Applied Nonparametric Econometrics

Bridging the gap between applied economists and theoretical nonparametric econometricians, this book explains basic to advanced nonparametric methods with applications.

Daniel J. Henderson (Author), Christopher F. Parmeter (Author)

9780521279680, Cambridge University Press

Paperback, published 12 January 2015

380 pages, 81 b/w illus. 34 tables
25.1 x 17.8 x 2.8 cm, 0.73 kg

'The aim of this book is to teach nonparametric methods to applied economists. The book does an excellent job of achieving this objective. The mix of rigor and intuition is perfect, and the availability of software to go with the book makes it easy to implement the techniques being taught.' Peter Schmidt, Michigan State University

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
Bibliography
Index.

Subject Areas: History of mathematics [PBX], Applied mathematics [PBW], Economic statistics [KCHS], Econometrics [KCH], Economics [KC]