How to deal with missing observations in surveys of professional forecasters
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DOI: 10.1080/15140326.2023.2185975
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- Constantin Bürgi, 2023. "How to Deal With Missing Observations in Surveys of Professional Forecasters," CESifo Working Paper Series 10203, CESifo.
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- Geoff Kenny & Thomas Kostka & Federico Masera, 2015.
"Can Macroeconomists Forecast Risk? Event-Based Evidence from the Euro-Area SPF,"
International Journal of Central Banking, International Journal of Central Banking, vol. 11(4), pages 1-46, December.
- 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.
- Olesya Grishchenko & Sarah Mouabbi & Jean‐Paul Renne, 2019.
"Measuring Inflation Anchoring and Uncertainty: A U.S. and Euro Area Comparison,"
Journal of Money, Credit and Banking, Blackwell Publishing, vol. 51(5), pages 1053-1096, August.
- Olesya V. Grishchenko & Sarah Mouabbi & Jean-Paul Renne, 2017. "Measuring Inflation Anchoring and Uncertainty : A US and Euro Area Comparison," Finance and Economics Discussion Series 2017-102, Board of Governors of the Federal Reserve System (U.S.).
- Antonello D’Agostino & Kieran Mcquinn & Karl Whelan, 2012.
"Are Some Forecasters Really Better Than Others?,"
Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(4), pages 715-732, June.
- Antonello D’agostino & Kieran Mcquinn & Karl Whelan, 2012. "Are Some Forecasters Really Better Than Others?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(4), pages 715-732, June.
- Antonello D’Agostino & Kieran McQuinn & Karl Whelan, 2010. "Are Some Forecasters Really Better Than Others?," Working Papers 201012, School of Economics, University College Dublin.
- D'Agostino, Antonello & McQuinn, Kieran & Whelan, Karl, 2010. "Are Some Forecasters Really Better Than Others?," Research Technical Papers 5/RT/10, Central Bank of Ireland.
- D'Agostino, Antonello & McQuinn, Kieran & Whelan, Karl, 2011. "Are some forecasters really better than others?," MPRA Paper 32938, University Library of Munich, Germany.
- Yongchen Zhao, 2021.
"The robustness of forecast combination in unstable environments: a Monte Carlo study of advanced algorithms,"
Empirical Economics, Springer, vol. 61(1), pages 173-199, July.
- Yongchen Zhao, 2015. "Robustness of Forecast Combination in Unstable Environment: A Monte Carlo Study of Advanced Algorithms," Working Papers 2015-04, Towson University, Department of Economics, revised Mar 2020.
- Yongchen Zhao, 2015. "Robustness of Forecast Combination in Unstable Environment: A Monte Carlo Study of Advanced Algorithms," Working Papers 2015-005, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
- 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.
- Poncela, Pilar & Rodríguez, Julio & Sánchez-Mangas, Rocío & Senra, Eva, 2011.
"Forecast combination through dimension reduction techniques,"
International Journal of Forecasting, Elsevier, vol. 27(2), pages 224-237, April.
- Poncela, Pilar & Rodríguez, Julio & Sánchez-Mangas, Rocío & Senra, Eva, 2011. "Forecast combination through dimension reduction techniques," International Journal of Forecasting, Elsevier, vol. 27(2), pages 224-237.
- Geoff Kenny & Thomas Kostka & Federico Masera, 2015.
"Density characteristics and density forecast performance: a panel analysis,"
Empirical Economics, Springer, vol. 48(3), pages 1203-1231, May.
- Kenny, Geoff & Kostka, Thomas & Masera, Federico, 2014. "Density characteristics and density forecast performance: a panel analysis," Working Paper Series 1679, European Central Bank.
- Scotti, Chiara, 2016.
"Surprise and uncertainty indexes: Real-time aggregation of real-activity macro-surprises,"
Journal of Monetary Economics, Elsevier, vol. 82(C), pages 1-19.
- Chiara Scotti, 2013. "Surprise and uncertainty indexes: real-time aggregation of real-activity macro surprises," International Finance Discussion Papers 1093, Board of Governors of the Federal Reserve System (U.S.).
- 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.
- Olivier Coibion & Yuriy Gorodnichenko, 2015.
"Information Rigidity and the Expectations Formation Process: A Simple Framework and New Facts,"
American Economic Review, American Economic Association, vol. 105(8), pages 2644-2678, August.
- Olivier Coibion & Yuriy Gorodnichenko, 2010. "Information Rigidity and the Expectations Formation Process: A Simple Framework and New Facts," Working Papers 102, Department of Economics, College of William and Mary.
- Mr. Olivier Coibion & Mr. Yuriy Gorodnichenko, 2012. "Information Rigidity and the Expectations Formation Process: A Simple Framework and New Facts," IMF Working Papers 2012/296, International Monetary Fund.
- Olivier Coibion & Yuriy Gorodnichenko, 2010. "Information Rigidity and the Expectations Formation Process: A Simple Framework and New Facts," NBER Working Papers 16537, National Bureau of Economic Research, Inc.
- Batchelor, R A, 1990. "All Forecasters Are Equal," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 143-144, January.
- Andrade, Philippe & Le Bihan, Hervé, 2013.
"Inattentive professional forecasters,"
Journal of Monetary Economics, Elsevier, vol. 60(8), pages 967-982.
- Hervé Le Bihan & Philippe Andrade, 2010. "Inattentive Professional Forecasters," 2010 Meeting Papers 1144, Society for Economic Dynamics.
- Andrade, P. & Le Bihan, H., 2010. "Inattentive professional forecasters," Working papers 307, Banque de France.
- Issler, João Victor & Lima, Luiz Renato, 2009.
"A panel data approach to economic forecasting: The bias-corrected average forecast,"
Journal of Econometrics, Elsevier, vol. 152(2), pages 153-164, October.
- Lima, Luiz Renato Regis de Oliveira & Issler, João Victor, 2007. "A panel data approach to economic forecasting: the bias-corrected average forecast," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 650, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
- Lima, Luiz Renato Regis de Oliveira & Issler, João Victor, 2008. "A panel data approach to economic forecasting: the bias-corrected average forecast," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 668, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
- Issler, João Victor & Lima, Luiz Renato Regis de Oliveira, 2007. "A panel data approach to economic forecasting: the bias-corrected average forecast," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 642, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
- Constantin Bürgi & Tara M. Sinclair, 2017.
"A nonparametric approach to identifying a subset of forecasters that outperforms the simple average,"
Empirical Economics, Springer, vol. 53(1), pages 101-115, August.
- Constantin Bürgi & Tara M. Sinclair, 2015. "A Nonparametric Approach to Identifying a Subset of Forecasters that Outperforms the Simple Average," Working Papers 2015-006, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
- Diebold, Francis X & Mariano, Roberto S, 2002.
"Comparing Predictive Accuracy,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
- Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-263, July.
- Francis X. Diebold & Roberto S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
- Kajal Lahiri & Huaming Peng & Yongchen Zhao, 2017. "Online learning and forecast combination in unbalanced panels," Econometric Reviews, Taylor & Francis Journals, vol. 36(1-3), pages 257-288, March.
- 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.
- Ghysels, Eric & Wright, Jonathan H., 2009.
"Forecasting Professional Forecasters,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 504-516.
- Eric Ghysels & Jonathan H. Wright, 2006. "Forecasting professional forecasters," Finance and Economics Discussion Series 2006-10, Board of Governors of the Federal Reserve System (U.S.).
- Raffaella Giacomini & Barbara Rossi, 2010.
"Forecast comparisons in unstable environments,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 595-620.
- Giacomini, Raffaella & Rossi, Barbara, 2008. "Forecast Comparisons in Unstable Environments," Working Papers 08-04, Duke University, Department of Economics.
- Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
- Rebecca R. Andridge & Roderick J. A. Little, 2010. "A Review of Hot Deck Imputation for Survey Non‐response," International Statistical Review, International Statistical Institute, vol. 78(1), pages 40-64, April.
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JEL classification:
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
- E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
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