Abstract

In this chapter, we examine semiparametric estimators that require non-parametric techniques. In most cases, the estimators will be obtained in two stages, where the first stage is a nonparametric method. See Delgado and Robinson (1992) and Powell (1994) for surveys. In most cases, we will restrict our discussion to \(\sqrt N\)-consistent estimators. Although we defined the term “semiparametrics” in a narrow sense that obtaining the estimates does not require nonparametric techniques, in this chapter we will often use the term “semiparametrics” in its wide sense as the union of semiparametrics and semi-nonparametrics.

Keywords

Efficient Score Nuisance Parameter Influence Function Kernel Estimator Closed Linear Span 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 1996

Authors and Affiliations

  • Myoung-jae Lee
    • 1
  1. 1.Department of EconometricsTilburg UniversityTilburgThe Netherlands

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