KAFP 6535 - Policy Analysis and Policy Evaluation - Intermediate

How do we effectively reduce early dropout from education systems? How can trust be (re)built in the state in areas where its reach is limited? What is the impact of implementing a universal basic income in high income countries? How can interventions address the material and nonmaterial incentives that contribute to participation in crime and violence? What programmes are more effective at tackling homelessness? How do we promote more women to join STEM fields?

Policy making is full of pressing, deep, and complex questions. Many of which have multiple potential good solutions. Unfortunately, time and resources are always limited and we need to choose. And the stakes of choosing correctly are high. How to choose among different policy options? How do we decide what programme or policy to implement? This course aims to equip you with a tool to make such decisions: science.

In this course we will work to understand how science can be put at the service of policy making. The aim of public policy evaluation is to understand the causal effect of policies. This course will provide an overview of the key concepts and techniques of causal inference. The aim of the course is twofold. First, to give students a solid understanding of why establishing the casual effect of a program X on an outcome Y is a hard problem (and why our every-day intuition and data can sometimes fail us). Second, to give students the tools to become critical consumers of scientific evidence and an understanding of how they can use this tool to design and implement policies.

To do so, we will introduce different research designs (including, selection on observables, randomized control trials, regression discontinuities, and difference-in-differences), discussing the identifying assumptions behind these designs and the conditions under which these assumptions are most likely to hold. To do all of this, we will use mathematical abstraction. We will not use statistical software but focus instead on the intuitions behind research designs. Throughout, we will use specific examples of policy evaluations to build intuition and encourage future policy-makers to design policy in a way that allows for rigorous evaluation

Arantxa Rodríguez-Uribe works at Paris School of Economics at the laboratory of public policy evaluation J-PAL. Her research agenda lies at the intersection of development and conflict. In particular, she focuses on understanding the long-run consequences of criminal governance, territorial control, and how governments can manage and mitigate these. Her regional expertise is Latin America. She is currently working on evaluating the effect of different policies aimed at reducing recruitment by gangs in Colombia. She holds a Master in Public Administration by the London School of Economics and a Ph.D. in Political Science from Princeton University. Before starting her Ph.D., she worked at Innovations for Poverty Action in Colombia where she worked on different projects on criminal governance.

• First, a mid-term exam will amount to 40% of your grade.
• Second, a group project due in December making up for the remaining 60% of your grade.