Forecasting With Real-Time Macroeconomic Data: The Ragged-Edge Problem and Revisions

Kees Bouwman; JPAM Jacobs

doi:10.1016/j.jmacro.2011.04.002

Forecasting With Real-Time Macroeconomic Data: The Ragged-Edge Problem and Revisions

Kees Bouwman, JPAM Jacobs

Econometrics

Research output: Contribution to journal › Article › Academic › peer-review

8 Citations (Scopus)

Abstract

Real-time macroeconomic data are typically incomplete for today and the immediate past (`ragged edge¿) and subject to revision. To enable more timely forecasts the recent missing data have to be imputed. The paper presents a state-space model that can deal with publication lags and data revisions. The framework is applied to the US leading index. We conclude that including even a simple model of data revisions improves the accuracy of the imputations and that the univariate imputation method in levels adopted by The Conference Board can be improved upon.

Original language	English
Pages (from-to)	784-792
Number of pages	9
Journal	Journal of Macroeconomics
Volume	33
Issue number	4
DOIs	https://doi.org/10.1016/j.jmacro.2011.04.002
Publication status	Published - 2011

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10.1016/j.jmacro.2011.04.002

http://hdl.handle.net/1765/67867

Cite this

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Forecasting With Real-Time Macroeconomic Data: The Ragged-Edge Problem and Revisions

Abstract

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