Implementing residual income valuation with linear information dynamics

Residual income (RI) valuation is a method of estimating firm value based o n expected future accounting numbers. This study documents the necessity of using linear information models (LIMs) of the time series of accounting nu mbers in valuation. I find that recent studies that make ad hoc modificatio ns to the LIMs contain internal inconsistencies and violate the no arbitrag e assumption. I outline a method for modifying the LIMs while preserving in ternal consistency. I also find that when estimated as a time series, the L IMs of Ohlson (1995), and Feltham and Ohlson (1995) provide Value estimates no better than book value alone. By comparing the implied price coefficien ts to coefficients from a price level regression, I find that the models im ply inefficient weightings on the accounting numbers. Furthermore, the medi an conservatism parameter of Feltham and Ohlson (1995) is significantly neg ative, contrary to the model's prediction, for even the most conservative f irms. To explain these failures, I estimate a LIM from a more carefully mod eled accounting system that provides two parameters of conservatism (the in come parameter and the book value parameter). However, this model also fail s to capture the true stochastic relationship among accounting variables. M ore complex models tend to provide noisier estimates of firm value than mor e parsimonious models.