Nonparametric and Semiparametric Methods and Applications

Instructor(s):

This course offers an introduction to standard and recent developments in nonparametric and semiparametric methods, with particular emphasis on empirical work in social sciences. Topics to be covered include nonparametric density and regression estimation, and simple semiparametric methods for semi-linear models, additively separable models, and average derivatives. Examples and applications will focus on program evaluation and treatment effects estimation.

Nonparametric and semiparametric methods allow for greater flexibility in data analysis, which can be very important for the type of research conducted in social sciences where simple/parametric models do not always adequately capture the underlying statistical features of interest. Course participants will learn how to leverage these techniques for their own research. The course will focus on implementation of the methods and interpretation of the results, with the underlying statistical theory introduced only briefly when strictly necessary. The course will be self-contained: all topics and concepts are introduced and explained along the training classes. The course is structured around a combination of lectures and computing exercises. The lectures will highlight the intuition and strengths of nonparametric and semiparametric methods, with less focus on econometric technicalities. Computer exercises will apply these methods to both real and simulated data to build familiarity with the concepts introduced in class. All course materials, including data and computer codes, will be made available in advance. The course will discuss nonparametric and semiparametric tools available both in R and Stata, so they will be used interchangeably.

Prerequisites: Basic working knowledge of statistics, econometrics, and program evaluation. A very basic knowledge of statistical software (R or STATA) will also be helpful.

Fee: Members = $1300; Non-members = $2600

Tags: Nonparametrics, semiparametrics, program evaluation, treatment effects

Course Sections