Concentrated Poverty 1 Flashcards
(16 cards)
What is the most common way to define “concentrated poverty”?
A census tract in which at least XX % of residents live below the official poverty line—most often thresholds between 20–40 % are used.
Why do researchers use census tracts to measure concentrated poverty?
Census tracts are the Census Bureau’s small “neighborhood” units (~4,000 people) that provide consistent spatial boundaries for comparing poverty rates.
What conceptual phenomenon does the “census-tract + XX %” definition of concentrated poverty aim to capture?
Neighborhoods with very high shares of extremely low-income people, where area‐level disadvantages can compound.
Why can standard tract-based poverty‐rate definitions understate concentrated poverty in high‐cost areas?
The federal poverty threshold does not adjust for regional cost-of-living. Wealthier areas with higher living costs therefore appear to have fewer high‐poverty tracts.
How do tract definitions bias against detecting poverty in low-density suburbs/rural areas?
In sparse regions tracts cover large geographies, diluting extreme pockets of poverty and thus classifying fewer areas as “high-poverty.”
According to Brookings (2005–09 vs. 2010–14), how did the overall concentrated poverty rate change?
It rose from 10.5 % to 13.5 % of the population living in high‐poverty tracts.
How do Black, Hispanic, and White concentrated‐poverty rates compare (2005–09 → 2010–14)?
Black: 21.2 % → 25.1 %
Hispanic: 12.9 % → 17.6 %
White: 4.1 % → 5.5 %
What do the race & income data reveal about poor children’s exposure to concentrated poverty?
Poor Black children: ~25 % live in high-poverty tracts (ages 0–17)
Poor Hispanic children: ~18 %
Poor White children: ~6–8 %
And poor minority children face much higher exposure than poor Whites at all ages, with the largest gaps among youngest children.
Nationally (2005–09 → 2010–14), how did the share of poor residents in high-poverty neighborhoods change in Cities, Suburbs, and Rural areas?
Cities: 66.8 % → 72.7 % (+5.9 ppt)
Suburbs: 31.0 % → 41.2 % (+10.2 ppt)
Small metros: 46.4 % → 54.1 % (+7.7 ppt)
Nonmetros: 47.6 % → 54.5 % (+6.9 ppt)
Which geography type saw the largest increase in the share of poor residents in high-poverty tracts between 2005–09 and 2010–14?
Suburbs, with a 10.2 ppt increase.
What four place‐level factors are strongly associated with higher concentrated poverty?
Higher overall poverty rate
Greater population density
Higher fraction of Black households
Higher fraction of households with young children
Why does greater density correlate with more concentrated poverty?
Dense urban settings can both contain and amplify poverty—small tracts capture many poor households in close proximity, increasing rates of “concentrated” poverty.
How does the fraction of young‐child households relate to concentrated poverty?
Areas with more families with young children often have higher poverty concentration, reflecting vulnerable demographics in disadvantaged neighborhoods.
Why might a place with a higher share of Black households also show elevated concentrated poverty?
Due to historical and structural segregation, Black households disproportionately reside in neighborhoods with high poverty, driving up measured concentration.
Summarize the measurement challenges of using census‐tract poverty rates for concentrated poverty.
Doesn’t adjust for cost of living → undercounts high-cost metros
Large tract sizes in rural/low-density areas → undercounts remote poverty pockets
Choice of XX % threshold influences sensitivity (20–40 % typical)
What is the key takeaway from the “Concentrated Poverty: Measurement Summary” slide?
Concentrated poverty is most pronounced in places that are poorer, denser, have a greater share of Black residents, and a higher share of young‐child households, highlighting the intersection of socioeconomic and demographic risk factors.
