Is upward mobility decreasing? — Evidence and local measures

What upward mobility in America means: definition and core measures (upward mobility america)

When researchers talk about upward mobility in America they usually mean intergenerational changes in economic status, specifically how children fare relative to their parents. A basic distinction in the literature is between absolute mobility, which looks at whether children earn more in dollar terms than their parents, and relative mobility, which compares a child s position in the income distribution to their parents position.

One commonly used empirical approach is the transition rate, which records the share of children born into a given childhood income decile who reach a specified adult income percentile by a certain age. Another standard method ranks individuals by percentile and compares percentile ranks across generations to measure mobility without focusing on inflation or absolute income levels. The Opportunity Atlas and related work set out these measures and provide mapping tools researchers use to visualize neighborhood outcomes Opportunity Atlas.

Put simply, think of a transition rate example: if 20 percent of children from the bottom decile in one neighborhood reach the middle income percentiles as adults while 40 percent do so in another neighborhood, researchers would say the second neighborhood shows higher upward mobility in relative terms. That percentile and transition framing lets analysts compare communities across time and place while adjusting for wider shifts in the economy, and it is central to many papers on intergenerational mobility Chetty et al., Nature paper.

Absolute versus relative mobility

Absolute mobility asks whether children are doing better in dollars than their parents, which depends heavily on macroeconomic growth and inflation. Relative mobility asks whether being born to lower-income parents makes it systematically harder to reach a higher income rank than for children from wealthier families. Both questions matter but answer different policy concerns. Comparative discussions of absolute mobility across countries are discussed in National Academies materials National Academies.

Common measures researchers use (transition rates, percentile ranks, mobility maps)

Transition rates and percentile ranks are complemented by geographic mapping. Maps that show the probability of reaching higher income percentiles by childhood location reveal how place matters for mobility. These measures are what the Opportunity Atlas and related projects make available for public use and dashboards such as the Urban Institute’s Upward Mobility Data Dashboard Upward Mobility Data Dashboard Opportunity Insights paper.

What the national data say about trends since the 1980s

Several high-quality analyses through 2024 examine whether upward mobility at the national level has improved, stagnated, or declined for cohorts born since the 1980s. Many of these syntheses find little or no improvement in broad measures of mobility for those cohorts, though estimates vary by method and the exact cohorts sampled Opportunity Insights paper. For a journalistic overview see a YaleNews summary of work on recent trends YaleNews.

Part of the reason studies reach different conclusions is methodological. Cohort studies follow groups born in the same years and compare outcomes decades later, while cross-sectional measures may mix cohorts and ages. Absolute and relative mobility also respond differently to macro trends such as wage growth and inequality, so a single national headline can mask important variation across measures and time windows NBER working paper.

Estimates also differ because data windows and age cutoffs matter: measuring adult outcomes at age 30 will show different mobility patterns than measuring at age 40. Researchers note these choices explicitly and caution that short windows can understate eventual mobility for later-coming career gains or continued education.

Given those methodological differences, the evidence through 2024 is best read as mixed: several analyses indicate slow or stagnant mobility for post-1980s cohorts in many measures, but the size and timing of any change depend on how mobility is defined and measured Opportunity Insights paper.

Cohort studies and time trends

Cohort analysis tracks specific birth cohorts and compares outcomes for those cohorts over their adult lives. This approach helps isolate generational changes but requires long follow up and careful sample construction. Some cohort studies find flat or modest declines in relative mobility for cohorts born after the 1970s and 1980s, which remains a subject of active research NBER working paper.

Why estimates differ by method and sample year

Different datasets, ages of measurement, and whether researchers adjust for changing family structure or returns to education all affect trend estimates. That explains why policy discussions often cite a range of findings rather than a single definitive number.

Where opportunity varies: the strong geography of upward mobility

One of the clearest findings in mobility research is that where a child grows up matters a great deal. Mapping work shows large, persistent neighborhood and metro variation in the probability a child will reach higher income percentiles as an adult Opportunity Atlas.

These differences are not small: adjacent census tracts can show markedly different transition rates and long-run outcomes for children, even within the same city. That geographic pattern helps explain why national averages can obscure very different local realities Chetty et al., Nature paper.

For readers interested in local checks, the Opportunity Atlas lets you enter an address or census tract to see long-run outcomes for children who grew up there. Using this tool alongside county and metropolitan summaries provides a clearer picture than relying on a single national statistic Opportunity Insights paper. You can also check the site’s news archive for related commentary.

As a practical matter, geographic variation matters for policy because place-specific conditions such as school quality, segregation, and local labor markets shape daily opportunities and access to stable jobs, not just family background. That is why many researchers emphasize place-based analysis when designing local interventions NBER working paper.

Neighborhood and metro patterns from the Opportunity Atlas

Maps from the Opportunity Atlas show persistent clusters of higher-opportunity neighborhoods and clusters where children face lower chances of upward movement. These patterns are tied to local institutions, housing markets, and historical patterns of segregation and investment Opportunity Atlas.

Examples of high-mobility and low-mobility areas and what that implies

Without naming specific cities here, studies describe profiles of communities with higher mobility that often combine stronger school outcomes, more stable family incomes, and local labor markets with middle-wage job opportunities. Low-mobility areas often show concentrated poverty, weaker school outcomes, and more limited access to steady jobs, which suggests different policy responses for different places Chetty et al., Nature paper.

Key drivers that research connects to mobility outcomes

Research consistently finds that family background, including parental income and education, is a major predictor of a child s long-run economic position. Parental resources influence early childhood conditions, educational opportunities, and networks that affect job access later in life Chetty et al., Nature paper.

Local school quality and neighborhood effects are also central. Schools shape skill accumulation and credentialing, while neighborhood conditions influence exposure to crime, peer networks, and local role models. Studies that compare places find these factors explain a substantial share of geographic differences in mobility NBER working paper.

Family background and parental resources

Parental education and income are associated with children s achievement and eventual earnings in many datasets. That association is not a strict causal law, but research identifies pathways such as access to enrichment, stable housing, and health care that link family resources to later outcomes Opportunity Atlas.

Local schools, segregation, and labor-market structure

Beyond family and schools, the structure of local labor markets matters: areas with diverse industry composition and greater job growth in middle-wage occupations tend to offer more routes to upward mobility than places with shrinking middle-skill employment. Analysts point to local job growth and wage dispersion as material determinants of opportunity Pew Research Center analysis.

Importantly, drivers interact. For example, a child from a low-income family may have better long-term prospects in a community with stronger schools and more stable local employers than in a place with weak schools and few steady jobs, which is why place and family context are considered together in many studies NBER working paper.

What policies and programs show evidence of improving mobility

Several policy areas have evidence of positive effects on mobility outcomes, though results are context dependent. Early childhood interventions, targeted place-based investments, and workforce development programs appear among the most promising levers identified in reviews and syntheses OECD report.

Early childhood programs can improve school readiness and later academic outcomes, which are linked to adult earnings in cohort studies. Place-based investments aim to alter neighborhood conditions, and workforce development focuses on aligning skills with local employer needs.

Evidence reviews emphasize that the design and scale of programs matter: small pilots may not scale directly to different local contexts, and impacts often depend on complementary services and sufficient funding. Readers should interpret program claims with attention to design details and local conditions NBER working paper.

Early childhood and education interventions

Programs that support children s early learning environments, health, and family supports show positive effects on cognitive and noncognitive skills that matter for later outcomes. The evidence base points to measurable benefits but also underscores variation by program model and implementation OECD report.

Place-based investments and workforce development

Targeted investments in neighborhoods, combined with training that connects residents to local job openings, are among policy options with empirical support in specific contexts. Analysts highlight that local labor demand and industry mix influence whether workforce programs translate into stable, higher-paying jobs Opportunity Insights paper.

How to assess whether upward mobility is changing in your community

Monitoring local mobility requires looking at multiple indicators rather than a single headline. Useful measures include transition rates from childhood income deciles to adult percentiles, school attainment and standardized test outcomes, and changes in local median wages and job counts by industry.

When using these sources watch for small-sample volatility at the census tract level and timing lags between childhood measures and adult earnings. Pair long-run transition data with up-to-date local labor market indicators to assess whether recent job growth or losses are likely to alter mobility trajectories Opportunity Insights paper.

Practical steps include downloading tract or county data from the Opportunity Atlas, checking state education department reports for school outcomes, and reviewing local BLS or county labor updates for shifts in industry employment and median wages. These steps help separate short-term noise from plausible long-term changes Opportunity Atlas. You can also compare these findings with local commentary on the Michael Carbonara homepage.

Typical mistakes and common misinterpretations to avoid

A common error is to conflate correlation with causation. For example, observing that neighborhoods with higher school test scores also show higher transition rates does not by itself prove that improving test scores will produce the same gains without considering other changes in the local environment Opportunity Insights paper.

Readers should also be cautious about small sample sizes at fine geographic scales. Census tract estimates can be noisy, and single-year changes may reflect sampling variation rather than durable shifts in opportunity.

Practical local scenarios: how voters and community groups can use this information

Scenario 1, high-mobility profile: a neighborhood with moderate childhood poverty, improving school graduation rates, and growth in middle-wage jobs shows rising transition rates in recent tract maps. For local actors, priorities might include supporting school programs that reinforce existing gains and tracking employer engagement in hiring pipelines Opportunity Atlas.

Scenario 2, low-mobility profile: a neighborhood with persistent concentrated poverty, stagnant school outcomes, and a declining base of steady employers shows low transition rates. Community responses could emphasize early-childhood supports, partnerships to attract stable employers, and programs that reduce housing instability while monitoring labor market shifts Pew Research Center analysis.

Community steps are typically nonpartisan: convene a local data review, compare tract maps with county labor statistics, and pilot evidence-based programs that fit local needs while evaluating results over time. Primary sources and careful attention to sample notes help prevent misreading short-term changes as lasting trends Opportunity Insights paper.

Conclusion: what we know, what remains uncertain, and next steps

High-quality research shows strong geographic variation in upward mobility and identifies family background, schools, and local labor markets as important drivers. Several analyses through 2024 find mixed evidence on national change for cohorts born since the 1980s, with outcomes sensitive to method and sample choice Opportunity Atlas.

Uncertainties to watch include how post-pandemic labor market changes, housing affordability pressures, and remote work trends will reshape local opportunity. For readers wanting to dig deeper, primary sources such as the Opportunity Atlas, Opportunity Insights syntheses, and NBER working papers are useful next reads Opportunity Insights paper. You can also learn more about the author on the about page.