Forecasting euro area inflation using a huge panel of survey expectations
Author
Abstract
Suggested Citation
Download full text from publisher
Other versions of this item:
- Huber, Florian & Onorante, Luca & Pfarrhofer, Michael, 2024. "Forecasting euro area inflation using a huge panel of survey expectations," International Journal of Forecasting, Elsevier, vol. 40(3), pages 1042-1054.
References listed on IDEAS
- 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.
- 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.
- Koop,Gary & Poirier,Dale J. & Tobias,Justin L., 2007.
"Bayesian Econometric Methods,"
Cambridge Books,
Cambridge University Press, number 9780521671736, June.
- Koop,Gary & Poirier,Dale J. & Tobias,Justin L., 2007. "Bayesian Econometric Methods," Cambridge Books, Cambridge University Press, number 9780521855716, June.
- Koop, Gary M & Poirier, Dale J & Tobias, Justin, 2007. "Bayesian Econometric Methods," Staff General Research Papers Archive 12722, Iowa State University, Department of Economics.
- Ferrari, Davide & Ravazzolo, Francesco & Vespignani, Joaquin, 2021.
"Forecasting energy commodity prices: A large global dataset sparse approach,"
Energy Economics, Elsevier, vol. 98(C).
- Davide Ferrari & Francesco Ravazzolo & Joaquin Vespignani, 2019. "Forecasting energy commodity prices: A large global dataset sparse approach," CAMA Working Papers 2019-90, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Davide Ferrari & Francesco Ravazzolo & Joaquin Vespignani, 2021. "Forecasting Energy Commodity Prices: A Large Global Dataset Sparse Approach," BEMPS - Bozen Economics & Management Paper Series BEMPS83, Faculty of Economics and Management at the Free University of Bozen.
- Ferrari, Davide & Ravazzolo, Francesco & Vespignani, Joaquin, 2019. "Forecasting energy commodity prices: a large global dataset sparse approach," Working Papers 2019-09, University of Tasmania, Tasmanian School of Business and Economics.
- Davide Ferrari & Francesco Ravazzolo & Joaquin Vespignani, 2019. "Forecasting Energy Commodity Prices: A Large Global Dataset Sparse Approach," Working Papers No 11/2019, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
- Davide Ferrari & Francesco Ravazzolo & Joaquin L. Vespignani, 2019. "Forecasting Energy Commodity Prices: A Large Global Dataset Sparse Approach," Globalization Institute Working Papers 376, Federal Reserve Bank of Dallas.
- Joshua C. C. Chan & Gary Koop & Simon M. Potter, 2013.
"A New Model of Trend Inflation,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(1), pages 94-106, January.
- Joshua Chan & Gary Koop & Simon Potter, 2012. "A New Model of Trend Inflation," Working Papers 1202, University of Strathclyde Business School, Department of Economics.
- Chan, Joshua & Koop, Gary & Potter, Simon, 2012. "A New Model Of Trend Inflation," SIRE Discussion Papers 2012-12, Scottish Institute for Research in Economics (SIRE).
- Joshua C C Chan & Gary Koop & Simon M Potter, 2012. "A New Model of Trend Inflation," CAMA Working Papers 2012-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Chan, Joshua & Koop, Gary & Potter, Simon, 2012. "A new model of trend inflation," MPRA Paper 39496, University Library of Munich, Germany.
- Jushan Bai & Serena Ng, 2002.
"Determining the Number of Factors in Approximate Factor Models,"
Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
- Jushan Bai & Serena Ng, 2000. "Determining the Number of Factors in Approximate Factor Models," Econometric Society World Congress 2000 Contributed Papers 1504, Econometric Society.
- Jushan Bai & Serena Ng, 2000. "Determining the Number of Factors in Approximate Factor Models," Boston College Working Papers in Economics 440, Boston College Department of Economics.
- Moretti, Laura & Onorante, Luca & Zakipour-Saber, Shayan, 2019.
"Phillips curves in the euro area,"
Research Technical Papers
8/RT/19, Central Bank of Ireland.
- Moretti, Laura & Onorante, Luca & Zakipour Saber, Shayan, 2019. "Phillips curves in the euro area," Working Paper Series 2295, European Central Bank.
- Carlos M. Carvalho & Nicholas G. Polson & James G. Scott, 2010. "The horseshoe estimator for sparse signals," Biometrika, Biometrika Trust, vol. 97(2), pages 465-480.
- Galvão, Ana Beatriz & Garratt, Anthony & Mitchell, James, 2021. "Does judgment improve macroeconomic density forecasts?," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1247-1260.
- Bańbura, Marta & Leiva-León, Danilo & Menz, Jan-Oliver, 2021.
"Do inflation expectations improve model-based inflation forecasts?,"
Discussion Papers
48/2021, Deutsche Bundesbank.
- Bańbura, Marta & Leiva-Leon, Danilo & Menz, Jan-Oliver, 2021. "Do inflation expectations improve model-based inflation forecasts?," Working Paper Series 2604, European Central Bank.
- Marta Bañbura & Danilo Leiva-León & Jan-Oliver Menz, 2021. "Do inflation expectations improve model-based inflation Forecasts?," Working Papers 2138, Banco de España.
- Christiane Baumeister & Dimitris Korobilis & Thomas K. Lee, 2022.
"Energy Markets and Global Economic Conditions,"
The Review of Economics and Statistics, MIT Press, vol. 104(4), pages 828-844, October.
- Christiane Baumeister & Dimitris Korobilis & Thomas K. Lee, 2020. "Energy Markets and Global Economic Conditions," Working Papers 2020_08, Business School - Economics, University of Glasgow.
- Christiane Baumeister & Dimitris Korobilis & Thomas K. Lee, 2020. "Energy Markets and Global Economic Conditions," NBER Working Papers 27001, National Bureau of Economic Research, Inc.
- Baumeister, Christiane & Korobilis, Dimitris & Lee, Thomas K., 2020. "Energy Markets and Global Economic Conditions," CEPR Discussion Papers 14580, C.E.P.R. Discussion Papers.
- Christiane Baumeister & Dimitris Korobilis & Thomas K. Lee, 2020. "Energy Markets and Global Economic Conditions," CESifo Working Paper Series 8282, CESifo.
- Florian Huber & Gary Koop & Luca Onorante, 2021.
"Inducing Sparsity and Shrinkage in Time-Varying Parameter Models,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(3), pages 669-683, July.
- Huber, Florian & Koop, Gary & Onorante, Luca, 2019. "Inducing Sparsity and Shrinkage in Time-Varying Parameter Models," Working Papers in Economics 2019-2, University of Salzburg.
- Florian Huber & Gary Koop & Luca Onorante, 2019. "Inducing Sparsity and Shrinkage in Time-Varying Parameter Models," Papers 1905.10787, arXiv.org, revised Dec 2019.
- Huber, Florian & Koop, Gary & Onorante, Luca, 2019. "Inducing sparsity and shrinkage in time-varying parameter models," Working Paper Series 2325, European Central Bank.
- Geweke, John & Amisano, Gianni, 2010.
"Comparing and evaluating Bayesian predictive distributions of asset returns,"
International Journal of Forecasting, Elsevier, vol. 26(2), pages 216-230, April.
- Amisano, Gianni & Geweke, John, 2008. "Comparing and evaluating Bayesian predictive distributions of assets returns," Working Paper Series 969, European Central Bank.
- Marek Jarociński & Michele Lenza, 2018.
"An Inflation‐Predicting Measure of the Output Gap in the Euro Area,"
Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(6), pages 1189-1224, September.
- Lenza, Michele & Jarociński, Marek, 2016. "An inflation-predicting measure of the output gap in the euro area," Working Paper Series 1966, European Central Bank.
- 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.
- James H. Stock & Mark W. Watson, 2007.
"Why Has U.S. Inflation Become Harder to Forecast?,"
Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 3-33, February.
- James H. Stock & Mark W. Watson, 2006. "Why Has U.S. Inflation Become Harder to Forecast?," NBER Working Papers 12324, National Bureau of Economic Research, Inc.
- Chan,Joshua & Koop,Gary & Poirier,Dale J. & Tobias,Justin L., 2019.
"Bayesian Econometric Methods,"
Cambridge Books,
Cambridge University Press, number 9781108437493, January.
- Chan,Joshua & Koop,Gary & Poirier,Dale J. & Tobias,Justin L., 2019. "Bayesian Econometric Methods," Cambridge Books, Cambridge University Press, number 9781108423380, November.
- Koop, Gary M & Poirier, Dale J & Tobias, Justin, 2007. "Bayesian Econometric Methods," Staff General Research Papers Archive 12722, Iowa State University, Department of Economics.
- 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.
- Sharon Kozicki & P. A. Tinsley, 2012.
"Effective Use of Survey Information in Estimating the Evolution of Expected Inflation,"
Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(1), pages 145-169, February.
- Sharon Kozicki & P. A. Tinsley, 2012. "Effective Use of Survey Information in Estimating the Evolution of Expected Inflation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(1), pages 145-169, February.
- Michael Weber & Francesco D'Acunto & Yuriy Gorodnichenko & Olivier Coibion, 2022.
"The Subjective Inflation Expectations of Households and Firms: Measurement, Determinants, and Implications,"
Journal of Economic Perspectives, American Economic Association, vol. 36(3), pages 157-184, Summer.
- Weber, Michael & D’Acunto, Francesco & Gorodnichenko, Yuriy & Coibion, Olivier, 2022. "The Subjective Inflation Expectations of Households and Firms: Measurement, Determinants, and Implications," IZA Discussion Papers 15391, Institute of Labor Economics (IZA).
- Weber, Michael & D'Acunto, Francesco & Gorodnichenko, Yuriy & Coibion, Olivier, 2022. "The Subjective Inflation Expectations of Households and Firms: Measurement, Determinants, and Implications," CEPR Discussion Papers 17406, C.E.P.R. Discussion Papers.
- Michael Weber & Francesco D’Acunto & Yuriy Gorodnichenko & Olivier Coibion, 2022. "The Subjective Inflation Expectations of Households and Firms: Measurement, Determinants, and Implications," NBER Working Papers 30046, National Bureau of Economic Research, Inc.
- Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-162, April.
- Ciccarelli, Matteo & García, Juan Angel, 2021. "Expectation spillovers and the return of inflation," Economics Letters, Elsevier, vol. 209(C).
- Niko Hauzenberger & Florian Huber & Gary Koop & Luca Onorante, 2022.
"Fast and Flexible Bayesian Inference in Time-varying Parameter Regression Models,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(4), pages 1904-1918, October.
- Niko Hauzenberger & Florian Huber & Gary Koop & Luca Onorante, 2019. "Fast and Flexible Bayesian Inference in Time-varying Parameter Regression Models," Papers 1910.10779, arXiv.org, revised Sep 2021.
- Rodolfo Arioli & Colm Bates & Heinz Dieden & Ioana Duca & Roberta Friz & Christian Gayer & Geoff Kenny & Aidan Meyler & Iskra Pavlova, 2016.
"EU Consumers’ Quantitative Inflation Perceptions and Expectations: An Evaluation,"
European Economy - Discussion Papers
038, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
- Arioli, Rodolfo & Bates, Colm & Dieden, Heinz Christian & Duca, Ioana & Friz, Roberta & Gayer, Christian & Kenny, Geoff & Meyler, Aidan & Pavlova, Iskra, 2017. "EU consumers’ quantitative inflation perceptions and expectations: an evaluation," Occasional Paper Series 186, European Central Bank.
- Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2015.
"Prior Selection for Vector Autoregressions,"
The Review of Economics and Statistics, MIT Press, vol. 97(2), pages 436-451, May.
- Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio E., 2012. "Prior selection for vector autoregressions," Working Paper Series 1494, European Central Bank.
- Domenico Giannone & Michèle Lenza & Giorgio E. Primiceri, 2012. "Prior Selection for Vector Autoregressions," Working Papers ECARES ECARES 2012-002, ULB -- Universite Libre de Bruxelles.
- Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio, 2012. "Prior Selection for Vector Autoregressions," CEPR Discussion Papers 8755, C.E.P.R. Discussion Papers.
- Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2012. "Prior Selection for Vector Autoregressions," NBER Working Papers 18467, National Bureau of Economic Research, Inc.
- James H. Stock & Mark W. Watson, 2007. "Erratum to "Why Has U.S. Inflation Become Harder to Forecast?"," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(7), pages 1849-1849, October.
- 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.
- de Vincent-Humphreys, Rupert & Dimitrova, Ivelina & Falck, Elisabeth & Henkel, Lukas & Meyler, Aidan, 2019. "Twenty years of the ECB Survey of Professional Forecasters," Economic Bulletin Articles, European Central Bank, vol. 1.
- Lucia Alessi & Eric Ghysels & Luca Onorante & Richard Peach & Simon Potter, 2014.
"Central Bank Macroeconomic Forecasting During the Global Financial Crisis: The European Central Bank and Federal Reserve Bank of New York Experiences,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(4), pages 483-500, October.
- Luci Alessi & Eric Ghysels & Luca Onorante & Richard Peach & Simon M. Potter, 2014. "Central bank macroeconomic forecasting during the global financial crisis: the European Central Bank and Federal Reserve Bank of New York experiences," Staff Reports 680, Federal Reserve Bank of New York.
- Onorante, Luca & Alessi, Lucia & Ghysels, Eric & Potter, Simon & Peach, Richard, 2014. "Central bank macroeconomic forecasting during the global financial crisis: the European Central Bank and Federal Reserve Bank of New York experiences," Working Paper Series 1688, European Central Bank.
- Claveria, Oscar & Pons, Ernest & Ramos, Raul, 2007. "Business and consumer expectations and macroeconomic forecasts," International Journal of Forecasting, Elsevier, vol. 23(1), pages 47-69.
- Faust, Jon & Wright, Jonathan H., 2013. "Forecasting Inflation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 2-56, Elsevier.
- James H. Stock & Mark W. Watson, 2007. "Erratum to “Why Has U.S. Inflation Become Harder to Forecast?”," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(7), pages 1849-1849, October.
- Randal J. Verbrugge & Saeed Zaman, 2021. "Whose Inflation Expectations Best Predict Inflation?," Economic Commentary, Federal Reserve Bank of Cleveland, vol. 2021(19), pages 1-7, October.
- James H. Stock & Mark W. Watson, 2007. "Why Has U.S. Inflation Become Harder to Forecast?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 3-33, February.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Philippe Goulet Coulombe & Maximilian Goebel & Karin Klieber, 2024. "Dual Interpretation of Machine Learning Forecasts," Papers 2412.13076, arXiv.org.
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.- Hauzenberger, Niko & Huber, Florian & Klieber, Karin, 2023.
"Real-time inflation forecasting using non-linear dimension reduction techniques,"
International Journal of Forecasting, Elsevier, vol. 39(2), pages 901-921.
- Niko Hauzenberger & Florian Huber & Karin Klieber, 2020. "Real-time Inflation Forecasting Using Non-linear Dimension Reduction Techniques," Papers 2012.08155, arXiv.org, revised Dec 2021.
- Niu, Linlin & Xu, Xiu & Chen, Ying, 2017.
"An adaptive approach to forecasting three key macroeconomic variables for transitional China,"
Economic Modelling, Elsevier, vol. 66(C), pages 201-213.
- Niu, Linlin & Xu, Xiu & Chen, Ying, 2015. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," BOFIT Discussion Papers 12/2015, Bank of Finland Institute for Emerging Economies (BOFIT).
- Niu, Linlin & Xu, Xiu & Chen, Ying, 2015. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," SFB 649 Discussion Papers 2015-023, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
- 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.
- Michael Pfarrhofer, 2024.
"Forecasts with Bayesian vector autoregressions under real time conditions,"
Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(3), pages 771-801, April.
- Michael Pfarrhofer, 2020. "Forecasts with Bayesian vector autoregressions under real time conditions," Papers 2004.04984, arXiv.org.
- Gao, Shen & Hou, Chenghan & Nguyen, Bao H., 2021. "Forecasting natural gas prices using highly flexible time-varying parameter models," Economic Modelling, Elsevier, vol. 105(C).
- Anthony Garratt & Ivan Petrella, 2022. "Commodity prices and inflation risk," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(2), pages 392-414, March.
- Joshua C.C. Chan & Rodney W. Strachan, 2023.
"Bayesian State Space Models In Macroeconometrics,"
Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 58-75, February.
- Joshua C.C. Chan & Rodney W. Strachan, 2020. "Bayesian state space models in macroeconometrics," CAMA Working Papers 2020-90, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Trucíos, Carlos & Mazzeu, João H.G. & Hotta, Luiz K. & Valls Pereira, Pedro L. & Hallin, Marc, 2021.
"Robustness and the general dynamic factor model with infinite-dimensional space: Identification, estimation, and forecasting,"
International Journal of Forecasting, Elsevier, vol. 37(4), pages 1520-1534.
- Trucíos Maza, Carlos César & Mazzeu, João H. G. & Hotta, Luiz Koodi & Pereira, Pedro L. Valls & Hallin, Marc, 2020. "Robustness and the general dynamic factor model with infinite-dimensional space: identification, estimation, and forecasting," Textos para discussão 521, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
- Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2020.
"Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors,"
The Review of Economics and Statistics, MIT Press, vol. 102(1), pages 17-33, March.
- Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2017. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," Working Papers (Old Series) 1715, Federal Reserve Bank of Cleveland.
- Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2017. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," Working Papers 2017-026, Federal Reserve Bank of St. Louis.
- Todd E Clark & Michael W McCracken & Elmar Mertens, 2017. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," BIS Working Papers 667, Bank for International Settlements.
- Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2017. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," Working Papers 17-15R, Federal Reserve Bank of Cleveland.
- Nataliia Ostapenko, 2022. "Do output gap estimates improve inflation forecasts in Slovakia?," Working and Discussion Papers WP 4/2022, Research Department, National Bank of Slovakia.
- Nima Nonejad, 2021. "An Overview Of Dynamic Model Averaging Techniques In Time‐Series Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 566-614, April.
- Florian Huber & Michael Pfarrhofer, 2021.
"Dynamic shrinkage in time‐varying parameter stochastic volatility in mean models,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(2), pages 262-270, March.
- Florian Huber & Michael Pfarrhofer, 2020. "Dynamic shrinkage in time-varying parameter stochastic volatility in mean models," Papers 2005.06851, arXiv.org.
- Niko Hauzenberger & Florian Huber & Luca Onorante, 2021.
"Combining shrinkage and sparsity in conjugate vector autoregressive models,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(3), pages 304-327, April.
- Niko Hauzenberger & Florian Huber & Luca Onorante, 2020. "Combining Shrinkage and Sparsity in Conjugate Vector Autoregressive Models," Papers 2002.08760, arXiv.org, revised Aug 2020.
- Kelly Trinh & Bo Zhang & Chenghan Hou, 2025. "Macroeconomic real‐time forecasts of univariate models with flexible error structures," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(1), pages 59-78, January.
- Nonejad, Nima, 2022. "Predicting equity premium out-of-sample by conditioning on newspaper-based uncertainty measures: A comparative study," International Review of Financial Analysis, Elsevier, vol. 83(C).
- Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
- Barkan, Oren & Benchimol, Jonathan & Caspi, Itamar & Cohen, Eliya & Hammer, Allon & Koenigstein, Noam, 2023.
"Forecasting CPI inflation components with Hierarchical Recurrent Neural Networks,"
International Journal of Forecasting, Elsevier, vol. 39(3), pages 1145-1162.
- Oren Barkan & Jonathan Benchimol & Itamar Caspi & Eliya Cohen & Allon Hammer & Noam Koenigstein, 2020. "Forecasting CPI Inflation Components with Hierarchical Recurrent Neural Networks," Papers 2011.07920, arXiv.org, revised Feb 2022.
- Oren Barkan & Jonathan Benchimol & Itamar Caspi & Eliya Cohen & Allon Hammer & Noam Koenigstein, 2023. "Forecasting CPI inflation components with Hierarchical Recurrent Neural Networks," Post-Print emse-04624940, HAL.
- Oren Barkan & Jonathan Benchimol & Itamar Caspi & Allon Hammer & Noam Koenigstein, 2021. "Forecasting CPI Inflation Components with Hierarchical Recurrent Neural Networks," Bank of Israel Working Papers 2021.06, Bank of Israel.
- Berg, Tim O. & Henzel, Steffen R., 2015.
"Point and density forecasts for the euro area using Bayesian VARs,"
International Journal of Forecasting, Elsevier, vol. 31(4), pages 1067-1095.
- Berg, Tim Oliver & Henzel, Steffen, 2013. "Point and Density Forecasts for the Euro Area Using Many Predictors: Are Large BVARs Really Superior?," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79783, Verein für Socialpolitik / German Economic Association.
- Tim Oliver Berg & Steffen Henzel, 2013. "Point and Density Forecasts for the Euro Area Using Many Predictors: Are Large BVARs Really Superior?," ifo Working Paper Series 155, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
- Tim Oliver Berg & Steffen Henzel, 2014. "Point and Density Forecasts for the Euro Area Using Bayesian VARs," CESifo Working Paper Series 4711, CESifo.
- Gael M. Martin & David T. Frazier & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2023. "Bayesian Forecasting in the 21st Century: A Modern Review," Monash Econometrics and Business Statistics Working Papers 1/23, Monash University, Department of Econometrics and Business Statistics.
- Thomas Hasenzagl & Filippo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2022.
"A Model of the Fed's View on Inflation,"
The Review of Economics and Statistics, MIT Press, vol. 104(4), pages 686-704, October.
- Hasenzagl, Thomas & Pellegrino, Filippo & Reichlin, Lucrezia & Ricco, Giovanni, 2017. "A Model of the Fed’s View on Inflation," Economic Research Papers 269087, University of Warwick - Department of Economics.
- Thomas Hasenzagl & Filippo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2020. "A Model of the Fed's View on Inflation," Papers 2006.14110, arXiv.org.
- Thomas Hasenzagl & Fillipo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2018. "A model of the FED's view on inflation," Working Papers hal-03458456, HAL.
- Hasenzagl, Thomas & Pellegrino, Filippo & Reichlin, Lucrezia & Ricco, Giovanni, 2017. "A Model of the Fed’s View on Inflation," The Warwick Economics Research Paper Series (TWERPS) 1145, University of Warwick, Department of Economics.
- Thomas Hasenzagl & Filippo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2018. "A model of FED'S view on inflation," Documents de Travail de l'OFCE 2018-03, Observatoire Francais des Conjonctures Economiques (OFCE).
- Reichlin, Lucrezia & Hasenzagl, Thomas & Pellegrino, Filippo & Ricco, Giovanni, 2018. "A Model of the Fed's View on Inflation," CEPR Discussion Papers 12564, C.E.P.R. Discussion Papers.
More about this item
NEP fields
This paper has been announced in the following NEP Reports:- NEP-CBA-2022-09-05 (Central Banking)
- NEP-EEC-2022-09-05 (European Economics)
- NEP-FOR-2022-09-05 (Forecasting)
- NEP-MON-2022-09-05 (Monetary Economics)
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:arx:papers:2207.12225. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.