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Semiparametric Methods in Econometrics
Author
Title
Semiparametric Methods in Econometrics [electronic resource] / by Joel L. Horowitz.
ISBN
9781461206217
Published
New York, NY : Springer New York : Imprint: Springer, 1998.
Physical Description
1 online resource.
Local Notes
Access is available to the Yale community.
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Access restricted by licensing agreement.
Summary
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.
Variant and related titles
Springer ebooks.
Other formats
Printed edition:
Format
Books / Online
Language
English
Added to Catalog
January 28, 2013
Series
Lecture Notes in Statistics, 131
Contents
Introduction
Single index models
Binary response models
Deconvolution problems
Transformation models
Appendix: Nonparametric Estimation.
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