The Econometrics of Panel Data. Handbook of Theory and Applications.

. Ed(s): Matyas, Laszlo; Sevestre, Patrick

ISBN 10: 9401066558 / ISBN 13: 9789401066556

Published by Springer, 2011

About this Item

Editor(s): Matyas, Laszlo; Sevestre, Patrick. Series: Advanced Studies in Theoretical and Applied Econometrics. Num Pages: 568 pages, biography. BIC Classification: KCH. Category: (P) Professional & Vocational. Dimension: 240 x 160 x 29. Weight in Grams: 901. . 2011. Softcover reprint of the original 1st ed. 1992. Paperback. . . . . Books ship from the US and Ireland.

Seller Inventory # V9789401066556

Bibliographic Details

• Title: The Econometrics of Panel Data. Handbook of Theory and Applications.
• Publisher: Springer
• Publication Date: 2011
• Language: English
• ISBN 10: 9401066558
• ISBN 13: 9789401066556
• Binding: Soft cover
• Condition: New

About this title

Synopsis

The aim of this volume is to provide a general overview of the econometrics of panel data, both from a theoretical and from an applied viewpoint. Since the pioneering papers by Kuh (1959), Mundlak (1961), Hoch (1962), and Balestra and Nerlove (1966), the pooling of cross section and time series data has become an increasingly popular way of quantifying economic relationships. Each series provides information lacking in the other, so a combination of both leads to more accurate and reliable results than would be achievable by one type of series alone. Over the last 30 years much work has been done: investigation of the properties of the applied estimators and test statistics, analysis of dynamic models and the effects of eventual measurement errors, etc. These are just some of the problems addressed by this work. In addition, some specific diffi­ culties associated with the use of panel data, such as attrition, heterogeneity, selectivity bias, pseudo panels etc., have also been explored. The first objective of this book, which takes up Parts I and II, is to give as complete and up-to-date a presentation of these theoretical developments as possible. Part I is concerned with classical linear models and their extensions; Part II deals with nonlinear models and related issues: logit and probit models, latent variable models, incomplete panels and selectivity bias, and point processes.