Teaching Statistical Learning in Econometrics
Mohamad A. Khaled,
Alicia Rambaldi () and
Christiern Rose
Additional contact information
Mohamad A. Khaled: University of Queensland
A chapter in Teaching Econometrics, 2026, pp 337-364 from Springer
Abstract:
Abstract Statistical learning techniques are increasingly being used by practising economists. Some bring new tools while others have existed in different forms as part of the standard econometrics toolbox. The increasing use of those methods is gradually bringing into focus a dichotomy between an emphasis on prediction and algorithms for statistical learning on the one hand and a focus on causal inference and identification in applied econometrics on the other, based on the fact that many causal inference methods rely on a prediction stage (e.g., instrumental variables first stage). Students, both at the undergraduate and graduate levels, should complete their training with an understanding of statistical learning models and their interaction with econometrics and statistics.
Date: 2026
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
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:spr:adschp:978-3-031-97942-2_19
Ordering information: This item can be ordered from
http://www.springer.com/9783031979422
DOI: 10.1007/978-3-031-97942-2_19
Access Statistics for this chapter
More chapters in Advanced Studies in Theoretical and Applied Econometrics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().