Book Description
This graduate text provides an intuitive but rigorous treatment of contemporary methods used in microeconometric research. The book makes clear that applied microeconometrics is about the estimation of marginal and treatment effects, and that parametric estimation is simply a means to this end. It also clarifies the distinction between causality and statistical association.
The book focuses specifically on cross section and panel data methods. Population assumptions are stated separately from sampling assumptions, leading to simple statements as well as to important insights. The unified approach to linear and nonlinear models and to cross section and panel data enables straightforward coverage of more advanced methods. The numerous end-of-chapter problems are an important component of the book. Some problems contain important points not fully described in the text, and others cover new ideas that can be analyzed using tools presented in the current and previous chapters. Several problems require the use of the data sets located at the author's website.
Customer Reviews:
Everything people say is true, but..........2007-09-05
This book has no graphs - not one. As long there are no graphs or figures, this work will remain incomplete.
The missing link for cross section, panel data and program evaluation.......2007-06-02
This book fills a real gap for those who are interested in things like ATE, ATET and topics related to impact evaluation that are only talked about now in research papers. The explanations are very very clear and they walk you through the thinking process by which the different methods were developed. Of course, it has the traditional coverage of panel data and cross section but with the clarity that Wooldridge always delivers on his books. For all that, this is a perfect addition to your econometric libraries as it covers topics that are not discussed in traditional and introductory econometric books.
A comprehensive survey.......2007-05-12
This book provides an excellent overview about state-of-the-art methodologies in econometrics. Instead of other textbooks it stresses more on conditionals and explains potential problems with underlying assumptions in more detail. As I find it sometimes hard to orientate myself, I give 4 stars.
Very good coverage on cross-sectional, but not enough of panel data.......2006-08-18
This book does an excellent job in covering cross-sectional and microeconometric models (Stata codes for all examples in the book are available from UCLA's webside). However, the exposure to panel data is limited. For a theoretical overview of panel data econometrics, I'd recommend Hsiao and Baltagi. For applied work, Edward Frees wrote a good book, although his book is more from the social science perspective (SAS and Stata codes are provided).
The best? Not for me (and everyone I know)........2005-09-30
Clearly this product is overrated. In my opinion the book is a complete mess, with definitions, propositions and theorems mixed with the main text and not clearly evidenced from it.
It's funny, because the book uses a panoplia of bolds, italics, etc in the main text (well, there is only main text here) which I dislike and think is unnecessary, and then do not use it to evidence the important results. As a result I think this is probably the worst book that I can remember of for reference.
There are better books and it's almost impossible to get one worse than this one.
Average customer rating:
- Solid coverage on theory, but...
- Good On Longitudinal Panels, but not current and almost nothing on Online Access Panels
- Well worth getting the update
- A classic.
- A book necessary for panel data analysis
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Analysis of Panel Data
Cheng Hsiao
Manufacturer: Cambridge University Press
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Similar Items:
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Panel Data Econometrics (Advanced Texts in Econometrics)
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Econometric Analysis of Cross Section and Panel Data
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Longitudinal and Panel Data: Analysis and Applications in the Social Sciences
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Econometric Analysis of Panel Data
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Solutions Manual and Supplementary Materials for Econometric Analysis of Cross Section and Panel Data
ASIN: 0521522714 |
Book Description
Panel data models have become increasingly popular among applied researchers due to their heightened capacity for capturing the complexity of human behavior, as compared to cross-sectional or time series data models. This second edition represents a substantial revision of the highly successful first edition (1986). Recent advances in panel data research are presented in an accessible manner and are carefully integrated with the older material. The thorough discussion of theory and the judicious use of empirical examples make this book useful to graduate students and advanced researchers in economics, business, sociology and political science.
Download Description
Panel data models have become increasingly popular among applied researchers due to their heightened capacity for capturing the complexity of human behavior as compared to cross-sectional or time series data models. As a consequence, richer panel data sets also have become increasingly available. This second edition is a substantial revision of the highly successful first edition of 1986. Recent advances in panel data research are presented in a rigorous and accessible manner and are carefully integrated with the older material. The thorough discussion of theory and the judicious use of empirical examples make this book useful to graduate students and advanced researchers in economics, business, sociology, political science, etc. Other specific revisions include the introduction of the notion of strict exogeneity with estimators presented in a generalized method of moments framework, the notion of incidental parameters, more intuitive explanations of pairwise trimming, and discussion of sample selection dynamic panel models.
Customer Reviews:
Solid coverage on theory, but..........2006-08-14
This book covers panel data econometrics theory very well. It's probably the best in this field. However, this book lacks data and more importantly computer codes on how to implement panel data models. The author didn't provide a website where you can get the data in the book, which makes it difficult for applied econometricians to learn and implement. It would a lot more useful if the author can provide some support on how to implement his models in either packages (e.g., Stata or SAS) or programming languages (e.g., Gauss or Matlab). I found biometricians and social scientists do a much better job in both research and implementation of panel data models than econometricians, although they have different names for the same thing (e.g., mixed effects, multilevel, or HLM, etc.)
Good On Longitudinal Panels, but not current and almost nothing on Online Access Panels.......2006-03-06
Good Book.
Important Academic treatment on longitudinal panel data. It is really a shame that longitudinal panels and longitudinal analysis is not used more often in market research. It is so much more powerful in many ways than dynamic panels, though there is obviously a need for both. My complaint would be that there wasn't much on static panels, and of course the copy write date, and thus lack of information on online panel data, either static or dynamic. So much of the what has been written on marketing research really needs to be updated now that almost everything is being done Online.
If you are looking for something current that deals with Online Panel data you may want to check out Andrei Postoaca's (IPSOS Interactive Services CEO), The Anonymous Elect: Market Research Through Online Access Panels which was just released by Springer.
Tom Anderson
Anderson Analytics, LLC
Well worth getting the update.......2004-02-14
Cheng Hsiao's 1986 monograph "Analysis of Panel Data" drew the attention of many to the inherent advantages of using longitudinal (ie. panel) data sets, where the same subjects are observed at different periods in time. Substantially as a result of Hsiao's excellent presentation of key issues, the volume of research using panel data increased dramatically during the next fifteen years.
It is especially timely that Hsiao has written an updated version of this classic. All the essential concepts from the first edition have been retained; in addition, the author does a very good job of providing coverage of the many advances which have been made in analysis of panel data since 1986.
Of special note, in relation to the second edition, are the chapters on dynamic models (Ch. 4) and discrete response models (Ch. 7). These two areas have been particularly in need of an updated treatment, since a great deal of recent research has taken place into the properties of estimators in these situations. Hsiao's treatments of these are correct up to and including 2001, which provides a major service for researchers interested in these topics.
An alternative book, by Badi Baltagi, exists. However, Hsiao's book is superior and should be purchased by all who wish to pursue modern empirical work.
A classic........2001-12-21
This book is a classic on panel data econometrics. Nevertheless, the materials in this book do not account for nonstationary panel data. I am anxiously waiting for Arellano's Panel Data Econometrics, which contains up-to-date treatment.
A book necessary for panel data analysis.......2000-07-07
This neat monograph is necessary for empirical research in panel data analysis. In particular, discussions about fixed effects,random effects, discrete data and dynamic models have been very helpful for my empirical analysis.
Book Description
Focusing on an analysis of models and data that arise from repeated observations of a cross-section of individuals, households or firms, this book also covers important applications within business, economics, education, political science and other social science disciplines. The author introduces the foundations of longitudinal and panel data analysis at a level suitable for quantitatively oriented social science graduate students as well as individual researchers. He emphasizes mathematical and statistical fundamentals but also demonstrates substantive applications from across the social sciences. These applications are enhanced by real-world data sets and software programs in SAS and Stata.
Customer Reviews:
Very comprehensive book.......2006-11-15
This book is an excelent complement to panel data textbooks (such as Arellano's and Balthagi's) because it deals with problems generally encountered in microdata, such as sample selection.
This is an EXCELLENT book on panel data analysis!!.......2006-09-15
This is a very good book on panel data analysis. The author nicely summarized the key ideas about panel data from a few academic fields (biostatistics, econometrics, social science, and general statistics). The analysis of panel data could be confusing because different people in different fields could call the same thing by different names. People in econometrics sometimes ignore what is well developed in biostatistics, and vice versa. The author built the bridge among all these fields using an unified language.
This is a book about applied statistics. Theories and mathematics are covered in the appendices at the end of each chapter and the end of the book. A lot of examples from economics and social science are demonstrated in the book. Exercises are well organized and used to provide additional insights.
Highly recommend for applied statisticians.
Book Description
This new edition of this established textbook reflects the rapid developments in the field covering the vast research that has been conducted on panel data since its initial publication. The book is packed with the most recent empirical examples from panel data literature, for example, a simultaneous equation on Crime will be added to chapter 7, which will be illustrated with STATA. Data sets will be provided as well as the programs to implement the estimation and testing procedures described in the book on the web site. Additional exercises will be added to each chapter and their solutions will be provided on the web site.
The text has also 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.
Download Description
This new edition of this established textbook reflects the rapid developments in the field covering the vast research that has been conducted on panel data since its initial publication. The book is packed with the most recent empirical examples from panel data literature, for example, a simultaneous equation on Crime will be added to chapter 7, which will be illustrated with STATA. Data sets will be provided as well as the programs to implement the estimation and testing procedures described in the book on the web site. Additional exercises will be added to each chapter and their solutions will be provided on the web site. The text has also 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.
Customer Reviews:
Another dimension.......2005-11-07
The fact that Prof. Baltagi goes in deep detail through his own (an extensive) work must be seen as a plus to those interested in becoming involved in research (specially in hypothesis testing). It is unfrequent that an author provides a guided tour through the backstage of his research papers, and Baltagi should be congratulated for this honest effort, it help me considerably with my own research. Whether it serves the purposes of casual readers looking for a broad introduction, is debatable (there were no book around when I learned this), in my opinion it does it.
Basically flawed.......2004-08-11
I have not read the second edition of this book, but my experience of the first edition when reading for my economics doctorate was that it was not an easy book to use. In particular, it had a rather ideosyncratic view of the literature. Certainly, it is curious that there are two pages of references to the Author's work and less that one of Maddala, Arrelano, Bond, Pesaran and Smith combined.
I found that "Analysis of Panel Data" by Cheng Hsiao combined with a few choice papers was a more useful strategy. The first edition of Hsiao has been a classic since it was released in the mid eighties and dispite it being an Econometric Society monograph, is much clearer and easier to understand. It has now been updated to include dynamic and discrete response models and will, I believe, remain the classic Panel Data text for years to come, although I have not read Arellano's book.
Mistake.......2000-09-14
The first sentence of the first comment apparently confuses "mere" with "slight". Also, his judgement is too harsh. The book definitely deserves two stars.
It is not so bad after all.......2000-09-01
The review posted by the anonymous reader from CT seems a little too harsh to me. The book offers a decent overview over many interesting areas of panel data. In particular, one and two way error components are discussed, one chapter is devoted to hypotheses testing, heteroscedasticity and serial correlation and dynamic panel data models respectively. However it is true, that the authour does not provide much help to understand the literature which is just reproduced (often word by word from the papers!). The book is not recommended to someone who wants to read about Panel Data but doesn't have a lot of knowledge about the subject yet.
Still no acceptable book about Panel Data.......2000-08-30
To say that this book is scandalous would only be a mere exaggeration. Instead of clarifying the literature on Panel Data, the author just sums up some papers (often citing them word by word; why bother then buying a book? Just copy the articles!) without adding any value to them. Even worse, while summarizing, the essence of the papers often goes missing. The only value of the book consists of a quite complete reference list of the literature up to 1994. (However, the list is of course a little biased in favor of the author. He mentions every minuscule and unimportant publication of himself. One could almost get the impression that he contributed to Panel Data) Expecting a book that provides the main ideas and clarifies them together with a clear notation and proofs of the result, I was very disappointed with Badi Baltagi's book! Not recommended at all! (Unfortunately there is no alternative I know of!)
Book Description
This is the essential companion to Jeffrey Wooldridge's widely-used graduate text Econometric Analysis of Cross Section and Panel Data (MIT Press, 2001). Already established as a leading graduate econometrics text, the book offers an intuitive yet rigorous treatment of two methods used in econometric research, cross section and panel data techniques. The numerous end-of-chapter problems are an important component of the book, encouraging the student to use the analytical tools presented in the text. This manual contains answers to selected problems, new examples, and supplementary materials designed by the author. Users of the textbook will find the manual a necessary adjunct to the book.
Customer Reviews:
Extremely useful book.......2007-01-10
The solved exercises are an excellent study tool to accompany the book Econometric Analysis of Cross Section and Panel Data.
Average customer rating:
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Panel Data and Structural Labour Market Models (Contributions to Economic Analysis)
D.T. Mortensen ,
N.M. Kiefer , and
P. Jensen
Manufacturer: North Holland
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ASIN: 0444503196 |
Book Description
Panel Data and Structural Labour Market Models is the latest volume in a series of four, reporting on the original work of an international group of scholars with research interests in the performance of the labour markets that condition the dynamic labour market experiences of individual workers.
The book contains papers focusing on theoretical and empirical modelling of the labour market covering both wage equilibrium models and models for labour market transition. Contributions range from the theoretical or econometric through empirical structural methods and exploratory data analysis based on employer and employee level data.
Academic libraries, labour economists, labour and industrial relations research institutes and statistical agencies will find this a particularly useful piece of work.
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Panel Data Econometrics: Methods-of-Moments and Limited Dependent Variables
Myoung-jae Lee
Manufacturer: Academic Press
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Econometric Analysis of Cross Section and Panel Data
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Panel Data Econometrics (Advanced Texts in Econometrics)
ASIN: 0124406564 |
Book Description
Applied econometric research is concerned with the measurement of the parameters of economic relationships and with the prediction (by means of these parameters) of the values of economic variables
Dependent variable is the value of a function that is determined by the function and the value(s) chosen for its independent variable(s). The generalized method of moments (GMM) estimation has emerged over the last decade as providing a ready to use, flexible tool of application to a large number of econometric and economic models by relying on mild, plausible assumptions. Panel, or longitudinal, data, are data on constant experimental units over a period of time. Nonparametric methods are any of various inferential procedures whose conclusions do not rely on assumptions about the distribution of the population of interest.
This book uses a GMM approach to make its presentation of panel data methods for weak model assumptions ("semiparametric"). These assumptions are useful because they can offer general approaches and explain real problems. So while the subjects covered by this book are narrower than those appearing in a comprehensive book on panel data, the utility of the material (that is, the book's ability to make accessible practical computation and implementation methods) is higher.
An economic system typically consists of many interdependent variables and the relationships among them. In estimating the equations of such systems, econometricians frequently encounter an obstacle known as "the identification problem." The latter is most easily illustrated by reference to the process of determination of price and output in a market. To model this process the econometrician must develop a quantitative estimate of both the demand and supply functions. Typically the data used to estimate these functions are past observations of price and output determined by the points of intersection between the demand and supply curves. If, in the past, the supply curve has been shifting (due, say, to production cost changes) while the demand curve has remained fixed, the resultant intersection points trace out the demand function. If the demand curve has shifted (due, say, to income changes) while the supply curve has remained fixed, the intersection points trace out the supply curve. The most likely outcome is movement of both curves yielding a pattern of price, quantity intersection points from which the econometrician will be unable, without further information, to distinguish the demand curve from the supply curve or estimate the parameters of either. This is the identification problem.
Key Features
* Describes recent developments in panel-data econometrics
* Emphasizes estimation methods
* Focuses on practical implemention and computational feasibility of estimation methods
* Compares parametric and semiparametric approaches, highlighting advantages of new methods
* Provides distribution-free estimators for limited response models
* Includes standard programs with accompanying data sets on disk
* Presents computational steps and recent methods in panel data analysis
* Describes main theoretical ideas behind the generalized method of moments (GMM) estimation
Book Description
Panel data, which consist of information gathered from the same individuals or units at several different points in time, are commonly used in the social sciences to test theories of individual and social change. This book provides an overview of models that are appropriate for the analysis of panel data, focusing specifically on the area where panels offer major advantages over cross-sectional research designs: the analysis of causal interrelationships among variables. Without "painting" panel data as a cure all for the problems of causal inference in nonexperimental research, the author shows how panel data offer multiple ways of strengthening the causal inference process. In addition, he shows how to estimate models that contain a variety of lag specifications, reciprocal effects, and imperfectly measured variables. Appropriate for readers who are familiar with multiple regression analysis and causal modeling, this book will offer readers the highlights of developments in this technique from diverse disciplines to analytic traditions.
Book Description
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 combines methods 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, the specification 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 errors are 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.
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Solutions Manual for Econometrics
Badi H. Baltagi
Manufacturer: Springer
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Binding: Paperback
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Econometrics
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Matrix Algebra: Exercises and Solutions
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Schaum's Outline of Statistics and Econometrics
ASIN: 3540638962 |
Book Description
This Solutions Manual is to accompany the Springer textbook "Econometrics" by Badi H. Baltagi. The manual provides solutions to selected exercises from each chapter of the textbook.The empirical exercises illustrate the testing and estimation methodology using popular econometric software. Some SAS programs are provided to replicate the results. The book also takes the reader step by step through simple yet rigorous theoretical exercises. In addition, the manual has a set of empirical illustrations demonstrating some of the basic results of the textbook. The computer output and programs are given to help the reader reproduce these results. The Solutions Manual is an important complement to the textbook and helps guide the reader through difficult problems.
Books:
- Econometric Analysis of Cross Section and Panel Data
- Econometrics: A Modern Introduction (Addison-Wesley Series in Economics)
- Essentials of Corporate Finance (Mcgraw-Hill/Irwin Series in Finance, Insurance, and Real Estate)
- Fast Track to Waste-Free Manufacturing: Straight Talk from a Plant Manager (Manufacturing and Production)
- Financial Accounting: An Introduction to Concepts, Methods, and Uses
- Financial Management: Theory and Practice, 10th Edition
- Financial Markets and Institutions (5th Edition) (Addison-Wesley Series in Finance)
- Financial Reporting and Analysis (3rd Edition)
- Financial Reporting and Analysis (3rd Edition)
- Foundations of Financial Management (The Mcgraw-Hill/Irwin Series in Finance, Insurance, and Real Estate)
Books Index
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Time Series Analysis
