Systematizing Macroframework Forecasting: High-Dimensional Conditional Forecasting with Accounting Identities
Forecasting a macroframework, which consists of many macroeconomic variables and accounting identities, is widely conducted in the policy arena to present an economic narrative and check its consistency. Such forecasting, however, is challenging because forecasters should extend limited information...
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| Format: | eBook |
| Language: | English |
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Washington, D.C.
International Monetary Fund
2022
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| Series: | IMF Working Papers
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| Collection: | International Monetary Fund - Collection details see MPG.ReNa |
| Summary: | Forecasting a macroframework, which consists of many macroeconomic variables and accounting identities, is widely conducted in the policy arena to present an economic narrative and check its consistency. Such forecasting, however, is challenging because forecasters should extend limited information to the entire macroframework in an internally consistent manner. This paper proposes a method to systematically forecast macroframework by integrating (1) conditional forecasting with machine-learning techniques and (2) forecast reconciliation of hierarchical time series. We apply our method to an advanced economy and a tourism-dependent economy using France and Seychelles and show that it can improve the WEO forecast |
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| Physical Description: | 25 pages |
| ISBN: | 9798400211683 |