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Optimality Tests for Multi-Horizon Forecasts

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  • Capistrán Carlos

Abstract

This paper develops and analyzes a series of tests to evaluate the optimality of forecasts when forecasts for more than one horizon are available. The tests are based on the property that the unconditional expected loss of optimal forecasts should not decrease with the forecast horizon (e.g., under quadratic loss the variance of optimal forecast errors should not decrease with the horizon). The tests complement existing methods of forecast evaluation, such as Mincer-Zarnowitz-type tests, by using an implication of optimality that directly concerns forecasts made at different horizons. The finite sample performance of the tests is analyzed and an illustration using the Survey of Professional Forecasters is provided.

Suggested Citation

  • Capistrán Carlos, 2007. "Optimality Tests for Multi-Horizon Forecasts," Working Papers 2007-14, Banco de México.
    • Handle: RePEc:bdm:wpaper:2007-14
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    Cited by:

    1. Capistrán, Carlos & López-Moctezuma, Gabriel, 2014. "Forecast revisions of Mexican inflation and GDP growth," International Journal of Forecasting, Elsevier, vol. 30(2), pages 177-191.
    2. Andrew Patton & Allan Timmermann, 2012. "Forecast Rationality Tests Based on Multi-Horizon Bounds," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 1-17.

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    More about this item

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications

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