Computing Synthetic Controls Using Bilevel Optimization

The synthetic control method (SCM) is a major innovation in the estimation of causal effects of policy interventions and programs in a comparative case study setting. In this paper, we demonstrate that the data-driven approach to SCM requires solving a bilevel optimization problem. We show how the SCM problem can be solved using iterative algorithms based on Tykhonov descent or KKT approximations