Decision-Making Using Complex Data
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This course will discuss a range of analytical techniques that can be used to answer key policy questions. Participants will learn how to measure the impact of policy and whether or not a particular policy improves individuals’ lives. The focus of the course will be on the assumptions, purpose and limitations of the techniques, rather than formulae and equations.
By using technical aspects that underpin impact evaluating approaches and focusing on use of intuition and examples this course will develop the ability to:
- assess the quality of data in research and Government reports
- understand the rationale of major contemporary approaches to the measurement of impact of Government policies
- critically assess the validity of causal claims in quantitative analysis
- determine the appropriate techniques to evaluate the impact of an event.
The aim of this course is to introduce and discuss a range of analytical techniques that can be used to answer key policy questions. The course will familiarise you with techniques that help target scarce resources, analyse the relationship between variables, use longitudinal data to understand change through time, and identify biases.
One of the key policy questions we focus on is whether or not a particular policy or program improves individual lives. This is a fundamental question that has relevance across many policy domains including social policy, economic policy, health, education, development assistance and many more. Such causal questions are surprisingly difficult to answer. We look at the main problem of causality in policy analysis – how to deal with selection. We then address some of the main techniques used to control unobserved heterogeneity, with a focus on their uses and limitations. The course is highly applied and we use examples from a range of policy domains to show how and when we can measure impact.