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Title: |
The Use of High Frequency Data to Improve Macroeconometric Forecast |
| Author: |
Liou, Ruey-Wan;
Shen, Chung-Hua |
| Author
Affiliation: |
Directorate-General of Budget Accounting & Statistics, ROC; National
ChengChi U |
| Source: |
International Economic Journal, Summer 1996, v. 10, no. 2, pp. 65-83 |
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Publication Date: |
Summer 1996 |
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Abstract: |
Monthly measurements generally provide
valuable information for future economic movements. This study
demonstrates how the high frequency data, through a subset of variables
in the monthly model, can be pooled in a systematic way via the
quarterly econometric model as well as improve the forecasting accuracy.
Three monthly models, VAR, BVAR, and ARIMA are used to capture the
monthly information. Single- and two-quarter-ahead forecasts are
combined with the monthly data. Results obtained by using the modified
Taiwan government quarterly model indicate the potential for significant
reductions in root mean squared errors over the one-quarter-ahead
forecasts. However, the gain appears to be of less relevance for the
longer-term forecast horizon. |
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