“We’re offering the model as a tool for city governments and anti-gentrification actors to be more proactive in targeting proven interventions in the most vulnerable neighborhoods,” said Németh, who co-authored the paper with Alessandro Rigolon, assistant professor of Recreation, Sport, and Tourism at the University of Illinois at Urbana-Champaign.
The researchers tested the predictive gentrification model in the five most populous U.S. regions: Chicago, Los Angeles, New York City, San Francisco and Washington, D.C.
Three “place” factors — access to jobs, proximity to transit stations and the quality of housing stock — emerged as strong predictors of a neighborhood’s likelihood to gentrify across all regions. As they heavily influence these place factors, this points to the critical role urban planners play in shaping gentrification forces.
The diversity of a neighborhood is the “people” factor with the strongest predictive value, the study found.
“We know from years of research on implicit bias that if a neighborhood has a very high share of Black or Latinx residents, it is much less likely to gentrify than one with a mix of several racial or ethnic groups,” said Németh. He and Rigolon said they weren’t surprised by the finding that racial/ethnic diversity is a strong predictor of gentrification.
Proven policy interventions
Although these factors weren’t tested in this national-level study, several recent studies in California have shown that local “policy” strategies proven to slow gentrification include rent controls, community land trusts, and anti-eviction ordinances.
This first-of-its-kind study offers communities a model to identify the neighborhoods most vulnerable to gentrification and a roadmap to implement proven anti-gentrification strategies before it’s too late.
For this research, gentrification is defined as the influx of middle- and upper-class residents in a spatially concentrated fashion, which often results in the displacement of long-time residents, who disproportionately are poorly educated, lower-income people of color.