Mexican Health Care Evaluation
An evaluation of the Mexican Seguro Popular program (designed to extend health insurance and regular and preventive medical care, pharmaceuticals, and health facilities to 50 million uninsured Mexicans), one of the world's largest health policy reforms of the last two decades. Our evaluation features a new design for field experiments that is more robust to the political interventions and implementation errors that have ruined many similar previous efforts; new statistical methods that produce more reliable and efficient results using fewer resources, assumptions, and data, as well as standard errors that are as much as 600% smaller; and an implementation of these methods in the largest randomized health policy experiment to date. (See the Harvard Gazette story on this project.)
Section 1
1. The evaluation design: . 2007. “A "Politically Robust" Experimental Design for Public Policy Evaluation, with Application to the Mexican Universal Health Insurance Program.” Journal of Policy Analysis and Management, 26, Pp. 479-506.Abstract
2. The statistical analysis methods: . 2009. “The Essential Role of Pair Matching in Cluster-Randomized Experiments, with Application to the Mexican Universal Health Insurance Evaluation.” Statistical Science, 24, Pp. 29–53.Abstract
2a. Comments from four scholars on previous article and rejoinder by us: . 2009. “Matched Pairs and the Future of Cluster-Randomized Experiments: A Rejoinder.” Statistical Science, 24, Pp. 64–72.Abstract
3. The results of the evaluation: . 2009. “Public Policy for the Poor? A Randomised Assessment of the Mexican Universal Health Insurance Programme.” The Lancet, 373, Pp. 1447-1454.Abstract
4. The replication data sets: . 2009. “Replication Data for: Public Policy for the Poor? A Randomised Assessment of the Mexican Universal Health Insurance Programme”. Publisher's Version
Related Research
Do Nonpartisan Programmatic Policies Have Partisan Electoral Effects? Evidence from Two Large Scale Experiments.” Journal of Politics, 81, 2, Pp. 714-730. Publisher's VersionAbstract
. 1/31/2020. “