dc.contributor
Universitat Ramon Llull. IQS
dc.contributor.author
LOPEZ-BUENACHE, GERMAN
dc.contributor.author
Borsi, Mihály Tamás
dc.contributor.author
Rosa-Garcia, Alfonso
dc.date.accessioned
2025-12-12T11:25:39Z
dc.date.available
2025-12-12T11:25:39Z
dc.identifier.issn
2204-2296
dc.identifier.uri
http://hdl.handle.net/20.500.14342/5700
dc.description.abstract
This paper empirically studies the relationship between credit and unemployment fluctuations in the U.S. economy for the period 1955–2023. Drawing on the business cycle literature that focuses on changes in output, we model unemployment dynamics using a Markov-switching framework extended with credit variables to assess the ability of credit to identify periods of labor market slack – instances where the unemployment rate exceeds its natural rate, exerting downward pressure on inflation. Our results show that contractions in real private credit carry valuable information for signaling labor market slack. Moreover, we find that cyclical variations in private credit have significant out-of-sample predictive power for labor market dynamics.
dc.relation.ispartof
Economic Analysis and Policy 2025, 88
dc.rights
Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri
http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject
Markov-switching
dc.title
Credit cycles as predictors of labor market slack: Evidence from the U․S․
dc.type
info:eu-repo/semantics/article
dc.description.version
info:eu-repo/semantics/publishedVersion
dc.identifier.doi
https://doi.org/10.1016/j.eap.2025.08.006
dc.rights.accessLevel
info:eu-repo/semantics/openAccess