Nonlinearity and the Permanent Effects of Recessions

This paper presents a new nonlinear time series model that captures a postrecession “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 U.S. 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 U.S. business cycle dynamics. When the model is applied to other countries, we find larger permanent effects of recessions.