Identifying and Forecasting the Turns of the Japanese Business Cycle
Konstantin A., Kholodilin
In this paper we identify and try to predict the turning points of the Japanese business cycle. As a measure of the business cycle we use a composite economic indicator (CEI). This indicator is endowed with nonlinear dynamics to capture the asymmetries between different cyclical phases. Two types of nonlinear dynamics are considered : Markov switching and smooth transition autoregression (STAR). The performance of these models in terms of forecasting the business cycle turns is compared. Both types of models produce statistically equivalent in-sample forecasting results, whilst the CEI with exponential STAR tends to outperform the CEI with Markov-switching and logistic STAR in the out-of-sample prediction.
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