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Forecasting U.S. Economic Growth in Downturns Using Cross-Country Data

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Abstract
To examine whether including economic data on other countries could improve the forecast of U.S. GDP growth, we construct a large data set of 77 countries representing over 90 percent of global GDP. Our benchmark model is a dynamic factor model using U.S. data only, which we extend to include data from other countries. We show that using cross-country data produces more accurate forecasts during the global financial crisis period. Based on the latest vintage data on August 6, 2020, the benchmark model forecasts U.S. real GDP growth in 2020:Q3 to be −6.9 percent (year-over-year rate) or 14.9 percent (quarter-over-quarter annualized rate), whereas the forecast is revised upward to −6.1 percent (year-over-year) or 19.1 percent (quarter-over-quarter) when cross-country data are used. These examples suggest that U.S. data alone may fail to capture the spillover effects of other countries in downturns. However, we find that foreign variables are much less useful in normal times.

Suggested Citation

  • , 2020. "Forecasting U.S. Economic Growth in Downturns Using Cross-Country Data," Research Working Paper RWP 20-09, Federal Reserve Bank of Kansas City.
    • Handle: RePEc:fip:fedkrw:88691
    DOI: 10.18651/RWP2020-09
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    1. Shouheng Tuo & Tianrui Chen & Hong He & Zengyu Feng & Yanling Zhu & Fan Liu & Chao Li, 2021. "A Regional Industrial Economic Forecasting Model Based on a Deep Convolutional Neural Network and Big Data," Sustainability, MDPI, vol. 13(22), pages 1-11, November.

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    More about this item

    Keywords

    Forecasting; Dynamic factor model; GDP growth; Cross-country data; Global financial crisis; COVID-19;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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