Nowcasting 'true' monthly US GDP during the pandemic

Koop, Gary and McIntyre, Stuart and Mitchell, James and Poon, Aubrey (2021) Nowcasting 'true' monthly US GDP during the pandemic. National Institute Economic Review, 256. pp. 44-70. ISSN 0027-9501 (https://doi.org/10.1017/nie.2021.8)

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Abstract

Expenditure side and income side GDP are both measured at the quarterly frequency in the US and contain measurement error. They are noisy proxies of 'true' GDP. Several econometric methods exist for producing estimates of true GDP which reconcile these noisy estimates. Recently, the authors of this paper developed a mixed frequency reconciliation model which produces monthly estimates of true GDP. In the present paper, we investigate whether this model continues to work well in the face of the extreme observations that occurred during the pandemic year of 2020 and consider several extensions of it. These extensions include stochastic volatility and error distributions that are fat tailed or explicitly allow for outliers. We also investigate the performance of conditional forecasting, where we estimate our models using data through 2019 and then use these to nowcast throughout 2020. Nowcasts are updated each month of 2020 conditionally on the new data releases which occur each month, but the parameters are not re-estimated. In total we compare the real-time performance of 12 nowcasting approaches over the pandemic months. We find that our original model with Normal homoskedastic errors produces point nowcasts as good or better than any of the other approaches. A property of Normal homoskedastic models that is often considered bad (i.e. that they are not robust to outliers), actually benefits the KMMP model as it reacts confidently to the rapidly evolving economic data. In terms of nowcast densities, we find many of the extensions lead to larger predictive variances reflecting the great uncertainty of the pandemic months.

  • Item type:Article
    ID code:76859
    Dates:
    Date
    Event
    23 June 2021
    Published
    31 May 2021
    Published Online
    8 March 2021
    Accepted
    Notes:Published in Spring 2021 as part of the special issue, 'The Impact of Covid-19 on Macroeconomic Forecasting' (Vol.256).
    Subjects:Social Sciences > Economic Theory
    Department:Strathclyde Business School > Economics
    Depositing user: Pure Administrator
    Date deposited:22 Jun 2021 12:52
    Last modified:11 Apr 2024 02:13
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/76859
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