Applied Nonparametric Econometrics

Applied Nonparametric Econometrics

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Daniel J. Henderson, Christopher F. Parmeter
Cambridge University Press
Edition: Illustrated, 1/19/2015
EAN 9781107010253, ISBN10: 110701025X

Hardcover, 380 pages, 25.4 x 17.8 x 2.2 cm
Language: English

The majority of empirical research in economics ignores the potential benefits of nonparametric methods, while the majority of advances in nonparametric theory ignore 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.

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