SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT |1 Carras Community Investment, Inc.
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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
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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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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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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:
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.
Figure 1: SEFLA Region
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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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Enti ty 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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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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Table 1: Data Sources for the Regional Background Profile Section Section Variable Data Source
Demographics Population totals and density
2010 Census SF1 Age
Segregation Race and Ethnicity 2010 Census SF1
Housing Tenancy
ACS 2006-2010 Cost Burdon
Poverty Family Poverty Rate
ACS 2006-2010 Poverty By Race & Ethnicity
Labor and Commuting
Unemployment
ACS 2006-2010 Labor force Participation Rate
Commute Time
Commute Mode
Table 2: Populated Census Tracts by County County Number of Populated Census Tracts
Indian River 29
St. Lucie 43
Martin 34
Palm Beach 331
Broward 360
Miami-Dade 508
Monroe 28
TOTAL 1,333
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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
County INDIAN RIVER
COUNTY ST. LUCIE COUNTY
MARTIN COUNTY
PALM BEACH COUNTY
BROWARD COUNTY MIAMI-DADE
COUNTY MONROE COUNTY
Entitlement Jurisdiction
• None
• City Of Port Saint Lucie
• City Of Fort Pierce
• None
• Palm Beach
County • City Of Boca
Raton • City Of Boynton
Beach • City Of Deerfield
Beach • City Of Delray
Beach • City Of West
Palm Beach • Town Of
Wellington • Town Of Jupiter
• Broward County • City Of Coconut
Creek • City Of Coral
Springs • City Of Hollywood • City Of Fort
Lauderdale • City Of Lauderhill • City Of Miramar • City Of Margate • City Of Pembroke
Pines • City Of Plantation • City Of Pompano
Beach • City Of Sunrise • City Of Tamarac • City Of Westin • Town Of Davie
• Miami-Dade
County • City Of
Miami • City Of
Miami Beach • City Of
Miami Gardens
• City Of North Miami
• City Of Homestead
• City Of Hialeah
• None
• 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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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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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
Figure 2: SEFLA, Total Population by Rank, 2010
• Total Population: 138,028 • Population Density: 274.5 people/mi2
• Dominant Age Group: 50-54
Indian River County
• Total Population: 277,789 • Population Density: 485.7 people/mi2
• Dominant Age Group: 45-49
St. Lucie County
• Total Population: 146,318 • Population Density: 269.2 people/mi2
• Dominant Age Group: 50-54
Martin County
• Total Population: 1,320,134 • Population Density: 670.2 people/mi2
• Dominant Age Group: 45 to 49
Palm Beach County
• Total Population: 1,748,066 • Population Density: 1,444.9 people/mi2
• Dominant Age Group: 45 to 49
Broward County
• Total Population: 2,496,435 • Population Density: 1.315.5 people/mi2
• Dominant Age Group: 45 to 49
Miami-Dade County
• Total Population: 73,090 • Population Density: 74.3 people/mi2
• Dominant Age Group: 55 to 59
Monroe County
73,090
138,028
146,318
277,789
1,320,134
1,748,066
2,496,435
Monroe County
Indian River County
Martin County
St. Lucie County
Palm Beach County
Broward County
Miami-Dade County
SEFLA, Total Population by Rank, 2010
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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 • Population Density: 807.4 people per mi2
• Dominant Age Group: 45-49 SEFLA
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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.
74.3
269.2
274.5
485.7
670.2
807.4
1315.5
1444.9
Monroe County
Martin County
Indian River County
St. Lucie County
Palm Beach County
7-County SE Florida Region
Miami-Dade County
Broward County
SEFLA, Population Density by Rank, 2010
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Indian River
Map 2: Indian River County Race/Ethnicity Dot Map
Figure 4: Indian River County, Population by Race/Ethnicity 2010
116,346
12,397
15,465
White
Black or African American
Hispanic or Latino:
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St. Lucie County
Map 3: St. Lucie County Race/Ethnicity Dot Map
Figure 5: St. Lucie County, Population by Race/Ethnicity 2010
Martin County
199,336
53,036
45,995
White Black or African American Hispanic or Latino:
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Map 4: Martin County Race/Ethnicity Dot Map
Figure 6: Martin County, Population by Race/Ethnicity 2010
Palm Beach County
Map 5: Palm Beach County Race/Ethnicity Dot Map
Figure 7: Palm beach County, Population by Race/Ethnicity 2010
199,336
53,036
45,995
White
Black or African American
Hispanic or Latino:
970,121
228,690
250,823 White
Black or African American
Hispanic or Latino:
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Broward County
Map 6: Broward County Race/Ethnicity Dot Map
Figure 8: Broward County, Population by Race/Ethnicity 2010
Miami-Dade County
1,102,231 467,519
438,247 White
Black or African American
Hispanic or Latino:
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Map 7: Miami-Dade County Race/Ethnicity Dot Map
Figure 9: Miami-Dade County, Population by Race/Ethnicity 2010
Monroe County
Map 8: Monroe County Race/Ethnicity Dot Map
1,841,887
472,976
1,623,859
White
Black or African American
Hispanic or Latino:
65,409
4,194
15,071 White
Black or African American
Hispanic or Latino:
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Figure 10: Monroe County, Population by Race/Ethnicity 2010
SEFLA Region
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Figure 11: Race/ethnicity for the SEFLA Region, 2010
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 populations. Similarly within these counties, the Hispanic and Black populations are relatively dispersed. St. Lucie County has higher percentages of minority populations than the three previously mentioned counties. Additionally within St. Lucie there is a segregated concentration of African Americans to the south of the St. Lucie County International Airport. Palm 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 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.
71%
20%
39%
White
Black or African American Hispanic or Latino
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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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Indian River
Figure 12: Indian River County, Cost Burdened households by tenure, 2010
Figure 13: Indian River Tenancy by Race/Ethnicity, 2010
Figure 14: Indian River County, Housing Occupancy by Tenure, 2010
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
Less than $20,000
$20,000 to $34,999
$35,000 to $49,999
$50,000 to $74,999
$75,000 or more
Households paying 30% or more of their income on monthly housing costs, 2010
Indian River County
Owner-occupied Renter-occupied
93%
5%
5%
81%
14%
14%
White
Black or African American
Hispanic or Latino origin
Renter-occupied housing units
44,186
13,374 Owner-occupied housing units
Renter-occupied housing units
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St. Lucie County
Figure 15: St. Lucie County, Cost Burdened households by tenure, 2010
Figure 16: St. Lucie County Tenancy by Race/Ethnicity, 2010
Figure 17: St. Lucie County, Housing Occupancy by Tenure, 2010
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
Less than $20,000
$20,000 to $34,999
$35,000 to $49,999
$50,000 to $74,999
$75,000 or more
Households paying 30% or more of their income on monthly housing costs, 2010
St. Lucie County
Owner-occupied Renter-occupied
84%
12%
9%
69%
24%
18%
White
Black or African American
Hispanic or Latino origin
Renter-occupied housing units
Owner-occupied housing units
78,340
24,763 Owner-occupied housing units
Renter-occupied housing units
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Martin County
Figure 18: Martin County, Cost Burdened households by tenure, 2010
Figure 19: Martin County, Tenancy by Race/Ethnicity, 2010
Figure 20: Martin County, Housing Occupancy by Tenure, 2010
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
Less than $20,000
$20,000 to $34,999
$35,000 to $49,999
$50,000 to $74,999
$75,000 or more
Households paying 30% or more of their income on monthly housing costs, 2010
Martin County
Owner-occupied Renter-occupied
96%
2%
4%
86%
7%
16%
White
Black or African American
Hispanic or Latino origin
Renter-occupied housing units
Owner-occupied housing units
47,063
12,140
Owner-occupied housing units
Renter-occupied housing units
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Palm Beach County
Figure 21: Palm Beach County, Cost Burdened households by tenure, 2010
Figure 22: Palm Beach County, Tenancy by Race/Ethnicity, 2010
Figure 23: Palm Beach County, Housing Occupancy by Tenure, 2010
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
Less than $20,000
$20,000 to $34,999
$35,000 to $49,999
$50,000 to $74,999
$75,000 or more
Households paying 30% or more of their income on monthly housing costs, 2010 Palm Beach County
Owner-occupied Renter-occupied
87%
9%
10%
67%
24%
21%
White
Black or African
American
Hispanic or Latino origin
Renter-occupied housing units
384,995
138,155 Owner-occupied housing units
Renter-occupied housing units
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Broward County
Figure 24: Broward County, Cost Burdened households by tenure, 2010
Figure 25: Broward County, Tenancy by Race/Ethnicity, 2010
Figure 26: Broward County, Housing Occupancy by Tenure, 2010
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
Less than $20,000
$20,000 to $34,999
$35,000 to $49,999
$50,000 to $74,999
$75,000 or more
Households paying 30% or more of their income on monthly housing costs, 2010
Broward County
Owner-occupied Renter-occupied
76%
17%
18%
59%
32%
23%
White
Black or African American
Hispanic or Latino origin
Renter-occupied housing units
Owner-occupied housing units
463,511
205,387
Owner-occupied housing units
Renter-occupied housing units
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SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT |32
CARRAS COMMUNITY INVESTMENT, INC.
Miami-Dade County
Figure 27: Miami-Dade County, Cost Burdened households by tenure, 2010
Figure 28: Miami-Dade County, Tenancy by Race/Ethnicity, 2010
Figure 29: Miami-Dade County, Housing Occupancy by Tenure, 2010
0.0% 5.0%
10.0% 15.0% 20.0% 25.0% 30.0% 35.0%
Less than $20,000
$20,000 to $34,999
$35,000 to $49,999
$50,000 to $74,999
$75,000 or more
Households paying 30% or more of their income on monthly housing costs, 2010 Miami-Dade County
Owner-occupied Renter-occupied
79%
14%
62%
71%
22%
66%
White
Black or African American
Hispanic or Latino origin
Renter-occupied housing units
Owner-occupied housing units
480,532
347,024
Owner-occupied housing units
Renter-occupied housing units
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CARRAS COMMUNITY INVESTMENT, INC.
Monroe County
Figure 30: Monroe County, Cost Burdened households by tenure, 2010
0.0%
5.0%
10.0%
15.0%
20.0%
Less than $20,000
$20,000 to $34,999
$35,000 to $49,999
$50,000 to $74,999
$75,000 or more
Households paying 30% or more of their income on monthly housing costs, 2010
Monroe County
Owner-occupied Renter-occupied
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT |34
CARRAS COMMUNITY INVESTMENT, INC.
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
units Owner-occupied housing
units Renter-occupied housing
units
Total 2,269,261 1,517,837 751,424
White 84% 87% 75%
Black or African American
12% 9% 19%
Hispanic or Latino origin 19% 17% 26%
95%
3%
12%
89%
8%
22%
White
Black or African American
Hispanic or Latino origin
Renter-occupied housing units
Owner-occupied housing units
19,210
10,581
Owner-occupied housing units
Renter-occupied housing units
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT |35
CARRAS COMMUNITY INVESTMENT, INC.
Tenure of Occupied Housing Units:
Map 9: Occupied Housing Units by tenure,2010, SEFLA Region
Figure 33: SEFLA Region, Occupied Housing Units by tenure, 2010
1,517,837
751,424
Owner-occupied housing units
Renter-occupied housing units
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CARRAS COMMUNITY INVESTMENT, INC.
Figure 34: Seven-50 SE Florida Region Occupied Housing Units by Tenure and County, 2010
46% 60%
34%
58% 43%
57%
35% 51%
42% 56%
48% 57% 50%
61% 46%
60% O
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7-County SE Florida Region Average
Indian River County, Florida
St. Lucie County, Florida
Martin County, Florida
Palm Beach County, Florida
Broward County, Florida
Miami-Dade County, Florida
Monroe County, Florida
Tenure of Occupied Housing by County and for the SEFLA Region
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CARRAS COMMUNITY INVESTMENT, INC.
Figure 35: Seve-50 SE Florida Region, Cost Burdened households by tenure, 2010
0.00%
5.00%
10.00%
15.00%
20.00%
Less than $20,000
$20,000 to $34,999
$35,000 to $49,999
$50,000 to $74,999
$75,000 or more
Households paying 30% or more of their income on monthly housing costs, 2010
SEFLA Region
Owner-occupied housing units Renter-occupied housing units
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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.
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT |39
CARRAS COMMUNITY INVESTMENT, INC.
Indian River
Figure 36: Indian River County, Individuals below poverty level, 2010
Figure 37: Indian River County, Family Poverty Rates, 2010
Figure 38: Indian River County, Poverty Rate by Race and Ethnicity, 2010
16,984
5,322
9,322
2,340
Population for whom poverty
status is determined
Under 18 years 18 to 64 years 65 years and over
9%
5%
27%
16%
9%
31%
% Families Below Poverty Level
% Married Couples below Poverty Level
% Female householders with no husband present below
Poverty Level
With related children under 18 years Families
7.50%
23.80%
18.20% White
Black or African American
Hispanic or Latino origin (of any race)
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT |40
CARRAS COMMUNITY INVESTMENT, INC.
St. Lucie County
Figure 39: St. Lucie County, Individuals below poverty level, 2010
Figure 40: St. Lucie County, Family Poverty Rates, 2010
Figure 41: St. Lucie County, Poverty Rate by Race and Ethnicity, 2010
36,457
12,725
19,513
4,219
Population for whom poverty
status is determined
Under 18 years 18 to 64 years 65 years and over
10%
6%
27%
17%
9%
37%
% Families Below Poverty Level
% Married Couples below Poverty Level
% Female householders with no husband present below
Poverty Level
With related children under 18 years Families
7.70%
19.60%
19.00%
White
Black or African American
Hispanic or Latino origin (of any race)
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CARRAS COMMUNITY INVESTMENT, INC.
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT |42
CARRAS COMMUNITY INVESTMENT, INC.
Martin County
Figure 42: Martin County, Individuals below poverty level, 2010
Figure 43: Martin County, Family Poverty Rates, 2010
Figure 44: Martin County, Poverty Rate by Race and Ethnicity, 2010
14,724
4,507
8,046
2,171
Population for whom poverty
status is determined
Under 18 years 18 to 64 years 65 years and over
6%
3%
25%
13%
7%
34%
% Families Below Poverty Level
% Married Couples below Poverty Level
% Female householders with no husband present below
Poverty Level
With related children under 18 years Families
4.80%
17.30%
30.90%
White
Black or African American
Hispanic or Latino origin (of any race)
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CARRAS COMMUNITY INVESTMENT, INC.
Palm Beach County
Figure 45: Palm Beach County, Individuals below poverty level, 2010
156,759
48,840
86,743
21,176
Population for whom poverty
status is determined
Under 18 years 18 to 64 years 65 years and over
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT |44
CARRAS COMMUNITY INVESTMENT, INC.
Figure 46: Palm Beach County, Family Poverty Rates, 2010
Figure 47: Palm Beach County, Poverty Rate by Race and Ethnicity, 2010
9%
5%
24%
15%
7%
31%
% Families Below Poverty Level
% Married Couples below Poverty Level
% Female householders with no husband present below
Poverty Level
With related children under 18 years Families
6.00%
19.80%
16.60% White
Black or African American
Hispanic or Latino origin (of any race)
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CARRAS COMMUNITY INVESTMENT, INC.
Broward County
Figure 48: Broward County, Individuals below poverty level, 2010
Figure 49: Broward County, Family Poverty Rates, 2010
Figure 50: Broward County, Poverty Rate by Race and Ethnicity, 2010
210,964
63,164
118,477
29,323
Population for whom poverty
status is determined
Under 18 years 18 to 64 years 65 years and over
9%
5%
21%
13%
6%
27%
% Families Below Poverty Level
% Married Couples below Poverty Level
% Female householders with no husband present below
Poverty Level
With related children under 18 years Families
6.20%
16.20%
9.40% White
Black or African American
Hispanic or Latino origin (of any race)
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT |46
CARRAS COMMUNITY INVESTMENT, INC.
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CARRAS COMMUNITY INVESTMENT, INC.
Miami-Dade County
Figure 51: Miami-Dade County, Individuals below poverty level, 2010
Figure 52: Miami-Dade County, Family Poverty Rates, 2010
Figure 53: Miami-Dade County, Poverty Rate by Race and Ethnicity, 2010
410,093
118,792
217,985
73,316
Population for whom poverty
status is determined
Under 18 years 18 to 64 years 65 years and over
14%
9%
26%
18%
10%
35%
% Families Below Poverty Level
% Married Couples below Poverty Level
% Female householders with no husband present below
Poverty Level
With related children under 18 years Families
11.90%
22.10%
13.90% White
Black or African American
Hispanic or Latino origin (of any race)
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CARRAS COMMUNITY INVESTMENT, INC.
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT |49
CARRAS COMMUNITY INVESTMENT, INC.
Monroe County
Figure 54: Monroe County, Individuals below poverty level, 2010
Figure 55: Monroe County, Family Poverty Rates, 2010
Figure 56: Monroe County, Poverty Rate by Race and Ethnicity, 2010
7,776
1,275
5,327
1,174
Population for whom poverty
status is determined
Under 18 years 18 to 64 years 65 years and over
7%
4%
25%
10%
3%
30%
% Families Below Poverty Level
% Married Couples below Poverty Level
% Female householders with no husband present below
Poverty Level
With related children under 18 years Families
6.70%
12.40%
12.60% White
Black or African American
Hispanic or Latino origin (of any race)
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CARRAS COMMUNITY INVESTMENT, INC.
SEFLA Region
Figure 57: SEFLA Region, Individuals below poverty level, 2010
Figure 58: SEFLA Region, Family Poverty Rates, 2010
Figure 59: SEFLA Region, Poverty Rate by Race and Ethnicity, 2010
853,757
254,625
465,413
133,719
Population for whom poverty
status is determined
Under 18 years 18 to 64 years 65 years and over
9%
5%
25%
15%
7%
32%
% Families Below Poverty Level
% Married Couples below Poverty Level
% Female householders with no husband present below
Poverty Level
With related children under 18 years Families
7.26%
18.74%
17.23% White
Black or African American
Hispanic or Latino origin (of any race)
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CARRAS COMMUNITY INVESTMENT, INC.
Figure 60: SEFLA Region, Percent Population below poverty level by census
tract, 2010
Figure 61: SEFLA Region, Percent Population below poverty level by county, 2010
13% 14%
10% 12% 12%
17%
11%
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT |52
CARRAS COMMUNITY INVESTMENT, INC.
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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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.
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT |54
CARRAS COMMUNITY INVESTMENT, INC.
Indian River
Figure 62: Indian River County, Labor Force, 2010
Figure 63: Indian River County, Mean Travel Time to Work by Travel Mode, 2010
54.50%
45.50%
In labor force Not in labor force
0
10
20
30
40
50
Total Drive Alone Carpool Public transportation
Mean travel time to work (minutes)
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT |55
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Figure 64: Indian River County, Travel Mode by housing tenure, 2010
Figure 65: Indian River County, Travel Mode by race/ethnicity, 2010
0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00%
Owner-occupied housing units
Renter-occupied housing units
0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00% 90.00%
100.00%
White
Black or African American
Hispanic or Latino origin (of any race)
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CARRAS COMMUNITY INVESTMENT, INC.
St. Lucie County
Figure 66: St. Lucie County, Labor Force, 2010
Figure 67: St. Lucie County, Mean Travel Time to Work by Travel Mode, 2010
58.40%
41.60%
In labor force Not in labor force 0
10
20
30
40
50
60
70
Total Drive Alone Carpool Public transportation
Mean travel time to work (minutes)
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Figure 68: St. Lucie County, Travel Mode by housing tenure, 2010
Figure 69: St. Lucie County, Travel Mode by race/ethnicity, 2010
Martin County
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
Owner-occupied housing units
Renter-occupied housing units
0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00% 90.00%
White
Black or African American
Hispanic or Latino origin (of any race)
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Figure 70: Martin County, Labor Force, 2010
Figure 71: Martin County, Mean Travel Time to Work by Travel Mode, 2010
Figure 72: Martin County, Travel Mode by housing tenure, 2010
Figure 73: Martin County, Travel Mode by race/ethnicity, 2010
54.70%
45.30%
In labor force Not in labor force
20
21
22
23
24
25
26
27
Total Drive Alone Carpool Public transportation
Mean travel time to work (minutes)
0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00% 90.00%
Owner-occupied housing units
Renter-occupied housing units
0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00% 90.00%
100.00%
White
Black or African American
Hispanic or Latino origin (of any race)
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Palm Beach County
Figure 74: Palm Beach County, Labor Force, 2010
Figure 75: Palm Beach County, Mean Travel Time to Work by Travel Mode, 2010
Figure 77: Palm Beach County, Travel Mode by race/ethnicity, 2010
60.50%
39.50%
In labor force Not in labor force
0
10
20
30
40
50
Total Drive Alone Carpool Public transportation
Mean travel time to work (minutes)
0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00%
White
Black or African American
Hispanic or Latino origin (of any race)
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Figure 76: Palm Beach County, Travel Mode by housing tenure, 2010
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
Owner-occupied housing units
Renter-occupied housing units
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Broward County
Figure 78: Broward County, Labor Force, 2010
Figure 79: Broward County, Mean Travel Time to Work by Travel Mode, 2010
67.40%
32.60%
In labor force Not in labor force
0
10
20
30
40
50
60
Total Drive Alone Carpool Public transportation
Mean travel time to work (minutes)
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT |62
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Figure 80: Broward County, Travel Mode by housing tenure, 2010
Figure 81: Broward County, Travel Mode by race/ethnicity, 2010
Miami-Dade County
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
Owner-occupied housing units
Renter-occupied housing units
0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00%
White
Black or African American
Hispanic or Latino origin (of any race)
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Figure 82: Miami-Dade County, Labor Force, 2010
Figure 83: Miami-Dade County, Mean Travel Time to Work by Travel Mode, 2010
Figure 84: Miami-Dade County, Travel Mode by housing tenure, 2010
Figure 85: Miami-Dade County, Travel Mode by race/ethnicity, 2010
62.80%
37.20%
In labor force Not in labor force
0
10
20
30
40
50
Total Drive Alone Carpool Public transportation
Mean travel time to work (minutes)
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
Owner-occupied housing units
Renter-occupied housing units
0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00% 90.00%
White
Black or African American
Hispanic or Latino origin (of any race)
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Monroe County
Figure 86: Monroe County, Labor Force, 2010
Figure 87: Monroe County, Mean Travel Time to Work by Travel Mode, 2010
65.00%
35.00%
In labor force Not in labor force
0
5
10
15
20
25
Total Drive Alone Carpool Public transportation
Mean travel time to work (minutes)
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT |65
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Figure 88: Monroe County, Travel Mode by housing tenure, 2010
Figure 89: Monroe County, Travel Mode by race/ethnicity, 2010
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
Owner-occupied housing units
Renter-occupied housing units
0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00% 90.00%
100.00%
White
Black or African American
Hispanic or Latino origin (of any race)
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SEFLA Region
Figure 90: SEFLA Region, Labor Force by County, 2010
Figure 91: SEFLA Region, Mean Travel Time to Work by Travel Mode, 2010
Figure 92: SEFLA Region, Travel Mode by housing tenure, 2010
Figure 93: SEFLA Region, Travel Mode by race/ethnicity, 2010
0% 20% 40% 60% 80% 100%
Indian River County Martin County
St. Lucie County Palm Beach County
Broward County Miami-Dade County
Monroe County 7-County SE Florida Region
In labor force Not in labor force
0
10
20
30
40
50
Total Drive Alone Carpool Public transportation
Mean travel time to work (minutes)
0%
10%
20%
30%
40%
50%
60%
70%
80%
Total Drive Alone Carpool Public transportation
Owner-occupied housing units
Renter-occupied housing units
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
Total Drive Alone Carpool Public transportation
White
Black or African American
Hispanic or Latino origin (of any race)
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Figure 94: SEFLA Region, County, Travel Mode by County
0% 10% 20% 30% 40% 50% 60% 70% 80%
Drive Alone
Carpool
Public Transportation
Travel Mode By County, 2010
Indian River County, Florida St. Lucie County, Florida Martin County, Florida Palm Beach County, Florida
Broward County, Florida Miami-Dade County, Florida Monroe County, Florida 7-County SE Florida Region
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3. Fair Housing Legal Evaluation Fair Housing Laws and Programs
Housing development and the affordability of what is produced is highly influenced both by public and private forces such as real estate markets, profits, zoning, land use, impact fees, and concurrency requirements. The existence of a regulatory framework is necessary to promote and protect fair housing opportunities. This section summarizes existing fair housing laws and programs at the federal, state, and local level.
Federal Fair Housing Act & U.S. HUD, Fair Housing and Equal Opportunity The 1968 Fair Housing Act prohibits discrimination during the sale and rental of housing so that all people in the United
States have an increased opportunity to maintain stable and healthy lives for themselves and their families. As amended by the Fair Housing Amendments Act of 1988, it is unlawful to discriminate on the basis of race, color, sex, religion, national origin, disability and familial status. The U.S. Department of Housing and Urban Development (HUD), and on occasion the U.S. Department of Justice, is responsible for investigating and enforcing violations of the Fair Housing Act. HUD also provides Fair Housing Assistance Program (FHAP) funds annually and on a noncompetitive basis to State and local agencies that enforce fair housing laws substantially equivalent to the Fair Housing Act.
Florida Fair Housing The Florida Fair Housing Act1, which closely reiterates the Federal Fair Housing Act, was passed by the Florida
Legislature in 1983, and amended in 1989. It declares it illegal to discriminate in the sale, rental, advertising, financing, or brokerage of housing. It goes on further to ensure the accessibility of all new multifamily developments built within Florida.
The preceding Regional Profile section highlights that affordable housing options, which are integral to fair housing
opportunity, are a problem for SEFLA. The issue of affordable housing has been long debated in Florida and there are a number of programs to fund this initiative. In Florida, Section 163.3177 Fla. Stat. (2000) and Rule 9J-5 of the Florida Administration Code require that each community, county and the State of Florida adopt a housing element in their Comprehensive Plan which must contain standards, plans, and principles to create and preserve safe and healthy affordable housing options. Of these laws the William E. Sadowski Affordable Housing Act, passed in 1992 is notably important. The act established one of the largest dedicated trust funds for affordable housing. Revenues are generated through a documentary stamp tax, a real estate transfer fee levied when registering a deed or mortgage into public records. The Sadowski Act increased the existing documentary stamp tax by 10 cents per $100 (from 60 cents to 70 cents)
1 State of Florida, Civil Rights Statutes, Title XLIX, Chapter 760.2
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for the purposes of funding housing programs in the State. Three years later, the bill reallocated an additional 10 cents to the housing trust. The funds are uniquely tied to the real estate market so that revenues increase as housing prices (and the subsidy required to house Florida’s workforce) increase.
The Sadowski Act not only funded existing state housing programs such as the Predevelopment Loan Program (PLP),
the State Apartment Incentive Loan (SAIL), and the Homeownership Assistance Program (HAP) but also established several new initiatives, including the Low-Income Emergency Home Repair Program, the HOME Investment Partnerships Program, the HOPE Program, the Florida Affordable Housing Guarantee Program, the Affordable Housing Catalyst Program for Technical Assistance and Training, and the State Housing Initiatives Partnership Program (SHIP). Programs ranged from rental housing, homeownership, special needs, and more recently, disaster relief and workforce housing.
The Florida Housing Finance Corporation (Florida Housing) was designated as the administrator for all of the programs,
directing 30 percent of the revenue into a statewide trust and the other 70 percent into a local housing trust. The local funds are distributed to all 67 counties and 48 entitlement cities in the State through the SHIP program. The SHIP program ensures both accountability and flexibility.
• Accountability: In order to receive funding, each local government must adopt a SHIP Plan in accordance with state guidelines and local comprehensive plans.
• Flexibility: Local jurisdictions are able to direct money towards the specific needs of their community. Locally adopted strategies set-aside funding for extremely low to moderate-income households and support a variety of services, including new construction, rehabilitation, down payment assistance, homebuyer education, and foreclosure prevention.
When the Florida House and Senate entered the 2008 session, they were confronted with a major budget shortfall. The current fiscal year faced over $1 billion deficit, estimates for 2009 were upwards of $3 billion. Legislators were forced to cut programs, limit spending, and search for other sources of revenue. Consequently, the Florida Legislature transferred $250 million from dedicated affordable housing trust funds to general revenue. They also implemented a $243 million cap on existing and future funding for affordable housing. Funds generated through the Sadowski Act above that amount will be automatically deposited into general revenue. It is estimated that as a result of the cap, an additional $185 million in housing funds will be lost over the next two years (FY07-08 and FY 08-09).
Although the budget cuts took place in the 2007-2008 fiscal year, they were originally authorized three years earlier
(prior to the budget crisis) under Governor Jeb Bush. The cap was approved after attempts to completely remove the housing trust fund failed in the 2003 and 2004 Legislative Sessions. The Governor decided to “maintain trust fund spending
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at levels consistent with historical expectations while using windfall revenues to fund other priorities.” Housing advocates argued that this view was misleading. They claimed that while revenues into the housing trust funds had grown substantially since their creation, funding was purposely tied to documentary stamp tax revenues so that subsidies for affordable housing would rise as the cost of land, construction and housing increased.
The loss of these revenues has drastically cut local housing programs. Housing supporters continue to advocate to the
State to “scrap the cap” and reauthorize the Sadowski Act, which is set to sunset. In the meantime, there is a strong need for a dedicated source of funding for affordable housing at the Regional, County and City level. Both a linkage fee program and inclusionary housing program have been considered, but never created.
Fair Housing Assistance Agencies within SEFLA
Table 4: SEFLA Fair Housing Assistance Agencies
County Name Agency Type
N/A- State Level Federal Commission on Human Rights State Agency; Government
Palm Beach
Legal Aid Society of Palm Beach County Private
Palm Beach County Office of Equal Opportunity
Government
Broward Broward County Office of Equal Opportunity | Civil Right Division
Government
Miami
Housing Opportunities for Project Excellence, H.O.P.E Inc.
Private
Miami-Dade Office of Human Rights and Fair Employment Practices (OHRFEP)
Government
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Exist ing Ass is ted Housing Inventory 2
Table 5: Total Properties and Units, Assisted Housing
Number of Properties
Total Units
Assisted Units
% Assisted
Indian River 26 2,858 2,856 99.9%
St. Lucie 18 2,623 2,480 95%
Martin 17 1,221 1,219 100%
Palm Beach 93 13,802 12,652 92%
Broward 121 21,116 17,129 81%
Miami-Dade 334 42,346 40,514 96%
Monroe 17 861 838 97%
7-County SE Florida Region 626 84,827 77,688 94.3%
Figure 95: Assisted Housing Units By County
Population Rank Assisted Units Rank
Indian River 6 4 St. Lucie 4 5 Martin 5 6 Palm Beach 3 3 Broward 2 2 Miami-Dade 1 1
Monroe 7 7 Table 6: Assisted Housing Units and Population, Ranks by County
Within SEFLA there are currently 626 properties providing assisted housing units for a total of almost 78-thousand units. These assisted units are highly concentrated: 94% of all units within properties that offer assisted units are assisted. Miami-Dade, Broward, Palm Beach, and Monroe are consistent in their ranking of assisted units in comparison to their rank in population. However, Indian River ranks 6th in population yet has more assisted units than St. Lucie and Martin counties which both have higher population totals.
2 All data within the Existing Assisted Housing Inventory is drawn from the Florida Housing Data Clearinghouse
2856 2480 1219 12652 17129
40514
838
77688
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Table 7 Income Restrictions, Florida Housing Properties
Number of Units Designated for Renters with Income:
<=35% AMI 40-50% AMI 55-60% AMI 65-80% AMI >80% AMI
Indian River 100 423 1790 8 0
St. Lucie 179 209 1853 0 0
Martin 60 50 770 1 0
Palm Beach 344 825 7708 324 62
Broward 460 652 9870 212 512
Miami-Dade 1537 3505 21771 136 40
Monroe 73 57 555 121 13
SEFLA 2753 5721 44317 802 627
Various assisted housing units are reserved for renters in certain income brackets. The vast majority of these are for renters in the 55-60% AMI. Regionally, there are 44 thousand units designated for this income bracket. For those in the lowest income bracket, and therefore those in the greatest need of housing opportunities designated specifically for
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Figure 96: Number of Units Designated for Renters with Income at
them, only 627 units are designated for these renters across the 7-county SEFLA region. 512 of these are in Broward County compared to 40 in Miami-Dade where 17% of the population is below poverty level and zero in Indian River, St. Lucie and Martin Counties.
Table 8 Target Population, Assisted Housing
Family Elderly Farmworker Fisher Homeless Persons with Disabilities
Indian River 2294 685 426 - - 16
St. Lucie 2090 286 104 - - -
Martin 1055 140 117 - - 24
Palm Beach 10170 3628 916 - 93 46
Broward 14383 4202 173 - - 71
Miami-Dade 28835 11981 1582 - 815 318
Monroe 777 28 14 92 - 19
Figure 97: Target Population, Assisted Housing, SEFLA
0 5000 10000 15000 20000
Indian River
St. Lucie
Martin
Palm Beach
Broward
Miami-Dade
Monroe
<=35% AMI 40-50% AMI 55-60% AMI 65-80% AMI >80% AMI
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SEFLA 59604 20950 3332 92 908 494
Figure 98: Target Population, Assisted Housing, By County
The target population for the vast majority of assisted housing is families followed by elderly peoples, farmworkers, homeless, persons with disabilities, and finally fishers (this is only a target population in Monroe County). All 7 counties have assisted housing targeting families, elderly and farmworkers. St. Lucie county is alone in its lack of any assisted housing targeting persons with disabilities. Finally homeless people are the target populations for assisted housing in only Palm Beach and Miami-Dade.
Family
Elderly
Farmworker
Fisher
Homeless
Persons with Disabilities
0 5000 10000 15000 20000 25000 30000
Indian River
St. Lucie
Martin
Palm Beach
Broward
Miami-Dade
Monroe
Persons with Disabilities
Homeless
Fisher
Farmworker
Elderly
Family
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Figure 99: Race and Ethnicity of Tenants in Assisted Housing Units as of 2008
Table 9 Race and Ethnicity of Tenants in Assisted Housing Units as of 2008
% Minority % Black % Hispanic
Indian River 8% 6% 0%
St. Lucie 81% 72% 9%
Martin 10% 2% 6%
Palm Beach 58% 37% 21%
Broward 68% 43% 24%
Miami-Dade 91% 21% 70%
Monroe 61% 9% 52%
SEFLA 54% 27% 26%
54% of the region’s assisted housing units have minority tenants; 27% are Black and 26% Hispanic. Miami-Dade has the highest percentage of minority tenants at 91% followed by St. Lucie County at 81% (72% or which are Black). People of Hispanic origin occupy notably none of Indian River’s assisted housing units.
0% 10% 20% 30% 40% 50% 60% 70% 80% 90%
100%
% Minority % Black % Hispanic
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Fair Housing Discr iminat ion Complaints : 2007-2012 This section details fair housing complaints reported to various authorized Fair Housing Agencies (FHAP) throughout the
region. The year that cases are closed in is the year that those complaints are accounted for. Data was collected from various sources: 1) already completed AIs for Palm Beach, Broward, and Miami-Dade Counties, 2) data compiled by HUD for all seven counties for years 2010-2012 specifically for the purposes of this report, 3) public records requests from the Florida Commission on Human Rights as well as the Palm Beach and Miami-Dade County Offices of Equal Opportunity.
It should be noted, that the total number of bases/issues in the housing discrimination complaint tables are not necessarily equal to the total number of individuals that filed complaints because oftentimes, the complaints alleged multiple bases and issues. Similarly, there may be overlap of reports between tables so trends therefore summary of the proportions of the basis for complaints are examined as opposed to total numbers. Furthermore, national studies conducted by HUD provide evidence of a major underreporting of housing discriminations3. Therefore, the following trends can be used as a tool to begin understanding housing discrimination within SEFLA but should not be interpreted to represent the problem of housing discrimination exhaustively.
3 “Do We Know More Now? Trends in Public Knowledge, Support, and Use of Fair Housing Laws,” 2006
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Indian River County Indian River County, Florida
Table 10 Housing Discrimination Complaints- 2010-8/31/2012 Reported to HUD/FHAP
2010 2011 2012 Total %
RACE 0 0 0 0 0%
COLOR 0 0 0 0 0%
NATIONAL ORIGIN 0 0 2 2 12%
RELIGION 0 0 0 0 0%
SEX 1 0 1 2 12%
FAMILIAL STATUS 0 0 1 1 6%
DISABILITY 2 2 5 9 53%
AGE 0 0 0 0 0%
OTHER 0 1 2 3 18%
Total 3 3 11 17
Indian River County, Florida Table 11 Housing Discrimination Complaints-
2007-2012 Florida Commission on Human Relations
2007 2008 2009 2010 2011 2012 Total %
RACE 0 1 0 0 0 0 1 5%
COLOR 0 0 0 0 0 0 0 0%
NATIONAL ORIGIN 0 0 8 0 0 0 8 42%
RELIGION 0 0 0 0 0 0 0 0%
SEX 0 0 0 0 0 0 0 0%
FAMILIAL STATUS 0 1 0 0 0 0 1 5%
DISABILITY 1 3 1 1 0 2 8 42%
AGE 0 0 0 0 0 0 0 0%
OTHER 0 1 0 0 0 0 1 5%
Total 1 6 9 1 0 2 19
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Figure 100: Average Summary Percentage of Housing Complaints for all Cited Agencies, Indian River County, 2007-2012
Figure 101: Summary of Housing Discrimination Complaints, By Year, Indian River County, 2007-2012
Table 12: Bases for Discrimination Complaints, Rank and Proportion, Indian River County 2007-2012
Basis % Rank
DISABILITY 48% 1
NATIONAL ORIGIN 27% 2
OTHER 11% 3
SEX 6% 4
FAMILIAL STATUS 6% 5
RACE 3% 6
RELIGION 0% 7
COLOR 0% 8
AGE 0% 9
There are relatively few fair housing complaints in Indian River. Lower population levels as well as a lack of local fair housing agencies may account this for. 48% of complaints registered over the 5 years are based on disability discrimination, and 27% are related to national origin. There are no fair housing complaints in alleged discrimination of religion, color, or age. 2012 showed a general spike in the proportion of complaints overall.
3%
27%
6%
6%
48%
11%
RACE
COLOR
NATIONAL ORIGIN
RELIGION
SEX
FAMILIAL STATUS
DISABILITY
AGE
OTHER 0%
5%
10%
15%
20%
25%
30%
35%
40%
2007 2008 2009 2010 2011 2012
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St. Lucie County St. Lucie County, Florida
Table 13 Housing Discrimination Complaints- 2010-8/31/2012 By HUD or FHAP
2010 2011 2012 Total %
RACE 5 0 0 5 25%
COLOR 0 0 0 0 0%
NATIONAL ORIGIN 2 0 0 2 10%
RELIGION 1 0 0 1 5%
SEX 2 0 0 2 10%
FAMILIAL STATUS 4 1 0 5 25%
DISABILITY 2 2 1 5 25%
AGE 0 0 0 0 0%
OTHER 0 0 0 0 0%
Total 16 3 1 20
St. Lucie County, Florida
Table 14: Housing Discrimination Complaints- 2007-2012 Florida Commission on Human Relations
2007 2008 2009 2010 2011 2012 Total %
RACE 2 4 2 1 0 0 9 24% COLOR 0 0 0 0 0 0 0 0% NATIONAL ORIGIN 0 0 0 0 0 0 0 0% RELIGION 0 0 0 0 0 0 0 0% SEX 0 0 2 1 0 0 3 8% FAMILIAL STATUS 0 4 1 2 1 0 8 21% DISABILITY 2 9 3 1 1 1 17 45% AGE 0 0 0 0 0 0 0 0% OTHER 0 1 0 0 0 0 1 3%
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Total 4 18 8 5 2 1 38
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Figure 102: Average Summary Percentage of Housing Complaints for all Cited Agencies, St. Lucie County, 2007-2012
Figure 103: Summary of Housing Discrimination Complaints, By Year, St. Lucie County, 2007-2012
Table 15: Bases for Discrimination Complaints, Rank and Proportion, St. Lucie County 2007-2012
Basis % Rank
DISABILITY 35% 1
RACE 24% 2
FAMILIAL STATUS 23% 3
SEX 9% 4
NATIONAL ORIGIN 5% 5
RELIGION 3% 6
OTHER 1% 7
Since 2010 the number of complaints has been declining in St. Lucie but over the five-year period the number of reported cases has varied substantially. 35% of complaints from 2007-2012 are based in disability discrimination, 24% for race and 23% for familial status. There are no registered fair housing complaints for either age or color.
24%
5%
3%
9%
23%
35%
1%
RACE
COLOR
NATIONAL ORIGIN
RELIGION
SEX
FAMILIAL STATUS
DISABILITY
AGE
OTHER
0%
5%
10%
15%
20%
25%
30%
35%
40%
2007 2008 2009 2010 2011 2012
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COLOR 0% 8
AGE 0% 9
Martin County Martin County, Florida
Table 16: Housing Discrimination Complaints- 2010-8/31/2012 By HUD or FHAP
2010 2011 2012 Total %
RACE 1 1 0 2 13% COLOR 0 0 0 0 0% NATIONAL ORIGIN 0 1 0 1 6% RELIGION 0 0 0 0 0% SEX 0 1 0 1 6% FAMILIAL STATUS 0 0 0 0 0% DISABILITY 4 2 4 10 63% AGE 0 0 0 0 0% OTHER 1 1 0 2 13% Total 6 6 4 16
Martin County, Florida
Table 17: Housing Discrimination Complaints- 2007-2012 Florida Commission on Human Relations
2007 2008 2009 2010 2011 2012 Total %
RACE 0 1 0 1 1 0 3 9% COLOR 0 0 0 0 0 0 0 0% NATIONAL ORIGIN 1 0 1 1 1 0 4 12% RELIGION 0 0 1 2 0 0 3 9% SEX 0 2 0 0 3 0 5 15% FAMILIAL STATUS 0 2 1 0 0 0 3 9% DISABILITY 1 2 0 7 2 2 14 42% AGE 0 0 0 0 0 0 0 0%
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OTHER 0 0 0 0 1 0 1 3% Total 2 7 3 11 8 2 33
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Figure 104 Average Summary Percentage of Housing Complaints for all Cited Agencies, Martin County, 2007-2012
Figure 105 Summary of Housing Discrimination Complaints, By Year, Martin County, 2007-2012
Table 18: Bases for Discrimination Complaints, Rank and Proportion, Martin County 2007-2012
Basis % Rank
DISABILITY 52% 1
RACE 11% 2
SEX 11% 3
NATIONAL ORIGIN 9% 4
OTHER 8% 5
RELIGION 5% 6
FAMILIAL STATUS 5% 7
COLOR 0% 8
AGE 0% 9
In Martin county between 2007 and 2012 over half of the registered fair housing complaints are against disability discrimination. All other categories (besides color, for which there are no complaints) range from 5-11%. There was a rise in the proportion of complaints in 2010.
11%
9%
5%
11%
5%
52%
8% RACE
COLOR
NATIONAL ORIGIN
RELIGION
SEX
FAMILIAL STATUS
DISABILITY
AGE
OTHER
0%
5%
10%
15%
20%
25%
30%
35%
40%
2007 2008 2009 2010 2011 2012
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Palm Beach County
Palm Beach County, Florida
Table 20: Housing Discrimination Complaints- 2007-2012 Florida Commission on Human Relations
2007 2008 2009 2010 2011 2012 Total %
RACE 0 0 0 1 1 0 2 12% COLOR 0 0 0 0 0 0 0 0% NATIONAL ORIGIN 0 0 0 1 0 0 1 6% RELIGION 0 0 0 0 0 0 0 0% SEX 0 1 0 1 0 1 3 18% FAMILIAL STATUS 1 1 0 0 1 0 3 18% DISABILITY 0 4 0 0 3 0 7 41% AGE 0 0 0 0 0 0 0 0% OTHER 0 0 0 0 1 0 1 6%
Palm Beach County, Florida
Table 19: Housing Discrimination Complaints- 2010-8/31/2012 By HUD/FHAP
2010 2011 2012 Total %
RACE 26 16 10 52 18% COLOR 2 3 1 6 2% NATIONAL ORIGIN 18 10 6 34 12% RELIGION 3 3 2 8 3% SEX 10 7 2 19 7% FAMILIAL STATUS 18 9 4 31 11% DISABILITY 54 42 32 128 44% AGE 0 0 0 0 0% OTHER 3 9 2 14 5% Total 134 99 59 292
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Total 1 6 0 3 6 1 17
Palm Beach County, Florida
Table 21: Housing Discrimination Complaints- FY 2007-2012 Legal Aid Society Of Palm Beach County, Inc.
2007 2008 2009 2010 2011 2012 Total %
RACE 11 16 15 9 11 --- 62 17% COLOR 0 0 0 0 0 --- 0 0% NATIONAL ORIGIN 12 20 17 9 16 --- 74 20% RELIGION 1 1 0 0 0 --- 2 1% SEX 6 3 1 1 1 --- 12 3% FAMILIAL STATUS 5 3 14 8 6 --- 36 10% DISABILITY 31 25 15 33 38 --- 142 39% AGE 2 4 8 10 0 --- 24 7% OTHER 4 2 2 2 0 --- 10 3% Total 72 74 72 72 72 --- 362
Palm Beach County, Florida
Table 22: Housing discrimination Complaints- FY 2007-2012 Palm Beach County Office of Equal Opportunity
2007 2008 2009 2010 2011 2012 Total %
RACE 25 13 13 20 16 14 101 19% COLOR 0 0 0 0 0 0 0 0% NATIONAL ORIGIN 12 6 6 15 7 7 53 10% RELIGION 1 1 3 2 1 2 10 2% SEX 4 0 4 6 4 5 23 4% FAMILIAL STATUS 15 9 24 30 1 9 88 16%
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DISABILITY 33 37 43 51 44 33 241 45% AGE 0 2 2 0 1 1 6 1% OTHER 6 2 1 2 2 3 16 3% Total 96 70 96 126 76 74 538
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Figure 106: Average Summary Percentage of Housing Complaints for all Cited Agencies, Palm Beach County, 2007-2012
Figure 107: Summary of Housing Discrimination Complaints, By Year, Palm Beach County, 2007-2012
Table 23: Bases for Discrimination Complaints, Rank and Proportion, Palm Beach County 2007-2012
Basis % Rank
DISABILITY 42% 1
RACE 16% 2
FAMILIAL STATUS 14% 3
NATIONAL ORIGIN 12% 4
SEX 8% 5
OTHER 4% 6
AGE 2% 7
RELIGION 1% 8
Palm Beach County had a spike in 2010 for fair housing complaints, and overall has larger number of complaints than its three northern counterparts. This makes sense given the larger population however as well as the fact that there are two local FHAPs, the Palm Beach County Office of Equal Opportunity and the Legal Aid Society of Palm Beach County. 42% of complaints are based on discrimination against disability, 16% against race, 14% against familial status, and 12% against national origin.
16%
1%
12%
1% 8%
14%
42%
2%
4% RACE
COLOR
NATIONAL ORIGIN
RELIGION
SEX
FAMILIAL STATUS
DISABILITY
AGE
OTHER
0%
5%
10%
15%
20%
25%
30%
2007 2008 2009 2010 2011 2012
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COLOR 1% 9
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Broward County Broward County, Florida
Table 24: Housing discrimination Complaints- 2010-8/31/2012 By HUD/FHAP
2010 2011 2012 Total %
RACE 27 32 13 72 20%
COLOR 0 4 0 4 1%
NATIONAL ORIGIN 22 28 10 60 16%
RELIGION 4 2 2 8 2%
SEX 8 6 5 19 5%
FAMILIAL STATUS 18 13 6 37 10%
DISABILITY 74 40 36 150 41%
AGE 0 0 0 0 0%
OTHER 6 2 8 16 4%
Total 159 127 80 366
Broward County, Florida
Table 25: Housing discrimination Complaints- 2007-2012 Florida Commission on Human Relations
2007 2008 2009 2010 2011 2012 Total %
RACE 0 4 5 4 3 0 16 21%
COLOR 0 0 1 0 0 0 1 1%
NATIONAL ORIGIN 1 4 2 2 3 1 13 17%
RELIGION 0 2 2 1 0 0 5 7%
SEX 0 2 1 1 1 0 5 7%
FAMILIAL STATUS 1 3 0 2 2 2 10 13%
DISABILITY 2 4 6 9 3 1 25 33%
AGE 0 0 0 0 0 0 0 0%
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OTHER 0 0 0 0 0 0 0 0%
Total 4 19 17 19 12 4 75
Broward County, Florida
Table 26: Housing discrimination Complaints – FY 2007-2012 HOPE FAIR HOUSING CENTER
2007 2008 2009 2010 2011 2012 Total %
RACE 16 14 17 8 ---- ---- 55 36%
COLOR 0 0 0 0 ---- ---- 0 0%
NATIONAL ORIGIN 2 3 1 0 ---- ---- 6 4%
RELIGION 0 0 0 1 ---- ---- 1 1%
SEX 0 2 1 0 ---- ---- 3 2%
FAMILIAL STATUS 0 11 1 2 ---- ---- 14 9%
DISABILITY 24 14 19 10 ---- ---- 67 44%
AGE 0 4 2 0 ---- ---- 6 4%
OTHER 0 0 2 0 ---- ---- 2 1%
Total 42 48 43 21 ---- --- 154
Broward County, Florida
Table 27: Housing discrimination Complaints- FY 2007-2012 Broward County Office of Equal Opportunity
2007 2008 2009 2010 2011 2012 Total %
RACE ---- 18 15 25 ---- ---- 58 19%
COLOR ---- 0 0 0 ---- ---- 0 0%
NATIONAL ORIGIN ---- 16 14 18 ---- ---- 48 15%
RELIGION ---- 2 1 2 ---- ---- 5 2%
SEX ---- 2 6 5 ---- ---- 13 4%
FAMILIAL STATUS ---- 6 8 10 ---- ---- 24 8%
DISABILITY ---- 54 47 56 ---- ---- 157 50%
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AGE ---- 1 0 1 ---- ---- 2 1%
OTHER ---- 1 2 1 ---- ---- 4 1%
Total ---- 100 93 118 ---- ---- 311
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Figure 108: Average Summary Percentage of Housing Complaints for all Cited Agencies, Broward County, 2007-2012
Figure 109: Summary of Housing Discrimination Complaints, By Year, Broward County, 2007-2012
Table 28: Bases for Discrimination Complaints, Rank and Proportion, Broward County 2007-2012
Basis % Rank
DISABILITY 42% 1
RACE 24% 2
NATIONAL ORIGIN 13% 3
FAMILIAL STATUS 10% 4
SEX 4% 5
RELIGION 3% 6
OTHER 2% 7
AGE 1% 8
COLOR 1% 9
Fair Housing Discrimination complaints within Broward County between 2007 & 2012 are quite similar to Palm Beach. Notably, complaints against race are more prevalent however which might be reflective of the larger proportion of minorities in Broward. Also similar to other counties in the region is the higher proportion of complaints closed in 2010. Broward County Office of Equal Opportunity did not provide data for 2007, 2011, and 2012. Likewise we were unable to obtain data for 2011 and 2012 for complaints registered with HOPE in Broward County. Data in tables 26 & 27 therefore is reflective of the county’s 2010 AI.
24%
1%
13%
3% 4%
10%
42%
1% 2%
RACE
COLOR
NATIONAL ORIGIN
RELIGION
SEX
FAMILIAL STATUS
DISABILITY
AGE
OTHER
0%
5%
10%
15%
20%
25%
30%
35%
40%
2007 2008 2009 2010 2011 2012
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Miami-Dade County Miami-Dade County, Florida
Table 29: Housing Discrimination Complaints- 2010-8/31/2012 By HUD or FHAP
2010 2011 2012 Total %
RACE 19 14 8 41 17%
COLOR 0 3 0 3 1%
NATIONAL ORIGIN 18 10 17 45 18%
RELIGION 5 3 3 11 5%
SEX 8 2 10 20 8%
FAMILIAL STATUS 10 3 8 21 9%
DISABILITY 39 26 24 89 36%
AGE 0 0 0 0 0%
OTHER 4 4 6 14 6%
Total 103 65 76 244
Miami-Dade County, Florida
Table 30: Housing discrimination Complaints- 2007-2012 Florida Commission on Human Relations
2007 2008 2009 2010 2011 2012 Total %
RACE 9 16 17 17 16 5 80 18%
COLOR 0 1 1 0 3 1 6 1%
NATIONAL ORIGIN 7 11 15 10 8 12 63 14%
RELIGION 0 3 8 4 4 2 21 5%
SEX 4 5 9 7 2 8 35 8%
FAMILIAL STATUS 6 9 9 6 3 7 40 9%
DISABILITY 20 42 39 32 29 23 185 41%
AGE 0 0 0 0 0 0 0 0%
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CARRAS COMMUNITY INVESTMENT, INC.
OTHER 4 6 6 5 2 3 26 6%
Total 50 93 104 81 67 61 456
Miami-Dade County, Florida
Table 31: Housing discrimination Complaints – FY 2007-2012 HOPE FAIR HOUSING CENTER
2007 2008 2009 2010 2011 2012 Total %
RACE 33 9 12 16 7 --- 77 36%
COLOR 0 1 0 0 0 --- 1 0%
NATIONAL ORIGIN 8 3 0 3 3 --- 17 8%
RELIGION 0 0 0 0 0 --- 0 0%
SEX 1 0 0 0 1 --- 2 1%
FAMILIAL STATUS 3 3 5 2 3 --- 16 7%
DISABILITY 27 7 22 19 7 --- 82 38%
AGE 0 0 2 2 0 --- 4 2%
OTHER 1 3 2 3 6 --- 15 7%
Total 73 26 43 45 27 --- 214
Miami-Dade County, Florida
Table 32: Housing discrimination Complaints- FY 2007-2012 Miami-Dade County Office of Human Rights and Fair Employment Practices
2007 2008 2009 2010 2011 2012 Total %
RACE 10 9 14 4 4 8 49 16%
COLOR 2 0 0 1 0 0 3 1%
NATIONAL ORIGIN 12 8 8 4 18 8 58 19%
RELIGION 5 0 1 0 1 0 7 2%
SEX 1 2 1 0 3 4 11 4%
FAMILIAL STATUS 1 2 2 0 6 5 16 5%
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DISABILITY 14 13 18 7 3 8 63 20%
AGE 3 1 3 0 2 3 12 4%
OTHER 25 11 24 1 21 12 94 30%
Total 73 46 71 17 58 48 313
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Figure 110: Average Summary Percentage of Housing Complaints for all Cited Agencies, Miami-Dade County, 2007-2012
Figure 111: Summary of Housing Discrimination Complaints, By Year, Miami-Dade County, 2007-2012
Table 33: Bases for Discrimination Complaints, Rank and Proportion, Miami-Dade County 2007-2012
Basis % Rank
DISABILITY 34% 1
RACE 21% 2
NATIONAL ORIGIN 15% 3
OTHER 12% 4
FAMILIAL STATUS 7% 5
SEX 5% 6
RELIGION 3% 7
AGE 1% 8
COLOR 1% 9
In Miami-Dade county, the range of fair housing complaints is more spread out between bases than for counties with smaller populations. 34% can be attributed to disability, 21% to race, 15% to national origin, and 12% to “other” complaints (mostly for retaliation). Over the five years, there is more stability in the proportion of complaints overall even though there is still a spike in 2010. As with Broward County, HOPE acts as a FHAP. We did not receive updated information for 2012 from this organization however so data in table 31 is cited from Miami-Dade Counties 2011 AI.
21%
1%
15%
3% 5%
7%
34%
1% 12% RACE
COLOR
NATIONAL ORIGIN
RELIGION
SEX
FAMILIAL STATUS
DISABILITY
AGE
OTHER
0%
5%
10%
15%
20%
25%
2007 2008 2009 2010 2011 2012
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT
CARRAS COMMUNITY INVESTMENT, INC.
Monroe County Monroe County, Florida
Table 34: Housing Discrimination Complaints- 2010-8/31/2012 By HUD or FHAP
2010 2011 2012 Total %
RACE 2 1 0 3 19%
COLOR 0 0 0 0 0%
NATIONAL ORIGIN 2 0 1 3 19%
RELIGION 0 1 0 1 6%
SEX 0 0 1 1 6%
FAMILIAL STATUS 0 1 2 3 19%
DISABILITY 3 1 0 4 25%
AGE 0 0 0 0 0%
OTHER 1 0 0 1 6%
Total 8 4 4 16
Monroe County, Florida
Table 35: Housing Discrimination Complaints- 2007-2012 Florida Commission on Human Relations
2007 2008 2009 2010 2011 2012 Total %
RACE 0 1 1 1 1 0 4 17%
COLOR 0 0 0 0 0 0 0 0%
NATIONAL ORIGIN 0 0 0 1 1 0 2 8%
RELIGION 0 0 0 0 0 0 0 0%
SEX 0 0 0 0 0 0 0 0%
FAMILIAL STATUS 0 0 0 0 1 1 2 8%
DISABILITY 4 8 0 1 2 1 16 67%
AGE 0 0 0 0 0 0 0 0%
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT
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OTHER 0 0 0 0 0 0 0 0%
Total 4 9 1 3 5 2 24
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Figure 112: Average Summary Percentage of Housing Complaints for all Cited Agencies, Monroe County, 2007-2012
Figure 113: Summary of Housing Discrimination Complaints, By Year, Monroe County, 2007-2012
Table 36: Bases for Discrimination Complaints, Rank and Proportion, Monroe County 2007-2012
Basis % Rank
DISABILITY 46% 1
RACE 18% 2
NATIONAL ORIGIN 14% 3
FAMILIAL STATUS 14% 4
RELIGION 3% 5
SEX 3% 6
OTHER 3% 7
COLOR 0% 8
AGE 0% 9
Monroe has very few fair housing complaints. Of those registered 46% claim discrimination based on disability, 18% on race, and 14% on both national origin and familial status. Over the time period there have been large variances in the proportion of complaints year by year with the largest amount in 2010.
18%
14%
3%
3% 14%
46%
3%
RACE
COLOR
NATIONAL ORIGIN
RELIGION
SEX
FAMILIAL STATUS
DISABILITY
AGE
OTHER
0%
5%
10%
15%
20%
25%
30%
2007 2008 2009 2010 2011 2012
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT
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SEFLA Figure 114: Average Summary Percentage of Housing Complaints for all Cited
Agencies, SEFLA, 2007-2012
Figure 115: Summary of Housing Discrimination Complaints, SEFLA
Table 37: Bases for Discrimination Complaints, Rank and Proportion, SEFLA 2007-2012
Basis % Rank
DISABILITY 43% 1
RACE 17% 2
NATIONAL ORIGIN 14% 3
FAMILIAL STATUS 11% 4
SEX 7% 5
OTHER 6% 6
RELIGION 2% 7
AGE 1% 8
COLOR 0.3% 9
Housing complaints based on discrimination against disability ranks highest in SEFLA by more than twice as much as racially based complaints which rank second. Disability is, over the 5-year period and for each county, the largest alleged discriminating factor in fair housing complaints (43%). For the region race (17%), national origin (13%), and familial status (11%) follow in ranking which has been consistent over time except for in 2012 when race dipped slightly below national origin (See Figure 117). There is variation of rank across individual counties (see figures 116). Within all counties except Indian River, there was a spike in reported fair housing complaints in 2010.
17%
0.3%
14%
2% 7%
11%
43%
1%
6% RACE
COLOR
NATIONAL ORIGIN
RELIGION
SEX
FAMILIAL STATUS
DISABILITY
AGE
OTHER 0%
5%
10%
15%
20%
25%
30%
2007 2008 2009 2010 2011 2012
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT
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Figure 116: Top 4 Ranked Bases for Complaints by County, 2007-2012 Average
0%
10%
20%
30%
40%
50%
60%
DISABILITY RACE NATIONAL ORIGIN FAMILIAL STATUS
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT
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Figure 117: Top 4 Ranked Bases for Complaints SEFLA 2007-2012
0
50
100
150
200
250
300
350
400
450
2007 2008 2009 2010 2011 2012
DISABILITY RACE NATIONAL ORIGIN FAMILIAL STATUS
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT
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4. Lending Profile 4 .1 Potent ia l Discr iminatory Lending Pract ices
Housing/Lending Discrimination on the Basis of Color, National Origin, Religion, Sex, Familial Status and Disability, (Protected class discrimination) Discrimination in housing acquisition and financing on the basis of color, national origin, religion, sex, familial status or disability is illegal under the Fair Housing Act, also known as Title VIII of the U.S. Civil Rights Act. Under the act, mortgage lenders cannot refuse a loan to one of the classes of people protected under the act, also referred to as protected classes, nor can they set different conditions to a loan based on the above factors (Palm Bay FL, 2009; U.S. Department of Housing and Urban Development, N.D.). Discrimination under Title VIII can occur in a variety of ways in addition to those already mentioned. Discrimination under Title VIII may occur when a financier or lender refuses to provide information to a member of a protected class based on their membership in that class.
Subprime Lending, Redlining & Predatory Lending Subprime lending is defined as higher than average rate loans given to persons who are of higher credit risk due to less than satisfactory credit. The higher rate regularly referred as “higher cost” reflects the increased risk of lending to a loan applicant with less than satisfactory credit. There are other indicators of subprime loans besides the loan rate being higher than average, like the potential for the loan to reset to much higher rates in the future (Coconut Creek AI, 2011). Subprime lending is more prevalent in minority-majority neighborhoods than in non-minority majority neighborhoods, suggesting an overrepresentation of minority recipients of mortgages that are subprime in nature (Department of Housing and Urban Development, N.D.). Because of the apparent concentration of subprime loans in minority neighborhoods and among minority loan applicants, it has been argued that subprime lenders target minority communities through reverse redlining.
Redlining was a practice that enabled minorities and their neighborhoods to be systematically excluded from acquiring home loans. This limited the housing choices for minorities, preventing them from improving and purchasing housing in their “red-lined” communities (Broward County, AI, 2011; Encyclopedia of Chicago, 2005). This practice led to deteriorating housing stock in minority-majority communities and increased rental tenancy in those areas.
Predatory lending has no officially recognized federal definition. The federal government does, however, associate certain practices with the act of predatory lending. These acts are seen as indicators of predatory lending and they include: high pressure and misleading sales practices, abusive and aggressive collection practices, balloon payments (an oversized payment due at the end of a loan), steering borrowers to higher cost mortgages when they qualify for lower cost ones and the failure to report credit information that allows borrowers to get the best rates on loans based on their complete credit history, among others (U.S. Senate Committee on Banking, Housing and Urban Affairs, 2000; www.Investopedia.com, 2012).
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4.2 Home Mortgage Disc losure Act Data Analys is (HMDA) 4 The following analysis examines the equity in lending trends within SEFLA. The South Florida region held over six million people in 2010, with 89.6 percent of them living in Miami-Dade, Broward and Palm Beach County. Because of the concentration of South Floridians that live in these three counties, a few statistics on the lending in the leading cities of these counties is warranted.
The City of Miami is located in Miami-Dade County, the most populous county in the seven-county South Florida region, and serves as its county seat. In Miami, American Indians/Alaskan Natives have the highest percentage of home loan denials among all racial groups, at 36.62%. African Americans have the second highest denial rate at 33% and Hispanics and Whites have moderate loan denial rates of 22% and 17% respectively. Asian/Pacific Islanders have the lowest home loan denials rates, at 15.15%. When looking at loan rates across income levels, home loan denial rates are highest among low income individuals and lowest among upper income individuals (City of Miami AI, 2007).
The City of Fort Lauderdale is located in Broward County, Florida, the second-most populous county in the seven-county South Florida region with a population of 1,780,172 people in 2010(U.S. Census Bureau, 2010). In Fort Lauderdale during the year 2008, African Americans earning less than 50% of the area’s median income (AMI) had the highest percentage of loan denials under FHA/VA loans and Hispanics/Latinos earning less than 50% of the area’s median income (AMI) had the highest percentage of loan denials under conventional loans, edging out the less than 50% AMI African American denial percentage by one percentage point. Rates of loan denials under both loan types generally dropped as the income class increased, except for a few instances, most notably, African Americans conventional loan applicants above 120+% AMI had a higher percentage of loan denials than their 1000-119% AMI counterparts at with rates of 41% to 35% respectively. The most prevalent reason for loan denials in the city for all races was debt (Fort Lauderdale AI, 2010).
The City of West Palm Beach is located in Palm Beach County, Florida, the third-most populous county in the seven-county South Florida region with a population of 1,320,134 people in 2010 (U.S. Census Bureau, 2010). In West Palm Beach in 2009, American Indian/Alaska Natives had the lowest percentage of approved and accepted loan applications, at 33.33%. Whites had the highest percentage of approved and accepted loan applications at 62.16%, almost twice that of American Indian/Alaska Natives. The range of approved and accepted applications across AMI income classes with available income fell within a percentage point 16 range, between a low of 46.50% for applicants earning less than 50% of the metropolitan statistical area (MSA) median income and a high of 62.83% for applicants earning 120% or more of the MSA median income (City of West Palm Beach, 2011).
4 Data source throughout HMDA Analysis:: 2010 Florida Housing Data Clearinghouse HMDA Home Mortgage Lending Data.
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Loan Dispositions in SEFLA Of the seven counties in the South Florida region, Martin County has the highest overall loan origination rate, at 68.88% and Miami-Dade County has the highest overall loan denial rate, at 25.64%. Only two counties in the region, Martin and Indian River Counties, have loan origination rates that are above the state’s loan origination average of 61.59%. Three South Florida Counties, Indian River County, Martin County and St. Lucie County, have loan denial rates below the state average of 19.61%. Four of the seven South Florida Counties have loan denial rates that are higher than the state rate of 19.01%.
Overall Loan Dispositions for the Seven County Southeast Florida Region & The State of Florida
County Originated/Approved Denied Other Total
Broward 12954 (55.87%)
5277 (22.76%)
4957 (21.38%)
23188
Indian River County
1133 (67.76%)
261 (15.61%)
278 (16.05%)
1672
Martin County
1193 (68.88%)
261 (15.07%)
278 (16.05%)
1732
Miami-Dade County
10807 (51.41%)
5390 (25.64%)
4824 (22.95%)
21,021
Monroe County
707 (59.97%)
242 (20.53%)
230 (19.51%)
1179
Palm Beach County
9765 (60.21%)
3241 (19.98%)
3213 (19.81%)
16219
St. Lucie County
2571 (61.35%)
802 (19.14%)
818 (19.52%)
4191
Florida 144931 (61.59%)
46139 (19.61%)
44259 (18.81%)
235329
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Loan Application Denial Reasons for the Seven County Southeast Florida Region By County County Debt-to-
Income Ratio Employment History
Credit History Collateral Insufficient Cash
Unverifiable Information
Credit Application Incomplete
Mortgage Insurance Denied
Other Reason Not Available
Total Denied Applications
Broward County
1363 (25.83%)
85 (1.61%) 516 (9.78%) 1234 (23.38%) 138 (2.61%) 208 (3.94%) 415 (7.86%) 6 (0.11%) 516 (9.78%) 796 (15.08%) 5277
Indian River County 76 (29.12%) 10 (3.83%) 23 (8.81%) 65 (24.90%) 10 (3.83%) 8 (3.07%) 35 (13.41%) 1 (0.38%) 15 (5.74%) 18 (6.90%) 261
Martin County 66 (25%) 4 (1.56%) 34 (12.89%) 69 (26.14%) 6 (2.27%) 15 (5.68%) 22 (8.34%) 1 (0.39%) 23 (8.71%) 24 (9.09%) 264
Miami-Dade County
1275 (23.65%)
61 (1.13%) 463 (8.59%) 1353 (25.10%) 116 (2.15%) 221 (4.10%) 438 (8.12%) 6 (0.11%) 511 (9.48%) 946 (17.55%) 5390
Monroe County 72 (29.75%) 3 (1.24%) 15 (6.20%) 63 (26.03%) 7 (2.89%) 13 (5.37%) 20 (8.26%) 0 (0%) 26 (10.74%) 23 (9.50%) 242
Palm Beach County
836 (25.79%)
50 (1.54%) 306 (9.44%) 689 (21.26%) 78 (2.41%) 136 (4.20%) 357 (11.02%) 6 (0.19%) 293 (9.04%) 490 (15.12%) 3241
St. Lucie County 224
(27.93%) 16 (2 %)
107 (13.34%)
152 (18.95%) 25 (3.12%) 41 (5.11%) 61 (7.60%) 4 (0.50%) 83 (10.35%) 89 (10.35%) 802
The most prevalent reason for loan application denials among the counties in South Florida in is the loan applicant’s debt to income ratio, with the largest percentage of 2010 county-wide loan denials in five of the regions’ counties (Broward County, Indian River County, Monroe County, Palm Beach County & St. Lucie County) attributed to that reason. The second leading reason for loan denials in South Florida was collateral, with the largest percentage of countywide loan denials in two of the regions’ counties, Miami-Dade County and Martin County, attributed to that reason.
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Disposition of Loans by Race Broward County
Applicant Race Loan Originated Loan Denied Other Total
American Indian or Alaska Native
40 (41.24%) 25 (25.77%) 32 (32.98%) 97
Asian 448 (55.24%) 171 (21.09%) 192 (23.67%) 811
Black or African American 2166 (49.83%) 1259 (28.96%) 922 (21.21%) 4347
Native Hawaiian or Other Pacific Islander
40 (42.55%) 34 (36.17%) 20 (21.28%) 94
White 9036 (59.48%) 3095 (20.37%) 3060 (20.14) 15191
Information not provided by applicant in mail, Internet, or telephone application
1165 (45.53%) 684 (26.72%) 710 (27.75%) 2559
Not applicable 59 (66.29%) 9 (10.11%) 21 (23.60%) 89
In Broward County, Native Hawaiian or Other Pacific Islander loan applicants had the highest loan denial rates in 2010. White loan applicants had the highest loan origination rates in the county, outpacing second place Asians by 4.24 percentage points.
Indian River County
Applicant Race Loan Originated Loan Denied Other Total
American Indian or Alaska Native
4 (80%) 0 (0%) 1 (20%) 5
Asian 11 (68.75%) 0 (0 %) 5 (31.25%) 16
Black or African American 41 (75.93%) 7 (12.96%) 6 (11.11%) 54
Native Hawaiian or Other Pacific Islander
0 0 0 0
White 982 (68.38%) 230 (16.02%) 224 (15.60%) 1436
Information not provided by applicant in mail, Internet, or telephone application
94 (58.75%) 24 (15%) 42 (26.25%) 160
Not applicable 1 (100%)
0 (0%) 0 (0%) 1
In Indian River County, White loan applicants had the highest loan denial rates in 2010. American Indian or Alaska Native loan applicants had the highest loan origination rates in the county, outpacing second place African American loan applicants by 4.07 percentage points.
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Martin County Applicant Race Loan Originated Loan Denied Other Total
American Indian or Alaska Native
2 (50%) 1 (25%) 1 (25%) 4
Asian 13 (72.22%) 2 (11.11%) 3 (16.67%) 18
Black or African American 10 (50%) 6 (30%) 4 (20%) 20
Native Hawaiian or Other Pacific Islander
0 (0%) 0 (0%) 1 (100%) 1
White 1062 (67.17%) 222 (14.04%) 297 (18.79%) 1581
Information not provided by applicant in mail, Internet, or telephone application
101 (58.05%) 32 (18.39%) 41 (23.56%) 174
Not applicable 5 (83.33%) 1 (16.67%) 0 (0%) 6
In Martin County, African American loan applicants had the highest loan denial rates in 2010. Asian loan applicants had the highest loan origination rates in the county, outpacing second place White loan applicants by 5.05 percentage points.
Miami-Dade County Applicant Race Loan Originated Loan Denied Other Total
American Indian or Alaska Native
32 (36.78%) 22 (25.29%) 33 (37.93%) 87
Asian 199 (50.90%) 99 (25.32%) 93 (23.80%) 391
Black or African American 941 (47.36%) 574 (28.90%) 472 (23.75%) 1987
Native Hawaiian or Other Pacific Islander
23 (32.85%) 38 (54.29%) 9 (12.86%) 70
White 8546 (52.85%) 4064 (25.13%) 3561 (22.02%) 16171
Information not provided by applicant in mail, Internet, or telephone application
840 (41.54%) 567 (28.04%) 615 (30.42%) 2022
Not applicable 226 (77.13%) 26 (8.87%) 41 (14%)
293
In Miami-Dade County, Native Hawaiian or Other Pacific Islander loan applicants had the highest loan denial rates in 2010. Whites had the highest loan origination rates in the county, outpacing second place Asian loan applicants by 1.95 percentage points.
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Monroe County
Applicant Race Loan Originated Loan Denied Other Total
American Indian or Alaska Native
2 (50%) 1 (25%) 1 (25%) 4
Asian 6 (85.71%) 1 (14.29%) 0 (0%) 7
Black or African American 5 (45.45%) 2 (18.18%) 4 (36.36%) 11
Native Hawaiian or Other Pacific Islander
1 (100%) 0 (0%) 0 (0%) 1
White 627 (61.35%) 218 (21.33%) 177 (17.32%) 1022
Information not provided by applicant in mail, Internet, or telephone application
51 (43.97%) 20 (17.24%) 45 (38.79%) 116
Not applicable 15 (83.33%) 0 (0%)
3 (16.67%) 18
In Monroe County, American Indian or Alaska Native loan applicants had the highest loan denial rates in 2010, though this may be attributed more to the low numbers of loan applicants from this racial category in the county than to any true outcome disparity. Native Hawaiian or Pacific Islander loan applicants had the highest loan origination rates in the county, outpacing second place Asians by 14.29 percentage points. It is important to note that, like the racial category in the county with the highest loan denial rates, the difference between the Native Hawaiian or Other Pacific Islander loan origination rate and that of all other rates may not indicate a disparity in that racial category favor due to its small applicant pool (1 applicant).
Palm Beach County Applicant Race Loan Originated Loan Denied Other Total
American Indian or Alaska Native
18 (40.90%) 13 (29.55%) 13 (29.55%) 44
Asian 284 (57.84%) 94 (19.14%) 113 (23.01%) 491
Black or African American 818 (51.97%) 444 (28.21%) 312 (19.82%) 1574
Native Hawaiian or Other Pacific Islander
27 (52.94%) 12 (23.53%) 12 (23.53%) 51
White 7815 (62.72%) 2308 (18.52%) 2338 (18.76%) 12461
Information not provided by applicant in mail, Internet, or telephone application
752 (49.25%) 362 (23.71%) 413 (27.05%) 1527
In Palm Beach County, American Indian or Alaskan Native loan applicants had the highest loan denial rates in 2010. White loan applicants had the highest loan origination rates in the county, outpacing second place Asians by 4.88 percentage points.
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT
CARRAS COMMUNITY INVESTMENT, INC.
Not applicable 51 (71.83%) 8 (11.27%) 12 (16.90%) 71
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St. Lucie County
Applicant Race Loan Originated Loan Denied Other Total
American Indian or Alaska Native
6 (42.86%) 4 (28.57%) 4 (28.57%) 14
Asian 44 (61.97%) 17 (23.94%) 10 (14.08%) 71
Black or African American 295 (59%) 116 (23.2%) 89 (17.8%)
500
Native Hawaiian or Other Pacific Islander
9 (64.29%) 3 (21.43%) 2 (14.29%) 14
White 2006 (62.94%) 553 (17.35%) 628 (19.71%) 3187
Information not provided by applicant in mail, Internet, or telephone application
203 (51.39%) 108 (27.34%) 84 (21.27%) 395
Not applicable 8 (80%)
1 (10%)
1 (10%)
10
In St. Lucie County, American Indian or Alaska Native loan applicants had the highest loan denial rates in 2010. Native Hawaiian or Other Pacific Islander loan applicants had the highest loan origination rates in the county, outpacing second place Whites by 1.35 percentage points.
Florida
Applicant Race Loan Originated Loan Denied Other Total
American Indian or Alaska Native
455 (46.19%) 244 (24.77%) 286 (29.04%) 985
Asian 3733 (59.20%) 1282 (20.33%) 1291 (20.47%) 6306
Black or African American 11349 (54.42%) 5621 (26.96%) 3881 (18.61%) 20851
Native Hawaiian or Other Pacific Islander
427 (53.58%) 225 (28.23%) 145 (18.19%) 797
White 114938 (63.66%) 33104 (18.34%) 32496 (18%) 180538
Information not provided by applicant in mail, Internet, or telephone application
13239 (53.28%) 5579 (22.45%) 6032 (24.27%) 24850
Not applicable 790 (78.84%) 84 (8.38%) 128 (12.77%) 1002
Statewide, Native Hawaiian or Other Pacific Islander loan applicants had the highest loan denial rates in 2010. Whites had the highest loan origination rates in the state, outpacing second place Asians by 4.46 percentage points.
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Loan Dispositions by Hispanic/Non-Hispanic Ethnicity
Broward County
Applicant Ethnicity
Loan Originated
Application Denied
Other Total
Hispanic or Latino
3014 (55.08%)
1353 (24.73%)
1105 (20.19%)
5472
Not Hispanic or Latino
8820 (57.60%)
3303 (21.57%)
3190 (20.83%)
15313
Information not provided by applicant in mail, Internet, or telephone application
1059 (45.80%)
612 (26.47%)
641 (27.72%)
2312
Not applicable 61 (85.92%)
9 (9.90%)
21 (23.10%)
91
Hispanic or Latino loan applicants in Broward County received loan denials at a higher rate than non-Hispanic loan applicants, with the Hispanic or Latino loan denial rate outpacing the non-Hispanic loan denial rate by 3.16 percentage points in 2010. Hispanics or Latino loan applicants in Broward received loan originations at a lower rate than non-Hispanics, with the Hispanic loan origination rate falling 2.52 percentage points behind the non-Hispanic loan origination rate in 2010.
Indian River County
Applicant Ethnicity
Loan Originated
Application Denied
Other Total
Hispanic or Latino
73 (73%)
14 (14%)
13 (13%)
100
Not Hispanic or Latino
964 (68.42%)
224 (15.90%)
221 (15.68%)
1409
Information not provided by applicant in mail, Internet, or telephone application
95 (58.64%)
23 (14.20%)
44 (27.16%)
162
Not applicable 1 (100%)
0 (0%)
0 (0%)
1
Hispanic or Latino loan applicants in Indian River County received loan denials at a lower rate than non-Hispanic loan applicants, with the non-Hispanic loan denial rate outpacing the Hispanic loan denial rate by 1.9 percentage points in 2010. Hispanic of Latino loan applicants in Indian River County received loan originations at a higher rate than non-Hispanic loan applicants, with the Hispanic loan origination rate outpacing the non-Hispanic loan origination rate by 4.58 percentage points in 2010.
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Martin County Applicant Ethnicity
Loan Originated
Application Denied
Other Total
Hispanic or Latino
45 (61.64%)
19 (26.02%)
9 (12.34%)
73
Not Hispanic or Latino
1042 (67.37%)
213 (13.77%)
292 (18.88%)
1547
Information not provided by applicant in mail, Internet, or telephone application
101 (56.74%)
31 (17.42%)
46 (25.84%)
178
Not applicable 5 (83.34%)
1 (16.67%)
0 (0%)
6
Hispanic or Latino loan applicants in Martin County received loan denials at a higher rate than non-Hispanics, with the Hispanic or Latino loan denial rate outpacing the non-Hispanic loan denial rate by 12.25 percentage points in 2010. Hispanics in Martin County received loan originations at a lower rate than non-Hispanics, with the Hispanic loan origination rate falling 5.73 percentage points behind the non-Hispanic loan origination rate in 2010.
Miami-Dade County
Applicant Ethnicity
Loan Originated
Application Denied
Other Total
Hispanic or Latino
6559 (51.79%)
3339 (26.37%)
2766 (21.84%)
12664
Not Hispanic or Latino
3338 (52.09%)
1571 (24.52%)
1498 (23.38%)
6407
Information not provided by applicant in mail, Internet, or telephone application
683 (41.29%)
453 (27.39%)
518 (31.32%)
1654
Not applicable 227 (76.69%)
27 (9.12%)
42 (14.19%)
296
Hispanic or Latino loan applicants in Miami-Dade County received loan denials at a higher rate than non-Hispanics, with the Hispanic loan denial rate outpacing the non-Hispanic loan denial rate by 1.85 percentage points in 2010. Hispanic or Latino loan applicants in Miami-Dade County received loan originations at a lower rate than non-Hispanics, with the Hispanic loan origination rate falling 0.3 percentage points behind the non-Hispanic loan origination rate in 2010.
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT
CARRAS COMMUNITY INVESTMENT, INC.
Monroe County
Applicant Ethnicity Loan Originated
Application Denied
Other Total
Hispanic or Latino 84 (59.57%)
34 (24.11%)
23 (16.31%)
141
Not Hispanic or Latino
554 (61.01%)
191 (21.03%)
163 (17.95%)
908
Information not provided by applicant in mail, Internet, or telephone application
54 (48.21%)
17 (15.18%)
41 (36.60%)
112
Not applicable 15 (83.33%)
0 (0%)
3 (16.67%)
18
Hispanic or Latino loan applicants in Monroe County received loan denials at a higher rate than non-Hispanics, with the Hispanic loan denial rate outpacing the non-Hispanic loan denial rate by 3.08 percentage points in 2010. Hispanic or Latino loan applicants in Monroe County received loan originations at a lower rate than non-Hispanics, with the Hispanic loan origination rate falling 1.44 percentage points behind the non-Hispanic loan origination rate in 2010.
Palm Beach County Applicant Ethnicity
Loan Originated
Application Denied
Other Total
Hispanic or Latino 1268 (56.10%)
578 (25.58%)
414 (18.32%)
2260
Not Hispanic or Latino
7692 (62.22%)
2300 (18.60%)
2371 (19.18%)
12363
Information not provided by applicant in mail, Internet, or telephone application
754 (49.54%)
355 (23.32%)
413 (27.14%)
1522
Not applicable 51 (68.91%)
8 (1.35%)
15 (20.27%)
74
Hispanic or Latino loan applicants in Palm Beach County received loan denials at a higher rate than non-Hispanics, with the Hispanic loan denial rate outpacing the non-Hispanic loan denial rate by 6.98 percentage points in 2010. Hispanic or Latino loan applicants in Palm Beach County received loan originations at a lower rate than non-Hispanics, with the Hispanic loan origination rate falling 6.12 percentage points behind the non-Hispanic loan origination rate in 2010.
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT
CARRAS COMMUNITY INVESTMENT, INC.
St. Lucie County
Applicant Ethnicity Loan Originated
Application Denied
Other Total
Hispanic or Latino 319 (57.89%)
118 (21.42%)
114 (20.69%)
551
Not Hispanic or Latino
2046 (63.07%)
580 (17.88%)
618 (19.05%)
3244
Information not provided by applicant in mail, Internet, or telephone application
198 (51.30%)
103 (26.68%)
85 (22.02%)
386
Not applicable 8 (80%)
1 (10%)
1 (10%)
10
Hispanic or Latino loan applicants in St. Lucie County received loan denials at a higher rate than non-Hispanic loan applicants, with the Hispanic loan denial rate outpacing the non-Hispanic loan denial rate by 3.54 percentage points in 2010. Hispanics in St. Lucie County received loan originations at a lower rate than non-Hispanics, with the Hispanic loan origination rate falling 5.18 percentage points behind the non-Hispanic loan origination rate in 2010.
Florida
Applicant Ethnicity Loan Originated
Application Denied
Other Total
Hispanic or Latino 21806 (55.59%)
9727 (24.80%)
7694 (19.61%)
39227
Not Hispanic or Latino
109580 (64.06%)
30903 (18.07%)
30565 (17.90%)
171048
Information not provided by applicant in mail, Internet, or telephone application
12749 (55.03%)
5423 (22.56%)
5868 (24.41%)
24040
Not applicable 796 (79.28%)
86 (8.56%)
132 (13.15%)
1004
Hispanic or Latino loan applicants statewide received loan denials at a higher rate than non-Hispanics, with the Hispanic loan denial rate outpacing the non-Hispanic loan denial rate by 6.73 percentage points in 2010. Hispanics in statewide received loan originations at a lower rate than non-Hispanics, with the Hispanic loan origination rate falling 8.47 percentage points behind the non-Hispanic loan origination rate in 2010.
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT
CARRAS COMMUNITY INVESTMENT, INC.
Loan Denial Disparities by Race and Ethnicity Loan Application Denial Disparities Across the Seven County South Florida
Region By Race
Applicant Race
Broward County
Disparity
Indian River
County Disparity
Martin County
Disparity
Miami-Dade
County Disparity
Monroe County
Disparity
Palm Beach County
Disparity
St. Lucie County
Disparity
American Indian or Alaska Native
1.27 N/V 1.78 1.01 1.17 1.59 1.64
Asian 1.04 N/V 0.79 1.01 0.67 1.03 1.38
Black or African American
1.42 0.8 2.14 1.15 0.85 1.52 1.34
Native Hawaiian or Other Pacific Islander
1.78 N/V N/V 2.16 N/V 1.27 1.24
White N/A N/A N/A N/A N/A N/A N/A
Loan Application Denial Disparities Across the Seven County South Florida Region By Hispanic/Non-Hispanic Ethnicity
Applicant Ethnicity
Broward County
Disparity
Indian River
County Disparity
Martin County
Disparity
Miami-Dade
County Disparity
Monroe County
Disparity
Palm Beach County
Disparity
St. Lucie County
Disparity
Hispanic 1.15 0.88 1.89 1.08 1.15 1.38 1.2
Across the seven-county South Florida Region, the applicant race with the largest loan application denial disparity from that of whites are Native Hawaiian or Other Pacific Islander loan applicants in Miami-Dade County, who are 2.16 times more likely than a white applicant in that county to receive a home loan denial. African-Americans in Martin County had the second largest disparity, being 2.14 times more likely to receive a loan denial than a white applicant. The applicant race with the lowest application denial disparity from that of whites are Asian loan applicants in Monroe County, who are .67 times more likely to receive a home loan than whites in Monroe County.
Across the seven-county South Florida region, the county the highest disparity between Hispanic or Latino and non-Hispanic loan applicants in 2010 was in Martin County, Florida. In Martin County, Hispanics were 1.89 times more likely to receive a loan denial in 2010.
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT
CARRAS COMMUNITY INVESTMENT, INC.
Non-Hispanic
N/A N/A N/A N/A N/A N/A N/A
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT
CARRAS COMMUNITY INVESTMENT, INC.
Subprime Lending Across the seven-county South Florida region, only Miami-Dade County had a subprime/high cost loan origination rate higher than the state average in 2010. The county with the lowest rate of subprime/high cost loans is Monroe County at 1.54% of all its loans in 2010.
Subprime/High Cost Loans in the Seven County Southeast Florida Region Compared to the State of Florida
County High Cost Non-High Cost or Unknown
Total
Broward County 334 (2.91%)
11148 (97.09%)
11482
Indian River County 19 (2.25%)
826 (97.75%)
845
Martin County 25 (2.73%)
891 (97.27%)
916
Miami-Dade County 410 (4.58%)
8551 (95.42%)
8961
Monroe County 5 (1.54%)
320 (98.46%)
325
Palm Beach County 201 (2.48%)
7896 (97.52%)
8097
St. Lucie County 51 (2.55%)
1950 (97.45%)
2001
Florida 4177 (3.50%)
115111 (96.50%)
119288
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT
CARRAS COMMUNITY INVESTMENT, INC.
Subprime Lending by Race Broward County
Race High-Cost Non-High Cost or Unknown
Total
American Indian or Alaska Native
0 37 (100%)
37
Asian 5 (1.25%)
395 (98.75%)
400
Black or African American 94 (4.56%)
1967 (95.43%)
2061
Native Hawaiian or Other Pacific Islander
1 (2.85%)
34 (97.14%)
35
White 221 (2.78%)
7726 (97.23%)
7947
Information not provided by applicant in mail, Internet, or telephone application
13 (1.30%)
988 (98.70%)
1001
Not applicable 0 (0%)
1 (100%)
1
Indian River Race High-Cost Non-High Cost
or Unknown Total
American Indian or Alaska Native
0 (0%)
3 (100%)
3
Asian 0 (0%)
8 (100%)
8
Black or African American 2 (5.12%)
37 (94.87%)
39
White 15 (2.05%)
715 (97.95%)
730
Information not provided by applicant in mail, Internet, or telephone application
2 (3.07%)
63 (96.92%)
65
African-American loan applicants had the highest rate of subprime/high cost loans in Broward County in the year 2010 at 4.56% of all its racial category loan originations. Asian loan applicants had the lowest rate of subprime/high cost loans in the county at 1.25% of all its racial category loan originations.
African-American loan applicants had the highest rate of subprime/high cost loans in Indian River County in the year 2010 at 5.12% of all its racial category loan originations. Asian loan applicants had the lowest rate of subprime/high cost loans in the county at 1.25% of all its racial category loan originations.
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT
CARRAS COMMUNITY INVESTMENT, INC.
Miami-Dade County Race High-Cost Non-High Cost
or Unknown Total
American Indian or Alaska Native
4 (14.81%)
23 (85.19%)
27
Asian 6 (3.77%)
153 (96.23%)
159
Black or African American 31 (3.42%)
876 (96.58)
907
Native Hawaiian or Other Pacific Islander
0 (0%)
18 (100%)
18
White 342 (4.79%)
6799 (95.21%)
7141
Information not provided by applicant in mail, Internet, or telephone application
27 (3.87%)
671 (96.13%)
698
Not applicable 0 (0%)
11 (100%)
11
Monroe County Race High-Cost Non-High Cost
or Unknown Total
American Indian or Alaska Native
0 (0%)
1 (100%)
1
Asian 0 (0%)
3 (100%)
3
Black or African American 0 (0%)
4 (100%)
4
Native Hawaiian or Other Pacific Islander
0 (0%)
1 (100%)
1
White 5 (1.69%)
291 (98.31%)
296
Information not provided by applicant in mail, Internet, or telephone application
0 (0%)
20 (100%)
20
White loan applicants had the highest rate of subprime/high cost loans in Monroe County in the year 2010 at 1.69% of all its racial category loan originations. For all other racial categories listed, none of their loan originations were high cost in 2010.
American Indian or Alaskan Native loan applicants had the highest rate of subprime/high cost loans in Miami-Dade County in the year 2010 at 14% of all its racial category loan originations. Native Hawaiian or Other Pacific Islander loan applicants had the lowest rates of subprime/high cost loans in the county at 0% of all its racial category loan originations.
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT
CARRAS COMMUNITY INVESTMENT, INC.
Palm Beach County Race High-Cost Non-High Cost
or Unknown Total
American Indian or Alaska Native
1 (7.14%)
13 (92.86%)
14
Asian 2 (.8%)
225 (99.12%)
227
Black or African American 28 (3.65%)
739 (96.34%)
767
Native Hawaiian or Other Pacific Islander
0 (0%)
24 (100%)
24
White 163 (2.57%)
6313 (97.48%)
6476
Information not provided by applicant in mail, Internet, or telephone application
7 (1.19%)
582 (98.81%)
589
St. Lucie County
Race High-Cost Non-High Cost or Unknown
Total
American Indian or Alaska Native
0 (0%)
6 (100%)
6
Asian 0 (0%)
33 (100%)
33
Black or African American 8 (3.2%)
242 (96.8%)
250
Native Hawaiian or Other Pacific Islander
0 (0%)
8 (100%)
8
White 39 (2.50%)
1519 (97.50%)
1558
American Indian or Alaskan Native loan applicants had the highest rate of subprime/high cost loans in Palm Beach County in the year 2010 at 7.14% of all its racial category loan originations. Native Hawaiian or Other Pacific Islander loan applicants had the lowest rates of subprime/high cost loans in the county at 0% of all its racial category loan originations.
African American loan applicants had the highest rate of subprime/high cost loans in St. Lucie County in the year 2010 at 3.2% of all its racial category loan originations. Native Hawaiian or Other Pacific Islander loan applicants had the lowest rates of subprime/high cost loans in the county at 0% of all its racial category loan originations.
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT
CARRAS COMMUNITY INVESTMENT, INC.
Information not provided by applicant in mail, Internet, or telephone application
4 (2.74%)
142 (97.26%)
146
Subprime Lending by Hispanic/Non Hispanic Ethnicity
Broward County Ethnicity High-Cost Non-High
Cost or Unknown
Total
Hispanic or Latino 103 (3.81%)
2599 (96.19%)
2702
Not Hispanic or Latino 219 (2.79%)
7638 (97.21%)
7857
Information not provided by applicant in mail, Internet, or telephone application
12 (1.30%)
908 (98.70%)
920
Not Applicable 0 (0%)
3 (100%)
3
Indian River County Ethnicity High-Cost Non-High
Cost or Unknown
Total
Hispanic or Latino 1 (1.56%)
63 (98.45%)
64
Not Hispanic or Latino 16 (2.29%)
700 (97.77%)
716
Information not provided by applicant in mail, Internet, or telephone application
2 (3.07%)
63 (96.92%)
65
In 2010, Hispanic or Latino loan applicants had a higher rate of high cost loan originations than non-Hispanic loan applicants in Broward County. The Hispanic loan applicant high cost loan origination rate in 2010 was 1.02 percentage points higher than the non-Hispanic loan applicant high cost loan origination rate.
In 2010, Hispanic or Latino loan applicants had a lower rate of high cost loan originations than non-Hispanic or Latino loan applicants in Indian River County. The Hispanic applicant high cost loan origination rate in 2010 was 0.73 percentage points lower than the non-Hispanic or Latino loan applicant high cost loan origination rate.
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT
CARRAS COMMUNITY INVESTMENT, INC.
Martin County Ethnicity High-Cost Non-High
Cost or Unknown
Total
Hispanic or Latino 0 (0%)
33 (100%)
33
Not Hispanic or Latino 24 (2.97%)
785 (97.03%)
809
Information not provided by applicant in mail, Internet, or telephone application
1 (1.35%)
73 (98.65%)
74
Miami-Dade County Ethnicity High-Cost Non-High
Cost or Unknown
Total
Hispanic or Latino 290 (5.21%)
5273 (94.79%)
5563
Not Hispanic or Latino 104 (3.68%)
2720 (96.32%)
2824
Information not provided by applicant in mail, Internet, or telephone
16 (2.85%)
546 (97.15%)
562
In 2010, Hispanic or Latino loan applicants had a lower rate of high cost loan originations than non-Hispanic or Latino loan applicants in Martin County. The Hispanic or Latino loan applicant high cost loan origination rate in 2010 was 2.97 percentage points lower than the non-Hispanic or Latino loan applicant high cost loan origination rate.
In 2010, Hispanic or Latino loan applicants had a higher rate of high cost loan originations than non-Hispanic or Latino loan applicants in Miami-Dade County. The Hispanic applicant high cost loan origination rate in 2010 was 1.53 percentage points higher than the non-Hispanic or Latino loan applicant high cost loan origination rate.
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT
CARRAS COMMUNITY INVESTMENT, INC.
application
Not applicable 0 (0%)
12 (100%)
12
Monroe County Ethnicity High-Cost Non-High
Cost or Unknown
Total
Hispanic or Latino 1 (2.56%)
38 (97.44%)
39
Not Hispanic or Latino 4 (1.52%)
260 (98.48%)
264
Information not provided by applicant in mail, Internet, or telephone application
0 (0%)
22 (100%)
22
Palm Beach County Ethnicity High-Cost Non-High
Cost or Unknown
Total
Hispanic or Latino 54 (4.60%)
1120 (95.40%)
1174
Not Hispanic or Latino 136 (2.15%)
6196 (97.85%)
6332
Information not provided by applicant in mail, Internet, or telephone application
11 (1.86%)
580 (98.14%)
591
In 2010, Hispanic or Latino loan applicants had a higher rate of high cost loan originations than non-Hispanic or Latino loan applicants in Monroe County. The Hispanic or Latino applicant high cost loan origination rate in 2010 was 1.04 percentage points higher than the non-Hispanic or Latino loan applicant high cost loan origination rate.
In 2010, Hispanic or Latino loan applicants had a lower rate of high cost loan originations than non-Hispanic or Latino loan applicants in St. Lucie County. The Hispanic applicant high cost loan origination rate in 2010 was 0.69 percentage points lower than the non-Hispanic or Latino loan applicant high cost loan origination rate.
In 2010, Hispanic or Latino loan applicants had a higher rate of high cost loan originations than non-Hispanic or Latino loan applicants in Palm Beach County. The Hispanic or Latino loan applicant high cost loan origination rate in 2010 was 2.45 percentage points higher than the non-Hispanic or Latino loan applicant high cost loan origination rate.
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT
CARRAS COMMUNITY INVESTMENT, INC.
St. Lucie County Ethnicity High-Cost Non-High Cost
or Unknown Total
Hispanic or Latino 5 (1.93%)
254 (98.07%)
259
Not Hispanic or Latino
42 (2.62%)
1561 (97.38%)
1603
Information not provided by applicant in mail, Internet, or telephone application
4 (2.83%)
135 (97.12%)
139
Subprime Lending Disparities by Race and Ethnicity High Cost Loan Disparity Across the Seven County South Florida Region By Race
Applicant Race Broward County Disparity
Indian River County Disparity
Martin County Disparity
Miami-Dade County Disparity
Monroe County Disparity
Palm Beach County Disparity
St. Lucie County Disparity
American Indian or Alaska Native
No High Cost Loans
No High Cost Loans
No High Cost Loans
3.09 No High Cost Loans
2.79 No High Cost Loans
Asian 0.45 No High Cost Loans
3.73 ,78 No High Cost Loans
0.31 No High Cost Loans
Black or African American
1.64 2.5 No High Cost Loans
0.71 No High Cost Loans
1.42 1.28
Native Hawaiian or Other Pacific Islander
1.03 Not Listed Not Listed No High Cost Loans
No High Cost Loans
No High Cost Loans
No High Cost Loans
White N/A N/A N/A N/A N/A N/A N/A
The applicant race with the greatest high cost loan rate disparity from that of Whites are Asian loan applicants in Martin County, who are 3.73 times more likely to receive a high-cost loan origination than their white counterparts. Asian loan applicants in Palm Beach County have the lowest high cost loan rate disparity from that of White loan applicants. They are .31 times as likely as their White loan applicant counterparts to receive a high-cost loan origination.
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT
CARRAS COMMUNITY INVESTMENT, INC.
High Cost Loan Disparity Across the Seven County South Florida Region by Hispanic Ethnicity Applicant Ethnicity
Broward County
Disparity
Indian River
County Disparity
Martin County
Disparity
Miami-Dade
County Disparity
Monroe County
Disparity
Palm Beach County
Disparity
St. Lucie County
Disparity
Hispanic Ethnicity 1.37 0.69 No High Cost Loans
1.42 1.69 2.14 0.74
Non-Hispanic Ethnicity
N/A N/A N/A N/A N/A N/A N/A
The greatest high cost loan origination disparity between Hispanic or Latino loan applicants and non-Hispanic or Latino loan applicants is in Palm Beach County, where Hispanics are 2.14 times more likely to receive a high cost loan than their non-Hispanic counterparts.
4.3 Summary of the Data 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. The full range of racial and ethnic groups included in this analysis has either higher loan denial or subprime lending rates in the counties analyzed.
All but three of the analyzed South Florida counties have overall loan origination rates higher than the state of Florida rate, which means that the counties with the higher rates, Broward, Monroe, Miami-Dade, Palm Beach & St. Lucie, have above average loan origination rates for the state of Florida. Interestingly, only three of the region’s seven counties, Indian River, Martin and St. Lucie, have loan denial rates below the state-wide rate. So, the region generally has a higher percentage of its loan applications that are originated but also a higher percentage of its loan originations that are denied than the state of Florida in general.
The most prevalent reason for loan denials within the counties of the South Florida region was the applicant’s debt to income ratio, the reason accounting for largest percentage of loan denial in five of the region’s seven counties (Broward County, Indian River County, Monroe County, Palm Beach County, & St. Lucie County). The second most prevalent reason for loan denials in the region, which accounted for the majority of loan denials in two of the region’s counties (Miami-Dade County & Martin County), was the amount of collateral the loan applicant had.
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT
CARRAS COMMUNITY INVESTMENT, INC.
As stated earlier, loan dispositions based on race and the racial groups with the highest adverse dispositions varied across the region’s seven counties. In three of the region’s counties, American Indian or Alaska Native loan applicants had the highest loan denial rates (Monroe County, Palm Beach County and St. Lucie County). In two of the region’s counties, Native Hawaiian or Other Pacific Islander loan applicants had the highest loan denial rates (Miami-Dade County and Broward County). White applicants had the highest loan denial rate in Indian River County and African Americans had the highest loan denial rate in Martin County.
Hispanic applicants received loan denials at a higher rate than that of non-Hispanic applicants in six out of the seven South Florida counties, with only Hispanic applicants in Indian River County having lower loan application rates than non-Hispanics.
When examining the disparity between white applicants and applicants of other races across the seven counties, it was discovered that the largest disparity in loan denial rates from that of whites in the region were that of Native Hawaiian or Other Pacific Islander applicants in Miami-Dade County. The least disparity was that of Asian applicants in Monroe County. When examining the disparity between Hispanics and non-Hispanics in a similar manner, the largest disparity in loan denial rates between Hispanics and that of non-Hispanics was in Martin County.
When examining subprime lending by race, no single race uniformly had the highest rates of subprime originations across all seven counties. African Americans had the highest rates of subprime loan originations in three of the region’s counties (Broward, Indian River and St. Lucie County). American Indian or Alaska Natives had the highest rates of subprime loan originations in two of the region’s counties (Palm Beach and Miami-Dade). Whites had the highest rates of subprime loan originations in one of the region’s counties (Indian River County).
Hispanics had higher rates of subprime loan origination in four of the region’s seven counties (Palm Beach County, Monroe County, Miami-Dade County and Broward County. In three of the region’s counties, Hispanics had lower rates of subprime loan origination (St. Lucie County, Martin County and Indian River County).
When examining the disparity in the rate of subprime loan originations between white applicants and that of other races, the greatest disparity was found among Asian applicants in Martin County. The greatest disparity in the rate of subprime originations between Hispanics and that of non-Hispanics was found in Palm Beach County.
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT
CARRAS COMMUNITY INVESTMENT, INC.
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT
CARRAS COMMUNITY INVESTMENT, INC.
5. Identified Impediments to fair housing 5 .1 Key Impediments Region-wide
0
5
10
15
20
Housing/Lending Discrimination on the Basis of Race,
Color, National Origin, Religion,
Sex, Familial status and Disability
(Protected Classes)
Lack of Knowledge,
Awarness of or Education on Fair
Housing Protections
Fair and Equal Lending Disparities
Housing Market Segregation
Shortage of Affordable Housing
Opportunities
Violations of Federal, State and Local Fair Housing
Laws
Limited Funding to Meet Need for
Affordable Housing
Predatory Lending Improvement of the Housing
Discrimination Complaint Process
Zoning/Land Use
15
19
15
9 10 9 7
9
4 6
Number of South Florida Jurisdictions Citing Issue as an Impeidment to Fair Housing Choice
Number of South Florida Jurisdictions Citing Issue as an Impeidment to Fair Housing Choice
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT
CARRAS COMMUNITY INVESTMENT, INC.
Impediment #1: Lack of Knowledge, Awareness of, or Education on Fair Housing Protections This impediment was found to be the most prevalent one within the seven county South Florida region, with 19 of the region’s 31 examined AIs finding it to be an impediment to fair housing choice in their communities. The cities of Coconut Creek and Miramar discuss this issue in detail in their AIs, stating that many potential homeowners lack the understanding of the path to homeownership. The city stated that a majority of loan denials were due to avoidable issues, such as incomplete loan applications, unverifiable information and collateral, among others (City of Coconut Creek, 2011; City of Miramar, 2011).
Impediment #2: Fair and Equal Lending Disparities This impediment was discussed in 15 of the region’s 31 examined AIs, making it the second most prevalent impediment in the region. The prevalence of this issue in the south Florida region is underlined in the subprime data discussed earlier in this analysis. The City of Miami discusses the impediment in its AI, stating that African Americans and Hispanics tend to have higher loan application failure rates when HMDA lending data is analyzed by race and ethnicity (City of Miami, 2007).
Impediment #3: Housing/Lending Discrimination on the Basis of Race, Color, National Origin, Religion, Sex, Familial Status and Disability This impediment was discussed in 15 of the region’s 31 examined AIs, making this issue tied with fair and equal lending disparities as the second most prevalent issue throughout the region. The data gathered on the lending patterns of the seven observed south Florida counties supports this finding, with the data indicating regular disparities on loan approvals and denials by race and by Hispanic/non-Hispanic ethnicity. The City of Fort Lauderdale’s AI discusses the impediment, stating that it occurs when, on the basis of a person being part of a protected class, lenders deny or alter services or access to housing through actions such as denying property insurance to applicants, conducting property appraisals in a discriminatory manner or by setting different terms or privileges in the sale of a dwelling, among other actions (City of Fort Lauderdale, 2010).
Impediment #4: Shortage of Affordable Housing Opportunities This impediment was discussed in 10 of the region’s 31 examined AIs, making it the region’s fourth most prevalent impediment. The city of Delray Beach discusses its particular situation under this impediment in detail, stating that it currently has 600 families on its waiting list for its City of Delray Beach Housing Choice Vouchers. The waiting list, due to the high number of families on it, has been closed until the number of families on the waiting list decreases to 200. In addition, families in the city seeking housing assistance typically wait four to five years before that assistance is received (City of Delray Beach, 2009).
Impediment #5: Violations of Federal, State and Local Housing Laws This impediment was discussed in nine of the region’s 31 examined AIs, making it tied with predatory lending as and Housing Market Segregation as the fifth most prevalent impediment to fair housing choice in the region. The City of Hollywood, Florida discusses this impediment in its AI, stating that it will tackle the impediment through a public relations campaign to promote the knowledge of fair
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT
CARRAS COMMUNITY INVESTMENT, INC.
housing laws and assistance programs through various forms of media and to provide information about fair housing and phone numbers for assistance on the city’s website (City of Hollywood, 2010).
Impediment #6: Housing Market Segregation This impediment was discussed in nine of the region’s 31 examined AIs, making it the fifth most prevalent impediment to fair housing choice in the region, tied with the violation of federal, state and local housing laws impediment and the predatory lending impediment. The City of North Miami Beach seeks to tackle this impediment head on, calling for activities that are geared toward creating city neighborhoods that are more open and inclusive though affirmative training technical assistance to developers in the city using federal funding dollars to develop and redevelop housing as well as provide such training to city staff, community advocates, housing providers and area financial institutions (North Miami, 2011).
Impediment #7: Predatory Lending This impediment was discussed in nine of the region’s 31 examined AIs, making it tied for fifth most prevalent impediment in the region, tied with the housing market segregation impediment and the shortage of affordable housing opportunities impediment. The impacts of predatory lending, which was discussed earlier in the report, are described in detail in the City of Delray Beach AI, which states that predatory lending, due to its high costs, abusive practices, and hard requirements, has the potential to strip borrowers of home equity, ruin their credit records and increases the odds of home foreclosure. The city states that some of its census tracts are experiencing high levels of abandonment due to pending foreclosures which may be attributed to predatory lending (City of Delray Beach, 2009).
Impediment #8: Limited Funding to Meet Need for Affordable Housing This impediment was discussed in seven of the region’s 31 examined AIs, making it the eighth most prevalent impediment in the region. The City of Miami discusses this impediment, stating that it stems to annual decreases of federal funding to support affordable housing creation efforts. The city plans on overcoming this impediment by reducing the amount of federal subsidies per household through the tightening of bedroom restrictions and to attempt to accommodate as many Housing Opportunities for Persons with Aids (HOPWA) residents as it can in its Long-term Rental Assistance Program (City of Miami, 2007).
Impediment #9: Zoning/Land Use This impediment was discussed in six of the region’s 31 examined AIs, making it the ninth most prevalent impediment in the region. The City of Miramar, Florida discusses the impediment in detail in their AI. The city admits that its existing zoning, land use and future land use regulation influence the number of housing options in their city and their quality. The city provides a way to work with the influence, stating that the more types of zoned housing districts that a jurisdiction has the more likely that it will be able to accommodate diverse housing types developable on varying lot sizes, lowering their cost and increasing their affordability. The city follows this approach, providing sixteen residential housing districts in their zoning code ranging from a rural district of one dwelling per many acres, to a
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT
CARRAS COMMUNITY INVESTMENT, INC.
Residential-25 with 25 dwellings per acre. The city also moved to remove regulatory barriers to the construction of affordable housing based in its zoning code and created a dense Traditional Neighborhood District along its State Road 7 Corridor (City of Miramar, 2011).
Impediment #10: Improvement of the Housing Discrimination Complaint Process This impediment was discussed in four of the region’s 31 examined AIs, making it the tenth most prevalent impediment in the region. Pembroke Pines, Florida discusses some of the issues under this impediment, stating that the complaint process is hampered by organizational deficiencies and redundancy. Pembroke Pines elaborates on these points through illustrations, to include the fact that there are three entities (Broward County Civil Rights Division 4, U.S. HUD and HOPE, Inc.) who receive complaints of housing discrimination in the county and since housing complaints may be, and are at times, files in more than one of the entities, calculating a true number or volume of housing discrimination incidents in the city is difficult, due to the numbers being skewed by redundancies. Another situation that the city details is the fact that Broward county, when they receive discrimination complaints, are not required to list more than the name of the lender involved in the complaint and the basis of the complaint, but not the location of the complaint. Because of this, the assessment of location-based levels of housing discrimination is made more difficult (Broward County, 2011).
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT
CARRAS COMMUNITY INVESTMENT, INC.
5.2 Key Impediments by County
Broward County
Key Impediments in Broward County Florida
Impediment Housing/Lending Discrimination on the Basis of Race, Color, National Origin, Religion, Sex, Familial status and Disability (Protected Classes)
Lack of Knowledge, Awareness of, or Education on, Fair Housing Protections
Fair and Equal Lending Disparities
Housing Market Segregation
Shortage of Affordable Housing Opportunities
Violations of Federal, State and Local Fair Housing Laws
Limited Funding to Meet Need for Affordable Housing
Predatory Lending Improvement of the Housing Discrimination Complaint Process
Zoning/Land Use
Number of Jurisdictions in Broward County Citing Impediment In Their AI
10 10 8 5 4 5 3 5 3 4
The most cited impediments to fair housing choice in Broward County is the lack of knowledge, awareness of, or education on fair housing protections impediment and the housing/lending discrimination on the basis of being a member of a protected class impediment, with ten jurisdictions in the county citing each as impediments to fair housing choice.
Indian River County
Key Impediments in Indian River County Florida
Impediment Housing/Lending Discrimination on the Basis of Race, Color, National Origin, Religion, Sex, Familial status and Disability (Protected Classes)
Lack of Knowledge, Awareness of, or Education on, Fair Housing Protections
Fair and Equal Lending Disparities
Housing Market Segregation
Shortage of Affordable Housing Opportunities
Violations of Federal, State and Local Fair Housing Laws
Limited Funding to Meet Need for Affordable Housing
Predatory Lending Improvement of the Housing Discrimination Complaint Process
Zoning/Land Use
Number of Jurisdictions in Broward County Citing Impediment In Their AI
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
Indian River County has no entitlement communities, thus, none of its jurisdictions have AI documents and impediment to fair housing choice information available.
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT
CARRAS COMMUNITY INVESTMENT, INC.
Martin County
Key Impediments in Martin County Florida
Impediment Housing/Lending Discrimination on the Basis of Race, Color, National Origin, Religion, Sex, Familial status and Disability (Protected Classes)
Lack of Knowledge, Awareness of, or Education on, Fair Housing Protections
Fair and Equal Lending Disparities
Housing Market Segregation
Shortage of Affordable Housing Opportunities
Violations of Federal, State and Local Fair Housing Laws
Limited Funding to Meet Need for Affordable Housing
Predatory Lending Improvement of the Housing Discrimination Complaint Process
Zoning/Land Use
Number of Jurisdictions in Broward County Citing Impediment In Their AI
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
Martin County has no entitlement communities, thus, none of its jurisdictions have AI documents and impediment to fair housing choice information available.
Miami-Dade County
Key Impediments in Miami-Dade County Florida
Impediment Housing/Lending Discrimination on the Basis of Race, Color, National Origin, Religion, Sex, Familial status and Disability (Protected Classes)
Lack of Knowledge, Awareness of, or Education on, Fair Housing Protections
Fair and Equal Lending Disparities
Housing Market Segregation
Shortage of Affordable Housing Opportunities
Violations of Federal, State and Local Fair Housing Laws
Limited Funding to Meet Need for Affordable Housing
Predatory Lending Improvement of the Housing Discrimination Complaint Process
Zoning/Land Use
Number of Jurisdictions in Broward County Citing Impediment In Their AI
2 7 6 3 3 4 4 1 1 0
The most cited impediment of fair housing choice in Miami-Dade County is a lack of knowledge, awareness of, or education on fair housing protections, with seven jurisdictions within the county citing the issue as an impediment to fair housing choice. The second most cited impediment in Miami-Dade County is fair and equal lending disparities, with six jurisdictions within the county citing it as an impediment to housing choice.
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT
CARRAS COMMUNITY INVESTMENT, INC.
Monroe County Key Impediments in Monroe County Florida
Impediment Housing/Lending Discrimination on the Basis of Race, Color, National Origin, Religion, Sex, Familial status and Disability (Protected Classes)
Lack of Knowledge, Awareness of, or Education on, Fair Housing Protections
Fair and Equal Lending Disparities
Housing Market Segregation
Shortage of Affordable Housing Opportunities
Violations of Federal, State and Local Fair Housing Laws
Limited Funding to Meet Need for Affordable Housing
Predatory Lending Improvement of the Housing Discrimination Complaint Process
Zoning/Land Use
Number of Jurisdictions in Broward County Citing Impediment In Their AI
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
Monroe County has no entitlement jurisdictions, thus, none of its jurisdictions have AI documents and impediment to fair housing choice information available.
Palm Beach County Key Impediments in Palm Beach County Florida
Impediment Housing/Lending Discrimination on the Basis of Race, Color, National Origin, Religion, Sex, Familial status and Disability (Protected Classes)
Lack of Knowledge, Awareness of, or Education on, Fair Housing Protections
Fair and Equal Lending Disparities
Housing Market Segregation
Shortage of Affordable Housing Opportunities
Violations of Federal, State and Local Fair Housing Laws
Limited Funding to Meet Need for Affordable Housing
Predatory Lending Improvement of the Housing Discrimination Complaint Process
Zoning/Land Use
Number of Jurisdictions in Broward County Citing Impediment In Their AI
1 1 0 0 1 0 0 3 0 2
The most cited impediment of fair housing choice in Palm Beach County is predatory lending, with three jurisdictions within the county citing the issue as an impediment to fair housing choice. The second most cited impediment in Palm Beach County is zoning/land use, with two jurisdictions within the county citing it as an impediment to housing choice.
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT
CARRAS COMMUNITY INVESTMENT, INC.
St. Lucie County Key Impediments in St. Lucie County Florida
Impediment Housing/Lending Discrimination on the Basis of Race, Color, National Origin, Religion, Sex, Familial status and Disability (Protected Classes)
Lack of Knowledge, Awareness of, or Education on, Fair Housing Protections
Fair and Equal Lending Disparities
Housing Market Segregation
Shortage of Affordable Housing Opportunities
Violations of Federal, State and Local Fair Housing Laws
Limited Funding to Meet Need for Affordable Housing
Predatory Lending Improvement of the Housing Discrimination Complaint Process
Zoning/Land Use
Number of Jurisdictions in Broward County Citing Impediment In Their AI
2 1 1 1 2 0 0 0 0 0
The most cited impediments of fair housing choice in St. Lucie County is housing/lending discrimination on the basis of being a member of a protected class and a shortage of affordable housing opportunities, with two jurisdictions within the county citing each issue as an impediment to fair housing choice.
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT
CARRAS COMMUNITY INVESTMENT, INC.
6. Appendix
HUD PD&R Data Package- F O R B R O W A R D , M I A M I - D A D E , & M O N R O E C O U N T I E S O N L Y
Analyzing Segregation A primary metric for identifying segregation is the dissimilarity index. A dissimilarity index represents a summary measure of the extent to which the distribution of any two groups (frequently racial or ethnic groups) differs across census tracts or block-groups. Another common approach to measuring segregation is the isolation index, which compares a group's share of the overall population in a jurisdiction to the average neighborhood share for members of that group.
South Florida Regional Planning Council (Broward, Miami-Dade, and Monroe Counties)
Race/Ethnic Segregation
Share of Population Dissimilarity Index Isolation Index
(2010)
Program Participant
Area (2000)
Program Participant
Area (2010)
Program Participant
Area (2000)
Program Participant
Area (2010)
Program Participant
Area (2000)
Program Participant
Area (2010)
(1) (2) (3) (4) (5) (6)
Non-White/White 63% 72% 0.56 0.54 0.14 0.09
Black-African American/White 19% 20% 0.72 0.68 0.38 0.34
Hispanic/White 40% 48% 0.58 0.56 0.23 0.19
Asian/White 2% 2% 0.36 0.37 0.01 0.02
Pacific-Islander/White 0% 0% 0.49 0.52 0.02 0.03
Native-American/White 0% 0% 0.65 0.70 0.00 0.00
Note: The values in column (1) and (2) are the share of racial/ethnic groups in the participant geography in years 2000 and 2010, respectively. Columns (3) and (4) are the dissimilarity index for years 2000 and 2010. The index compares the spatial distribution of the two groups identified in the left-hand column, summarizing neighborhood differences over a larger geography (program participant geography or metro). Higher values of dissimilarity imply higher residential segregation. Column (5) is the isolation index calculated over the program participant geography for the year 2000, column (6) is the same for the year 2010. The isolation index
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT
CARRAS COMMUNITY INVESTMENT, INC.
compares average neighborhood minority share for a minority person to the average minority share in the larger geography (program participant geography or metro). Again, higher values imply higher levels of segregation. These indexes are calculated using block group 100% count data from the 2000 and 2010 Decennial Census SF1.
Racially/Ethnically-Concentrated Areas of Poverty To assist communities in identifying racially/ethnically-concentrated areas of poverty (RCAPs/ECAPs), HUD PD&R has developed a census tract based definition for RCAP/ECAPs. The definition involves a racial/ethnic concentration threshold and a poverty test. The racial/ethnic concentration threshold is straightforward: RCAP/ECAPs must have a non-white population of 50 percent or more. Census tracts with this extreme poverty that satisfy the racial/ethnic concentration threshold are deemed RCAPs/ECAPs
South Florida Regional Planning Council (Broward, Miami-Dade, and
Monroe Counties)
RCAP /ECAP - Race & Ethnicity Summary Program Participant Area
Count Share
(1) (2)
RCAP/ECAP Tracts 34 3.8%
In RCAP/ECAP Tracts:
Total Population: 127,253 3.0%
Non-White: 121,166 3.9%
Black/African-American 63,959 7.3%
Note: Column (1) is the number of RCAP/ECAP tracts, and the total of persons in those RCAP/ECAP tracts in the program participant area. Column (2) is the share of tracts designated as, and population groups living in, RCAP/ECAPs.
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CARRAS COMMUNITY INVESTMENT, INC.
Disparity in Access to Neighborhood Opportunity - All Persons South Florida Regional Planning Council (Broward, Miami-Dade, and Monroe Counties)
Panel A - All Persons Disparities
All
Persons White
Persons
Black /African
American Persons
Hispanic or Latino Persons
Asian Persons
Native American
Persons
Pacific Isldr.
Persons
Black - White [(3)-(2)]
Hispanic - White [(4)-(2)]
Asian -
White [(5)-(2)]
Native Amer. - White
[(6)-(2)]
Pacific Isldr. - White
[(7)-(2)]
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)
Opportunity Dimensions:
Poverty Index 47 63 35 45 58 42 48 28 18 4 20 14
School Proficiency Index 52 65 37 53 64 49 49 28 11 1 16 16
Labor Market Engagement Index 51 66 33 50 63 44 51 33 16 3 22 16
Job Access Index 48 50 44 46 49 49 48 7 5 2 2 2
Transit Access Index 55 46 62 54 43 53 52 -17 -8 2 -7 -7
Health Hazards Exposure Index 39 47 32 37 44 40 42 15 10 3 7 5
Counts 4,293,858 816,041 781,303 1,700,000 78,769 7,067 1,150
Panel B: Persons in Poverty Disparities
All Poor Persons
Poor White
Persons
Poor Black
Persons
Poor Hispanic or Latino Persons
Poor Asian
Persons
Poor Native
American Persons
Poor Pacific
Isldr. Persons
Poor Black - White [(3)-(2)]
Poor Hispanic - White [(4)-(2)]
Poor Asian
- White [(5)-(2)]
Poor Native Amer. - White
[(6)-(2)]
Poor Pacific Isldr. - White
[(7)-(2)]
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)
Opportunity Dimensions:
Poverty Index 33 50 23 32 51 0 0 27 18 -1 0 0
School Proficiency Index 41 54 29 43 59 0 0 25 11 -4 0 0
Labor Market Engagement Index 37 52 23 40 54 0 0 29 13 -2 0 0
Job Access Index 48 54 45 47 53 0 0 9 7 1 0 0
Transit Access Index 63 56 69 63 57 0 0 -13 -7 -1 0 0
Health Hazards Exposure Index 35 43 31 35 39 0 0 12 7 4 0 0
Counts 627,257 107,032 205,043 308,797 10,931 841 28
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT
CARRAS COMMUNITY INVESTMENT, INC.
Note: Columns (1)-(7) provided a weighted average neighborhood percentile ranking for each dimension (row) described in the left-hand column, weighted by corresponding population group in each column header in Panel A. The percentiles are expressed as 100 centile buckets. Higher percentile values always reflect more favorable average neighborhood characteristics irrespective of the dimension being an asset (proficient schools) or a stressor (poverty). Exposure weighted average are calculated of the program participant geography. Columns (8)-(12) are the differences across average neighborhood conditions between whites and the column group indicated in the header. Positive values imply that whites are in a differentially higher ranking neighborhood on average than the particular group for the given dimension. Negative values imply the reverse, which the given racial/ethnic group is in a differentially higher ranking neighborhood relative to whites along the given dimension. Panel B repeats the analysis in Panel A, but focuses on the average neighborhood of persons in poverty (income< federal poverty line) . Disparities may differ due to rounding. Data for the opportunity dimensions are described in detail in the data documentation. Data on the populations in Panel A is from the 2010 Decennial Census SF1. Data on impoverished population in Panel B comes from the American Community Survey (ACS) 2006-2010 five year estimates. Population groups smaller than 250 people (in census 2010) or 1,000 people for ACS-sourced data are coded as zero. The higher minimum population threshold for the ACS data is motivated by concerns about sampling error.
HUD has developed a two-stage process for analyzing disparities in access to neighborhood opportunity. The first stage involves quantifying the degree to which a neighborhood offers features commonly associated with opportunity. This stage uses metrics that rank each neighborhood along a set of key dimensions. In the second stage, HUD combines these dimension rankings with data on where people in particular subgroups live to develop a measure of that group's general access or exposure to each opportunity dimension. These summary measures can then be compared across subgroups to characterize disparities in access to opportunity. HUD considers opportunity a multi-dimensional notion. To focus the analysis, HUD developed methods to quantify a selected number of the important stressors and assets in every neighborhood. These dimensions were selected because existing research suggests they have a bearing on a range of individual outcomes. In particular, HUD has selected six dimensions upon which to focus:
• Neighborhood School Proficiency • Poverty • Labor Market Engagement • Job Accessibility • Health Hazards Exposure • Transit Access
Invariably, these dimensions do not capture everything that is important to the well being of individuals and families. In quantifying indicators of neighborhood opportunity, HUD is not making a definitive assessment of one's life chances based on geography. HUD is quantifying features of neighborhoods for the purpose of assessing whether significant disparities exist in the spatial access or exposure of particular groups to these quality of life factors.
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT
CARRAS COMMUNITY INVESTMENT, INC.
While these important dimensions capture a number of key concepts identified by research as important to quality of life, the measures are not without limitations. PD&R constrained the scope of HUD-provided items to those that are closely linked to neighborhood geographies and could be measured consistently at small area levels across the country. For example, HUD's measure of school performance only reacts to elementary school proficiency. It does not capture academic achievement for higher-grades of schooling, which is important to a community's well being, but likely less geographically-tied to individual neighborhoods than elementary schools. Similarly, the health hazard exposure measure only captures outdoor toxins, missing in-door exposures. The national-availability restriction is a necessity given that all HUD program participants must complete an Assessment of Fair Housing. HUD realizes that there are other assets and stressors that are relevant for opportunity, such as neighborhood crime or housing unit lead and radon levels. However, these lack consistent neighborhood-level data across all program participant geographies. As a consequence, HUD encourages program participants to supplement the data it provides with robust locally available data on these other assets and stressors, so that the analysis is as all encompassing as possible.
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT
CARRAS COMMUNITY INVESTMENT, INC.
Disparity in Access to Neighborhood Opportunity - All Children South Florida Regional Planning Council (Broward, Miami-Dade, and Monroe Counties)
Panel A - All Persons Disparities
All
Children White
Children
Black /African
American Children
Hispanic or Latino Children
Asian Children
Native American Children
Pacific Isldr.
Children
Black -
White [(3)-(2)]
Hispanic - White [(4)-(2)]
Asian -
White [(5)-(2)]
Native Amer. - White
[(6)-(2)]
Pacific Isldr. - White
[(7)-(2)]
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)
Opportunity Dimensions:
Poverty Index 54 57 30 45 70 45 0 27 12 -‐13 12 0 School Proficiency Index 51 53 33 47 63 48 0 19 5 -‐10 4 0 Labor Market Engagement Index 53 55 37 49 76 48 0 18 7 -‐20 7 0 Job Access Index 48 47 58 52 52 50 0 -‐11 -‐5 -‐6 -‐4 0 Transit Access Index 10 10 10 10 10 10 0 0 0 0 0 0 Health Hazards Exposure Index 52 55 31 43 51 48 0 24 11 4 7 0 Counts 153,056 126,662 11,988 6,887 2,184 476 144
Panel B: Persons in Poverty Disparities
All Poor Children
Poor White
Children
Poor Black
Children
Poor Hispanic or Latino Children
Poor Asian
Children
Poor Native
American Children
Poor Pacific
Isldr. Children
Poor Black
- White [(3)-(2)]
Poor Hispanic - White [(4)-(2)]
Poor Asian
- White [(5)-(2)]
Poor Native Amer. - White
[(6)-(2)]
Poor Pacific Isldr. - White
[(7)-(2)]
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)
Opportunity Dimensions:
Poverty Index 31 36 13 34 0 0 0 23 3 0 0 0 School Proficiency Index 43 47 31 45 0 0 0 15 2 0 0 0 Labor Market Engagement Index 35 38 26 40 0 0 0 13 -‐2 0 0 0
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT
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Job Access Index 51 46 63 57 0 0 0 -‐17 -‐10 0 0 0 Transit Access Index 10 10 10 10 0 0 0 0 0 0 0 0 Health Hazards Exposure Index 44 52 25 34 0 0 0 26 18 0 0 0 Counts 27,055 18,007 6,090 2,804 92 8 0
Note: columns (1)-(7) provided a weighted average neighborhood percentile ranking for each dimension (row) described in the left-hand column, weighted by corresponding population group in each column header in Panel A. The percentiles are expressed as 100 centile buckets. Higher percentile values always reflect more favorable average neighborhood characteristics irrespective of the dimension being an asset (proficient schools) or a stressor (poverty). Exposure weighted average are calculated of the program participant geography. Columns (8)-(12) are the differences across average neighborhood conditions between whites and the column group indicated in the header. Positive values imply that whites are in a differentially higher-ranking neighborhood on average than the particular group for the given dimension. Negative values imply the reverse, which the given racial/ethnic group is in a differentially higher ranking neighborhood relative to whites along the given dimension. Panel B repeats the analysis in Panel A, but focuses on the average neighborhood of children in poverty (income< federal poverty line) . Disparities may differ due to rounding. Data for the opportunity dimensions are described in detail in the data documentation. Data on the populations in Panel A is from the 2010 Decennial Census SF1. Data on impoverished population in Panel B comes from the American Community Survey (ACS) 2006-2010 five year estimates. Population groups smaller than 250 people (in census 2010) or 1,000 people for ACS-sourced data are coded as zero. The higher minimum population threshold for the ACS data is motivated by concerns about sampling error.
Identified Impediments to Fair Housing- Matrix
County Place
Housing/Lending
Discrimination on the Basis of Race, Color, National Origin,
Religion, Sex, Familial status and Disability (Protected Classes)
Lack of Knowledge, Awareness of or Education
on Fair Housing
Protections
Fair and Equal Lending
Disparities
Housing Market
Segregation
Shortage of Affordable Housing
Opportunities
Violations of Federal, State and Local Fair Housing Laws
Limited Funding to
Meet Need for Affordable Housing
Predatory Lending
Improvement of the Housing Discrimination Complaint Process
Zoning/Land Use
Broward
Broward County, FL
X X X X X
Broward
Coconut Creek, FL
X X X X X
Broward Coral Springs
X X X X
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT
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, FL
Broward Davie, FL X X
Broward
Fort Lauderdale, FL
X X X X X
Broward Hollywood, FL X X X
Broward Lauderhill, FL X X X X
Broward Margate, FL X
Broward Miramar, FL X X X X X
Broward
Pembroke Pines, FL
X X X X X
Broward Plantation, FL
X X X X
Broward
Pompano Beach, FL
X X X X X X
Broward Sunrise, FL X X X
Broward Tamarac, FL X X X X X
Indian River County
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
Miami Dade
Miami-‐Dade County, FL
X X X
Miami Dade
Hialeah, FL X X X X
Miami Dade
Homestead, FL
X X X
Miami Dade
Miami, FL X X X X X X X
Miami Dade
Miami Beach, FL
X X X X X
Miami Dade
Miami Gardens, FL
X X X X X
SEVEN50 REGIONAL ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING DRAFT
CARRAS COMMUNITY INVESTMENT, INC.
Miami Dade
North Miami, FL
X X X X
Martin
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
Monroe
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
No Entitlement Communities
Palm Beach
Palm Beach County
X X
Palm Beach
Boca Raton, FL
X
Palm Beach
Boynton Beach, FL
X
Palm Beach
Delray Beach, FL
X X X
Palm Beach
Wellington, FL
Palm Beach
West Palm Beach, FL
X
St. Lucie
Port St. Lucie, FL
X X
St. Lucie
Fort Pierce, FL
X X X X X