Matching methods improve the validity of causal inference by reducing model dependence and offering intuitive diagnostics. While they have become a part of the standard tool kit across disciplines, ma
We propose a simplified approach to matching for causal inference that simultaneously optimizes both balance (similarity between the treated and control groups) and matched sample size. Existing appro
Diaz, Juan, Rau, Tomas, and Rivera, Jorge (2015) " A Matching Estimator Based on a Bi-level Optimization Problem." Review of Economics and Statistics 97:4, 813-826.
