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.

A short problem set for the class is here.

Lecture 1

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

A do-file for the class can be found here.

Slides are here.

Lecture 2

Aims: More technical details on Kernel methods and Semiparametric Methods.

Slides are here. 

Lecture 3

Aims: Application to Regression Discontinuity Design.

Slides are here.

D. Lee and T. Lemieux (2010), ‘Regression Discontinuity Designs in Economics’, Journal of Economic Literature

G. Imbens and T. Lemieux (2008), ‘Regression Discontinuity Designs: A Guide to Practise’, Journal of Econometrics


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