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Semiparametric Methods in Econometrics

  • Joel L. Horowitz

Part of the Lecture Notes in Statistics book series (LNS, volume 131)

Table of contents

  1. Front Matter
    Pages i-x
  2. Joel L. Horowitz
    Pages 1-3
  3. Joel L. Horowitz
    Pages 5-53
  4. Joel L. Horowitz
    Pages 55-102
  5. Joel L. Horowitz
    Pages 103-139
  6. Joel L. Horowitz
    Pages 141-178
  7. Back Matter
    Pages 179-206

About this book

Introduction

Many econometric models contain unknown functions as well as finite- dimensional parameters. Examples of such unknown functions are the distribution function of an unobserved random variable or a transformation of an observed variable. Econometric methods for estimating population parameters in the presence of unknown functions are called "semiparametric." During the past 15 years, much research has been carried out on semiparametric econometric models that are relevant to empirical economics. This book synthesizes the results that have been achieved for five important classes of models. The book is aimed at graduate students in econometrics and statistics as well as professionals who are not experts in semiparametic methods. The usefulness of the methods will be illustrated with applications that use real data.

Keywords

Estimator Finite Random variable Variable econometrics function semiparametric methods statistics

Authors and affiliations

  • Joel L. Horowitz
    • 1
  1. 1.Department of EconomicsUniversity of IowaIowa CityUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4612-0621-7
  • Copyright Information Springer-Verlag New York, Inc. 1998
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Print ISBN 978-0-387-98477-3
  • Online ISBN 978-1-4612-0621-7
  • Series Print ISSN 0930-0325
  • Buy this book on publisher's site
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