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引文資料
題名:
Modeling Lunar Calendar Holiday Effects in Taiwan
書刊名:
臺灣經濟預測與政策
作者:
林金龍
/
劉天賜
作者(外文):
Lin, Jin-lung
/
Liu, Tian-syh
出版日期:
2003
卷期:
33:2
頁次:
頁1-37
主題關鍵詞:
經濟活動
;
農曆
;
移動假日
;
臺灣
原始連結:
連回原系統網址
相關次數:
被引用次數:期刊(
7
) 博士論文(0) 專書(0) 專書論文(0)
排除自我引用:
7
共同引用:
4
點閱:98
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。
以文找文
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.
以文找文
期刊論文
1.
Chang, Ih、Tiao, George C.、Chen, Chung(1988)。Estimation of Time Series Parameters in the Presence of Outliers。Technometrics,30(2),193-204。
2.
Hurvich, Clifford M.、Tsai, Chih-Ling(1989)。Regression and Time Series Model Selection in Small Samples。Biometrika,76(2),297-307。
3.
Pugh, M. G.、Monsell, B. C.、Shulman, H. B.、Findley, D. F.(1990)。Sliding-spans diagnostics for seasonal and related adjustments。Journal of American Statistical Association,85(410),345-355。
4.
Hillmer, S. C.、Bell, W. R.(1983)。Modeling Time Series with Calendar Variation。Journal of the American Statistical Association,78,526-534。
5.
Liu, Lon-Mu(1980)。Analysis of time series with calendar effects。Management Science,26,106-112。
6.
Pfeffermann, D.、Morris, N. D.(1984)。A Kalman filter approach to the forecasting of monthly series affected by moving festivals。Journal of Time Series Analysis,5,255-268。
7.
彭淮南(1982)。貨幣供給額之季節調整:兼論移動日期之春節對通貨及存款貨幣季節影響之處理。中央銀行季刊,4(1),8-61。
延伸查詢
8.
Findley, D. F.、Chen, Bor-Chung、Otto, M. C.、Bell, W. R.、Monsell, B. C.(1998)。New Capabilities and Methods of the X-12-ARIMA Seasonal Adjustment Program。Journal of Business & Economic Statistics,16(2),127-177。
會議論文
1.
Findley, D. F.、Soukup, R. J.(2001)。Modeling and model selection for moving holidays。The Business and Economic Statistics Section of the American Statistical Association。Alexandria, VA:American Statistical Association。102-107。
2.
Findley, D. F.、Soukup, R. J.(2001)。Detection and Modeling of Trading Day Effects。Alexandria, VA。743-753。
圖書
1.
Maravall, A.(1995)。Unobserved components in economic time series。The Handbook of Applied Econometrics, 1。Oxford, UK。
其他
1.
Young, Allan H.(1965)。Estimating trading day variation in monthly economic time series,Washington, DC。
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