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On a Bootstrap Test for Forecast Evaluations

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  • Marian Vavra

    (National Bank of Slovakia, Research Department)

Abstract

This paper is concerned with the problem of testing for the equal forecast accuracy of competing models using a bootstrap-based Diebold-Mariano test statistic. The finite-sample properties of the test are assessed via Monte Carlo experiments. As an illustration, the forecast accuracy of the US Survey of Professional Forecasters is compared to that of an autoregressive model. The empirical results indicate that professionals beat AR models systematically only for a single economic variable – the unemployment rate

Suggested Citation

  • Marian Vavra, 2015. "On a Bootstrap Test for Forecast Evaluations," Working and Discussion Papers WP 5/2015, Research Department, National Bank of Slovakia.
    • Handle: RePEc:svk:wpaper:1034
    as

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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Forecast evaluation; Diebold-Mariano test; Sieve bootstrap;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • 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
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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