In this presentation, I share findings from a working paper in which I apply Process Tracing as a novel ‘Small n’ method for evaluating Outcomes-Based Contracts such as Social Impact Bonds. Focusing on the case of the Greater Manchester Homes Partnership (GM Homes), I ask: In what ways, and through which mechanisms, did GM Homes produce systems-level effects? By taking a Process Tracing approach, the evaluation is able to account for the complexity of the GM Homes program, which evolved over time and was delivered in a system where many factors contributed to outcomes that were achieved. Through this case study, I seek to demonstrate how ‘Small n’ methods may be useful for evaluating future Outcomes-Based Contracts - or other innovative policy tools - by offering new evidence-based insights without relying on large sample sizes, counterfactuals, or statistical controls.

Chapter 7 in the book “Social and Sustainable Finance for Social Innovation and Sustainable Development Goals (SDGs),” this paper provides novel evidence on the benefits and costs of Development Impact Bonds (DIBs) as a form of results-based funding. Analyzing data from seven recent DIBs in low- and middle-income counties, the chapter finds that the DIB’s provision of outcomes-focused risk capital helped enable a collaborative and adaptive approach to service delivery. This approach then generated evidence of blended returns and increased organizational capacity, as well as spurred cultural shifts towards more sustainable outcomes-based working. The chapter also uncovers a range of costs and challenges in DIB implementation – especially around garnering institutional buy-in, negotiating contract terms, and managing changing relationships.

In this presentation, I explore whether Social Outcomes Contracts can be designed to impact their wider service delivery systems. Taking a novel process tracing approach, I evaluate the case of the Greater Manchester Homes Partnership (GM Homes) and test three hypotheses related to asset-based working, innovation, and collaboration. Analyzing evidence from 21 interviews, primary documents, user data, and secondary literature, I find compelling evidence that GM Homes helped generate systems-level effects, particularly in the areas of housing provider policies and dual diagnosis services. Findings further suggest that asset-based working was the most influential causal mechanism, but that adaptive management and large-scale collaborative working were vital to enabling this approach.

With college students increasingly struggling to afford basic needs, emergency aid (EA) programs seek to help students overcome short-term financial hardships and improve longer-term academic success by providing small one-time grants. However, EA programs often face trade-offs between minimizing administrative burden and targeting limited resources to the highest-need students. We explore these trade-offs by analyzing the learning, psychological, and compliance costs that students face when applying for EA. Using data from two EA programs in Los Angeles, we find that the programs were able to ease burdens, especially compliance costs, and that the vast majority of EA went to high-need students.

This presentation explores how Emergency Aid (EA) programs can be designed to reach those students most in need while responsibly managing limited budgets and without imposing overly-burdensome application requirements. The study explores the impacts of intentional administrative easing through the examination of two Los Angeles-based EA programs – one at the University of Southern California (USC) and one at the Los Angeles Community College District (LACCD) – both iteratively designed to lower the burdens faced by students in accessing aid.

In this poster presentation, we discuss the application of Process Tracing, which assumes causation is generative, and Qualitative Comparative Analysis (QCA) with assumes causation is multiple, to evaluate the impact of different elements of a Social Outcome Contract. We compare how these two different approaches were used to evaluate the same Social Outcome Contract, offering insights into the potential of using small ‘n’ methodologies for future analyses.

This presentation discusses an ongoing study which asks: What do stakeholders view as the Theories of Change through which Development Impact Bonds(DIBs) affect social change past the terms of the contract? The study answers these questions through interviews with DIB stakeholders. The DIB sample was drawn from the GoLab Impact Bond Dataset, which includes 13 DIBs. The presentation draws on data collected through stakeholder interviews conducted thus far, which prompt individuals to reflect on their decisions to participate in DIBs as well as on their experiences and lessons learned as participants.

While many commentators recognize the potential for Social Impact Bonds (SIBs) to encourage innovation, empirical evidence is less clear cut. We argue that for SIBs to realize their full potential as incubators of innovation, they need to incorporate a stronger element of co-creation and strengths-based working. We analyze four UK SIBs as case studies and find that strengths-based service delivery models and co-production helped catalyze early-stage innovation, although evidence of co-creation was limited. Our findings suggest that SIBs can support innovation by providing greater autonomy for service providers, shifting risk to investors, and offering long-term, flexible funding.

In this presentation, we discuss the application of Process Tracing, which assumes causation is generative, and Qualitative Comparative Analysis (QCA) with assumes causation is multiple, to evaluate the impact of different elements of a Social Outcome Contract. We compare how these two different approaches were used to evaluate the same Social Outcome Contract, offering insights into the potential of using small ‘n’ methodologies for future analyses.

Outcomes-Based Commissioning (OBC) – for example, Pay for Success (in the US) or Payment by Results (in the UK) – has been suggested as a way to provide ‘more’ social services for ‘less’ public resources. Using data from the Social Finance UK Database, this paper evaluates whether Social Impact Bonds (SIBs) align with the theoretical predictions of social innovation. The results show limited evidence that SIBs facilitate private capital injections into social goods production but do contribute to parts of the social innovation process, such as piloting and scaling.