Please use this identifier to cite or link to this item:
https://ah.lib.nccu.edu.tw/handle/140.119/74184
題名: | Forecasting macroeconomic variables using data of different periodicities | 作者: | Shen, Chung-Hua 沈中華 |
貢獻者: | 金融系 | 關鍵詞: | Combining forecasts; VAR model; BVAR model; ARIMA model; Macro model | 日期: | 1996 | 上傳時間: | 30-Mar-2015 | 摘要: | 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. | 關聯: | International Journal of Forecasting - INT J FORECASTING , vol. 12, no. 2, pp. 269-282 | 資料類型: | article | DOI: | http://dx.doi.org/10.1016/0169-2070(95)00659-1 |
Appears in Collections: | 期刊論文 |
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