 Are professional forecasters Bayesian?Sebastiano Manzan Journal of Economic Dynamics and Control, 2021, vol. 123, issue C Abstract: I investigate how professional forecasters update their uncertainty forecasts of output and inflation in response to macroeconomic news. I obtain a measure of individual uncertainty from the density forecasts of the Survey of Professional Forecasters for the United States (US-SPF) and the Euro area (ECB-SPF) and use it to test the prediction of Bayesian learning that uncertainty should decline as the forecast date nears the target date. Empirically, I find that the prediction is occasionally violated, in particular when forecasters experience unexpected news in the most recent data release, and following quarters in which they produce narrow density forecasts. The evidence indicates also significant heterogeneity in the updating behavior of forecasters in response to changes in these variables. In addition, I propose a method to solve the problem of the truncation of the density forecasts that occurs when a significant amount of probability is assigned to the open intervals. JEL-codes: E17 E37 (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:dyncon:v:123:y:2021:i:c:s016518892030213x DOI: 10.1016/j.jedc.2020.104045 Access Statistics for this article Journal of Economic Dynamics and Control is currently edited by J. Bullard, C. Chiarella, H. Dawid, C. H. Hommes, P. Klein and C. Otrok More articles in Journal of Economic Dynamics and Control from Elsevier |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.