Artículo de revista
A Matching estimator based on a bilevel optimization problem
Fecha
2015Registro en:
The Review of Economics and Statistics, October 2015, 97(4): 803–812
0034-6535
DOI: 10.1162/REST_a_00504
Autor
Díaz Maureira, Juan
Rau, Tomás
Rivera Cayupi, Jorge
Institución
Resumen
This paper proposes a novel matching estimator where neighbors
used and weights are endogenously determined by optimizing a covariate
balancing criterion. The estimator is based on finding, for each unit that
needs to be matched, sets of observations such that a convex combination
of them has the same covariate values as the unit needing matching or with
minimized distance between them. We implement the proposed estimator
with data from the National Supported Work Demonstration, finding outstanding
performance in terms of covariate balance. Monte Carlo evidence
shows that our estimator performs well in designs previously used in the
literature.