Strategic judgment: its game-theoretic foundations,its econometric elicitation
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Victor Richmond R. Jose & Robert F. Nau & Robert L. Winkler, 2008. "Scoring Rules, Generalized Entropy, and Utility Maximization," Operations Research, INFORMS, vol. 56(5), pages 1146-1157, October.
- T. S. Breusch & A. R. Pagan, 1980.
"The Lagrange Multiplier Test and its Applications to Model Specification in Econometrics,"
The Review of Economic Studies, Review of Economic Studies Ltd, vol. 47(1), pages 239-253.
- Breusch, T.S. & Pagan, A.R., 1980. "The Lagrange multiplier test and its applications to model specification in econometrics," LIDAM Reprints CORE 412, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Vladimir Vovk & Glenn Shafer, 2005. "Good randomized sequential probability forecasting is always possible," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(5), pages 747-763, November.
- Terasvirta, Timo & Tjostheim, Dag & Granger, Clive W. J., 2010. "Modelling Nonlinear Economic Time Series," OUP Catalogue, Oxford University Press, number 9780199587155.
- Diks, Cees & Panchenko, Valentyn & van Dijk, Dick, 2011.
"Likelihood-based scoring rules for comparing density forecasts in tails,"
Journal of Econometrics, Elsevier, vol. 163(2), pages 215-230, August.
- Cees Diks & Valentyn Panchenko & Dick van Dijk, 2011. "Likelihood-based scoring rules for comparing density forecasts in tails," Post-Print hal-00834423, HAL.
- Tilmann Gneiting & Roopesh Ranjan, 2011. "Comparing Density Forecasts Using Threshold- and Quantile-Weighted Scoring Rules," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(3), pages 411-422, July.
- Engel, J. & Haugh, D. & Pagan, A., 2005.
"Some methods for assessing the need for non-linear models in business cycle analysis,"
International Journal of Forecasting, Elsevier, vol. 21(4), pages 651-662.
- James Engel & David Haugh & Adrian Pagan, 2004. "Some methods for assessing the need for non-linear models in business cycle analysis," CAMA Working Papers 2004-07, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National 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.
- Gneiting, Tilmann & Ranjan, Roopesh, 2011. "Comparing Density Forecasts Using Threshold- and Quantile-Weighted Scoring Rules," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(3), pages 411-422.
- repec:hal:journl:peer-00834423 is not listed on IDEAS
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.- Emilio Zanetti Chini, 2018.
"Forecasters’ utility and forecast coherence,"
CREATES Research Papers
2018-23, Department of Economics and Business Economics, Aarhus University.
- Emilio Zanetti Chini, 2018. "Forecaster’s utility and forecasts coherence," DEM Working Papers Series 145, University of Pavia, Department of Economics and Management.
- Emilio Zanetti Chini, 2018. "Forecaster’s utility and forecasts coherence," CREATES Research Papers 2018-01, Department of Economics and Business Economics, Aarhus University.
- Kapetanios, G. & Mitchell, J. & Price, S. & Fawcett, N., 2015.
"Generalised density forecast combinations,"
Journal of Econometrics, Elsevier, vol. 188(1), pages 150-165.
- Fawcett, Nicholas & Kapetanios, George & Mitchell, James & Price, Simon, 2013. "Generalised Density Forecast Combinations," EMF Research Papers 05, Economic Modelling and Forecasting Group.
- 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.
- Luisa Bisaglia & Matteo Grigoletto, 2021. "A new time-varying model for forecasting long-memory series," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(1), pages 139-155, March.
- 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.
- Taillardat, Maxime & Fougères, Anne-Laure & Naveau, Philippe & de Fondeville, Raphaël, 2023. "Evaluating probabilistic forecasts of extremes using continuous ranked probability score distributions," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1448-1459.
- David T. Frazier & Ruben Loaiza-Maya & Gael M. Martin, 2021.
"Variational Bayes in State Space Models: Inferential and Predictive Accuracy,"
Papers
2106.12262, arXiv.org, revised Feb 2022.
- David T. Frazier & Gael M. Martin & Ruben Loaiza-Maya, 2022. "Variational Bayes in State Space Models: Inferential and Predictive Accuracy," Monash Econometrics and Business Statistics Working Papers 1/22, Monash University, Department of Econometrics and Business Statistics.
- Ramon de Punder & Timo Dimitriadis & Rutger-Jan Lange, 2024.
"Kullback-Leibler-based characterizations of score-driven updates,"
Papers
2408.02391, arXiv.org, revised Sep 2024.
- Ramon de Punder & Timo Dimitriadis & Rutger-Jan Lange, 2024. "Kullback-Leibler-based characterizations of score-driven updates," Tinbergen Institute Discussion Papers 24-051/III, Tinbergen Institute, revised 22 Oct 2024.
- Clements, Michael P., 2018.
"Are macroeconomic density forecasts informative?,"
International Journal of Forecasting, Elsevier, vol. 34(2), pages 181-198.
- Michael Clements, 2016. "Are Macroeconomic Density Forecasts Informative?," ICMA Centre Discussion Papers in Finance icma-dp2016-02, Henley Business School, University of Reading.
- Jonas R. Brehmer & Tilmann Gneiting, 2020. "Properization: constructing proper scoring rules via Bayes acts," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(3), pages 659-673, June.
- Xiaochun Meng & James W. Taylor & Souhaib Ben Taieb & Siran Li, 2020. "Scores for Multivariate Distributions and Level Sets," Papers 2002.09578, arXiv.org, revised Jun 2023.
- Diks, Cees & Fang, Hao, 2020. "Comparing density forecasts in a risk management context," International Journal of Forecasting, Elsevier, vol. 36(2), pages 531-551.
- Tobias Fissler & Hajo Holzmann, 2022. "Measurability of functionals and of ideal point forecasts," Papers 2203.08635, arXiv.org.
- Arora Siddharth & Little Max A. & McSharry Patrick E., 2013. "Nonlinear and nonparametric modeling approaches for probabilistic forecasting of the US gross national product," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(4), pages 395-420, September.
- Carol Alexander & Michael Coulon & Yang Han & Xiaochun Meng, 2021. "Evaluating the Discrimination Ability of Proper Multivariate Scoring Rules," Papers 2101.12693, arXiv.org.
- Luisa Bisaglia & Matteo Grigoletto, 2018. "A new time-varying model for forecasting long-memory series," Papers 1812.07295, arXiv.org.
- Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2023. "Large Time‐Varying Volatility Models for Hourly Electricity Prices," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 545-573, June.
- 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, 2014. "Optimal portfolio choice under decision-based model combinations," Working Paper 2014/15, Norges Bank.
- Chuliá, Helena & Garrón, Ignacio & Uribe, Jorge M., 2024.
"Daily growth at risk: Financial or real drivers? The answer is not always the same,"
International Journal of Forecasting, Elsevier, vol. 40(2), pages 762-776.
- Helena Chuliá & Ignacio Garrón & Jorge M. Uribe, 2022. ""Daily Growth at Risk: financial or real drivers? The answer is not always the same"," IREA Working Papers 202208, University of Barcelona, Research Institute of Applied Economics, revised Jun 2022.
- repec:bny:wpaper:0088 is not listed on IDEAS
- Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87.
- Pfarrhofer, Michael, 2022.
"Modeling tail risks of inflation using unobserved component quantile regressions,"
Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
- Michael Pfarrhofer, 2021. "Modeling tail risks of inflation using unobserved component quantile regressions," Papers 2103.03632, arXiv.org, revised Oct 2021.
More about this item
Keywords
Business Cycle; Predictive Density; Forecast Evaluation; Coherence Testing; Scoring Rules and Structures;All these keywords.
JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
NEP fields
This paper has been announced in the following NEP Reports:- NEP-ECM-2019-12-02 (Econometrics)
- NEP-ORE-2019-12-02 (Operations Research)
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:sap:wpaper:wp190. 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: Luisa Giuriato (email available below). General contact details of provider: https://edirc.repec.org/data/dprosit.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.