Concentrated Poverty 4 Flashcards
(25 cards)
What was the Gautreaux case and why did it matter?
In the 1960s–70s, Black families in Chicago public-housing sued the CHA and HUD, arguing that housing programs reinforced segregation and substandard conditions. The court ordered vouchers so plaintiffs could relocate to predominantly white, suburban neighborhoods—a landmark precursor to later mobility experiments.
What outcomes did Gautreaux movers experience?
Children who moved to suburbs had just a 5 % high-school dropout rate (vs. 20 % for city-stayers), 27 % went on to college (vs. 4 %), and among non-college youth 75 % were employed (vs. 41 %).
What was the primary research question of MTO?
Whether relocating low-income families from high-poverty public housing to lower-poverty neighborhoods causally improves life outcomes for adults and children.
How were MTO participants recruited and selected?
In 1994, ~4,600 families living in public or assisted housing in census tracts with > 40 % poverty in five cities volunteered. Those who wished to enroll were then randomized.
What were the three MTO arms?
1) Control (stay in public housing; 1,439 HHs)
2) Unrestricted Voucher (standard Section 8 voucher, no counseling; 1,346 HHs)
3) Experimental (Low-Poverty) Voucher (< 10 % poverty tract restriction for 1 year + mobility counseling; 1,819 HHs)
Why include an Unrestricted Voucher arm?
To isolate the effect of simply receiving a voucher from the effect of moving to a low-poverty neighborhood and receiving counseling.
What was ‘imperfect compliance’ in MTO?
Only 47 % of the Experimental group actually moved to a low-poverty tract (63 % moved with an unrestricted voucher).
What happened to many Control families?
Some left public housing anyway—especially due to HUD’s HOPE VI demolition of distressed developments—blurring the pure ‘stay’ counterfactual.
What supply-side constraints limited moves?
Limited rental availability in low-poverty areas, landlord discrimination against vouchers, and payment standards that didn’t fully cover local rents.
What are ‘neighborhood effects’?
The causal impact of neighborhood context—where one lives or grows up—on life outcomes (e.g., health, education, earnings, crime).
What is the ‘sorting’ hypothesis?
That people with poorer outcomes self-select into poor neighborhoods (e.g., because of fewer resources), so observed correlations aren’t causal.
Why can’t we simply randomize people into ‘good’ vs. ‘bad’ neighborhoods?
Ethical and practical barriers—coercively placing families into harmful environments is neither permissible nor politically feasible.
How might physical isolation affect neighborhoods?
Proximity to jobs, services, and networks varies by location. A remote neighborhood may limit access to employment and social capital.
How does neighborhood composition influence outcomes?
The demographic and socioeconomic mix (e.g., share of high- vs. low-skilled residents) shapes peer effects, role models, and social norms.
What role does quality of services play in neighborhoods?
Differences in school quality, policing, transit, parks, and community organizations influence child development and adult well-being.
How does environmental quality impact neighborhoods?
Factors like pollution, green space, and housing conditions affect physical and mental health.
How is concentrated poverty typically defined?
A census tract where at least XX % of residents live below the federal poverty line (commonly thresholds of 20–40 %).
What are key measurement issues in concentrated poverty?
Cost-of-living: Federal poverty line isn’t regionally adjusted, undercounting real hardship in high-cost areas.
Geography: Large tracts in low-density suburbs/rural zones may dilute pockets of poor residents.
What were the racial/ethnic disparities in concentrated poverty from 2005–09 vs. 2010–14?
Poor Black households in high-poverty tracts rose from 21.2 % → 25.1 %, Hispanic poor 12.9 % → 17.6 %, White poor 4.1 % → 5.5 %.
What trends were observed in metro types regarding concentrated poverty?
Nationwide share of poor in high-poverty tracts rose 47.4 % → 54.7 %; suburbs saw the largest jump, + 10.2 ppt (31.0 % → 41.2 %).
List major causes linked to (and distinct from) racial segregation.
Mortgage-lending discrimination (Dymski 2006)
Rental/housing-search discrimination (Christensen & Timmins 2018)
Information asymmetries (Bergman et al. 2019)
Restrictive zoning (Schill & Wachter 1995)
Self-segregation (Becker & Murphy 2000)
Public-housing siting policies (De Souza Briggs 2005)
Why intervene to reduce concentrated poverty?
If spatial concentration of poor households generates negative externalities—on neighbors, service provision, crime, or future generations—there is an economic rationale for corrective policy.
What is the Intention-To-Treat (ITT) effect?
The causal effect of being assigned to the treatment group, regardless of whether one actually receives the treatment.
What is the Treatment-On-Treated (TOT) effect?
The causal impact among those who actually receive the treatment; estimated by scaling ITT by the compliance fraction:
\text{TOT} = \frac{\text{ITT}}{\text{% who took up treatment}}
