On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates
Author
Suggested Citation
DOI: 10.21799/frbp.wp.2021.06
Download full text from publisher
To our knowledge, this item is not available for download. To find whether it is available, there are three options:1. Check below whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
Other versions of this item:
- Diebold, Francis X. & Shin, Minchul & Zhang, Boyuan, 2023. "On the aggregation of probability assessments: Regularized mixtures of predictive densities for Eurozone inflation and real interest rates," Journal of Econometrics, Elsevier, vol. 237(2).
- Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2021. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone In?ation and Real Interest Rates," PIER Working Paper Archive 21-002, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2022. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates," NBER Working Papers 29635, National Bureau of Economic Research, Inc.
- Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2020. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates," Papers 2012.11649, arXiv.org, revised Jun 2022.
References listed on IDEAS
- Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2021.
"Economic Predictions With Big Data: The Illusion of Sparsity,"
Econometrica, Econometric Society, vol. 89(5), pages 2409-2437, September.
- Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio, 2017. "Economic Predictions with Big Data: The Illusion Of Sparsity," CEPR Discussion Papers 12256, C.E.P.R. Discussion Papers.
- Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2018. "Economic predictions with big data: the illusion of sparsity," Staff Reports 847, Federal Reserve Bank of New York.
- Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio E., 2021. "Economic predictions with big data: the illusion of sparsity," Working Paper Series 2542, European Central Bank.
- Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2018. "Economic Predictions with Big Data: The Illusion of Sparsity," Liberty Street Economics 20180521, Federal Reserve Bank of New York.
- Billio, Monica & Casarin, Roberto & Ravazzolo, Francesco & van Dijk, Herman K., 2013.
"Time-varying combinations of predictive densities using nonlinear filtering,"
Journal of Econometrics, Elsevier, vol. 177(2), pages 213-232.
- Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2012. "Time-varying Combinations of Predictive Densities using Nonlinear Filtering," Tinbergen Institute Discussion Papers 12-118/III, Tinbergen Institute.
- Anne Sofie Jore & James Mitchell & Shaun P. Vahey, 2010.
"Combining forecast densities from VARs with uncertain instabilities,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 621-634.
- Anne-Sofie Jore & James Mitchell & Shaun P. Vahey, 2008. "Combining forecast densities from VARs with uncertain instabilities," Working Paper 2008/01, Norges Bank.
- Anne Sofie Jore & James Mitchell & Shaun Vahey, 2008. "Combining Forecast Densities from VARs with Uncertain Instabilities," Reserve Bank of New Zealand Discussion Paper Series DP2008/18, Reserve Bank of New Zealand.
- Ross Askanazi & Francis X. Diebold & Frank Schorfheide & Minchul Shin, 2018.
"On the Comparison of Interval Forecasts,"
Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 953-965, November.
- Ross Askanazi & Francis X. Diebold & Frank Schorfheide & Minchul Shin, 2018. "On the Comparison of Interval Forecasts," PIER Working Paper Archive 18-013, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 02 Aug 2018.
- Graham Elliott & Allan Timmermann, 2016.
"Economic Forecasting,"
Economics Books,
Princeton University Press,
edition 1, number 10740.
- Graham Elliott & Allan Timmermann, 2008. "Economic Forecasting," Journal of Economic Literature, American Economic Association, vol. 46(1), pages 3-56, March.
- Timmermann, Allan & Elliott, Graham, 2007. "Economic Forecasting," CEPR Discussion Papers 6158, C.E.P.R. Discussion Papers.
- Fabio Busetti, 2017.
"Quantile Aggregation of Density Forecasts,"
Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(4), pages 495-512, August.
- Fabio Busetti, 2014. "Quantile aggregation of density forecasts," Temi di discussione (Economic working papers) 979, Bank of Italy, Economic Research and International Relations Area.
- Christian Kascha & Francesco Ravazzolo, 2010.
"Combining inflation density forecasts,"
Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 231-250.
- Christian Kascha & Francesco Ravazzolo, 2008. "Combining inflation density forecasts," Working Paper 2008/22, Norges Bank.
- Timmermann, Allan, 2006.
"Forecast Combinations,"
Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 4, pages 135-196,
Elsevier.
- Timmermann, Allan, 2005. "Forecast Combinations," CEPR Discussion Papers 5361, C.E.P.R. Discussion Papers.
- Aiolfi Marco & Capistrán Carlos & Timmermann Allan, 2010. "Forecast Combinations," Working Papers 2010-04, Banco de México.
- Marco Aiolfi & Carlos Capistrán & Allan Timmermann, 2010. "Forecast Combinations," CREATES Research Papers 2010-21, Department of Economics and Business Economics, Aarhus University.
- Francis X. Diebold & Minchul Shin, 2017.
"Assessing point forecast accuracy by stochastic error distance,"
Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 588-598, October.
- Francis X. Diebold & Minchul Shin, 2014. "Assessing Point Forecast Accuracy by Stochastic Error Distance," PIER Working Paper Archive 14-038, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- Francis X. Diebold & Minchul Shin, 2016. "Assessing Point Forecast Accuracy by Stochastic Error Distance," NBER Working Papers 22516, National Bureau of Economic Research, Inc.
- Geweke, John & Amisano, Gianni, 2011.
"Optimal prediction pools,"
Journal of Econometrics, Elsevier, vol. 164(1), pages 130-141, September.
- John Geweke & Gianni Amisano, 2008. "Optimal Prediction Pools," Working Paper series 22_08, Rimini Centre for Economic Analysis.
- Amisano, Gianni & Geweke, John, 2009. "Optimal Prediction Pools," Working Paper Series 1017, European Central Bank.
- Capistrán, Carlos & Timmermann, Allan, 2009.
"Forecast Combination With Entry and Exit of Experts,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 428-440.
- Timmermann Allan & Capistrán Carlos, 2006. "Forecast Combination with Entry and Exit of Experts," Working Papers 2006-08, Banco de México.
- Carlos Capistrán & Allan Timmermann, 2008. "Forecast Combination With Entry and Exit of Experts," CREATES Research Papers 2008-55, Department of Economics and Business Economics, Aarhus University.
- Genre, Véronique & Kenny, Geoff & Meyler, Aidan & Timmermann, Allan, 2013. "Combining expert forecasts: Can anything beat the simple average?," International Journal of Forecasting, Elsevier, vol. 29(1), pages 108-121.
- Gianni Amisano & John Geweke, 2017.
"Prediction Using Several Macroeconomic Models,"
The Review of Economics and Statistics, MIT Press, vol. 99(5), pages 912-925, December.
- Amisano, Gianni & Geweke, John, 2013. "Prediction using several macroeconomic models," Working Paper Series 1537, European Central Bank.
- Graham Elliott & Allan Timmermann, 2016.
"Forecasting in Economics and Finance,"
Annual Review of Economics, Annual Reviews, vol. 8(1), pages 81-110, October.
- Timmermann, Allan & Elliott, Graham, 2016. "Forecasting in Economics and Finance," CEPR Discussion Papers 11354, C.E.P.R. Discussion Papers.
- Elliott, Graham & Timmermann, Allan G, 2016. "Forecasting in Economics and Finance," University of California at San Diego, Economics Working Paper Series qt6z55v472, Department of Economics, UC San Diego.
- Roopesh Ranjan & Tilmann Gneiting, 2010. "Combining probability forecasts," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(1), pages 71-91, January.
- Claudia Czado & Tilmann Gneiting & Leonhard Held, 2009. "Predictive Model Assessment for Count Data," Biometrics, The International Biometric Society, vol. 65(4), pages 1254-1261, December.
- Conflitti, Cristina & De Mol, Christine & Giannone, Domenico, 2015.
"Optimal combination of survey forecasts,"
International Journal of Forecasting, Elsevier, vol. 31(4), pages 1096-1103.
- Cristina Conflitti & Christine De Mol & Domenico Giannone, 2012. "Optimal Combination of Survey Forecasts," Working Papers ECARES ECARES 2012-023, ULB -- Universite Libre de Bruxelles.
- Giannone, Domenico & De Mol, Christine & Conflitti, Cristina, 2012. "Optimal Combination of Survey Forecasts," CEPR Discussion Papers 9096, C.E.P.R. Discussion Papers.
- G. Elliott & C. Granger & A. Timmermann (ed.), 2006. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 1, number 1.
- McAlinn, Kenichiro & West, Mike, 2019. "Dynamic Bayesian predictive synthesis in time series forecasting," Journal of Econometrics, Elsevier, vol. 210(1), pages 155-169.
- Kenneth Wallis, 2011. "Combining forecasts - forty years later," Applied Financial Economics, Taylor & Francis Journals, vol. 21(1-2), pages 33-41.
- Hall, Stephen G. & Mitchell, James, 2007. "Combining density forecasts," International Journal of Forecasting, Elsevier, vol. 23(1), pages 1-13.
- Diebold, Francis X & Gunther, Todd A & Tay, Anthony S, 1998. "Evaluating Density Forecasts with Applications to Financial Risk Management," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 863-883, November.
- Kapetanios, G. & Mitchell, J. & Price, S. & Fawcett, N., 2015.
"Generalised density forecast combinations,"
Journal of Econometrics, Elsevier, vol. 188(1), pages 150-165.
- N. Fawcett & G. Kapetanios & J. Mitchell & S. Price, 2014. "Generalised Density Forecast Combinations," CAMA Working Papers 2014-24, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Fawcett, Nicholas & Kapetanios, George & Mitchell, James & Price, Simon, 2014. "Generalised density forecast combinations," Bank of England working papers 492, Bank of England.
- Diebold, Francis X. & Shin, Minchul, 2019.
"Machine learning for regularized survey forecast combination: Partially-egalitarian LASSO and its derivatives,"
International Journal of Forecasting, Elsevier, vol. 35(4), pages 1679-1691.
- Francis X. Diebold & Minchul Shin, 2018. "Machine Learning for Regularized Survey Forecast Combination: Partially Egalitarian Lasso and its Derivatives," PIER Working Paper Archive 18-014, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 17 Aug 2018.
- Francis X. Diebold & Minchul Shin, 2018. "Machine Learning for Regularized Survey Forecast Combination: Partially-Egalitarian Lasso and its Derivatives," NBER Working Papers 24967, National Bureau of Economic Research, Inc.
- Chen, Nai-Fu & Roll, Richard & Ross, Stephen A, 1986. "Economic Forces and the Stock Market," The Journal of Business, University of Chicago Press, vol. 59(3), pages 383-403, July.
- Friedman, Milton, 1977. "Nobel Lecture: Inflation and Unemployment," Journal of Political Economy, University of Chicago Press, vol. 85(3), pages 451-472, June.
- Hounyo, Ulrich & Lahiri, Kajal, 2023.
"Estimating the variance of a combined forecast: Bootstrap-based approach,"
Journal of Econometrics, Elsevier, vol. 232(2), pages 445-468.
- Ulrich Hounyo & Kajal Lahiri, 2021. "Estimating the Variance of a Combined Forecast: Bootstrap-Based Approach," CREATES Research Papers 2021-14, Department of Economics and Business Economics, Aarhus University.
- Gneiting, Tilmann & Raftery, Adrian E., 2007. "Strictly Proper Scoring Rules, Prediction, and Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 359-378, March.
- Hui Zou & Trevor Hastie, 2005. "Addendum: Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(5), pages 768-768, November.
- K=osaku Takanashi & Kenichiro McAlinn, 2019. "Equivariant online predictions of non-stationary time series," Papers 1911.08662, arXiv.org, revised Jun 2023.
- Hui Zou & Trevor Hastie, 2005. "Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(2), pages 301-320, April.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Chernis Tony, 2024.
"Combining Large Numbers of Density Predictions with Bayesian Predictive Synthesis,"
Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 28(2), pages 293-317, April.
- Tony Chernis, 2023. "Combining Large Numbers of Density Predictions with Bayesian Predictive Synthesis," Staff Working Papers 23-45, Bank of Canada.
- Garratt, Anthony & Henckel, Timo & Vahey, Shaun P., 2023.
"Empirically-transformed linear opinion pools,"
International Journal of Forecasting, Elsevier, vol. 39(2), pages 736-753.
- Anthony Garratt & Timo Henckel & Shaun P. Vahey, 2019. "Empirically-transformed linear opinion pools," CAMA Working Papers 2019-47, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Ricardo P. Masini & Marcelo C. Medeiros & Eduardo F. Mendes, 2023.
"Machine learning advances for time series forecasting,"
Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 76-111, February.
- Ricardo P. Masini & Marcelo C. Medeiros & Eduardo F. Mendes, 2020. "Machine Learning Advances for Time Series Forecasting," Papers 2012.12802, arXiv.org, revised Apr 2021.
- 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.
- Ganics, Gergely & Mertens, Elmar & Clark, Todd E., 2023. "What Is the Predictive Value of SPF Point and Density Forecasts?," VfS Annual Conference 2023 (Regensburg): Growth and the "sociale Frage" 277622, Verein für Socialpolitik / German Economic Association.
- Bańbura, Marta & Brenna, Federica & Paredes, Joan & Ravazzolo, Francesco, 2021. "Combining Bayesian VARs with survey density forecasts: does it pay off?," Working Paper Series 2543, European Central Bank.
- Wang, Xiaoqian & Hyndman, Rob J. & Li, Feng & Kang, Yanfei, 2023. "Forecast combinations: An over 50-year review," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1518-1547.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022.
"Forecasting: theory and practice,"
International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
- Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
- Wang, Xiaoqian & Hyndman, Rob J. & Li, Feng & Kang, Yanfei, 2023. "Forecast combinations: An over 50-year review," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1518-1547.
- Knut Are Aastveit & James Mitchell & Francesco Ravazzolo & Herman van Dijk, 2018. "The Evolution of Forecast Density Combinations in Economics," Tinbergen Institute Discussion Papers 18-069/III, Tinbergen Institute.
- Federico Bassetti & Roberto Casarin & Francesco Ravazzolo, 2019. "Density Forecasting," BEMPS - Bozen Economics & Management Paper Series BEMPS59, Faculty of Economics and Management at the Free University of Bozen.
- Barbara Rossi, 2019.
"Forecasting in the presence of instabilities: How do we know whether models predict well and how to improve them,"
Economics Working Papers
1711, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.
- 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.
- Rossi, Barbara, 2020. "Forecasting in the Presence of Instabilities: How Do We Know Whether Models Predict Well and How to Improve Them," CEPR Discussion Papers 14472, C.E.P.R. Discussion Papers.
- 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.
- Li Li & Yanfei Kang & Feng Li, 2021. "Bayesian forecast combination using time-varying features," Papers 2108.02082, arXiv.org, revised Jun 2022.
- Peter McAdam & Anders Warne, 2024.
"Density forecast combinations: The real‐time dimension,"
Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(5), pages 1153-1172, August.
- McAdam, Peter & Warne, Anders, 2020. "Density forecast combinations: the real-time dimension," Working Paper Series 2378, European Central Bank.
- Conflitti, Cristina & De Mol, Christine & Giannone, Domenico, 2015.
"Optimal combination of survey forecasts,"
International Journal of Forecasting, Elsevier, vol. 31(4), pages 1096-1103.
- Giannone, Domenico & De Mol, Christine & Conflitti, Cristina, 2012. "Optimal Combination of Survey Forecasts," CEPR Discussion Papers 9096, C.E.P.R. Discussion Papers.
- Cristina Conflitti & Christine De Mol & Domenico Giannone, 2012. "Optimal Combination of Survey Forecasts," Working Papers ECARES ECARES 2012-023, ULB -- Universite Libre de Bruxelles.
- Ruben Loaiza‐Maya & Gael M. Martin & David T. Frazier, 2021.
"Focused Bayesian prediction,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 517-543, August.
- Ruben Loaiza-Maya & Gael M. Martin & David T. Frazier, 2019. "Focused Bayesian Prediction," Papers 1912.12571, arXiv.org, revised Aug 2020.
- Ruben Loaiza-Maya & Gael M Martin & David T. Frazier, 2020. "Focused Bayesian Prediction," Monash Econometrics and Business Statistics Working Papers 1/20, Monash University, Department of Econometrics and Business Statistics.
- 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.
- Ruben Loaiza-Maya & Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Andres Ramirez Hassan, 2020. "Optimal probabilistic forecasts: When do they work?," Monash Econometrics and Business Statistics Working Papers 33/20, Monash University, Department of Econometrics and Business Statistics.
- Gael M. Martin & Rub'en Loaiza-Maya & David T. Frazier & Worapree Maneesoonthorn & Andr'es Ram'irez Hassan, 2020. "Optimal probabilistic forecasts: When do they work?," Papers 2009.09592, arXiv.org.
- Garratt, Anthony & Henckel, Timo & Vahey, Shaun P., 2023.
"Empirically-transformed linear opinion pools,"
International Journal of Forecasting, Elsevier, vol. 39(2), pages 736-753.
- Anthony Garratt & Timo Henckel & Shaun P. Vahey, 2019. "Empirically-transformed linear opinion pools," CAMA Working Papers 2019-47, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Knut Are Aastveit & Jamie L. Cross & Herman K. van Dijk, 2023.
"Quantifying Time-Varying Forecast Uncertainty and Risk for the Real Price of Oil,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(2), pages 523-537, April.
- Knut Are Aastveit & Jamie L. Cross & Herman K. van Dijk, 2021. "Quantifying time-varying forecast uncertainty and risk for the real price of oil," Working Paper 2021/3, Norges Bank.
- Knut Are Aastveit & Jamie Cross & Herman K. Djik, 2021. "Quantifying time-varying forecast uncertainty and risk for the real price of oil," Working Papers No 03/2021, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
- Knut Are Aastveit & Jamie Cross & Herman K. van Dijk, 2021. "Quantifying time-varying forecast uncertainty and risk for the real price of oil," Tinbergen Institute Discussion Papers 21-053/III, Tinbergen Institute.
- Davide Pettenuzzo & Francesco Ravazzolo, 2016.
"Optimal Portfolio Choice Under Decision‐Based Model Combinations,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1312-1332, November.
- Davide Pettenuzzo & Francesco Ravazzolo, 2014. "Optimal Portfolio Choice under Decision-Based Model Combinations," Working Papers 80, Brandeis University, Department of Economics and International Business School.
- Davide Pettenuzzo & Francesco Ravazzolo, 2015. "Optimal Portfolio Choice under Decision-Based Model Combinations," Working Papers No 9/2015, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
- Davide Pettenuzzo & Francesco Ravazzolo, 2014. "Optimal portfolio choice under decision-based model combinations," Working Paper 2014/15, Norges Bank.
- Malte Knüppel & Fabian Krüger, 2022.
"Forecast uncertainty, disagreement, and the linear pool,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 23-41, January.
- Knüppel, Malte & Krüger, Fabian, 2017. "Forecast Uncertainty, Disagreement, and Linear Pools of Density Forecasts," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168294, Verein für Socialpolitik / German Economic Association.
- Knüppel, Malte & Krüger, Fabian, 2019. "Forecast uncertainty, disagreement, and the linear pool," Discussion Papers 28/2019, Deutsche Bundesbank.
- Weron, Rafał, 2014.
"Electricity price forecasting: A review of the state-of-the-art with a look into the future,"
International Journal of Forecasting, Elsevier, vol. 30(4), pages 1030-1081.
- Rafal Weron, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," HSC Research Reports HSC/14/07, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
- Fabio Busetti, 2017.
"Quantile Aggregation of Density Forecasts,"
Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(4), pages 495-512, August.
- Fabio Busetti, 2014. "Quantile aggregation of density forecasts," Temi di discussione (Economic working papers) 979, Bank of Italy, Economic Research and International Relations Area.
- K=osaku Takanashi & Kenichiro McAlinn, 2019. "Equivariant online predictions of non-stationary time series," Papers 1911.08662, arXiv.org, revised Jun 2023.
- Hasumi, Ryo & Iiboshi, Hirokuni & Matsumae, Tatsuyoshi & Nakamura, Daisuke, 2019. "Does a financial accelerator improve forecasts during financial crises? Evidence from Japan with prediction-pooling methods," Journal of Asian Economics, Elsevier, vol. 60(C), pages 45-68.
- Knut Are Aastveit & Francesco Ravazzolo & Herman K. van Dijk, 2018.
"Combined Density Nowcasting in an Uncertain Economic Environment,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 131-145, January.
- Knut Are Aastveit & Francesco Ravazzolo & Herman K. van Dijk, 2014. "Combined Density Nowcasting in an Uncertain Economic Environment," Tinbergen Institute Discussion Papers 14-152/III, Tinbergen Institute.
- Knut Are Aastveit & Francesco Ravazzolo & Herman K. van Dijk, 2014. "Combined Density Nowcasting in an uncertain economic environment," Working Paper 2014/17, Norges Bank.
- Wang, Shengjie & Kang, Yanfei & Petropoulos, Fotios, 2024. "Combining probabilistic forecasts of intermittent demand," European Journal of Operational Research, Elsevier, vol. 315(3), pages 1038-1048.
More about this item
Keywords
Density forecasts; forecast combinations; survey forecasts; shrinkage; model selection; regularization; partially egalitarian LASSO; model averaging; subset averaging;All these keywords.
JEL classification:
- C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
- C5 - Mathematical and Quantitative Methods - - Econometric Modeling
- C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:fip:fedpwp:89897. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Beth Paul (email available below). General contact details of provider: https://edirc.repec.org/data/frbphus.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.