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Nowcasting Annual National Accounts with Quarterly Indicators: An Assessment of Widely Used Benchmarking Methods
Author:
Mr. Marco Marini
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Series:
IMF Working Papers
Volume/Issue:
Volume 2016: Issue 071
Language:
English
Publication Date:
18 Mar 2016
DOI:
https://doi.org/10.5089/9781484301180.001
ISBN:
9781484301180
ISSN:
1018-5941
Pages:
25
Keywords:
WP; Chow-Lin method; BI ratio; absolute error; Cholette-Dagum method; Benchmarking; Extrapolation; Quarterly National Accounts; regression model; Chow-Lin projection; Exports; Imports; Trade in goods
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IMF Working Papers describe research in progress by the author(s) and are published to elicit comments and to encourage debate. The views expressed in IMF Working Papers are those of the author(s) and do not necessarily represent the views of the IMF, its Executive Board, or IMF management.
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Benchmarking methods can be used to extrapolate (or “nowcast”) low-frequency benchmarks on the basis of available high-frequency indicators. Quarterly national accounts are a typical example, where a number of monthly and quarterly indicators of economic activity are used to calculate preliminary annual estimates of GDP. Using both simulated and real-life national accounts data, this paper aims at assessing the prediction accuracy of three benchmarking methods widely used in the national accounts compilation: the proportional Denton method, the proportional Cholette-Dagum method with first-order autoregressive error, and the regression-based Chow-Lin method. The results show that the Cholette-Dagum method provides the most accurate extrapolations when the indicator and the annual benchmarks move along the same trend. However, the Denton and Chow-Lin methods could prevail in real-life cases when the quarterly indicator temporarily deviates from the target series.
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Cover IMF Working Papers
IMF Working Papers
ISSN:
1018-5941
Publisher:
International Monetary Fund
Volume 2016: Issue 071