Identifiable Intangible Assets in Business Combinations -A Quantitative Study of US Companies

This thesis is a quantitative study of how U.S. companies allocate purchase prices paid in acquisitions to identified intangible assets in relation to goodwill. It seeks to identify how the percentage of identified intangible assets in business combinations varies with acquirer firm characteristics. Since SFAS 141 and SFAS 142 are the two principle-based standards that regulate how U.S. companies account for acquired intangible assets, the study seeks to indicate whether these seem to work efficiently, providing the users of financial statements with relevant information that reflect the economic values of the intangible assets correctly. The economy seems to have become increasingly knowledge-driven and technology based during the last couple of decades. This has resulted in intangible assets representing a larger proportion of balance sheet totals and subsequently the proportion of acquired assets in business combinations. Problems related to the accounting for intangible assets led to FASB’s issuance of standards SFAS 141 and SFAS 142 that have brought changes in the way to account for intangibles. Since few studies have focused on how acquired intangible assets are identified in business combinations post the issuance of SFAS 141 and 142, it has been of this study’s objective to provide additional knowledge and increased insight about this. Current knowledge and previous research literature has guided and supported this study throughout the hypothesis development, methodology and analysis. A similar methodology as Rehnberg (2012) used in her thesis studying identification of intangible assets in business combinations, has been applied but this thesis studies U.S. companies instead of Swedish companies, it studies acquisitions made between 2010-2014 (the large majority of the observations can be found between 2011-2013) and it has a significantly greater sample. This was facilitated through the usage and data collection from database Compustat. Two multiple regression models are used to draw conclusions about five hypothesis regarding acquirer firm characteristics relationship to the level of identified intangible assets. The findings of this paper is that the size and profitability of the acquirer, with a 95% confidence, has a negative correlation with the percentage of purchase price allocated to identified intangible assets in U.S. business combinations. The authors do not find that the debt to equity ratio and book to market ratio of the acquirer can explain this level. The percentage of identified acquired intangible assets varies between industries and profitability and size affect the percentage of identified intangible assets differently in different industries. The Energy, Materials, Industrials, Consumer Discretionary, Information Technology, Telecommunication Services, and Utilities industries identified significantly less intangible assets in business combinations than the Consumer Staples industry (43% versus 56,7%). The mean percentage of identified intangible assets across industries was found to be 47%. Most findings are not in line with the ones in previous research and the thesis does not attempt to explain why. One reason could however be that the years of study for this paper is a typical post-crisis period characterized with impairment of goodwill and other assets whilst the one of Rehnberg was characterized by significant growth. The study cannot draw a conclusion whether the levels of identified intangible assets in business combinations observed in this research indicate efficient principle-based standards but the finding that the level of identified intangible assets varies between industries is a sign that they do