A note on the robustness of quantile treatment effect estimands
Karim Chalak ()
Economics Letters, 2019, vol. 185, issue C
Abstract:
This note examines the robustness of two quantile treatment effect estimands to a perturbation away from the common effect assumption. The first estimand QY1−Y0(τ) is the τ-quantile of the difference between the potential outcomes and the second estimand QY1(τ)−QY0(τ) is the difference between the τ-quantiles of the potential outcomes. To this end, this note provides a simple “trembling hand” example whereby the treatment effect deviates from the common effect β for only one individual in a large population. As a result, each estimand deviates from β, and may have the opposite sign than β, in a distinct range of τ. In general, this perturbation leads QY1−Y0(⋅) to differ from β more severely but only in a small and extreme range of τ whereas it leads QY1(⋅)−QY0(⋅) to differ from β less severely but over a substantial and central range of τ. This example suggests that researchers should carefully evaluate estimates or bounds for QY1−Y0(τ) and especially QY1(τ)−QY0(τ) over a large range of τ.
Keywords: Heterogeneity; Quantile treatment effect; Robustness (search for similar items in EconPapers)
JEL-codes: C18 C21 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0165176519303507
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:ecolet:v:185:y:2019:i:c:s0165176519303507
DOI: 10.1016/j.econlet.2019.108703
Access Statistics for this article
Economics Letters is currently edited by Economics Letters Editorial Office
More articles in Economics Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().