Valuation Errors Caused by Conservative Accounting in Residual Income and Abnormal Earnings Growth Valuation Models
Kenth Skogsvik () and
Juettner-Nauroth, Beate Additional contact information Kenth Skogsvik: Dept. of Business Administration, Stockholm School of Economics, Postal: Stockholm School of Economics, P.O. Box 6501, SE-113 83 Stockholm, Sweden
Juettner-Nauroth, Beate: Deutsche Bundesbank, Postal: Deutsche Bundesbank, Hachenburg, Germany
Abstract:
The impact of conservative accounting in residual income valuation (RIV) and abnormal earnings growth (AEG) valuation modeling is investigated in this paper. Unconstrained and two types of constrained model specifications are evaluated regarding their ability to withstand biases in book values and earnings due to accounting conservatism. Given that the “clean surplus relation” holds and that the precision of forecasted accounting numbers is unaffected by the type of accounting principles, the unconstrained valuation models are – not surprisingly – found to be immune to conservatism. This does not hold for the constrained models, even though conservatism can be accommodated in these if the time-series specification of the conservative bias fulfils certain conditions. In a comparison between terminal value constrained models, the AEG model is found to be superior to the RIV model if the growth of the conservative bias in the terminal period is not too extreme. Comparing the information dynamics constrained models being proposed in Ohlson (1995) and Ohlson & Juettner-Nauroth (2005), the AEG model is potentially more accurate than the RIV model. However, in a company steady state setting with constant growth, there is no comparative advantage for the AEG model. Also, using the same set of forecasted accounting numbers in the information dynamics constrained RIV model as in the corresponding AEG model, the two models cannot be ranked.
More papers in Working Paper Series in Business Administration from Stockholm School of Economics Address: The Economic Research Institute, Stockholm School of Economics, P.O. Box 6501, SE 113 83 Stockholm, Sweden Contact information at EDIRC. Series data maintained by Helena Lundin ().
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