Peter Easton
The Ohio State University
Steve Monahan
University of Chicago
Abstract: We develop and implement a method for comparing the measurement error in estimates of the expected rate of return on equity. We combine the Campbell [1991] and Vuolteenaho [2002] return decomposition with the econometric method described in Garber and Klepper [1980] and Barth [1991] to infer cross-sectional measurement error variances. We evaluate a variety of estimates of expected returns that are discussed in the extant accounting literature (e.g., Gebhardt, Lee, and Swaminathan [2001], Easton [2002], and Gode and Mohanram [2002]). Our results show that the estimate that is based on the simplest model (i.e., price-to-forward earnings) is as reliable as more sophisticated proxies. This result is also observed when the analyses are repeated for portfolios of observations. Predicted values based on instrumental variables that are, a priori, expected to be correlated with the true expected return but uncorrelated with the measurement error have considerably lower measurement error variances. Nonetheless, the crudest proxy still performs at least as well as more sophisticated proxies.
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