Asymptotic Theory for Econometricians
- 1st Edition - April 1, 1984
- Latest edition
- Author: Halbert White
- Editor: Karl Shell
- Language: English
This book is intended to provide a somewhat more comprehensive and unified treatment of large sample theory than has been available previously and to relate the fundamental tools… Read more
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Description
Description
This book is intended to provide a somewhat more comprehensive and unified treatment of large sample theory than has been available previously and to relate the fundamental tools of asymptotic theory directly to many of the estimators of interest to econometricians. In addition, because economic data are generated in a variety of different contexts (time series, cross sections, time series--cross sections), we pay particular attention to the similarities and differences in the techniques appropriate to each of these contexts.
Readership
Readership
Graduate students taking courses in Econometrics beyond the introductory level.
Table of contents
Table of contents
Preface.
The Linear Model and Instrumental Variables Estimators.
Consistency.
Laws of Large Numbers.
Asymptotic Normality.
Central Limit Theory.
Estimating Asymptotic Covariance Matrices.
Efficient Estimation with Estimated Error Covariance.
Directions for Further Study.
Solutions Set.
Index.
The Linear Model and Instrumental Variables Estimators.
Consistency.
Laws of Large Numbers.
Asymptotic Normality.
Central Limit Theory.
Estimating Asymptotic Covariance Matrices.
Efficient Estimation with Estimated Error Covariance.
Directions for Further Study.
Solutions Set.
Index.
Product details
Product details
- Edition: 1
- Latest edition
- Published: December 6, 2014
- Language: English
About the editor
About the editor
KS
Karl Shell
Affiliations and expertise
Cornell UniversityAbout the author
About the author
HW
Halbert White
Affiliations and expertise
University of California, San Diego, La Jolla, U.S.A.View book on ScienceDirect
View book on ScienceDirect
Read Asymptotic Theory for Econometricians on ScienceDirect