Financial well-being is a marker of economic success in itself, affords adults control and autonomy over their lives, and allows parents to invest in the well-being of their children. Rising incomes reflect upward economic mobility and can facilitate greater financial well-being. In contrast, people with low or irregular incomes and insufficient savings are less able to weather life’s inevitable challenges and disruptions, leading to instability and stress that can undermine the ability to make effective decisions and contribute to feelings of powerlessness.
To see more information about these predictors, see our updated report, Boosting Upward Mobility: Metrics to Inform Local Action, Second Edition. For more insight into the decisions behind updates to the predictors and metrics, see that paper’s accompanying Technical Report.
PREDICTORS
Opportunities for Income
Financial Security
Wealth-Building Opportunities
Opportunities for Income
Income is a strong indication of a family’s material well-being. Families need a certain base level of income to meet their basic needs for food, clothing, shelter, health care, and any costs related to sustaining a job. Further, children raised in higher-income households demonstrate higher academic achievement and educational attainment, better physical and mental health, and fewer behavioral problems than their peers from lower-income households.
Metric: Household income at the 20th, 50th, and 80th percentiles
Household income is a standard measure of financial well-being. The Working Group recommended the metrics at these three levels to track how and for whom incomes are changing in a given place as well as whether incomes are rising across the board or are rising more for those with higher incomes. To identify income percentiles, all households are ranked by income from lowest to highest. The income level at the threshold between the poorest 20 percent of households and the richest 80 percent is the 20th percentile. Similarly, the threshold between the poorest and richest halves is the 50th percentile (or median), and the threshold between the poorest 80 percent and richest 20 percent is the 80th percentile.
Validity: These are well-established measures, and several federal agencies and many scholars frequently use them to assess families’ financial well-being.
Availability: Data on household income are available from the Census Bureau’s American Community Survey and Public Use Microdata Sample.
Frequency: New data for the metric are available annually. For subgroup analyses in less populated areas, several years of data may need to be pooled to obtain reliable estimates.
Geography: Data are available at the county and metropolitan levels.
Consistency: Income data are measured the same way across all geographies in the same year. The measure is fairly consistent over time, but changes in the phrasing and sequence of income source questions might affect comparisons over time. When such changes have occurred in other federal surveys, such as the Current Population Survey, the Census Bureau provides bridge-year data so users can assess the effects of survey changes
Subgroups: The metric can be disaggregated by race or ethnicity, gender, and other demographic factors. For less populated areas and for certain demographic groups, several years of data may need to be pooled to obtain reliable estimates.
Limitations: The purchasing power of any particular level of income will vary based on the local cost of living. Also, because household sizes differ, the same income may be stretched across larger average households in some places relative to others. Like all metrics based on the characteristics of people living in an area, it can change because of residential mobility.
Financial Security and Wealth-Building Opportunities
Financial security extends beyond income and reflects the overall ability of a household to meet its current and future financial obligations and withstand potential financial shocks. Research finds that even a modest amount of savings can help buffer a short period of being unemployed or help face a medical emergency. Financial security can also include access to credit, debt loads, and financial management.
Metric: Share of households with debt in collections
This metric accounts for the share of households in an area with debt that has progressed from being past due to being in collections.
Validity: Delinquent debt as measured by debt in collections is a valid and strong measure of financial distress.
Availability: Drawn directly from credit reports, the credit bureau data are national and uniform across the country. The data are restricted and are not accessible directly from credit bureaus but are made available publicly on the Urban Institute’s Debt in America website.
Frequency: New data for this metric are available annually.
Geography: Data on households with debt in collections are available by zip code or county.
Consistency: The share of households with debt in collections can be measured consistently for all geographies. The measure is likely to remain consistent over time unless the credit bureaus change the way overdue debt is captured in credit reporting.
Subgroups: The credit bureau data do not include information about race. But the debt value can be disaggregated by subarea when used in combination with the American Community Survey to identify the racial or ethnic composition of neighborhoods (zip codes) with more or less debt in collections. We distinguish zip codes that are majority non-Hispanic white or majority nonwhite. We define a majority as at least 60 percent of residents.
Limitations: Along with the limitations related to subgroups, these data do not capture “credit invisible” households, meaning those without a credit record. As a measure of financial well-being, even if few households have debt in collections, many may still have too little wealth or savings to be primed for upward mobility. This metric is somewhat sensitive to residential mobility. If many residents without overdue debt move in or out of a county or zip code, or if many residents with overdue debt move in or out, this metric could shift.
Employment Opportunities
People experiencing periods of unemployment suffer a loss of income in the short term and potentially lower earnings once they find a new job. A job loss and associated unemployment and a struggle to find work contribute to a rise in depressive symptoms and anxiety as well as losses in self-esteem, life satisfaction, and sense of control. Those who become unemployed are also less likely to be socially engaged than those with jobs. Further, parental job loss and the attendant stress it brings spills over onto children, whose academic performance and behaviors suffer. People who have become so discouraged that they stop looking for work are jobless but no longer technically unemployed. As such, employment is a critical driver of mobility from poverty.
Metric: Employment-to-population ratio for adults ages 25 to 54
This metric is the ratio of the number of employed adults ages 25 to 54 in a given jurisdiction to the total number of adults in that age range living there.
Validity: Employment captures what share of adults in a jurisdiction are engaging in work for pay. The employment-to-population ratio (EP) is a standard labor market metric reported monthly by the Bureau of Labor Statistics (BLS) and based on the Current Population Survey. The Working Group recommends applying the methodology used to compute the EP to similar data collected in the Census Bureau’s American Community Survey (ACS).
Availability: Data on employment are available from the ACS and Public Use Microdata Sample.
Frequency: New data for the metric are available annually. For subgroup analyses in less populated areas, several years of data may need to be pooled to obtain reliable estimates.
Geography: Data are available at the county and metropolitan levels.
Consistency: Information on employment and age is measured the same way across all geographies in the same year and over time in the ACS.
Subgroups: The metric can be disaggregated by race or ethnicity, gender, and other demographic factors. For less populated areas and for certain demographic groups, several years of data may need to be pooled to obtain reliable estimates.
Limitations: The BLS reports the official EP monthly for those age 16 and up as well those age 20 and up. As such, the BLS-reported measure could be lower for jurisdictions that have many young adults attending college rather than working as well as for those that have many retirees. Consequently, for our purposes, we recommend computing the EP for adults ages 25 to 54 using data from the ACS rather than relying on BLS reports. Even when using ACS data, the EP can drop if unemployed people leave an area or if working people move in.
Access to Jobs Paying a Living Wage
Even if most community members are working, the jobs they hold may not pay them enough to escape poverty or offer prospects for advancement. Ideally, work should be both financially and personally rewarding while allowing workers to meet their family needs; in other words, they need access to jobs paying a living wage. Although many different attributes of a job can contribute to mobility, jobs that offer higher earnings tend to also offer employer benefits such as paid time off and health and pension benefits, and workers in better-paying jobs tend to have more stable employment. Further, children in families with higher-earning parents tend to be in better health and on better developmental trajectories than children with lower-earning parents. Earnings that equal or exceed the cost of a family’s basic needs for food, clothing, shelter, child care, health care, and transportation are an important threshold for predicting economic and social mobility.
Metric: Ratio of pay on the average job to the cost of living
This metric shows what a typical job pays relative to the cost of living in a particular area. The metric is computed by dividing the average weekly earnings across all jobs in an area by the cost of meeting a family of three’s (one parent and two children) basic expenses in that area.
Validity: Employer-reported data on wages paid are a reliable indicator of what jobs pay, and the metric is based on data collected and disseminated by BLS. Data on what it costs to meet basic expenses requires detailed studies of the cost of food, clothing, shelter, health care, and work-related expenses for each jurisdiction. We rely on the work of well-regarded scholars at the Massachusetts Institute of Technology (MIT) to obtain estimates of the local cost of living.
Availability: Data on wages are available quarterly from the BLS’s Quarterly Census of Employment and Wages, and estimates of the cost of meeting a family’s basic needs, referred to as a living wage, are available annually from MIT.
Frequency: New data for the metric are available annually.
Geography: Data on wages are available at the county and metropolitan levels. Data on living wages are available at the county level.
Consistency: Information on quarterly wages is collected consistently by the BLS. MIT uses a consistent methodology to compute living wages by county.
Subgroups: The data cannot be disaggregated by demographics because they describe jobs rather than the people in them, but we can disaggregate by industry type.
Limitations: The metric can only be computed for the 365 largest counties and cannot be disaggregated by subgroups. The metric relies on MIT’s computations of “living wages.”
