Impact of cross-country M&A on operating profit margin

The aim of this article is to check the impact of cross-country mergers and acquisitions (M&A) on the operating profit margin. The previous article explained the methodology followed in order to achieve the objectives of this research.

  1. Compare the pre and post-merger performance of selected cross-country mergers and acquisitions (M&A) deals.
  2. Examine the impact of the announcement of mergers and acquisitions (M&A) on the excess returns on the shares.

To achieve these objectives, quantitative analysis was carried in a series of articles. The present article deals with the analysis of the first objective.

In the previous article five main dependent variables were identified:

  1. operating profit margin,
  2. operating cost margin,
  3. EBITDA margin,
  4. current ratio and,
  5. shareholders’ wealth.

Selection of deals to test the impact of M&A on operating profit margin

For this purpose, 100 cross country M&A deals which occurred in Asian and European countries within the time period of 2000-2017 were selected on the basis of the deal size. The data of the financial ratios and the excess returns were collected from the database of the United Nations Conference on Trade and Development (UNCTAD) and the international merger market. In order to test the effect of the M&A on the operating profit of the acquiring companies, the independent variables that were employed in the study included:

  • size of the firm,
  • geographic expansion,
  • R&D innovation and,
  • leverage ratio.

Proposed hypothesis

In order to examine the impact of mergers and acquisitions on the operating profit of the firms, the following null hypothesis has been framed.

H0: There is no effect of cross -country mergers and acquisitions on operating profit in the period 2000- 2017.

The dependent variable is operating profit and the set of independent variables include the size of the firm, geographical expansion, R &D innovation and the leverage ratio. The data set is divided into two periods:

  1. The time period t-1 represents the pre-merger period and,
  2. the time period t+1 represents the post-merger period.

In the post-merger period, the deal size and the industry relatedness are also considered as independent variables. These variables could also impact the profitability of the firm after the M&A.

An empirical analysis of pre-merger performance

The following table represents the regression results of the acquiring firm before the deal (t-1). The independent variables included in the pre-merger period are:

  1. size of the firm,
  2. geographical expansion,
  3. R&D innovation and,
  4. leverage ratio.
Dependent variableIndependent variablesCoefficientP-valueR2-valueAdjusted R2-value
Operating profit marginSize of firm9.578362 0.047 0.8096 0.7115
  Geographical expansion 5.762598 0.407    
  R&D innovation 6.732632 0.36    
  Leverage ratio 0.883139 0    

Table 1: Premerger performance (t-1)

The R-squared and the adjusted R-squared values are 0.80 and 0.71 respectively. This indicates that the independent variables explain about 71% variation in the dependent variable and the model is good to explain the variation (Sarstedt M, Mooi, 2014). Thus, there is a probability that the null hypothesis can be rejected.

Out of the four variables; the size of the firm, geographic expansion, R&D innovation and leverage ratio, the results clearly indicate that only leverage ratio and size of the firm have a significant impact on the operating profit margin. This is because these variables have the ‘p’ value which is less than the significance value of 0.05. It meets the criteria of the confidence interval which is set at 95%.

The leverage ratio is positively related to growth

The coefficient of leverage ratio indicates that with one unit of increase in the leverage ratio, the operating profit increased by about 0.88 units. This means that as the debt of the firm increases, its operating profit rises and the leverage is positively related to the growth of the firm. This is supported by the study of Anton (2017). Furthermore, the study also highlighted that the leverage ratio is the ability of the firms to use their fixed cost assets or funds in order to magnify the operating profit or return to its shareholders. Fixed cost includes the advertising expenses, administrative cost, equipment and technology.  

Profits increase with the size of the firm

The coefficient for the size of the firm indicates that as the size of the firm increases by 1 unit, the operating profit increased by about 9.5 units. This means that as the firm size expands, it witnesses a rise in profit. This is consistent with the study conducted by Aydın Unal, Unal, & Isık (2017). Due to the presence of economies of scale large firms are able to enhance their profitability by minimizing the cost steaming from production processes. Moreover, large businesses exploiting their size may access the public debt markets in a much more easy and cheaper way in order to fulfil their financial needs. Furthermore, larger firms have higher market power, more diversified, employ better technology and thus contribute more to the firm profitability.

Other variables such as geographical expansion and R&D innovation have a ‘p’ value greater than 0.05 hence these variables do not have any impact on the acquiring firms’ and operating profit margin.  

Post-merger performance

The following table represents the regression results of the acquiring firm after the M&A deal. It is represented by ‘t+1’. The independent variables included in the post-merger period are:

  • size of the firm,
  • industry relatedness,
  • deal size,
  • geographical expansion,
  • R&D innovation and,
  • leverage ratio.
Dependent variableIndependent variablesCoefficientP-valueR2-valueAdjusted R2-value
Operating profit margin Size of firm 2.589111 0.31 0.7168 0.7067
  Industry relatedness 2.224647 0.504    
  Deal size 0.67506 0.031    
  Geographical expansion 4.480701 0.045    
  R&D innovation -2.84863 0.246    
  Leverage ratio -0.07189 0.615    

Table 2: Post-merger performance (t+1)

R-squared and the adjusted R-squared values are 0.71 and 0.70 respectively. This indicates that the independent variables explain about 70% variation in the dependent variable and the model is good enough to explain the variation.  Thus, there is a probability that the null hypothesis will be rejected.

The results clearly indicate that among all the independent variables, deal size and geographic expansion have a significant impact on the operating profit of the firm since both these variables have ‘p’ value which is less than the significance value of 0.05. It meets the criteria of the confidence interval which is set at 95%.

Profits increase with the deal size

The coefficient for the deal size indicates that with one unit of increase in deal size, the operating profit increased by about .67 units. This means that greater is the amount of deal size of the firm, higher is the level of operating profit for the firm. Deal size leads to major fluctuations in the prices of stock that affect the shareholder’s wealth. A greater value of deal size could be an indication of a profitable opportunity for investors. After the formation of the merger investors displays rational behaviour by increasing their investment.

Furthermore, this rise in the level of investment, in turn, results in profits for the firm (Visser & Nazliben, 2017). Osoro & Ogeto (2014) in their study, have taken shareholders wealth as a proxy of operational profit because it is the shareholder’s wealth maximization that translates into the company’s operating profit.

Geographical expansions have a significant impact on the operating profit

Another variable that has a significant impact on the operating profit of a firm is the geographical expansion. The coefficient value reflects that with one unit increase in the geographical expansion, the operating profit increased by 4.48 units. This means that as the firms expand geographically after M&A, the operating profit of the firm increases. After M&A, the amount of capital investment in the firm increases. With an increase in the amount of investment, the firm’s capability to expand also increases. As the firm expands its business in different geographical locations, the amount of revenue earned by the firm also rises. This, in turn, increases the prospects for long term growth of the firm (Piedo, 2014).

On the other hand, variables like the size of the firm, industry relatedness, R&D innovation and leverage ratio did not have any impact on the firm operating profit as they have the significant value which was greater than 0.05.

H0: There is no effect of cross -country mergers and acquisitions on operating profit margin in the period 2000-2017

Thus, the above hypothesis was rejected.

Deal size and geographical expansion affect operating profit margin after M&A

Operating performance describes the extent to which efficiency can be generated in the utilization of fixed assets. Enhanced efficiency can contribute to synergies in the form of reduced cost and increased revenue. This, in turn, improves the profitability and performance of the firm.

Operating profit margin is a good indicator of the profitability and efficiency of a firm. A high level of operating profit margin sets a long-term growth pathway for M&A. When the firm is operating as a single entity, the debt raised acts as an indicator of growth. Rise in the amount of debt among the cross-country mergers leads to a rise in the operating profit. This rise is attributed to the increase in the debt-financed investment that raises the capital of the firm. Additionally, a firm’s size is a clear indicator of its production capacity. However, in post-merger period, geographical expansion and deal size contributed to the rise in the profits of the firm. The amount of deal size acts as a major determinant for the fluctuations in the stock prices. On the other hand, geographical expansion allows firms to improve their production capacity. 

References

  • Anton, S. G. (2017). The Impact of Leverage on Firm Growth. Empirical Evidence from Romanian Listed Firms. Review of Economic and Business Studies, 9(2), 147–158. https://doi.org/10.1515/rebs-2016-0039
  • Aydın Unal, E., Unal, Y., & Isık, O. (2017). the Effect of Firm Size on Profitability: Evidence From Turkish Manufacturing Sector. Pressacademia, 6(4), 301–308. https://doi.org/10.17261/pressacademia.2017.762
  • Osoro, C., & Ogeto, W. (2014). Macro Economic Fluctuations Effects on the Financial Performance of Listed Manufacturing Firms in Kenya. International Journal of Social Sciences, 21(1), 26–40.
  • Piedo, J. (2014). Mergers and Acquisitions in International Business. Mergers and Acquisitions, 43–56.
  • Sarstedt M, Mooi, E. (2014). Conducting a Cluster Analysis. In A Concise Guide to Market Research. https://doi.org/10.1007/978-3-642-53965-7
  • Visser, B., & Nazliben, K. (2017). Post-merger operational performance of M&As and the influence of underlying merger purposes.

Ashni Walia

Research consultant at Project Guru
Ashni is a master of Economics from Amity University. She has been an active
member of Enactus and has participated in the 12th sustainability summit. She was also associated with the YES Foundation during her master’s programme. Apart from her interest in research, she has a keen interest in music and
reading fiction.
Ashni Walia

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