Methodology

Mobility Framework Methodology

In early 2019, the Urban Institute formed a Working Group composed of 11 distinguished scholars with expertise in economics, sociology, political science, and psychology and with diverse perspectives with respect to race, geography, policy domains, and political ideology. Their charge was to advise Urban on our development of a set of evidence-based metrics that local leaders can use to assess conditions and track progress on boosting upward mobility. Specifically, the Working Group members aimed to

develop a concise set of practical metrics of mobility that have wide credibility for application by policymakers, practitioners, and researchers. These metrics will reflect a clear theory of change that connects longer-term mobility outcomes to measures that can be tracked in the short and medium term. The metrics chosen will embody the comprehensive definition of economic and social mobility developed by the US Partnership on Mobility from Poverty.

With this objective, the group systematically reviewed various factors that influence mobility from poverty for adults, families, and children. They applied rigorous criteria to reach a consensus on metrics that are supported by strong evidence of predictive relationships to mobility and that can be influenced by local and state policies.

Members convened for three full-day working sessions over nine months and provided structured input between meetings to advise on the most current evidence about key drivers of mobility and how best to reflect the Partnership’s holistic definition of mobility from poverty. They also advised on how to address the role of structural barriers in blocking mobility, including patterns of racism, discrimination, and disinvestment experienced by people of color, and on the best available metrics for monitoring short- to medium-term progress by cities or counties. As part of this process, Urban developed a series of research assessments that are described below in the Evidence Resource Library section. (For more information about the Working Group’s research process, see “Our Process” in Boosting Upward Mobility from Poverty: Metrics to Inform Local Action.)

In conjunction with the Working Group’s deliberations, Urban experts held a series of discussions and webinars with policymakers, researchers, and practitioners. These half-day interactive sessions brought together approximately 30 local stakeholders in each of four different locations (San Francisco, New Orleans, Chicago, and Cleveland) to provide feedback on the preliminary slate of socioeconomic metrics for measuring mobility from poverty. We also hosted webinars with networks of city and county governments and community foundations such as the National Association of Counties, the National League of Cities, and the Community Foundation Opportunity Network. Through the sessions and webinars, Urban sought to understand how the preliminary set of metrics could be relevant and valuable to local changemakers and how the metrics could be applied to inform local advocacy, planning, action, and accountability. These insights were incorporated into the final set of metrics and have informed our work with the Upward Mobility Cohort.

The insights ultimately informed Urban’s development of a framework for boosting mobility that is represented by three key drivers that have been shown to propel people up and out of poverty over the course of their lives. These three drivers contribute to people’s economic success, their power and autonomy, and their sense of being valued in their community. For each of these drivers, Urban experts and Working Group members identified key predictors and an associated metric from across policy domains that can be used to compare and monitor a community’s effort to boost upward mobility over time.

In selecting the metrics, Urban focused on six key shared characteristics. Ideally, each metric should be

  1. valid, meaning that it accurately measures the concepts, indicators, or outcomes of mobility from poverty;
  2. widely available, meaning that it draws upon existing and accessible data for communities nationwide;
  3. repeated at regular intervals, meaning that it is routinely measured to allow for effective monitoring and to signal the potential effects of policy interventions;
  4. geographically mindful, meaning that it is available at the neighborhood, city, or county level and is not sensitive to resident turnover, so local leaders can spark on-the-ground change;
  5. consistent over time and across geographies, meaning that it ensures meaningful tracking and clear comparison within and across localities; and
  6. inclusive of important subgroups, meaning that it considers how people’s experiences vary by race and ethnicity, gender, age, citizenship, and prior incarceration status (among other factors), acknowledging that people experience poverty and upward mobility differently.

Ultimately, Urban and the Working Group selected 25 predictors that communities can use to catalyze and guide action to increase mobility from poverty and address racial inequities. Although these metrics are not perfect, they provide valuable information about how well conditions in a community support residents’ upward mobility. Our current work with communities, scholars, and practitioners is providing additional feedback on the metrics that will result in updates to the Boosting Upward Mobility framework.

Evidence Resource Library Methodology

Our Evidence Resource Library consists of several short “assessments” that summarize the evidence on the relationship between predictors of mobility from poverty and intermediate mobility outcomes. You can use these assessments to gain a quick understanding of the evidence, to inform research papers and grant applications, and as a starting point for deeper literature reviews.

As described previously in the methodology for the Boosting Upward Mobility framework, Urban Institute experts and the Working Group considered many short- and intermediate-term factors that influence the conditions that promote long-term mobility. To winnow down a concise list of the strongest predictors, we sought to better understand the strength of evidence linking these different factors to mobility. Therefore, Urban experts conducted literature reviews to gain insight into how each predictor was related to intermediate-term outcomes, such as a person’s physical health and civic engagement, that are connected to long-term upward mobility in people’s lives.

The resulting assessments were critical to selecting the final suite of predictors. The Working Group used a consensus-building process in which voting helped focus the discussion. The voting process prioritized predictors that covered more stages of the life course and more dimensions of mobility from poverty.

Each predictor assessment includes the following elements:

  • A description of the predictor, the mobility outcomes it is related to, and which aspects of the definition of mobility from poverty it is connected to
  • Summaries of seminal evidence explaining the strength of the connection between the predictor and outcomes related to long-term mobility
  • A brief, exploratory description of local investments or initiatives that can lead to improvements in the predictor at the local level
  • A list of references of the cited evidence

These assessments are intended to give readers an entry point for better understanding how different factors influence upward mobility, but they are not exhaustive. The predictors are by no means the only factors that affect upward mobility. And although each review delves into the research base and prioritizes seminal studies and research overviews, they do not capture all relevant research. In writing the assessments, we focused on identifying a review article or meta-analysis that assesses prior literature.

Urban will release the assessments in batches, and our Evidence Resource Library will eventually include about 50 assessments. Our library may also evolve over time to add additional predictors or update the research on existing ones. Further research could also deepen understanding of how these predictors influence mobility and better explore how local policy levers can improve mobility outcomes.

Visit the Evidence Resource Library.