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Economic Applications of Quantile Regression

  • Bernd Fitzenberger
  • Roger Koenker
  • José A. F. Machado

Part of the Studies in Empirical Economics book series (STUDEMP)

Table of contents

  1. Front Matter
    Pages I-VI
  2. Bernd Fitzenberger, Roger Koenker, José A. F. Machado
    Pages 1-5
  3. Bernd Fitzenberger, Reinhard Hujer, Thomas E. MaCurdy, Reinhold Schnabel
    Pages 41-86
  4. Jaume García, Pedro J. Hernández, Angel López-Nicolás
    Pages 149-167
  5. Eduardo Pontual Ribeiro
    Pages 183-197
  6. Victor Chernozhukov, Len Umantsev
    Pages 271-292
  7. Gilbert W. Bassett Jr., Hsiu-Lang Chen
    Pages 293-305
  8. Herman J. Bierens, Donna K. Ginther
    Pages 307-324

About this book

Introduction

Quantile regression has emerged as an essential statistical tool of contemporary empirical economics and biostatistics. Complementing classical least squares regression methods which are designed to estimate conditional mean models, quantile regression provides an ensemble of techniques for estimating families of conditional quantile models, thus offering a more complete view of the stochastic relationship among variables. This volume collects 12 outstanding empirical contributions in economics and offers an indispensable introduction to interpretation, implementation, and inference aspects of quantile regression.

Keywords

Conditional Distribution Economic Application Quantile Regression Regression analysis education modeling regression statistics value at risk value-at-risk

Editors and affiliations

  • Bernd Fitzenberger
    • 1
  • Roger Koenker
    • 2
  • José A. F. Machado
    • 3
  1. 1.Department of EconomicsUniversity of MannheimMannheimGermany
  2. 2.Department of EconomicsUniversity of IllinoisChampaignUSA
  3. 3.Faculdade de Economiay, Tr. Estevão Pinto — CampolideUniversidade Nova de LisboaLisboaPortugal

Bibliographic information

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