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政大機構典藏 > 商學院 > 金融學系 > 期刊論文 > Item 140.119/74184

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/74184

Title:	Forecasting macroeconomic variables using data of different periodicities
Authors:	Shen, Chung-Hua 沈中華
Contributors:	金融系
Keywords:	Combining forecasts;VAR model;BVAR model;ARIMA model;Macro model
Date:	1996
Issue Date:	2015-03-30 12:01:55 (UTC+8)
Abstract:	A formal statistical method is used in this study to combine forecasts from a quarterly macroeconometric model for Taiwan with monthly time series forecasts. Three monthly models, i.e. vector autoregressive (VAR), Bayesian vector autoregressive (BVAR) and Autoregressive integrated moving average (ARIMA) were alternately applied to examine whether a superior monthly model can achieve better quarterly forecasts. For variables that are observed both quarterly and monthly, combined forecasts are generally found to be superior to the macro forecasts but inferior to the monthly ones. With respect to variables that are available only quarterly, results in this study indicate that the gain in forecasting accuracy due to the inclusion of the monthly data is substantial even when no monthly information is available for the quarter.
Relation:	International Journal of Forecasting - INT J FORECASTING , vol. 12, no. 2, pp. 269-282
Data Type:	article
DOI 連結:	http://dx.doi.org/10.1016/0169-2070(95)00659-1
DOI:	10.1016/0169-2070(95)00659-1
Appears in Collections:	[金融學系] 期刊論文

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