Learning and Heterogeneity in GDP and Inflation Forecasts

Citations

Cited by:

1. Capistrán, Carlos & López-Moctezuma, Gabriel, 2014. "Forecast revisions of Mexican inflation and GDP growth," International Journal of Forecasting, Elsevier, vol. 30(2), pages 177-191.
   • López Moctezuma Gabriel & Capistrán Carlos, 2010. "Forecast Revisions of Mexican Inflation and GDP Growth," Working Papers 2010-11, Banco de México.
2. Sinclair, Tara M. & Gamber, Edward N. & Stekler, Herman & Reid, Elizabeth, 2012. "Jointly evaluating the Federal Reserve’s forecasts of GDP growth and inflation," International Journal of Forecasting, Elsevier, vol. 28(2), pages 309-314.
   • Tara M. Sinclair & Edward N. Gamber & H.O. Stekler & Elizabeth Reid, 2008. "Jointly Evaluating the Federal Reserve’s Forecasts of GDP Growth and Inflation," Working Papers 2008-002, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting, revised Mar 2011.
3. Clements, Michael P., 2014. "Probability distributions or point predictions? Survey forecasts of US output growth and inflation," International Journal of Forecasting, Elsevier, vol. 30(1), pages 99-117.
   • Clements, Michael P, 2012. "Probability Distributions or Point Predictions? Survey Forecasts of US Output Growth and Inflation," The Warwick Economics Research Paper Series (TWERPS) 976, University of Warwick, Department of Economics.
   • Clements, Michael P., 2012. "Probability Distributions or Point Predictions? Survey Forecasts of US Output Growth and Inflation," Economic Research Papers 270748, University of Warwick - Department of Economics.
4. Pedersen, Michael, 2015. "What affects the predictions of private forecasters? The role of central bank forecasts in Chile," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1043-1055.
5. Chen, Qiwei & Costantini, Mauro & Deschamps, Bruno, 2016. "How accurate are professional forecasts in Asia? Evidence from ten countries," International Journal of Forecasting, Elsevier, vol. 32(1), pages 154-167.
6. Clements, Michael P., 2012. "Do professional forecasters pay attention to data releases?," International Journal of Forecasting, Elsevier, vol. 28(2), pages 297-308.
   • Clements, Michael P., 2011. "Do Professional Forecasters Pay Attention to Data Releases?," Economic Research Papers 270768, University of Warwick - Department of Economics.
   • Clements, Michael P, 2011. "Do Professional Forecasters Pay Attention to Data Releases?," The Warwick Economics Research Paper Series (TWERPS) 956, University of Warwick, Department of Economics.
7. Bruno Deschamps, 2015. "Are aggregate corporate earnings forecasts unbiased and efficient?," Review of Quantitative Finance and Accounting, Springer, vol. 45(4), pages 803-818, November.
8. Constantin ANGHELACHE & Mădălina-Gabriela ANGHEL & Ștefan Virgil IACOB & Tudor SAMSON, 2020. "Analysis of the quarterly evolution of the Gross Domestic Product," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(3(624), A), pages 243-260, Autumn.
9. Jonas Dovern & Matthias Hartmann, 2017. "Forecast performance, disagreement, and heterogeneous signal-to-noise ratios," Empirical Economics, Springer, vol. 53(1), pages 63-77, August.
   • Hartmann, Matthias & Dovern, Jonas, 2016. "Forecast Performance, Disagreement, and Heterogeneous Signal-to-Noise Ratios," VfS Annual Conference 2016 (Augsburg): Demographic Change 145925, Verein für Socialpolitik / German Economic Association.
   • Dovern, Jonas & Hartmann, Matthias, 2016. "Forecast Performance, Disagreement, and Heterogeneous Signal-to-Noise Ratios," Working Papers 0611, University of Heidelberg, Department of Economics.
10. An, Zidong & Zheng, Xinye, 2023. "Diligent forecasters can make accurate predictions despite disagreeing with the consensus," Economic Modelling, Elsevier, vol. 125(C).
11. Sensoy, Ahmet & Serdengeçti, Süleyman, 2020. "Impact of portfolio flows and heterogeneous expectations on FX jumps: Evidence from an emerging market," International Review of Financial Analysis, Elsevier, vol. 68(C).
12. Rybacki, Jakub, 2020. "Polish GDP Forecast Errors: A Tale of Ineffectiveness," MPRA Paper 98952, University Library of Munich, Germany.
13. Konstantin A. Kholodilin & Boriss Siliverstovs, 2009. "Do forecasters inform or reassure?," KOF Working papers 09-215, KOF Swiss Economic Institute, ETH Zurich.
14. Ruttachai Seelajaroen & Pornanong Budsaratragoon & Boonlert Jitmaneeroj, 2020. "Do monetary policy transparency and central bank communication reduce interest rate disagreement?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 368-393, April.
15. Sheng, Xuguang (Simon), 2015. "Evaluating the economic forecasts of FOMC members," International Journal of Forecasting, Elsevier, vol. 31(1), pages 165-175.
16. Patton, Andrew J. & Timmermann, Allan, 2010. "Why do forecasters disagree? Lessons from the term structure of cross-sectional dispersion," Journal of Monetary Economics, Elsevier, vol. 57(7), pages 803-820, October.
17. Gabriel Caldas Montes & Caio Ferrari Ferreira, 2019. "Does monetary policy credibility mitigate the effects of uncertainty about exchange rate on uncertainties about both inflation and interest rate?," International Economics and Economic Policy, Springer, vol. 16(4), pages 649-678, October.
18. Jitmaneeroj, Boonlert & Lamla, Michael J. & Wood, Andrew, 2019. "The implications of central bank transparency for uncertainty and disagreement," Journal of International Money and Finance, Elsevier, vol. 90(C), pages 222-240.
    • Jitmaneeroj, Boonlert & Lamla, Michael J & Wood, Andrew, 2018. "The Implications of Central Bank Transparency for Uncertainty and Disagreement," Essex Finance Centre Working Papers 23347, University of Essex, Essex Business School.
    • Boonlert Jitmaneeroj & Michael Lamla, 2018. "The Implications of Central Bank Transparency for Uncertainty and Disagreement," KOF Working papers 18-445, KOF Swiss Economic Institute, ETH Zurich.
19. Lena Draeger & Michael J. Lamla, 2015. "Disagreement à la Taylor: Evidence from Survey Microdata," KOF Working papers 15-380, KOF Swiss Economic Institute, ETH Zurich.
    • Lena Dräger & Michael J. Lamla, 2015. "Disagreement à la Taylor: Evidence from Survey Microdata," Macroeconomics and Finance Series 201503, University of Hamburg, Department of Socioeconomics.
20. Eicher, Theo S. & Kuenzel, David J. & Papageorgiou, Chris & Christofides, Charis, 2019. "Forecasts in times of crises," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1143-1159.
    • Theo S. Eicher & David J. Kuenzel & Mr. Chris Papageorgiou & Mr. Charalambos Christofides, 2018. "Forecasts in Times of Crises," IMF Working Papers 2018/048, International Monetary Fund.
21. Sheen, Jeffrey & Wang, Ben Zhe, 2021. "Measuring macroeconomic disagreement – A mixed frequency approach," Journal of Economic Behavior & Organization, Elsevier, vol. 189(C), pages 547-566.
22. Sheng, Xuguang (Simon) & Thevenot, Maya, 2015. "Quantifying differential interpretation of public information using financial analysts’ earnings forecasts," International Journal of Forecasting, Elsevier, vol. 31(2), pages 515-530.
23. Jakub Rybacki, 2021. "Polish GDP forecast errors: a tale of inefficiency," Bank i Kredyt, Narodowy Bank Polski, vol. 52(2), pages 123-142.
24. Jing Tian & Firmin Doko Tchatoka & Thomas Goodwin, 2022. "Are internally consistent forecasts rational?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(7), pages 1338-1355, November.
25. Dimitrios Papastamos & George Matysiak & Simon Stevenson, 2014. "A Comparative Analysis of the Accuracy and Uncertainty in Real Estate and Macroeconomic Forecasts," Real Estate & Planning Working Papers rep-wp2014-06, Henley Business School, University of Reading.
26. Vereda, Luciano & Savignon, João & Gouveia da Silva, Tarciso, 2021. "A new method to assess the degree of information rigidity using fixed-event forecasts," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1576-1589.