recession Year	−0.0089	−0.0047	−0.0094
	[0.372]	[0.668]	[0.198]
N	282	282	282
Adj. R²	0.0440	0.0600	0.0440
F	2.0850	2.5070	1.9480
p-value	0.0181	0.0039	0.0292

Source: The authors.

Notes: This table presents the robustness tests of the results of the cross-sectional OLS regression analysis. The dependent variable that is the cumulative abnormal return, observed over different event windows is considered for the robustness tests. The p-values are in brackets. Note that *p < 0.1, **p < 0.05 and ***p < 0.01.

Further, we conduct the difference of means tests to determine if the difference in the mean of the valuation factor (price-to-book ratio) of the stock deals with negative announcement returns, and the mean of the valuation factor of the stock deals with positive announcement returns, is significantly different from zero. The results of the student t-test are presented in Table 6 (Panels A, B and C). We compare the stock deals with the most negative and the most positive abnormal returns, that is, the deals at the extreme end of the abnormal-returns spectrum and test if the valuation factor (market-to-book) is significantly different in these subsamples. The means of these subsamples suggest that there is a negative association between the market-to-book ratio and abnormal returns, but the difference of these means is not significant. Thus, we observe that there is no difference in the valuations of the most-positive return and the most-negative return stock deals.

Additionally, we also compare market-to-book ratios of all the positive abnormal return stock deals with all the stock deals exhibiting negative abnormal returns. In all the cases, we observe that there is no significant difference in the pre-announcement acquirer valuations of the stock deals with negative abnormal returns and the stock deals with positive abnormal returns. Moreover, the association of acquirer’s liquidity with the likelihood of cash offer, although insignificant (presented in Table 7 and discussed in the next section), also suggest that firms that offer stock payments are low on internal liquidity.

One could argue that the cash deal bidders were firms that had better access to debt markets than their counterparts who offer stock payment. To verify this notion, we looked at the sources of new debt for cash deal bidders up to a year prior to a deal announcement. We observed that most of the new debt was raised through the bank route for funding organic growth.

Further, a counter argument to the pseudo-cash deal hypothesis is that some cash deals could be ‘pseudo-stock’ deals. One cannot deny the possibility that a bidder could have raised equity to finance a deal, and if that is the case, then such cash deals could be aptly termed as pseudo-stock deals. This idea led us to examine if there are significant rights issues in the period prior to a deal. Only in some cases of cash deals do we observe this phenomenon, that is, there are rights offerings made prior to a cash deal.² However, the value of such right issues when compared to the deal value is quite insignificant, and hence, we do not find any incidence of pseudo-stock deals in our data.

Table 6.

Difference of Means Tests to Identify Differences in Bidder Valuations in Stock Deals

Panel A: Extreme 7 Stock Deals
Variable	N	Diff. of Means	T-stat	P-value
CAR Day −2 to 0	(7, 6)	0.2164	0.3331	0.7453
CAR Day −1 to 1	(7, 7)	1.0057	1.2312	0.2418
CAR Day −2 to 1	(6, 7)	0.5679	0.7365	0.4769
Panel B: Extreme 10 Stock Deals
Variable	N	Diff. of Means	T-stat	P-value
CAR Day −2 to 0	(10, 9)	−1.1422	−0.975	0.3432
CAR Day −1 to 1	(9, 10)	−0.7023	−0.4306	0.6722
CAR Day −2 to 1	(9, 10)	−0.9953	−0.6138	0.5475
Panel C: All Stock Deals
Variable	N	Diff. of Means	T-stat	P-value
CAR Day −2 to 0	(22, 27)	−1.0809	−1.3404	0.1866
CAR Day −1 to 1	(22, 27)	−0.4185	−0.5107	0.6119
CAR Day −2 to 1	(25, 24)	−1.2290	−1.5408	0.1301

Source: The authors.

Notes: This table presents the output of the difference of means of market-to-book ratio to determine if the average valuations of the negative return deals and the positive return stock deals are significantly different from zero. The null hypothesis for the t-test is: the difference of means is 0. N is the number of deals in the subsample for which the valuation ratios are available, where the first figure represents the deals in the negative return sample and the second figure represents the deals in the positive returns subsample.

Thus, the aforementioned analysis and arguments help us to claim that these stock deals in India are, in fact, pseudo-cash deals.

4.4. Determinants of the Choice of Payment Method: Logistic Regression Results

This section discusses the results of the logistic regression (Table 7). Model 1 is the base model, and the subsequent models are augmented versions of the base model. Promoter Holdings Acq50 is a significant explanatory variable in all the models. Thus, in confirmation with our Hypothesis 2, the results suggest that the higher promoter holdings of a bidder leads to a lower likelihood of stock offers when per cent acquired is more than 50. This result finds support in the ownership hypothesis (Amihud et al., 1990; Stulz, 1998) which suggests that insider owners, in our case promoters, would be reluctant to dilute their stake.

Table 7.
Logistic Regression: Determinants of the Payment Method in M&A

Variables Model 1 Model 2 Model 3 Model 4

Promoter Holdings Acq50 −3.284* −3.264* −3.200* −3.878*

[0.001] [0.001] [0.002] [0.004]

Liquidity −1.904 −1.752 −1.896 −1.6790

[0.114] [0.155] [0.133] [0.295]

Relatedness −0.334 −0.346 −0.318 −0.0469

[0.361] [0.347] [0.402] [0.913]

Per cent acquired 9.056* 8.995* 8.857* 9.487*

[0.000] [0.000] [0.000] [0.000]

Target Listing 2.596* 2.606* 2.591* 2.667*

[0.000] [0.000] [0.000] [0.000]

Deal Size 0.245 0.260* 0.241** 0.228*

[0.010] [0.009] [0.017] [0.054]

Cross-border −4.486* −4.461* −4.393* −4.351*

[0.003] [0.004] [0.005] [0.009]

Debt-to-equity −1.038 −1.095* −0.930 −0.3850

[0.013] [0.007] [0.033] [0.459]

5-year CAGR Revenue 0.6790 0.6820 0.2320 0.8430

[0.580] [0.580] [0.865] [0.617]

Business Group −0.011 −0.002 −0.034 −0.1960

[0.979] [0.995] [0.935] [0.668]

Operating Profit Acquirer −0.270 −0.185 −0.0467

[0.379] [0.547] [0.890]

Price-to-book ratio −0.1310

[0.641]

IT Software Ind. 1.669 1.676 1.767 1.717*

[0.019] [0.018] [0.020] [0.061]

Recession Year 0.6690 0.8040

[0.182] [0.145]

N 370 370 370 287

Pseudo R² 0.4060 0.4090 0.4150 0.4430

χ ² 67.940 66.800 74.580 69.890

p-Value 0.0000 0.0000 0.0000 0.0000

Variables	Model 1	Model 2	Model 3	Model 4
Promoter Holdings Acq50	−3.284***	−3.264***	−3.200***	−3.878***
	[0.001]	[0.001]	[0.002]	[0.004]
Liquidity	−1.904	−1.752	−1.896	−1.6790
	[0.114]	[0.155]	[0.133]	[0.295]
Relatedness	−0.334	−0.346	−0.318	−0.0469
	[0.361]	[0.347]	[0.402]	[0.913]
Per cent acquired	9.056***	8.995***	8.857***	9.487***
	[0.000]	[0.000]	[0.000]	[0.000]
Target Listing	2.596***	2.606***	2.591***	2.667***
	[0.000]	[0.000]	[0.000]	[0.000]
Deal Size	0.245**	0.260***	0.241**	0.228*
	[0.010]	[0.009]	[0.017]	[0.054]
Cross-border	−4.486***	−4.461***	−4.393***	−4.351***
	[0.003]	[0.004]	[0.005]	[0.009]
Debt-to-equity	−1.038**	−1.095***	−0.930**	−0.3850
	[0.013]	[0.007]	[0.033]	[0.459]
5-year CAGR Revenue	0.6790	0.6820	0.2320	0.8430
	[0.580]	[0.580]	[0.865]	[0.617]
Business Group	−0.011	−0.002	−0.034	−0.1960
	[0.979]	[0.995]	[0.935]	[0.668]
Operating Profit Acquirer		−0.270	−0.185	−0.0467
		[0.379]	[0.547]	[0.890]
Price-to-book ratio				−0.1310
				[0.641]
IT Software Ind.	1.669**	1.676**	1.767**	1.717*
	[0.019]	[0.018]	[0.020]	[0.061]
Recession Year			0.6690	0.8040
			[0.182]	[0.145]
N	370	370	370	287
Pseudo R²	0.4060	0.4090	0.4150	0.4430
χ ²	67.940	66.800	74.580	69.890
p-Value	0.0000	0.0000	0.0000	0.0000

Source: The authors.

Notes: The table presents the results of the logit regression model used to study the determinants of the choice of payment method. The dependent variable is the method of payment which takes the value one if it is a stock offer, and zero if it is a cash offer. The VIFs of the following models are in the acceptable range. The p-values are in brackets. Note that *p < 0.1, **p < 0.05 and ***p < 0.01.

Liquidity displays a negative relation with the likelihood of a stock offer, thus, suggesting that the higher the liquidity the lower is the likelihood of a stock offer. However, this result fails to confirm the cash flow hypothesis (Jensen, 1986; Martin, 1996; Zhang, 2001), since the coefficient is not significant (Hypothesis 4).

Higher debt-equity ratio predicts a higher likelihood of cash offers, which is contrary to the observations in Faccio and Masulis (2005) and Alshwer, Sibilkov, and Zaiats (2011). The percentage of stake acquired in a deal shows a positive relation with the likelihood of a stock offer. Similarly, the log of deal size has a positive relation with the likelihood of a stock offer. For bigger deals, or deals that involve higher stake purchase, finding internal accruals to match the size could be a challenge.

The unlisted target shareholders might consider a takeover offer as an exit opportunity, and hence a target’s listing status could motivate bidders to offer cash. Similarly, listed company target shareholders would not have a problem accepting a stock swap arrangement, since exit is not an issue for them. Conforming to this explanation, we find that if a target is a listed company, there is a higher likelihood of a stock offer. Our results are consistent with Faccio and Masulis (2005), who argue that bidders offer cash to ‘avoid forming of a new block-holder’; this argument is also relevant from the Indian context of high insider ownership.

The Indian companies have been shopping abroad for suitable targets, and the preferred mode of payment in such deals has been cash. Arranging bank funding is not a problem in international deals, and also, target shareholders in a foreign country would be reluctant to accept shares of a company listed abroad. Thus, if a deal is a cross-border deal, then there is a high likelihood of a cash offer.

We have also tested for the significance of bidder overvaluation in explaining the method of payment. As the results suggest, bidder overvaluation as measured by price-to-book ratio fails to explain the choice of cash payment or stock payment in M&A deals done by Indian acquirers. Industry relatedness dummy fails to explain the payment method choice phenomenon and so does the investment opportunity hypothesis variable (Hypothesis 5). Thus, this section, uncovers how the method of payment is chosen in the presence of high promoter ownership and lack of debt funding. Our results suggest that in the absence of internal accruals, bidders may offer stock, but they are more willing to do so if they are not acquiring a significant stake in a target company.

5. Conclusions

Against the backdrop of an emerging economy’s characteristics, such as missing market institutions and high economic growth, with India in focus, we have attempted to study the impact of two conflicting forces—high promoter holdings and lack of debt funding—on the medium of exchange and on bidder returns. We observe that deal announcement effects are positive for cash deals but mostly for the windows leading up to the event day. Thus, we find an evidence indicative of information leakage before deal announcements and that of market efficiency post such announcements. Additionally, contrary to the informational asymmetry hypothesis prediction, we find that stock deals display non-negative abnormal returns.

The structural factors specific to India help us to justify the above-mentioned anomaly. The Indian banks cannot fund local M&A; therefore, only when a deal is an international transaction, banks can lend funds. This feature along with high promoter holdings of Indian acquirers, lead us to proffer the ‘pseudo-cash deal hypothesis to explain the positive abnormal returns for stock deals. The absence of an established source of funding makes Indian companies depend on their cash reserves or turn to debt capital markets. Since the debt capital market in India is underdeveloped, bidders at times have to offer stock. It is important to note here that these bidders are offering stock not due to overvaluation reasons; hence, such deals do not carry signals that informational asymmetry models suggest. Therefore, we term such deals as pseudo-cash deals.

A characteristic unique to stock deals is that they are larger in size, and this factor lends further support to the possibility that the stock deals are, in fact, pseudo-cash deals. It is plausible to think that these deals would have been cash deals if the debt funding was available either through bank loans or through the capital market.

As expected based on the predictions of ‘ownership’ hypothesis, greater promoter holdings reduce the likelihood of a stock offer. However, the likelihood of a cash offer decreases with the increase in deal size and percentage of stake acquired. All the debt funding woes of Indian bidders vanish when they undertake cross-border deals; hence such acquisitions, even if some of them are large acquisitions, use cash as the method of payment. The investment-opportunity and industry-relatedness hypotheses, and bidder overvaluation, fail to explain the short-run shareholder wealth effects around deal announcements and also the choice of payment method in India. Therefore, in a market with institutional voids, we observe promoter ownership, deal size, per cent acquired, listing status of the target firm, cross-border nature of the deal and pre-announcement leverage as important factors driving the method of payment choice.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The authors received no financial support for the research, authorship and/or publication of this article.

Footnotes

Acknowledgements

The authors would like to thank the conference participants and discussants at the Midwest Finance Association’s Annual Meeting 2013 for their valuable inputs and feedback. We also thank the editors of the Journal of Emerging Market Finance and greatly acknowledge the helpful comments from an anonymous reviewer.

Notes

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