Credit cycles as predictors of labor market slack: Evidence from the U․S․

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 credi...

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Detalles Bibliográficos
Autores: LOPEZ-BUENACHE, GERMAN, Borsi, Mihály Tamás, Rosa-Garcia, Alfonso
Tipo de recurso: artículo
Fecha de publicación:2025
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:20.500.14342/5700
Acceso en línea:http://hdl.handle.net/20.500.14342/5700
https://doi.org/10.1016/j.eap.2025.08.006
Access Level:acceso abierto
Palabra clave:Credit cycle
Unemployment
Forecast
Markov-switching
Crèdit
Atur
Previsió
33
Descripción
Sumario: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.