Synthetic Controls with spillover effects: A comparative study

TL;DR

This paper introduces the Iterative Synthetic Control Method, a new approach that improves predictive accuracy by accounting for spillover effects, and compares it with existing SCM variants through extensive simulations.

Contribution

The study proposes the Iterative SCM, a novel modification that enhances predictive performance by incorporating spillover effects, and demonstrates its effectiveness against other SCM methods.

Findings

Inclusive SCM performed best across all settings.

Iterative SCM achieved near-best performance with simpler implementation.

Simulation results validated the effectiveness of the proposed methods.

Abstract

Iterative Synthetic Control Method is introduced in this study, a modification of the Synthetic Control Method (SCM) designed to improve its predictive performance by utilizing control units affected by the treatment in question. This method is then compared to other SCM modifications: SCM without any modifications, SCM after removing all spillover-affected units, Inclusive SCM, and the SP SCM model. For the comparison, Monte Carlo simulations are utilized, generating artificial datasets with known counterfactuals and comparing the predictive performance of the methods. Generally, the Inclusive SCM performed best in all settings and is relatively simple to implement. The Iterative SCM, introduced in this paper, was in close seconds, with a small difference in performance and a simpler implementation.