This document discusses the role of federal policy in promoting or limiting opportunities for low-income people and people of color in America. It provides historical examples of how policies around schooling, housing, transportation and lending influenced racial inequities that persist today. It also examines unemployment insurance and finds that while Black and Latino Americans face higher unemployment rates, they are underrepresented among recipients of unemployment benefits compared to their share of the unemployed population. Geographic distribution of minority groups in states with less generous unemployment systems as well as ineligibility factors may partially explain these disparities.

1. POLICY AND PROMISE FOR
LOW-INCOME PEOPLE IN
AMERICA
john a. powell, Executive Director, The Kirwan Institute
March 10. 2011 Racial Equity and Federal Policy

2. Overview
 Opportunity Matters
 Historic role of Federal Policy
 Example Policy: Unemployment Insurance
 Post-Racialism or Targeted Universalism?

3. Opportunity Matters
Structural Racialization and Systems Dynamics

4. Why do some people have access to the “good
life” while others do not?

5. Our opportunity context matters
Some people ride the “Up” Others have to run up the
escalator to reach “Down” escalator to get there
opportunity

6. Opportunity is….
Racialized… Spatialized… Globalized…
• In 1960, African- • marginalized people • Economic
American families in of color and the very
poverty were 3.8 times globalization
poor have been
more likely to be spatially isolated from
concentrated in high- opportunity via • Climate change
poverty neighborhoods reservations, Jim Crow,
than poor whites. Appalachian
mountains, ghettos, • the Credit and
• In 2000, they were 7.3 barrios, and the Foreclosure crisis
times more likely. culture of
incarceration.

7. It’s more than a matter of choice…
The Cumulative Impacts of Spatial, Racial and
Opportunity Segregation
Segregation impacts a number of life-opportunities
Impacts on Health
School Segregation
Impacts on Educational Achievement
Exposure to crime; arrest
Transportation limitations and other
inequitable public services
Neighborhood Job segregation
Segregation
Racial stigma, other
psychological impacts
Impacts on community power and
individual assets
Adapted from figure by Barbara Reskin at: http://faculty.washington.edu/reskin/

8. From a one- dimensional understanding…
• One variable can explain
why differential outcomes.
…to a multi-dimensional understanding….
• Structural Inequality
– Example: a Bird in a cage.
Examining one bar cannot
explain why a bird cannot fly.
But multiple bars, arranged
in specific ways, reinforce
each other and trap the bird.

9. ...to an understanding of processes and
relationships
• Understanding the
relationships among
these multiple
dimensions, and how
these complex intra-
actions change
processes
• Relationships are
neither static nor
discrete

10. We need to think about the ways in which the
institutions that mediate opportunity are arranged
 The order of the structures
 The timing of the interaction between them
 The relationships that exist between/among them

11. Who’s to blame?
11

12. Federal Policy
Historic Examples of Federal Impact on
Opportunity

13. Historic Government Role
 A series of federal policies have contributed to the
disparities we see today
 School Policy
 Suburbanization & Homeownership
 Urban Renewal
 Public Housing
 Transportation

14. Redlining and Opportunity
 Philadelphia Mortgage
Insurance and Redlining
 Historic Lending and Today’s
Opportunity Landscape

15. Unemployment Insurance
The Role of Federal Policy in Racial Equity

16. Blacks and Latinos have endured especially
high unemployment during the latest recession

17. Blacks and Latinos also are overrepresented among the
long-term unemployed (Dec 2010)
25
20
% of Labor Force
15
% of Unemployed
% of Long-term Unemployed (52
10 weeks+)
5
0
BLACKS LATINOS ASIAN AMERICANS
Source: Bureau of Labor Statistics, Current Population Survey

18. The relationship between race/ethnicity
and long-term unemployment holds over time

19. However, Blacks seem to be somewhat underrepresented
and Latinos very underrepresented among UI recipients
There are 15 states for which we have fairly good race/ethnicity data on UI recipients
in 2009. The unemployed in these states include 2.9 million whites, 1.1 million
African Americans, and 360,000 Latinos.
Recipiency rates by race/ethnicity across 15 states, 2009
45.0%
40.0% 42.8%
41.0%
35.0% 39.1%
30.0% 32.4%
25.0%
20.0%
15.0%
10.0%
5.0%
0.0%
Overall White Black Latino
Source: BLS Local Area Employment Statistics and DOL Employment and Training Administration, Characteristics of the Insured Unemployed
for Calendar Year 2009; BLS Preliminary 2009 Data on Employment Status by State and Demographic Group

20. There is significant variation in relative
recipiency rates by race/ethnicity at the state level
Recipiency rates by race/ethnicity in most populous of the 15 states, 2009
70%
60%
White recipiency rate
Black recipiency rate
50%
Latino recipiency rate
40%
30%
20%
10%
0%
Ohio Maryland Georgia Illinois North Carolina Pennsylvania Tennessee
Source: DOL Employment and Training Administration, Characteristics of the Insured Unemployed for Calendar Year 2009; BLS Preliminary
2009 Data on Employment Status by State and Demographic Group

21. Even “high income” African American
families can ill afford missed paychecks
Source: Institute on Assets and Social Policy, “The Racial Wealth Gap Increases Fourfold.” May 2010.

22. Possible explanations: It may be that…
1. Blacks and Latinos more likely to live/work in low-
coverage states (geographic distribution/bad-luck )
2. Blacks and Latinos less likely to meet state eligibility
criteria (worker status issue/bad luck)
3. Disparities by race/ethnicity are not coincidental; the
Unemployment Insurance program is “racialized” in
design and by the role of bureaucratic discretion in its
implementation
4. Unemployed Blacks/Latinos less likely to apply for UI
5. Undocumented immigrants more likely to count among
the unemployed than to receive UI benefits

23. 1. Relative to Whites, Blacks and Latino populations are
unfavorably distributed in re state UI recipiency rates
Distribution of US population by race/ethnicity and state recipiency rates –
low (20%-41%), medium (41%-50%), and high (51%-69%) – in November 2009
100%
90%
27% 27% 32%
80% 33%
70%
60% 20%
37%
31% High
50% 32%
Medium
40% Low
30%
53%
20% 35% 36% 38%
10%
0%
White population Black population Latino population Entire population
Source: U.S. Census Bureau, "Estimates of the Resident Population by Race and Hispanic Origin for the United States and States: July
1, 2008 (SC-EST2008-04),“ and ProPublica, “Is Your State's Unemployment System in Danger? November 2009/
http://www.propublica.org/special/is-your-states-unemployment-system-in-danger-603

24. 2. Blacks and Latinos overrepresented among
unemployed workers most likely to be ineligible
 Among unemployed, African Americans less likely than whites
to be “job losers” in 4th quarter, 2010
 58% and Blacks and 64% of whites were “job losers” (vs.
new entrants, reentrants, etc)
 Blacks and Latinos disproportionately low-income. The EPI
estimated that in 2009:
 Blacks were 11% of the workforce, but 18% of workers
affected minimum wage increase to $7.25/hr.
 Hispanics were 14% of the workforce and 19% of workers
affected by increase.

25. 3. Is UI racialized in design and through
the role of discretion in its implementation?
 If so, one would expect, for example:
A positive association between recipiency rates and
proportion African American and/or Latino
A positive association between wrongful denial of UI
benefits and proportion Black and/or Latino
 Relatively favorable results to African Americans and
Latinos in states that rely more on automation
 Greater denial of African Americans and Latinos than
of similarly situated White claimants

26. Black-White Implicit Association Test Results
Strong preference for Blacks 2%
Moderate preference for Blacks 4%
Slight preference for Blacks 6%
Little to no preference 17%
Slight preference for Whites 16%
Moderate preference for Whites 27%
Strong preference for Whites 27%
0% 5% 10% 15% 20% 25% 30%
N = 732,881

27. A few proven behavioral implications of implicit bias
 In “shooter game,” mistakes follow clear pattern: people shoot
more unarmed blacks and fail to shoot armed whites
 Doctors’ implicit racial attitudes  unequal treatment for
Latinos and Blacks compared to Whites
 Resumes with “white-sounding” names (Emily, Greg, Jill, Todd)
receive 50% more call-backs than those with “black-sounding”
(Jamaal, Latoya, Tyrone, Lakesha) names.
 Neighborhoods with White-only residents evaluated much more
favorably than same neighborhoods with black residents or
racially mixed residents
 More or less implicit bias corresponds to comfort level and body
language in interracial interactions
“Emergency Treatment May Only Be Skin Deep.” Science Daily 11 Aug. 2007

28. Back to UI -- states with higher proportions of
Black Americans do also have lower coverage rates
Black state population shares x recipiency rates (2010)
(Correlation = -0.40)
0.6
0.5
0.4
IUR/TUR Recipiency
0.3
0.2
0.1
0
0.000 0.100 0.200 0.300 0.400 0.500 0.600
Pct. of State Population African American
Source: http://www.doleta.gov/unemploy/chartbook/chartrpt.cfm

29. Same is true for Latinos, but the relation-
ship is weaker than for African Americans
Latino state population shares x recipiency rate (2010)
(Correlation = -0.16)
0.6
0.5
0.4
IUR/TUR Recipiency
0.3
0.2
0.1
0
0.000 0.050 0.100 0.150 0.200 0.250
Pct. of State Population Latino
Source: http://www.doleta.gov/unemploy/chartbook/chartrpt.cfm

30. For Whites, the reverse is true: the greater the
White proportion, the higher the coverage rate
White population shares & recipiency rates (2010)
(Correlation = 0.22)
0.600
0.500
0.400
IUR/TUR Recipiency
0.300
0.200
0.100
0.000
0.000 0.200 0.400 0.600 0.800 1.000 1.200
Pct. of State Population White
Source: http://www.doleta.gov/unemploy/chartbook/chartrpt.cfm

31. The distribution of the black population nationally has
not changed dramatically between 1930 and 2000
 1930
2000 
31

32. State shares of B’s/L’s were positively associated with improper
monetary denial rates, not with separation/non-separation errors
(Correlation = .27)
45%
40%
Improper monetary denial rates
35%
30%
25%
20%
15%
10%
5%
0%
0.0 10.0 20.0 30.0 40.0 50.0 60.0
Percent of state population that is Black and Latino
Source: DOL Employment and Training Administration, Benefit Accuracy Measurement, Denied Claims Accuracy Report 2009.
http://www.ows.doleta.gov/unemploy/bam/2009/Denied_Claims_Accuracy_Rates_CY_2009.xls

33. Potential Responses
To possibility of racial/ethnic bias:
 Make race/ethnicity data collection mandatory for
all UI applicants
 Conduct audit tests for bias in claims processing
 Reduce bureaucratic discretion through still-greater
use of automation
 Offer de-biasing training

34. Potential Responses (cont.)
Expanding access and speeding transfer:
 Support wider state adoption of modernization
reforms
 Require employers to distribute UI information
to displaced workers
 Change the benefit calculation formula to aid
low-income workers
 Allow workers to bank their benefits over time