Forecasting US economic growth in downturns using cross-country data

Yifei Lyu, Jun Nie and Shu-Kuei X. Yang

Economics Letters, 2021, vol. 198, issue C

Abstract: The Covid-19 pandemic has created tremendous downward pressure on economic activity and revived interest in forecasting economic growth during severe downturns. However, most dynamic factor models used to forecast GDP growth include only domestic data. We construct a large data set of 77 countries representing over 90 percent of global GDP and show that including cross-country data helps produce more accurate forecasts of US GDP growth during economic downturns, but is less helpful in normal times. We provide explanations why this is the case.

Keywords: Forecasting; Dynamic factor model; GDP growth; Cross-country data; Global financial crisis; Covid-19 (search for similar items in EconPapers)
JEL-codes: C32 C38 C53 C55 E32 E37 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Working Paper: Forecasting U.S. Economic Growth in Downturns Using Cross-Country Data (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecolet:v:198:y:2021:i:c:s0165176520304286

DOI: 10.1016/j.econlet.2020.109668

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