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Reinterpreting demand estimation

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  • Jiafeng Chen

Abstract

This paper connects the literature on demand estimation to the literature on causal inference by interpreting nonparametric structural assumptions as restrictions on counterfactual outcomes. It offers nontrivial and equivalent restatements of key demand estimation assumptions in the Neyman-Rubin potential outcomes model, for both settings with market-level data (Berry and Haile, 2014) and settings with demographic-specific market shares (Berry and Haile, 2024). This exercise helps bridge the literatures on structural estimation and on causal inference by separating notational and linguistic differences from substantive ones.

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  • Jiafeng Chen, 2025. "Reinterpreting demand estimation," Papers 2503.23524, arXiv.org.
    • Handle: RePEc:arx:papers:2503.23524
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    References listed on IDEAS

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    1. Atı̇la Abdulkadı̇roğlu & Joshua D. Angrist & Yusuke Narita & Parag Pathak, 2022. "Breaking Ties: Regression Discontinuity Design Meets Market Design," Econometrica, Econometric Society, vol. 90(1), pages 117-151, January.
    2. James J. Heckman, 1976. "Introduction to "Annals of Economic and Social Measurement, Volume 5, number 4"," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 5, number 4, National Bureau of Economic Research, Inc.
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