The Econometrics of Panel Data

1. Front Matter

   Pages i-2

   PDF

2. Formulation and Estimation of Econometric Models for Panel Data

   1. Formulation and Estimation of Econometric Models for Panel Data

      • Marc Nerlove, Pietro Balestra

      Pages 3-22

3. Linear Models

   1. Front Matter

      Pages 23-23

      PDF

   2. Introduction to Linear Models for Panel Data

      • Pietro Balestra

      Pages 25-33

   3. Fixed Effect Models and Fixed Coefficient Models

      • Pietro Balestra

      Pages 34-49

   4. Error Components Models

      • László Mátyás

      Pages 50-76

   5. Random Coefficients Models

      • Hsiao Cheng

      Pages 77-99

   6. Linear Models with Random Regressors

      • Patrick Sevestre, Alain Trognon

      Pages 100-119

   7. Dynamic Linear Models

      • Patrick Sevestre, Alain Trognon

      Pages 120-144

   8. Dynamic Linear Models for Heterogenous Panels

      • Hashem Pesaran, Ron Smith, Kyung So Im

      Pages 145-195

   9. Simultaneous Equations

      • Jayalakshmi Krishnakumar

      Pages 196-235

   10. Panel Data with Measurement Errors

       • Erik Biørn

       Pages 236-279

   11. Pseudo Panel Data

       • Marno Verbeek

       Pages 280-292

   12. Specification Issues

       • Badi H. Baltagi

       Pages 293-306

   13. The Pooling Problem

       • G. S. Maddala, Wanhong Hu

       Pages 307-322

   14. The Chamberlain Approach

       • Bruno Crépon, Jacques Mairesse

       Pages 323-395

4. Nonlinear Models

   1. Front Matter

      Pages 397-397

      PDF

   2. Introduction to Nonlinear Models

      • Christian Gourieroux

      Pages 399-409

   3. Logit and Probit Models

      • Cheng Hsiao

      Pages 410-428

   4. Nonlinear Latent Variable Models

      • Cheng Hsiao

      Pages 429-448

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 Edwin Kuh (1959), Yair Mundlak (1961), Irving Hoch (1962), and Pietro Balestra and Marc Nerlove (1966), the pooling of cross sections 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 pro bit models, latent variable models, duration and count data models, incomplete panels and selectivity bias, point processes, and simulation techniques.

• count data
• econometrics
• panel data
• Simulation
• statistics
• time series

• Monash University, Melbourne and Budapest University of Economics, Australia

  László Mátyás

• ERUDITE, Université de Paris-Val-de-Marne, France

  Patrick Sevestre

Policies and ethics