Skip to main content

Research Repository

Advanced Search

Extrapolation of causal effects – hopes, assumptions, and the extrapolator’s circle

Khosrowi, Donal

Extrapolation of causal effects – hopes, assumptions, and the extrapolator’s circle Thumbnail


Authors

Donal Khosrowi



Abstract

I consider recent strategies proposed by econometricians for extrapolating causal effects from experimental to target populations. I argue that these strategies fall prey to the extrapolator’s circle: they require so much knowledge about the target population that the causal effects to be extrapolated can be identified from information about the target alone. I then consider comparative process tracing (CPT) as a potential remedy. Although specifically designed to evade the extrapolator’s circle, I argue that CPT is unlikely to facilitate extrapolation in typical econometrics and evidence-based policy applications. To argue this, I offer a distinction between two kinds of extrapolation, attributive and predictive, the latter being prevalent in econometrics and evidence-based policy. I argue that CPT is not helpful for predictive extrapolation when using the kinds of evidence that econometricians and evidence-based policy researchers prefer. I suggest that econometricians may need to consider qualitative evidence to overcome this problem.

Citation

Khosrowi, D. (2019). Extrapolation of causal effects – hopes, assumptions, and the extrapolator’s circle. Journal of Economic Methodology, 26(1), 45-58. https://doi.org/10.1080/1350178x.2018.1561078

Journal Article Type Article
Publication Date 2019
Deposit Date Feb 8, 2019
Publicly Available Date Feb 14, 2019
Journal Journal of Economic Methodology
Print ISSN 1350-178X
Electronic ISSN 1469-9427
Publisher Taylor and Francis Group
Peer Reviewed Peer Reviewed
Volume 26
Issue 1
Pages 45-58
DOI https://doi.org/10.1080/1350178x.2018.1561078
Public URL https://durham-repository.worktribe.com/output/1699919

Files

Published Journal Article (1.4 Mb)
PDF

Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/

Copyright Statement
© 2019 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/),
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.






Downloadable Citations