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Business, housing, and credit cycles

Author

Listed:
  • Gerhard Rünstler
  • Marente Vlekke

Abstract

We use multivariate unobserved components models to estimate trend and cyclical components in gross domestic product (GDP), credit volumes, and house prices for the USA and the five largest European economies. With the exception of Germany, we find large and long cycles in credit and house prices, which are highly correlated with a medium‐term component in GDP cycles. Differences across countries in the length and size of cycles appear to be related to the properties of national housing markets. The precision of pseudo real‐time estimates of credit and house price cycles is roughly comparable to that of GDP cycles.

Suggested Citation

  • Gerhard Rünstler & Marente Vlekke, 2018. "Business, housing, and credit cycles," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(2), pages 212-226, March.
    • Handle: RePEc:wly:japmet:v:33:y:2018:i:2:p:212-226
    DOI: 10.1002/jae.2604
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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

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