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.
| Original language | English |
|---|---|
| Pages (from-to) | 1097-1111 |
| Number of pages | 15 |
| Journal | Economic Analysis and Policy |
| Volume | 88 |
| DOIs | |
| Publication status | Published - Dec 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 8 Decent Work and Economic Growth
Keywords
- Credit cycle
- Forecast
- Markov-switching
- Unemployment
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