Treatment effects in market equilibrium

Date
Tue November 2nd 2021, 4:30pm
Location
Hewlett 102
Speaker
Stefan Wager, Stanford Statistics

In evaluating social programs, it is important to measure treatment effects within a market economy, where interference arises due to individuals buying and selling various goods at the prevailing market price. We introduce a stochastic model of potential outcomes in market equilibrium, where the market price is an exposure mapping. We prove that average direct and indirect treatment effects converge to interpretable mean-field treatment effects, and provide estimators for these effects through a unit-level randomized experiment augmented with randomization in prices. We also provide a central limit theorem for the estimators that depends on the sensitivity of outcomes to prices. For a variant where treatments are continuous, we show that the sum of direct and indirect effects converges to the total effect of a marginal policy change. We illustrate the coverage and consistency properties of the estimators in simulations of different interventions in a two-sided market.