The Chen-Tindall system and the lasso operator: improving automatic model performance
Jiaqi Chen and
No 16-1, Occasional Papers from Federal Reserve Bank of Dallas
Using U.S. monthly macroeconomic data, the automatic model system presented in Chen and Tindall  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)
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)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
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 ().