Inter-industry mergers and acquisitions have become common in today’s business world due to the benefits associated with them. The effect of mergers and acquisitions manifests in many ways determining a firm’s financial performance.
The aim of this study is to examine the effect of mergers and acquisitions in the post-deal financial performance of the firms. For this purpose, this study takes into consideration selected deals that have transpired in the last decade in Asia and Europe.
This article defines the methodology used to examine the effect of inter-industry mergers and acquisitions on financial performance. It defines the independent and dependent variables in the study, the data collection procedure, data sources and time period for which this data was collected. Subsequently, it highlights the modelled framework considered for the analysis.
Sampling data of 100 inter-industry mergers and acquisitions
For the present study, 100 inter-industry mergers and acquisitions which occurred in Asian and European countries within the time period of 2000-2017. In order to select the companies, a list of mergers have been prepared according to the deal size. The data of the financial ratios and the excess returns have been collected from the database of the United Nations Conference on Trade and Development and the international merger market. The data for all the dummy variables including:
- geographical expansion,
- investor’s protection,
- industry relatedness and,
- R&D innovation was collected.
Role of dummy variables
Dummy variables were given binary coding, i.e. value of 0 and 1.
The value of 1 indicates that the company is able to achieve the investor’s protection or industry relatedness or geographic expansion or R&D innovation as per the standards after the merger or acquisition has occurred. Otherwise, the value of the variable is 0.
The data for these dummy variables are collected from the annual reports of the acquiring companies. The collected data was entered into STATA software for further analysis.
Furthermore, in order to compare the pre-merger and post-merger performance, the data is collected for three time periods t, t-1 and t+1.
The time period t+1 represents its performance one year after the merger or acquisition occurred. t-1 indicates its performance one year before the merger or acquisition.
The data of these three time periods assisted in assessing the short-run impact of merger or acquisition on the acquiring firm’s performance. The short-run impact was measured because most of the negotiations or dealings are based upon economic and financial perspectives. However, the data for the dummy variables will remain constant for all three time periods t, t-1 and t+1.
Furthermore, in order to measure the shareholder’s value, the market-adjusted model is used to measure the cumulative returns on the shareholder value using 2 windows. These two windows are (-1,1) which is used to measure the pre-merger and the post-merger perfect during the one year. The second window is (-2,2), used to measure the pre-merger and the post-merger performance considering the time span of two years.
Impact of merger and acquisitions
The first objective of this study is to determine the impact of a merger or acquisition on the financial performance of the acquiring firm. For this purpose, its post-merger performance has to be compared with pre-merger performance on the basis of certain parameters.
The performance of an organization can be measured through a set of metrics which signify the profitability and growth of the organization. These metrics also measure the outcomes in terms of reliability, the cycle of production and returns to inventory. This section highlights the metrics, i.e. independent and dependent variables used in the study.
- Leverage ratio: The leverage ratio indicates the amount of debt that the firm has undertaken against the other accounts or assets in its financial statements. It indicates the extent to which the company’s assets and liabilities are financed through business operations (Al-Hroot 2016). Leverage ratio is an important indicator of a firm’s financial performance (Gadzo, 2018). The formula for leverage ratio is total debt / total equity.
- Deal size: Deal size acts as one of the significant components that measure the financial performance of the firm after the merger or acquisition (Moatti 2014). It highlights the potential of the firm to generate larger synergy opportunities. The deal size is given by the amount which the acquirer firm pays in order to gain the equity stake in the acquired firm.
- Size of the firm: The size of the firm is important to evaluate the degree of concentration within the industry (Cefis, Marsili, & Schenk, 2009). A large firm is any firm with a monthly turnover of more than USD 10,00,000. Dummy variables are used for the size of the firm wherein the value of 1 indicates that the firm is non-large. On the other hand, the value of 0 indicates that the firm is large.
- Industry relatedness: The financial performance of the firm could also be affected through inter-industry merger or acquisition (Poornima & Subhashini, 2013). If the merger is between two companies belonging to the same industry, it is a horizontal merger. If the deal has taken place between companies of different industries then it is a vertical merger. Annual reports of the acquirer and the acquiree firm indicate whether the merger is horizontal or vertical. Industry relatedness is evaluated using categorical binary code, i.e. if the merger is vertical then it is coded ‘0’ and if it is horizontal then it is ‘1’.
- Geographic expansion: Mergers and acquisitions allow the companies to expand their reach across the geographical areas, thus affecting their financial performance (Poornima & Subhashini, 2013). Annual reports of the firms are used to examine the extent of geographical expansion of companies after the merger. This variable takes the value 1 if the geographical expansion is in more than 5 countries. Otherwise, the value of this dummy variable is 0.
- R & D innovation: Technological advancement can deliver effective changes into the business operations which in turn improves the business performance Prasad & Sahay (2018). The annual reports of firms indicate the amount of investment made in research and development activities. If the amount of investment is more than 20% of the total investment, then this variable takes the value 1. Otherwise, it takes the value 0.
The dependent variable in this study is the financial performance of the firms. A company’s financial performance can be assessed in many ways. For the purpose of this study, the following indicators of financial performance are used as the dependent variable. The data for all the variables were extracted from the acquiring firms’ financial statements.
- EBITDA margin (Earnings before Interest, Tax, Depreciation and Amortization): EBITDA margin is one of the commonly used metrics denoting the financial performance of a firm. It refers to the ability of the firm to generate additional cash for the growth of the company Duggal (2015).
EBITDA margin = (Operating income + Depreciation + Ammortization) / Net sales
- Operating cost: It measures the cost used in the normal course of the business. It comprises of the expenses which are directly related to the production of goods and services. This cost is subtracted from the operating income to calculate the net profits.
Operating cost = Sales expenses + Management expenses + Labor cost
- Operating Profit margin: Operating profit margin is the profitability measure which is used to examine the percentage of profits produced by the companies. The operating profit is calculated by subtracting the operational expenses, interests and taxes from the gross profit (Eriotis, Frangouli, & Ventoura-Neokosmides, 2010).
Operating profit margin = Operating profit / Total revenue
- Current ratio: The current ratio is the ratio to which the current asset of a firm can be used to pay back liabilities Al-Hroot (2016).
Current ratio = Current assets / Current liabilities
The data collected was entered in MS Excel and was further imported in STATA for analysis. Correlation and multiple regression were used to examine the impact of merger and acquisitions performers on the profitability indicators:
- EBITDA margin,
- operating profit ratio,
- operating cost and,
- the current ratio.
For the regression analysis, three models were framed to measure premerger and post-merger performance. The first two models analyzed the impact of independent variables on the probability indicators in t-1 and t+1 time period. The last model includes the differenced values of the variables in the t+1 and t-1 time periods.
The values of the differenced models were used to measure the difference between the pre-merger and post-merger performance. Multivariate regression analysis was conducted to examine the impact of independent variables. Deal size and industry relatedness were not used in the models representing the pre-merger performance.
Impact of announcement
The second objective of this study is to examine the impact of the announcement of mergers and acquisitions on the excess returns of the shares. The data and analysis plan followed for this objective is vastly different from the first objective. The main data involved in the analysis of this objective is the stock prices of the acquiring firm post announcement of the merger. This is compared to its stock prices before the announcement.
The announcement of mergers and acquisitions lead to major fluctuations in the value as well as the price of stocks. These fluctuations in the current and expected future value of the stocks are referred to as the announcement effect (Harvey, 2010). Cumulative abnormal returns (CAR) value is used to calculate the daily excess returns on the stock prices.
- Excess returns: The excess returns are calculated using the following formula:
- Abnormal returns: The abnormal returns will be calculated as the difference of the daily excess returns and the expected returns of that period:
- Cumulative abnormal returns: The cumulative abnormal returns are calculated as:
The previous article highlighted that the formation of merger or acquisition has major impact on the shareholder value. This impact is attributed to the fluctuations in the stock market prices post the formation of the merger. In order to evaluate the fluctuations in the stock prices after the merger, the announcement effect was examined. Due to the announcement effect, the return on the stocks could increase or decrease depending on the market value of the firm.
- Al-Hroot, Y. A. K. (2016). The Impact of Mergers on Financial Performance of the Jordanian Industrial Sector. International Journal of Management & Business Studies, 6(1), 2230–9519.
- Cefis, E., Marsili, O., & Schenk, H. (2009). The effects of mergers and acquisitions on the firm size distribution. Journal of Evolutionary Economics, 19(1), 1–20. https://doi.org/10.1007/s00191-008-0105-9
- Duggal, N. (2015). Post Merger Performance of Acquiring Firms : A Case Study on Indian Pharmaceutical Industry. International Journal of Research in Management & Business Studies, 2(3), 24–28.
- Eriotis, N. P., Frangouli, Z., & Ventoura-Neokosmides, Z. (2010). Profit Margin And Capital Structure : The Journal of Applied Business Research, 18(2), 85–88.
- Gadzo, S. G. (2018). Degree of Leverage: Empirical Analysis from the Insurance Sector. Xlibris Corporation.
- Harvey, S. K. (2010). The Role of Mergers and Acquisitions in Firm Performance: A Ghanaian Case Study. Journal of Child Psychology and Psychiatry, 51(11), 1188–1197. https://doi.org/10.1111/j.1469-7610.2010.02280.x
- Moatti. (2014). Disentangling the performance effects of efficiency and bargaining power in horizontal growth strategies: an empirical investigation in the global retail industry. Strategic Management Journal, (August). https://doi.org/10.1002/smj
- Poornima, S., & Subhashini, S. (2013). Impact of Mergers and Acquisitions Across Industries in India. International Journal of Management Research and Development, 3(2), 113–125.
- Prasad, K., & Sahay, M. (2018). MERGERS AND ACQUISITIONS: Analysis on Indian merger and acquisition in India with reference from 2005-2015. 118(20), 4411–4417.