This paper investigates how noisy evaluation of worker skills affects human capital investments and hiring. Individuals distort investments toward skills that most managers can evaluate. Dynamically, when workers become managers, managerial expertise can become increasingly skewed over time, raising investment distortions and reducing output. If firms select managerial expertise strategically, efficient investments can be retrieved when (a) identifying whether workers' skills matter more than distinguishing among skilled workers, and (b) initial investment distortions are small. Otherwise, such strategic design worsens long-run outcomes. Finally, we determine when short-run affirmative action policies are effective.

This paper develops a test for herding in forecasts by professional financial analysts that is robust to (a) correlated information amongst analysts; (b) common unforecasted industry-wide earnings shocks; (c) information arrival over the forecasting cycle; (d) the possibility that the earnings that analysts forecast differ from what the econometrician observes; and (e) systematic optimism or pessimism among analysts. We find that forecasts are biased, but that analysts do not herd. Instead, analysts “anti-herd”: Analysts systematically issue biased contrarian forecasts that overshoot the publicly-available consensus forecast in the direction of their private information.