Abstract

This study presents a novel semiparametric prediction system for the Taipei's unemployment rate series. The prediction method incorporated into the system consists of a fuzzy time series model that estimates the trend, as well as a Box-Jenkins prediction of the residual series. In terms of the adaptability of the Box-Jenkins method, the prediction intervals of the system can be successfully constructed. The extensive studies are performed on the robustness of the built fuzzy model using different specified model basis. To demonstrate the effectiveness of our proposed method, the Taipei's monthly unemployment rate from Feb. 1983 to Oct. 1996 was evaluated using a fuzzy time series model with the Box-Jenkins time series technique. Analysis results demonstrate that the proposed method outperforms than the traditional fuzzy time series method.