Testing for Forecast Consensus
AbstractA panel of forecasts may be defined to be in consensus when individual forecasters place identical weights on a common latent variable. We suggest this definition and formulate a dynamic latent-variable model to test for consensus. This method also tests whether it is valid to use the mean forecast as the consensus forecast. In applications to surveys of U.S. macroeconomic forecasters, there is greater consensus in forecasts for output growth than for inflation or unemployment, but idiosyncratic forecast autocorrelation from year to year is present for most forecasters.
Download InfoTo our knowledge, this item is not available for download. To find whether it is available, there are three options:
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
Bibliographic InfoArticle provided by American Statistical Association in its journal Journal of Business and Economic Statistics.
Volume (Year): 19 (2001)
Issue (Month): 1 (January)
Contact details of provider:
Web page: http://www.amstat.org/publications/jbes/index.cfm?fuseaction=main
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- James Mitchell & George Kapetanios & Yongcheol Shin, 2012.
"A Nonlinear Panel Data Model of Cross-Sectional Dependence,"
Discussion Papers in Economics
12/01, Department of Economics, University of Leicester.
- George Kapetanios & James Mitchell & Shin, Y., 2010. "A Nonlinear Panel Data Model of Cross-sectional Dependence," NIESR Discussion Papers 370, National Institute of Economic and Social Research.
- ChiUng Song & Bryan L. Boulier & Herman O. Stekler, 2008.
"Measuring Consensus in Binary Forecasts: NFL Game Predictions,"
2008-006, The George Washington University, Department of Economics, Research Program on Forecasting.
- Song, ChiUng & Boulier, Bryan L. & Stekler, Herman O., 2009. "Measuring consensus in binary forecasts: NFL game predictions," International Journal of Forecasting, Elsevier, vol. 25(1), pages 182-191.
- Driver, Ciaran & Trapani, Lorenzo & Urga, Giovanni, 2013. "On the use of cross-sectional measures of forecast uncertainty," International Journal of Forecasting, Elsevier, vol. 29(3), pages 367-377.
- Paxton, Julia & Thraen, Cameron, 2003. "An application of Mean-Covariance Structure Models for the analysis of group lending behavior," Journal of Policy Modeling, Elsevier, vol. 25(9), pages 863-868, December.
- Lahiri, Kajal & Sheng, Xuguang, 2009.
"Learning and heterogeneity in GDP and inflation forecasts,"
21448, University Library of Munich, Germany.
- Lahiri, Kajal & Sheng, Xuguang, 2010. "Learning and heterogeneity in GDP and inflation forecasts," International Journal of Forecasting, Elsevier, vol. 26(2), pages 265-292, April.
- Kajal Lahiri & Xuguang Sheng, 2009. "Learning and Heterogeneity in GDP and Inflation Forecasts," Discussion Papers 09-05, University at Albany, SUNY, Department of Economics.
- Lahiri, Kajal & Sheng, Xuguang, 2008. "Evolution of forecast disagreement in a Bayesian learning model," Journal of Econometrics, Elsevier, vol. 144(2), pages 325-340, June.
- George Kapetanios & James Mitchell & Yongcheol Shin, 2010. "A Nonlinear Panel Model of Cross-sectional Dependence," Working Papers 673, Queen Mary, University of London, School of Economics and Finance.
- Gregory, Allan W. & Yetman, James, 2004. "The evolution of consensus in macroeconomic forecasting," International Journal of Forecasting, Elsevier, vol. 20(3), pages 461-473.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum).
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 references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.