The Measurement of Post Deal Performance. An Empirical Analysis of European M&A Transactions


Bachelor Thesis, 2018

46 Pages, Grade: 1,3


Excerpt

Index

Index of abbreviations

Table of figures

1. Introduction

2. Literature Review
2.1 Accounting Measures
2.1.1 Ratios
2.1.2 Growth measures
2.1.3 Operating Cash Flows
2.2 Abnormal Returns
2.3 Other Measures
2.4 Measure Comparison

3. Empirical Analysis: European M&A Transactions
3.1 Research Design
3.1.1 Sample
3.1.2 Model
3.1.3 Variables
3.2 Results

4. Discussion

5. Conclusion

Appendix

References

Index of abbreviations

Abbildung in dieser Leseprobe nicht enthalte

Table of figures

Figure 1: Return on Assets Regression

Figure 2: Return on Sales Regression

Figure 3: Profit Growth Regression

Figure 4: Asset Growth Regression

Figure 5: Sales Growth Regression

Figure 6: Operating Cash Flow Regression

Table 1: Measure Overview.

Table 2: Sample Origin

Table 3: Sample Industry Composition

Table 4: Return on Assets Results

Table 5: Return on Sales Results

Table 6: Profit Growth Results

Table 7: Asset Growth Results

Table 8: Sales Growth Results

Table 9: Operating Cash Flow Returns Results

Table 10: Cumulative Abnormal Returns Results

Table 11: Measure Correlation

Table 12: Measure Result Overview.

Table 13: Return on Assets Regression Table

Table 14: Return on Sales Regression Table

Table 15: Profit Growth Regression Table

Table 16: Asset Growth Regression Table

Table 17: Sales Growth Regression Mode

Table 18: Operating Cash Flow Regression Table

Equation 1: ROA (Papadakis & Thanos, 2010, p. 866

Equation 2: ROS distortion (Meeks & Meeks, 1981, p. 336

Equation 3: ROE financing distortion

Equation 4: Profitability growth (Morosini & Singh (1994, p. 395

Equation 5: Pre-deal operating cash flow returns (Healy et al., 1992, p. 139

Equation 6: Pre-deal industry adjusted operating cash flow returns (Healy et al., 1992

Equation 7: Post-deal operating cash flow returns (Healy et al., 1992, pp. 139-140

Equation 8: Post-deal industry adjusted operating cash flow returns (Healy et al., 1992

Equation 9: Abnormal returns (Schoenberg, 2006, pp. 364-365

Equation 10: Cumulative abnormal returns (Schoenberg, 2006, pp. 364-365

Equation 11: Abnormal returns (Finkelstein & Haleblian, 2002, pp. 41-42

Equation 12: Cumulative abnormal returns (Finkelstein & Haleblian, 2002, pp. 41-42

Equation 13: Cross-sectional regression mode

Equation 14: Pre-deal return on assets

Equation 15: Post-deal return on assets

Equation 16: Market adjusted return on assets

Equation 17: Market adjusted retorn on assets regression mode

Equation 18: Pre-deal return on sales

Equation 19: Post-deal return on sales

Equation 20: Market adjusted return on sales

Equation 21: Market adjusted return on sales regression mode

Equation 22: Pre-deal profit growth

Equation 23: Post-deal profit growth

Equation 24: Market adjusted profit growth

Equation 25: Market adjusted profit growth regression mode

Equation 26: Pre-deal asset growth

Equation 27: Post-deal asset growth

Equation 28: Market adjsuted asset growth

Equation 29: Market adjusted asset growth regression mode

Equation 30: Pre-deal sales growth

Equation 31: Post-deal sales growth

Equation 32: Market adjusted sales growth

Equation 33: Market adjusted sales growth regression mode

Equation 34: Operating cash flow.

Equation 35: Pre-deal operating cash flow returns

Equation 36: Market adjusted operating cash flow returns

Equation 37: Post-deal operating cash flow returns

Equation 38: Market adjusted operating cash flow returns regression mode

Equation 39: Abnormal returns

Equation 40: Cumulative abnormal returns.

1. Introduction

There are several studies that showed that on average 50% of all M&A deals lead to a failure (e.g. Cartwright & Schoenberg, 2006, p. 5; Kitching, 1974, p. 125; Papadakis & Thanos, 2010, p. 868; Schoenberg, 2006, p. 366; Tetenbaum, 1999, p. 23). There are some explanations for the high rate of failures in empirical research, e.g. hubris which is the overconfidence of the management as first mentioned by Roll (1986, pp. 197–201) or managerialism (e.g. Seth, Song, & Pettit, 2000, pp. 391–392). Still M&A transactions take place frequently and shareholders do not prohibit them. Cartwright & Schoenberg (2006, p. 4) suggest that this unchanged acceptance of shareholders for M&A activities exists because there are some synergies or gains, but the measures used in research do not acknowledge them properly. They state that in a market environment such inefficiencies (value destroying M&A transaction) are hard to believe. I want to contribute to this debate by identifying, describing and finally analyzing several measures that are used in research and apply them on the same sample. According to Thanos & Papadakis (2012, p. 118) the used measure in a study seems to highly influence the outcome. They found that return on assets (ROA) measures often lead to a negative outcome while cash flow measures often lead to a positive outcome. They state that the usage of several measures in the same study could lead to more robust results. There are a lot of different measures used to analyze M&A performance. Meglio & Risberg (2011, p. 422) divide these measures into a financial domain including measures for market performance and measures for accounting performance and a non-financial domain including measures for operational performance and measures for overall performance. In my empirical analysis I will focus on accounting and market measures due to data availability. The accounting measures can be separated into three major categories: ratios, growth measures and operating cash flows (Thanos & Papadakis, 2012, pp. 112-114). I will start with a literature review to examine what measures are used to measure M&A Deal performance in research. Therefore, I categorize the accounting measures according to the framework of Thanos & Papadakis (2012, pp. 112-114) like described above and add the market measure abnormal returns to my analysis. Following my literature review I will discuss the pros and cons of the different measures and which measures seem eligible in which situation. After that I will analyze European M&A transactions using data from the Thomson Eikon Databank. Most research focuses on US M&A deals which results in an underrepresentation of research for European transactions (Meglio & Risberg, 2011, p. 423). By analyzing the latter, I address this problem.

I will analyze the performance by comparing the market adjusted pre-deal numbers with the market adjusted post-deal numbers in a seven-year time frame around the deal execution and conduct a cross-sectional regression analysis to derive the effect of the M&A transaction on the measure and to derive the success rate. Furthermore, I will research the correlation between these measures. Following this analysis, I will discuss my results and finish my bachelor thesis with a conclusion and suggestions for further research.

2. Literature Review

2.1 Accounting Measures

2.1.1 Ratios

One type of measures frequently used to measure the post deal performance of M&A transactions are ratios. In their literature review of accounting based measures used in studies that were published in leading journals Thanos & Papadakis (2012, pp. 112-113) found that the usage of them increased rapidly in the last decades. They furthermore found that most researchers are focusing their level of analysis on acquiring firms since financial data for target firms is often not available. The period analyzed in these studies ranged from some months to ten years and wasn’t stated at all in one fourth of the studies. They found five ratios used in these studies: Return on assets (ROA), return on sales (ROS), return on investment (ROI), return on equity (ROE) and return on capital employed (ROCE). Meeks & Meeks (1981, pp. 335-340) give a comprehensive overview about the ratios used to measure post deal performance. According to the literature review of Thanos & Papadakis (2012, p. 112) ratios are used to indicate post-deal performance by comparing the pre-deal ratio of the acquirer with the post-deal ratio of the acquirer or by comparing the pre-deal ratio of the pro-forma combined firm with the post-deal ratio of the combined firm using a weighted average. The ratio that is used by far the most is ROA and it is measuring a firms profitability (Thanos & Papadakis, 2012, pp. 112-114). ROA equals income before interest and taxes divided by total assets (Stanton, 1987, p. 294). Papadakis & Thanos (2010, p. 866) calculated the change in return on assets induced by M&As as follows:

Equation 1: ROA (Papadakis & Thanos, 2010, p. 866)

So, the change in return on assets (ROA) equals the asset weighted average of the ROA of the target and the ROA of the acquirer two years after the acquisition minus the industry average ROA two years after the acquisition subtracted by the asset weighted average of ROA of the target and the acquirer two years before the acquisition minus the industry average ROA two years before the acquisition. They did not state if they also used asset weights for the industry ROA if target and acquirer did not share the same industry and they did not state how they measured the weighted average after the deal when the target financials are represented in the acquirer’s annual reports. If the ROA increased after the deal it is considered as successful and when it is not it is considered as unsuccessful. Thanos & Papadakis (2012, p. 113) state that using raw ROA was criticized since it is not considering industry effects. Therefore, a ROA that is adjusted for industry effects by subtracting the average industry ROA is preferred in newer studies. There are several studies that showed that M&A deals lead to a performance decrease when ROA is used as a performance measure (e.g. Papadakis & Thanos, 2010, p. 868). A possible explanation could be that the recognition of goodwill on the combined balance sheet is inflating the assets without changing the return of the separated businesses (Meeks & Meeks, 1981, p. 341). This problem is only existent for firms that accounted under the purchase method because under the pooling for interest method market values are not transforming into book values by means of goodwill and the revaluation of assets and liabilities to market values (Healy, Palepu, & Ruback, 1992, pp. 139-140). The pooling for interest method was abolished in the USA in 2001 and 2004 the IASB followed but for acquisitions prior to the abolishment the accounting choice has to be considered. Meeks & Meeks (1981, pp. 139-140) state that ROS and ROE also suffer some accounting distortions. Using ROS as a performance measure for firm’s efficiency (Thanos & Papadakis, 2012, p. 114) the post-deal returns are divided by the post-deal sales of the merged entities and then compared to the weighted average numbers of both entities in their pre-deal state. A problem with this measure arises due to accounting practices. When two businesses traded before the M&A which is not uncommon especially in a vertical integration but also in other types of M&As then the sales resulting from this transaction are not accounted for in the sales because they get internalized. Therefore, the denominator decreases which increases the ratio. Thus, this measure can overstate the effect on performance because it is not considering the accounting implications sufficiently (Meeks & Meeks, 1981, p. 336).

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Details

Title
The Measurement of Post Deal Performance. An Empirical Analysis of European M&A Transactions
College
LMU Munich  (Institut für Rechnungswesen und Wirtschaftsprüfung)
Grade
1,3
Author
Year
2018
Pages
46
Catalog Number
V584714
ISBN (eBook)
9783346162731
ISBN (Book)
9783346162748
Language
English
Tags
M&A, Accounting, Finance, Empirical, European
Quote paper
Tim Ulbricht (Author), 2018, The Measurement of Post Deal Performance. An Empirical Analysis of European M&A Transactions, Munich, GRIN Verlag, https://www.grin.com/document/584714

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