Semiparametric approach to estimation of marginal mean effects and marginal quantile effects

Seong ho Lee; Yanyuan Ma; Elvezio Ronchetti

doi:10.1016/j.jeconom.2023.05.002

Semiparametric approach to estimation of marginal mean effects and marginal quantile effects

Seong ho Lee, Yanyuan Ma, Elvezio Ronchetti

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Abstract

We consider a semiparametric generalized linear model and study estimation of both marginal mean effects and marginal quantile effects in this model. We propose an approximate maximum likelihood estimator, and rigorously establish the consistency, the asymptotic normality, and the semiparametric efficiency of our method in both the marginal mean effect and the marginal quantile effect estimation. Simulation studies are conducted to illustrate the finite sample performance, and we apply the new tool to analyze a Swiss non-labor income data and discover a new interesting predictor.

Original language	English (US)
Journal	Journal of Econometrics
DOIs	https://doi.org/10.1016/j.jeconom.2023.05.002
State	Accepted/In press - 2023

All Science Journal Classification (ASJC) codes

Economics and Econometrics
Applied Mathematics

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10.1016/j.jeconom.2023.05.002

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title = "Semiparametric approach to estimation of marginal mean effects and marginal quantile effects",

abstract = "We consider a semiparametric generalized linear model and study estimation of both marginal mean effects and marginal quantile effects in this model. We propose an approximate maximum likelihood estimator, and rigorously establish the consistency, the asymptotic normality, and the semiparametric efficiency of our method in both the marginal mean effect and the marginal quantile effect estimation. Simulation studies are conducted to illustrate the finite sample performance, and we apply the new tool to analyze a Swiss non-labor income data and discover a new interesting predictor.",

author = "Lee, {Seong ho} and Yanyuan Ma and Elvezio Ronchetti",

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year = "2023",

doi = "10.1016/j.jeconom.2023.05.002",

language = "English (US)",

journal = "Journal of Econometrics",

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T1 - Semiparametric approach to estimation of marginal mean effects and marginal quantile effects

AU - Lee, Seong ho

AU - Ma, Yanyuan

AU - Ronchetti, Elvezio

PY - 2023

Y1 - 2023

N2 - We consider a semiparametric generalized linear model and study estimation of both marginal mean effects and marginal quantile effects in this model. We propose an approximate maximum likelihood estimator, and rigorously establish the consistency, the asymptotic normality, and the semiparametric efficiency of our method in both the marginal mean effect and the marginal quantile effect estimation. Simulation studies are conducted to illustrate the finite sample performance, and we apply the new tool to analyze a Swiss non-labor income data and discover a new interesting predictor.

AB - We consider a semiparametric generalized linear model and study estimation of both marginal mean effects and marginal quantile effects in this model. We propose an approximate maximum likelihood estimator, and rigorously establish the consistency, the asymptotic normality, and the semiparametric efficiency of our method in both the marginal mean effect and the marginal quantile effect estimation. Simulation studies are conducted to illustrate the finite sample performance, and we apply the new tool to analyze a Swiss non-labor income data and discover a new interesting predictor.

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DO - 10.1016/j.jeconom.2023.05.002

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SN - 0304-4076

JO - Journal of Econometrics

JF - Journal of Econometrics

ER -

Semiparametric approach to estimation of marginal mean effects and marginal quantile effects

Abstract

All Science Journal Classification (ASJC) codes

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