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Evaluating density forecasts: forecast combinations, model mixtures, calibration and sharpness

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  • James Mitchell
  • Kenneth F. Wallis

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Bibliographic Info

Article provided by John Wiley & Sons, Ltd. in its journal Journal of Applied Econometrics.

Volume (Year): 26 (2011)
Issue (Month): 6 (09)
Pages: 1023-1040

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Handle: RePEc:wly:japmet:v:26:y:2011:i:6:p:1023-1040

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Cited by:
  1. Shaun P Vahey & Elizabeth C Wakerly, 2013. "Moving towards probability forecasting," BIS Papers chapters, in: Bank for International Settlements (ed.), Globalisation and inflation dynamics in Asia and the Pacific, volume 70, pages 3-8 Bank for International Settlements.
  2. Tsyplakov, Alexander, 2013. "Evaluation of Probabilistic Forecasts: Proper Scoring Rules and Moments," MPRA Paper 45186, University Library of Munich, Germany.
  3. Knüppel, Malte & Schultefrankenfeld, Guido, 2013. "The empirical (ir)relevance of the interest rate assumption for central bank forecasts," Discussion Papers 11/2013, Deutsche Bundesbank, Research Centre.
  4. Barbara Rossi & Tatevik Sehkposyan, 2013. "Evaluating Predictive Densities of U.S. Output Growth and Inflation in a Large Macroeconomic Data Set," Working Papers 689, Barcelona Graduate School of Economics.
  5. Rossi, Barbara & Sekhposyan, Tatevik, 2014. "Evaluating predictive densities of US output growth and inflation in a large macroeconomic data set," International Journal of Forecasting, Elsevier, vol. 30(3), pages 662-682.
  6. Anthony Garratt & James Mitchell & Shaun P. Vahey, 2011. "Measuring Output Gap Nowcast Uncertainty," CAMA Working Papers 2011-16, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  7. Piergiorgio Alessandri & Haroon Mumtaz, 2014. "Financial Conditions and Density Forecasts for US Output and Inflation," Working Papers 715, Queen Mary, University of London, School of Economics and Finance.
  8. Andres, Philipp, 2014. "Maximum likelihood estimates for positive valued dynamic score models; The DySco package," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 34-42.
  9. Andres, P. & Harvey, A., 2012. "The Dyanamic Location/Scale Model: with applications to intra-day financial data," Cambridge Working Papers in Economics 1240, Faculty of Economics, University of Cambridge.
  10. Ito, Ryoko, 2013. "Modeling dynamic diurnal patterns in high frequency financial data," Cambridge Working Papers in Economics 1315, Faculty of Economics, University of Cambridge.
  11. Tsyplakov, Alexander, 2014. "Theoretical guidelines for a partially informed forecast examiner," MPRA Paper 55017, University Library of Munich, Germany.
  12. Manzan, Sebastiano & Zerom, Dawit, 2013. "Are macroeconomic variables useful for forecasting the distribution of U.S. inflation?," International Journal of Forecasting, Elsevier, vol. 29(3), pages 469-478.
  13. Tsyplakov, Alexander, 2012. "Assessment of probabilistic forecasts: Proper scoring rules and moments," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 27(3), pages 115-132.
  14. Kenny, Geoff & Kostka, Thomas & Masera, Federico, 2013. "Can macroeconomists forecast risk? Event-based evidence from the euro area SPF," Working Paper Series 1540, European Central Bank.

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