Causal inference targeting a concentration index for studies of health inequalities

Fuente: arXiv
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Auteurs principaux: Ghasempour, Mohammad, de Luna, Xavier, Gustafsson, Per E.
Format: Preprint
Publié: 2024
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author Ghasempour, Mohammad
de Luna, Xavier
Gustafsson, Per E.
author_facet Ghasempour, Mohammad
de Luna, Xavier
Gustafsson, Per E.
contents A concentration index, a standardized covariance between a health variable and relative income ranks, is often used to quantify income-related health inequalities. There is a lack of formal approach to study the effect of an exposure, e.g., education, on such measures of inequality. In this paper we contribute by filling this gap and developing the necessary theory and method. Thus, we define a counterfactual concentration index for different levels of an exposure. We give conditions for their identification, and then deduce their efficient influence function. This allows us to propose estimators, which are regular asymptotic linear under certain conditions. In particular, these estimators are $\sqrt n$-consistent and asymptotically normal, as well as locally efficient. The implementation of the estimators is based on the fit of several nuisance functions. The estimators proposed have rate robustness properties allowing for convergence rates slower than $\sqrt{n}$-rate for some of the nuisance function fits. The relevance of the asymptotic results for finite samples is studied with simulation experiments. We also present a case study of the effect of education on income-related health inequalities for a Swedish cohort.
format Preprint
id arxiv_https___arxiv_org_abs_2410_08849
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Causal inference targeting a concentration index for studies of health inequalities
Ghasempour, Mohammad
de Luna, Xavier
Gustafsson, Per E.
Methodology
Statistics Theory
A concentration index, a standardized covariance between a health variable and relative income ranks, is often used to quantify income-related health inequalities. There is a lack of formal approach to study the effect of an exposure, e.g., education, on such measures of inequality. In this paper we contribute by filling this gap and developing the necessary theory and method. Thus, we define a counterfactual concentration index for different levels of an exposure. We give conditions for their identification, and then deduce their efficient influence function. This allows us to propose estimators, which are regular asymptotic linear under certain conditions. In particular, these estimators are $\sqrt n$-consistent and asymptotically normal, as well as locally efficient. The implementation of the estimators is based on the fit of several nuisance functions. The estimators proposed have rate robustness properties allowing for convergence rates slower than $\sqrt{n}$-rate for some of the nuisance function fits. The relevance of the asymptotic results for finite samples is studied with simulation experiments. We also present a case study of the effect of education on income-related health inequalities for a Swedish cohort.
title Causal inference targeting a concentration index for studies of health inequalities
topic Methodology
Statistics Theory
url https://arxiv.org/abs/2410.08849