Nonlinearity and the permanent effects of recessions

Chang Jin Kim, James Morley, Jeremy Piger

Research output: Contribution to journalArticlepeer-review

72 Citations (Scopus)

Abstract

This paper presents a new nonlinear time series model that captures a post-recession 'bounce-back' in the level of aggregate output. While a number of studies have examined this type of business cycle asymmetry using recession-based dummy variables and threshold models, we relate the 'bounce-back' effect to an endogenously estimated unobservable Markov-switching state variable. When the model is applied to US real GDP, we find that the Markov-switching regimes are closely related to NBER-dated recessions and expansions. Also, the Markov-switching form of nonlinearity is statistically significant and the 'bounce-back' effect is large, implying that the permanent effects of recessions are small. Meanwhile, having accounted for the 'bounce-back' effect, we find little or no remaining serial correlation in the data, suggesting that our model is sufficient to capture the defining features of US business cycle dynamics. When the model is applied to other countries, we find larger permanent effects of recessions.

Original languageEnglish
Pages (from-to)291-309
Number of pages19
JournalJournal of Applied Econometrics
Volume20
Issue number2
DOIs
Publication statusPublished - 2005

ASJC Scopus subject areas

  • Social Sciences (miscellaneous)
  • Economics and Econometrics

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