Selected Demographics

1
Access to Opportunity in the Twin Cities
Metropolitan Area-Myron Orfield-
2
Overall Growth Patterns
3
(No Transcript)
4
(No Transcript)
5
(No Transcript)
6
(No Transcript)
7
(No Transcript)
8
(No Transcript)
9
(No Transcript)
10
Poverty and Race
11
(No Transcript)
12
(No Transcript)
13
(No Transcript)
14
(No Transcript)
15
(No Transcript)
16

• Minneapolis Schools
• Segregation by race and income has intensified in
  City schools

17
(No Transcript)
18
(No Transcript)
19
(No Transcript)
20
(No Transcript)
21
(No Transcript)
22
(No Transcript)
23
(No Transcript)
24

• Free Lunch Eligibility

25
(No Transcript)
26
(No Transcript)
27
(No Transcript)
28
(No Transcript)
29
(No Transcript)
30
(No Transcript)
31
(No Transcript)
32

• Similar patterns are apparent
• in many inner-ring suburbs
• Northwest Suburbs
• Race and Ethnicity

33
(No Transcript)
34
(No Transcript)
35
(No Transcript)
36
(No Transcript)
37
(No Transcript)
38
(No Transcript)
39
(No Transcript)
40
(No Transcript)
41
(No Transcript)
42
(No Transcript)
43
(No Transcript)
44
Northwest SuburbsFree Lunch Eligibility
45
(No Transcript)
46
(No Transcript)
47
(No Transcript)
48
(No Transcript)
49
(No Transcript)
50
(No Transcript)
51
(No Transcript)
52
(No Transcript)
53
(No Transcript)
54
Southwest SuburbsRace and Ethnicity
55
(No Transcript)
56
(No Transcript)
57
(No Transcript)
58
(No Transcript)
59
(No Transcript)
60
(No Transcript)
61
(No Transcript)
62
(No Transcript)
63
(No Transcript)
64
(No Transcript)
65
(No Transcript)
66
Southwest Suburbs Free Lunch Eligibility
67
(No Transcript)
68
(No Transcript)
69
(No Transcript)
70
(No Transcript)
71
(No Transcript)
72
(No Transcript)
73
(No Transcript)
74
(No Transcript)
75
(No Transcript)
76
How Does This Happen?

• Pervasive Housing Discrimination
• Steering
• Discrimination in sales and rentals
• Mortgage discrimination
• Consequences
• Whites steered away
• Housing prices suffer and residents lose home
  equity the main source of wealth for
  middle-class households
• Poor move in
• Schools lose income and racial diversity
• Process perpetuates itself

77
How Does This Happen?

• The Association between racial segregation of
  African American students and poverty intensified
  during the 1990s in the Twin Cities Metropolitan
  Area
• In 1992, 55 of students in predominantly Black
  schools were eligible for the free lunch program
• By 2002, the percentage had grown to 73
• Free lunch eligibility rates declined in all
  other school types (predominantly White,
  White/Hispanic integrated, White/Black
  integrated, White/Other integrated and
  Multi-ethnic
• In 2002, 53 of Black students went to elementary
  schools with free lunch eligibility rates greater
  than 40, compared to 5 for White students

78
How Does This Happen?

• Public Programs
• Low-Income Housing Tax Credits
• Section 8 Housing Vouchers

79
(No Transcript)
80
(No Transcript)
81
(No Transcript)
82
(No Transcript)
83
How Does This Happen?

• Decisions by School Districts

84
(No Transcript)
85
What Can We Do?

• Work as a region to integrate our schools and
  neighborhoods
• Segregation in schools and neighborhoods are
  closely related.
• Guaranteed access to integrated schools helps
  neighborhoods to remain integrated.

86
(No Transcript)
87
(No Transcript)
88
(No Transcript)
89
Fiscal Capacity and Fiscal Stress
90
(No Transcript)
91
(No Transcript)
92
(No Transcript)
93
(No Transcript)
94
Fiscal Inequality and the Fiscal Disparities
Program

• Despite the fact that fragmentation correlates
  with fiscal inequality, the Twin Cities metro
  compares relatively well to other regions,
  ranking 6th best
• Its Gini coefficient is 35 lower than predicted
  by its fragmentation rate, largely as the result
  of the Fiscal Disparities Program
• But we could do better. Portland, which has no
  tax base sharing program has a Gini 50 lower
  than predicted

95
(No Transcript)
96
(No Transcript)
97
The Fiscal Disparities Program currently
reduces inequality (measured by the Gini
coefficient) in the 7-county area by about 20.
98
(No Transcript)
99

• Adding the collar counties a low tax capacity
  part of the region to the program would further
  reduce inequality.
• If the collar counties were part of Fiscal
  Disparities
• 78 of 88 collar county municipalities would be
  net beneficiaries and the typical net increase in
  tax base would be 11 percent
• 80 percent of collar county population is in
  these municipalities

100
(No Transcript)
101
Community Classification

• Grouped all of the municipalities in the
  11-county metropolitan area by
• Tax Capacity per household
• Jobs per household
• Poverty rate
• Household growth from 1993 to 2003
• Household density
• Median age of housing

102
(No Transcript)
103
(No Transcript)
104
Access to Growing Job Centersin the Suburbs
105

• Important trends in the Twin Cities affecting
  access to jobs for minority and low-income
  populations
• Continuing decentralization of jobs and
  population
• Increasing traffic congestion, especially in
  suburban areas where jobs are growing most
  quickly
• Lack of affordable housing in highest-opportunity
  parts of the region

106
Twin Cities Job Centers

• Defined as contiguous Traffic Analysis Zones
  (TAZs) with greater than average numbers of jobs
  per square mile. Large job agglomerations like
  those in the centers of Minneapolis and St. Paul
  were divided into components based on job
  densities.
• This yielded 41 employment centers. (See map and
  table following two pages.)
• Job centers are scattered across the region but
  are more likely to be in the western and
  southwestern parts of the region. They range in
  size from 140,000 to 1,100 jobs in 2000.

107
(No Transcript)
108
(No Transcript)
109
Job Growth and Race of Workers by Type of Job
Center

• Employment centers were grouped into five
  categories Central Business Districts Other
  Central City Centers Inner Suburbs Middle
  Suburbs and Outer Suburbs
• In 2000, 24 of regional jobs were in the two
  central city categories, down from 28 in 1990.
  The share of jobs in the 3 suburban categories
  was 28 in both years. The share outside of job
  centers increased from 45 to 48.
• Job center growth rates increased with distance
  from the core of the region and the number of
  jobs outside of job centers grew more quickly
  than in any of the job center categories except
  outer suburbs. Jobs were decentralizing and
  becoming more diffused.

110
(No Transcript)
111
(No Transcript)
112
Race of Workers by Type of Job Center

• In 2000, Black workers were far more likely to
  work in the central cities than other population
  groups 40 of Blacks worked in the 2 central
  city categories compared to 23 for Whites, 29
  for Hispanics and 32 for other races.
• Black workers were less likely than any other
  group to work in middle suburb job centers, outer
  suburb job centers or areas outside of job
  centers the types of job centers that were
  growing most rapidly.

113
(No Transcript)
114
Commuter-shed Analysis

• Journey-to-work data compiled at the Traffic
  Analysis Zone (TAZ) level by the 1990 and 2000
  Census Transportation Planning Packages was used
  to analyze commuting patterns into the 22 largest
  job centers.
• Data for travel time from every TAZ to every
  other TAZ was used to derive the areas around
  each job center representing 0-20 minute, 20-30
  minute, 30-40 minute and gt 40 minute commutes
  into the centers.
• The characteristics of the population residing
  within each type of commuter shed were derived by
  overlaying the commuter-sheds on 2000 Census data.

115
Commuter-shed Analysis General Patterns

• The farther the job center is from the core of
  the region, the less accessible the center is to
  affordable housing, lower income people and
  people of color. (Affordable housing rates are
  highest closest to the Minneapolis CBD and the
  University of Minnesota center and in the 30-40
  minute commuting zone in Eden Prairie.
• Commuting zones are larger for suburban centers
  than urban centers in both years, reflecting
  greater congestion in the core.

116
Commuter-shed Analysis General Patterns

• Commuter-sheds shrunk during the 1990s
  everywhere, reflecting growing traffic
  congestion. Prior work showed that commuter-sheds
  increased in size during the 1980s when
  congestion levels were significantly lower.
• Commuter-shed shrinkage was proportionately
  greater in suburban job centers. Commuter-sheds
  were much more similar (urban versus suburban) in
  2000 than in 1990. The implication is that
  congestion increased more rapidly in the suburbs,
  making access from the core more difficult.
• Two examples that illustrate these general
  patterns are shown on the following pages the
  Minneapolis CBD and the Eden Prairie job center
  (a high income middle suburb).

117
(No Transcript)
118
(No Transcript)
119
(No Transcript)
120
(No Transcript)
121
(No Transcript)
122
Contact Ushttp//www.irpumn.org