Earnings Management and Earnings Quality: Theory and Evidence

We study a dynamic model of earnings quality and earnings management in which firms take into account both long- and short-term considerations when reporting earnings. In addition to providing predictions about time series properties of earnings quality and reporting bias, the model offers a distinction between two components of investors’ uncertainty: (i) fundamental economic uncertainty and (ii) information asymmetry between the manager and investors due to reporting or accounting distortions. We also structurally estimate the parameters of the model, to separate these two components of investors’ uncertainty. This allows us to address existing concerns about archival studies on earnings quality, such as the concerns raised by Dichev et al. (2013) that “archival research cannot satisfactorily parse out the portion of managed earnings from the one resulting from fundamental earnings process.” We compute the ratio of the variance of noise introduced by the reporting process per period, to the variance of economic earnings innovation per period, and find that, on average, it is around half, suggesting that the noise added by the reporting process significantly contributes to investors’ uncertainty about firm values.