Credit cycles and labor market slacks: predictive evidence from Markov-switching models

Lopez Buenache, German and Borsi, Mihály Tamás and Rosa-García, Alfonso (2020): Credit cycles and labor market slacks: predictive evidence from Markov-switching models.

Abstract

We model unemployment and credit cycle dynamics as a Markov-switching process with two states to identify labor market slacks i.e., periods of unemployment above its natural rate. Our results for the US economy between 1955 and 2015 show that credit contractions improve the identification of high unemployment states. Moreover, we find that credit cycles have a sizable out-of-sample predictive power on labor market slacks. This implies that the evolution of credit can be used as a leading indicator for economic policies.

• Item Type: MPRA Paper
• Language: English
• Keywords: credit cycle; unemployment; forecast; Markov-switching
• Subjects: C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C32 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes ; State Space Models; E - Macroeconomics and Monetary Economics > E2 - Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy > E24 - Employment ; Unemployment ; Wages ; Intergenerational Income Distribution ; Aggregate Human Capital ; Aggregate Labor Productivity; E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E32 - Business Fluctuations ; Cycles; E - Macroeconomics and Monetary Economics > E5 - Monetary Policy, Central Banking, and the Supply of Money and Credit > E51 - Money Supply ; Credit ; Money Multipliers

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