Causal Inference under Interference through Designed Markets

Abstract

In auction and matching markets, estimating the welfare effects of demand-side treatments is challenging because of spillovers through the mechanism. We develop a quasi-experimental approach that avoids parametric assumptions typically imposed by structural methods. For a class of strategy-proof "cutoff" mechanisms, we propose an estimator that runs a weighted and perturbed version of the mechanism on data from a single market. The estimator is semi-parametrically efficient, asymptotically normal, and robust to a wide class of demand-side specifications. We propose spillover-aware targeting rules with vanishing asymptotic regret. Empirically, spillovers diminish the effect of information on inequality in Chilean schools.