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Credible Causal Inference for Empirical Legal Studies

Posted: 10 Jan 2012  

Daniel E. Ho

Stanford Law School

Donald B. Rubin

Harvard University - Department of Statistics

Date Written: December 2011

Abstract

We review advances toward credible causal inference that have wide application for empirical legal studies. Our chief point is simple: Research design trumps methods of analysis. We explain matching and regression discontinuity approaches in intuitive (nontechnical) terms. To illustrate, we apply these to existing data on the impact of prison facilities on inmate misconduct, which we compare to experimental evidence. What unifies modern approaches to causal inference is the prioritization of research design to create -- without reference to any outcome data -- subsets of comparable units. Within those subsets, outcome differences may then be plausibly attributed to exposure to the treatment rather than control condition. Traditional methods of analysis play a small role in this venture. Credible causal inference in law turns on substantive legal, not mathematical, knowledge.

Suggested Citation

Ho, Daniel E. and Rubin, Donald B., Credible Causal Inference for Empirical Legal Studies (December 2011). Annual Review of Law and Social Science, Vol. 7, pp. 17-40, 2011. Available at SSRN: https://ssrn.com/abstract=1982342 or http://dx.doi.org/10.1146/annurev-lawsocsci-102510-105423

Daniel E. Ho (Contact Author)

Stanford Law School ( email )

559 Nathan Abbott Way
Stanford, CA 94305-8610
United States
650-723-9560 (Phone)

HOME PAGE: http://dho.stanford.edu

Donald B. Rubin

Harvard University - Department of Statistics ( email )

Science Center 7th floor
One Oxford Street
Cambridge, MA 02138-2901
United States

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