This course deals with the econometric and statistical tools that have been developed to estimate the causal impact on one or more outcomes of interest of any generic 'treatment' - from government programmes, policies or reforms, to the returns to education, the impact of unionism on wages, or of smoking on own and children's health.

This is a PEPA masterclass presented by Petra Todd (University of Pennsylvania).

This course will examine econometric methods for evaluating effects of program interventions. Typical interventions that might be of interest include job training or other active labor market programs, education programs (such as school subsidy programs), or health programs.

The first part of the course will consider methods for ex ante evaluation, that is, methods for evaluating programs that do not yet exist or for evaluating alternative versions of existing programs. These methods usually specify and estimate behavioral models and use the models in assessing the effects of alternative programs or policies. The course will also examine a variety of methods for ex post evaluation that are applicable after the program has been implemented when data are available on persons who participated in some program and on people who did not participate in the program. These methods include random assignment, regression estimators, control function estimators, matching estimators, instrumental-variables based methods, regression-discontinuity approaches, bounding methods and quantile estimators. We will consider the behavioral assumptions needed to justify various approaches and the different parameters that can be identified.

It is helpful preparation for this course to have some background in nonparametric estimation (such as kernel density and kernel or local linear regression approaches), but we will spend some time reviewing these topics.