# Impact of cross-country M&A on current ratio

The previous article aimed to test the impact of **merger and acquisition (M&A)** activities on acquiring firms’ operating profit. A dataset containing the values of 100 M&A deals from Europe and Asia during 2007-2017 was chosen. It showed that **M&A** deals had a significant impact on the operating profit margins of the acquiring firm. In this article, the impact of **M&A** on the acquiring firms’ current ratio is tested.

It is one of the key ratios indicating the financial performance of a firm (Almajali, Alamro, & Al-Soub, 2012). It is also known as the liquidity ratio and refers to the ability of a business to pay for its short-term debts i.e. the debt obligations due in the next 12 months. Hence, this shows its ability to manage the working capital without the need for external finance. A higher current ratio means that firms will be better able to deal with unexpected contingencies during the times of low earnings (Liargovas & Skandalis, 2010). In this article quantitative analysis using regression is applied to the dataset to show the acquirer’s pre-merger and post-merger current ratio performance.

## Proposed hypothesis

In order to examine the impact of **M&A** on the current ratio of the firms, the following hypothesis is prepared:

H

_{0}: There is no effect of cross-country mergers and acquisitions on current ratio in the period 2000- 2017.

The data set is divided into two periods. The time period t-1 represents the pre-merger period and 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 **M&A**.

## An empirical analysis of pre-merger performance

The following table represents the regression results of the acquirer firm before the **M&A** which is represented by the t-1. The regression test was performed on STATA. The dependent variable is the current ratio and the set of independent variables include:

- size of the firm,
- geographical expansion,
- R &D innovation,
- leverage ratio.

Dependent variable | Independent variables | Coefficient | P-value | R^{2}– value | Adjusted R^{2}-value |
---|---|---|---|---|---|

CurrentRatio | Size of firm | -0.8343 | 0.771 | 0.7034 | 0.6997 |

Geographical expansion | -4.93139 | 0.074 | |||

R&D innovation | 1.794928 | 0.512 | |||

Leverage ratio | 0.85729 | 0.000 |

Table 1: pre-merger performance (t-1)

The R-squared and the adjusted R-squared values are 0.70 and 0.69 respectively. This indicates that the independent variables; the size of the firm, geographical expansion, R&D innovation, Leverage ratio, explain about 69% variation in the dependent variable i.e the CurrentRatio. This means that the model is robust enough to explain variation in the dependent variable (Mooi, 2014). Thus, there is a probability that the null hypothesis will be rejected.

## Variables affecting the pre-merger performance of acquiring firms

The results in the regression table above clearly indicate that only the leverage ratio has a significant impact on the current ratio of the firm. This is because the ‘p’ value of only the leverage ratio (0.000) is less than the significance value of 0.05. The other variables such as the size of the firm, geographical expansion and R&D innovation have a ‘p’ value greater than 0.05 indicating a non-significant impact on the current ratio. The coefficient of leverage ratio indicates that with one unit of increase in the leverage ratio, the CurrentRatio increases by about 0.85 units.

The leverage and the current ratio are generally interlinked. Firms hold these liquid assets to absorb the economic shocks and also the future fixed charges. A firm with high liquidity levels employs more equity so as to finance its activities that are persuading to low leverage levels (Owino, 2011). According to a study conducted by (Šarlija & Harc, 2012), firms with more of liquid assets or high liquidity ratio prefer a higher degree of leverage ratio without making any changes in the structure of their liquid assets.

## An empirical analysis of post-merger performance

The following table represents the STATA results of the acquiring firm’s performance in the post-merger period. The independent variables that can possibly affect the current ratio in the post-merger period included:

- size of the firm,
- industry relatedness,
- deal size,
- geographic expansion,
- R&D innovation,
- leverage ratio.

Dependent variable | Independent variables | Coefficient | P-value | R^{2}– value | Adjusted R^{2}-value |
---|---|---|---|---|---|

CurrentRatio | Size of firm | -0.06198 | 0.926 | 0.9132 | 0.9039 |

Industry relatedness | -0.52985 | 0.551 | |||

Deal size | 7.42E-06 | 0.005 | |||

Geographical expansion | -0.02551 | 0.967 | |||

R&D innovation | -0.12753 | 0.838 | |||

Leverage ratio | 0.952627 | 0 |

TABLE 2: post-merger performance (t+)

R square and the adjusted R squared values are 0.91 and 0.90 respectively. This indicates that the independent variables explain about 90% variation in the dependent variable. This means that the model is good enough to explain variation in the dependent variable (Mooi, 2014). Thus, there is a probability that the null hypothesis will be rejected.

## Variables affecting the post-merger performance of acquiring firms

The regression results for the post-merger performance are shown in the above table. The results clearly indicate that among all the independent variables, deal size and leverage ratio have a significant impact after the **M&A** deal takes place. This is because they have a ‘p’ value of less than the significance value of 0.05. Other variables like the size of the firm, industry relatedness, geographic expansion and R&D innovation have ‘p’ value which was greater than the significance value of 0.05, indicating that these variables have no impact on the current ratio of the firms in the post-merger period.

## The positive relation between deal size

The coefficient for the deal size indicates that with one unit of increase in deal size, the current ratio increases by about 7.4 units. This means that greater the amount of deal size, higher is the level of the current ratio for the firm. According to the study conducted by Warrad (2015), a greater deal size increases the firm’s profitability and thus enhances its ability to pay for the short term debts.

## Leverage ration has a significant impact

Another variable that has a significant impact is the leverage ratio. The coefficient value reflects that with one unit increase in the leverage ratio, the current ratio increases by 0.95 units. In support of the study conducted by Hao & Jaffe (2007), there is a positive relationship between the current ratio and the leverage ratio, the more leveraged firms are more will be the current ratio. And by increasing the inventory levels they tend to increase the leverage.

Thus, the hypothesis H

_{0}: There is no effect of cross -country mergers and acquisitions on operating profit margin in the period 2000- 2017 is rejected.

## Deal size increases profitability

The current ratio or liquidity ratio affects every aspect of corporate life. Firms need to maintain an adequate liquidity level, which is its ability to pay short term debts, a firm not having the appropriate liquidity ratio will ultimately shutdown. However it should neither be in excess nor be inadequate, excessive means that firms have idle and inadequate means and it will affect the creditworthiness of the firm (Chukwunweike, 2014). In the pre-merger period the leverage ratio leads to an increase in the liquidity ratio. While in the post-merger period it was the deal size and the leverage ratio that had a significant impact. The deal size increased the firm profitability, thus helped them maintain the ability to pay debts while the high level of leverage tends to increase in liquidity ratio without affecting the capital structure.

#### References

- Almajali, A. Y., Alamro, S. A., & Al-Soub, Y. Z. (2012). Factors Affecting the Financial Performance of Jordanian Insurance Companies Listed at Amman Stock Exchange.
*Journal of Management Research*,*4*(2), 266–289. https://doi.org/10.5296/jmr.v4i2.1482 - Amihud, Y., & Miller, G. (2011).
*Bank Mergers & Acquisitions*. https://doi.org/10.1007/978-1-4757-2799-9 - Chukwunweike, V. (2014). The Impact of Liquidity on Profitability of Some Selected Companies : The Financial Statement Analysis ( FSA ) Approach.
*Research Journal of Finance and Accounting*,*5*(5), 81–90. - Hao, K. Y., & Jaffe, A. B. (2007). Effect of liquidity on firms’ r&d spending.
*Economics of Innovation and New Technology*,*2*(4), 275–282. https://doi.org/10.1080/10438599300000008 - Liargovas, P., & Skandalis, K. (2010). Factors Affecting Firms’ Performance: The Case of Greece. In
*Global Business and Management Research: An International Journal*(Vol. 2). - Owino, O. E. (2011).
*The relationship between liquidity and leverage of companies quoted at the NSE*. Retrieved from http://erepository.uonbi.ac.ke/bitstream/handle/11295/13648/Oduol_The relationship between liquidity and leverage of companies quoted at the NSE.pdf - Šarlija, N., & Harc, M. (2012). The impact of liquidity on the capital structure: a case study of Croatian firms.
*Business Systems Research*,*3*(1). https://doi.org/10.2478/v10305-012-0005-1 - 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 - Warrad, L. (2015). The Effect of CurrentRatio on Jordanian Real Estate Sector ’ s Net Profit Margin The Effect of CurrentRatio on Jordanian Real Estate Sector ’ s Net Profit Margin.
*European Journal of Economics, Finance and Administrative Sciences*,*63*(2), 34–39.

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