Imperfect Information and Slow Recoveries in the Labor Market
Abstract
The unemployment rate remains persistently high after recessions even after job losses subside. Standard search and matching models have difficulty capturing this pattern. In this paper, I provide new evidence that noise shocks, which capture agents’ expectational errors due to the noise in received signals about the persistence of aggregate productivity, generate substantial persistence in the unemployment rate. I first identify these noise shocks using a novel structural VAR and find that unemployment would have recovered to its pre-recession level six quarters earlier in the absence of noise shocks in the 1968-2019 period. To understand these findings, I set up a general equilibrium search and matching model with on-the-job search, endogenous search effort and wage rigidity and consider three shocks: a permanent productivity shock; a transitory productivity shock and a noise shock. The presence of imperfect information and noise shocks allows the model to match the longer unemployment recovery than in a full information setting. The results point to the importance of imperfect information in explaining the slow recoveries, through two channels. First, responses to persistent productivity shocks are more persistent as it takes time for agents to learn whether a shock is persistent or not. Second, noise shocks provide an additional source of persistence, which are amplified through sticky wages, on-the-job search and firms’ vacancy posting decisions.
Presentations:
EEA-ESEM 2026*, 5th DC SaM Workshop 2026, FRB St. Louis-WashU-LAEF Macro Conference 2026, System Macro Conference 2025, Columbia Junior Macro-Micro Labor Conference 2025, SED 2025, EU SaM 2025, Ashoka University Annual Conference 2024, ISI Winter School 2024, Midwest Macro 2023