EconPapers    
Economics at your fingertips  
 

Combining Disaggregate Forecasts or Combining Disaggregate Information to Forecast an Aggregate

David Hendry () and Kirstin Hubrich ()

Journal of Business & Economic Statistics, 2011, vol. 29, issue 2, 216-227

Abstract: To forecast an aggregate, we propose adding disaggregate variables, instead of combining forecasts of those disaggregates or forecasting by a univariate aggregate model. New analytical results show the effects of changing coefficients, misspecification, estimation uncertainty, and mismeasurement error. Forecast-origin shifts in parameters affect absolute, but not relative, forecast accuracies; misspecification and estimation uncertainty induce forecast-error differences, which variable-selection procedures or dimension reductions can mitigate. In Monte Carlo simulations, different stochastic structures and interdependencies between disaggregates imply that including disaggregate information in the aggregate model improves forecast accuracy. Our theoretical predictions and simulations are corroborated when forecasting aggregate United States inflation pre and post 1984 using disaggregate sectoral data.

Date: 2011
References: Add references at CitEc
Citations: View citations in EconPapers (66) Track citations by RSS feed

Downloads: (external link)
http://hdl.handle.net/10.1198/jbes.2009.07112 (text/html)
Access to full text is restricted to subscribers.

Related works:
Journal Article: Combining Disaggregate Forecasts or Combining Disaggregate Information to Forecast an Aggregate (2011) Downloads
Working Paper: Combining disaggregate forecasts or combining disaggregate information to forecast an aggregate (2010) Downloads
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:jnlbes:v:29:y:2011:i:2:p:216-227

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/UBES20

DOI: 10.1198/jbes.2009.07112

Access Statistics for this article

Journal of Business & Economic Statistics is currently edited by Eric Sampson, Rong Chen and Shakeeb Khan

More articles in Journal of Business & Economic Statistics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2021-05-08
Handle: RePEc:taf:jnlbes:v:29:y:2011:i:2:p:216-227