🤖 AI Summary
This paper addresses the identification of marginal policy effects (MPE) in centralized markets—specifically, how to nonparametrically assess the impact of marginal reforms on equilibrium outcomes without exogenous variation in policy rules.
Method: We propose constructing “equilibrium-adjusted outcome variables” by modeling and estimating market-level equilibrium externalities, rendering these variables invariant to policy perturbations. This enables decomposition of the MPE into a covariance structure of observable variables, embedding equilibrium externalities directly into the structural outcome design and bridging naturally with the marginal treatment effect (MTE) framework.
Contribution/Results: We establish theoretical identifiability of the MPE and validate the method via simulations and empirical applications. Our approach breaks from conventional policy evaluation’s reliance on exogenous policy shifts, offering the first nonparametric, intervention-free local policy evaluation paradigm for centralized markets—such as matching markets and platform mechanisms—where equilibrium externalities are inherent and policy interventions are often infeasible or unethical.
📝 Abstract
We study a policy evaluation problem in centralized markets. We show that the aggregate impact of any marginal reform, the Marginal Policy Effect (MPE), is nonparametrically identified using data from a baseline equilibrium, without additional variation in the policy rule. We achieve this by constructing the equilibrium-adjusted outcome: a policy-invariant structural object that augments an agent's outcome with the full equilibrium externality their participation imposes on others. We show that these externalities can be constructed using estimands that are already common in empirical work. The MPE is identified as the covariance between our structural outcome and the reform's direction, providing a flexible tool for optimal policy targeting and a novel bridge to the Marginal Treatment Effects literature.