Article ID: | iaor2005653 |
Country: | Netherlands |
Volume: | 20 |
Issue: | 2 |
Start Page Number: | 255 |
End Page Number: | 271 |
Publication Date: | Apr 2004 |
Journal: | International Journal of Forecasting |
Authors: | Franses Philip Hans, Paap Richard, Vroomen Bjrn |
Keywords: | forecasting: applications, social |
Monthly observed unemployment typically displays explosive behavior in recessionary periods, while there seems to be stationary behavior in expansions. Allowing parameters in an autoregression to vary across regimes, and hence over time, can capture this feature. In this paper, we put forward a new autoregressive time series model with time-varying parameters, where this variation depends on a linear indicator variable. When the value of this variable exceeds a stochastic threshold level, the parameters change. We discuss representation, estimation and interpretation of the model. Also, we analyze its forecasting performance for unemployment series of three G-7 countries, and we compare it with various related models.