# «Leif Atle Beisland University of Agder Dissertation submitted to the Department of Accounting, Auditing and Law at the Norwegian School of Economics ...»

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Table description Table 7 lists the number and percentage share of companies reporting respectively negative earnings, extraordinary items, intangible assets, and impairment from 1994 to 2004.

Table 8: Detailed Accruals Panel A: Value Relevance of Positive and Negative Earnings

Table description Table 8 describes the value relevance of detailed earnings components for a sample of Norwegian firms from 1992 to 2004. It summarises the regression coefficients (Coefficient), White-adjusted t-values (t-statistic), total explanatory power (adj. R2), number of observations (n) and mean variance inflation factor (Mean VIF) for positive and negative earnings sub-samples, respectively. Data is analysed using the following regression

**specifications:**

**The standard specification is applied in panel A and the leftmost analysis of panel B:**

RETi,t = β 0 + β1CFi,t + β 2 ∆CFi,t + β 3 ∆INVi,t + β 4 ∆∆INVi,t + β5 ∆REC i,t + β 6 ∆∆RECi,t + β 7 ∆PAYi,t + β8 ∆∆PAYi,t + β9 DEPR i,t + β10 ∆DEPR i,t + β11IMPi,t + β12 ∆IMPi,t + β13 ∆DTi,t + β14 ∆∆DTi,t + ε i,t

**Dummy variable for negative earnings is applied in the rightmost analysis of panel B:**

where RETi,t is the stock return for company i in year t, CF is cash flow from operations, INV is inventory, REC is receivables, PAY is payables, DEPR is depreciation, IMP is impairment and DT is deferred taxes. D is a dummy variable equal to 1 when earnings are negative, 0 otherwise. ∆ denotes yearly change in the variables.

The accounting variables are scaled by the market value of equity on 30 December in year t-1. Coefficients in bold denote a statistical significance at a 5% level using a two sided test.

Table 9: VIF per Regression Coefficient

Table description Table 9 lists the regression coefficients’ individual variance inflation factor in the following regressions (see

**Panel C of table 4):**

**Standard specification:**

RETi,t = β 0 + β1CFi,t + β 2 ∆CFi, t + β 3 ∆WC i,t + β 4 ∆∆WC i,t + β 5 DEPi,t + β 6 ∆DEPi,t + β 7 ∆DTi,t + β 8 ∆∆DTi, t + ε i,t

where RETi,t is the stock return for company i in year t, CF is cash flow from operations, WC is working capital, DEP is depreciation and impairment, and DT is deferred taxes. D is a dummy variable equal to 1 when earnings

Table 10 presents descriptive statistics for the control variables (see Tables 5 and 6) company size (SIZE = log of market value of equity), intangible asset intensity (INTANG = sum of intangible assets at time t divided by the market value of equity at the beginning of year t), the book-to-market ratio (BM = book value of equity divided by market value of equity at time t), interest rate (INTEREST = the expected return on 5-year risk free government bonds), stock price volatility (VOL = the standard deviation of monthly returns on Oslo Stock Exchange) and net extraordinary items (EXTRA = total extraordinary items at time t divided by the market value of equity at the beginning of year t). It summarises the mean, first quarter, median, third quarter, standard deviation, and number of observations for the positive and the negative earnings sample, respectively.

Table description Table 11 describes the value relevance of earnings for a sample of Norwegian firms from 1992 to 2004 when control variables are included in the regression analyses (see Table 5). It summarises the regression coefficients (Coefficient), White-adjusted t-values (t-statistic), total explanatory power (adj. R2) and number of observations (n) for the positive and negative earnings samples, respectively. Data is analysed using 3 different earnings aggregation levels.

where RETi,t is the stock return for company i in year t, EARN is earnings before extraordinary items, CF is cash flow from operations, ACC is total accruals, WC is working capital, DEP is depreciation and impairment, and DT is deferred taxes. ∆ denotes yearly change in the variables. The accounting variables are scaled by the market value of equity on 30 December in year t-1. CVi is control variable i. The control variables are company size (SIZE = log of market value of equity), intangible asset intensity (INTANG = sum intangible assets at time t divided by the market value of equity at the beginning of year t), the book-to-market ratio (BM = book value of equity divided by market value of equity at time t), interest rate (INTEREST = the expected return on 5-year risk free government bonds), stock price volatility (VOL = the standard deviation of monthly returns on Oslo Stock Exchange) and net extraordinary items (EXTRA = total extraordinary items at time t divided by the market value of equity at the beginning of year t).

Table description Table 12 describes the value relevance of earnings for a sample of Norwegian firms from 1992 to 2004 when control variables are included in the regression analyses (see Table 6). It summarises the regression coefficients (Coefficient), White-adjusted t-values (t-statistic), total explanatory power (adj. R2) and number of observations (n) for the total sample. Data is analysed using 3 different earnings aggregation levels.

**Panel A presents the results of the following regressions:**

where RETi,t is the stock return for company i in year t, EARN is earnings before extraordinary items, CF is cash flow from operations, ACC is total accruals, WC is working capital, DEP is depreciation and impairment, and DT is deferred taxes. D is a dummy variable equal to 1 when earnings are negative, 0 otherwise. ∆ denotes yearly change in the variables. The accounting variables are scaled by the market value of equity on 30 December in year t-1. CVi is control variable i. The control variables are company size (SIZE = log of market value of equity), intangible asset intensity (INTANG = sum intangible assets at time t divided by the market value of equity at the beginning of year t), the book-to-market ratio (BM = book value of equity divided by market value of equity at time t), interest rate (INTEREST = the expected return on 5-year risk free government bonds), stock price volatility (VOL = the standard deviation of monthly returns on Oslo Stock Exchange) and net extraordinary items (EXTRA = total extraordinary items at time t divided by the market value of equity at the beginning of year t).

## Abstract

Firms listed on European stock exchanges are required to report according to International Financial Reporting Standards, IFRS, in their consolidated financial statements as of 2005. We use a sample of 741 firm-year observations from the Oslo Stock Exchange in Norway over the years 2003-2006 to examine whether this shift in reporting regime from local GAAP to IFRS has changed how investors respond to accounting information. After controlling for economic drivers of response coefficients, we find that while the association between stock prices and book values has increased after the transition to IFRS, the earnings response coefficients have been reduced. The increase in investors’ response to book values is attributed to more recognition of intangible assets and more measurement at fair value. The lower response to earnings is found to be driven mainly by nonrecurring items. Thus, fair value revaluations appear to be detrimental to the value relevance of earnings.International Financial Reporting Standards, IFRS, from 2005 and onwards in their consolidated financial accounts.1 We use this mandatory transition to IFRS to study the effect on how investors respond to this new reporting regime, relative to the previously used regime – in our case Norwegian Generally Accepted Accounting Principles, NGAAP. According to Gjerde, Knivsflå and Sættem (2008), there are two main differences between IFRS and NGAAP;

more recognition of intangible assets and more measurement at fair values for financial instruments and investment properties, as well as for certain operating assets such as biological assets.

We form testable hypotheses on how these two major differences in reporting between IFRS and NGAAP will influence investors’ response to earnings and book values, based on previous empirical findings about the effect of increased recognition of intangible assets (e.g. Lev and Sougiannis, 1996) and measurement at fair value (e.g. Hann, Heflin and Subramanayam, 2007). We expect the stock price’s response coefficient to the corresponding book value to increase, though the hypothesis is formulated and tested two-sided. The response coefficient of the stock price to earnings per share is also expected to be different after the adoption of IFRS, as there is a potential trade-off between at least two effects. More recognition of intangible assets may increase the coefficient, while more measurement at fair value may make earnings more transitory and hence make the price less responsive to earnings. After controlling for other differences between the IFRS and NGAAP samples, such as differences in risk, loss reporting, intangible asset intensity and non-recurrence of earnings, we find evidence that the balance sheet becomes more important under IFRS whereas the value relevance of the The European Economic Area is comprised of the members of the European Union plus Norway, Iceland and Lichtenstein.

balance sheet more value relevant, while fair value revaluations seem to create transitory ‘noise’ in the income statement; compare Penman (2007).

This paper is unique in several aspects. We are the first to provide long term evidence on the effects of adopting IFRS in Norway. Gjerde, Knivsflå and Sættem (2008) only focus on one year, 2004, in which they analyze the NGAAP figures with their restated IFRS counterparts in

2005. We analyze the effect over the four year period from 2003 to 2006, with considerably more observations. Secondly, we use a methodological technique to study the structural break between NGAAP and IFRS involving controlled moderation effects on the response coefficients of both earnings and book values. This means that we avoid potential criticism by comparing the explanatory power in terms of the adjusted R2 in two different samples; see e.g.

Easton and Sommers (2003) and Gu (2007). Finally, we are able to control for a large set of other value relevance drivers not purely related to differences in accounting regime, such as the degree of loss reporting, the intangible asset intensity and the non-recurrence of earnings.

Our first hypothesis is that the stock price responds differently to the book value of equity under IFRS than under NGAAP. There is empirical evidence suggesting that more recognition and ‘better’ measurement increases the response coefficient of the balance sheet relative to the case where it is based on expensing as incurred and past transactional cost; see e.g. Lev and Sougiannis (1996) and Aboody and Lev (1998) in relation to intangible asset recognition versus expensing as incurred, and e.g. Barth, Beaver and Landsman (1996), Khurana and Kim (2003) and Henn, Heflin and Subramanyam (2007) in relation to measurement at fair value versus transactional cost.