Policy-relevant treatment effect estimation in a marketplace setting requires assessing both the direct treatment benefit and spillovers induced by changes to the market equilibrium. We show how to identify and estimate policy-relevant treatment effects using a unit-randomized trial run within a single large market. A Bernoulli-randomized trial allows consistent estimation of direct effects and of treatment-heterogeneity measures that enable welfare-improving targeting. Estimating spillovers—and providing confidence intervals for the direct effect—requires estimates of price elasticities, which we provide using an augmented experimental design. We illustrate our results using a simulation calibrated to a conditional cash-transfer experiment in the Philippines.

We study a prominent energy regulation affecting large Chinese manufacturers that are part of broader conglomerates. Using detailed firm-level data and difference-in-differences research designs, we show that regulated firms cut output and shifted some production to unregulated firms within their conglomerate instead of improving their energy efficiency. To account for conglomerate and market spillovers, we interpret these results through the lens of an industry equilibrium model featuring conglomerate production. The policy raises welfare if the per ton benefits of carbon reduction exceed $161. Alternative policies that exploit public information on business networks can increase aggregate energy savings by 10 percent.