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Scoring rules and survey density forecasts

Citations

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Cited by:

  1. Alexander, Carol & Han, Yang & Meng, Xiaochun, 2023. "Static and dynamic models for multivariate distribution forecasts: Proper scoring rule tests of factor-quantile versus multivariate GARCH models," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1078-1096.
  2. Ambrocio, Gene, 2017. "The real effects of overconfidence and fundamental uncertainty shocks," Research Discussion Papers 37/2017, Bank of Finland.
  3. repec:zbw:bofrdp:2017_037 is not listed on IDEAS
  4. Krüger, Fabian & Pavlova, Lora, 2019. "Quantifying subjective oncertainty in survey expectations," Working Papers 0664, University of Heidelberg, Department of Economics.
  5. Jan-Egbert Sturm & Jakob Haan, 2011. "Does central bank communication really lead to better forecasts of policy decisions? New evidence based on a Taylor rule model for the ECB," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 147(1), pages 41-58, April.
  6. Hana Braitsch & James Mitchell & Taylor Shiroff, 2024. "Practice Makes Perfect: Learning Effects with Household Point and Density Forecasts of Inflation," Working Papers 24-25, Federal Reserve Bank of Cleveland.
  7. Rosa, Carlo, 2011. "Words that shake traders," Journal of Empirical Finance, Elsevier, vol. 18(5), pages 915-934.
  8. Corona Francisco & Horrillo Juan de Dios Tena & Wiper Michael Peter, 2017. "On the importance of the probabilistic model in identifying the most decisive games in a tournament," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 13(1), pages 11-23, March.
  9. Geoff Kenny & Thomas Kostka & Federico Masera, 2015. "Density characteristics and density forecast performance: a panel analysis," Empirical Economics, Springer, vol. 48(3), pages 1203-1231, May.
  10. David Harris & Gael M. Martin & Indeewara Perera & Don S. Poskitt, 2017. "Construction and visualization of optimal confidence sets for frequentist distributional forecasts," Monash Econometrics and Business Statistics Working Papers 9/17, Monash University, Department of Econometrics and Business Statistics.
  11. Michael K. Adjemian & Valentina G. Bruno & Michel A. Robe, 2020. "Incorporating Uncertainty into USDA Commodity Price Forecasts," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(2), pages 696-712, March.
  12. Casey, Eddie, 2021. "Are professional forecasters overconfident?," International Journal of Forecasting, Elsevier, vol. 37(2), pages 716-732.
  13. Berg, Tim O. & Henzel, Steffen R., 2015. "Point and density forecasts for the euro area using Bayesian VARs," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1067-1095.
  14. Gregor Bäurle & Elizabeth Steiner & Gabriel Züllig, 2021. "Forecasting the production side of GDP," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 458-480, April.
  15. Constandina Koki & Loukia Meligkotsidou & Ioannis Vrontos, 2020. "Forecasting under model uncertainty: Non‐homogeneous hidden Markov models with Pòlya‐Gamma data augmentation," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(4), pages 580-598, July.
  16. repec:zbw:bofrdp:037 is not listed on IDEAS
  17. Alexander Glas & Matthias Hartmann, 2022. "Uncertainty measures from partially rounded probabilistic forecast surveys," Quantitative Economics, Econometric Society, vol. 13(3), pages 979-1022, July.
  18. Pavlova, Lora, 2024. "Framing effects in consumer expectations surveys," ZEW Discussion Papers 24-036, ZEW - Leibniz Centre for European Economic Research.
  19. Clements, Michael P., 2018. "Are macroeconomic density forecasts informative?," International Journal of Forecasting, Elsevier, vol. 34(2), pages 181-198.
  20. Ng, Jason & Forbes, Catherine S. & Martin, Gael M. & McCabe, Brendan P.M., 2013. "Non-parametric estimation of forecast distributions in non-Gaussian, non-linear state space models," International Journal of Forecasting, Elsevier, vol. 29(3), pages 411-430.
  21. Kannika Duangnate & James W. Mjelde, 2020. "Prequential forecasting in the presence of structure breaks in natural gas spot markets," Empirical Economics, Springer, vol. 59(5), pages 2363-2384, November.
  22. Laurent L. Pauwels & Andrey L. Vasnev, 2017. "Forecast combination for discrete choice models: predicting FOMC monetary policy decisions," Empirical Economics, Springer, vol. 52(1), pages 229-254, February.
  23. BAN Kanemi & KAWAGOE Masaaki & MATSUOKA Hideaki, 2013. "Evaluating Density Forecasts with Applications to ESPF," ESRI Discussion paper series 302, Economic and Social Research Institute (ESRI).
  24. 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.
  25. Krüger, Fabian & Pavlova, Lora, 2024. "Quantifying subjective uncertainty in survey expectations," International Journal of Forecasting, Elsevier, vol. 40(2), pages 796-810.
  26. Clements, Michael P., 2021. "Do survey joiners and leavers differ from regular participants? The US SPF GDP growth and inflation forecasts," International Journal of Forecasting, Elsevier, vol. 37(2), pages 634-646.
  27. Tsyplakov, Alexander, 2014. "Theoretical guidelines for a partially informed forecast examiner," MPRA Paper 55017, University Library of Munich, Germany.
  28. repec:syb:wpbsba:01/2013 is not listed on IDEAS
  29. Berg, Tim O. & Henzel, Steffen R., 2015. "Point and density forecasts for the euro area using Bayesian VARs," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1067-1095.
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