The efficiency of the second-order nonlinear least squares estimator and its extension

Mijeong Kim, Yanyuan Ma

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

We revisit the second-order nonlinear least square estimator proposed in Wang and Leblanc (Anne Inst Stat Math 60:883-900, 2008) and show that the estimator reaches the asymptotic optimality concerning the estimation variability. Using a fully semiparametric approach, we further modify and extend the method to the heteroscedastic error models and propose a semiparametric efficient estimator in this more general setting. Numerical results are provided to support the results and illustrate the finite sample performance of the proposed estimator.

Original languageEnglish
Pages (from-to)751-764
Number of pages14
JournalAnnals of the Institute of Statistical Mathematics
Volume64
Issue number4
DOIs
StatePublished - Aug 2012

Keywords

  • Heteroscedasticity
  • Moments
  • Second-order least squares estimator
  • Semiparametric methods

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