The Econometrics of Panel data: Handbook of Theory and Applications

Book Preface

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.

Contents

Preface

1. Formulation and Estimation of Econometric Models for Panel Data

Part I. Linear Models

2. Introduction to Linear Models for Panel Data 21 (Pietro Balestra)

3. Fixed Effect Models and Fixed Coefficient Models 30 (Pietro Balestra)

4. Error Components Models 46 (Laszlo Matyas)

5. Random Coefficients Models 72 (Cheng Hsiao)

6. Linear Dynamic Models  (Patrick Sevestre and Alain Trognon)

7. Simultaneous Equations (J ayalakshmi Krishnakumar)

8. Panel Data with Measurement Errors 152 (Erik Bif6rn)

9. Specification Issues 196 (Badi H. Baltagi)

Part II. Nonlinear Models

10. Introduction to Nonlinear Models 213 (Christian Gourieroux)

11. Logit and Probit Models 223 (Cheng Hsiao)

12. Nonlinear Latent Variable Models 242 (Cheng Hsiao)

13. Incomplete Panels and Selection Bias 262 (Marno Verbeek and Theo Nijman)

14. Pseudo Panel Data (~arno”erbeek)

15. Point Processes (Jean-Pierre Florens and Denis Fougere)