Policy Evaluation Beyond Averages: Distributional Impact Analysis.

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Assessing the impact of social and economic policies is a central concern for policymakers. However the way those policies are evaluated is often not effective, which means that a policy can be put in place that does not benefit to the right people in society, or might even harm those it is meant to help. This work will enable policymakers to make much more informed and accurate decisions in relation to developing and implementing policy, meaning that society as a whole will benefit as policy can be more accurately be designed to meet the right needs of the right people.The diagnostic tools employed by the vast majority of impact studies focus on average gains or losses from a policy. This is a potentially important shortcoming since, in practice, most individuals will not receive the average benefit or loss. The average effect of a policy is not informative about who loses and who benefits from a policy, and both the direction and magnitude of the effect may vary substantially across individuals. In this research, I develop quantitative techniques which allow for more nuanced policy evaluation. I intend to produce a statistical tool that will enable social scientists and policymakers to go beyond calculating average effects, while ensuring that their analysis captures the diverse effects of the policy under study.By allowing for differentiated impact evaluation across individuals, my novel perspective on causal analysis will provide innovative methods that will help improve allocation of resources and the design of policies targeted at specific populations, and has potential to achieve far-reaching benefits. I will focus on three specific tasks:1. Producing tools capturing the diversity of causal effects. I will introduce statistical methods for causal analysis and policy evaluation that allow for researchers and policymakers to uncover the complexity and diverse impacts of policies and treatments. By generalising a classical method (the so-called instrumental variables method), I will establish new theoretical results necessary for the sound application of my approach, and will illustrate these results with concrete examples from several fields, such as economics and health sciences.2. Promoting nuanced quantitative policy evaluation. My approach will change the practice of quantitative policy evaluation by allowing policymakers and social scientists to determine who benefits and who loses from a policy or treatment. They will be able to formulate nuanced and accurate policy diagnostics reducing the risks inherent to policy implementation. I will visit leading policy-oriented institutions, and collaborate with practitioners outside the scientific community in order to demonstrate how my methods will allow them to address a range of new policy questions and achieve more nuanced policy diagnostics.3. Making my methods available. I will provide practitioners with the technology and documentation necessary for the implementation of my methods through a freely available and open source software. I will also advertise my methods directly to practitioners through the organisation of workshops and presentations in leading academic and nonacademic institutions.