Applied Nonparametric Econometrics
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Applied Nonparametric Econometrics
Author: Daniel J. Henderson
language: en
Publisher: Cambridge University Press
Release Date: 2015-01-19
The majority of empirical research in economics ignores the potential benefits of nonparametric methods, while the majority of advances in nonparametric theory ignores the problems faced in applied econometrics. This book helps bridge this gap between applied economists and theoretical nonparametric econometricians. It discusses in depth, and in terms that someone with only one year of graduate econometrics can understand, basic to advanced nonparametric methods. The analysis starts with density estimation and motivates the procedures through methods that should be familiar to the reader. It then moves on to kernel regression, estimation with discrete data, and advanced methods such as estimation with panel data and instrumental variables models. The book pays close attention to the issues that arise with programming, computing speed, and application. In each chapter, the methods discussed are applied to actual data, paying attention to presentation of results and potential pitfalls.
Nonparametric Econometrics
This is a graduate textbook for econometricians and statisticians containing developments in the field. It emphasises nonparametric methods for real world problems containing the mix of discrete and continuous data found in many applications.
Applied Nonparametric Regression
Author: Wolfgang Härdle
language: en
Publisher: Cambridge University Press
Release Date: 1990
This is the first book to bring together in one place the techniques for regression curve smoothing involving more than one variable.