Bridging the gap between applied economists and theoretical nonparametric econometricians, this book explains basic to advanced nonparametric methods with applications.
Bridging the gap between applied economists and theoretical nonparametric econometricians, this book explains basic to advanced nonparametric methods with applications.
Daniel J. Henderson is the J. Weldon and Delores Cole Faculty Fellow at the University of Alabama, as well as a research fellow at the Institute for the Study of Labor (IZA) in Bonn, Germany, and at the Wang Yanan Institute for Studies in Economics, Xiamen University, in Xiamen, China. He was formerly an associate and Assistant Professor of Economics at the State University of New York at Binghamton. He has held visiting appointments at the Institute of Statistics, Université catholique de Louvain, in Louvain-la-Neuve, Belgium, and in the Department of Economics at Southern Methodist University in Dallas, Texas. He received his PhD in economics from the University of California, Riverside. His work has been published in journals such as the Economic Journal, the European Economic Review, the International Economic Review, the Journal of Applied Econometrics, the Journal of Econometrics, the Journal of Human Resources, the Journal of the Royal Statistical Society, and the Review of Economics and Statistics.
Inhaltsangabe
1. Introduction 2. Univariate density estimation 3. Multivariate density estimation 4. Inference about the density 5. Regression 6. Testing in regression 7. Smoothing discrete variables 8. Regression with discrete covariates 9. Semiparametric methods 10. Instrumental variables 11. Panel data 12. Constrained estimation and inference Bibliography Index.
1. Introduction; 2. Univariate density estimation; 3. Multivariate density estimation; 4. Inference about the density; 5. Regression; 6. Testing in regression; 7. Smoothing discrete variables; 8. Regression with discrete covariates; 9. Semiparametric methods; 10. Instrumental variables; 11. Panel data; 12. Constrained estimation and inference; Bibliography; Index.
1. Introduction 2. Univariate density estimation 3. Multivariate density estimation 4. Inference about the density 5. Regression 6. Testing in regression 7. Smoothing discrete variables 8. Regression with discrete covariates 9. Semiparametric methods 10. Instrumental variables 11. Panel data 12. Constrained estimation and inference Bibliography Index.
1. Introduction; 2. Univariate density estimation; 3. Multivariate density estimation; 4. Inference about the density; 5. Regression; 6. Testing in regression; 7. Smoothing discrete variables; 8. Regression with discrete covariates; 9. Semiparametric methods; 10. Instrumental variables; 11. Panel data; 12. Constrained estimation and inference; Bibliography; Index.
Rezensionen
'A clear and thorough treatment of nonparametric and semiparametric econometrics. The text will be valuable to empirical researchers, who can expand their methodological toolkits without resorting to difficult journal articles. Even advanced topics, such as nonparametric instrumental variables and nonparametric models with panel data, are treated at an accessible level.' Jeffrey M. Wooldridge, Michigan State University
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