The way out of recessions: Evidence from a bounce-back augmented threshold regression

This paper proposes a two-regime Bounce-Back Function augmented Self-Exciting Threshold AutoRegression (SETAR) model which allows for various shapes of recoveries from the recession regime. It relies on the bounce-back effects which were first analyzed in a Markov-Switching setup by Kim, Morley, and Piger (2005), and were recently extended by Bec, Bouabdallah, and Ferrara (2011). This approach is then applied to the post-1973 quarterly growth rates of French, German, Italian, Spanish and Euro area real GDPs. Both the linear autoregression and the standard SETAR without the bounce-back effect null hypotheses are strongly rejected against the Bounce-Back augmented SETAR alternative in all cases but Italy. The relevance of our proposed model is further assessed by a comparison of its short-term forecasting performances with those obtained from a linear autoregression and a standard SETAR. It turns out that the bounce-back model’s one-step-ahead forecasts generally outperform the other ones, particularly during the last recovery period in 2009Q3–2010Q4.