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


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


Density Estimation