信息不完整与劳动力市场复苏缓慢

International Finance Discussion Papers ISSN 1073-2500 (Print)ISSN 2767-4509 (Online) Number 1423 September 2025 Imperfect Information and Slow Recoveries in the Labor Market Anushka Mitra Please cite this paper as:Mitra, Anushka (2025). “Imperfect Information and Slow Recoveries in the Labor Market,”International Finance Discussion Papers 1423.Washington:Board of Governors of theFederal Reserve System, https://doi.org/10.17016/IFDP.2025.1423. NOTE: International Finance Discussion Papers (IFDPs) are preliminary materials circulated to stimu-late discussion and critical comment.The analysis and conclusions set forth are those of the authors anddo not indicate concurrence by other members of the research staff or the Board of Governors. Referencesin publications to the International Finance Discussion Papers Series (other than acknowledgement) shouldbe cleared with the author(s) to protect the tentative character of these papers. Recent IFDPs are availableon the Web at www.federalreserve.gov/pubs/ifdp/. This paper can be downloaded without charge from theSocial Science Research Network electronic library at www.ssrn.com. Imperfect Information and Slow Recoveries in the LaborMarket Anushka Mitra* Federal Reserve Board Abstract Abstract:The unemployment rate remains elevated long after recessions, a persistence that standardsearch-and-matching models cannot explain. I show that noise shocks—expectational errors due to thenoise in received signals about aggregate shocks—account for much of this sluggishness. Using a structuralVAR, I find that absent noise shocks unemployment would have recovered to its pre-recession level sixquarters earlier over 1968–2019. To interpret this evidence, I develop a search-and-matching model with on-the-job search, endogenous search effort, and wage rigidity. Embedding imperfect information generatestwo channels of persistence: slow learning amplifies the effects of persistent productivity shocks, andnoise shocks provide an additional source of sluggishness, further magnified by sticky wages and vacancyposting. The model successfully replicates both the slow recovery of unemployment and systematicforecast errors, highlighting imperfect information as a key mechanism behind post-recession labormarket dynamics. Keywords:Imperfect Information, Labor Market, Business CyclesJEL Codes:E24, E32, E70 1Introduction One of the long-standing challenges for conventional business cycle models has been to match thepersistence in the recovery of the labor market, especially of the unemployment rate followingrecessions. In this paper, I document a new stylized fact: professional forecasters systematicallyoverestimate the time that it takes unemployment to recover from a recession, suggesting thatex-ante they expect the recoveries to be even longer than observed. This systematic overestima-tion suggests the presence of information frictions, where agents misperceive the persistence ofaggregate shocks and rely on noisy signals to form expectations. The presence of such frictionsoffer a potential mechanism to slow job creation and search activity, thereby generating a positivefeedback cycle that lead to slower unemployment recoveries. To investigate such a channel, Iestimate noise shocks, persistent TFP shocks, and transitory TFP shocks from a tri-variate VAR. Ifind that the noise shocks play an essential role in explaining the persistence of the labor market. Ithen incorporate the noise shocks into a model of labor search with imperfect information, andconfirm that the presence of imperfect information is key for the model’s success in matching thesluggishness of the unemployment rate during recoveries. I begin by presenting a set of empirical facts using data on the unemployment rate andforecasts from the Survey of Professional Forecasters (SPF). It takes between 5 and 16 quartersfor the unemployment rate in the United States, to recover half of its recessionary increase, andmore than 20 quarters to return to its pre-recession level. Using forecast data from the SPF, I nextdocument that professional forecasters are even more pessimistic about the recovery than therealized data suggest. There is a consistent wedge between expected and actual unemploymentrates across recessions, with forecasts predicting even slower recoveries. This pattern suggeststhat forecasters, like agents in the economy, may lack perfect information about the aggregate stateand instead rely on noisy signals to form expectations about whether changes in fundamentalsare persistent or transitory. Such misperceptions can influence key economic decisions, such ashiring and investment, thereby contributing to a sluggish labor market recovery. To understand these facts, I build upon the identification strategy from Chahrour, Nimark,and Pitschner, 2021 and Enders, Kleemann, and Müller, 2021, to estimate noise shocks (shocksthat arise from changes in expectations without any changes in fundamentals), persistent TFPshoc