Whose Benefits Matter?: Case of Cost-Benefit Analysis of Home Visiting Programs

Abstract Information: Cost-Benefit Analysis is the leading evidence-based method for guiding decisions about whether a government program or policy improves the well-being of society. There has been significant research on the benefits of social programs targeting young children, which shows that the benefits of early childhood programs such as Home Visiting Programs and Preschool programs far outweigh the costs of these programs. The typical approach to conducting benefit-cost analysis considers the societal benefits, i.e., the benefits for all members of the society. However, should benefits to everyone be weighed equally? We may disaggregate the benefits of a program to (a) the intended beneficiaries, (b) the taxpayers or “government savings,” and (c) to the public at large. In the case of early childhood programs for children from low-income families, studies have reported that the benefits for the second and third categories are far larger than the first category. So, how does the distribution of benefits impact the decision to fund the program? In this study, using a case of economic evaluations of Home Visting programs, I discuss the implications of restricting the calculation of benefits to certain stakeholders while excluding others. I discuss, two new financial approaches - Social Impact Bonds and Data-Driven Philanthropy, where benefits to only a particular category matter. Social Impact Bond deals compare the costs of expanding services to the benefits measured solely in terms of government cost savings. Whereas, with data-driven philanthropy, only the benefits received by members of low-income communities matter. I draw on the existing economic evaluations of Home Visiting Programs to disaggregate the benefits for each category. I find that even after restricting the definition of benefits in these ways, the benefits of Home Visiting Programs outweigh the costs of the program, making it a worthwhile investment for Social Impact Bond projects as well data-driven philanthropy endeavors. Finally, I suggest that data-driven philanthropy can help integrate concerns about equity into benefit-cost analysis and help target resources to communities most in need.

Relevance Statement: Early childhood development (ECD) is a critical period of growth and development that lays the foundation for future success. However, disparities in early childhood development in the United States persist, with some groups of children facing greater challenges than others. Research consistently shows that children of color, particularly Black and Hispanic children, and children from low-income families are more likely to be born with developmental disabilities, experience a lack of access to quality healthcare and education, and are more likely to be exposed to environmental toxins. Public funding plays a critical role in addressing disparities in early childhood development. High-quality early childhood education programs, such as Head Start and other pre-K programs, have been shown to improve children's cognitive and socioemotional skills, leading to benefits that last for decades through adulthood, particularly for children from disadvantaged backgrounds. In addition to early childhood education programs, public funding can also support access to quality healthcare and nutritious food, as well as programs that provide support for families, such as home visiting programs and parent education programs. However, public funds are limited, and therefore, allocating public resources across a wide range of programs that serve children can be a challenge. Benefit-Cost analysis can help guide policymakers in making data-driven decisions to support programs that yield the highest benefits. However, most benefit-cost analyses consider the societal benefits, i.e., the benefits for all members of the society. This raises equity concerns, as the benefits to the people who need these programs the most may be outweighed by the benefits to society. Through this study, I discuss the different ways we can conduct a benefit-cost analysis by weighing the benefits for different stakeholders differently. I show that even after restricting the definition of benefits in these ways, the benefits of Home Visiting Programs outweigh the costs of the program, making it a worthwhile investment for Social Impact Bond projects as well data-driven philanthropy endeavors. This research is timely and relevant as more and more philanthropies around the US are considering the data-driven approach for expanding social programs. Some of these philanthropies are Robinhood Foundation in New York, Constellation Fund in Minneapolis, and Tipping Point and GiveWell in San Fransisco.