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How can we know if the policies and interventions implemented in low- and middle-income countries are making a difference, if they are really improving outcomes? This course provides the experimental and statistical tools needed to rigorously measure the effects of policies and programs, with a particular focus on questions of causal attribution, the design and conduct of randomized control trials and quasi-experimental methods, and estimation of impacts using regression techniques.
Identifying effective policies is a process of trial and error, innovation and experimentation, success and failure. This course provides the basic scientific and statistical tools needed to identify whether a policy or program is generating impact. Organized into modules, the course covers topics ranging from the attribution problem to what is meant by statistical significance (margin of error) to the analysis of data generated by a randomized control trial. The course also helps answer practical questions related to impact evaluation, such as how large of a sample is needed and what can be done when compliance with an experimental design is imperfect or when data is missing for part of the sample.
This course was created collaboratively by Georgetown University and the World Bank's Strategic Impact Evaluation Fund with support from the Georgetown Center for New Designs in Learning and Scholarship, Georgetown University Initiative of Innovation, Development and Evaluation (gui2de), and The Open Learning Campus of the World Bank Group.
