ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING

PHASE I HURRICANE IMPACTED COMMUNITIES

State of Texas Texas Department of Housing and Community Affairs Texas Department of Rural Affairs In conjunction with the AI Committee

March 2011

Approved by U.S Department of Housing and Urban Development May 13, 2011

TABLE OF CONTENTS

INDEX OF TABLES, GRAPHS, CHARTS, ETC...... 3

SECTION 1. PURPOSE OF PHASE 1, ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING

AND EXECUTIVE SUMMARY...... 8

SECTION 2. BACKGROUND OF REGION...... 18

SECTION 3. EVALUATION OF LARGE URBAN CENTERS AND SURROUNDING AREAS--

HOUSTON AND GALVESTON...... 36

SECTION 4. GOLDEN TRIANGLE AND SURROUNDING COMMUNITIES...... 68

SECTION 5. LOWER RIO GRANDE VALLEY...... 99

SECTION 6. EVALUATION OF SMALL COMMUNITIES—DEEP EAST TEXAS COUNCIL OF

GOVERNMENTS ...... 127

SECTION 7. FAIR HOUSING COMPLAINTS AND SURVEY OF FAIR HOUSING

COMPLAINT PROCEDURES IN THE TEXAS DISASTER RELIEF AREA...... 157

SECTION 8. COMPENDIUM OF IMPEDIMENTS AND POSSIBLE ACTIONS...... 162

APPENDICES APPENDIX A - EXECUTED AND APPROVED CONCILIATION AGREEMENT APPENDIX B -COUNTY MAPS OF SECTION 8 HOUSING AS HELD BY HUD APPENDIX C - FAIR HOUSING FILINGS FROM TEXAS WOKFORCE COMMISSION AND REGION 6 HUD APPENDIX D - DEMOGRAPHIC DATA FROM 2000 AND 1990 CENSUS APPENDIX F - LIST OF PROJECTS AND PROGRAMS BY JURISDICTION 2005 TO PRESENT APPENDIX G - INTERVIEWS/FOCUS GROUPS CONDUCTED BY SOUTHWEST FAIR HOUSING COUNCIL APPENDIX H - SUPPORTING DATA FOR HOME MORTGAGE DISCLOSURE ACT ANALYSIS

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INDEX OF TABLES, GRAPHS, CHARTS, ETC.

TABLE 2-1 PROJECTED POPULATION STATE OF TEXAS ...... 18 TABLE 2.2 AGE BY AGE GROUP AND RACE/ETHNICITY ...... 19 TABLE 2.3 ANNUAL POVERTY ESTIMATES BY RACE AND LATINO ORIGIN – TEXAS, 2006 TO 2008 ...... 21 TABLE 2-5 PERSONS WITH DISABILITIES – TEXAS, 2000 ...... 24 TABLE 2-6 PHA UNITS – TEXAS, 2010 ...... 25 TABLE 2-7 PERSONS WITH HIV/AIDS – TEXAS, 2008 ...... 27 TABLE 2-8 COLONIA RESIDENTS – TEXAS, ESTIMATED 2010 ...... 28 TABLE 2-9 MIGRANT SEASONAL FARMWORKER POPULATION ESTIMATES – TEXAS, 2000 ...... 29 TABLE 2-10 HOUSEHOLDS WITH ONE OR MORE HOUSING NEEDS - TEXAS, 2009 ...... 30 FIGURE 2-1 NUMBER OF UNITS LACKING KITCHEN AND/OR PLUMBING BY AFFORDABILITY CATEGORY – TEXAS, 2009 ...... 31 FIGURE 2-2 RENTER HOUSEHOLDS WITH SUBSTANDARD HOUSING BY PERCENT – TEXAS, 2009 ...... 32 FIGURE 2-3 OWNER HOUSEHOLDS WITH SUBSTANDARD HOUSING PERCENT – TEXAS, 2009 ...... 32 FIGURE 2-4 RENTER HOUSEHOLDS WITH EXTREME HOUSING COST BURDEN (>30% OF INCOME) BY PERCENT – TEXAS, 2009 ...... 33 FIGURE 2-5 OWNER HOUSEHOLDS WITH EXCESS HOUSING COST BURDEN (>30% OF INCOME) BY PERCENT – TEXAS 2009 ...... 33 FIGURE 2-6EXCESS HOUSING COST BURDEN BY INCOME GROUP – TEXAS, 2009 ...... 34 FIGURE 2-7 ...... 34 RENTER HOUSEHOLDS WITH INCIDENCE OF OVERCROWDING BY PERCENT – TEXAS, 2009 ...... 34 FIGURE 2-8OWNER HOUSEHOLDS WITH INCIDENCE OF OVERCROWDING BY PERCENT...... 35 FIGURE 2-9OVERCROWDED HOUSEHOLDS BY INCOME GROUP – TEXAS, 2009 ...... 35 TABLE 3-1PROJECTED POPULATION H-GAC REGION ...... 39 TABLE 3-2AGE BY AGE GROUP AND RACE/ETHNICITY ...... 40 REGION 6 POVERTY FIGURES, 2010 ...... 40 REGION 6 HOUSEHOLD INCOME ...... 41 TABLE 3-3 INCOME LEVELS FOR REGION 6 AS COMPARED TO STATE AS A WHOLE ...... 41 TABLE 3-4 H-GAC HOMELESS, 2010 ...... 42 TABLE 3-5REGION 6 PERSONS WITH, WITHOUT DISABILITIES, 2000 ...... 43 TABLE 3-6 PUBLIC HOUSING UNITS IN REGION 6 ...... 44

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TABLE 3-7 H-GAC PUBLIC ASSISTANCE REQUEST INVENTORY, SFY 2010 ...... 44 TABLE 3-8 H-GAC PERSONS LIVING WITH HIV/AIDS, 2008 ...... 45 TABLE 3-9 H-GAC MIGRANT AND SEASONAL FARMWORKER POPULATION, 2000 ...... 45 TABLE 3-10 REGION 6 HOUSING SUPPLY, 2010 ...... 46 TABLE 3-11 H-GAC HOUSEHOLDS WITH HOUSING PROBLEMS, 2009 ...... 47 CHART 3-1A – DERIVED FROM DATA IN TABLE 1A ...... 50 CHART 3-2A – DERIVED FROM DATA IN TABLE 2A ...... 50 CHART 3-3A – DERIVED FROM DATA IN TABLE 3A ...... 51 CHART 3-1B – DERIVED FROM DATA IN TABLE 1B ...... 52 CHART 3- 2B – DERIVED FROM DATA IN TABLE 2B ...... 52 CHART 3-3B – DERIVED FROM DATA IN TABLE 3B ...... 53 CHART 3-1C – DERIVED FROM DATA IN TABLE 1C ...... 53 CHART 3-2C – DERIVED FROM DATA IN TABLE 2C ...... 54 CHART 3C – DERIVED FROM DATA IN TABLE 3C ...... 54 CHART 3.1.1A – DERIVED FROM DATA IN CHART 1A ...... 56 CHART 3-1.2A – DERIVED FROM DATA IN TABLE 2A ...... 57 CHART 3-3.3A – DERIVED FROM DATA IN TABLE 3A ...... 57 CHART 3-1.1B – DERIVED FROM DATA IN TABLE 1B ...... 58 CHART 3-1.2B – DERIVED FROM DATA IN TABLE 2B ...... 58 CHART 3-1.3B – DERIVED FROM DATA IN TABLE 3B ...... 58 CHART 3-1.1C – DERIVED FROM DATA IN TABLE 1C ...... 59 CHART 3-1.2C – DERIVED FROM DATA IN TABLE 2C ...... 59 CHART 3-1.3C – DERIVED FROM DATA IN TABLE 3C ...... 60 TABLE 4-1 PROJECTED POPULATION SETRPC REGION ...... 72 TABLE 4-2 AGE BY AGE GROUP AND RACE/ETHNICITY...... 73 TABLE 4-3 SETRPC POVERTY FIGURES, 2010 ...... 73 REGION 5 HOUSEHOLD INCOMES...... 73 TABLE 4-4 SETRPC HOUSEHOLD INCOME ...... 74 TABLE 4-5 REGION 5 PERSONS IN OTHER GROUP QUARTERS, 2010 ...... 74 TABLE 4-6 SETRPC PERSONS WITH DISABILITIES 2000 ...... 75 TABLE 4-7 REGION 5 PERSONS WITH HIV/AIDS, 2008 ...... 75 TABLE 4-8 SETRPC/GOLDEN TRIANGLE MIGRANT AND SEASONAL FARMWORKER POPULATION, 2000 ...... 75 TABLE 4-9 SETRPC/GOLDEN TRIANGLE PUBLIC ASSISTANCE REQUEST INVENTORY, SFY 2010 ...... 76 TABLE 4-10 REGION 5 HOUSING SUPPLY, 2010 ...... 77 TABLE 4-11 SETRPC/GOLDEN TRIANGLE HOUSEHOLDS WITH HOUSING PROBLEMS, 2009 ...... 77 CHART 4-1A – DERIVED FROM DATA IN TABLE 1A ...... 80 CHART 4-2A – DERIVED FROM DATA IN TABLE 2A ...... 80

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CHART 3A – DERIVED FROM DATA IN TABLE 3A ...... 81 CHART 4-1B – DERIVED FROM DATA IN TABLE 1B ...... 82 CHART 4-2B – DERIVED FROM DATA IN TABLE 2B ...... 82 CHART 4-3B – DERIVED FROM DATA IN TABLE 3B ...... 83 CHART 4-1C – DERIVED FROM DATA IN TABLE 1C ...... 83 CHART 4-2C – DERIVED FROM DATA IN TABLE 2C ...... 84 CHART 4-3C – DERIVED FROM DATA IN TABLE 3C ...... 84 CHART 4-1.1A – DERIVED FROM DATA IN TABLE1A ...... 86 CHART 4-1.2A – DERIVED FROM DATA IN TABLE 2A ...... 87 CHART 4-1.3A – DERIVED FROM DATA IN TABLE 3A ...... 87 CHART 4-1.1B – DERIVED FROM DATA IN TABLE 1B ...... 88 CHART 4-1.2B – DERIVED FROM DATA IN TABLE 2B ...... 89 CHART 4-1.3B – DERIVED FROM DATA IN TABLE 3B ...... 89 CHART 4-1.1C – DERIVED FROM DATA IN TABLE 1C ...... 90 CHART 4-1.2C – DERIVED FROM DATA IN TABLE 2C ...... 90 CHART 4-1.3C – DERIVED FROM DATA IN TABLE 3C ...... 91 TABLE 4-12 LOT SIZES IN SETRPC ...... 95 TABLE 4-13 MINIMUM SQUARE FOOTAGE REQUIREMENTS OVER 1000 SQ FEET ...... 96 TABLE 5-1 PROJECTED POPULATION LRGVDC REGION ...... 101 TABLE 5-2 AGE BY AGE GROUP AND ETHNICITY ...... 102 TABLE 5-3 LRGV POVERTY FIGURES, 2010 ...... 102 TABLE 5-4 LRGVDC PERSONS IN OTHER GROUP QUARTERS, 2010 ...... 104 TALE 5-5 PERSONS WITH DISABILITIES ...... 104 TABLE 5-6 REGION 11 PERSONS LIVING WITH HIV/AIDS, 2008 ...... 104 TABLE 5-7 LRGV COLONIA POPULATION, ESTIMATED 2010 ...... 105 TABLE 5-8 MIGRANT AND SEASONAL FARMWORKER POPULATION, 2000 ...... 105 TABLE 5-9 REGION 11 PUBLIC ASSISTANCE REQUEST INVENTORY, SFY 2010 ...... 106 TABLE 5-10 NUMBER OF UNITS LACKING KITCHEN AND/OR PLUMBING BY AFFORDABILITY CATEGORY – LRGV, 2005-2007 ...... 107 BAR GRAPH 5-1 RENTER HOUSEHOLDS WITH SUBSTANDARD HOUSING BY INCOME CATEGORY – TEXAS, 2005-2007 ...... 107 BAR GRAPH 5-2 OWNER HOUSEHOLDS WITH SUBSTANDARD HOUSING BY INCOME CATEGORY – TEXAS, 2005-2007 ...... 108 BAR GRAPH 5-3 RENTER HOUSEHOLDS WITH HOUSING COST BURDEN BY INCOME CATEGORY – TEXAS, 2005-2007 ...... 108 BAR GRAPH 5-4 RENTER HOUSEHOLDS WITH HOUSING COST BURDEN BY INCOME CATEGORY – TEXAS, 2005-2007 ...... 109 TABLE 5-11 LRGVDC HOUSEHOLDS WITH A COST BURDEN >30% ...... 109 BAR GRAPH 5-5 RENTER HOUSEHOLDS WITH INCIDENCE OF OVERCROWDING BY INCOME GROUP – TEXAS, 2005-2007 ...... 110

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BAR GRAPH 5-6 OWNER HOUSEHOLDS WITH INCIDENCE OF OVERCROWDING BY INCOME GROUP – TEXAS, 2005-2007 ...... 110 TABLE 5-12 LRGVDC HOUSEHOLDS THAT ARE OVERCROWDED ...... 111 CHART 5-1A – DERIVED FROM DATA IN TABLE 1A ...... 113 CHART 5-2A – DERIVED FROM DATA IN TABLE 2A ...... 113 CHART 5-3A – DERIVED FROM DATA IN TABLE 3A ...... 114 CHART 5-1B – DERIVED FROM DATA IN TABLE 1B ...... 115 CHART 5-2B – DERIVED FROM DATA IN TABLE 2B ...... 115 CHART 5-3B – DERIVED FROM DATA IN TABLE 3B ...... 116 CHART 5-1C – DERIVED FROM DATA IN TABLE 1C ...... 116 CHART 5-2C – DERIVED FROM DATA IN TABLE 2C ...... 117 CHART 5-3C – DERIVED FROM DATA IN TABLE 3C ...... 117 CHART 5-1.1A – DERIVED FROM DATA IN TABLE 1A ...... 119 FHA CHART 5-1.2A – DERIVED FROM DATA IN TABLE 2A ...... 119 FHA CHART 5-1.3A – DERIVED FROM DATA IN TABLE 3A ...... 120 CHART 5-1.1B – DERIVED FROM DATA IN TABLE 1B ...... 121 CHART 5-1.2B – DERIVED FROM DATA IN TABLE 2B ...... 121 CHART 5-1.3B – DERIVED FROM DATA IN TABLE 3B ...... 121 CHART 5-1.1C – DERIVED FROM DATA IN TABLE 1C ...... 122 CHART 5-1.2C – DERIVED FROM DATA IN TABLE 2C ...... 122 CHART 5-1.3C – DERIVED FROM DATA IN TABLE 3C ...... 123 TABLE 6-1 PROJECTED POPULATION DETCOG REGION ...... 130 TABLE 6-2 PROJECTED POPULATION ANDERSON COUNTY ...... 130 TABLE 6-3 PROJECTED POPULATION CASS COUNTY ...... 130 TABLE 6-4 PROJECTED POPULATION CHEROKEE COUNTY ...... 130 TABLE 6-5 PROJECTED POPULATION GRIMES COUNTY ...... 130 TABLE 6-6 PROJECTED POPULATION HARRISON COUNTY ...... 131 TABLE 6-7 PROJECTED POPULATION LEON COUNTY ...... 131 TABLE 6-8 PROJECTED POPULATION MADISON COUNTY ...... 131 TABLE 6-9 PROJECTED POPULATION MARION COUNTY ...... 131 TABLE 6-10 PROJECTED POPULATION MILAM COUNTY ...... 131 TABLE 6-11 PROJECTED POPULATION MORRIS COUNTY ...... 132 TABLE 6-12 PROJECTED POPULATION PANOLA COUNTY ...... 132 TABLE 6-13 PROJECTED POPULATION ROBERTSON COUNTY ...... 132 TABLE 6-14 PROJECTED POPULATION RUSK COUNTY...... 132 TABLE 6-15 PROJECTED POPULATION WASHINGTON COUNTY ...... 132 TABLE 6-16 AGE BY AGE GROUP AND ETHNICITY ...... 133 REGION 5 HOUSEHOLD INCOMES...... 133 TABLE 6-17 REGION 5 POVERTY FIGURES, 2010 ...... 133

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TABLE 6-18 REGION 5 PERSONS IN OTHER GROUP QUARTERS, 2010 ...... 134 TABLE 6-19 BY COUNTY PERSONS IN OTHER GROUP QUARTERS, 2010 ...... 134 TABLE 6-20 REGION 5 PERSONS WITH AND WITHOUT DISABILITIES, 2000 ...... 135 TABLE 6-21 BY COUNTY PERSON WITH DISABILITIES ...... 135 TABLE 6-22 REGION 5 PERSONS WITH HIV/AIDS, 2008 ...... 136 TABLE 6-23 REGION 5 MIGRANT AND SEASONAL FARMWORKER POPULATION, 2000 ...... 137 TABLE 6-24 BY COUNTY MIGRANT AND SEASONAL FARMWORKER POPULATION, 2000 ...... 137 TABLE 6-25 EAST TEXAS IMPACTED AREAS PUBLIC ASSISTANCE REQUEST INVENTORY, SFY 2010 ...... 138 TABLE 6-26 REGION 4 HOUSING SUPPLY, 2010 ...... 139 TABLE 6-27 REGION 4 HOUSEHOLDS WITH HOUSING PROBLEMS, 2009 ...... 139 TABLE 6-28 REGION 5 HOUSING SUPPLY, 2010 ...... 140 TABLE 6-29 REGION 5 HOUSEHOLDS WITH HOUSING PROBLEMS, 2009 ...... 141 TABLE 6-30 REGION 8 HOUSING SUPPLY, 2010 ...... 141 TABLE 6-31 REGION 8 HOUSEHOLDS WITH HOUSING PROBLEMS, 2009 ...... 142 CHART 6-1A – DERIVED FROM DATA IN TABLE 1A ...... 143 CHART 6-2A - APPENDIX H 2A – DERIVED FROM DATA IN TABLE 2A ...... 144 CHART 6-3A – DERIVED FROM DATA IN TABLE 3A ...... 144 CHART 6-1B – DERIVED FROM DATA IN TABLE 1B ...... 145 CHART 6-2B – DERIVED FROM DATA IN TABLE 2B ...... 146 CHART 6-3B – DERIVED FROM DATA IN TABLE 3B ...... 146 CHART 6-1C – DERIVED FROM DATA IN TABLE 1C ...... 147 CHART 6-2C – DERIVED FROM DATA IN TABLE 2C ...... 147 CHART 6-3C – DERIVED FROM DATA IN TABLE 3C ...... 148 CHART 6-1.1A – DERIVED FROM DATA IN TABLE 1A ...... 149 CHART 6-1.2A – DERIVED FROM DATA IN TABLE 2A ...... 150 CHART 6-1.3A – DERIVED FROM DATA IN TABLE 3A ...... 150 CHART 6-1.1B – DERIVED FROM DATA IN TABLE 1B ...... 151 CHART 6-1.2B – DERIVED FROM DATA IN TABLE 2B ...... 151 CHART 6-1.3B – DERIVED FROM DATA IN TABLE 3B ...... 151 CHART 6-1.1C – DERIVED FROM DATA IN TABLE 1C ...... 152 CHART 6-1.2C – DERIVED FROM DATA IN TABLE 2C ...... 152 CHART 6-1.3C – DERIVED FROM DATA IN TABLE 3C ...... 153 TABLE 7-1 TWC COMPLAINTS ...... 160

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SECTION 1. PURPOSE OF PHASE 1, ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING, AND EXECUTIVE SUMMARY.

EXECUTIVE SUMMARY.

This Phase I Analysis of Impediments to Fair Housing directly pertains to the $1.6 billion in the second round of Community Development Block Grant funding allocated to the State of Texas by the U.S. Department of Housing and Urban Development (HUD) to assist citizens and communities to recover from the devastation of Hurricanes Dolly and Ike, both of which heavily impacted the Texas Coast during 2008. The Phase I Analysis of Impediments is the result of two important factors: a greatly heightened emphasis by HUD on compliance with federal requirements to Affirmatively Further Fair Housing; and a fair housing complaint to HUD filed by two housing advocacy groups against the State of Texas. The fair housing complaint resulted in a HUD-approved, legally binding conciliation agreement between the State and the complainants.

Nothing in this document constitutes a legal finding that the State or any of its jurisdictions has violated or is in violation of any federal laws. Nor is anything in this document intended to set forth a requirement or standard on which any allegation of a future violation may be based. The State’s plan to pursue specific action steps as described in this document presumes continued federal and state appropriations authority to conduct such activities. Where changes in state law or increased funding are necessary to carry out recommendations, the parties to this document acknowledge that is the ultimate decision of the Texas Legislature whether to enact laws and appropriate funds.

This document also contains numerous recommendations for increased training of locally elected officials and their staffs. The State recognizes and respects the autonomy of independently elected officials and acknowledges there are limitations on its ability to direct independent, locally elected officials to take certain actions. Nothing herein is intended to relieve the State of any of its obligations to comply with federal housing laws and the Conciliation Agreement, entered into May 25, 2010. These obligations will

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 8 of 196 continue to be met by the designated state agencies, TDHCA and TDRA, or any successor agencies designated by the Legislature.

One of the primary items included in the conciliation agreement (included as Appendix A) is that the State will complete a Phase I Analysis of Impediments to Fair Housing for the areas within the Dolly and Ike impacted areas and submit the Phase I Analysis of Impediments to HUD for review by January 1, 2011.

The Phase I AI is intended to be a tool used by state agencies, and recipients and subrecipients of CDBG disaster recovery funds to promote the State’s goal that infrastructure, housing and economic development projects affirmatively further fair housing within the impacted communities, as required by federal law.

The Phase I AI identifies 16 impediments to fair housing and includes individual recommended actions that recipients and subrecipients of funding should consider as they allocate funding and prepare applications for projects that will be funded by the remainder of round 2 funds. The impediments fall into four basic categories: education, training, planning, and enforcement. Some impediments pertain to activities to be conducted by the State. Others pertain to local governments. Not all impediments or recommended actions pertain to any single entity. Specific impediments and recommendations are presented in Section 8.

The State completed the Phase I AI under a very demanding schedule using a variety of resources – from specialized consultants and demographers to input from citizens, local governments and advocacy groups. The Phase I AI also underwent substantial discussion and review by an AI Committee (as required in the conciliation agreement). The AI Committee included representation by the complainants, the Texas Department of Housing and Community Affairs (“TDHCA”), Texas Department of Rural Affairs (“TDRA”), Association of Rural Communities In Texas (“ARC”), and the four councils of government most impacted by Dolly and Ike (i.e., Deep East Texas Council of Governments, Houston-Galveston Area Council, Lower Rio Grande Valley Regional Development Council, and the South East Regional Planning Commission).

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Purpose of the Phase 1 Analysis of Impediments.

It is almost impossible to describe a typical Texas community, much less identify all of its characteristics, its citizens and its challenges in a single document and we do not attempt to do so in this, Phase 1 of the state’s Analysis to Impediments to Fair Housing (AI). In section eight of this AI titled Compendium of Impediments and Possible Solutions, the state has identified several actions to help build a greater understanding of the Fair Housing Act and specifically to affirmatively further fair housing. That section also identifies impediments and action steps to provide guidance on issues to address in a community’s individual analysis of impediments to fair housing and as it seeks to affirmatively further fair housing.

In examining impediments to Fair Housing for members of protected classes under the Fair Housing Act1 – race, color, religion, national origin, sex, disability, and familial status - in this AI, we will also look at current federal and state complaints that allege any direct violations of the Fair Housing Act for root causes caused by public policies or by practices in the private market place whether intentional or unintentional that may limit fair housing choices for all Texans.

As a result of heightened emphasis on fair housing by HUD and the conciliation agreement, the approach of this AI is different than previous versions presented by the State. It reflects a change in what constitutes a comprehensive review of fair housing in communities. This AI seeks to provide foundational research information regarding racial housing patterns and to provide guidance to assist a community in analyzing what it means to affirmatively further fair housing in their community in both housing and infrastructure projects.

A Fair Housing Complaint Against the State of Texas.

In 2008, HUD accepted a fair housing complaint filed by Texas housing advocates raising issues about Texas’ ability to certify that it considered affirmatively furthering fair housing with disaster recovery funds.2 HUD sent Texas a “Request for Response” to the issues raised in the complaint and indicated that after the response was received, they would conduct an investigation if necessary. Among the points raised in the complaint was that the State, and

1 42 USC §3601 2 Case No. 06-1—0410-8 (Title VII) and Case No. 06-10-0410-9 (§109)

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 10 of 196 several potential local sub-recipients of the disaster funding, had inadequate or outdated AI’s with which to certify that the state was affirmatively furthering fair housing.

Development of a Conciliation Agreement.

HUD informed the state that absent reaching a conciliation agreement with the housing advocates, HUD would immediately launch an investigation in Texas, much as it did with Westchester County, N.Y., and halt all CDBG funding in the state, including disaster recovery funding. Rather than delay the funds for the length of a pending investigation, the State moved toward a Conciliation Agreement3 with the Complainants to ensure Texas had access to more than $3.1 billion in disaster recovery funds. The Conciliation Agreement is included as Appendix A.

An Overview of the Phase I AI Process.

To meet the concerns raised in the complaint the parties agreed to develop the state’s updated AI in two Phases. Phase 1 will focus on areas of the state that are receiving the majority of disaster funding awarded to Texas by Congress.4 Phase 2 will address the balance of the state.

In preparing the AI under these unusual circumstances, the state had to look at combining elements of both a traditional statewide AI with selective elements of a local AI to help provide guidance to the cities and counties receiving disaster funds. In reality, the ability to take on this task in roughly 120 days and cover each community was not possible using a traditional method. In the Conciliation Agreement, TDHCA agreed to appoint a committee to work with the state.5 The Committee, in an effort to make the AI document more user friendly, determined that in many cases, communities fell into four groups that were similar in nature. These groups are represented in Sections three through six of this document, and include:

Section 3. Evaluation of Large Urban Centers and Surrounding Areas—Houston and Galveston.

Section 4. Golden Triangle and Surrounding Communities.

3 Attached as Addendum A 4 Public Law 110-329. 5 The Committee was made up of two representatives from the housing advocacy community, two members from Texas Department of Rural Affairs, two members from TDHCA, one representative of rural communities, and one representative from each of the four non-pool COGs.

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Section 5. Lower Rio Grande Valley.

Section 6. Evaluation of Small Communities—Deep East Texas Council of Governments.

With that distinction, information could be gathered that might not address each issue in every community, but represent a fairly comprehensive set of circumstances that would provide direction to similar size and resourced cities as to what to consider in reviewing their commitment to affirmatively further fair housing.

In order to complete the work in a timely fashion, the state determined that a collaborative approach would be necessary and contracted with the Southwest Fair Housing Council (SWFHC) in Tucson, Arizona selected from a list of recommended consultants, as the primary contractor to develop the AI. SWFHC conducted interviews, held focus groups and gathered data on allegations of individual acts of discrimination for the report as well as coordinating additional efforts and supervising subcontractors. SWFHC contracted with National Community Reinvestment Coalition to conduct a portfolio and market share analysis using 2008 Home Mortgage Disclosure Act data and the HOPE Fair Housing Center for information regarding complaints. Rice University and Dr. Steve Murdock (a former census bureau director and former state chief demographer) were retained to help provide the demographic and community housing patterns for the document. TDHCA staff were also involved in the research and drafting process.

The AI as drafted has foundational information regarding the members of protected classes, residential patterns, and use of public funds to be used as resources for the public or a community planning staff to assist in their own reviews regarding affirmatively furthering fair housing.

Appendix C provides a table of individual fair housing complaints made to HUD identified by type and outcomes by county. Appendix D contains tables using 1990 and 2000 census information that break out the demographic data—including racial segregation patterns in neighborhood groups—for communities over 10,000 in population. Presented with this are visual representations of the concentration of minorities and poverty in the communities by neighborhood groups. Also included in Appendix D is a representative sample of smaller communities (those having more than one census tract for comparisons) to demonstrate the racial concentrations in smaller communities.

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Communities in the hurricane impacted area have provided their funding patterns for the past seven years as Appendix F in this document. This provides information on the way other communities with similar populations and funding use their public funds in both infrastructure and housing programs.

Appendix H provides a resource for the Home Mortgage Disclosure Act tables used to develop the section on mortgage lending trends related to race. The mortgage information does take into account similar income patterns, but does not conduct a cross- analysis for all reasons why loans were denied. Appendix B provides a map of the location of subsidized housing and Housing Choice Voucher holders in the relevant jurisdictions.

Relevance of the Phase I AI.

In developing this Analysis of Impediments to Fair Housing (AI), the State of Texas has worked closely with representatives from the communities impacted by Hurricanes Ike and Dolly, persons representing fair housing, and civil rights advocacy groups. The public was also invited to provide input through surveys, focus groups, and public comment periods.

The State of Texas is anticipated to continue its population growth and to move toward a different ethnic make-up with Hispanics increasing as a percentage of the population in a steady growth rate. Although not all portions of the hurricane impacted areas will see growth, the population will change. The state’s and the impacted region’s population is also aging, with a greater need to provide support as the number of persons who are 65 and older increases. As such, accessibility and the availability of affordable housing could be even more in demand in the future.

Texas is a diverse culture and faces many challenges. The challenges include the size of Texas and its growing population and the demands placed on the state as a result. The Texas labor force at 12 million is second only to the California’s labor force of 18 million. Texas ranks as the number one state for Projected Job Growth from 2009 to 2019.6 In addition to the increasing population within, Texas remains the number one relocation destination in the U.S. for the fifth year in a row based on Allied Van Lines’ 42nd Annual Magnet Report, which tracks U.S.

6 Time Magazine, May 25, 2009.

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 13 of 196 migration patterns.7 Part of the reason for the migration is that, according to the Missouri Economic Research & Information Center, Texas ranks fifth in the nation for lowest cost-of- living.8

Still, despite it cost of living and projected job growth, the AI has identified that hurricane impacted communities, and the state as a whole, have groups that need special consideration to fully integrate these communities and make fair housing choice a reality. In addition to protected classes under the Fair Housing Act, the AI specifically identifies homeless populations, colonias communities, migratory farm workers, persons with special needs, persons with HIV/AIDS, and the incidences of poverty in communities, as well as the barriers that exist to providing these populations with access to housing.

The report identifies limitations on the availability of safe, quality, affordable housing, especially in high opportunity areas, as defined by future rules. The report also identifies challenges due to substandard housing with incomplete plumbing, overcrowding and cost burdens that limit fair housing choices for persons of limited means.

Several impediments are identified that are consistent by region, as well as some that are localized into certain regions or only parts of a region. Below is a quick summary of the identified impediments and the action steps identified to help overcome the impediment. For a full list, please review Section 8 of this AI.

HMDA research shows that, in general, minorities tend to receive fewer loans, or receive less favorable terms, as a percentage of the population than non-Hispanic whites. The analysis does not look at all factors that go into a loan, such as credit history, but it does try to compare similar levels of income. Several action steps were identified to assist in creating better access, including seeking additional education for mortgage professionals, TDHCA adding into its First time Homebuyer Programs affirmatively furthering fair housing training, and additional monitoring of that program to determine if the racial percentages correspond to the racial make- up of the market place. The HMDA research, however, does not address the impact of federal mandates on lending institutions that led to risky, sub-prime loans that placed persons in homes

7 SIRVA, Inc., Jan. 2010 8 http://www.missourieconomy.org/indicators/cost_of_living/index.stm

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 14 of 196 they could not afford and eventually helped precipitate the collapse of the housing industry – and the impact that has had on financing and construction of affordable housing.

In addition, while not a clear representative sample, allegations of discriminatory acts were identified in the focus groups regarding the rental and sale markets. National research by civil rights advocates has indicated that, in some communities, there is a practice of steering persons of color into communities populated by persons of the same race. No surveys or testing were conducted in Texas specifically for this AI, but based on racial patterns and the prevalence found in other testing, Texas proposes to look at testing and enforcement provisions coordinated and paid for by TDHCA. In addition, the AI proposes that TDHCA and TDRA will request more training for real estate related professionals about affirmatively furthering fair housing in real estate transactions. TDHCA proposes to monitor its programs for compliance and consistency, and to place more emphasis on subrecipients in developing affirmative marketing plans.

TDHCA proposes to work with the Texas Workforce Commission, which is the Fair Housing enforcement agency in Texas, to better educate the public on Fair Housing issues and how to report claims of violations. The state intends to work collectively to build coalitions and promote programs that provide a greater awareness of the Fair Housing Act.

The report identifies the Not In My Back Yard (“NIMBY”) syndrome as a potential impediment to locating multi-family housing in high opportunity areas. Through coalitions and education, the actions steps identify ways to lessen the impact of NIMBYism including education of leadership in communities.

In the public sector, the AI identifies some areas where public policy, either intentionally or unintentionally, may have promoted racial segregation. The section identifies 20 action steps that involve the review of public policies, commitments to rebuild, and how to make forward- looking funding decisions after careful review of current on-the-ground situations.

As was previously stated, not much in the way of testing or enforcement of Fair Housing issues has gone on in Texas by any level of government. The AI proposes to increase testing and enforcement where appropriate. Further, it proposes that the state and local governments will work to increase awareness of the Fair Housing claim process through additional literature or placement of a contact about Fair Housing issues on its website.

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Another area called for in AI’s and represented in this document is an examination of local land use or zoning requirements. While not every jurisdiction’s ordinances have been reviewed, in Section 4 we walk through some of the more common issues that may limit fair housing choice and identify action steps to encourage a review of local ordinances that may impact those choices.

An ongoing concern directly related to the impacted areas is the ability of the federal, state and local governments to re-house persons after a disaster. While this impediment cuts across the board, it can be especially hard on persons with special needs or those living in poverty. The action steps encourage a more complete review—including duplication of benefits issues—to assist people in relocating quickly.

Potential barriers to those with special needs are included in this report. With the population aging, this could become a greater concern. The action steps include proposals for removing barriers, locating sites and removing public barriers and altering private attitudes to locating special needs housing in communities where it has the greatest access.

The lack of resources available to: increase housing, provide more access, and despite Texas leading in job growth, create jobs is also identified as an impediment in this AI. Using these limited resources more efficiently and targeting the resources should be done. In addition, developing a comprehensive Section 3 plan could provide more jobs and allow for movement of low-income persons.

Texas has dedicated significant resources to working with the issue of Colonias in Texas. However, there is still work which needs to be done. The AI identifies potential impediments of directing people due to national origin and recommends looking at creating a greater awareness of the issues in the areas that remain under served or un-served.

As a result of looking at storm damage, the state is aware of insurance patterns and the high cost of insurance to homeowners in the most impacted areas. The state plans to include training in its homebuyer programs that will counsel applicants on the importance of shopping for and maintaining insurance.

With this AI, the state is moving to improve the information gathered and analyzed in the pursuit of affirmatively furthering fair housing in conjunction with current national trends in drafting of

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 16 of 196

AIs being discussed by HUD. The state and local communities plan for increased training and looking at information in a manner that encourages informed decisions going forward.

In conclusion, the state and the local jurisdictions have identified major steps to providing a path that will help bring greater awareness about the Fair Housing Act to the public in decision making processes.

Next Steps.

The draft Phase I AI will be submitted first to the public for comment and then to the TDHCA Board for approval prior to submission to HUD. Once the Phase I AI is accepted by HUD, the State will begin the process of working with the Councils of Government to develop regional methods of distribution to support allocation and release of remaining round 2 funding.

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 17 of 196

SECTION 2. BACKGROUND OF REGION.

Demographics.

Population Growth.

Texas is experiencing incredible growth, adding approximately 3,111,480 people between 2002 and 2008. In fact, Texas has grown much faster than the national average, a difference of 14.6percent to 8.3percent respectively.9 Accompanying this growth in population, traditional population characteristics are also changing. The Non Hispanic White population is anticipated to decrease in both raw numbers and as a percentage of the population by 2040.10 Depending on the selected migration formula, the percentage of the population that is black is expected to decrease in the future when looking at the Zero Net Migration formula remaining relatively flat in raw numbers.11 If a different model is used, the percentages will still decline based on other groups’ projected growth, but the raw number of persons grows. The “other” classification remains relatively stable under the Zero Net Formula but more than doubles in population under the 0.5 formula. Under any model, both as a raw number and as a percentage of the population, the Hispanic group is expected to grow dramatically to where Hispanics will be the largest classification in 2040 representing approximately 52percent of the population under the Net Migration of 0.5percent formula.12

Table 2-1 Projected Population State of Texas Year Non Black Hispanic Other Total Hispanic White 2000 11,074,716 2,604.162 6,669,666 685,785 20,581,820 Year Non Non Black Black Hispanic Hispanic Other 0ther Total Total Hispanic Hispanic 0.0 0.5 0.0 0.5 Scenario 0.0 0.5 Scenario 0.0 Scenario 0.5 White White Scenario Scenario Scenario Scenari Scenario 0.0 0.5 o scenario Scenario 2010 11,292,858 11,494,673 2,604,162 2,730,659 7,986,640 8,999,827 776,088 953,348 22,659,748 24,178,507

2020 11,320,857 11,735,043 2,727,365 3,004,173 9,220,971 11,742,820 828,786 1,256,342 24,097,979 27,738,378

2040 10,559,190 11,382,992 2,697,888 3,282,413 11,408,456 18,391,333 856,047 1,854,592 25,561,581 35,012,330

9 U.S. Census Bureau, 2002, 2008 Community Survey 10 Table 2.7 Population for the State of Texas and Councils of Government Regions in Texas in 200 and Projections to 2040 Assuming Alternative Population Scenarios, retrieved at http://txsdc.utsa.edu/pubsrep/ 11 Ibid. 12 Ibid.

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 18 of 196

Additional information regarding population sizes, including growth by race, will be covered in each of the sections that deal with specific communities or areas. In addition, the materials contained in Appendix D will provide more direct population figures for all 63 impacted counties and selected communities. The information in Appendix D will analyze the growth factor in population and race from 1990 to 2000. A subsequent report will provide the additional data from the 2010 U.S. Census that is unavailable at the time of this report. It is anticipated that 2010 information should be ready not later than March of 2011.

Age.

Included in the changing demographics is the aging of the population in Texas. Under all migration scenarios, the median age of the population will increase across the board as will the corresponding percentage of the population that is 65 and older in all race categories. This aging of the population has significant impacts on the availability of housing and resources that can accommodate special needs persons.

Table 2.2 shows the population’s anticipated aging according to the demographers located at the University of Texas at San Antonio. This table demonstrates that the percentage of the population who is over sixty five will increase in raw numbers within the age category and as a percentage of the population as a whole.13 The 2040 data assumes rates of net migration equal to one-half of 1990-2000 (.5 Scenario) and is neither the least nor the most conservative estimate by the demographers.

Table 2.2 Age by Age Group and Race/Ethnicity Age Non Non Black Black Hispanic Hispanic Other Other Total Total Group Hispanic Hispanic 2000 2040 2000 2040 2000 2040 2000 2040 White White 2000 2040 <18 23.0 17.2 31.7 19.8 35.8 26.0 26.1 15.5 28.2 22.0 18-24 8.8 7.6 11.2 9.2 13.2 10.1 11.2 6.5 10.6 9.0 25-44 30.1 23.9 32.1 27.6 31.8 29.4 37.7 24.2 31.1 27.1 45-64 24.4 25.4 17.7 26.8 14.0 22.3 20.1 25.5 20.2 23.9 65+ 13.7 25.9 7.3 16.6 5.2 12.2 4.9 28.3 9.9 18.00 Median 38.0 46.0 29.6 40.4 25.5 34.2 31.1 47.9 32.3 38.8

13 Table 2.14 Percentage of population for the State of Texas and Council of Government Regions in Texas by Age and Race/Ethnicity of the Population and Median Age by Race/Ethnicity in 2000 and Projections to 2040 Assuming Alternative Projection Scenarios. http://txsdc.utsa.edu/pubsrep/

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 19 of 196

Aging populations place different pressures on infrastructure and housing. One indicator of increased need is that the 2005 to 2007 American Community Survey found that 45.3 percent of the population 65 years and older had a disability during this time period.14 Additionally, the Aging Texas Well Indicators Survey Report for 2009 reported that “14 percent of Texans age 60 and older reported that their homes’ doorways, hallways, kitchen, bathrooms, and closets needed substantial modification to make it easier to get around inside. Thirty-eight percent of older Texans did not know where to go for help in making these types of improvements.”15 The same survey found that among older Texans more than 80 percent own their own homes and 60 percent of those do not make mortgage payments.16 The survey conducted in 2008 found that 20 percent of seniors rent with only 4 percent having some form of rent-free situation. The survey also points out that 56 percent of seniors in 2008 spent more than one-third of their income for total household expenses including 21 percent that spent more than half of their income for household related expenses.17

Poverty and Income.

According to census data updated by HISTA projections, approximately 3,585,250 people in Texas lived below the poverty line in 2009. According to the American Community Survey for 2006 to 2008, Texas had a poverty rate of 16.3 percent during this time period compared to the national poverty rate of 13.2 percent. Conditions are particularly acute in the colonias, unincorporated areas along the Texas-Mexico border lacking infrastructure and decent housing.

Minority populations continue to be overrepresented in the Texas population under the poverty level. According to the 2006 to 2008 American Community Survey, during that three-year period, the percent of Black or African American and Some Other Race populations under the poverty level were 23.9 to 24.10 percent, respectively. Other recorded races show a much lower poverty rate ranging from 14.10 percent to 17.8 percent. Similarly, the Hispanic population in poverty was 16.2 percent higher than white alone.18

14 U.S. Census Bureau, 2005-2007 American Community Survey. (n.d.) Subject Tables. Retrieved from http://factfinder.census.gov. 15 Aging Texas Well, Indicators Survey Overview Report 2009, Texas Department of Aging and Disability Services Center for Policy and Innovation, April 2009, at page 55. 16 Ibid at page 54. 17 Ibid. 18 U.S. Census Bureau, 2006-2008 American Community Survey. (n.d.). Subject tables. Retrieved from http://factfinder.census.gov.

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 20 of 196

Poverty is an issue in Texas across all race groups as Table 2.3 indicates. The lowest percentage below the poverty rate is among Asians with 11.40 percent and the highest is among Hispanic or Latino origin with just under one-in-four below the poverty level.

Table 2.3 Annual Poverty Estimates by Race and Latino Origin – Texas, 2006 to 2008 Percent below poverty Total Below poverty level level One race 22,798,691 3,721,271 16.30% White 16,637,808 2,352,590 14.10% Black or African American 2,597,993 620,334 23.90% American Indian and Alaska Native 114,474 20,355 17.80% Asian 796,800 91,128 11.40% Native Hawaiian and Other Pacific Islander 17,365 2,885 16.60% Some other race 2,634,251 633,979 24.10% Two or more races 433,501 70,817 16.30%

Hispanic or Latino origin (of any race) 8,397,171 2,086,053 24.80% White alone, not Hispanic or Latino 11,113,284 952,621 8.60%

Source: 2006 to 2008 American Community Survey 3-Year Estimates

Many families who rely on low-wage occupations for a living find it difficult to cover all essential expenses. According to a study by the Center for Public Policy Priorities, “a significant proportion of families throughout the state struggle paycheck-to-paycheck to make ends meet.” The study examined a typical family’s fundamental expenses, such as housing, food, child care, medical costs, transportation, taxes, etc., and compared the total bill to typical wages earned in the 27 Texas Metropolitan Statistical Areas. The study asserts that a family of four in Texas requires a household hourly income of $18 to $22 per hour (depending on the metro area in which the family lives) to simply meet its most basic needs. In a majority of Texas metro areas, however, half of the total employment is in occupations with a median wage under $10 per hour.19

In addition, expected economic growth will not necessarily lift the lowest-income groups. The Texas Comptroller’s Biennial Revenue Estimate predicts that the fastest growing sector of the state economy for 2010-2011 will be the professional and business services. This sector was also

19 Center for Public Policy Priorities. (2002, September 1). Making it: what it really takes to live in Texas. Retrieved from http://www.cppp.org/research.php?aid=120.

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 21 of 196 the fastest growing in 2008-2009, and it requires specialized education and skills.20 While this growth may buoy the state economy, it may not raise many low-income families, who may not have the necessary education or training, from their current positions.

Homeless Persons.

The National Alliance to End Homelessness estimates that for Texas in 2007, there were approximately 39,761 homeless people using a point-in-time estimate in January. The number of homeless in 2007 decreased from 2005 by 8.87 percent.21 However, estimates of homeless populations vary widely; the migratory nature of the homeless population, the stigma associated with homelessness, and the fact that many homeless individuals lack basic documentation all contribute to the difficulty of making an accurate count. Most homeless counts are “point in time” estimates, which do not capture the revolving-door phenomenon of persons moving in and out of shelters over time. The Texas Interagency Council for the Homeless estimates that approximately 200,000 people in Texas, or about 1 percent of the population, are homeless, which is higher than the National Alliances to End Homelessness’ point in time estimate.22 Furthermore, the homeless population can be classified into three categories: literally homeless, which describes those who have no permanent residence and stay in shelters or public places; marginally homeless, which includes those who live temporarily with other people and have no prospects for housing; and people at risk of homelessness. People at risk of homelessness generally have incomes below the poverty level, rely on utility and rental assistance, and may be unable to absorb unexpected events such as the loss of a job or serious illness.

The homeless population is not homogenous: there are homeless families with children, homeless youth, homeless minorities, homeless in rural areas, homeless victims of domestic violence, homeless persons with mental illness and disabilities, elderly persons, homeless veterans, and chronically homeless people. Though these subpopulations may have different characteristics, the two main trends significant in the rise of homelessness can be connected to

20 Texas Comptroller of Public Accounts. (2009, January). Biennial revenue estimate: 2010-2011. Retrieved from http://www.window.state.tx.us/taxbud/bre2010/outlook.html. 21 National Alliance to End Homelessness, Homeless Research Institute. (2009, January). Homeless counts: Changes in homelessness from 2005 to 2007. Retrieved from http://www.endhomelessness.org/content/article/detail/2158. 22 Texas Interagency Council for the Homeless. (2000). Key facts. Retrieved from http://www.tich.state.tx.us/facts.htm

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 22 of 196 the poverty (characterized by the decline in employment opportunities and public assistance programs) and a shortage of affordable housing.23

Table 2-4 breaks out the homeless population in Texas by the Comptroller’s standard regions. Note that the issue is present in every region in both Rural and Urban areas.

Table 2-4 Homeless, group quarters population by region – Texas, 2010 Region Rural Urban Total 1 510 1,986 2,496 2 451 1,761 2,212 3 756 12,937 13,693 4 722 2,230 2,952 5 537 990 1,527 6 976 17,340 18,316 7 197 8,015 8,212 8 571 1,639 2,210 9 751 6,497 7,248 10 428 2,631 3,059 11 309 2,083 2,392 12 226 1,084 1,310 13 15 2,056 2,071 State Total 6,449 61,249 67,698 Source: Nielsen Claritas, Ribbon Demographics, 2010.

Persons with Disabilities.

In the past, public-program spending for long-term services and supports for persons with disabilities in Texas was allocated in large part to institutional facilities such as nursing homes. However, over the last two decades, with the advent of Medicaid waivers, home- and community-based service alternatives have become an increasingly significant option and choice, as witnessed through recent federal and state legislation. With these services and supports provided in a residential setting, Texas has witnessed a large drop in its institutionalized 24 population, from over 12,000 in 1977 to 4,789 in 2008.

A significant number of persons with disabilities face extreme housing needs. Research conducted by the national Housing Task Force of the Consortium for Citizens with Disabilities found that as many as 2.4 million households with disabilities have “worst-case housing needs,” defined by HUD as unassisted renters with income below 50 percent of their area’s median

23 National Coalition for the Homeless. (2008, June). Why are people homeless? NCH Fact Sheet #1. Retrieved from http://www.nationalhomeless.org/factsheets/who.html 24 Research and Training Center on Community Living, (2009) Residential Services for Persons with Developmental Disabilities: Status and Trends Through 2008: Profiles of Trends in State Residential Services by State, Retrieved from http://rtc.umn.edu/docs/risp2008.pdf

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 23 of 196 income who pay more than half of their income for housing or live in severely substandard housing, or both.25 This is in line with the finding that the incidence of poverty is much higher for persons ages 25 to 64 with a severe disability (27%) or non-severe disability (12%) as compared to no disability (9%).26 In fact, HUD’s Office of Policy Development and Research reported that almost two-thirds of unassisted very low-income renter households with disabilities have worst-case housing needs.27

Texas has a slightly lower proportion of persons with disabilities compared to the national average of 19.3 percent of the total population. Of those Texans with disabilities, approximately 82 percent live in urban areas. Persons with disabilities are more likely to be living in urban areas due to the ability to access transportation and the close proximity to health-related and other services and supports.28 Table 2-5 provides estimates of persons with disabilities in Texas by the Comptroller’s standard regions.

Table 2-5 Persons with disabilities – Texas, 2000 Region Rural Urban Total 1 58,338 80,182 138,520 2 58,455 46,870 105,325 3 43,463 844,754 888,217 4 100,532 113,221 213,753 5 75,970 74,559 150,529 6 30,563 770,873 801,436 7 19,633 170,593 190,226 8 58,664 102,079 160,743 9 42,046 295,495 337,541 10 54,085 87,507 141,592 11 51,933 205,905 257,838 12 34,372 57,428 91,800 13 5,455 122,545 128,000 State Total 633,509 2,972,011 3,605,520 Source: Census 2000, urban defined by designation as an MSA.

Public Housing Residents.

Beginning in the 1930s, local public housing authorities (PHA) built and managed properties for low-income residents primarily through funding provided by the U.S. Department of Housing and Community Affairs (HUD). Most of the public housing developments were completed in

25 Technical Assistance Collaborative Inc., Housing Task Force of the Consortium for Citizens with Disabilities, (2008) The Hidden Housing Crisis: Worst Case Housing Needs Among Adults With Disabilities, http://www.tacinc.org/downloads/HiddenHousCrisis.pdf 26 National Council on Disability, (January 2010) The State of Housing in America in the 21st Century: A Disability Perspective 27 US Department of Housing and Urban Development, Office of Policy Development and Research, (May 2010) Worst Case Housing Needs 2007: A Report to Congress 28 Housing & Health Services Coordination Council, Testimony of Theresa Cruz, Director of the State Office of Rural Health, Texas Department of Rural Affairs: HHSCC Public Forums, 8 February 2010.

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 24 of 196 the 1970s. By 1993, HUD created HOPE VI to replace deteriorating public housing stock with mixed-income developments. Nationwide in the mid-1990s, 61 percent of public housing is located in the central city, 19 percent in the suburbs, and 20 percent in non-metropolitan areas. The median length of stay in public housing is 4.7 years and families with children stay a median of 3.2 years.29

A study entitled Federal Programs for Addressing Low-Income Housing Needs: A Policy Primer (2002) found that a majority of public housing residents were employed or searching for employment. However, most residents worked part-time, low-paying jobs offering no fringe benefits.30 Public housing residents may have educational barriers or transportation barriers that prevent them from transitioning to market-rate housing. 31

In Texas, according to HUD, there are 63,416 public housing units as of 2010.

Table 2-6 PHA Units – Texas, 2010 Region Rural Urban PHA Units 1 479 1,095 1,574 2 1,864 2,056 3,920 3 4,998 5,313 10,311 4 654 2,731 3,385 5 645 2,606 3,251 6 5,462 300 5,762 7 3,215 309 3,524 8 3,414 774 4,188 9 7,953 268 8,221 10 3,904 673 4,577 11 3,548 3,867 7,415 12 604 649 1,253 13 - 6,035 6,035 State Total 36,740 26,676 63,416 Source: US Department of Housing and Urban Development.

Persons Living with HIV/AIDS.

According to the Texas Department of State Health Services’ 2010 Texas Integrated Epidemiologic Profile for HIV/AIDS Prevention and Services Planning, HIV/AIDS cases are not evenly distributed across Texas. In 2008, Persons Living with HIV/AIDS (PLWHA) were concentrated in metropolitan areas, with over half residing in the Houston and Dallas

29 Turner, M. A. & Kingsley, G. T. (2008, December). Federal programs for addressing low-income housing needs: A policy primer. The Urban Institute. Retrieved from http://www.urban.org/uploadedPDF/411798_low-income_housing.pdf. 30 Martinez, J. M. (2002, September). The employment experiences of public housing residents: Findings from the jobs-plus baseline survey. Retrieved from http://www.mdrc.org/publications/25/overview.html. 31 Turner, M. A. & Kingsley, G. T. (2008, December). Federal programs for addressing low-income housing needs: A policy primer. The Urban Institute. Retrieved from http://www.urban.org/uploadedPDF/411798_low-income_housing.pdf.

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 25 of 196 metropolitan areas. In contrast, South and West Texas had the lowest rates of PLWHA in 2008.32 The highest rates of living cases were in the 45-54 age groups.

In looking at how client services funds were allocated by service category, the 2008-2010 Texas Statewide Coordinate Statement of Need (SCSN) found that housing was the second largest allocation category, with $14,765,131 provided to PLWHA in 2007. 33 However, SCSN also reported affordable housing as one of the two most frequent gaps in services identified by clients in six of the seven HIV Service Delivery Areas (HSDAs) assessed in Texas. For certain PLWHA, specifically for single women and single men without children, the availability of Ryan White & Housing Opportunities for Persons with AIDS (HOPWA) funded housing is a particular problem. Also, many HIV positive women with children who have had access to stable housing through Ryan White funds will lose this benefit once their children turn 18 and leave the home. Finally, through informant interviews, the SCSN found that reimbursement rates for housing are below fair market rates, which place clients into housing in high crime/low income areas which may lead to substance abuse issues, crime, and other factors that are known to affect access and maintenance in care.

Over 95 percent of PLWHA live in urban areas. The reason behind such a large urban concentration, as found in the SCSN, is a lack of available health care choices in non-urban service areas and the effect on access to care, especially for specialty services and the availability of affordable housing.34 See Table 2-7 for more details on persons living with HIV/AIDS in Texas.

32 Texas Department of State Health Services, (April 2010) 2010 Texas Integrated Epidemiologic Profile for HIV/AIDS Prevention and Services Planning, http://www.dshs.state.tx.us/hivstd/reports/HIVandAIDSinTexas.pdf 33 Texas Department of State Health Services (June 2008), 2008 – 2010 Texas Statewide Coordinated Statement of Need, http://www.dshs.state.tx.us/hivstd/planning/docs/SCSN_2008-2010.pdf 34 Texas Department of State Health Services, (June 2008), 2008 – 2010 Texas Statewide Coordinated Statement of Need, http://www.dshs.state.tx.us/hivstd/planning/docs/SCSN_2008-2010.pdf

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 26 of 196

Table 2-7 Persons with HIV/AIDS – Texas, 2008 Region Rural Urban Total 1 442 636 1,078 2 161 268 429 3 153 19,333 19,486 4 472 915 1,387 5 456 878 1,334 6 211 20,707 20,918 7 68 4,293 4,361 8 254 917 1,171 9 114 4,382 4,496 10 148 629 777 11 164 1,685 1,849 12 111 351 462 13 7 1,562 1,569 State Total 2,761 56,556 59,317 Source: Texas Department of State Health Services, 2010 Texas Integrated Epidemiologic Profile for HIV/AIDS Prevention and Services Planning

Note: Figures do not include those unaware of their HIV infection of those who tested HIV positive solely through an anonymous HIV test. Cases diagnosed at the Texas Department of Criminal Justice System are not attributed to a geographic area.

Colonia Residents.

Major issues affecting colonias include high rates of unemployment, extremely low-incomes, lack of sufficient infrastructure for water and sewer service, higher rates of certain diseases, lack of educational resources, substandard housing, and use of contract for deed. The latter two issues are directly related to housing. Housing in colonias is often constructed by residents using only available materials; professional builders are not often used.35 According to 2000 Census data, colonias have a 75 percent homeownership rate. Despite this rate, colonia homes are inadequate: 4.9 percent of colonia dwellings lack kitchen facilities and 5.3 percent lack plumbing facilities. It is estimated that 50 percent of colonia residents lack basic water and sewage systems: 51 percent use septic tanks, 36 percent use cesspools, 7 percent use outhouses, and 6 percent use other wastewater systems.36

Furthermore, properties in colonias are often purchased with contracts for deed, which are seller- financed transactions that do not transfer the title and ownership of the property to the buyer until the purchase price is paid in full. Contracts for deeds are often used in colonias because many residents do not have a credit history or qualify for a loan from a financial institution. Because

35 Federal Reserve Bank of Dallas. (n.d.). Texas colonias. Retrieved from http://www.dallasfed.org/ca/pubs/colonias.html. 36 Moncada, N. (2001). A Colonias Primer. A briefing presented to the US Department of Housing and Urban Development. Retrieved from http://www.nationalmortgagenews.com/nmn/plus93.htm.

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 27 of 196 of a lack of other options, contracts for deed often have high interest rates and are subject to abusive financial practices.37

Colonia residents have several needs that include increased affordable housing opportunities, such as down payment assistance and low-interest-rate loans, homeowner education, construction education and assistance, owner-occupied home repair, access to adequate infrastructure, and the conversion of remaining contracts for deed to conventional mortgages. According to the Office of Attorney General’s colonia estimates accessed in 2010, the number of colonia residents for Texas is 418,406.

Table 2-8 Colonia Residents – Texas, estimated 2010 Region Rural Urban Total 9 2,212 - 2,212 10 10,634 13,808 24,442 11 100,971 205,243 306,214 12 5,130 - 5,130 13 3,239 77,169 80,408 State Total 122,186 296,220 418,406

Source: Texas Office of the Attorney General, Border Colonia Geographic Database.

Migrant Seasonal Farmworkers.

Texas leads the nation in the quantity and size of farms and ranches with 247,500 properties covering 130.4 million acres. The economic impact of the food and fiber sector totals more than $100 billion; cash receipts from the agriculture and ranching industries total $19.8 billion.38 One of every seven working Texans (14%) is in an agriculture-related job, and many employed in this sector are migrant and seasonal farmworkers.

Migrant farmworkers have a particularly difficult time finding available, affordable housing because of extremely low and sporadic incomes and the fact that they will reside in a given location only a short time. Many of the small, rural communities in which migrant workers may seek employment do not have the rental units available for the seasonal influx. While TDHCA- licensed facilities are inspected annually and are required to meet health and safety standards,

37 Federal Reserve Bank of Dallas. (n.d.). Texas colonias. Retrieved from http://www.dallasfed.org/ca/pubs/colonias.html. 38 Texas Department of Agriculture, Texas Ag Stats, Retrieved from: http://www.agr.state.tx.us/agr/main_render/0,1968,1848_37142_0_0,00.html?channelId=37142

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 28 of 196 substandard conditions and overcrowding are believed to be widespread in other migrant labor housing situations. In addition, migrant workers may not be able to afford security deposits, pass credit checks, or commit to long-term leases.39

Table 2-9 Migrant Seasonal Farmworker Population Estimates – Texas, 2000 Region Rural Urban Total 1 71,055 9,407 80,462 2 20,252 775 21,027 3 3,308 11,370 14,678 4 8,912 1,518 10,430 5 2,755 304 3,059 6 3,463 6,133 9,596 7 928 3,418 4,346 8 4,970 1,088 6,058 9 10,929 8,028 18,957 10 10,811 11,098 21,909 11 35,022 87,925 122,947 12 32,971 4,028 36,999 13 6,201 4,745 10,946 State Total 211,577 149,837 361,414

Source: MSFW Enumeration Profiles Study – TX, Larson, Alice, 2000.

Housing Analysis.

Affordable Housing Need.

Texas has a significant need for affordable housing. The Texas Department of Housing and Community Affairs estimates in it Legislative Appropriation Request that it meets less than 1 percent of the total affordable housing need.40 This does not take into account the amount of housing directly funded by entitlement communities, but does indicate the amount of need in the state. When analyzing local housing markets and developing strategies for meeting housing problems, HUD suggests the consideration of several factors. The factors include how much a household spends on housing costs (also called the Housing Burden), the physical condition of the housing and whether or not the household is overcrowded. Table 2-10 reveals the number and percentage of households with at least one housing need by income category and household

39 Texas Department of Housing & Community Affairs, (September 2006), Migrant Labor Housing Facilities in Texas: A Report on the Quantity, Availability, Need, and Quality of Migrant Labor Housing in the State 40 TDHCA legislative Appropriations Request for the biennium 2012-2013.

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 29 of 196 type. The information that follows also provides more guidance as to the typical household issues that are part of this table.41

Table 2-10 Households with One or More Housing Needs - Texas, 2009 Renter Households Owner Households Percent Total Percent with At Least Total with At At Least Total Households At Least One One Need Households Least One One Need Households Need Need

Elderly Households 67,925 109,400 62.1% 117,016 175,853 66.5% 184,941

Small Related Households 186,654 235,214 79.4% 88,731 118,834 74.7% 275,385

Large Related Households 73,461 79,887 92.0% 45,537 51,417 88.6% 118,998

30% AMFI 30% - 0 Other Households 153,443 210,593 72.9% 45,667 68,579 66.6% 199,110

Total Households 481,483 635,093 75.8% 296,951 414,683 71.6% 778,434

Elderly Households 42,065 70,501 59.7% 72,987 194,982 37.4% 115,052

Small Related Households 153,646 207,834 73.9% 91,647 278,560 32.9% 245,293

Large Related Households 66,852 77,365 86.4% 62,532 121,022 51.7% 129,384

50% 50% AMFI -

31 Other Households 117,404 146,135 80.3% 28,305 79,216 35.7% 145,709

Total Households 379,966 501,835 75.7% 255,471 673,780 37.9% 635,437

Elderly Households 22,924 54,656 41.9% 47,761 244,435 19.5% 70,685

Small Related Households 112,716 287,855 39.2% 140,597 327,510 42.9% 253,313

Large Related Households 66,685 94,163 70.8% 94,937 153,426 61.9% 161,622

80% 80% AMFI -

51 Other Households 91,019 242,223 37.6% 41,734 92,646 45.0% 132,754

Total Households 293,344 678,898 43.2% 325,029 818,017 39.7% 618,373

Elderly Households 4,184 15,825 26.4% 11,464 91,545 12.5% 15,648

Small Related Households 21,057 105,448 20.0% 46,574 171,542 27.2% 67,631

Large Related Households 16,263 28,655 56.8% 29,629 62,440 47.5% 45,892

95% AMFI 95% - 1 Other Households 13,552 103,756 13.1% 16,297 47,030 34.7% 29,848

Total Households 55,055 253,684 21.7% 103,964 372,557 27.9% 159,019

Elderly Households 9,394 62,264 15.1% 27,207 577,016 4.7% 36,601

Small Related Households 50,431 460,030 11.0% 153,049 2,029,389 7.5% 203,480

Large Related Households 40,814 85,861 47.5% 106,986 418,592 25.6% 147,799

Other Households 19,619 389,239 5.0% 40,506 351,997 11.5% 60,125 More Than 95% 95% AMFI Than More Total Households 120,258 997,395 12.1% 327,748 3,376,994 9.7% 448,005

41 Many materials regarding the Housing Analysis is taken with permission from the 2010 State of Texas Low Income Housing Plan and Annual Report, prepared by TDHCA. Communities are encouraged to look for changes in data as this report is published not later than March 18 of each year in assisting in their Fair Housing reviews and plans

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 30 of 196

Renter Households Owner Households Percent Total Percent with At Least Total with At At Least Total Households At Least One One Need Households Least One One Need Households Need Need

Elderly Households 146,492 312,646 46.9% 276,435 1,283,831 21.5% 422,927

Small Related Households 524,504 1,296,381 40.5% 520,598 2,925,834 17.8% 1,045,101

Large Related Households 264,075 365,931 72.2% 339,620 806,897 42.1% 603,695

Other Households 395,037 1,091,947 36.2% 172,509 639,469 27.0% 567,546 Total Households Total

Total Households 1,330,106 3,066,905 43.4% 1,309,162 5,656,031 23.1% 2,639,268 Source: CHAS 2000 with projections based on HISTA data.

Physical Inadequacy (Lack of Kitchen and Plumbing Facilities).

The measure of physical inadequacy available from the CHAS database tabulation is the number of units lacking complete kitchen and/or plumbing facilities. While this is not a complete measure of physical inadequacy, the lack of plumbing and/or kitchen facilities can serve as a strong indication of one type of housing inadequacy. Figure 2-1 demonstrates that among the physically inadequate housing units, 31 percent are occupied by extremely low-income households.42

Figure 2-1 Number of Units Lacking Kitchen and/or Plumbing by Affordability Category – Texas, 2009

Income Group Units Percent 0% to 30% 29,690 31% 31% to 50% 18,293 19% 51% to 80% 18,792 20% 80% to 95% 4,838 5% Over 95% 22,778 24%

Total 94,391 Source: CHAS Database with projections based on HISTA data

The state defines “standard condition” of housing as properties that meet the federal Housing Quality Standards, or the state Colonia Housing Standards, as applicable. “Substandard condition but suitable for rehabilitation” refers to properties that do not meet the above standards but are not sufficiently deteriorated to justify demolition or replacement. These definitions refer to the condition of properties prior to the receipt of assistance.

42 Ibid

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 31 of 196

Figure 2-2 shows the distribution of this problem by income group. Households in the lowest income group earning 30 percent HAMFI or less have the highest incidence of physically inadequate rental housing.

Figure 2-2 Renter Households with Substandard Housing by Percent – Texas, 2009

3.0% 2.7%

2.5%

2.0% 2.0%

1.5% 1.5%

1.0% 1.0% 1.0%

0.5% Percent of Percent RenterHouseholds

0.0% 0% to 31% to 51% to 81% to Over 95% 30% 50% 80% 95% Income Categories

Source: CHAS Database with projections based on HISTA data.

Following the same trend as renter households, owner households in the lowest-income category have more incidents of substandard housing. Approximately three percent of owner households earning 30 percent HAMFI or less have substandard housing.

Figure 2-3 Owner Households with Substandard Housing Percent – Texas, 2009 3.5% 3.0% 3.0%

2.5%

2.0% 1.8%

1.5% 1.1% 1.0% 0.6% 0.4%

0.5% Percent of Percent Owner Households 0.0% 0% to 31% to 51% to 81% to Over 95% 30% 50% 80% 95%

Income Categories Source: CHAS Database with projections based on HISTA data

Extreme Housing Cost Burden.

An excess cost burden is identified when a household pays more than 30 percent of its gross income for housing costs. When so much is spent on housing, other basic household needs may suffer. As Figure 2-4 shows, a majority of renter households in the lowest two income categories, totaling more than 621,200 households, is burdened by paying an excess portion of income

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 32 of 196 toward housing. This is much greater than in the highest income category, above 95 percent HAMFI, where only 2.2 percent of households, or 22,005 households, experience the problem.43

Figure 2-4 Renter Households with Extreme Housing Cost Burden (>30% of Income) by Percent – Texas, 2009 60.0% 55.2% 53.7%

50.0%

40.0%

30.0% 25.1%

20.0%

8.3% 10.0%

Percent of HouseholdsRenterPercent 2.2% 0.0% 0% to 30% 31% to 51% to 81% to Over 95% 50% 80% 95% Income Categories Source: CHAS Database with projections based on HISTA data

As shown in figure 2-5, excess housing cost burden affects 59.3 percent of owner households in the lowest income category. This figure, representing a majority, is much higher than the 5.7 percent of households affected in the highest income category. The graph illustrates the direct correlation between an owner household’s income category and an owner household’s likelihood of experiencing this problem.

Figure 2-5 Owner Households with Excess Housing Cost Burden (>30% of Income) by Percent – Texas 2009

70.0% 59.3% 60.0%

50.0% 41.3% 40.0% 27.9% 30.0% 19.3% 20.0%

10.0% 5.7% Percent of Owner Households Owner Percent of 0.0% 0% to 31% to 51% to 81% to Over 30% 50% 80% 95% 95% Income Categories

Source: CHAS Database with projections based on HISTA data

Figure 2-6 shows the total number and percentage of households with excess housing cost burden by income group.

43 Ibid

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 33 of 196

Figure 2-6 Excess housing Cost Burden by Income Group – Texas, 2009

Over 95% AMFI, 214,784, 12% 81% to 95% 0% to 30% AMFI, 93,253, AMFI, 597,941, 5% 34%

51% to 80% AMFI, 399,733, 23%

31% to 50% AMFI, 465,149, 26%

Source: CHAS Database with projections based on HISTA data

Overcrowding.

Overcrowded housing conditions occur when a residence accommodates more than one person per each room in the dwelling. Overcrowding may indicate a general lack of affordable housing in a community where households have been forced to share space, either because other housing units are not available or because the units available are too expensive.

Lower income renter households experience overcrowded conditions more frequently than higher income households. Almost 18 percent of renter households in the extremely low income category and 19.9 percent of renter households in the low income category are afflicted by overcrowding.44

Figure 2-7 Renter Households with Incidence of Overcrowding by Percent – Texas, 2009 25.0%

19.9% 20.0% 17.8% 16.6%

15.0% 12.4%

10.0% 8.9%

5.0% Percent of Renter Households of Renter Percent

0.0% 0% to 31% to 51% to 81% to Over 95% 30% 50% 80% 95% Income Category

Source: CHAS Database with projections based on HISTA data

44 Ibid

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 34 of 196

Lower income owner households also experience overcrowded conditions more frequently than higher income owner households. More than 21 percent of owner households earning less than 50 percent HAMFI live in overcrowded conditions compared to 11.4 percent of owner households over 80 percent HAMFI.

Figure 2-8 Owner Households with Incidence of Overcrowding by percent

12.0% 11.1% 10.7%

10.0% 9.2% 7.8% 8.0%

6.0%

3.6% 4.0%

2.0% Percent of Owner Households of Owner Percent

0.0% 0% to 31% to 51% to 81% to Over 95% 30% 50% 80% 95% Income Category Source: CHAS Database with projections based on HISTA data

Figure 2-9 shows the total incidence of overcrowded households by income group.

Figure 2-9 Overcrowded Households by Income Group – Texas, 2009

0% to 30% , Over 95% , 151,051, 19% 210,500, 27%

31% to 50% , 81% to 95% , 152,317, 20% 60,765, 8%

51% to 80% , 200,208, 26% Source: CHAS Database with projections based on HISTA data

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 35 of 196

SECTION 3. EVALUATION OF LARGE URBAN CENTERS AND SURROUNDING AREAS--HOUSTON AND GALVESTON.

The area defined by the Houston – Galveston Area Council (“H-GAC”) is large and extremely diverse. At the heart of it is one of the largest cities in the country, bounded on the south by the world’s largest petrochemical complex and the Gulf of Mexico, site of some of the most devastating natural disasters ever to hit the United States. Outlying areas in H-GAC are a variety of smaller towns, including some very rural areas, and a wide array of progressively larger cities, including Galveston. This section is not intended to provide a complete AI for each community in the H-GAC Region. In fact, some communities in the H-GAC region may find that they have more in common with the Golden Triangle Section in terms of availability of resources, staff, and recent experience with growth. Others may find that the small community section, where the focus is on cities of less than 2,500, provides an analysis of conditions more like those they are facing and find that they provide more useful guidance on ways to overcome Fair Housing impediments.

This section will target issues that are present in the communities of Houston and surrounding areas like Galveston. These cities are grouped together because of the urban setting and their relative proximity and use of many combined or shared resources. Houston with a population of 2,024,37945 has different resources, staff, taxing structures and challenges than a city like Galveston with a population of 52,82146 or La Porte with a population of 36,77947 and especially a small community like Shoreacres with a population of 1,488.48

Even with size differences and clear differences in zoning and enforcement, many of these communities rely on a very similar community of professionals in the real estate and mortgage industries and on similar and often shared media outlets. Both Houston and Galveston experience many of the same issues common to urban areas. Many cities in the region have commuters that work in Houston but live a suburban or rural setting in distinctly separate

45 U.S. Census Bureau American FactFinder, Fact Sheet Houston city, Texas Data Profile Highlights 2006-2008 retrieved at http://factfinder.census.gov 46 U.S. Census Bureau American FactFinder, Fact Sheet Galveston city, Texas Data Profile Highlights 2006-2008 retrieved at http://factfinder.census.gov 47 U.S. Census Bureau American FactFinder, Fact Sheet La Porte city, Texas Data Profile Highlights 2006-2008 retrieved at http://factfinder.census.gov 48 Texas State Directory 2009, 52nd Edition, Texas State Directory Press, Inc.

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 36 of 196 communities. As the demographic data in Section 2 of this AI demonstrates, both urban and rural areas in H-GAC face many of the same challenges with homelessness, persons with aids, an aging society, poverty and a need for additional affordable housing.

This section is designed to identify existing impediments to developing an integrated community meeting the goals of the Fair Housing Act.

Historical Recap.

The H-GAC area is large and diverse representing one of the largest urban areas in the United States, with Houston alone being the fourth most populous cities in the country.49 The population diversity of the Houston Region50 is such that the region has no racial or ethnic majority.51 The region has more jobs than all of Colorado.52 Living costs for the region are 21 percent below the average for major metropolitan areas.53

From its earliest days, Houston has been a magnet for industry and individuals experiencing dramatic growth from the population of 34,772 in 1850 to more that 4.8 million people today. 54 The Port of Houston, one of four ports in the region, among us ports was first in import tonnage and second in export tonnage and second in total tonnage.55 In addition, it was the 14th largest port in the world for tonnage passing through the port. Despite the U.S. economy, Houston has continued to grow in diverse economic opportunities and it posted the fastest job growth among the major metropolitan centers. 56

Previously—in the 1970’s—Houston had a boom in the economy from speculative commercial and individual housing building that later had a tremendous negative impact. In the current economy, Houston’s ability to readily accommodate increased demand for new homes allowed it to escape the national “housing bubble” and subsequent collapse. The apartment market in the region as of year-end 2007 had an occupancy rate of 87.4 percent with an inventory of 536,829 units in 2,751 complexes.

49 2008/2009 Houston Facts Discover the Houston Region, Greater Houston Partnership. 50 Report includes 10 counties, Austin, Brazoria, Chambers, Fort Bend, Galveston, Harris, Liberty, Montgomery, San Jacinto, and Waller counties. 51 2008/2009 Houston Facts Discover the Houston Region 52 Ibid. 53 Ibid. 54 Ibid. 55 Ibid 56 Ibid.

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 37 of 196

In 2005, Houston became a key figure in the disaster recovery efforts of Hurricane Katrina opening its community to nearly 400,000 people from other states that were left without homes by Katrina. Houston opened up its public facilities to the evacuees with 77.9 percent of the evacuees in Houston staying at least temporarily at the Astrodome, Reliant Center, or the George R. Brown Convention Center.57 Of the approximately 150,000 Katrina evacuees that remained in Houston one year after the storm, 68.6 percent of those asked said they planned to remain in Houston.

Even with the commitment made to the Katrina evacuees at the time of the storm, research has shown that the evacuees that remain behind are thought of by the overall population in a similar pattern to immigration in general.58 The views were held by most Houstonians according to research by Dr. Jason Shelton. He said it was common even though many African Americans “believed that racism was the reason why the Katrina situation became so dire in the first place.”59 However, his research found that even in the African American community, “the outsiders from New Orleans were draining the city’s resources and were responsible for increased violent crime.”

In sheltering Hurricane Katrina evacuees in Houston the limited affordable housing options available at the time resulted in some unintended concentrations of evacuees. There is a continuing need to provide housing choice options to those new Houstonians in to order to further fair housing. The state dedicated $60 million in federal disaster recovery funds to the City of Houston and Harris County to assist in the process of helping to transition Katrina evacuees into the community.60 Houston identified some concentrations of Katrina residents that warranted spending funds to rehabilitate multi-family homes to provide a better community for these new Houstonians.61

The Houston region is working together on many of its issues to help the economic and increasing livability for all of its residents. Hurricane Ike greatly impacted the region and it is still recovering from the damages inflicted by the hurricane.

57 Katrina Evacuees in Houston: One-year out, Division of Social Sciences, Rice University, Rick Wilson and Robert Stein 58 Study links immigration and evacuee fears, Houston Chronicle, http://www.chron.com/disp/story.mpl/metropolitan/6565106.html 59 Katrina evacuees finding limits to our hospitality, Houston Chronicle, Jason E Shelton, http://www.chron.com/disp/story.mpl/editoial/outlook/6590368.html 60 State of Texas Partial Action Plan for Hurricanes Katrina, Rita and Wilma 61 Amendment to State of Texas Partial Action Plan for Hurricanes Katrina. Rita and Wilma

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 38 of 196

Regional Demographic Recap.

As one of the largest Urban Areas in the State, much of the information presented here will resemble the trends in the state demographic data presented in Section 2. As with the information presented in Section 2, the specific demographic data presented in Appendix D will provide many communities with a look at the current racial segregation overall in individual communities of populations of 10,000 or more. The demographic data presented here is for the purpose of looking at regional challenges and how the growth of one area may actually impact surrounding communities as people look to either relocate or look for more affordable housing, better schools, less commute time, more open space or the variety of other reasons that people relocate.

Population.

As with the state as a whole, Non Hispanic White and Black populations will decrease as a percentage of the population—with Non Hispanic Whites actually decreasing in total population by 2040 under either scenario62—while the “Other” increase in raw numbers and Hispanic populations increase and become the largest community by race.

Table 3-1 Projected Population H-GAC Region Year Non Black Hispanic Other Total Hispanic White

2000 2,383,452 823,761 1,389,915 257,326 4,854,454 Year Non Non Black Black Hispanic Hispanic Other 0ther Total Total Hispanic Hispanic 0.0 0.5 0.0 0.5 0.0 0.5 0.0 0.5 White White Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario 0.0 0.5 scenario Scenario

2010 2,453,613 2,426,826 886,809 922,584 1,682,614 1,981,417 285,742 357,448 5,308,778 5,688,275

2020 2,472,990 2,361,456 926,783 1,003,400 1,952,820 1,981,417 301,083 357,448 5,653,676 5,688,275

2040 2,284,711 2,122,363 911,262 1,067,490 2,428,908 4,490,358 300,916 716,700 5,925,797 8,483,600

62 These projections assume the One-Half 1990-2000 Migration (0.5) Scenario. According to the State Demographer: this scenario has been prepared as an approximate average of the zero (0.0) and 1990-2000 (1.0) scenarios. It assumes rates of net migration one-half of those of the 1990s. The reason for including this scenario is that many counties in the State are unlikely to continue to experience the overall levels of relative extensive growth of the 1990s. A scenario which projects rates of population growth that are approximately an average of the zero and the 1990-2000 scenarios is one that suggest slower than 1990-2000 but steady growth. 62

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 39 of 196

Age.

Table 3-2 shows the population’s anticipated aging according to the demographers located at the University of Texas at San Antonio for the H-GAC Region. This table demonstrates that the percentage of the population who is over sixty five will increase in raw numbers within the age category and as a percentage of the population as a whole.63 The 2040 data assumes rates of net migration equal to one-half of 1990-2000 (.5 Scenario) and is neither the least nor the most conservative estimate by the demographers.

Table 3-2 Age by Age Group and Race/Ethnicity Age Non Non Black Black Hispanic Hispanic Other Other Total Total Group Hispanic Hispanic 2000 2040 2000 2040 2000 2040 2000 2040 White White 2000 2040 <18 24.0 17.7 31.5 19.5 3.1 25.3 26.3 14.7 28.9 21.7 18-24 7.5 7.1 10.8 8.9 13.9 9.9 9.6 5.8 10.0 8.7 25-44 31.5 23.7 31,9 26.1 34.3 30.9 36.4 23.1 33.6 27.8 45-64 25.8 25.5 18.8 27.0 12,5 22.5 22.3 26.4 20.6 24.1 65+ 11.2 26.0 7.0 18.5 3.2 11.4 5.4 29.9 7.9 17.7 Median 38.00 46.2 30.0 41.7 25.0 34.3 32.5 49.8 32.0 39.0

When compared to the state as a whole, the H-GAC region estimates appears to age only slightly more than the state as a whole in median age. The aging of a population matters as it signals anticipated greater need to address special needs that an older population may have, as previously discussed in Section 2.

Poverty and Income Region 6 Poverty Figures, 2010 The table to the right depicts the number of At or above poverty Below poverty families living below the poverty line in Families Percent Families Percent Rural 40,011 86.8% 6,105 13.2% Region 6. Of the 165,313 families living Urban 1,292,572 89.0% 159,208 11.0% below poverty, approximately 96.3 percent Region 6 Total 1,332,583 89.0% 165,313 11.0% are living in urban areas, with the remaining Source: Nielsen Claritas, Ribbon Demographics, 2010. 3.7 percent in rural areas. However, the

63 Table 2.14 Percentage of population for the State of Texas and Council of Government Regions in Texas by Age and Race/Ethnicity of the Population and Median Age by Race/Ethnicity in 2000 and Projections to 2040 Assuming Alternative Projection Scenarios HGAC Region data http://txsdc.utsa.edu/pubsrep/

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 40 of 196 percentage of total rural families that are below poverty is slightly higher than the percentage of total urban families. This may be due to the region’s rural counties lagging behind the Houston MSA in recent and expected job creation.64

Region 6 Household Income The pie chart to the left depicts the income Extremely Low breakdown of the 1,691,811 households in the region. Income (0-30%), Approximately 40 percent of households are low 12% Very Low Income income. There are 754,675 individuals living in (31%-50%), 11% Higher Income poverty in the region, which makes up 13.6 percent of Low Income (over 95%), 52% the regional population. According to the Texas (51%-80%), 17% Comptroller’s Texas In Focus report, many Region 6 Moderate Income (81%-95%) , 8% jobs exceed the state’s 2008 per capita income level of $37,774, with 376 occupations paying more than this amount.65

The H-GAC region has the second largest number of households in the state (second to Region 3 Dallas Fort Worth area) and the second largest number of households with income registered as low to extremely low for the state. Just under 60 percent of the region’s households are at 80.1 percent income or higher. Table 3-3 compares the Region 6 which covers the H-GAC Region to the state total.

Table 3-3 Income Levels for Region 6 as compared to state as a whole66 Moderate Extremely Very Low Low Income Income Service Total Low Income Income (51% to (80.1% and Region67 Households (0% to 30% (31% to 80% AMFI) above AMFI) 50% AMFI) AMFI)

6 1,694,284 209,305 187,666 285,397 1,011,916 Source: 2000 CHAS Database

64 Texas Comptroller of Public Accounts, “Texas in Focus: Gulf Coast Region,” October 2008. http://www.window.state.tx.us/specialrpt/tif/gulf/ (accessed October 6, 2010). 65 Texas Comptroller of Public Accounts, “Texas in Focus: Gulf Coast Region,” October 2008. http://www.window.state.tx.us/specialrpt/tif/gulf/ (accessed October 6, 2010). 66 Includes Colorado County which is not in the disaster impacted area. 67 Where the term Service Region is used in this section, the term means Comptroller’s 13 Uniform State Service Regions of Texas, the Region system used by TDHCA for funding

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 41 of 196

Homeless Persons.

According to 2010 population projections by Ribbon Demographics, this region has approximately 27.1 percent of the statewide total of people in non-institutional group quarters, including shelters.

Region 6 also experienced damage from Hurricane Rita, which hit the southeast Texas area in September 2005 and Hurricane Ike in September 2008. According to FEMA, $28.3 million worth of damage was reported after Hurricane Rita and $29.4 billion after the 2008 hurricane season. Households affected by the hurricane have unexpected needs.

Table 3-4 H-GAC Homeless, 2010 County Homeless Persons Austin 43 Brazoria 413 Chambers 15 Fort Bend 1,513 Galveston 604 Harris 14,378 Liberty 28 Matagorda 35 Montgomery 294 Walker 537 Waller 95 Wharton 295 Total 18,250 Source: Nielsen Claritas, Ribbon Demographics, 2010.

Persons with Disabilities.

According to the US Census, of the total population in Region 6, persons with disabilities account for approximately 16.5 percent of the population. Of this total, approximately 96 percent are residing in urban areas, with the remaining 4 percent in rural areas.

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 42 of 196

Table 3-5 Region 6 Persons with, without disabilities, 2000 Persons with a County disability County Population Austin 4,173 23,590 Brazoria 37,517 241,767 Chambers 4,175 26,031 Fort Bend 46,724 354,452 Galveston 42,616 250,158 Harris 573,025 3,400,578 Liberty 13,516 70,154 Matagorda 7,063 37,957 Montgomery 47,386 293,768 Walker 8,101 61,758 Waller 5,914 32,663 Wharton 7,477 41,188 797,687 4,834,064 Source: US Census 2000.

Public Housing.

There are 5,762 public housing units present in the H-GAC region. The vast majority of these sites are in urban areas as Table 3-6 demonstrates. The PHAs address housing needs via a system of housing units and vouchers,

Hurricane Ike damaged units on Galveston Island leading the city to condemn the buildings and for them to be destroyed. As part of the process of tearing down the damaged units, an agreement to rebuild 569 units of public housing was drafted between the Galveston Housing Authority and its tenants represented by Lone Star Legal Aid for the benefit of Low Income Galvestonians. The Conciliation Agreement signed by the State of Texas carried this commitment forward. Rebuilding these units continues to be controversial with a portion of the city’s population However, the Galveston City Council has voted twice to move forward and restore public housing – by allocating $25 million in funding during Round 1 and by passing a resolution requiring the rebuilding of 569 public housing units and instructing the Galveston Public Housing Authority to prepare a redevelopment plan for City Council approval. Prior to the hurricane, Texas City had embarked on a process to replace old-style public housing with a voucher program.

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 43 of 196

The state committed in the Conciliation Agreement to set aside tens of millions of dollars in disaster recovery funds to make sure that all public housing damaged or destroyed by the storm in the H-GAC region was replaced or rebuilt.

Table 3-6 Public Housing units in Region 6 Region Rural Urban PHA Units 6 300 5,462 5,762 State Total 26,676 36.740 63,416

Local Input on Housing Assistance.

According to the TDHCA Public Request Assistance Inventory for State Fiscal year 2010, the agency received 48,488 public assistance requests from Region 6, which accounted for 23.0 percent of total annual requests. Of requests from Region 6, the three most requested categories of assistance were, in order: Rental Assistance; Homebuyer Assistance, and Utility Assistance.

Table 3-7

H-GAC Public Assistance Request Inventory, SFY 2010

Legal Legal

Utility Rental

Repair

ssistance

Disaster Disaster

Assistance Assistance

Assistance A Assistance Assistance

Emergency Emergency

Foreclosure Homebuyer

Austin 3 0 0 3 0 3 0 4 Brazoria 16 0 1 15 0 23 5 5 Chambers 1 0 0 1 0 0 0 0 Fort Bend 12 1 1 12 0 7 2 5 Galveston 35 1 2 35 2 33 3 9 Harris 190 3 12 187 6 145 27 40 Liberty 5 0 1 5 1 8 1 5 Matagorda 3 0 1 3 0 5 0 2 Montgomery 19 0 0 20 0 25 3 8 Walker 9 0 1 9 0 4 0 3 Waller 5 0 0 5 0 9 0 1 Wharton 1 1 0 1 0 2 3 2 299 6 19 296 9 264 44 84 Source: TDHCA Public Request Assistance Inventory for SFY2010.

Persons with HIV/AIDS

According to the Texas Department of State Health Services’ 2010 Texas Integrated Epidemiologic Profile for HIV/AIDS Prevention and Services Planning, there are 20,898 persons living with HIV/AIDS in the H-GAC impacted Region, Approximately 99 percent of this population is living in urban areas, with the remaining 1 percent in rural areas. Region 6 has a high rate of persons living with HIV/AIDS compared to the state as a whole, with the Houston

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 44 of 196 metropolitan area accounting for 31.4 percent of the total. Additionally, the Houston metropolitan area has a rate of 392 persons per 100,000, which is the highest in the state.

Table 3-8 H-GAC Persons living with HIV/AIDS, 2008 County HIV/AIDS Number HIV/AIDS Rate Population 2008 Austin 25 90.3 27,032 Brazoria 262 87 301,228 Chambers 10 30 29,366 Fort Bend 541 103 532,609 Galveston 641 225 288,489 Harris 18,751 476 3,980,602 Liberty 89 109 75,335 Matagorda 45 116 37,038 Montgomery 350 81 431,238 Walker 60 92 63,554 Waller 63 156 35,970 Wharton 61 141 40,863 20,898 5,843,324 Source: Texas Department of State Health Services. 2010 Texas Integrated Epidemiologic Profile for HIV/AIDS Prevention and Services Planning: HIV/AIDS in Texas. Population from US Census Population Estimates, 2008.68

Migrant Farmworkers.

In a study prepared for the US Health Resources and Services Administration, Region 6 was found to have a very low proportion of the state’s Migrant and Seasonal Farmworker (MSFW) population, accounting for just 2.7 percent of the 361,414 MSFWs in the state of Texas.69

Table 3-9 H-GAC Migrant and Seasonal Farmworker Population, 2000

Migrant Seasonal % of MSFW Statewide County Farmworkers population Austin 224 0.06% Brazoria 1,150 0.32% Chambers - 0.00% Fort Bend 1,329 0.37% Galveston 85 0.02% Harris 3,147 0.87% Liberty 71 0.02% Matagorda 917 0.25% Montgomery 107 0.03% Walker 190 0.05% Waller 244 0.07% Wharton 1,995 0.55% 9,459 361,414 Source: HRSA Migrant Health Program, 2000.

68 Note: Figures do not include those unaware of their HIV infection of those who tested HIV positive solely through an anonymous HIV test. Cases diagnosed at the Texas Department of Criminal Justice System are not attributed to a geographic area. 69 Migrant and Seasonal Farmworker Enumeration Profiles Study – TX, Larson, Alice, 2000.

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 45 of 196

HOUSING ASSESSMENT.

A housing assessment includes the current housing supply, a sample of market-rate housing costs, the housing needs and the availability of subsidized housing.

Housing Supply.

According to the 2010 projection, 90.1 percent of the housing units in the region are occupied. Of the total housing stock, 65.8 percent are one unit; 1.3 percent are two units; 18 percent are three or more units; 5.5 percent are mobile homes; and the rest are RVs and boats.

Table 3-10 Region 6 Housing Supply, 2010 Rural Urban Total Total housing units 80,727 2,235,809 2,316,536 Vacant housing units 14,251 214,745 228,996 Housing units, 1 unit 54,073 1,469,553 1,523,626 Housing units, 2 units 1,604 28,028 29,632 Housing units, 3 to 4 units 3,065 59,430 62,495 Housing units, 5 to 19 units 6,442 357,880 364,322 Housing units, 20 to 49 units 862 87,726 88,588 Housing units, 50+ units 1,486 117,592 119,078 Housing units, mobile home 13,101 113,494 126,595 Housing units, other 94 2,106 2,200 Source: Nielsen Claritas, Ribbon Demographics, 2010.

Sample of Market Housing Costs.

Samples of Market Housing Costs include median home prices for the region’s largest city, a highly impacted coastal city (Galveston). According to the Multiple Listing Service records for August 2010, the median home prices for Houston and Galveston are $157,500 and $180,000 respectively.70 In addition, the fair market rent for a two bedroom unit in Houston/Baytown/Sugar Land HMFA and Galveston County is $892, requiring an annual income of approximately $35,680.71

Housing Need.

The housing need indicators analyzed in this section include housing cost burden, substandard housing conditions and housing overcrowding for renter and owner households. The following

70 Real Estate Center at Texas A&M University, “Texas Residential MLS Activity,” http://recenter.tamu.edu/data/hs/hs250b.htm (accessed September 24, 2010). 71 National Low Income Housing Coalition. (2010). Out of reach 2010. Retrieved from http://www.nlihc.org/oor/oor2010/

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 46 of 196 information comes from the 2000 CHAS database update with HISTA population projections. There were approximately 621,947 owners and renters with housing problems in 2009.

Table 3-11 H-GAC Households with Housing Problems, 2009 Units Lacking Complete Plumbing/Kitchen, CHAS 2000 Total units NAME all incomes 0-30% HAMFI 31-50% HAMFI 51-80% HAMFI >80% HAMFI Texas 78,129 35,692 19,997 14,463 7,977 Austin 200 131 26 17 26 Brazoria 691 416 183 66 26 Chambers 146 105 19 17 5 Fort Bend 758 414 163 113 68 Galveston 904 465 236 165 38 Harris 8,714 2,343 3,355 2,139 877 Liberty 436 243 86 68 39 Matagorda 204 119 31 27 27 Montgomery 540 315 127 40 58 Walker 194 114 37 38 5 Waller 250 96 81 18 55 Wharton 412 271 74 32 35 13,449 5,032 4,418 2,740 1,259

Households with a Cost Burden >30%, CHAS 2000 NAME total households 0-30% 31-50% 51-80% 81-95% > all incomes HAMFI HAMFI HAMFI HAMFI 95%HAMFI Texas 1,493,227 562,331 370,229 292,093 76,387 192,187 Austin 1,437 723 293 212 84 125 Brazoria 11,416 4,896 2,841 2,100 590 989 Chambers 1,177 580 309 138 36 114 Fort Bend 15,893 3,727 2,498 3,393 1,402 4,873 Galveston 19,757 8,334 5,021 3,493 795 2,114 Harris 254,158 99,914 65,347 46,538 11,609 30,750 Liberty 4,088 2,387 895 559 101 146 Matagorda 2,555 1,383 539 362 83 188 Montgomery 14,978 5,085 3,669 3,021 946 2,257 Walker 4,589 2,169 915 1,056 145 304 Waller 1,855 1,049 404 185 68 149 Wharton 2,682 1,264 624 493 82 219 334,585 131,511 83,355 61,550 15,941 42,228

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Households that are Overcrowded, CHAS 2000 NAME total households 0-30% HAMFI 31-50% HAMFI 51-80% HAMFI 81-95% HAMFI > all incomes 95%HAMFI Texas 469,895 116,809 96,455 113,821 40,778 102,032 Austin 442 82 39 107 75 139 Brazoria 3,901 792 762 1,056 332 959 Chambers 349 95 51 93 20 90 Fort Bend 4,963 935 799 1,205 570 1,454 Galveston 4,201 1,181 792 1,028 357 843 Harris 95,911 23,863 20,214 24,236 8,471 19,127 Liberty 1,108 254 337 291 99 127 Matagorda 1,158 255 224 245 123 311 Montgomery 3,352 780 731 874 336 631 Walker 927 211 95 306 83 232 Waller 515 113 145 107 24 126 Wharton 983 233 177 221 78 274 117,810 28,794 24,366 29,769 10,568 24,313

Identification of Impediments to Fair Housing.

The H-GAC region is diverse because of the differences in community size and the amount and type of employment. It is home to almost a quarter of the refining production in the United States. It also has four operational ports with one being one of the busiest ports in the United States. Galveston Bay and the Gulf also provide one of the largest fisheries in the state. It has 23.3 percent of the state’s population and Houston is the fourth largest city in the United States. As previously mentioned, about 48 percent of its population’s income earns less than 80 percent of the area median family income. The region has no ethnic group representing a majority of the population, although currently Non Hispanic Whites still make up the largest single portion of the population.

Despite its diversity, it is not a region without Fair Housing challenges. As discussed above, the need for more affordable housing is an impediment. This AI will not focus on that issue unless there is an unusual circumstance that requires special attention—like public housing or repair of affordable rental housing.

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 48 of 196

Home Mortgage Disclosure Act Analysis.72

The State of Texas contracted with the National Community Reinvestment Coalition (“NCRC”) to conduct a portfolio and market share analysis using 2008 Home Mortgage Disclosure Act (“HMDA”) data for the Houston Galveston Area Council (“H-GAC”). The following counties comprise the Ike affected portion of H-GAC: Austin, Brazoria, Chambers, Fort Bend, Galveston, Harris, Liberty, Matagorda, Montgomery, Walker, Waller, and Wharton.73

Portfolio Share Analysis of All Conventional Single Family Lending in Houston, Galveston, Texas.

Hispanics are the largest minority group in Houston Galveston, TX, representing more than 21 percent of all households. African Americans account for about 17 percent of households and Asians account for about 4 percent of households in Houston Galveston. Table 1a (see corresponding Chart 1a) of the conventional lending report shows that the portions of all prime loans received by Hispanic borrowers and African American borrowers were lower than the portion of loans received by non-Hispanic white borrowers compared to their portion of households. Hispanic borrowers received only 14.41 percent of prime loans that was lower than their portion of households (21.34 percent). African American borrowers received only 5.3 percent of prime loans that was considerably less than their portion of households (17.3 percent). In contrast, non-Hispanic whites received 65.93 percent of prime loans that was higher than their portion of households (55.97 percent). Asians were overrepresented in prime loans (10.44 percent of prime loans versus 4.14 percent of households).

72 The AI committee acknowledges a few important points associated with Home Mortgage Disclosure Act analysis. 1. Credit scores are not considered in HMDA analyses.2. Factors that are often associated with high-cost loans:  Credit scores  Sparse credit history (can be an issue for immigrants)  Small loans (often associated with less expensive and smaller housing or piggyback loan)  Manufactured Housing  Age (i.e., very young or elderly tend to have higher interest loans)  High debt to income ratios  High loan to value ratios  Small down payment amounts  Refinancing (when cashing out of equity) 73 The State hired Southwest Fair Housing Council to be the primary contractor and they contracted with the National Community Reinvestment Council on behalf of the state. This report is largely un-edited except for formatting to be consistent with the balance of the AI.

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 49 of 196

74 Chart 3-1a – Derived from data in Table 1a

In Table 3-2a (see corresponding Chart 2a), all low- and moderate-income (LMI) non- Hispanic whites, Hispanics, and African Americans received a higher portion of high-cost loans than their portion of prime loans during 2008. However, the difference was worse for Hispanics, and African Americans. Almost 18 percent of the high-cost loans were issued to LMI Hispanics while just about 4 percent of the prime loans were issued to LMI Hispanics. Similarly, LMI African Americans received less than one percent of prime loans and almost 5 percent of high- cost loans. In contrast, LMI non-Hispanic whites received more than 7 percent of prime loans and about 10 percent high-cost loans. (Note: Census data does not break out Hispanic households by income level so we are unable to compare the share of loans by income level to the share of Hispanic households by income level. We are able to compare the share of loans by income level to the share of households by race and income level since Census data does break out households by income level for each race).

Chart 3-2a – Derived from data in Table 2a

74 All references to the data tables in this section can be found in Appendix H

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 50 of 196

Table 3-3a (see corresponding Chart 3a) likewise reveals a disproportionate amount of high-cost loans received by middle- and upper-income (MUI) Hispanics and MUI African Americans. MUI Hispanics received approximately 16 percent and about 9 percent of high-cost and prime loans, respectively. In contrast, MUI non-Hispanic whites received 56.7 percent and 32.8 percent of prime and high-cost loans, respectively.

Chart 3-3a – Derived from data in Table 3a

Substantially minority neighborhoods received a disproportionate amount of high-cost loans as shown by Table 4a of the tables displaying conventional lending by minority level of neighborhood. Substantially minority neighborhoods with 50 to 79 percent of the residents being minority contain about 18 percent of the owner-occupied housing units and received more than 24 percent of the high-cost loans. In contrast, neighborhoods with 20 to 49 percent of minorities received a portion of high-cost loans (37.12 percent) that was almost equal to their portion of owner-occupied units (37.18 percent). These mixed racial neighborhoods (neighborhoods with 20 to 49 percent of minorities) received a portion of prime loans (42.28 percent) that was greater than their portion of high-cost loans and owner-occupied units.

Market Share Analysis of All Conventional Single Family Lending in Houston Galveston, Texas.

Appendix H Table 1b (see corresponding Chart 3-1b) shows market share ratios in Houston Galveston that are not controlled for income. The table reveals that Hispanics are 2.86 times more likely than non-Hispanic whites to receive a high-cost loan (divide 30.2 percent for Hispanics by 10.6 percent for non-Hispanic white borrowers). Similarly, African Americans are 2.76 times more likely to receive a high-cost loan than non-Hispanic white borrowers.

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Chart 3-1b – Derived from data in Table 1b

In Appendix H Table 2b (see corresponding Chart 3-2b), LMI Hispanics are almost twice as likely to receive a high-cost loan as LMI non-Hispanic whites. LMI African Americans are 2.25 times more likely to receive a high-cost loan compared to LMI non-Hispanic white borrowers (the ratio is calculated by dividing 45.5 percent of loans being high-cost for LMI African Americans by 20.2 percent of loans being high-cost for LMI non-Hispanic whites).

Chart 3-2b – Derived from data in Table 2b

Appendix H Table 3b (see corresponding Chart 3-3b) shows that MUI Hispanics are 2.58 times more likely to receive a high-cost loan than MUI non-Hispanic whites (divide 23.9 percent of the loans being high-cost for MUI Hispanics by 9.3 percent of the loans being high-cost for MUI non-Hispanic whites). MUI African Americans are 2.54 times more likely to receive a high-cost loan than MUI non-Hispanics whites (divide 23.6 percent of the loans being high-cost for MUI African Americans by 9.3 percent of the loans being high-cost for MUI non-Hispanic whites). Ethnic and racial disparities in lending increase as income levels increase. The disparity ratio is higher when comparing MUI Hispanics and MUI African Americans to MUI non-Hispanic whites than when comparing LMI Hispanics and LMI African Americans to LMI non-Hispanic whites.

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 52 of 196

Chart 3-3b – Derived from data in Table 3b

Residents of minority neighborhoods are much more likely than those of predominantly white neighborhoods to receive high-cost loans. Table 4b of conventional lending by minority level of neighborhood shows that residents of substantially minority neighborhoods (50 to 79 percent minorities) are 2.1 times more likely to receive high-cost loans than residents of neighborhoods with less than 10 percent minorities (divide 20.3 percent of loans being high-cost in substantially minority neighborhoods by 9.7 percent of the loans being high-cost in neighborhoods less than 10 percent). Likewise residents of predominantly minority neighborhoods are 3.56 times more likely than predominantly white neighborhoods to receive high-cost loans.

Conventional Denial Disparity Analysis.

The overall denial rate (Appendix H Table 1c, see Chart 3-1c) is about 29 percent in Houston Galveston. The denial rate for non-Hispanic white individuals is about 20 percent, whereas the denial rates for the African Americans and Hispanics are 50.23 percent and 42.61 percent, respectively. African Americans and Hispanics are 2.5 and 2.13 times more likely, respectively, than non-Hispanic whites to be denied a loan.

Chart 3-1c – Derived from data in Table 1c

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 53 of 196

LMI African American borrowers have a denial rate of 58.12 percent for loans that is about 15 percentage points higher than the overall denial rate for all LMI loan applicants of 42.64 percent (Appendix H Table 2c, see Chart 3-2c). LMI Hispanic borrowers have a denial rate of about 48 percent which is higher than the overall denial rate for all LMI loan applicants. In contrast, LMI non-Hispanic white borrowers experience denial rates 11 percentage points lower than the overall denial rate.

Chart 3-2c – Derived from data in Table 2c

Among MUI individuals (Appendix H Table 3c, see Chart 3-3c), Hispanic and African American borrowers experience denial rates noticeably higher than those of non-Hispanic whites. MUI African Americans have a denial rate of 46.25 percent in contrast to MUI non-Hispanic whites with a denial rate of 17.86 percent. MUI African Americans are therefore 2.59 times more likely to be denied than MUI non-Hispanic whites. MUI Hispanics have a denial rate of 38.08 percent and therefore 2.13 times more likely than MUI non-Hispanic whites to be denied. Ethnic and racial disparities in denials increase as income levels increase.

Chart 3c – Derived from data in Table 3c

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 54 of 196

Residents of substantially minority neighborhoods (50 to 79 percent minorities) are 1.83 times more likely than residents of white neighborhoods (less than 10 percent minorities) to be denied loans. More than 35 percent of the applicants from substantially minority neighborhoods are denied loans in contrast to about 19 percent of the applicants from white neighborhoods.

Portfolio Share Analysis of All FHA Single Family Lending in Houston Galveston, Texas.

NCRC expanded the Houston Galveston analysis to include information on FHA lending. FHA loans are guaranteed by the Federal government, specifically the Federal Housing Administration (FHA). Borrowers pay an upfront premium and an annual premium to help fund FHA insurance. The FHA insurance covers the costs of defaults. In other words, the government, through FHA fees on borrowers, covers the costs of defaults. In contrast, conventional lending involves lenders themselves absorbing the costs of defaults. Often, lending institutions will protect themselves against loss by requiring borrowers to pay for private mortgage insurance.

The total number of FHA loans was smaller than total number of conventional loans in Houston Galveston in 2008. Lenders issued 18,759 prime FHA loans and 55,609 prime conventional loans, and 3,647 high-cost FHA loans and 9,357 high-cost conventional loans during 2008 in Houston Galveston.

What is particularly relevant for our analysis is whether minorities are much more likely relative to non-Hispanic whites to receive high-cost FHA loans. FHA lending has not been saddled with the abusive tricks, traps, and fees of many subprime loans. Yet, it remains the case that FHA loans are more expensive than conventional loans. If minorities receive a disproportionate amount of high-cost FHA loans and/or prime FHA loans relative to conventional loans, stakeholders should take steps to increase the amount of conventional lending to minorities.

Appendix Table 1a (see corresponding Chart 3-1.1a) for FHA lending shows that Hispanics have a high ratio of high-cost FHA loans compared to the percentage of households. With about 21 percent of the households in Houston Galveston, Hispanics received 30.34 percent of high-cost FHA loans. The share of high-cost FHA loans for Hispanic was 1.42 times greater than their share of households in Houston Galveston in 2008. Hispanics also received a higher share of prime FHA loans (26.08) than their share of households (21.34 percent). It should also be noted that Hispanics received a higher share of prime FHA loans than prime conventional loans (26.08 percent versus 14.41 percent) during 2008.

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Similarly, African Americans received a higher share of high-cost FHA loans than high-cost conventional loans (16.87 percent versus 12.62 percent), and also a higher share of prime FHA loans than prime conventional loans (16.87 percent versus 5.31 percent). Since FHA loans are more expensive than prime loans, stakeholders should increase their efforts to make prime conventional loans to Hispanics and African Americans.

In contrast to Hispanics and African Americans, non-Hispanic whites received a share of high- cost FHA loans (of 42.95 percent) that were lower than their share of households (of 55.97 percent) in Houston Galveston. In contrast to African Americans and Hispanics, non-Hispanic whites received a higher share of prime conventional loans (65.9 percent) than prime FHA loans (49.2 percent).

Chart 3.1.1a – Derived from data in Chart 1a

Appendix H Table 2a (see corresponding Chart 3-1.2a) for FHA lending shows that both LMI non-Hispanic whites and Hispanics received disproportionate amounts of high-cost FHA loans. About 10 percent of the high-cost FHA loans were issued to LMI non-Hispanic whites and 7.95 percent of the prime FHA loans were issued to LMI non-Hispanic whites. Similarly, 12.9 percent of the high-cost FHA loans were issued to LMI Hispanics and 8.92 percent of the prime FHA loans were issued to LMI Hispanics.

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 56 of 196

Chart 3-1.2a – Derived from data in Table 2a

Appendix H Table 3a (see corresponding Chart 3-3.3a) shows disparities in high-cost FHA lending for middle- and upper-income borrowers. MUI Hispanics, for example, received 14.8 percent of prime FHA loans which was similar to their share of high-cost FHA loans (15.27 percent). MUI African Americans received a share of prime FHA loans that was 2.5 percentage points lower than their share of high-cost FHA loans. In contrast, MUI non-Hispanic whites received a share of prime FHA loans that was 6.4 percentage points greater than their share of high-cost FHA loans.

Chart 3-3.3a – Derived from data in Table 3a

Market Share Analysis of All FHA Single Family Lending in Houston Galveston, Texas –

The overall market share ratio (Appendix H Table 1b, see Chart 3-1.2b) shows that 20.1 percent of the loans received by African Americans and 18.7 percent of the loans received by Hispanics are high-cost FHA loans while 14.7 percent of the loans received by non-Hispanic whites were high-cost FHA loans. Thus, Hispanics are 1.37 times and African Americans are 1.27 times more likely to receive a high-cost FHA loan than non-Hispanics whites.

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 57 of 196

Chart 3-1.1b – Derived from data in Table 1b

LMI Hispanics are 1.12 times more likely to receive a high-cost FHA loan than LMI non- Hispanic whites, and LMI African Americans are 1.15 times more likely to receive a high cost FHA loan than LMI non -Hispanic whites (Appendix Table H Table 3-1.2b, see Chart 2b).

Chart 3-1.2b – Derived from data in Table 2b

MUI African Americans are 1.44 times more likely to receive high-cost FHA loans and MUI Hispanics are 1.24 times more likely to receive high-cost FHA loans when compared to their non-Hispanic white counterparts (Appendix H Table 3b, see Chart 3b). Thus, the trend of increasing ethnic and racial disparities as income levels increase are observed with high-cost FHA lending as in high-cost conventional lending.

Chart 3-1.3b – Derived from data in Table 3b

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FHA Loan Denial Disparity Analysis.

The overall denial rate for all FHA loans (Appendix H Table 1c, Chart 3-1.1c) in Houston Galveston is 19.35 percent. The denial rate for non-Hispanic whites is lower at 14.68 percent. The denial rate for Hispanics (21.95 percent), Asians (19.74 percent) and African Americans (25.89 percent) are all higher than the overall denial rate. African Americans are 1.76 times more likely than non-Hispanic whites to be denied an FHA loan during 2008 in Houston Galveston.

Chart 3-1.1c – Derived from data in Table 1c

The overall denial rate for LMI individuals (Appendix H Table 2c, Chart 3-1.2c) is 24.55 percent, with the denial rate for LMI non-Hispanics whites being 19.49 percent, LMI Hispanics being 25.07 percent, and LMI African Americans being 29.83 percent. LMI African Americans are 1.53 times and LMI Hispanics are 1.29 times more likely than LMI non-Hispanic whites to be denied an FHA loan.

Chart 3-1.2c – Derived from data in Table 2c

MUI non-Hispanic whites experienced a denial rate of 13.45 percent whereas MUI Hispanics and MUI African Americans had a denial rate of 19.57 percent and 23.6 percent, respectively for

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 59 of 196

FHA loans. MUI Hispanics were denied 1.46 times and MUI African Americans were denied 1.76 times more often than MUI non-Hispanic whites for FHA loans. Both FHA lending and conventional lending share the same trend that ethnic and racial disparities in denials increase with income levels (See Appendix H Table 3c, Chart 3-1.3c).

Chart 3-1.3c – Derived from data in Table 3c

Summary and Conclusions.

 In Houston Galveston, the portions of all prime conventional loans received by Hispanics (14.41 percent of prime loans versus 21.34 percent of households) were lower than the loans received by non-Hispanic whites (65.93 percent of prime loans versus 55.97 percent of households) compared to their portions of households.

 In Houston-Galveston region, Hispanic households received a lower share of prime conventional loans than non-Hispanic whites. Hispanics own 21.34 percent of the homes and only hold 14.41 percent of all prime conventional loans, while non-Hispanic whites own 55.97 of the homes and hold 65.93 percent of the prime loans.

 Similarly, the portion of all prime loans received by African American borrowers was also lower than the loans received by non-Hispanic white borrowers compared to their portion of households.

 Hispanics are 2.86 times more likely than non-Hispanic whites to receive a high-cost loan and African Americans are 2.76 times more likely to receive a high-cost loan than non- Hispanic white borrowers.  MUI Hispanics are 2.58 times more likely to receive a high-cost loan than MUI non- Hispanics whites. LMI Hispanics are 1.97 times more likely to receive a high-cost loan than

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 60 of 196

LMI non-Hispanic whites during 2008. Ethnic disparities in conventional lending increase as income levels increase in Houston Galveston.

 MUI African Americans are 2.54 times more likely to receive a high-cost loan than MUI non-Hispanics whites. LMI African Americans are 2.25 times more likely to receive a high- cost loan compared to LMI non-Hispanic white borrowers. Racial disparities in conventional lending increase as income levels increase.

 The denial disparity ratio is higher when comparing MUI Hispanics and MUI African Americans to MUI non-Hispanic whites than when comparing LMI Hispanics and LMI African Americans to LMI non-Hispanic whites. Ethnic and racial disparities in denials increase as income levels increase.  Hispanics received a higher share of prime FHA loans than prime conventional loans (26.08 percent versus 14.41 percent) in Houston Galveston. Also, with 21.34 percent of the households in Houston Galveston, Hispanics received 30.34 percent of high-cost FHA loans during 2008. The trends were the same for African Americans. Since FHA loans are more expensive than prime loans, stakeholders should increase their efforts to make prime conventional loans to Hispanics and African Americans.

 Hispanics are 1.37 times and African Americans are 1.27 times more likely to receive a high- cost FHA loan than non-Hispanics whites.

 Ethnic and racial disparities are observed in both conventional and FHA lending, and also in denying applications for both conventional and FHA loans. Stakeholders should take steps to narrow disparities in both conventional and FHA lending.

Concentration and Racial Segregation.

The demographic materials in Appendix D show a clear pattern of concentration based on racial classification. For instance when you look at City of Houston the population is 30.8 percent Non Hispanic White. In looking at the dissimilarity index 60.46 percent Hispanics and 75.20 percent of blacks would need to move to make the city racially integrated.75 Compare this with the City of Lake Jackson where the population is 77 percent Non Hispanic White and has a dissimilarity

75 Appendix D category of communities 50K+ data and maps.

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 61 of 196 index of 30.24 percent for Hispanics and 29.44 percent for Blacks demonstrating a relatively integrated community.76

The materials provide communities with a way to target concentrations of racial classes by providing individuals the ability to relocate using disaster recovery funds and, in entitlement communities, HOME and CDBG dollars.

Maps of Houston show a significant concentration of minorities exceeding 65 percent in most of the community while other areas show less than a 35% minority concentration indicating segregated neighborhood blocks.77 Contrast that with the Lake Jackson map that show no areas where the racial concentration is greater than 65%.78 In the Housing Guidelines for Round 2 funds, Houston would be a community that could and should be targeted for Round 2 disaster recovery funds for the Homeowner Opportunity Program. This program will assist in allowing qualified applicants in the most heavily concentrated areas for race and poverty federal assistance in moving out of these areas into high opportunity or more racially diverse areas.

A challenge that is currently facing Houston is the proliferation of high cost apartments and condominiums displacing affordable housing in traditionally lower income and more affordable areas—a process known as gentrification.79 Frequently these areas are near downtown or on the edge of otherwise desirable areas. When a large influx of expensive homes comes in, it has the effect of increasing land costs and taxable values on existing homes. Where elderly or low income person own these homes, they are sometimes forced out because of the increased costs, especially taxation, to live in the home. In other cases where the tenant rents, the land becomes more valuable and results in either rental increases or a sale of property, either way likely displacing the low income tenant with limited choices available.

This information is provided for communities to use in planning how to address concentration patterns in spending federal funds. Each community over 10,000 has maps available to it that highlight racial makeup of their community by census tract.

76 Appendix D category of communities between 25,000 and 49,999 data and maps. 77 Appendix D category of communities 50K+ data and maps. 78 Appendix D category of communities between 25,000 and 49,999 data and maps. 79 City of Houston Analysis of Impediments April 2010.

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Not In My Backyard—The impediment of NIMBYism.

The concept of NIMBYism can be summarized by citizen opposition to development (infrastructure or housing) simply because the residents are reluctant to have new development in their community. NIMBYism often manifests itself at public hearings and meetings where residents come together and express their opinions related to potential affordable housing or infrastructure projects like sewage treatment plants, waste disposal facilities or similar community necessary projects. NIMBYism is often represented by small numbers of citizens with strong opinions who are very vocal and organized, and do not necessarily represent the majority of local public opinion.

Currently the City of Galveston is undergoing a strong resident reaction to rebuilding public housing in the community. However, the Galveston City Council has voted to move forward and restore public housing twice – by allocating $25 million in funding during Round 1 and by passing a resolution requiring the rebuilding of 569 public housing units and instructing the Galveston Public Housing Authority to prepare a redevelopment plan for City Council approval. Thanks to strong leadership from the Galveston Mayor locally and the State requiring the units to be built as part of the Conciliation Agreement, this effort to stop public housing does not look like it will be successful.80 Another example of NIMBYism occurred at a public hearing to discuss multifamily development within the impacted area.. A recent exchange between residents and a developer was reported in the local newspaper as:

“(Our demographers) indicated that the number of students that come out of these types of developments are far more than a standard, normal apartment, and that’s the stand that we have taken.” [school district representative]

A resident and former HOA board member from the area, asked residents if they knew that more than $250,000 of their property dues each year is spent to pay for facilities.

“The apartment people pay zero – that means we have to pay for transients or people who do not have a vested interest in this community as we do,” he said. “There’s a bond for additional things that we don’t have the money for right now. Yet, they want

80 See, Galveston Daily News, October 29 and October 14, 2010

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to bring in 250 families who can’t afford to pay for their homes or any of the taxes that’s needed to support our community.

“That’s a bad idea folks,” she told the crowd. “Ask the right questions. Don’t get upset with these people up here who are doing their jobs. Your job, as a community, is to stand up and say, ‘Hell no.’” 81

As the developer has withdrawn its application to TDHCA, this NIMBYism effort has already been successful. These are examples of hearings where local residents raised concerns about how low income housing might impact their schools (overcrowding), traffic (increase), property values (lower) and crime rates (increase). Issues relating NIMBYism were raised in the focus groups, a summary of which can be found by region in Appendix F.

It is important to note that despite occurrence of NIMBYism, 70,630 multifamily housing units have been constructed in the H-GAC region over the past 3 years.82

Discrimination in Housing Markets.

No direct testing of the real estate industry was done as part of this AI. However, participants in the focus groups identified a pattern of discrimination in private sector real estate markets toward racial minorities. A report by the National Fair Housing Association provided information on the treatment of the minority testers they sent to look for rental units in 17 cities spread across 5 states. Although not specifically listed as a problem city, Houston is included in the list of tested cities.83 The results of the 2005 undercover professional test groups of representative races was that the black testers were less likely to be told about available units, called back, or shown properties than their white test group counterparts enough times to be statistically relevant to the report.84 The Houston AI cites a study by the Greater Houston Fair Housing Center that found in conducting a similar test using minority applicants for rental facilities that the African American testers “encountered differential treatment 80% of the time when they responded to [an]

81 Breaking News: Gardens on Kingsland withdraws TDHCA application, Residents voice opposition to low-income apartments by Tracy Dang, Thursday October 28 2010,Katy Times 82 http://recenter.tamu.edu/data/bp/bpc/cnty481.asp by permits issued for years 2007-2009 83 No Home for the Holidays—Discrimination for Katrina Evacuees 2005, National Fair Housing Alliance 84 Ibid

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 64 of 196 advertisement about rental housing in Houston.”85 The potential discrimination is not just limited to rental markets.

Although not including communities within the scope of this Phase I AI, another report by the National Fair Housing Alliance titled Dr. King’s Dream Denied: Forty Years of Failed Federal Enforcement provides a national context for fair housing issues –and found that “in the twelve metropolitan areas investigated to date, NHFA’s testing revealed discriminatory steering practices and illegal behaviors that are both striking and pervasive.86 The Justice Department has settled a lawsuit for $120,000 with a major real estate firm in Chicago related to steering of minority clients toward minority neighborhoods and away from Non Hispanic White neighborhoods.87

Collectively, even if not all in this area, it supports the concept that steering creates an impediment to integrated housing patterns. There has been no state testing since Hurricanes Ike and Dolly to confirm the pattern is true and that in itself could be an impediment to Fair Housing. Failure to enforce the laws already written should be reviewed.

Policies Restricting Person in Flood Zones.

During Hurricane Ike Round 1, housing guidelines were established by the City of Houston that restricted the use of funds by persons in floodplains.88 While the goal of not rebuilding in most floodplains may be practical, limiting access to disaster recovery funds intended to mitigate flood hazards both frustrates the purpose of these funds and will potentially have a disproportionate impact on members of protected classes. Regulating or limiting rebuilding in most floodplains is well accepted. However, governments should consider providing other housing options for residents that could include allowing them to move out of a floodplain into a safer environment or mitigating flooding rather than denying residents any disaster recovery assistance. These types of restrictions should be evaluated to determine if this policy more severely impacts people of color due to existing housing patterns.

85 City of Houston Analysis of Impediments April 2010 at page 19. 86 titled Dr. King’s Dream Denied: Forty Years of Failed Federal Enforcement, National Fair Housing Alliance April 8, 2008. 87 Justice Department Obtains $120,000 Discrimination Lawsuit Against Chicago Area Realtors, Feb. 18, 2009 retrieved from http://reuters.com/article/idUS202030+18-Feb-2009+PRN20090218 88 City of Houston Housing Guidelines, Hurricane Ike Recovery Round 1, 2009.

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Lack of Knowledge about what Constitutes Fair Housing Violations.

In addition to the real estate steering and rental discrimination, the focus groups indicated that the Fair Housing Act remains a mystery to many. Even clearer is that not many people even if they believe they are being discriminated against know how to take action to file a complaint or report the violation. In Appendix C of this document, all the housing discrimination complaints filed with HUD are listed by county. The H-GAC region has more than five million people living in the community. During interviews in focus groups in the Houston and Galveston areas, the individuals participating in the focus groups raised housing discrimination issues and yet from January 2005 through September 2010 only 750 complaints were made to HUD from this region. In addition, the Texas Workforce Commission received 692 complaints in the total hurricane impacted region (61 counties). Of those, 432, or 62.4 percent were from Harris County. In an indication that the public may not understand the issues, of the 692 complaints 323 of them received findings of “no cause.”89

Looking at Project Placement.

In reviewing the projects contained in Appendix F, two issues become obvious. Most CDBG funds, when not including disaster funds, whether supplied by the State or used by entitlement communities go to infrastructure projects. The difficulty of determining how the funds are spent is compounded by the manner in which data is reported. Looking at the table very few infrastructure projects have a clear delineation of whom they are directly serving and where the project is located. Without an ability to reference the population served (other than the generic 51 percent plus LMI language), it is difficult to determine who is receiving the benefit of the projects. Because so many of the regular CDBG funds are listed in this manner at both the entitlement jurisdiction and the State the information is not useable to determine if a community is using funds to further fair housing.

In addition, in reviewing Appendix F, very little of non-disaster CDBG funds go to housing. In part this may be because funds may be used to address substantial infrastructure needs (especially with regard to wastewater and drinking water projects in rural areas and small cities). A state or local preference for infrastructure use may have been present, but the CDBG Action

89 Housing Discrimination Complaints Section 7. herein.

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Plan has a policy that says it supports the use of CDBG funds for the construction of housing. The highly competitive nature of the limited CDBG funding for non-entitlement communities directly factors into the use of funds. Despite the CDBG Action Plan expressed support for building housing with CDBG funds, competitive applications rounds should be reviewed to see if they favor infrastructure over housing in scoring.

To underscore the support expressed by the TDRA GDBG Action Plan that housing be considered in the use of CDBG funds, future rounds of funding should include serious consideration of housing as a priority by each Regional Review Committee as they establish funding priorities and scoring criteria.

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SECTION 4. GOLDEN TRIANGLE AND SURROUNDING COMMUNITIES.

The area referred to as the Golden Triangle is an area where the development of the petrochemical industry and the development of communities surrounding and interwoven with that complex is central, to what it is. As you move inland from the Gulf Coast, however, the area very quickly becomes typical of rural East Texas. So much of the area is urban, much is industrial, and much has a rural character. This section is not intended to provide a complete AI for each community in the Golden Triangle area. In fact, some communities in the region may find more in common with the small community section where the focus is on cities of less than 2,500 and provides more similar conditions to what they are facing and looks at similar ways to overcome Fair Housing impediments.

This area has size differences between communities, but they share a lot of similar interests including what has now been more than five years of disaster recovery beginning with their support of Hurricane Katrina evacuees before becoming themselves the victim of the devastating Hurricane Rita and then Hurricane Ike.

While the region does not have a large urban population like its nearby neighbor Houston, it does have approximately 400,000 people that call the region home. The community has a strong presence in refineries, colleges, and other industries.

This section will more clearly develop the local demographic information and look at potential impediments to Fair Housing that exist in the area.

Historical Recap.

Located along Texas’ Gulf Coast, Southeast Texas is a geographic, economic, and cultural sub region encompassing Hardin, Jefferson, and Orange Counties. The major metropolitan areas within this region, Beaumont, Port Arthur and Orange, are collectively referred to as the “Golden Triangle.” Culturally the region is said to have Cajun, Louisiana Creole, and rural southern influences, particularly in regards to dialect, mannerisms, religion, and cuisine.

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The Beaumont-Port Arthur Metropolitan Statistical Area (MSA) is the largest in the region. Beaumont traces its roots to ranching and farming settlements eventually establishing itself as a town in 1835.90 Beaumont got its big start more than 100 years ago. It was named after Mary Dewburleigh Barlace Warren Beaumont, the wife of businessman Henry Millard. Beaumont officially became a town on December 16, 1838, and was a center for cattle raisers and farmers in its early years.

In the late 1800s, Beaumont became an important lumber and rice-milling town. Because Beaumont is strategically-located on the Neches River and had an active river port, the city was ideally positioned to capitalize on the lumber boom of the late 19th century. The city helped ship lumber across the country, most importantly to help rebuild the railroads after the Civil War. The first commercial rice mill in Texas, the Beaumont Rice Mill, was also founded during this period in Beaumont's history.

On January 10, 1901, the Lucas Gusher on Spindletop Hill exploded, shooting oil hundreds of feet in the air. The explosion was so intense that nine days later the oil column was still gushing nearly 200 feet high, producing around 100,000 barrels a day.

The Lucas Gusher dramatically displayed the natural resource that lay below Beaumont. Within a few days of the Lucas Gusher explosion, over 40,000 curious sightseers, speculators and job- seekers descended on Beaumont. Restaurants, hotels and retail establishments were overwhelmed as the city's population grew from 9,000 in January 1901 to 30,000 in March 1901, leading to a Texas-sized building boom.

Over the next few years, dozens of oil companies were chartered. Six wells were erected on Spindletop Hill, helping make the US the world's leading petroleum-producing nation. Spindletop became the first major oil field and the largest in American history, ushering in the Petroleum Age.91

The growth of the petroleum age also created other issues. In the neighborhood adjacent to the Beaumont Exxon Mobile refinery (the sixth largest in the US), 95 percent of residents are African American and 54 percent of those are at or below the poverty level (www.txpeer.com).

90 http://www.tshaonline.org/handbook/online/articles/BB/hdb2.html 91 http://www.beaumontcvb.com/about/history/

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These percentages are similar to other minority neighborhoods in the area.92 As mentioned by several interviewees, environmental pollution is a major problem and may be a major factor in “white flight” from the downtown and other areas of Beaumont and Port Arthur. The Beaumont Exxon Mobil Complex is consistently in the nation’s top ten percent of worst polluting refineries and chemical plants. Emissions are around 385 percent above the state’s refinery average. African American communities near refineries are disproportionately burdened by environmental impacts due to lack of enforcement of environmental laws. As a result, there have been many violations of Title VI of the 1964 Civil Rights Act.93

Since 2005, natural disasters have taken center stage and impacted the area greatly. Following Hurricane Katrina in 2005 many Texas communities welcomed Katrina evacuees from nearby Louisiana. Many of the evacuees were people of color. Some evacuees settled in the East Texas town of Vidor. To some, this was surprising. Vidor is a small city of about 11,000 people near the Texas Gulf Coast. There are very few blacks there; it’s mostly white. That is in large part because of racism in Vidor, a past that continues to haunt the present. “We’ve been trying to live down something for 40 or 50 years,” said Orange County Commissioner Beamon Minton. “Once convicted, you’re a convicted felon. You can’t ever put that aside.” Vidor was one of hundreds of communities in America known as “sundown towns”, places where blacks were not welcome after dark. In some of these towns, signs –handwritten or printed—were posted, saying things like “Whites Only After Dark.” But in general, sundown towns existed by reputation. Blacks knew they were places to avoid after dark.94 Vidor also had a reputation as a haven for the Ku Klux Klan.95 Issues with the Klan date back as early as the 1920’s. In the 1990’s, after four black families moved into a public housing complex, Klansmen in full regalia staged marches, cross-burning and fund-raising to “Keep Vidor White”. The families soon moved away.96 While perceptions persist, the Vidor community’s actions following Hurricane Katrina give indication that things are changing. In an article written just short of a month after the landfall of Hurricane Katrina, a reporter for the Waterbury Republican-American states that a number of Vidorians see in this unprecedented disaster more than just an opportunity to help people in need; to many this is a chance to make amends for the wrongs of the past, to change

92 www.txpeer.org 93 ibid 94 CNN U.S. December 8, 2006 Keith Oppenheim CNN, http://articles.conn.com/2006-12-08/us/oppenheim.sundown.town_1_vidor-black-families-klan- rally?_s=PM:US 95 Ibid 96 Waterbury Republican-American September 26, 2005 Todd Lewan (A.P.), http://www.freerepublic.com/focus/f-news/1491470/posts

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 70 of 196 the way insiders and outsiders view this community. It’s an opportunity Vidor can’t let slip away, says Carl Thibodeaux, a Louisiana native who came to East Texas 34 years ago. He’s now the Orange County Judge, which makes him the area’s chief official. “The racist stigma,” says Thibodeaux, who is white, “has been here too long.”97 During the Hurricane Katrina disaster, citizens of Vidor stepped up to offer help. Folks opened their doors to Katrina’s victims. “We took in lots of people of color,” said Wendy Harris, a 36-year-old mother of two. Positive feedback was garnered from many black evacuees who received help. Trisha Reaux says, “We’ve been completely accepted with open arms.” Melvin Bahan, 47, a baker from New Orleans, goes farther: “The people of Vidor have shown us nothing but love – the true love of God.” Mr. Bahan went on to say “The people here told me all about the racial problems Vidor has had. They didn’t hide nothing; came right out an told us. Truth, that’s what they gave us. I appreciate that.98

Shortly after the Katrina evacuees arrived, the area suffered a significant hurricane event with Rita. The damage was extensive99 and recovery programs are only now being completed five years after the event.100 The evacuation caused major delays and took significant time to return persons who were displaced during the storm. In 2008, another hurricane event—Hurricane Ike—caused additional damage and has resulted in billions of dollars of damage.

Regional Demographic Recap.

The Golden Triangle is represented by the Southeast Texas Regional Planning Commission (SETRPC). SETRPC is located within TDHCA Region 5101 The three counties are Jefferson, Orange and Hardin and are considered to be an MSA. Jefferson County is the largest of the communities with more than 242,000.102 Beaumont, located in Jefferson County, is the largest city in the area with an estimated population of 112,210.103

97 Ibid 98 Ibid 99Texas Rebounds, Hurricane Rita 2005, by State of Texas Office of the Governor 100 TDHCA, Report to the Governing board, 12-17-2010, www.tdhca.org 101 Region 5 is the Texas Comptroller’s 13 Uniform State Service Regions of Texas and the primary way funds are distributed to non-entitlement communities by TDHCA based on a Regional Allocation Formula as required under Texas Government Code § 2306.1115. Many of the demographic references are related under the Region 5 banner. Where possible, data has been corrected to include only the three counties. 102 American FactFinder Jefferson County, Texas 2006-2008 Community Survey 3-Year Estimates, U.S. Census Bureau retrieved at http://factfinder.census.gov 103 American FactFinder Beaumont city, Texas 2006-2008 Community Survey 3-Year Estimates, U.S. Census Bureau retrieved at http://factfinder.census.gov

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Population.

The Golden Triangle is not expected, compared to other parts of Texas, to experience significant growth between now and 2040 according to the state demographers at the University of Texas at San Antonio. Under the Zero Net Migration formula (0.0 Scenario) unlike other parts of Texas, the Hispanic population grows only slightly and the racial make-up of the community remains roughly the same as it is currently with a slight movement toward a larger minority population by 2040. Assuming rates of net migration equal to one-half of 1990-2000 totals (0.5 Scenario) the Hispanic population grows significantly changing the area to a majority minority population by 2040.104

Table 4-1 Projected Population SETRPC Region Non Year Hispanic Black Hispanic Other Total White

2000 248,509 95,835 30,832 9,914 385,090 Non Non Hispanic Hispanic Black Black Hispanic Hispanic Other 0ther Total Total Year White White 0.0 0.5 0.0 0.5 0.0 0.5 0.0 0.5 0.0 0.5 Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario scenario Scenario

2010 248,931 242,373 101,384 103,655 35,477 43,069 11,353 13,573 397,115 402,670

2020 246,724 232.988 105,656 110,319 40,022 59,879 17,884 357,448 404,963 421,070

2040 228,207 197,648 105,616 114,178 47,392 108,198 13,726 27.602 394,941 447,626

Age.

Table 4-2 shows the population’s anticipated aging according to the demographers located at the University of Texas at San Antonio for the SETRPC Region. This table demonstrates that the percentage of the population who is over sixty five will increase in raw numbers within the age category and as a percentage of the population as a whole.105 The 2040 data assumes rates of net migration equal to one-half of 1990-2000 (.5 Scenario) and is neither the least nor the most conservative estimate by the demographers.

104 These projections assume the One-Half 1990-2000 Migration (0.5) Scenario. According to the State Demographer: This scenario has been prepared as an approximate average of the zero (0.0) and 1990-2000 (1.0) scenarios. It assumes rates of net migration one-half of those of the 1990s. The reason for including this scenario is that many counties in the State are unlikely to continue to experience the overall levels of relative extensive growth of the 1990s. A scenario which projects rates of population growth that are approximately an average of the zero and the 1990-2000 scenarios is one that suggest slower than 1990-2000 but steady growth. Information for Table 4-1 pulled from Table 2.7 Population for the State of Texas and Council of Government Regions in Texas and Projections to 2040 Assuming Alternative Projection Scenarios SETRPC Region data http://txsdc.utsa.edu/pubsrep/ 105 Table 2.14 Percentage of Population for the State of Texas and Council of Government Regions in Texas by Age and Race/Ethnicity of the Population and Median Age by Race/Ethnicity in 2000 and Projections to 2040 Assuming Alternative Projection Scenarios HGAC Region data http://txsdc.utsa.edu/pubsrep/

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Table 4-2 Age by Age Group and Race/Ethnicity Non Non Age Hispanic Hispanic Black Black Hispanic Hispanic Other Other Total Total Group White White 2000 2040 2000 2040 2000 2040 2000 2040 2000 2040

<18 23.3 17.2 31.8 19.9 33.5 25.7 32.0 19.2 26.5 19.0

18-24 8.5 6.8 11.0 8.9 13.2 10.5 10.4 7.0 9.5 7.8

25-44 27.9 24.7 28.9 28.8 35.1 28.4 34.7 23.2 28.9 26.2

45-64 24.2 27.1 18.9 27.7 13.5 21,2 17.9 25.0 21.9 26.5

65+ 16.2 24.2 9.4 14.7 4.7 14,2 5.0 25.6 7.9 20.5

Median 39.1 46.1 30.3 39.8 26.7 34.6 29.7 45.5 35.6 42.7

Poverty and Income.

The information on poverty presented below in the table is for the counties that are in the SETRPC region.

Table 4-3 SETRPC Poverty Figures, 2010

Families At or Above Poverty Families Below Poverty

County Number Percent Number Percent Hardin 13,601 88.5% 1,774 11.5% Jefferson 52,967 85.8% 8,802 14.2% Orange 21,425 88.4% 2,819 11.6%

Region 5 Household Incomes. The pie chart to the left depicts the income Extremely Low breakdown of the 274,543 households in Region 5 Income (0-30%), 14% as a whole. Approximately 43 percent of the Very Low Income (31%-50%), 12% Higher Income households are low income. There are 138,673 Low Income (over 95%), 50% individuals living in poverty in the region, which (51%-80%), 17% makes up 15.2 percent of the regional population. Moderate Income (81%-95%) , 7%

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Income levels for SETRPC/Golden Triangle are represented in the following table:

Table 4-4 SETRPC Household Income 80.1 % and 30% AMI or less 30.1-50% AMI 50.1-80% AMI above AMI Grand Total Hardin 155,333 137,987 209,282 702,549 1,205,151 Jefferson 13,849 11,508 14,616 52,840 92,813 Orange 4,074 3,365 5,419 18,781 31,639 Source: CHAS 2000.

Special Needs Populations

Some data for persons with special needs is only available at the state level. For example, the number of persons with alcohol and substance abuse is not maintained at TDHCA at the county level, so analysis could only be done at the state level. In addition, the regional number of public housing units, in which public housing residents live, is not included in the Special Needs Population section of each regional analysis because it is included in the Assisted Housing Inventory.

Homeless Persons.

According to 2010 population projections by Ribbon Demographics, Region 5 has approximately 2.3 percent of the statewide total of people in non-institutional group quarters, including shelters.

Table 4-5 Region 5 persons in other group quarters, 2010 Region 5 Homeless persons Hardin 23 Jefferson 845 Orange 122 Source: Nielsen Claritas, Ribbon Demographics, 2010.

Persons with Disabilities.

According to the U.S. Census, of the total population in SETRPC/Golden Triangle, persons with disabilities account for just under 20 percent of the population.

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Table 4-6 SETRPC Persons With Disabilities 2000

County Persons with a disability County Population Hardin 8,688 48,073 Jefferson 48,472 252,051 Orange 17,399 84,966 Source: Census 2000

Persons with HIV/AIDS.

According to the Texas Department of State Health Services’ 2010 Texas Integrated Epidemiologic Profile for HIV/AIDS Prevention and Services Planning, there are 1,334 persons living with HIV/AIDS in SETRPC. The area has a low rate of persons living with HIV/AIDS compared to the state as a whole, with the East Texas area accounting for only 6 percent of the total. The East Texas area has a rate of 147 persons per 100,000.

Table 4-7 Region 5 Persons with HIV/AIDS, 2008 County HIV/AIDS Number HIV/AIDS Rate Population 2008 Hardin 35 68 52,405 Jefferson 754 309 242,201 Orange 89 105 82,871 Source: Texas Department of State Health Services. 2010 Texas Integrated Epidemiologic Profile for HIV/AIDS Prevention and Services Planning: HIV/AIDS in Texas. Population from US Census Population Estimates, 2008. Note: Figures do not include those unaware of their HIV infection of those who tested HIV positive solely through an anonymous HIV test. Cases diagnosed at the Texas Department of Criminal Justice System are not attributed to a geographic area.

Migrant Farmworkers.

In a study prepared for the US Health Resources and Services Administration, SETRPC was found to have a very low proportion of the state’s Migrant and Seasonal Farmworker (MSFW) population in the State of Texas.106

Table 4-8 SETRPC/Golden Triangle Migrant and Seasonal Farmworker Population, 2000 Percent of statewide MSFW County MSFW Estimate population

Hardin 155 0.04% Jefferson 104 0.03% Orange 44 0.01%

106 HRSA Migrant Health Program 2000.

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Local Input on Housing Assistance.

According to the TDHCA Public Request Assistance Inventory for State Fiscal Year 2010, the agency received 180 public assistance requests from SETRPC. Of requests from SETRPC the three most requested categories of assistance were, in order: Rental Assistance, Repair and Weatherization, and Homebuyer Assistance.

Table 4-9

SETRPC/Golden Triangle Public Assistance Request Inventory, SFY 2010

Repair

Foreclosure

Legal Assistance Legal

Utility Assistance Utility Rental Assistance

Disaster Assistance Disaster Emergency Assistance Emergency Assistance Homebuyer Hardin 4 0 0 4 0 4 1 3 Jefferson 28 0 1 26 9 30 7 22 Orange 10 1 0 10 3 14 1 2 Total 42 1 1 40 12 48 9 27

Housing Assessment.

This housing assessment includes SETRPC current housing supply, a sample of market-rate housing costs, the housing needs and the availability of subsidized housing.

Housing Supply.

According to the 2010 projection, 83.3 percent of the housing units in the region are occupied. Of the total housing stock, 70.7 percent are one unit; 2.0 percent are two units; 11 percent are three or more units; and 17.4 percent are mobile homes. Boats and RVs make up the rest of the housing stock.

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Table 4-10 Region 5 Housing Supply, 2010 Hardin Co. Jefferson Co. Orange Co. Housing Units, 1 unit 14,855 14,855 14,855 Housing Units, 2 units 129 1,899 763 Housing Units, 3to 4 units 115 2,979 115 Housing Units, 5 to 19 units 534 10,714 534 Housing Units, 20-49 units 212 1,658 212 Housing Units, 50+ units 320 2,656 363 Housing Units, Manufactured Housing 5,657 3,415 7,007 Housing Units, Other units 100 94 154

Total Units 21,922 103,868 35,773 Source: Nielsen Claritas, Ribbon Demographics, 2010.

Sample of Market Housing Costs.

According to the Multiple Listing Service records for August 2010, the median home prices for Beaumont and Port Arthur are $124,300 and $110,000, respectively.107 In addition, the fair market rent for a two bedroom unit in Beaumont-Port Arthur MSA is $692, requiring an annual income of approximately $27,680.108

Housing Need.

The housing need indicators analyzed in this section include housing cost burden, substandard housing conditions and housing overcrowding for renter and owner households. The following information comes from the 2000 CHAS database updated with HISTA population projections. There were approximately 83,490 owners and renters with housing problems in 2009.

Table 4-11 SETRPC/Golden Triangle Households with Housing Problems, 2009 Units Lacking Complete Plumbing/Kitchen Total units 0-30% 31-50% 51-80% >80% NAME all incomes HAMFI HAMFI HAMFI HAMFI Texas 78,129 35,692 19,997 14,463 7,977 Hardin County 218 155 21 42 - Jefferson County 776 290 180 242 64 Orange County 229 86 65 54 24

Households with a Cost Burden >30% Total households 0-30% 31-50% 51-80% 81-95% NAME all incomes HAMFI HAMFI HAMFI HAMFI > 95%HAMFI Texas 1,493,227 562,331 370,229 292,093 76,387 192,187 Hardin County 2,535 1,300 623 346 104 162 Jefferson County 20,160 9,601 5,281 3,537 618 1,123 Orange County 5,201 2,562 1,516 798 121 204

107 Real Estate Center at Texas A&M University, “Texas Residential MLS Activity,” http://recenter.tamu.edu/data/hs/hs440b.htm (accessed September 24, 2010). 108 National Low Income Housing Coalition. (2010). Out of reach 2010. Retrieved from http://www.nlihc.org/oor/oor2010/

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Households that are Overcrowded Total households 0-30% 31-50% 51-80% 81-95% NAME all incomes HAMFI HAMFI HAMFI HAMFI > 95%HAMFI

Texas 469,895 116,809 96,455 113,821 40,778 102,032

Hardin County 657 171 114 151 65 156

Jefferson County 4,131 1,158 728 789 308 1,148

Orange County 1,297 278 215 242 109 453 Source: CHAS Database 2000.

Identification of Impediments to Fair Housing.

The Golden Triangle faces a many difficult challenges related to Fair Housing. During focus groups, many of the participants felt there was a residual negative impression based on the Young v. Martinez109 desegregation suit where the court found that 36 counties in East Texas were continuing patterns of segregation in public housing authorities. Some of the participants believed that there was more housing choice now for those who could afford it, but the physical delineation of the minority communities remains apparent throughout the Golden Triangle.

In addition, there are limited resources to rebuild from the impact of two severe hurricanes in the past five years. In many locations, despite the construction of almost 3,000 homes with federal funds, the area remains racially segregated in many parts.

The rebuilding process for public housing has been funded with HOPE VI funds, tax credits and disaster recovery funds. It is clear from looking at the maps in Appendix D that there is work to do in integrating communities. This section will look at some of the potential impediments to Fair Housing in the Golden Triangle.

109 Young. V. Martinez

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110 Home Mortgage Disclosure Act Analysis.

The State of Texas contracted with the National Community Reinvestment Coalition (NCRC) to conduct a portfolio and market share analysis using 2008 Home Mortgage Disclosure Act (HMDA) data for the Southeast Texas Regional Planning Commission (SETRPC) area. Hardin County, Jefferson County, and Orange County comprise The Golden Triangle.111

Portfolio Share Analysis of All Conventional Single Family Lending in Southeast Texas.

African Americans are the largest minority group in Southeast Texas, representing almost 23 percent of all households. Hispanics, Asians, and Native Americans combined account for about 7 percent of households in Southeast Texas. Appendix H Table 1a (see corresponding Chart 4- 1a) of the conventional lending report shows that the portion of all prime loans received by African American borrowers was lower than the portion of loans received by non-Hispanic white borrowers compared to their portion of households. African Americans received only 5.64 percent of prime loans that was considerably less than their portion of households (22.98 percent), while non-Hispanic whites received 83.1 percent of prime loans that was higher than their portion of households (69.2 percent). The portion of all prime loans received by Hispanic borrowers was also lower than the loans received by non-Hispanic white borrowers compared to their portion of households.

110 The AI committee acknowledges a few important points associated with Home Mortgage Disclosure Act analysis. 1. Credit scores are not considered in HMDA analyses.2. Factors that are often associated with high-cost loans:  Credit scores  Sparse credit history (can be an issue for immigrants)  Small loans (often associated with less expensive and smaller housing or piggyback loan)  Manufactured Housing  Age (i.e., very young or elderly tend to have higher interest loans)  High debt to income ratios  High loan to value ratios  Small down payment amounts  Refinancing (when cashing out of equity) 111 The State hired Southwest Fair Housing Council to be the primary contractor and they contracted with the National Community Reinvestment Council on behalf of the state. This report is largely un-edited except for formatting to be consistent with the balance of the AI.

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Chart 4-1a – Derived from data in Table 1a

In Appendix H Table 2a (see corresponding Chart 4-2a), both low- and moderate-income (LMI) African Americans and LMI Hispanics received a disproportionate amount of high-cost loans in contrast to LMI non-Hispanic whites during 2008. More than 6 percent of the high-cost loans were issued to LMI African Americans while just 1.12 percent of the prime loans were issued to LMI African Americans. Similarly, more than 3 percent of the high-cost loans were issued to LMI Hispanics while just 1.16 percent of the prime loans were issued to LMI Hispanics. In contrast, LMI non-Hispanic whites received almost 10 percent of prime and 14.7 percent of high- cost loans. (Note: census data does not break out Hispanic households by income level so we are unable to compare the share of loans by income level to the share of Hispanic households by income level. We are able to compare the share of loans by income level to the share of households by race and income level since census data does break out households by income level for each race).

Chart 4-2a – Derived from data in Table 2a

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Appendix H Table 3a (see corresponding Chart 4-3a) likewise reveals a disproportionate amount of high-cost loans received by middle- and upper-income (MUI) African Americans. MUI African Americans received 8.77 percent and 4.38 percent of high-cost and prime loans, respectively. In contrast, MUI non-Hispanic whites received 71.66 percent and 54.39 percent of prime and high-cost loans, respectively.

Chart 3a – Derived from data in Table 3a

Substantially minority neighborhoods received a disproportionate amount of high-cost loans as shown by Table 4a of the tables displaying conventional lending by minority level of neighborhood. Substantially minority neighborhoods with 50 to 79 percent of the residents being minority contain about 10.6 percent of the owner-occupied housing units but received only 5.5 percent of prime loans. However, substantially minority neighborhoods received about 12 percent of the high-cost loans. In contrast, neighborhoods with 20 to 49 percent of minorities received a portion of prime loans (25.6 percent) that was greater than their portion of owner- occupied units (17.6 percent). These mixed racial neighborhoods received a portion of prime loans that was greater than their portion of high-cost loans (22.1 percent). Mixed neighborhoods did even better than the predominantly white neighborhoods. Predominantly white neighborhoods received a portion of prime loans equal to their share of owner-occupied housing units.

Market Share Analysis of All Conventional Single Family Lending in Southeast Texas. Appendix H Table 1b (see corresponding Chart 4-1b below) shows market share ratios in Southeast Texas that are not controlled for income. The table reveals that African American borrowers are 2.16 times more likely to receive a high-cost loan than non-Hispanic white borrowers during 2008. About 47 percent of all loans to African Americans are high-cost

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 81 of 196 compared to 21.7 percent of all loans to non-Hispanic whites being high-cost. Dividing 46.9 percent by 21.7 percent yields the result that African Americans are 2.16 times more likely to receive a high-cost loan than non-Hispanic white borrowers. Finally, Hispanics are 1.61 times more likely to receive a high-cost loan than non-Hispanic whites.

Chart 4-1b – Derived from data in Table 1b

In Appendix H Table 2b (see corresponding Chart 4-2b), LMI African Americans are twice as likely to receive a high-cost loan compared to LMI non-Hispanic white borrowers (the ratio is calculated by dividing 63.8 percent of loans being high-cost for LMI African Americans by 31.8 percent of loans being high-cost for LMI non-Hispanic whites).

Chart 4-2b – Derived from data in Table 2b

Appendix H Table 3b (see corresponding Chart 4-3b below) shows that MUI African Americans are almost twice as likely to receive a high-cost loan as MUI non-Hispanic whites (divide 39.5 percent of the loans being high-cost for MUI African Americans by 19.9 percent of the loans being high-cost for MUI non-Hispanic whites).

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 82 of 196

Chart 4-3b – Derived from data in Table 3b

Residents of minority neighborhoods are much more likely than those of predominantly white neighborhoods to receive high-cost loans. Appendix Table 4b of conventional lending by minority level of neighborhood shows that residents of substantially minority neighborhoods (50 to 79 percent minorities) are 1.85 times more likely to receive high-cost loans than residents of neighborhoods with less than 10 percent minorities (divide 41.2 percent of loans being high-cost in substantially minority neighborhoods by 22.3 percent of the loans being high-cost in neighborhoods with less than 10 percent minorities).

Conventional Denial Disparity Analysis.

The overall denial rate (Appendix H Table 1c, see Chart 4-1c) is approximately 31 percent in Southeast Texas. The denial rate for non-Hispanic white individuals is about 26 percent, and the denial rates for the African Americans and Hispanics are about 52 percent and about 40 percent respectively. African Americans and Hispanics are twice and 1.5 times more likely than non- Hispanic whites to be denied a loan.

Chart 4-1c – Derived from data in Table 1c

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 83 of 196

LMI African American borrowers have a denial rate of about 60 percent for loans that is 16 percentage points higher than the overall denial rate for all LMI loan applicants of about 44 percent (Appendix H Table 2c, see Chart 4-2c). LMI Asian borrowers have a similar denial rate with approximately 60 percent of applications being denied. In contrast, LMI non-Hispanic white borrowers experience denial rates about 6 percentage points lower than the overall denial rate.

Chart 4-2c – Derived from data in Table 2c

Among MUI individuals (Appendix H Table 3c, see Chart 4-3c), African American and Hispanic borrowers experience denial rates noticeably higher than those of whites. MUI African Americans are almost twice as likely to be denied as non-Hispanic white borrowers. MUI African Americans have a denial rate of 47.31 percent in contrast to MUI non-Hispanic whites with a denial rate of 23.75 percent. MUI Hispanics have a denial rate of 36.82 percent in contrast to MUI non-Hispanic whites with a denial rate of 23.75 percent. MUI Hispanics are therefore 1.55 times more likely than MUI non-Hispanic whites to be denied.

Chart 4-3c – Derived from data in Table 3c

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 84 of 196

Residents of substantially minority neighborhoods (50 to 79 percent minority) are 1.62 times more likely than residents of white neighborhoods (less than 10 percent minority) to be denied loans. Almost 43 percent of the applicants from substantially minority neighborhoods are denied loans in contrast to about 26 percent of the applicants from white neighborhoods.

Portfolio Share Analysis of All FHA Single Family Lending in Southeast Texas.

NCRC expanded the Southeast Texas analysis to include information on FHA lending. FHA loans are guaranteed by the Federal government, specifically the Federal Housing Administration (FHA). Borrowers pay an upfront premium and an annual premium to help fund FHA insurance. The FHA insurance covers the costs of defaults. In other words, the government, through FHA fees on borrowers, covers the costs of defaults. In contrast, conventional lending involves lenders themselves absorbing the costs of defaults. Often, lending institutions will protect themselves against loss by requiring borrowers to pay for private mortgage insurance.

The total number of FHA loans was smaller than total number of conventional loans in Southeast Texas in 2008. Lenders issued 616 prime FHA loans and 2,612 prime conventional loans, and 203 high-cost FHA loans and 850 high-cost conventional loans in Southeast Texas.

What is particularly relevant for our analysis is whether minorities are much more likely relative to whites to receive high-cost FHA loans. FHA lending has not been saddled with the abusive tricks, traps, and fees of many subprime loans. Yet, it remains the case that FHA loans are more expensive than conventional loans. If minorities receive a disproportionate amount of high-cost FHA loans and/or prime FHA loans relative to conventional loans, stakeholders should take steps to increase the amount of conventional lending to minorities.

Appendix H Table 1a (see corresponding Chart 4-1.1a) for FHA lending shows that Hispanics have a high ratio of high-cost FHA loans compared to the percentage of households. With only 5 percent of the households in Southeast Texas, Hispanics received more than 10 percent of high- cost FHA loans. The share of high-cost FHA loans for Hispanic or Latinos was 2.03 times greater than their share of households in Southeast Texas. Hispanics also received a slightly higher share of prime FHA loans (6.64 percent) than their share of households (5.16 percent). It should also be noted that Hispanics received a higher share of high-cost FHA loans than high- cost conventional loans (10.47 percent versus 5.2 percent), and also a higher share of prime FHA loans than prime conventional loans (6.64 percent versus 4.46 percent).

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 85 of 196

Similarly, African Americans received a higher share of high-cost FHA loans than high-cost conventional loans (27.98 percent versus 15.69 percent), and also a higher share of prime FHA loans than prime conventional loans (15.11 percent versus 5.59 percent). Since FHA loans are more expensive than prime loans, stakeholders should increase their efforts to make prime conventional loans to Hispanics and African Americans.

In contrast to Hispanics and African Americans, non-Hispanic whites received shares of high- cost FHA loans (of 59 percent) that were lower than their share of households (of 69 percent) and a share of prime FHA loans (of 73 percent) higher than the share of households in Southeast Texas. Non-Hispanic whites also received a higher share of prime conventional loans (of 83 percent) than their share of households (of 69 percent). It should be noted that non-Hispanic whites received higher share of prime conventional loans than prime FHA loans.

Chart 4-1.1a – Derived from data in Table1a

Appendix H Table 2a (see corresponding Chart 4-1.2a) for FHA lending shows that LMI African Americans and LMI Hispanics received a disproportionate amount of high-cost FHA loans. More than 8 percent of the high-cost FHA loans were issued to LMI African Americans, and 5.4 percent of the prime FHA loans were issued to LMI African Americans. Similarly, about 3 percent of the high-cost FHA loans were issued to LMI Hispanics, and 1.48 percent of the prime FHA loans were issued to LMI Hispanics. In contrast to Hispanics and African Americans, LMI non-Hispanic whites were issued a slightly lower percentage of high-cost FHA loans than prime FHA loans (12.32 percent of high-cost FHA loans and 13.3 percent of prime FHA loans).

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 86 of 196

Chart 4-1.2a – Derived from data in Table 2a

Similar to Appendix H Table 2a, Appendix H Table 3a (see corresponding Chart 4-1.3a) shows that both MUI African Americans and MUI Hispanics received a disproportionate amount of high-cost FHA loans. About 19 percent of the high-cost FHA loans were issued to MUI African Americans, and 8.86 percent of the prime FHA loans were issued to MUI African Americans. Similarly, more than 7 percent of the high-cost FHA loans were issued to MUI Hispanics, and 4.87 percent of the prime FHA loans were issued to MUI Hispanics. In contrast to Hispanics and African Americans, MUI non-Hispanic whites received a share of prime FHA loans that was about 3 percentage points greater than their share of FHA loans and 13 percentage points greater than their share of high-cost FHA loans.

Chart 4-1.3a – Derived from data in Table 3a

An examination of FHA lending trends by minority level of neighborhood shows that the predominant lending disparity is the overall share of FHA loans issued to substantially minority neighborhoods (50 to 79 percent of the residents are minority). Lenders issued slightly higher percentage of FHA loans (8 percent) to these neighborhoods than the conventional loans (7 percent). Substantially minority neighborhoods with 50 to 79 percent of the residents received only 6.8 percent of prime FHA loans and 11.8 percent of the high-cost FHA loans compared to

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 87 of 196 the portion of owner-occupied units (10.6 percent) in Southeast Texas. In contrast, neighborhoods with 20 to 49 percent of minorities received a portion of prime FHA loans (34.2 percent) that was greater than their portion of owner-occupied units (17.6 percent). These mixed racial neighborhoods received a portion of prime FHA loans that was greater than their portion of high-cost loans (32.5 percent).

Market Share Analysis of All FHA Single Family Lending in Southeast Texas.

The overall market share ratio (Appendix H Table 1b, see Chart 4-1.1b) shows that about 38 percent of the loans received by African Americans are high-cost FHA loans and about 34 percent of the loans received by Hispanics are high-cost FHA loans, while only about 21 percent of the loans received by non-Hispanic whites were high-cost FHA loans. Thus, African Americans are 1.8 times more likely to receive a high-cost FHA loan than non-Hispanic whites, and Hispanics are 1.6 times more likely to receive a high-cost FHA loan than non-Hispanic whites.

Chart 4-1.1b – Derived from data in Table 1b

LMI Hispanics are 1.7 times more likely to receive a high-cost FHA loan than LMI non-Hispanic whites, and LMI African Americans are 1.44 times more likely to receive a high-cost FHA loan than LMI non-Hispanic whites (Appendix H Table 2b, see Chart 4-1.2b).

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 88 of 196

Chart 4-1.2b – Derived from data in Table 2b

MUI African Americans are twice as likely to receive a high-cost FHA loan as MUI non- Hispanic whites, and MUI Hispanics are 1.61 times more likely to receive a high-cost FHA loan when compared to their non-Hispanic white counterparts (Appendix H Table 3b, see Chart 4- 1.3b). This shows that racial disparities increase as income levels increase, which in contrast was not observed with high-cost conventional lending.

Chart 4-1.3b – Derived from data in Table 3b

FHA Loan Denial Disparity Analysis.

The overall denial rate for all FHA loans (Appendix H Table 1c, see Chart 4-1.1c) in Southeast Texas is 22.4 percent. The denial rate for non-Hispanic white is considerably lower at 15.9 percents. The denial rate for African Americans (29.2 percent), Hispanics (25.5 percent), and Asians (25 percent) are all higher than the overall denial rate. African Americans are 1.83 times more likely than non-Hispanic whites to be denied an FHA loan and Hispanics are 1.57 times more likely than non-Hispanic whites to be denied an FHA loan during 2008 in Southeast Texas.

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 89 of 196

Chart 4-1.1c – Derived from data in Table 1c

The overall denial rate for LMI individuals (Appendix H Table 2c, see Chart 4-1.2c) is 27.3 percent, with the denial rate for all LMI white borrowers being 21.9 percent and LMI African Americans being 31.2 percent. LMI African Americans are 1.63 times more likely than LMI non-Hispanic whites to be denied an FHA loan. Similarly, LMI Hispanics are 1.47 times more likely than LMI non-Hispanic whites to be denied an FHA loan.

Chart 4-1.2c – Derived from data in Table 2c

MUI African Americans were denied 1.88 times more often than MUI non-Hispanic whites for FHA loans. Similarly, MUI Hispanics were denied 1.62 times more often than MUI whites for FHA loans. Ethnic and racial denial rate disparities increased with income levels. (Appendix H Table 3c, see Chart 4-1.3c)

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 90 of 196

Chart 4-1.3c – Derived from data in Table 3c

Summary and Conclusions.

 In Southeast Texas, the portions of all prime conventional loans received by African American borrowers (5.64 percent of prime loans versus 22.98 percent of households) were lower than the loans received by non-Hispanic white borrowers (90.15 percent of prime loans versus 71.95 percent of households) compared to their portions of households.

 The share of high-cost conventional loans received by Hispanics is 1.46 times greater than their share of households even though the share of total conventional loans received by Hispanics is proportional to their share of households (about 5 percent).

 Both MUI African Americans and LMI African Americans are twice more likely to receive a high-cost loan than their non-Hispanic white counterpart during 2008. MUI Hispanics are 1.5 times more likely to receive a high-cost loan than MUI non-Hispanic white. LMI Hispanics are 1.43 times more likely to receive a high-cost loan than LMI white non- Hispanic during 2008.

 The denial ratio is higher when comparing MUI African Americans and MUI Hispanics to MUI non-Hispanic whites than when comparing LMI African Americans and LMI Hispanics to LMI non-Hispanic whites. MUI African Americans are twice more likely than MUI non- Hispanic white to be denied. LMI African Americans are 1.56 times more likely than LMI non-Hispanic white be denied. Ethnic and racial disparities in denials increases as income levels increase in Southeast Texas.

 With only 5 percent of the households in Southeast Texas, Hispanics received more than 10 percent of high-cost FHA loans. Hispanics also received a slightly higher share of prime

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 91 of 196

FHA loans (6.64 percent) than their share of households (5.16 percent). It should also be noted that Hispanics received a higher share of high-cost FHA loans than high-cost conventional loans (10.47 percent versus 5.2 percent), and also a higher share of prime FHA loans than prime conventional loans (6.64 percent versus 4.46 percent).

 African Americans received a higher share of high-cost FHA loans than high-cost conventional loans (27.98 percent versus 15.69 percent), and also a higher share of prime FHA loans than prime conventional loans (15.11 percent versus 5.59 percent). Since FHA loans are more expensive than prime loans, stakeholders should increase their efforts to make prime conventional loans to Hispanics and African Americans.

 In contrast to Hispanics and African Americans, non-Hispanic whites received higher share of high-cost conventional loans than high-cost FHA loans (72 percent versus 59 percent). It should also be noted that non-Hispanic whites received higher share of prime conventional loans than prime FHA loans.

 Racial and ethnic disparities are observed in denying applications for both conventional and FHA loans. Stakeholders should take steps to narrow disparities in both conventional and FHA lending.

Concentration and Racial Segregation.

The demographic materials in Appendix D show a clear pattern of concentration based on racial classification. Beaumont’s population is 42.6 percent Non Hispanic White and 42.58 percent Black. The dissimilarity index shows that in order to obtain racial integration, 62.79 percent of the Black community would need to move.112

The materials provide communities with a way to target concentrations of racial classes. In order to break up the racial concentrations local jurisdictions should provide the ability to relocate individuals using disaster recovery funds and in entitlement communities, HOME and CDBG dollars.

When you look at the map of Beaumont, it shows a significant majority of the neighborhood blocks as either a concentration of minorities exceeding 65 percent or less than 35 percent

112 Appendix D category of communities 50K+ data and maps.

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 92 of 196 minorities in the neighborhood block.113. In the Housing Guidelines for Round 2 funds, this would be a community that could and should be targeted for Round 2 disaster recovery funds for the Homeowner Opportunity Program. This program will assist in allowing qualified applicants in the most heavily concentrated areas for race and poverty to receive federal assistance in moving out of these areas into high opportunity or more racially diverse areas.

This information is provided for communities to use in planning how to address concentration patterns in spending federal funds. Each community over 10,000 has maps available to it that highlight the racial makeup of their community by census tract.

Not In My Backyard—The Impediment of NIMBYism.

A common problem for all communities is the organized public opposition to building low- income, public, or affordable housing. This issue was identified by the focus group in Beaumont and Port Arthur. While there is public housing in each community it tends to be built in areas that are traditionally minority or low-income neighborhoods. Some participants said they raise this issue frequently and receive support from elected officials on a theoretical level. However when a development is proposed outside of the traditional areas by the housing authority or private developers, the uproar from the neighborhood residents causes their city to back down. Typically the standard reasons for not accepting affordable housing that are brought forward are decrease in property values, an increase in crime, etc. TDHCA also confirms that this type of opposition has been raised with respect to multi-family developments under its programs.

Discrimination in Housing Markets.

No direct testing of the real estate industry was done as part of this AI. However, persons interviewed in the community identified a pattern of discrimination in private sector real estate markets toward racial minorities. Most of the interviewees agreed that they were aware of instances of illegal housing discrimination. Most mentioned steering by realtors of clients that were both white and African American. In fact, two of the interviewees had direct experience of steering by realtors. Others mentioned “For Rent” ads in local newspapers that clearly stated “No HUD” and “No Housing.” Although they are cognizant that this is not necessarily illegal they

113 Ibid.

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 93 of 196 believe that the assumption is made by the population in general that “HUD” and “Housing” is synonymous with “African American.”

A report by the National Fair Housing Association, provided information on the treatment of the minority testers they sent to look for rental units in Houston.114 The results of the 2005 undercover test group was that black testers were substantially less likely to be told about available units, called back, or shown properties than their white test group counterparts.115 The potential discrimination is not just limited to rental markets. Another report by the National Fair Housing Alliance titled Dr. King’s Dream Denied: Forty Years of Failed Federal Enforcement demonstrated that in 12 cities across the United States the report found that “in the twelve metropolitan areas investigated to date, NHFA’s testing revealed discriminatory steering practices and illegal behaviors that are both striking and pervasive.116 The Katrina report is included as one of the metropolitan areas that make up this report. The Justice Department has settled a lawsuit for $120,000 with a major Real Estate firm in Chicago related to steering of minority clients toward minority neighborhoods and away from Non Hispanic White neighborhoods.117

Collectively, even if not all in this area, it supports the concept that steering creates an impediment to integrated housing patterns. There has been no state testing to confirm the pattern is true and that in itself could be an impediment to Fair Housing. Whether governments have failed to enforce the Fair Housing Act and the Texas Property Code Chapter 301 (Texas Fair Housing Act) as written should be reviewed.

Challenges Presented by Local Ordinances and Restrictions.

During the interview process, at least one of the interviewees made reference to lot size and zoning as one of the problems for not moving forward with affordable housing. In looking at the Golden Triangle, some communities have no regulations, no building codes and permit through the county rather than a local government.118 One of the “neutral” mechanisms to potentially prevent racial integration of communities is to establish standards that increase the cost of

114 No Home for the Holidays—Discrimination for Katrina Evacuees 2005, National Fair Housing Alliance 115 Ibid 116 titled Dr. King’s Dream Denied: Forty Years of Failed Federal Enforcement, National Fair Housing Alliance April 8, 2008. 117 Justice Department Obtains $120,000 Discrimination Lawsuit Against Chicago Area Realtors, Feb. 18, 2009 retrieved from http://reuters.com/article/idUS202030+18-Feb-2009+PRN20090218 118 Information provided by URS Architects, Engineers and Planners and made available to SETRPC in chart format based on ordinance reviews and interviews with local staff and inspectors. The information was valid as of June 10, 2010.

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 94 of 196 building affordable housing encouraging people who are building smaller homes to look elsewhere. No direct investigation as to the racial impact on the zoning restrictions mentioned was conducted for this AI. Had we conducted this investigation, it would have required that we look at the number of permits issued in communities with restrictions on lot sizes and minimum home sizes and analyze the number of racial minorities or persons with disabilities that have built in that community since the restrictions were put in place measured against other nearby communities or the percentage of the existing minority population.

As TDHCA has rebuilt homes in Port Arthur, we have had at least 46 applicants who may have been denied assistance to rebuild their home as their lots were considered to be substandard— most due to the lot being considered too small. The City did in most of the cases look for alternative lots, but at some point when the alternative lots were gone, it increased the cost to the program.119 The table below shows the communities that have a minimum lot size equal to or greater than Port Arthur.

Table 4-12 Lot Sizes in SETRPC Location Lot Width Lot Minimum Square Footage Port Arthur 50’ 7,000 Sabine Pass 50’ 7,000 Port Acres 50’ 7,000 Silsbee 65’ 7,500 Bridge City 65’ 7,800 Lumberton 75’ 9,000

Another mechanism that has been determined to have potential Fair Housing violations is a minimum square footage for homes. This not only increases costs, but can also bar manufactured housing from a community, both potentially affecting low income persons which can disproportionably impact racial minorities. Several communities have requirements that exceeded the floor plans built in Rounds I and II of Hurricane Rita. The SETRPC program in Ike Round 1 adjusted to meet most communities by increasing their minimum size home for the program. At the time, all but one city would have been included in the 1,300 square foot home.

119 Based on information supplied by TDHCA Rita Round II supplier ACS. Information was valid as of October 25, 2010. Of the applicants with the substandard lot 23 were served. Some were not served for other reasons including lack of program funds.

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 95 of 196

The following table includes communities with minimum square footages for homes over 1,000 square feet.

Table 4-13 Minimum Square Footage Requirements over 1000 sq feet Municipality Minimum Square Footage for Home Groves 1,200 Lumberton 1,200 Nederland 1,200 Port Neches 1,300 Taylor Landing 2,000

There may actually not be issues with any of these requirements as long as they do not have the effect of keeping out protected classes including racial minorities and persons with disabilities. If it appears that these local ordinances and restrictions have lessened the number of protected classes from building in communities the purpose of the requirements would need to be examined by the local community to see if they had a discriminatory affect.

Current ordinances and policies in the region have not been reviewed to identify all potential discriminatory issues. To make it easier for local communities to conduct a broad review of common examples the list below are examples of other ordinances and policies found in legal actions that could have a discriminatory effect. These include:

 Definitions of “family” (who can live in housing -- extended families?; children?)

 Density requirements/limits

 Parking requirements/limits

 Signage / notification requirements for proposed developments that treat certain projects differently

 Lot size requirements

 Minimum square footage requirements

 Building code requirements that increase the cost of residences (for example, all masonry construction requirements)

 Limits on the number of bedrooms for multi-family dwellings

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 96 of 196

 Limits on second / accessory units

 Anti-multifamily moratoria

 Zoning as “commercial” or “industrial” if services or other non-residential activities offered on-site (triggers different building/zoning requirements than for residential)

 Requiring conditional use permits for residential facilities

 Dimensional requirements for commercial/business zones that are not conducive to residential development

 Street and utility requirements on new building that can increase building costs (e.g., street width, curbing type, sidewalk surfaces for internal development spaces)

Lack of Knowledge about what Constitutes Fair Housing Violations.

In addition to claims of real estate steering and rental discrimination, the focus groups indicated that the Fair Housing Act remains a mystery to much of the public. Even more clear is that not many people, even if they believe they are being discriminated against, know how to take action to file a complaint or report a violation. In Section 7 of this document a list of all the housing discrimination complaints filed with HUD are listed by county. The Golden Triangle region has nearly 400,000 people living in the community. During interviews and in focus groups in the area, the individuals that participated raised housing discrimination issues and yet from January 2005 through September 2010 only 8 complaints were made to HUD from this region. In addition, the Texas Workforce Commission received 692 complaints (9 as shown in Section 7.) in the total hurricane impacted region (61 counties). As an indication that the public may not understand the issues, of the 692 complaints 323 of them received findings of “no cause.”120

Looking at Project Placement.

In reviewing the projects contained in Appendix F, two issues become obvious. Most CDBG funds not including disaster funds, whether supplied by the State or used by entitlement communities go almost exclusively to infrastructure projects. The difficulty of determining how the funds are spent is compounded by the manner in which data is reported. Looking at the table very few infrastructure projects have a clear delineation of whom they are directly serving and

120 Housing Discrimination Complaints Section 7. herein.

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 97 of 196 where the project is located. Without an ability to reference the population served (other than the generic 51 percent plus LMI language), it is difficult to determine who is receiving the benefit of the projects. Because so many of the regular CDBG funds are listed in this manner at both the entitlement jurisdiction and the State the information is not useable to determine if a community is using funds to further fair housing, or if communities with concentrations of protected classes are being underserved

In addition, in reviewing Appendix F, very little of non-disaster CDBG funds go to housing. In part this may be because of available funds for infrastructure. A state or local preference for infrastructure use may have been present, but the CDBG Action Plan has a policy that says it supports the use of CDBG funds for the construction of housing. The limitations of funds available and the competitive nature of the funds may factor into the use of funds. Despite the CDBG Action Plan expressing support for building housing with CDBG funds, competitive application rounds should be reviewed to see if they favor infrastructure over housing in scoring.

The impediment here may actually be the lack of specificity and record keeping by local and state governments for use in conducting their analysis of impediments to fair housing.

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 98 of 196

SECTION 5. LOWER RIO GRANDE VALLEY.

This section is not intended to provide a complete AI for each community in the Lower Rio Grande Valley. In fact, some communities in the region may find more in with common the small community section where the focus is on cities of less than 2,500, provides more similar conditions that they are facing and looks at similar ways to overcome Fair Housing impediments.

Given the racial composition of this region, much of the Fair Housing issues will focus on the Colonias, migrant farm workers and national origin issues. Part of the Fair Housing questions will center on infrastructure issues and how federal funds are spent. Even with the predominate Hispanic make-up, there can still be biases within the private sector as are demonstrated in access to private capital and real estate transactions.

This section will more clearly develop the local demographic information and look at the potential impediments to Fair Housing that exist in the area.

Historical Recap.

Located at the southeastern tip of Texas, the Lower Rio Grande Valley includes Cameron, Hidalgo and Willacy Counties as well as the cities of Brownsville, Harlingen, Weslaco, San Benito, Edinburg, Mission, and Pharr.

The ethnic history of this region is dominated by the predominant indigenous Hispanic population, its proximity to Mexico, the development of agriculture and ranching and the need for labor.

The historical racial and ethnic groups populating the Lower Rio Grande Valley include Native Americans, Spanish and Mexicans. In fact the percentage of Hispanic population in the Valley is more than twice that of the state as a whole.121 The black population in the Valley is very low at less than one percent. The Spanish occupied the area in the mid-1700s and established cattle ranches. Brownsville was the first American settlement. Mass migration of mid-westerners and Mexican immigrants resulted in rapid population growth in the early twentieth century. By 1930

121 http://www.lafepolicycenter.org/documents/LRGV.SENIOR.12.09.pdf

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 99 of 196 the population of the Valley numbered approximately 176,000. The 1940s saw urbanization take hold in the region, although much of the area is still agricultural. Growth continued through the following decades; however, Hidalgo and Starr Counties were consistently ranked as two of the poorest counties in the entire country during the 1980s and 1990s.122

Some of this poverty is attributed to the establishment of colonias by developers and the movement of poor Mexican Americans and immigrants from Mexico and Central America into these substandard residential neighborhoods. Colonias developed beginning in the early 1900s and were established as towns by land speculators. A few colonias began as small communities of farm laborers employed by a single rancher or farmer. However the majority of colonias emerged in the 1950’s as developers discovered a large market of aspiring homebuyers who could not afford to purchase in cities or who did not have access to conventional finance mechanisms.123 Many of these unincorporated subdivisions lay in floodplains. The plots were small, had little to no infrastructure and were affordable. Furthermore many colonias lack electricity, plumbing, potable water and other amenities.

A significant number of colonias are purchased through a contract for deed in which buyers pay a low down payment and low monthly payments and do not receive a title to the property until all payments are complete. Contracts for deed have been a significant source of abusive loan tactics and have been identified as the most common form of predatory lending in the Lower Rio Grande Valley.124 Many of the buildings in colonias are constructed by residents and substandard construction is the norm.

Texas is the state with the largest number of colonias (2,294). The overwhelming majority of these house Hispanic residents. Due to a limited supply of affordable housing in border areas colonias continue to attract many people, primarily those who come from lower economic backgrounds. Concerns for public health and quality of life are significant in colonias due to the lack of infrastructure especially wastewater and potable water. Even when water lines and sewer systems are in place many cannot access the services because their homes do not meet county

122 http://www.tshaonline.org/handbook/online/articles/RR/ryr1.html 123 2010 State of Texas Low Income Housing Action Plan and Annual Report: Colonia Action Plan 124 See McAllen Focus Group in this AI

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 100 of 196 building codes. A lack of public funding for the improvement of colonias exacerbates the problems for people who live in these areas.125

Regional Demographic Recap.

The area represented by the Lower Rio Grande Valley Development Council had a population of 924,772 according to the 2000 Census but estimates from 2006-2008 put the population at well over 1,000,000.126 The largest county is Hidalgo County with a total population of 706,039.127

Population.

The Lower Rio Grande Valley is anticipated to have dramatic growth between now and 2040 according to the state demographers at the University of Texas at San Antonio. Under the Zero Net Migration formula (0.0 Scenario) population is expected to more than double assuming rates of net migration equal to one-half of 1990-2000 totals (0.5 Scenario) by 2040.128

Table 5-1 Projected Population LRGVDC Region Non Hispanic Year Black Hispanic Other Total White

2000 112,088 3,453 803,045 6,186 924,772 Non Non Hispanic Hispanic Black Black Hispanic Hispanic Other 0ther Total Total Year White White 0.0 0.5 0.0 0.5 0.0 0.5 0.0 0.5 0.0 0.5 Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario scenario Scenario

2010 104,532 106,299 3,717 3,737 984,081 1,063,098 7,250 8,779 1,099,580 1,181,913

2020 96,193 98,200 4,059 4,075 1,163,898 1,358,585 8,208 12,153 1,272,358 1,473,013

2040 84,202 80,433 4,163 4,043 1,524,736 2,022,496 9,200 20,626 1,622,301 2,127,598

125 http://www.sos.state.tx.us/border/colonias/faqs.shtml 126 American FactFinder, Hidalgo County and Cameron County, Texas, 2006-2008 American Community Survey 3-year estimates. U.S. Census Bureau retrieved at http://factfinder.census.gov 127 American FactFinder, Hidalgo County, Texas, 2006-2008 American Community Survey 3-year estimates. U.S. Census Bureau retrieved at http://factfinder.census.gov 128 These projections assume the One-Half 1990-2000 Migration (0.5) Scenario. According to the State Demographer: This scenario has been prepared as an approximate average of the zero (0.0) and 1990-2000 (1.0) scenarios. It assumes rates of net migration one-half of those of the 1990s. The reason for including this scenario is that many counties in the State are unlikely to continue to experience the overall levels of relative extensive growth of the 1990s. A scenario which projects rates of population growth that are approximately an average of the zero and the 1990-2000 scenarios is one that suggest slower than 1990-2000 but steady growth. Information for Table 4-1 pulled from Table 2.7 Population for the State of Texas and Council of Government Regions in Texas and Projections to 2040 Assuming Alternative Projection Scenarios SETRPC Region data http://txsdc.utsa.edu/pubsrep/

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Age.

Table 4-2 shows the population’s anticipated aging according to the demographers located at the University of Texas at San Antonio for the LRGDV Region. This table demonstrates that the percentage of the population who is over sixty five will increase in raw numbers within the age category and as a percentage of the population as a whole.129 The 2040 data assumes rates of net migration equal to one-half of 1990-2000 (.5 Scenario) and is neither the least nor the most conservative estimate by the demographers.

Table 5-2 Age by Age Group and Ethnicity Age Non Non Black Black Hispanic Hispanic Other Other Total Total Group Hispanic Hispanic 2000 2040 2000 2040 2000 2040 2000 2040 White White 2000 2040

<18 16.7 15.8 24.1 10.7 37.3 27.6 29.3 21.0 34.7 27.1

18-24 4.8 6.7 15.7 14.9 11.9 10.5 6.6 8.5 11.0 10.3

25-44 19.2 19.2 40.3 34.1 28.3 26.7 37.0 25.0 27.3 26.5

45-64 25.0 20.5 16.0 24.2 15.5 21.1 20.8 21.4 16.7 21.0

65+ 34.3 37.8 3.9 16.1 7.0 14.1 6.3 24.1 10.3 20.5

Median 52.5 53.2 30.0 39.6 25.5 33.4 33.2 41.6 27.9 34.0

Poverty and Income.

About 83.3 percent of Region 11130 families live in urban areas. Table 5-3 depicts the number of families living below the poverty line in LRGV.

Table 5-3 LRGV Poverty Figures, 2010 Families At or Above Poverty Families Below Poverty County Number Percent Number Percent Cameron 68,568 69.4% 30,201 30.6%

Hidalgo 124,937 68.7% 56,885 31.3% Willacy 2,984 61.0% 1,905 39.0% Source: Nielsen Claritas, Ribbon Demographics, 2010.

129 Table 2.14 Percentage of Population for the State of Texas and Council of Government Regions in Texas by Age and Race/Ethnicity of the Population and Median Age by Race/Ethnicity in 2000 and Projections to 2040 Assuming Alternative Projection Scenarios HGAC Region data http://txsdc.utsa.edu/pubsrep/ 130 Region 11 is the Texas Comptroller’s 13 Uniform State Service Regions of Texas and the primary way funds are distributed to non-entitlement communities by TDHCA based on a Regional Allocation Formula as required under Texas Government Code 2306.1115. We will use the three county information when available, but if not available we will refer to Region 11.

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Region 11 Household Incomes. The pie chart to the left depicts the income breakdown of Extremely Low Income (0-30%), 19% the 377,276 households in the region. Approximately 55 percent of households are low income. The 2000 CHAS Higher Income Very Low Income (over 95%), 45% figures for moderate and higher income household in (31%-50%), 17% Region 11 indicate that there are only 199 persons with Low Income Moderate Income income between 80-95 percent of the AMFI. TDHCA has (51%-80%), 19% (81%-95%) , 0% been unable to get more accurate information for this segment of the population.

There are 523,671 individuals living in poverty in the region, which makes up 33.3 percent of the regional population. According to the Texas Comptroller’s Texas In Focus report, the top five occupations with high projected job growth in Region 11 are low paying (average annual wage of $16,103) and do not require a post-secondary education.131 Additionally, floodplains in the colonias in Webb and Hidalgo counties have discouraged investors and developers from investing in the region’s rural areas.132

Special Needs Populations.

Some data for persons with special needs is only available at the state level. For example, the number of persons with alcohol and substance abuse is not available at the county level, so analysis could only be done at the state level. In addition, the regional number of public housing units, in which public housing residents live, is not included in the Special Needs Population section of each regional analysis because it is included in the Assisted Housing Inventory at the end of each regional analysis

Homeless Persons.

According to 2010 population projections by Ribbon Demographics, there are only 1,101 persons that are homeless, in non-institutional group quarters. LRGVDC also experienced damage from Hurricane Dolly, which hit the Lower Rio Grande area in July 2008. Households affected by the hurricane have unmet needs.

131 Texas Comptroller of Public Accounts, “Texas in Focus: South Texas,” August 2008. http://www.window.state.tx.us/specialrpt/tif/southtexas/ (accessed October 6, 2010). 132 US Government Accountability Office, Report to Congressional Committees, Rural Homelessness: Better Collaboration by HHS and HUD Could Improve Delivery of Services in Rural Areas,” July 2010. http://www.gao.gov/new.items/d10724.pdf

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Table 5-4 LRGVDC persons in other group quarters, 2010 Homeless persons Statewide Homeless Population Cameron 639

Hidalgo 452 Willacy 10 Total 1,101 67,698 Source: Nielsen Claritas, Ribbon Demographics, 2010.

Persons with Disabilities.

According to the US Census, of the total population in the LRGVDC area, persons with disabilities account for approximately 13 percent of the population of Region 11.

Tale 5-5 Persons with Disabilities County Number of Persons with Disabilities Cameron 65,392 Hidalgo 105,969 Willacy 3,596 Source: Census 2000, Urban defined by presence of an MSA.

Persons with HIV/AIDS.

According to the Texas Department of State Health Services’ 2010 Texas Integrated Epidemiologic Profile for HIV/AIDS Prevention and Services Planning, there are 1,849 persons living with HIV/AIDS in Region 11. Approximately 80.9 percent of this population is living in urban areas, with the remaining 19.1 percent in rural areas. Region 11 has a fairly low rate of persons living with HIV/AIDS compared to the state as a whole, with the US –Mexico Border area accounting for just 5.5 percent of the total, and a rate of 137 persons per 100,000. Note that Texas DSHS defines the border area as those 32 counties within 100 kilometers of the US- Mexico border, a standard definition in health and human services reports.

Table 5-6 Region 11 Persons living with HIV/AIDS, 2008 County HIV/AIDS Number HIV/AIDS Rate Population 2008 Cameron 572 142.8 289,164 Hidalgo 804 108 721,275 Willacy 41 189 20,382 Total 1,417 1,030,821 Source: Texas Department of State Health Services. 2010 Texas Integrated Epidemiologic Profile for HIV/AIDS Prevention and Services Planning: HIV/AIDS in Texas. Population from US Census Population Estimates, 2008.133

133 Note: Figures do not include those unaware of their HIV infection of those who tested HIV positive solely through an anonymous HIV test. Cases diagnosed at the Texas Department of Criminal Justice System are not attributed to a geographic area.

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Colonia Residents.

The Office of the Attorney General maintains an extensive Colonia Geographic Database, accounting for over 1,800 colonia areas in 29 counties. The table below depicts the estimated colonia population in Region 11. The region contains a very large portion of the state’s colonia population, accounting for over 73.2 percent of the 418,406 residents, with a large portion residing in Hidalgo County.134

Table 5-7 LRGV Colonia Population, estimated 2010

Colonia Population Estimate Cameron 100,971 Hidalgo 138,458 Willacy 3,465 Total 242,894 Statewide total 418,406

Migrant Farmworkers.

In a study prepared for the US Health Resources and Services Administration, Region 11 was found to have a very high proportion of the state’s Migrant and Seasonal Farmworker (MSFW) population, accounting for 34.0 percent of the 361,414 MSFWs in the state of Texas.135 The high farmworker population correlates with a dominant agricultural industry in Region 11, an area which produces large amounts of the nation’s sugarcane, sorghum for grain, cotton, citrus, and onions. The crop and animal production sectors provided 20,000 jobs to Region 11 in 2007.136 Below is the estimate of MSFW in the three county area of LRGV.

Table 5-8 Migrant and Seasonal Farmworker Population, 2000137

LRGVDC MSFW Estimate Cameron 15,568 Hidalgo 70.850 Willacy 4,058

134 Texas Office of the Attorney General, Border Colonia Geographic Database 135 Migrant and Seasonal Farmworker Enumeration Profiles Study – TX, Larson, Alice, 2000. 136 Texas Comptroller of Public Accounts, “Texas in Focus: South Texas,” August 2008. http://www.window.state.tx.us/specialrpt/tif/southtexas/ (accessed October 6, 2010). 137 Migrant and Seasonal Farmworker Enumeration Profiles Study – TX, Larson, Alice, 2000.

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Local Input on Housing Assistance.

According to the TDHCA Public Assistance Inventory for SFY2010, the agency received 18,821 public assistance requests from Region 11, which accounted for 8.9 percent of total annual requests. Of requests from Region 11, the three most requested categories of assistance were, in order: Utility Assistance, Repair and Weatherization and Rental Assistance.

Table 5-9

Region 11 Public Assistance Request Inventory, SFY 2010

Legal

Utility Rental

Repair

Disaster Disaster

Assistance

Assistance Assistance Assistance Assistance Assistance

Emergency

Foreclosure Homebuyer

Cameron 10 1 0 10 1 13 2 5 Hidalgo 15 0 2 14 0 25 2 7 Willacy 0 0 0 0 0 0 0 2 Total 25 1 2 24 1 38 4 14

Affordable Housing Need.

When analyzing local housing markets and developing strategies for meeting housing problems, HUD suggests the consideration of several factors. These factors include how much a household spends on housing costs (also called Housing Cost Burden), the physical condition of the housing and whether or not the unit is overcrowded. The following table reveals the number and percentage of households with at least one housing need by income category and household type.

Of renter households, those at 31-50 percent AMI are the most likely to have at least one housing problem. Of owner households, those at 0-30 percent AMI are the most likely to have at least one housing problem.

Physical Inadequacy (Lack of Kitchen and Plumbing Facilities).

The table below breaks out the information for the LRGVDC area. As you can tell from the information, those who have the least ability to change their situations are more likely to live in an environment that would not be considered acceptable to many people.

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Table 5-10 Number of Units Lacking Kitchen and/or Plumbing by Affordability Category – LRGV, 2005-2007 Units Lacking Complete Plumbing/Kitchen Extremely Very Low All Low Income Income (31- Low Income Higher Incomes incomes (0-30%) 50%) (51-80%) (81% and up) Willacy County 396 256 114 18 8 Cameron County 3,330 1,629 1,006 483 212 Hidalgo County 7,420 4,857 1,710 643 210 Total 11,146 6,742 2,830 1,144 430 Source: CHAS 2000.

The state defines the “standard condition” of housing as properties that meet the Federal Housing Quality Standards, or the State Colonia Housing Standards, as applicable. “Substandard condition but suitable for rehabilitation” refers to properties that do not meet the above standards but are not sufficiently deteriorated to justify demolition or replacement. These definitions refer to the condition of properties prior to the receipt of assistance.

Bar Graph 5-1 shows the distribution of substandard housing by income group. Households in the lowest income group earning 30 percent AMFI or less have the highest percentage of physically inadequate rental housing. The bar graph shows the percentage of households with housing problems in each income category compared to households in the corresponding income category.

Bar Graph 5-1 Renter Households with Substandard Housing by Income Category – Texas, 2005-2007

2.5 2.1% 2.0

1.5 1.4% 1.1% 0.9% 0.9% Percent 1.0

0.5

0.0 30% AMI or 30.1%-50% 50.1%-80% 80.1%-95% 95.1% AMI less AMI AMI AMI and above Income Category Source: CHAS 2005-07 statewide figures.

The same trend holds true for owner households. Bar Graph 5-2 shows the percentage of households with housing problems in each income category compared to households in the corresponding income category.

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Bar Graph 5-2 Owner Households with Substandard Housing by Income Category – Texas, 2005-2007

2.0 1.8% 1.8 1.6 1.4 1.2 1.0 0.9% 0.9%

Percent 0.8 0.6% 0.6 0.4% 0.4 0.2 0.0 30% AMI or 30.1%-50% 50.1%-80% 80.1%-95% 95.1% AMI less AMI AMI AMI and above Income Category Source: CHAS 2005-07 statewide figures.

Housing Cost Burden.

A cost burden is identified when a household pays more than 30 percent of its gross income for housing costs. When so much is spent on housing, other basic household needs may suffer. As Bar Graph 5-3 shows, a majority of renter households in the lowest two income categories, totaling more than 551,000 households, is burdened by paying an excess portion of income toward housing. This is much greater than in the highest income category, above 95 percent AMFI, where only 0.4 percent of households, or 3,480 households, experience the problem. The bar graph shows the percentage of households with cost burden in each income category compared to households in the corresponding income category.

Bar Graph 5-3 Renter Households with Housing Cost Burden by Income Category – Texas, 2005-2007

70.0 64.1% 60.0

50.0

40.0

30.0 26.6% Percent 20.0

10.0 4.5% 1.0% 0.4% 0.0 30% AMI or 30.1-50% AMI 50.1-80% AMI 80.1-95% AMI 95.1% AMI less and above Income Category Source: CHAS 2005-07 statewide figures.

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As shown in the following bar graph, housing cost burden affects 217,070, or 58.2 percent of owner households in the lowest income category. This figure, representing a majority, is much higher than the 1.1 percent of households affected in the highest income category. Bar Graph 5-4 illustrates the direct correlation between an owner household’s income category and an owner household’s likelihood of experiencing this problem. The graph shows the percentage of households with cost burden in each income category compared to households in the corresponding income category.

Bar Graph 5-4 Renter Households with Housing Cost Burden by Income Category – Texas, 2005-2007

70.0 58.2% 60.0

50.0

40.0 29.6% Percent 30.0

20.0 11.7% 10.0 5.3% 1.1% 0.0 30% AMI or less 30.1-50% AMI 50.1-80% AMI 80.1-95% AMI 95.1% AMI and Income Category above Source: CHAS 2005-07 statewide figures.

LRGV is consistent with a disproportionate share of those with a significant cost burden in the lower income areas as Table 5-12 demonstrates.

Table 5-11 LRGVDC Households with a Cost Burden >30% Extremely Low Income Very Low Income Low Income Higher Incomes All incomes (0-30%) (31-50%) (51-80%) (81% and up) Willacy County 1,044 683 192 88 81 Cameron County 17,202 8,549 4,061 2,783 1,809 Hidalgo County 23,535 12,340 5,288 3,355 2,552 Total 41,781 21,572 9,541 6,226 4,442 Source: CHAS 2000.

Overcrowding.

Overcrowded housing conditions occur when a residence accommodates more than one person per each room in the dwelling. Overcrowding may indicate a general lack of affordable housing in a community where households have been forced to share space, either because other housing units are not available or because the units available are too expensive.

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Lower income renter households experience overcrowded conditions more frequently than higher income households. Over 10.2 percent of renter households in the extremely low income category and 11.5 percent of renter households in the very low income category are afflicted by overcrowding. Bar Graph 5-5 shows the percentage of households experiencing overcrowding in each income category compared to households in the corresponding income category.

Bar Graph 5-5 Renter Households with Incidence of Overcrowding by Income Group – Texas, 2005-2007

14.0 11.5% 12.0 10.2% 10.0 7.9% 8.0 6.2%

6.0 Percent 4.0 3.4%

2.0

0.0 30% AMI or 30.1-50% AMI 50.1-80% AMI 80.1-95% AMI 95.1% AMI less and above Income Category Source: CHAS 2005-07 statewide figures.

Lower income owner households also experience overcrowded conditions more frequently than higher income owner households. More than 6.5 percent of owner households earning less than 50 percent HAMFI live in overcrowded conditions compared to 4.6 percent of owner households over 80 percent HAMFI. Bar Graph 5-6 shows the percentage of households experiencing overcrowding in each income category compared to households in the corresponding income category.

Bar Graph 5-6 Owner Households with Incidence of Overcrowding by Income Group – Texas, 2005-2007 7.0 6.5% 6.0% 6.2% 6.0

5.0 4.6%

4.0

3.0 Percent 2.0 1.7%

1.0

0.0 30% AMI or 30.1-50% AMI 50.1-80% AMI 80.1-95% AMI 95.1% AMI less and above Income Category Source: CHAS 2005-07 statewide figures.

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In the LRGVDC, the problem of overcrowding cuts across all income levels. While this may be more of a family custom, it could demonstrate that housing in the region may need additional resources to provide adequate living space.

Table 5-12 LRGVDC Households that are Overcrowded Very Low Extremely Low Low Income Higher Incomes All incomes Income (31- Income (0-30%) (51-80%) (81% and up) 50%) Willacy County 1,080 361 244 185 290 Cameron County 17,302 5,228 3,714 3,641 4,719 Hidalgo County 26,515 8,092 5,710 6,068 6,645 Total 44,897 13,681 9,668 9,894 11,654 Source: CHAS 2000.

Identification of Impediments to Fair Housing.

The Lower Rio Grande Valley region (“LRGV”) has a different set of impediments than much of the hurricane impacted areas. While most areas have flooding problems, the LRGV Region has multi county drainage system that leaves some lower income areas out of the system resulting in perennial floods with tropical storms and hurricanes. With the racial make-up of the LRGV the concentration of racial minorities is not as significant an issue. However, areas where some residents are steered into Colonias or other low income areas present similar Fair Housing issues. The extent of belief that there is public corruption makes it difficult for people to believe that funds provided are going to make it to the people who need it most and creates a confidence issue in government and how programs are administered. The LRGV has similar impediments as other communities with access to private capital and steering, although both take a slightly different look here.

Certainly the issue of how to work with Colonias is one of the key housing problems of the region. A key problem that the State is trying to address is the system of contract for deeds in Colonias. To the extent that the people in Colonias are denied access to infrastructure, low standard housing conditions, and enforcement against developers taking advantage of people who have little alternatives but to move into the Colonias, this could be the most significant Fair Housing issue in the region.

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Home Mortgage Disclosure Act Analysis.

The State of Texas contracted with the National Community Reinvestment Coalition (NCRC) to conduct a portfolio and market share analysis using 2008 Home Mortgage Disclosure Act (HMDA) data for the Lower Rio Grande Valley Development Corporation area. Cameron, Hidalgo, and Willacy Counties comprise this region.138

Portfolio Share Analysis of All Conventional Single Family Lending in Lower Rio Grande Valley, Texas.

Hispanics are the largest minority group in Lower Rio Grande Valley, representing 79.18 percent of all households. Asians, Native Americans, and African Americans combined account for 1.46 percent of households in the Lower Rio Grande Valley. Table 1a (see corresponding Chart 1a) of the conventional lending report shows that the portion of all prime loans received by Hispanic borrowers was lower than non-Hispanic white borrowers compared to their portion of households. Hispanics received 72.48 percent of prime loans that was lower than their portion of households (79.18 percent), while non-Hispanic whites received 20.66 percent of prime loans that was slightly higher than their portion of households (19.43 percent). Hispanic borrowers also received a disproportionally high percentage of high-cost loans (91.56 percent), while Hispanics constitute 79.18 percent of Lower Rio Grande Valley’s households. As a comparison, non- Hispanic whites received only 6.12 percent of all high-cost loans while they comprised 19.43 percent of all households during 2008.

Asians were overrepresented in prime loans (2.93 percent of prime loans versus 0.60 percent of households) and received a similar portion of high-cost loans (0.57 percent) compared to their portion of households (0.60 percent of households) while African-Americans were just a little overrepresented in prime loans (0.56 percent of prime loans versus 0.39 percent of households).

138 The State hired Southwest Fair Housing Council to be the primary contractor and they contracted with the National Community Reinvestment Council on behalf of the state. This report is largely un-edited except for formatting to be consistent with the balance of the AI.

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Chart 5-1a – Derived from data in Table 1a

Appendix H Table 2a (see corresponding Chart 5-2a) shows that low- and moderate-income (LMI) Hispanics received a disproportionate amount of high-cost loans. More than 17 percent of the high-cost loans were issued to LMI Hispanics while just 5.1 percent of the prime loans were issued to LMI Hispanics. (Note: Census data does not break out Hispanic households by income level so we are unable to compare the share of loans by income level to the share of Hispanic households by income level. We are able to compare the share of loans by income level to the share of households by race and income level since Census data does break out households by income level for each race).

Chart 5-2a – Derived from data in Table 2a

Appendix H Table 3a (see corresponding Chart 5-3a) likewise reveals a disproportionate amount of high-cost loans received by middle- and upper-income (MUI) Hispanics. MUI Hispanics received about 71 percent and 65.3 percent of high-cost and prime loans, respectively. In contrast, MUI non-Hispanic whites received 5.34 percent and 19.76 percent of high-cost and prime loans, respectively.

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Chart 5-3a – Derived from data in Table 3a

Predominantly minority neighborhoods received a disproportionate amount of high-cost loans as shown by Table 4a of the tables displaying conventional lending by minority level of neighborhood. Predominantly minority neighborhoods with 80 to 100 percent of the residents being minority contain about 54.36 percent of the owner-occupied housing units but received 76.29 percent of the high-cost loans. In contrast, neighborhoods with 50 to 79 percent of minorities received a portion of high-cost loans (23 percent) that was almost half of their portion of owner-occupied units (42 percent). These substantially minority neighborhoods received a portion of prime loans (35 percent) that was greater than their portion of high-cost loans.

Market Share Analysis of All Conventional Single Family Lending in Lower Rio Grande Valley, Texas.

Appendix H Table 1b (see corresponding Chart 5-1b) shows market share ratios in Lower Rio Grande Valley that are not controlled for income. The table reveals that Hispanics are 2.6 times more likely to receive a high-cost loan than non-Hispanic whites. About 51 percent of all loans to Hispanics are high-cost compared to 19.6 percent of all loans to non-Hispanic whites being high-cost. Dividing 50.7 percent by 19.6 percent yields the result that Hispanics are 2.6 times more likely to receive a high-cost loan than non-Hispanic whites during 2008.

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Chart 5-1b – Derived from data in Table 1b

In Appendix H Table 2b (see corresponding Chart 5-2b), LMI Hispanics are 1.19 times more likely to receive a high-cost loan compared to LMI non-Hispanic white borrowers. (The ratio is calculated by dividing 73.2 percent of loans being high-cost for LMI Hispanics by 61.5 percent of loans being high-cost for LMI non-Hispanic whites).

Chart 5-2b – Derived from data in Table 2b

Appendix H Table 3b (see corresponding Chart 5-3b) shows that, MUI Hispanics are 2.57 times more likely to receive a high-cost loan than MUI non-Hispanic whites (divide 47.3 percent of the loans being high-cost for MUI Hispanics by 18.4 percent of the loans being high-cost for MUI non-Hispanic whites). Ethnic disparities in lending increase as income levels increase. The disparity ratio is higher when comparing MUI Hispanics to MUI non-Hispanic whites than when comparing LMI Hispanics to LMI non-Hispanic whites.

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Chart 5-3b – Derived from data in Table 3b

Residents of minority neighborhoods are much more likely than those of predominantly white neighborhoods to receive high-cost loans. Appendix H Table 4b of conventional lending by minority level of neighborhood shows that residents of substantially minority neighborhoods (50 to 79 percent minorities) are 1.59 times more likely to receive high-cost loans than residents of neighborhoods with 20 to 49 percent minorities (divide 34.7 percent of loans being high-cost in substantially minority neighborhoods by 21.8 percent of the loans being high-cost in neighborhoods with 20 to 49 percent minorities).

Conventional Denial Disparity Analysis.

The overall denial rate (Appendix H Table 1c, see Chart 5-1c) is approximately 47 percent in Lower Rio Grande Valley. The denial rate for non-Hispanic white individuals is about 32 percent, and the denial rate for Hispanics is about 50 percent, which shows that Hispanics are 1.53 times more likely to be denied (divide 50 percent of the denial rate for all Hispanics by 32 percent of the denial rate for all non-Hispanic whites). The denial ratio for African Americans is 1.5 times higher than non-Hispanic whites (divided 48.75 percent of the denial rate for all African Americans by 32 of the denial rate for all non-Hispanic whites).

Chart 5-1c – Derived from data in Table 1c

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LMI Hispanic or Latino borrowers have a denial rate for loans (61.5 percent) that is just four percentage points higher than the denial rate (of 57.5 percent) of LMI non-Hispanic whites (Appendix H Table 2c, see Chart 5-2c).

Chart 5-2c – Derived from data in Table 2c

Among MUI individuals (Appendix H Table 3c, see Chart 5-3c), Hispanic or Latino borrowers experience denial rates noticeably higher than those of non-Hispanic whites. MUI Hispanics are 1.53 times more likely to be denied compared with MUI non-Hispanic white borrowers. LMI Hispanics are 1.07 times more likely than LMI non-Hispanic whites to be denied. Similarly, MUI African-Americans are 1.51 times more likely than MUI non-Hispanic whites to be denied. Ethnic and racial denial disparities increase as income levels increase.

Chart 5-3c – Derived from data in Table 3c

Residents of substantially minority neighborhoods (50 to 79 percent minority) are 1.33 times more likely than the mixed neighborhoods (20 to 49 percent minority) to be denied loans. Almost 41 percent of the applicants from substantially minority neighborhoods are denied loans in contrast to 31 percent of the applicants from the mixed neighborhoods. Similarly, residents of

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 117 of 196 predominantly minority neighborhoods (80 to 100 percent minority) are 1.62 times more likely than the mixed neighborhoods (20 to 49 percent minority) to be denied loans.

Portfolio Share Analysis of All FHA Single Family Lending in Lower Rio Grande Valley, Texas.

NCRC expanded the Lower Rio Grande Valley analysis to include information on FHA lending. FHA loans are guaranteed by the Federal government, specifically the Federal Housing Administration (FHA). Borrowers pay an upfront premium and an annual premium to help fund FHA insurance. The FHA insurance covers the costs of defaults. In other words, the government, through FHA fees on borrowers, covers the costs of defaults. In contrast, conventional lending involves lenders themselves absorbing the costs of defaults. Often, lending institutions will protect themselves against loss by requiring borrowers to pay for private mortgage insurance.

The total number of FHA loans was smaller than total number of conventional loans in Lower Rio Grande Valley in 2008. Lenders issued 477 high-cost FHA loans and 2,855 high-cost conventional loans, and 1,581 prime FHA loans and 3,518 prime conventional loans in Lower Rio Grande Valley.

What is particularly relevant for our analysis is whether minorities are much more likely relative to whites to receive high-cost FHA loans. FHA lending has not been saddled with the abusive tricks, traps, and fees of many subprime loans. Yet, it remains the case that FHA loans are more expensive than conventional loans. If minorities receive a disproportionate amount of high-cost FHA loans and/or prime FHA loans relative to conventional loans, stakeholders should take steps to increase the amount of conventional lending to minorities.

Similar to the results for conventional lending, Appendix H Table 1a (see corresponding Chart 5- 1.1a) for FHA lending shows that Hispanics have a high ratio of high-cost FHA loans compared to the percentage of households. With 79 percent of the households in Lower Rio Grande Valley, Hispanics received 90.2 percent of high-cost FHA loans. The share of high-cost FHA loans for Hispanics or Latinos was 1.14 times greater than their share of households in Lower Rio Grande Valley. Hispanics also received a higher share of prime FHA loans (84.1 percent) than their share of households (79 percent). It should also be noted that Hispanics received a higher share of prime FHA loans than prime conventional loans (84.1 percent versus 72.5 percent). Since

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FHA loans are more expensive than prime loans, stakeholders should increase their efforts to make prime conventional loans to Hispanics.

Chart 5-1.1a – Derived from data in Table 1a

In contrast to Hispanics, non-Hispanic whites received shares of prime (10.4 percent) and high- cost (7.4 percent) FHA loans that were lower than their share of households (19.4 percent) in Lower Rio Grande Valley. Non-Hispanic whites also received a share of prime conventional loans (of 20 percent) that was the almost equal to their share of households and a share of high- cost conventional loans (6 percent) smaller than their share of households. It should be noted that non-Hispanic whites received higher share of prime conventional loans than prime FHA loans.

Appendix H Table 2a (See corresponding Chart 5-1.2a) for FHA lending shows that LMI Hispanics received a disproportionate amount of high-cost FHA loans. About 8 percent of the high-cost FHA loans were issued to LMI Hispanics while just 5.1 percent of the prime FHA loans were issued to LMI Hispanics.

FHA Chart 5-1.2a – Derived from data in Table 2a

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Similar to Appendix H Table 2a, Appendix H Table 3a (see corresponding Chart 5-1.3a) shows disparities in high-cost FHA lending for middle- and upper-income borrowers. MUI Hispanics received a share of prime FHA loans (76.6 percent) that was 4.3 percentage points lower than their share of high-cost FHA loans (80.9 percent). In contrast, MUI non-Hispanic whites received 9.61 percent of prime FHA loans which was 2.5 percentage points higher than their share of high-cost FHA loans (7.05 percent).

FHA Chart 5-1.3a – Derived from data in Table 3a

An examination of FHA lending trends by minority level of neighborhood shows that the predominant lending disparity is the overall share of FHA loans issued to predominantly minority neighborhoods (80 to 100 percent of the residents are minority). Predominantly minority neighborhoods received 74.4 percent of the high-cost FHA loans but received 69.7 percent of prime FHA loans in 2008. In contrast, neighborhoods with 50 to 79 percent of minorities received a portion of high-cost FHA loans (24.9 percent) that was lower than their portion of prime FHA loans (29.3 percent).

Market Share Analysis of All FHA Single Family Lending in Lower Rio Grande Valley, Texas.

The overall market share ratio (Appendix H Table 1b, see Chart 5-1.1b) shows that 24.3 percent of the loans received by Hispanics are high-cost FHA loans while 17.4 percent of the loans received by non-Hispanic whites were high-cost FHA loans during 2008. Thus, Hispanics are 1.4 times more likely to receive a high-cost FHA loan than non-Hispanic whites.

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Chart 5-1.1b – Derived from data in Table 1b

LMI Hispanics are 1.57 times more likely to receive a high cost FHA loan than LMI non- Hispanic whites (Appendix H Table 2b, see Chart 5-1.2b).

Chart 5-1.2b – Derived from data in Table 2b

MUI Hispanics are also 1.34 times more likely to receive high cost FHA loans when compared to their white counterparts (Table Appendix H 3b, see Chart 5-1.3b). Thus, the trend of increasing ethnic disparities as income levels increase are not observed with high-cost FHA lending in contrast to high-cost conventional lending.

Chart 5-1.3b – Derived from data in Table 3b

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FHA Loan Denial Disparity Analysis.

The overall denial rate for all FHA loans (Appendix H Table 1c, see Chart 5-1.1c) in Lower Rio Grande Valley is 23.5 percent. The denial rate for non-Hispanic whites (22.6 percent) and Hispanics (23 percent) is similar to the overall denial rate. In contrast, African Americans (8 percent) and Asians (11.8 percent) have lower denial rates compared to the overall denial rate.

Chart 5-1.1c – Derived from data in Table 1c

The overall denial rate for LMI individuals (Appendix H Table 2c, see Chart 5-1.2c) is 40.5 percent, with the denial rate for LMI non-Hispanic white borrowers being 50 percent and LMI Hispanics being 39 percent.

Chart 5-1.2c – Derived from data in Table 2c

MUI non-Hispanic whites experienced a denial rate of 21.7 percent and MUI Hispanics had a denial rate of 20.7 percent for FHA loans.

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Chart 5-1.3c – Derived from data in Table 3c

Summary and Conclusions.

 In Lower Rio Grande Valley, the portion of all prime conventional loans received by Hispanic borrowers (72.5 percent of prime loans versus 79.2 percent of households) were lower than the loans received by non-Hispanic white borrowers (20.7 percent of prime loans versus 19.4 percent of households) compared to their portions of households.

 The share of high-cost conventional loans received by Hispanics is 1.16 times greater than their share of households.

 Both MUI Hispanics and LMI Hispanics are more likely to receive a high-cost loan than their non-Hispanic white counterparts during 2008. MUI Hispanics are about 3 times more likely to receive a high-cost loan than MUI non-Hispanic whites and LMI Hispanics are 1.2 times more likely to receive a high-cost loan than LMI non-Hispanic whites. Ethnic disparities in conventional lending increase as income levels increase in Lower Rio Grande Valley.

 The denial rate of conventional loans is higher when comparing MUI Hispanics to MUI non-Hispanic whites than when comparing LMI Hispanics to LMI non-Hispanic whites. MUI Hispanics are 1.53 times more likely to be denied than MUI non-Hispanic whites, while LMI Hispanics are just 1.07 times more likely than LMI non-Hispanic whites to be denied. Again, ethnic disparities in conventional lending increase as income levels increase in Lower Rio Grande Valley.

 Both MUI and LMI Hispanics received a higher share of FHA high-cost loans than their non-Hispanic white counterparts. MUI Hispanics are 1.34 times more likely to receive a high-cost FHA loan than MUI non-Hispanic whites, while LMI Hispanics are 1.57 times more likely to receive a high-cost FHA loan than LMI non-Hispanic whites during 2008.

 Hispanics received a higher share of prime FHA loans than prime conventional loans (84.1 percent versus 72.5 percent) in Lower Rio Grande Valley. Also, with 79.2 percent of the households in Lower Rio Grande Valley, Hispanics received 90.2 percent of high-

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 123 of 196

cost FHA loans during 2008. Since FHA loans are more expensive than prime loans, stakeholders should increase their efforts to make prime conventional loans to Hispanics.

 Non-Hispanic whites received a slightly higher share of high-cost conventional loans than high-cost FHA loans (7.4 percent versus 6.1 percent). However, it should be noted that non-Hispanic whites received a higher share of prime conventional loans than prime FHA loans (20.7 percent versus 10.4 percent).

 While ethnic disparities are observed in prime and high-cost conventional lending, disparities do not appear to increase as income levels increase in FHA lending in contrast to conventional lending. This suggests that fair lending concerns maybe of a lower magnitude in FHA than conventional lending since disparities in FHA lending do not increase as income levels increase. Stakeholders should nevertheless take steps to narrow disparities in both conventional and FHA lending through more marketing of conventional loans in minority communities.

Lack of Affordable Housing.

While this is an impediment almost everywhere in Texas, it is especially a problem in the LRGV. Information from local organizations indicated that there were more than 6,500 people on a public housing waiting list in Cameron County and Hidalgo Housing Authority reports that it has 1,794 on its housing voucher waiting list. The Colonias, (addressed on their own later) also indicate that there is a lack of affordable housing up to standards available for rent or purchase in the region. Many homes that are available have flooding problems or other infrastructure failings.

Bureaucracy in Delivery Systems.

Closely related to questions about how money is spent, interviews indicated that there is a perception about the various levels that must be navigated to receive benefits. Specifically, the expenditure of disaster recovery funds was highlighted as a problem. Many people did not understand how the programs were being administered—especially the FEMA declarations of not availability due to deferred maintenance—and felt that the system was somehow not fair.

Looking at Project Placement.

In reviewing the projects contained in Appendix F, two issues become obvious. Most CDBG funds not including disaster funds, whether supplied by the State or used by entitlement communities go almost exclusively to infrastructure projects. The difficulty of determining how

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 124 of 196 the funds are spent is compounded by the manner in which data is reported. Looking at the table very few infrastructure projects have a clear delineation of whom they are directly serving and where the project is located. Without an ability to reference the population served (other than the generic 51 percent plus LMI language), it is difficult to determine who is receiving the benefit of the projects. Because so many of the regular CDBG funds are listed in this manner at both the entitlement jurisdiction and the State the information is not useable to determine if a community is using funds to further fair housing.

In addition, in reviewing Appendix F, very little of non-disaster CDBG funds go to housing. In part this may be because of available funds for infrastructure. A state or local preference for infrastructure use may have been present, but the CDBG Action Plan has a policy that says it supports the use of CDBG funds for the construction of housing. The limitations of funds available and the competitive nature of the funds may factor into the use of funds. Despite the CDBG Action Plan expressed support for building housing with CDBG funds, competitive applications rounds should be reviewed to see if they favor infrastructure over housing in scoring.

The impediment here may actually be the lack of specificity and record keeping by local and state governments for use in conducting their analysis of impediments to fair housing.

Colonias.

Neighborhood classification was identified as a significant problem in focus groups, interviews and background research. The areas brought up were colonias, “barrios,” or “mexicano” where people had moved into better neighborhoods and the vacant areas that were inhabitant by less established residents or in the case of colonias potentially unscrupulous developers took advantage of low income or unsophisticated people to crate large infrastructure free areas through a contract for deed system. The Colonias create a legal nightmare as the land has not been platted, homes have not been built to codes along with a myriad of other problems.

According to a report by the Dallas Federal Reserve System in 2001, many Colonias still use septic tanks and cesspools and purchase water by the bucket and drum or use potentially contaminated wells. The report found that as recently as June 2000, only 54 percent of Texas colonia residents surveyed had sewer service and more than 50 percent drank water from sources other than taps. Even when the infrastructure is put in place many colonias residents do not have

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 125 of 196 hookups because their houses can't pass inspections to qualify and the owners can't afford repairs or improvements to meet codes. The report notes that Colonia Legislation passed in 1995 prohibits developers from selling lots in existing colonias without water and wastewater treatment services, although some cities and counties lack staffing to enforce the complex law.139

Several Community groups have formed together to attempt to stop the development of further Colonias and assist the people living in the existing Colonias. Several state run programs are dedicated to repair and replacement of Colonias. There are Contract for Deed conversions, Self- Help Centers, legal assistance by groups like CDC-Brownsville and Proyecto Azteca, that was created in 1991 by United Farm Workers (UFW) and Texas Rural Legal Aid (TRLA).

Enforcement actions are being done to deter future colonia developments. Texas Attorney General Abbott has raised and resolved issues including a legal action against the Cameron County colonia developer of Tierra Linda Gardens for $30,000 in civil penalties for unlawful colonia subdivision.140

Status of Undocumented Aliens.

Nowhere is the issue of how to treat undocumented or “illegal” aliens a bigger issue than in the LRGV. The subject is the matter of intense debate in the state’s and nation’s capitols, and it is high stakes politics for many elected officials. The federal government has uneven and/or confusing rules as to who can or cannot be included in programs statutorily excluding them in some programs and remaining silent in others. This lack of guidance creates different standards and leaves the matter up for local public debate as to whether it is even in the Fair Housing question as this form of discrimination is not based on a protected class status, but on a legal status.

139 Texas Colonias Housing and Infrastructure Issues by Ariel Cisneros Federal Reserve Bank of Dallas June 2001, retrieved at http://www.dallasfed.org/research/border/tbe_cisneros.html 140 New Release Feb 11, 2008 Office of the Attorney General of Texas retrieved from https://www.oag.state.tx.us/oagnews/release.php?id=2365

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SECTION 6. EVALUATION OF SMALL COMMUNITIES—DEEP EAST TEXAS COUNCIL OF GOVERNMENTS.

Up to this point we have predominately looked at urban areas (or communities in close proximity or within the MSA) that are either participating jurisdictions or have staff resources to potentially address issues. In this section the AI will look toward the smaller communities—targeting smaller counties and cities with less than 2500 residents—that even if they are participating jurisdictions, the amount of funding is not adequate for the purpose of hiring significant staff or operating large programs.

For some of the analysis, the major disaster funding recipient, Deep East Texas Council of Governments (DETCOG), will be the representative organization. Other analysis will include data from the rural portions of the Comptroller’s Uniform State Service Regions that fall within the disaster areas. Even though the entire region is not included in the impacted areas that make up DETCOG or the other counties, we will include data for the Upper East Texas Region (4), Southeast Texas Region (5) (rural), and the Central Texas Region (8) (rural). Where we have the information available we will provide breakouts at the county level. Finally, for some data we will need to include statewide information as the best available.

This section will more clearly develop the local demographic information and look at potential impediments to Fair Housing that exist in the area.

Historical Recap.

The twelve counties comprising the Deep East Texas Council of Governments (DETCOG) are: Angelina, Houston, Jasper, Nacogdoches, Newton, Polk, Sabine, San Augustine, San Jacinto, Shelby, Trinity and Tyler. The “Deep East Texas” descriptor comes from the phrase “Deep in the Pineywoods of East Texas.” Geographically this is an area noted for its temperate climate, high annual rainfall amounts and long growing season that has resulted in the development of forest with dense undergrowth.

This region was originally populated by the Ayish, Alabama, Atakapa, Caddo, Cherokee, Coushatta and Kickapoo Indians. Spanish missions were established in Houston County (1690)

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 127 of 196 and San Augustine County (1717) to bring organized western religion to Native Americans and provide a barrier to French encroachment from Louisiana. Spanish land grants attracted Anglo Settlers to the region in the early 1800’s. Several of the first counties of the Republic of Texas were formed in the Deep East Texas Region. Records indicate Houston County once had cotton plantations worked by slaves. San Augustine, Shelby and Newton Counties were noted as antebellum slave holding areas.

Forestry and the forest products industry dominated the regional economy since the civil war, but they have seen a decline in the last twenty years. Since World War II the poultry raising and processing industry has developed in the northern parts of the region. The 2000 Census shows the top three highest numbers of people per employment classification in the region as being Manufacturing (14.7%) and Retail Trade (12.6%) with Education Services (11.2%) and Health Care and Social Assistance (11.2%) a close third.141

Counties of Deep East Texas are mostly rural with the total population in 2008 of all twelve counties comprising the Deep East Texas Council of Government (DETCOG) region at slightly more than 286,000.142 The counties are similar demographically averaging slightly under 80 percent white, 15 percent African American and 6 percent Hispanic. Sabine has the largest percentage of white residents with 87.5 percent and the lowest percentage of African Americans with 10 percent. It also has the lowest percentage of Hispanic residents with 2.5 percent. Houston County had the lowest percentage of white residents at 72.4 percent and the highest percentage of African Americans at 26.1 percent. Shelby County had the highest percentage of Hispanics with 15.8 percent.

In the mid-1970’s a coalition of Black Leaders, most notably Texas State Representative, Paul B. Ragsdale of Dallas, and activist lawyers organized “The East Texas Project.” A U.S. Supreme Court ruling prohibited the dilution of minority voting strength in the drawing of political boundaries. The “East Texas Project” sued 48 counties/cities in East Texas with significant concentrations of black voters for having political boundaries that diluted the voting power of minority citizens. The settlements of these cases resulted in local redistricting that created precincts and wards where it was possible to elect black officials. Since that time there have

141 From Texas statutes, Fulmore’s History and Geography of Texas as told in County Names, WPA Historical Records Survey, Texas Centennial Commission Report, the New Handbook of Texas, and the 2000 Census. 142 U.S. Census Bureau; American Community Survey 2008. This is also the source for the other demographic percentages in this paragraph.

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 128 of 196 been Black county commissioners in at least 6 of the 12 counties that comprise the Deep East Texas Council of Governments. Black city commissioners have been elected in several municipalities. As an example, in late 2010 four of the five city commissioners serving in Jasper are Black. That’s a considerable improvement since the 1998 dragging death of James Byrd, Jr. and the subsequent two death sentences handed down by predominantly white juries in Deep East Texas.

Several Black mayors have served the region in Jasper, San Augustine (2), Browndell and Huntington. In the early 1980s board structure of the Deep East Texas Council of Governments was also changed to include a voting “minority representative” from each county to increase participation in the council and to affirmatively further fair housing in the region.143

Regional Demographic Recap.

Population.

The DETCOG area is not expected, compared to other parts of Texas, to experience significant growth between now and 2040 according to the state demographers at the University of Texas at San Antonio. Under the Zero Net Migration formula (0.0 Scenario) unlike other parts of Texas, the Hispanic population grows only slightly and the racial make-up of the community remains roughly the same as it is currently with a slight movement toward a larger minority population by 2040. Assuming rates of net migration equal to one-half of 1990-2000 totals (0.5 Scenario) the Hispanic population grows significantly, accounting for most of the growth in the region along with slight increases in Anglo and Black population by 2040.144

122 Murder of James Byrd, Jr. – Wikipedia, the free encyclopedia, en.widipedia.org/wiki/Murder_of_James Byrd. Jr., DETCOG Board Minutes, May 1980, Volume III, page, 5. 144 These projections assume the One-Half 1990-2000 Migration (0.5) Scenario. According to the State Demographer: This scenario has been prepared as an approximate average of the zero (0.0) and 1990-2000 (1.0) scenarios. It assumes rates of net migration one-half of those of the 1990s. The reason for including this scenario is that many counties in the State are unlikely to continue to experience the overall levels of relative extensive growth of the 1990s. A scenario which projects rates of population growth that are approximately an average of the zero and the 1990-2000 scenarios is one that suggest slower than 1990-2000 but steady growth. Information for Table 4-1 pulled from Table 2.7 Population for the State of Texas and Council of Government Regions in Texas and Projections to 2040 Assuming Alternative Projection Scenarios SETRPC Region data http://txsdc.utsa.edu/pubsrep/

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Table 6-1 Projected Population DETCOG Region Year Anglo Black Hispanic Other Total

2000 262,411 58,721 31,203 3,527 355,862 Anglo Anglo Black Black Hispanic Hispanic Other 0ther Total Total Year 0.0 0.5 0.0 0.5 0.0 0.5 0.0 0.5 0.0 0.5 scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario

2010 256,441 271,642 60,564 61,772 38,431 43,568 3,921 3,955 359,357 380,937

2020 250,426 278,147 62,242 64,187 45,907 59,276 4,259 4,372 362,834 405,982

2040 235,086 270.604 60,841 63,537 58,239 99,626 4,496 4,707 359,662 438,474

Table 6-2 Projected Population Anderson County Year Anglo Black Hispanic Other Total

2000 34,970 13,006 6,705 428 55,109 Anglo Anglo Black Black Hispanic Hispanic Other 0ther Total Total Year 0.0 0.5 0.0 0.5 0.0 0.5 0.0 0.5 0.0 0.5 scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario

2010 35,471 36,369 13,494 13,696 7,840 8,503 498 499 57,303 59,067

2040 34,704 35,290 14,133 14,942 11,357 15,373 658 704 60,852 66,309

Table 6-3 Projected Population Cass County Year Anglo Black Hispanic Other Total

2000 23,709 5,999 526 204 30,438 Year Anglo Anglo Black Black Hispanic Hispanic Other 0ther Total Total 0.0 0.5 0.0 0.5 0.0 0.5 0.0 0.5 0.0 0.5 scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario

2010 23,185 23,501 6,201 6,288 625 628 230 234 30,241 30,651

2040 20,271 19,739 6,529 6,713 873 798 306 318 27,979 27,568

Table 6-4 Projected Population Cherokee County Year Anglo Black Hispanic Other Total

2000 32,568 7,545 6,718 368 46,659 Year Anglo Anglo Black Black Hispanic Hispanic Other 0ther Total Total 0.0 0.5 0.0 0.5 0.0 0.5 0.0 0.5 0.0 0.5 scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario

2010 32,519 33,658 7,916 8,091 8,014 9,221 391 394 48,840 51,364

2040 31,014 33,051 8,690 9,151 13,806 24,0109 392 395 53,902 66,607

Table 6-5 Projected Population Grimes County Year Anglo Black Hispanic Other Total

2000 14,904 4,716 3,787 145 23,552 Year Anglo Anglo Black Black Hispanic Hispanic Other 0ther Total Total 0.0 0.5 0.0 0.5 0.0 0.5 0.0 0.5 0.0 0.5 scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario

2010 15,060 36,369 5,118 13,696 4,602 8,503 162 499 24,942 27,227

2040 14,805 21,059 5,725 6,297 6,959 9,938 145 150 27,634 37,444

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Table 6-6 Projected Population Harrison County Year Anglo Black Hispanic Other Total

2000 42,356 14,900 3,316 448 62,110 Year Anglo Anglo Black Black Hispanic Hispanic Other 0ther Total Total 0.0 0.5 0.0 0.5 0.0 0.5 0.0 0.5 0.0 0.5 scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario

2010 43,962 46,097 15,404 16,088 4,346 5,685 489 491 64,201 68,361

2040 40,245 45,744 14,783 16,888 8,078 22,326 510 515 63,616 85,473

Table 6-7 Projected Population Leon County Year Anglo Black Hispanic Other Total

2000 12,428 1,596 1,213 98 15,335 Year Anglo Anglo Black Black Hispanic Hispanic Other 0ther Total Total 0.0 0.5 0.0 0.5 0.0 0.5 0.0 0.5 0.0 0.5 scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario

2010 12,205 13,452 1,690 1,709 1,442 1,551 104 106 15,441 16,818

2040 11,490 14,457 1,847 1,818 1,948 2,532 108 109 15,393 18,916

Table 6-8 Projected Population Madison County Year Anglo Black Hispanic Other Total

2000 7,857 2,945 2,042 96 12,940 Year Anglo Anglo Black Black Hispanic Hispanic Other 0ther Total Total 0.0 0.5 0.0 0.5 0.0 0.5 0.0 0.5 0.0 0.5 scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario

2010 7,912 8,474 3,154 3,103 2,484 2,426 93 95 13,643 14,098

2040 8,193 9,860 3,270 3,163 3,256 4,002 87 91 14,086 17,116

Table 6-9 Projected Population Marion County Year Anglo Black Hispanic Other Total

2000 7,919 2,644 263 115 10,941 Year Anglo Anglo Black Black Hispanic Hispanic Other 0ther Total Total 0.0 0.5 0.0 0.5 0.0 0.5 0.0 0.5 0.0 0.5 scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario

2010 7,600 8,409 2,808 2,826 279 281 130 131 10,817 11,647

2040 6,266 8,185 3,197 3,171 294 291 153 154 9,910 11,801

Table 6-10 Projected Population Milam County Year Anglo Black Hispanic Other Total

2000 16,878 2,669 4,516 175 24,238 Year Anglo Anglo Black Black Hispanic Hispanic Other 0ther Total Total 0.0 0.5 0.0 0.5 0.0 0.5 0.0 0.5 0.0 0.5 scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario

2010 16,441 17,015 3,011 3,014 5,627 5,869 184 183 25,263 26,081

2040 15,501 16,228 3,523 3,411 8,773 10,532 165 163 27,962 30,334

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Table 6-11 Projected Population Morris County Year Anglo Black Hispanic Other Total 13,048 2000 9,298 3,166 477 107 Year Anglo Anglo Black Black Hispanic Hispanic Other 0ther Total Total 0.0 0.5 0.0 0.5 0.0 0.5 0.0 0.5 0.0 0.5 scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario

2010 9,177 9,276 3,329 3,340 587 598 116 118 13,219 13,332

2040 8,252 35,290 3,326 14,942 947 15,373 151 152 12,972 12,599

Table 6-12 Projected Population Panola County Year Anglo Black Hispanic Other Total

2000 17,744 4,061 798 153 22,756 Year Anglo Anglo Black Black Hispanic Hispanic Other 0ther Total Total 0.0 0.5 0.0 0.5 0.0 0.5 0.0 0.5 0.0 0.5 scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario

2010 17,811 18,280 4,408 4,498 970 999 162 163 23,351 23,940

2040 34,704 16,912 14,133 5,111 11,357 1,620 658 164 60,852 23,807

Table 6-13 Projected Population Robertson County Year Anglo Black Hispanic Other Total

2000 9,687 3,858 2,359 96 16,000 Year Anglo Anglo Black Black Hispanic Hispanic Other 0ther Total Total 0.0 0.5 0.0 0.5 0.0 0.5 0.0 0.5 0.0 0.5 scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario

2010 9,507 10,158 4,237 4,298 2,891 3,084 105 103 16,740 17,643

2040 9,275 10,729 5,255 5,360 4,550 6,055 119 118 19,199 22,262

Table 6-14 Projected Population Rusk County Year Anglo Black Hispanic Other Total

2000 33,924 9,148 3,998 302 47,372 Year Anglo Anglo Black Black Hispanic Hispanic Other 0ther Total Total 0.0 0.5 0.0 0.5 0.0 0.5 0.0 0.5 0.0 0.5 scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario

2010 33,583 34,251 9,251 9,375 5,055 5,854 337 338 48,226 48,226

2040 31,182 31,182 8,865 8,865 8,254 8,254 389 389 48,690 48,600

Table 6-15 Projected Population Washington County Year Anglo Black Hispanic Other Total

2000 21,608 5,670 2,647 448 30,373 Year Anglo Anglo Black Black Hispanic Hispanic Other 0ther Total Total 0.0 0.5 0.0 0.5 0.0 0.5 0.0 0.5 0.0 0.5 scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario

2010 20,689 22,193 6,185 6,275 3,438 3,894 522 525 30,835 32,887

2040 34,704 22,196 14,133 7,406 11,357 9,178 658 712 60,852 39,492

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Age.

Table 6-17 shows the population’s anticipated aging according to the demographers located at the University of Texas at San Antonio for the DETCOG Region. This table demonstrates that the percentage of the population who is over sixty five will increase in raw numbers within the age category and as a percentage of the population as a whole.145 The 2040 data assumes rates of net migration equal to one-half of 1990-2000 (.5 Scenario) and is neither the least nor the most conservative estimate by the demographers.

Table 6-16 Age by Age Group and Ethnicity Age Group Anglo Anglo Black Black Hispanic Hispanic Other Other Total Total 2000 2040 2000 2040 2000 2040 2000 2040 2000 2040 <18 22.4 19.0 30.3 19.2 37.2 28.8 27.5 16.9 25.1 21.2 18-24 9.2 6.8 10.3 8.9 12.1 10.5 10.9 7.0 10.2 10.0 25-44 24.8 23.4 28.8 29.8 33.1 30.0 30.5 22.8 26.3 25.9 45-64 25.2 24.2 18.7 27.7 11.1 20.4 22.1 20.8 22.8 23.5 65+ 18.3 24.2 10.6 13.0 2.9 8.7 9.0 30.6 15.6 19.1 Median 40.3 43.5 31.0 38.7 23.7 30.5 32.7 46.4 36.8 39.2

Poverty and Income.

The table to the right depicts the number of Table 6-17 Region 5 Poverty Figures, 2010 families living below the poverty line in Region At or above poverty Below poverty 5. Of the 30,061 families living below poverty, Families Percent Families Percent approximately 44.6 percent are living in urban Rural 84,231 83.5% 16,666 16.5% Urban 87,993 86.8% 13,395 13.2% areas, with the remaining 55.4 percent in rural Region 5 Total 172,224 85.1% 30,061 14.9% 146 areas. Additionally, the percentage of total rural Source: Nielsen Claritas, Ribbon Demographics, 2010. families that are below poverty is slightly higher than the percentage of total urban families.

Region 5 Household Incomes. The pie chart to the left depicts the income Extremely Low Income (0-30%), breakdown of the 274,543 households in the region. 14% Approximately 43 percent of the households are low Very Low Income (31%-50%), 12% Higher Income income. There are 138,673 individuals living in Low Income (over 95%), 50% poverty in the region, which makes up 15.2 percent (51%-80%), 17% of the regional population. Moderate Income (81%-95%) , 7%

145 Table 2.14 Percentage of Population for the State of Texas and Council of Government Regions in Texas by Age and Race/Ethnicity of the Population and Median Age by Race/Ethnicity in 2000 and Projections to 2040 Assuming Alternative Projection Scenarios HGAC Region data http://txsdc.utsa.edu/pubsrep/ 146 DETCOG region is all the rural section of Region 5. The Urban areas are represented by Southeast Texas Regional Planning Commission

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Homeless Persons.

According to 2010 population projections by Ribbon Demographics, this region has approximately 2.3 percent of the statewide total of people in non-institutional group quarters, including shelters.

Region 5 also experienced significant damage from Hurricane Rita, which hit the southeast Texas area in September 2005 and Hurricane Ike in September 2008. According to FEMA, $190 million worth of damage was reported after Hurricane Rita and $29.4 billion after the 2008 hurricane season. Households affected by the hurricane have unmet needs.

Table 6-18 Region 5 persons in other group quarters, 2010 Region 5 Homeless persons % of State Total Statewide Homeless Population Rural 537 8.3% 6,449 Urban 990 1.6% 61,249 Total 1,527 2.3% 67,698 Source: Nielsen Claritas, Ribbon Demographics, 2010.

Table 6-19 By County persons in other group quarters, 2010 County Homeless Persons3 Anderson 81 Angelina 287 Bowie 358 Brazos 286 Burleson 0 Cass 11 Cherokee 133 Gregg 296 Grimes 5 Hardin 23 Harrison 93 Houston 0 Jasper 10 Leon 0 Madison 10 Marion 0 Milam 1 Morris 0 Nacogdoches 143 Newton 0 Panola 17 Polk 63 Robertson 3 Rusk 22

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County Homeless Persons3 Sabine 4 San Augustine 1 San Jacinto 3 Shelby 26 Smith 1389 Trinity 0 Tyler 0 Upshur 0 Washington 61 US Census Bureau 2000

PERSONS WITH DISABILITIES.

According to the US Census, of the total population in Region 5, persons with disabilities account for approximately 20 percent of the population. Of this total, approximately 49.5 percent are residing in urban areas, with the remaining 50.5 percent in rural areas.

Table 6-20 Region 5 Persons With and Without Disabilities, 2000 Persons with Persons without disabilities disabilities Total Rural 121,482 468,082 589,564 Urban 29,047 122,341 151,388 Total 150,529 590,423 740,952 Source: Census 2000, Urban defined by presence of an MSA.

Table 6-21 breaks out the disability population by county for the Central and East Texas Counties that are disaster fund eligible. Every county has some percentage of their population with disabilities and this could increase with the aging of the population.

Table 6-21 By County Person with Disabilities

County Persons with a disability Anderson 9,200 Angelina 16,023 Bowie 18,284 Brazos 17,616 Burleson 3,795 Cass 7,177 Cherokee 10,049 Gregg 22,192 Grimes 4,553

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County Persons with a disability Hardin 8,688 Harrison 12,777 Houston 4,336 Jasper 7,693 Leon 3,422 Madison 2,285 Marion 3,165 Milam 4,584 Morris 2,988 Nacogdoches 10,869 Newton 3,513 Panola 4,870 Polk 9,222 Robertson 3,744 Rusk 9,547 Sabine 2,594 San Augustine 2,173 San Jacinto 5,289 Shelby 5,891 Smith 35,024 Trinity 3,491 Tyler 4,876 Upshur 7,414 Washington 5,384 Nielsen Claritas, Ribbon Demographics, 2010.

Persons with HIV/AIDS.

According to the Texas Department of State Health Services’ 2010 Texas Integrated Epidemiologic Profile for HIV/AIDS Prevention and Services Planning, there are 1,334 persons living with HIV/AIDS in Region 5. Approximately 66 percent of this population is living in urban areas, with the remaining 34 percent in rural areas. Region 5 has a low rate of persons living with HIV/AIDS compared to the state as a whole, with the East Texas area accounting for only 6 percent of the total. The East Texas area has a rate of 147 persons per 100,000.

Table 6-22 Region 5 Persons with HIV/AIDS, 2008 Persons with HIV/AIDS, 2008 Population 2008 Rural 456 367,834 Urban 878 377,477 Total 1,334 745,311

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Migrant Farmworkers.

In a study prepared for the US Health Resources and Services Administration, Region 5 was found to have a very low proportion of the state’s Migrant and Seasonal Farmworker (MSFW) population, accounting for just 0.8 percent of the 361,414 MSFWs in the state of Texas.147

Table 6-23 Region 5 Migrant and Seasonal Farmworker Population, 2000 Percent of statewide Region 5 MSFW Estimate MSFW Statewide Estimate MSFW population Rural 2,755 1.3% 211,577 Urban 304 0.2% 149,837 Total 3,059 0.8% 361,414

Table 6-24 represents is a county break out of Migrant farm workers.

Table 6-24 by County Migrant and Seasonal Farmworker Population, 2000 Migrant Seasonal County Farmworker Population Anderson 219 Angelina 80 Bowie 213 Brazos 134 Burleson 488 Cass 354 Cherokee 534 Gregg - Grimes 68 Hardin 155 Harrison 124 Houston 915 Jasper 122 Leon 438 Madison 39 Marion 86 Milam 698 Morris 80 Nacogdoches 255 Newton - Panola 60 Polk - Robertson 384 Rusk 1,012 Sabine - San Augustine 186 San Jacinto 17 Shelby 1,101 Smith 763

147 Migrant and Seasonal Farmworker Enumeration Profiles Study – TX, Larson, Alice, 2000.

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Migrant Seasonal County Farmworker Population Trinity 19 Tyler 60 Upshur 78 Washington 73

Local Assistance on Housing Assistance

According to the TDHCA Public Request Assistance Inventory for State Fiscal Year 2010, the agency received 6,880 public assistance requests from Region 5, which accounted for 3.3 percent of total annual requests. Of requests from Region 5, the three most requested categories of assistance were, in order: Rental Assistance, Repair and Weatherization, and Homebuyer Assistance.

Table 6-25

East Texas Impacted Areas Public Assistance Request Inventory, SFY 2010

tance

Legal Legal

Utility Rental

Repair/ Repair/

Disaster Disaster

Assistance Assistance

Assistance Assistance Assistance Assis

Emergency Emergency

Foreclosure Homebuyer Weatherization Region 4 1,525 0 12 1,373 0 3.163 1,210 2,711 Region 5 956 1 2 826 16 2,168 1,130 1,779 Region 8 1,465 3 11 1,779 0 2,675 1,087 1,892 Statewide Total 28,531 29 99 52,437 27 59,711 34,319 35,184

Housing Assessment.

A housing assessment includes the current housing supply, a sample of market-rate housing costs, the housing needs and the availability of subsidized housing.

Region 4 - Housing Supply.

According the 2010 projection, 88.4 percent of the housing units in the region are occupied. Of the total housing stock, 72.3 percent are one unit; 2.2 percent are two units; 11 percent are three or more units; 16.7 are mobile homes; and the rest are boats and RVs.

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Table 6-26 Region 4 Housing Supply, 2010 Rural Urban Total Total housing units 216,801 252,135 468,936 Vacant housing units 29,776 24,812 54,588 Housing units, 1 unit 162,197 176,819 339,016 Housing units, 2 units 3,751 6,447 10,198 Housing units, 3 to 4 units 4,459 7,417 11,876 Housing units, 5 to 19 units 4,628 15,329 19,957 Housing units, 20 to 49 units 1,524 2,160 3,684 Housing units, 50+ units 1,005 3,771 4,776 Housing units, mobile home 38,690 39,706 78,396 Housing units, other 547 486 1,033 Source: Nielsen Claritas, Ribbon Demographics, 2010.

Sample of Market Housing Costs.

According to the Multiple Listing Service records for August 2010, the median home prices for Tyler and Longview-Marshall are $143,100 and $128,400, respectively.148 In addition, the fair market rent for a two bedroom unit in Tyler MSA is $716, requiring an annual income of approximately $28,640, and in Longview-Marshall MSA is $738, which requires an annual income of approximately $29,520. In a sample rural county, Hopkins fair market rent on a two- bedroom apartment is $621, which requires an annual income of approximately $24,840.149

Housing Need.

The housing need indicators analyzed in this section include housing cost burden, substandard housing conditions and housing overcrowding for renter and owner households. The following information comes from the 2000 CHAS database updated with HISTA population projections. There were approximately 115,387 owners and renters with housing problems in 2009.

Table 6-27 Region 4 Households with Housing Problems, 2009 Region Extremely Low Income Very Low Income Low Income Higher Incomes Total (0-30%) (31-50%) (51-80%) (81% and up) Households Extreme Cost Burden 87,846 31,977 23,560 18,322 13,988 Lacking Kitchen and/or Plumbing 5,578 1,724 994 1,002 1,858 Overcrowding 21,963 3,657 3,640 5,408 9,258 Total 115,387 37,357 28,194 24,732 25,104 Source: CHAS Database with projections based on HISTA data.

148 Real Estate Center at Texas A&M University, “Texas Residential MLS Activity,” http://recenter.tamu.edu/data/hs/hs320b.htm (accessed September 24, 2010). 149 National Low Income Housing Coalition. (2010). Out of reach 2010. Retrieved from http://www.nlihc.org/oor/oor2010/

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Region 5 - Housing Supply.

According to 2010 projection, 83.3 percent of the housing units in the region are occupied. Of the total housing stock, 70.7 percent are one unit; 2.0 percent are two units; 11 percent are three or more units; and 17.4 percent are mobile homes. Boats and RVs make up the rest of the housing stock.

Table 6-28 Region 5 Housing Supply, 2010 Rural Urban Total Total housing units 179,313 161,563 340,876 Vacant housing units 37,556 19,213 56,769 Housing units, 1 unit 120,473 120,411 240,884 Housing units, 2 units 3,881 2,791 6,672 Housing units, 3 to 4 units 3,213 3,812 7,025 Housing units, 5 to 19 units 5,355 12,508 17,863 Housing units, 20 to 49 units 918 2,275 3,193 Housing units, 50+ units 1,793 3,339 5,132 Housing units, mobile home 43,306 16,079 59,385 Housing units, other 374 348 722 Source: Nielsen Claritas, Ribbon Demographics, 2010.

Sample of Market Housing Costs.

According to the Multiple Listing Service records for August 2010, the median home prices for Beaumont and Port Arthur are $124,300 and $110,000, respectively.150 In addition, the fair market rent for a two bedroom unit in Beaumont-Port Arthur MSA is $692, requiring an annual income of approximately $27,680.151 In a sample rural county, San Augustine, fair market rent on a two-bedroom apartment is $588, which requires an annual income of approximately $23,520.

Housing Need.

The housing need indicators analyzed in this section include housing cost burden, substandard housing conditions and housing overcrowding for renter and owner households. The following information comes from the 2000 CHAS database updated with HISTA population projections. There were approximately 83,490 owners and renters with housing problems in 2009.

150 Real Estate Center at Texas A&M University, “Texas Residential MLS Activity,” http://recenter.tamu.edu/data/hs/hs440b.htm (accessed September 24, 2010). 151 National Low Income Housing Coalition. (2010). Out of reach 2010. Retrieved from http://www.nlihc.org/oor/oor2010/

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Table 6-29 Region 5 Households with Housing Problems, 2009 Region Extremely Low Income Very Low Income Low Income Higher Incomes Total (0-30%) (31-50%) (51-80%) (81% and up) Households Extreme Cost Burden 62,016 25,949 16,662 11,413 7,993 Lacking Kitchen and/or Plumbing 3,836 1,270 633 733 1,202 Overcrowding 17,638 3,350 2,548 3,968 7,772 Total 83,490 30,569 19,843 16,114 16,967 Source: CHAS Database with projections based on HISTA data.

REGION 8 - Housing Assessment.

Housing Supply.

According to the 2010 projection, 87.4 percent of the total housing units in the region are occupied. Of the total housing stock, 67.3 percent are one unit; 5.4 are two units; 17.0 percent are three or more units; 10.2 percent are mobile homes; and the rest are boats and RVs.

Table 6-30 Region 8 Housing Supply, 2010 Rural Urban Total Total housing units 138,151 303,809 441,960 Vacant housing units 25,190 30,356 55,546 Housing units, 1 unit 103,755 193,464 297,219 Housing units, 2 units 3,032 20,725 23,757 Housing units, 3 to 4 units 2,711 18,968 21,679 Housing units, 5 to 19 units 2,898 37,521 40,419 Housing units, 20 to 49 units 430 6,107 6,537 Housing units, 50+ units 227 6,284 6,511 Housing units, mobile home 24,730 20,561 45,291 Housing units, other 368 179 547 Source: Nielsen Claritas, Ribbon Demographics, 2010.

SAMPLE OF MARKET HOUSING COSTS.

According to the Multiple Listing Service records for August 2010, the median home price for Bryan-College Station is $148,500.152 In addition, the fair market rent for a two bedroom unit in Bryan/College Station MSA is $836, requiring an annual income of approximately $33,440.153 In a sample rural county, Hill, fair market rent on a two-bedroom apartment is $588, which requires an annual income of approximately $23,520.

152 Real Estate Center at Texas A&M University, “Texas Residential MLS Activity,” http://recenter.tamu.edu/data/hs/hs180b.htm (accessed September 24, 2010). 153 National Low Income Housing Coalition. (2010). Out of reach 2010. Retrieved from http://www.nlihc.org/oor/oor2010/

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Housing Need.

The housing need indicators analyzed in this section include housing cost burden, substandard housing conditions and housing overcrowding for renter and owner households. The following information comes from the 2000 CHAS database updated with HISTA population projections. There were approximately 119,258 owners and renters with housing problems in 2009.

Table 6-31 Region 8 Households with Housing Problems, 2009 Region Extremely Low Income Very Low Income Low Income Higher Incomes Total (0-30%) (31-50%) (51-80%) (81% and up) Households Extreme Cost Burden 90,612 34,211 23,462 19,895 13,043 Lacking Kitchen and/or Plumbing 4,173 1,240 805 789 1,340 Overcrowding 24,473 4,191 3,775 6,648 9,859 Total 119,258 39,641 28,042 27,332 24,242 Source: 2000 CHAS Database with projections based on HISTA data.

Identification of Impediments to Fair Housing.

There is no question to what the most cited impediment to Fair Housing in DETCOG and smaller communities is—lack of funds. Whether you are talking about individuals seeking housing, communities building infrastructure, or developers looking for capital to build more housing, the community claims are the same—funds are just not there. There is at least some belief among the people interviewed that there are homes available if people had the money to purchase them.

Of course, that is a common refrain for affordable housing. But in looking at projects for infrastructure very few—if any, are used for housing-related issues.

Some of the interviewees are of the opinion that there are no longer racial issues in housing in the DETCOG region. However follow up comments led the interviewers to believe that there are still discriminatory acts in housing. These largely center around NIMBYism by larger communities in the region and resistance by councils in locating low-income housing outside of minority concentration areas.

It will be more difficult to determine levels of concentration in these areas because many of them have only one census tract and this AI is not going to the neighborhood datasets because of their unreliability. In Appendix D, there are representative smaller jurisdictions where the data could provide more information about segregation.

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ACCESS TO PRIVATE CAPITAL.

The State of Texas contracted with the National Community Reinvestment Coalition (“NCRC”) to conduct a portfolio and market share analysis using 2008 Home Mortgage Disclosure Act (“HMDA”) data for the Deep East Texas Council of Governments. The following counties comprise Deep East Texas: Angelina, Houston, Jasper, Nacogdoches, Newton, Polk, Sabine, San Augustine, San Jacinto, Shelby, Trinity, and Tyler.154

Portfolio Share Analysis of All Conventional Single Family Lending in Deep East Texas.

African Americans are the largest minority group in Deep East Texas, representing 14.65 percent of all households. Hispanics, Asians, and Native Americans combined account for about 6 percent of all households in Deep East Texas. Appendix H Table 1a (see corresponding Chart 6- 1a) of the conventional lending report shows that the portion of all prime loans received by African American borrowers was lower than the portion of loans received by non-Hispanic white borrowers compared to their portion of households in 2008. African Americans received only about two percent of prime loans that was considerably less than their portion of households (14.65 percent). In contrast, non-Hispanic whites received 88.56 percent of prime loans that was higher than their portion of households (78.42 percent). The portion of all prime and high-cost loans received by Hispanic borrowers was comparable to their portion of households.

Chart 6-1a – Derived from data in Table 1a

In Appendix H Table 2a (see corresponding Chart 6-2a), both low- and moderate-income (LMI) non-Hispanic whites and LMI African Americans received a share of loans that was less than their share of households but the disparity was worse for LMI African Americans. LMI non-

154 The State hired Southwest Fair Housing Council to be the primary contractor and they contracted with the National Community Reinvestment Council on behalf of the state. This report is largely un-edited except for formatting to be consistent with the balance of the AI.

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Hispanic whites received a share of prime loans about one third the share of their households while LMI African Americans received a share about one ninth their share of households. (Note: Census data does not break out Hispanic households by income level so we are unable to compare the share of loans by income level to the share of Hispanic households by income level. We are able to compare the share of loans by income level to the share of households by race and income level since Census data does break out households by income level for each race).

Chart 6-2a - Appendix H 2a – Derived from data in Table 2a

Appendix H Table 3a (see corresponding Chart 6-3a) reveals a disproportionate amount of high- cost loans received by middle- and upper-income (MUI) African Americans. MUI African Americans received 5.6 percent and 1.8 percent of high-cost and prime loans, respectively. In contrast, MUI non-Hispanic whites received 77.74 percent and 60.6 percent of prime and high- cost loans, respectively. MUI Hispanics received 4.8 percent and 4 percent of high-cost and prime loans, respectively.

Chart 6-3a – Derived from data in Table 3a

Substantially minority neighborhoods received a proportionate amount of loans as shown by Appendix H Table 4a of the tables displaying conventional lending by minority level of neighborhood. Substantially minority neighborhoods with 50 to 79 percent of the residents being

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 144 of 196 minority contain 4.42 percent of the owner-occupied housing units and received 3.82 percent of prime loans and 6.26 percent of the high-cost loans. In contrast, neighborhoods with 20 to 49 percent of minorities received a portion of prime loans (37.61 percent) that was greater than their portion of owner-occupied units (26.58 percent).

Market Share Analysis of All Conventional Single Family Lending in Deep East Texas.

Appendix H Table 1b (see corresponding Chart 6-1b) shows market share ratios in Deep East Texas that are not controlled for income. The table reveals that African American borrowers are 2.38 times more likely to receive a high-cost loan than non-Hispanic white borrowers. About 65 percent of all loans to African Americans are high-cost compared to 27.6 percent of all loans to non-Hispanic whites being high-cost. Dividing 65.7 percent by 27.6 percent yields the result that African Americans are 2.38 times more likely to receive a high-cost loan than non-Hispanic white borrowers. Finally, Hispanics are 1.23 times more likely to receive a high-cost loan than non-Hispanic whites.

Chart 6-1b – Derived from data in Table 1b

In Appendix H Table 2b (see corresponding Chart 6-2b), LMI African Americans are twice as likely to receive a high-cost loan compared to LMI non-Hispanic white borrowers (the ratio is calculated by dividing 88.9 percent of loans being high-cost for LMI African Americans by 44 percent of loans being high-cost for LMI non-Hispanic whites).

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Chart 6-2b – Derived from data in Table 2b

Appendix H Table 3b (see corresponding Chart 6-3b) shows that MUI African Americans are 2.27 times more likely to receive a high-cost loan than MUI non-Hispanic whites (divide 57.1 percent of the loans being high-cost for MUI African Americans by 25.2 percent of the loans being high-cost for MUI non-Hispanic whites). Racial disparities in lending remain as income levels increase.

Chart 6-3b – Derived from data in Table 3b

Residents of minority neighborhoods are much more likely than those of predominantly white neighborhoods to receive high-cost loans. Appendix H Table 4b of conventional lending by minority level of neighborhood shows that residents of substantially minority neighborhoods (50 to 79 percent minorities) are 1.46 times more likely to receive high-cost loans than residents of neighborhoods with less than 10 percent minorities (divide 41.3 percent of loans being high-cost in substantially minority neighborhoods by 28.2 percent of the loans being high-cost in neighborhoods with less than 10 percent minorities).

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Conventional Denial Disparity Analysis.

The overall denial rate (Appendix H Table 1c, see Chart 6-1c) is almost 34 percent in Deep East Texas. The denial rate for non-Hispanic white individuals is about 30 percent, the denial rate for the Hispanics is about 41 percent, and the denial rate for African American is about 61 percent. African Americans and Hispanics are 2.04 and 1.37 times more likely, respectively, than non- Hispanic whites to be denied a loan.

Chart 6-1c – Derived from data in Table 1c

LMI African American borrowers have a denial rate for loans (67.86 percent) that is about 25 percentage points higher than the denial rate of LMI non-Hispanic whites of 42.55 percent. LMI Hispanic or Latino borrowers have a denial rate for loans (56 percent) that is about 13 percentage points higher than the denial rate of LMI non-Hispanic whites of 42.55 percent (Appendix H Table 2c, see Chart 6-2c).

Chart 6-2c – Derived from data in Table 2c

Among MUI individuals (Appendix H Table 3c, see Chart 6-3c), Hispanic and African American borrowers experience denial rates noticeably higher than those of non-Hispanic whites. African Americans are twice as likely to be denied as non-Hispanic white borrowers. MUI African

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Americans have a denial rate of 55.49 percent in contrast to MUI non-Hispanic whites with a denial rate of 27.29 percent. MUI Hispanics have a denial rate of 35.46 percent in contrast to MUI non-Hispanic whites with a denial rate of 27.29 percent. MUI Hispanics are therefore 1.3 times more likely than MUI non-Hispanic whites to be denied.

Chart 6-3c – Derived from data in Table 3c

Residents of substantially minority neighborhoods (50 to 79 percent minorities) are 1.26 times more likely than residents of predominantly white neighborhoods (less than 10 percent minorities) to be denied loans. More than 46 percent of the applicants from substantially minority neighborhoods are denied loans in contrast to 36.8 percent of the applicants from predominantly white neighborhoods. Mixed neighborhoods (20 to 49 percent minorities) had a slightly lower denial rate than the predominantly white neighborhoods. Only 35.37 percent of applicants from mixed neighborhoods are denied loans.

Portfolio Share Analysis of All FHA Single Family Lending in Deep East Texas.

NCRC expanded the Deep East Texas analysis to include information on FHA lending. FHA loans are guaranteed by the Federal government, specifically the Federal Housing Administration (FHA). Borrowers pay an upfront premium and an annual premium to help fund FHA insurance. The FHA insurance covers the costs of defaults. In other words, the government, through FHA and fees assessed on borrowers, covers the costs of defaults. In contrast, conventional lending involves lenders themselves absorbing the costs of defaults. Often, lending institutions will protect themselves against loss by requiring borrowers to pay for private mortgage insurance.

The total number of FHA loans was smaller than total number of conventional loans in Deep East Texas in 2008. Lenders issued 352 prime FHA loans and 1,231 prime conventional loans, and 104 high-cost FHA loans and 527 high-cost conventional loans in Deep East Texas in 2008.

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What is particularly relevant for our analysis is whether minorities are much more likely relative to whites to receive high-cost FHA loans. FHA lending has not been saddled with the abusive tricks, traps, and fees of many subprime loans. Yet, it remains the case that FHA loans are more expensive than conventional loans. If minorities receive a disproportionate amount of high-cost FHA loans and/or prime FHA loans relative to conventional loans, stakeholders should take steps to increase the amount of conventional lending to minorities.

Appendix H Table 1a (see corresponding Chart 6-1.1a) for FHA lending shows that the portion of FHA loans received by African American borrowers was lower than the FHA loans received by non-Hispanic white borrowers compared to their portion of households in Deep East Texas. Hispanics received a slightly higher share of prime FHA loans (6.12 percent) than their share of households (5.31 percent). Non-Hispanic whites received a share of prime FHA loans that was equal to their share of households and high-cost FHA loans higher than their share of households in Deep East Texas.

Chart 6-1.1a – Derived from data in Table 1a

In Appendix H Table 2a (see corresponding Chart 6-1.2a), both LMI non-Hispanic whites and LMI African Americans received a share of FHA loans lower than their share of households but the disparity was worse for LMI African Americans. LMI non-Hispanic whites received a share of FHA loans about one half the share of their households while LMI African Americans received a share about one fifth their share of households.

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Chart 6-1.2a – Derived from data in Table 2a

Appendix H Table 3a (see corresponding Chart 6-1.3a) shows that both MUI non-Hispanic whites and MUI African Americans received a share of FHA loans greater than their share of households.

Chart 6-1.3a – Derived from data in Table 3a

Market Share Analysis of All FHA Single Family Lending in Deep East Texas.

The overall market share ratio (Appendix H Table 6-1.1b, see Chart 1b) shows that both Hispanics and African Americans received smaller share of high-cost loans compared to non- Hispanic whites. More than 20 percent of the loans received by African Americans are high-cost FHA loans, while about 24 percent of the loans received by non-Hispanic whites are high-cost FHA loans.

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 150 of 196

Chart 6-1.1b – Derived from data in Table 1b

Chart 6-1.2b – Derived from data in Table 2b

Chart 6-1.3b – Derived from data in Table 3b

FHA Loan Denial Disparity Analysis.

The overall denial rate for all FHA loans (Appendix H Table 1c, see Chart 6-1.1c) in Deep East Texas is almost 22 percent. The denial rate for non-Hispanic whites is 21 percent. The denial rate for Hispanics (36.17 percent) is higher than the denial rate of non-Hispanic whites. Hispanics are 1.72 times more likely than non-Hispanic whites to be denied an FHA loan during 2008 in

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Deep East Texas. The denial rate for African Americans is 20 percent, which is lower than the denial rate for non-Hispanic whites.

Chart 6-1.1c – Derived from data in Table 1c

The overall denial rate for LMI individuals (Appendix H Table 2c, see Chart 6-1.2c) is 24.6 percent, with the denial rate for LMI non-Hispanic white borrowers being 22.9 percent and LMI Hispanics being 46.2 percent. LMI Hispanics are twice as likely as LMI non-Hispanic whites to be denied an FHA loan.

Chart 6-1.2c – Derived from data in Table 2c

MUI non-Hispanic whites experienced a denial rate of 20.9 percent and MUI Hispanics had a denial rate of 31.25 percent for FHA loans. MUI Hispanics were denied 1.5 times more often than MUI non-Hispanic whites for FHA loans during 2008 in Deep East Texas.

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 152 of 196

Chart 6-1.3c – Derived from data in Table 3c

Summary and Conclusions.

 In Deep East Texas, the portion of all prime conventional loans received by African American borrowers (2.01 percent of prime loans versus 14.65 percent of households) was lower than the loans received by non-Hispanic white borrowers (88.56 percent of prime loans versus 78.42 percent of households) compared to their portion of households.

 Both LMI non-Hispanic whites and LMI African Americans received a share of conventional loans that was less than their share of households but the disparity was worse for LMI African Americans. LMI non-Hispanic whites received a share of prime loans about one third the share of their households while LMI African Americans received a share about one ninth their share of households.

 MUI African Americans are 2.27 times more likely to receive a high-cost loan as MUI non- Hispanic whites. LMI African Americans are twice as likely to receive a high-cost loan compared to LMI non-Hispanic white borrowers. Racial disparities in conventional lending remain as income levels increase in Deep East Texas.

 The denial ratio is higher when comparing MUI African Americans to MUI non-Hispanic whites than when comparing LMI African Americans to LMI non-Hispanic whites. MUI African Americans are twice as likely as MUI non-Hispanic whites to be denied. LMI African Americans are 1.59 times more likely than LMI non-Hispanic whites to be denied. Racial disparities in denials increases as income levels increase in Deep East Texas.

 The portion of FHA loans received by African American borrowers was lower than the FHA loans received by non-Hispanic white borrowers compared to their portion of households in Deep East Texas. Hispanics received a slightly higher share of prime FHA loans than their share of households.

 Both LMI non-Hispanic whites and LMI African Americans received a share of FHA loans lower than their share of households but the disparity was worse for LMI African Americans. LMI non-Hispanic whites received a share of FHA loans about one half the

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 153 of 196

share of their households while LMI African Americans received a share about one fifth their share of households.

 Both MUI non-Hispanic whites and MUI African Americans received a share of FHA loans greater than their share of households.

 LMI Hispanics were denied twice as often as LMI non-Hispanic whites for an FHA loans and MUI Hispanics were denied 1.5 times more often than MUI non-Hispanic whites for FHA loans.

Concentration and Racial Segregation.

The demographic materials in Appendix D are not as complete for all communities in this region. The communities in the region over 10,000 in population show a pattern of concentration based on racial classification. For instance when you look at Lufkin in Angelina County, the population is 53.7 percent Non Hispanic White in contrast to the minority population which is shown at 46.3 percent. When you look at the dissimilarity index, 50.3 percent of Hispanics and 54 percent of Blacks would need to move in order to achieve equal integration.155

The materials provide communities with a way to target concentrations of racial classes. In order to break up the racial concentrations local jurisdictions should provide the ability to relocate individuals using disaster recovery funds and in entitlement communities, HOME and CDBG dollars.

When you look at map provided for Lufkin, it shows a concentration of minorities exceeding 65 percent in much of the community. Compare this map with Nacogdoches, where only two of the block groups show concentrations over 65 percent.156 In the Housing Guidelines for Round 2 funds, this would be a community that could and should be targeted for Round 2 disaster recovery funds for the Homeowner Opportunity Program. This program will assist in allowing qualified applicants in the most heavily concentrated areas for race and poverty federal assistance in moving out of these areas into high opportunity or more racially diverse areas.

This information is provided for communities to use in planning how to address concentration patterns in spending federal funds. Each community over 10,000 has maps available to it that highlight racial makeup of their community by census tract.

155 Appendix D category of communities between 25,000 and 49,999 data and maps. 156 Ibid

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Not In My Backyard—The Impediment of NIMBYism.

A common problem for all communities is the organized public opposition to building low- income, public, or affordable housing. This issue as identified by the focus group in Beaumont and Port Arthur. While there is public housing in each community it tends to be built in areas that are traditionally minority or low-income neighborhoods. Some participants said they raise this issue frequently and receive support from elected officials on a theoretical level. However when a development is proposed outside of the traditional areas by the housing or private developers, the uproar from the neighborhood residents causes their city to back down. Typically the standard reasons for not accepting affordable housing that are brought forward are decrease in property values, increase in crime, impact on schools/overcrowding, lack of tax revenue to support services, stress on public services, traffic congestion among other causes other than race for not accepting affordable properties. TDHCA confirms that this type of opposition has been raised with respect to multi-family developments under its programs.

Lack of Knowledge about what constitutes Fair Housing violations.

In addition to the real estate steering and rental discrimination, the focus groups indicated that the Fair Housing Act remains a mystery to many. Even more clear is that not many people even if they believe they are being discriminated against know how to take action to file a complaint or report the violation. In Section 7 of this document a list of all the housing discrimination complaints filed with HUD are listed by county. During interviews and in focus groups in the area, the housing discrimination issues were believed to be discussed and yet from January 2005 through September 2010 only 142 complaints were made to HUD from the counties identified in this section—including 6 counties that had no complaints. In addition, the Texas Workforce Commission received 692 complaints in the total hurricane-impacted region (61 counties). In an indication that the public may not understand the issues, of the 692 complaints 323 of them received findings of “no cause.”157

Looking at Project Placement.

In reviewing the projects contained in Appendix F, two issues become obvious. Most CDBG funds not including disaster funds, whether supplied by the State or used by entitlement

157 Housing Discrimination Complaints Section 7. herein.

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 155 of 196 communities go almost exclusively to infrastructure projects. The difficulty of determining how the funds are spent is compounded by the manner in which data is reported. Looking at the table very few infrastructure projects have a clear delineation of whom they are directly serving and where the project is located. Without an ability to reference the population served (other than the generic 51 percent plus LMI language), it is difficult to determine who is receiving the benefit of the projects. Because so many of the regular CDBG funds are listed in this manner at both the entitlement jurisdiction and the State the information is not useable to determine if a community is using funds to further fair housing.

In addition, in reviewing Appendix F, very little of non-disaster CDBG funds go to housing. In part this may be because of available funds for infrastructure. A state or local preference for infrastructure use may have been present, but the CDBG Action Plan has a policy that says it supports the use of CDBG funds for the construction of housing. The limitations of funds available and the competitive nature of the funds may factor into the use of funds. Despite the CDBG Action Plan expressing support for building housing with CDBG funds, competitive applications rounds should be reviewed to see if they favor infrastructure over housing in scoring.

The impediment here may actually be the lack of specificity and record keeping by local and state governments for use in conducting their analysis of impediments to fair housing.

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 156 of 196

SECTION 7. FAIR HOUSING COMPLAINTS AND SURVEY OF FAIR HOUSING COMPLAINT PROCEDURES IN THE TEXAS DISASTER RELIEF AREA.

HOPE Fair Housing Center obtained all the fair housing discrimination complaints filed with HUD in sixty-one counties and organized them in tables for comparison and analysis. The tables are in Appendix C.

HOPE also contacted twenty-nine city jurisdictions to conduct a brief survey of ten questions to identify procedures for filing housing discrimination complaints. The survey also looked to identify any impediments to fair housing choice in these jurisdictions that could be interfering with people’s rights to equal housing under the law. The jurisdictions ranged in size and demographics to get an all-around idea of the structures used to handle complaints alleging housing discrimination.158

Fair Housing Complaint Procedure Survey Results.

The most prominent data obtained from the survey was the number of jurisdictions that relied entirely on the Department of Housing and Urban Development (HUD) to deal with instances of discrimination. In approximately 30 percent of the jurisdictions surveyed, the complaint process was delegated to HUD. These cities would provide phone numbers, and in a majority of cases, they would assist a person with filling out the proper HUD forms to register the complaint. Many of them would also have the HUD forms on hand at their government offices, but once the issue had been filed with HUD, the cities had no more involvement. One impediment that surfaced with a majority of these jurisdictions was the difficulty in finding the correct person to contact. If someone were to call the main number for their government office, there is a good chance that they will be transferred to between three and five different people. In one instance, a call to the city of Mission was transferred from the City Manager’s office to the City Secretary’s office, to the Planning and Community Development office, and to the Code Enforcement office. The Code Enforcement employee then explained that they were not in charge of handling housing discrimination complaints and said, “Maybe you should try the Housing Authority because this isn’t our job,” and ended the conversation.

158 Tables with the complaint information obtained from HUD are included in the Section 2 Appendix.

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 157 of 196

In another eight percent of cases, there was little knowledge or understanding of the concept of fair housing. When asked how cases of housing discrimination are handled in Conroe, Texas, the response received was “By fair housing do you mean, like, building homes for the poor?” In College Station, Texas, the Assistant City Manager explained that the Chamber of Commerce handles all housing discrimination complaints. When the Chamber of Commerce was contacted, they clarified that they had nothing to do with housing discrimination complaints, and that the Better Business Bureau was who needed to be contacted. Sugarland, Texas explained that they do not record or refer complaints because they do not have any public housing.

One possible reason for the lack of understanding of fair housing or the discrimination complaint process is that the jurisdictions do not deal with these issues often. In around thirty percent of cases, municipalities had not received a housing discrimination complaint in the past five years. Education and outreach are very important because with the lack of knowledge regarding housing discrimination in the municipal governments, even less understanding of tenant and fair housing rights likely exists in the general public. The lack of understanding regarding fair housing rights likely results in the low number of fair housing complaint filings.

In cases where complaints are not immediately forwarded to HUD, internal investigations are conducted. Few jurisdictions had fair housing ordinances in place that were equivalent to either the Texas State Statute or the Federal Fair Housing Act. In these cases, community development departments were in charge. They would complete intake forms gathering information if someone had a complaint. They will then investigate if there is reason to believe that discrimination occurred. The investigations normally consist of interviews with complainants and respondents. In only one case were complaints taken past the investigation level and moved on to legal fields. In Corpus Christi, depending on jurisdiction and the response from HUD, they may send a complaint to their legal department where it will be taken to the municipal courts.

Corpus Christi has one of the best-organized systems for registering complaints where they have the ability to enter intake information directly into the Teapots Directory that HUD uses to store all the information they compile in regards to their investigations. They also have a system in place to do their own investigations, and are constantly on-hand to provide advice and literature to people who believe they experienced housing discrimination.

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 158 of 196

Fair Housing Complaint Analysis – HUD Teapots.

For part one of the General Agreement between the Southwest Fair Housing Council and HOPE Fair Housing Center, it was necessary to obtain documentation of complaints filed in sixty-one counties throughout Texas. A major impediment uncovered throughout this survey and investigation came from HUD. HUD was contacted ten different times over the course of five weeks, and every other phone conversation had a different person in charge of our FOIA request. The documents were received more than a month after they had been formally requested. This brings up a concern for the fact that almost eleven percent of the 1,221 complaints filed with HUD were dismissed because “Complainant failed to cooperate.” Are complainants actually failing to cooperate, or is slow response and disorganization leading to complainants becoming lost in the system and ultimately having their complaints closed?

The largest number of complaints came from Harris and Nueces Counties. There were 633 and 177 complaints respectively between January 1, 2005 and September 2010. In the sixty-one counties analyzed, the highest number of complaints of discrimination, 531 or forty-four percent of the total, came from persons with disabilities. The next highest was racial discrimination, with 459 complaints, or thirty-eight percent. Third was national origin with seventeen percent, and fourth was familial status comprising thirteen percent. The rest of the complaints were spread out between sex, religion and color. The outcomes of the cases varied as well with “No Cause” determinations being rendered for forty-one percent of all complaints, which can be expected. What stood out was the number of cases that were closed because the complainant failed to cooperate. No reason was found about how a complainant is deemed to have failed to cooperate, but approximately eleven percent of all cases were closed for this reason. The reason was revealed because of a large number of complaints that were filed in Harris County against Cecilia Rojas. Analyzing the data showed that a very small number of the complaints actually made it successfully through conciliation, but a majority of the complaints were closed for lack of complainant cooperation or lack of jurisdiction.

Complaints Filed with the Texas Workforce Commission.

Fair housing complaints can also be filed with the Texas Workforce Commission (TWC). Since TWC has a Fair Housing Assistance Program (FHAP) agreement with HUD, all complaints received by TWC are also reported and entered into HUD’s database know as “Teapots.” While

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 159 of 196 we obtained the complaints filed with TWC, the basis for the analysis presented in the section above was complaints from Teapots. This was done in order to avoid duplication in the complaints used for the analysis. The fact that HUD had received about twice as many complaints as TWC in the period considered here appears to indicate that many complaints in Texas are filed or referred directly to HUD and not first to TWC. It is also problematic that HUD reports only 10 of the over 1,221 complaints received by HUD since January 1, 2005 were recorded as originating from TWC. This could indicate that the vast majority of complaints they handle are being filed directly with HUD and then delegated to them to process in accordance with the FHAP agreement. If this were the case, it would appear that TWC is not marketing complaint intake and instead defers to complaint referral by public and private agencies to HUD. More investigation needs to be conducted to understand better the reason for this statistic that is troubling on its face.

Regardless of duplication, an independent analysis of TWC shows that it reported receiving 692 complaints originating in the sixty-one counties in the disaster relief area in the past five years. Of these 432, or 62.4 percent, were from Harris County. In reference to outcome, 323, or 46.7 percent, of these complaints received findings of “no cause.” “No cause” means that TWC determined there was a lack of sufficient evidence that illegal housing discrimination occurred and would take no further action and close the case. Nevertheless, complainants can continue to pursue the case through a private attorney if they choose. TWC also reported that they closed 116 or 16.8 percent of the complaints they received by successfully conciliating them. The remainder of the cases, eleven percent (11%), was closed for what TWC termed as a failure of the complainant to cooperate, the inability to contact a respondent, the withdrawal of the complaint by a complainant or for administrative reasons.

The bases of the complaints received by TWC in the last 5 years were as follows:

Table 7-1 TWC Complaints Basis Number Race 277 Disability 230 National Origin 115 Familial Status 75 Sex 46 Religion 16 Color 3 TOTAL 762* *There can be more than one basis for a complaint.

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 160 of 196

As indicated in the analysis of HUD complaints, this is a relatively small number of complaints over a five-year period for an area consisting of over sixty counties and a population exceeding eight million. This averages about 138 complaints per year and if you factor out Harris County, it leaves about 210 complaints over five years for 60 counties with a total population of about 2.5 million. Again, as HUD points out in its Fair Housing Planning Guide, and similar to the HUD data, an inordinate lack of complaints (almost a third of the rural counties reported none) is a red flag that can indicate a poor understanding of housing rights and ineffective complaint procedures.

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 161 of 196

SECTION 8. COMPENDIUM OF IMPEDIMENTS AND POSSIBLE ACTIONS.

NOTICE: When reading this section, jurisdictions should note that certain recommended action steps are the responsibility of the state, while some action steps apply to local

situations only (i.e., colonias). However, jurisdictions should use the information contained within this AI and other data about their communities to determine if an action step applies to their community. For example, if a community does not have a provision

that limits participation in flood plains, that action step (#5-14) does not apply. All communities using federal disaster recovery funds should submit a Fair Housing Action Statement for Texas (FHAST) certifying that they have reviewed all the impediments and

action steps and proposed to implement those that are applicable (#5-10). The state will

review each jurisdiction’s FHAST statement prior to approval of projects or programs.

The action steps identified in this AI will apply to programs and funds beyond the Federal CDBG Ike/Dolly Disaster Recovery funds as applicable to regions in which specified impediments may exist and are identified, but in drafting this AI, it was anticipated that the first application of the action steps would begin with Round 2 funds under the

Federal CDBG Disaster Recovery Program being administered by the state after HUD approval of this document. State agencies and local communities should include these action steps in their ordinary course of business, in the first round of program or funds

after the AI is approved. For example, NOFAs or application rounds currently in the field will not be required to retroactively apply action steps, but new rules or application rounds after approval will need to take this AI into consideration for the impacted areas.

This AI document will play a critical role in the deployment of more than $2 billion in disaster recovery Community Development Block Grant (“CDBG”) funding that has been appropriated and allocated by the federal government to help citizens and local governments recover from the devastation of Hurricanes Ike and Dolly in 2008. The impediments and recommendations contained within this document and supporting materials pertain to furthering fair housing choice. While some impediments are reflective of practices in other states and regions, those case studies have been utilized in this document with the intention of providing guidance to furthering

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 162 of 196 fair housing in the Ike and Dolly impacted regions of Texas, which stretch across counties with substantial damage, many of which are within one of four major councils of government – the Deep East Texas Council of Governments, Houston-Galveston Area Council, Lower Rio Grande Valley Council of Governments, and South East Texas Regional Planning Commission. To determine if the federal legal requirement of affirmatively furthering fair housing is being met, one fundamental question to ask is whether governmental entities have intentionally or unintentionally limited free housing choice by policy and budget decisions. Another critical question is whether those administering and receiving federal funds have sufficiently educated the public about the Fair Housing Act and taken proper steps to enforce that Act.

The impediments to fair housing and action steps to address those impediments outlined will apply to different jurisdictions in different ways. Prior to signing a certification that they have a current and compliant analysis of their impediments to Fair Housing choice and that they are affirmatively furthering fair housing, jurisdictions should examine the impediments below and determine if any apply to their situation. Not every impediment can be resolved quickly and some may never be solved, but it is necessary for each jurisdiction to assess its situation, examine its policies, and confirm that it is taking appropriate actions related to the furtherance of Fair Housing. This is a federally mandated requirement prior to applying for public funds such as these CDBG funds. While HUD did not impose strict adherence to AFFH rules for CDBG disaster recovery funds prior to 2008, since 2008, HUD has more vigorously enforced the AFFH requirement and has required Texas to update its 2003 AI as a condition of receiving Round 2 disaster recovery funds..

The content of this AI is not intended to find that the state or localities are in violation of federal law. This AI document is intended to identify historic impediments to affirmatively furthering fair housing through research of AFFH case studies, literature, and laws as they are represented throughout the nation and serve as a guide for state and local governments to ensure compliance with federal law. Nothing herein is intended to relieve the State of any of its obligations to comply with federal housing laws and the Conciliation Agreement, entered into May 25, 2010. These obligations will continue to be met by the designated state agencies, TDHCA and TDRA, or any successor agencies designated by the Legislature.

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 163 of 196

The impediments are presented in two major categories—Private Sector Impediments and Public Sector Impediments—but otherwise listed in no particular order. Placement of the topic is not intended to designate relative importance compared to other impediments.

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 164 of 196

Private Sector Impediments.

When one analyzes the Home Mortgage Disclosure Act information,159 the results of testing by national Fair Housing organizations,160 on steering of potential purchasers of homes, and the views expressed in the focus groups, it appears there could be residual race-based factors impeding fair housing choice in the market place at some level. Government has a role to play in helping eliminate impediments in a free housing market and enforcing existing laws like the federal and state Fair Housing Acts to eliminate housing choice discrimination.

Both the federal and state Fair Housing Acts cover discrimination by private property owners and those who work in related real estate fields.161 Private sector impediments to affirmatively furthering fair housing for the purposes of this AI center on mortgage lending issues, racial steering in home sales and rental rejections based on factors impacting protected classes at a higher level.

► Impediment #1. Protected classes may experience disparities in home mortgage lending and high cost loans.

The Home Mortgage Disclosure Act data that was assessed for this AI162 indicates that based on population totals, racial minorities do not receive prime home mortgage loans in equivalent numbers to non-Hispanic whites. This is true even when adjusting for income levels and comparing similar incomes against white applicants.163 Since 2002, all homeowners have grown in number with Blacks increasing in home ownership by 65,802 and Hispanic or Latinos

159 Unless otherwise specifically referenced this information refers to topics discussed in Sections 3, 4, 5, and 6 of this AI 160 No Home for the Holidays—Discrimination for Katrina Evacuees 2005, National Fair Housing Alliance 161 42 USC §§3604-3606, Texas Property Code §§301.026 and 301.027 162 State hired Southwest Fair Housing Council to be the primary contractor and they contracted with the National Community Reinvestment Council on behalf of the state. 163 The AI committee acknowledges a few important points associated with Home Mortgage Disclosure Act analysis. 1. Credit scores are not considered in HMDA analyses.2. Factors that are often associated with high-cost loans:  Credit scores  Sparse credit history (can be an issue for immigrants)  Small loans (often associated with less expensive and smaller housing or piggyback loan)  Manufactured Housing  Age (i.e., very young or elderly tend to have higher interest loans)  High debt to income ratios  High loan to value ratios  Small down payment amounts  Refinancing (when cashing out of equity)

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 165 of 196 increasing in the number of homeowners by 320,671.164 The current data indicates that Hispanics and African Americans tend to obtain more costly loans and/or loans with other unfavorable features if they are available. Several factors can contribute to the type of loan a borrower receives, including (but not limited to) the type of housing, size of the loan, debt ratios, and other non-racial and protected class considerations that could affect the conclusions of the AI.

* Recommended Action—Impediment 1.

1. Existing real estate regulations require most persons working in the industry to be licensed and receive substantial training to obtain and maintain their licenses.165 Texas requires initial education for licensing and (unless exempted by law) that existing licensees complete at least 15 hours of continuing education every two years to renew a license. The state should consider amending the Texas Finance Code Chapter 156 (the Mortgage Broker License Act) to require training in Fair Housing, including a course in affirmatively furthering fair housing, as part of the initial training education requirements166 and the 15 hour continuing education requirement for license renewal every two years.167

2. TDHCA, as a pilot program in the impacted areas and provided sufficient bond proceeds, should consider implementing its existing First Time Homebuyer training as allowed under the bond indentures168 to include training on affirmatively furthering fair housing for its participating brokers and originators.

3. TDHCA, as a pilot program in the impacted areas and dependent on sufficient appropriations, should consider requiring individuals who are going through homebuyer education classes169 to receive training in how to recognize racially based mortgage declines or other race-based adverse treatment and how to file complaints with the appropriate agency if they believe they are being discriminated against.

164 American Community Survey years 2002-2009, U.S. Census Bureau 165 Texas Finance Code Chapter 156 166 Texas Finance Code §136.204 167 Texas Finance Code §136.208 168 Texas Government Code §2306.142(g) 169 Ibid

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 166 of 196

4. TDHCA should monitor its First Time Homebuyer Program, comparing the market’s make-up of members of classes of persons protected under the Fair Housing Act (thereinafter “members of protected classes”) and the makeup of its approved borrowers to determine if the program is achieving loan originations in line with those expected. This is relevant to the Hurricane impacted areas as many of the First Time Homebuyer loans are provided in the impacted regions. The result of this analysis and actions taken to improve fair access to mortgage credit should be reported in the State Low Income Housing Plan and Annual Report.

5. The State legislature should consider requiring similar training and monitoring provided in action steps under this impediment for all statewide housing programs that offer single family mortgage products using the state’s private activity bonds.

6. TDHCA should work with housing and mortgage organizations to provide educational materials related to affirmatively furthering fair housing at financial conventions it attends, whether in print or as part of a presentation.

7. As part of the ongoing conversations with persons interested in housing at all levels, TDHCA should request that when meeting with lenders and mortgage brokers to discuss issues and problems they include issues indicated by the analysis of Home Mortgage Disclosure Act (“HMDA”) data and Community Reinvestment Act (“CRA”) requirements in minority and low-to-moderate income residential areas and in serving the home mortgage credit needs of members of the protected classes.

8. TDHCA staff already provides education materials in print and on its website. As part of its continuing commitment to increasing knowledge of housing related issues, the agency, dependent on sufficient appropriations, should develop and distribute educational materials describing the duties of lenders with regard to fair housing and in particular the duty of lenders participating in programs administered by government agencies to affirmatively further fair housing.

9. As part of the counseling system in round 2, TDHCA should require homebuyer education programs for disaster recovery recipients and recipients of other existing TDHCA loans to include a financial literacy component designed to educate the homebuyers regarding the responsible use of home equity refinancing.

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 167 of 196

10. TDHCA should, subject to applicable law, build into its existing first-time homebuyer programs requirements for the collection of data about loan applicants with a sufficient level of data acquisition (including borrower credit scores, incomes, down payment, debt ratio, loan to debt ratios, and other factors). Participating borrowers should be required to report information on loan applications and rejections with reference to applicants who are members of protected classes. This data should be reported annually in the State Low Income Housing Report and should be used to determine lender eligibility for participation in the state's programs.

11. Similar to the current process to protect public investment in affordable housing for self- help housing programs, the state should consider specific term protections to prevent equity stripping abuses affecting persons receiving assistance through disaster recovery and other government-subsidized loans.

► Impediment #2. There is inadequate information available to the real estate community, governments and the public about fair housing requirements and enforcement procedures.

Due to the urgency to develop this AI so disaster recovery funds could flow to those Texans in need, the State did not conduct any direct surveys or market tests to determine if “steering,” which is defined as “the illegal practice of directing members of minority groups to, or away from, certain areas or neighborhoods,”170 was taking place in the hurricane impacted area. With the limited amount of testing done in No Home for the Holidays that found discrimination in renting was occurring (the report included testing in Houston and in post-Katrina New Orleans and revealed discrimination against both racial minorities and persons with disabilities) this AI has looked to external information that patterns of steering exist in other U.S. communities. Due to steering’s potential impact on housing choice, it is identified as an impediment in this document. Due to lack of Texas-based information, this AI considered external information like the Justice Department’s judgment of $120,000 against Chicago area Re//Max East-West171 and the National Fair Housing Alliance’s 12 city survey finding that racial steering occurred at least 87 percent of the time.

170 Real Estate Directory Rea1 Estate Glossary retrieved from http://www.agentsrelestate.us/glossary 171 Justice Department Obtains $120,000 Discrimination Lawsuit Against Chicago Area Realtors, Feb. 18, 2009 retrieved from http://reuters.com/article/idUS202030+18-Feb-2009+PRN20090218

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 168 of 196

Given the NFHA No Home for the Holidays report in 2005172 discussion of discriminatory rental practices and the public comments in the focus groups, it appears that individuals seeking housing and professionals involved in producing, renting and selling housing would benefit from additional discussion. Additional training regarding the Fair Housing Act and specifically the affirmatively furthering fair housing provisions should be suggested to private organizations and offered by TDHCA and TDRA.

There is a lack of understanding of the requirements of the Fair Housing Act. In addition, when, coupled with a lack of understanding of the complaint process for persons experiencing discrimination, this lack of understanding can result in substantial impediments. Making certain that people understand their rights and duties can be best solved by education.

* Recommended Action—Impediment 2.

1. In Texas, real estate sales are a regulated activity including licensing requirements and continuing legal education requirements for the professionals assisting people in buying and selling real estate.173 Current statutes require education for persons involved in the listing and selling of real estate both initially and to maintain their licenses. The Texas Legislature, or the entity or entities responsible for determining continuing education requirements, should consider delineating that the existing requirement that fair housing laws be taught as part of the continuing education requirements, in the Texas Occupations Code, Title 7 §11101.455. The anticipated change would require a minimum of two hours of the required six hours combined during the compliance period be for education on the Fair Housing Act including Fair Housing requirements and enforcement provisions related to steering violations.

2. TDHCA should add to the educational materials prepared for real estate professionals utilizing its programs, the concepts of Fair Housing and affirmatively furthering fair housing. TDHCA should require a certification that the materials were read and understood prior to participating in TDHCA programs utilizing real estate professionals including the disaster recovery programs.

172 No Home for the Holidays—Discrimination for Katrina Evacuees 2005, National Fair Housing Alliance 173 Texas Occupations Code Title7.Chapter 1101

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3. TDHCA should work with agencies or other entities responsible for providing educational materials to all real estate professionals, to expand existing materials on how to utilize the TDHCA's programs, to include concepts of affirmatively furthering fair housing and fair housing duties of real estate professionals.

4. TDHCA should require a portion of the existing Homebuyer Education Programs for persons using public funds to purchase homes to include training on Fair Housing and how and where to report suspected violations of the Fair Housing Act.

5. TDHCA should review the distribution of home purchases by members of protected classes against the entire pool of applicants in its existing programs that use real estate professionals to provide a useful measurement of whether the process is working to provide Fair Housing choice

6. The state legislature should consider requiring similar training and monitoring as provided under the actions steps in this impediment for other statewide housing entities that use private activity bond funds or single family mortgages in transactions that involve real estate professionals.

7. TDHCA should expand its existing educational materials, whether in print or as a presentation, to include information related to affirmatively furthering fair housing, and use them at the real estate conventions and other real estate meetings TDHCA currently attends.

8. TDHCA should, with its established relationship with real estate support organizations, seek to work collaboratively to determine the best ways to help provide guidance to licensed real estate professionals on working with clients under the rules of the state and federal Fair Housing Acts and the full range of their housing options.

9. TDHCA should work to establish a section on its website to educate consumers on fair housing law and on how to identify discrimination

10. TDHCA should offer to consult with organizations that provide education to attorneys involved in real estate or financing of real estate transactions to develop continuing legal

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 170 of 196

education required by the Government Code or the State Bar of Texas rules174 providing training on Fair Housing and affirmatively furthering fair housing. It is further recommended that this training should provide a continuing legal education ethics credit.

11. TDHCA should include written materials and potentially a presentation in its existing “First Thursday” compliance training program for leasing professionals regarding the Fair Housing Act, including affirmatively furthering fair housing training.

12. As part of its ongoing education relationship with organizations that work with apartment ownership and management groups, TDHCA should request that it be allowed to include Fair Housing Act training at the association educational seminars, including affirmatively furthering fair housing. TDHCA should offer written materials or conduct the training in a breakout session.

13. TDHCA should request that it be allowed to include Fair Housing Act training, including affirmatively furthering fair housing at home and apartment building trade associations meetings. TDHCA should offer written materials or to conduct the training in a breakout session.

14. In grant contracts with local communities, TDHCA and TDRA should require that chief locally-elected officials of funded subrecipients receive Fair Housing training. The agencies should request that appropriate city and county organizations or associations, provide education for elected officials on Fair Housing Act, including affirmatively furthering fair housing. TDHCA and TDRA should assist as available when requested and offer written materials or conduct the training in a breakout session.

15. To assist all subrecipients of federal funds from TDRA and TDHCA in being able to certify that they are affirmatively furthering fair housing, the agencies should create new rules that requires third party consultants administering or performing any role in the administration of CDBG or other federal housing or community development funds to complete an affirmatively furthering fair housing training seminar and demonstrate competency in the area.

174 Texas Government Code §81.113

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16. TDHCA should establish minimum standards and best practices for fair housing and equal housing opportunity marketing plans of contractors directed at outreach to members of protected classes to meet the state rule requirements.175

17. TDHCA and TDRA, if applicable housing is performed, should require that all recipients of funding for owner or renter occupied housing maintain an application log, with notation when the applicant is a member of a protected class. These logs should be monitored by the agency on a regular basis for fair housing compliance. TDHCA should require the Texas State Affordable Housing Corporation (“TSAHC”) to do the same on any funds provided to TSAHC by TDHCA and request TSAHC to do the same of their state funds.

18. TDHCA should require that all subrecipients of disaster recovery funds establish affirmative fair housing marketing plans that set targets for serving members of protected classes. Success in achieving goals should be a consideration in scoring future applications for funding from subrecipients.

19. All applicants for housing, community development, or infrastructure funds from TDHCA and/or TDRA should be required to participate in a training session that includes requirements to affirmatively further fair housing.

20. Depending on sufficient appropriations, TDHCA and TDRA should each provide sufficient staff resources to assure fair housing compliance within their respective agencies. These staff should also be responsible for arranging, providing, and certifying regular training on fair housing and affirmatively furthering fair housing for agency staff and recipients.

► Impediment #3. The public is not sufficiently aware of their Fair Housing rights and how to obtain the assistance necessary to protect those rights.

Local focus groups, the high dismissal rate of Fair Housing Complaints made to HUD and national studies176 suggest that there is a need for enhanced consumer information concerning the Fair Housing Act and reporting complaints.

175 10 Texas Administrative Code Chapter 60

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 172 of 196

Recommended Actions—Impediment 3.

1. TDHCA working with other agencies involved in Fair Housing should jointly produce Fair Housing Act Public Service Announcements to be made available for broadcast in the disaster impacted area to increase the public’s awareness of a) Fair Housing rights, b)identifying discrimination, and c) methods for accessing fair housing resources to report discrimination.

2. Depending on sufficient appropriation, TDHCA should work with other agencies and organizations to distribute fair housing literature at housing related events, trainings and presentations, additional and other distribution sites. Distribution sites in the impacted areas may include city offices, libraries, CDBG funded agencies and Community Action Agencies. Materials should be available in English, Spanish and other languages as appropriate to ensure that protected population sectors are reached, even if significant portions of them are not proficient in English.

3. Consistent with the Fair Housing Act, TDHCA, TDRA and funded sub-recipients have historically conducted fair housing activities at various times of the year and should continue to fund, depending on sufficient appropriations, or collaborate with public and private agencies, organizations and groups to plan and conduct fair housing activities.

4. Consistent with the Fair Housing Act, TDHCA, TDRA and funded sub-recipients should continue to promote and conduct events to celebrate April as Fair Housing Month, and direct sub recipients to do the same. These events can demonstrate support for fair housing and build awareness.

5. If federal funding is available, TDHCA and TDRA should establish and maintain a website page or a link for statewide fair housing information as outlined in other recommendations in this AI through which information is made available to the public regarding fair housing law, the duties of the state and local jurisdictions to affirmatively further fair housing, access to FHAST Forms as provided elsewhere in this AI for each local jurisdiction, a streamlined and expedited process for submitting complaints of individual acts of violation of the fair housing law online and a streamlined and

176 Dr. King’s Dream Denied

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 173 of 196

expedited process for submitting complaints of the failure of government entities to affirmatively further fair housing. This website should provide linkages and referrals to HUD's FHEO division.

► Impediment #4. "Not in my Backyard” (NIMBY) may be an impediment to fair housing in Texas communities.

As discussed in the earlier sections of this document, the phenomenon known as NIMBY (Not in My Backyard) is often a significant factor that can impede the development of affordable housing, the building of public housing, the placement of Section 8 Voucher holders and group homes, and numerous other housing programs. This is suggested by reviewing records of public testimony at TDHCA Governing Board meetings and public hearings.

NIMBY can impact decisions on the location of infrastructure projects like sewage treatment plants, waste disposal facilities or similar community necessary projects. This very vocal NIMBY is expressed not only through public testimony but in the lobbying of public officials, and is often reported in the media, in blogs and on websites.

* Recommended Action—Impediment 4.

1. NIMBY opposition needs to be anticipated and planning and outreach should occur on the front end of projects. To mitigate defensive and reactive responses, planning should include strategies for education, outreach and marketing that provide accurate information and promote the positive aspects and benefits of affordable housing to build support among community residents.177

2. Specific examples of prior actions by communities are listed in HUD’s Fair Housing Guide: Volume 2, pgs 7-106 – 7-110 and includes a number of examples that communities have used to mitigate NIMBY opposition. Generally communities should consider:

 Working with local officials, editorial boards, religious and civic organizations and other community leaders to initiate education programs.

177 “In the face of NIMBY attitudes grantees can adopt a stance that in essence goes along with them or strongly counters such sentiments with positive actions to overcome them and allay fears and concerns with facts.” HUD’s Fair Housing Guide: Volume 2, pg 7-106

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 Seeking opportunities to present information to community organizations by requesting to be placed on their meeting agendas.

 Including a visit to the group home residence as part of an education program.

 Answering all questions.

 Talking with local neighborhood leaders, including elected representatives, and setting up a neighborhood meeting.

 Setting up a liaison committee consisting of advocates, group residents, and neighborhood residents to discuss issues.

 Identifying areas that meet AFFH targets where the community supports development, has worked with community groups and potentially uses funds to assist the development of multi-family affordable housing.

3. TDHCA should include in its regional allocation formula, factors regarding the presence within jurisdictions of members of protected classes, families of extremely low income, and opportunity indicators including access to high-quality public education, concentration of poverty, racial segregation, environmental quality, access to health care, access to sustainable jobs, and crime rates as defined in rules to be issued.

4. TDHCA should expand its relationship with the Texas A&M Real Estate Center to assist in research projects as requested regarding distribution of funds by TDHCA related to fair housing impacts.

5. Providing sufficent approriations are available, or this is determined to be eligible for federal funding, TDHCA and TDRA should provide data to an institution of higher education in the state, with a Geographic Information Services (“GIS”) database on the fund distribution of federal housing and community development funds from federaly funded sources starting with information currently held by the agencies that is readily accessible in electronic format. This GIS system should be available to the public and to academic researchers, state and local governments for purposes of assessing the fair housing impact of government funding decisions utilizing federal funds. If HUD develops similar technology within the action step timeline date, there is no need to

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create a duplicate system, but TDHCA and TDRA should provide information to HUD’s system.

Public Sector Impediments.

► Impediment #5. Certain governmental policies and practices may not meet current HUD policy concerning affirmatively furthering fair housing. Jurisdictions should act to ensure that their policies affirmatively further fair housing, address mal-distribution of resources, and that they do not unnecessarily impact housing choice.

Communities may have policies that may unintentionally fail to affirmatively further fair housing. These can be reflected in a city’s comprehensive plan, capital improvement projects or zoning or subdivision ordinances. One of the goals of this AI is to assist local officials with guidance on issues to review prior to making the required certification of affirmatively furthering fair housing when receiving HUD funds. Jurisdictions should ensure that their practices do not promote concentrations of protected classes; that they are affirmatively furthering fair housing; and that policies do not intentionally or unintentionally preclude housing affordability or restrict accessibility to housing for persons with disabilities.

One result of infrastructure issues can be the disproportionate presence of members of protected classes in environmentally degraded or geographically vulnerable locations which presents an impediment to equitable access to disaster recovery programs and to fair housing choice. For example:

 Some reconstructions in minority neighborhoods in Beaumont during the Rita program were unable to pass environmental review for rebuilding because of the proximity to a refinery.

 Minority neighborhoods in disaster impacted areas in flood plains have been prevented from accessing disaster rebuilding programs and denied disaster recovery infrastructure funds to alleviate flooding due to local jurisdictions decisions.

In fact, floodplains are an issue throughout the impacted region. People living in floodplains should be assisted to address flooding danger to make their home livable or the household should

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 176 of 196 be offered a voluntary relocation option. In the Valley and in selected areas in Harris County, colonias with limited infrastructure and poor drainage present a special problem based on the drainage/flood/levy system. Communities should examine policies that prohibit flood control improvements and assistance to households located in flood plains, as that can be an impediment to relocating and therefore not allow for movement and integration of neighborhoods using public funds. The lack of funds to assist flood plain areas is different than limiting the rebuilding of homes in floodways. In cases where entire communities are in the flood plain, the cost of elevating could be an impediment that would need assistance with viable solutions like additional dedicated funding caps to meet the cost of compliance with floodplain requirements for elevation.

* Recommended Action—Impediment 5.

1. As part of certifying that a community is affirmatively furthering fair housing, jurisdictions that have long-term infrastructure plans should review them to determine if the plan promotes racial concentrations or otherwise inadvertently results in disparate treatment of members of protected classes. While not intended to direct a community to hire a consultant, it is anticipated that a community will review its long term infrastructure plans as part of this recommended action. In reviewing the project list in Appendix F there are many projects that are listed as being of community-wide benefit. The records do not indicate the actual location of the projects or provide adequate discussion of how the projects benefit the entire community. Later we will discuss record keeping as an impediment to AFFH enforcement.

2. As it has been determined under federal law that Fair Housing applies to all federal housing and community development funds, to reduce “siloing” the fair housing component into only housing related programs, fair housing should be considered in all activities for all local community planning staff.

3. It would be beneficial for local elected officials to require senior staff of any subrecipient such as a city or county—including managers and attorneys—to receive available Fair Housing training within the first 12 months of their employment or engagement.

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4. As part of what is usually a common initial training by the associations that provide education opportunities for newly appointed board members or newly elected council or commissioners court members of cities and counties, the state should request that training include specific information on the Fair Housing Act—with a discussion of affirmatively furthering fair housing obligations.

5. Local communities should consider limiting the concentration of infrastructure improvements like waste water treatment, solid waste disposal, or similar necessary but not desirable infrastructure projects in residential areas where there are concentrations of protected classes.

6. Communities electing to provide publicly financed housing incentives should be requested to call for recipients to engage in affirmative marketing.

7. If a jurisdiction is a non-entitlement community, when working in LMI areas to replace roads or other infrastructure, the jurisdiction should consider making application for additional sources of funding to provide assistance to repair substandard housing associated with the project (i.e., TDHCA or HUD).

8. Most infrastructure projects take into account items like curb cuts, sidewalks, hearing and visually impaired indicators at intersections. When approving non-federally funded projects, similar special needs construction should be required for infrastructure improvements. Projects should also address other legacy discrimination issues, such as accessibility in public access areas like courthouses, community centers and other high traffic areas.

9. Each jurisdiction applying for Community Development Block Grant funds or other federal housing and community development funds should submit a Fair Housing Activity Statement-Texas with their application reviewing their infrastructure needs and housing needs and how the proposed activity promotes fair housing or results in more equitable treatment of protected classes. Projects with community wide benefits should be accompanied by explicit commitments on the part of the local jurisdictions to undertake additional activities to affirmatively further fair housing along with a monitoring and reporting process.

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10. As part of the non-housing disaster recovery program, jurisdictions should consider low- income areas and areas populated principally by members of protected classes to determine the potential for flooding and consider making infrastructure expenditures to help protect the impacted communities—including colonias.

11. If applicable, all policies should be reviewed regarding denying applicants’ access to disaster recovery CDBG funds if their residence is located in the flood plain. If the policy does not allow participation by restricting building in flood plains, then the policy should be assessed to see if alternative housing programs could be implemented for the residents. Local jurisdictions should analyze the results and see if protected classes are more frequently harmed by flood plain restrictions. This action does not apply to the TDRA CDBG Disaster Relief Fund that limits property purchase “unless TXCDBG receives satisfactory evidence that the property to be purchased was not constructed or purchased by the current owner after the property site location was officially mapped and included in a designated flood plain.”

12. When an entire community is in a flood plain, the community should establish clear standards that allow for proper elevation, or relocation and that also allows for visitability/special needs considerations consistent with state178 and federal law.

13. Local jurisdictions that accommodated the relocation of disaster survivors resulting in concentrations of protected class survivors in specific areas should establish Moving to Opportunity Programs and include renters in their Moving to Opportunity Programs as defined under Round 2.

14. Consistent with the process established in the conciliation agreement, local jurisdictions and state agencies should work together to determine a demographic and economic profile of victims of the natural disaster and establish goals for assisting these populations in no less that the proportions they were impacted by the disaster. These goals should be performance goals and disaster recovery funds should be extended incrementally in a manner to ensure that these populations are equitably assisted with benefits.

178 Texas Government Code §2306.514

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15. All infrastructure programs funded with disaster recovery funds should be designed in a manner such that any publicly accessible infrastructure projects and associated facilities assisted by the infrastructure program are fully accessible to persons with disabilities.

16. Consistent with the Conciliation Agreement, family and elderly public housing units damaged or destroyed by the disaster should be reconstructed or repaired in a manner that affirmatively furthers fair housing utilizing disaster recovery funds within 24 months of approval of the initial application for disaster recovery assistance for the local jurisdiction.

► Impediment #6. Governmental entities at all levels do not appear to have been proactive in the enforcement of both the Fair Housing Act and the obligation to affirmatively further fair housing. The State and subrecipients should implement a robust and effective structure for identifying and pursuing suspected violations.

Outside of the information provided in Section 7 of this AI, it does not appear that the state or local jurisdictions perform systematic testing to determine if the Fair Housing Act is being implemented. To the extent that private entities perform self testing the state would not know because of the privileged status of self-testing and self correction provisions as provided for under the Fair Housing Act.179 HUD itself has admitted that it has not fully enforced the affirmatively furthering fair housing issues with jurisdictions. With little enforcement by the public sector much of the Fair Housing Act enforcement falls to private civil rights groups who also have inadequate funding.180

Many public and private agencies in the disaster area need more effective fair housing referral processes that provide fair housing information and assistance to victims of illegal discrimination and disclose any prevalence of housing discrimination. As with many laws, at least the potential for testing and enforcement is necessary to obtain compliance.

* Recommended Action—Impediment 6.

1. Given the potential for increase in Fair Housing enforcement action by federal and state agencies and private organizations, an ongoing fair housing testing program for areas

179 §814A, Fair Housing Act 180 Dr. King’s Dream Denied: Forty Years of Failed Enforcement, 2008 Fair Housing Report, published April 8, 2008 by the National Fair Housing Alliance

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that receive federal housing and community development funds could be beneficial to protect state agencies and subrecipients from potential repayment. Fair housing enforcement is a valid use of CDBG funding and can be used to establish testing programs by agencies trained in HUD testing procedures. The state, or local jurisdictions combining together, should consider conducting tests in areas that include the following: steering in sales and rental; the denial of and different terms and conditions based on race, national origin, familial status, and disability in sales and rental; predatory and disparate terms and conditions in lending and insurance; and foreclosure modification schemes targeting minority neighborhoods. The state should also consider education to applicable entities on self testing and self correction.

2. TDHCA should, as a pilot program, allocate funds to independent third parties or a combined jurisdiction team identified in point 1 of this section to provide similar testing in the area to determine if additional enforcement is necessary.

3. Impacted agencies that provide certification that they are affirmatively furthering fair housing as required by federal law, should consider publishing a public document on enforcement that provides the public and communities with a clear description (and chart) of the state and Federal Fair Housing Act.

4. Each community should place on its website (if one is available) the contact , at the local, state and federal levels for reporting a Fair Housing complaint, if citizens believe they were victims of housing discrimination.

5. TDHCA and TDRA should seek to sign MOUs with the Texas Workforce Commission to confirm the existing relationship between the agencies if a Fair Housing complaint is made, binding the agencies to refer alleged or suspected violations immediately for appropriate investigation and handling and to participate in the investigation if requested by the victim.

6. TDHCA and TDRA should request their boards to include a discussion of Fair Housing issues and trends at board education sessions at least every two years as federal law requires the certification of affirmatively furthering fair housing by the Board Chair when receiving federal funds.

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7. Given the issues identified in Section 7, the state and HUD should work together to examine the fair housing complaint investigation system and determine whether and where the shortfalls are in the system. Once the review is completed, the parties should recommend a joint plan of action to improve the complaint system.

8. Each local jurisdiction should publish on its website a clear statement, approved jointly by TDRA and TDHCA, expressing the jurisdiction's obligation to affirmatively further fair housing and providing a method for reporting suspected noncompliance to the state and to HUD. The jurisdiction’s contact person should be able to refer to clear local Fair Housing procedures for the complaint process, keep logs and records of all inquiries, allegations, complaints and referrals. These reports should be sent to the appropriate funding agency. Where these reports show that a jurisdiction has administered programs inconsistently with this AI and had the effect of discouraging applications from members of protected classes who are deemed eligible under this plan for assistance, affirmative marketing plans should be developed and submitted to the appropriate agency.

► Impediment #7. Many local jurisdictions have zoning codes, land use controls, and administrative practices that may impede free housing choice and fail to affirmatively further fair housing.

Local jurisdictions that place restrictions like minimum square footage requirements, minimum lot sizes, special features like attached garages or significant code requirements above the IRC or similar codes may have created an impediment to fair housing choice. There is a difference between affordable housing and Fair Housing and the restrictions should be assessed to determine if they are a barrier for either.

* Recommended Action—Impediment 7.

1. Legal requirements, including local zoning ordinances and the like, need to be directed to specific, legitimate, non-discriminatory objectives and structured and administered in a manner consistent with fair housing requirements.181 Communities are encouraged to

181 In reauthorizing the Fair Housing Act included in legislative history was “The Committee intends that the prohibition against discrimination against those with handicaps apply to zoning decisions and practices. The Act is intended to prohibit the application of special requirements through land-use regulations, restrictive

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review zoning or other land use controls and analyze if they contribute to fair housing barriers. TDRA, during recent AFFH trainings conducted with Ike funding, has urged the review and improvement of zoning ordinances etc. for all applicants. Twenty-eight applicants have already included a commitment to this process for Round 2, Phase 2 funding.

2. The law anticipates that ordinances creating disparate impact should also be reviewed for change.182 If a disparate impact is determined to exist by the local jurisdiction, it could repeal or amend the restriction, use public funds to offset the cost through homebuyer assistance programs, a waiver of fees or other offsets to make the home more affordable.

3. To help limit concentrations that could be considered impediments to affirmatively furthering fair housing, jurisdictions that have long term planning documents for housing growth or redevelopment or revitalization plan, the jurisdiction should consider allowing or encouraging mixed income affordable housing in the plan and provide incentives for development of this type housing in areas that are not concentrated.

4. Local jurisdictions seeking CDBG Disaster Recovery funds from the state should consider offering expedited permitting and review processes for affordable housing projects within high opportunity target zones.

5. Likewise, the federal government should consider expediting environmental and other federal reviews to expedite recovery in disaster areas. To that extent, the federal government should establish by rule that any environmental impact statement not denied within 30 days is deemed approved so as to speed recovery to protected classes.

► Impediment #8. Inadequate planning for re-housing after an emergency situation creates a situation where persons who are uninsured or under insured, low income, or special needs can be displaced for long periods of time.

covenants, and conditional or special use permits that have the effect of limiting the ability of such individuals to live in the residence of their choice in the community.” H. Rep. No. 100-711, at 24 (1988), reprinted in, 1988 U.S.C.C.A.N. 2173, 2185. 182 Page 5 Discriminatory Zoning and the Fair Housing Act, Pennsylvania Disability Rights Network of Pennsylvania, http://www.drnpa.org/File/publications/discriminatory-zoning-and-the-fair-housing-act.pdf

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Re-housing immediately after a disaster is expected to be handled by FEMA. The State examined issues discovered during evacuations for Hurricane Rita and addressed the impediments to a safe and effective evacuation. The plans made were effective for evacuation in Hurricanes Dolly and Ike. FEMA still has significant issues in the short-term re-housing program.

There is sufficient evidence that protected classes under the Fair Housing Act were disproportionately and adversely affected by the issue of duplication of benefits following Hurricane Rita. Initial assistance after a disaster, whether from FEMA, state agencies, or non- profit organizations, is given to assist disaster victims with immediate needs such as shelter, food and medicine. In long term recovery efforts, protected class homeowners are expected to payback or provide detailed receipts for the initial assistance before receiving long term recovery benefits, which will move them from damaged, dilapidated housing to safe, decent and sanitary housing. This situation has occurred throughout the disaster areas of Hurricane Ike and Dolly, and applicants for long term recovery housing assistance, particularly those who are members of protected classes under the Fair Housing Act, are disproportionately represented in this issue. HUD should rewrite its rules so that the initial assistance given after a disaster is not be considered a long term recovery permanent benefit for the protected classes but is considered a temporary mitigation measure to provide survival needs to the homeowner. The current impediment is that protected classes, who own their own homes, may have no long term decent, safe and sanitary housing due to their inability to pay back or account for temporary disaster assistance they received, often times years ago.

Following Hurricane Dolly in July 2008, FEMA denied half of all applications for housing assistance, alleging “deferred maintenance.” FEMA has refused to disclose the rules and standards by which it makes these eligibility decisions, or even to provide a definition of “deferred maintenance,” which is not an official denial code. There is ongoing litigation in the United States District Court for the Southern District of Texas over FEMA’s failure to publish its standards and procedures in violation of the Stafford Act.183 These denials may have had a disproportionate impact on low-income households and members of protected classes.

183LUPE v. FEMA (S.D. Texas: 08-487) Preliminary Injunction, August 6, 2009. The Fifth Circuit vacated the preliminary injunction

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FEMA also denied at least 85 percent of claims for housing assistance in Texas after Hurricane Ike. Although some applications were denied for reasons as minor as an omitted middle initial,184 the most common denial code used (in over 100,000 cases185) was “insufficient damage,” particularly in low-income households and neighborhoods. Many low-income applicants have been told informally by FEMA that their “insufficient damage” denials were actually based on “deferred maintenance.”

FEMA may have denied many of these applicants unfairly and erroneously. After Hurricane Katrina, the City of Houston sent its own housing inspectors to New Orleans in May 2006 and determined that two-thirds of FEMA’s habitability determinations were “suspect or wrong.”186 The City of Houston believes there were similar problems with housing assistance denials after Hurricane Ike, but “[t]he ‘solution’ that a family deemed ineligible may appeal their determination is not realistic.”187 Examples of erroneous housing assistance denials following Hurricane Ike include: declaring homes habitable that have been condemned by city officials, declared unsafe by Child Protective Services, and that are inaccessible to individuals with disabilities. Non-profit groups in Houston report entire neighborhoods of damaged home that have been deemed to have “insufficient damage”188 largely in low-income and traditionally minority areas.

The emergency and interim disaster relief that FEMA provides has a strong impact on the ability of both individuals and communities to achieve long-term recovery from a disaster. Homes that are not repaired to safe and sanitary condition following a disaster continue to deteriorate, resulting in higher costs to repair and rebuild these homes and as HUD’s own research has demonstrated, increasing the cost and difficulty of recovery for entire neighborhoods and communities.189

184 Mike Snyder, “Pre-Ike damage restricts funding / Homes were in bad shape already, FEMA tells many,” Houston Chronicle, Section B, Page 1, January 25, 2009. 185 Email from FEMA External Affairs to the Houston Chronicle, June 26, 2009 and FEMA “Top Five Reasons for FEMA Ineligibility for Housing,” Last modified June 4, 2009. Available: http://www.fema.gov/hazard/hurricane/2008/ike/factsheets/housing.shtm 186 Far From Home: Deficiencies in Federal Disaster Housing Assistance After Hurricanes Katrina and Rita and Recommendations for Improvement, Special Report, prepared by the Ad Hoc Subcommittee on Disaster Recovery of the Senate Committee on Homeland Security and Governmental Affairs, February 2009, at 204 187 Far From Home: Deficiencies in Federal Disaster Housing Assistance After Hurricanes Katrina and Rita and Recommendations for Improvement, Special Report, prepared by the Ad Hoc Subcommittee on Disaster Recovery of the Senate Committee on Homeland Security and Governmental Affairs, February 2009, at 205. 188 Mike Snyder, “Pre-Ike damage restricts funding / Homes were in bad shape already, FEMA tells many,” Houston Chronicle, Section B, Page 1, January 25, 2009.; Associated Press “FEMA defends 650K denials for post-Ike housing aid,” February 8, 2009.; Associated Press, “Agency says many misunderstand its mission,” February 9, 2009; Mike Snyder, “FEMA's inspection process criticized / Temporary contract workers who lack skills are getting blame,” Houston Chronicle, Section B, Page 1, February 8, 2009. 189 74 Fed. Reg. 41146, Appendix 1, August 14, 2009.

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* Recommended Action--Impediment 8.

1. Some legislators, the Sunset Commission, and communities acknowledge that while temporary disaster housing is a federal program, Texas should continue to provide guidance to local governments on additional planning that needs to be done as part of the emergency preparedness planning to most efficiently work with FEMA.

2. As much of what FEMA has previously offered is travel trailers or manufactured housing, local governments should review their zoning requirements or other land use provisions that restrict temporary housing or housing on an existing lot during the building process and look at potential waivers that do not risk or negatively impact health, safety, and welfare during a period after disasters so that low income persons can move back to their existing communities with temporary housing while waiting for redevelopment.

3. As part of their disaster preparedness plans, local communities should work with the Texas Department of Emergency Management (TDEM), their respective local emergency management departments, and TDHCA to establish temporary housing plans prior to storms to provide rapid deployment of housing into communities where disasters could happen.

4. TDHCA should work with TDEM to update TDEM’s Emergency Management Plan to develop a major natural disaster housing reconstruction best practices guide no later than January 2012 to ensure that housing is restored fairly and equitably to members of protected classes in the wake of future major disasters.

5. Federal duplication of benefit interpretations impacts need to be included as a planning point in any disaster recovery plan so that low-income persons will be eligible for disaster recovery funds in the long term recovery program. The State, subrecipients, and advocates should join together in requesting HUD to provide a less draconian interpretation of the Duplication of Benefits.

6. TDHCA should monitor the Homeowner Opportunity Program to determine its success at providing mobility options for individuals or families from high concentrations of minorities and poverty and flood plains with the first monitoring assessment coming not

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later than January 2012. At the end of the program, TDHCA and its subrecipients should review the success of the program and evaluate its effectiveness for future planning in the event of disaster programs.

7. The disparate impact of lack of clear title on protected classes should be included as a planning point in any disaster recovery plan so that low-income persons will be eligible for long-term disaster recovery funds. Advocates commit to working with law schools to provide free assistance to determining title.

► Impediment #9. There are impediments in public and private actions and private attitudes to housing choice for persons with disabilities.

The Fair Housing Act accords persons with disabilities the right to live in communities regardless of the disability. A difference of opinion exists on whether boarding houses (group homes) should be used for some persons rather than integrating persons with special needs into traditional housing resources. But, to the extent that this form of housing is beneficial to persons with special needs, in the Hurricane impacted areas the research to develop this AI found no direct regulations in place that restrict the homes.190 However, it does appear that there may be incidences of indirect regulation in the form of zoning restrictions, food service permitting and other local ordinance making it difficult to site these homes in all residential areas of these communities. One potential ordinance that could have a negative impact on these special needs facilities are restrictions that prohibit a certain number of non-related occupants from sharing the same residence.

* Recommended Action—Impediment 9.

1. To meet federal Fair Housing requirements for zoning and neighborhood uses, jurisdictions should look to determine if there are direct or indirect limitations in codes that would prevent facilities or personal residences to provide assistance or communities of choice or service enriched environments that directly impact special needs persons.

190 Report on Texas Boarding Houses H.B. 1168 Submitted to the Office of the Governor and Legislature January 2009 retrieved from http://www.hhsc.state.tx.us/news/presentations/BoardingHouses 0109.pdf

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2. Local jurisdictions should work to ensure that zoning or code requirements do not unnecessarily impose stricter commercial building requirements, such as emergency access or protection services, on group homes, thereby dramatically increasing housing costs for persons with special needs.

3. Local jurisdictions should consider coordinating with the legislatively created Housing and Health Services Coordination Council for best practices on working with supportive services.

4. Within six months of this AI being approved, each COG should convene a community board composed of persons with special needs, advocacy organizations and local jurisdictions to advise the COG on priorities and needs for housing persons with special needs,

► Impediment #10. There are barriers to mobility and free housing choice for Housing Choice Voucher holders including: inadequate tenant counseling services and mobility assistance, failure of PHAs to apply for the FMR pilot demonstration, and government policies, procedures, and regulations that tend to decrease participation by private housing providers and to restrict available housing to “racially or low-income populated neighborhoods” with little access to economic, educational, or other opportunity.

Texas has a higher than average poverty rate, resulting in a higher than average demand for affordable housing and housing assistance. As discussed in this AI, there is a waiting list in every impacted region for public housing or Section 8 vouchers. Concentration of public housing may be a problem in some communities, but lack of availability is universal. Hurricanes Rita and Ike damaged many units and they have been slow to rebuild.

* Recommended Action—Impediment 10.

1. Consistent with the Conciliation Agreement, when using Hurricane Ike funds, local communities should place Land Use Restriction Amendments requiring acceptance of Section 8 vouchers on multi-family developments or any single developer who rebuilds more than 20 units with public funds. This should increase the housing availability for Fair Housing purposes.

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2. Consistent with the Conciliation Agreement, the State of Texas, the Deep East Texas Council of Governments, the Houston-Galveston Area Council, the Lower Rio Grande Valley Development Council, and the Southeast Texas Regional Planning Commission should join with housing advocacy groups to request an additional 2,500 vouchers for the hurricane impacted communities. If granted and if sufficient resources are appropriated, TDHCA should support the vouchers with up to one million dollars a year in assistance for relocation from state funds to the best of TDHCA’s ability.

3. Concurrent with the existing State Low Income Housing Plan, the State of Texas and local jurisdictions should work with housing advocacy groups, demographers and academic experts to conduct research on the need for rent subsidies for very low and extremely low income households.

4. Local jurisdictions and TDHCA should cooperate with local public housing authorities to establish tenant counseling and fair housing education programs and curriculum that can be provided to each Section 8 housing choice voucher holder within the affected region on a biannual basis concurrent with eligibility recertification.

5. A HUD map included as Appendix B and contains information of the geographic distribution of Section 8 Housing Choice Vouchers is intended to be used as a research tool by the state and local jurisdictions in looking at the success of Section 8 programs and the mobility the program provides.

6. TDHCA should inform local PHA’s of FMR pilot demonstration programs that could be used in their areas to expand fair housing choices.

► Impediment #11. Loss of housing stock in Hurricanes Dolly and Ike compounded the shortage of affordable housing in disaster recovery areas. This shortage is particularly acute in safe, low poverty neighborhoods with access to standard public services, job opportunities and good schools.

One of the largest impediments to fair housing choice is the lack of safe, decent, and affordable housing in the hurricane impacted area. Prior to the hurricanes, there was a shortage of

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 189 of 196 affordable housing and the damage caused by the disasters further reduced available affordable housing. Limited state and federal resources were directed to rebuild damaged housing instead of adding new housing.

Programs funded by Texas that create affordable housing should maintain better records to demonstrate they are sufficient to assure that the projects will affirmatively further fair housing.

* Recommended Action—Impediment 11.

1. Current economic conditions and the housing bubble burst have greatly slowed the development process unless it is funded with public funds or insurance proceeds. TDHCA through Hurricane Rita disaster recovery funds was one of the largest financing organizations for new homes in the state the last three years working with their COG partners to build more than 3,000 homes. TDHCA and TDRA are working to provide the greatest efficiencies possible and meet the affirmatively furthering fair housing requirements, including added costs of the state’s accessibility standards.

2. To help offset the costs of developments that feature reduced rents without government support, local jurisdictions should consider establishing density bonuses to allow for higher levels of units per site for multifamily developments and single- family developments that propose increased affordability.

3. TDHCA and HUD have developed programs that preserve affordable housing. Continuing in this vein, the state and local jurisdictions should work to preserve existing affordable housing development and discourage them from converting to market rate housing. Requirements should be included in all publicly funded developments providing tenants with early and clear notification of the intention of management to convert to market rate housing and providing first right of refusal to nonprofit and public entities and organizations to purchase units to maintain affordability.

4. The state should consider adopting incentive structures in their programs to encourage local jurisdictions to identify needs and to set priorities for fair housing and community development.

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5. The state and local jurisdictions should consider using CDBG funds to buy down the cost of land in high-cost and high-opportunity development areas to increase affordable housing options in these areas.

► Impediment #12. Lack of financial resources for both individuals and housing providers limits Fair Housing choice. Using an effective program under Section 3 of the Housing and Urban Development Act of 1968 may help members of protected classes gain economic opportunities necessary to allow them to exercise fair housing choice.

No list of impediments to Fair Housing would be complete without discussing the lack of financial resources for providers and families. Despite the fact that Texas has a lower unemployment rate than the national average, many Texans are unemployed or underemployed making it difficult to afford housing, or if they are in housing the relative cost of housing to wages creates a Housing Burden as discussed it Section 2. In addition the subprime markets and aggressive posture for homeownership have resulted in foreclosures.

The hurricanes and the economy have also hit hard the economies of the local communities and the State of Texas through reduced revenues from property taxes at the local level and sales taxes at both levels, resulting in less local and state funding available to assist persons needing additional help. That leaves federal help in the case of Hurricanes Rita, Ike and Dolly the state received less than 25 percent of its identified need in disaster recovery funds.

* Recommended Action—Impediment 12.

1. The state is maximizing its resources in Round 2 of the Ike/Dolly funding to affirmatively further fair housing in single family and multi-family developments. As called for in the Conciliation Agreement, the state is looking to provide more integrated housing options for persons in racially concentrated or poverty concentrated neighborhood groups. In single-family programs, the state should require subrecipients to offer the opportunity to relocate out of floodplain areas, concentrations of racial minorities, or concentrations of poverty—through the Homeowner Opportunity Program. Any relocation should be into an area that does not result in simply relocating the high-concentration from one area to another.

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2. Although general revenue funds are extremely tight and increased funding by the 83rd Texas Legislature is highly doubtful, TDHCA has asked for a continued commitment by the legislature to a Housing Trust Fund appropriation of state dollars to assist in the voucher relocation program.

3. Jurisdictions receiving federal funds from HUD, directly or indirectly, should ensure they have a compliant Section 3 program to meet HUD requirements regarding notification to LMI eligible persons of potential job creation at the impacted neighborhood level with federal funds.

4. TDHCA and TDRA, using existing resources, should continue to develop and review best practices for Section 3 within their respective agencies and should include training on this topic as part of the regular training it provides or arranges.

5. TDRA and TDHCA should provide training materials to organizations that typically provide training to elected officials, public officials, any third party consultants, or subcontractors administering or playing any role in the administration of CDBG or other HUD federal housing or community development funds complete a fair housing act training seminar, including affirmatively furthering fair housing, prior to application submission.

► Impediment #13. Location and lack of housing accessibility and visitability standards within political jurisdictions limits fair housing choice for persons with disabilities.

Often the only housing available for a person with special needs is a facility specifically designed for them and every unit within that facility is designed for that function. Where this is not the case it can be difficult to find units that have the accessibility features. TDHCA has addressed this by adopting the Integrated Housing Rule at 10 TAC 1.15 that requires that in TDHCA funded developments not more than 18 percent of units in large developments and not more than 36 percent of units in small developments should be occupied by persons with special needs.

The difficulty of commuting to medical facilities especially impacts persons with special needs to a greater degree than others. The state and communities should consider the distance between

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 192 of 196 the new residential communities it builds and proximity of services for persons with special needs. This would also be convenient for elderly persons.

* Recommended Action—Impediment 13.

1. Local jurisdictions should consider establishing incentives for affordable housing applicants to create an increased set-aside of housing units for persons with disabilities or persons who are elderly without violating the existing TDHCA integrated housing rule.

2. To assist local communities in assisting service-enriched housing as defined by TDHCA rules, TDHCA should consider language in TDHCA’s Housing Trust Fund Plan which assigns an additional priority to the development of service-enriched housing apart from the dedicated programs for special needs.

3. TDHCA should review modifications of the multifamily bond program rules to support the development of service-enriched housing.

4. To the extent allowed by law, TDHCA should explore collaboration with the national Disability Opportunity Fund to bring funding opportunities to Texas to help communities with additional special needs funding.

5. TDHCA and TDRA should explore how state Community Development Block Grant (“CDBG”) funding allocations can be used to address the service-enriched housing needs of rural communities. The TDRA CDBG Action Plan encourages a portion of the annual federal allocation be used towards affordable housing development in any region under its existing programs.

6. TDHCA and local jurisdictions should consider adding proximity to medical facilities as a scoring incentive for competitive programs using federal funds for proximity to medical facilities.

7. TDHCA should require that all federally funded housing construction be built to accessibility standards found in Texas Government Code §2306.514.

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► Impediment #14. Many colonias residents live in developments that have insufficient infrastructure and protections against flooding and are impacted by flooding beyond events like Hurricanes Dolly and Ike.

There are ongoing issues of the basic livability in colonias areas. The importance of infrastructure is exposed during flooding, attempted access by vehicles, the lack of potable water, and lack of wastewater services. All of these are areas of critical concern in colonias communities that should be discussed in greater detail at every level. Although the state had invested almost half a billion dollars of primarily federal funding into colonias improvements as of 2007, much of which was aimed at providing these basic infrastructure services necessary for housing development/redevelopment to take place, more work needs to be done. The state should better coordinate the colonias programs currently fragmented in numerous state agencies to better address the issues and more efficiently use tax dollars.

* Recommended Action—Impediment 14.

1. The state, COGs, and local jurisdictions should examine the infrastructure needs in colonias, in particular the use of CDBG disaster recovery funds to provide drainage improvements to correct flooding problems in the wake of Hurricane Dolly, and the historical provision of public infrastructure and housing assistance to meet those needs in border and non-border colonias.

► Impediment #15. Minority neighborhoods in disaster areas are primarily served by non- regulated insurance companies that do not adhere to underwriting guidelines and may be discriminated against in the provision of insurance. Texas has passed aggressive statutes to prevent insurance “redlining.” National research indicates that protected classes face unwarranted disparities in the cost of insurance, the amount of coverage, and cancellation191 of policies without notice to the homeowner.

As part of new home construction using federal funds, insurance must be maintained on the home to be eligible for future federal funds in the event of another disaster. The cost of the insurance is expensive and due to lack of availability and limited funds, homeowners may not maintain insurance after the compliance period, putting the federal resources in jeopardy.

191 Other factors not covered here may cause the cancellation of insurance.

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* Recommended Action—Impediment 15.

1. Within the current Homebuyer counseling programs connected with federally-funded and state-operated programs, TDHCA should include a component on the types of property insurance and dealing with the insurance claims process.

► Impediment #16. Many jurisdictions do not have adequate Analysis of Impediments to Fair Housing or Fair Housing Plans, and do not keep sufficient records of their activities.

There is a need to update AIs when the new guidance from HUD is received to meet the new expectations for compliance with affirmatively furthering fair housing.

Appendix F is a collection of data from numerous entities in the impacted areas that receive and / or use federal funds (generally only FEMA, HUD and state of Texas funds were requested) to provide a list of activities where those federal funds were used. It should be noted that local jurisdictions were asked to provide the data in a specific format and were given only two weeks to provide seven years of records. In analyzing the list, it is clear there is not a standard for reporting or recording this information to be able to determine if the funds were used to affirmatively further fair housing. This impediment is related to Impediment 5 in this document.

*Recommended Action—Impediment 16.

1. TDHCA and TDRA should continue Fair Housing training already underway to all impacted area subrecipients (regardless of the agency administering a particular program) regarding their obligations to affirmatively further fair housing, how to plan for AFFH, and how to use planning to direct housing, infrastructure, and economic development activities.

2. TDHCA and TDRA should work together to develop a plan for continued regular training and to incorporate fair housing into ongoing training activities in the impacted area.

3. As TDHCA and TDRA have to comply with the Conciliation Agreement, the agencies should continue to provide a continued fair housing resource to provide technical assistance with planning to AFFH, incorporate the findings of the Disaster-Area and new Statewide AIs, and combat potential discriminatory practices. This may be of

March 2011 State of Texas Analysis to Impediments to Fair Housing Page 195 of 196

particular importance for jurisdictions conducting non-housing activities and it is particularly recommended that TDRA continue to use the services of an independent fair housing consultant at least until the obligation of all Round 2 funds has taken place.

4. Recipients of CDBG funds from HUD for housing should maintain records as required by the Fair Housing Act, HUD regulations, and the Conciliation Agreement in order to document that they are carrying out their Fair Housing Action Plans and affirmatively furthering fair housing.

5. As required under the Conciliation Agreement, the State will conduct a new Statewide AI after HUD approval of this Phase 1 AI. Entitlement communities should conduct new AIs or update current AIs to ensure that they address all recommended data and issues and specifically address issues related to all protected classes under the Fair Housing Act. Race and national origin, as well as the other protected classes, must be identified independent of low and moderate-income categories in order to understand the impact of actions, practices, regulations, ordinances, and other factors on them.

6. To assist them in meeting their requirements to certify that it is affirmatively furthering fair housing, TDHCA and TDRA should include as part of its regular training, information on record keeping needed to meet the terms of the Conciliation Agreement and analysis of programs to identify impediments to fair housing.

7. Agencies using federal CDBG or other federal housing and community development funds should adopt a FHAST Form for use by subrecipients that offers a standardized method for analyzing, monitoring and ensuring compliance with obligations to affirmatively further fair housing.

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