Treatment Effects with Targeting Instruments

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Hauptverfasser: Lee, Sokbae, Salanié, Bernard
Format: Preprint
Veröffentlicht: 2020
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author Lee, Sokbae
Salanié, Bernard
author_facet Lee, Sokbae
Salanié, Bernard
contents Multivalued treatments are commonplace in applications. We explore the use of discrete-valued instruments to control for selection bias in this setting. Our discussion revolves around the concept of targeting: which instruments target which treatments. It allows us to establish conditions under which counterfactual averages and treatment effects are point- or partially-identified for composite complier groups. We explore the additional identifying power of a positive selection assumption. We illustrate its usefulness by revisiting the findings of Kline and Walters (2016) on the Head Start Impact Study. We derive informative bounds that suggest less beneficial effects of Head Start expansions than their parametric estimates.
format Preprint
id arxiv_https___arxiv_org_abs_2007_10432
institution arXiv
publishDate 2020
record_format arxiv
spellingShingle Treatment Effects with Targeting Instruments
Lee, Sokbae
Salanié, Bernard
Econometrics
Methodology
Multivalued treatments are commonplace in applications. We explore the use of discrete-valued instruments to control for selection bias in this setting. Our discussion revolves around the concept of targeting: which instruments target which treatments. It allows us to establish conditions under which counterfactual averages and treatment effects are point- or partially-identified for composite complier groups. We explore the additional identifying power of a positive selection assumption. We illustrate its usefulness by revisiting the findings of Kline and Walters (2016) on the Head Start Impact Study. We derive informative bounds that suggest less beneficial effects of Head Start expansions than their parametric estimates.
title Treatment Effects with Targeting Instruments
topic Econometrics
Methodology
url https://arxiv.org/abs/2007.10432