Search results for ""author jeffrey scott racine""

A comprehensive, up-to-date textbook on nonparametric methods for students and researchersUntil now, students and researchers in nonparametric and semiparametric statistics and econometrics have had to turn to the latest journal articles to keep pace with these emerging methods of economic analysis. Nonparametric Econometrics fills a major gap by gathering together the most up-to-date theory and techniques and presenting them in a remarkably straightforward and accessible format. The empirical tests, data, and exercises included in this textbook help make it the ideal introduction for graduate students and an indispensable resource for researchers.Nonparametric and semiparametric methods have attracted a great deal of attention from statisticians in recent decades. While the majority of existing books on the subject operate from the presumption that the underlying data is strictly continuous in nature, more often than not social scientists deal with categorical data—nominal and ordinal—in applied settings. The conventional nonparametric approach to dealing with the presence of discrete variables is acknowledged to be unsatisfactory.This book is tailored to the needs of applied econometricians and social scientists. Qi Li and Jeffrey Racine emphasize nonparametric techniques suited to the rich array of data types—continuous, nominal, and ordinal—within one coherent framework. They also emphasize the properties of nonparametric estimators in the presence of potentially irrelevant variables.Nonparametric Econometrics covers all the material necessary to understand and apply nonparametric methods for real-world problems.

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This Volume of "Advances in Econometrics" contains a selection of papers presented initially at the 7th Annual Advances in Econometrics Conference held on the LSU campus in Baton Rouge, Louisiana during November 14-16, 2008. The theme of the conference was 'Nonparametric Econometric Methods', and the papers selected for inclusion in this Volume span a range of nonparametric techniques including kernel smoothing, empirical copulas, series estimators, and smoothing splines along with a variety of semiparametric methods. The papers in this Volume cover topics of interest to those who wish to familiarize themselves with current nonparametric methodology. Many papers also identify areas deserving of future attention. There exist survey papers devoted to recent developments in nonparametric nance, constrained nonparametric regression, miparametric/nonparametric environmental econometrics and nonparametric models with non-stationary data. There exist theoretical papers dealing with novel approaches for partial identification of the distribution of treatment effects, xed effects semiparametric panel data models, functional coefficient models with time series data, exponential series estimators of empirical copulas, estimation of multivariate CDFs and bias-reduction methods for density estimation. There also exist a number of applications that analyze returns to education, the evolution of income and life expectancy, the role of governance in growth, farm production, city size and unemployment rates, derivative pricing, and environmental pollution and economic growth. In short, this Volume contains a range of theoretical developments, surveys, and applications that would be of interest to those who wish to keep abreast of some of the most important current developments in the field of nonparametric estimation.

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Until now, students and researchers in nonparametric and semiparametric statistics and econometrics have had to turn to the latest journal articles to keep pace with these emerging methods of economic analysis. Nonparametric Econometrics fills a major gap by gathering together the most up-to-date theory and techniques and presenting them in a remarkably straightforward and accessible format. The empirical tests, data, and exercises included in this textbook help make it the ideal introduction for graduate students and an indispensable resource for researchers. Nonparametric and semiparametric methods have attracted a great deal of attention from statisticians in recent decades. While the majority of existing books on the subject operate from the presumption that the underlying data is strictly continuous in nature, more often than not social scientists deal with categorical data--nominal and ordinal--in applied settings. The conventional nonparametric approach to dealing with the presence of discrete variables is acknowledged to be unsatisfactory. This book is tailored to the needs of applied econometricians and social scientists. Qi Li and Jeffrey Racine emphasize nonparametric techniques suited to the rich array of data types--continuous, nominal, and ordinal--within one coherent framework. They also emphasize the properties of nonparametric estimators in the presence of potentially irrelevant variables. Nonparametric Econometrics covers all the material necessary to understand and apply nonparametric methods for real-world problems.

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