EconPapers    
Economics at your fingertips  
 

Does noncausality help in forecasting economic time series?

Henri Nyberg, Markku Lanne and Erkka Saarinen ()
Additional contact information
Erkka Saarinen: University of Helsinki

Economics Bulletin, 2012, vol. 32, issue 4, 2849-2859

Abstract: In this paper, we compare the forecasting performance of univariate noncausal and conventional causal autoregressive models for a comprehensive data set consisting of 170 monthly U.S. macroeconomic and financial time series. The noncausal models consistently outperform the causal models. For a collection of quarterly time series, the improvement in forecast accuracy due to allowing for noncausality is found even greater.

Keywords: Noncausal autoregression; forecast comparison; macroeconomic variables; financial variables (search for similar items in EconPapers)
JEL-codes: C2 C5 (search for similar items in EconPapers)
Date: 2012-10-11
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (19) Track citations by RSS feed

Downloads: (external link)
http://www.accessecon.com/Pubs/EB/2012/Volume32/EB-12-V32-I4-P274.pdf (application/pdf)

Related works:
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:ebl:ecbull:eb-12-00360

Access Statistics for this article

More articles in Economics Bulletin from AccessEcon
Bibliographic data for series maintained by John P. Conley ().

 
Page updated 2022-10-28
Handle: RePEc:ebl:ecbull:eb-12-00360