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Dr Mylene Lagarde COW 3.02

This course is available on the Executive MSc in Health Economics, Outcomes and Management in Clinical Sciences and Executive MSc in Health Economics, Policy and Management. This course is not available as an outside option.

Clinicians have long used experimental methods (randomized trials) to test the efficacy of drugs and other medical treatments. Whilst economists and other social scientists have used alternative quasi-experimental  methods to determine the causal effects of policies, they are increasingly using the experimental approach to evaluate the effects of a range of public policies.

The objective of this course is to teach students about the different quasi-experimental approaches and to unpack the principles of experimental (randomised) methods for evaluating policies, programmes, and interventions relevant to health policy. This course will draw on examples from LMICs (low and middle income countries).

This course will provide an overview of the principles and models of evaluation, including the importance of developing a theory of change. We will then provide an overview the main quasi-experimental designs for evaluating health interventions and policies. Next we will focus on key technical principles of experimental approaches (including issues of statistical power and sample size calculation), and discuss the nature and impact of a range of problems (e.g. attrition, spillovers, compliance) to the internal validity of a study design. Data and measurement considerations for quantitative studies will be discussed. The course will conclude with practical and ethical issues when undertaking randomised evaluations.

This course will be delivered as a combination lectures and seminars, totalling a minimum of 20 hours. As well as access to lectures, students will work in small groups to develop their research design during seminars. 

1,000 word outline

Glennerster, R., & Takavarasha, K. (2013). Running Randomized Evaluations (STU - Student edition ed.): Princeton University Press.

Gertler, Paul J., Sebastian Martinez, Patrick Premand, Laura B. Rawlings, and Christel M. J. Vermeersch. (2016) Impact Evaluation in Practice, second edition. Washington, DC: Inter-American Development Bank and World Bank. doi:10.1596/978-1- 4648-0779-4.

Cartwright, N. & Hardie, J. (2012). Evidence-Based Policy: A practical guide to doing it better. Oxford, UK: Oxford University Press.

Gerber, A. S., & Green, D. P. (2012). Field Experiments: Design, Analysis and Interpretation. New York, NY: Norton.

1 x Protocol (100%) 3,000 words max