prince william countys3.relmanlaw.com.s3.amazonaws.com/database/virginia2009... · 2015. 3. 3. ·...

PRINCE WILLIAM COUNTY ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING CHOICE

Prepared for Office of Housing and Community Development Mr. Elijah T. Johnson, Executive Director Mr. Bill J. Lake, Community Development and Preservation Manager 15941 Donald Curtis Drive, Suite 112 Woodbridge, Virginia 22191 Prepared by J-Quad Planning Group 14683 Midway Road, Suite 210 Addison, Texas 75001 www.jquad.com

Final Report October, 2009

Introduction and Acknowledgements Introduction

This report provides an Analysis of Impediments to Fair Housing Choice (AI) for Prince William County, Manassas, and Manassas Park prepared during program year 2008 - 2009. This AI was conducted using a methodology consistent with the U.S. Department of Housing and Urban Development (HUD) guidelines. HUD requires that each jurisdiction receiving federal funds certifies that it is affirmatively furthering fair housing. The certification specifically requires jurisdictions to do the following: Conduct an analysis of impediments to fair housing choice within the state or local jurisdiction. Take appropriate actions to overcome the effects of any impediments identified through that analysis. Maintain records reflecting the analysis and actions in this regard. Lead and Participating Agencies The Prince William County Office of Housing and Community Development was responsible for oversight and coordination of the AI process. Prince William County retained J-Quad Planning Group, a Community Development, Urban Planning and Housing Consulting firm to assist in the preparation of the AI. Acknowledgements Data collected in preparing the AI relied in part on input from the public. The process included information gathered from citizen focus groups and key persons interviews. We also acknowledge the participation of representatives from the financial, housing development, non-profit, social services, business and real estate industries. We extend special thanks to the Prince William County Human Rights Commission and the Prince William County Housing Board for their participation and contributions toward making the AI process a success and the local governments of Manassas and Manassas Park for providing input, data and hosting focus group sessions.

Table of Contents Executive Summary............................................................................................. i Section 1 – Community Profiles…………………………………………………….1

Introduction ................................................................................................1 1.1 Demographic Profile.............................................................................2 1.2. Income Profile ...................................................................................15 1.3. Employment and Education Profile ...................................................26 1.4. Public Transportation Profile .............................................................36 1.5. Housing Profile..................................................................................38

Section 2 – Fair Housing Law, Municipal Policies and Complaint Analysis 55

Introduction ..............................................................................................55 2.1. Fair Housing Law ..............................................................................56 2.2. Enforcement......................................................................................64 2.3. Production and Availability of Affordable Units..................................65 2.4. Regulatory and Public Policy Review................................................65 2.5. Analysis of Fair Housing Complaints.................................................66 2.6. Conclusions and Implications for Fair Housing Barriers ....................67

Section 3 – Focus Groups and Community Engagement...…………………...69

Introduction ..............................................................................................69 3.1. Focus Group Concerns and Comments ............................................69 3.2. Solutions ...........................................................................................72

Section 4 - Home Mortgage Disclosure Act Data (HMDA) Analysis…………74

Introduction ..............................................................................................74 4.1. Analysis.............................................................................................74 4.2. Conclusions.......................................................................................78

Section 5 - Fair Housing Index……………………………………………………102

Introduction ............................................................................................102 5.1. Methodology....................................................................................102 5.2. Findings...........................................................................................104

Section 6 – Impediments and Remedial Activities…………………………....107

Introduction ............................................................................................107 6.1. Real Estate Impediments ................................................................107 6.2. Banking, Finance, Insurance and other Industry Impediments........113 6.3. Socio-Economic Impediments.........................................................118 6.4. Neighborhood Conditions Related Impediments .............................120

Section 7 – Oversight, Monitoring and Maintenance of Records….............123

1

Section 1: Community Profile Introduction The Community Profile is a review of demographic, income, employment, public transportation, and housing data for Prince William County primarily gathered from the 2005-2007 American Community Survey (ACS) 3-Year estimates, 2008 Census Annual Population estimates, 1990 and 2000 U.S. Census, Prince William County demographic datasets, and other sources. The following sections provide an overview and analysis of the current status of Prince William County:

1. Demographic Profile - examines the basic structure of the community in terms of racial diversity, population growth, and family structure.

2. Income Profile - analyzes income sources, the distribution of income across income class, and poverty.

3. Employment Profile - examines unemployment rates, occupation trends, and major employers.

4. Public Transportation Profile – analyzes the access and availability of public transportation systems.

5. Housing Profile - examines data relative to housing stock, with particular attention to the age of the housing stock, vacancy rates, tenure, and cost burdens.

Our evaluation of impediments to fair housing necessarily involves an evaluation of the aforementioned socioeconomic characteristics of Prince William County, in order to establish a context for the evaluation of the environment in which impediments to fair housing might exist. The characteristics of the county will also provide a context for the remedial solutions recommended and the County’s action plan for remedying any impediments identified. The 2007 American Community Survey (ACS) 1-year data released by U.S. census Bureau provides data for geographic areas with a population of 65,000 or more. These estimates are available for Prince William County but are not available for Manassas and Manassas Park. The 2005-2007 ACS 3-year data release provides data for geographic areas with a population of 20,000 or more. These estimates are available for Prince William County and Manassas and not available for Manassas Park. The 2005-2007 ACS 3-year estimates represent the average characteristics over this three-year period. More recent estimates are provided in the report based on the availability of datasets for each geography. Our detailed analyses in each of the sections will concentrate on differences among major racial and ethnic groups in Prince William County: White, African-American, and Hispanic. All other ethnic groups are relatively small in number and percentage and, therefore, will not be examined in detail. The data most critical to our analyses and conclusions are presented in the tables and maps and directly referenced in the text. There may be some cases where additional information was included for the reader’s benefit, though not noted in the text. For the most part, the Community

2

Table 1.1 Population Growth of Prince William County (1950-2009)

Census Population Change % Change

1950 22,612

1960 50,164 27,552 121.85%

1970 111,102 60,938 121.48%

1980 144,703 33,601 30.24%

1990 215,686 70,983 49.05%

2000 280,813 65,127 30.20%

2009 (2nd Quarter) 392,900 112,087 39.92%

Chart 1.1: Population Growth of Prince William County (1950-2009)

0

50,000

100,000

150,000

200,000

250,000

300,000

350,000

400,000

450,000

1950 1960 1970 1980 1990 2000 2009

Sources: U.S. Department of Commerce, U.S. Bureau of the Census, 2009 Population (2nd quarter estimates) – Prince William County Department of Economic Development

Profile utilizes tables, charts and maps to visually present data for the entire county by census tract. 1. Demographic Profile The demographic analysis for Prince William County concentrates on the changes in magnitude of population occurring between 1950 and 2008, and the changes in composition of population occurring between 1990 and 2000 and 2000 and 2007, to the extent that data was available for that period. Please note that the attached tables present the data for Prince William County, Manassas, and Manassas Park, while the maps present data for the Prince William County area by census tract. For reference, Map 1.1 on the following page provides a visual representation of the area, with the census tract boundaries. Table 1.1 and Chart 1.1, to the right, show that the population of Prince William County grew 39.92 percent between 2000 and 2009 to 392,900 people. This compares to a 30.20 percent increase in 1990s, 49.05 percent in the 1980s, a 30.24 percent in the 1970s, a 121.48 percent increase in the 1960s, and an increase of 121.85 percent from 1950 to 1960. According to the 2008 Census population estimates, the population of Manassas was 35,205 and Manassas Park was 11,319.

3

9011

9015.01

9013.02

9015.02

9014.06

9010.01

9014.05

9012.17

9012.18

9008

9012.19

9001

9013.01

9104

9009.02

9007

9012.20

9005

9103

9003

9014.049019

9010.07

9012.14

9102

9010.06

9004.03

9002

9004.06

9012.13

9012.10

9101

9010.05

9014.03

9016.02

9202

9006

9012.23

9004.05

9012.03

9009.01

9012.12

92019017.01

9012.08

9012.09

9010.08

9004.04

9012.21

9202

9016.01

9012.11

9017.02

9012.22

9009.03

Manassas Park

Manassas

Dale City

Gainesville

Nokesville

Woodbridge

Lake Ridge

Linton Hall

Montclair

Quantico Station

Triangle

Bull Run

YorkshireSudley

Dumfries

West Gate

Haymarket

Occoquan

Legend

Manassas City

Manassas Park City

City Limits

Census Tracts 2000

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Prince William County, VirginiaMap 1.1:

Incorporated Towns and Census Designated Places

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Table 1.2 Total population by race for Prince William County, 1990-2000.

Prince William County Manassas Manassas Park

1990 2000 1990 2000 1990 2000

White 180,042 83.47% 193,069 68.75% 23,343 83.50% 25,234 71.82% 5,941 88.22% 7,475 72.64%

African-American 24,942 11.56% 52,873 18.83% 2,893 10.35% 4,542 12.93% 501 7.44% 1,109 10.78% American Indian and Eskimo 604 0.28% 1,262 0.45% 111 0.40% 45 0.13% 10 0.15% 46 0.45% Asian and Pacific Islander 6,895 3.20% 10,678 3.81% 827 2.96% 1,103 3.14% 166 2.47% 385 3.74%

Other 3,203 1.49% 12,329 4.39% 783 2.80% 2,955 8.41% 116 1.72% 874 8.49%

Total 215,686 100.00% 280,813 100.00% 27,957 100.00% 35,135 100.00% 6,734 100.00% 10,290 100.00%

Hispanic 9,161 4.25% 27,266 9.71% 1,626 5.82% 5,344 15.21% 318 4.72% 1,565 15.21% Source: 1990 & 2000 U.S. Census

According to the Census data shown in Table 1.2, below, and Chart 1.2, on the following page, Prince William County experienced a 197.63 percent increase in the Hispanic population, a 111.98 percent increase in the African-American population, a 54.87 percent increase in the Asian population, and a 30.20 percent increase in the total population in the 1990s. In Manassas, the Hispanic population increased by 228.66 percent, the African-American population grew by 57.0 percent, and the total population increased by 25.68 percent since 1990. In Manassas Park, the total population increased by 52.81 percent, Hispanic population grew by 392.14 percent, and the African-American population increased by 121.36 percent since 1990. The Census Bureau does not recognize Hispanic as a race, but rather as an ethnicity. Ethnic Hispanics often choose the ‘other’ category on the Census for race rather than White or African-American.

Based on the 2005-2007 ACS 3-Year estimates, in Prince William County, 61.26 percent of the total population were Whites, 19.14 percent were African-Americans, 18.26 percent were Hispanics, 6.96 percent were Asian and Pacific Islanders, 0.50 percent were American Indian and Eskimos and 12.14 percent accounted for other category. During the three year period, in Manassas, 64.68 percent of the total population was White, 11.63 percent were African-Americans, 25.93 percent were Hispanics, 4.40 percent were Asians and Pacific Islanders, 0.21 percent were American Indians and Eskimos and 19.08 percent accounted for the other category.

5

Chart 1.2: Composition of population by race for Prince William Area, 2000.

White

African-American

American Indian

Asian

Hawaiian

Other

Two or more

Hispanic

The percent change in the Hispanic and African-American populations from 1990 to 2000 is shown in the Map 1.2 on the following page. Following map 1.2 are a series of maps (Maps 1.3 through 1.6) that indicate spatial concentrations of the various racial and ethnic groups within Prince William County. This includes the location of Asian and American Indian/Eskimo populations. These groups were not included in the discussion above due to their low percentages in the total population.

6

Percent American Indian and Eskimo

901498

901501

901302

901100

901598

901216

901001

901298

901398

900800

900902

900100

901215

901004

901098

900700

901404

910198

901214900403

900498

901213

900500

910400

901210

910398

900300

901207

901900

901497910298

901602

900200

900405

901203

901798

901208

901209

900901

901212

900497 900600

901601920100

901211

901298

901702

920200920200

902098

900496

902196

900903

910198

910898

920200

902198 910896

010201

910798

910400

910698

910997

910598

910797

901398

910998

910398

902298

902195

Manassas Park

Manassas

Dale City

Gainesville

Nokesville

Linton Hall

Montclair

Woodbridge

Lake Ridge

Quantico Station

Triangle

Bull Run

YorkshireSudley

Dumfries

Haymarket

Occoquan901498

901501

901302

901100

901598

901216

901001

901298

901398

900800

900902

900100

901215

901004

901098

900700

901404

910198

901214900403

900498

901213

900500

910400

901210

910398

900300

901207

901900

901497910298

901602

900200

900405

901203

901798

901208

901209

900901

901212

900497 900600

901601920100

901211

901298

901702

920200920200

902098

900496

902196

900903

910198

910898

920200

902198 910896

010201

910798

910400902197

910698

910997

910598

910797

901398

910998

910398

902298

902195

Manassas

Dale City

Gainesville

Nokesville

Woodbridge

Linton Hall

Montclair

Lake Ridge

Quantico Station

Triangle

Bull Run

YorkshireSudley

Dumfries

Haymarket

Occoquan

Legend

Manassas Park City

Manassas City

City Limits

Percent Change in Hispanic 1990-2000

-68.75% - 0%

0.01% - 50%

50.01% - 100%

100% and above

Legend

Manassas Park City

Manassas City

City Limits

Percent Change in African-American 1990-2000

-43.03% - 0%

0.01% - 50%

50.01% - 100%

100% and above

±

Prince William County

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Percent Change in African-American and Hispanic 1990-2000Map 1.2:



7


9011

9015.01

9013.02

9015.02

9014.06

9010.01

9014.05

9012.17

9012.18

9008

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9001

9013.01

9104

9009.02

9007

9012.20

9005

9103

9003

9014.049019

9010.07

9012.14

9102

9010.06

9004.03

9002

9004.06

9012.13

9012.10

9101

9010.05

9014.03

9016.02

9202

9006

92019017.01

9012.09

9010.08

9012.23

9004.05

9012.03

9009.01

9012.12

9012.08

9004.04

9012.21

9202

9016.01

9012.11

9017.02

9012.22

9009.03

Manassas Park

Manassas

Dale City

Gainesville

Nokesville

Linton Hall

Woodbridge

Lake Ridge

Montclair

Quantico Station

Triangle

Bull Run

YorkshireSudley

Dumfries

Haymarket

Occoquan901498

901501

901302

901100

901598

901216

901001

901298

901398

900800

900902

900100

901215

901004

901098

900700

901404

910198

901214900403

900498

901213

900500

910400

901210

910398

900300

901207

901900

901497910298

901602

900200

900405

901203

901798

901208

901209

900901

901212

900497 900600

901601920100

901211

901702

920200

902098

900496

902196

900903

910898902198 910896

010201

910798

902197

910698

910997

910598

910797 910998

902398

902298

902195

Manassas

Dale City

Gainesville

Nokesville

Woodbridge

Linton Hall

Montclair

Lake Ridge

Quantico Station

Triangle

Bull Run Yorkshire

Sudley

Dumfries

Loch Lomond

Haymarket

Occoquan

Percent of African-American 1990-2000

Legend

Manassas Park City

Manassas City

City Limits

Percent African-American 2000

1.59% - 10%

10.01% - 20%

20.01% - 30%

30.01% - 42.68%

Legend

Manassas Park City

Manassas City

City Limits

Percent African-American 1990

1.56% - 5%

5.01% - 10%

10.01% - 15%

15.01% - 25.11%

±

Map 1.3:


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Incorporated Towns and Census Designated Places Incorporated Towns and Census Designated Places

8


9011

9015.01

9013.02

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9008

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9001

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9104

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9005

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9003

9014.049019

9010.07

9012.14

9102

9010.06

9004.03

9002

9004.06

9012.13

9012.10

9101

9010.05

9014.03

9016.02

9202

9006

92019017.01

9012.09

9010.08

9012.23

9004.05

9012.03

9009.01

9012.12

9012.08

9004.04

9012.21

9202

9016.01

9012.11

9017.02

9012.22

9009.03

Manassas Park

Manassas

Dale City

Gainesville

Nokesville

Linton Hall

Woodbridge

Lake Ridge

Montclair

Quantico Station

Triangle

Bull Run

YorkshireSudley

Dumfries

Haymarket

Occoquan901498

901501

901302

901100

901598

901216

901001

901298

901398

900800

900902

900100

901215

901004

901098

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910198

901214900403

900498

901213

900500

910400

901210

910398

900300

901207

901900

901497910298

901602

900200

900405

901203

901798

901208

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900901

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900497 900600

901601920100

901211

901298

901702

920200920200

902098

900496

902196

900903

910198

910898

920200

902198 910896

010201

910798

910400902197

910698

910997

910598

910797

901398

910998

910398

902298

902195

Manassas

Dale City

Gainesville

Nokesville

Woodbridge

Linton Hall

Montclair

Lake Ridge

Quantico Station

Triangle

Bull Run

YorkshireSudley

Dumfries

Haymarket

Occoquan

Legend

Manassas Park City

Manassas City

City Limits

Percent Hispanic 2000

1.09% - 2%

2.01% - 5%

5.01% - 10%

10.01% - 25.82%

Legend

Manassas Park City

Manassas City

City Limits

Percent Hispanic 1990

0.85% - 2%

2.01% - 5%

5.01% - 10%

10.01% - 12.98%

±


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Map 1.4: Percent of Hispanic 1990-2000


9


9011

9015.01

9013.02

9015.02

9014.06

9010.01

9014.05

9012.17

9012.18

9008

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9104

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9005

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9010.07

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9102

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9002

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9101

9010.05

9014.03

9016.02

9202

9006

92019017.01

9012.09

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9012.23

9004.05

9012.03

9009.01

9012.12

9012.08

9004.04

9012.21

9202

9016.01

9012.11

9017.02

9012.22

9009.03

Manassas Park

Manassas

Dale City

Gainesville

Nokesville

Linton Hall

Woodbridge

Lake Ridge

Montclair

Quantico Station

Triangle

Bull Run

YorkshireSudley

Dumfries

Haymarket

Occoquan901498

901501

901302

901100

901598

901216

901001

901298

901398

900800

900902

900100

901215

901004

901098

900700

901404

910198

901214900403

900498

901213

900500

910400

901210

910398

900300

901207

901900

901497910298

901602

900200

900405

901203

901798

901208

901209

900901

901212

900497 900600

901601920100

901211

901298

901702

920200920200

902098

900496

902196

900903

910198

910898

920200

902198 910896

010201

910798

910400902197

910698

910997

910598

910797

901398

910998

910398

902298

902195

Manassas

Dale City

Gainesville

Nokesville

Woodbridge

Linton Hall

Montclair

Lake Ridge

Quantico Station

Triangle

Bull Run

YorkshireSudley

Dumfries

Haymarket

Occoquan

Legend

Manassas Park City

Manassas City

City Limits

Percent American Indian and Eskimo 2000

0% - 0.1%

0.11% - 0.4%

0.41% - 0.8%

0.81% - 1.70%

Legend

Manassas Park City

Manassas City

City Limits

Percent American Indian and Eskimo 1990

0.06% - 0.1%

0.11% - 0.4%

0.41% - 0.8%

0.81% - 1.45%

±


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Map 1.5: Percent of American Indian and Eskimo 1990-2000


10


9011

9015.01

9013.02

9015.02

9014.06

9010.01

9014.05

9012.17

9012.18

9008

9012.19

9001

9013.01

9104

9009.02

9007

9012.20

9005

9103

9003

9014.049019

9010.07

9012.14

9102

9010.06

9004.03

9002

9004.06

9012.13

9012.10

9101

9010.05

9014.03

9016.02

9202

9006

92019017.01

9012.09

9010.08

9012.23

9004.05

9012.03

9009.01

9012.12

9012.08

9004.04

9012.21

9202

9016.01

9012.11

9017.02

9012.22

9009.03

Manassas Park

Manassas

Dale City

Gainesville

Nokesville

Linton Hall

Woodbridge

Lake Ridge

Montclair

Quantico Station

Triangle

Bull Run

YorkshireSudley

Dumfries

Haymarket

Occoquan901498

901501

901302

901100

901598

901216

901001

901298

901398

900800

900902

900100

901215

901004

901098

900700

901404

910198

901214900403

900498

901213

900500

910400

901210

910398

900300

901207

901900

901497910298

901602

900200

900405

901203

901798

901208

901209

900901

901212

900497 900600

901601920100

901211

901298

901702

920200920200

902098

900496

902196

900903

910198

910898

920200

902198 910896

010201

910798

910400902197

910698

910997

910598

910797

901398

910998

910398

902298

902195

Manassas

Dale City

Gainesville

Nokesville

Woodbridge

Linton Hall

Montclair

Lake Ridge

Quantico Station

Triangle

Bull Run

YorkshireSudley

Dumfries

Haymarket

Occoquan

Legend

Manassas Park City

Manassas City

City Limits

Percent Asian and Pacific Islander 2000

0.30% - 2%

2.01% - 3%

3.01% - 4%

4.01% - 18.98%

Legend

Manassas Park City

Manassas City

City Limits

Percent Asian and Pacific Islander 1990

0.62% - 2%

2.01% - 3%

3.01% - 4%

4.01% - 5.55%

±


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Map 1.6: Percent of Asian and Pacific Islander 1990-2000


11

Table 1.3 Family structures by race for Prince William Area, 1990-2000


1990 2000 1990 2000 1990 2000

White # % # % # % # % # % # %

Married-couple 41,533 86.84% 44,189 84.03% 5,124 84.14% 5,180 80.87% 1,243 79.32% 1,511 76.93%

With Children 25,067 52.41% 23,079 43.89% 2,962 48.64% 2,859 44.64% 748 47.73% 829 42.21%

Female Headed 4,401 9.20% 5,807 11.04% 666 10.94% 867 13.54% 235 15.00% 296 15.07%

With Children 3,011 6.30% 3,627 6.90% 452 7.42% 550 8.59% 155 9.89% 171 8.71%

Total Families 47,827 52,589 6,090 6,405 1,567 1,964

1990 2000 1990 2000 1990 2000

African-American # % # % # % # % # % # %

Married-couple 4,570 37.81% 8,548 63.37% 462 34.79% 659 61.94% 69 29.36% 202 69.18%

With Children 3,235 26.76% 5,578 41.35% 336 25.30% 413 38.82% 50 21.28% 127 43.49%

Female Headed 1,289 10.66% 3,942 29.22% 176 13.25% 320 30.08% 45 19.15% 67 22.95%

With Children 1,050 8.69% 2,929 21.71% 127 9.56% 204 19.17% 34 14.47% 43 14.73%

Total Families 12,087 13,489 1,328 1,064 235 292

1990 2000 1990 2000 1990 2000

Hispanic # % # % # % # % # % # %

Married-couple 1,757 84.67% 4,255 78.42% 229 78.97% 690 74.59% 51 76.12% 210 76.92%

With Children 1,312 63.23% 3,224 59.42% 161 55.52% 567 61.30% 37 55.22% 173 63.37%

Female Headed 164 7.90% 666 12.27% 25 8.62% 110 11.89% 4 5.97% 29 10.62%

With Children 127 6.12% 485 8.94% 16 5.52% 95 10.27% 2 2.99% 18 6.59%

Total Families 2,075 5,426 290 925 67 273 Source: 2000 US Census

In many communities, female-headed households and female-headed households with children face a high rate of housing discrimination. Incidents of discrimination among female headed households tend to increase even more for such households when headed by ethnic minorities. From Table 1.3 and Chart 1.3, on the following page, an examination of the structure of families in Prince William County reveals that the percentage of female-headed families with children increased between 1990 and 2000 among White, African-American, and Hispanic households, with the exception of White households in Manassas Park. For African-American families, the data show an increase from 8.69 percent to 21.71 percent in Prince William County, 9.56 percent to 19.17 percent in Manassas, and 14.47 percent to 14.73 percent in Manassas Park. For Hispanic families, the increase was from 6.12 percent to 8.94 percent in Prince William County, 5.52 percent to 10.27 percent in Manassas, 2.99 percent to 6.59 percent in Manassas Park. For White families the increase was from 6.3 percent to 6.9 percent in Prince William County, 7.42 percent to 8.59 percent in Manassas. In Manassas Park, the percent female-headed with children for White households decreased in Manassas Park from 9.89 percent to 8.71 percent between 1990 and 2000. The higher percentages present a cause for concern with respect to fair housing choice.

12

Chart 1.3: Family structure by race for Prince William Area, 1990-2000

0%10%20%30%40%50%60%70%80%90%

100%

Whi

te

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ican

-A

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ican

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Prince WilliamCounty

Manassas Manassas Park

Race

Per

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es With Children

Female Headed

With Children

Married-couple

Families with children and large family households face similar challenges in the rental housing market. When considering all family types with children present, the data show that 53.53 percent of all White households in Prince William County, 56.41 percent of all White households in Manassas, and 54.79 percent of all White households in Manassas Park have children under the age of 18 present. This compares to 67.69 percent of all African-American households in Prince William County, 62.62 percent of all African-American households in Manassas, and 64.04 percent of all African-American households in Manassas Park. Just over 73 percent of all Hispanic households in Prince William County, 78.92 percent of all Hispanic households in Manassas, and 75.09 percent of all Hispanic households in Manassas Park were in this category. Non-family households consist of single person households and unrelated individuals sharing a housing unit. These households sometimes have difficulties with fair housing choice because of their household structure. In this case, White non-family households make-up 23.81 percent of all White households in Prince William County, 30.22 percent of all White households in Manassas, and 22.98 percent of all White households in Manassas Park. African-American non-family households accounted for 23.45 percent of all African-American households in Prince William County, 24.91 percent of all African-American households in Manassas, and 17.75 percent of all African-American households in Manassas Park. Hispanic non-family households represent 12.82 percent of all Hispanic households in Prince William County, 12.74 percent of all Hispanic households in Manassas, and 11.07 percent of all Hispanic households in Manassas Park. According to 2005-2007 ACS 3-Year estimates, 12.61 percent of all households in Prince William County were female-headed households and 8.13 percent of households were female-headed households with children. About 43 percent of all

13

households in the County had children below 18 years of age and over 23 percent were non-family households. During the three-year period, over 14.61 percent of total households in Manassas were female-headed households and 11.30 percent were female-headed households with children. About 46 percent of all households in Manassas had children and about 23 percent were non-family households during the same period. The spatial distribution of female-headed households with children is shown in Map 1.7 on the following page.

14

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Percent Female-Headed HH W/Children 2000

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15

2. Income Profile Low-income households tend to be housed in less desirable housing stock and less desirable areas in a city or county. A lack of resources to pay housing expenses often prevents those households from moving to areas where local amenities raise the value of the housing. Income plays a very important part in securing and maintaining housing. Overall, household Incomes for African Americans and Hispanics were disproportionately lower compared to that of White households based on the Census data in 2000 and 2007 and detailed in Table 2.2 on page 17. Table 2.1, below, and Chart 2.1, on the following page, show the contributions of various industries to personal income over time and indicate a large change in income among industries. In Prince William County, the government sector contributed 28.62 percent of earnings in 1990. This accounts for the largest single sector earnings reported in that year.

The service industry was the second largest contributor to personal earnings in 1990, contributing 17.99 percent. By 2000, earnings from services (which include hotels, personal services, private households, business services, auto repair, amusement and recreation, motion pictures, health services, legal services, educational services, social services, museums, and membership organizations), increased to 26.66 percent. This represents an 8.67 percentage point increase for the service sector. The government sector dropped to second place, with a decrease of 2.66 percentage points, to 25.97 percent between 1990 and 2000.

Table 2.1 Personal earnings by industry for Prince William Area,

1990-2002, in thousands of dollars

Industry

1990 (by SIC

industry) 1990

Percent

2000 (by SIC

industry) 2000

Percent

Percent Point

Change

2002 (by NAICS

industry) 2002

Percent

Farm 1,011 0.04% 2,374 0.05% 0.01% 2,263 0.04%

Agricultural services, Forestry 18,110 0.72% D - - D -

Mining 7,346 0.29% D - - D -

Construction 333,038 13.29% 689,608 14.14% 0.85% 845,382 14.75%

Manufacturing 360,071 14.37% 248,205 5.09% -9.28% D -

Transportation and public utilities 139,176 5.55% D - - D -

Wholesale trade 80,601 3.22% 231,992 4.76% 1.54% 208,631 3.64%

Retail trade 334,463 13.35% 676,642 13.87% 0.53% 602,113 10.50% Finance, insurance, and real estate 64,004 2.55% D - - D -

Services 450,990 17.99% 1,300,352 26.66% 8.66% 1,394,162 24.32%

Government 717,403 28.62% 1,266,787 25.97% -2.66% 1,468,728 25.62%

Total 2,506,213 100.00% 4,878,205 100.00% 5,732,832 100.00% D: Not shown to avoid disclosure of confidential information, but the estimates for this item are included in the totals. Source: Bureau of Economic Analysis

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Chart 2.1: Personal earnings by industry for Prince William Area, 2000

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Farm Construction Wholesaletrade

Retail trade Services Government

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The largest percentage point increase in personal earnings from 1990 to 2000 occurred in the service industry (8.67%) and the largest percentage point decrease (-9.28%) occurred in the manufacturing industry. All other industries reflected relatively little change. Wholesale trade increased from 3.22 percent of personal earnings in 1990 to 4.76 percent in 2000. Construction increased from 13.29 percent of personal earnings in 1990 to 14.14 percent in 2000, a 0.85 percentage point increase. The data in Table 2.2, on the following page and Chart 2.2, on page 18, show the distribution of income across income classes and reveal the differences in income between Whites and minorities in Prince William County. Overall, the income distribution data show a higher incidence of low-income households within the African-American and Hispanic communities. Limitations on fair housing choice are more commonly found to effect housing decisions among low-income persons. The range of areas within which affordable housing is available is much more limited for low-income households than for higher income households. Chart 2.2 shows that the most frequent income class for African-Americans and Hispanics is the $50,000 to $74,999 range in Prince William County. Nearly 25 percent of all African-American households in Prince William County, nearly 29 percent of all African-American households in Manassas, and over 31 percent of all African-American households in Manassas Park fall into this income range. Nearly 27 percent of Hispanic households fall into this income class, in Prince William County, while nearly 28 percent and over 20 percent of all Hispanic households report earnings in this range in Manassas and Manassas Park, respectively. The most frequently reported income for Whites is $100,000 or more, with 27 percent of households in Prince William County, over 22 percent in Manassas, and over 14 percent in Manassas Park.

17

Table 2.2 Households by race by income class for Prince William Area, 2000

Prince William County Manassas Manassas Park Income class in White Number Percent Number Percent Number Percent

Less than $10,000 1,453 2.21% 253 2.92% 74 3.03%

$10,000 to $14,999 1,033 1.57% 301 3.47% 82 3.36%

$15,000 to $24,999 3,146 4.79% 532 6.14% 133 5.45%

$25,000 to $34,999 4,786 7.28% 791 9.12% 176 7.21%

$35,000 to $49,999 8,851 13.46% 1,332 15.36% 404 16.56%

$50,000 to $74,999 16,042 24.40% 1,930 22.26% 746 30.57%

$75,000 to $99,999 12,676 19.28% 1,587 18.30% 482 19.75%

$100,000 or more 17,749 27.00% 1,944 22.42% 343 14.06%

Total: 65,736 100.00% 8,670 100.00% 2,440 100.00%

Prince William County Manassas Manassas Park Income class in African-American Number Percent Number Percent Number Percent

Less than $10,000 671 3.75% 41 2.80% 9 2.95%

$10,000 to $14,999 490 2.74% 48 3.27% 0 0.00%

$15,000 to $24,999 1,268 7.08% 117 7.98% 10 3.28%

$25,000 to $34,999 2,043 11.42% 164 11.19% 51 16.72%

$35,000 to $49,999 3,274 18.29% 326 22.24% 17 5.57%

$50,000 to $74,999 4,422 24.71% 423 28.85% 95 31.15%

$75,000 to $99,999 2,912 16.27% 216 14.73% 81 26.56%

$100,000 or more 2,817 15.74% 131 8.94% 42 13.77%

Total: 17,897 100.00% 1,466 100.00% 305 100.00%

Prince William County Manassas Manassas Park Income class in Hispanic Number Percent Number Percent Number Percent

Less than $10,000 169 2.68% 45 4.01% 5 1.48%

$10,000 to $14,999 121 1.92% 23 2.05% 2 0.59%

$15,000 to $24,999 463 7.34% 121 10.79% 38 11.24%

$25,000 to $34,999 832 13.18% 147 13.11% 53 15.68%

$35,000 to $49,999 1,240 19.65% 165 14.72% 58 17.16%

$50,000 to $74,999 1,684 26.68% 310 27.65% 68 20.12%

$75,000 to $99,999 867 13.74% 175 15.61% 67 19.82%

$100,000 or more 935 14.82% 135 12.04% 47 13.91%

Total: 6,311 100.00% 1,121 100.00% 338 100.00% Source: 2000 US Census

18

Chart 2.2: Households by race by income class for Prince William Area, 2000

0.00%

5.00%

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15.00%

20.00%

25.00%

30.00%

Less than$10,000

$10,000 to$14,999

$15,000 to$24,999

$25,000 to$34,999

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$75,000 to$99,999

$100,000or more

Income Group

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s

White

African-American

Hispanic

Over six percent of African-American households had 2000 incomes below $15,000 in Prince William County and Manassas, while nearly three percent of the African-American households in Manassas Park fall in this income range. This compares to nearly four percent of White households in Prince William County, and over six percent of White households in Manassas and Manassas Park. Nearly five percent of Hispanic households fall in this income range, compared to over six and over two percent of all Hispanic households in Manassas and Manassas Park, respectively. Over 71 percent of White households reported incomes above $50,000 in Prince William County, with nearly 63 percent in Manassas and over 64 percent in Manassas Park. African-American households in the same income groups represented nearly 57 percent of all African-American households in Prince William County, nearly 53 percent in Manassas, and over 71 percent in Manassas Park. Over 55 percent of Hispanics in Prince William County and Manassas, and nearly 54 percent of Hispanics households in Manassas Park fall into this category in 2000. Over 27 percent of White households in Prince William County, over 22 percent of White households in Manassas, and over 14 percent of White households in Manassas Park had incomes above $100,000. Nearly 16 percent of African-American households in Prince William County, nearly nine percent in Manassas and nearly 14 percent in Manassas Park were in this income category. Nearly 15 percent of Hispanic households in Prince William County, over 12 percent in Manassas, and nearly 14 percent in Manassas Park were reported in this group.

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According to the 2005-2007 ACS 3-Year estimates, in Prince William County, the median household income for White households was $95,150, for African-American households was $74,802, and Hispanic households was $65,883. In comparison, median household income for the overall county was $85,538. The median household income in Manassas was $83,009 for White households, $58,488 for African-American households, and $60,051 for Hispanic households during the three year period. In comparison, median household income for Manassas was $74,221. The geographic distribution of income is represented in Maps 2.1, 2.2, and 2.3 on the following pages. The first map shows the distribution of incomes below $15,000. The second shows incomes from $15,000 to $25,000. The third shows incomes from $25,000 to $35,000.

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Poverty also negatively impacts fair housing choice. Similar to the income distribution data reported above, the poverty data on Table 2.3 and Chart 2.3, on the following pages, show major effects on the African-American and Hispanic communities. The incidence of poverty among African-Americans in 2000 was reported to be 6.99 percent of the total population in Prince William County, 8.64 percent in Manassas, and 3.25 percent in Manassas Park. Just over eight percent of Hispanics in Prince William County, 18.19 percent in Manassas, and 7.17 percent in Manassas Park lived in poverty in 2000. Among White persons, the data reported 2.98 percent living in poverty in Prince William County, 3.99 percent in Manassas, and 4.86 percent in Manassas Park. Of equal concern, among children below the age of 5, nearly 11 percent of all African-Americans in Prince William County and Manassas were living in poverty. Among Hispanics, over nine percent in Prince William County, nearly 18 percent in Manassas, and over seven percent in Manassas Park were living in poverty. Comparatively, nearly four percent of all White children below the age of 5, are living in poverty in Prince William County, over four percent in Manassas, and nearly five percent in Manassas Park. Living in poverty restricts the quality of life of these children due to the limited housing options available to their parents.

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Table 2.3 Poverty Status by race for Prince William Area, 2000


White In Poverty

Total Pop. Percent In Poverty

Total Pop. Percent

In Poverty

Total Pop. Percent

Under 5 years 519 13,372 3.88% 72 1,677 4.29% 59 616 9.58%

5 years 124 2,924 4.24% 23 292 7.88% 0 143 0.00%

6 to 11 years 530 17,084 3.10% 102 2,320 4.40% 49 602 8.14%

12 to 17 years 696 16,036 4.34% 97 2,057 4.72% 41 598 6.86%

18 to 64 years 3,074 120,025 2.56% 560 15,105 3.71% 146 4,527 3.23%

65 to 74 years 184 6,530 2.82% 33 890 3.71% 23 272 8.46%

75 years and over 222 3,593 6.18% 26 529 4.91% 16 114 14.04%

Total: 5,349 179,564 2.98% 913 22,870 3.99% 334 6,872 4.86%


African-American In Poverty


Total Pop. Percent

In Poverty

Total Pop. Percent

Under 5 years 505 4,762 10.60% 37 342 10.82% 0 82 0.00%

5 years 107 1,269 8.43% 16 63 25.40% 0 19 0.00%

6 to 11 years 621 6,518 9.53% 74 511 14.48% 0 165 0.00%

12 to 17 years 618 5,916 10.45% 76 492 15.45% 0 111 0.00%

18 to 64 years 1,676 32,475 5.16% 131 2,676 4.90% 36 697 5.16%

65 to 74 years 89 729 12.21% 18 113 15.93% 0 35 0.00%

75 years and over 25 436 5.73% 14 40 35.00% 0 0 0.00%

Total: 3,641 52,105 6.99% 366 4,237 8.64% 36 1109 3.25%


Hispanic In Poverty


Total Pop. Percent

In Poverty

Total Pop. Percent

Under 5 years 285 3,086 9.24% 130 733 17.74% 15 210 7.14%

5 years 36 670 5.37% 0 125 0.00% 0 5 0.00%

6 to 11 years 328 3,087 10.63% 88 435 20.23% 0 191 0.00%

12 to 17 years 253 2,834 8.93% 69 490 14.08% 8 139 5.76%

18 to 64 years 1,226 16,658 7.36% 502 3,290 15.26% 72 981 7.34%

65 to 74 years 17 322 5.28% 0 41 0.00% 5 18 27.78%

75 years and over 0 126 0.00% 0 13 0.00% 4 11 36.36%

Total: 2,145 26,783 8.01% 789 4,338 18.19% 104 1,451 7.17%

Source: 2000 US Census

25

Chart 2.3: Percent in Poverty by race for Prince William Area, 2000

0.00%

2.00%

4.00%

6.00%

8.00%

10.00%

12.00%

14.00%

Under 5years

5 years 6 to 11years

12 to 17years

18 to 64years

65 to 74years

75 yearsand over

Total:

Age Group

Po

vert

y R

ate

White

African-American

Hispanic

According to the 2005-2007 ACS 3-Year estimates, in Prince William County, the poverty rate for Whites was 2.77 percent, African-Americans 6.09 percent, and Hispanics was 9.77 percent. In comparison, the poverty rate for the overall county was 4.77 percent. The poverty rate in Manassas was 5.45 percent for Whites, 10.54 percent for African-Americans, and 20.61 percent for Hispanics during the three year period. In comparison, the poverty rate for Manassas was 10.92 percent. Families living at or below the poverty level are more likely to be dependant on federally funded housing choice vouchers (Section 8) to meet their monthly payment of housing. Without government assistance, many of these households will be forced to choose rental units strictly based on affordability, and sometimes units in substandard condition or housing units that are deficient relative to their family size or to accommodate those with disabilities.

26

3. Employment Profile Employment opportunities and educational levels of employees have a significant impact on housing affordability and the location choice of residents. According to the estimates provided by the Virginia Workforce Connection and the Prince William County Department of Economic Development, unemployment remains low for the area. The County’s unemployment rate was 5.6 percent in May 2009, compared to seven percent statewide and nine percent for the U.S. in March 2009. The data presented in Table 3.1 and Chart 3.1, on pages 27 and 28, provide a portrait of the unemployed in Prince William County. The unemployment rate for Prince William County, as measured by the 2000 Census, was 2.84 percent , compared to 4.09 percent for Virginia and 5.72 percent for U.S overall. The unemployment rates in Manassas and Manassas Park were 3.71 percent and 2.2 percent respectively. A closer look at the make-up of this total, however, indicates that even though the rate remained low, more of the unemployment was centered in the African-American and Hispanic community. In the 2000 Census, 2.2 percent of White persons age 16 and over reported being unemployed in Prince William County, compared to 4.03 percent of African-Americans and 4.47 percent of Hispanics. In Manassas, African-American persons in the same age group reported an 8.08 percent unemployment rate and Hispanics reported a 4.12 percent rate, compared to 2.62 percent of Whites. In Manassas Park, the unemployment rate for African-Americans was 1.98, Hispanics was 7.08, and Whites was 1.4 percent. Map 3.1 on the page 29, shows the distribution of unemployed persons in Prince William County in 2000. According to the 2005-2007 ACS 3-Year estimates, in Prince William County, the unemployment rate for Whites was 3.25 percent, African-Americans was 5.64 percent, and Hispanics was 5.09 percent. In comparison, unemployment rate for the overall county was 3.99 percent. The unemployment rate for Manassas was 4.83 percent during the three-year period. The employment data by race is not available for Manassas and Manassas Park due to the small sample size. In Prince William County, the difference in the unemployment rate between the three groups can, to some extent, be attributed to limitations due to educational attainment, particularly, for the Hispanic population. Looking at educational attainment, according to the 2000 Census, as shown in Table 3.2 and Chart 3.2 on pages 30 and 31, 10.05 percent of African-Americans age 25 and above report less than a high school education in Prince William County, compared to 7.97 percent of Whites and 38.38 percent for Hispanics in the same age group. In Manassas, 22.79 percent of African-Americans and 62.38 percent of Hispanics had less than high school education, compared to 9.78 percent of Whites. In Manassas Park, 22.78 percent of African-Americans and 60.8 percent of Hispanics did not attain a high school degree, compared to 18.71 percent of Whites.

27

Table 3.1 Employment Status by race for Prince William Area, 2000

Prince William County Manassas Manassas Park Employment Status in White Number Percent Number Percent Number Percent

In labor force:

In Armed Forces 5,364 5.06% 114 0.87% 28 0.69%

Civilian:

Employed 98,220 92.73% 12,708 96.51% 3,976 97.91%

Unemployed 2,335 2.20% 345 2.62% 57 1.40%

Total 105,919 100.00% 13,167 100.00% 4,061 100.00%

Not in labor force 30,719 4,336 1,010

Total 136,638 17,503 5,071

Prince William County Manassas Manassas Park Employment Status in African-American Number Percent Number Percent Number Percent

In labor force:

In Armed Forces 1867 6.48% 28 1.15% 6 1.08%

Civilian:

Employed 25,776 89.49% 2,213 90.77% 539 96.94%

Unemployed 1,160 4.03% 197 8.08% 11 1.98%

Total 28,803 100.00% 2,438 100.00% 556 100.00%

Not in labor force 7,237 816 195

Total 36,040 3,254 751

Prince William County Manassas Manassas Park Employment Status in Hispanic Number Percent Number Percent Number Percent

In labor force:

In Armed Forces 456 3.57% 18 0.72% 0 0.00%

Civilian:

Employed 11,737 91.96% 2,377 95.16% 656 92.92%

Unemployed 570 4.47% 103 4.12% 50 7.08%

Total 12,763 100.00% 2,498 100.00% 706 100.00%

Not in labor force 5,431 1,100 352

Total 18,194 3,598 1,058

Prince William County Manassas Manassas Park Overall Employment Status Number Percent Number Percent Number Percent

In labor force:

In Armed Forces 8046 5.12% 170 0.89% 34 0.60%

Civilian:

Employed 144,748 92.05% 18,238 95.40% 5,513 97.20%

Unemployed 4,460 2.84% 710 3.71% 125 2.20%

Total 157,254 100.00% 19,118 100.00% 5,672 100.00%

Not in labor force 46,748 6,601 1676

Total 204,002 25,719 7,348 Source: 2000 US Census

28

Chart 3.1: Employment Status by race for Prince William Area, 2000

0.00%

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According to the 2005-2007 ACS 3-Year estimates, in Prince William County, the percentage of population with less than high school education for Whites was 6.14 percent, African-Americans was 6.60 percent, and Hispanics was 39.45 percent. In comparison, this percentage for the overall county was 11.87 percent. The percentage of population with less than high school education in Manassas was 9.47 percent for Whites, 19.42 percent for African-Americans, and 51.18 percent for Hispanics during the three year period. In comparison, this percentage for Manassas was 20.4 percent. This larger number of poorly educated individuals tends to result in a significant pool of workers who bring no special knowledge or skills to the workplace. The majority of these workers often end up in low-paying, low-skilled positions in the service and manufacturing industries. Map 3.2, on page 32, provides a look at the geographic distribution of persons with less than a high school degree in 2000.

29

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Unemployment Rate

0.74% - 1%

1.01% - 2%

2.01% - 4%

4.01% - 5.8%

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30

Table 3.2 Educational attainment by race, Prince William Area, 2000.

Prince William County Manassas Manassas Park White Educational

Attainment Number Percent Number Percent Number Percent

< 9th grade 2,293 1.96% 417 2.80% 135 3.05%

9th to 12th grade 7,043 6.01% 1,040 6.98% 693 15.66%

High school graduate 29,825 25.46% 3,674 24.67% 1,404 31.74%

College 29,034 24.78% 3,757 25.22% 1,125 25.43%

Associate degree 8,593 7.33% 992 6.66% 245 5.54%

Bachelor's degree 25,490 21.76% 3,154 21.18% 562 12.70%

Graduate 14,874 12.70% 1,860 12.49% 260 5.88%

Total 117,152 100.00% 14,894 100.00% 4,424 100.00%

Prince William County Manassas Manassas Park African-American Educational Attainment Number Percent Number Percent Number Percent

< 9th grade 838 2.83% 125 4.66% 27 4.35%

9th to 12th grade 2,141 7.22% 486 18.13% 115 18.52%

High school graduate 7,736 26.09% 744 27.75% 111 17.87%

College 8,988 30.31% 710 26.48% 146 23.51%

Associate degree 2,571 8.67% 156 5.82% 56 9.02%

Bachelor's degree 5,043 17.01% 308 11.49% 133 21.42%

Graduate 2,337 7.88% 152 5.67% 33 5.31%

Total 29,654 100.00% 2,681 100.00% 621 100.00%

Prince William County Manassas Manassas Park Hispanic Educational Attainment Number Percent Number Percent Number Percent

< 9th grade 3,310 24.14% 831 32.49% 285 35.80%

9th to 12th grade 1,953 14.24% 739 28.89% 199 25.00%

High school graduate 2,978 21.72% 420 16.42% 140 17.59%

College 2,748 20.04% 220 8.60% 75 9.42%

Associate degree 633 4.62% 94 3.67% 48 6.03%

Bachelor's degree 1,456 10.62% 163 6.37% 29 3.64%

Graduate 633 4.62% 91 3.56% 20 2.51%

Total 13,711 100.00% 2,558 100.00% 796 100.00%


31

Chart 3.2: Educational attainment by race, Prince William Area, 2000.

0.00%

5.00%

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15.00%

20.00%

25.00%

30.00%

35.00%

< 9th grade 9th to 12thgrade

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College Associatedegree

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Graduate

Educational Status

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Hispanic

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Percent Less than High School Degree

1.54% - 5%

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10.71% - 15%

15.28% - 33.25%


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Table 3.3 Occupation of employed persons for Prince William Area, 1990 & 2000


Occupation of employed 1990 2000

Percent Point

Change 1990 2000

Percent Point

Change 1990 2000

Percent Point

Change

Agriculture, forestry, fishing, hunting, and mining 1.15% 0.32% -0.83% 1.38% 0.24% -1.14% 1.14% 0.20% -0.94%

Construction 10.82% 8.88% -1.95% 12.36% 11.56% -0.80% 18.82% 17.20% -1.63%

Manufacturing 6.51% 4.74% -1.77% 6.84% 6.38% -0.46% 8.99% 3.75% -5.24%

Wholesale trade 3.10% 2.16% -0.94% 4.18% 2.06% -2.12% 4.04% 2.81% -1.22%

Retail trade 16.80% 12.03% -4.77% 15.85% 12.30% -3.55% 18.45% 13.68% -4.77%

Transportation and warehousing, and utilities 8.98% 10.64% 1.67% 8.99% 11.04% 2.05% 9.56% 12.21% 2.65%

Finance, insurance, real estate and rental and leasing 6.16% 5.66% -0.50% 6.38% 5.21% -1.17% 4.14% 6.60% 2.46%

Professional, scientific, management, administrative services 7.09% 15.26% 8.17% 10.53% 14.56% 4.04% 6.74% 12.26% 5.52%

Educational, health and social services 11.24% 15.53% 4.29% 10.91% 15.39% 4.48% 10.86% 14.51% 3.65%

Arts, entertainment, recreation, accommodation and food services 3.44% 6.23% 2.79% 3.39% 7.48% 4.09% 4.01% 4.93% 0.93%

Other services (except public administration) 8.49% 5.37% -3.11% 7.95% 5.23% -2.71% 6.83% 6.00% -0.82%

Public administration 16.23% 13.19% -3.04% 11.25% 8.55% -2.70% 6.42% 5.84% -0.58% Source: 2000 US Census

Table 3.3, below, and Chart 3.3, on the following page, provide a look at occupation data, which indicate that there has been a shift in the distribution of occupations over the past decade. In 1990, 16.8 percent of all employed persons 16 years of age and older in Prince William County were employed in retail trade; 16.23 percent in public administration; 11.24 percent in educational, health, and social services; 10.82 percent in construction; 8.98 percent in transportation, warehousing, and utilities; 8.49 percent in other services (except public administration); and 7.09 percent in professional, scientific, management, and administrative services. By 2000, professional, scientific, management, and administrative service occupations had the largest increase, up 8.17 percentage points to 15.26 percent. Retail trade realized the largest reduction to 12.03 percent of the workforce, a 4.18 percentage point drop. Public administration and other services experienced more than a three percent drop. Educational, health, and social services increased by 4.29 percentage points to 15.53 percent of the work force. Arts, entertainment, recreation, accommodation and food services showed an increase to 6.23 percent of the workforce, up 2.79 percentage points. In 2000, educational, health, and social services employed the highest percentage pf populations in Manassas and Manassas Park, at 15.39 percent and 14.51 percent respectively. In Manassas, the highest percentage point increase in occupation

34

Chart 3.3: Occupation of employed in Prince William Area, 2000

Agriculture, forestry, fishing, hunting, and miningConstruction

Manufacturing

Wholesale trade

Retail trade

Transportation and utilities

Information

Finance and real estate

Professional and management

Educational and health

Arts, entertainment, andrecreationOther services

Public administration

occurred in educational, health, and social services, at 4.48 percentage points. Retail trade experienced a drop of 3.55 percentage points to 12.3 percent in Manassas, between 1990 to 2000. During the period, in Manassas Park, professional, scientific, management, administrative services grew by 5.52 percent to 12.26 percent. Manufacturing sector in Manassas Park decreased by 5.24 percentage points to 3.75 percent in 2000.

Based on the 2005-2007 ACS 3-Year estimates, Professional, scientific, management, administrative services employed the highest percentage of population at 21.27 percent during the three-year period. The next largest sector was educational, health and social services at 16.97 percent. Public Administration sector employed 12.96 percent of the workforce. Construction sector employed 11.64 percent. Retail trade employed 10.54 percent during this period. A list of major corporate employers, as reported by Prince William Department of Economic Development, is found in Table 3.4, to the right. Among local employers, the largest is Prince William County with over 33,000 employees (including school administration). Among the corporate employers largest is Micron Technologies with 1,800 employees. Other major employers in the county are Lockheed Martin Naval Electronics and Survey System with 1,200 employees and General Dynamics with 800 employees.

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Table 3.4 Major Employers in Prince William County

Major Corporate Employers Employees

Micron Technologies 1,800

Lockheed Martin 1,200

General Dynamics 800

US Foodservice 360

American Type Culture Collection 350

BAE Systems 330

Northern Virginia Electric Cooperative

300

Comcast 233

Source: Prince William Department of Economic Development

The availability of jobs for low-income persons can be largely dependent on the geographic location of the jobs and transportation and mobility. If jobs are concentrated in areas far removed from lower income persons, or areas poorly served by public transportation, their ability to get to and from work may be restricted, sometimes causing hardships on employees or potential employees. To examine this issue, we reviewed public transportation and its ability to accommodate the various communities’ mobility needs.

36

4. Public Transportation Profile

The Potomac and Rappahannock Transportation Commission (PRTC) provides a variety of public transportation services in the Prince William Area. These services include commuter services during peak hours (COMMUTERIDE) into the Greater Washington employment area, including the Pentagon, Crystal City, and the Vienna Metro station.

For local transportation, the PRTC offers OmniLink, a local weekday service that combines fixed transit stops and flexible routing-- if the origin or destination is not near a stop. The Virginia Railway Express (VRE) commuter rail service offers service from Manassas and Manassas Park to Union Station (DC) on week days. This service is also provided on the eastern end of the County with stops at Quantico, Rippon and Woodbridge. The train has stops at Lorton, Franconia/Springfield, Alexandria, Crystal City, L’Enfant Plaza and Union Station which are all major locations of employment. The VRE also runs on the weekend on a limited schedule. OmniRide is a comfortable and efficient commuter bus service from eastern Prince William County and the Manassas area to downtown Washington, the Pentagon, Crystal City, and the Washington Navy Yard. MetroDirect, operated by PRTC, is an all-day connection to the Franconia-Springfield Metro Station from eastern Prince William or to the Vienna and West Falls Church Metro from Manassas. The commission also offers OmniMatch, which is a free ridematching service for carpoolers and vanpoolers. Map 4.1, on the following page, provides a geographic representation of the 2000 Census data for persons using public transportation.

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Table 5.1 Tenure for housing in Prince William Area, 2000


Housing Units Number Percent Number Percent Number Percent

Owner-occupied 67,787 69.13% 8,203 67.72% 2,560 76.08%

Renter-occupied 26,783 27.32% 3,554 29.34% 694 20.62%

Vacant 3,482 3.55% 357 2.95% 111 3.30%

Total: 98,052 100.00% 12,114 100.00% 3,365 100.00%


Chart 5.1: Tenure for housing in Prince William Area, 2000

69.19%

27.33%

3.48%

Ow ner occupied

Renter occupied

Vacant

5. Housing Profile As per the data provided by Prince William County, there were an estimated 137,381 housing units in the county in June 2009. This represents an additional 39,329 units (40.1%) since April 2000. The vacancy rate in the county was 3.6 percent in June 2009, According to the 2005-2007 ACS 3-Year estimates, there were 130,101 housing units in Prince William County. Of the total housing units in the county, 70.46 percent were owner-occupied, 23.31 percent were renter-occupied, and the remaining 6.23 percent were vacant. During the same period, Manassas had 12,824 housing units. Of the total housing units in Manassas, 63.65 percent were owner-occupied, 27.61 percent were renter-occupied, and the remaining 8.74 percent were vacant. As presented in Table 5.1 and Chart 5.1, to the right, there were 98,052 housing units located within Prince William County, 12,114 in Manassas, and 3,365 in Manassas Park in 2000. In Prince William County, 69.13 percent of housing units were owner-occupied, 27.32 percent were renter-occupied, and the remaining 3.55 percent were vacant. Of the occupied units in Prince William County, 71.68 percent were owner-occupied and 28.32 percent were renter-occupied. In Manassas, 67.72 percent of housing units were owner-occupied, 29.34 percent were renter-occupied, and the remaining 2.95 percent were vacant. Of the occupied housing units in Manassas, 69.77 percent were owner-occupied and 30.23 percent were renter-occupied. In Manassas Park, 76.08 percent of housing units were owner-occupied, 20.62 percent were renter-occupied, and the remaining 3.3 percent were vacant. Of the occupied units in Manassas, 78.67 percent were owner-occupied and 21.33 percent were renter-occupied. According to the Metropolitan Information System (MRIS) and the data provided by Prince William County, the average sold price of a home in Prince William County in May 2009 was $238,231, which represents a 16.3 percent decline year-over-year. The total number of units sold in May 2009 in Prince William County was 753, a four percent increase year-over year. According to the estimates provided by the Prince William County, the median home value for single-family homes was $290,447 in 2009. According to the

39

Table 5.2 Housing type for Prince William Area, 2000

Prince William County Manassas Manassas Park Units in Structure Number Percent Number Percent Number Percent Single-Family detached 52,826 53.88% 5,197 42.90% 2,203 65.47% Single-Family attached 26,288 26.81% 4,029 33.26% 1,111 33.02%

2-4 unit 1,900 1.94% 311 2.57% 18 0.53%

Multifamily 15,232 15.53% 2,392 19.75% 19 0.56%

Other 1,806 1.84% 185 1.53% 14 0.42%

Total 98,052 100.00% 12,114 100.00% 3,365 100.00%


2005-2007 ACS 3-Year estimates, the median home value for single-family houses in Prince William County was $421,300 and the median contract rent was $1,104. During the same period, in Manassas, the median housing value was $377,600 and the median contract rent was $1,045. The median housing value in Manassas Park was reported to be $115,700 and the median contract rent was reported to be $741. As per the data provided by Prince William County, of the total number of housing units in the County in June 2009, it is estimated that 76,458 (55.65%) were single-family detached, 35,471 (25.81%) were townhouses, 23,646 (17.21%) were units in multifamily structures, and 1,806 (1.34%) were reported as “other units”. Table 5.2, below, shows that of all housing units in Prince William County, 53.88 percent were categorized as single-family detached, 26.81 percent as single-family attached, 1.94 percent contained 2 to 4 units, 15.53 percent as multifamily, and 1.84 percent as mobile home or other. In Manassas, 42.9 percent were categorized as single-family detached, 33.26 percent as single-family attached, 2.57 percent contained 2 to 4 units, 19.75 percent as multifamily, and 1.53 percent as mobile home or other. In Manassas Park, 65.47 percent were categorized as single-family detached, 33.02 percent as single-family attached, 0.53 percent contained 2 to 4 units, 0.56 percent as multifamily, and 0.42 percent as mobile home or other. According to the 2005-2007 ACS 3-Year estimates, of all the housing units in Prince William County 81.83 percent were single-family units, 1.86 percent had 2 to 4 units, 15.12 percent were multifamily units, and 1.18 percent were other types of units. During this period, Manassas had 76.97 percent single-family units, 2.38 percent duplex to four-plex units, 18.85 percent multifamily units, and 1.81 percent other types of units.

Table 5.3, on the following page, details the age of the housing units, according to the 2000 census. In Prince William County, 3.05 percent were built prior to 1950, 4.64 percent were built between 1950 and 1959, 12.9 percent were built between 1960 and 1969, 22.29 percent were built between 1970 and 1979, and 57.12 percent were built after 1979. In Manassas, 4.64 percent were built prior to 1950, 6.25 percent were built between 1950 and 1959, 11.99 percent were built between 1960 and 1969, 17.56 percent were built between 1970 and 1979, and 59.56

40

Table 5.3 Age of Housing Stock in Prince William Area, 2000

Prince William

County Manassas Manassas Park

Housing Built Number Percent Number Percent Number Percent

Built 1939 or earlier 1,491 1.52% 341 2.81% 15 0.45%

Built 1940 to 1949 1,503 1.53% 222 1.83% 81 2.41%

Built 1950 to 1959 4,548 4.64% 757 6.25% 980 29.12%

Built 1960 to 1969 12,645 12.90% 1,453 11.99% 470 13.97%

Built 1970 to 1979 21,855 22.29% 2,127 17.56% 307 9.12%

Built 1980 to 1989 27,341 27.88% 4,648 38.37% 335 9.96%

Built 1990 to 1994 12,516 12.76% 1,778 14.68% 310 9.21%

Built 1995 to 1998 12,039 12.28% 706 5.83% 536 15.93% Built 1999 to March 2000 4,114 4.20% 82 0.68% 331 9.84%

Total: 98,052 100.00% 12,114 100.00% 3,365 100.00%

Chart 5.3: Age of Housing Stock in Prince William Area, 2000

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

Built1939 orearlier

Built1940 to

1949

Built1950 to

1959

Built1960 to

1969

Built1970 to

1979

Built1980 to

1989

Built1990 to

1994

Built1995 to

1998

Built1999 toMarch2000

Year Structure Built

Per

cen

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ou

sin

g U

nit

s

Source: 2000 U.S. Census

percent were built after 1979. In Manassas Park, 2.86 percent were built prior to 1950, 29.12 percent were built between 1950 and 1959, 13.97 percent were built between 1960 and 1969, 9.12 percent were built between 1970 and 1979, and 44.94 percent were built after 1979. Maps 5.1 and 5.2, on pages 41 and 42, indicate the distribution of single-family and multifamily housing across the Area. Map 5.3, on the page 43, provides a geographic representation of the distribution of the oldest housing stock in the county.

41

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Percent Single-Family Units 2000

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9202

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9012.08

9012.09

9010.08

9004.04

9012.21

9202

9016.01

9012.11

9017.02

9012.22

9009.03

Manassas Park

Manassas

Dale City

Gainesville

Nokesville

Woodbridge

Lake Ridge

Linton Hall

Montclair

Quantico Station

Triangle

Bull Run

YorkshireSudley

Dumfries

West Gate

Haymarket

Occoquan

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Manassas Park City

City Limits

Percent Multifamily Units 2000

0% - 1%

1.01% - 20%

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30.01% - 58.33%


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9010.07

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9101

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9016.02

9202

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92019017.01

9012.08

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9010.08

9004.04

9012.21

9202

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9017.02

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Manassas Park

Manassas

Dale City

Gainesville

Nokesville

Woodbridge

Lake Ridge

Linton Hall

Montclair

Quantico Station

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YorkshireSudley

Dumfries

West Gate

Haymarket

Occoquan

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City Limits

Pre-1960 Housing Stock

0% - 10%

10.01% - 20%

20.01% - 40%

40.01% - 65.42%


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Percent Pre-1960 Housing Stock

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Table 5.4 Tenure by race for Housing in Prince William Area, 2000


White Number Percent Number Percent Number Percent

Owner 52,195 76.02% 6,668 73.10% 2,003 78.95%

Rental 16,468 23.98% 2,454 26.90% 534 21.05%

Total 68,663 100.00% 9,122 100.00% 2,537 100.00%


African-American Number Percent Number Percent Number Percent

Owner 10,383 58.56% 821 57.01% 238 68.79%

Rental 7,347 41.44% 619 42.99% 108 31.21%

Total 17,730 100.00% 1,440 100.00% 346 100.00%


Hispanic Number Percent Number Percent Number Percent

Owner occupied 3,729 60.66% 507 48.70% 226 76.09%

Renter occupied 2,418 39.34% 534 51.30% 71 23.91%

Total: 6,147 100.00% 1,041 100.00% 297 100.00%


When considering tenure by the race of the householder, the 2000 data shown in Table 5.4, below, indicate that 76.02 percent of White households in Prince William County owned their home, while 23.98 percent rented. This compares to 58.56 percent of African-American households who owned their home and 41.44 percent who rented and 60.66 percent of Hispanic households who owned and 39.34 percent who rented. In Manassas, 73.1 percent of White households owned their home and 26.9 percent rented. Over 57 percent of African-American households owned their home and 42.99 percent rented and 48.7 percent of Hispanic households owned their home and 51.3 percent rented. In Manassas Park, 78.95 percent of White households owned their home, while 21.05 percent rented. Comparatively, 68.71 percent of African-American households owned their home and 31.21 percent rented and 76.09 percent of Hispanics owned their home and 23.91 percent rented.

45

Chart 5.4: Tenure by race for Housing in Prince William Area, 2000

0.00%

10.00%

20.00%

30.00%

40.00%

50.00%

60.00%

70.00%

80.00%

White African-American Hispanic

Race

Per

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ou

seh

old

ers

Ow ner

Rental

According to the 2005-2007 ACS 3-Year estimates, in Prince William County, 80.16 percent of White households owned their home, compared to 59.94 percent of African-American households, and 69.60 percent of Hispanic households owned their home. During this period, in Manassas, 72.07 percent of White households owned their home, compared to 65.84 percent of African-American households, and 58.25 percent of Hispanic households owned their home. Table 5.5, on the following page, and Chart 5.5, on page 47, show that the modal rent category for Whites, African-Americans, and Hispanics in Prince William County, Manassas, and Manassas Park was $750 to $999. In Prince William County, over 40 percent of White households, nearly 42 percent of African-American households, and over 41 percent of Hispanic households were in this rent range in 2000. In Manassas, over 41 percent of White households, over 56 percent of African-American households, and nearly 68 percent of Hispanic households were in the modal rent category. In Manassas Park, nearly 51 percent of White households, over 69 percent of African-American households, and nearly 66 percent of Hispanic households were in the modal rent category.

46

Table 5.5

Gross rent by race for Prince William Area, 2000

Prince William County Manassas Manassas Park Gross Rent in White Number Percent Number Percent Number Percent

Less than $200 208 1.36% 4 0.18% 0 0.00%

$200 to $299 206 1.34% 0 0.00% 0 0.00%

$300 to $499 529 3.45% 187 8.20% 23 4.69%

$500 to $749 3,112 20.30% 715 31.35% 34 6.94%

$750 to $999 6,136 40.03% 946 41.47% 248 50.61%

$1,000or more 4,104 26.77% 361 15.83% 160 32.65%

No cash rent 1,033 6.74% 68 2.98% 25 5.10%

Total 15328 100.00% 2281 100.00% 490 100.00%

Prince William County Manassas Manassas Park Gross Rent in African-American Number Percent Number Percent Number Percent

Less than $200 150 2.05% 10 1.62% 0 0.00%

$200 to $299 78 1.07% 8 1.29% 0 0.00%

$300 to $499 258 3.52% 39 6.30% 0 4.69%

$500 to $749 1,866 25.49% 146 23.59% 33 30.55%

$750 to $999 3,060 41.80% 348 56.22% 75 69.44%

$1,000or more 1,718 23.47% 68 10.99% 0 0.00%

No cash rent 191 2.61% 0 0.00% 0 0.00%

Total 7,321 100.00% 619 100.00% 108 100.00%

Prince William County Manassas Manassas Park Gross Rent in Hispanic Number Percent Number Percent Number Percent

Less than $200 40 1.66% 0 0.00% 0 0.00%

$200 to $299 27 1.12% 0 0.00% 0 0.00%

$300 to $499 123 5.10% 7 1.31% 7 9.86%

$500 to $749 691 28.65% 102 19.10% 0 0.00%

$750 to $999 999 41.42% 361 67.60% 47 66.20%

$1,000or more 438 18.16% 64 11.99% 17 23.94%

No cash rent 94 3.90% 0 0.00% 0 0.00%

Total 2,412 100.00% 534 100.00% 71 100.00% Source: 2000 US Census

47

Chart 5.5: Gross rent by number of households for Prince William Area, 2000

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

35.00%

40.00%

45.00%

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Less than$200

$200 to$299

$300 to$499

$500 to$749

$750 to$999

$1,000ormore

No cashrent

Gross Rent

Per

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f R

ace

White

African-American

Hispanic

According to the 2005-2007 ACS 3-Year estimates, median gross rent in Prince William County was $1,227. During this period, median gross rent in Manassas was $1,153. Maps 5.4 and 5.5, on the following pages, provide a geographic depiction of the distribution of rents and housing values across the county.

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9011

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9101

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Manassas Park

Manassas

Dale City

Gainesville

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Montclair

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YorkshireSudley

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West Gate

Haymarket

Occoquan

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Manassas Park City

City Limits

Median Housing Value 2000

$23,800 - $80,000

$80,000 - $150,000

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$200,000 - $268,600


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Median Contract Rent 2000

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Data contained in the Comprehensive Housing Affordability Strategy (CHAS) tables, for the years 1990 and 2000, duplicated in Table 5.6 and Table 5.7, on pages 52 and 53, indicate that the impact of housing costs on household incomes is very severe on low- and very low-income households. Table 5.6 indicates that 79 percent of all very low-income renters (those earning between 0 percent and 30 percent of the median family income) and nearly 84 percent of very low-income homeowner households paid more than 30 percent of their income on housing expenses in Prince William County in 1990. Over 74 percent of all very low-income renters and 81 percent of very low-income homeowner households in Prince William County are in this category, in 2000. In Prince William County, over 67 percent of very low-income renters and nearly 65 percent of very low-income homeowners paid more than 50 percent of their incomes on housing expenses in 1990. In 2000, over 60 percent of very low-income renters and over 65 percent of very low-income homeowners have a cost burden greater than 50 percent. In Manassas, nearly 74 percent of very low-income renters and over 80 percent of very low-income homeowners paid more than 30 percent of their incomes on housing expenses in 2000. In Manassas Park, over 79 percent of renters and nearly 75 percent of owners were in this category. In Manassas, over 52 percent of very low-income renters and nearly 65 percent of very low-income homeowners paid more than 50 percent of their incomes on housing expenses in 2000. In Manassas Park, nearly 58 percent of renters and 62 percent of owners were in this category in 2000. Looking at the “Other Low-Income” households (those earning between 31 percent and 50 percent of the median family income) in Prince William County, nearly 73 percent of low-income renters and nearly 71 percent of low-income homeowners paid more than 30 percent on housing expenses in 1990. Also, nearly 23 percent of renters and over 41 percent of homeowners were paying more than 50 percent on housing expenses in 1990. In 2000, the category shows about 65 percent of renters and over 71 percent of homeowners with rent burdens in excess of 30 percent, with nearly 13 percent renters and nearly 33 percent of homeowners paying more than 50 percent on housing expenses. In Manassas, around 64 percent of both very low-income renters and very low-income homeowners paid more than 30 percent of their incomes on housing expenses in 2000. In Manassas Park, over 86 percent of renters and nearly 78 percent of owners were in this category. In Manassas, over six percent of very low-income renters and over 21 percent of very low-income homeowners paid more than 50 percent of their incomes on housing expenses in 2000. In Manassas Park, over nine percent of renters and over 25 percent of owners were in this category in 2000. In 1990, moderate income (those earning between 51 percent and 80 percent of the median family income) in Prince William County showed 54 percent of renters and nearly 66 percent of homeowners with rent burdens in excess of 30 percent, with over one percent renters and over 20 percent of homeowners paying more than 50 percent on housing expenses. Over 30 percent of renters and 58 percent of

51

homeowners had rent burdens in excess of 30 percent, with nearly two percent renters and over ten percent of homeowners paying more than 50 percent on housing expenses, under this category in 2000. In Manassas, around 25 percent of very low-income renters and around 42 percent of very low-income homeowners paid more than 30 percent of their incomes on housing expenses in 2000. In Manassas Park, over 33 percent of renters and over 57 percent of owners were in this category. In Manassas, less than one percent of very low-income renters and nearly nine percent of very low-income homeowners paid more than 50 percent of their incomes on housing expenses in 2000. In Manassas Park, over 11 percent of owners were in this category in 2000. According to the 2005-2007 ACS 3-Year estimates, the percentage of all owner households paying more than 30 percent of household income towards housing expenses was 38.76 percent in Prince William County and 32.98 percent in Manassas. Over 13 percent of all owner households in Prince William County and Manassas paid more than 50 percent of household income towards housing expenses. The percentage of all renter households paying more than 30 percent of household income towards housing expenses was 46.65 percent in Prince William County and 56.71 percent in Manassas. About 20 percent of all renter households in Prince William County and 30.10 percent of renter households in Manassas paid more than 50 percent of household income towards housing expenses.

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Table 5.6 Rent Burden by income and tenure, 1990

Very Low-Income (Household Income <=30% MFI)


Renters % Cost Burden

> 30%

% Cost Burden >

50% % Cost Burden >

30%

% Cost Burden >

50%

% Cost Burden >

30% % Cost

Burden > 50%

Elderly 74.4 57.2 80 62 33.3 33.3

Small Related 81.8 69 85.1 78.4 89.7 55.2

Large Related 71.9 59.7 71.4 71.4 100 100

Other 81.8 77.2 88.3 88.3 0 0

Total Renters 79 67.4 83.8 77.6 73.3 51.1

Owners

Elderly 79.2 48 56.1 29.5 79.3 62.1

Other 86.8 75.3 100 85.5 68.1 27.7

Total Owners 83.9 64.7 72.1 50 72.4 40.8

Total Households 80.9 66.4 79.1 66.3 72.9 46.4

Other Low-Income (Household Income >30 to <=50% MFI)



> 30%

% Cost Burden >

50% % Cost Burden >

30%

% Cost Burden >

50%

% Cost Burden >

30% % Cost

Burden > 50%

Elderly 69.5 29 100 56.8 N/A N/A

Small Related 68.7 20.2 88 12.4 66 5.7

Large Related 68.4 19.1 80.6 19.4 72 0

Other 87.2 30 94.4 24 100 100

Total Renters 72.7 22.6 90 19.2 68.4 8.1

Owners

Elderly 39.2 14.8 34.3 10.4 15.2 0

Other 82.9 51.5 64.9 24.1 87.5 66.7

Total Owners 70.8 41.3 56.4 20.3 58 39.5

Total Households 72 29.3 78.9 19.6 64.5 19.8

Moderate Income (Household Income >50 to <=80% MFI)



> 30%

% Cost Burden >

50% % Cost Burden >

30%

% Cost Burden >

50%

% Cost Burden >

30% % Cost

Burden > 50%

Elderly 29.1 0 64 0 0 0

Small Related 51.8 0.5 57.7 0 66.7 0

Large Related 53.2 1.2 60.7 0 21.1 0

Other 62.4 3.8 77.4 6.1 100 0

Total Renters 54 1.4 66.9 2.6 41.7 0

Owners

Elderly 20.3 5.3 11.4 11.4 0 0

Other 74.6 23.3 73.4 41.1 61.9 7.5

Total Owners 65.9 20.4 56.3 32.9 56.6 6.9


Source: 2000 CHAS tables

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Table 5.7 Rent Burden by income and tenure, 2000

Very Low-Income (Household Income <=30% MFI)



> 30%

% Cost Burden >

50% % Cost Burden >

30%

% Cost Burden >

50%

% Cost Burden >

30% % Cost

Burden > 50%

Elderly 60.3 45.8 86.1 66 50 50

Small Related 75 63.9 79.4 56.2 81.3 56.3

Large Related 83.8 58.6 39.2 5.4 N/A N/A

Other 81.7 69.6 70 60 100 100

Total Renters 74.4 60.5 73.6 52.3 79.3 57.6

Owners

Elderly 71.1 43 72 55.2 54.8 9.5

Small Related 85.1 76.5 100 86.7 92.6 92.6

Large Related 90.2 80.4 95.2 59 100 100

Other 79.5 64.1 66.7 66.7 55.9 55.9

Total Owners 81 65.5 80.5 64.8 74.7 62


Other Low-Income (Household Income >30 to <=50% MFI)



> 30%

% Cost Burden >

50% % Cost Burden >

30%

% Cost Burden >

50%

% Cost Burden >

30% % Cost

Burden > 50%

Elderly 82.1 36.6 68.2 22.7 100 0

Small Related 59.7 9.6 65.8 0 91.7 8.3

Large Related 49.6 6.5 35.8 0 63.6 0

Other 75.7 13.5 73.6 10.2 100 100

Total Renters 64.6 12.9 64.3 6.2 86.4 9.1

Owners

Elderly 43 17.2 49.4 19.1 52.8 37.7

Small Related 79.7 34.8 74.4 25.6 94.9 31.6

Large Related 78.7 38.2 35.8 9.2 81.8 0

Other 80 43.3 91.7 29.2 50 50

Total Owners 71.2 32.7 63.8 21.5 77.9 25.1


Moderate Income (Household Income >50 to <=80% MFI)



> 30%

% Cost Burden >

50% % Cost Burden >

30%

% Cost Burden >

50%

% Cost Burden >

30% % Cost

Burden > 50%

Elderly 51.9 28.8 50 0 100 0

Small Related 29 0.2 17.5 0 21.4 0

Large Related 16.2 0 7.4 0 0 0

Other 35.2 0.6 35 1.1 83.3 0

Total Renters 30.1 1.7 24.6 0.5 33.1 0

Owners

Elderly 36.3 5.5 44.9 24.5 28.6 0

Small Related 62.8 11.6 51.5 5.5 62.5 13.6

Large Related 52.1 5 3 3 30 0

Other 67.2 16 45.9 13.8 69.2 15.4

Total Owners 58 10.3 41.8 8.6 57.2 11.2

Total Households 44.9 6.3 33.1 4.5 50.6 8.1 Source: 2000 CHAS tables

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Overall, minorities and African Americans in particular, face a number of demographic concerns that typically impact housing choice and affordability negatively. One of the most revealing indicators that minorities lag far behind Whites in obtaining housing of their choice is in the category of homeownership. According to the 2005-2007 ACS estimates, the homeownership rate among Whites was 80.16 percent, 20.22 percent higher than African Americans at 59.94 percent and 10.56 percent higher than that of Hispanics, reporting a homeownership rate of 69.60 percent. There is no public housing in Prince William County, Manassas, or Manassas Park. The Prince William County Office of Housing and Community Development (OHCD) administers the Federal rental subsidy program, also known as the Section 8 Housing Choice Voucher Program. Participants of the program receive assistance to rent privately owned housing units that are located in apartment complexes, condominiums, townhouses, or single-family homes. The OHCD currently administers over 1,900 Housing Choice Vouchers. The County Housing Choice Voucher Program waiting list is currently not open. As of 11/2/09 there were 385 households on the County Waiting List for assistance. Manassas City Department of Family Services administers the Housing Choice Voucher program for Manassas City and Manassas Park through an administrative agreement with the Virginia Housing Development Authority (VHDA). Currently they are serving over 200 households with over 400 households on their Waiting List.

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Section 2: Fair Housing Law, Municipal Policies, and Complaint Analysis Overview This section examines current polices and laws that affect fair housing choice. This analysis entails a review of state and local laws, regulations, administrative policies, procedures, and practices and assesses whether any of these impede the location, availability, affordability, and accessibility of housing. Introduction Impediments to fair housing choice may be acts that violate a law or acts or conditions that do not violate a law, but preclude people with varying incomes from having equal access to decent, safe, and affordable housing. Fair housing choice is defined, in part, as the ability of people with similar incomes to have similar access to housing. The first part of this section will address the existing statutory and case law that works to remove impediments and promote fair housing choice. The federal fair housing law can be effective in mitigating barriers to fair housing choice, depending upon enforcement efforts. Related laws and case law that provide further interpretation, understanding, and support to the Fair Housing Act will also be discussed. The Virginia Fair Housing Act was reviewed and compared to the federal fair housing law to determine whether it offered similar rights, remedies, and enforcement to the federal law and might be construed as being substantially equivalent. Pertinent related laws, such as the Community Reinvestment Act and Home Mortgage Disclosure Act, were analyzed to determine their effectiveness in facilitating fair lending. Various judicial case decisions pertaining to fair housing issues were reviewed and were incorporated into the analysis with relevant issues and decisions discussion below. On Jan. 15, 1993, the Prince William County Board of Supervisors enacted the Human Rights Ordinance establishing the Human Rights Commission. The Human Rights Ordinance prohibits discriminatory practices based on race, color, sex, national origin, religion, marital status or disability, in employment, housing, public accommodations, education and credit, in Prince William County. The second section discusses the level of enforcement activity in Prince William County. All investigations of fair housing complaints in the Prince William County jurisdiction are conducted through the Prince William County Human Rights Commission. The Commission accepts and investigates complaints and provides fair housing literature and training to both the public and private sectors. The more difficult, but intertwined, aspect of fair housing choice is the availability of affordable housing. Adequate, decent, safe, and affordable housing for people of varying incomes should be available. Minimizing housing costs for very low- and low-income households usually requires some form of subsidy that is,

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oftentimes, generated utilizing federal, state, and/or local government dollars. Prince William County operates HUD funded entitlement grant programs designed to rehabilitate and produce affordable housing, and to provide rental and homebuyer assistance. These efforts are detailed in the third section. Regulatory and public polices are reviewed in the fourth section. Numerous documents were collected and analyzed to complete these sections. The key documents were the Consolidated Plan, prepared by Prince William County Office of Housing and Community Development, the community profile section of this impediment analysis, City and County zoning ordinances, and documentation on various housing programs and projects, including new initiatives offered by the City’s of Manassas and Manassas Park, and Prince William County Office of Housing and Community Development. An analysis of fair housing complaints is covered in the fifth section. The Fair Housing Act, as amended in 1988, makes it unlawful to discriminate on the basis of race, color, religion, national origin, disability or familial status. Therefore, complaints can be filed under any of these bases. The last section contains conclusions about fair housing barriers based on the existing law, enforcement efforts, complaint analysis, and availability of affordable housing. 2.1. Fair Housing Law The Federal Fair Housing Act (the Act) was enacted in 1968, and amended in 1974 and 1988 to add protected classes, provide additional remedies, and strengthen enforcement. The Act, as amended, makes it unlawful for a person to discriminate on the basis of race, color, sex, religion, national origin, handicap, or familial status. Generally, the Act prohibits discrimination based on one of the previously mentioned protected classes in all residential housing, residential sales, advertising, and residential lending and insurance related transactions. Prohibited activities under the Act, as well as examples, are listed below. It is illegal to do the following based on a person's membership in a protected class: Misrepresent that a house or apartment is unavailable by:

Providing false or misleading information about a housing opportunity, Discouraging a protected class member from applying for a rental unit or

making an offer of sale, or Discouraging or refusing to allow a protected class member to inspect

available units; Refuse to rent or sell or to negotiate for the rental or sale of a house or

apartment or otherwise make unavailable by:

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Failing to effectively communicate or process an offer for the sale or rental of a home,

Utilizing all non-minority persons to represent a tenant association in reviewing applications from protected class members, or

Advising prospective renters or buyers that they would not meld with the existing residents;

Discriminate in the terms, conditions, or facilities for the rental or sale of housing by:

Using different provisions in leases or contracts for sale, Imposing slower or inferior quality maintenance and repair services, Requiring a security deposit (or higher security deposit) of protected class

members, but not for non-class members, Assigning persons to a specific floor or section of a building, development,

or neighborhood, or Evicting minorities, but not Whites, for late payments or poor credit;

Make, print, publish, or post (direct or implied) statements or advertisements that housing is not available to members of a protected class;

Persuade or attempt to persuade people, for profit, to rent or sell their housing due to minority groups moving into the neighborhood by: Real estate agents mailing notices to homeowners in changing area with a

listing of the homes recently sold along with a picture of a Black real estate agent as the successful seller, or

Mailed or telephonic notices that the "neighborhood is changing" and now is a good time to sell, or noting the effect of the changing demographics on property values;

Deny or make different loan terms for residential loans due to membership in a protected class by: Using different procedures or criteria to evaluate credit worthiness, Purchasing or pooling loans so that loans in minority areas are excluded, Implementing a policy that has the effect of excluding a minority area, or Applying different procedures (negative impact) for foreclosures on

protected class members; Deny persons the use of real estate services; Intimidate, coerce or interfere; or Retaliate against a person for filing a fair housing complaint. In addition to prohibiting certain discriminatory practices, the Act places no limit on the amount of recovery and imposes substantial fines. The fine for the first offense can be up to $10,000; the second offense, up to $25,000; and the third offense, up to $50,000. The Virginia Fair Housing Act includes a similar list of unfair housing practices, unfair housing practices by financial institutions, prohibition on blockbusting, retaliation, coercion, interference, or obstruction.

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Prince William County has not enacted a fair housing ordinance but enacted a local Human Rights Ordinance in 1993. The County’s Human Rights Commission was designated to receive complaints and investigate to determine their validity under the County Human Rights Ordinance and Federal Fair Housing Act. The Commission makes referrals to HUD as appropriate. Fair Housing Act and Advertising It is unlawful to make, print, publish, or post (direct or implied) statements or advertisements that housing is not available to members of a protected class. According to the Federal Act, advertisement under this section refers not only to published ads in newspapers, but also to any other statements that are written, verbal, or non-verbal. Discriminatory advertisements include, but are not limited to, applications, brochures, signs, banners, photographs, symbols, human models, and spoken words and phrases which convey the message that dwellings are available or are not available to a particular protected class. Generally, ads should not contain words that express a preference based on a protected class. There are a few exemptions, such as housing for older persons, private clubs, shared-living housing, and religious organizations. A general rule of thumb on terms to use when advertising the sale or rental of a dwelling is to describe the property, not the person. Catchwords, such as “exclusive”, “private” or “integrated” may convey a preference for one group over another and send signals about a community’s makeup. The Fair Housing Act does not require the use of the Equal Opportunity logo or slogan in any ad. However, using the logo is good solid evidence of the company’s commitment to fair housing compliance. Regulations do require the display of the HUD fair housing poster at any brokerage office and at dwellings under construction. A review of local advertisements in real estate publications was conducted for March and April 2009. Publications included the Washington D.C, Maryland and Virginia Apartment Guide, March and April 2009; The Ryan Homes New Homes Guide, March/April 2009; The Washington Post Apartment Showcase, April – June 2009; and Homes & Land, Volume 9 – Issue 7, March and April 2009; It should be noted that these publications generally cover a larger area than Prince William County. There were no major concerns revealed. Many of the advertisers advertise with the equal housing opportunity logo or slogan, even when it was not required by the Act. Including the logo helps educate the home seeking public that the property is available to all persons. A failure to display the symbol or slogan may become evidence of discrimination if a complaint is filed. The 1972 amendment to the federal Fair Housing Act of 1968 instituted the use of an equal housing opportunity poster. This poster, which can be obtained from HUD, features the equal housing opportunity slogan, an equal housing statement, and the equal housing opportunity logo. When HUD investigates a broker for discriminatory practices, it considers failure to display the poster as evidence of discrimination.

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In a landmark ruling in United States v. Hunter, 459 F.2d 205 (4th Cir.), the Court of Appeals ruled that the Fair Housing Act applies to newspapers and other media that publish discriminatory advertisements even though another person placed the advertisement. That case, decided in 1972, involved a classified advertisement seeking a tenant for an apartment in a “white home”. The United States Government brought the case against the newspaper seeking injunctive relief to prohibit the newspaper from publishing discriminatory real estate advertisements. The Court also ruled that section 3604(c) of the Fair Housing Act, the provision stating that discriminatory real estate advertising is prohibited, is not a violation of the First Amendment and it further ruled that the basis for determining whether an ad violates section 3604(c) is determined by how an “ordinary” reader would interpret the ad. FHAP / FHIP Explanation The U. S. Department of Housing and Urban Development (HUD) provides funding to state and local governmental agencies to enforce local fair housing laws that are substantially equivalent to the Fair Housing Act. Once a state and/or city have a substantially equivalent fair housing law, they can attempt to become certified as a Fair Housing Assistance Program (FHAP) Agency and receive funds for investigating and conciliating fair housing complaints, or they can become a Fair Housing Initiatives Program (FHIP) Agency and receive funds for education, promoting fair housing, and investigating allegations. It should be noted that a jurisdiction must be located in a state with a fair housing law that has been determined by HUD to be substantially equivalent. The jurisdiction must then adopt a local ordinance that HUD concludes is substantially equivalent in order to participate in the FHAP Program. The local law must contain the seven protected classes - race, color, national origin, sex, religion, handicap, and familial status - and must have substantially equivalent violations, remedies, investigative processes, and enforcement powers. In addition, the process for investigating and conciliating complaints must mirror HUD’s. HUD’s enforcement process begins when an aggrieved person files a complaint within one year of the date of the alleged discriminatory housing or lending practice. The complaint must be submitted to HUD in writing. This process can be initiated by a phone call. HUD will complete a complaint form, also known as a 903, and mail it to the complainant to sign. The complaint must contain the name and address of the complainant and respondent, address and description of the housing involved, and a concise statement of the facts, including the date of the occurrence and the complainant’s affirmed signature. Upon filing, HUD is obligated to investigate, attempt conciliation, and resolve the case within 100 days. Resolution can be a dismissal, withdrawal, settlement or conciliation, or no determination as to cause. The FHAP certification process includes a two-year interim period when HUD closely monitors the intake and investigative process of the governmental entity

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or non-profit applying for substantial equivalency certification. Also, the local law must provide enforcement for aggrieved citizens where cause is found. It can be through an administrative hearing process or filing suit on behalf of the aggrieved complainant in court. The FHIP certification process is contingent on the type of funding for which the agency is applying. There are four programs to which an agency can apply; Fair Housing Organizations Initiative (FHOI), Private Enforcement Initiative (PEI), Education Outreach Initiative (EOI), and Administrative Enforcement Initiative (AEI). Fair Housing Court Case Legal actions and judicial decisions have served to augment, further define or promote fair housing choice. Our analysis focused on recent judicial cases, key ruling and legal precedence established by court cases and decisions that have developed in fair housing, as well as other laws that have been utilized to enhance fair housing efforts. Since the inception of the Act, insurance companies maintained that they were not covered by the Act. However, in 1992 a Wisconsin Appeals Court determined that the Act “applies to discriminatory denials of insurance and discriminatory pricing that effectively preclude ownership of housing because of the race of an applicant.” The case was a class action lawsuit brought by eight African-American property owners, the NAACP, and the American Civil Liberties Union against the American Family Insurance Company. The plaintiffs claimed they were either denied insurance, underinsured, or their claims were more closely scrutinized than Whites. American Family’s contention was that the Act was never intended to prohibit insurance redlining. The appeals Court stated, “Lenders require their borrowers to secure property insurance. No insurance, no loan; no loan, no house; lack of insurance thus makes housing unavailable.” A 1998 court verdict against Nationwide Insurance further reinforced previous court action with a $100 million judgment for illegally discriminating against blacks. A real estate sales related case was settled for $250,000 in Maryland when Baltimore Neighbors, Inc., a non-profit organization, alleged that real estate agents were steering. Fine Homes’ real estate agents were accused of steering prospective African-American buyers away from predominantly White neighborhoods, and Whites were almost never shown homes in predominantly African-American zip codes. A 1999 joint statement from the Department of Justice and HUD details changing attitudes concerning group homes for disabled and mentally ill persons situated in residential neighborhoods. The statement indicates that group homes should be treated no different than non-related individuals sharing a home. If a jurisdiction has zoning rules limiting the number of non-related individuals living in a home in a residential area, similar limits may be imposed on group homes for

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the disabled or mentally ill. If no such zoning rules exist limiting non-related individuals, none may be set for group homes. This statement does not include half-way homes for ex-convicts, drug users, or persons who have been convicted of the manufacture or sale of illegal drugs. In City of Edmonds v. Oxford House, the United States Supreme Court ruled that the Fair Housing Amendments Act of 1988 prevents communities from excluding group homes for the handicapped from single-family residential zones. Oxford House is a nonprofit umbrella organization with hundreds of privately operated group homes throughout the country that house recovering alcoholics and drug addicts. Recovering alcoholics and drug addicts, in the absence of current drug use or alcohol consumption, are included under the protected class of handicapped in the Fair Housing Act as amended in 1988. In Oxford House v. Township of Cherry Hill, 799 F. Supp. 450 (D. N.J. 1991), the federal court rejected a state court ruling that said recovering alcoholic and drug addicted residents in a group home do not constitute a single-family under the Township’s zoning ordinance. In Oxford House-Evergreen v. City of Plainfield, 769 F. Supp. 1329 (D. N.J. 1991) the court ruled that the City’s conduct, first announcing that the Oxford House was a permitted use only to deny it as a permitted use after neighborhood opposition, was intentionally discriminatory.

The U.S. Supreme Court in the Olmstead case determined “Unjustified institutionalization of persons with mental disabilities...qualifies as discrimination"- as stated in its majority opinion of the U.S. Supreme Court. In a landmark decision by a 6-3 vote, the Court ruled in June 1999, that a state may not discriminate against psychiatric patients by keeping them in hospitals instead of community homes. The Court said that the Americans with Disabilities Act (ADA) may require that states provide treatment in community-based programs rather than in a segregated setting. This Court further ruled that community placement is a must when deemed appropriate by state professionals, agreed to by the individual with the disability, and resources available are sufficient. The Court also agreed with “the most integrated setting” provision of the ADA.

In 2003, a settlement was ordered by the District Court in New Jersey for the owner of the internet website www.sublet.com, who was found guilty of publishing discriminatory rental advertisements which is prohibited by the Fair Housing Act. It was the first of its kind to be brought by the Justice Department. It was thought to be imperative that the federal laws that prohibit discriminatory advertising should be enforced with the same vigor with regard to internet advertising as it would for print and broadcast media. The court ordered the site to establish a $10,000 victim fund to compensate individuals injured by the discrimination. They were also ordered to pay a civil penalty of $5,000, adopt a non-discrimination policy to be published on the website, and require all employees to undergo training on the new practices.

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In February 2005, a federal court jury in Detroit sided with a 55-year-old disabled registered nurse in a decision that could solidify the right of mentally ill people to obtain exceptions to no-pet policies in apartment, condominium, and cooperative housing complexes. The verdict, which awarded $14,209 in actual damages and $300,000 in punitive damages to the nurse, is believed to be the first federal jury verdict to recognize mental illness as a disability under the federal Act.

Under the Fair Housing Act, apartment complexes and condominiums with four or more units and no elevator, built for first occupancy after March 13, 1991, must include accessible common and public use areas in all ground-floor units. An apartment complex near Rochester, New York was ordered to pay $300,000 to persons with disabilities for not making its housing facility fully accessible, with $75,000 set aside for the plaintiffs. They were required to publish a public notice of the settlement fund for possible victims and pay a $3,000 civil penalty. In 2005, the Connecticut Commission on Human Rights and Opportunities (CHRO) issued a charge of discrimination on the basis of disability when an apartment manager refused to rent a person with disabilities a unit in the first floor due to the absence of access ramp or make a modification to add a ramp. The court recognized that the renter has a disability and the defendant knew the fact and refused to make accommodations. The court concluded that the renter was entitled to compensatory and emotional distress damages of $10,000 and imposed a civil penalty of $1,000. In 2007, the 9th Circuit Court of Appeals rendered a decision in support of the Fair Housing Council of San Fernando Valley stating that Roommates.com had violated the fair housing laws by matching roommates by gender, sexual orientation, and parenthood. By asking prospective roommates to put in their status relative to these criteria for the purpose of allowing prospective roommates to judge them on that basis is a violation of Fair Housing Act. In 2005, the National Association for the Advancement of Colored People (NAACP), The National Association of Home Builders (NAHB), and the Home Builders Association (HBA) of Greater Austin, filed a federal lawsuit against the City of Kyle, TX. The plaintiffs contended that ordinances passed by the Kyle City Council, imposing requirements such as all-masonry construction, expanded home size, and expanded garage size, drive up the cost of starter homes by over $38,000 per new unit. The allegation is that this increase has a disproportionate impact on minorities and this effect violates the Fair Housing Act. The City of Kyle filed a motion to dismiss, asserting that both NAACP and NAHB lack standing. The federal district court recognized the plaintiff’s standing in 2006. Thereafter, the cities of Manor, Round Rock, Pflugerville, and Jonestown, all moved to join the litigation on the grounds that they each have ordinances similar to the one being challenged in Kyle and that any positive decision in this case would allow NAHB and NAACP to sue them at some later date. In May the court decided that the cities could participate as friends of the court but may not

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join in the litigation otherwise. This case is in progress and a judgment is expected in 2009. Fair Lending Laws Unfair lending is difficult to detect and to prove. However, there are laws, other than the fair housing law, to assist communities in aggressively scrutinizing fair lending activity. One such law is the Home Mortgage Disclosure Act (HMDA), which requires banks to publish a record of their lending activities annually. Frequently, fair housing enforcement agencies and nonprofits use these data to help substantiate a discrimination claim or to determine a bank's racial diversification in lending. Another law frequently utilized by community organizations is the Community Reinvestment Act (CRA). When a bank wants to merge with or buy another bank or establish a new branch, the community has an opportunity to comment. Usually, the CRA commitments made by the bank are analyzed, utilizing other data such as HMDA, to determine adherence. The community can challenge the action if the bank has a poor record. Sometimes compromise agreements have been reached based on the bank promising a certain level of commitment to the community. Additionally, the Equal Credit Opportunity Act (ECOA) prohibits discrimination in lending generally and can be significant when it comes to securing information about unfair lending practices and imposing remedies, which may include up to one percent of the gross assets of the lending institution. The Fair Housing Act and Homelessness

Homelessness is defined as lacking a fixed, regular, and adequate night-time residence; or the primary night-time residence is:

A supervised publicly or privately operated shelter designed to provide temporary living accommodations;

An institution that provides temporary residence for individuals intended to be institutionalized; or,

A public or private place not designed for, or ordinarily used as, a regular sleeping accommodation for human beings.

The Fair Housing Act’s definition of “dwelling” does not include overnight or temporary residence so mistreatment of the homeless is not specifically covered by the Fair Housing Law, although the inability of persons to find affordable housing, which may lead to homelessness, is a protected right of Fair Housing.

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Testing Rights It has long been settled that fair housing testing is legal and that non-profit enforcement agencies have standing to sue when certain criteria are met. These decisions make it feasible for non-profits to engage in fair housing enforcement activities. 2.2. Enforcement Prince William County’s Human Rights Commission / Fair Housing Officer (FHO) receive phone calls and complaints on fair housing issues and investigate to determine if the complaint is valid under the law. Both HUD and the Human Rights Commission in Prince William County have the right to conduct investigations of fair housing complaints in the county. The Human Rights Commission also distributes fair housing educational materials and literature to the general public and local businesses. Virginia is part of HUD’s Region 3 Office, located in Philadelphia, Pennsylvania. When HUD Regional Office investigates complaints of discrimination, an investigator generally dedicates time for on-site investigation, interviewing the complainant, respondents, and witnesses, reviewing records and documentation, while observing the environment. A detailed discussion of the complaints filled with HUD follows in Section 2.4. Education and Outreach An essential ingredient of fair housing opportunity and enforcement is education of the public regarding the rights and responsibilities afforded by the fair housing law. This includes the education of housing and financial providers, as well as citizens, the potential victims of discrimination. It is important for potential victims of housing and/or lending discrimination to be aware of fair housing issues generally, know what may constitute a violation, and what they can do in the event they believe they may have been discriminated against. Likewise, it is important for lenders, housing providers, and their agents to know their responsibilities and when they may be violating fair housing law. Often, people may be unaware of their fair housing rights. Present day housing discrimination tends to be more subtle. Instead of saying that no children are allowed, landlords may impose unreasonable occupancy standards that have the effect of excluding families with children. Rather than saying, “We do not rent to Hispanics,” they may say, “Sorry we do not have any vacancies right now, try again in a few months,” when, in fact, they do have one or more vacancies. Printed advertisements do not have to state, “no families with children or minorities allowed” to be discriminatory. A series of ads run over an extended period of time that always or consistently exclude children or minorities may very well be discriminatory. In addition, a person who believes he/she may have been discriminated against will probably do nothing if he/she does not realize that a simple telephone call can initiate intervention and a resolution on his/her behalf,

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without the expenditure of funds or excessive time. Thus, knowledge of available fair housing rights, enforcement resources and assistance is a critical component. 2.3. Production and Availability of Affordable Units An overview of the key characteristics affecting the housing environment in Prince William County will assist in assessing the adequacy and effectiveness of the housing programs designed and implemented by the County in reaching the target market and identifying and serving those who have the greatest need. Much of the information is taken from the 2005-2009 Consolidated Plan, the 2007 and 2008 Consolidated Annual Performance and Evaluation Report (CAPER), the 2007 and 2008 Annual Action Plan, and other documentation provided by Prince William County. According to the Annual Action Plan for 2010, Prince William County anticipated a budget of $4,926,400 including $2,819,210 in Entitlement Allocations, and $2,107,190 in program income from Community Development Block Grant (CDBG), HOME Investment Partnership (HOME), and Emergency Shelter Grant (ESG) funding. In addition, Prince William County anticipated supplemental funding as follows: Supplemental Allocations of Funds Neighborhood Stabilization Program $4,134,612 Contract authorization signed March 2009 Contract authorization signed March 2009 Homeless Prevention and Rapid Re-Housing Program $ 789,775 Authorized for FY 2009/expenditures FY2010 Contract Agreement signed July 21, 2009 American Recovery and Reinvestment Act of 2009 (CDBG R) $ 516,528 (CDBG R) Contract agreement signed August 13, 2009 These programs are operated efficiently and appear to be achieving the program objectives of the previous 2006 – 2010 Consolidated Plan. 2.4. Regulatory and Public Policy Review The County zoning ordinance and public policies were examined to reveal any current ordinances or policies that impede fair housing. Prince William County’s zoning ordinance and public policies do not appear to be an impediment to fair housing choice. Other concerns relative to a City of Manassas ordinance designed to address overcrowding have been resolved. The ordinance was

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repealed after concerns that it might be illegally targeting Hispanic families by banning extended family members from living together by narrowing the legal definition of "family," The resolution included an agreement that the City of Manassas now monitors the impacts of its ordinances on fair housing. 2.5. Analysis of Fair Housing Complaints Fair housing complaint information was received from the regional office of the U.S. Department of Housing and Urban Development in Philadelphia. The data provides a breakdown of complaints filed for Prince William County from January 1, 2002 through December 31, 2008. Thirty three cases were filed according to one or more of seven bases, including; National Origin, Color, Religion, Familial Status, Handicap, Sex, and Race. Table 2.2, below, shows a total of 35 complaints because some of the 33 cases cited multiple bases in their claim. Table 2.2: Number of Complaints by Protected Class by Year (2002-2008) Source: HUD Philadelphia Regional Office

Of the 33 cases, all were closed with a satisfactory resolution. Four cases were closed with conciliation where probable cause was found prior to being conciliated. Twenty seven cases were closed with a no cause determination. This means that justification for the complaint was not applicable to the Fair Housing Law. Two cases were closed due to the lack of cooperation from the complainant. Table 2.3, on the following page, provides the details for case closure by types and by year the case was opened.

Protected Class

Race/ Color

National Origin

Familial Status

Disability Sex Religion Totals

2002 4 1 5

2003 2 2

2004 4 1 5

2005 6 1 2 9

2006 1 3 1 1 6

2007 3 1 1 5

2008 2 1 3

Totals 30 6 1 17 5 2 35

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Table 2.3: Number of Complaints by Protected Class by Year (2002-2008)

Source: HUD Philadelphia Regional Office

2.6. Conclusions and Implications for Fair Housing Barriers The State of Virginia has enacted a fair housing law that is substantially equivalent to the federal Fair Housing Act. Prince William County has not enacted a fair housing ordinance. However, in 1993, the County enacted a Human Rights Ordinance and authorized the Human Rights Commission to receive and investigate complaints and to determine their validity under the County Human Rights Ordinance and Federal Fair Housing Act. The Commission makes referrals to HUD as appropriate. Fair housing complaint information was received from the regional office of the U.S. Department of Housing and Urban Development in Philadelphia. The data provides a breakdown of complaints filed for Prince William County from January 1, 2002 through December 31, 2008. Thirty three cases were filed according to one or more of seven bases, including; National Origin, Color, Religion, Familial Status, Handicap, Sex, and Race. According to the 2008 CAPER, Prince William County anticipated a budget of $4,926,400 including $2,819,210 in Entitlement Allocations, and $2,107,190 in program income from Community Development Block Grant (CDBG), HOME Investment Partnership (HOME), Emergency Shelter Grant (ESG), and American Dream Down-payment funding. In addition, Prince William County anticipates supplemental funding of $5,440,915 from Neighborhood Stabilization Program, Homeless Prevention and Rapid Re-Housing Program and American Recovery and Reinvestment Act of 2009 (CDBG R). All of these programs are operated

Type of Closure 2002 2003 2004 2005 2006 2007 2008 Totals

Case Conciliated 1 1 1 1 4

No Probable Cause 3 1 5 7 4 4 3 27

Withdrawn

Lack of Jurisdiction

Complainant failed to cooperate

1 1 2

Unable to locate

Untimely Filed

Totals

5 2 5 8 5 5 3 33

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efficiently and the funds appear to be achieving the program objectives of the previous Consolidated Plan. The County’s zoning ordinance and public policies were examined and did not reveal any current ordinances or policies that violate fair housing. An examination of local advertisements in real estate publications from September through November 2008 revealed no violation of fair housing law.

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Section 3: Focus Group Sessions and Community Engagement

Introduction

This section will report on the results from the three focus group sessions held during the months of March and April 2009. Participants in the focus groups included City of Manassas, City of Manassas Park and Prince William County staff representatives and elected officials; representatives from non-profit organizations, legal services, housing professionals, real estate, financial and insurance industry representatives; and the general public and other community representatives. Also participating were representatives from the Prince William County Housing Board and the Prince William County Human Rights Commission. Attendees were gathered by invitations sent to select resident and community leaders, organizations, industry professionals and public officials. At each focus group session, general issues related to the housing market and specific concerns pertaining to fair housing choice in Prince William County were discussed. Supplemental interviews were conducted with individuals from the various communities and industry representatives to obtain information from those unable to attend the sessions. All of our sessions were hosted by the Prince William County Office of Housing and Community Development in conjunctions with the local jurisdictions of Manassas and Manassas Park. The focus group session locations were selected based on a desire to reach as many participants as possible with locations including the Dr. A. J. Ferlazzo Building Auditorium on March 31st, 15941 Donald Curtis Drive, Woodbridge, Virginia; and the Manassas City Hall Council Chambers on April 2nd, 9027 Center Street, Manassas, Virginia. These meetings were advertised in local newspapers. It should be noted that the comments summarized in this section represent the comments and views of the focus group participants. J-Quad has made every effort to document all comments as a matter of record, and to ensure that the comments, as presented on the following pages, have not been altered to reflect our analysis, investigation or substantiation of information obtained during these sessions. Focus Group Comments and information obtained during interviews were later analyzed and to the extent substantiated or collaborated by the data and analysis, included in Section Six, Impediments and Remedial Actions. Comments from participants included the following.

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3.1. Focus Group Concerns and Comments Public Policy and Public Awareness of Fair Housing Participants cited a lack of public awareness of fair housing rights as a concern. They felt that many residents are simply unaware of their rights and that the number of violations reported and cases substantiated may be much lower than the number of violations actually occurring. Others felt that residents often fear retaliation by those who violated the laws. For example, attendees felt that in some instances, people do not register complaints for fear of retaliation by their landlords, or if they report code enforcement violations, enforcement will result in higher rents or evictions. Participants also felt that residents needed increased access to homebuyer education and counseling when considering purchase of a home and rental housing and tenant’s rights counseling and advocacy for renters. They were concerned that first-time home buyers often do not know where to go for help or how to start the process of purchasing a home. Anecdotal accounts by attendees included obstacles faced by renters such as denial of rental applications based on having no prior address, prior addresses limited to shelters, and frequent gaps in their rental histories; and condominium and homeowner association agreements that restrict owners/organizations from renting the units they own or having selective enforcement of their regulations disproportionately affecting protected class member and minorities. For some rental applicants, participants cited their having received denials of their applications based on the aforementioned rental histories although they demonstrated consistent income over that same period of rental history. Social-Economic Conditions Among the social-economic issues frequently mentioned in the focus group sessions was the perception that the supply of affordable housing is inadequate and the cost to purchase homes or to rent housing continues to soar beyond the range affordable to many local area residents. Others believed that poverty was on the rise, severely impacting housing choice for the lowest income households. Participants indicated that poverty is not only a concern with regard to social equity and the plight of renters, but poverty and limited incomes are also having an impact on the condition and quality of single family owner occupied housing in some areas. In areas where a majority of homeowners cannot afford routine maintenance and rising utility costs, poor housing conditions may quickly become the prevalent state of affairs. The decline of the local economy, lack of job opportunities and sufficient income to afford decent housing were cited as contributing factors. All of these issues were perceived to be adversely impacting fair housing choice.

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Housing Supply, Neighborhood Conditions, and Infrastructure Focus group participants wanted to have a greater emphasis placed on financial assistance to acquire housing suitable to meet the needs of the changing demographics in the county and specific problems faced by residents and the working poor relative to foreclosure. Participants also felt that housing counseling-both pre-purchase and post purchase support-was needed to help applicants qualify for financing and to remain current with mortgage payments and home maintenance needs. Funding sources should be identified to provide rental assistance to those needing assistance with rent and utilities and security deposits necessary to initiate a lease. Participants emphasized the need for increased funding for project based rental assistance due to a reduction in Section 8 Vouchers and increased demand for rental assistance. Access to Banking and Financial Institutions Predatory lending practices were identified by focus group participants as a major issue. The focus group participants’ perception is that predatory lenders are absorbing much of the market formerly controlled by FDIC insured banks and other reputable financial institutions and fast becoming lenders of choice in some low income and minority concentrated areas. In other instances, persons facing economic hardships are being preyed upon due to their inability to qualify for traditional lending and banking services. For example, predatory businesses provide individuals with loans backed by the title to their car or house at relatively high interest rates. Lenders are quick to foreclose in the event the borrower misses a payment. Attendees were concerned that a growing number of people have fallen prey to sub prime loans because they have a poor credit rating or limited to no credit history. Some attendees were currently experiencing foreclosure of their homes and others were seeking alternative lending that could be used to refinance their existing loans in an effort to avoid foreclosure. Lending, Foreclosures and the Mortgage Industry The inability to obtain home mortgages was seen as a major barrier that limits housing choice. Criminal background histories and immigration status are relatively new factors contributing to the inability to qualify for home purchases and rental housing leases. Credit issues appeared to be the major barrier, based on focus group participants’ comments. Both a lack of qualified applicants and an adequate pool of applicants for mortgages, coupled with the inability of some housing units to qualify based on lending program guidelines were cited as barriers. Participants felt that greater emphasis should be placed on credit counseling and financial literacy being accessible to a broader population including youth and young adults age eighteen to thirty. Greater emphasis should be given to preventing damage to one’s credit history and providing a solid foundation that could prevent future financial problems. Persons with a criminal felony record and those convicted of sex crimes are having particular problems finding housing to rent as well as qualifying for mortgages.

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In other instances, participants were concerned with underwriting criteria used by lenders and their failure to provide financing with more favorable terms to meet the needs of lower income clients. Products that once addressed these issues as part of a financial institution’s Community Reinvestment Act initiatives are no longer available. Some banks no longer offer such products due in part to the influences of recent increases in foreclosure rates and sub prime lending on mortgage approvals and higher private mortgage insurance for small loans. Other participants cited instances in which elderly and other owners of affordable housing are no longer able to afford routine maintenance on their home. Any major systems failure such as roof replacement, foundation problems or even heating and air conditioning replacement can render their home a health and safety risk or place the homeowner in violation of local property standards codes. Special Needs Housing Participants were concerned that greater funding be provided for the elderly to age in place, and to provide housing for others in need of special needs housing. Without such funding elderly persons are sometimes placed in nursing homes prematurely, even though they could otherwise continue to live on their own with some limited assistance where they currently reside. Participants were also concerned that limited options exist for persons in need of transitional housing whether they be recently paroled, mentally ill or physically handicapped, or homeless or at risk of being homeless. Others cited a need for more permanent supportive housing. Participants felt that more public resources should also be identified and dedicated to homeless programs, shelters and supportive services to the homeless and elderly. These services tend to be concentrated in the more populated cities with limited availability in smaller and rural areas. Public Transportation and Mobility Participants cited limited mobility and public transportation as impediments to housing choice. These limitations were also a concern for the elderly and disabled persons in need of transportation to access supportive services. 3.2. Solutions Attendees indicated a need for more effective public policy to mitigate the impacts of increased incidents of discrimination or impediments to housing for persons with disabilities, renters with past criminal records or prior convictions for sexual abuse related crimes, those in need of special needs housing or facing evictions, foreclosures and homelessness. Participants wanted an increased emphasis on credit education and housing consumer counseling. Increased financial literacy courses taught in high schools was seen as solutions as well.

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The representatives of the Human Rights Commission stressed the need for additional funding for fair housing outreach, education and enforcement. While successful in raising awareness of fair housing as reflected in increased complaint filings, the commission representatives cited a need to reach more persons and the need to provide outreach to landlords, homeowner associations and other likely violators of fair housing law. Participants emphasized the need for increased project based rental assistance and the overall allocation of Section 8 Vouchers due to increased demand for rental assistance.

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Section 4: Home Mortgage Disclosure Act (HMDA) Data Analysis Introduction The Federal Financial Institutions Examination Council (FFIEC) gathers data on home mortgage activity from the federal agencies that regulate the home mortgage industry. The data contain variables that facilitate analysis of mortgage lending activity, such as race, income, census tract, loan type, and loan purpose. The FFIEC provides the HMDA databases and retrieval software on compact disk. Data can be summarized within the software package or downloaded in its raw form for analysis. For this analysis, the FFIEC databases were utilized for 1997 through 2006. The data reported here are summarized by a variety of methods. Tables 4.1, Tables 4.2 and 4.4 provide information for the Prince William Area. Tables 4.3, 4.5 and 4.6 present the data by census tract income groups. The maps, provided at the end of this section, present data according to census tracts for Prince William Area with outlines of Manassas and Manassas Park. Analysis Table 4.1 examines home loan activities in the Area. Data are presented by loan type, ethnicity, income of the census tract, and loan purpose. White applicants represent the largest number of loan applicants at 313,440. Origination rates for Whites exceed 70 percent. African-Americans were the next largest applicant group with 69,750 applications submitted and an origination rate of over 60 percent. Asian origination rates were the second highest at about 66 percent, with about 23,630 applications reported. The Hispanic origination rate was about 60 percent with 50,900 applications. High-income applicants showed both the highest number of applications, at over 271,670, and the highest origination rate, at about 72 percent. Both the number of applications and the origination rates drop significantly for all other income groups, with over 79,600 applications from middle-income applicants and about 60 percent origination rate. Conventional loans account for the largest number of applications for loan type, at over 534,200, and the lowest origination rate, over 54 percent. Refinance loans show the highest number of applications for loan purpose, at 372,100 with an origination rate about 53 percent. Home Improvement Loans show the lowest origination rate of about 43 percent with 40,750 applications. Table 4.2 displays the HMDA data for the same data categories (Loan Type, Ethnicity, Income, and Loan Purpose). On this table, however, percentages are taken within category, rather than demonstrating the percentage of applications that result in loan originations. For instance, the first percentage in the “Origin.” column indicates that 75.27 percent of originations in the Area were for conventional loans compared to 54.15 percent origination rate from Table 4.1. For comparison, ethnic percentages were included under the “Pop.” column to compare the percentage of originations by ethnic group to their percentage in the population.

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For Loan Type, “Conventional” shows the highest percentages, at over 75 percent of all originations. FHA loans, which are government insured and have more stringent lending criteria, were about 17 percent of the originations. Referring back to Table 3.1, government insured loans had a higher origination rate than conventional, at about 57 percent for government insured versus less than 55 percent for conventional. For Ethnicity, “White” shows the highest percentage of origination at about 57 percent of the total, while their presence in the population was nearly 65 percent of all residents. African-American applicants account for just over 11 percent of originations, while their presence in the population was nearly 18 percent of all residents. Asian applicants represent just over four percent of originations with nearly four percent of the total population. Hispanic applicants accounted for nearly eight percent of all originations, with over 10 percent of the total population. This is likely a reflection on the reality that African-Americans and Hispanics are more likely to fall within lower-income groups and, therefore, less likely to qualify for mortgage financing. For Income, the highest income group (>120% median) displays the highest percentage of originations, nearly 51 percent of all originations. While it stands to reason that the highest income group would have the greatest success in being approved for loans, it is somewhat troubling that a relatively small group accounts for almost 50 percent of all loans. Loan Purpose data show that refinance loans accounted for almost 51 percent of the originations. Home purchase loans were the second most frequent purpose, at about 44 percent. Home improvement loans accounted for less than five percent of all originations. Table 4.3 compares the HMDA data for Very Low-Income tracts and High-income tracts. It should be noted that there are a very low number of loan applications in Very Low-Income tracts and 2000 Census data indicates that there are no very low-income tracts in Prince William County. This indicates that higher income groups are occupying the tracts that were Very Low-Income tracts in 1990s, resulting in the absence of Very Low-Income tracts in the county by 2000. Table 4.4 compares origination rates between minorities and White applicants for the various loan purposes and income groups. For all loan purposes shown, White origination rates are higher than minorities. For home purchase loans, origination rates were about 66 percent for Whites and over 62 percent for minorities, a difference of 3.3 percentage points. White applicants for home improvement loans are successful nearly 15.31 percentage points more often than minorities. The rates for refinance loans show a 12.47 percentage point difference.

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Looking at the income group comparison, minorities have origination rates 1.75 to 6.98 percentage points lower than Whites. With High-Income applicants (>120% MFI), White origination rates are more than six percentage points higher than Minorities. In the Middle-Income group (96 to120% MFI), White origination rates are seven percentage points higher. Within each income group, Whites and minorities are entering the loan markets with relatively equal incomes. Tables 4.5 and 4.6 provide a detailed look at loan activity, by loan purpose, minority status, and year, for Very Low- and High-Income census tracts. In the Very Low-Income tracts, the small number of loan applications provides a somewhat inconsistent view of mortgage activity. Table 4.6 shows higher origination rates for White applicants than Minorities in all years, for all loan purposes in the high-income tracts. High numbers for the Not Provided category reflect a change in reporting methodology that includes loan purchases as an application outcome. These records tend to not report ethnicity or income of the borrowers and account for the low origination rates for the Not Provided group, where Purchased is another option, as opposed to originated or declined. Chart 4.1 provides a look at origination rates by census tract income for the loan types: conventional, FHA, and VA. As would be expected, government insured loans have higher origination rates in all income groups. Conventional origination rates closed the gap as incomes rise. The origination rates in vary low income tracts are higher due to very low number of loan applications. Chart 4.2 shows origination rates by ethnicity and income of the census tract. Whites have the highest origination rates in all income tracts except Very Low-Income tracts. Asians have the second highest origination rate in all income tracts except in very low- and moderate- income tracts. In moderate-income tracts Hispanic rates exceed the Asians. In Very Low-Income tracts, Native Americans had the highest origination rate. The higher origination rates in very low income tracts and Asian rates in some of the income categories are based on relatively low numbers of applications. Chart 4.3 looks at origination rates by the income of the applicant and the income of census tracts. As would be expected, higher income applicants have higher origination rates. The evidence of redlining can be seen in the much lower origination rates of similar income individuals in lower income tracts, where high income applicants do not have as high an approval rate as lower income applicants in higher income tracts. Chart 4.4 looks at origination rates by loan purpose and income of the census tract. The Very Low-Income tracts show high origination rates due to very low number of loan applications. Except Very Low-Income tracts, applications for home purchase loans have a higher success rate as the tract income increases,

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as do home improvement and refinance loans, peaking at almost 60 percent for the High Income tracts. Home Improvement loans have the lowest origination rates (except Very Low-Income tracts), overall, and are about 35 percent in Low- and Moderate- Income tracts. In all income categories, home purchase loans show the highest origination rates. Chart 4.5 examines the percentage of originations by ethnicity within tract income groups. In the Very Low-Income tracts, African-American applicants received over 30 percent of the originations. In all income categories, White applicants had the most originations of any ethnic group, with over 50 percent in all the income tracts except Low and Moderate-Income tracts. Chart 4.6 looks at the percentage of originations by applicant income within tract income groups. In all tracts, High-Income applicants received the most loans. Low-Income applicants in the Very Low-Income tracts had a higher percentage of the originations than the High-Income applicants. Chart 4.7 shows the percentage of originations going to the various loan purposes within tract income groups. In Very Low- and Low-Income tracts home purchase loans account for the most loan activity and refinance loans provide the second most active loan purpose. In the Moderate-, Middle-, and High-Income tracts, refinance represents the most loan activity, with home purchase loans as the second most active. In Low-Income tracts, home purchase and refinance loans showed almost the same activity. Maps 4.1 and 4.3 through 4.7 provide loan activity by census tract. The ratio of denials to originations was calculated for each loan purpose and loan type. Tracts shown in the darkest red indicate those areas where at least 100 applications are denied for every 100 applications that are originated. The medium red areas indicate those areas where between 75 and 100 applications are denied for every 100 applications originated. The mauve areas show 50 to 75 applications denied for every 100 applications originated. The pink areas show 0 to 50 applications denied for every 100 applications originated. Map 4.2 shows the total number of loan originations by census tract. Less active areas are shown in the lighter colors, with the most active areas in dark red. Unlike the other maps, the light areas are meant to indicate areas of concern, either for a lack of loan activity or for their low rate of application originations in relation to denials. A look at reasons for denial showed that the majority related to the applicants’ credit history or their debt-to-income ratio. About 26,540 (46.23%) denials were blamed on the applicants’ credit history in the five years of the study. Over 9,670 (19.34%) denials were blamed on the applicants’ debt-to-income ratio in those same years, and nearly 8,660 (18.61%) were blamed on collateral. Other possible reasons for not originating a loan included incomplete applications,

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employment history, mortgage insurance denied, unverifiable information, and insufficient cash for down-payment and/or closing costs. The housing foreclosure rates across the country continue to soar and the impacts are being felt in Prince William Area as well. Numerous web sites are providing numerical counts and locations for homes with foreclosure filings across the country and for jurisdictions in Virginia. Based on the foreclosure data provided by RealtyTrac.com, Prince William County had the second highest foreclosure rates in Virginia 1,044 foreclosures, after Fairfax County at 1,195. Map 4.9 provides Foreclosure rates in Virginia and Prince William County. One in every 128 units in Prince William County was foreclosed in April 2009. Relatively higher foreclosure rates were noted in Woodbridge at 1 in 529 units and Manassas at 1 in 243 units in April 2009. Conclusions The analysis does not provide conclusive evidence of fair housing impediments; however the data tend to suggest that characteristics of redlining may be adversely impacting loan originations in some low-income census tracts in the area. While low-income applicants tend to have lower success rates in their loan applications compared to higher income applicants, within the low-income census tracts even high-income applicants showed a poor success rate. The least success in lending was found in the home improvement loan sector. Very low origination rates were found in most areas and through most income groups. There are very low number of Very Low-Income tracts in Prince William Area with very less number of loan applications in those tracts. This reflects that higher income groups are replacing the very low-income groups in those tracts. The mortgage markets seem to have peaked in 2000 and 2001. Rising interest rates appear to be having an impact on lending activity in the county, with the number of applications slowing in recent years.

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Table 4.1

Home Mortgage Disclosure Act (HMDA) Analysis

Comparison of Number of Loan Applications and Origination Rates Prince William Area

1997 - 2006 Number Origin. Loan Type: Conventional 534,239 54.15% FHA 111,473 57.28% VA & Other 53,347 58.43% Ethnicity: Native 2,802 56.85% Asian 23,631 65.78% Black 69,750 60.36% Hispanic 50,900 59.87% White 313,440 70.32% Other 9,745 51.89% Not Provided 157,440 42.66% Unknown 71,350 2.78% Income: <51% median 21,836 45.13% 51-80% median 80,861 55.06% 81-95% median 51,616 55.12% 96-120% median 79,601 59.93% >120% median 271,671 72.08% Not Provided 193,473 29.97% Loan Purpose: Home Purchase 286,068 59.87% Home Improvement 40,750 42.69% Refinance 372,127 52.57% Multifamily Dwelling 110 51.80% Totals 699,056 54.98%

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Table 4.2

Home Mortgage Disclosure Act (HMDA) Analysis

Comparison of Originations Within Categories

Prince William Area

1997 - 2006

Origin. Percent Pop.

Loan Type:

Conventional 289,291 75.27%

FHA 63,852 16.61%

VA & Other 31,171 8.11%

Ethnicity:

Native 1,593 0.41% 0.41%

Asian 15,544 4.04% 3.73%

Black 42,101 10.95% 17.94%

Hispanic 30,474 7.93% 10.48%

White (non-Hispanic) 220,411 57.35% 64.90%

Other 5,056 1.32% 4.95%

Not Provided 67,164 17.48%

Unknown 1,984 0.52%

Income:

<51% median 9,855 2.56%

51-80% median 44,522 11.58%

81-95% median 28,451 7.40%

96-120% median 47,705 12.41%

>120% median 195,823 50.95%

Not Provided 57,990 15.09%

Loan Purpose:

Home Purchase 171,269 44.56%

Home Improvement 17,396 4.53%

Refinance 195,627 50.90%

Multifamily Dwelling 57 0.01%

Totals 384,350 100.0%

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Table 4.3

Analysis of Home Mortgage Disclosure Act Data, 1997-2006

Comparison of Very Low-Income and High-Income Census Tracts

# of Apps. % Orig. % Denied

Very Low Income Tracts

<51% median 66 33.67% 54.43%

51-80% median 116 43.81% 38.64%

81-95% median 49 47.18% 38.85%

96-120% median 46 49.43% 34.43%

>120% median 112 42.41% 27.59%

Not Provided 483 91.00% 4.57%

High Income Tracts

<51% median 2,779 46.89% 29.84%

51-80% median 10,984 56.59% 20.03%

81-95% median 9,434 65.00% 14.07%

96-120% median 18,273 66.00% 16.34%

>120% median 95,020 77.34% 11.06%

Not Provided 30,592 28.00% 6.26%

Difference Between High and Very Low Tracts

(percentage point difference)

<51% median 13.22% -24.59%

51-80% median 12.78% -18.61%

81-95% median 17.82% -24.78%

96-120% median 16.57% -18.09%

>120% median 34.93% -16.53%

Not Provided -63.00% 1.69%

Origination Rates for the Area

<51% median 45.13%

51-80% median 55.06%

81-95% median 55.12%

96-120% median 59.93%

>120% median 72.08%

Not Provided 29.97%

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Table 4.4: Analysis of Home Mortgage Disclosure Act Data

HMDA Activity for Prince William Area, 1997-2006

# Apps. % of Apps. % Denied % Orig.

Home Purchase Loans

Minorities 80,182 28.03% 7.00% 62.46%

White 136,983 47.88% 5.00% 65.71%

Not Provided 68,903 24.09% 6.23% 26.27%

Home Improvement Loans Minorities 5,768 14.15% 40.71% 38.95%

White 11,085 27.20% 25.00% 54.26%

Not Provided 23,897 58.64% 39.62% 34.89%

Refinance Loans Minorities 66,094 17.76% 12.87% 56.60%

White 161,047 43.28% 7.00% 69.07%

Not Provided 144,986 38.96% 21.54% 29.97%

Multi Family Dwelling Minorities 6 5.45% 48.00% 26.30%

White 34 30.91% 17.79% 80.29%

Not Provided 70 63.64% 13.00% 36.45%

All Loan Purposes Minorities 160,891 23.02% 10.90% 58.95%

White 313,440 44.84% 6.09% 65.90%

Not Provided 224,725 32.15% 18.89% 29.39%

Income Groups <51% MFI Minorities 7,300 33.43% 20.76% 47.25%

White 7,493 34.31% 19.00% 49.00%

Not Provided 7,043 32.25% 42.86% 25.16%

51 to 80% MFI Minorities 28,123 34.78% 13.89% 56.25%

White 34,645 42.85% 11.00% 63.23%

Not Provided 18,093 22.38% 36.25% 30.93%


White 22,154 42.92% 9.00% 59.00%

Not Provided 12,009 23.27% 31.30% 37.49%


White 38,003 47.74% 6.62% 66.03%

Not Provided 19,565 24.58% 26.86% 40.38%

>120% MFI Minorities 49,983 18.40% 11.00% 61.00%

White 156,903 57.75% 4.36% 67.70%

Not Provided 64,785 23.85% 18.76% 48.99%

Demographics % Minority % Owner Occ. % Vacant

Area wide 34.28% 68.03% 9.45%

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Table 4.5: HMDA Activity for Prince William Area -- Very Low Income Tracts, 1997 - 2006

#

Apps. % of Year % Denied % Orig.

Home Purchase Loans 1997 95 47.03% 2.11% 95.79%

Minorities 1998 3 8.11% 0.00% 100.00%

1999 1 3.03% 0.00% 100.00%

2000 5 50.00% 20.00% 60.00%

2001 11 50.00% 18.18% 45.45%

2002 3 45.00% 18.16% 44.45%

2003 4 40.00% 18.14% 43.45%

2004 3 38.23% 18.12% 53.45%

2005 2 30.00% 18.10% 41.45%

2006 1 25.00% 18.08% 40.45%

White 1997 98 48.51% 12.24% 80.61%

1998 31 83.78% 48.39% 45.16%

1999 30 90.91% 43.33% 33.33%

2000 5 71.43% 0.00% 60.00%

2001 4 40.00% 25.00% 50.00%

2002 6 27.27% 0.00% 33.33%

2003 10 66.67% 25.00% 50.00%

2004 11 71.32% 33.35% 44.44%

2005 12 84.65% 25.00% 54.54%

2006 14 57.45% 54.65% 44.44%

Not Provided 1997 9 4.46% 0.00% 100.00%

1998 3 8.11% 0.00% 66.67%

1999 2 6.06% 0.00% 0.00%

2000 2 28.57% 50.00% 0.00%

2001 1 10.00% 0.00% 100.00%

2002 5 22.73% 40.00% 20.00%

2003 2 13.33% 100.00% 0.00%

2004 3 18.68% 46.67% 60.00%

2005 4 20.35% 54.55% 46.34%

2006 4 22.01% 35.54% 33.33%

Home Improvement Loans 1997-2001 No loan activity reported.

Minorities 2002 1 100.00% 100.00% 0.00%

2003-2006 No loan activity reported.

White 1997 3 75.00% 0.00% 100.00%


Not Provided 1997 1 25.00% 0.00% 100.00%

1998 1 100.00% 0.00% 100.00%


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Table 4.5 (Cont'd): HMDA Activity for Prince William Area -- Very Low Income Tracts, 1997 - 2006

# Apps. % of Year %Denied % Orig.

Refinance Loans

Minorities 1997 4 19.05% 0.00% 100.00%


2000 1 16.67% 0.00% 100.00%


White 1997 16 76.19% 6.25% 93.75%

1998 7 70.00% 0.00% 100.00%

1999 5 55.56% 20.00% 80.00%

2000 1 16.67% 0.00% 0.00%

2001 3 50.00% 0.00% 66.67%

2002 4 40.00% 25.00% 50.00%

2003 12 61.90% 7.69% 38.46%

2004 3 62.53% 18.59% 23.50%

2005 5 68.48% 22.43% 9.39%

2006 16 74.43% 26.28% 5.00%

Not Provided 1997 1 4.76% 0.00% 100.00%

1998 3 30.00% 0.00% 66.67%

1999 4 44.44% 0.00% 25.00%

2000 4 66.67% 75.00% 0.00%

2001 3 50.00% 33.33% 0.00%

2002 6 60.00% 16.67% 33.33%

2003 5 23.81% 40.00% 20.00%

2004 7 18.41% 36.67% 37.78%

2005 8 56.00% 16.00% 30.00%

2006 9 22.00% 25.00% 20.00%

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Table 4.6: HMDA Activity for Prince William Area -- High Income Tracts, 1997 - 2006

# Apps. % of Year %Denied

% Orig.

Home Purchase Loans 1997 416 15.82% 9.86% 66.35%

Minorities 1998 434 14.76% 10.37% 67.28%

1999 542 13.49% 12.55% 64.58%

2000 822 16.11% 10.71% 60.83%

2001 1,104 17.89% 6.61% 64.67%

2002 1,394 20.98% 5.88% 66.28%

2003 1,561 23.62% 6.15% 63.23%

2004 1847 26.56% 6.42% 63.29%

2005 2,098 29.43% 10.48% 62.57%

2006 2,348 32.29% 11.74% 61.85%

White 1997 1,689 64.22% 6.04% 71.05%

1998 1,893 64.39% 3.80% 69.78%

1999 2,411 60.02% 4.06% 69.43%

2000 3,134 61.40% 5.23% 67.01%

2001 3,507 56.83% 2.99% 67.29%

2002 3,656 55.02% 2.79% 67.12%

2003 3,500 52.96% 3.57% 67.43%

2004 3,547 51.07% 3.70% 67.42%

2005 3,544 49.13% 3.99% 67.49%

2006 3,540 47.20% 4.28% 67.56%

Not Provided 1997 525 19.96% 4.19% 16.19%

1998 613 20.85% 4.40% 17.62%

1999 1,064 26.49% 2.73% 17.86%

2000 1,148 22.49% 4.70% 29.53%

2001 1,560 25.28% 4.17% 29.49%

2002 1,595 24.00% 3.51% 34.80%

2003 1,548 23.42% 3.62% 27.58%

2004 1940.2857 25.42% 3.61% 36.18%

2005 2137.75 25.98% 3.54% 39.04%

2006 2,335 26.53% 3.46% 41.90%

Home Improvement Loans 1997 55 10.28% 38.18% 45.45%

Minorities 1998 54 11.16% 31.48% 51.85%

1999 54 8.61% 31.48% 40.74%

2000 40 6.13% 32.50% 42.50%

2001 55 8.22% 29.09% 43.64%

2002 45 7.10% 40.00% 44.44%

2003 142 20.61% 38.73% 47.18%

2004 168 24.37% 45.58% 48.63%

2005 211 30.56% 50.40% 50.40%

2006 255 36.76% 55.22% 52.17%

White 1997 236 44.11% 22.88% 61.86%

1998 193 39.88% 21.76% 61.14%

1999 223 35.57% 19.73% 60.09%

2000 185 28.37% 19.46% 57.84%

2001 176 26.31% 22.73% 61.93%

2002 174 27.44% 12.07% 54.60%

2003 330 47.90% 24.24% 49.09%

2004 381 55.47% 21.19% 42.37%

2005 458 66.27% 21.95% 35.95%

2006 535 77.06% 22.70% 29.53%

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Table 4.6 (cont’d): HMDA Activity for Prince William Area -- High Income Tracts, 1997 - 2006

# Apps. % of Year %Denied % Orig.

Not Provided 1997 244 45.61% 34.84% 50.82%

1998 237 48.97% 27.85% 54.01%

1999 350 55.82% 25.43% 43.71%

2000 427 65.49% 30.44% 40.28%

2001 438 65.47% 26.03% 36.07%

2002 415 65.46% 23.86% 46.51%

2003 217 31.49% 31.34% 35.48%

2004 286 42.14% 28.99% 37.34%

2005 258 37.27% 29.52% 36.32%

2006 230 32.40% 30.04% 35.30%

Refinance Loans

Minorities 1997 180 12.09% 16.67% 59.44%

1998 392 9.85% 19.13% 61.73%

1999 305 11.11% 20.98% 49.18%

2000 164 10.11% 29.27% 40.85%

2001 754 10.72% 11.01% 65.38%

2002 1,301 12.03% 10.38% 65.10%

2003 2,652 14.19% 12.29% 58.56%

2004 3467 15.78% 12.51% 56.19%

2005 4,416 17.52% 13.15% 52.78%

2006 5,365 19.25% 13.79% 49.37%

White 1997 749 50.30% 10.81% 69.03%

1998 2,333 58.65% 6.64% 73.90%

1999 1,388 50.56% 10.30% 64.91%

2000 583 35.94% 19.90% 55.57%

2001 3,189 45.34% 4.77% 74.60%

2002 5,119 47.35% 4.10% 73.10%

2003 10,598 56.70% 4.95% 67.79%

2004 8,697 48.03% 4.75% 69.04%

2005 10,016 47.72% 3.75% 69.19%

2006 11,334 47.42% 2.74% 69.35%

Not Provided 1997 560 37.61% 21.79% 20.36%

1998 1,253 31.50% 15.72% 29.93%

1999 1,052 38.32% 16.63% 27.00%

2000 875 53.95% 35.89% 20.69%

2001 3,090 43.94% 15.44% 35.70%

2002 4,392 40.62% 13.39% 37.30%

2003 5,442 29.11% 8.69% 34.88%

2004 6,660 23.06% 5.76% 35.14%

2005 7,836 15.65% 2.38% 34.73%

2006 9,012 8.23% -0.99% 34.32%

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Chart 4.1 Origination Rates by Loan Type by Income of Census Tracts

0

10

20

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40

50

60

70

80

90

100

Very Low Low Moderate Middle High

Income Group of Tracts

Ori

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Ra

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Conventional

FHA

Va

Income Groups

Very Low <51% median

Low 51-80% median

Moderate 81-95% median

Middle 96-120% median

High >120% median

88

Chart 4.2 Origination Rates by Ethnicity by Income of Census Tract

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Ori

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Native

Asian

Black

Hispanic

White

Other

Not Provided

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Income Groups


Low 51-80% median



High >120% median

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Chart 4.3 Origination Rates by Applicant Income by Income of Census Tract

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Low 51-80% median



High >120% median

90

Chart 4.4 Origination Rates by Loan Purpose by Income of Census Tract

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Ori

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Improvement

Refinance

Income Groups


Low 51-80% median



High >120% median

91

Chart 4.5 Percentage of Originations by Ethnicity within Tract Income Groups

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Pe

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Native

Asian

Black

Hispanic

White

Other

Not Prov.

Unknown

Income Groups


Low 51-80% median



High >120% median

92

Chart 4.6 Percentage of Originations by Applicant Income within Tract Income Groups

0

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Pe

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Very Low

Low

Moderate

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Income Groups


Low 51-80% median



High >120% median

93

Chart 4.7 Percentage of Originations by Loan Purpose within Tract Income Groups

0

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Pe

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Improvement

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Low 51-80% median



High >120% median

94

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902098

900496

902196

900903

910898

902198910896

010201

910798

910897

902197

910698

910997

910598

910797 910998

902398

902298

902195

Manassas Park

Manassas

Dale City

Gainesville

Nokesville

Woodbridge

Lake Ridge

Linton Hall

Montclair

Quantico Station

Triangle

Bull Run

YorkshireSudley

Dumfries

West Gate

Haymarket

Occoquan

Quantico

Legend

Manassas City

Manassas Park City

City Limits

Census Tracts

0.000 - 0.505

0.506 - 0.755

0.756 - 1.005

1.006 - 1.388

Ratio of All Loan TypesDenials to Originations, 1997-2003

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Map 4.1: Ratio of All Loan Types, Denials to Originations, 1997-2006

95

901498

901501

901302

901100

901598

901216

901001

901298

901398

900800

900902

900100

901215

901004

901098

900700

901404

910198

901214900403

900498

901213

900500

910400

901210

910398

900300

901207

901900

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910298

901602

900200901209

900901

900405

901203

901212

901798

900497 900600

901208

901601920100

901702

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920200

902098

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900903

910898

902198910896

010201

910798

910897

902197

910698

910997

910598

910797 910998

902398

902298

902195

Manassas Park

Manassas

Dale City

Gainesville

Nokesville

Woodbridge

Lake Ridge

Linton Hall

Montclair

Quantico Station

Triangle

Bull Run

YorkshireSudley

Dumfries

West Gate

Haymarket

Occoquan

Quantico

Legend

Manassas City

Manassas Park City

City Limits

Total Number of Loan Applications

0 - 1,000

1,001 - 3,000

3,001 - 6,000

6,001 - 11,894

Total Number of Loan Applications, 1997-2003

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Map 4.2: Total Number of Loan Applications, 1997-2006

96

901498

901501

901302

901100

901598

901216

901001

901298

901398

900800

900902

900100

901215

901004

901098

900700

901404

910198

901214900403

900498

901213

900500

910400

901210

910398

900300

901207

901900

901497

910298

901602

900200901209

900901

900405

901203

901212

901798

900497 900600

901208

901601920100

901702

901211

920200

902098

900496

902196

900903

910898

902198910896

010201

910798

910897

902197

910698

910997

910598

910797 910998

902398

902298

902195

Manassas Park

Manassas

Dale City

Gainesville

Nokesville

Woodbridge

Lake Ridge

Linton Hall

Montclair

Quantico Station

Triangle

Bull Run

YorkshireSudley

Dumfries

West Gate

Haymarket

Occoquan

Quantico

Legend

Manassas City

Manassas Park City

City Limits

Census Tracts

0.000 - 0.505

0.506 - 0.755

0.756 - 1.005

1.006 - 2.000

Ratio of Conventional LoanDenials to Originations, 1997-2003

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Map 4.3: Ratio of Conventional Loan Denials to Originations, 1997-2006

97

901498

901501

901302

901100

901598

901216

901001

901298

901398

900800

900902

900100

901215

901004

901098

900700

901404

910198

901214900403

900498

901213

900500

910400

901210

910398

900300

901207

901900

901497

910298

901602

900200901209

900901

900405

901203

901212

901798

900497 900600

901208

901601920100

901702

901211

920200

902098

900496

902196

900903

910898

902198910896

010201

910798

910897

902197

910698

910997

910598

910797 910998

902398

902298

902195

Manassas Park

Manassas

Dale City

Gainesville

Nokesville

Woodbridge

Lake Ridge

Linton Hall

Montclair

Quantico Station

Triangle

Bull Run

YorkshireSudley

Dumfries

West Gate

Haymarket

Occoquan

Quantico

Legend

Manassas City

Manassas Park City

City Limits

Census Tracts

0.000 - 0.505

0.506 - 0.755

0.756 - 1.005

1.006 - 0.400

Ratio of Government Backed LoanDenials to Originations, 1997-2003

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Map 4.4: Ratio of Government Backed Loan Denials to Originations, 1997-2006

98

Map 4.5:

901498

901501

901302

901100

901598

901216

901001

901298

901398

900800

900902

900100

901215

901004

901098

900700

901404

910198

901214900403

900498

901213

900500

910400

901210

910398

900300

901207

901900

901497

910298

901602

900200901209

900901

900405

901203

901212

901798

900497 900600

901208

901601920100

901702

901211

920200

902098

900496

902196

900903

910898

902198910896

010201

910798

910897

902197

910698

910997

910598

910797 910998

902398

902298

902195

Manassas Park

Manassas

Dale City

Gainesville

Nokesville

Woodbridge

Lake Ridge

Linton Hall

Montclair

Quantico Station

Triangle

Bull Run

YorkshireSudley

Dumfries

West Gate

Haymarket

Occoquan

Quantico

Legend

Manassas City

Manassas Park City

City Limits

Census Tracts

0.000 - 0.505

0.506 - 0.755

0.756 - 1.000

Ratio of Refinance LoanDenials to Originations, 1997-2003

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Map 4.5: Ratio of Refinance Loan Denials to Originations, 1997-2006

99

901498

901501

901302

901100

901598

901216

901001

901298

901398

900800

900902

900100

901215

901004

901098

900700

901404

910198

901214900403

900498

901213

900500

910400

901210

910398

900300

901207

901900

901497

910298

901602

900200901209

900901

900405

901203

901212

901798

900497 900600

901208

901601920100

901702

901211

920200

902098

900496

902196

900903

910898

902198910896

010201

910798

910897

902197

910698

910997

910598

910797 910998

902398

902298

902195

Manassas Park

Manassas

Dale City

Gainesville

Nokesville

Woodbridge

Lake Ridge

Linton Hall

Montclair

Quantico Station

Triangle

Bull Run

YorkshireSudley

Dumfries

West Gate

Haymarket

Occoquan

Quantico

Legend

Manassas City

Manassas Park City

City Limits

Census Tracts

0.000 - 0.505

0.506 - 0.755

0.756 - 1.005

1.006 - 1.427

Ratio of Home Improvement LoanDenials to Originations, 1997-2003

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Map 4.6: Ratio of Home Improvement Loan Denials to Originations, 1997-2006

100

901498

901501

901302

901100

901598

901216

901001

901298

901398

900800

900902

900100

901215

901004

901098

900700

901404

910198

901214900403

900498

901213

900500

910400

901210

910398

900300

901207

901900

901497

910298

901602

900200901209

900901

900405

901203

901212

901798

900497 900600

901208

901601920100

901702

901211

920200

902098

900496

902196

900903

910898

902198910896

010201

910798

910897

902197

910698

910997

910598

910797 910998

902398

902298

902195

Manassas Park

Manassas

Dale City

Gainesville

Nokesville

Woodbridge

Lake Ridge

Linton Hall

Montclair

Quantico Station

Triangle

Bull Run

YorkshireSudley

Dumfries

West Gate

Haymarket

Occoquan

Quantico

Legend

Manassas City

Manassas Park City

City Limits

Census Tracts

0.000 - 0.505

0.506 - 0.755

0.756 - 1.005

1.006 - 2.262

Ratio of Home Purchase LoanDenials to Originations, 1997-2003

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Map 4.7: Ratio of Home Purchase Loan Denials to Originations, 1997-2006

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Map 4.8: Foreclosure Rate Trend – Prince William County and Virginia April 2009

Source: http://www.realtytrac.com/TrendCenter

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Section 5: Fair Housing Index Introduction The Fair Housing Index is a measure developed specifically for Analyses of Impediments to Fair Housing. The index combines the effects of several demographic variables with Home Mortgage Disclosure Act (HMDA) data and maps the results by census tract. Data for ten variables, shown in the Fair Housing Index table are standardized and added to classify the conditions in various census tracts into degree of problems that may cause impediments to fair housing choice. The map provides a general indication of geographic regions in the Prince William Area, including Manassas and Manassas Park, where residents may experience various levels of housing discrimination or have problems finding affordable, appropriate housing. The discussion is highly technical and contains statistical techniques that may not be familiar or easily understood depending on the statistical experience of the readers. Therefore, the findings presented at the end of this section are intended to provide a summary of the significant factors identified in this analysis. Methodology Data for ten variables were gathered, by census tract, for analysis. These ten variables were: percent minority, percent female-headed households with children, median housing value, median contract rent, percent of the housing stock constructed prior to 1960, median household income, percent of the population with less than a high school degree, percent of the workforce unemployed, percent of the workforce dependent upon public transportation to go to and from work, and the ratio of loan denials to loan originations for 1997 through 2006 from the Home Mortgage Disclosure Act (HMDA) report published by the Federal Financial Institutions Examination Council. With the exception of the HMDA data, all data were found in the 2000 U.S. Census of Population and Housing. Each variable contained data for every census tract in the city as defined by the 2000 U.S. Census. When the database was complete, Pearson correlation coefficients (a statistical measure that indicates the degree to which one variable changes in relation to changes in another variable and range in value from –1 to 1) were calculated to assure that all variables displayed a high relationship to each other. It is important, in this type of analysis, that the variables selected are measuring similar aspects of the population. The results of the calculations showed that all variables displayed moderate to high degrees of correlation with other variables in the model, ranging up to 0.8942. Once the relationship of the variables was established, each variable was standardized. This involves calculating a Z-score for each record by variable. For instance, for the variable percent minority, a mean and standard deviation were calculated. The mean for the variable was subtracted from data for each census tract and divided by the standard deviation. The result was a value

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representing the distance that the data point lay from the mean of the variable, reported in number of standard deviations. This process allows all variables to be reported in the same units (standard deviations from the mean) and, thus, allows for mathematical manipulations using the variables. When all variables were standardized, the data for each census tract were summed with negative or positive values given to each variable to assure that effects were being combined. For instance, in a fair housing environment, high minority concentrations raise suspicions that there may be problems relative to housing conditions and housing choices in the area based on correlations between these variables found in the census data. Therefore, the percent minority variable would be given a negative value. Conversely, in areas of high housing values, the current residents are likely not having problems with fair housing choice. High housing value, therefore, would be assigned a positive value. Each variable was considered in this light and assigned an appropriate sign, thus combining effects. This new variable, the total for each census tract, was then standardized as described for the original ten variables above. The standardized form of the total variable provides a means of identifying individual census tracts where fair housing choice is at high risk due to demographic factors most often associated with housing discrimination. With the data presented in standardized form, the results can be compared to the standard normal distribution, represented by a bell curve with a mean of 0 and a standard deviation of 1. The analysis shows Extreme Problem areas as those census tracts with standard scores below –2.00. Scores between -1.99 and -1 are designated Problem areas. Scores between -0.99 and 0 are reported as Below Average and above 0 as Above Average. The results are summarized in the following section. It should be emphasized that the data used to perform this analysis do not directly report fair housing violations. The data were utilized in order to measure potential problems based on concentrations of demographic groups who most often experience restrictions to fair housing choice. Areas identified as having extreme problems are those where there is a high concentration of minorities, female-headed households, unemployment, high school dropouts, low property values, and, most likely, are areas where a large proportion of loans (conventional home mortgages, FHA or VA home mortgages, refinance, or home improvement) have been denied. Included following the map is the correlation table (Table 5.1). MedValue is the median home value according to the 2000 census. MedRent is the median contract rent. XMinority is the percent minority. XFemHH is the percent female-headed household. XPre60 is the percent of housing built prior to 1960. MedHHI is the median household income. XLessHS is the percent of the population 25 years of age and older that has less than a high school degree. XUnemp is the unemployment rate for the population aged 16 and older considered being in the labor force. XPubTrans is the percent utilizing public

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transportation to get to and from work. AllRat is the ratio of denials to originations from the HMDA data from 1997 to 2006. Findings Looking first at the correlation table (Table 5.1), several correlations are worth noting. First, the loan origination variable, the ratio of denials to originations for all loan types, has a moderate negative correlation to household income (-0.6374). This means that in areas with lower household incomes, the loan origination rate tends to be lower. High positive correlation is noted between the denials to origination ratio and the percentage of the pre-1960 housing stock (0.7836), which indicates that lower loan originations were found in the areas with older housing stock. Second, the correlation between percentage minority and percentage female-headed households with children is significantly high and positive (0.7269), meaning that the minority community has a higher rate of female-headed households with children than the non-minority community. The percentage of minority has a moderate positive correlation with unemployment rate (0.5513), which indicates that minorities have higher unemployment rates than non-minorities. The median household income has strong negative correlation with percent minority (-0.7042) and the percentage of female headed households with children (-0.7257). Also, the median housing value has moderate negative correlation with percent minority (-0.6995) and percent female headed households with children (-0.6469). This indicates that minorities and single mothers tend to earn lower incomes and live in lower valued housing. The percentage not graduating from high school has a moderately strong, negative correlation to median household income (-0.6041). Non-high school graduates live in much lower value owner-occupied housing (-0.5004). As indicated on Map 5.1, the census tracts designated as having problems are concentrated in the eastern and southeastern census tracts of the Prince William Area, namely census tracts 9011, 9009.03, 9002, and 9006, although there is one problem area within Manassas Park, 9201. One extreme problem area is in census tract 9009.01. These areas of greatest concern contain the oldest housing stock, most likely in poor condition, with lower housing values and rents, and are primarily occupied by minority households that have higher percentages of households headed by females with children than that of other census tracts or areas. There is a higher than average unemployment rate and lower than average level of educational attainment.

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9011

9015.01

9013.02

9015.02

9014.06

9010.01

9014.05

9012.17

9012.18

9008

9012.19

9001

9013.01

9104

9009.02

9007

9012.20

9005

9103

9003

9014.049019

9010.07

9012.14

9102

9010.06

9004.03

9002

9004.06

9012.13

9012.10

9101

9010.05

9014.03

9016.02

9202

9006

9012.23

9004.05

9012.03

9009.01

9012.12

92019017.01

9012.08

9012.09

9010.08

9004.04

9012.21

9202

9016.01

9012.11

9017.02

9012.22

9009.03

Manassas Park

Manassas

Dale City

Gainesville

Nokesville

Woodbridge

Lake Ridge

Linton Hall

Montclair

Quantico Station

Triangle

Bull Run

YorkshireSudley

Dumfries

West Gate

Haymarket

Occoquan

Legend

Manassas City

Manassas Park City

City Limits

Fair Housing Index

Extreme Problems

Problems

Below Average

Above Average

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Map 5.1: Fair Housing Index

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Table 5.1 Correlation Table of Index Variables

AllRat XPubTrans XLessHS XUnemp MedHHI XPre60 MedRent MedValue XMinority XFemHH

AllRat 1.0000

XPubTrans 0.0817 1.0000

XLessHS 0.2635 0.2057 1.0000

XUnemp 0.1673 0.0384 0.4026 1.0000

MedHHI -0.6374 -0.0002 -0.6041 -0.4718 1.0000

XPre60 0.7836 0.0501 0.4078 0.1117 -0.4222 1.0000

MedRent -0.3452 -0.1891 -0.3782 -0.0309 0.2535 -0.3329 1.0000

MedValue -0.7434 -0.0044 -0.5004 -0.4035 0.8942 -0.4445 0.1607 1.0000

XMinority 0.3364 0.1382 0.3939 0.5513 -0.7042 0.0612 -0.0868 -0.6995 1.0000

XFemHH 0.2734 0.1196 0.3310 0.3885 -0.7257 0.0017 -0.1929 -0.6469 0.7269 1.0000

Variable Definition

XFemHH % Female Headed Households, 2000

XMinority % Minority, 2000

MedValue Median Home Value, 2000

MedRent Median Contract Rent, 2000

XPre60 % of Housing Built Prior to 1960, 2000

MedHHI Median Household Income, 2000

XLessHS % Less than High School Degree, 2000

XUnemp % Unemployed, 2000

XPubTrans % Taking Public Transportation to Work, 2000

AllRat Denial to Origination ratio, All Loan Types, 1997 - 2006

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Section 6: Impediments to Fair Housing and Remedial Actions Introduction This section draws on the information collected and analyzed in previous sections to provide a detailed look at fair housing impediments in Prince William County. Five major categories of impediments were analyzed: Real Estate Impediments; Public Policy Impediments; Banking, Finance, and Insurance Related Impediments; Socioeconomic Impediments; and Neighborhood Conditions as Impediments. For each of the categories, impediment were identified and presented along with a summary of the issues and impacts. Remedial actions are recommended to address each impediment. Some of the remedial actions presented in this section are conceptual frameworks for addressing the impediments. These actions will require further research, analysis, and final design by Prince William County for implementation. Evaluating fair housing concerns is a complex process involving diverse and wide-ranging considerations. The role of economics, housing patterns, and personal choice are important to consider when examining fair housing. Prince William County has relatively few impediments to fair housing. However, some issues were identified. We applaud Prince William County for it strides in supporting the creation of new affordable housing units and its commitment to fair housing outreach and enforcement. We also encourage the County and its nonprofit partners to expand these efforts in providing affordable housing as a primary means of expanding fair housing choice. The impediments identified in this section can be directly linked to and supported by data and analysis from the previous sections. In some instances, footnotes have been provided as links to the corresponding sections should the reader need to refer to those sections for more details. 6.1 Real Estate Impediments

Impediment: Supply of affordable housing.

Issues: According to data provided by Prince William County, there were an estimated 137,381 housing units in the county in June 2009. This represents an additional 39,329 units (40.1%) since April 2000. The 2009 estimates also represent a significant increase compared to the 2007 American Community survey estimate of 130,101 housing units in Prince William County. The vacancy rate in the county was 3.6 percent in June 2009. Of the total housing units in the county, 70.46 percent were owner-occupied, 23.31 percent were renter-occupied, and the remaining 6.23 percent were vacant. During the same period, Manassas had 12,824 housing units. Of the total housing units in Manassas, 63.65 percent were

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owner-occupied, 27.61 percent were renter-occupied, and the remaining 8.74 percent were vacant. According to the 2000 census, in Prince William County, 3.05 percent of all housing units were built prior to 1950, 4.64 percent were built between 1950 and 1959, 12.9 percent were built between 1960 and 1969, 22.29 percent were built between 1970 and 1979, and 57.9 percent have been built since 1979.1 This means that approximately 79 percent of the County’s housing stock is less than 40 years old, built prior to 1970, a relatively recently built housing stock likely experiencing few lead based paint issues. According to the 2005-2007 ACS 3-Year estimates, in Prince William County, 80.16 percent of White households owned their home, compared to 59.94 percent of African-American households, and 69.60 percent of Hispanic households owned their home. During this period, in Manassas, 72.07 percent of White households owned their home, compared to 65.84 percent of African-American households, and 58.25 percent of Hispanic households owned their home. According to the Metropolitan Information System (MRIS) and the data provided by Prince William County, the average sold price of a home in Prince William County in May 2009 was $238,231, which represents a 16.3 percent decline year-over-year. The total number of units sold in May 2009 in Prince William County was 753, a four percent increase year-over year. Also according to the estimates provided by the Prince William County, the median home value for single-family homes was $290,447 from January to June 2009. This is a significant decline since 2005-2007 based on ACS 3-Year estimates which reported the median home value for single-family houses in Prince William County at $421,300 and the median contract rent at $1,104 in 2007. During the same period, in Manassas, the median housing value was $377,600 and the median contract rent was $1,045. The median housing value in Manassas Park was reported to be $115,700 and the median contract rent was reported to be $741. The average income required to qualify for a mortgage based on the year 2007 median home price of $420,000 to $378,000 is approximately $105,000 to $95,000 in household income. This means that even in a 2009 depressed market where home prices are significantly lower than 2 years ago, home ownership may not be attainable to many in the County given that the 2007 median household income for White households was $95,150, for African-American households was $74,802, and Hispanic households was $65,883. In comparison, median household income for the overall county was $85,538. In 2000, approximately 73 percent of White person households,

1 Table 5.3Age of Housing Stock, Community Profile page 40

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85 percent of African American households and 84 percent of Hispanic households were earning less than $100,000 in annual income. Even if the 2009 median home value of $290,000 continues, a median income of $75,000 or more would be necessary to meet most mortgage underwriting standards. The median home price does not indicate that housing below that price and affordable housing for purchase to incomes below $95,000 to $75,000 does not exist. However, we are concerned that there is an inadequate supply of affordable housing in standard condition and available to meet the fair housing choice in home ownership for persons of all incomes in Prince William County. The Prince William County Office of Housing and Community Development, through partnerships with non-profit organizations and local builders, has supported the development and financing of affordable housing to qualified buyers to help bring some balance to this need. However, these housing initiatives serve a small percentage of the overall needs of the population of very low, low, and moderate-income families. A wide range of interconnected issues influence the development of affordable housing and housing affordability. These issues include the rapidly rising cost of land, materials, and construction; a lack of income; development fees; or the investment needed to rehabilitate substandard housing. This combination of rising costs and the lack of affordability for lower income groups, elderly and renters have made attainable housing harder to secure. This was reflected in the perceptions of focus group participants who voiced particular concern that the supply of affordable homes for working families is in short supply in certain areas where it is needed which is only adding to the overall affordable housing shortage. Impacts: Affordable housing impacts the structure and stability of neighborhoods. Income diversified neighborhoods and neighborhoods that are accessible to a mix of incomes have shown a greater potential to maintain themselves as a viable community. That is, people are most likely to maintain housing they own or when it is their housing of choice. In 2000, there was a significant gap between the percentages of minorities owning their own homes compared to Whites.2 The Home Mortgage Disclosure Act data indicates that minority buyers have lower loan origination rates than Whites and the rates are disproportionate when compared to minority percentage of Prince William County’s population. Origination rates throughout Prince William County were lower in low income census tracts when comparing groups with the same income seeking to purchase in high income tracts. This means that minority loan

2 According to the 2000 Census 76.02 percent of White households, 56.6 percent of African American households and 60.66 percent of Hispanic households owned their own home in Prince William County (Table 5.4 on page 44 of the Community Profiles.)

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applicants and lower income census tracts that often have higher concentrations of minorities are facing a lack of access to capital for home loan financing. The lack of affordable housing and investment dollars limits housing choice and, to the extent that household income is correlated with housing value, this limitation is even greater.3 High percentages of minorities fall into lower income groups.4 An analysis of household income and cost burden factors suggests that there is a strong need for affordable housing in the County. Without adequate affordable housing options lower income and minority households tend to be cost burdened with regard to their monthly mortgage (principal, interest, taxes, insurance, and utilities) or rent payments.5 Remedial Actions: Prince William County should continue to work with local developers and non-profit organizations to expand the stock of affordable housing. Attention should be given to increasing the production of new affordable housing units and assistance toward the purchase and renovation of housing in existing neighborhoods. Greater emphasis should be placed on capacity building and technical assistance initiatives aimed at expanding non-profit, faith based organizations and private developers’ production activities in the County and expanding resources for housing. In an effort to expand local resources, we also recommend that the County research and consider one particular policy change, inclusionary zoning, as one alternative means of promoting balanced housing development. Inclusionary zoning has been used in other communities to ensure that some portion of new housing development is affordable. This becomes important as higher income individuals move into a neighborhood. As housing prices rise, low to moderate-income residents may be displaced without the use of Inclusionary Zoning which helps to create mixed-income communities. Mixed-income communities broaden access to services and jobs and provide openings through which low-wage earning families can buy homes in appreciating housing markets and, as a result, accumulate wealth.

Inclusionary Zoning, also known as inclusionary housing, can be implemented by enacting provisions in the local Zoning or Development Ordinances that require a given share of new construction houses be affordable to people with low to moderate incomes. The term inclusionary zoning is derived from the fact that these ordinances seek to counter

3 Fair Housing Index Table 5.1 on page 106 shows a strong correlation between lower income groups relative to housing values and rents. 4 According to the 2000 Census, Table 2.2 page 17, 29.3 percent of White households, 43.3 percent African-American households, and 44.8 percent of Hispanic households earned less than $50,000 in 2000. 5 According to Comprehensive Affordability Strategy (CHAS) data, Table 5.7 on page 53 of the Community Profile in year 2000, 64.6 percent of low-income renter-occupied households are 30% cost burden, and 67.5 percent of low-income owner-occupied households paid more than 30% of their household income on housing expenses.

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exclusionary zoning practices which aim to exclude affordable housing from a jurisdiction through the zoning code. In practice, these policies involve placing restrictions on 10% - 30% of new houses or apartments in a given development in order to make the costs of the housing affordable to lower income households. The mix of "affordable" and "market-rate" housing in the same neighborhood is seen as beneficial by many, especially in jurisdictions where housing shortages have become acute. Inclusionary Zoning is becoming a common tool for local jurisdictions in the United States to help provide a wider range of housing options than the market provides on its own. The zoning code must be amended to include this provision and can also be applied when residential planned unit development zoning is requested. Implementation is triggered at the building permitting phase. The importance of Inclusionary Zoning is that Prince William County could increase the resources for affordable housing through private developer built units or developer dollars allocated in lieu of building units. Currently affordable housing programs are primarily funded through the County’s CDBG and HOME programs. Inclusionary Zoning could generate additional resources for affordable housing since the federal grant programs cannot address all of the County’s needs for affordable housing.

Inclusionary Zoning Ordinances vary substantially between jurisdictions. These variables can include:

Mandatory or voluntary ordinance. While many cities and counties require inclusionary housing, many more offer zoning bonuses, expedited permits, reduced fees, cash subsidies, or other incentives for developers who voluntarily build affordable housing.

A percentage of units dedicated as inclusionary housing. This varies quite substantially between jurisdictions, but appears to range between 10-30%.

Minimum size of development that the ordinance applies to. Most jurisdictions exempt smaller developments, but some require that even developments incurring only a fraction of an inclusionary housing unit pay a fee.

Whether inclusionary housing must be built on site. Some programs allow housing to be built nearby, in case of hardship.

Whether fees can be paid in lieu of building inclusionary housing. Fees-in-lieu allow a developer to "buy out" of his/her inclusionary housing obligation. This may seem to defeat the purpose of inclusionary zoning, but in some cases the cost of building one affordable unit on-site could purchase several affordable units off-site.

Income level or price defined as "affordable," and buyer qualification methods. Most ordinances seem to target inclusionary units to low- or moderate-income households, earning approximately the regional median income or somewhat below. Inclusionary housing typically does not create housing for those with very low incomes.

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Appearance and integration of inclusionary housing units. Many jurisdictions require that inclusionary housing units be indistinguishable from market-rate units, but this can increase costs.

Longevity of price restrictions attached to inclusionary housing units, and allowable appreciation. Ordinances that allow the "discount" to expire essentially grant a windfall profit to the inclusionary housing buyer, preventing that subsidy from being recycled to other needy households. Therefore, many programs restrict annual price appreciation, often tying it to inflation plus market value of home improvements, striving to balance the community's interest in long-term affordability with the homeowner's interest in accruing equity over time.

The County, in coordination with local Chamber of Commerce, should encourage major employers and lenders to design and implement Employer-Assisted Housing (EAH) programs, encouraging employers to work with employees in their efforts to purchase housing. In some instances, the County and the Chamber will have to help raise the awareness among local employers and increase their understanding that not all wage levels permit ready entry into homeownership, without some sort of subsidy. This is important in that the private sector and employment community often view the use of subsidies to help low to moderate income households achieve homeownership as a public responsibility. In reality, with limited resources, the County government can only assist a small percentage of those in need. Employer-Assisted Housing programs benefit employers, employees, and the community. Employers benefit through greater employee retention. Employees receive aid to move into home-ownership. Ultimately, communities benefit though investment in the neighborhoods where the employers and employees are located. The most common benefits provided by employers are grants, forgivable loans, deferred or repayable loans, matched savings, interest-rate buy downs, shared appreciation, and home-buyer education (provided by an employer-funded counseling agency). Successful EAH programs use a combination of some of the benefits listed above. One program that has met with success was developed by Fannie Mae, which not only has their own EAH program, but also helps employers implement EAH programs. Fannie Mae's own EAH program has made it possible for 2,200 of its employees to become homeowners. Seventy-six percent of all Fannie Mae employees own their own homes, compared with a national average of 68 percent.

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6.2 Banking, Finance, Insurance and other Industry related impediments Impediment: Impacts of the Sub-Prime Mortgage Lending Crises and increased Foreclosures.

Issues: Housing foreclosure rates across the country continue to soar and Prince William County residents have been impacted greatly. Numerous web sites are providing numerical counts and locations for homes with foreclosure filings across the country and for jurisdictions in the State of Virginia. According to realtytrac.com, a total of 6,094 units in Prince William County were identified as being in foreclosure. This included 3,896 bank-owned properties in Prince William County in August 2009. In addition to these foreclosed properties, there were another 2,198 identified as available through trustee sale. Foreclosure units represent a growing proportion of the available home on the market. With foreclosed units being sold at a discount to move them out of bank ownership, the glut of these homes on the market can have a depressing effect on market price, as seen in the recent drop in median sales price shown above. The rise in foreclosure rates may be related to both the rise in unemployment rates and the rise and fall of sub-prime lending market. According to the 2005-2007 ACS 3-Year estimates, in Prince William County, the unemployment rate for Whites was 3.25 percent, compared to African-Americans at 5.64 percent, and Hispanics at 5.09 percent. In comparison, unemployment rate for the overall county was 3.99 percent. The unemployment rate for Manassas was 4.83 percent during the three-year period. The employment data by race is not available for Manassas and Manassas Park due to the small sample size. This meant significant loss of income for a number of households since 2000. In the 2000 Census, 2.2 percent of White persons age 16 and over reported being unemployed in Prince William County, compared to 4.03 percent of African-Americans and 4.47 percent of Hispanics. Sub-prime lending was also a factor with lenders offering loans to less-creditworthy borrowers, borrowers that lack sufficient down-payments to afford the property, and risk based borrowers that speculate on the real estate market by acquiring real estate with no equity investment/down-payment in hopes that the property will appreciate in value over a short period of time. This national trend included loans generally offered at higher interest rates or through products involving adjustable interest rates and balloon payments. When the borrower cannot meet the increased mortgage payment they default and the property goes into foreclosure. Neighborhood Housing Services, NHS, and Neighbor Works America are two national housing intermediaries that have created innovated programs

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in Chicago, Baltimore, and New York City designed to reduce the impacts of foreclosures and sub-prime lending in those affordable housing markets.

Remedial Actions:

Investigate initiatives that reduce mortgage defaults and foreclosure rates among low and moderate income home buyers.

Work with National Non-Profit Housing Intermediaries, Federal Home Loan Bank (FHLB) and HUD to develop programs that reduces the mortgage default rate and foreclosure rates among low and moderate income home buyers and existing home owners. Such initiatives could include: Evaluate a loan default prevention program based on providing counseling to affected borrowers, assistance with identifying alternative products that helps borrowers avoid sub-prime lending, and assistance with re-negotiation for more favorable terms for borrowers with sub-prime loans. This program would identify government assistance programs that also serve to assist distressed borrowers. Evaluate the feasibility of creating a maintenance and replacement reserve account for affordable home buyers assisted with the County’s federal funds to insure that funds are escrowed to help cover the cost of major repairs such as foundations, roofs, and heating and air conditions.

Evaluate the feasibility of creating a loan loss reserve mortgage default and foreclosure prevention fund for affordable home buyers assisted with federal funds and those purchasing foreclosed property under the Neighborhood Stabilization Program. For example, funding could be requested under the FHLB Affordable Housing Program to create a loan loss reserve for mortgages of buyers with marginal credit or regarded as risky by bank underwriting standards. The Loan Loss Reserve fund could be used by mortgage lenders to write down interest rates and to insure loans in the event of default. This fund could also be used to fund workouts for mortgages in the event of unexpected income and job loss. Evaluate the feasibility of creating and implement post purchase support programs in conjunction with non profit development partners to provide housekeeping and preventive maintenance training, and organize neighborhood programming such as associations, crime watch and other initiatives aimed at strengthening and maintaining neighborhood stability.

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Impediment: Low number of loan applications from minorities.

Issues: A look at the Home Mortgage Disclosure Act data for Prince William County indicates that the overall experience of minority groups within the home mortgage loan market differs from that of Whites. We recognize that removal of this impediment is not solely within the control of the government, and that finance industry policies, consumer credit worthiness, and economic trends all impact this issue. However, it is important that the County play a dual role of providing programming and leadership that impacts the problem. The disparity between the loan origination rates among White applicants and minorities, and the extent to which the aforementioned factors contribute to their denial rates must be addressed. This is evidenced in our HMDA analysis that shows African Americans and Hispanics accounting for the second and third highest percentages of the County’s population in year 2000, but their percentages of loan originations much lower compared to their percentage of population in the County.6 White applicants had the highest number of applications and highest percentage of the population. The number of home purchase loan applications for Whites was 313,440 with an origination rate of 70.32 percent compared to 69,750 applications and a 60.3 percent origination rate for African Americans, and 50,900 applications for Hispanics and an origination rate of 59.8 percent. Origination percentages for all types of home loan applications combined, including refinance and home improvements, were higher for Whites when compared to minority applicants.7 It should be noted that as of 2006, there have been even further increases in the minority population as a percentage of Prince William County’s total population, widening the disparity in lending. Impacts: The lower percentage of loan applications among minority groups and lower income households indicates that fewer minority households are purchasing homes or improving housing conditions. Disparity in lending practices suggests that a higher proportion of Hispanic and African American households will remain renters, thereby limiting the potential for these citizens to build equity through homeownership opportunities. Higher percentages of lower income groups and minority households also tend to live in older housing stock in the County. A lack of home improvement loans and a higher percentage of renters among low income households and minorities means persons not likely to receive improvements to the home they are living in and therefore more likely to

6 As shown in HMDA Table 4.2, on page 80, Whites constituted 64.9 percent of the County’s population and 57.35 percent of the home loan originations between 1997 and 2006. African-Americans were 17.95 percent of the population and 10.95 percent of the originations. Hispanics (based on ethnicity rather than race so population percentages exceed 100%) made up 10.48 percent of the population and 7.93 percent of the loan originations. 7 As shown in the HMDA Analysis Tables pages 79 - 86, which compared all loan purposed applications by race and ethnicity, there were higher origination rate for White applicants compared minorities.

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be living in substandard housing. This leads to the further deterioration of the housing stock and the evolution of minority concentrated neighborhoods. These factors combined reduce the chance that a neighborhood sustain itself and its resident can provide the homeowner and rental maintenance necessary to maintain stable neighborhoods. Remedial Actions: Prince William County should continue its homebuyer outreach and education efforts in order to increase the number of minorities who apply for mortgage loans. The County should encourage financial institutions and mortgage companies to expand their homebuyer support services to more people as a means of improving the origination rates among minorities. The County could initiate this recommendation by discussing findings in this study relative to the HMDA data with lending institutions and ask them to develop strategies to improve the success rate among loan applications submitted by minority applicants.

Financial literacy should remain a high priority for the County as indicated in the 2005 AI. Financial literacy is an important factor in the successful management of personal finances, which sets the stage for all of life’s important purchases such as house, car, etc. A well ordered personal budget prepares households to qualify with the best credit terms, eliminates the major obstacles in the home buying process, and enables households to build equity through homeownership. An early start in managing personal finances can prepare an individual for those major purchases. Prince William County should continue to work with lenders and Prince William County, Manassas and Manassas Park school districts to expand financial literacy and life skills programs as part of the high school curriculum. The Reality Store program implemented through a partnership with the county, financial institutions, businesses, universities, and chambers during FY 2008 has worked well in addressing this issue.

Another example is a program launched by the Texas Credit Union Foundation, the Texas Cooperative Extension, and the National Endowment for Financial Education (NEFE) on March 29, 2007 in Dallas, Texas. Project NEFE is part of a statewide collaborative initiative to bring the accredited High School Financial Planning Program along with comprehensive training to schools across Texas, all free of charge. Signed into law in 2005 by Gov. Rick Perry, House Bill 492 by Rep. Beverly Woolley (R-Houston), requires school districts and open-enrollment charter schools to incorporate instruction in personal financial literacy beginning with the 2006-2007 school years. The National Endowment for Financial Education (NEFE) has provided both leadership and funding for this effort. The NEFE curriculum will be used by participating Texas schools and that curriculum meets the learning objectives and standards approved by the Texas Education Agency and State Board of Education to meet the requirement.

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Since 1984, The National Endowment for Financial Education (NEFE) has been addressing youth financial literacy with the nationally known NEFE High School Financial Planning Program® (HSFPP). The HSFPP consists of a seven unit student manual, instructor’s guide that offer a large, continually growing collection of resources, articles, and financial tools for teachers, students, and parents. To learn more about the HSFPP, visit http://hsfpp.nefe.org. Unit Include:

Your Financial Plan: Where It All Begins Budgeting: Making the Most of Your Money Investing: Making Money Work for You Good Debt, Bad Debt: Using Credit Wisely Your Money: Keeping It Safe and Secure Insurance: Protecting What You Have Your Career: Doing What Matters Most

The County should encourage the school district to apply for NEFE funding as a possible source of financing for credit education programs in schools. Continued emphasis should also be placed on homeownership and credit education provided through bilingual instructors and counselors to address the needs of Spanish speaking residents.

Impediment: Predatory lending and other industry practices.

Issue: Predatory lending practices continue to be a widespread concern in Prince William County. Anecdotal comments and perceptions were cited, by person interviewed and those attending the focus group sessions, suggesting unfavorable lending practices.8 The focus group participants’ perception is that predatory lenders are replacing banks and other reputable financial institutions as lenders of choice in some areas. These perceptions were also supported by a growing number of pay-day loans, check-cashing, and title-loan stores observed in the County. Focus Group participants were also concerned with extremely high interest rates being charged by not only predatory lenders, but traditional banks and financial institutions for credit cards, auto loans, and other consumer loans. It should be noted that in some instances, predatory lending is fueled by poor credit rating, limited credit history, or lack of understanding of the borrowers as to alternative lending options. Appraisals that fail to provide adequate comparables to support mortgage refinance loans is especially of concern for residents throughout the County. In other instances, participants were concerned with underwriting criteria used by lenders, failure to adjust ratios or provide funding with more favorable terms, or simply the influences of the foreclosure rates and

8 Focus Group Sessions page 71.

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sub-prime lending on mortgage approvals and higher private mortgage insurance for small loans. Impact: Predatory lending practices often result in a lower-income household losing their home, automobile or other collateral. In some cases, Focus Group participants cited instances where homeowners who had already paid off their original mortgage were losing their home when used as collateral on a loan for a small fraction of the home’s value. The analysis revealed limited success of minority and lower income applicants in accessing financing from traditional banks and credit unions, and lower approval rates for applicants at all income levels when submitting loan applications to buy property in lower income census tracts. Perceptions of person contributing to this analysis is that some residents are more likely to utilize the services of sub-prime lenders and check-cashing stores that may charge exorbitant interest rates and have severe default penalties. Predatory lending may further impair an individual’s credit and monopolize more of a low-income person’s monthly income with high interest rates and finance charges, leaving less money for housing and necessities. Some consumers felt that they had little recourse to address adverse industry practices that impact their housing choice. Remedial Actions: The County should encourage lending institutions to provide greater outreach to the low income and minority communities to lessen the use of predatory lenders. The emphasis should be on offering products and services that help establish or reestablish checking, saving, and credit accounts for residents that commonly utilize check cashing services. This may require establishing “fresh start programs” for those with poor credit and previous non compliant bank account practices. Lending institutions should therefore be encouraged to tailor products to better accommodate the past financial deficiencies of low income applicants with credit issues.

6.3 Socio-Economic Impediments Impediment: Poverty and low-income among minority populations.

Issues: For many households, low or no income is a major factor preventing their exercise of housing choice. Minority populations in the County as a whole are confronted with even higher percentage of their population living in poverty than Whites.11 The incidence of poverty among African-Americans in 2000 was reported to be 6.99 percent of the total population in Prince William County, 8.64 percent in Manassas, and 3.25 percent in Manassas Park. Just over eight percent of Hispanics in Prince William County, 18.19 percent in Manassas, and 7.17 percent in

11 Table 2.3 Poverty status by Race on page 24 of the Community Profiles

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Manassas Park lived in poverty in 2000. Among White persons, the data reported 2.98 percent living in poverty in Prince William County, 3.99 percent in Manassas, and 4.86 percent in Manassas Park. Of equal concern, among children below the age of 5, nearly 11 percent of all African-Americans in Prince William County and Manassas were living in poverty. Among Hispanics, over nine percent in Prince William County, nearly 18 percent in Manassas, and over seven percent in Manassas Park were living in poverty. Comparatively, nearly four percent of all White children below the age of 5, are living in poverty in Prince William County, over four percent in Manassas, and nearly five percent in Manassas Park. Living in poverty restricts the quality of life of these children due to the limited housing options available to their parents.12 At a time when minority populations are increasing, many homes will be priced above any reasonable rate for purchase or rent by many of these households. Factors such as family size, education and job skill levels, and unemployment are also major contributors to the plight of these households. Impacts: Households experiencing a severe lack of income and those unemployed typically must accept housing in the poorest areas of town. Housing tends to be segregated by income class and sometimes by race or ethnicity, where the housing stock is most likely in poor condition, there are higher reported incidents of criminal activity, and opportunities for improving a person’s quality of life are low. Children from these households grow up in an environment that sometimes dooms them to replicate their community’s living standards, continuing the cycle of poverty for generations to come. Focus group participants voiced a perception that certain areas of the County are home to a disproportionate number of low-income persons, living in substandard multifamily housing developments. Participants indicated that the concentration of poverty is not only a concern with regard to social equity and the plight of renters, but poverty is also having a significant impact on the condition and quality of single family housing in the neighborhoods where there are high concentrations of home owners. In areas where a majority of homeowners cannot afford routine maintenance, poor housing conditions may quickly become the prevalent state of affairs. Lack of job opportunities and lack of sufficient income to afford decent housing were cited as concerns. Both crime and perception of crime were discussed as critical issues that are hindering some residents from living in various areas of Prince William County. Remedial Actions: The County and local Chamber of Commerce should continue to work on expanding job opportunities through the recruitment of corporations, the provision of incentives for local corporations seeking

12Chart 2.2 Household Income by Race on page 18 of the Community Profiles

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expansion opportunities, assistance with the preparation of small business loan applications, and other activities whose aim is to reduce unemployment and expand the base of higher income jobs. A particular emphasis should be to recruit jobs that best mirror the job skills and education levels of those populations most in need of jobs. For Prince William County, this means jobs that support person with high school education, GED’s and in some instances, community college or technical training. These persons are evident in the workforce demographics and in need of jobs paying minimum wage to moderate hourly wages. The County should also continue to support agencies that provide workforce development programs and continuing education courses to increase the educational level and job skills of residents. The goal should be to increase the GED, high school graduation, technical training, and college matriculation rates among residents. This will help in the recruitment of industry such as “call centers”, clerical and manufacturing jobs. Call centers and customer service centers where employees are recruited to process sales or provide customer service support for various industries, have become more and more attracted to areas with similar demographics to that of Prince William County. The combination of lower priced land, government incentives for relocation and the workforce to support their industries, have all become incentives in recent years.

6.4 Neighborhood Conditions Related Impediments Impediment: Limited resources to assist lower income, elderly and indigent homeowners maintain their homes and stability in neighborhoods.

Issue: While Prince William County neighborhoods are relatively stable today and its housing stock in fair to good condition, area conditions will decline if routine and preventive maintenance does not occur in a timely manner. The population is aging, which means more households with decreasing incomes to pay for basic needs. This increase in elderly households coupled with the steady rise in the cost of housing and the cost of maintaining housing means that many residents will not be able to limit their housing related cost to 30 percent of household income and still maintain their property. Rental property owners will be faced with increasing rents to pay for the cost of maintenance and updating units rendering rental units unaffordable to households as well. Government programs utilizing HOME and CDBG HUD funding and other sources impact only a small percentage of those in need of assistance. Increased support from volunteers and community resources will be needed to close the gap between total needs and resources available. Impact: Neighborhoods and homeowners and renters must devise a means for residents and landlords to keep pace with the maintenance

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demands of housing, an aging housing stock, and support those persons unable to maintain their properties on their own. This will enhance and support a healthy neighborhood “Image and Identity” and help attract new residents and retain existing residents and businesses. An essential component of this recommendation will include becoming healthier, sustainable neighborhoods, able to meet the essential quality of life needs of its residents and to improve the physical character of the neighborhood. Neighborhood assets must be protected and improved. Structures should be strategically removed if found to no longer contribute to the well being of the community. Maintaining vacant lots, including clearing weed, litter, and junk, and maintaining tree growth, would immediately improve the appearance of neighborhoods. Other amenities such as providing streetscape enhancements in the medians and pedestrian areas along residential streets, adding street lighting, sidewalks, shrubs, and new development on vacant lots, would significantly improve the neighborhoods. Most of all, there is a need to revive the “sense of community and trust” and encourage participation and cooperation from residents to maintain their homes, yards, and surroundings and to actively participate in community empowerment activities such as Crime Watch, neighborhood associations and self help initiatives. Remedial Actions: The County should continue to expand its Centralized Program of Self-Help Initiatives based on volunteers providing housing assistance to designated elderly and indigent property owners and assist them in complying with municipal housing codes. This may include expanding recruiting effort to gain greater involvement from volunteers, community organizations, religious organizations/institutions and businesses as a means of supplementing available financial resources for housing repair and neighborhood cleanups. While there have been successful initiatives of this nature, initiated and funded both by the Prince William County and nonprofit agencies, a more comprehensive effort, perhaps coordinated by the County, needs to be designed and implemented that fully utilizes the resources of the community and area businesses. The program will be based on a case management system where the select needs of designated area property owners are matched with volunteer resource teams capable of responding to property with active code violations and other exterior repairs for select properties. Requests for assistance would be received from code enforcement officials, housing program administrators, social service agencies, community institutions, and homeowners. Priority will be given to those owners immediately affected by an active code compliance case, a targeted block or area project, and those with life threatening or uninhabitable conditions.

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Eligibility for assistance will require verification of income or status as elderly or disabled. Levels of assistance would be based on the specific needs to be addressed and the ability of the property owners and their family to assist in the effort. The County could fund a Program Coordinator designated to conduct home visits of each program participant, evaluate the appropriateness for volunteers to perform the work, and determine and advise the homeowner of their responsibilities in support of the effort. The Program Coordinator, upon securing a match between volunteers and property owner, will coordinate project dates, materials, supplies, and project support for the day of the project. Again, some of these activities may have been initiated in the past, so in some instances, our recommendations are that activities be continued, offer an enhanced level of programming, or that the county apply for funds as they become available. Activities that could be considered for the centralized self-help initiatives program include:

o Expand existing self-help initiatives such as the Neighborhood

Clean Up Program through Neighborhood Services and "fix-up," "paint-up," or "clean-up" campaigns and "corporate repair projects". Continue to seek greater involvement of volunteers in order to increase resources available for these efforts.

o Organize a “Compliance Store” where home builders, building

supply stores, merchants, and celebrities, such as radio and television personalities, are used to demonstrate simple, cost effective ways to make improvements to houses and donate building supplies for use in self-help projects. The supplies and storage facility for supplies could be provided to enrollees by building supply stores, contractors, and hardware stores.

o Continue "adopt-a-block" and "adopt-an-intersection" campaigns

where neighborhood groups, residents, scout troops, and businesses adopt key vistas and intersections to maintain and implement beautification projects, such as flower and shrub plantings and maintenance.

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Section 7: Oversight, Monitoring and Maintenance of Records Introduction This section summarizes the ongoing responsibilities of the jurisdiction relative to oversight of efforts to implement the remedial actions recommended in Section Six of this report. It also sets forth the monitoring and maintenance of records procedures that will be put into action to insure that implementation efforts can be evaluated and accomplishments reported to HUD in a timely manner. Oversight and Monitoring The Analysis of Impediment process has been conducted under the oversight and coordination of Prince William County, Office of Housing and Community Development (OHCD), with the support of an independent consultant. The Office of Housing and Community Development will be responsible for ongoing oversight, self-evaluation, monitoring, maintenance and reporting of the jurisdictions’ progress in implementing the remedial actions and other efforts to further fair housing choice. The OHCD will therefore provide oversight of the following activities. OHCD will evaluate each of the recommendations and remedial actions presented in this report, and ensure consultation with appropriate county departments and outside agencies and organizations to determine the feasibility and timing of implementation. Feasibility and timing of implementation will be influenced by county policies, fiscal impacts, anticipated resolutions to the fair housing impediment identified, adherence to federal, state and local regulations and the accomplishment of desired outcomes. OHCD will provide recommendations for implementation to the appropriate departments, organizations and municipalities. OHCD will continue to ensure that all sub-grantees receiving CDBG funds have an up-to-date Affirmative Fair Housing Marketing Plan; display a Fair Housing poster and include the Fair Housing logo on all printed materials as appropriate; and provide beneficiaries with information on what constitutes a protected class member and instructions on how to file a complaint. OHCD will ensure that properties and organizations assisted with federal, state and local funding are compliant with uniform federal accessibility standards during any ongoing physical inspections or based on any complaints of non-compliance received by the County. OHCD will expand its Fair Housing outreach and education activities by hosting or participating in a community fair or workshop annually; providing fair housing information brochures at public libraries and county facilities; and sponsoring public service announcements with media organizations that provide such a service to local government.

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OHCD will incorporate fair housing requirements in its grant program community outreach and training sessions. Maintenance of Records In accordance with Section 2.14 in the HUD Fair Housing Planning Guide, OHCD will maintain the following data and information as documentation of the County’s efforts to affirmatively further fair housing choice. A copy of the Analysis of Impediments and any updates will be maintained and made available upon request. A list of actions taken as part of the implementation of this report and the County’s Fair Housing Plan will be maintained and made available upon request. OHCD will submit an update of its progress to HUD at the end of each program year.

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