I investigate whether management earnings forecasts fully reflect the implications of accruals for future earnings. I find that managers overestimate accrual persistence in range forecasts but not in point forecasts and that managers’ accrual-related forecast bias in range forecasts increases with forecast range and forecast horizon. My results suggest that managers overestimate accrual persistence when faced with greater difficulty forecasting earnings. Moreover, I find that managers’ accrual-related forecast bias in range forecasts is somewhat affected by managerial opportunism and fear of litigation. Finally, I find accrual mispricing for firms issuing range forecasts but not for firms issuing point forecasts.

Disentangling peer effects from other confounding effects is difficult,and separately identifying endogenous and contextual effects is impossible for the linear-in-means model. This study confronts these problems by using spatial autoregressive models with group fixed effects. The nonlinearity introduced by the variations in the peer measurements provides information to identify both endogenous and contextual effects,thus resolving the "reflection problem." The group fixed effects term captures the confounding effects of the common variables.Applying the model to data sets from the National Longitudinal Studyof Adolescent Health, I find strong evidence for both endogenous and contextual effects in student academic achievement. (c) 2010 by The University of Chicago. Allrights reserved.

We develop a specification test and a sequence of model selection procedures for non-nested, overlapping, and nested models based on the second Hansen-Jagannathan distance, which requires a good asset pricing model to not only have small pricing errors but also be arbitrage free. Our methods have reasonably good finite sample performances and are more powerful than existing ones in detecting misspecified models with small pricing errors but are not arbitrage-free and in differentiating models that have similar pricing errors of a given set of test assets. Using the Fama and French size and book-to-market portfolios, we reach dramatically different conclusions on model performances based on our approach and existing methods.