Sieve extremum estimation of a semiparametric transformation model

Yingqian Lin and Yundong Tu

Economics Letters, 2020, vol. 189, issue C

Abstract: This paper considers the estimation of a semiparametric transformation model, Λ(yt,β0)=g(xt)+ut, where Λ(⋅,β0) is a strictly increasing function known up to an ℓ-dimensional parameter β0, g is an unknown link function. Hermite polynomial expansion is used to approximate the link function g, which leads to an extreme estimator for β0 and a plug-in estimator for g. Asymptotic properties of the estimators are established. Simulation results demonstrate that the estimators perform well in finite samples. An example on Canadian occupation prestige is provided to illustrate the practical value of the proposed model.

Keywords: Extremum estimation; Hermite polynomials; Semiparametrics; Sieve method; Transformation (search for similar items in EconPapers)
JEL-codes: C13 C14 C5 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecolet:v:189:y:2020:i:c:s0165176520300446

DOI: 10.1016/j.econlet.2020.109020

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