Applied Nonparametric Econometrics

by Daniel J. Henderson, Christopher F. Parmeter

Overview

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.

Product Details

ISBN-13:	9781107010253
Publisher:	Cambridge University Press
Publication date:	01/19/2015
Edition description:	New Edition
Pages:	380
Product dimensions:	6.89(w) x 10.12(h) x 0.98(d)

About the Author

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.

Christopher F. Parmeter is an Associate Professor at the University of Miami. He was formerly an Assistant Professor in the Department of Agricultural and Applied Economics at Virginia Polytechnic Institute and State University. He was also a visiting scholar in Dipartimento di Studi su Politica Diritto e Societa at the University of Palermo. He received his PhD in economics from the State University of New York, Binghamton. His research focuses on applied econometrics across a broad array of fields in economics, including economic growth, microfinance, international trade, environmental economics, and health economics. His work has been published in journals such as the Economic Journal, the European Economic Review, Health Economics, the Journal of Applied Econometrics, the Journal of Econometrics, the Journal of Environmental Economics and Management, and Statistica Sinica.

Table of Contents

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.

Editorial Reviews

"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

"Taking theory to data is difficult for most students, but this book provides substantial help by providing cogent explanations of practical considerations, including how well methods that work "in theory" might be expected to work with real data in the quantities that researchers might have available."
Paul W. Wilson, Clemson University

"Daniel Henderson and Chris Parmeter have provided a modern survey of nonparametric econometrics. Newcomers will enjoy their applications-oriented introduction to this growing field. Theorists will find a compact survey of the most important foundations. Researchers of all sorts will want to add this valuable resource to their libraries."
William Greene, Stern School of Business, New York University

"This well-written textbook represents a rigorous yet accessible introduction to nonparametric methods, one that makes clear the importance of these techniques for empirical research. Henderson and Parmeter have performed a valuable service for students throughout the social sciences."
Steven N. Durlauf, University of Wisconsin

"Nonparametric econometric methods have by now become quite common in applied research, yet, as in almost all areas of research, theory precedes practice. The current hands-on approach of the book comes to fill the gap and offer the applied researcher a manual of how to properly use these methods without compromising rigor. It will complement other more theoretical books on the subject and as such it will prove very useful to many practitioners and students alike."
Thanasis Stengos, University of Guelph

"The authors advertise right at the beginning that this book was written to help bridge the gap between applied economists and theoretical nonparametric econometricians. Having worked on both sides I can say that this book keeps this promise in almost all aspects: the way it is written, the selection of topics, and the selection of methods."
Stefan Sperlich, Université de Genève

"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

From the Publisher