Panel Data Econometrics

Panel Data Econometrics

Panel Data Econometrics

Panel Data Econometrics

Synopsis

This book, by one of the world's leading experts on dynamic panel data, presents a modern review of some of the main topics in panel data econometrics. The author concentrates on linear models, and emphasizes the roles of heterogeneity and dynamics in panel data modelling. The book combinesmethods and applications, so will appeal to both the academic and practitioner markets. The book is divided in four parts. Part I concerns static models, and deals with the problem of unobserved heterogeneity and how the availability of panel data helps to solve it, error component models, and error in variables in panel data. Part II looks at time series models with error components. Its chapters deal with the problem of distinguishing between unobserved heterogeneity and individual dynamics in short panels, modelling strategies of time effects, moving average models, inference from covariance structures, thespecification and estimation of autoregressive models with heterogeneous intercepts, and the impact of assumptions about initial conditions and heteroskedacity on estimation. Part III examines dynamics and predeterminedness. Its two chapters consider alternative approaches to estimation from small and large T perspectives, looking at models with both strictly exogenous and lagged dependent variables allowing for autocorrelation of unknown form, models in which the errorsare mean independent of current and lagged values of certain conditioning variables but not with their future values. Together Parts II and III provide a synthesis, and unified perspective, of a vast literature that has had a significant impact on recent econometric practice. Part IV reviews the main results in the theory of generalized method of moments estimation and optimal instrumental variables.

Excerpt

The objective of this book is to review some of the main topics in panel data econometrics. It deals with linear static and dynamic models, and it is aimed at a readership of graduate students and applied researchers. Parts of the book can be used in a graduate course on panel data econometrics, and as a reference source for practitioners.

I have tried to survey as many modelling ideas as possible, rather than trying to present them with the greatest generality. Modelling ideas are often the key input in applied econometrics, and although the book is concerned with econometric methodology, an effort has been made to motivate techniques in the context of applications.

Familiarity with linear regression analysis and basic concepts in probability theory is required. For the most part I adopt a generalized method of moments (GMM) approach, and I make frequent use of instrumental variable arguments. When available, I also present likelihood approaches drawing links to their regression or GMM counterparts. Since the degree of exposure of economists to GMM varies with cohort and style of undergraduate training, I have included two appendices, one on GMM and another on optimal instruments, in order to make the book reasonably self-contained. These two appendices are a revised version of the notes I have used over the years in teaching graduate students at CEMFI.

Acknowledgements

I started writing this book in the Winter of 2000 during a stay at the Faculty of Economics and Politics, University of Cambridge, whose hospitality I am pleased to acknowledge. It was finished at CEMFI two years later, and I gratefully thank my colleagues for their forbearance. Its existence owes much to Andrew Schuller's belief that I was capable of writing at book length on panel data; my warmest thanks to him for his encouragement and patience. Over the years I have been fortunate to be close to teachers, colleagues, and students that provided decisive stimulus to my work. My teachers and mentors, Steve Nickell and David Hendry, and especially my Ph.D. adviser, Denis Sargan, greatly influenced my understanding of econometrics. I have enormously benefited from close interaction with Richard

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