IDEAS home Printed from https://ideas.repec.org/r/fip/fedcwp/1715.html
   My bibliography  Save this item

Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Kajal Lahiri & Huaming Peng & Xuguang Simon Sheng, 2022. "Measuring Uncertainty of a Combined Forecast and Some Tests for Forecaster Heterogeneity," Advances in Econometrics, in: Essays in Honor of M. Hashem Pesaran: Prediction and Macro Modeling, volume 43, pages 29-50, Emerald Group Publishing Limited.
  2. Li, Zheng & Zeng, Jingjing & Hensher, David A., 2023. "An efficient approach to structural breaks and the case of automobile gasoline consumption in Australia," Transportation Research Part A: Policy and Practice, Elsevier, vol. 169(C).
  3. Li, Zheng & Zhou, Bo & Hensher, David A., 2022. "Forecasting automobile gasoline demand in Australia using machine learning-based regression," Energy, Elsevier, vol. 239(PD).
  4. Oliver Grothe & Fabian Kachele & Fabian Kruger, 2022. "From point forecasts to multivariate probabilistic forecasts: The Schaake shuffle for day-ahead electricity price forecasting," Papers 2204.10154, arXiv.org.
  5. Efrem Castelnuovo, 2022. "Uncertainty Before and During COVID-19: A Survey," "Marco Fanno" Working Papers 0279, Dipartimento di Scienze Economiche "Marco Fanno".
  6. Knüppel, Malte & Schultefrankenfeld, Guido, 2019. "Assessing the uncertainty in central banks’ inflation outlooks," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1748-1769.
  7. Adams, Patrick A. & Adrian, Tobias & Boyarchenko, Nina & Giannone, Domenico, 2021. "Forecasting macroeconomic risks," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1173-1191.
  8. Schick, Manuel, 2024. "Real-time Nowcasting Growth-at-Risk using the Survey of Professional Forecasters," Working Papers 0750, University of Heidelberg, Department of Economics.
  9. repec:wrk:wrkemf:35 is not listed on IDEAS
  10. Corradi, Valentina & Fosten, Jack & Gutknecht, Daniel, 2023. "Out-of-sample tests for conditional quantile coverage an application to Growth-at-Risk," Journal of Econometrics, Elsevier, vol. 236(2).
  11. Yoosoon Chang & Yong-gun Kim & Boreum Kwak & Joon Y. Park, 2024. "Using Density Forecast for Growth-at-Risk to Improve Mean Forecast of GDP Growth in Korea," CAEPR Working Papers 2024-005 Classification-C, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
  12. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2024. "Addressing COVID-19 Outliers in BVARs with Stochastic Volatility," The Review of Economics and Statistics, MIT Press, vol. 106(5), pages 1403-1417, September.
  13. Reifschneider, David & Tulip, Peter, 2019. "Gauging the uncertainty of the economic outlook using historical forecasting errors: The Federal Reserve’s approach," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1564-1582.
  14. Grothe, Oliver & Kächele, Fabian & Krüger, Fabian, 2023. "From point forecasts to multivariate probabilistic forecasts: The Schaake shuffle for day-ahead electricity price forecasting," Energy Economics, Elsevier, vol. 120(C).
  15. Simón Sosvilla-Rivero & María del Carmen Ramos-Herrera, 2018. "Inflation, real economic growth and unemployment expectations: an empirical analysis based on the ECB survey of professional forecasters," Applied Economics, Taylor & Francis Journals, vol. 50(42), pages 4540-4555, September.
  16. Knüppel, Malte, 2018. "Forecast-error-based estimation of forecast uncertainty when the horizon is increased," International Journal of Forecasting, Elsevier, vol. 34(1), pages 105-116.
  17. Dibiasi, Andreas & Sarferaz, Samad, 2023. "Measuring macroeconomic uncertainty: A cross-country analysis," European Economic Review, Elsevier, vol. 153(C).
  18. Barbara Rossi, 2018. "Identifying and estimating the effects of unconventional monetary policy in the data: How to do It and what have we learned?," Economics Working Papers 1641, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2020.
  19. Tamás Kiss & Stepan Mazur & Hoang Nguyen & Pär Österholm, 2023. "Modeling the relation between the US real economy and the corporate bond‐yield spread in Bayesian VARs with non‐Gaussian innovations," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 347-368, March.
  20. Fabian Kruger & Hendrik Plett, 2022. "Prediction intervals for economic fixed-event forecasts," Papers 2210.13562, arXiv.org, revised Mar 2024.
  21. Mirela Miescu, 2019. "Uncertainty shocks in emerging economies," Working Papers 277077821, Lancaster University Management School, Economics Department.
  22. Barbara Rossi, 2019. "Forecasting in the Presence of Instabilities: How Do We Know Whether Models Predict Well and How to Improve Them," Working Papers 1162, Barcelona School of Economics.
  23. Bas Scheer, 2022. "Addressing Unemployment Rate Forecast Errors in Relation to the Business Cycle," CPB Discussion Paper 434, CPB Netherlands Bureau for Economic Policy Analysis.
  24. repec:wrk:wrkemf:33 is not listed on IDEAS
  25. Weiqi Zhang & Huong Ha & Hui Ting Evelyn Gay, 2020. "Analysts’ forecasts between last consensus and earning announcement date," Journal of Financial Reporting and Accounting, Emerald Group Publishing Limited, vol. 18(4), pages 779-793, November.
  26. Todd E. Clark & Gergely Ganics & Elmar Mertens, 2022. "What is the Predictive Value of SPF Point and Density Forecasts?," Working Papers 22-37, Federal Reserve Bank of Cleveland.
  27. Sharpe, Steven A. & Sinha, Nitish R. & Hollrah, Christopher A., 2023. "The power of narrative sentiment in economic forecasts," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1097-1121.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.