EconPapers    
Economics at your fingertips  
 

The Chen-Tindall system and the lasso operator: improving automatic model performance

Jiaqi Chen and Michael Tindall

No 16-1, Occasional Papers from Federal Reserve Bank of Dallas

Abstract: Using U.S. monthly macroeconomic data, the automatic model system presented in Chen and Tindall [2016] outperforms the lasso automatic system, but the lasso is improved where Bayesian model averaging is employed to combine its forecasts with those from autoregressive schemes. The best performance is obtained using Bayesian model averaging to combine the Chen–Tindall system, the lasso, and autoregressive schemes. Performance is virtually the same using this combined approach where the elastic-net operator is substituted for the lasso. Similar overall outcomes are found for France and Germany treated as a single economic system and for Canada.

Keywords: Automatic model building; Bayesian model averaging; the lasso; the elastic net. (search for similar items in EconPapers)
Date: 2016-05-31
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
http://www.dallasfed.org/assets/documents/banking/occasional/1601.pdf Full text (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:fip:feddop:2016_001

Ordering information: This working paper can be ordered from

Access Statistics for this paper

More papers in Occasional Papers from Federal Reserve Bank of Dallas Contact information at EDIRC.
Bibliographic data for series maintained by Amy Chapman ().

 
Page updated 2019-04-22
Handle: RePEc:fip:feddop:2016_001