Identifying and Forecasting the Turns of the Japanese Business Cycle
AbstractIn 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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Bibliographic InfoPaper provided by Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES) in its series Discussion Papers (IRES - Institut de Recherches Economiques et Sociales) with number 2003008.
Date of creation: 01 Jun 2003
Date of revision:
composite economic indicator; Markov switching; smooth transition autoregression; turning points; reference cycle; forecasting;
Find related papers by JEL classification:
- C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
- C5 - Mathematical and Quantitative Methods - - Econometric Modeling
This paper has been announced in the following NEP Reports:
- NEP-ALL-2004-03-14 (All new papers)
- NEP-ECM-2004-03-14 (Econometrics)
- NEP-MAC-2004-03-14 (Macroeconomics)
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