This course is designed for those who design policy experiments or demonstration projects, those who commission or manage projects which undertake evaluations (or impact assessments), or make decisions on the basis of the estimated impact of policies. It will introduce participants to the various empirical methods that can be used to estimate the impact of a specific policy intervention. The intention is not to teach participants how to estimate the impact of a specific policy intervention or programme but to give an understanding of the suitability of these methods given the nature of the policy under consideration and the available data.
Detailed statistical knowledge is not a pre-requisite.
Sessions will cover the following:
1. The impact evaluation problem, and how randomized experiments “solve” it
2. Methods that mimic an experiment: natural experiments, instrumental variables and the regression discontinuity design
3. Methods that control for confounding factors: multiple regression, matching and taking advantage of longitudinal data
There will also be a group session where participants will be asked to apply their knowledge to comment on the suitability of specific evaluation designs.
By the end of the course, participants will be able to:
Assess whether an actual or proposed design for a programme evaluation is likely to give reliable results, given the nature of the policy under consideration and the available data
Understand what factors to consider when the results from a programme evaluation are being used in policy-making