Please note: In order to keep Hive up to date and provide users with the best features, we are no longer able to fully support Internet Explorer. The site is still available to you, however some sections of the site may appear broken. We would encourage you to move to a more modern browser like Firefox, Edge or Chrome in order to experience the site fully.

Topics In Advanced Econometrics : Volume II Linear and Nonlinear Simultaneous Equations, Hardback Book

Topics In Advanced Econometrics : Volume II Linear and Nonlinear Simultaneous Equations Hardback

Hardback

Description

This book is intended for second year graduate students and professionals who have an interest in linear and nonlinear simultaneous equations mod­ els.

It basically traces the evolution of econometrics beyond the general linear model (GLM), beginning with the general linear structural econo­ metric model (GLSEM) and ending with the generalized method of mo­ ments (GMM).

Thus, it covers the identification problem (Chapter 3), maximum likelihood (ML) methods (Chapters 3 and 4), two and three stage least squares (2SLS, 3SLS) (Chapters 1 and 2), the general nonlinear model (GNLM) (Chapter 5), the general nonlinear simultaneous equations model (GNLSEM), the special ca'3e of GNLSEM with additive errors, non­ linear two and three stage least squares (NL2SLS, NL3SLS), the GMM for GNLSEIVl, and finally ends with a brief overview of causality and re­ lated issues, (Chapter 6).

There is no discussion either of limited dependent variables, or of unit root related topics.

It also contains a number of significant innovations.

In a departure from the custom of the literature, identification and consistency for nonlinear models is handled through the Kullback information apparatus, as well as the theory of minimum contrast (MC) estimators.

In fact, nearly all estimation problems handled in this volume can be approached through the theory of MC estimators.

The power of this approach is demonstrated in Chapter 5, where the entire set of identification requirements for the GLSEM, in an ML context, is obtained almost effortlessly, through the apparatus of Kullback information.

Information

  • Format:Hardback
  • Pages:402 pages, XVIII, 402 p.
  • Publisher:Springer-Verlag New York Inc.
  • Publication Date:
  • Category:
  • ISBN:9780387941561

Other Formats

Save 17%

£66.99

£55.55

Item not Available
 
Free Home Delivery

on all orders

 
Pick up orders

from local bookshops

Information

  • Format:Hardback
  • Pages:402 pages, XVIII, 402 p.
  • Publisher:Springer-Verlag New York Inc.
  • Publication Date:
  • Category:
  • ISBN:9780387941561