Regional Analysis of Impediments to Fair Housing (RAI) Part 1
1. CARRAS
COMMUNITY INVESTMENT, INC.
Part 1:
Seven/50
Regional Analysis of Impediments to Fair Housing (RAI)
OCTOBER 2012 DRAFT
In partial fulfillment of the requirements of Fair Housing Planning for the Seven|50 Southeast Florida
Prosperity Plan—HUD Sustainable Communities Regional Planning Initiative
PART 1, SECTIONS:
1 Introduction: Analyzing Impediments to Fair Housing
2 SEFLA Region Background Data
3 Fair Housing Profile
4 Lending Profile
5 Identified Impediments
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT |1
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2. Executive Summary
This report contains a Regional Analysis of Impediments to fair housing (RAI) which identifies, explains, and analyzes the fair housing
milieu in Southeast Florida (SEFLA). It is produced in partial fulfillment of HUD defined Fair Housing Equity Assessment (FHEA)
requirements for the Seven|50 regional plan. This plan is being produced by a consortium led by the South Florida and Treasure Coast
Regional Planning Councils as a grantee of HUD’s Sustainable Communities Regional Planning Initiative. The counties included in this
analysis, listed in order from north to south, are 1) Indian River, 2) Martin, 3) St. Lucie, 4) Palm Beach, 5) Broward, 6) Miami-Dade, and 7)
Monroe.
Summary of Key Findings:
1. SEFLA Region Background Data
The region has very high levels of cost-burdened households especially for renters. 60% of renting households, regardless of
income, pay more than 30% of their monthly income on housing costs while 46% of household that own pay the same
proportion.
Our analysis identifies single female householders with children as especially in need. As a region, one third of all single-
female households with children are below poverty level.
efficient public transportation options are lacking throughout the entire region—the development of which are especially
essential near areas that are primarily minority and renter-occupied when employment opportunities are not located near
these areas
2. Fair Housing Profile
Assisted housing units are highly concentrated: 94% of all units within properties that offer assisted housing are assisted.
The vast majority of assisted housing units are reserved for renters in the 55-60% AMI. Only 627 of the nearly 85,000 assisted
housing units in SEFLA are reserved for those in the lowest income bracket, and therefore those in the greatest need of
affordable housing opportunities. 512 of these are in Broward County compared to only 40 in Miami-Dade (which has the
highest poverty rate in the region at 17%); none are located in Indian River, St. Lucie and Martin Counties.
Disability is, over the 5-year period and for each county, the largest alleged discriminating factor in fair housing
complaints (43%). This is followed by race (17%), national origin (13%), and familial status (11%).
3. Lending Profile
There are disparities in loan origination rates and subprime lending rates across the seven South Florida counties. Though
these disparities are seen across racial groups, the data suggests no racial group at a significant disparity or disadvantage
across all seven counties.
4. Top 10 Identified Impediments
1: Lack of Knowledge, Awareness of, or Education on Fair Housing Protections
2: Fair and Equal Lending Disparities
3: Housing/Lending Discrimination on the Basis of Race, Color, National Origin, Religion, Sex, Familial Status and Disability
4: Shortage of Affordable Housing Opportunities
5: Violations of Federal, State and Local Housing Laws
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3. 6: Housing Market Segregation
7: Predatory Lending
8: Limited Funding to Meet Need for Affordable Housing
9: Zoning/Land Use
10: Improvement of the Housing Discrimination Complaint Process
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4. 1. Analyzing Impediments to Fair Housing
The right to fair housing choice is among America’s most basic civil
rights as defined by federal, state and local laws and as such it is
structurally integral to the Sustainable Communities Regional
Planning Grant program. Specifically, HUD defines impediments to
fair housing choice as:
• Any actions, omissions, or decisions taken because of race,
color, religion, sex, disability, familial status, or national origin
which restrict housing choices or the availability of housing
choices
• Any actions, omissions, or decisions which have the effect
of restricting housing choices or the availability of housing
choices on the basis of race, color, religion, sex, disability,
familial status, or national origin.
All households, regardless of arbitrary factors such as familial status
and race are guaranteed equal access to housing opportunities
yet disparities in the receipt of these opportunities based in such
grounds are still commonplace throughout regions. The seven-
county Southeast Florida Region (SEFLA) is no different.
Sustainable Communities Regional Grantees are therefore
required to complete a Fair Housing and Equity Assessment (FHEA)
and recommended to produce a Regional Analysis of
Impediments to fair housing (Regional AI) in hopes of addressing
these disparities.
The broad purpose of performing a Regional AI is to increase
housing choice through assembling fair housing information and
identifying problems. More specifically focusing on furthering fair
housing on a regional scale allows grantees to: Figure 1: SEFLA Region
1. Overcome spatial segregation making assisted housing
accessible to all in all areas of the metro region, which overcomes jurisdictional and artificial program delivery barriers.
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5. 2. The ability to integrate assisted housing waiting lists into one regional waiting list & the integration of racial or ethnic groups into
areas where they have low impact (areas where they compose less than 30% of population).
3. To make public housing a path to social mobility rather than housing of last resort by modernizing them to be appealing to both
current residents and suburban residents.
4. To secure the cooperation of other important actors whose impact upon fair housing is substantial (jobs, schools, transportation
agencies, social service agencies, Government not for Profits, Government Agencies).
5. To break down the statistical racial disparity between HUD’s public housing program and its Section 8 existing housing program
by encouraging more non-minorities by promoting desegregation within assisted and insured programs by establishing a one
stop metropolitan wide housing assistance, marketing, information and referral center.
6. To discourage discrimination in all programs by encouraging all persons regardless of color, national origin, sex, disability or
familial status to consider all housing options.
This report contains the SEFLA Regional AI. The counties included in this analysis, listed in order from north to south, are 1) Indian River, 2)
Martin, 3) St. Lucie, 4) Palm Beach, 5) Broward, 6) Miami-Dade, and 7) Monroe. While the study area is relatively large and
heterogeneous, there are definite benefits to conducting an AI at this scale as many fair housing issues, especially those most
intractable, are best addressed at a regional level. By analyzing fair housing on this level, the jurisdiction seeks to overcome spatial
separation and segregation by eliminating housing delivery barriers, integrating waiting lists between jurisdictions, and broadening the
housing choices available to all eligible participants throughout SEFLA.
As outlined in the U.S. Department of Housing and Urban Development, Office of Fair Housing and Equal Opportunity, Fair Housing
Planning Guide, recipients of HUD’s housing and community development grants must certify that they will affirmatively further fair
housing (AFFH). These provisions are found within the mandate of Section 808(e)(5) of the Fair Housing Act. The extent of the AFFH
obligation has never been defined statutorily. However, HUD defines it as requiring a grantee to:
1. Conduct an analysis to identify impediments to fair housing choice within the jurisdiction
2. Take appropriate actions to overcome the effects of any impediments identified through the analysis
3. Maintain records reflecting the analysis and actions taken in this regard. Grantee jurisdiction providing opportunities for inclusive
patterns of housing occupancy regardless of race, color religion, sex familial status, disability and national origin.
This report fulfills the first of three AFFH requirements by reviewing impediments to fair housing choice in the public and private sector.
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6. Entity Engaged to Conduct the 2012, Seven-50 SEFLA Regional AI
Carras Community Investment Inc. (CCI, Inc.)
CCI, Inc. is a nationally recognized leader in implementing asset-based strategies for housing and community
development. Our professional expertise in affordable housing, fair lending, and economic development includes
advisory services in market analysis, strategic planning, and financing. Over the past thirty years, CCI, Inc. has provided
planning services to over 200 clients across the country, resulting in over $10 billion of investment in underserved
communities.
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7. Methodology and Data Sources
Regional Profile - Methodology
This section includes background data on the jurisdiction to serve as bases for identifying and contextualizing
impediments. Variable are chosen that relate to the degree of segregation and restricted housing by race and ethnicity,
and families with children in particular (see table1). Variables and data sources are also chosen to parallel as best as
possible a dataset compiled by HUD’s office of Policy Development & Research (PD&R). This dataset was intended to
provide program participants with data to support this analysis and additional fair housing research. Regrettably
however, the data package provided for SEFLA was incomplete (only data for the three most southern counties was
provided -Broward, Miami-Dade and Monroe) and therefore inappropriate to use for the full regional profile. However,
given that a large proportion of the population, especially minority residents, is located within Broward and Miami-Dade
counties this information is still relevant to the discussion. Therefore, this data is summarized in the Appendix under the HUD
PD&R Data Package section. Descriptions of their variables and methodology are cited directly from the FHEA 2012 Data
Documentation guide provided to all entitlement regions through HUD’s regional planning grant program.
Data within this section is collected at both the census tract and county level. Given the large area analyzed in this report
most data is summarized at a county level. Data displayed within maps, however, utilizes census tract level data to show,
in detail, the spatial relationship and patterns of variables within counties and throughout the region as a whole. Per the
2010 Census, a total of 1,333 populated census tracts exist across the seven counties of Southeast Florida: 29 in Indian
River County, 43 in St. Lucie County, 34 in Martin County, 331 in Palm Beach County, 360 in Broward County, 508 in Miami-
Dade County, and 28 in Monroe County. When reading the report maps, it is important to consider that lower population
densities and distributions are likelier to occur in geographically larger areas such as those in the Western portions of most
counties and the more northern counties.
Most data comes from the American Community Survey 2006-2010 estimates. Where census 2010 data is available
however it is used in place of ACS data to allay concerns about sampling error. Table 2 lists the specific data source for
variables within the Regional Profile section.
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8. Table 1: Data Sources for the Regional Background Profile Section Table 2: Populated Census Tracts by County
Section Variable Data Source County Number of Populated Census Tracts
Population totals and density Indian River 29
Demographics 2010 Census SF1
Age St. Lucie 43
Segregation Race and Ethnicity 2010 Census SF1
Martin 34
Tenancy
Housing ACS 2006-2010 Palm Beach 331
Cost Burdon
Broward 360
Family Poverty Rate
Poverty ACS 2006-2010 Miami-Dade 508
Poverty By Race & Ethnicity
Unemployment Monroe 28
Labor force Participation Rate TOTAL 1,333
Labor and Commuting ACS 2006-2010
Commute Time
Commute Mode
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9. Fair Housing Profile - Methodology
The process creating a Fair Housing Profile included review national and local studies/reports, and data gathered from local agencies
and organizations. Major data sources include:
• All most-recent existing AIs produced by local jurisdictions within SEFLA
INDIAN RIVER ST. LUCIE MARTIN PALM BEACH MIAMI-DADE MONROE
County BROWARD COUNTY
COUNTY COUNTY COUNTY COUNTY COUNTY COUNTY
• None • City Of Port • None • Palm Beach • Broward County • Miami-Dade • None
Saint Lucie County • City Of Coconut County
• City Of Fort • City Of Boca Creek • City Of
Pierce Raton • City Of Coral Miami
• City Of Boynton Springs • City Of
Beach • City Of Hollywood Miami Beach
• City Of Deerfield • City Of Fort • City Of
Beach Lauderdale Miami
• City Of Delray • City Of Lauderhill Gardens
Beach • City Of Miramar • City Of North
Entitlement • City Of West • City Of Margate Miami
Jurisdiction Palm Beach • City Of Pembroke • City Of
• Town Of Pines Homestead
Wellington • City Of Plantation • City Of
• Town Of Jupiter • City Of Pompano Hialeah
Beach
• City Of Sunrise
• City Of Tamarac
• City Of Westin
• Town Of Davie
• Florida Housing Data Clearing House (Existing Assisted Housing Inventory)
• Data from various state and local Fair Housing Agencies
o Florida Commission on Human Relations
o Palm Beach County Office of Equal Opportunity
o Broward County Office of Equal Opportunity | Civil Rights Division
o Miami-Dade Office of Human Rights and Fair Employment Practices
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10. Lending Profile- Methodology
Lending data for this section was retrieved from the University of Florida Housing Data Clearinghouse. Racial lending data and overall
2010 lending data by county and for the State of Florida were analyzed to identify disparities and trends in lending patterns by race,
ethnicity and by county. The data used for the county lending analysis is original research, due to the fact that the most recent lending
data in the existing county-level Analysis of Impediments to Fair Housing documents available (Miami-Dade & Broward County) are
from the years 2008 & 2009. The data used in this analysis is more recent, from the year 2010.
Identified Impediments to Fair Housing- Methodology
This section of the South Florida Regional Analysis of Impediments to Fair Housing Choice examines the ten most prevalent impediments
to fair housing choice in the region. This examination was done through the examination of available analysis of impediments (AIs) to
fair housing choice documents for entitled communities within the study-recognized seven-county south Florida region, both at the
municipal and at the county level. Three countywide and twenty-eight municipal-level AIs were consulted in this analysis. Two counties
in the region, Martin County & Monroe County, lack entitled communities and information on the impediments to fair housing within
these counties are not included within this analysis, though, since the issues pointed out in the other counties and municipalities in the
region are largely similar, it is likely that the non-entitled counties experience impediments similar to those discussed in this analysis.
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11. CARRAS
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2. SEFLA Regional Background Data: CONTEXTUALIZING THE FAIR HOUSING DISCUSSION
This section discusses data primarily at the county and regional level, although maps are displayed using census tract level data to
more accurately represent spatial patterns. Municipalities and landmark areas are referenced occasionally to contextualize and orient
the discussion but are not the primary units of analysis.
Demographics
• Total Population: 138,028
Indian River • Population Density: 274.5 people/mi2
County • Dominant Age Group: 50-54
SEFLA, Total Population by Rank, 2010
• Total Population: 277,789
St. Lucie • Population Density: 485.7 people/mi2
County • Dominant Age Group: 45-49
Miami-Dade County 2,496,435
• Total Population: 146,318
Martin • Population Density: 269.2 people/mi2 Broward County 1,748,066
County • Dominant Age Group: 50-54
Palm Beach County 1,320,134
• Total Population: 1,320,134
Palm Beach • Population Density: 670.2 people/mi2 St. Lucie County 277,789
County • Dominant Age Group: 45 to 49
Martin County 146,318
• Total Population: 1,748,066
Broward • Population Density: 1,444.9 people/mi2
Indian River County 138,028
County • Dominant Age Group: 45 to 49
Monroe County 73,090
• Total Population: 2,496,435
Miami-Dade • Population Density: 1.315.5 people/mi2
County • Dominant Age Group: 45 to 49 Figure 2: SEFLA, Total Population by Rank, 2010
• Total Population: 73,090
Monroe • Population Density: 74.3 people/mi2
County • Dominant Age Group: 55 to 59
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12. The three most populous counties are, in decreasing
order, Miami-Dade, Broward, and Palm Beach.
These three counties are similarly the densest in terms
of population per square mile. Given Broward
County’s smaller land area however, population
density is actually higher within Broward than Miami-
Dade. Map 1, to the left, shows that the region’s
population is also concentrated in the eastern
portion of the counties, which is a reflection of both
historic settlement patterns as well as the Everglade
swamp areas to the west. In all, the region has a
total population of over 6 million and a population
density of around 800 people per square mile. That
is equivalent to the 5th largest metropolitan region in
the United States.
Map 1: Population Density, Seven-50 SE Florida Region, 2010
• Total Population: 6,199,860
SEFLA • Population Density: 807.4 people
per mi2
• Dominant Age Group: 45-49
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13. SEFLA, Population Density by Rank, 2010
Broward County 1444.9
Miami-Dade County 1315.5
7-County SE Florida Region 807.4
Palm Beach County 670.2
St. Lucie County 485.7
Indian River County 274.5
Martin County 269.2
Monroe County 74.3
Figure 3: SEFLA, Population Density by Rank, 2010
Race & Ethnicity
Three primary categories of race and ethnicity are discussed within this analysis (White, African American, and Hispanic/Latino). These
three categories account for the large majority of all persons living in SEFLA. Persons of other ancestries or of two or more races are not
analyzed in this report because of their less significant representation within the study area. It is important to note, people of Hispanic
origin may be any race. This should be kept in mind when comparing race and ethnicity, which is done throughout the report.
Someone of Black or White race may also be categorized as Hispanic due to Census methodology.
Within this section, the spatial and segregation patterns of residence by race and ethnicity are the focus. Beyond segregation patterns,
race & ethnicity are analyzed in conjunction with other variables throughout the remainder of the Regional Profile; in analyzing
equitable access to fair housing, understanding the relationship of race and ethnicity to other germane variables is fundamentally
important.
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14. Indian River
15,465
12,397
116,346
White
Black or African American
Hispanic or Latino:
Map 2: Indian River County Race/Ethnicity Dot Map Figure 4: Indian River County, Population by Race/Ethnicity 2010
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15. St. Lucie County
45,995
53,036
199,336
White
Black or African American
Hispanic or Latino:
Map 3: St. Lucie County Race/Ethnicity Dot Map Figure 5: St. Lucie County, Population by Race/Ethnicity 2010
Martin County
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16. 45,995
53,036
199,336
White
Black or African American
Hispanic or Latino:
Figure 6: Martin County, Population by Race/Ethnicity 2010
Map 4: Martin County Race/Ethnicity Dot Map
Palm Beach County
250,823 White
Black or African
228,690 American
970,121 Hispanic or Latino:
Figure 7: Palm beach County, Population by Race/Ethnicity 2010
Map 5: Palm Beach County Race/Ethnicity Dot Map
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17. Broward County
White
438,247
Black or African
American
467,519 1,102,231 Hispanic or Latino:
Figure 8: Broward County, Population by Race/Ethnicity 2010
Map 6: Broward County Race/Ethnicity Dot Map
Miami-Dade County
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18. White
1,623,859 Black or
1,841,887
African
American
Hispanic or
Latino:
472,976
Figure 9: Miami-Dade County, Population by Race/Ethnicity 2010
Map 7: Miami-Dade County Race/Ethnicity Dot Map
Monroe County
15,071
White
4,194 Black or African
American
65,409 Hispanic or
Latino:
Map 8: Monroe County Race/Ethnicity Dot Map
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19. Figure 10: Monroe County, Population by Race/Ethnicity 2010
SEFLA Region
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20. Within the regions total population of 6.1 million, nearly 4.5
million are white accounting for two thirds of the population.
2.1 million African American persons and 2.4 Hispanics of all
races reside within the SEFLA jurisdictional boundary. Monroe,
Martin, and Indian River Counties have the largest
percentages of white people in comparison to their total
39% populations. Similarly within these counties, the Hispanic and
Black populations are relatively dispersed. St. Lucie County
White has higher percentages of minority populations than the three
71% previously mentioned counties. Additionally within St. Lucie
Black or African there is a segregated concentration of African Americans to
American
20% the south of the St. Lucie County International Airport. Palm
Hispanic or Latino
Beach, Broward, and Monroe are more diverse in population
yet they also have higher levels of segregation. Areas where
African Americans are highly concentrated include north
Miami-Dade County, central Broward County, and the Belle
Figure 11: Race/ethnicity for the SEFLA Region, 2010 Glade and West Palm Beach areas in Palm Beach County.
Central Broward County and north Miami-Dade County both
have neighborhoods of historical African American affiliation
including Sistrunk, Lauderdale Lakes and Lauderhill in Broward
and Opa-locka and Miami Gardens in Miami-Dade.
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21. Housing
Housing occupancy by tenancy and monthly housing costs are the two major variables analyzed within this section. A
breakdown of these variables by race and ethnicity is also undertaken. Housing occupancy by tenure relates to
neighborhood stability in that high rental turnover tends to lend itself to fluctuating neighborhood conditions which is
generally viewed negatively. A housing unit is considered to be owner-occupied if the owner or co-owner lives in the unit,
even if it is mortgaged or not fully paid for. All other occupied units are classified as "renter occupied," including units
rented for cash rent and those occupied without payment of cash rent. Monthly housing costs as a percentage of
household income provides information on the cost of monthly housing expenses for owners and renters. The information
offers an excellent measure of housing affordability and excessive shelter costs. Households spending more than 30
percent of their monthly income on housing costs and considered cost-burdened and tend to be at risk of economic
hardship over time.
The trends of housing occupancy by tenancy and housing costs burden on a county scale are similar throughout the
SEFLA. Throughout the region, the vast majority of housing units are owner-occupied. This trend holds true for the white
population of each county, but is reversed for both Hispanics and African American households in each county. Renter-
occupied households as a whole are more likely to spend more than 30% of their monthly income on housing costs than
those that own. When considering various incomes, within lower income brackets there are more renters than owners.
Also within this income range, households that rent have higher probabilities of paying above 30% of their household
income than those that own. Conversely within the higher income brackets there are more owner-occupied housing
units and henceforth more owners are cost-burdened in these brackets. Proportionally, however renting households
making less than $20,000 are the most cost-burdened group within each county in SEFLA
In the region as a whole, there are 1.5 million owner-occupied housing units in comparison to .75 million renter-
occupied units. Spatially, in the urbanized areas of the counties, owner occupied housing is prominent inland in the more
suburban areas. Conversely rental opportunities are more common in the eastern and denser portions of the region. The
region has very high levels of cost-burdened households especially for renters. 60% of renting households, regardless of
income, pay more than 30% of their monthly income on housing costs while 46% of household that own pay the same
proportion. Moving into the future, more affordable housing options is a key issue for SEFLA.
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22. Indian River
Households paying 30% or more of their income on monthly housing
costs, 2010
Indian River County
30.0%
25.0%
20.0%
15.0%
10.0%
5.0%
0.0%
Less than $20,000 to $35,000 to $50,000 to $75,000 or
$20,000 $34,999 $49,999 $74,999 more
Owner-occupied Renter-occupied
Figure 12: Indian River County, Cost Burdened households by tenure, 2010
Hispanic or Latino 14%
origin 5%
Black or African Owner-
14% 13,374
American 5% occupied
housing units
81%
White Renter-
44,186 occupied
93% housing units
Renter-occupied housing units
Figure 13: Indian River Tenancy by Race/Ethnicity, 2010 Figure 14: Indian River County, Housing Occupancy by Tenure, 2010
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24. St. Lucie County
Households paying 30% or more of their income on monthly housing
costs, 2010
St. Lucie County
25.0%
20.0%
15.0%
10.0%
5.0%
0.0%
Less than $20,000 to $35,000 to $50,000 to $75,000 or
$20,000 $34,999 $49,999 $74,999 more
Owner-occupied Renter-occupied
Figure 15: St. Lucie County, Cost Burdened households by tenure, 2010
18%
Hispanic or Latino origin
9%
Black or African 24% Owner-
24,763
American 12% occupied
housing units
69% Renter-
White occupied
84% 78,340
housing units
Renter-occupied housing units
Owner-occupied housing units
Figure 16: St. Lucie County Tenancy by Race/Ethnicity, 2010 Figure 17: St. Lucie County, Housing Occupancy by Tenure, 2010
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26. Martin County
Households paying 30% or more of their income on monthly housing
costs, 2010
Martin County
25.0%
20.0%
15.0%
10.0%
5.0%
0.0%
Less than $20,000 to $35,000 to $50,000 to $75,000 or
$20,000 $34,999 $49,999 $74,999 more
Owner-occupied Renter-occupied
Figure 18: Martin County, Cost Burdened households by tenure, 2010
16%
Hispanic or Latino origin
4%
12,140
Black or African 7% Owner-occupied
American 2% housing units
Renter-occupied
86% housing units
White 47,063
96%
Renter-occupied housing units
Owner-occupied housing units
Figure 20: Martin County, Housing Occupancy by Tenure, 2010
Figure 19: Martin County, Tenancy by Race/Ethnicity, 2010
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28. Palm Beach County
Households paying 30% or more of their income on monthly
housing costs, 2010
Palm Beach County
25.0%
20.0%
15.0%
10.0%
5.0%
0.0%
Less than $20,000 to $35,000 to $50,000 to $75,000 or
$20,000 $34,999 $49,999 $74,999 more
Owner-occupied Renter-occupied
Figure 21: Palm Beach County, Cost Burdened households by tenure, 2010
Hispanic or 21%
Latino origin 10%
Black or 138,155 Owner-
24%
African occupied
9%
American housing units
384,995
Renter-
67% occupied
White
87% housing units
Renter-occupied housing units
Figure 23: Palm Beach County, Housing Occupancy by Tenure, 2010
Figure 22: Palm Beach County, Tenancy by Race/Ethnicity, 2010
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30. Broward County
Households paying 30% or more of their income on monthly
housing costs, 2010
Broward County
25.0%
20.0%
15.0%
10.0%
5.0%
0.0%
Less than $20,000 to $35,000 to $50,000 to $75,000 or
$20,000 $34,999 $49,999 $74,999 more
Owner-occupied Renter-occupied
Figure 24: Broward County, Cost Burdened households by tenure, 2010
Hispanic or Latino origin 23%
18%
Black or African 32% Owner-
American 17% 205,387 occupied
housing units
White 59%
76% Renter-
463,511 occupied
housing units
Renter-occupied housing units
Owner-occupied housing units
Figure 25: Broward County, Tenancy by Race/Ethnicity, 2010
Figure 26: Broward County, Housing Occupancy by Tenure, 2010
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32. Miami-Dade County
Households paying 30% or more of their income on monthly
housing costs, 2010
Miami-Dade County
35.0%
30.0%
25.0%
20.0%
15.0%
10.0%
5.0%
0.0%
Less than $20,000 to $35,000 to $50,000 to $75,000 or
$20,000 $34,999 $49,999 $74,999 more
Owner-occupied Renter-occupied
Figure 27: Miami-Dade County, Cost Burdened households by tenure, 2010
Hispanic or Latino origin 66%
62% Owner-
occupied
Black or African 22% 347,024 housing units
American 14%
480,532 Renter-
occupied
White 71%
79% housing units
Renter-occupied housing units
Owner-occupied housing units
Figure 28: Miami-Dade County, Tenancy by Race/Ethnicity, 2010 Figure 29: Miami-Dade County, Housing Occupancy by Tenure, 2010
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33. Monroe County
Households paying 30% or more of their income on monthly
housing costs, 2010
Monroe County
20.0%
15.0%
10.0%
5.0%
0.0%
Less than $20,000 to $35,000 to $50,000 to $75,000 or
$20,000 $34,999 $49,999 $74,999 more
Owner-occupied Renter-occupied
Figure 30: Monroe County, Cost Burdened households by tenure, 2010
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34. 22%
Hispanic or Latino origin
12%
Owner-
Black or African 8% occupied
10,581
American 3% housing units
19,210 Renter-
occupied
89% housing units
White
95%
Renter-occupied housing units
Owner-occupied housing units
Figure 31: Monroe County, Tenancy by Race/Ethnicity, 2010 Figure 32: Monroe County, Housing Occupancy by Tenure, 2010
SEFLA Region
Table 3: Occupied Housing Units by Race/Ethnicity and Tenure, 2010- SEFLA Region
Occupied housing Owner-occupied housing Renter-occupied housing
units units units
Total 2,269,261 1,517,837 751,424
White 84% 87% 75%
Black or African
12% 9% 19%
American
Hispanic or Latino origin 19% 17% 26%
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35. Tenure of Occupied Housing Units:
751,424
1,517,837
Owner-occupied housing units
Renter-occupied housing units
Figure 33: SEFLA Region, Occupied Housing Units by tenure, 2010
Map 9: Occupied Housing Units by tenure,2010, SEFLA Region
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36. Tenure of Occupied Housing by County and for the SEFLA Region
60% 58% 57% 56% 57% 61% 60%
46% 51% 48% 50% 46%
43% 42%
34% 35%
Renter-occupied
Renter-occupied
Renter-occupied
Renter-occupied
Renter-occupied
Renter-occupied
Renter-occupied
Renter-occupied
Owner-occupied
Owner-occupied
Owner-occupied
Owner-occupied
Owner-occupied
Owner-occupied
Owner-occupied
Owner-occupied
7-County SE Florida Indian River St. Lucie County, Martin County, Palm Beach Broward County, Miami-Dade Monroe County,
Region Average County, Florida Florida Florida County, Florida Florida County, Florida Florida
Figure 34: Seven-50 SE Florida Region Occupied Housing Units by Tenure and County, 2010
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37. Households paying 30% or more of their income on monthly
housing costs, 2010
SEFLA Region
20.00%
15.00%
10.00%
5.00%
0.00%
Less than $20,000 to $35,000 to $50,000 to $75,000 or
$20,000 $34,999 $49,999 $74,999 more
Owner-occupied housing units Renter-occupied housing units
Figure 35: Seve-50 SE Florida Region, Cost Burdened households by tenure, 2010
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38. Poverty
This section summarizes both individual and family poverty rates within the 7 counties individually as well as for SEFLA as
a whole. Poverty indicators show the percentage of individuals or families that are below poverty threshold. The Census
Bureau identifies poverty thresholds according to the composition of the household; different types of households (by age
and size) have different poverty thresholds. Since poverty is defined at the family level and not the household level, the
poverty status of the household is determined by the poverty status of the householder. “Population below poverty level”
refers to the sum of people in families and the number of unrelated individuals identified as poor. We summarize individual
poverty rates by race/ethnicity and age. The family poverty rate distinguishes between families and families with children
under the age of 18, which is then further divided into various household types including married couples below the
poverty level and single female householders below the poverty level.
For SEFLA poverty is a large concern. In total there are over 850,000 people below poverty level, 13% percent of the
total population. 15% of all families with children under the age of 18 are below the poverty level and of the population
under 18, one fifth are living below the poverty line. Miami-Dade has the highest proportion of individuals living in poverty
at 17%. Furthermore, poverty is clearly linked to race and ethnicity throughout the region. While the predominant race
throughout the region is white, proportionally there are about half as many white people in poverty in comparison to both
African American and Hispanic populations. Finally, our analysis identifies single female householders with children as
especially in need. As a region, one third of all single-female households with children are below poverty level. In St. Lucie
County, the proportion reaches its highest at 37% and within other counties the lowest this percentage reaches is 27% in
Broward.
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39. Indian River
16,984
9,322
5,322
2,340
Population for Under 18 years 18 to 64 years 65 years and
whom poverty over
status is
determined
Figure 36: Indian River County, Individuals below poverty level, 2010
% Female householders with no 7.50%
31%
husband present below White
27%
Poverty Level
18.20%
% Married Couples below 9% Black or African
Poverty Level 5% American
Hispanic or Latino origin
16% 23.80% (of any race)
% Families Below Poverty Level
9%
With related children under 18 years Families
Figure 37: Indian River County, Family Poverty Rates, 2010
Figure 38: Indian River County, Poverty Rate by Race and Ethnicity, 2010
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40. St. Lucie County
36,457
19,513
12,725
4,219
Population for Under 18 years 18 to 64 years 65 years and
whom poverty over
status is
determined
Figure 39: St. Lucie County, Individuals below poverty level, 2010
37% 7.70%
% Female householders with
no husband present below White
27%
Poverty Level
19.00%
% Married Couples below 9% Black or African
Poverty Level 6% American
Hispanic or Latino origin
% Families Below Poverty 17% (of any race)
Level 10% 19.60%
With related children under 18 years Families
Figure 40: St. Lucie County, Family Poverty Rates, 2010
Figure 41: St. Lucie County, Poverty Rate by Race and Ethnicity, 2010
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42. Martin County
14,724
8,046
4,507
2,171
Population for Under 18 years 18 to 64 years 65 years and
whom poverty over
status is
determined
Figure 42: Martin County, Individuals below poverty level, 2010
4.80%
% Female householders with no
34%
husband present below White
25%
Poverty Level
% Married Couples below 7% Black or African
Poverty Level 3% 17.30% American
30.90%
Hispanic or Latino origin
13% (of any race)
% Families Below Poverty Level
6%
With related children under 18 years Families
Figure 43: Martin County, Family Poverty Rates, 2010
Figure 44: Martin County, Poverty Rate by Race and Ethnicity, 2010
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43. Palm Beach County
156,759
86,743
48,840
21,176
Population for Under 18 years 18 to 64 years 65 years and
whom poverty over
status is
determined
Figure 45: Palm Beach County, Individuals below poverty level, 2010
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44. 6.00%
% Female householders with no
31%
husband present below White
24%
Poverty Level
16.60%
% Married Couples below 7% Black or African
Poverty Level 5% American
Hispanic or Latino origin
15% (of any race)
% Families Below Poverty Level 19.80%
9%
With related children under 18 years Families
Figure 46: Palm Beach County, Family Poverty Rates, 2010
Figure 47: Palm Beach County, Poverty Rate by Race and Ethnicity, 2010
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45. Broward County
210,964
118,477
63,164
29,323
Population for Under 18 years 18 to 64 years 65 years and
whom poverty over
status is
determined
Figure 48: Broward County, Individuals below poverty level, 2010
6.20%
% Female householders with no
27%
husband present below 9.40% White
21%
Poverty Level
% Married Couples below 6% Black or African
Poverty Level 5% American
Hispanic or Latino origin
13% (of any race)
% Families Below Poverty Level
9%
16.20%
With related children under 18 years Families
Figure 49: Broward County, Family Poverty Rates, 2010
Figure 50: Broward County, Poverty Rate by Race and Ethnicity, 2010
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47. Miami-Dade County
410,093
217,985
118,792
73,316
Population for Under 18 years 18 to 64 years 65 years and
whom poverty over
status is
determined
Figure 51: Miami-Dade County, Individuals below poverty level, 2010
% Female householders with no
35% 11.90%
husband present below 13.90% White
26%
Poverty Level
% Married Couples below 10% Black or African
Poverty Level 9% American
Hispanic or Latino origin
18% (of any race)
% Families Below Poverty Level
14%
22.10%
With related children under 18 years Families
Figure 52: Miami-Dade County, Family Poverty Rates, 2010
Figure 53: Miami-Dade County, Poverty Rate by Race and Ethnicity, 2010
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49. Monroe County
7,776
5,327
1,275 1,174
Population for Under 18 years 18 to 64 years 65 years and
whom poverty over
status is
determined
Figure 54: Monroe County, Individuals below poverty level, 2010
6.70%
% Female householders with no
30%
husband present below White
25%
Poverty Level 12.60%
% Married Couples below 3% Black or African
Poverty Level 4% American
Hispanic or Latino origin
10% (of any race)
% Families Below Poverty Level
7% 12.40%
With related children under 18 years Families
Figure 55: Monroe County, Family Poverty Rates, 2010
Figure 56: Monroe County, Poverty Rate by Race and Ethnicity, 2010
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50. SEFLA Region
853,757
465,413
254,625
133,719
Population for Under 18 years 18 to 64 years 65 years and
whom poverty over
status is
determined
Figure 57: SEFLA Region, Individuals below poverty level, 2010
% Female householders with 7.26%
32%
no husband present below
25%
Poverty Level
White
% Married Couples below 7% 17.23%
Poverty Level 5%
Black or African
American
% Families Below Poverty 15%
Level 9% Hispanic or Latino origin
(of any race)
18.74%
With related children under 18 years Families
Figure 58: SEFLA Region, Family Poverty Rates, 2010
Figure 59: SEFLA Region, Poverty Rate by Race and Ethnicity, 2010
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51. 17%
14%
13% 12% 12%
10% 11%
Figure 61: SEFLA Region, Percent Population below poverty level by county, 2010
Figure 60: SEFLA Region, Percent Population below poverty level by census
tract, 2010
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52. Labor Force and Commuting
This section examines the labor force participation rate as well as basic commuting trends by county and for the
region. The labor force participation rate is a representation of the proportion of the area’s population in the labor force.
This includes both employed and unemployed (job-seeking) civilians 16 years and over as well as members of the U.S.
Armed Forces (people on active duty with the United States Army, Air Force, Navy, Marine Corps, or Coast Guard).
Conversely, those not in the labor force includes all people 16 years old and over who are not accounted for by the labor
force participation rate. These are typically students, retired workers, homemakers, institutionalized people and people
doing incidental unpaid family work. Of the 7 counties, Broward has the highest labor force participation rate at 68%.
Both Martin and Indian River have the lowest at 55%. The region on average has a labor force participation of 60%
compared to 65% in the United State.
Commuting trends may seem out of place in a fair housing assessment but commuting patterns are directly reflective
of the relationship between housing and jobs. To understand commuting trends in this section we summarize mean travel
time to work by mode of travel, mode of travel by tenure, and mode of travel by race/ethnicity. Mean travel time to work
is measured in minutes and represents the average travel time that workers usually took to get from home to work. The
travel time also accounts for time spent waiting for public transportation, as well as for picking up carpool passengers.
Mode of travel refers to the method of transportation used to get from home to work. High travel times may indicate an
imbalance between jobs and housing. Similarly the relationship between tenure and transportation mode can inform the
type of transportation options that should be readily available to certain demographics.
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53. We find in the region that individuals utilizing public transportation options have higher average travel times to work.
And in all counties more renters use public transit than homeowners. The same is true of minorities in comparison to white
persons. Overall there is a staggering difference between those that drive alone (78% in the 7-county area) and those
that use public transportation only (4%). This all indicates that efficient public transportation options are lacking
throughout the entire region—the development of which are especially essential near areas that are primarily minority
and renter-occupied when employment opportunities are not located near these areas.
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54. Indian River
50
40
30
45.50%
20
10
54.50%
0
Total Drive Alone Carpool Public
transportation
In labor force Not in labor force
Mean travel time to work (minutes)
Figure 62: Indian River County, Labor Force, 2010 Figure 63: Indian River County, Mean Travel Time to Work by Travel Mode, 2010
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55. 100.00%
90.00%
80.00%
80.00%
70.00% 70.00%
60.00% 60.00%
50.00% 50.00%
40.00%
40.00%
30.00%
30.00% 20.00%
20.00% 10.00%
10.00% 0.00%
0.00%
White
Black or African American
Owner-occupied housing units
Renter-occupied housing units Hispanic or Latino origin (of any
race)
Figure 64: Indian River County, Travel Mode by housing tenure, 2010 Figure 65: Indian River County, Travel Mode by race/ethnicity, 2010
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56. St. Lucie County
70
60
50
41.60%
40
30
58.40% 20
10
In labor force Not in labor force 0
Total Drive Alone Carpool Public
transportation
Figure 66: St. Lucie County, Labor Force, 2010
Mean travel time to work (minutes)
Figure 67: St. Lucie County, Mean Travel Time to Work by Travel Mode, 2010
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