Nonparametric Econometrics

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

Extra Lectures on Structural Estimation

Introduction to Different Approaches

Slides.

Overview of Key Structural Methods

  • A. Adams, D. Clarke and S. Quinn, ‘Microeconometrics and MATLAB: An Introduction’, Chapters 3 and 4
  • L. Lockwood, ‘Incidental Bequests‘, 2017

Slides

Density Estimation

Slides.