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Forecasting US Output Growth with Large Information Sets

Author

Listed:
  • Afees A. Salisu

    (Centre for Econometric & Allied Research, University of Ibadan, Ibadan, Nigeria)

  • Umar Bida Ndako

    (Economic Policy Directorate, Central Bank of Nigeria)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, South Africa)

Abstract

We forecast US output growth using an array of both Classical and Bayesian models including the recently developed Dynamic Variable Selection prior with Variational Bayes [DVSVB] of Koop and Korobilis (2020). We accommodate over 300 predictors that are incrementally captured from 5 factors, 60 factors to over 300 factors covering relevant economic agents. For robustness, we allow for both constant and time varying coefficients as well as alternative proxies for output growth. Using data covering 1960:Q1 to 2018:Q4, our results consistently support the use of high-dimensional models when forecasting US output growth regardless of the choice of forecast measure. For the density forecast of real GDP growth in particular, the results favour the DVSVB and time varying parameter assumption.

Suggested Citation

  • Afees A. Salisu & Umar Bida Ndako & Rangan Gupta, 2021. "Forecasting US Output Growth with Large Information Sets," Working Papers 202103, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:202103
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    More about this item

    Keywords

    US Output Growth; High-Dimensional Models; Forecast Evaluation;
    All these keywords.

    JEL classification:

    • O41 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - One, Two, and Multisector Growth Models
    • O51 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - U.S.; Canada
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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