Reconciled Estimates of Monthly GDP in the US

Gary Koop (), Stuart McIntyre (), James Mitchell () and Aubrey Poon ()

EMF Research Papers from Economic Modelling and Forecasting Group

Abstract: In the US, income and expenditure side estimates of GDP (GDPI and GDPE) measure “true” GDP with error and are available at the quarterly frequency. Methods exist for producing reconciled quarterly estimates of GDP based on GDPI and GDPE. In this paper, we extend these methods to provide reconciled historical GDP estimates at the monthly frequency from 1960. We do this using a Bayesian Mixed Frequency Vector Autoregression involving GDPE, GDPI, unobserved true GDP and monthly indicators of short-term economic activity. We illustrate how the new monthly data contribute to our historical understanding of business cycles.

Keywords: state-space model; vector autoregressions; Bayesian methods; turning points (search for similar items in EconPapers)
JEL-codes: E01 E32 (search for similar items in EconPapers)
Date: 2020
New Economics Papers: this item is included in nep-ets and nep-mac
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https://warwick.ac.uk/fac/soc/wbs/subjects/finance ... papers/emf_wp_37.pdf

Related works:
Working Paper: Reconciled Estimates of Monthly GDP in the US (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:wrk:wrkemf:37

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