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Macroeconomic forecasting with mixed-frequency data: forecasting output growth in the United States

Clements, M. P. ORCID: https://orcid.org/0000-0001-6329-1341 and Galvão, A. B. (2008) Macroeconomic forecasting with mixed-frequency data: forecasting output growth in the United States. Journal of Business and Economic Statistics, 26 (4). pp. 546-554. ISSN 0735-0015

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To link to this item DOI: 10.1198/073500108000000015

Abstract/Summary

Many macroeconomic series, such as U.S. real output growth, are sampled quarterly, although potentially useful predictors are often observed at a higher frequency. We look at whether a mixed data-frequency sampling (MIDAS) approach can improve forecasts of output growth. The MIDAS specification used in the comparison uses a novel way of including an autoregressive term. We find that the use of monthly data on the current quarter leads to significant improvement in forecasting current and next quarter output growth, and that MIDAS is an effective way to exploit monthly data compared with alternative methods.

Item Type:Article
Refereed:Yes
Divisions:Henley Business School > ICMA Centre
ID Code:34032
Publisher:Taylor & Francis

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