The Effect of the Goodwill Amortization on the Informative of Earnings - Research Paper Example

The Effect of the Goodwill Amortization on the Informative of Earnings Executive summary This paper aims at the discussion of the effects of the goodwill amortization on the informative of the earnings. Starting with the changed policy of the FASB (2001) regarding the amortization of the goodwill, the paper moves onto discuss how the new policy has affected the different companies. The paper then adopts a contrasting approach considering the information provided by the earnings of the companies before and after the new guidelines. This approach is important as it helps determine how informative the earnings are with and without the amortization of the goodwill. The paper also focuses on particular examples and analyses the differences caused by the changed guidelines by considering many literature reviews and statistics. Further it takes into account a data set that provides information about certain performance measures of the companies. Taking the hypothesis that the information content of the income without the extraordinary items is something that is significantly equal to the income that is generated after the exclusion of the goodwill amortization, the data is used to generate empirical results to prove the hypothesis. Through the results and through the performance measures deductions are made about the information contents of the variables use. Hence the paper basically, at the end, tries to prove how the exclusion of the goodwill amortization affects the informative of the earnings of certain companies. Although the data set is a limited one (having a hundred observations only), yet it does seek to prove the hypothesis. The results of the income before the extraordinary items are compared to the income after the exclusion of the goodwill amortization and the net cash flow from observations to find the relative content ranking of all three. The paper also provides explanations for the results that may not seem to be accurate and tends to question if the substitution of the income after the exclusion of goodwill amortization for the income before extraordinary items undertaken by the FASB was a proper step, Introduction In 2001, according to a report by the Working Council for Chief Financial Officers (2002) the FASB adopted the Statement of Financial Accounting Standards (SFAS) No.142 Goodwill and Other Intangible Assets which meant that a new set of rules were introduced to deal with the accounting information related to the goodwill amortization. The statement proposed that the goodwill and the intangible assets had an infinite life and so there was no need for the amortization of such assets, as Choi and Federick (2003) relate. In the past the companies used to report a portion of the goodwill in their income statements. As a result, the managers of certain companies, according to James et al. (2008) were likely to report the lower goodwill charges (because the profits were likely to increase). Busse von Colbe (2004) believes that this methodology adopted by the managers was against the true accounting objectives which aim at portraying the true economic picture of the firms and the businesses. As a direct consequence, the goodwill amortization was removed so that there was no chance of the managers exploiting the investors through false reporting. The statement issued by the FASB in 2001 regarding the goodwill amortization meant that the companies were no longer required taking into account the goodwill charges. However, according to a report by the Working Council for Chief Financial Officers (2002), they were to periodically determine whether the goodwill was impaired. This was to be done, as Li et al. (2005) believe, by the cash flow analysis of the companies. Hence this meant that the goodwill could be a part of the budget sheet forever unless something happened that caused the managers to realize that they overpaid for the company. The change of the guidelines by the FASB had many effects on the companies, especially in the US. According to Huefner and Largay (2009) the implications on the companies were varied. Since the goodwill could not be amortized now, certain companies like the General Electric, as Huefner and Largay (2009) relate, considered the goodwill as a corporate cost rather than a segment one. The result was that there was no effect on the profits of the users. Huefner and Largay’s (2009) study further shows that certain companies like Kraft benefited from the changed goodwill guidelines in terms of the improvement of the tax burden. The reason given by Kraft was that ‘the Company no longer required amortizing goodwill and indefinite life intangible assets as a charge to earnings.’ Other companies like the AOL Time Warner felt that the goodwill downplayed the impact of the company because, according to the new accounting principles, the company faced a $54 billion write off although it was non operational in nature. From the above examples and also from the study of Ampofo and Selani (2005), it can be seen that the effects of the changed guidelines of the goodwill have been different for different companies. While some have benefited from the changed accounting standards and some have remained indifferent, others have actually suffered. It is important to consider all the effects of the goodwill amortization on the The purpose of this essay is hence to elaborate in detail how the goodwill amortization has affected the earnings of particular companies as Segal (2003) does in his thesis. The paper basically focuses on the companies that recorded the goodwill as a charge to the balance sheets in the past and compares it to the earnings of the companies that do not include the amortization of the good will in their balance sheets. This way it concentrates on the differences in the earnings caused due to the goodwill amortization. Thesis statement and Research Methodology The main question to be answered in this essay is about the effects of the goodwill amortization on the information provided by the earnings. In other words, the paper is to determine to what extent the earnings can explain the goodwill charges. For the purpose of the secondary research I have basically studied and analysed certain literature reviews. I have also analyzed the balance sheets and the annual reports of some of the major companies focusing specially on the mergers (as they have bee n the most affected due to the change in the guidelines of the reporting of the goodwill). Prior Research and Hypothesis Development Throughout history, accounting researchers, like Dechow and Ge (2006), have concentrated on the informativeness of the earnings of the companies versus the cash flows of the companies. Prior studies have also shown the importance of the earnings and the cash flows to the companies. For example, Bowen et al.’s (1987) study shows the importance of the accruals and the cash flows for the accounting firms. The first paper that was aimed at relating the cash flows with the earnings was written by Dechow (1994). According to him, the earnings of the company were directly related to the stock returns. The cash flows, however, did not have strong impacts on the stock returns although they were linked to the return as Hermann et al. (2000) relate. Biddle et al. (1995) also find that the earnings are more important than the cash flows while providing the information about the economic realities of the companies. Many researchers like Master-stouts et al. (2008) have also linked the information content of the earnings to the funds from the operations and the consequent tenure of the CEOs. Vincent (1999) argues that the information provided by such operations is far less than the information that the earnings can provide. Many other authors have also considered the concept of the economic value added (EVA) and have linked it to the notion of cash flows. According to Moehrle et al. (2001), the EVA basically refers to the modification of the earnings such that a charge of the equity capital is also considered one of the adjustments. Stewart (1994) was of the view that the EVA is better at the providing of data than the earnings. However, greater study on to this notion stated otherwise according to Alciatore et al. (2000). It was deduced that the earnings represent the situation of the company or organization in the best possible manner unlike cash flows and EVA. Another fact that was observed, according to Barth et al. (2001), was that the information content of the earnings decreases as soon as the measurement of the income is moved away from the accrual methods to the cash flow ones. This paper basically examines the effect of the information content of the earnings once the amortization is excluded. Since the notion of the exclusion of amortization is something that is relatively new (as the policy was changed after 2001), there is less research that could corroborate to the effects on the information content of earnings. Yet, there have been some papers written on this notion. One such example is that of Jennings et al.’s study (2001) that seeks to describe the usefulness of the earnings with regard to the goodwill amortization. Similarly Ramanna and Watts (2009) also consider the usefulness of the non-impairments of the goodwill. According to the research carried out by Jennings et al. (2001), the earnings before the goodwill amortization were better at explaining the distribution of share prices for publicly traded companies in the period 1993-1998 than the earnings excluding the goodwill amortization. Henning and Shaw (2003) also add to this observation stating that the amortization of the goodwill is a better and reliable predictor of the success of the acquisition in terms of both the earnings and the stock performance in the future. Therefore, from the above researches and studies it can be seen that the accrual methods are better at explaining the earnings than the cash flow methods. The prior literature also states that the earnings that exclude the goodwill amortization are likely to have lesser information content than the earnings that include the goodwill amortization. Also, the movement away from the accrual methods means that that the ‘performance measure loses explanatory powers,’ as Moehrle et al. (2001) relates. Since the paper is based on the question of the informative of the earnings with regard to the goodwill amortization, it is important that the before and after effects of the exclusion of goodwill amortization are studied. To study these effects it is important to control for other variables. A regression analysis of a sample data is the best way this can be achieved. Hence from now on through the course of the paper, the adjusted R-squared would be studied to determine the relative explanatory power of income before explanatory power (IB), income that does not include goodwill amortization (IBAI), and net cash flow from operations (CFO). The hypothesis that is used in the paper is similar to the one used in Moehrle et al.’s study i.e. IB= IBAI > CFO in terms of the corresponding information content of each. Research Design and Sample Selection The data that has been used here considers the Hamdard companies, from the year 1998-2000. The data is a time series one with variables that account for the performance measures (mentioned above) and the returns on the equity. Since the amortization is the only expense that is considered the results may be biased (Greater percentage results for returns as will be seen later). However they would account only for the amortization expense. The number of observations that are present is 100. From the data it can be seen that the amortization is greater than zero for all the companies. This leaves us with 100 observations to consider. Also, it is important to consider the number of observations in which the amortization is greater than 10% of the value of IB. This is because in such cases, the amortization exclusion has a significant effect on the difference of the information content of IB and IBAI. It is important to notice that these cases actually make half of the data at 49 observations. Hence, I have a total of 100 observations for one year, where amortization is greater than zero and 49 cases, where the amortization is greater than 10% of the IB. The model that is followed in the paper is very similar to the one followed in the study of Moehrle et al. (2001). The adjusted R-squared of each of the regression of the returns (market adjusted ones) on the performance measures are compared in order to come to the conclusion of the relative information content of IB, IBAI, and CFO. The returns are measured over a period of 12 months so that the important and relevant accounting information that affects the information content is not something that can be ignored. A theoretical equation for such a model is as follows. MARt= β0 +β1Xt + β2Xt-1+ γt (1) Where: MA is the value for the Market Adjusted Returns Xt is the respective performance measure (i.e. IB, IBAI, CFO) for the current year. Xt-1 is the respective performance measure (i.e. IB, IBAI, CFO) for the previous year. However, from Model (1) it can be seen that it is not a very accurate model. There is no way this model could control for heteroskedasticity. Also there is no distinction in this model about the positive and negative returns of the companies. Therefore, it is important to expand this model into something that is more practical and accounts for constant variance. Thereby the following method is used MARt= α0+ α1 Xt, pos/MVEt-1 + α2 Xt, neg/MVEt-1 + α3Xt-1, pos)/ MVEt-1 + α4Xt-1,neg)/ MVEt-1 + €t (2) Where: MA is the value for the Market Adjusted Returns Xt, neg is the respective performance measure (i.e. IB, IBAI, CFO) for negative earnings in the current year. Xt-1, neg is the respective performance measure (i.e. IB, IBAI, CFO) for negative earnings in the previous year. Xt, pos is the respective performance measure (i.e. IB, IBAI, CFO) for positive earnings in the current year. Xt-1, pos is the respective performance measure (i.e. IB, IBAI, CFO) for positive earnings in the previous year. MVE is the market value of the equity for the previous year. Using the above model, I estimate the effect of goodwill amortization on the returns. The R-squared would then be compared to assess the relative information content of the performance measures namely the IB, IBAI, and the CFO. The statistical significance of each would also be compared so that the regression coefficients can be estimated to have significance. Each of the variables is deflated using the market value of equity so that the heteroskedasticity is accounted for. Further, the performance measures for the negative and the positive return are considered separately. This is because, according to the study of Collins et al. (1997) and Dichev (1997), the earnings response coefficients for each of the firms are different. For the firms that are suffering from a loss, such coefficients are smaller. Empirical Results Table 1a shows the key data statistics of the main variables found in the data. The data shows the means, medians, and the standard deviations of the main variables concerned. The mean of IBAI is $513.32 million while the mean for the IB is $549.551 million. The difference between the means of IB and IBAI are approximately $51.23 million is the mean amount of amortization that is experienced by al the firms It is interesting to note that the amortization expense accounted for 61% of the revenue which means that approximately 61.4% of the revenue earned is spent in the expensing out for the amortization expense. The mean of CFO totalled to equal approximately $555.2626 million. The table also shows that the MAR (or the market adjusted returns) are decreasing by almost 85% (Amortization expense is the only expense considered here in this data set therefore the results or the effects on the MAR are higher). Table 1b shows the same key data statistics however this time they focus on the main variables involved for cases where the amortization difference is significantly greater or 10% of the IB. In such cases, the mean of the IBAI is lower than before that is 519.3878 million whereas the mean of IBAI is also lower than before at 513.3232million. The amortization expense accounts for 73 % of the revenue which means that the 73% of the revenue is spent in the expensing out of amortization. An interesting thing to be noted here is that the IBAI counts towards approximately 93% of the reported IB. Here it is important to mention that the numbers of observations are very small and therefore the results may not be very accurate. A sample data of a hundred, according to Hsiao (2000), is something that cannot portray a normal data. At least a thousand observations are needed to deduce the respective effects of the variables on each other or in comparison with each other. The CFO mean totals out to be equal to$501.549 million in this case. . Table 1A Descriptive Statistics for Variables 1998 (one year) Firms with Amortization>0 AM/ MEV IB IBAI CFO MAR Mean 0.614004 549.551 513.3232 555.2626 -0.85279 Median 0.195538 272.5 249 265 -8.40336 St Dev 1.413333 783.5592 718.8996 774.9183 39.98116 No of Firms 100 Where: IB is equal to the net income that is calculated before the extraordinary items IBAI is equal to the net income after the exclusion of the amortization expense (The measure that has been proposed by the FASB to replace the notion of earnings per share) CFO is equal to the net cash flow from operations. (Amounts are in millions of dollars) MAR is equal to the market adjusted returns that comprise of the compounded stock returns minus the 12 month compounded market-wide return. AM/REV is the ratio of the amortization expense to the Revenues. Table 1B For Firms with Amortization greater than 10 AM/REV IB IBAI CFO MAR Mean 0.73225 519.3878 464.7551 501.549 -11.5423 Median 0.234857 230 205 229 -11.7438 St Dev 1.790971 698.3355 626.5881 676.5289 30.43248 Number of Observations: 49 Where: IB is equal to the net income that is calculated before the extraordinary items IBAI is equal to the net income after the exclusion of the amortization expense (The measure that has been proposed by the FASB to replace the notion of earnings per share) CFO is equal to the net cash flow from operations. (Amounts are in millions of dollars) MAR is equal to the market adjusted returns that comprise of the compounded stock returns minus the 12 month compounded market-wide return AM/REV is the ratio of the amortization expense to the Revenues. In Table 2a, the respective correlations (adjusted R-squared) are reported and then compared. The data shows, as expected, a very high correlation between IB and IBAI. Also, there is a fairly high correlation of CFO with IB too. Since there is a high correlation of CFO with IB and IB has a higher correlation with IBAI, obviously the correlation of IBAI and CFO is also very high. Here, it should be added that the IBAI is always correlated with the CFO higher than the IB as Moehrle (2001) states. This is because the goodwill being a non cash expense is added to the IB in the computation of the CFO and the IBAI. The addition means that they both are highly correlated, at least greater than the correlation between IB and IBAI. The trends also show that the correlation of the CFO with the IB and IBAI is lower in the cases where the amortization is greater than 10% of the IB as compared to the cases where the amortization is only greater than zero. Table 2a Correlations between the Three Performance Measures and the Market Adjusted Returns for the Current Year For Firms with Amortization greater than zero IB IBAI CFO MAR IB 1.00 IBAI 0.99924939 1.00 CFO 0.9998216 0.999291501 1.00 MAR -0.063616097 -0.060677086 -0.060831734 1.00 Number of Observations = 100 Where: IB is equal to the net income that is calculated before the extraordinary items IBAI is equal to the net income after the exclusion of the amortization expense (The measure that has been proposed by the FASB to replace the notion of earnings per share) CFO is equal to the net cash flow from operations. (Amounts are in millions of dollars) MAR is equal to the market adjusted returns that comprise of the compounded stock returns minus the 12 month compounded market-wide return. Table 2b For Firms with Amortization greater than 10% of IB IB IBAI CFO MAR IB 1.00 IBAI 0.999961563 1.00 CFO 0.99978818 0.99814589 1.00 MAR -0.041692467 -0.03994011 -0.038764639 1.00 Number of Observations= 49 Where: IB is equal to the net income that is calculated before the extraordinary items IBAI is equal to the net income after the exclusion of the amortization expense (The measure that has been proposed by the FASB to replace the notion of earnings per share) CFO is equal to the net cash flow from operations. (Amounts are in millions of dollars) MAR is equal to the market adjusted returns that comprise of the compounded stock returns minus the 12 month compounded market-wide return. Table 3 (below) shows the regression analysis of each of the performance variables according to the model (2) given above. The variables that are considered are Market adjusted returns, the positive and negative performance measures for each year and the previous one year. The table is used the test hypothesis that was mentioned before that is that the information content of both the IB and the IBAI would not very different from each other (significantly) however with regard to the CFO they would be different. Table 3a provides the regression analysis for all the firms that have the amortization expense as greater than zero. Based on the table given below the Adjusted r-squared for 1B is -2.4% while that of IBAI and CFO are -1.13 and -1.46 respectively. It is interesting to note here that the results do not go here with the original hypothesis. According to the table results, the information content of the IB is greater than CFO. This is true according to the hypothesis and the prior studies. CFO does affect the informative of earnings severely. However, a striking fact here is that the information content according, to the table, of the IBAI is lesser than that of the CFO since the adjusted R-squared is lower. It is noteworthy that the explanatory power of the IB and IBAI is explained usually by the positive earnings. This is because the coefficients of the positive earnings are higher as compared to the negative ones. This means that the deduction that the firms that suffer a loss generally have lower coefficients is true. The Table 3b shows the regression analysis of the same sample however in these cases, the amortization is greater than 10% of the IB. From the table it can be seen that the Adjusted R-squared for the IB is -0.3% while the Adjusted r-squared for IBAI and CFO are -1.2% and -1.9% respectively. This sample has actually been used to find out whether the information content of IBAI increases more than the information content of IB. When the amortization increases, the values of IB and IBAI become very different from each other. However, from the tables it can be seen that the differences between the adjusted R squared are not enough. In fact the difference is quite small. Hence, the information content of both the IB and the IBAI can be said to be approximately equal even if the adjusted R-squared for the IBAI is slightly higher. From table3, one can also deduce that the coefficients for IBAI, when the earnings are smaller, are smaller. Therefore, these cases may also be used to deduce that the firms that suffer from the losses are more likely to have smaller earnings. Table 3a Regression analysis Firms with amortization greater than zero IB IBAI CFO Intercept (t-stat) -0.656956113 (-0.146292652) 0.233353915 (0.05187151) 0.608204445 (0.136238829) Xt, pos (t-stat) -2.676539988 (-0.631057151) -3.079812394 (-0.661897859) 3.342815161 (0.587635971) Xt, neg (t-stat) -0.792236485 (-0.149220046) 3.185950212 (1.036737634) -5.418330582 (-1.119251688) Xt-1, pos (t-stat) 2.812154263 (0.674814955) 3.125606772 (0.703096341) -3.170313311 (-0.560006119) Xt-1, neg (t-stat) 0.531027661 (0.102527008) -3.885673273 (-1.123691478) 5.063973064 (1.068712728) F-statistic (p-value) 0.402461947 (0.80643833) 0.724594707 (0.577298182) 0.645659768 (0.631312) Adjusted R-squared -0.024999017 -0.01136883 -0.014675111 Number of Observations = 200 Where: IB is equal to the net income that is calculated before the extraordinary items IBAI is equal to the net income after the exclusion of the amortization expense (The measure that has been proposed by the FASB to replace the notion of earnings per share) CFO is equal to the net cash flow from operations. (Amounts are in millions of dollars) Xt, neg is the respective performance measure (i.e. IB, IBAI, CFO) for negative earnings in the current year. Xt-1, neg is the respective performance measure (i.e. IB, IBAI, CFO) for negative earnings in the previous year. Xt, pos is the respective performance measure (i.e. IB, IBAI, CFO) for positive earnings in the current year. Xt-1, pos is the respective performance measure (i.e. IB, IBAI, CFO) for positive earnings in the previous year. MVE is the market value of the equity for the previous year. Table 3b Regression Analysis Firms with Amortization greater than 10% of IB IB IBAI CFO Intercept (t-stat) 0.659900619 (0.150628) 0.595359 (0.135804) 1.039354162 (0.238038823) Xt, pos (t-stat) -6.715042406 (-0.83514) -6.81782 (-0.77819) -2.163972699 (-0.237116839) Xt, neg (t-stat) 8.412246072 (0.76849) 0.6866 (0.109458) -0.221846854 (-0.009863866) Xt-1, pos (t-stat) 6.722807731 (0.841413) 6.65336 (0.784799) 2.198498272 (0.242332301) Xt-1, neg (t-stat) -9.72449 (-0.87915) -1.99896 (-0.32352) -1.048763765 (-0.045018289) F-statistic (p-value) 0.906182169 (0.463714306) 0.704993 (0.590482) 0.536116036 (0.709520323) Adjusted R-squared -0.003844019 -0.01219 -0.019299456 Number of Observations = 98 Where: IB is equal to the net income that is calculated before the extraordinary items IBAI is equal to the net income after the exclusion of the amortization expense (The measure that has been proposed by the FASB to replace the notion of earnings per share) CFO is equal to the net cash flow from operations. (Amounts are in millions of dollars) Xt, neg is the respective performance measure (i.e. IB, IBAI, CFO) for negative earnings in the current year. Xt-1, neg is the respective performance measure (i.e. IB, IBAI, CFO) for negative earnings in the previous year. Xt, pos is the respective performance measure (i.e. IB, IBAI, CFO) for positive earnings in the current year. Xt-1, pos is the respective performance measure (i.e. IB, IBAI, CFO) for positive earnings in the previous year. MVE is the market value of the equity for the previous year. Explanations for results in comparison with other studies The results, although to some extent may be different, are similar to the studies that have been undertaken by many accountants on the subject of the exclusion of goodwill amortization. This is because the information content of the income before the extraordinary items that was found out was not very different significantly from the information content of the income that excluded goodwill amortization; this is in accordance with the principles that are laid down by the FASB (2001). Although overall, the results crudely are similar to the proposed hypothesis. Yet there are discrepancies. For instance, the adjusted R squared of the market returns when regressed on the IB is lesser than that achieved when the market returns are regressed on the IBIA. In reality or at least according to the prior studies, this should not be the case. In fact the adjusted R squared should have been higher for the IB as compared to the IBAI. Another discrepancy is that the coefficients of the regression of market returns on the negative earnings are greater than the positive ones. This is also a contradiction because throughout the paper the notion that has been used is that the firms that suffer from a loss are likely to have smaller coefficients. Also, the increased value of the adjusted R squared of the CFO poses a problem. The initial hypothesis was that the information content of the CFO is something that is lesser compared to that of the IB and IBAI. These problems may exist due to different reasons. The first and foremost of the reasons why the results may be different from the hypothesis is the reduced number of observations. The number of observations for the cases where the amortization is greater than zero is only hundred where as the ones for the amortization greater than 10% of the IB is just 49. The reduced number of observations lead to the biasedness and inconsistency of the regression estimates in a time series data, as Clements et al. (2004) relates. As a result, the regression results may have discrepancies like the one mentioned above. Another thing is that the model was deflated by the market value of equity so that the heteroskedasticity is controlled for. However, there is no way to prove if the model really does have constant covariance. Furthermore, although the model may seem complete, it may actually be suffering from an omitted variable bias. This means that the leaving out of certain instruments or factors (that are a part of the error term in the model) may actually have significant effects on the market returns. Similarly, the consideration of just one kind of expense (the amortization expense in this case) may actually be a reason why the results are so different. The model needs to control for other variables too. Conclusion In the paper, I tried to test the information content of the income before extraordinary items (IB) and income after the exclusion of the goodwill amortization. From the results, it can be seen that the exclusion of the goodwill amortization does not change the information content of the earnings to a greater extent. Although the information content of the IBAI is obviously lower than that of the IB to some extent, there is less difference between the two. In comparison to the information content of the CFO, both the IB and the IBAI are better at the informative of earnings. My results, overall, show that the exclusion of the goodwill does not have a very significant effect on the informative of earnings and is much similar to the income before extraordinary items (in terms of the information content) as Zaleha et al. (2004) state. As a consequence, my research complies with the set of principles put down by the FASB in 2001 about the exclusion of the goodwill amortization. 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