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. This book describes recent developments in panel-data econometrics. It emphasizes estimation methods. It focuses on practical implemention and computational feasibility of estimation methods. It compares parametric and semiparametric approaches, highlighting advantages of new methods. It provides distribution-free estimators for limited response models. It includes standard programs with accompanying data sets on disk. It presents computational steps and recent methods in panel data analysis. It describes main theoretical ideas behind the generalized method of moments (GMM) estimation.
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"This is a useful reference work that brings together many recent developments in estimation with panel data. The emphasis on semiparametric and limited dependent variable methods provides a good complement to other recent books on the subject."
-Arthur Lewbel, Boston College
"Professor Lee has combined accessible technical discussions of modern panel data treatments with their empirical implementation in models containing limited dependent variables. It arrives on the scene soon after our profession recognized the importance of such models by awarding of the 2000 Nobel Prize in Economics to D. McFadden and J. Heckman. A must for any serious graduate student who intends to carry out modern research in econometric theory and/or empirical research in the social sciences."
-Robin C. Sickles, Professor of Economics and Statistics, Rice University
This practical, accessible, detailed examination of recent developments in panel data econometrics highlights semiparametric approaches, providing distribution-free estimators for limited response models. It offers detailed accounts of delicate subjects, such as panel data sample selection models, and is well supplemented by examples and empirical exercises. For both empirical researchers who wish to apply panel data methods and the person who is serious about using semi-parametric methods in panel data analysis, Professor Lee's comprehensive examination of recent estimation methods, his practical clues and insights, and his discussions of computational feasibility separate his book from other econometrics texts.
* Focuses on practical implementation 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 innovative 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
Department of Economics, Sungkyunkwan University, Seoul, South Korea
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