Systematizing Macroframework Forecasting: High-Dimensional Conditional Forecasting with Accounting Identities
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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.
Series:
Working Paper No. 2022/110
Subject:
Balance of payments Current account balance GDP measurement National accounts
Frequency:
regular
English
Publication Date:
June 3, 2022
ISBN/ISSN:
9798400211683/1018-5941
Stock No:
WPIEA2022110
Pages:
25
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