Predective Density and Conditional Confidence Interval Accuracy Tests

Citations

Cited by:

1. Juan Carlos Pérez-Velasco Pavón, 2009. "Determinantes de la demanda por la denominación promedio de billete: el caso de México," Monetaria, CEMLA, vol. 0(4), pages 523-548, octubre-d.
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   • Norman R. Swanson & Nii Ayi Armah, 2011. "Predictive Inference Under Model Misspecification with an Application to Assessing the Marginal Predictive Content of Money for Output," Departmental Working Papers 201103, Rutgers University, Department of Economics.
3. Ivana Komunjer & Michael T. Owyang, 2012. "Multivariate Forecast Evaluation and Rationality Testing," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1066-1080, November.
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   • Komunjer, Ivana & OWYANG, MICHAEL, 2007. "Multivariate Forecast Evaluation And Rationality Testing," University of California at San Diego, Economics Working Paper Series qt81w8m5sf, Department of Economics, UC San Diego.
4. Delle Monache, Davide & Petrella, Ivan, 2017. "Adaptive models and heavy tails with an application to inflation forecasting," International Journal of Forecasting, Elsevier, vol. 33(2), pages 482-501.
   • Delle Monache, Davide & Petrella, Ivan, 2016. "Adaptive models and heavy tails with an application to inflation forecasting," MPRA Paper 75424, University Library of Munich, Germany.
   • Davide Delle Monache & Ivan Petrella, 2016. "Adaptive models and heavy tails with an application to inflation forecasting," BCAM Working Papers 1603, Birkbeck Centre for Applied Macroeconomics.
5. Oleg Korenok & Stanislav Radchenko & Norman R. Swanson, 2010. "International evidence on the efficacy of new-Keynesian models of inflation persistence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 31-54.
   • Oleg Korenok & Stanislav Radchenko & Norman R. Swanson, 2010. "International evidence on the efficacy of new‐Keynesian models of inflation persistence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 31-54, January.
   • Norman Swanson & Oleg Korenok & Stanislav Radchenko, 2006. "International Evidence on the Efficacy of new-Keynesian Models of Inflation Persistence," Departmental Working Papers 200617, Rutgers University, Department of Economics.
   • Oleg Korenok & Stanislav Radchenko & Norman R. Swanson, 2006. "International Evidence on the Efficacy of new-Keynesian Models of Inflation Persistence," Working Papers 0602, VCU School of Business, Department of Economics.
   • Norman R. Swanson & Oleg Korenok & Stanislav Radchenko, 2011. "International Evidence on the Efficacy of new-Keynesian Models of Inflation Persistence," Departmental Working Papers 201104, Rutgers University, Department of Economics.
6. Rossi, Barbara & Sekhposyan, Tatevik, 2013. "Conditional predictive density evaluation in the presence of instabilities," Journal of Econometrics, Elsevier, vol. 177(2), pages 199-212.
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7. Corradi, Valentina & Swanson, Norman R., 2011. "Predictive density construction and accuracy testing with multiple possibly misspecified diffusion models," Journal of Econometrics, Elsevier, vol. 161(2), pages 304-324, April.
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   • Valentina Corradi & Norman R. Swanson, 2011. "Predictive density construction and accuracy testing with multiple possibly misspecified diffusion models," Post-Print hal-00796745, HAL.
8. Francesco Giancaterini & Alain Hecq & Claudio Morana, 2022. "Is Climate Change Time-Reversible?," Econometrics, MDPI, vol. 10(4), pages 1-18, December.
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9. Swanson, Norman R. & Urbach, Richard, 2015. "Prediction and simulation using simple models characterized by nonstationarity and seasonality," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 312-323.
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11. Jian Wang & Jason J. Wu, 2012. "The Taylor Rule and Forecast Intervals for Exchange Rates," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(1), pages 103-144, February.
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16. Martin, Gael M. & Loaiza-Maya, Rubén & Maneesoonthorn, Worapree & Frazier, David T. & Ramírez-Hassan, Andrés, 2022. "Optimal probabilistic forecasts: When do they work?," International Journal of Forecasting, Elsevier, vol. 38(1), pages 384-406.
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17. Maneesoonthorn, Worapree & Martin, Gael M. & Forbes, Catherine S. & Grose, Simone D., 2012. "Probabilistic forecasts of volatility and its risk premia," Journal of Econometrics, Elsevier, vol. 171(2), pages 217-236.
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18. Christian Pape & Arne Vogler & Oliver Woll & Christoph Weber, 2017. "Forecasting the distributions of hourly electricity spot prices," EWL Working Papers 1705, University of Duisburg-Essen, Chair for Management Science and Energy Economics, revised May 2017.
19. Todd E. Clark & Michael W. McCracken, 2010. "Testing for unconditional predictive ability," Working Papers 2010-031, Federal Reserve Bank of St. Louis.
20. Cees Diks & Valentyn Panchenko & Dick van Dijk, 2008. "Partial Likelihood-Based Scoring Rules for Evaluating Density Forecasts in Tails," Tinbergen Institute Discussion Papers 08-050/4, Tinbergen Institute.
    • Cees Diks & Valentyn Panchenko & Dick van Dijk, 2008. "Partial Likelihood-Based Scoring Rules for Evaluating Density Forecasts in Tails," Discussion Papers 2008-10, School of Economics, The University of New South Wales.
    • Dijk, D. van & Diks, C.G.H. & Panchenko, V., 2008. "Partial Likelihood-Based Scoring Rules for Evaluating Density Forecasts in Tails," CeNDEF Working Papers 08-03, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
21. Zdeněk Zmeškal & Dana Dluhošová & Karolina Lisztwanová & Antonín Pončík & Iveta Ratmanová, 2023. "Distribution Prediction of Decomposed Relative EVA Measure with Levy-Driven Mean-Reversion Processes: The Case of an Automotive Sector of a Small Open Economy," Forecasting, MDPI, vol. 5(2), pages 1-19, May.
22. Gordy, Michael B. & McNeil, Alexander J., 2020. "Spectral backtests of forecast distributions with application to risk management," Journal of Banking & Finance, Elsevier, vol. 116(C).
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23. Davide Delle Monache & Ivan Petrella, 2014. "Adaptive Models and Heavy Tails," Birkbeck Working Papers in Economics and Finance 1409, Birkbeck, Department of Economics, Mathematics & Statistics.
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