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Forecast uncertainty: sources, measurement and evaluation

Author

Listed:
  • Matteo Ciccarelli

    (European Central Bank, Frankfurt am Main, Germany)

  • Kirstin Hubrich

    (European Central Bank, Frankfurt am Main, Germany)

Abstract

No abstract is available for this item.

Suggested Citation

  • Matteo Ciccarelli & Kirstin Hubrich, 2010. "Forecast uncertainty: sources, measurement and evaluation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 509-513.
    • Handle: RePEc:jae:japmet:v:25:y:2010:i:4:p:509-513
    DOI: 10.1002/jae.1179
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    Cited by:

    1. Li, Li & Kang, Yanfei & Li, Feng, 2023. "Bayesian forecast combination using time-varying features," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1287-1302.
    2. Pedersen, Michael, 2019. "Anomalies in macroeconomic prediction errors–evidence from Chilean private forecasters," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1100-1107.
    3. Constantin Mitru? & Mihaela Bratu (Simionescu), 2013. "The Indicators’ Inadequacy and the Predictions’ Accuracy," Acta Universitatis Danubius. OEconomica, Danubius University of Galati, issue 9(4), pages 430-442, August.
    4. Mihaela SIMIONESCU, 2013. "The Assessment Of Parameter Uncertainty In A Vector Error Correction Model For Romania," Romanian Journal of Economics, Institute of National Economy, vol. 37(2(46)), pages 124-134, December.
    5. López Menéndez, Ana Jesús & Pérez Suárez, Rigoberto, 2017. "Forecasting Performance and Information Measures. Revisiting the M-Competition /Evaluación de Predicciones y Medidas de Información. Reexamen de la M-Competición," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 35, pages 299-314, Mayo.
    6. Eva A. Arnold, 2013. "The Role of Data Revisions and Disagreement in Professional Forecasts," Macroeconomics and Finance Series 201303, University of Hamburg, Department of Socioeconomics.

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