春節、端午節與中秋節為華人社會的三大節慶，對生產、消費與其他經濟活動有顯著的影響。例如，許多產品的製造與銷售在春節前達到高峰，在春節期間則幾乎停擺，在春節過後則逐漸加溫，恢復平日水準。三大節慶的日期係依農曆而定，在陽曆的日期則逐年變動，造成經濟變數尤其是月資料不規則的變化。本文應用 Bel1與 Hillmer(1983) 處理復活節的方法，以加入假日迴歸變數的方法來消彌移動假日的影響。我們區分假日前、假日中與假日後三種不同的影響，分別以這三個期間落在每月份的比例作為解釋變數，並應用 AICC 與樣本外預測來決定這三段期間的長度，最後以離群值檢定與滑動樣本分析來診斷所選定模型的正確性。本文分析 10個台灣的總體經濟月資料，實證結果發現假日變數的方法確能有效控制移動假期的影響，並得以改善估計季節因子的準確度。一般說來，移動假期因子的影響較季節因子為小。我們更進一步發現失業率的移動假日效果與季節效果逐年遞減，這應是高失業率所造成的後果。

　　　　　 The three most important Chinese holidays, Chinese New Year, the Dragon-boat Festival, and Mid-Autumn Holiday have dates determined by a lunar calendar and move between two solar months. Consumption, production, and other economic behavior in countries with large Chinese population including Taiwan are strongly affected by these holidays. For example, production accelerates before lunar new year, almost completely stops during the holidays and gradually rises to an average level after the holidays. This moving holiday often creates difficulty for empirical modeling using monthly data and this paper employs an approach that uses regressors for each holiday to distinguish effects before, during and after holiday. Assuming that the holiday effect is the same for each day of the interval over which the regressor is nonzero in a given year, the value of the regressor in a given month is the proportion of this interval that falls in the month. Bell and Hillmer (1983) proposed such a regressor for Easter which is now extensively used in the U.S. and Europe. We apply the Bell and Hillmer's method to analyze ten important series in Taiwan, which might be affected by moving holidays. AICC and out-of-sample forecast performance were used for selecting number of holiday regressors and their interval lengths. The results are further checked by various diagnostic checking statistics including outlier detection and sliding spans analysis. The empirical results support this approach. Adding holiday regressors can effectively control the impact of moving holidays and improves the seasonal decomposition. AICC and accumulated forecast error are useful in regressor selection. We find that unemployment rates in Taiwan have holiday effects and seasonal factors cannot be consistently estimated unless the holiday factor is included. Furthermore, as the unemployment is rising, the magnitude of holiday and seasonal factor are decreasing. Finally, we find that holiday factors are generally smaller than seasonal factors but should not be ignored.