Social Interactions and the Optimal Design of Welfare Systems

关于提供公共服务，无论是在教育、保健、扶贫还是其他方面，无论是在发达国家还是在发展中国家，服务的质量都与数量一样重要。这些服务是由教师、医生、护士或社会工作者（例如）提供的，讨论服务质量意味着讨论他们的招聘和表现。我们的项目在福利系统中研究这一点。我们专注于社会工作者（SW）质量的重要性，他们所服务的家庭，以及如何重新设计分配的SW家庭，以提高系统的整体efficiency.We检查的社会计划，智利团结（CS），针对最贫穷的2.5%智利人，并概括了其他情况下的经验教训。我们还提供了新的统计和经济工具，以解决我们分析中的重要和具有挑战性的问题：如何衡量社会工作质量，如何考虑贫困家庭的选择和行为中的社会互动，如何最佳地将社会工作分配给有或没有社会互动的家庭。社工对他们所服务的家庭的结果有什么影响？是什么决定了它们的有效性？每个家庭的SW选择有多重要？大多数评估福利服务的研究忽略了提供质量，主要是因为质量难以衡量。然而，提供者之间的质量差异可能会导致其影响的巨大差异。由于难以收集相关的，可观察的输入为基础的质量措施，研究人员已经转向基于性能的措施。最明显的例子是教育，教师增值（VA）估计作为衡量教师质量的一个指标已经获得了吸引力。教师VA衡量的是由特定教师授课的儿童的平均学习情况。在这个项目中，我们将产生第一个估计的SW VA智利福利计划，针对社会最贫困的成员（收入分配的底部2.5%）。我们认识到，社会工作者对家庭生活的几个方面起作用。因此，我们将根据不同的结局计算VA，并评估SW在结局方面的专业化程度。社会项目参与的溢出效应有多大？它们通过哪些机制运作？溢出效应如何影响社会项目的设计和目标定位？典型的社会方案评价侧重于个别影响。然而，人们越来越担心社会方案的影响远远超出了个人。从接受治疗的个人到社区其他成员的可能溢出效应越来越多地被纳入计划评估，甚至影响了他们的设计。在反贫困计划的背景下研究溢出效应尤其合适。社会互动可能会影响这些方案的实施（例如，通过潜在的耻辱感，或通过信息共享），以及它们对穷人生活的影响。然而，研究这种溢出效应的经验模型相对有限，迄今为止忽略了同一群体成员之间相互作用产生的反馈效应。反馈效应很有意思，因为它们可以扩大或削弱方案的影响，可能导致参与和不参与的陷阱。我们建立在最近的计量经济学工作，这些主题，以确定和估计模型与社会相互作用。我们如何在社会互动的情况下量化SW VA？交互作用如何改变SWs在家庭中的最优分配？将这些问题放在一起，并在存在溢出的情况下重新检查SW VA的计算是很自然的。在这种情况下，一个软件的影响可以远远超出其对目标家庭的结果的影响。这种类型的社会互动可以影响家庭和SW的最佳匹配。重要的不仅是这种匹配，还有它通过网络传播的方式。

Regarding the provision of public services, whether in education, health, poverty alleviation, or others, quality of service is as important as quantity in both developed and developing nations. Those services are provided by teachers, doctors, nurses, or social workers (for example), and discussing quality of services means discussing their recruitment and performance.Our project studies this within the welfare system. We focus on the importance of social worker (SW) quality for the families they serve, and on how to redesign the allocation of SWs to families to improve the overall effectiveness of the system.We examine a social programme, Chile Solidario (CS), targeting the poorest 2.5% Chileans, and generalise the lessons learned to other contexts. We also provide new statistical and economic tools to address important and challenging issues in our analysis: how to measure SW quality, how to account for social interactions in the choices and behaviours of poor families, how to optimally allocate SWs to families with or without the presence of social interactions across families.1. What difference do SWs make to the outcomes of the families they serve? What determines their effectiveness? How important is the selection of SWs for each family?Most studies evaluating welfare services ignore the provision quality, mainly because quality is difficult to measure. Yet, quality differences between providers may drive large differences in their impact. Because of the difficulty in collecting relevant, observable input-based quality measures, researchers have turned to performance-based measures. The most glaring example is education, where teacher value added (VA) estimates have gained traction as a measure of teacher quality. Teacher VA measures the average learning of children taught by a particular teacher. In this project we will produce the first estimates of SW VA for a Chilean welfare program targeting the poorest members of society (bottom 2.5% of the income distribution). We recognise that SWs operate on several dimensions of families' lives. Therefore, we will compute VA in terms of different outcomes and will assess the extent to which SWs specialise across outcomes.2. How large are spillovers in social program participation? Through which mechanisms do they operate? How do spillovers affect the design and targeting of social programs?Typical social programme evaluations focus on individual impacts. There is however increasing concern that social programs have impacts well beyond the individual. Possible spillovers from treated individuals to other members of the community have been increasingly added into program evaluations, and even influenced their designs. It is particularly fitting to examine spillovers in the context of anti-poverty programs. Social interactions may influence both the take up of such programs (say, through the potential of stigma, or through the sharing of information), and their impacts on the lives of the poor. The empirical models studying such spillovers are relatively limited though, so far ignoring feedback effects generated by interactions between members of the same group. Feedback effects are interesting because they can amplify or dampen programme impacts, possibly leading to participation and non-participation traps. We build on recent econometric work on these topics to identify and estimate models with social interactions.3. How do we quantify SW VA in the presence of social interactions? How do interactions change the optimal allocation of SWs to families? It is natural to put these questions together and re-examine the calculation of SW VA in the presence of spillovers. In this context, the impact of a SW can go well beyond its impact on the outcomes of the targeted family. Social interactions of this type can affect the optimal match of families and SW. What matters is not only this match, but also the way it spreads through the network.