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Treatment Effects in Market Equilibrium

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  • Evan Munro
  • Stefan Wager
  • Kuang Xu

Abstract

When randomized trials are run in a marketplace equilibriated by prices, interference arises. To analyze this, we build a stochastic model of treatment effects in equilibrium. We characterize the average direct (ADE) and indirect treatment effect (AIE) asymptotically. A standard RCT can consistently estimate the ADE, but confidence intervals and AIE estimation require price elasticity estimates, which we provide using a novel experimental design. We define heterogeneous treatment effects and derive an optimal targeting rule that meets an equilibrium stability condition. We illustrate our results using a freelance labor market simulation and data from a cash transfer experiment.

Suggested Citation

  • Evan Munro & Stefan Wager & Kuang Xu, 2021. "Treatment Effects in Market Equilibrium," Papers 2109.11647, arXiv.org, revised Jan 2023.
    • Handle: RePEc:arx:papers:2109.11647
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    References listed on IDEAS

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    Cited by:

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    2. Roshni Sahoo & Stefan Wager, 2022. "Policy Learning with Competing Agents," Papers 2204.01884, arXiv.org, revised Apr 2024.
    3. Toru Kitagawa & Guanyi Wang, 2023. "Individualized Treatment Allocation in Sequential Network Games," Papers 2302.05747, arXiv.org, revised Jul 2023.
    4. Jiafeng Chen, 2021. "Nonparametric Treatment Effect Identification in School Choice," Papers 2112.03872, arXiv.org, revised Oct 2023.

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