Evan Munro - UC Berkeley

Causal Inference under Interference through Designed Markets

Abstract

In many markets a centralized mechanism allocates goods. When an individual-level intervention affects submissions to the mechanism, program evaluation is challenging due to spillover effects that occur through the mechanism. We show that if the mechanism is truthful and has a ``cutoff" structure, then it is possible to estimate the Global Treatment Effect (GTE) under a selection-on-observables assumption. Our proposed estimator is doubly-robust and semi-parametrically efficient. We also characterize heterogeneous treatment effects and propose estimators for the optimal targeting rule in equilibrium. Adjusting for equilibrium effects notably diminishes the estimated effect of information on inequality in the Chilean school system.

Additional information:

  • Speaker: Evan Munro
  • Time: Thursday, 07.11.2024, 16:00 - 17:00
  • Location: Faculty Meetingroom, U 1.040
  • Further links:
  • Organizer: Statistics Group
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