A Graphical Approximation to Generalization: Definitions and Diagrams
García Fernando Martel () and
Wantchekon Leonard
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García Fernando Martel: 2800 Woodley Rd. N.W., Apt 324, Washington D.C. 20008, USA
Wantchekon Leonard: Princeton University and African School of Economics, ASE – USA, Princeton University, 230 Corwin Hall, Princeton, NJ 08544-1012, USA Department of Politics, Princeton, University 130 Corwin Hall, Princeton, NJ 08544-1012, USA
Journal of Globalization and Development, 2015, vol. 6, issue 1, 71-86
Abstract:
The fundamental problem of external validity is not to generalize from one experiment, so much as to experimentally test generalizable theories. That is, theories that explain the systematic variation of causal effects across contexts. Here we show how the graphical language of causal diagrams can be used in this endeavour. Specifically we show how generalization is a causal problem, how a causal approach is more robust than a purely predictive one, and how causal diagrams can be adapted to convey partial parametric information about interactions.
Keywords: causal diagrams; econometric methodology; external validity; generalized causal inference; nonparametric methods; policy experiments (search for similar items in EconPapers)
JEL-codes: B0 C1 C14 C18 C99 (search for similar items in EconPapers)
Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:bpj:globdv:v:6:y:2015:i:1:p:71-86:n:5
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DOI: 10.1515/jgd-2014-0013
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