Written by one of the world's leading researchers and writers in the field, Econometric Analysis of Panel Data has become established as the leading textbook for postgraduate courses in panel data. This new edition reflects the rapid developments in the field covering the vast research that has been conducted on panel data since its initial publication. Featuring the most recent empirical examples from panel data literature, data sets are also provided as well as the programs to implement the estimation and testing procedures described in the book. These programs will be made available via an accompanying website which will also contain solutions to end of chapter exercises that will appear in the book. The text has been fully updated with new material on dynamic panel data models and recent results on non-linear panel models and in particular work on limited dependent variables panel data models.

This textbook offers a comprehensive introduction to panel data econometrics, an area that has enjoyed considerable growth over the last two decades. Micro and Macro panels are becoming increasingly available, and methods for dealing with these types of data are in high demand among practitioners. Software programs have fostered this growth, including freely available programs in R and numerous user-written programs in both Stata and EViews. Written by one of the world’s leading researchers and authors in the field, Econometric Analysis of Panel Data has established itself as the leading textbook for graduate and postgraduate courses on panel data. It provides up-to-date coverage of basic panel data techniques, illustrated with real economic applications and datasets, which are available at the book’s website on springer.com. This new sixth edition has been fully revised and updated, and includes new material on dynamic panels, limited dependent variables and nonstationary panels, as well as spatial panel data. The author also provides empirical illustrations and examples using Stata and EViews. “This is a definitive book written by one of the architects of modern, panel data econometrics. It provides both a practical introduction to the subject matter, as well as a thorough discussion of the underlying statistical principles without taxing the reader too greatly." Professor Kajal Lahiri, State University of New York, Albany, USA. "This book is the most comprehensive work available on panel data. It is written by one of the leading contributors to the field, and is notable for its encyclopaedic coverage and its clarity of exposition. It is useful to theorists and to people doing applied work using panel data. It is valuable as a text for a course in panel data, as a supplementary text for more general courses in econometrics, and as a reference." Professor Peter Schmidt, Michigan State University, USA. “Panel data econometrics is in its ascendancy, combining the power of cross section averaging with all the subtleties of temporal and spatial dependence. Badi Baltagi provides a remarkable roadmap of this fascinating interface of econometric method, enticing the novitiate with technical gentleness, the expert with comprehensive coverage and the practitioner with many empirical applications.” Professor Peter C. B. Phillips, Cowles Foundation, Yale University, USA.

‘Econometric Analysis of Panel Data’ has become established as the leading textbook for postgraduate courses in panel data. This book is intended as a companion to the main text. The prerequisites include a good background in mathematical statistics and econometrics. The companion guide will add value to the existing textbooks on panel data by solving exercises in a logical and pedagogical manner, helping the reader understand, learn and teach panel data. These exercises are based upon those in Baltagi (2008) and are complementary to that text even though they are stand alone material and the reader can learn the basic material as they go through these exercises. The exercises in this book start by providing some background material on partitioned regressions and the Frisch-Waugh-Lovell theorem, showing the reader some applications of this material that are useful in practice. Then it goes through the basic material on fixed and random effects models in a one-way and two-way error components models, following the same outline as in Baltagi (2008). The book also provides some empirical illustrations and examples using Stata and EViews that the reader can replicate. The data sets are available on the Wiley web site (www.wileyeurope.com/college/baltagi).

The second edition of a comprehensive state-of-the-art graduate level text on microeconometric methods, substantially revised and updated. The second edition of this acclaimed graduate text provides a unified treatment of two methods used in contemporary econometric research, cross section and data panel methods. By focusing on assumptions that can be given behavioral content, the book maintains an appropriate level of rigor while emphasizing intuitive thinking. The analysis covers both linear and nonlinear models, including models with dynamics and/or individual heterogeneity. In addition to general estimation frameworks (particular methods of moments and maximum likelihood), specific linear and nonlinear methods are covered in detail, including probit and logit models and their multivariate, Tobit models, models for count data, censored and missing data schemes, causal (or treatment) effects, and duration analysis. Econometric Analysis of Cross Section and Panel Data was the first graduate econometrics text to focus on microeconomic data structures, allowing assumptions to be separated into population and sampling assumptions. This second edition has been substantially updated and revised. Improvements include a broader class of models for missing data problems; more detailed treatment of cluster problems, an important topic for empirical researchers; expanded discussion of "generalized instrumental variables" (GIV) estimation; new coverage (based on the author's own recent research) of inverse probability weighting; a more complete framework for estimating treatment effects with panel data, and a firmly established link between econometric approaches to nonlinear panel data and the "generalized estimating equation" literature popular in statistics and other fields. New attention is given to explaining when particular econometric methods can be applied; the goal is not only to tell readers what does work, but why certain "obvious" procedures do not. The numerous included exercises, both theoretical and computer-based, allow the reader to extend methods covered in the text and discover new insights.

This book is a collection of 20 chapters on chosen topics from cross-section and panel data econometrics. It explores both theoretical and practical aspects of selected cutting-edge techniques which are gaining popularity among applied econometricians, while following the motto of “keeping things simple”. Each chapter gives a basic introduction to one such method, directs readers to supplementary references, and shows an application. The book takes into account that—A: The field of econometrics is evolving very fast and leading textbooks are trying to cover some of the recent developments in revised editions. This book offers basic introduction to state-of-the-art techniques and recent advances in econometric models with detailed applications from various developing and developed countries. B: An applied researcher or practitioner may prefer reference books with a simple introduction to an advanced econometric method or model with no theorems but with a longer discussion on empirical application. Thus, an applied econometrics textbook covering these cutting-edge methods is highly warranted; a void this book attempts to fills.The book does not aim at providing a comprehensive coverage of econometric methods. The 20 chapters in this book represent only a sample of the important topics in modern econometrics, with special focus on econometrics of cross-section and panel data, while also recognizing that it is not possible to accommodate all types of models and methods even in these two categories. The book is unique as authors have also provided the theoretical background (if any) and brief literature review behind the empirical applications. It is a must-have resource for students and practitioners of modern econometrics.

This monograph deals with spatially dependent nonstationary time series in a way accessible to both time series econometricians wanting to understand spatial econometics, and spatial econometricians lacking a grounding in time series analysis. After charting key concepts in both time series and spatial econometrics, the book discusses how the spatial connectivity matrix can be estimated using spatial panel data instead of assuming it to be exogenously fixed. This is followed by a discussion of spatial nonstationarity in spatial cross-section data, and a full exposition of non-stationarity in both single and multi-equation contexts, including the estimation and simulation of spatial vector autoregression (VAR) models and spatial error correction (ECM) models. The book reviews the literature on panel unit root tests and panel cointegration tests for spatially independent data, and for data that are strongly spatially dependent. It provides for the first time critical values for panel unit root tests and panel cointegration tests when the spatial panel data are weakly or spatially dependent. The volume concludes with a discussion of incorporating strong and weak spatial dependence in non-stationary panel data models. All discussions are accompanied by empirical testing based on a spatial panel data of house prices in Israel.

This proceedings volume presents new methods and applications in applied economic research with an emphasis on advances in panel data analysis. Featuring papers presented at the 2017 International Conference on Applied Economics (ICOAE) held at Coventry University, this volume provides current research on econometric panel data methodologies as they are applied in microeconomics, macroeconomics, financial economics and agricultural economics. International Conference on Applied Economics (ICOAE) is an annual conference that started in 2008 designed to bring together economists from different fields of applied economic research in order to share methods and ideas. Applied economics is a rapidly growing field of economics that combines economic theory with econometrics to analyse economic problems of the real world usually with economic policy interest. In addition, there is growing interest in the field for panel data estimation methods, tests and techniques. This volume makes a contribution in the field of applied economic research in this area. Featuring country specific studies, this book will be of interest to academics, students, researchers, practitioners, and policy makers in applied economics and economic policy.

For the last four decades, the uses of econometric tools and techniques, irrespective of discipline, have been increasing rapidly for solving problems, appropriate decision-making and policy formulation. Generally, it is accepted that the study of modern business and economics is incomplete without a proper knowledge of econometric tools and techniques. In view of the increasing complexity and variety of problems in business and economics, students and researchers may not be able to cope and hence may remain unfamiliar with many aspects of business and economic problems. Thus, this book was written to explore basic and advanced studies of econometrics for undergraduate and graduate students of business and economics, as well as for researchers already engaged in these fields who require an introduction to econometric methods and their application for solving of real-life problems. The book offers a balanced presentation of fundamental and advanced levels of econometric concepts and methods, along with practical examples of their effective application in real-life problems.

Panel data is a data type increasingly used in research in economics, social sciences, and medicine. Its primary characteristic is that the data variation goes jointly over space (across individuals, firms, countries, etc.) and time (over years, months, etc.). Panel data allow examination of problems that cannot be handled by cross-section data or time-series data. Panel data analysis is a core field in modern econometrics and multivariate statistics, and studies based on such data occupy a growing part of the field in many other disciplines. The book is intended as a text for master and advanced undergraduate courses. It may also be useful for PhD-students writing theses in empirical and applied economics and readers conducting empirical work on their own. The book attempts to take the reader gradually from simple models and methods in scalar (simple vector) notation to more complex models in matrix notation. A distinctive feature is that more attention is given to unbalanced panel data, the measurement error problem, random coefficient approaches, the interface between panel data and aggregation, and the interface between unbalanced panels and truncated and censored data sets. The 12 chapters are intended to be largely self-contained, although there is also natural progression. Most of the chapters contain commented examples based on genuine data, mainly taken from panel data applications to economics. Although the book, inter alia, through its use of examples, is aimed primarily at students of economics and econometrics, it may also be useful for readers in social sciences, psychology, and medicine, provided they have a sufficient background in statistics, notably basic regression analysis and elementary linear algebra.