This course will provide a practical introduction to nonparametric and semiparametric estimation techniques.

Helpful textbook coverage can be found in:

*Applied nonparametric regression,*Wolfgang Hardle,Cambridge : Cambridge University Press, 1990*Density estimation for statistics and data analysis,*B.W. Silverman, London : Chapman and Hall, 1986.*Semiparametric regression for the applied econometrician,*Adonis Yatchew, Cambridge: Cambridge University Press, 2003.*Nonparametric curve estimation : methods, theory and applications,*Sam Efromovich,

New York : Springer, 1999.

### Lecture 1

Aims: Introduction to Nonparametric Regression (with simple Stata commands)

This will take place in the Computer Lab. A do-file for the class can be found here.

Slides are here.

### Lecture 2

Aims: More technical details on Kernel methods and the Curse.

Slides are here

Short exericse set is here.

### Lecture 3

Aims: Introduction to key Semiparametric methods (the partially linear model and single index model)

Slides are here