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Implementing tests for forecast evaluation in the presence of instabilities

Author

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  • Barbara Rossi

    (University of Pompeu Fabra)

  • Matthieu Soupre

    (University of Pompeu Fabra)

Abstract

In this article, we review methodologies to fix the size distortions of tests for forecast evaluation in the presence of instabilities. The methodologies implement tests for relative and absolute forecast evaluation that are robust to instabilities. We also introduce the giacross and rosssekh commands, which implement these procedures in Stata. Copyright 2017 by StataCorp LP.

Suggested Citation

  • Barbara Rossi & Matthieu Soupre, 2017. "Implementing tests for forecast evaluation in the presence of instabilities," Stata Journal, StataCorp LP, vol. 17(4), pages 850-865, December.
    • Handle: RePEc:tsj:stataj:v:17:y:2017:i:4:p:850-865
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    Cited by:

    1. Carlos Henrique Dias Cordeiro de Castro & Fernando Antonio Lucena Aiube, 2023. "Forecasting inflation time series using score‐driven dynamic models and combination methods: The case of Brazil," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 369-401, March.
    2. Monique Reid & Pierre Siklos, 2023. "Rationality and biases insights from disaggregated firm level inflation expectations data," Working Papers 11050, South African Reserve Bank.

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