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.