Applied Nonparametric Econometrics
by Daniel J. Henderson, Christopher F. Parmeter
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.
