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Identification of multi-valued treatment effects with unobserved heterogeneity

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  • Koki Fusejima

Abstract

In this paper, we establish sufficient conditions for identifying treatment effects on continuous outcomes in endogenous and multi-valued discrete treatment settings with unobserved heterogeneity. We employ the monotonicity assumption for multi-valued discrete treatments and instruments, and our identification condition has a clear economic interpretation. In addition, we identify the local treatment effects in multi-valued treatment settings and derive closed-form expressions of the identified treatment effects. We provide examples to illustrate the usefulness of our result.

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  • Koki Fusejima, 2020. "Identification of multi-valued treatment effects with unobserved heterogeneity," Papers 2010.04385, arXiv.org, revised Apr 2023.
    • Handle: RePEc:arx:papers:2010.04385
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    Cited by:

    1. Toshiki Tsuda, 2022. "Treatment Effects with Multidimensional Unobserved Heterogeneity: Identification of the Marginal Treatment Effect," Papers 2209.11444, arXiv.org, revised Jan 2024.

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