Policy Evaluation Beyond Averages: Distributional Impact Analysis.

评估社会和经济政策的影响是决策者关注的中心问题。然而，这些政策的评估方式往往是无效的，这意味着一项政策的实施可能不会使社会中正确的人受益，甚至可能伤害那些它想要帮助的人。这项工作将使政策制定者能够在制定和实施政策方面做出更加知情和准确的决策，这意味着，随着政策能够更准确地设计出来，以满足正确人群的正确需求，整个社会将受益。绝大多数影响研究使用的诊断工具侧重于一项政策的平均收益或损失。这是一个潜在的重要缺点，因为在实践中，大多数人不会得到平均收益或损失。一项政策的平均效果并不能说明谁从一项政策中损失谁从中受益，而且影响的方向和幅度可能在个人之间有很大差异。在这项研究中，我开发了量化技术，允许更细致入微的政策评估。我打算开发一种统计工具，使社会科学家和政策制定者能够超越计算平均效应的范畴，同时确保他们的分析能够捕捉到所研究政策的不同效应。通过允许对个体进行差异化的影响评估，我对因果分析的新观点将提供创新的方法，有助于改善资源分配和针对特定人群的政策设计，并有可能实现深远的效益。我将侧重于三个具体任务：1.；生产工具捕捉因果效应的多样性。我将介绍因果分析和政策评估的统计方法，使研究人员和政策制定者能够揭示政策和治疗的复杂性和多样性影响。通过推广经典方法（所谓的工具变量方法），我将建立新的理论结果，为我的方法的合理应用所必需，并将用几个领域的具体例子来说明这些结果，如经济学和健康科学。推进细致入微的量化政策评估。我的方法将改变定量政策评估的做法，允许政策制定者和社会科学家确定谁从一项政策或治疗中受益，谁又损失。他们将能够制定细微而准确的政策诊断，减少政策实施的内在风险。我将访问主要的政策导向机构，并与科学界以外的从业者合作，以展示我的方法如何使他们能够解决一系列新的政策问题，并实现更细致入微的政策诊断。使我的方法可用。我将通过一个免费的开源软件为从业者提供实现我的方法所必需的技术和文档。我还将通过在领先的学术和非学术机构组织研讨会和演讲，直接向从业者宣传我的方法。

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.