A “politically robust” experimental design for public policy evaluation, with application to the Mexican Universal Health Insurance program
We develop an approach to conducting large-scale randomized public policy experiments intended to be more robust to the political interventions that have ruined some or all parts of many similar previous efforts. Our proposed design is insulated from selection bias in some circumstances even if we lose observations; our inferences can still be unbiased even if politics disrupts any two of the three steps in our analytical procedures; and other empirical checks are available to validate the overall design. We illustrate with a design and empirical validation of an evaluation of the Mexican Seguro Popular de Salud (Universal Health Insurance) program we are conducting. Seguro Popular, which is intended to grow to provide medical care, drugs, preventative services, and financial health protection to the 50 million Mexicans without health insurance, is one of the largest health reforms of any country in the last two decades. The evaluation is also large scale, constituting one of the largest policy experiments to date and what may be the largest randomized health policy experiment ever. © 2007 by the Association for Public Policy Analysis and Management
Volume (Year): 26 (2007)
Issue (Month): 3 ()
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- Elizabeth Ty Wilde & Robinson Hollister, 2007. "How close is close enough? Evaluating propensity score matching using data from a class size reduction experiment," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 26(3), pages 455-477.
- Harry J. Holzer & John M. Quigley & Steven Raphael, 2003.
"Public transit and the spatial distribution of minority employment: Evidence from a natural experiment,"
Journal of Policy Analysis and Management,
John Wiley & Sons, Ltd., vol. 22(3), pages 415-441.
- Holzer, Harry J. & Quigley, John M. & Raphael, Steven, 2004. "Public Transit and the Spatial Distribution of Minority Employment: Evidence from a Natural Experiment," Berkeley Program on Housing and Urban Policy, Working Paper Series qt0f3725dm, Berkeley Program on Housing and Urban Policy.
- Holzer, Harry J. & Quigley, John M. & Raphael, Steven, 2003. "Public Transit and the Spatial Distribution of Minority Employment: Evidence from a Natural Experiment," University of California Transportation Center, Working Papers qt1x09f824, University of California Transportation Center.
- David Reiley & John List, 2008.
Artefactual Field Experiments
00091, The Field Experiments Website.
- William G. Howell, 2004. "Dynamic selection effects in means-tested, urban school voucher programs," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 23(2), pages 225-250.
- Steven Glazerman Daniel P Mayer Paul T Decker, 2006.
"Alternative Routes to Teaching: The Impacts of Teach For America on Student Achievement and Other Outcomes,"
Mathematica Policy Research Reports
0eae07a7e88b43759856043ce, Mathematica Policy Research.
- Steven Glazerman & Daniel Mayer & Paul Decker, 2006. "Alternative routes to teaching: The impacts of Teach for America on student achievement and other outcomes," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 25(1), pages 75-96.
- James J. Heckman & Jeffrey A. Smith, 1995. "Assessing the Case for Social Experiments," Journal of Economic Perspectives, American Economic Association, vol. 9(2), pages 85-110, Spring.
- Barnard J. & Frangakis C.E. & Hill J.L. & Rubin D.B., 2003. "Principal Stratification Approach to Broken Randomized Experiments: A Case Study of School Choice Vouchers in New York City," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 299-323, January.
- Daniel Ho & Kosuke Imai & Gary King & Elizabeth A. Stuart, . "MatchIt: Nonparametric Preprocessing for Parametric Causal Inference," Journal of Statistical Software, American Statistical Association, vol. 42(i08).
- Michael J. Camasso & Radha Jagannathan & Carol Harvey & Mark Killingsworth, 2003. "The use of client surveys to gauge the threat of contamination in welfare reform experiments," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 22(2), pages 207-223.
- David H. Greenberg & Charles Michalopoulos & Philip K. Robin, 2006. "Do experimental and nonexperimental evaluations give different answers about the effectiveness of government-funded training programs?," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 25(3), pages 523-552.
- Thomas S. Dee & Benjamin J. Keys, 2004. "Does merit pay reward good teachers? Evidence from a randomized experiment," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 23(3), pages 471-488.
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