Assessing External Validity in Practice
Sebastian Galiani and
Brian Quistorff
No 30398, NBER Working Papers from National Bureau of Economic Research, Inc
Abstract:
We review, from a practical standpoint, the evolving literature on assessing external validity (EV) of estimated treatment effects. We review existing EV measures, and focus on methods that permit multiple datasets (Hotz et al., 2005). We outline criteria for practical usage, evaluate the existing approaches, and identify a gap in potential methods. Our practical considerations motivate a novel method utilizing the Group Lasso (Yuan and Lin, 2006) to estimate a tractable regression-based model of the conditional average treatment effect (CATE). This approach can perform better when settings have differing covariate distributions and allows for easily extrapolating the average treatment effect to new settings. We apply these measures to a set of identical field experiments upgrading slum dwellings in three different countries (Galiani et al., 2017).
JEL-codes: C55 (search for similar items in EconPapers)
Date: 2022-08
New Economics Papers: this item is included in nep-ecm and nep-exp
Note: DEV
References: Add references at CitEc
Citations:
Published as Sebastian Galiani & Brian Quistorff, 2024. "Assessing external validity in practice," Research in Economics, .
Downloads: (external link)
http://www.nber.org/papers/w30398.pdf (application/pdf)
Related works:
Journal Article: Assessing external validity in practice (2024) 
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:nbr:nberwo:30398
Ordering information: This working paper can be ordered from
http://www.nber.org/papers/w30398
Access Statistics for this paper
More papers in NBER Working Papers from National Bureau of Economic Research, Inc National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.. Contact information at EDIRC.
Bibliographic data for series maintained by ().