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Forecasting using a random coefficient autoregression

Author

Listed:
  • Philip Hans Franses

    (Econometric Institute, Erasmus School of Economics)

  • Dmitriy Knyazhitskiy

    (Econometric Institute, Erasmus School of Economics)

Abstract

We consider point forecasts for economic time series using a basic random coefficient autoregression. We show using simulations that these point forecasts do not improve much on the point forecasts from fixed coefficient autoregressive models. Various empirical illustrations emphasize the simulations-based evidence.

Suggested Citation

  • Philip Hans Franses & Dmitriy Knyazhitskiy, 2025. "Forecasting using a random coefficient autoregression," Empirical Economics, Springer, vol. 69(6), pages 3001-3017, December.
    • Handle: RePEc:spr:empeco:v:69:y:2025:i:6:d:10.1007_s00181-025-02824-y
    DOI: 10.1007/s00181-025-02824-y
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    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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