Econometric Analysis

Econometric Analysis
by William H. Greene

For a one-year graduate course in Econometrics. This text has two objectives. The first is to introduce students to applied econometrics, including basic techniques in regression analysis and some of the rich variety of models that are used when the linear model proves inadequate or inappropriate. The second is to present students with sufficient theoretical background that they will recognize new variants of the models learned about here as merely natural extensions that fit within a common body of principles. The Fifth Edition features a complete update of techniques and developments, a reorganization of material for improved presentation, and new material and applications.

The Econometric Analysis of Transition Data
by Tony Lancaster

This book presents statistical methods for analysis of the duration of events. The primary focus is on models for single-spell data, events in which individual agents are observed for a single duration. Some attention is also given to multiple-spell data. The first part of the book covers model specification, including both structural and reduced form models and models with and without neglected heterogeneity. The book next deals with likelihood based inference about such models, with sections on full and semiparametric specification. A final section treats graphical and numerical methods of specification testing. This is the first published exposition of current econometric methods for the study of duration data.

Econometric Analysis of Cross Section and Panel Data
by Jeffrey M. Wooldridge

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.


The Econometric Analysis of Time Series
by Andrew C. Harvey

This new edition of A.C. Harvey’s clearly written, upper-level text has been revised and several sections have been completely rewritten. There is new material on a number of topics, including unit roots, ARCH, and cointegration.

The Econometric Analysis of Time Series focuses on the statistical aspects of model building, with an emphasis on providing an understanding of the main ideas and concepts in econometrics rather than presenting a series of rigorous proofs. It explores the way in which recent advances in time series analysis have affected the development of a theory of dynamic econometrics, sets out an integrated approach to the problems of estimation and testing based on the method of maximum likelihood, and presents a coherent strategy for model selection.

A.C. Harvey is Professor of Econometrics at the London School of Economics.


Econometric Analysis of Count Data
by Rainer Winkelmann

This monograph deals with econometric models for the analysis of event counts. The interest of econometricians in this class of models has started in the mid-eighties. After more than one decade of intensive research, the litera ture has reached a level of maturity that calls for a systematic and accessible exposition of the main results and methods. Such an exposition is the aim of the book. Count data models have found their way into the curricula of micro-econometric classes and are available on standard computer software. The basic methods have been used in countless applications in fields such as labor economics, health economics, insurance economics, urban economics, and economic demography, to name but a few. Other, more recent, methods are poised to become standard tools soon. While the book is oriented towards the empirical economists and applied econometrician, it should be useful to statisticians and biometricians as well. A first edition of this book was published in 1994 under the title “Count Data Models – Econometric Theory and an Application to Labor Mobility” . While this edition keeps the character and broad organization of this first edition, and its emphasis on combining a summary of the existing literature with several new results and methods, it is substantially revised and enlarged. Many parts have been completely rewritten and several new sections have New sections include: count data models for dependent processes; been added.

Econometric Analysis of Panel Data
by Badi H. Baltagi

“Econometric Analysis of Panel Data” has become established as one of the leading textbooks for students of panel data.

The significantly revised and updated third edition from one of the leading researchers and writers in this field builds upon the success of previous editions, and includes the most recent empirical examples from panel data literature.

Updated topics include dynamic panels, nonstationary panels, limited dependent variable models, heteroskedastic panels, heterogeneous panels and spatial panels.

Other notable features of this third edition: The chapter on nonstationary panels has been completely rewritten and updated to include the recent unit root panel tests with cross-section dependence, and an empirical application is given on purchasing power parity, which is illustrated using Eviews.An empirical example on nursing labor supply has been added, illustrating limited dependent variables methods with panel data.Additional exercises have been added to each chapter and their solutions will be provided on the website. TSP, EViews and Stata output examples are given throughout the book.A simultaneous equation on crime has been added and is illustrated with Stata.Material on heteroske4dasticity in panels is completely revised and updated with recent estimation and testing results.


Econometric Analysis
by William H. Greene

This study introduces students to applied econometrics, including basic techniques in regression analysis. Key topics in this text include self-contained summaries of the matrix algebra, statistical theory and mathematical statistics used in the book. The book covers Estimator, ML, GMM, and 2 step; panel data, heteroscedasticity, qualitative responsive models, and limited dependant variables. It emphasizes nonlinear models. Topics such as GMM estimation methods, Lagrange multiplier tests and time series analysis are also covered.

Econometric Analysis of Panel Data
by Badi Baltagi

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.  


Econometric Analysis of Stochastic Dominance
by Yoon-Jae Whang

This book offers an up-to-date, comprehensive coverage of stochastic dominance and its related concepts in a unified framework. A method for ordering probability distributions, stochastic dominance has grown in importance recently as a way to measure comparisons in welfare economics, inequality studies, health economics, insurance wages, and trade patterns. Whang pays particular attention to inferential methods and applications, citing and summarizing various empirical studies in order to relate the econometric methods with real applications and using computer codes to enable the practical implementation of these methods. Intuitive explanations throughout the book ensure that readers understand the basic technical tools of stochastic dominance.


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