The “inconclusive” existing literature on long-term horizon studies of mergers is the motivation of this paper to reexamine the post-merger performance and explore the reasons of unsatisfactory performance. We test efficiency theory of mergers by examining the industry adjusted operating performance of mergers. Unlike the existing literature which examines the operating performance of mergers at end level (ROA or ROE), we not only examine the operating performance at end level but also analyze the performance at each stage of operation i.e . material, labor, overheads, tax, interest and sales. We do not find synergy creation at the end level ( i.e . ROA level). However, we observe synergy creation at tax and interest level and synergy destruction at labor and overheads level. The performance of different categories of mergers which are group/non-group mergers, related/unrelated mergers and BIFR/non-BIFR mergers is also examined. Factors explaining the post-merger profitability, efficiency and cash flows are also examined.
Mergers and acquisitions (M & As) have attracted international attention due to economic integration and removal of barriers to trade at the global level. Due to increasing competition, companies are competing not only in domestic markets but also in foreign markets to maintain a competitive edge. Different firms undertake mergers with different motives as explained by various theories behind merger motives. These theories are developed and tested by various researchers across the globe in different time periods. The various theories of mergers are efficiency theory, monopoly theory, raider theory, valuation theory, empire building theory, process theory, agency theory, etc. The most prominent among all the theories is efficiency theory. According to efficiency theory, mergers are planned and executed to achieve synergies. These synergies can be in the form of reduction in cost or increase in sales. However, this is not always observed, and so a question of relevance to ask of each deal is: “Does the merger provide benefits in the form of synergies?” Thus, in this paper, we make an attempt to find out, “Do we really achieve efficiency gains or reduction in costs after the merger?” In this way, this paper tests the efficiency theory of mergers in India.
The efficiency theory of mergers, which views mergers as effective tools to reap benefits of synergy, is still the basis of many merger studies. Though the efficiency theory of mergers has dominated the field of research on merger motives for many years, its empirical validity is still very limited. For testing the efficiency theory of mergers, various researchers have carried out event studies to analyze if there is a change in the efficiency of the firm after a merger in terms of creation of shareholders’ wealth. The results of event studies are more or less generalizable but the main drawback of such studies is that these are short term studies and deal only with the announcement period abnormal stock returns for both the target and bidder firm’s shareholders. Another limitation of event study is that the methodology cannot be used to examine the performance of unlisted companies. Thus, there is a need to understand the long-term financial performance of firms after mergers to know if mergers lead to efficiency gains in the form of synergies. Since, it takes long-time to fully realize the benefits of merger, if there are any; the studies with long-term horizon may provide better insights on whether mergers have served the intended purpose. This is one of the motivations for the present study in which we test efficiency theory of mergers by using long-term horizon studies/operating studies.
Even the existing literature on long-term horizon studies/operating studies is inconclusive. The studies which are based on pre- and post-merger financial/accounting measures do not provide clear evidence about the efficiency effects of mergers. Most of the studies find no significant change in the performance after merger whereas a few of the studies find that there is a decline in the performance after merger. These results raise a question, “If there are no efficiency gains in mergers, if there is no improvement in the performance of firms post- merger, then why are mergers still taking place at a rapid rate?” This question motivates us to test efficiency theory and reexamine the post-merger performance to find reasons for unsatisfactory performance.
The long-term horizon multi-industry studies show that many mergers are not successful. Unfortunately, we cannot infer from these studies whether mergers are efficient. Thus, we carry out our analysis in one industry because most of the previous studies are on multiple industries and only a very few studies on a single industry have given fruitful results and validated efficiency theory. According to [
So, the present study aims at testing the efficiency theory of mergers in the manufacturing sector of India by examining operating performance. We have broadly four objectives. One, we examine the impact of mergers on the operating performance of the acquiring companies. Two, we identify the sources of operating synergy created by merger and find out synergy creation at each stage of operation. For this, we decompose return on assets (ROA) into six cost and efficiency components which are at material level, labor level, overheads level, tax level, interest level and sales level. Three, we study the pattern of synergy creation at each stage of operation for different categories of mergers which are group versus non-group mergers, related versus unrelated mergers and BIFR versus non-BIFR mergers. Four, we examine the factors which explain the post-merger profitability and efficiency.
We consider the fact that the impact of merger is different in different categories of mergers which has also been ignored by many of the previous studies. We examine three kinds of mergers; one of them is country-spe- cific and found mainly in India. We compare related with unrelated mergers, group with non-group mergers and Board for Industrial and Financial Reconstruction (BIFR) with non-BIFR mergers. Related mergers are those mergers in which the acquirer and target operate in the same industry sector whereas in unrelated mergers acquirer and target both come from different industries. Group mergers are the mergers in which acquirer and target belong to same business group whereas in non-group mergers acquirer and target come from different business groups. BIFR category of mergers is a different story altogether. These mergers are unique and prevalent only in India. In this type of merger, a healthy company takes over a financially sick company which is suffering from losses in order to fulfill the mandatory order of Board for Industrial and Financial Reconstruction (BIFR). Savings in tax is the incentive for a healthy company to acquire loss-making company. Savings in tax results from the writing off accumulated losses of sick company from the profits of the healthy company or the acquirer. An important reason to examine the different categories of mergers is to understand the differences in mergers of developed and developing countries. Existence of family business groups is one of the important characteristics which differentiate business structure of developing country like India from many other developed countries. Unlike most of the developed countries but like many developing countries such as Japan, Korea, Turkey, Brazil, Israel, etc. India has high percentage of family business groups in India. Therefore, it is important to study group and non-group category of mergers. Moreover, prevalence of BIFR mergers only in India makes India different from rest of the world and hence, it is important to examine BIFR category of mergers independently. Since all categories of mergers are planned and executed with different motives, we cannot expect the same type of outcome from different types of mergers and hence, examination of different kinds of mergers in isolation is important. For instance, related mergers are undertaken to achieve operating synergy that could be in the form of reduction in cost or increase in sales whereas the main objective of unrelated merger is to achieve financial synergy which could be in the form of reduction in the financial cost. The objectives behind the group merger could be the use of resources of firms under the same business umbrella (group), access to internal capital markets, tunneling, etc. whereas the same may not be true for non-group mergers. Similarly, the objective of acquirer in BIFR merger is to get the tax advantage. All these reasons seek for examination of different types of mergers in isolation.
Although we do not find significant change in the end level (ROA, ROE, and Cash flows from operations divided by total assets) performance parameters but we observe significant differences in the decomposed parameters after merger. We find significant improvement in tax to sales and interest to sales and significant decline in labor to sales and overheads to sales in post-merger period in most of cases. The remaining two―material to sales and sales to assets do not show any significant change. The synergy creation at two or more stages of operation is neutralized by synergy destruction at other two stages of operation. Our results vary with respect to different categories of mergers. We also find that apart from the type of merger, various pre-merger cost specific parameters explain the post-merger profitability, efficiency and cash flows to assets.
The remainder of the paper is organized as follows: Section 2 provides a brief literature review and hypotheses are formulated in Section 3. Data and methodology is explained in Section 4 and results are discussed in Section 5. Finally, Section 6 concludes the paper.
In this section, we provide prior evidence related to our study. Prior evidence presents review of international as well as Indian studies which look at the impact of mergers on the operating performance of firms along with other related issues.
[
From international studies mentioned above, we find that majority of studies find that mergers do not significantly improve the operating performance of firms but Indian studies add few new dimensions to the literature. In Indian context [
On the basis of literature review, it can be said that many studies assess the economic impact of mergers on the performance by analyzing the changes in the profitability or other measures of the combined firm. Studies prior to early 90s are based on the analysis of accrual accounting measures and from 90s onwards, researchers have started using cash flow measures in addition to accrual accounting measures to examine the changes in the operating performance after merger. The first study that uses cash flow measures and has given new direction to this research is [
H1: There is no significant improvement in the operating performance of firms after merger.
While examining the impact of mergers on the operating performance of the acquiring firms, it is not sufficient to examine the end level performance parameters such as ROA, ROE and CFO alone. Instead, examination of operating performance ought to be completed only after examining performance at each stage of operation. According to [
H2: Mergers do not create synergy at any stage of operation.
One of the determinants of successful mergers is the type of merger. [
H3: There are no significant differences in pre-merger and post-merger performance of different categories of mergers-related/unrelated mergers, group/non-group mergers and BIFR/non-BIFR mergers.
The present study deals with the mergers which took place in post liberalization era in Indian manufacturing sector. The data consists of all the mergers which took place in manufacturing sector in India from April 1, 2000 to March 31, 2010. The time period is selected to focus on the mergers which took place after the economic reforms of 1991 and to have sufficient post-merger operating performance data. We restrict our study only to manufacturing companies in order to minimize the potential confounding of extraneous variables [
To examine the performance of different types of mergers, we classify our sample into three categories. On the basis of ownership group, first we classify our sample mergers into group and non-group mergers. We use the ownership classification given by Prowess database of CMIE (Centre for Monitoring Indian Economy) to find the ownership status of acquirer and target firms. Prowess gives a firm an ownership status as Private (Indian) if the firm is an independent firm and does not belong to any family business group whereas if the firm belongs to a particular business group then Prowess gives the name of that particular business group as the ownership status of the firm. Out of 62 mergers in our sample, 39 are group mergers and 23 are non-group mergers. Second, on the basis of relatedness of the nature of the business, we classify our sample mergers into related and unrelated mergers. We use National Industry Classification (NIC) given by Prowess database to classify mergers into related and unrelated mergers. NIC codes used in India are similar to Standard Industry Classification (SIC) codes used in U.S. to classify firms into different industries. The broad category of classification in SIC codes is called “Division” whereas it is called “Section” in NIC codes. In SIC codes, each division is further sub divided into various groups whereas in NIC codes, each section is further sub divided into various divisions. Our sample contains all the mergers of section C that is manufacturing section. We classify a merger as related merger if the five digit NIC codes of acquirer and target are same and unrelated merger if the five digit NIC codes of acquirer and target are different. According to the classification based on the related of the nature of the business, there are 46 related and 16 unrelated mergers in our sample. Most of mergers in our sample are concentrated in division 24 which is “manufacture of basis metals”. Third, we classify our sample into BIFR and non-BIFR mergers which are explained earlier. CMIE classify a merger as BIFR merger if the merger is on the order of BIFR. We have 10 BIFR mergers and 52 non-BIFR mergers in our sample.
It is obvious that the pre-merger (Pre1) and post-merger (Post2) operating performance of firms involved in merger could be affected due to economy wide and industry factors, or simply could be continuation of per merger performance. In order to control economy wide and industry factors, the study employs an adjusted performance measure while evaluating the post-merger operating performance. The study follows [
Financial data for five years prior and five years post-merger for each firm (62 acquiring firms, 66 target firms) and for each industry average is extracted from Prowess database of CMIE. The extracted financial data encompasses the period from 1999-2000 to 2009-2010. The end level operating performance parameters which are used in the study are: Return on Assets (ROA), Return on Equity (ROE) and Cash flow from operations to total assets (CFO/TA). All these measures are calculated for pre-merger and post-merger period. Pre-merger performance measure is the weighted average of acquirer and target firm(s), weights being assets for calculating weighted ROA and CFO/TA and equity for calculating weighted ROE. Post-merger parameter is the parameter of the acquirer (since target got merged into acquirer). Both pre-merger and post-merger parameters are adjusted against the industry averages each year. ROA is computed as ratio of profit after tax plus interest expense to total assets, which is given as ROA = (PAT + Interest expense)/Total Assets. ROE is computed as ratio of profit after tax minus preference dividend to net worth minus preference share capital, which is given as ROE = (PAT − Preference Dividend)/(Net Worth − Preference share capital). Cash flow from operations to total assets is net cash flow from operations divided by total assets. Net cash flow from operating activities is directly available in Prowess. It can also be calculated by using the following formula given by [
Cash flow from operations (CFO) = WCFO ± changes in (Trade receivables + Prepayments + Inventories + other receivables) ± changes in (Trade creditors + Interest received + Provision for employee entitlements + other creditors).
Working capital from operations (WCFO) = (Operating profit before tax + Interest expense +/− Extraordinary items + Depreciation + Loss on sale of assets and investment + other write off) − (Profit on sale of assets and investment).
In addition to end level parameters, we also examine synergy at each stage of operation by decomposing ROA into six sub level parameters: material to sales, labor to sales, overheads to sales, tax to sales, interest to sales and sales to total assets. These are the sources of economic gain/synergy on merger. All these parameters are calculated for pre-merger and post-merger period. Pre-merger parameter is the weighted average of acquirer and target(s), weights being combined sales of acquirer and target(s). Post-merger parameter is the parameter of the acquirer (since target gets merged into acquirer). Pre-merger parameters and post-merger parameters are adjusted against industry average each year.
1) Match paired t test: The paper examines the proposed hypotheses using statistical data based on mean. Matched paired t test is used to compare five pre-merger industry adjusted performance parameters and five post-merger industry adjusted performance parameters. The year “0” i.e., the year of event is excluded from the analysis. The year of event (year “0”) figures are affected by onetime merger cost incurred during the year. So, it is difficult to compare the results of year “0” with the other years. The test determines whether there is a significant change in the “before/after merger” performance and allows us to attribute the result to the merger. Match paired t test compares pre-merger and post-merger industry adjusted parameters for overall sample and also for different categories of mergers.
2) Cross Section Regression: While using the matched pair t test on mean basis, we assume that the pre- merger performance will continue in future. But it is unreasonable to assume that pre-merger performance will continue in post-merger period at a constant rate [
where, Postxi is the average post-merger industry adjusted performance parameter x for company i. Prexi is average pre-merger industry adjusted performance parameter x for company i. β1 represents the association between pre-merger and post-merger industry adjusted performance. A significant β1 indicates the continuance of pre-merger performance in the post-merger period. α1 is the intercept which is independent of the pre-merger performance and indicates the extent to which post-merger performance is a function of merger [
We use the following regression the find the factor which explain post-merger performance:
where,
company i.
Group is a dummy variable which takes the value 1 if the merger is group merger and 0 if the merger is non- group merger. Related is a dummy variable which takes the value 1 if the merger is related merger and 0 if the merger is unrelated merger. BIFR is a dummy variable which takes the value 1 if the merger is BIFR merger and 0 if the merger is non-BIFR merger. PublicAcquirer is also a dummy variable which takes the value 1 if the acquirer is public company and 0 if the acquirer is private company.
The multivariate regression is used in order to know the factors including type of merger which explain the post-merger profitability, efficiency and cash flows.
The section is divided into three sub sections. Section 4.1 presents the summary statistics of the measures of profitability, efficiency and size of acquirer and target on the basis of five year average before the merger. We measure profitability by using ROA, efficiency by using Sales/TA and size by using assets and sales of the companies engaged in merger. Section 4.2 presents the results of matched paired t test comparing the pre-merger industry adjusted performance and post-merger industry adjusted performance for the overall sample and also for the decomposed sample. The sample is decomposed into subsamples on the basis of types of mergers. These are group vs. non-group mergers, related vs. unrelated mergers and BIFR vs. non-BIFR mergers. Section 4.3 provides results of the regressions. Lastly, section 4.4 presents the overall results of synergy creation at each stage of operation for two categories of mergers: related/non-related mergers and group/non-group mergers in order to examine the differences in the motives of these two categories of mergers.