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A Market Interpretation of Treatment Effects

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Abstract

Markets, likened to an invisible hand, often appear to contradict econometric assumptions that rule out spillovers of one person’s treatment on another’s outcomes. This paper provides a simple statistical framework highlighting that controls are indirectly affected by the treatment through the market. Further, the effect of the treatment on the treated reveals only part of the consequence for the treated of treating the entire market. When combined with economic theory, our framework leads to a new application of Marshall’s Laws of Derived Demand that relates econometric estimates of treatment effects in the marketplace to the substitution and scale effects of demand theory. We show how treatment-effect estimators can diverge – both in magnitude and direction – from the causal effects of treatment on the treated or counterfactual policies treating all market participants. The framework shows how the consequences of targeted treatments reveal the effects of marketwide treatments, and the role of market frictions in that inference. Examples from labor, public finance, economic geography, development, and the macro literature on the “missing intercept” are provided.

Suggested Citation

  • Robert Minton & Casey B. Mulligan, 2024. "A Market Interpretation of Treatment Effects," Finance and Economics Discussion Series 2024-096, Board of Governors of the Federal Reserve System (U.S.).
  • Handle: RePEc:fip:fedgfe:2024-96
    DOI: 10.17016/FEDS.2024.096
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    File URL: https://www.federalreserve.gov/econres/feds/files/2024096pap.pdf
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    More about this item

    Keywords

    Treatment effects; Spillovers; Difference-in-differences;
    All these keywords.

    JEL classification:

    • D41 - Microeconomics - - Market Structure, Pricing, and Design - - - Perfect Competition
    • L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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