A Bayesian Approach to Inference on Probabilistic Surveys
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Note: Revised August 2024.
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- Bassetti, Federico & Casarin, Roberto & Del Negro, Marco, 2024. "A Bayesian Approach for Inference on Probabilistic Surveys," CEPR Discussion Papers 19426, C.E.P.R. Discussion Papers.
References listed on IDEAS
- Jensen, Mark J. & Maheu, John M., 2010.
"Bayesian semiparametric stochastic volatility modeling,"
Journal of Econometrics, Elsevier, vol. 157(2), pages 306-316, August.
- Mark J Jensen & John M Maheu, 2008. "Bayesian semiparametric stochastic volatility modeling," Working Papers tecipa-314, University of Toronto, Department of Economics.
- Mark J. Jensen & John M. Maheu, 2009. "Bayesian Semiparametric Stochastic Volatility Modeling," Working Paper series 23_09, Rimini Centre for Economic Analysis.
- Mark J. Jensen & John M. Maheu, 2008. "Bayesian semiparametric stochastic volatility modeling," FRB Atlanta Working Paper 2008-15, Federal Reserve Bank of Atlanta.
- Keisuke Hirano, 2002. "Semiparametric Bayesian Inference in Autoregressive Panel Data Models," Econometrica, Econometric Society, vol. 70(2), pages 781-799, March.
- Kent Daniel & David Hirshleifer, 2015.
"Overconfident Investors, Predictable Returns, and Excessive Trading,"
Journal of Economic Perspectives, American Economic Association, vol. 29(4), pages 61-88, Fall.
- Kent Daniel & David Hirshleifer, 2016. "Overconfident Investors, Predictable Returns, and Excessive Trading," NBER Working Papers 21945, National Bureau of Economic Research, Inc.
- Ulrike Malmendier & Timothy Taylor, 2015. "On the Verges of Overconfidence," Journal of Economic Perspectives, American Economic Association, vol. 29(4), pages 3-8, Fall.
- Olivier Coibion & Yuriy Gorodnichenko, 2012.
"What Can Survey Forecasts Tell Us about Information Rigidities?,"
Journal of Political Economy, University of Chicago Press, vol. 120(1), pages 116-159.
- Olivier Coibion & Yuriy Gorodnichenko, 2008. "What Can Survey Forecasts Tell Us About Informational Rigidities?," NBER Working Papers 14586, National Bureau of Economic Research, Inc.
- Yuriy Gorodnichenko & Olivier Coibion, 2010. "What can survey forecasts tell us about informational rigidities?," 2010 Meeting Papers 277, Society for Economic Dynamics.
- Manzan, Sebastiano, 2021. "Are professional forecasters Bayesian?," Journal of Economic Dynamics and Control, Elsevier, vol. 123(C).
- Laura Liu, 2018.
"Density Forecasts in Panel Data Models : A Semiparametric Bayesian Perspective,"
Finance and Economics Discussion Series
2018-036, Board of Governors of the Federal Reserve System (U.S.).
- Laura Liu, 2020. "Density Forecasts in Panel Data Models: A Semiparametric Bayesian Perspective," CAEPR Working Papers 2020-003, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
- Laura Liu, 2018. "Density Forecasts in Panel Data Models: A Semiparametric Bayesian Perspective," Papers 1805.04178, arXiv.org, revised Oct 2021.
- Fair, Ray C & Shiller, Robert J, 1990. "Comparing Information in Forecasts from Econometric Models," American Economic Review, American Economic Association, vol. 80(3), pages 375-389, June.
- Jeff Dominitz & Charles F. Manski, 1996.
"Eliciting Student Expectations of the Returns to Schooling,"
Journal of Human Resources, University of Wisconsin Press, vol. 31(1), pages 1-26.
- J. Dominitz & C. F. Manski, "undated". "Eliciting student expectations of the returns to schooling," Institute for Research on Poverty Discussion Papers 1049-94, University of Wisconsin Institute for Research on Poverty.
- Jeff Dominitz & Charles F. Manski, 1994. "Eliciting Student Expectations Of The Returns To Schooling," Econometrics 9411002, University Library of Munich, Germany.
- Jeff Dominitz & Charles F. Manski, 1994. "Eliciting Student Expectations of the Returns to Schooling," NBER Working Papers 4936, National Bureau of Economic Research, Inc.
- Patton, Andrew J. & Timmermann, Allan, 2007. "Properties of optimal forecasts under asymmetric loss and nonlinearity," Journal of Econometrics, Elsevier, vol. 140(2), pages 884-918, October.
- Binder, Carola C., 2017. "Measuring uncertainty based on rounding: New method and application to inflation expectations," Journal of Monetary Economics, Elsevier, vol. 90(C), pages 1-12.
- Pelenis, Justinas, 2014. "Bayesian regression with heteroscedastic error density and parametric mean function," Journal of Econometrics, Elsevier, vol. 178(P3), pages 624-638.
- Engelberg, Joseph & Manski, Charles F. & Williams, Jared, 2009.
"Comparing the Point Predictions and Subjective Probability Distributions of Professional Forecasters,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 27, pages 30-41.
- Joseph Engelberg & Charles F. Manski & Jared Williams, 2006. "Comparing the Point Predictions and Subjective Probability Distributions of Professional Forecasters," NBER Working Papers 11978, National Bureau of Economic Research, Inc.
- J. E. Griffin, 2011. "Inference in Infinite Superpositions of Non-Gaussian Ornstein--Uhlenbeck Processes Using Bayesian Nonparametic Methods," Journal of Financial Econometrics, Oxford University Press, vol. 9(3), pages 519-549, Summer.
- Fushang Liu & Kajal Lahiri, 2006.
"Modelling multi-period inflation uncertainty using a panel of density forecasts,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(8), pages 1199-1219.
- Kajal Lahiri & Fushang Liu, 2006. "Modelling multi‐period inflation uncertainty using a panel of density forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(8), pages 1199-1219, December.
- Kajal Lahiri & Fushang Liu, 2006. "Modeling Multi-Period Inflation Uncertainty Using a Panel of Density Forcasts," Discussion Papers 06-05, University at Albany, SUNY, Department of Economics.
- Gianna Boero & Jeremy Smith & Kenneth F. Wallis, 2008.
"Uncertainty and Disagreement in Economic Prediction: The Bank of England Survey of External Forecasters,"
Economic Journal, Royal Economic Society, vol. 118(530), pages 1107-1127, July.
- Gianna Boero & Jeremy Smith & KennethF. Wallis, 2008. "Uncertainty and Disagreement in Economic Prediction: The Bank of England Survey of External Forecasters," Economic Journal, Royal Economic Society, vol. 118(530), pages 1107-1127, July.
- Boero, Gianna & Smith, Jeremy & Wallis, Kenneth F., 2006. "Uncertainty and disagreement in economic prediction: the Bank of England Survey of External Forecasters," Economic Research Papers 269751, University of Warwick - Department of Economics.
- Boero,Gianna & Smith,Jeremy & Wallis,Kenneth F, 2006. "Uncertainty and disagreement in economic prediction : the Bank of England Survey of External Forecasters," The Warwick Economics Research Paper Series (TWERPS) 811, University of Warwick, Department of Economics.
- Chib, Siddhartha & Hamilton, Barton H., 2002. "Semiparametric Bayes analysis of longitudinal data treatment models," Journal of Econometrics, Elsevier, vol. 110(1), pages 67-89, September.
- Kozeniauskas, Nicholas & Orlik, Anna & Veldkamp, Laura, 2018. "What are uncertainty shocks?," Journal of Monetary Economics, Elsevier, vol. 100(C), pages 1-15.
- Simon M. Potter, 2016. "The advantages of probabilistic survey questions: remarks at the IT Forum and RCEA Bayesian Workshop, keynote address, Rimini, Italy, May 2016," Speech 211, Federal Reserve Bank of New York.
- Jiaying Gu & Roger Koenker, 2017. "Unobserved Heterogeneity in Income Dynamics: An Empirical Bayes Perspective," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(1), pages 1-16, January.
- Robert Rich & Joseph Tracy, 2010. "The Relationships among Expected Inflation, Disagreement, and Uncertainty: Evidence from Matched Point and Density Forecasts," The Review of Economics and Statistics, MIT Press, vol. 92(1), pages 200-207, February.
- Zarnowitz, Victor & Lambros, Louis A, 1987. "Consensus and Uncertainty in Economic Prediction," Journal of Political Economy, University of Chicago Press, vol. 95(3), pages 591-621, June.
- Norets, Andriy & Pelenis, Justinas, 2012. "Bayesian modeling of joint and conditional distributions," Journal of Econometrics, Elsevier, vol. 168(2), pages 332-346.
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More about this item
Keywords
Bayesian nonparametrics; probabilistic surveys; noisy rational expectations;All these keywords.
JEL classification:
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
- E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
- E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
- E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
NEP fields
This paper has been announced in the following NEP Reports:- NEP-ECM-2022-08-15 (Econometrics)
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