NCRC is pleased to announce the release of a new longitudinal dataset designed to help communities, advocates and policymakers better understand how neighborhoods have changed over time and where gentrification pressures are most evident.
This dataset draws on US Census data spanning multiple decades (from the 1970s through 2010s) and covering thousands of neighborhoods tracking demographic, economic and housing trends at the neighborhood (census tract) level across metropolitan areas nationwide.
Why this matters
Gentrification is one of the most debated topics in the housing and community development fields. Depending on how it’s measured, the same neighborhood can look like a success story or a displacement crisis. This dataset was built to cut through that confusion. It applies five research-tested methods for identifying gentrification so users can see how conclusions shift depending on the approach — and which methods are best supported by real-world evidence.
NCRC’s own research, published in the Journal of Urban Affairs, found that the methods included in this dataset were among the most accurate at tracking actual patterns of class change, racial turnover and housing market pressure. Using these methods, we estimate that roughly 60,000 Black residents left gentrifying neighborhoods in Washington, DC between 1990 and 2020 alone.
This new dataset has provided researchers and advocates with a more transparent and evidence-based way to understand where and how gentrification is occurring.
What’s in the dataset
The dataset includes neighborhood-level indicators over time, such as:
- Population and demographic change
- Income and poverty levels
- Housing values and market activity
- Employment and occupational shifts
- Gentrification indicators by decade
These indicators allow researchers to make consistent, decade-by-decade comparisons across thousands of neighborhoods in urban areas nationwide.
What we found
Using this dataset and our evaluation approach, we found that in Washington, DC – one of the most studied cases of gentrification – neighborhoods identified as gentrifying were also the primary sites of significant Black population loss between 1990 and 2020.
However, this does not mean every move was forced. But it does show that population changes were not random as they were concentrated in areas experiencing rapid economic and social transformation.
How this helps communities
This dataset is designed to support:
- Better public understanding of neighborhood change;
- More informed policy decisions, including tenant protections and anti-displacement strategies;
- Targeted investment by focusing resources where pressures are greatest; and allows for more
- Local analysis, allowing cities to apply consistent evaluation methods to their own communities.
A tool for action
By grounding the measurement of gentrification in real-world indicators, this dataset helps move the conversation beyond competing definitions and toward practical solutions.
When we can clearly identify where change is happening — and who is affected — we are better equipped to protect communities and promote equitable development.
To access the dataset and learn more about the evaluation methods, please see the following resources:Â
- https://www.openicpsr.org/openicpsr/project/250783/version/V1/view
- https://www.tandfonline.com/doi/full/10.1080/07352166.2026.2621717
Funding SourcesÂ
National Institutes of Health’s National Institute on Aging (R01AG080401)
Bruce C. Mitchell with the Principal Researcher with NCRC’s Research team.
Photo credit: Erik McLean via Pexels.
