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Low-income families in the United States tend to live in neighborhoods that offer limited opportunities for upward income mobility. One potential explanation for this pattern is that families prefer such neighborhoods for other reasons, such as affordability or proximity to family and jobs. An alternative explanation is that they do not move to high-opportunity areas because of a lack of information or barriers that prevent them from making such moves. We test between these explanations using a twophase randomized controlled trial with housing voucher recipients in Seattle and King County. We first provided a bundle of resources to facilitate moves to high-upward-mobility neighborhoods: information about high-opportunity areas, short-term financial assistance, customized assistance during the housing search process, and connections to landlords. This bundled intervention increased the fraction of families who moved to high-upward-mobility areas from 15% in the control group to 53% in the treatment group. To understand the mechanisms underlying this effect, we ran a second phase with three arms: (1) information about high-opportunity areas and financial assistance only; (2) reduced support services in addition to information and financial assistance; and (3) full support services, as in the original bundled intervention. The full services had five times as large a treatment effect as the information and financial incentives treatment and three times as large an effect as the reduced support intervention, showing that high-intensity, customized support enables moves to opportunity. Interviews with randomly selected families reveal that the program succeeded by relaxing families’ bandwidth constraints and addressing their specific needs, from identifying suitable units to providing emotional support to brokering with landlords. Families induced to move to higher opportunity areas tend to stay in their new neighborhoods in subsequent years and report higher levels of neighborhood satisfaction after moving. Our findings imply that many low-income families do not have a strong preference to stay in low-opportunity areas and that barriers in the housing search process are a central driver of residential segregation by income. 

Investing in college carries high returns but comes with considerable risk. Financial products like equity contracts can mitigate this risk, yet college is typically financed through non-dischargeable, government-backed student loans. This paper argues that adverse selection has unraveled private markets for college-financing contracts that mitigate risk. We use survey data on students’ expected post-college outcomes to estimate their knowledge about future outcomes and quantify the threat of adverse selection in markets for equity contracts and several state-contingent debt contracts. We find students hold significant private knowledge of their future earnings, academic persistence, employment, and loan repayment likelihood, beyond what is captured by observable characteristics. Our empirical results imply that a typical college-goer must expect to pay back $1.64 in present value for every $1 of equity financing to cover the financier’s costs of covering those who would adversely select their contract. We estimate that college-goers are not willing to accept these terms so that private markets unravel. Nonetheless, our framework quantifies significant welfare gains from government subsidies that would open up these missing markets and partially insure college-going risks. 

Should choice be offered in social insurance programs? This review presents a conceptual framework that identifies the key forces determining the social value of offering choice. We show that the value of offering choice is higher the larger the variation in individual valuations for extra insurance is, but it gets reduced by both selection on risk and selection on moral hazard. Besides adverse selection, the implementation of choice-based policies is further challenged by the presence of choice frictions or the obligation to offer basic uncompensated care. All these inefficiencies can be seen as externalities that do not rationalize the absence of providing choice per se but point to the need for regulatory policies and suggest the potential value of corrective pricing à la Pigou. Applying this framework to the existing evidence on these forces in the context of unemployment insurance, we find that offering insurance choice can be valuable even in the presence of significant adverse selection. We conclude by showing how this framework can constitute a fruitful guide for further empirical research in different insurance domains. 

Abstract Low levels of social interaction across class lines have generated widespread concern 1–4 and are associated with worse outcomes, such as lower rates of upward income mobility 4–7 . Here we analyse the determinants of cross-class interaction using data from Facebook, building on the analysis in our companion paper 7 . We show that about half of the social disconnection across socioeconomic lines—measured as the difference in the share of high-socioeconomic status (SES) friends between people with low and high SES—is explained by differences in exposure to people with high SES in groups such as schools and religious organizations. The other half is explained by friending bias—the tendency for people with low SES to befriend people with high SES at lower rates even conditional on exposure. Friending bias is shaped by the structure of the groups in which people interact. For example, friending bias is higher in larger and more diverse groups and lower in religious organizations than in schools and workplaces. Distinguishing exposure from friending bias is helpful for identifying interventions to increase cross-SES friendships (economic connectedness). Using fluctuations in the share of students with high SES across high school cohorts, we show that increases in high-SES exposure lead low-SES people to form more friendships with high-SES people in schools that exhibit low levels of friending bias. Thus, socioeconomic integration can increase economic connectedness in communities in which friending bias is low. By contrast, when friending bias is high, increasing cross-SES interactions among existing members may be necessary to increase economic connectedness. To support such efforts, we release privacy-protected statistics on economic connectedness, exposure and friending bias for each ZIP (postal) code, high school and college in the United States at https://www.socialcapital.org . 

Abstract Social capital—the strength of an individual’s social network and community—has been identified as a potential determinant of outcomes ranging from education to health 1–8 . However, efforts to understand what types of social capital matter for these outcomes have been hindered by a lack of social network data. Here, in the first of a pair of papers 9 , we use data on 21 billion friendships from Facebook to study social capital. We measure and analyse three types of social capital by ZIP (postal) code in the United States: (1) connectedness between different types of people, such as those with low versus high socioeconomic status (SES); (2) social cohesion, such as the extent of cliques in friendship networks; and (3) civic engagement, such as rates of volunteering. These measures vary substantially across areas, but are not highly correlated with each other. We demonstrate the importance of distinguishing these forms of social capital by analysing their associations with economic mobility across areas. The share of high-SES friends among individuals with low SES—which we term economic connectedness—is among the strongest predictors of upward income mobility identified to date 10,11 . Other social capital measures are not strongly associated with economic mobility. If children with low-SES parents were to grow up in counties with economic connectedness comparable to that of the average child with high-SES parents, their incomes in adulthood would increase by 20% on average. Differences in economic connectedness can explain well-known relationships between upward income mobility and racial segregation, poverty rates, and inequality 12–14 . To support further research and policy interventions, we publicly release privacy-protected statistics on social capital by ZIP code at https://www.socialcapital.org . 

We describe a frame work for empirical welfare analysis that uses the causal estimates of a policy’s impact on net government spending. This framework provides guidance for which causal effects are (and are not) needed for empirical welfare analysis of public policies. The key ingredient is the construction of each policy’s marginal value of public funds (MVPF). The MVPF is the ratio of beneficiaries’ willingness to pay for the policy to the net cost to the government. We discuss how the MVPF relates to “traditional” welfare analysis tools such as the marginal excess burden and marginal cost of public funds. We show how the MVPF can be used in practice by applying it to several canonical empirical applications from public finance, labor, development, trade, and industrial organization. 

Abstract The willingness to pay for insurance captures the value of insurance against only the risk that remains when choices are observed. This article develops tools to measure the ex ante expected utility impact of insurance subsidies and mandates when choices are observed after some insurable information is revealed. The approach retains the transparency of using reduced-form willingness to pay and cost curves, but it adds one additional sufficient statistic: the percentage difference in marginal utilities between insured and uninsured. I provide an approach to estimate this additional statistic that uses only the reduced-form willingness to pay curve, combined with a measure of risk aversion. I compare the approach to structural approaches that require fully specifying the choice environment and information sets of individuals. I apply the approach using existing willingness to pay and cost curve estimates from the low-income health insurance exchange in Massachusetts. Ex ante optimal insurance prices are roughly 30% lower than prices that maximize observed market surplus. While mandates reduce market surplus, the results suggest they would actually increase ex ante expected utility. 

Abstract We conduct a comparative welfare analysis of 133 historical policy changes over the past half-century in the United States, focusing on policies in social insurance, education and job training, taxes and cash transfers, and in-kind transfers. For each policy, we use existing causal estimates to calculate the benefit that each policy provides its recipients (measured as their willingness to pay) and the policy’s net cost, inclusive of long-term effects on the government’s budget. We divide the willingness to pay by the net cost to the government to form each policy’s Marginal Value of Public Funds, or its ``MVPF''. Comparing MVPFs across policies provides a unified method of assessing their effect on social welfare. Our results suggest that direct investments in low-income children’s health and education have historically had the highest MVPFs, on average exceeding 5. Many such policies have paid for themselves as the government recouped the cost of their initial expenditures through additional taxes collected and reduced transfers. We find large MVPFs for education and health policies among children of all ages, rather than observing diminishing marginal returns throughout childhood. We find smaller MVPFs for policies targeting adults, generally between 0.5 and 2. Expenditures on adults have exceeded this MVPF range in particular if they induced large spillovers on children. We relate our estimates to existing theories of optimal government policy, and we discuss how the MVPF provides lessons for the design of future research.