Shocks to Shocks: A Theoretical Foundation for the Information Content of Earnings

This study maintains that the value-relevance of accounting information cannot be measured solely by reference to Ball-Brown earnings response coefficient (ERC) analysis. The contribution of accounting information to return volatility is equally crucial. Synthesizing and generalizing results from earlier studies, this paper rigorously develops Ball-Brown and volatility measures of the information content of earnings from underlying primitives using Vuolteenaho's 2002 accounting return decomposition model. The well-known Ball-Brown metric is obtained by assuming that (a) the time series of (log-deflated) earnings is stationary AR(l), (b) "other information" shocks are nonexistent, and (c) expected future discount rates are intertemporally constant. This measure is initially extended to include "other information" shocks and dynamic discount rates that are also stationary AR(l). Generalized Ball-Brown and variance measures of information content are further obtained where the time series of earnings, "other information", and expected future discount rates follow either loglinear stationary ARMA(p, q) processes or a loglinear stationary VAR process. Closed-form solutions of information content are also obtained for earnings components (e.g., cash flows and accruals). Applications of the theory are offered that show how this framework improves on extant empirical methodologies and suggests further lines of research.