Consistent Good News and Inconsistent Bad News
|Speaker:||Kelly Shue, University of Chicago|
|Date:||Tuesday 4 October 2016|
|Location:||Constantine Leventis Teaching Room, Building: one|
Good news is more persuasive when it is more consistent, and bad news is less damaging when it is less consistent. We show when Bayesian updating supports this intuition so that a biased sender has mean-variance news preferenceswhere more or less variance in the news helps the sender depending on whether the mean of the news exceeds expectations. We apply the result to selective news distortion of multiple projects by a manager interested in enhancing the perception of his skill. If news from the different projects is generally good, boosting relatively bad projects increases consistency across projects and provides a stronger signal that the manager is skilled. But if the news is generally bad, instead boosting relatively good projects reduces consistency and provides some hope that the manager is unlucky rather than incompetent. We test for evidence of such distortion by examining the consistency of reported segment earnings across
dfferent units in rms. As predicted by the model, managers appear to shift discretionary cost allocations to report more consistent earnings when overall earnings are above rather than below expectations. The mean-variance news preferences that we identify also apply to media bias, p-value hacking, and other situations beyond our career concerns application, and differ from standard mean-variance preferences in that more variable news sometimes helps and better news sometimes hurts.