Methods of Moments and Semiparametric Econometrics for Limited Dependent Variable Models.

Myoung-jae Lee

ISBN 10: 0387946268 / ISBN 13: 9780387946269

Edité par Springer Verlag, 1996

A propos de cet article

Gebraucht - Sehr gut Zustand: Sehr gut, Mängelexemplar, XII, 279 p. 20 illus. About this book: In this book the author surveys new techniques in econometrics which may be used to analyse semiparametric models. As well as covering topics such as instrumental variable estimation, nonparametric density and regression function estimation and semiparametric limited dependent variable models, the book provides details of how these methods may be implemented using software.

N° de réf. du vendeur 18283

Détails bibliographiques

• Titre: Methods of Moments and Semiparametric Econometrics for Limited Dependent Variable Models.
• Éditeur: Springer Verlag
• Date de parution: 1996
• Langue: anglais
• ISBN à 10 chiffres: 0387946268
• ISBN à 13 chiffres: 9780387946269
• Reliure: Gebunden
• État de l'article: Sehr gut

A propos de ce titre

Synopsis

The classical econometric approach to modelling has been to specify a model up to a finite-dimensional parameter vector, and estimation and testing techniques have been widely used on these finite-dimensional parameter spaces. In the last fifteen years or so however, new methods have been developed to allow more flexible models which utilise infinite-dimensional parameters. Simultaneously, methods of moments estimation have also become more widely used and applied. In this book, the author provides a survey of these modern techniques and how they are applied to limited dependent variable (LDV) models. As well as covering many classical approaches, the topics covered include: instrumental variable estimation, the generalized method of moments, extremum estimators, methods of simulated moments, minimum distance estimation, nonparametric density and regression function estimation, and semiparametric methods for LDV. As a result, many graduate students and research workers will appreciate this up-to-date account. There is an appendix that describes the use of the software package GAUSS to implement these methods in conjunction with some real data sets.