1

Redistribution Effect

of Introducing 2010 Census

and 2005-2009 ACS Data

Into the CDBG Formula

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REDISTRIBUTION EFFECT OF

INTRODUCING 2010 CENSUS

AND 2005–2009 ACS DATA

INTO THE CDBG FORMULA

Prepared for

U.S. Department of Housing and Urban Development

Office of Policy Development and Research

Prepared by

Paul Joice

Ben J. Winter

Heidi Johnson

December 2011

TABLE OF CONTENTS

i

Executive Summary ��������������������������������������������������������������������������������������������������������������������� iii Chapter 1–Introduction �����������������������������������������������������������������������������������������������������������������1

Chapter 2–Redistributive Effects of New Data on Community Development Block Grant Entitlement Communities ��������������������������������������������������������������������������������������������������������������������������������6

Chapter 3–Redistributive Effects of New Data on Community Development Block Grant Nonentitlement Communities ������������������������������������������������������������������������������������������������������������������������������24

Chapter 4–Confirming Key Trends ������������������������������������������������������������������������������������������������29

Conclusion ��������������������������������������������������������������������������������������������������������������������������������33

Acknowledgements ��������������������������������������������������������������������������������������������������������������������34

References ���������������������������������������������������������������������������������������������������������������������������������35

Additional Reading ��������������������������������������������������������������������������������������������������������������������36

Appendix 1–HUD Administrative Regions (map) ����������������������������������������������������������������������������37

Appendix 2–All FY 2011 Entitlement Jurisdictions ��������������������������������������������������������������������������38

ii

EXECUTIVE SUMMARY

The Community Development Block Grant (CDBG) program is one of the longest running programs of the U�S� Department of Housing and Urban Development’s (HUD) Office of Community Planning and Development (CPD)� CDBG is a grant to states and local governments that is distributed by a need-based formula� Fiscal year (FY) 2012 marks the first year that the CDBG allocation formula will rely on the Census Bureau’s new annual data source—the American Community Survey (ACS)—and the 2010 Census population counts� This report introduces the ACS to CDBG stakeholders and provides detailed information on how using the 2010 Census and ACS data shifts funding amounts� This analysis compares actual FY

2011 allocations with alternate allocations using FY 2011 appropriations, the FY 2011 grantee universe, and the new data that will be used in FY 2012� Allocations presented should not be interpreted as actual FY 2012 grant amounts�

The CDBG statute specifies that funding be allocated based on the most recent data compiled by the United States Bureau of the Census demonstrating population, poverty, overcrowded housing, pre-1940 housing, and growth lag� Starting in FY 2012, population and growth lag will be computed using the 1960 and 2010 Censuses; in FY 2011, these variables were derived from the 2009 Intercensal Population Estimates and the 1960 Census� Poverty, overcrowding, and pre-1940 housing will be calculated with the 2005–

2009 ACS 5-year estimates in FY 2012, replacing data from the 2000 Census, which was used in the FY

2011 allocations� The ACS estimates of overcrowding and pre-1940 housing are particularly noteworthy�

At a national level, the estimated number of overcrowded housing units in metropolitan areas in the 2005–2009 ACS is 46�4 percent lower than in the 2000 Census� Because the CDBG formula is allocated based on a grantee’s share of each variable, any entitlement community that experiences a decrease in overcrowding of less than 46�4 percent (or an increase) receives additional CDBG funding allocated by that variable�1 Even more puzzling, the estimated number of pre-1940 housing units in all metropolitan areas, as of 2005–2009, is 7�7 percent higher than the estimate in the 2000 Census� Any entitlement community that experiences an increase of less than 7�7 percent in pre-1940 housing (or a decrease) loses CDBG funding allocated by that variable�

This report observes several interesting trends by jurisdiction type, region, and size� Among entitlement communities:

w Principal cities and urban counties receive more funds (0�2 and 1�2 percent, respectively), while satellite cities lose 3�1 percent� These changes are driven largely by increasing shares of poverty in urban counties, decreasing shares of overcrowding in satellite cities, and increasing shares of pre-1940

housing in principal cities�

w The Rocky Mountain, Great Plains, and Midwest regions have the largest increase in average grant amount, at 9�7, 6�9, and 5�2 percent, respectively�

w Entitlement grantees in Puerto Rico see their grants go down by an average of 22�7 percent due to decreasing shares of all formula variables, but particularly due to decreasing shares of poverty and overcrowding�

1 This report uses the terms “increase” and “decrease” to refer to differences between the 2000 Census and 2005-2009 ACS� For reasons discussed throughout the report, the differences between the Census and ACS estimates reflect differences in the methods used by the two surveys in addition to differences in conditions between the two time periods� While “increase” and “decrease” may overstate the temporal aspect of the difference, we use the language for simplicity�

w The largest grantees (cities with a population of 1 million or more) experience a slight decrease in iii

average funding (-0�9 percent)� The smallest grantees (cities with a population of 50,000 to 99,999

and under 50,000) experience larger funding decreases of 1�2 and 3�4 percent, respectively�

w Grantees with a population of 200,000 to 999,999 see their average grant go up 1�5 percent but, due to population growth, their per capita grant remains constant�

Table ES-1. Distribution of Funds to Entitlement Jurisdictions, by Type, Region, and Size FY 2011 Allocation ($)

New Data Allocation ($)

Percent Change (%)

Entitlement

Average

Average

Jurisdictions

Grant

Per Capita

Grant

Per Capita

Average

Per Capita

(n)

(thousands)

Grant2

(thousands)

Grant

Grant

Grant

Jurisdiction Type

Principal city

637

2,390

15.2

2,395

15.2

0.2

0.0

Satellite city

347

830

11.2

805

10.8

– 3.0

– 3.6

Urban county

182

2,725

6.6

2,755

6.6

1.1

0.0

Region

New England

77

1,490

19.8

1,510

20.0

1.3

1.0

New York/

New Jersey

105

3,375

15.0

3,355

15.0

– 0.6

0.0

Mid-Atlantic

102

2,580

13.2

2,450

12.4

– 5.0

– 6.1

Southeast

189

1,370

8.0

1,365

8.0

– 0.4

0.0

Midwest

205

2,035

13.6

2,140

14.4

5.2

5.9

Southwest

120

1,855

9.4

1,920

9.8

3.5

4.3

Great Plains

39

1,740

11.2

1,860

12.0

6.9

7.1

Rocky Mountain

46

980

6.8

1,075

7.6

9.7

11.8

Pacific/Hawaii

204

2,165

10.4

2,100

10.2

– 3.0

– 1.9

Northwest/

Alaska

52

1,265

8.0

1,295

8.2

2.4

2.5

Puerto Rico

27

2,075

23.6

1,605

18.2

– 22.7

– 22.9

Community Size

1 million or more

16

32,800

15.4

32,500

15.2

– 0.9

– 1.3

200,000–

999,999

260

3,775

9.8

3,830

9.8

1.5

0.0

100,000–

199,999

184

1,540

11.0

1,545

11.0

0.3

0.0

50,000–

99,999

435

825

11.8

815

11.6

– 1.2

– 1.7

49,999 or fewer

271

580

17.2

560

16.6

– 3.4

– 3.5

All Entitlements

1,166

1,980

11.4

1,980

11.4

0.0

0.0

2 While the FY 2011 CDBG allocation amount uses 2009 population estimates and the new data allocation uses 2010 Census population counts, per capita amounts in this table are calculated using 2010 Census population counts in the denominator�

iv

Several of the changes observed with the introduction of new data are noteworthy—in particular the increase in pre-1940 housing units, dramatic drop in overcrowded housing units, and changes in population between the 2009 population estimates and 2010 Census population counts� However, these trends are confirmed by other research and have a variety of plausible explanations� Among these explanations are differences in nonsampling error between the different surveys, residency rules, and unique trends in migration and vacancy rates in the years following the 2000 Census� Most significant among these are the differences in nonsampling error—specifically, the ACS data collection methods are more likely to result in more accurate estimates of the number of rooms in a housing unit and the age of the structure than the methods employed by the decennial census� The decennial census relied more heavily on mail-in survey responses, whereas ACS interviewers have better opportunities to explain the survey questions and to verify responses�

The ACS 5-year estimates will be updated every year, and HUD intends to use the annual updates for the CDBG allocation formula� These annual data will provide up-to-date estimates of conditions in CDBG

communities across the country, and have the added benefit of stability from year to year�

CHAPTER

1

1INTRODUCTION

Purpose

The law implementing the Community Development Block Grant (CDBG) program calls for using “the most recent data compiled by the United States Bureau of the Census” for allocating the CDBG funds (42 U�S�C�

ch� 69, sec� 5302 (b))� When CDBG was created in 1974, the most recent data was the 1970 Census�

Since then, the most significant updates followed the 1980, 1990, and 2000 Censuses� But in the years following the 2000 Census, the Census Bureau began a major transition to an annual survey known as the American Community Survey (ACS)� The ACS generally asks the same questions as the old long form of the census and will now be the Census Bureau’s most comprehensive, nationally available source of information on demographic, social, economic, and housing characteristics�

Fiscal year (FY) 2012 marks the first year that new ACS data will be used in the CDBG formula� The purpose of this report is to introduce the ACS to CDBG stakeholders who may not be familiar with this new source of data, and to provide detailed information on how using the 2010 Census and the ACS

data leads to shifts in CDBG funding� This chapter provides background on both the CDBG program and the ACS� Chapter 2 discusses how the new data affect allocations for entitlement grantees, focusing on redistribution across regions and types of grantees� Chapter 3 presents similar analysis for nonentitlement areas� Chapter 4 verifies key trends we observe and probes further to identify possible explanations�

Attached to this report are two appendixes; appendix 1 is a map showing the U�S� Department of Housing and Urban Development (HUD) Administrative Regions plus Puerto Rico, and the table in appendix 2

illustrates how the new data affect the allocation of each FY 2011 CDBG grantee�

History of the CDBG Program and Formula

Title I of the Housing and Community Development Act of 1974 specifically terminated several grant programs: Urban Renewal, Model Cities, open space land and beautification grants, neighborhood facilities grants, basic water and sewer facilities grants, and public facility loans� These programs were competitive grants, meaning that HUD reviewed applications from local authorities and chose the projects that appeared to have the greatest merit and need� They were also categorical grants, meaning that different programs existed for different needs�

As part of the Nixon Administration’s New Federalism, federal policymakers merged these categorical grants to create CDBG� CDBG was intended to simplify the federal role in community development and to provide more decision-making authority to local officials, who were believed to be more able to assess the specific community development needs in their jurisdiction� The formula-based design enables HUD to quickly and easily allocate funds to local officials, while still targeting funds based on objectively measured needs� It also enables long-term planning by local governments by establishing a relatively stable annual funding stream�

The statutory objective of CDBG is the development of viable urban communities, by providing decent housing and a suitable living environment and expanding economic opportunities, principally for people with low and moderate incomes� This objective served as the driving force in designing the original needs formula (Bunce, 1976), which allocated funds using a weighted combination of three variables: population, poverty, and overcrowded housing�3

3 HUD defines overcrowded as having more than one person per room 2

Congress required that the Secretary of HUD submit a report by March 31, 1977, containing recommendations for modifying the original parameters of the CBDG program, including the formula design� The HUD study found that the existing formula was highly responsive to the poverty dimension but unresponsive to the nonpoverty dimensions of community development need� A separate study conducted by the Brookings Institution also found that the major flaw of the 1974 formula was its unresponsiveness to the severe physical, social, and fiscal problems of older, deteriorating metropolitan cities (Bunce, 1976)�

As a result of this evidence, HUD argued that two additional variables were needed—number of housing units built before 1940 and population growth lag—to guarantee funding to cities experiencing long-term physical decline (Bunce and Goldberg, 1979)� This work led to the creation of the dual-formula system that HUD continues to use�

The other significant development in the CDBG program occurred in 1981 with the creation of the State CDBG Program� Before 1981, HUD reserved 20 percent of CBDG funds to be used in nonmetropolitan areas that were not receiving direct CDBG grants� HUD administered a competition for these funds�

Beginning in FY 1982, HUD offered states the opportunity to administer this program� In doing so, the formula was modified so that the total state nonentitlement areas, including both metropolitan and nonmetropolitan areas, would receive a 30 percent share of the CDBG allocation, with the remaining 70

percent allocated exclusively to entitlement communities (Bunce, Neal, and Gardner, 1983)� Since 1981, the process and formula for CDBG allocations have remained essentially the same�4

Basic Formula Operation

There are three types of CDBG grantees: metropolitan cities, urban counties, and states�5 Metropolitan cities and urban counties are collectively known as entitlement communities, while states may also be referred to as nonentitlement areas� The process for allocating funds begins with identifying entitlement communities�

Entitlement communities, which must meet criteria established in section 102 of the Housing and Community Development Act, are broadly divided into metropolitan cities and urban counties� A metropolitan city qualifies by being the principal city of a metropolitan area or by being a satellite city within a metropolitan area that has a population of 50,000 or more�6 Urban counties are counties in metropolitan areas that have a population of 200,000 or more after excluding entitlement cities� All areas that are not part of a metropolitan city or urban county are nonentitlement areas; states receive funding based on their nonentitlement areas from the 30 percent set-aside established in 1981 for the State CDBG

Program�

Because of the 70/30 funding split and slightly different treatment of metropolitan cities, urban counties, and states, the CDBG “formula” is actually five formulas—not one� Here we present a brief overview of how these formulas work; for a full description, see chapter 2 of Richardson and Meehan (2003)�

Formula A—the original CDBG formula created in 1975—has three variables: population, people in poverty, and overcrowded units� Formula B—the formula added in 1979—uses population growth lag since 1960, people in poverty, and pre-1940 housing units� These variables are each divided by a total to 4 Several changes have been made to the CDBG statute related to the qualification criteria for certain types of jurisdictions, as well as provisions meant to prevent abrupt funding decreases as a result of annexation or consolidation of city and county governments� The formula, variables, and variable weights have not changed� For more information see Richardson and Meehan’s (2003) appendix C�

5 The Hawaii nonentitlement CDBG program is administered by the three nonentitlement counties in the state, but funds are allocated to the program the same way as to other state nonentitlement programs� This report groups the Hawaii program with other state grantees�

6 Principal city, a designation of the Office of Management and Budget (OMB), refers to a core city of a metropolitan or micropolitan statistical area� This term has replaced the central city designation previously used by OMB and HUD� Because cities in micropolitan statistical areas do not qualify as CDBG entitlements, they are the same thing for these purposes� Satellite city is not a formal HUD or OMB designation and simply refers to any metropolitan city that is not a central city� See GAO (2004) for more information�

determine each grantee’s “share” of that characteristic�7 Those shares are then weighted and 3

multiplied by the available funding� Table 1-1 shows the actual FY 2011 figures that went into the grant calculation for Phoenix, Arizona, a Formula A grantee� The first two rows show population, poverty, and overcrowding statistics for Phoenix and for all metropolitan areas� The third row is Phoenix’s share of each�

Each variable is then multiplied by its weight and the available funding ($2�3 billion in FY 2011) to show how much it contributed to Phoenix’s overall FY 2011 grant of $17,676,581�

Table 1-1. Sample FY 2011 Formula A Grant Calculation (Phoenix, Arizona) Population

Poverty

Overcrowding

Phoenix

1,593,659

205,320

58,109

All metropolitan areas

261,125,846

28,710,022

5,674,944

Phoenix share

0.61%

0.72%

1.02%

Variable weight

0.25

0.50

0.25

Phoenix share of grant

money

$3,081,105

$7,220,857

$5,169,432

Formula B for entitlement communities is slightly more complicated because of the denominator used to calculate a grantee’s share of each variable� Poverty and pre-1940 housing are calculated as shares of all metropolitan areas, whether the grantee is a metropolitan city or an urban county� Growth lag for a metropolitan city is calculated relative to the total for all metropolitan cities, but growth lag for an urban county is calculated relative to the total for all entitlement communities (metropolitan cities and urban counties)� For an example of a Formula B allocation see Table 1-2, which presents the data that went into the FY 2011 allocation for Detroit, Michigan�

Table 1-2. Sample FY 2011 Formula B Grant Calculation (Detroit, Michigan) Growth Lag

Poverty

Pre-1940 Housing

Detroit

1,599,276

243,153

112,022

Total

32,391,457

28,710,022

13,370,481

Detroit share

4.94%

0.85%

0.84%

Variable weight

0.20

0.30

0.50

Detroit share of grant money

$19,940,863

$5,862,153

$9,665,317

The formula for the nonentitled areas of states generally operates like the entitlement formula, with two exceptions: Formula B uses population instead of growth lag, and the denominator for all the variables is the sum for all nonentitled areas instead of the sum for nonmetropolitan areas�

Allocations are calculated from both Formula A and Formula B for every grantee, and the grantee receives whichever amount is greater� This method causes the sum of all allocations to exceed the available appropriations, so a pro rata reduction is applied to all grantees� In FY 2011 the pro rata reduction was 12�475 percent for entitlements and 17�704 percent for nonentitlements� The allocation amounts in Tables 1-1 and 1-2 have the pro rata reduction factored in�

Data Sources for Formulas Before the 2010 Census

Since the establishment of the CDBG program, the decennial census has been the primary source of the data in the CDBG formula� Before 2010, it was the only nationwide source of data for poverty, 7 The denominator varies by formula type, variable, and grantee type�

4

overcrowding, and pre-1940 housing that was available for all communities eligible for CDBG� In the years following the release of the decennial census data, the Census Bureau’s Population Estimates Program creates population estimates based on administrative records for births, deaths, and migration� These estimates are provided to HUD for all units of general local government, and HUD uses them to update the population variable (Formula A) and the growth lag variable (Formula B) for every grantee� The Census Bureau also identifies new incorporations and reports major boundary changes (usually due to annexation); in these cases, HUD has reassigned the data that corresponds to the area being annexed or incorporated�

Aside from annual population estimate updates and adjustments due to new incorporations or annexations, HUD has not historically been able to update the formula data between decennial censuses�

American Community Survey

Amid the information revolution of the 1980s and 1990s, researchers and federal policymakers began to call for regular data to fill the void between each decennial census� In 1985, Congress authorized a mid-decade census, but funds were not appropriated� In 1994, the Census Bureau began developing a continuous measurement survey that might provide current and consistent nationwide data on social, demographic, and economic conditions� The Census Bureau tested the American Community Survey (ACS) throughout the late 1990s, and, in 2000, the agency carried out a large-scale demonstration called the Census 2000 Supplementary Survey (C2SS)� The C2SS was similar to the ACS but was coordinated with the 2000 Census and carried out in 1,239 counties� After extensive study of the data quality produced in C2SS and ACS test sites, the Census Bureau concluded that continuous measurement was feasible and could be done reliably and cost effectively� The ACS was implemented nationwide in 2005�

In many ways, the ACS is very similar to the long form of the decennial census� Households that receive the ACS are legally obligated to respond, just as they were when they received the short form or long form of the 2000 Census� Every question in the ACS must be justified to the Office of Management and Budget (OMB), and nearly all questions are necessary to carry out a federal law or implementing regulation� In the first year the survey was conducted, the content of the ACS survey instrument was nearly identical to the 2000 Census long form, and changes from year to year are kept to a minimum� However, the methodology of the ACS differs from the decennial census in some important ways, four of which this report highlights: sample size, period estimates, margins of error, and residence rules�

The first and most critical difference between the ACS and the decennial census long form is the sample size� The long form of the 2000 Census was mailed to one in six households (approximately 18 million), all within several months of April 1, 2000� Administering a survey to such a large sample on a continuous basis was determined to be infeasible, so the ACS sample includes only 3 million households per year�8

ACS surveys go out by mail each month to 250,000 independently sampled households� Each monthly sample receives 2 months of followup (first by telephone and then in person), so at all times one sample is in the mail survey phase, one sample is in the telephone followup phase, and one sample is in the in-person followup phase� This reliance on a smaller, and continuous, sample leads to the second key difference between the decennial census and the ACS, which is the use of period estimates� The decennial census has always been a count of the population as of April 1st of the year in question� The ACS is administered year-round, so the results must be interpreted as representative for the entire year, rather than a point in time� In addition, the fact that the annual sample for the ACS is about one-sixth the size of the sample for the 2000 Census long form has led the Census Bureau to create multiyear estimates� By combining multiple years of survey responses, the Census Bureau can effectively increase the sample size and continue to release estimates for small geographic areas� The resulting data release program includes

“1-year” estimates for places with a population of more than 65,000, “3-year” estimates for places with 8 When the ACS began, 3 million was 2�5 percent of all housing units, but the sample size did not increase with the number of U�S� households�

In FY 2011, the Census Bureau budget included funds to expand the sample size to around 3�5 million�

a population of more than 20,000, and “5-year” estimates for all geographies down to the census tract�9

5

Because of the small geographic units necessary to build CDBG grantee boundaries (particularly urban counties), HUD will use 5-year ACS estimates for the CDBG formula� The data discussed in this report are based on surveys from 2005 to 2009 and represent conditions averaged over that period�

Even in the 5-year estimates, the full sample size is only 12�5 percent of households—considerably less than the 16�7 percent of households that received the long form of the 2000 Census� This small sample size leads to the third important difference between the decennial census and the ACS: precision and accuracy of data� Data quality problems can stem from either sampling error or nonsampling error�

Sampling error represents the possibility that the households that were surveyed are not representative of all households, simply due to the random nature of a survey sample� Sampling error can be measured and expressed by margins of error and similar figures� Due to its smaller sample size, the ACS has a higher sampling error—in other words, it is less precise—than the decennial census long form survey�

Nonsampling error includes any other mistakes in the administration of a survey, such as data entry errors or misunderstandings (such as cases in which survey recipients do not understand a question)� Any such issues might lead the survey results to be biased—in other words, consistently inaccurate� The ACS is continually administered by a professional survey staff and has well-developed protocols for addressing errors in nonresponse, measurement, and data processing� As a result, the ACS minimizes nonsampling error� Although nonsampling error is very difficult to explicitly measure, it is likely that nonsampling error in the ACS is actually lower than it was for the 2000 Census long form survey, which relied heavily on temporary workers (Love et al�, 2004; Salvo et al�, 2007)�

The final notable difference between the ACS and the long form of the decennial census is the “residence rule,” which determines who should respond to a survey� For the decennial census, households receiving a long form survey were required to respond if the sampled housing unit was their “usual place of residence” as of April 1st of the year in question� A household that lived in Arizona from September to May but spent its summers in a vacation home in Maine would not have responded to a census form mailed to the Maine home� The ACS uses “current residence,” which is defined as a house where you have lived, or plan to live, for at least 2 months�10 If the household in the previous example received an ACS survey at its Maine residence in June, they would be considered a current resident of that housing unit and would respond to the survey� This rule can substantially affect the population being surveyed in places with a large percentage of seasonal residents (Love et al�, 2004)� For instance, if Arizona households that summer in Maine are consistently high-income households, the ACS would indicate higher household incomes in Maine and lower household incomes in Arizona when compared with the 2000 Census (independent of any actual change in income)�

These four methodological issues are among the many reasons that the Census Bureau cautions users against comparing ACS estimates with estimates from previous decennial censuses� For reasons discussed throughout this report, the differences between the Census and ACS estimates reflect differences in the methods used by the two surveys in addition to differences in conditions between the two time periods� Of course, this report directly compares estimates from the two surveys to measure the shifts in funding caused by differences between them� For the sake of simplicity, this report uses the terms increase and decrease to describe differences between the 2000 Census estimates and the 2005-2009 estimates; readers should be aware that increases and decreases may be the result of differences between the two surveys more than actual changes in conditions�

9 Full list of geographies in the 5-year data: http://www�census�gov/acs/www/data_documentation/geography/�

10 Note: The 2010 Census continues to use the “usual place of residence” rule�

CHAPTER

6

2REDISTRIBUTIVE EFFECTS OF NEW DATA ON

COMMUNITY DEVELOPMENT BLOCK GRANT

ENTITLEMENT COMMUNITIES

For the fiscal year (FY) 2012 formula allocation, the U�S� Department of Housing and Urban Development (HUD) will introduce 2010 Census population data as well as estimates of poverty, overcrowding, and pre-1940 housing from the 2005–2009 American Community Survey (ACS) data� This chapter addresses how introducing these new data affects the distribution of Community Development Block Grant (CDBG) funding across entitlement jurisdictions� It focuses on how funds are redistributed by region, jurisdiction size, jurisdiction type (principal city, satellite city, or urban county), and allocation formula� For purposes of comparison, this study keeps constant the overall CDBG appropriation amount and the CDBG grantee universe from FY 2011� All other variables (population, poverty, overcrowding, growth lag, and pre-1940

housing) are updated� Actual funding amounts for jurisdictions in FY 2012 will depend on congressional appropriations and the number of new entitlement jurisdictions that qualify for CDBG funding�

A. Introduction of New Data in the CDBG Formula and the Effect on Allocations to Entitlement Jurisdictions Table 2-1 shows the sources of data for the FY 2011 and FY 2012 CDBG allocations� Since FY 2003, HUD has used the intercensal population estimates and the 1960 Census for the population and growth lag variables� Also since FY 2003, HUD has used the 2000 Census long form data to calculate the poverty, overcrowding, and pre-1940 housing variables�

Because new population counts are now available with the 2010 Census, HUD will use those data for allocations in FY 2012� As described in the previous chapter, the long form data collected in previous decennial censuses have been replaced with ACS� Starting in FY 2012, HUD will use 5-year ACS estimates to maintain the most recent data possible in the CDBG formula�

Table 2-1. Comparison of Formula Variables and Data Sources From FY 2011 and FY 2012 Allocations Factors

FY 2011 Allocation

FY 2012 Allocation

Population

2009 Population Estimates

2010 Census

mula

Poverty

2000 Census

2005–2009 ACS

For A Factors Overcrowding

2000 Census

2005–2009 ACS

Growth lag

2009 Population Estimates and

1960 Census

2010 Census and 1960 Census

mula B

Poverty

2000 Census

2005–2009 ACS

For Factors Pre-1940 housing

2000 Census

2005–2009 ACS

Table 2-2 gives a general picture of how the CDBG formula data have changed since the 2009 Population Estimates and the 2000 Census� Because all CDBG entitlement jurisdictions lie within metropolitan areas, these tables focus only on the aggregate of metropolitan areas� To show how the change of variables may affect the distribution of funds for grantees, Table 2-2 disaggregates the metropolitan geography by entitlement cities (which consist of principal city and satellite city entitlement communities) and the rest of the outlying areas in metropolitan areas, otherwise known as the “balance” (which consist of urban county entitlements and other nonentitlement portions of metropolitan areas)� The “Balance of Metropolitan Areas” can be thought of as suburban or rural areas within metropolitan areas, and the cities can be thought of as the urban portions of metropolitan areas�

Table 2-2. Change in Formula Variables in Metropolitan Areas 7

Entitlement Cities

Balance of Metropolitan

Total Metropolitan Areas

Areas

Population

2009 Population Estimates

126,330,750

134,795,096

261,125,846

2010 Census

125,843,466

136,008,672

261,852,138

Percent Change

– 0.4%

0.9%

0.3%

People in Poverty

2000 Census

18,401,833

10,308,189

28,710,022

2005–2009 ACS

20,671,664

12,724,840

33,396,504

Percent Change

12.3%

23.4%

16.3%

Overcrowded Housing Units

2000 Census

3,861,310

1,813,634

5,674,944

2005–2009 ACS

2,002,160

1,037,538

3,039,698

Percent Change

– 48.1%

– 42.8%

– 46.4%

Pre-1940 Housing Units

2000 Census

8,338,128

5,032,353

13,370,481

2005–2009 ACS

9,320,169

5,084,319

14,404,488

Percent Change

11.8%

1.0%

7.7%

On average, the 2010 Census counts fewer people in cities and more people in the suburban portion of metropolitan areas than the 2009 Population Estimates Program� This statistic does not necessarily mean that in one year, cities lost population while their suburban counterparts grew� It could also mean that the 2010 Census figures are actually more accurate in measuring population than are intercensal estimates�

Even so, future years of CDBG funding between decennial census years must use intercensal population estimates in an attempt to capture the most recent changes in entitlement growth and contraction�

As shown in Table 2-3, this change in population measurement tends to favor urban county entitlement jurisdictions under Formula A, as their shares of total metropolitan population increase while cities’ shares are flat� Conversely, the change in population tends to favor principal cities under Formula B, as population loss contributes to greater growth lag�

The 5-year ACS estimates show an overall increase in the number of people living under the poverty line in metropolitan areas since the 2000 Decennial Census� The percentage increase of people in poverty is almost twice as great in the suburban portions of metropolitan areas as in cities� Table 2-3 shows how this difference tends to favor urban counties more than cities in both Formula A and B entitlements� For Formula A grantees, urban counties benefit from a 2�7 percent increase in the amount of funding allocated by poverty while satellite cities experience a 1�1 percent decrease; principal cities see only a modest 0�1

percent increase�

The ACS estimates drastically lower amounts of overcrowded units than the 2000 Census estimated� It is not entirely clear why this phenomenon is occurring (see chapter 4 for a discussion of this change)�

On average the ACS estimates a greater decline of overcrowded units in cities than it does in suburban portions of metropolitan areas� As a result, urban county entitlements in Formula A gain a modest 0�1

percent in the amount of funding allocated by the overcrowding variable while principal and satellite cities experience a 0�2 and 1�1 percent decline in funding, respectively, because their metropolitan share of overcrowded units decreases�

The ACS also estimates drastically higher counts of housing units built before 1940 than the 2000 Census estimated� The difference is especially prevalent in cities, where the ACS estimates of pre-1940 housing are a remarkable 11�8 percent higher than estimates from the 2000 Census; in comparison, suburban portions 8

of metropolitan areas show only a 1 percent increase� In particular, the ACS shows an additional 252,000 pre-1940 units in New York City alone, 107,000 additional units in Chicago, 60,000 in Los Angeles, 30,000 in Detroit, and about 20,000 extra in Cleveland, St� Louis, and Milwaukee�11 Together, these additional units have a substantial effect on the distribution of CDBG funding�

Table 2-3 shows that principal cities using Formula B experience a 1�3 percent increase in funding allocated by this variable, while satellite cities and urban counties lose 0�3 and 1�4 percent, respectively�

Table 2-3. Average Change of Entitlement Grant Amounts by Entitlement Type Grant Amount (000,000’s)

Percent Change by Variable

Formula A

Formula B

otal

otal

ty

ty

Switching mulas

Jurisdiction Type

No. of Jurisdictions

FY 2011 T Allocation Amount

New Data T Allocation Amount

Total % Change

% Change Due To For

Population

Pover

Overcrowding

Growth Lag

Pover

Pre-1940 Housing

Principal city

637

1,523

1,526

0.2

– 0.4

0.0

0.1

– 0.2

0.2

– 0.9

1.3

Satellite city

347

288

279

– 3.1

0.2

0.0

– 1.1

– 1.1

– 0.8

0.0

– 0.3

Urban county

182

496

502

1.2

0

0.3

2.7

0.1

– 0.5

0.0

– 1.4

B. The Effect of Introducing 2010 Census and ACS Data on Individual Formula Grants To illustrate how data from the 2010 Census and 2005–2009 ACS 5-year estimates affect the grants that entitlement jurisdictions receive, this report details these changes for three grantees: Phoenix, Arizona, a Formula A entitlement city; Chicago, Illinois, a Formula B entitlement city; and Arlington County, Virginia, an urban county that switches from Formula A to Formula B with the introduction of the new data�

Phoenix is a Formula A entitlement city� Formula A grantees are generally growing communities with poverty and overcrowding� As with many other entitlement cities, however, Phoenix’s population as measured by the 2010 Census is lower than the 2009 population estimate� Because a jurisdiction’s need is assessed relative to other jurisdictions for CDBG funding purposes, population loss does not guarantee a loss of funding, even for a Formula A grantee� Funding allocations based on the population variable are reduced only if the jurisdiction’s share of population across all metropolitan areas is reduced� Metropolitan areas as a whole experience a small increase in population from the 2009 population estimates to the 2010 Census� Therefore, Phoenix’s reduction in its share of population is slightly greater than its reduction in population itself�

Based on the ACS 5-year estimates there are an additional 71,464 people in poverty in Phoenix compared with the 2000 Census� Other metropolitan areas do not have such a large increase in people in poverty, so Phoenix’s share of this variable also increases� The poverty column in Table 2-4 represents how Phoenix’s allocation would change if no change existed in population or overcrowding with the introduction of new data�

11 These figures are rounded to the nearest thousand�

The last variable that determines Phoenix’s allocation as a Formula A grantee is overcrowding� As 9

discussed earlier in this report, the ACS estimates drastically lower amounts of overcrowded units across the country compared with the 2000 Census� Phoenix’s level of overcrowding drops steeply but not as much as in other metropolitan areas, as the total drop for all metropolitan areas exceeds 46 percent� A Formula A entitlement grantee who experiences either an increase in overcrowding or a loss less than 46

percent will gain in its allocation share of this variable� Phoenix therefore sees a small gain in funding from this variable, despite its large reduction in the estimated number of overcrowded units� On balance, the reductions in Phoenix’s grant amount due to a greater population loss relative to other metropolitan areas is offset by its gains due to poverty and overcrowding�

Table 2-4. Effect of 2010 Census and 2005–2009 ACS Data on Formula A Grantee (Phoenix, Arizona) Population

Poverty

Overcrowding

Total

Data

FY 2011 (n)

1,593,659

205,320

58,109

2010 Census and

1,445,632

276,784

33,552

2005–2009 ACS

data (n)

Change (%)

– 9.3

34.8

– 42.3

Share

FY 2011 (%)

0.61

0.72

1.02

2010 Census and

0.55

0.83

1.10

2005–2009 ACS

data (%)

Change (%)

– 10

16

8

Grant

FY 2011 ($000s)

3,081

7,221

5,169

15,471

2010 Census and

2,787

8,345

5,549

16,681

2005–2009 ACS

data ($000s)

Change (%)

– 10

16

7

7.8

Chicago is an older city whose CDBG grant is allocated by Formula B� Formula B includes population growth lag, which is the difference between an entitlement city’s actual growth since 1960 and the average growth since 1960 for all entitlement cities� From the 2009 population estimates to the 2010

Census, Chicago’s population decreases by 155,670; the increase in Chicago’s growth lag indicates that its rate of growth is less than that of all entitlement cities�

The number of people in poverty in Chicago increases between the 2000 Census and the 2005–2009

ACS by 3�5 percent� Instead of gaining funds, however, Chicago’s allocation is reduced by the poverty variable because its share of poverty across all metropolitan areas declines� Here again, it is clear how an entitlement’s standing relative to other areas on each variable is an essential component of the formula mechanics� This loss, however, is offset by Chicago’s gain in funding from pre-1940 housing units� While central cities gained pre-1940 housing units nationally, the units gained in Chicago gave that city a greater share of the metropolitan total than it had held previously� Note that the increase in Chicago’s grant amount due to pre-1940 housing is not as large as the increase in its share of the pre-1940 housing variable; this is due to the pro rata reduction that brings grant amounts in line with actual allocations�

10

Table 2-5. Effect of 2010 Census and 2005–2009 ACS Data on a Formula B Grantee (Chicago, Illinois) Growth Lag

Poverty

Pre-1940 Housing

Total

Data

FY 2011 (n)

2,484,926

556,791

438,095

2010 Census and

2,599,394

576,344

545,476

2005–2009 ACS

data (n)

Change (%)

4.6

3.5

24.5

Share

FY 2011 (%)

7.67

1.94

3.28

2010 Census and

7.98

1.73

3.79

2005–2009 ACS

data (%)

Change (%)

4

– 11

16

Grant

FY 2011 ($000s)

30,984

11,749

33,084

75,816

2010 Census and

32,207

10,425

38,128

80,761

2005–2009 ACS

data ($000s)

Change (%)

4

– 11

15

6.6

The characteristics of jurisdictions can change over time, and the formula that provides them with the most funding can also change� Arlington County is one such grantee, which as an urban county had previously been allocated CDBG funds using Formula A� With the introduction of new data, however, the formula yielding the larger allocation switched to Formula B� People in poverty is a component of both Formula A and Formula B; however, it is assigned a lower weight in Formula B� This is advantageous to Arlington County, where poverty was reduced, in contrast to other metropolitan areas where poverty increased as a whole� The reduction in allocation share that Arlington County experiences on this variable therefore has less effect on its overall grant as a Formula B entitlement�

Population is also a component of both formulas, although Formula B focuses on growth lag since the 1960

Census� Population loss generally benefits a jurisdiction’s allotment more as a Formula B grantee, while gains in population are more beneficial among Formula A grantees� The biggest change for Arlington County, however, is in its overcrowded housing units� Overcrowding decreases by a whopping 70�6

percent when using ACS data, which far exceeds the drop in overcrowding in other metropolitan areas�

Overcrowding had contributed the most to Arlington County’s allocation in FY 2011, and such a drastic reduction in its share of overcrowded units likely pushes it into Formula B� Despite Arlington County’s reduction in share on two of the Formula B variables (poverty, and pre-1940 housing units), its reduction in share on Formula A variables is more severe�

Table 2-6. Effect of 2010 Census and 2005–2009 ACS Data on a Grantee Switching From Formula A 11

to Formula B (Arlington County, Virginia)

ty

Population

Growth Lag

Pover

Overcrowding

Pre-1940 Housing

Total

Data

FY 2011 (n)

229,440

31,467

14,803

7,259

10,358

2010 Census and 2005–2009 ACS data (n)

219,959

38,934

14,772

2,131

9,451

Change (%)

– 4.1

23.7

– 0.2

– 70.6

– 8.8

Share

FY 2011 (%)

0.09

0.09

0.05

0.13

0.08

2010 Census and 2005–2009 ACS data (%)

0.08

0.11

0.04

0.07

0.07

Change (%)

– 4

24

– 14

– 45

– 15

Grant

FY 2011 ($000s)

444

0

521

646

0

1,610

2010 Census and 2005–2009 ACS data

($000s)

0

442

267

0

661

1,370

Change (%)

– 15

C. The Effect of Introducing 2010 Census and ACS Data on Entitlement Jurisdictions When appropriation levels are held constant, formulas are “zero sum�” That is, if one jurisdiction increases its funding from a formula change, funding for one or more other jurisdictions will decrease� This section focuses on how the addition of population from the 2010 Census and poverty, overcrowding, and pre-1940 housing from the 2005–2009 ACS 5-year estimates affect the redistribution of funds among CDBG

entitlement jurisdictions�

Change in Average Distribution of Grants to Entitlement Jurisdictions Table 2-7 gives an overview of the changes in average and per capita grant amounts by Jurisdiction Type, HUD Administrative Region, and Community Size due to the introduction of new data� In FY 2011, HUD

allocated funds to principal cities at a rate of $15�20 per capita, satellite cities at a rate of $11�20 per capita and urban counties at a rate of $6�60 per capita� By introducing new census and ACS variables, funding per capita decreases by about 3�6 percent in satellite cities, but remains constant in principal cities and urban county entitlement jurisdictions�

By introducing the new variables, communities in Puerto Rico, the Mid-Atlantic, and the Pacific/Hawaii regions experience the highest percentage declines in per capita funding, at 22�9, 5�9, and 1�9 percent, respectively� Jurisdictions in the Rocky Mountain, Great Plains, and Midwest regions experience the greatest increases in per capita funding, with 11�8, 7�1, and 5�9 percent, respectively�

The smallest communities (under 50,000 inhabitants) stand to lose the most funding per capita— about 60 cents per person, some 3�5 percent less than what was allocated in FY 2011� Communities between 200,000 and 1 million inhabitants see the largest increase in average grant amounts, but funding per capita remains constant at $9�80 per person (lower than both larger and smaller communities)� For the nation’s largest cities and communities (more than 1 million inhabitants), the average grant amount declines by 0�9 percent, and funding per capita decreases by 1�3 percent, or 20 cents per person�

12

Table 2-7. Distribution of Funds to Entitlement Jurisdictions FY 2011 Allocation ($)

New Data Allocation ($)

Percent Change (%)

Average

Average

Entitlements (n)

Grant

Per Capita

Grant

Per Capita

Average

Per Capita

(thousands)

Grant12

(thousands)

Grant

Grant13

Grant

Jurisdiction Type

Principal city

637

2,390

15.2

2,395

15.2

0.2

0.0

Satellite city

347

830

11.2

805

10.8

– 3.0

– 3.6

Urban county

182

2,725

6.6

2,755

6.6

1.1

0.0

Region

New England

77

1,490

19.8

1,510

20.0

1.3

1.0

New York/

105

3,375

15.0

3,355

15.0

– 0.6

0.0

New Jersey

Mid–Atlantic

102

2,580

13.2

2,450

12.4

– 5.0

– 6.1

Southeast

189

1,370

8.0

1,365

8.0

– 0.4

0.0

Midwest

205

2,035

13.6

2,140

14.4

5.2

5.9

Southwest

120

1,855

9.4

1,920

9.8

3.5

4.3

Great Plains

39

1,740

11.2

1,860

12.0

6.9

7.1

Rocky Mountain

46

980

6.8

1,075

7.6

9.7

11.8

Pacific/Hawaii

204

2,165

10.4

2,100

10.2

– 3.0

– 1.9

Northwest/

52

1,265

8.0

1,295

8.2

2.4

2.5

Alaska

Puerto Rico

27

2,075

23.6

1,605

18.2

– 22.7

– 22.9

Community Size

1 million or more

16

32,800

15.4

32,500

15.2

– 0.9

– 1.3

200,000–

260

3,775

9.8

3,830

9.8

1.5

0.0

999,999

100,000–

184

1,540

11.0

1,545

11.0

0.3

0.0

199,999

50,000–

435

825

11.8

815

11.6

– 1.2

– 1.7

99,999

49,999 or fewer

271

580

17.2

560

16.6

– 3.4

– 3.5

All Entitlements

1,166

1,980

11.4

1,980

11.4

0.0

0.0

Effect Caused by Changes in Each Variable

As described in earlier sections of this paper, a grantee’s share of funding is mostly derived from its share of each variable’s national metropolitan total� If a particular variable increases for a grantee more than the aggregate rate of change at the metropolitan level, the CDBG formula will increase funding to that grantee for that particular variable� For variables that decrease at a national metropolitan level (like overcrowding with the introduction of the ACS) a grantee will receive an increase of CDBG funding if it experiences a growth (or lesser decline) than the metropolitan rate of change�

12 While the FY 2011 CDBG allocation amount uses 2009 population estimates and the New Data Allocation uses 2010 Census population counts, per capita amounts in this table are shown as allocation amount over population as counted in the 2010 Census�

13 This column shows the percent change in the average grant amount, while Table 2-3 shows the percent change in total grant amount�

Table 2-8 shows the distribution of rates of change for population, poverty, overcrowding, and pre-1940

13

housing for entitlement jurisdictions� The table shows the rate of change for population and poverty for all grantees, as both variables are used in both formulas� However, overcrowding is shown only for Formula A grantees and pre-1940 housing for Formula B grantees� To illustrate which grantees would lose funding due to the introduction of new variables, the highlighted cells indicate where the national metropolitan totals lie�

All grantees that fall below the highlighted cells experience an increase in CDBG funding allocated by that particular variable because their share of that variable increases� Conversely, grantees that fall above the highlighted cells have a decrease in funding� The national change in population is not indicated, as that variable is used to determine growth lag in Formula B as well as population in Formula A�

Table 2-8. Distribution of Grantees by Percent of Funding Gained or Lost for Population, Poverty, Overcrowding, and Pre-1940 Housing Variables14

Loss/Gain

Population

Poverty

Overcrowding

Pre-1940 Housing

(Formula A)

(Formula B)

>20% loss

6

19

634

10

10–20% loss

29

68

43

34

5–10% loss

85

49

2

37

0–5% loss

381

65

7

75

0–5% gain

501

70

6

76

5–10% gain

128

101

5

63

10–20% gain

30

169

5

75

>20% gain

6

625

7

56

Total

1,166

1,166

709

426

The table shows that change in population among grantees has a somewhat normal distribution, where most grantees fall within a 5 percent positive to 5 percent negative change� The poverty, overcrowding, and pre-1940 housing variables are much more skewed� More than three-fourths of entitlement jurisdictions experienced a growth in poverty of more than 5 percent, and over half experienced a growth in poverty of more than 20 percent� Given that the overall growth in poverty in metropolitan areas was 16�3 percent, grantees whose poverty grew less than 16�3 percent ultimately will lose CDBG funding allocated by that variable�

Of Formula A grantees, 89 percent experience a decline in overcrowded units greater than 20 percent�

Equally as remarkable, 63 percent of Formula B grantees exhibit an apparent increase in pre-1940

housing units since 2000� At a national level, overcrowded units decreased by 46�4 percent� Thus, any grantee that experienced a decline in overcrowding less than 46�4 percent receives additional CDBG

funding allocated by that variable� The variable for pre-1940 housing units increased by 7�7 percent at a national level� Thus, any grantee whose rate of change for that variable is less than 7�7 percent loses CDBG funding allocated by pre-1940 housing�

14 Overcrowding and Pre-1940 Housing columns exclude grantees that switch formulas, because they either lose 100 percent or gain from a starting point of zero�

14

Effect by Region

The introduction of the 2010 Census and ACS 5-year estimates into the CDBG formula affects regions very differently across the country� Even more diverse is the experience of jurisdictions within regions� Tables 2-9, 2-10, and 2-11 shed light on these changes by demonstrating the shifting shares of entitlement funds across and within regions as well as the average change of grants due to particular variables�

Table 2-9 illustrates the average percent change of funding due to the shifting shares of each variable by HUD Administrative Region�15 Nationally, jurisdictions in Formula A gain the most funding by increasing shares of poverty, while Formula B grantees lose the most funding by declining shares of poverty� Formula B

grantees gain the most funding by their increasing shares of pre-1940 housing� Overall, five HUD regions lose funding and six gain funding� A total of $39�7 million, or 1�7 percent of the total appropriation, shifts from the five losing regions to the six gaining regions�

Table 2-9. Shifting Shares of CDBG Entitlement Funding by Region Entitlement Communities

Share of Entitlement Funds (%)

Region

(n)

(%)

FY 2011

New Data

% Change of Funding

New England

77

6.6

5.0

5.0

1.3

New York/New Jersey

105

9.0

15.4

15.3

– 0.6

Mid-Atlantic

102

8.7

11.4

10.8

– 4.9

Southeast

189

16.2

11.2

11.2

– 0.2

Midwest

205

17.6

18.1

19.0

5.3

Southwest

120

10.3

9.6

10.0

3.5

Great Plains

39

3.3

2.9

3.1

6.8

Rocky Mountain

46

3.9

2.0

2.1

9.5

Pacific/Hawaii

204

17.5

19.2

18.6

– 3.1

Northwest/Alaska

52

4.5

2.8

2.9

2.2

Puerto Rico

27

2.3

2.4

1.9

– 22.6

Total

1,166

100.0

100.0

100.0

0.0

15 The regions used here are the 10 HUD administrative regions plus Puerto Rico� See appendix 1 for a map�

Table 2-10. Average Change of Entitlement Grant Amounts by Jurisdiction 15

Grant Amount (000,000’s)

Formula A

Formula B

ty

ty

otal

mulas

Region

No. of

Jurisdictions

FY 2011 T

Allocation

Amount

New Data

Total Allocation

Amount

Total % Change

Due to

Switching

For

Due to

Population

Due to Pover

Due to

Overcrowding

Due to Growth

Lag

Due to Pover

Due to Pre-940

Housing

New

77

115

116

1.3

0.0

0.00

0.00

0.00

– 1.10

– 0.70

3.20

England

New

York/

105

354

352

– 0.6

0.1

0.00

– 0.10

0.10

– 0.40

– 2.80

2.60

New

Jersey

Mid-

102

263

250

– 4.9

– 0.1

0.10

– 0.10

– 0.40

– 0.80

– 0.90

– 2.80

Atlantic

Southeast

189

259

258

– 0.2

– 1.3

0.10

3.90

– 3.30

0.60

– 0.20

0.20

Midwest

205

417

439

5.3

0.1

0.10

1.80

0.20

0.50

0.60

2.00

Southwest

120

222

230

3.5

0.0

0.10

4.20

0.60

0.00

– 0.70

– 0.70

Great

39

68

73

6.8

0.4

0.10

2.30

0.40

0.70

0.80

2.10

Plains

Rocky

46

45

49

9.5

—

– 0.10

9.10

1.70

– 0.30

0.40

– 1.30

Mountain

Pacific/

204

442

428

–3.1

0.0

0.00

– 4.00

1.00

0.00

– 0.20

0.00

Hawaii

NW/

52

66

67

2.2

0.0

0.10

3.60

0.20

– 0.60

0.10

– 1.20

Alaska

Puerto

27

56

43

– 22.6

– 4.2

– 0.50

– 10.00

– 7.90

–

–

–

Rico

TOTAL

1,166

2,307

2,307

0.0

– 0.2

0.00

0.50

– 0.20

– 0.10

– 0.60

0.60

Funding Decreases—Puerto Rico, Mid-Atlantic, Pacific/Hawaii The regions that experience the largest percentage loss of funding are Puerto Rico (-22�6 percent), the Mid-Atlantic (-4�9 percent), and the Pacific/Hawaii regions (-3�1 percent), with a net loss of more than $12�5

million each� Within Puerto Rico, almost all entitlement jurisdictions (96�4 percent) stand to lose more than 10 percent of their CDBG funding due to the introduction of new data� In the Mid-Atlantic region, more than one-half of grantees lose more than 5 percent of funding, while only 16�7 percent gain more than 5

percent of funding� Funding declines are less severe in the Pacific region, where 41�1 percent of grantees lose more than 5 percent of funding, while one-fourth gain more than 5 percent�

Decreases in funding for Puerto Rico jurisdictions are driven by their large drop in shares of poverty and overcrowding, and to a lesser extent, their decline in population as measured from the 2009 population estimates to the 2010 Census� Richardson and Meehan (2003) found similar results from the introduction of 2000 Census data to the CDBG formula; 95 percent of jurisdictions in Puerto Rico experienced declines in CDBG funding in FY 2003� That same study found that the Great Plains and Midwest were other regions that experienced the largest declines due to the introduction of the 2000 Census data� However, those two regions are among the top gainers by introducing the 2010 Census and 5-year ACS data sources into the CDBG formula�

16

Funding Increases—Rocky Mountain, Great Plains, Midwest, and Southwest The Rocky Mountain, Great Plains, Midwest, and Southwest regions experience the greatest percentage increases in funding, at 9�5, 6�8, 5�3, and 3�5 percent, respectively� The Midwest alone stands to receive an increase of $22 million, or 5�3 percent, about one-half of the funding from the net loss of the five regions that lose funding� Their increase in funding is largely due to their growing share of metropolitan poor for Formula A grantees, and a combination of Formula B grantees’ increasing shares of growth lag, poverty, and to a larger extent, pre-1940 housing� In fact, the ACS shows an additional 202,618 units than the 2000 Census in Chicago, Detroit, Cleveland, and Milwaukee, which accounts for 20 percent of the overall net increase of pre-1940 housing units in metropolitan areas�

In the Rocky Mountain region, almost three-fourths of grantees receive funding at least 5 percent greater than their FY 2011 allocation� This increase of funding is largely due to the region’s sharp increase in shares of the nation’s metropolitan poor�

About 60 percent of grantees in the Great Plains see similar increases in funding� This collective increase is largely due to increasing shares of poverty for both Formula A and B grantees and significant increases in Formula B grantees’ share of pre-1940 housing� To a lesser extent, increases in the Great Plains can be attributed to higher shares of overcrowding and growth lag�

In the Southwest, more than one-half of grantees see an increase of funding in excess of 5 percent� These increases are largely caused by sharp rises in their share of the metropolitan poor for Formula A grantees�

Stable—New England

Only one region exhibits somewhat “stable” changes in the amount of funding distributed by the new data sources� Of entitlement jurisdictions in New England, 48 percent have gains or losses of less than 5

percent� In total, the region experiences a small net gain of funding, although 36�4 percent of grantees lose more than 5 percent and only 15�6 percent gain funding� The net gain is largely due to the region’s sharp increase of pre-1940 housing, as measured by the ACS� The ACS shows 37,131 additional pre-1940

units in Boston, Hartford, and Providence, alone� Together, those three cities account for 4 percent of the national net increase in pre-1940 housing�

Mixed—Northwest/Alaska, Southeast, and New York/New Jersey

The Northwest/Alaska region experiences an overall increase in funding, largely due to their Formula A grantees’ increasing share of people in poverty� However, Formula B grantees in the region experience losses of funding due to their declining shares of pre-1940 housing and growth lag�

The Southeast is the most mixed region, where 28 percent of grantees lose more than 5 percent of funding and 44�5 percent gain more than 5 percent� The most significant source of funding declines in the Southeast is the region’s declining share of people in overcrowded units, but that is more than offset by sharp increases in the region’s share of metropolitan poor�

The New York/New Jersey region would experience a net decline in funding, if not for the extremely large increase in pre-1940 housing� In New York City alone, the ACS estimates 251,689 more pre-1940

housing units, which accounts for almost one-fourth of the total national increase in pre-1940 housing units�

In fact, almost one-half of all grantees in the region lose more than 5 percent of funding, while only 14�3

percent experience funding increases in excess of 5 percent�

Table 2-11. Percent of Jurisdictions by Region Gaining and Losing Funds Due to New Data 17

Region

Entitlement Communities (n)

Loss >10%

Loss 5–10%

Loss 5–Gain 5%

Gain 5–10%

Gain >10%

New England

77

10.4

26.0

48.1

9.1

6.5

New York/New Jersey

105

18.1

28.6

39.0

5.7

8.6

Mid-Atlantic

102

21.6

32.4

29.4

6.9

9.8

Southeast

189

16.9

11.1

26.5

11.1

34.4

Midwest

205

5.4

13.7

37.1

15.1

28.8

Southwest

120

10.8

8.3

30.0

10.8

40.0

Great Plains

39

2.6

10.3

28.2

7.7

51.3

Rocky Mountain

46

4.3

2.2

19.6

8.7

65.2

Pacific/Hawaii

204

27.9

13.2

32.4

10.3

16.2

Northwest/Alaska

52

5.8

13.5

34.6

15.4

30.8

Puerto Rico

27

96.3

3.7

0.0

0.0

0.0

Total

1167

16.6

15.6

32.1

10.4

25.3

Effect by Jurisdiction Type

This section analyzes changes in CDBG funding by three different types of entitlement communities: principal cities, satellite cities, and urban counties� In FY 2011, CDBG funding was allocated to 1,166

entitlement communities, which consist of 637 principal cities, 347 satellite cities, and 182 urban counties�

Table 2-12 shows that the introduction of new variables results in a loss of funding for 45 percent of principal cities and 55 percent of satellite cities, but only 37 percent of urban counties�

Table 2-12. Number of Entitlement Jurisdictions Gaining or Losing Funds by Jurisdiction Type Loss/Gain

Total (n)

Principal Cities

Satellite Cities

Urban Counties

>20% loss

42

19

22

1

10–20% loss

152

76

61

15

5–10% loss

182

97

58

27

0–5% loss

170

94

51

25

0–5% gain

204

125

53

26

5–10% gain

121

74

27

20

10–20% gain

186

106

38

42

>20% gain

109

46

37

26

Total

1,166

637

347

182

The evidence of more urban county gainers and, to a lesser extent, principal cities, signals an overall shift of funding from satellite cities to urban counties� Table 2-13 indicates that urban counties experience an increased share of overall CDBG funding from 21�5 to 21�8 percent as a result of introducing the new data� As described earlier in this chapter, this is mainly due to the fact that suburban portions of metropolitan areas have gained larger metropolitan shares of people in poverty, overcrowded units, and population as a whole� Funding through Formula B shifts some dollars towards principal cities, mainly through the greater rate of change for their share of metropolitan housing units built before 1940� As Table 2-10 indicates, principal cities’ overall share of funds slightly increases due to the change in data�

18

Table 2-13. Changing Share of Entitlement Funding by Jurisdiction Type Entitlement Communities

Share of Entitlement Funds (%)

Region

(n)

(%)

FY 2011

New Data

Principal city

637

54.6

66.0

66.1

Satellite city

347

29.8

12.5

12.1

Urban county

182

15.6

21.5

21.8

Total

1,166

100.0

100.0

100.0

Effect by Formula Type

As described in the previous chapter, the CDBG formula is a dual allocation system, in which grantees are assigned to the track on which they score the highest� As a result of introducing new data sources, 31 of 1,166 entitlement jurisdictions switch formula tracks, with 10 going from Formula A to Formula B and 21

going from Formula B to Formula A� Formula A targets communities that are growing in population and exhibit high poverty and overcrowding rates� Formula B targets slow-growth or contracting jurisdictions that have high poverty and an old, deteriorating housing stock� Like Tables 2-12 and 2-13, Tables 2-14 and 2-15 show the distribution of jurisdictions gaining or losing funds by formula type and the changing shares of entitlement funding by formula� Although the aggregate share of funding for Formula B grantees remains relatively constant, this masks substantial variation� Of Formula B grantees, 63 percent lose funding, while only 37 percent of Formula A grantees lose funding� Of those that switched formulas, 58 percent lose funding, which translates into a net loss of funding in that cohort�

Table 2-14. Number of Entitlement Jurisdictions Gaining or Losing Funds by Formula Type Loss/Gain

Total (n)

Formula A

Formula B

Switch Formulas

>20% loss

42

31

8

3

10–20% loss

152

99

48

5

5–10% loss

182

61

119

2

0–5% loss

170

69

93

8

0–5% gain

204

108

92

4

5–10% gain

121

83

34

4

10–20% gain

186

157

27

2

>20% gain

109

101

5

3

Total

1,166

709

426

31

Table 2-15. Changing Share of Entitlement Funding by Formula Type Share of Entitlement Funds (%)

Formula

Total (n)

%

FY 2011

New Data

A

709

60.8

46.2

46.5

B

426

36.5

51.8

51.8

Switch

31

2.7

1.9

1.7

Total

1,166

100.0

100.0

100.0

D. Big Cities, Big Gainers, Big Losers

19

Big Cities

The 25 cities with the largest populations in 2010 account for about 27 percent of the funds allocated by the CDBG entitlement formula� Even small changes in the formula can result in millions of dollars of change in allocations to these communities� Table 2-16 shows that, in aggregate, the largest cities experience a modest 0�5 percent decrease in funding due to the introduction of new variables; however, about one-half of these cities experienced changes in entitlement amounts in excess of 5 percent�

Table 2-16. Largest Entitlement Cities, Ranked by 2010 Population (Part 1) Reason for Change (%)—

Reason for Change (%)—

Formula A

Formula B

ty

ty

City

($000)

($000)

Pover

Pover

Change (%)

Population

Pre-1940 Housing

FY 2011 Grant

New Data Grant

Overcrowding

Growth lag

New

York, NY 163,359 168,010

2.85

—

—

—

0.80

– 4.76

6.81

(B)

Los

Angeles,

64,578

59,056

– 8.55

–0.15

–10.33

1.93

—

—

—

CA (A)

Chicago,

IL (B)

75,816

80,761

6.52

—

—

—

1.61

– 1.75

6.65

Houston,

TX (A)

27,343

27,161

– 0.66

– 1.16

1.95

– 1.45

—

—

—

Phila-

delphia,

46,187

43,091

– 6.70

—

—

—

– 0.30

– 1.32

– 5.08

PA (B)

Phoenix,

AZ (A)

15,471

16,681

7.82

– 1.90

7.26

2.46

—

—

—

San

Antonio,

13,226

12,959

– 2.02

– 0.73

2.99

– 4.28

—

—

—

TX (A)

San

Diego,

13,603

11,999

– 11.79

– 0.04

– 7.97

– 3.79

—

—

—

CA (A)

Dallas, TX

(A)

15,882

16,139

1.62

– 1.28

5.68

– 2.78

—

—

—

Honolulu,

HI (A)

8,786

8,442

– 3.91

0.95

– 6.86

2.00

—

—

—

San Jose,

CA (A)

9,151

8,790

– 3.95

– 0.45

0.83

– 4.33

—

—

—

Indian-

apolis,

8,670

9,580

10.49

—

—

—

– 2.97

5.97

7.49

IN (B)

20

Table 2-16. Largest Entitlement Cities, Ranked by 2010 Population (Part 2) Reason for Change (%)—

Reason for Change (%)—

Formula A

Formula B

ty

ty

City

($000)

($000)

Pover

Pover

Change (%)

Population

Pre-1940 Housing

FY 2011 Grant

New Data Grant

Overcrowding

Growth lag

San

Francisco,

18,584

18,181

– 2.17

—

—

—

– 0.02

– 0.98

– 1.17

CA (B)

Austin, TX

(A)

6,878

7,503

9.09

0.05

8.89

0.15

—

—

—

Columbus,

OH (A)

5,845

7,061

20.81

0.51

13.64

6.65

—

—

—

Fort

Worth, TX

6,153

6,536

6.22

0.36

7.87

– 2.01

—

—

—

(A)

Louisville,

KY

10,777

7,482

– 30.57

– 8.70

– 3.39

– 2.43

– 20.99

– 3.39

4.94

(Switch)

Charlotte,

NC (A)

4,358

4,951

13.61

1.11

12.30

0.20

—

—

—

Detroit,

MI (B)

33,531

37,533

11.94

—

—

—

6.19

0.84

4.90

El Paso,

TX (A)

7,676

7,780

1.36

0.68

2.46

– 1.78

—

—

—

Memphis,

TN (A)

7,320

7,387

0.92

– 0.83

2.89

– 1.14

—

—

—

Nashville-

Davidson,

4,508

4,778

6.00

– 0.46

7.14

– 0.68

—

—

—

TN (A)

Baltimore,

MD (B)

21,039

20,066

– 4.63

—

—

—

0.04

– 3.74

– 0.93

Boston,

MA (B)

17,497

17,882

2.20

—

—

—

1.20

– 1.51

2.52

Seattle,

WA (B)

10,729

10,400

– 3.07

—

—

—

0.01

– 0.73

– 2.35

In total, 9 out of the 25 most populous cities experience an increase greater than 5 percent of their FY

21

2011 grant amount due to the introduction of the new data� Columbus, Ohio, a Formula A grantee, experienced the largest percentage increase of 20�81 percent (an additional $1�216 million)� This change is largely due to that city’s increasing shares of poverty and overcrowding, and to a lesser extent, a modest increase in its share of metropolitan population�

Only four of the largest cities experienced a decline in funding greater than 5 percent� The most severe, Louisville, is due to a technical change in its formula allocation� 42 U�S�C� 5306(b)(6)(A) stipulates that for certain city-county consolidated governments, HUD may allocate CDBG funding to each portion of the city as if the consolidation never occurred� In the past, HUD received special tabulations of census data to enable the allocation of funding to the old Louisville city jurisdiction under Formula B, and the county balance under Formula A� That method allowed the old Louisville city jurisdiction to be allocated funding using the growth lag factor and the balance of the county to take advantage of the variables that tend to favor growing jurisdictions� In April 2011, staff in the Census Bureau’s population estimates office informed HUD staff they did not have a method for producing population estimates for the old Louisville city boundaries after 2010, so that data would no longer be available� Barring further developments with the Census Bureau, HUD plans to treat the Louisville-Jefferson County consolidated government as all other entitlement jurisdictions� The effect on Louisville funding causes a decrease of funding by 30�57 percent, largely due to the growth lag variable’s sharp decline, which the central portion of the city received under the FY 2011 allocation�

The introduction of new variables causes San Diego, Los Angeles, and Philadelphia to lose 11�8, 8�6, and 6�7 percent, respectively, of their total allocations� This loss is mostly driven by San Diego and Los Angeles’s shrinking share of the country’s metropolitan poor� Philadelphia’s funding shrank largely because of its declining shares of pre-1940 housing counts�

Big Gainers

Table 2-17 shows the entitlement jurisdictions that experienced the largest percentage growth in formula allocation due to the introduction of the new data� The average change between these top 10 gainers is 53�53 percent, totaling an aggregate increase of only $2�53 million� Most of the changes can be attributed to an increase in poverty and overcrowding shares� Increases due to the share of population are pronounced only in Elk Grove, California, Johns Creek, Georgia, and Surprise City, Arizona, where populations increased 13�11, 24�17, and 23�4 percent, respectively, from the 2009 population estimates to the 2010 Census population counts� Notably, all these grantees receive allocations through Formula A, and most are suburban jurisdictions that grew substantially from 2000 to 2010�

22

Table 2-17. Biggest Percentage Gainers of CDBG Entitlement Funds Reason for Change (%)—Formula A

City

FY 2011

New Data

Change (%)

Population

Poverty

Overcrowding

Grant ($000)

Grant ($000)

Elk Grove, CA

(A)

455

763

67.59

7.35

35.59

24.65

Springdale,

AR (A)

473

774

63.76

0.46

27.22

36.09

Nampa, ID (A)

491

784

59.57

0.04

46.21

13.32

Johns Creek

City, GA (A)

162

254

56.83

17.56

30.33

8.93

Missouri City,

TX (A)

271

413

52.23

– 5.47

46.43

11.27

Horry County,

SC (A)

1,403

2,081

48.35

1.17

21.31

25.87

McKinney City,

499

TX (A)

738

47.79

1.19

33.07

13.53

Surprise City,

342

AZ (A)

503

47.12

12.40

27.18

7.54

Avondale City,

461

AZ (A)

677

46.72

– 3.85

33.97

16.61

Bellevue, NE

224

(A)

325

45.37

– 0.90

22.40

23.88

Big Losers

The average loss for the 10 grantees with the largest percentage declines in funding is 32�3 percent, with an aggregate loss of $12�145 million� These grantees’ absolute value of aggregate change is much higher than the top gainers’ change because these grantees are generally larger in size� The grantee with the largest percentage decline in funding is Hialeah, FL, which loses 40�94 percent of their CDBG funding�

This decline in funding is mainly caused by a drastic 85�35 percent decline in overcrowded units, much higher than the national decline� Miami Beach and Miami-Dade County lose significant amounts of CDBG

funding, mainly due to their decreasing shares of poverty and overcrowded units�

Hammonton, NJ is a small community of only 14,791� This city loses much of its funding because of a large decrease in pre-1940 housing� The 2010 Census also measures a 10 percent increase in population since the 2009 population estimates, which eliminates that grantee’s growth lag�

Table 2-18. Biggest Percentage Losers of CDBG Entitlement Funds 23

Reason for Change (%)—

Reason for Change (%)—

Formula A

Formula B

ty

ty

City

FY 2011

Pover

Pover

Pre-1940 Housing

Grant ($000)

New Data Grant ($000)

Change (%)

Population

Overcrowding

Growth lag

Hialeah,

FL (A)

3,809

2,250

– 40.94

0.26

– 4.41

– 36.79

—

—

—

Hammon-

ton, NJ (B)

147

89

– 39.05

—

—

—

– 11.72

2.70

– 30.03

Miami

Beach, FL

1,572

1,020

– 35.14

– 0.07

– 17.65

– 17.43

—

—

—

(A)

Alex-

andria,

1,143

760

– 33.45

– 1.76

– 8.18

– 23.51

—

—

—

VA (A)

Alhambra,

CA (A)

1,240

859

– 30.74

– 0.34

– 8.67

– 21.72

—

—

—

Louisville,

KY

10,777

7,482

– 30.57

– 8.70

– 3.39

– 2.43

– 20.99

– 3.39

4.94

(Switch)

Cano-

vanas

Municipio,

1,207

838

– 30.53

– 0.09

– 20.86

– 9.58

—

—

—

PR (A)

Guaynabo

Municipio,

1,727

1,229

– 28.82

– 0.61

– 13.09

– 15.12

—

—

—

PR (A)

Miami-

Dade

County, FL

16,285

11,896

– 26.95

0.12

– 6.10

– 20.97

—

—

—

(A)

Arecibo

Municipio,

2,472

1,809

– 26.81

– 0.52

– 13.09

– 13.20

—

—

—

PR (A)

CHAPTER

24

3REDISTRIBUTIVE EFFECTS OF NEW DATA ON

COMMUNITY DEVELOPMENT BLOCK GRANT

NONENTITLEMENT COMMUNITIES

As noted earlier in chapter 1, the CDBG formula includes a 30 percent set-aside for the 50 states and Puerto Rico� These state grantees administer funds on behalf of communities not served by the entitlement program� Table 3-1 shows how the formula variables change with the introduction of new data from the 2010 Census and 2005–2009 ACS, comparing trends in entitlement communities with trends in nonentitled areas� The trends in nonentitlement areas are generally consistent with the findings presented in chapter 2, although the increase in pre-1940 housing is much less pronounced in nonentitlement areas�

Table 3-1. Change in Formula Variables in Entitlement and Nonentitlement Areas Entitlement Communities

Nonentitled Areas

Population

2009 Population Estimates

201,180,773

108,932,489

2010 Census

201,270,119

110,340,632

Percent Change

0.0%

1.3%

People in Poverty

2000 Census

23,471,950

11,978,807

ACS 2005–2009

27,014,044

14,008,083

Percent Change)

15.1%

16.9%

Overcrowded Housing Units

2000 Census

5,019,582

1,232,717

ACS 2005–2009

2,630,534

778,680

Percent Change

– 47.6%

– 36.8%

Pre-1940 Housing Units

2000 Census

10,576,185

6,825,438

ACS 2005–2009

11,578,443

6,882,096

Percent Change

9.5%

0.8%

Tables 3-2 and 3-3 show how the nonentitlement allocation is broken down between the two formulas, the variables for actual FY 2011 allocations, and for the projected allocations with new data� Both Formula A and Formula B include population and poverty, but they are more heavily weighted under Formula A� Incorporating new data leads to a larger percentage of nonentitlement funds being allocated through Formula A� These tables also show how much funding is distributed by each variable, which is influenced by the weight assigned to it and by the distribution of values for the variable� In both FY 2011

actual allocations and allocations using new data, overcrowding, poverty, and pre-1940 housing have the greatest influence on the allocation results� The per capita funding amount went down for Formula A grantees and is stable or up for Formula B grantees, which makes sense because the population is typically rising in Formula A jurisdictions and stable or falling in Formula B jurisdictions� Incorporating the new data also causes the number of dollars allocated for each overcrowded household to increase substantially, from $165 to $264�7�

Table 3-2. Significance of Formula Variables to Nonentitlement Allocations, FY 2011

25

FY 2011

Variable (weight)

Grant ($000s)

Per Capita ($)16

Dollars per unit

Formula A

Population (0.25)

104,120

1.8

1.8

Poverty (0.5)

258,148

4.6

34.0

Overcrowding (0.25)

149,329

2.6

165.0

Subtotal

511,596

9.0

NA

Formula B

Population (0.2)

79,455

1.5

1.5

Poverty (0.3)

89,237

1.7

20.4

Pre-1940 housing (0.5)

308,522

5.7

59.6

Subtotal

477,214

8.9

NA

Total

988,810

18.4

NA

Table 3-3. Significance of Formula Variables to Nonentitlement Allocations, New Data New Data

Variable (weight)

Grant ($000s)

Per Capita ($)

Dollars per unit

Formula A

Population (0.25)

116,853

1.9

1.9

Poverty (0.5)

277,466

4.4

29.4

Overcrowding (0.25)

149,514

2.4

264.7

Subtotal

543,833

8.7

NA

Formula B

Population (0.2)

71,429

1.5

1.5

Poverty (0.3)

80,887

1.7

17.7

Pre-1940 housing (0.5)

292,661

6.1

59.9

Subtotal

444,978

9.3

NA

Total

988,810

9.0

NA

Table 3-4 lists all 51 state CDBG programs, grouped by region, and demonstrates the effect of the new data on allocation amounts� As in chapter 2, this analysis uses the universe of actual FY 2011 grantees�

Any newly qualified entitlement grantees in FY 2012 will cause a decrease in funding for most other CDBG grantees� Although new entitlements can form out of urban counties or even entitlement cities, this more commonly affects state programs because they get credit only for nonentitled parts of the state (Richardson and Meehan, 2003)� Because of the 30 percent set-aside for nonentitled areas, the addition of a new entitlement has some strange effects� The state in which the new entitlement is located would lose funding for its nonentitlement program� All other entitlement grantees would lose a small amount, because more grantees would be sharing the same pot of 70 percent of the appropriations� However, other state programs would gain because the nonentitlement total for each variable would decrease� By decreasing the denominator in all formula calculations all states would have an increased share, except the state where the new entitlement is located�

16 Per capita funding is calculated with 2010 Census population counts in both Tables 3-2 and 3-3� Dollars per unit in Table 3-2 uses 2009

population estimates�

26

Table 3-4. State-by-State Effect of New Data on Allocations (Part 1) States

Formula

FY 2011 New Data Change (%) Population Poverty (%)

Over-

Pre-1940

Type

Grant

Grant

(%)

crowding

Housing

($000)

(%)

(%)

New England

CT

B

12,319

12,495

1.4

0.2

0.4

—

0.9

MA

B

30,463

31,113

2.1

– 0.1

– 0.4

—

2.6

ME

B

11,497

11,868

3.2

0.0

0.0

—

3.2

NH

B

8,394

8,682

3.4

– 0.1

1.3

—

2.3

RI

B

4,753

5,142

8.2

0.0

– 1.6

—

9.8

VT

B

6,743

6,966

3.3

0.0

0.4

—

2.9

New York/New Jersey

NJ

B

6,279

6,369

1.4

0.0

– 0.2

—

1.7

NY

B

44,032

45,004

2.2

0.1

– 0.5

—

2.6

Mid-Atlantic

DE

A

1,873

2,012

7.4

0.9

6.2

0.2

—

MD

B

7,340

7,463

1.7

0.3

– 0.5

—

1.9

PA

B

42,284

42,103

– 0.4

0.2

– 0.8

—

0.2

VA

Switch

17,861

18,477

3.4

6.6

21.2

20.8

– 45.2

WV

B

15,384

14,775

– 4.0

0.3

– 5.9

—

1.6

Southeast

AL

A

23,605

23,277

– 1.4

0.6

– 3.6

1.5

—

FL

A

24,841

25,804

3.9

0.6

2.8

0.5

—

GA

A

36,631

39,521

7.9

0.3

6.8

0.7

—

KY

A

24,941

25,876

3.7

0.0

– 1.7

5.4

—

MS

A

27,635

26,701

– 3.4

0.2

– 2.4

– 1.2

—

NC

A

41,132

45,975

11.8

0.5

8.0

3.2

—

SC

A

20,113

20,243

0.6

0.3

2.5

– 2.1

—

TN

A

24,450

27,666

13.2

0.3

7.1

5.7

—

Midwest

IL

B

29,385

29,509

0.4

0.2

1.8

—

– 1.5

IN

B

28,548

30,402

6.5

0.3

5.0

—

1.3

MI

B

32,656

34,028

4.2

0.1

5.7

—

– 1.6

MN

B

18,513

18,769

1.4

0.2

1.6

—

– 0.4

OH

B

43,395

44,889

3.4

0.2

2.8

—

0.5

WI

B

25,705

26,359

2.5

0.2

2.7

—

– 0.4

Table 3-4. State-by-State Effect of New Data on Allocations (Part 2) 27

States

Formula

FY 2011 New Data Change (%) Population Poverty (%)

Over-

Pre-1940

Type

Grant

Grant

(%)

crowding

Housing

($000)

(%)

(%)

Southwest

AR

A

17,627

18,299

3.8

0.4

– 0.1

3.5

—

LA

A

25,670

23,377

– 8.9

0.4

– 9.6

0.3

—

NM

A

13,018

9,453

– 27.4

0.4

– 8.0

– 19.7

—

OK

A

14,578

14,579

0.0

0.4

– 0.9

0.5

—

TX

A

66,605

65,939

– 1.0

0.6

– 1.4

– 0.2

—

Great Plains

IA

B

23,878

23,614

– 1.1

0.2

0.6

—

– 1.9

KS

B

15,291

15,268

– 0.2

0.2

– 0.1

—

– 0.2

MO

Switch

21,614

22,471

4.0

5.4

23.5

24.0

– 48.9

NE

B

11,183

11,145

– 0.3

1.0

– 0.9

—

– 0.4

Rocky Mountain

CO

A

8,703

8,924

2.5

– 0.2

2.6

0.1

–

MT

B

6,260

6,165

– 1.5

0.5

– 3.2

—

1.2

ND

B

4,429

4,057

– 8.4

0.5

– 5.4

—

– 3.4

SD

B

6,049

5,921

– 2.1

0.1

– 2.7

—

0.4

UT

A

4,308

4,580

6.3

0.3

1.4

4.6

—

WY

B

2,957

2,872

– 2.9

0.9

– 7.2

—

3.4

Pacific/Hawaii

AZ

A

11,109

9,962

– 10.3

0.6

1.0

– 11.9

—

CA

A

35,842

33,527

– 6.5

0.1

– 3.3

– 3.3

—

HI

A

4,867

5,235

7.6

0.8

– 5.4

12.2

—

NV

A

2,543

2,488

– 2.2

0.2

5.9

– 8.2

—

Northwest/Alaska

AK

A

2,633

2,387

– 9.3

0.4

– 0.2

– 9.6

—

ID

A

7,927

8,276

4.4

0.3

3.9

0.1

—

OR

A

13,153

13,445

2.2

0.1

2.4

– 0.3

—

WA

A

14,094

13,590

– 3.6

0.1

0.9

– 4.6

—

Puerto Rico

PR

A

43,699

31,750

– 27.3

– 0.3

– 8.6

– 18.4

—

Two states are poised to switch formula types; Missouri and Virginia go from Formula B to Formula A and see their grants increase by 4 and 3�4 percent, respectively� The remaining 49 programs are split with 24

using Formula B and 25 using Formula A�

Some regional trends are quickly apparent� All state grantees in the New England region are Formula B

grantees, and all see their grants increase with the addition of new census and ACS data, primarily due to the increase in pre-1940 housing� Rhode Island has a particularly significant increase of 8�2 percent, the third largest percentage increase� A similar story can be seen in the Midwest, where all state grantees receive funds under Formula B and all grantees see their funding increase� However, driving the change in the Midwest is an increase in poverty rather than in pre-1940 housing�

28

The Southeast region has only Formula A grantees and almost all are poised to see their grants increase, including the two states with larger increases than Rhode Island—Tennessee (13�2 percent) and North Carolina (11�8 percent)� The changes in individual variables are mixed in the southeast, but the poverty variable is primarily driving funding changes in the states poised to receive larger grants�

In the Southwest—where all five states are Formula A grantees—a consistent decrease in the share of poverty is bringing grants down� The only two state programs slated to gain funding are Arkansas and Oklahoma, which offset their decreasing shares of poverty with increasing shares of population and overcrowding�

Two state programs have particularly severe decreases in funding� New Mexico and Puerto Rico experience 27�4 and 27�3 percent declines in funding largely as a result of substantial relative decreases in poverty and overcrowding� Other states that experience significant declines in funding are varied in geography and characteristics, although four out of five (all except North Dakota) are Formula A grantees: Arizona (-10�3 percent), Alaska (-9�3 percent), Louisiana (-8�9 percent), North Dakota (-8�4 percent), and California (-6�5 percent)�

As demonstrated in chapters 2 and 3, changes from the 2000 Census to the 2005–2009 ACS have significant implications for the CDBG formula allocations, particularly associated with certain variables�

CHAPTER

29

4CONFIRMING KEY TRENDS

Apparent declines in overcrowding and increases in pre-1940 housing are particularly substantial and surprising� In some cases we also observe large and unexpected changes from the 2009 population estimates used for the FY 2011 allocation to the 2010 Census population count that will be used for the FY 2012 allocation� This chapter investigates these key trends in an attempt to confirm their validity and to explore their possible causes�

Drop in Overcrowding

The most dramatic finding of this report is the nationwide decrease in levels of overcrowding and its significant effect on CDBG allocations� Ong and Ong (2009) note similar results in California between the 2000 Decennial Census and the 2005–2007 ACS 3-year estimates� Overcrowding decreased for households of all sizes and units of all sizes, although the greatest drop in California is for units with three or fewer rooms� A Census Bureau report comparing the 2000 Census with ACS 3-year estimates for a sample of counties and tracts also finds differences in overcrowding, and concludes that they may be driven by differences in number of rooms reported, as household size is quite similar between the two surveys�

Table 4-1 presents figures from the 2000 Census and the 2005–2009 ACS on the components of overcrowding, which HUD defines as greater than one person per room� Between the 2000 Census and the 2005–2009 ACS, overcrowding rates drop from 5�7 to 3�0 percent� This change constitutes a drop of 47�7 percent, and is nearly identical for both owner-occupied and renter-occupied units� It appears that both elements of overcrowding, household size and rooms per unit, contribute to the negative change in overcrowding between the two surveys� There is a modest increase in the percentage of small households (with one or two people), and a decrease in the percentage of households of all other sizes� The most substantial decrease is among the largest households: the percentage of households with seven or more people is 18�4 percent lower in the 2005–2009 ACS than in the 2000 Census� The median number of rooms per unit increases only slightly, from 5�3 to 5�4� However, a much smaller portion of households reported having only one or two rooms in the 2005–2009 ACS, and the percentage of units with four or more rooms increased� The largest changes are in units with one room (from 2�2 to 1�4 percent of all units), two rooms (from 4�8 to 2�8 percent of all units), and with nine or more rooms (from 7�7 to 9�2 percent of all units)� According to the American Housing Survey (AHS), overcrowding in the period from 2000 to 2009 was generally around 2�3 percent, suggesting that the ACS estimate is more accurate than the 2000

Census estimate�17

17 Table 2-3 of the AHS reports a rate of overcrowding of 2�3 percent in 2001, 2�4 percent in 2003, 2�4 percent in 2005, 2�5 percent in 2007, and 2�2 percent in 2009�

30

Table 4-1. Change in Overcrowding, 2000 Census Compared With 2005–2009 ACS

2000 Census

2005–2009 ACS

% Change

(%)

(%)

Overcrowded units

5�7

3�0

– 47�7

Owner occupied

3.1

1.6

– 47.4

Renter occupied

11.0

5.8

– 47.0

Household size (mean)

2�59

2�60

0�4

1 person

25.8

27.3

5.9

2 people

32.6

33.4

2.3

3 people

16.5

15.9

– 3.7

4 people

14.2

13.6

– 4.0

5 people

6.7

6.2

– 7.5

6 people

2.5

2.2

– 11.0

7 or more people

1.6

1.3

– 18.4

Unit size (median rooms)

5�3

5�4

1�9

1 room

2.2

1.4

– 36.8

2 rooms

4.8

2.8

– 42.3

3 rooms

9.8

9.1

– 7.9

4 rooms

16.0

17.0

6.6

5 rooms

20.9

21.2

1.7

6 rooms

18.5

18.7

1.3

7 rooms

12.1

12.4

2.5

8 rooms

8.1

8.3

2.5

9 or more rooms

7.7

9.2

18.9

Increase in Pre-1940 Housing

The increase in pre-1940 housing units is surprising because if these data were true population parameters, such an increase would hardly be possible� Pre-1940 structures can be removed from the housing stock through demolition, but can be added in only a few circumstances� If a pre-1940 housing structure is renovated and additional units are added (such as splitting a four-bedroom apartment into two, two-bedroom apartments), the number of pre-1940 housing units would increase� Also, because the census and ACS do not survey nonresidential buildings, converting an old industrial or commercial building to residential use could increase the number of pre-1940 housing units� These scenarios may explain part of the apparent increase in pre-1940 housing, but it is likely that the number of pre-1940 units removed from the housing stock each year substantially exceeds the number of pre-1940 units added to the housing stock� This is confirmed by the Components of Inventory Change (CINCH) reports that HUD issues using data from the AHS� According to the authors’ analysis of CINCH reports, between 2001 and 2007, a total of 726,000 pre-1940 housing units were added to the national housing stock while 1,507,000 were removed from the housing stock� The net change of -781,000 suggests that the pre-1940 housing stock did not actually increase from the 2000 Census to the 2005–2009 ACS�

A more likely cause derives from the fact that both the 2000 Census and the 2005–2009 ACS are surveys, with varying degrees of error (both sampling and nonsampling)� A Census Bureau report in 2004

compared 2000 Census figures with 2005–2007 ACS figures and found the ACS consistently reported higher levels of pre-1940 housing (Diffendal et al�, 2004)� Similarly, the C2SS ascribes a larger portion of the housing stock to pre-1940 construction than the decennial census did� The difference is not as large (1�3 percentage points) as seen in the change from 2000 Census data to the 2005–2009 ACS estimates; however, wide variation existed across counties� The Census Bureau found significant differences in 9 of 31

the 18 counties studied, and the differences ranged from a Census 2000 estimate that was 0�2 percentage points higher in Broward, Florida, to 11�6 percentage points lower in the Bronx, New York (Love et al�, 2004)� Salvo et al� (2007) compare ACS estimates in the Bronx with administrative data sources and find that the administrative data show even higher levels of pre-1940s housing than that captured by the ACS, but that the ACS estimates are much closer than the 2000 Census estimates�

Possible Causes for Discrepancies Between Census and ACS Data As discussed in chapter 1, the year-round administration of the ACS combined with the “current residence” rule, means that the population responding to the ACS and the population that responded to the 2000

Census are not exactly the same� This could broadly affect places with large concentrations of vacation homes or students (Love et al�, 2004)� Communities and states where many people live only a few months of the year see their characteristics become more reflective of the part-time residents (and their housing units), while the communities and states where those people come from (their “usual residence”) see their characteristics become less reflective of the part-time residents� The different levels of publicity for each survey may also influence who responds� The decennial census is more publicized and may elicit a better response rate than the ACS, particularly from hard-to-reach populations�

Perhaps the most likely cause of the apparent changes in overcrowding and pre-1940 housing is the level of nonsampling error in the two surveys� The Census Bureau believes that historically there has been confusion about how to correctly respond to the question of how many rooms are in a housing unit, based on discrepancies between the number of bedrooms and the total number of rooms reported in a housing unit (Woodward et al�, 2007)� Questions that confuse or mislead respondents are more problematic for the census than the ACS, because the census relies more on mail-in responses� The ACS extensively uses telephone and in-person interviewers who are able to explain to respondents what does and does not count as a “room�” Similarly, it is possible that households in old multifamily buildings do not know exactly when their building was built� Evidence from the C2SS suggests that interviewers visiting vacant units found higher levels of pre-1940 housing and more rooms per unit than would be expected based on 2010

Census data (Love et al, 2004)�18 This would lead the ACS to indicate higher (and more accurate) levels of pre-1940 housing units than the census indicates�

The Census Bureau cautions data users from comparing estimates from the decennial census and the ACS�

This guidance is particularly emphasized when questions on a subject change� After an ACS Content Test in 2006 indicated widespread underreporting of rooms the Census Bureau changed the rooms question to improve accuracy� As a result, the Census Bureau recommends comparing the ACS and census measures of overcrowding “with caution” (U�S� Census Bureau, 2010)�

Population Changes

In several places, the 2010 Census yields population counts substantially different from the 2009

population estimates—usually suggesting population declines from 2009 to 2010� Fulton County, Georgia, had a population of 298,408 according to the Census Bureau’s 2009 population estimates, but only 271,536 according to the 2010 Census� In Puerto Rico, all 27 entitlement communities and the state program are poised to lose funding from introducing the new data into the CDBG formula, partly because the 2009 population estimates are higher than the 2010 Census count for every Puerto Rico grantee�

Everywhere except Puerto Rico, the annual population estimates are constructed in part using data from the National Center for Health Statistics (NCHS) on the number of births� According to the Census Bureau, NCHS data generally indicate a larger population of young children than what is counted by the decennial 18 See chapter 1 for an explanation of the Census 2000 Supplementary Survey (C2SS)�

32

Census� This creates discrepancies between the annual estimates and the Census that are compounded annually to create the largest difference at the end of a decade� Despite this common issue, the national population estimate and most state estimates for 2010 aligned closely with the 2010 Census� The 2010

population estimates use the same methodology as all annual estimates, and so differences between this estimate and the census provide an indication of the reliability of prior-year estimates� Nationally, the population estimate predicted 232,406 more people than the census counted in 2010, or 0�075 percent more� This represents a significant improvement over the previous decade’s annual population estimates, which undercounted the population on April 1, 2000, by more than 6�8 million (Cohn, 2011)� The Pew Research Center conducted an analysis of state population estimates using similar (but not identical) methodology as the Census Bureau to predict 2010 estimates� They found that the estimates differed from the census by more than 2 percent for only six states, not including Puerto Rico, and the largest difference was found in Arizona, where the population estimate was 4�6 percent higher than the census count (Cohn, 2011)�

The Census Bureau estimates Puerto Rico’s population using data on births and deaths from the Puerto Rico Planning Board, instead of the NCHS� Migration is also estimated differently; the Census Bureau estimates total migration in the previous decade as the difference in projected population for 2000 and actual population for 2000, then derives an annual rate, which is applied to each year between 2000 and 2010�

This method assumes a constant rate of migration each decade (1990 to 2000 and 2000 to 2010), which may not be accurate� An increase in emigration after 2000 would cause annual population estimates to be inflated relative to the true population�

Funding to entitlement grantees is based on smaller area population estimates, which incorporate data on housing units to allocate population� For the 2009 population estimates, housing unit counts had to be estimated using vacancy rates and household size from the 2000 Census� If occupancy rates or household size changed differently within a county from the Census 2000, the population estimates of those jurisdictions may have been distorted� Some speculation exists that changes in vacancy rates since the 2000 Census are one possible cause for the drop in population in urban areas at the 2010 Census (Exner, 2011)� Vacancy rates increase across the country between the 2000 and 2010 Census; among CDBG

grantees, the average increase is 2�8 percentage points� As shown in Table 4-2, vacancy increases more in entitlement cities than in other types of jurisdictions� Jurisdictions that experience a greater increase in vacancy rates, especially compared with their county as a whole, may have inflated population estimates for 2009�19

Table 4-2. Average Increase in Vacancy Rate Among CDBG Grantees Grantee Type

Increase in Vacancy Rate

(percentage points)

Principal cities

3.0

Satellite cities

2.9

Urban counties

2.5

Nonentitlements

2.0

Total

2.8

19 Vacancy rates are calculated from the ACS 2005–2009 5-year average� Grantees from Wyoming are not included�

CONCLUSION

33

This report demonstrates the effects of incorporating updated data from the Census Bureau into the Community Development Block Grant formula� These data partially represent changes that have occurred since the 2000 Census in communities across the country� The study observes small population growth, considerable growth in poverty, and the extension of poverty from principal cities to the suburbs (satellite cities and urban counties) and beyond (nonentitlement areas)� In addition to presenting those very real changes, this report also highlights the challenge of making the transition from the decennial census to the American Community Survey as the basis of nationwide formula allocations� Sharp breaks in several variables are at least partially attributable to changes between the surveys� Many grantees will have their funding cut as a result, while others will get an unexpected increase�

The ACS methodology has been rigorously tested and justified� The benefits that the ACS offers—

particularly its low nonsampling error and annual updates—are substantial, and the ACS is rightfully the authoritative and comprehensive data source from the Census Bureau� The allocation changes described in this report are substantial for some grantees, but FY 2012 may be the last time such drastic changes occur as the result of new data�20 By using annual updates of the ACS 5-year estimates, HUD expects future allocations to be stable and accurately reflect conditions in CDBG communities across the country�

20 In FY 2013 HUD will use ACS 2006-2010 estimates, which will be weighted to match population totals from the 2010 Census� This reweighting may cause slight funding shifts�

34

ACKNOWLEDGEMENTS

The authors thank Abubakari Zuberi in the U�S� Department of Housing and Urban Development (HUD) Office of Community Planning and Development (CPD) for assembling the data for this report—a monumental task that should not go unnoticed� The authors also thank Dwight Jefferson, Barry Steffen, Peter Kahn, Kurt Usowski, and Kevin Neary of HUD’s Office of Policy Development and Research (PD&R) and Steve Johnson of CPD for their thoughtful comments and suggestions� Finally, the authors thank Todd Richardson from PD&R and Bob Meehan, formerly of CPD, because this study borrowed heavily from their 2003 report that studied the effects of introducing 2000 Census data into the CDBG formula�

Any errors and omissions that remain in the report are those of the authors, not of those who have contributed, nor of the Department�

The contents of this report are the views of the authors and do not necessarily reflect the views or policies of the U�S� Department of Housing and Urban Development or the U�S� Government�

REFERENCES

35

Bunce, Harold L� 1976� An Evaluation of the Community Development Block Grant Formula� Washington, DC: U�S� Department of Housing and Urban Development�

Bunce, Harold L�, and Robert L� Goldberg� 1979� City Need and Community Development Funding�

Washington, DC: U�S� Department of Housing and Urban Development�

Bunce, Harold L�, Sue G� Neal, and John L� Gardner� 1983� Effects of the 1980 Census on Community Development Funding� Washington, DC: U�S� Department of Housing and Urban Development�

Diffendal, Gregg J�, Rita Jo Petroni, and Andre L� Williams� 2004� Meeting 21st Century Demographic Data Needs—Implementing the American Community Survey Report 8: Comparison of the American Community Survey Three-Year Averages and the Census Sample for a Sample of Counties and Tracts�

Washington, DC: U�S� Census Bureau�

Exner, Rich� 2011� Census Bureau’s 2009 Population Estimate for Cleveland Was Way Off Mark: Behind the Numbers� Available at http://www�cleveland�com/datacentral/index�ssf/2011/03/census_

bureaus_2009_population�html� (Accessed July 2011)�

Government Accountability Office (GAO)� 2004� Metropolitan Statistical Areas: New Standards and Their Impact on Selected Federal Programs� Washington, DC: Government Accountability Office�

Love, Susan P�, Joan K� Broadwater, Deborah H� Griffin, Theresa F� Leslie, and David A� Raglin� 2004�

Meeting 21st Century Demographic Data Needs—Implementing the American Community Survey Report 10: Comparing Selected Physical and Financial Characteristics of Housing With the Census 2000�

Washington, DC: U�S� Census Bureau�

Ong, Paul, and Jonathan Ong� 2009� Dramatic Decline in Household Overcrowding? An Analysis of California and Los Angeles� Los Angeles: UCLA School of Public Affairs�

Richardson, Todd, and Robert Meehan� 2003� Redistribution Effect of Introducing Census 2000 Data Into the CDBG Formula� Washington, DC: U�S� Department of Housing and Urban Development�

Salvo, Joseph J�, Arun Peter Lobo, Adam L� Willett, and Joel A� Alvarez� 2007� An Evaluation of the Quality and Utility of ACS Five Year Estimates for Bronx Census Tracts and Neighborhoods� New York: New York City Department of City Planning�

U�S� Census Bureau� 2010� Comparing 2009 American Community Survey Data� Available at http://

www�census�gov/acs/www/guidance_for_data_users/comparing_2009/� (Accessed July 2011)�

Woodward, Jeanne, Ellen Wilson, and John Chesnut� 2007� Evaluation Report Covering Rooms and Bedrooms� Washington, DC: U�S� Census Bureau�

U�S� Census Bureau� 2009� A Compass for Understanding and Using American Community Survey Data: What Researchers Need To Know� Washington, DC: U�S� Census Bureau�

36

ADDITIONAL READING

———� 2009� Design and Methodology: American Community Survey� Washington, DC: U�S� Census Bureau�

———� 2009� Methodology for the United States Resident Population Estimates by Age, Sex, Race, and Hispanic Origin (Vintage 2009): April 1, 2000 to July 1, 2009� Washington, DC: U�S� Census Bureau�

———� 2010� Methodology for the Puerto Rico Commonwealth and Municipio Population Estimates by Age and Sex (Vintage 2009): April 1, 2000 to July 1, 2009� Washington, DC: U�S� Census Bureau�

———� 2010� Methodology for the Subcounty Total Resident Population Estimates (Vintage 2009): April 1, 2000 to July 1, 2009� Washington, DC: U�S� Census Bureau�

———� 2002� National Intercensal Population Estimates Methodology� Washington, DC: U�S� Census Bureau� Available at http://www�census�gov/popest/archives/methodology/intercensal_nat_meth�pdf�

APPENDIX 1: HUD ADMINISTRATIVE REGIONS

37

Rocky Mountain

New York/

New Jersey

Northwest/Alaska

New

England

Midwest

Mid-

Great Plains

Atlantic

Pacific/Hawaii

Southwest

Southeast

Northwest/Alaska

Pacific/Hawaii

Puerto Rico

38

APPENDIX 2: ALL FY 2011 ENTITLEMENT JURISDICTIONS

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

1,708

553

497

657

A

AK

ANCHORAGE

New Data Grant

1,920

563

710

647

A

Change (%)

12.4

1.6

42.6

-1.6

FY 2011 Grant

599

115

337

147

B

AL

ANNISTON

New Data Grant

579

100

336

144

B

Change (%)

-3.2

-12.6

-0.4

-2.2

FY 2011 Grant

662

112

28

523

A

AL

AUBURN

New Data Grant

554

103

32

419

A

Change (%)

-16.4

-8.0

12.8

-19.8

FY 2011 Grant

637

168

317

151

B

AL

BESSEMER

New Data Grant

557

126

324

107

B

Change (%)

-12.4

-25.2

2.2

-29.2

FY 2011 Grant

6,022

1,231

3,544

1,247

B

AL

BIRMINGHAM

New Data Grant

6,235

1,061

3,693

1,481

B

Change (%)

3.6

-13.8

4.2

18.8

FY 2011 Grant

461

109

72

280

A

AL

DECATUR

New Data Grant

465

107

56

302

A

Change (%)

0.8

-1.6

-23.0

7.8

FY 2011 Grant

488

131

47

310

A

AL

DOTHAN

New Data Grant

494

126

49

319

A

Change (%)

1.2

-3.2

3.6

2.6

FY 2011 Grant

376

151

118

107

B

AL

FLORENCE

New Data Grant

360

76

22

262

A

Change (%)

-4.2

73.8

FY 2011 Grant

1,053

182

631

240

B

AL

GADSDEN

New Data Grant

955

153

617

186

B

Change (%)

-9.2

-16.0

-2.2

-22.6

FY 2011 Grant

262

141

48

73

A

AL

HOOVER

New Data Grant

303

157

39

107

A

Change (%)

15.8

11.6

-18.0

46.0

FY 2011 Grant

1,179

347

144

687

A

AL

HUNTSVILLE

New Data Grant

1,209

347

139

723

A

Change (%)

2.6

0.0

-3.6

5.2

FY 2011 Grant

1,851

688

195

967

A

AL

JEFFERSON

COUNTY

New Data Grant

1,839

697

243

899

A

Change (%)

-0.6

1.2

24.8

-7.2

39

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

2,608

866

1,189

553

B

AL

MOBILE

New Data Grant

2,416

732

1,183

501

B

Change (%)

-7.4

-15.4

-0.4

-9.4

FY 2011 Grant

1,792

411

277

1,103

A

AL

MOBILE COUNTY New Data Grant

1,817

418

340

1,060

A

Change (%)

1.4

1.6

22.6

-4.0

FY 2011 Grant

1,883

391

294

1,198

A

AL

MONTGOMERY

New Data Grant

1,739

397

250

1,092

A

Change (%)

-7.6

1.6

-15.0

-8.8

FY 2011 Grant

236

54

38

144

A

AL

OPELIKA

New Data Grant

254

51

27

176

A

Change (%)

7.6

-6.4

-29.2

22.6

FY 2011 Grant

851

180

88

583

A

AL

TUSCALOOSA

New Data Grant

959

174

63

721

A

Change (%)

12.6

-3.2

-27.8

23.6

FY 2011 Grant

174

71

33

70

A

AR

BENTONVILLE

New Data Grant

194

68

22

104

A

Change (%)

11.4

-4.4

-33.4

48.6

FY 2011 Grant

387

115

44

228

A

AR

CONWAY

New Data Grant

470

114

46

310

A

Change (%)

21.4

-1.2

4.2

36.4

FY 2011 Grant

594

149

76

368

A

AR

FAYETTEVILLE

New Data Grant

606

142

71

393

A

Change (%)

2.0

-4.8

-7.4

6.8

FY 2011 Grant

751

165

149

436

A

AR

FORT SMITH

New Data Grant

866

166

210

490

A

Change (%)

15.4

0.4

41.2

12.2

FY 2011 Grant

359

138

36

184

B

AR

HOT SPRINGS

New Data Grant

375

140

88

147

B

Change (%)

4.4

1.4

141.0

-20.2

FY 2011 Grant

247

61

43

143

A

AR

JACKSONVILLE

New Data Grant

237

55

38

145

A

Change (%)

-3.6

-10.6

-11.6

1.6

FY 2011 Grant

506

128

52

326

A

AR

JONESBORO

New Data Grant

587

130

106

351

A

Change (%)

16.0

1.4

105.0

7.6

FY 2011 Grant

1,506

371

233

901

A

AR

LITTLE ROCK

New Data Grant

1,499

373

231

895

A

Change (%)

-0.4

0.6

-1.2

-0.8

40

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

687

204

349

134

B

AR

NORTH LITTLE

ROCK

New Data Grant

651

234

312

104

B

Change (%)

-5.2

15.0

-10.6

-22.4

FY 2011 Grant

659

273

261

124

B

AR

PINE BLUFF

New Data Grant

606

241

268

97

B

Change (%)

-8.0

-11.6

2.4

-22.0

FY 2011 Grant

388

114

102

172

A

AR

ROGERS

New Data Grant

449

108

118

224

A

Change (%)

15.8

-5.4

15.6

30.2

FY 2011 Grant

473

132

140

200

A

AR

SPRINGDALE

New Data Grant

774

135

311

329

A

Change (%)

63.8

1.6

121.6

64.4

FY 2011 Grant

287

58

29

200

A

AR

TEXARKANA

New Data Grant

257

58

28

171

A

Change (%)

-10.4

-1.2

-1.2

-14.2

FY 2011 Grant

378

53

55

270

A

AR

WEST MEMPHIS

New Data Grant

388

51

63

275

A

Change (%)

2.8

-3.8

14.8

1.6

FY 2011 Grant

461

165

124

173

A

AZ

AVONDALE CITY

New Data Grant

677

147

201

329

A

Change (%)

46.8

-10.8

61.8

90.8

FY 2011 Grant

1,270

482

378

409

A

AZ

CHANDLER

New Data Grant

1,381

455

383

543

A

Change (%)

8.8

-5.6

1.2

32.6

FY 2011 Grant

559

117

134

308

A

AZ

FLAGSTAFF

New Data Grant

597

127

169

301

A

Change (%)

6.8

8.4

26.4

-2.4

FY 2011 Grant

655

429

100

125

A

AZ

GILBERT

New Data Grant

839

402

134

303

A

Change (%)

28.2

-6.4

33.8

142.2

FY 2011 Grant

2,011

490

618

903

A

AZ

GLENDALE

New Data Grant

2,336

437

766

1,132

A

Change (%)

16.2

-10.8

24.0

25.4

FY 2011 Grant

2,059

826

425

808

A

AZ

MARICOPA

COUNTY

New Data Grant

2,537

941

505

1,092

A

Change (%)

23.2

13.8

18.8

35.2

FY 2011 Grant

3,105

903

970

1,232

A

AZ

MESA

New Data Grant

3,561

846

1,111

1,603

A

Change (%)

14.6

-6.2

14.6

30.2

41

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

633

316

120

198

A

AZ

PEORIA CITY

New Data Grant

748

297

162

289

A

Change (%)

18.0

-5.8

35.0

46.0

FY 2011 Grant

15,471

3,081

5,169

7,221

A

AZ

PHOENIX

New Data Grant

16,681

2,787

5,549

8,345

A

Change (%)

7.8

-9.6

7.4

15.6

FY 2011 Grant

2,412

898

497

1,016

A

AZ

PIMA COUNTY

New Data Grant

2,715

865

595

1,255

A

Change (%)

12.6

-3.8

19.6

23.6

FY 2011 Grant

265

83

33

150

A

AZ

PRESCOTT

New Data Grant

250

77

26

147

A

Change (%)

-5.8

-7.0

-20.0

-2.0

FY 2011 Grant

1,053

460

184

410

A

AZ

SCOTTSDALE

New Data Grant

1,056

419

168

469

A

Change (%)

0.4

-8.8

-8.4

14.6

FY 2011 Grant

342

184

64

95

A

AZ

SURPRISE CITY

New Data Grant

503

227

89

188

A

Change (%)

47.2

23.0

40.6

98.4

FY 2011 Grant

1,463

345

348

770

A

AZ

TEMPE

New Data Grant

1,500

312

308

880

A

Change (%)

2.4

-9.6

-11.4

14.2

FY 2011 Grant

5,598

1,052

1,503

3,043

A

AZ

TUCSON

New Data Grant

5,723

1,003

1,536

3,184

A

Change (%)

2.2

-4.6

2.2

4.6

FY 2011 Grant

846

176

287

384

A

AZ

YUMA

New Data Grant

950

179

306

465

A

Change (%)

12.2

1.8

6.8

21.2

FY 2011 Grant

1,231

124

309

798

B

CA ALAMEDA

New Data Grant

1,142

118

265

758

B

Change (%)

-7.2

-4.8

-14.0

-5.0

FY 2011 Grant

1,758

500

723

536

A

CA ALAMEDA

COUNTY

New Data Grant

1,677

519

556

602

A

Change (%)

-4.6

3.8

-23.0

12.4

FY 2011 Grant

1,240

164

652

424

A

CA ALHAMBRA

New Data Grant

859

160

382

316

A

Change (%)

-30.8

-2.6

-41.4

-25.4

FY 2011 Grant

4,494

653

2,235

1,607

A

CA ANAHEIM

New Data Grant

4,575

648

2,642

1,284

A

Change (%)

1.8

-0.8

18.2

-20.0

42

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

653

196

188

270

A

CA ANTIOCH

New Data Grant

739

197

170

372

A

Change (%)

13.2

0.8

-9.4

37.6

FY 2011 Grant

575

136

113

327

A

CA APPLE VALLEY

New Data Grant

652

133

121

398

A

Change (%)

13.4

-1.6

7.2

21.6

FY 2011 Grant

3,034

627

867

1,540

A

CA BAKERSFIELD

New Data Grant

3,372

670

1,091

1,611

A

Change (%)

11.2

6.8

25.8

4.6

FY 2011 Grant

1,325

149

700

476

A

CA BALDWIN PARK

New Data Grant

1,171

145

642

384

A

Change (%)

-11.6

-2.4

-8.2

-19.4

FY 2011 Grant

1,067

141

526

400

A

CA BELLFLOWER

New Data Grant

890

148

465

277

A

Change (%)

-16.6

4.8

-11.6

-30.8

FY 2011 Grant

2,941

411

803

1,726

B

CA BERKELEY

New Data Grant

2,598

306

661

1,631

B

Change (%)

-11.6

-25.6

-17.6

-5.4

FY 2011 Grant

912

154

450

308

A

CA BUENA PARK

New Data Grant

801

155

422

223

A

Change (%)

-12.2

0.6

-6.2

-27.4

FY 2011 Grant

1,056

221

404

431

B

CA BURBANK

New Data Grant

1,012

152

386

474

B

Change (%)

-4.2

-31.2

-4.6

9.8

FY 2011 Grant

323

124

93

106

A

CA CAMARILLO

New Data Grant

309

126

93

91

A

Change (%)

-4.2

1.6

-0.4

-14.2

FY 2011 Grant

461

190

110

161

A

CA CARLSBAD

New Data Grant

455

203

105

146

A

Change (%)

-1.4

6.8

-4.6

-9.0

FY 2011 Grant

985

178

518

289

A

CA CARSON

New Data Grant

787

177

385

225

A

Change (%)

-20.2

-0.8

-25.6

-22.2

FY 2011 Grant

343

99

154

90

A

CA CERRITOS

New Data Grant

266

95

85

86

A

Change (%)

-22.4

-4.4

-45.0

-3.8

FY 2011 Grant

873

164

134

575

A

CA CHICO

New Data Grant

862

166

130

566

A

Change (%)

-1.4

1.2

-3.2

-1.6

43

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

565

160

230

175

A

CA CHINO

New Data Grant

490

150

221

119

A

Change (%)

-13.2

-6.2

-3.6

-32.2

FY 2011 Grant

380

143

117

120

A

CA CHINO HILLS

New Data Grant

339

144

103

92

A

Change (%)

-10.8

1.0

-12.0

-24.0

FY 2011 Grant

1,814

433

736

646

A

CA CHULA VISTA

New Data Grant

1,841

470

758

613

A

Change (%)

1.4

8.8

3.0

-5.2

FY 2011 Grant

578

164

171

244

A

CA CITRUS HEIGHTS

New Data Grant

598

161

166

272

A

Change (%)

3.4

-1.8

-2.6

11.2

FY 2011 Grant

583

180

150

253

A

CA CLOVIS CITY

New Data Grant

595

184

140

271

A

Change (%)

2.0

2.2

-6.6

7.0

FY 2011 Grant

1,859

182

771

906

A

CA COMPTON

New Data Grant

1,778

186

930

662

A

Change (%)

-4.4

2.4

20.6

-27.0

FY 2011 Grant

921

236

363

322

A

CA CONCORD

New Data Grant

942

235

366

340

A

Change (%)

2.2

-0.4

1.0

5.8

FY 2011 Grant

3,119

1,132

931

1,055

A

CA CONTRA COSTA

COUNTY

New Data Grant

3,093

1,144

833

1,116

A

Change (%)

-0.8

1.0

-10.6

5.8

FY 2011 Grant

1,082

292

430

360

A

CA CORONA

New Data Grant

1,202

294

539

370

A

Change (%)

11.0

0.6

25.2

2.6

FY 2011 Grant

1,228

213

542

472

A

CA COSTA MESA

New Data Grant

1,177

212

557

409

A

Change (%)

-4.2

-0.6

2.6

-13.6

FY 2011 Grant

353

105

160

88

A

CA CUPERTINO CITY

New Data Grant

348

112

168

68

A

Change (%)

-1.4

7.2

5.2

-23.2

FY 2011 Grant

1,120

198

667

256

A

CA DALY CITY

New Data Grant

1,011

195

630

186

A

Change (%)

-9.6

-1.2

-5.4

-27.4

FY 2011 Grant

729

122

111

496

A

CA DAVIS

New Data Grant

670

127

86

458

A

Change (%)

-8.0

4.0

-22.6

-7.6

44

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

747

102

308

336

A

CA DELANO CITY

New Data Grant

652

102

235

314

A

Change (%)

-12.8

0.2

-23.8

-6.6

FY 2011 Grant

1,337

207

717

412

A

CA DOWNEY

New Data Grant

1,169

215

621

332

A

Change (%)

-12.6

4.0

-13.4

-19.4

FY 2011 Grant

1,129

183

402

544

A

CA EL CAJON

New Data Grant

1,121

192

415

514

A

Change (%)

-0.6

5.0

3.2

-5.4

FY 2011 Grant

608

80

232

296

A

CA EL CENTRO

New Data Grant

530

82

197

251

A

Change (%)

-12.8

3.0

-15.4

-15.0

FY 2011 Grant

2,435

235

1,147

1,053

A

CA EL MONTE

New Data Grant

2,207

219

1,237

751

A

Change (%)

-9.4

-6.8

7.8

-28.6

FY 2011 Grant

455

262

87

106

A

CA ELK GROVE

New Data Grant

763

295

199

268

A

Change (%)

67.6

12.8

128.8

152.2

FY 2011 Grant

364

119

96

148

A

CA ENCINITAS

New Data Grant

310

115

76

119

A

Change (%)

-14.6

-3.6

-20.8

-19.6

FY 2011 Grant

1,568

271

672

625

A

CA ESCONDIDO

New Data Grant

1,547

277

700

569

A

Change (%)

-1.4

2.4

4.2

-8.8

FY 2011 Grant

738

200

239

299

A

CA FAIRFIELD

New Data Grant

738

203

235

300

A

Change (%)

0.0

1.4

-1.6

0.4

FY 2011 Grant

1,909

363

801

744

A

CA FONTANA

New Data Grant

1,983

378

936

669

A

Change (%)

4.0

4.0

16.8

-10.0

FY 2011 Grant

316

108

126

83

A

CA FOUNTAIN

VALLEY

New Data Grant

304

107

101

97

A

Change (%)

-3.8

-1.2

-19.8

17.2

FY 2011 Grant

1,498

397

717

384

A

CA FREMONT

New Data Grant

1,277

413

545

319

A

Change (%)

-14.8

3.8

-24.0

-17.0

FY 2011 Grant

6,891

928

2,105

3,858

A

CA FRESNO

New Data Grant

6,424

954

2,290

3,180

A

Change (%)

-6.8

2.8

8.8

-17.6

45

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

3,588

578

1,266

1,744

A

CA FRESNO COUNTY New Data Grant

3,576

575

1,453

1,549

A

Change (%)

-0.4

-0.6

14.8

-11.2

FY 2011 Grant

1,363

256

609

498

A

CA FULLERTON

New Data Grant

1,426

261

756

410

A

Change (%)

4.6

1.6

24.2

-17.8

FY 2011 Grant

2,344

322

1,221

801

A

CA GARDEN GROVE New Data Grant

2,174

329

1,201

643

A

Change (%)

-7.2

2.4

-1.6

-19.8

FY 2011 Grant

827

113

400

315

A

CA GARDENA

New Data Grant

678

113

299

266

A

Change (%)

-18.0

0.6

-25.2

-15.6

FY 2011 Grant

445

97

198

149

A

CA GILROY CITY

New Data Grant

374

94

165

115

A

Change (%)

-16.0

-3.0

-17.0

-23.2

FY 2011 Grant

2,949

381

1,516

1,052

A

CA GLENDALE

New Data Grant

2,173

370

1,083

720

A

Change (%)

-26.4

-2.8

-28.6

-31.6

FY 2011 Grant

301

96

105

100

A

CA GLENDORA CITY

New Data Grant

221

97

63

61

A

Change (%)

-26.8

0.4

-40.0

-38.8

FY 2011 Grant

242

57

101

84

A

CA GOLETA

New Data Grant

216

58

83

75

A

Change (%)

-10.8

0.8

-17.8

-10.4

FY 2011 Grant

487

97

142

248

A

CA HANFORD

New Data Grant

467

104

158

205

A

Change (%)

-4.2

7.6

11.0

-17.4

FY 2011 Grant

1,541

162

785

593

A

CA HAWTHORNE

New Data Grant

1,317

163

724

430

A

Change (%)

-14.6

0.2

-7.8

-27.6

FY 2011 Grant

1,554

279

787

488

A

CA HAYWARD

New Data Grant

1,389

278

633

478

A

Change (%)

-10.6

-0.4

-19.6

-2.0

FY 2011 Grant

635

139

167

330

A

CA HEMET

New Data Grant

783

152

262

368

A

Change (%)

23.2

9.2

57.4

11.8

FY 2011 Grant

666

167

191

308

A

CA HESPERIA

New Data Grant

919

174

294

452

A

Change (%)

38.0

4.4

53.8

46.6

46

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

1,234

374

423

438

A

CA HUNTINGTON

BEACH

New Data Grant

1,060

366

337

357

A

Change (%)

-14.0

-2.0

-20.2

-18.6

FY 2011 Grant

1,438

117

780

541

A

CA HUNTINGTON

PARK

New Data Grant

1,422

112

874

436

A

Change (%)

-1.2

-4.4

12.0

-19.4

FY 2011 Grant

864

164

334

366

A

CA INDIO CITY

New Data Grant

1,018

147

452

419

A

Change (%)

17.8

-10.8

35.6

14.4

FY 2011 Grant

2,010

217

914

879

A

CA INGLEWOOD

New Data Grant

1,657

211

838

607

A

Change (%)

-17.6

-2.6

-8.2

-31.0

FY 2011 Grant

1,210

405

369

435

A

CA IRVINE

New Data Grant

1,292

409

356

526

A

Change (%)

6.8

1.0

-3.4

21.0

FY 2011 Grant

4,767

764

1,463

2,540

A

CA KERN COUNTY

New Data Grant

5,062

777

1,844

2,440

A

Change (%)

6.2

1.8

26.2

-4.0

FY 2011 Grant

733

115

350

268

A

CA LA HABRA

New Data Grant

748

116

447

184

A

Change (%)

2.0

1.2

27.8

-31.2

FY 2011 Grant

398

107

112

178

A

CA LA MESA

New Data Grant

378

110

91

177

A

Change (%)

-5.0

2.4

-19.2

-0.4

FY 2011 Grant

303

125

90

88

A

CA LAGUNA NIGUEL New Data Grant

260

121

40

99

A

Change (%)

-14.0

-2.8

-55.8

13.0

FY 2011 Grant

432

147

170

116

A

CA LAKE FOREST

New Data Grant

465

149

204

112

A

Change (%)

7.6

1.6

20.0

-3.4

FY 2011 Grant

647

151

292

205

A

CA LAKEWOOD

New Data Grant

495

154

230

111

A

Change (%)

-23.4

2.2

-21.2

-45.6

FY 2011 Grant

1,245

282

321

641

A

CA LANCASTER

New Data Grant

1,553

302

426

825

A

Change (%)

24.8

7.2

32.6

28.6

FY 2011 Grant

414

157

121

137

A

CA LIVERMORE

New Data Grant

395

156

107

132

A

Change (%)

-4.8

-0.4

-11.6

-3.8

47

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

676

119

227

330

A

CA LODI

New Data Grant

706

120

306

280

A

Change (%)

4.6

0.8

34.8

-15.0

FY 2011 Grant

7,806

894

3,273

3,638

A

CA LONG BEACH

New Data Grant

6,779

891

3,302

2,585

A

Change (%)

-13.2

-0.4

0.8

-29.0

FY 2011 Grant

64,578

7,408

28,998

28,172

A

CA LOS ANGELES

New Data Grant

59,056

7,312

30,243

21,500

A

Change (%)

-8.6

-1.2

4.2

-23.6

FY 2011 Grant

26,692

4,400

11,666

10,626

A

CA LOS ANGELES

COUNTY

New Data Grant

23,554

4,375

11,193

7,985

A

Change (%)

-11.8

-0.6

-4.0

-24.8

FY 2011 Grant

1,417

135

725

557

A

CA LYNWOOD

New Data Grant

1,260

135

734

391

A

Change (%)

-11.0

-0.2

1.2

-29.8

FY 2011 Grant

876

110

277

490

A

CA MADERA

New Data Grant

964

118

442

404

A

Change (%)

10.0

8.0

59.6

-17.6

FY 2011 Grant

1,441

485

407

549

A

CA MARIN COUNTY

New Data Grant

1,307

487

358

463

A

Change (%)

-9.2

0.4

-12.2

-15.6

FY 2011 Grant

1,130

147

367

615

A

CA MERCED

New Data Grant

1,065

152

323

590

A

Change (%)

-5.6

3.2

-12.0

-4.0

FY 2011 Grant

533

131

297

105

A

CA MILPITAS CITY

New Data Grant

438

129

194

115

A

Change (%)

-17.8

-2.0

-34.4

9.4

FY 2011 Grant

441

183

136

122

A

CA MISSION VIEJO

New Data Grant

442

180

148

114

A

Change (%)

0.2

-1.6

9.4

-7.0

FY 2011 Grant

2,109

392

684

1,033

A

CA MODESTO

New Data Grant

1,910

388

593

930

A

Change (%)

-9.4

-1.0

-13.4

-10.0

FY 2011 Grant

944

119

458

367

A

CA MONTEBELLO

New Data Grant

804

120

412

271

A

Change (%)

-14.8

1.0

-10.0

-26.2

FY 2011 Grant

252

44

77

131

B

CA MONTEREY

New Data Grant

215

46

73

95

B

Change (%)

-15.0

4.0

-4.6

-27.4

48

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

874

119

427

327

A

CA MONTEREY PARK New Data Grant

646

116

302

228

A

Change (%)

-26.0

-2.4

-29.4

-30.4

FY 2011 Grant

1,619

371

540

708

A

CA MORENO VALLEY New Data Grant

2,083

373

898

813

A

Change (%)

28.8

0.6

66.4

14.8

FY 2011 Grant

619

140

313

167

A

CA MOUNTAIN

VIEW

New Data Grant

562

143

280

139

A

Change (%)

-9.2

2.2

-10.4

-16.8

FY 2011 Grant

615

146

244

225

A

CA NAPA CITY

New Data Grant

728

148

338

242

A

Change (%)

18.4

1.8

38.2

7.4

FY 2011 Grant

986

109

483

395

A

CA NATIONAL CITY

New Data Grant

873

113

405

355

A

Change (%)

-11.4

4.0

-16.0

-10.2

FY 2011 Grant

324

158

56

110

A

CA NEWPORT

BEACH

New Data Grant

393

164

86

143

A

Change (%)

21.4

4.0

53.6

30.0

FY 2011 Grant

1,384

198

762

424

A

CA NORWALK

New Data Grant

1,201

203

684

313

A

Change (%)

-13.2

2.6

-10.2

-26.2

FY 2011 Grant

7,579

1,614

1,786

4,179

B

CA OAKLAND

New Data Grant

8,141

1,247

1,951

4,943

B

Change (%)

7.4

-22.8

9.2

18.2

FY 2011 Grant

1,640

334

655

650

A

CA OCEANSIDE

New Data Grant

1,324

322

561

440

A

Change (%)

-19.2

-3.6

-14.4

-32.2

FY 2011 Grant

2,184

332

1,003

849

A

CA ONTARIO

New Data Grant

1,941

316

997

628

A

Change (%)

-11.0

-4.8

-0.6

-26.0

FY 2011 Grant

1,197

265

496

436

A

CA ORANGE

New Data Grant

1,276

263

673

341

A

Change (%)

6.6

-0.6

35.6

-22.0

FY 2011 Grant

3,390

991

1,276

1,123

A

CA ORANGE

COUNTY

New Data Grant

3,371

972

1,324

1,075

A

Change (%)

-0.6

-2.0

3.8

-4.2

FY 2011 Grant

2,472

363

1,213

897

A

CA OXNARD

New Data Grant

2,313

382

1,113

818

A

Change (%)

-6.4

5.2

-8.2

-8.8

49

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

320

100

87

132

A

CA PALM DESERT

New Data Grant

317

93

88

137

A

Change (%)

-0.6

-6.8

0.8

3.0

FY 2011 Grant

455

93

137

225

A

CA PALM SPRINGS

New Data Grant

349

86

105

158

A

Change (%)

-23.4

-7.8

-23.2

-29.8

FY 2011 Grant

1,357

278

436

643

A

CA PALMDALE

New Data Grant

1,460

295

447

719

A

Change (%)

7.6

5.8

2.4

11.8

FY 2011 Grant

607

59

230

318

B

CA PALO ALTO

New Data Grant

482

59

168

254

B

Change (%)

-20.6

0.4

-26.8

-20.0

FY 2011 Grant

199

51

35

113

A

CA PARADISE

New Data Grant

177

51

25

102

A

Change (%)

-11.2

-1.2

-29.6

-10.2

FY 2011 Grant

1,085

106

557

422

A

CA PARAMOUNT

CITY

New Data Grant

896

104

488

303

A

Change (%)

-17.4

-2.0

-12.4

-28.0

FY 2011 Grant

2,056

441

390

1,225

B

CA PASADENA

New Data Grant

1,967

343

452

1,172

B

Change (%)

-4.4

-22.2

15.8

-4.4

FY 2011 Grant

583

109

219

256

A

CA PERRIS CITY

New Data Grant

730

132

294

304

A

Change (%)

25.2

21.4

34.6

18.8

FY 2011 Grant

311

107

91

114

A

CA PETALUMA

New Data Grant

314

112

104

98

A

Change (%)

0.8

4.8

15.0

-14.0

FY 2011 Grant

816

122

418

276

A

CA PICO RIVERA

New Data Grant

725

121

427

176

A

Change (%)

-11.2

-0.2

2.0

-36.0

FY 2011 Grant

590

126

235

229

A

CA PITTSBURG

New Data Grant

605

122

241

243

A

Change (%)

2.6

-3.2

2.2

6.0

FY 2011 Grant

250

131

62

57

A

CA PLEASANTON

CITY

New Data Grant

269

136

67

67

A

Change (%)

8.0

3.8

8.0

17.4

FY 2011 Grant

2,552

295

1,162

1,095

A

CA POMONA

New Data Grant

2,278

287

1,282

709

A

Change (%)

-10.8

-2.4

10.4

-35.2

50

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

724

101

227

396

A

CA PORTERVILLE

New Data Grant

732

104

260

368

A

Change (%)

1.2

3.6

14.4

-7.2

FY 2011 Grant

627

122

208

297

A

CA RANCHO

CORDOVA CITY

New Data Grant

628

125

198

306

A

Change (%)

0.2

2.6

-4.8

2.8

FY 2011 Grant

919

332

272

315

A

CA RANCHO

CUCAMONGA

New Data Grant

902

319

336

247

A

Change (%)

-1.8

-4.0

23.6

-21.4

FY 2011 Grant

221

96

78

48

A

CA RANCHO SANTA

MARGARITA

New Data Grant

223

92

83

48

A

Change (%)

0.6

-3.6

6.8

-1.0

FY 2011 Grant

751

175

143

433

A

CA REDDING

New Data Grant

788

173

194

421

A

Change (%)

5.0

-1.0

35.4

-2.8

FY 2011 Grant

512

135

148

228

A

CA REDLANDS

New Data Grant

451

133

115

204

A

Change (%)

-11.8

-2.0

-22.8

-10.6

FY 2011 Grant

367

129

107

131

A

CA REDONDO

BEACH

New Data Grant

299

129

71

99

A

Change (%)

-18.6

-0.2

-34.0

-24.0

FY 2011 Grant

653

144

354

155

A

CA REDWOOD CITY

New Data Grant

759

148

382

229

A

Change (%)

16.2

2.8

7.8

47.4

FY 2011 Grant

1,196

191

450

555

A

CA RIALTO

New Data Grant

1,181

191

585

405

A

Change (%)

-1.2

0.2

30.0

-27.2

FY 2011 Grant

1,228

199

471

558

A

CA RICHMOND

New Data Grant

1,145

200

488

458

A

Change (%)

-6.8

0.2

3.6

-18.0

FY 2011 Grant

3,036

576

1,086

1,374

A

CA RIVERSIDE

New Data Grant

3,053

586

1,344

1,123

A

Change (%)

0.6

1.8

23.8

-18.2

FY 2011 Grant

8,045

2,127

2,453

3,465

A

CA RIVERSIDE

COUNTY

New Data Grant

8,635

2,219

3,036

3,379

A

Change (%)

7.4

4.4

23.8

-2.4

FY 2011 Grant

185

104

24

58

A

CA ROCKLIN CITY

New Data Grant

203

110

28

65

A

Change (%)

9.6

6.0

15.2

13.2

51

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

1,028

105

500

424

A

CA ROSEMEAD

New Data Grant

765

104

449

212

A

Change (%)

-25.6

-1.2

-10.2

-50.0

FY 2011 Grant

473

224

112

138

A

CA ROSEVILLE

New Data Grant

581

229

137

215

A

Change (%)

22.8

2.4

22.2

56.2

FY 2011 Grant

5,228

902

1,521

2,804

A

CA SACRAMENTO

New Data Grant

4,643

899

1,518

2,226

A

Change (%)

-11.2

-0.4

-0.2

-20.6

FY 2011 Grant

5,247

1,259

1,469

2,519

A

CA SACRAMENTO

COUNTY

New Data Grant

5,094

1,256

1,546

2,292

A

Change (%)

-3.0

-0.4

5.2

-9.0

FY 2011 Grant

2,223

279

1,111

833

A

CA SALINAS

New Data Grant

2,106

290

1,065

751

A

Change (%)

-5.2

4.0

-4.2

-9.8

FY 2011 Grant

3,245

384

1,073

1,788

A

CA SAN

BERNARDINO

New Data Grant

3,152

405

1,222

1,525

A

Change (%)

-2.8

5.6

14.0

-14.8

SAN

FY 2011 Grant

6,414

1,202

2,069

3,144

A

CA BERNARDINO

New Data Grant

6,516

1,214

2,407

2,895

A

COUNTY

Change (%)

1.6

1.0

16.4

-8.0

FY 2011 Grant

783

202

268

313

A

CA SAN

BUENAVENTURA

New Data Grant

827

205

294

328

A

Change (%)

5.6

1.6

9.6

4.6

FY 2011 Grant

358

119

107

132

A

CA SAN CLEMENTE

New Data Grant

358

122

105

131

A

Change (%)

0.0

2.8

-2.2

-0.8

FY 2011 Grant

13,603

2,526

5,010

6,068

A

CA SAN DIEGO

New Data Grant

11,999

2,521

4,494

4,984

A

Change (%)

-11.8

-0.2

-10.2

-17.8

FY 2011 Grant

4,245

1,185

1,379

1,682

A

CA SAN DIEGO

COUNTY

New Data Grant

3,772

1,193

1,173

1,406

A

Change (%)

-11.2

0.8

-15.0

-16.4

FY 2011 Grant

18,584

1,827

3,707

13,050

B

CA SAN FRANCISCO New Data Grant

18,181

1,645

3,703

12,833

B

Change (%)

-2.2

-10.0

-0.2

-1.6

FY 2011 Grant

2,526

630

809

1,087

A

CA SAN JOAQUIN

COUNTY

New Data Grant

2,639

639

913

1,087

A

Change (%)

4.4

1.4

12.8

0.0

52

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

9,151

1,865

4,522

2,764

A

CA SAN JOSE

New Data Grant

8,790

1,824

4,125

2,840

A

Change (%)

-4.0

-2.2

-8.8

2.8

FY 2011 Grant

656

152

327

177

A

CA SAN LEANDRO

New Data Grant

629

164

292

173

A

Change (%)

-4.2

7.8

-10.6

-2.4

FY 2011 Grant

1,887

479

434

974

A

CA SAN LUIS OBISPO

COUNTY

New Data Grant

1,909

485

475

948

A

Change (%)

1.2

1.2

9.6

-2.6

FY 2011 Grant

635

156

247

232

A

CA SAN MARCOS

CITY

New Data Grant

680

162

281

238

A

Change (%)

7.2

3.6

13.6

2.6

FY 2011 Grant

711

179

334

197

A

CA SAN MATEO

New Data Grant

727

187

365

175

A

Change (%)

2.4

4.4

9.2

-11.0

FY 2011 Grant

2,564

748

1,104

712

A

CA SAN MATEO

COUNTY

New Data Grant

2,780

732

1,250

797

A

Change (%)

8.4

-2.0

13.2

12.0

FY 2011 Grant

6,217

658

3,263

2,295

A

CA SANTA ANA

New Data Grant

6,368

626

4,028

1,714

A

Change (%)

2.4

-5.0

23.4

-25.4

FY 2011 Grant

970

167

387

417

A

CA SANTA BARBARA New Data Grant

888

170

367

351

A

Change (%)

-8.4

2.0

-5.0

-15.8

FY 2011 Grant

1,820

382

572

866

A

CA SANTA BARBARA

COUNTY

New Data Grant

1,741

384

637

720

A

Change (%)

-4.4

0.4

11.4

-16.8

FY 2011 Grant

979

217

489

274

A

CA SANTA CLARA

New Data Grant

886

225

365

297

A

Change (%)

-9.6

3.8

-25.4

8.2

FY 2011 Grant

1,585

288

790

507

B

CA SANTA CLARA

COUNTY

New Data Grant

1,500

287

790

422

B

Change (%)

-5.4

-0.2

0.0

-16.6

FY 2011 Grant

1,015

327

351

337

A

CA SANTA CLARITA

New Data Grant

1,215

340

496

379

A

Change (%)

19.8

4.0

41.4

12.6

FY 2011 Grant

551

110

147

294

A

CA SANTA CRUZ

New Data Grant

555

174

0

381

B

Change (%)

0.8

-40.8

53

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

1,148

168

459

521

A

CA SANTA MARIA

New Data Grant

1,316

192

691

433

A

Change (%)

14.6

14.2

50.6

-17.0

FY 2011 Grant

1,250

182

468

600

B

CA SANTA MONICA

New Data Grant

1,131

171

426

533

B

Change (%)

-9.6

-6.2

-9.0

-11.0

FY 2011 Grant

1,135

304

394

436

A

CA SANTA ROSA

New Data Grant

1,367

324

489

554

A

Change (%)

20.4

6.2

24.0

27.2

FY 2011 Grant

287

107

81

99

A

CA SANTEE

New Data Grant

303

103

79

121

A

Change (%)

5.2

-3.8

-3.0

21.8

FY 2011 Grant

368

66

168

134

A

CA SEASIDE

New Data Grant

386

64

224

98

A

Change (%)

5.0

-3.2

33.6

-27.0

FY 2011 Grant

650

234

190

227

A

CA SIMI VALLEY

New Data Grant

613

240

184

189

A

Change (%)

-5.8

2.4

-3.2

-16.6

FY 2011 Grant

1,788

501

559

727

A

CA SONOMA

COUNTY

New Data Grant

1,758

497

588

672

A

Change (%)

-1.6

-0.8

5.2

-7.6

FY 2011 Grant

1,895

186

1,062

648

A

CA SOUTH GATE

New Data Grant

1,772

182

1,086

504

A

Change (%)

-6.4

-2.2

2.4

-22.2

FY 2011 Grant

543

121

311

111

A

CA SOUTH SAN

FRANCISCO

New Data Grant

458

123

214

121

A

Change (%)

-15.8

1.0

-31.2

9.4

FY 2011 Grant

2,297

422

810

1,065

A

CA STANISLAUS

COUNTY

New Data Grant

2,212

428

782

1,001

A

Change (%)

-3.8

1.4

-3.4

-6.0

FY 2011 Grant

3,777

556

1,223

1,999

A

CA STOCKTON

New Data Grant

3,479

562

1,287

1,630

A

Change (%)

-7.8

1.2

5.2

-18.4

FY 2011 Grant

1,118

259

608

251

A

CA SUNNYVALE

New Data Grant

1,117

270

609

238

A

Change (%)

0.0

4.2

0.2

-5.2

FY 2011 Grant

607

239

167

201

A

CA THOUSAND

OAKS

New Data Grant

637

244

195

197

A

Change (%)

4.8

2.2

16.8

-2.0

54

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

1,054

271

472

310

A

CA TORRANCE

New Data Grant

871

280

331

260

A

Change (%)

-17.4

3.4

-30.0

-16.2

FY 2011 Grant

646

111

209

326

A

CA TULARE

New Data Grant

705

114

268

323

A

Change (%)

9.2

2.8

28.4

-0.8

FY 2011 Grant

673

133

230

310

A

CA TURLOCK

New Data Grant

542

132

165

245

A

Change (%)

-19.4

-0.6

-28.4

-20.8

FY 2011 Grant

731

140

391

200

A

CA TUSTIN

New Data Grant

658

146

332

181

A

Change (%)

-10.0

3.8

-15.0

-9.4

FY 2011 Grant

585

141

291

153

A

CA UNION CITY

New Data Grant

483

134

190

159

A

Change (%)

-17.4

-4.8

-34.8

4.4

FY 2011 Grant

636

141

209

286

A

CA UPLAND

New Data Grant

602

142

268

191

A

Change (%)

-5.4

0.8

28.6

-33.2

FY 2011 Grant

499

178

152

169

A

CA VACAVILLE

New Data Grant

462

178

111

173

A

Change (%)

-7.2

0.2

-26.8

2.6

FY 2011 Grant

1,051

222

422

408

A

CA VALLEJO

New Data Grant

1,017

224

335

459

A

Change (%)

-3.2

0.8

-20.6

12.6

FY 2011 Grant

1,806

392

748

666

A

CA VENTURA

COUNTY

New Data Grant

1,602

391

700

511

A

Change (%)

-11.2

-0.2

-6.4

-23.2

FY 2011 Grant

841

214

209

418

A

CA VICTORVILLE

New Data Grant

1,040

223

247

569

A

Change (%)

23.6

4.2

18.2

36.2

FY 2011 Grant

1,111

236

330

545

A

CA VISALIA

New Data Grant

1,133

240

365

528

A

Change (%)

2.0

1.6

10.6

-3.0

FY 2011 Grant

1,071

179

451

441

A

CA VISTA

New Data Grant

1,019

181

458

380

A

Change (%)

-4.8

1.0

1.4

-13.8

FY 2011 Grant

285

124

79

83

A

CA WALNUT CREEK

New Data Grant

258

124

49

86

A

Change (%)

-9.4

0.0

-37.8

3.6

55

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

775

99

370

306

A

CA WATSONVILLE

New Data Grant

827

99

444

284

A

Change (%)

6.8

0.0

19.8

-7.2

FY 2011 Grant

1,068

204

534

331

A

CA WEST COVINA

New Data Grant

991

205

460

326

A

Change (%)

-7.2

0.4

-13.8

-1.2

FY 2011 Grant

1,121

173

535

413

A

CA WESTMINSTER

New Data Grant

962

173

510

279

A

Change (%)

-14.2

-0.2

-4.6

-32.4

FY 2011 Grant

842

158

383

301

A

CA WHITTIER

New Data Grant

708

165

348

196

A

Change (%)

-16.0

4.0

-9.2

-34.8

FY 2011 Grant

527

107

216

204

A

CA WOODLAND

New Data Grant

457

107

188

162

A

Change (%)

-13.2

0.0

-13.0

-20.6

FY 2011 Grant

245

128

56

62

A

CA YORBA LINDA

New Data Grant

220

124

55

41

A

Change (%)

-10.4

-3.2

-1.6

-33.6

FY 2011 Grant

512

119

156

236

A

CA YUBA CITY

New Data Grant

556

125

190

241

A

Change (%)

8.6

5.2

21.4

1.8

FY 2011 Grant

1,359

413

395

551

A

CO ADAMS COUNTY New Data Grant

1,807

419

545

843

A

Change (%)

33.0

1.4

38.2

53.0

FY 2011 Grant

924

343

239

342

A

CO ARAPAHOE

COUNTY

New Data Grant

1,168

347

258

563

A

Change (%)

26.4

1.2

7.6

64.6

FY 2011 Grant

461

209

65

187

A

CO ARVADA

New Data Grant

491

205

82

204

A

Change (%)

6.6

-2.0

26.2

9.2

FY 2011 Grant

2,244

625

767

852

A

CO AURORA

New Data Grant

2,882

627

788

1,467

A

Change (%)

28.4

0.2

2.8

72.2

FY 2011 Grant

853

194

129

531

A

CO BOULDER

New Data Grant

897

188

92

617

A

Change (%)

5.2

-3.0

-28.2

16.2

FY 2011 Grant

204

108

40

56

A

CO BROOMFIELD

CITY/COUNTY

New Data Grant

207

108

19

81

A

Change (%)

1.4

-0.4

-53.6

44.6

56

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

273

194

18

60

A

CO CENTENNIAL

New Data Grant

335

194

18

123

A

Change (%)

22.4

-0.4

-4.0

104.0

FY 2011 Grant

2,328

773

472

1,083

A

CO COLORADO

SPRINGS

New Data Grant

2,605

803

469

1,333

A

Change (%)

11.8

3.8

-0.6

23.0

FY 2011 Grant

7,940

1,642

1,645

4,652

B

CO DENVER

New Data Grant

7,804

1,844

1,690

4,270

B

Change (%)

-1.8

12.2

2.8

-8.2

FY 2011 Grant

758

557

71

130

A

CO DOUGLAS

COUNTY

New Data Grant

850

550

72

228

A

Change (%)

12.2

-1.2

1.6

74.6

FY 2011 Grant

844

376

149

318

A

CO EL PASO COUNTY New Data Grant

977

377

165

435

A

Change (%)

15.8

0.0

10.4

37.0

FY 2011 Grant

923

268

98

557

A

CO FORT COLLINS

New Data Grant

1,096

278

62

757

A

Change (%)

18.6

3.4

-37.0

35.8

FY 2011 Grant

329

113

47

169

A

CO GRAND

JUNCTION

New Data Grant

417

113

59

245

A

Change (%)

26.8

0.0

26.4

44.8

FY 2011 Grant

790

179

172

439

A

CO GREELEY

New Data Grant

894

179

155

560

A

Change (%)

13.2

0.0

-9.8

27.4

FY 2011 Grant

987

469

152

366

A

CO JEFFERSON

COUNTY

New Data Grant

1,045

467

120

458

A

Change (%)

5.8

-0.4

-21.2

25.0

FY 2011 Grant

820

274

194

352

A

CO LAKEWOOD

New Data Grant

984

276

219

490

A

Change (%)

20.0

0.4

12.8

39.4

FY 2011 Grant

493

171

128

195

A

CO LONGMONT

New Data Grant

597

166

148

282

A

Change (%)

21.0

-2.8

16.0

45.0

FY 2011 Grant

275

128

47

101

A

CO LOVELAND

New Data Grant

323

129

29

165

A

Change (%)

17.4

0.6

-37.8

64.4

FY 2011 Grant

1,513

371

401

742

B

CO PUEBLO

New Data Grant

1,390

375

364

651

B

Change (%)

-8.2

1.2

-9.2

-12.2

57

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

509

227

131

150

A

CO THORNTON

New Data Grant

640

229

154

257

A

Change (%)

25.8

0.6

17.4

71.2

FY 2011 Grant

507

211

130

166

A

CO WESTMINSTER

New Data Grant

587

205

102

280

A

Change (%)

15.8

-3.0

-21.4

68.6

FY 2011 Grant

3,009

526

1,226

1,258

B

CT

BRIDGEPORT

New Data Grant

3,114

481

1,109

1,523

B

Change (%)

3.4

-8.4

-9.4

21.0

FY 2011 Grant

575

83

92

400

B

CT

BRISTOL

New Data Grant

578

84

91

403

B

Change (%)

0.6

1.6

-0.4

0.6

FY 2011 Grant

566

120

0

446

B

CT

DANBURY

New Data Grant

599

156

250

193

A

Change (%)

5.8

60.4

FY 2011 Grant

599

107

218

275

B

CT

EAST HARTFORD

New Data Grant

584

122

178

284

B

Change (%)

-2.6

14.4

-18.4

3.4

FY 2011 Grant

511

32

148

331

B

CT

FAIRFIELD

New Data Grant

483

30

117

336

B

Change (%)

-5.4

-6.8

-20.4

1.4

FY 2011 Grant

862

51

230

580

B

CT

GREENWICH

New Data Grant

818

40

236

542

B

Change (%)

-5.2

-22.6

2.4

-6.6

FY 2011 Grant

496

88

45

364

B

CT

HAMDEN TOWN New Data Grant

389

75

3

311

B

Change (%)

-21.6

-14.8

-92.4

-14.6

FY 2011 Grant

3,483

754

1,492

1,236

B

CT

HARTFORD

New Data Grant

3,985

663

1,451

1,871

B

Change (%)

14.4

-12.0

-2.8

51.4

FY 2011 Grant

608

91

86

432

B

CT

MANCHESTER

New Data Grant

585

77

56

452

B

Change (%)

-3.8

-14.8

-34.4

4.6

FY 2011 Grant

845

133

234

478

B

CT

MERIDEN

New Data Grant

871

165

204

502

B

Change (%)

3.0

24.0

-12.8

5.0

FY 2011 Grant

380

66

20

294

B

CT

MIDDLETOWN

New Data Grant

446

94

24

328

B

Change (%)

17.2

42.2

21.2

11.4

58

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

479

41

77

361

B

CT

MILFORD TOWN

New Data Grant

501

39

116

346

B

Change (%)

4.6

-4.4

50.4

-4.2

FY 2011 Grant

1,717

238

661

818

B

CT

NEW BRITAIN

New Data Grant

1,698

228

612

858

B

Change (%)

-1.0

-4.2

-7.4

5.0

FY 2011 Grant

3,362

583

1,312

1,468

B

CT

NEW HAVEN

New Data Grant

3,630

501

1,202

1,928

B

Change (%)

8.0

-14.0

-8.4

31.4

FY 2011 Grant

807

77

314

416

B

CT

NEW LONDON

New Data Grant

759

65

289

405

B

Change (%)

-5.8

-15.6

-7.8

-2.6

FY 2011 Grant

890

125

225

539

B

CT

NORWALK

New Data Grant

953

122

192

639

B

Change (%)

7.2

-3.0

-14.8

18.6

FY 2011 Grant

911

86

265

560

B

CT

NORWICH

New Data Grant

826

93

210

523

B

Change (%)

-9.4

7.6

-20.8

-6.4

FY 2011 Grant

1,046

194

228

623

B

CT

STAMFORD

New Data Grant

984

236

387

360

A

Change (%)

-6.0

85.8

FY 2011 Grant

637

52

233

352

B

CT

STRATFORD

New Data Grant

557

41

195

321

B

Change (%)

-12.6

-21.6

-16.4

-8.8

FY 2011 Grant

2,079

354

672

1,054

B

CT

WATERBURY

New Data Grant

2,108

384

612

1,112

B

Change (%)

1.4

8.4

-8.8

5.6

FY 2011 Grant

1,004

56

410

537

B

CT

WEST HARTFORD New Data Grant

907

62

369

477

B

Change (%)

-9.6

9.4

-10.2

-11.2

FY 2011 Grant

670

94

145

431

B

CT

WEST HAVEN

New Data Grant

648

94

106

448

B

Change (%)

-3.2

-0.2

-26.8

4.0

FY 2011 Grant

16,329

2,311

6,840

7,178

B

DC DISTRICT OF

COLUMBIA

New Data Grant

15,626

1,848

6,661

7,117

B

Change (%)

-4.4

-20.0

-2.6

-0.8

FY 2011 Grant

248

71

35

142

A

DE

DOVER

New Data Grant

254

69

30

154

A

Change (%)

2.6

-1.6

-13.2

8.6

59

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

2,144

892

342

911

A

DE

NEW CASTLE

COUNTY

New Data Grant

2,336

902

391

1,043

A

Change (%)

9.0

1.0

14.6

14.6

FY 2011 Grant

2,224

313

885

1,027

B

DE

WILMINGTON

New Data Grant

2,390

286

893

1,211

B

Change (%)

7.4

-8.6

1.0

18.0

FY 2011 Grant

431

167

79

184

A

FL

BOCA RATON

New Data Grant

443

163

40

239

A

Change (%)

2.8

-2.6

-48.8

29.8

FY 2011 Grant

479

135

135

210

A

FL

BOYNTON

BEACH

New Data Grant

494

132

125

238

A

Change (%)

3.0

-2.4

-7.0

13.0

FY 2011 Grant

434

104

99

231

A

FL

BRADENTON

New Data Grant

444

96

138

211

A

Change (%)

2.2

-8.4

39.6

-8.8

FY 2011 Grant

1,379

543

174

662

A

FL

BREVARD

COUNTY

New Data Grant

1,323

552

169

601

A

Change (%)

-4.0

1.8

-2.6

-9.2

FY 2011 Grant

3,312

734

1,013

1,565

A

FL

BROWARD

COUNTY

New Data Grant

2,811

720

730

1,361

A

Change (%)

-15.2

-2.0

-27.8

-13.0

FY 2011 Grant

624

298

77

250

A

FL

CAPE CORAL

New Data Grant

826

297

138

391

A

Change (%)

32.2

-0.2

79.6

56.6

FY 2011 Grant

838

205

174

460

A

FL

CLEARWATER

New Data Grant

807

208

140

459

A

Change (%)

-3.8

1.2

-19.4

0.0

FY 2011 Grant

206

32

35

139

A

FL

COCOA

New Data Grant

225

33

56

136

A

Change (%)

9.2

3.4

58.6

-2.2

FY 2011 Grant

255

98

50

107

A

FL

COCONUT

CREEK

New Data Grant

262

102

48

112

A

Change (%)

2.8

4.4

-3.8

4.6

FY 2011 Grant

1,949

541

586

822

A

FL

COLLIER COUNTY New Data Grant

2,038

550

572

916

A

Change (%)

4.6

1.6

-2.4

11.6

FY 2011 Grant

814

245

234

336

A

FL

CORAL SPRINGS

New Data Grant

657

233

162

263

A

Change (%)

-19.2

-4.6

-30.8

-21.8

60

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

597

177

152

268

A

FL

DAVIE

New Data Grant

583

177

126

280

A

Change (%)

-2.4

0.0

-17.6

4.6

FY 2011 Grant

738

123

124

491

A

FL

DAYTONA

BEACH

New Data Grant

624

118

71

435

A

Change (%)

-15.4

-4.6

-42.6

-11.4

FY 2011 Grant

669

145

178

346

A

FL

DEERFIELD BEACH New Data Grant

631

145

142

344

A

Change (%)

-5.8

-0.4

-20.2

-0.6

FY 2011 Grant

524

125

150

249

A

FL

DELRAY BEACH

New Data Grant

463

117

105

241

A

Change (%)

-11.6

-6.8

-29.6

-3.0

FY 2011 Grant

450

161

91

197

A

FL

DELTONA

New Data Grant

495

164

72

259

A

Change (%)

10.0

1.6

-21.6

31.6

FY 2011 Grant

1,883

479

261

1,143

A

FL

ESCAMBIA

COUNTY

New Data Grant

1,889

470

367

1,052

A

Change (%)

0.4

-1.8

40.4

-8.0

FY 2011 Grant

625

82

139

403

A

FL

FORT PIERCE

New Data Grant

545

80

135

329

A

Change (%)

-12.8

-2.6

-2.8

-18.4

FY 2011 Grant

127

36

21

70

A

FL

FORT WALTON

BEACH

New Data Grant

140

38

37

65

A

Change (%)

10.4

4.6

80.8

-7.8

FY 2011 Grant

1,865

357

543

965

A

FL

FT LAUDERDALE

New Data Grant

1,736

319

469

948

A

Change (%)

-7.0

-10.8

-13.6

-1.8

FY 2011 Grant

681

125

171

385

A

FL

FT MYERS

New Data Grant

740

120

247

373

A

Change (%)

8.6

-4.0

44.6

-3.2

FY 2011 Grant

1,258

225

127

905

A

FL

GAINESVILLE

New Data Grant

1,461

240

107

1,114

A

Change (%)

16.2

6.4

-16.0

23.2

FY 2011 Grant

3,809

423

1,925

1,461

A

FL

HIALEAH

New Data Grant

2,250

433

524

1,293

A

Change (%)

-41.0

2.4

-72.8

-11.4

FY 2011 Grant

5,417

1,646

1,328

2,442

A

FL

HILLSBOROUGH

COUNTY

New Data Grant

5,803

1,723

1,242

2,839

A

Change (%)

7.2

4.6

-6.6

16.2

61

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

1,363

276

446

641

A

FL

HOLLYWOOD

New Data Grant

1,146

271

272

602

A

Change (%)

-16.0

-1.6

-39.0

-6.0

FY 2011 Grant

723

116

256

351

A

FL

HOMESTEAD CITY New Data Grant

839

117

240

482

A

Change (%)

16.0

0.8

-6.4

37.2

FY 2011 Grant

6,106

1,654

1,268

3,184

A

FL

JACKSONVILLE-

DUVAL COUNTY

New Data Grant

6,039

1,664

1,055

3,320

A

Change (%)

-1.2

0.6

-16.8

4.2

FY 2011 Grant

556

121

181

254

A

FL

KISSIMMEE

New Data Grant

581

115

153

313

A

Change (%)

4.4

-5.0

-15.8

23.4

FY 2011 Grant

934

429

118

387

A

FL

LAKE COUNTY

New Data Grant

1,139

378

158

603

A

Change (%)

22.0

-12.0

34.8

56.0

FY 2011 Grant

702

181

111

409

A

FL

LAKELAND

New Data Grant

766

188

198

379

A

Change (%)

9.2

3.6

78.8

-7.4

FY 2011 Grant

420

142

60

219

A

FL

LARGO

New Data Grant

488

150

73

266

A

Change (%)

16.2

5.8

21.4

21.4

FY 2011 Grant

844

130

296

417

A

FL

LAUDERHILL

New Data Grant

758

129

208

421

A

Change (%)

-10.2

-1.2

-29.8

1.0

FY 2011 Grant

1,936

712

371

854

A

FL

LEE COUNTY

New Data Grant

2,325

775

530

1,020

A

Change (%)

20.0

9.0

42.8

19.4

FY 2011 Grant

1,393

492

267

633

A

FL

MANATEE

COUNTY

New Data Grant

1,730

511

390

828

A

Change (%)

24.2

3.8

45.8

30.8

FY 2011 Grant

64

30

6

29

A

FL

MARCO ISLAND

CITY

New Data Grant

90

32

25

34

A

Change (%)

40.0

4.0

354.8

17.6

FY 2011 Grant

374

105

112

157

A

FL

MARGATE

New Data Grant

315

103

58

154

A

Change (%)

-15.8

-2.4

-47.8

-1.8

FY 2011 Grant

1,603

513

234

856

A

FL

MARION

COUNTY

New Data Grant

1,683

516

223

943

A

Change (%)

5.0

0.6

-4.8

10.2

62

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

504

150

78

276

A

FL

MELBOURNE

New Data Grant

498

147

61

290

A

Change (%)

-1.2

-2.0

-22.0

5.0

FY 2011 Grant

7,503

837

3,135

3,531

A

FL

MIAMI

New Data Grant

5,567

770

1,548

3,249

A

Change (%)

-25.8

-8.0

-50.6

-8.0

FY 2011 Grant

1,572

170

734

668

A

FL

MIAMI BEACH

New Data Grant

1,020

169

460

391

A

Change (%)

-35.2

-0.6

-37.4

-41.6

FY 2011 Grant

1,264

211

450

602

A

FL

MIAMI GARDENS

CITY

New Data Grant

1,058

207

312

540

A

Change (%)

-16.2

-2.2

-30.8

-10.4

FY 2011 Grant

16,285

2,886

6,738

6,662

A

FL

MIAMI-DADE

COUNTY

New Data Grant

11,896

2,905

3,323

5,668

A

Change (%)

-27.0

0.6

-50.6

-15.0

FY 2011 Grant

702

211

283

208

A

FL

MIRAMAR

New Data Grant

722

235

233

254

A

Change (%)

2.8

11.4

-17.8

22.0

FY 2011 Grant

101

43

16

43

A

FL

NAPLES

New Data Grant

119

38

24

57

A

Change (%)

17.0

-12.2

52.8

33.4

FY 2011 Grant

1,115

112

509

494

A

FL

NORTH MIAMI

New Data Grant

834

113

370

350

A

Change (%)

-25.2

1.0

-27.2

-29.2

FY 2011 Grant

442

107

63

272

A

FL

OCALA

New Data Grant

498

109

78

311

A

Change (%)

12.4

1.0

23.2

14.4

FY 2011 Grant

5,556

1,541

1,421

2,595

A

FL

ORANGE

COUNTY

New Data Grant

5,513

1,640

1,123

2,751

A

Change (%)

-0.8

6.4

-21.0

6.0

FY 2011 Grant

2,047

456

570

1,021

A

FL

ORLANDO

New Data Grant

2,059

459

509

1,091

A

Change (%)

0.6

0.8

-10.6

6.8

FY 2011 Grant

1,081

402

246

433

A

FL

OSCEOLA

COUNTY

New Data Grant

1,375

403

280

692

A

Change (%)

27.2

0.2

14.0

59.8

FY 2011 Grant

560

195

102

263

A

FL

PALM BAY

New Data Grant

618

199

90

329

A

Change (%)

10.4

1.8

-11.2

25.0

63

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

6,139

1,812

1,642

2,685

A

FL

PALM BEACH

COUNTY

New Data Grant

6,521

1,901

1,572

3,047

A

Change (%)

6.2

5.0

-4.2

13.4

FY 2011 Grant

377

124

167

86

B

FL

PANAMA CITY

New Data Grant

343

106

163

74

B

Change (%)

-8.8

-14.2

-2.4

-13.8

FY 2011 Grant

2,366

873

297

1,197

A

FL

PASCO COUNTY New Data Grant

2,719

858

388

1,473

A

Change (%)

15.0

-1.6

30.6

23.2

FY 2011 Grant

793

283

253

256

A

FL

PEMBROKE PINES New Data Grant

742

298

139

304

A

Change (%)

-6.4

5.2

-44.8

18.6

FY 2011 Grant

883

189

393

301

B

FL

PENSACOLA

New Data Grant

774

150

405

219

B

Change (%)

-12.4

-20.8

3.0

-27.0

FY 2011 Grant

2,676

938

379

1,359

A

FL

PINELLAS

COUNTY

New Data Grant

2,679

938

323

1,419

A

Change (%)

0.2

0.0

-14.8

4.4

FY 2011 Grant

464

164

113

187

A

FL

PLANTATION

New Data Grant

425

164

77

185

A

Change (%)

-8.4

-0.2

-32.0

-1.2

FY 2011 Grant

2,677

784

550

1,344

A

FL

POLK COUNTY

New Data Grant

3,229

808

892

1,529

A

Change (%)

20.6

3.2

62.2

13.8

FY 2011 Grant

1,108

198

336

574

A

FL

POMPANO

BEACH

New Data Grant

966

193

274

499

A

Change (%)

-12.8

-3.0

-18.4

-13.0

FY 2011 Grant

255

105

29

121

A

FL

PORT ORANGE

New Data Grant

295

108

47

140

A

Change (%)

15.4

2.4

61.8

15.4

FY 2011 Grant

630

299

87

245

A

FL

PORT ST LUCIE

New Data Grant

847

317

131

398

A

Change (%)

34.6

6.4

51.8

62.8

FY 2011 Grant

73

33

7

33

A

FL

PUNTA GORDA

New Data Grant

74

32

0

42

A

Change (%)

2.0

-3.2

-100

28.2

FY 2011 Grant

405

99

81

225

A

FL

SANFORD

New Data Grant

438

103

92

243

A

Change (%)

8.2

4.8

13.0

7.8

64

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

506

101

114

291

A

FL

SARASOTA

New Data Grant

434

100

71

262

A

Change (%)

-14.2

-0.4

-37.6

-9.8

FY 2011 Grant

1,348

605

164

578

A

FL

SARASOTA

COUNTY

New Data Grant

1,635

623

212

800

A

Change (%)

21.4

3.0

29.2

38.4

FY 2011 Grant

83

40

8

36

A

FL

SEBASTIAN CITY

New Data Grant

100

42

7

50

A

Change (%)

20.0

6.2

-3.0

39.8

FY 2011 Grant

1,766

700

348

718

A

FL

SEMINOLE

COUNTY

New Data Grant

1,904

712

282

909

A

Change (%)

7.8

1.6

-18.8

26.8

FY 2011 Grant

1,993

472

390

1,130

A

FL

ST PETERSBURG

New Data Grant

1,755

472

294

989

A

Change (%)

-12.0

0.0

-24.6

-12.4

FY 2011 Grant

661

173

200

287

A

FL

SUNRISE

New Data Grant

575

163

167

246

A

Change (%)

-13.0

-6.2

-16.8

-14.4

FY 2011 Grant

1,743

334

215

1,195

A

FL

TALLAHASSEE

New Data Grant

1,901

350

190

1,362

A

Change (%)

9.0

4.8

-11.6

14.0

FY 2011 Grant

377

115

89

174

A

FL

TAMARAC

New Data Grant

344

117

65

163

A

Change (%)

-8.8

1.0

-26.8

-6.0

FY 2011 Grant

3,389

665

845

1,879

A

FL

TAMPA

New Data Grant

3,042

647

576

1,819

A

Change (%)

-10.2

-2.6

-31.8

-3.2

FY 2011 Grant

305

86

46

173

A

FL

TITUSVILLE

New Data Grant

280

84

34

161

A

Change (%)

-8.4

-2.0

-25.0

-7.0

FY 2011 Grant

1,746

559

252

935

A

FL

VOLUSIA

COUNTY

New Data Grant

1,826

554

221

1,051

A

Change (%)

4.6

-0.8

-12.2

12.4

FY 2011 Grant

990

192

273

525

A

FL

WEST PALM

BEACH

New Data Grant

920

193

212

516

A

Change (%)

-7.2

0.2

-22.4

-1.8

FY 2011 Grant

249

64

50

134

A

FL

WINTER HAVEN

New Data Grant

344

65

95

183

A

Change (%)

38.2

1.4

90.2

36.4

65

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

1,039

146

188

704

A

GA ALBANY

New Data Grant

847

149

89

608

A

Change (%)

-18.4

2.2

-52.4

-13.6

FY 2011 Grant

1,332

225

181

926

A

GA ATHENS-CLARKE

COUNTY

New Data Grant

1,425

225

165

1,036

A

Change (%)

7.0

0.0

-9.0

11.8

FY 2011 Grant

7,018

2,020

2,628

2,370

B

GA ATLANTA

New Data Grant

8,741

1,906

4,037

2,797

B

Change (%)

24.6

-5.6

53.6

18.0

AUGUSTA-

FY 2011 Grant

2,040

386

342

1,312

A

GA RICHMOND

New Data Grant

1,932

387

293

1,252

A

COUNTY

Change (%)

-5.4

0.2

-14.4

-4.6

FY 2011 Grant

396

95

203

98

B

GA BRUNSWICK

New Data Grant

371

87

210

74

B

Change (%)

-6.4

-8.8

3.6

-24.6

FY 2011 Grant

788

415

111

263

A

GA CHEROKEE

COUNTY

New Data Grant

1,009

412

169

428

A

Change (%)

28.0

-0.8

53.0

62.8

FY 2011 Grant

1,916

530

565

821

A

GA CLAYTON

COUNTY

New Data Grant

2,061

498

416

1,147

A

Change (%)

7.6

-6.0

-26.4

39.6

FY 2011 Grant

2,969

1,252

662

1,054

A

GA COBB COUNTY

New Data Grant

3,433

1,218

587

1,629

A

Change (%)

15.6

-2.8

-11.4

54.6

COLUMBUS-

FY 2011 Grant

1,623

368

280

976

A

GA MUSCOGEE

New Data Grant

1,580

580

578

422

B

COUNTY

Change (%)

-2.6

-40.6

FY 2011 Grant

368

65

147

156

A

GA DALTON

New Data Grant

420

64

131

225

A

Change (%)

14.2

-1.6

-11.2

45.0

FY 2011 Grant

5,193

1,365

1,537

2,291

A

GA DE KALB COUNTY New Data Grant

5,548

1,274

1,160

3,115

A

Change (%)

6.8

-6.6

-24.6

36.0

FY 2011 Grant

1,838

577

434

827

A

GA FULTON COUNTY New Data Grant

1,903

524

327

1,053

A

Change (%)

3.6

-9.2

-24.6

27.2

FY 2011 Grant

364

69

112

182

A

GA GAINESVILLE

New Data Grant

426

65

147

214

A

Change (%)

17.2

-5.8

31.2

17.4

66

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

3,828

1,590

1,052

1,186

A

GA GWINNETT

COUNTY

New Data Grant

4,842

1,577

1,035

2,229

A

Change (%)

26.4

-0.8

-1.6

88.0

FY 2011 Grant

271

59

54

158

A

GA HINESVILLE

New Data Grant

247

64

24

158

A

Change (%)

-9.0

8.6

-54.8

0.0

FY 2011 Grant

162

119

12

30

A

GA JOHNS CREEK

CITY

New Data Grant

254

148

27

79

A

Change (%)

56.8

23.8

118.0

162.2

FY 2011 Grant

1,184

179

163

842

A

GA MACON

New Data Grant

1,134

176

163

795

A

Change (%)

-4.2

-1.6

0.2

-5.6

FY 2011 Grant

627

129

181

317

A

GA MARIETTA

New Data Grant

635

109

215

310

A

Change (%)

1.2

-15.8

19.2

-2.0

FY 2011 Grant

472

142

155

175

B

GA ROME

New Data Grant

431

150

146

135

B

Change (%)

-8.6

5.8

-5.8

-22.8

FY 2011 Grant

418

170

107

141

A

GA ROSWELL

New Data Grant

468

170

106

192

A

Change (%)

12.2

0.4

-1.4

36.6

FY 2011 Grant

489

166

129

194

A

GA SANDY SPRINGS

CITY

New Data Grant

473

181

115

177

A

Change (%)

-3.4

9.4

-11.4

-8.8

FY 2011 Grant

2,408

580

1,117

710

B

GA SAVANNAH

New Data Grant

2,373

511

1,069

793

B

Change (%)

-1.4

-12.0

-4.4

11.6

FY 2011 Grant

565

101

83

381

A

GA VALDOSTA

New Data Grant

586

105

76

405

A

Change (%)

3.8

4.2

-8.4

6.4

FY 2011 Grant

418

120

73

225

A

GA WARNER ROBINS New Data Grant

486

128

60

298

A

Change (%)

16.4

7.0

-18.2

32.8

FY 2011 Grant

8,786

1,755

4,079

2,952

A

HI

HONOLULU

New Data Grant

8,442

1,838

4,255

2,350

A

Change (%)

-4.0

4.8

4.4

-20.4

FY 2011 Grant

445

110

37

299

A

IA

AMES

New Data Grant

573

114

46

413

A

Change (%)

28.6

3.8

26.6

38.0

67

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

281

75

20

186

A

IA

CEDAR FALLS

New Data Grant

294

76

7

212

A

Change (%)

4.8

1.2

-67.0

14.0

FY 2011 Grant

1,188

187

132

870

B

IA

CEDAR RAPIDS

New Data Grant

1,222

278

135

809

B

Change (%)

3.0

49.2

2.8

-7.0

FY 2011 Grant

978

123

290

565

B

IA

COUNCIL BLUFFS New Data Grant

959

150

257

552

B

Change (%)

-2.0

21.2

-11.2

-2.4

FY 2011 Grant

1,575

284

404

888

B

IA

DAVENPORT

New Data Grant

1,490

284

409

797

B

Change (%)

-5.4

0.2

1.2

-10.2

FY 2011 Grant

3,844

462

1,416

1,966

B

IA

DES MOINES

New Data Grant

3,747

512

1,341

1,894

B

Change (%)

-2.6

10.8

-5.2

-3.6

FY 2011 Grant

1,127

109

347

671

B

IA

DUBUQUE

New Data Grant

1,042

102

332

609

B

Change (%)

-7.6

-6.4

-4.4

-9.4

FY 2011 Grant

604

134

40

430

A

IA

IOWA CITY

New Data Grant

716

131

48

538

A

Change (%)

18.6

-2.0

18.8

25.0

FY 2011 Grant

1,740

195

637

908

B

IA

SIOUX CITY

New Data Grant

1,693

223

623

847

B

Change (%)

-2.6

14.4

-2.2

-6.6

FY 2011 Grant

1,262

196

512

554

B

IA

WATERLOO

New Data Grant

1,261

206

478

577

B

Change (%)

0.0

5.2

-6.6

4.2

FY 2011 Grant

213

110

30

73

A

IA

WEST DES

MOINES

New Data Grant

249

109

34

106

A

Change (%)

16.8

-0.8

15.2

44.0

FY 2011 Grant

1,176

398

239

539

A

ID

BOISE

New Data Grant

1,283

397

205

682

A

Change (%)

9.0

-0.2

-14.4

26.4

FY 2011 Grant

282

85

44

153

A

ID

COEUR D'ALENE

New Data Grant

294

85

57

152

A

Change (%)

4.4

0.4

27.6

-0.2

FY 2011 Grant

370

107

73

190

A

ID

IDAHO FALLS

New Data Grant

352

110

52

191

A

Change (%)

-4.8

2.4

-28.4

0.2

68

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

242

77

0

166

B

ID

LEWISTON

New Data Grant

256

83

0

173

B

Change (%)

5.6

8.0

4.4

FY 2011 Grant

231

132

31

68

A

ID

MERIDIAN

New Data Grant

288

145

48

95

A

Change (%)

24.8

9.2

56.6

40.6

FY 2011 Grant

491

157

112

222

A

ID

NAMPA

New Data Grant

784

157

178

449

A

Change (%)

59.6

0.2

58.2

102.4

FY 2011 Grant

453

106

76

270

A

ID

POCATELLO

New Data Grant

412

105

33

274

A

Change (%)

-9.0

-1.8

-57.2

1.6

FY 2011 Grant

908

117

442

349

B

IL

ALTON CITY

New Data Grant

882

111

450

320

B

Change (%)

-2.8

-4.8

1.8

-8.2

FY 2011 Grant

255

141

47

66

A

IL

ARLINGTON

HEIGHTS

New Data Grant

272

145

48

79

A

Change (%)

6.8

2.4

2.8

19.4

FY 2011 Grant

1,111

334

353

423

A

IL

AURORA

New Data Grant

1,324

382

319

623

A

Change (%)

19.2

14.2

-9.6

47.2

FY 2011 Grant

667

100

184

383

B

IL

BELLEVILLE

New Data Grant

626

89

138

399

B

Change (%)

-6.2

-10.8

-25.0

4.2

FY 2011 Grant

1,258

89

397

772

B

IL

BERWYN

New Data Grant

1,149

101

300

747

B

Change (%)

-8.6

13.8

-24.4

-3.2

FY 2011 Grant

547

103

0

444

B

IL

BLOOMINGTON

New Data Grant

624

144

0

480

B

Change (%)

14.0

39.8

8.0

FY 2011 Grant

286

137

67

82

A

IL

BOLINGBROOK

New Data Grant

346

141

86

118

A

Change (%)

21.0

3.2

29.2

44.2

FY 2011 Grant

698

155

72

471

A

IL

CHAMPAIGN

New Data Grant

788

156

78

553

A

Change (%)

12.8

0.6

9.2

17.4

FY 2011 Grant

75,816

11,749

30,984

33,084

B

IL

CHICAGO

New Data Grant

80,761

10,425

32,207

38,128

B

Change (%)

6.6

-11.2

4.0

15.2

69

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

547

120

264

163

B

IL

CHICAGO

HEIGHTS

New Data Grant

589

130

259

200

B

Change (%)

7.6

8.0

-1.8

22.6

FY 2011 Grant

1,328

278

297

753

B

IL

CICERO

New Data Grant

1,532

234

238

1,061

B

Change (%)

15.4

-16.0

-19.8

40.8

FY 2011 Grant

8,859

3,014

2,345

3,499

A

IL

COOK COUNTY

New Data Grant

9,603

3,098

2,409

4,095

A

Change (%)

8.4

2.8

2.8

17.0

FY 2011 Grant

883

119

380

384

B

IL

DANVILLE

New Data Grant

936

153

364

419

B

Change (%)

6.0

27.6

-4.0

9.2

FY 2011 Grant

1,403

274

512

617

B

IL

DECATUR

New Data Grant

1,391

261

498

632

B

Change (%)

-0.8

-4.8

-2.6

2.4

FY 2011 Grant

376

88

52

235

A

IL

DEKALB

New Data Grant

462

85

71

307

A

Change (%)

22.8

-4.4

34.6

30.6

FY 2011 Grant

300

110

97

93

A

IL

DES PLAINES

New Data Grant

302

113

80

110

A

Change (%)

0.8

2.4

-17.2

18.0

FY 2011 Grant

199

24

0

175

B

IL

DOWNERS

GROVE

New Data Grant

184

33

0

152

B

Change (%)

-7.2

37.0

-13.2

FY 2011 Grant

3,136

1,325

889

922

A

IL

DU PAGE

COUNTY

New Data Grant

3,349

1,300

883

1,167

A

Change (%)

6.8

-1.8

-0.8

26.6

FY 2011 Grant

1,644

230

1,173

241

B

IL

EAST ST LOUIS

New Data Grant

1,651

201

1,175

274

B

Change (%)

0.4

-12.6

0.2

13.6

FY 2011 Grant

769

208

301

261

A

IL

ELGIN

New Data Grant

779

209

239

331

A

Change (%)

1.4

0.4

-20.4

27.0

FY 2011 Grant

1,753

159

515

1,080

B

IL

EVANSTON

New Data Grant

1,782

122

542

1,118

B

Change (%)

1.6

-23.0

5.2

3.6

FY 2011 Grant

715

75

368

272

B

IL

GRANITE CITY

New Data Grant

718

83

371

265

B

Change (%)

0.4

10.6

0.6

-2.6

70

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

272

104

91

78

A

IL

HOFFMAN

ESTATES

New Data Grant

291

100

98

93

A

Change (%)

6.8

-3.6

8.0

19.6

FY 2011 Grant

840

285

169

385

A

IL

JOLIET

New Data Grant

1,037

284

238

515

A

Change (%)

23.6

-0.4

40.6

33.8

FY 2011 Grant

1,079

538

234

308

A

IL

KANE COUNTY

New Data Grant

1,187

527

239

421

A

Change (%)

10.0

-2.0

2.2

36.8

FY 2011 Grant

542

118

184

240

B

IL

KANKAKEE

New Data Grant

534

147

170

217

B

Change (%)

-1.4

24.0

-7.4

-9.4

FY 2011 Grant

2,296

1,137

456

703

A

IL

LAKE COUNTY

New Data Grant

2,604

1,115

567

921

A

Change (%)

13.4

-2.0

24.4

31.0

FY 2011 Grant

1,265

334

18

914

B

IL

MADISON

COUNTY

New Data Grant

1,204

415

152

637

A

Change (%)

-4.8

91.0

FY 2011 Grant

1,190

644

211

335

A

IL

MCHENRY

COUNTY

New Data Grant

1,429

624

274

532

A

Change (%)

20.0

-3.2

29.6

58.8

FY 2011 Grant

819

86

264

469

B

IL

MOLINE

New Data Grant

745

78

250

417

B

Change (%)

-9.0

-9.8

-5.0

-11.0

FY 2011 Grant

325

103

131

92

A

IL

MOUNT

PROSPECT

New Data Grant

273

104

73

95

A

Change (%)

-16.0

1.8

-44.0

3.8

FY 2011 Grant

433

278

57

99

A

IL

NAPERVILLE

New Data Grant

468

273

58

137

A

Change (%)

8.0

-1.6

1.2

38.4

FY 2011 Grant

369

102

19

249

A

IL

NORMAL

New Data Grant

459

101

40

317

A

Change (%)

24.2

-0.8

115.8

27.6

FY 2011 Grant

273

63

84

126

A

IL

NORTH

CHICAGO

New Data Grant

235

73

20

141

B

Change (%)

-14.2

-42.0

FY 2011 Grant

247

102

40

104

A

IL

OAK LAWN

New Data Grant

264

109

51

105

A

Change (%)

7.2

6.8

26.2

0.4

71

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

1,726

61

483

1,182

B

IL

OAK PARK

New Data Grant

1,672

54

486

1,132

B

Change (%)

-3.2

-11.8

0.8

-4.2

FY 2011 Grant

368

129

130

109

A

IL

PALATINE

VILLAGE

New Data Grant

400

132

119

149

A

Change (%)

8.6

2.6

-9.0

37.0

FY 2011 Grant

387

62

109

216

B

IL

PEKIN

New Data Grant

369

72

98

199

B

Change (%)

-4.8

15.0

-10.2

-7.8

FY 2011 Grant

1,744

427

500

817

B

IL

PEORIA

New Data Grant

1,784

365

489

930

B

Change (%)

2.4

-14.4

-2.4

14.0

FY 2011 Grant

332

29

262

41

B

IL

RANTOUL

New Data Grant

327

45

248

34

B

Change (%)

-1.4

54.8

-5.2

-17.0

FY 2011 Grant

1,059

114

497

448

B

IL

ROCK ISLAND

New Data Grant

1,017

112

475

430

B

Change (%)

-4.0

-1.8

-4.4

-4.0

FY 2011 Grant

1,924

430

413

1,080

B

IL

ROCKFORD

New Data Grant

2,151

603

447

1,100

B

Change (%)

11.8

40.4

8.2

1.8

FY 2011 Grant

308

138

92

78

A

IL

SCHAUMBURG

VILLAGE

New Data Grant

303

143

65

95

A

Change (%)

-1.6

3.8

-30.0

22.4

FY 2011 Grant

471

71

284

116

B

IL

SKOKIE

New Data Grant

504

89

294

121

B

Change (%)

7.0

25.4

3.8

3.8

FY 2011 Grant

1,163

271

89

803

B

IL

SPRINGFIELD

New Data Grant

1,146

327

98

721

B

Change (%)

-1.4

20.6

10.8

-10.2

FY 2011 Grant

1,316

443

222

651

B

IL

ST CLAIR

COUNTY

New Data Grant

1,277

403

183

692

A

Change (%)

-3.0

56.2

FY 2011 Grant

421

77

52

292

A

IL

URBANA

New Data Grant

407

80

48

279

A

Change (%)

-3.6

2.8

-8.2

-4.4

FY 2011 Grant

951

175

351

424

A

IL

WAUKEGAN

New Data Grant

781

172

265

344

A

Change (%)

-17.8

-2.0

-24.8

-18.8

72

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

210

105

39

65

A

IL

WHEATON CITY

New Data Grant

193

102

20

71

A

Change (%)

-8.0

-3.4

-48.2

9.2

FY 2011 Grant

1,329

827

150

352

A

IL

WILL COUNTY

New Data Grant

1,685

801

291

594

A

Change (%)

26.8

-3.2

93.8

68.8

FY 2011 Grant

871

162

206

503

B

IN

ANDERSON

New Data Grant

902

188

211

503

B

Change (%)

3.6

15.8

2.4

0.2

FY 2011 Grant

762

139

38

584

A

IN

BLOOMINGTON

New Data Grant

869

155

35

678

A

Change (%)

14.0

11.4

-8.2

16.2

FY 2011 Grant

181

134

13

34

A

IN

CARMEL

New Data Grant

227

153

11

64

A

Change (%)

25.4

13.6

-19.6

90.2

FY 2011 Grant

266

65

0

200

B

IN

COLUMBUS

New Data Grant

247

85

32

130

A

Change (%)

-7.0

98.6

FY 2011 Grant

1,235

166

708

361

B

IN

EAST CHICAGO

New Data Grant

1,258

176

698

385

B

Change (%)

1.8

6.2

-1.4

6.6

FY 2011 Grant

683

146

93

444

B

IN

ELKHART

New Data Grant

790

208

113

469

B

Change (%)

15.6

42.6

21.2

5.6

FY 2011 Grant

2,686

338

1,239

1,109

B

IN

EVANSVILLE

New Data Grant

2,687

374

1,201

1,112

B

Change (%)

0.0

10.6

-3.0

0.2

FY 2011 Grant

1,926

539

0

1,387

B

IN

FORT WAYNE

New Data Grant

2,213

655

0

1,558

B

Change (%)

15.0

21.6

12.4

FY 2011 Grant

3,313

551

2,148

614

B

IN

GARY

New Data Grant

3,606

577

2,300

729

B

Change (%)

8.8

4.6

7.0

18.8

FY 2011 Grant

251

54

0

197

B

IN

GOSHEN

New Data Grant

274

80

0

193

B

Change (%)

9.0

48.4

-1.8

FY 2011 Grant

581

394

47

140

A

IN

HAMILTON

COUNTY

New Data Grant

734

367

91

276

A

Change (%)

26.4

-6.8

93.6

97.2

73

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

2,114

249

1,139

726

B

IN

HAMMOND

New Data Grant

2,097

298

1,062

736

B

Change (%)

-0.8

19.6

-6.8

1.4

FY 2011 Grant

8,670

1,924

2,284

4,463

B

IN

INDIANAPOLIS

New Data Grant

9,580

2,441

2,026

5,112

B

Change (%)

10.4

27.0

-11.2

14.6

FY 2011 Grant

913

124

318

470

B

IN

KOKOMO

New Data Grant

963

181

309

473

B

Change (%)

5.4

45.4

-3.0

0.6

FY 2011 Grant

453

49

132

273

B

IN

LA PORTE

New Data Grant

411

56

118

237

B

Change (%)

-9.4

15.6

-10.6

-13.2

FY 2011 Grant

587

154

0

433

B

IN

LAFAYETTE

New Data Grant

675

208

0

467

B

Change (%)

15.0

34.6

7.8

FY 2011 Grant

1,204

565

196

444

A

IN

LAKE COUNTY

New Data Grant

1,451

588

198

664

A

Change (%)

20.4

4.2

1.2

49.8

FY 2011 Grant

655

85

283

287

B

IN

MICHIGAN CITY

New Data Grant

671

104

287

280

B

Change (%)

2.6

23.0

1.6

-2.4

FY 2011 Grant

496

95

0

401

B

IN

MISHAWAKA

New Data Grant

473

99

19

356

B

Change (%)

-4.6

3.6

9860.4

-11.2

FY 2011 Grant

1,284

298

440

546

B

IN

MUNCIE

New Data Grant

1,318

326

399

593

B

Change (%)

2.6

9.4

-9.4

8.6

FY 2011 Grant

661

106

241

314

B

IN

NEW ALBANY

New Data Grant

662

114

248

300

B

Change (%)

0.2

7.4

3.0

-4.4

FY 2011 Grant

2,552

368

1,183

1,001

B

IN

SOUTH BEND

New Data Grant

2,549

426

1,194

929

B

Change (%)

-0.2

15.6

1.0

-7.2

FY 2011 Grant

1,648

211

612

825

B

IN

TERRE HAUTE

New Data Grant

1,661

245

587

829

B

Change (%)

0.8

16.0

-4.2

0.6

FY 2011 Grant

399

61

18

320

A

IN

WEST LAFAYETTE

New Data Grant

429

57

14

358

A

Change (%)

7.4

-6.4

-22.0

11.8

74

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

1,067

594

156

317

A

KS

JOHNSON

COUNTY

New Data Grant

1,292

600

209

483

A

Change (%)

21.0

1.0

33.6

52.6

FY 2011 Grant

2,257

524

843

890

B

KS

KANSAS CITY

New Data Grant

2,277

536

785

956

B

Change (%)

1.0

2.2

-6.8

7.4

FY 2011 Grant

730

178

72

480

A

KS

LAWRENCE

New Data Grant

850

169

58

623

A

Change (%)

16.4

-5.0

-19.4

29.8

FY 2011 Grant

326

60

0

266

B

KS

LEAVENWORTH

New Data Grant

330

71

0

259

B

Change (%)

1.4

18.4

-2.6

FY 2011 Grant

472

102

37

333

A

KS

MANHATTAN

CITY

New Data Grant

630

101

101

428

A

Change (%)

33.4

-1.4

174.8

28.4

FY 2011 Grant

593

338

88

166

A

KS

OVERLAND PARK New Data Grant

663

334

93

236

A

Change (%)

11.8

-1.2

5.2

41.8

FY 2011 Grant

208

119

33

56

A

KS

SHAWNEE

New Data Grant

248

120

31

98

A

Change (%)

19.6

0.6

-5.4

74.6

FY 2011 Grant

1,802

310

718

774

B

KS

TOPEKA

New Data Grant

1,805

383

659

764

B

Change (%)

0.2

23.4

-8.4

-1.4

FY 2011 Grant

2,580

720

523

1,337

A

KS

WICHITA

New Data Grant

2,881

737

551

1,593

A

Change (%)

11.6

2.4

5.2

19.2

FY 2011 Grant

625

84

321

220

B

KY

ASHLAND

New Data Grant

579

77

309

192

B

Change (%)

-7.4

-8.6

-3.6

-12.6

FY 2011 Grant

512

109

66

336

A

KY

BOWLING

GREEN

New Data Grant

556

112

64

380

A

Change (%)

8.6

2.4

-2.2

12.8

FY 2011 Grant

1,495

164

594

737

B

KY

COVINGTON

New Data Grant

1,580

157

612

811

B

Change (%)

5.6

-4.0

3.0

10.0

FY 2011 Grant

144

47

17

80

A

KY

ELIZABETHTOWN New Data Grant

164

55

10

99

A

Change (%)

13.8

16.0

-41.4

24.4

75

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

230

92

0

137

B

KY

HENDERSON

New Data Grant

240

55

33

151

A

Change (%)

4.4

63.6

FY 2011 Grant

261

62

26

173

A

KY

HOPKINSVILLE

New Data Grant

281

61

27

193

A

Change (%)

7.8

-1.8

5.4

11.8

FY 2011 Grant

1,904

573

207

1,124

A

KY

LEXINGTON-

FAYETTE

New Data Grant

2,235

570

252

1,413

A

Change (%)

17.4

-0.6

21.8

25.6

FY 2011 Grant

10,777

938

262

2,202

4,370

3,006

A/B

KY

LOUISVILLE

New Data Grant

7,482

1,837

2,107

3,538

B

Change (%)

-30.6

-16.6

-51.8

17.8

FY 2011 Grant

494

176

101

218

B

KY

OWENSBORO

New Data Grant

477

110

61

306

A

Change (%)

-3.4

74.0

FY 2011 Grant

600

94

69

436

A

LA

ALEXANDRIA

New Data Grant

534

92

108

334

A

Change (%)

-11.0

-2.6

56.6

-23.6

FY 2011 Grant

3,752

734

620

2,398

A

LA

BATON ROUGE

New Data Grant

3,624

741

569

2,314

A

Change (%)

-3.4

1.0

-8.2

-3.4

FY 2011 Grant

478

122

73

284

A

LA

BOSSIER CITY

New Data Grant

482

118

86

278

A

Change (%)

0.8

-3.4

18.4

-1.8

FY 2011 Grant

1,111

211

210

690

A

LA

HOUMA-

TERREBONNE

New Data Grant

988

216

227

546

A

Change (%)

-11.0

2.0

8.0

-20.8

FY 2011 Grant

3,234

726

675

1,833

A

LA

JEFFERSON

PARISH

New Data Grant

2,810

705

564

1,541

A

Change (%)

-13.0

-2.8

-16.4

-16.0

FY 2011 Grant

605

131

140

334

A

LA

KENNER

New Data Grant

512

129

126

257

A

Change (%)

-15.4

-2.0

-9.8

-23.0

FY 2011 Grant

1,480

345

262

873

A

LA

LAFAYETTE

New Data Grant

1,357

362

206

789

A

Change (%)

-8.2

4.8

-21.2

-9.6

FY 2011 Grant

782

282

296

204

B

LA

LAKE CHARLES

New Data Grant

737

271

279

187

B

Change (%)

-5.8

-4.2

-5.6

-8.4

76

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

788

100

124

564

A

LA

MONROE

New Data Grant

793

297

360

136

B

Change (%)

0.6

-47.4

FY 2011 Grant

14,914

2,762

7,335

4,816

B

LA

NEW ORLEANS

New Data Grant

12,187

1,345

7,335

3,507

B

Change (%)

-18.2

-51.4

0.0

-27.2

FY 2011 Grant

2,347

385

396

1,566

A

LA

SHREVEPORT

New Data Grant

2,005

384

293

1,328

A

Change (%)

-14.6

-0.2

-26.0

-15.2

FY 2011 Grant

179

53

21

104

A

LA

SLIDELL

New Data Grant

185

52

17

116

A

Change (%)

3.6

-1.8

-20.8

11.2

FY 2011 Grant

999

375

131

492

A

LA

ST TAMMANY

PARISH

New Data Grant

1,125

380

207

538

A

Change (%)

12.6

1.4

57.8

9.2

FY 2011 Grant

194

70

71

53

B

LA

THIBODAUX

New Data Grant

160

53

67

39

B

Change (%)

-17.6

-24.0

-5.8

-25.4

FY 2011 Grant

1,174

36

416

721

B

MA ARLINGTON

New Data Grant

1,147

34

392

721

B

Change (%)

-2.2

-6.6

-5.8

-0.2

FY 2011 Grant

424

54

0

370

B

MA ATTLEBORO

New Data Grant

391

60

0

331

B

Change (%)

-7.6

12.4

-10.6

FY 2011 Grant

319

88

0

231

B

MA BARNSTABLE

New Data Grant

308

57

0

251

B

Change (%)

-3.4

-35.8

9.0

FY 2011 Grant

17,497

2,303

5,021

10,173

B

MA BOSTON

New Data Grant

17,882

2,038

5,231

10,613

B

Change (%)

2.2

-11.4

4.2

4.4

FY 2011 Grant

1,386

283

198

905

B

MA BROCKTON

New Data Grant

1,424

218

183

1,023

B

Change (%)

2.8

-23.0

-7.6

13.0

FY 2011 Grant

1,469

109

309

1,051

B

MA BROOKLINE

New Data Grant

1,385

127

271

987

B

Change (%)

-5.8

16.6

-12.4

-6.0

FY 2011 Grant

2,797

238

662

1,897

B

MA CAMBRIDGE

New Data Grant

3,094

268

688

2,139

B

Change (%)

10.6

12.2

3.8

12.8

77

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

1,163

139

456

567

B

MA CHICOPEE

New Data Grant

1,149

153

452

544

B

Change (%)

-1.2

9.8

-0.8

-4.0

FY 2011 Grant

2,742

325

740

1,676

B

MA FALL RIVER

New Data Grant

2,772

305

746

1,721

B

Change (%)

1.2

-6.2

0.8

2.8

FY 2011 Grant

1,037

119

281

637

B

MA FITCHBURG

New Data Grant

1,038

133

295

610

B

Change (%)

0.2

12.0

5.4

-4.4

FY 2011 Grant

484

108

0

375

B

MA FRAMINGHAM

New Data Grant

487

92

0

395

B

Change (%)

0.8

-15.0

5.4

FY 2011 Grant

726

55

103

568

B

MA GLOUCESTER

New Data Grant

699

38

120

541

B

Change (%)

-3.8

-31.4

16.8

-4.8

FY 2011 Grant

958

111

101

746

B

MA HAVERHILL

New Data Grant

991

127

102

762

B

Change (%)

3.4

15.0

1.4

2.0

FY 2011 Grant

1,211

213

484

514

B

MA HOLYOKE

New Data Grant

1,198

203

479

515

B

Change (%)

-1.0

-4.6

-0.8

0.2

FY 2011 Grant

1,583

363

449

771

B

MA LAWRENCE

New Data Grant

1,466

343

364

759

B

Change (%)

-7.4

-5.6

-18.8

-1.6

FY 2011 Grant

464

82

0

382

B

MA LEOMINSTER

New Data Grant

438

65

11

363

B

Change (%)

-5.4

-21.2

-5.0

FY 2011 Grant

2,173

360

424

1,388

B

MA LOWELL

New Data Grant

2,172

317

382

1,473

B

Change (%)

0.0

-11.8

-10.0

6.0

FY 2011 Grant

2,301

306

679

1,315

B

MA LYNN

New Data Grant

2,472

304

627

1,542

B

Change (%)

7.4

-1.0

-7.8

17.2

FY 2011 Grant

1,408

108

381

919

B

MA MALDEN

New Data Grant

1,321

115

329

877

B

Change (%)

-6.2

6.4

-13.6

-4.6

FY 2011 Grant

1,589

72

525

992

B

MA MEDFORD

New Data Grant

1,586

84

505

998

B

Change (%)

-0.2

16.0

-3.8

0.6

78

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

2,741

391

785

1,565

B

MA NEW BEDFORD

New Data Grant

2,772

358

716

1,699

B

Change (%)

1.2

-8.6

-8.8

8.6

FY 2011 Grant

2,028

71

677

1,280

B

MA NEWTON

New Data Grant

1,894

74

652

1,168

B

Change (%)

-6.6

4.0

-3.6

-8.8

FY 2011 Grant

686

53

208

426

B

MA NORTHAMPTON

New Data Grant

661

57

202

402

B

Change (%)

-3.8

8.4

-2.8

-5.6

FY 2011 Grant

420

53

0

366

B

MA PEABODY CITY

New Data Grant

398

62

0

336

B

Change (%)

-5.2

15.6

-8.2

FY 2011 Grant

1,369

107

556

706

B

MA PITTSFIELD

New Data Grant

1,257

124

515

618

B

Change (%)

-8.2

15.4

-7.2

-12.4

FY 2011 Grant

358

56

0

302

B

MA PLYMOUTH

TOWN

New Data Grant

361

54

0

307

B

Change (%)

0.8

-3.8

1.6

FY 2011 Grant

1,893

133

503

1,257

B

MA QUINCY

New Data Grant

1,928

146

472

1,310

B

Change (%)

1.8

10.0

-6.2

4.2

FY 2011 Grant

764

145

107

512

B

MA REVERE CITY

New Data Grant

704

101

99

504

B

Change (%)

-7.8

-30.6

-6.8

-1.6

FY 2011 Grant

1,042

80

219

743

B

MA SALEM

New Data Grant

1,014

83

212

719

B

Change (%)

-2.6

3.4

-3.0

-3.2

FY 2011 Grant

2,586

198

821

1,567

B

MA SOMERVILLE

New Data Grant

2,735

198

811

1,726

B

Change (%)

5.8

-0.2

-1.2

10.2

FY 2011 Grant

3,718

713

1,330

1,676

B

MA SPRINGFIELD

New Data Grant

4,120

729

1,327

2,064

B

Change (%)

10.8

2.2

-0.2

23.2

FY 2011 Grant

822

117

75

630

B

MA TAUNTON

New Data Grant

752

102

68

582

B

Change (%)

-8.6

-13.0

-10.0

-7.6

FY 2011 Grant

966

79

283

604

B

MA WALTHAM

New Data Grant

1,056

114

273

670

B

Change (%)

9.4

43.8

-3.6

11.0

79

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

404

89

0

315

B

MA WESTFIELD

New Data Grant

357

83

0

273

B

Change (%)

-11.8

-6.6

-13.2

FY 2011 Grant

4,141

614

1,216

2,310

B

MA WORCESTER

New Data Grant

4,456

539

1,205

2,712

B

Change (%)

7.6

-12.4

-1.0

17.4

FY 2011 Grant

744

65

230

449

B

MA WEYMOUTH

TOWN

New Data Grant

744

64

224

456

B

Change (%)

0.2

-1.6

-2.4

1.6

FY 2011 Grant

125

46

14

65

A

MA YARMOUTH

New Data Grant

106

46

18

42

A

Change (%)

-14.8

-0.4

32.4

-35.0

FY 2011 Grant

310

94

0

216

B

MD ANNAPOLIS

New Data Grant

238

59

0

179

B

Change (%)

-23.4

-37.8

-17.2

FY 2011 Grant

1,899

936

265

698

A

MD ANNE ARUNDEL

COUNTY

New Data Grant

1,964

962

322

680

A

Change (%)

3.4

2.8

21.6

-2.6

FY 2011 Grant

21,039

3,028

9,650

8,361

B

MD BALTIMORE

New Data Grant

20,066

2,242

9,658

8,166

B

Change (%)

-4.6

-26.0

0.0

-2.4

FY 2011 Grant

3,748

1,527

547

1,674

A

MD BALTIMORE

COUNTY

New Data Grant

4,052

1,552

689

1,810

A

Change (%)

8.2

1.6

26.2

8.2

FY 2011 Grant

146

103

15

28

A

MD BOWIE CITY

New Data Grant

185

106

34

46

A

Change (%)

26.4

2.2

126.6

62.0

FY 2011 Grant

905

88

371

445

B

MD CUMBERLAND

New Data Grant

811

68

359

385

B

Change (%)

-10.4

-23.0

-3.2

-13.6

FY 2011 Grant

352

79

0

273

B

MD FREDERICK

New Data Grant

344

80

0

264

B

Change (%)

-2.4

0.6

-3.2

FY 2011 Grant

407

116

161

131

A

MD GAITHERSBURG

New Data Grant

410

116

153

142

A

Change (%)

0.6

-0.4

-5.0

8.6

FY 2011 Grant

839

138

188

513

B

MD HAGERSTOWN

New Data Grant

743

129

186

428

B

Change (%)

-11.6

-6.4

-1.2

-16.6

80

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

948

469

103

376

A

MD HARFORD

COUNTY

New Data Grant

963

472

102

389

A

Change (%)

1.6

0.6

-1.2

3.4

FY 2011 Grant

1,061

545

183

334

A

MD HOWARD

COUNTY

New Data Grant

1,005

553

121

331

A

Change (%)

-5.4

1.6

-34.0

-0.8

FY 2011 Grant

4,663

1,741

1,407

1,516

A

MD MONTGOMERY

COUNTY

New Data Grant

4,284

1,739

1,192

1,353

A

Change (%)

-8.2

-0.2

-15.2

-10.8

PRINCE

FY 2011 Grant

5,457

1,502

1,873

2,082

A

MD GEORGES

New Data Grant

4,802

1,549

1,487

1,766

A

COUNTY

Change (%)

-12.0

3.2

-20.6

-15.2

FY 2011 Grant

274

55

34

185

A

MD SALISBURY

New Data Grant

271

59

64

148

A

Change (%)

-1.0

6.8

86.6

-19.8

FY 2011 Grant

580

57

173

351

B

ME AUBURN

New Data Grant

547

59

166

323

B

Change (%)

-5.6

3.4

-3.8

-8.0

FY 2011 Grant

937

104

337

495

B

ME BANGOR

New Data Grant

838

92

310

437

B

Change (%)

-10.6

-12.2

-8.2

-11.8

FY 2011 Grant

443

59

94

290

B

ME BIDDEFORD

New Data Grant

452

52

92

308

B

Change (%)

2.0

-11.0

-2.2

6.2

FY 2011 Grant

1,544

210

0

1,334

B

ME CUMBERLAND

COUNTY

New Data Grant

1,614

269

0

1,344

B

Change (%)

4.6

28.0

0.8

FY 2011 Grant

948

109

328

512

B

ME LEWISTON

New Data Grant

854

146

301

407

B

Change (%)

-10.0

34.6

-8.2

-20.4

FY 2011 Grant

1,941

187

574

1,180

B

ME PORTLAND CITY

New Data Grant

1,895

193

521

1,181

B

Change (%)

-2.4

3.4

-9.4

0.2

FY 2011 Grant

1,191

157

538

496

B

MI

BATTLE CREEK

New Data Grant

1,255

186

519

550

B

Change (%)

5.4

18.4

-3.4

11.0

FY 2011 Grant

1,312

113

583

616

B

MI

BAY CITY

New Data Grant

1,235

116

558

562

B

Change (%)

-5.8

2.8

-4.4

-8.8

81

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

421

99

224

98

B

MI

BENTON

HARBOR

New Data Grant

497

94

229

174

B

Change (%)

18.0

-5.8

2.6

77.0

FY 2011 Grant

312

156

57

100

A

MI

CANTON TWP

New Data Grant

357

174

44

139

A

Change (%)

14.2

11.8

-23.0

39.2

FY 2011 Grant

467

186

88

193

A

MI

CLINTON TWP

New Data Grant

546

187

72

288

A

Change (%)

16.8

0.6

-19.0

48.8

FY 2011 Grant

2,035

332

1,045

659

B

MI

DEARBORN

New Data Grant

1,728

331

854

543

B

Change (%)

-15.0

-0.2

-18.2

-17.6

FY 2011 Grant

1,031

75

862

95

B

MI

DEARBORN

HEIGHTS

New Data Grant

954

107

759

88

B

Change (%)

-7.6

43.4

-12.0

-7.0

FY 2011 Grant

33,531

5,131

19,941

8,460

B

MI

DETROIT

New Data Grant

37,533

5,414

22,017

10,103

B

Change (%)

12.0

5.6

10.4

19.4

FY 2011 Grant

537

88

51

398

A

MI

EAST LANSING

New Data Grant

510

94

40

376

A

Change (%)

-5.2

6.4

-22.4

-5.6

FY 2011 Grant

330

152

62

116

A

MI

FARMINGTON

HILLS

New Data Grant

386

154

62

171

A

Change (%)

16.8

1.0

-0.6

47.0

FY 2011 Grant

3,947

685

2,301

961

B

MI

FLINT

New Data Grant

4,028

708

2,370

950

B

Change (%)

2.0

3.4

3.0

-1.2

FY 2011 Grant

1,595

575

204

816

A

MI

GENESEE

COUNTY

New Data Grant

1,869

591

267

1,010

A

Change (%)

17.2

2.8

30.8

23.8

FY 2011 Grant

3,684

626

908

2,150

B

MI

GRAND RAPIDS

New Data Grant

3,856

732

947

2,178

B

Change (%)

4.6

16.8

4.4

1.2

FY 2011 Grant

325

72

40

213

B

MI

HOLLAND

New Data Grant

326

75

48

202

B

Change (%)

0.0

3.6

21.6

-5.2

FY 2011 Grant

1,269

147

535

588

B

MI

JACKSON

New Data Grant

1,290

165

522

604

B

Change (%)

1.6

12.4

-2.4

2.8

82

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

1,675

351

630

693

B

MI

KALAMAZOO

New Data Grant

1,764

416

597

751

B

Change (%)

5.4

18.4

-5.4

8.4

FY 2011 Grant

1,403

665

205

533

A

MI

KENT COUNTY

New Data Grant

1,644

661

172

812

A

Change (%)

17.2

-0.8

-16.0

52.4

FY 2011 Grant

2,018

419

601

997

B

MI

LANSING

New Data Grant

2,043

506

576

960

B

Change (%)

1.2

20.8

-4.2

-3.6

FY 2011 Grant

793

65

580

148

B

MI

LINCOLN PARK

New Data Grant

729

88

524

117

B

Change (%)

-8.0

36.6

-9.8

-21.0

FY 2011 Grant

329

173

46

110

A

MI

LIVONIA

New Data Grant

317

187

23

107

A

Change (%)

-3.6

8.2

-50.0

-2.8

FY 2011 Grant

1,497

711

230

557

A

MI

MACOMB

COUNTY

New Data Grant

1,776

720

242

813

A

Change (%)

18.6

1.4

5.2

46.0

FY 2011 Grant

219

79

15

125

A

MI

MIDLAND

New Data Grant

241

81

27

133

A

Change (%)

10.2

2.4

89.2

6.2

FY 2011 Grant

486

58

165

263

B

MI

MONROE

New Data Grant

461

58

168

235

B

Change (%)

-5.0

0.6

1.8

-10.6

FY 2011 Grant

911

153

382

377

B

MI

MUSKEGON

New Data Grant

930

189

383

358

B

Change (%)

2.0

24.0

0.4

-5.2

FY 2011 Grant

421

75

222

124

B

MI

MUSKEGON HTS New Data Grant

463

89

227

147

B

Change (%)

10.0

19.4

2.0

18.6

FY 2011 Grant

308

34

119

155

B

MI

NILES

New Data Grant

293

47

112

134

B

Change (%)

-4.6

38.6

-5.8

-13.2

FY 2011 Grant

129

25

44

61

B

MI

NORTON

SHORES

New Data Grant

116

36

32

48

B

Change (%)

-10.2

45.8

-27.0

-21.0

FY 2011 Grant

3,504

1,654

589

1,261

A

MI

OAKLAND

COUNTY

New Data Grant

3,952

1,660

643

1,649

A

Change (%)

12.8

0.4

9.2

30.8

83

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

1,416

303

715

398

B

MI

PONTIAC

New Data Grant

1,602

324

782

496

B

Change (%)

13.2

6.8

9.4

24.6

FY 2011 Grant

793

113

295

385

B

MI

PORT HURON

New Data Grant

737

137

293

308

B

Change (%)

-7.0

21.2

-0.8

-20.2

FY 2011 Grant

192

90

27

76

A

MI

PORTAGE

New Data Grant

240

89

25

126

A

Change (%)

24.8

-0.6

-7.2

66.6

FY 2011 Grant

932

55

777

100

B

MI

REDFORD

New Data Grant

880

63

718

99

B

Change (%)

-5.6

14.6

-7.6

-0.8

FY 2011 Grant

536

80

358

99

B

MI

ROSEVILLE

New Data Grant

556

101

341

114

B

Change (%)

3.8

26.2

-4.4

15.6

FY 2011 Grant

1,244

54

798

392

B

MI

ROYAL OAK

New Data Grant

1,230

66

780

383

B

Change (%)

-1.2

23.4

-2.2

-2.4

FY 2011 Grant

2,275

367

1,153

755

B

MI

SAGINAW

New Data Grant

2,381

362

1,178

842

B

Change (%)

4.6

-1.4

2.2

11.4

FY 2011 Grant

456

146

109

201

A

MI

SOUTHFIELD

New Data Grant

465

138

75

252

A

Change (%)

2.0

-5.2

-30.8

25.2

FY 2011 Grant

862

49

684

129

B

MI

ST CLAIR SHORES New Data Grant

882

83

677

122

B

Change (%)

2.2

69.0

-1.2

-5.2

FY 2011 Grant

605

246

131

228

A

MI

STERLING

HEIGHTS

New Data Grant

700

250

148

302

A

Change (%)

15.6

1.8

12.8

32.4

FY 2011 Grant

443

115

82

246

A

MI

TAYLOR

New Data Grant

459

122

83

254

A

Change (%)

3.8

6.2

2.2

3.2

FY 2011 Grant

762

259

148

356

A

MI

WARREN

New Data Grant

908

258

172

477

A

Change (%)

19.0

-0.2

16.2

34.2

FY 2011 Grant

1,990

544

337

1,110

A

MI

WASHTENAW

COUNTY

New Data Grant

2,127

538

243

1,346

A

Change (%)

6.8

-1.0

-28.0

21.2

84

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

323

137

57

129

A

MI

WATERFORD

TOWNSHIP

New Data Grant

406

138

60

207

A

Change (%)

25.8

1.0

5.6

61.0

FY 2011 Grant

5,685

965

2,241

2,480

B

MI

WAYNE COUNTY New Data Grant

5,174

1,093

1,776

2,305

B

Change (%)

-9.0

13.2

-20.8

-7.0

FY 2011 Grant

1,073

123

858

93

B

MI

WESTLAND

New Data Grant

1,019

170

754

95

B

Change (%)

-5.0

38.8

-12.0

2.6

FY 2011 Grant

420

137

108

176

A

MI

WYOMING

New Data Grant

524

139

82

304

A

Change (%)

24.8

1.8

-24.2

72.6

FY 2011 Grant

1,025

521

173

332

A

MN ANOKA COUNTY New Data Grant

1,215

520

245

451

A

Change (%)

18.6

-0.2

41.4

36.0

FY 2011 Grant

361

160

84

118

A

MN BLOOMINGTON

New Data Grant

408

160

83

165

A

Change (%)

12.8

-0.4

-0.8

40.6

FY 2011 Grant

272

121

48

103

A

MN COON RAPIDS

New Data Grant

316

119

67

130

A

Change (%)

16.2

-1.6

39.4

26.2

FY 2011 Grant

1,550

803

267

480

A

MN DAKOTA

COUNTY

New Data Grant

1,727

805

290

633

A

Change (%)

11.4

0.2

8.8

31.8

FY 2011 Grant

2,568

266

950

1,351

B

MN DULUTH

New Data Grant

2,402

286

906

1,209

B

Change (%)

-6.4

7.6

-4.6

-10.4

FY 2011 Grant

233

121

46

67

A

MN EDEN PRAIRIE

New Data Grant

273

117

64

92

A

Change (%)

17.0

-2.8

40.0

36.8

FY 2011 Grant

2,187

982

492

712

A

MN HENNEPIN

COUNTY

New Data Grant

2,479

987

515

977

A

Change (%)

13.4

0.6

4.6

37.2

FY 2011 Grant

347

116

0

232

B

MN MANKATO CITY

New Data Grant

399

163

0

236

B

Change (%)

14.8

40.6

1.8

FY 2011 Grant

12,043

1,310

4,244

6,489

B

MN MINNEAPOLIS

New Data Grant

11,983

1,415

4,183

6,385

B

Change (%)

-0.4

8.0

-1.4

-1.6

85

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

169

98

24

47

A

MN MINNETONKA

New Data Grant

176

96

16

63

A

Change (%)

3.6

-2.4

-32.8

35.2

FY 2011 Grant

259

71

24

164

A

MN MOORHEAD

New Data Grant

242

73

10

158

A

Change (%)

-6.6

3.2

-57.4

-3.4

FY 2011 Grant

80

18

0

63

B

MN NORTH

MANKATO CITY

New Data Grant

66

17

0

48

B

Change (%)

-18.2

-0.8

-23.0

FY 2011 Grant

238

141

39

59

A

MN PLYMOUTH

New Data Grant

259

136

28

95

A

Change (%)

8.6

-3.4

-27.0

60.6

FY 2011 Grant

929

436

162

331

A

MN RAMSEY COUNTY New Data Grant

1,070

431

170

468

A

Change (%)

15.2

-1.0

4.8

41.4

FY 2011 Grant

524

200

92

232

A

MN ROCHESTER

New Data Grant

561

206

88

267

A

Change (%)

7.0

2.8

-3.8

14.8

FY 2011 Grant

432

151

0

281

B

MN ST CLOUD

New Data Grant

566

127

52

387

A

Change (%)

31.0

156.0

FY 2011 Grant

2,201

219

848

1,134

B

MN ST LOUIS

COUNTY

New Data Grant

1,924

205

826

892

B

Change (%)

-12.6

-6.4

-2.4

-21.4

FY 2011 Grant

7,217

913

2,367

3,937

B

MN ST PAUL

New Data Grant

7,080

965

2,259

3,855

B

Change (%)

-2.0

5.6

-4.6

-2.0

FY 2011 Grant

582

335

73

174

A

MN WASHINGTON

COUNTY

New Data Grant

678

337

81

260

A

Change (%)

16.6

0.6

10.4

49.6

FY 2011 Grant

157

111

19

27

A

MN WOODBURY CITY New Data Grant

192

119

20

53

A

Change (%)

22.0

7.8

3.8

93.4

FY 2011 Grant

206

108

18

80

A

MO BLUE SPRINGS

New Data Grant

238

101

28

108

A

Change (%)

15.0

-6.0

57.2

34.0

FY 2011 Grant

774

198

61

516

A

MO COLUMBIA

New Data Grant

900

209

95

596

A

Change (%)

16.2

5.8

56.8

15.4

86

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

201

98

32

71

A

MO FLORISSANT

New Data Grant

242

101

49

92

A

Change (%)

20.4

2.8

54.6

29.0

FY 2011 Grant

683

204

0

479

B

MO INDEPENDENCE

New Data Grant

830

225

145

460

A

Change (%)

21.6

125.0

FY 2011 Grant

290

85

14

191

B

MO JEFFERSON CITY

New Data Grant

256

84

0

172

B

Change (%)

-12.0

-1.2

-100

-10.2

FY 2011 Grant

1,034

422

148

464

A

MO JEFFERSON

COUNTY

New Data Grant

1,179

421

160

598

A

Change (%)

14.0

-0.4

8.6

28.8

FY 2011 Grant

587

136

109

342

B

MO JOPLIN

New Data Grant

543

154

103

286

B

Change (%)

-7.6

12.8

-5.2

-16.4

FY 2011 Grant

7,655

1,307

2,898

3,450

B

MO KANSAS CITY

New Data Grant

8,480

1,439

3,090

3,951

B

Change (%)

10.8

10.0

6.6

14.6

FY 2011 Grant

287

167

25

95

A

MO LEES SUMMIT

New Data Grant

324

176

25

123

A

Change (%)

12.8

5.2

-0.6

29.4

FY 2011 Grant

230

152

25

53

A

MO O'FALLON

New Data Grant

258

153

33

72

A

Change (%)

11.8

0.4

33.2

35.2

FY 2011 Grant

1,219

305

125

789

A

MO SPRINGFIELD

New Data Grant

1,324

308

133

883

A

Change (%)

8.6

1.0

6.4

12.0

FY 2011 Grant

285

127

31

127

A

MO ST CHARLES

New Data Grant

317

127

31

160

A

Change (%)

11.4

0.0

-1.8

26.0

FY 2011 Grant

1,572

190

543

839

B

MO ST JOSEPH

New Data Grant

1,493

201

521

771

B

Change (%)

-5.0

5.6

-4.0

-8.2

FY 2011 Grant

17,829

1,760

9,609

6,460

B

MO ST LOUIS

New Data Grant

18,894

1,524

9,903

7,467

B

Change (%)

6.0

-13.4

3.0

15.6

FY 2011 Grant

5,089

1,412

599

3,078

B

MO ST LOUIS

COUNTY

New Data Grant

5,120

1,561

465

3,094

B

Change (%)

0.6

10.6

-22.4

0.6

87

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

686

402

75

209

A

MO ST CHARLES

COUNTY

New Data Grant

703

410

64

229

A

Change (%)

2.4

1.8

-14.2

9.4

FY 2011 Grant

511

146

255

111

B

MS BILOXI

New Data Grant

440

102

268

70

B

Change (%)

-14.0

-30.0

5.2

-37.0

FY 2011 Grant

682

137

122

423

A

MS GULFPORT

New Data Grant

616

131

115

370

A

Change (%)

-9.8

-4.6

-6.0

-12.4

FY 2011 Grant

568

102

69

396

A

MS HATTIESBURG

New Data Grant

647

89

103

455

A

Change (%)

14.0

-13.4

49.2

14.8

FY 2011 Grant

2,257

338

449

1,469

A

MS JACKSON

New Data Grant

2,074

335

360

1,380

A

Change (%)

-8.0

-1.2

-19.8

-6.0

FY 2011 Grant

155

27

30

98

A

MS MOSS POINT

New Data Grant

117

26

17

73

A

Change (%)

-24.8

-2.0

-42.4

-25.6

FY 2011 Grant

274

46

47

181

A

MS PASCAGOULA

New Data Grant

227

43

28

156

A

Change (%)

-17.0

-5.8

-41.6

-13.6

FY 2011 Grant

646

205

76

366

A

MT BILLINGS

New Data Grant

639

201

75

363

A

Change (%)

-1.0

-1.8

-0.6

-0.6

FY 2011 Grant

845

169

295

381

B

MT GREAT FALLS

New Data Grant

806

158

296

352

B

Change (%)

-4.6

-6.2

0.2

-7.6

FY 2011 Grant

574

133

64

376

A

MT MISSOULA

New Data Grant

629

129

42

459

A

Change (%)

9.8

-3.4

-34.8

22.0

FY 2011 Grant

1,098

218

298

582

B

NC ASHEVILLE

New Data Grant

1,029

259

215

556

B

Change (%)

-6.2

18.6

-28.0

-4.4

FY 2011 Grant

399

100

81

218

A

NC BURLINGTON

New Data Grant

516

96

133

287

A

Change (%)

29.4

-3.4

64.8

31.2

FY 2011 Grant

452

264

75

113

A

NC CARY

New Data Grant

471

261

68

142

A

Change (%)

4.0

-1.4

-9.0

25.2

88

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

530

104

125

302

A

NC CHAPEL HILL

New Data Grant

460

110

30

320

A

Change (%)

-13.0

6.6

-75.6

6.0

FY 2011 Grant

4,358

1,362

1,012

1,985

A

NC CHARLOTTE

New Data Grant

4,951

1,410

1,020

2,521

A

Change (%)

13.6

3.6

0.8

27.0

FY 2011 Grant

355

130

69

157

A

NC CONCORD

New Data Grant

472

152

107

212

A

Change (%)

32.6

17.2

56.6

35.0

FY 2011 Grant

923

312

502

109

B

NC CUMBERLAND

COUNTY

New Data Grant

959

229

143

586

A

Change (%)

4.0

87.8

FY 2011 Grant

1,764

443

385

936

A

NC DURHAM

New Data Grant

1,837

440

380

1,017

A

Change (%)

4.2

-0.6

-1.4

8.6

FY 2011 Grant

1,398

401

238

760

A

NC FAYETTEVILLE

New Data Grant

1,503

387

218

898

A

Change (%)

7.6

-3.6

-8.2

18.2

FY 2011 Grant

579

141

96

342

A

NC GASTONIA

New Data Grant

650

138

128

383

A

Change (%)

12.2

-2.0

33.6

12.2

FY 2011 Grant

360

74

47

239

A

NC GOLDSBORO

New Data Grant

380

70

50

260

A

Change (%)

5.6

-5.2

7.0

8.8

FY 2011 Grant

1,740

492

330

918

A

NC GREENSBORO

New Data Grant

2,121

520

335

1,266

A

Change (%)

22.0

5.8

1.8

37.8

FY 2011 Grant

744

158

79

506

A

NC GREENVILLE

New Data Grant

876

163

83

630

A

Change (%)

17.8

3.0

4.0

24.4

FY 2011 Grant

288

80

63

144

A

NC HICKORY

New Data Grant

340

77

63

200

A

Change (%)

18.2

-3.8

-0.4

38.4

FY 2011 Grant

708

200

118

390

A

NC HIGH POINT

New Data Grant

891

201

118

572

A

Change (%)

26.0

0.6

0.4

46.6

FY 2011 Grant

483

156

83

244

A

NC JACKSONVILLE

New Data Grant

411

135

53

223

A

Change (%)

-14.8

-13.2

-36.6

-8.6

89

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

322

80

76

166

B

NC KANNAPOLIS

New Data Grant

397

137

81

180

B

Change (%)

23.2

70.6

5.8

8.2

FY 2011 Grant

132

35

15

83

A

NC LENOIR

New Data Grant

165

35

18

112

A

Change (%)

25.6

1.8

24.2

35.8

FY 2011 Grant

433

243

50

140

A

NC MECKLENBURG

COUNTY

New Data Grant

488

193

79

216

A

Change (%)

12.6

-20.6

57.4

54.2

FY 2011 Grant

134

33

27

75

A

NC MORGANTON

New Data Grant

177

33

18

126

A

Change (%)

32.2

-1.0

-30.6

69.4

FY 2011 Grant

2,256

784

424

1,048

A

NC RALEIGH

New Data Grant

2,750

779

470

1,501

A

Change (%)

21.8

-0.8

10.8

43.2

FY 2011 Grant

602

115

96

391

A

NC ROCKY MOUNT

New Data Grant

549

111

85

354

A

Change (%)

-8.8

-3.8

-11.2

-9.6

FY 2011 Grant

258

82

27

149

B

NC SALISBURY

New Data Grant

285

65

62

157

A

Change (%)

10.2

91.6

FY 2011 Grant

1,329

648

181

501

A

NC WAKE COUNTY

New Data Grant

1,596

657

333

606

A

Change (%)

20.0

1.4

84.6

21.0

FY 2011 Grant

802

196

83

523

A

NC WILMINGTON

New Data Grant

889

205

80

603

A

Change (%)

10.8

4.8

-2.8

15.2

FY 2011 Grant

1,703

444

312

947

A

NC WINSTON-SALEM New Data Grant

2,123

443

443

1,237

A

Change (%)

24.6

-0.4

42.0

30.6

FY 2011 Grant

313

118

37

158

A

ND BISMARCK

New Data Grant

316

118

30

168

A

Change (%)

1.0

-0.2

-18.8

6.4

FY 2011 Grant

621

185

74

362

A

ND FARGO

New Data Grant

718

203

82

432

A

Change (%)

15.6

10.2

10.8

19.2

FY 2011 Grant

376

99

44

233

A

ND GRAND FORKS

New Data Grant

432

102

32

298

A

Change (%)

15.0

2.8

-26.6

27.8

90

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

224

99

34

91

A

NE BELLEVUE

New Data Grant

325

97

88

141

A

Change (%)

45.4

-2.0

155.2

55.4

FY 2011 Grant

1,598

456

0

1,142

B

NE LINCOLN

New Data Grant

1,754

498

242

1,014

A

Change (%)

9.8

122.2

FY 2011 Grant

4,192

911

530

2,751

B

NE OMAHA

New Data Grant

5,167

1,106

998

3,063

B

Change (%)

23.2

21.4

88.2

11.4

FY 2011 Grant

319

46

0

272

B

NH DOVER

New Data Grant

276

45

0

232

B

Change (%)

-13.2

-3.0

-15.0

FY 2011 Grant

1,729

234

292

1,202

B

NH MANCHESTER

New Data Grant

1,789

270

274

1,245

B

Change (%)

3.6

15.4

-6.2

3.6

FY 2011 Grant

667

121

0

546

B

NH NASHUA

New Data Grant

614

110

0

504

B

Change (%)

-8.0

-9.4

-7.8

FY 2011 Grant

594

40

248

307

B

NH PORTSMOUTH

New Data Grant

534

26

240

268

B

Change (%)

-10.2

-34.2

-3.2

-12.6

FY 2011 Grant

276

50

0

227

B

NH ROCHESTER

New Data Grant

253

72

0

182

B

Change (%)

-8.4

43.8

-19.8

FY 2011 Grant

412

106

119

188

B

NJ

ASBURY PARK

New Data Grant

465

87

121

257

B

Change (%)

13.0

-17.4

2.0

37.0

FY 2011 Grant

1,224

199

622

403

B

NJ

ATLANTIC CITY

New Data Grant

1,228

170

610

448

B

Change (%)

0.4

-14.6

-1.8

11.0

FY 2011 Grant

1,186

412

256

518

A

NJ

ATLANTIC

COUNTY

New Data Grant

1,130

414

239

476

A

Change (%)

-4.8

0.6

-6.6

-8.0

FY 2011 Grant

1,729

132

663

934

B

NJ

BAYONNE

New Data Grant

1,577

128

591

858

B

Change (%)

-8.8

-3.0

-11.0

-8.0

FY 2011 Grant

9,879

916

3,140

5,822

B

NJ

BERGEN COUNTY New Data Grant

8,958

897

2,934

5,128

B

Change (%)

-9.4

-2.2

-6.6

-12.0

91

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

1,067

58

426

582

B

NJ

BLOOMFIELD

New Data Grant

876

54

372

450

B

Change (%)

-18.0

-8.4

-12.8

-22.6

FY 2011 Grant

319

152

47

120

A

NJ

BRICK TOWNSHIP New Data Grant

308

145

45

118

A

Change (%)

-3.4

-5.0

-3.6

-1.4

FY 2011 Grant

373

103

83

187

B

NJ

BRIDGETON

New Data Grant

343

88

73

182

B

Change (%)

-8.0

-14.6

-11.6

-3.0

FY 2011 Grant

1,432

737

202

492

A

NJ

BURLINGTON

COUNTY

New Data Grant

1,416

738

182

496

A

Change (%)

-1.2

0.2

-10.0

0.8

FY 2011 Grant

2,540

565

1,213

761

B

NJ

CAMDEN

New Data Grant

2,452

528

1,207

718

B

Change (%)

-3.4

-6.6

-0.6

-5.8

FY 2011 Grant

2,394

370

271

1,753

B

NJ

CAMDEN

COUNTY

New Data Grant

2,299

375

276

1,647

B

Change (%)

-4.0

1.6

2.0

-6.0

FY 2011 Grant

425

58

301

66

B

NJ

CHERRY HILL

New Data Grant

426

56

287

82

B

Change (%)

0.2

-1.8

-4.6

23.6

FY 2011 Grant

1,317

104

563

650

B

NJ

CLIFTON

New Data Grant

1,162

125

474

563

B

Change (%)

-11.8

20.0

-15.8

-13.4

FY 2011 Grant

1,565

278

635

652

B

NJ

EAST ORANGE

New Data Grant

1,467

273

631

562

B

Change (%)

-6.4

-1.6

-0.6

-13.8

FY 2011 Grant

578

193

223

162

A

NJ

EDISON

New Data Grant

616

193

189

234

A

Change (%)

6.6

0.0

-15.4

44.6

FY 2011 Grant

1,901

442

456

1,003

B

NJ

ELIZABETH

New Data Grant

2,091

241

1,233

618

A

Change (%)

10.0

39.6

FY 2011 Grant

5,698

409

1,916

3,374

B

NJ

ESSEX COUNTY

New Data Grant

4,999

323

1,709

2,967

B

Change (%)

-12.2

-21.2

-10.8

-12.0

FY 2011 Grant

210

41

46

122

B

NJ

EWING

TOWNSHIP

New Data Grant

215

53

49

113

B

Change (%)

2.6

28.6

5.4

-7.2

92

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

292

116

87

89

A

NJ

FRANKLIN

TOWNSHIP

New Data Grant

263

120

58

85

A

Change (%)

-9.8

3.8

-33.0

-5.2

FY 2011 Grant

1,280

293

0

987

B

NJ

GLOUCESTER

COUNTY

New Data Grant

1,205

333

0

872

B

Change (%)

-5.8

13.8

-11.8

FY 2011 Grant

313

125

49

138

A

NJ

GLOUCESTER

TWP

New Data Grant

296

125

67

105

A

Change (%)

-5.4

-0.4

35.0

-24.4

FY 2011 Grant

554

76

89

389

B

NJ

HAMILTON

New Data Grant

548

72

106

370

B

Change (%)

-1.2

-5.2

18.6

-4.8

FY 2011 Grant

147

24

17

106

B

NJ

HAMMONTON

New Data Grant

89

28

0

62

B

Change (%)

-39.0

16.8

-100

-41.6

FY 2011 Grant

197

100

26

72

A

NJ

HOWELL

TOWNSHIP

New Data Grant

177

98

11

68

A

Change (%)

-10.0

-1.2

-56.6

-5.8

FY 2011 Grant

3,412

468

782

2,162

B

NJ

HUDSON

COUNTY

New Data Grant

3,009

383

578

2,048

B

Change (%)

-11.8

-18.2

-26.0

-5.2

FY 2011 Grant

1,022

220

413

389

B

NJ

IRVINGTON

New Data Grant

1,005

166

429

410

B

Change (%)

-1.6

-24.4

3.8

5.4

FY 2011 Grant

180

103

22

55

A

NJ

JACKSON

TOWNSHIP

New Data Grant

218

106

47

65

A

Change (%)

21.0

2.8

116.4

18.0

FY 2011 Grant

5,931

930

2,150

2,851

B

NJ

JERSEY CITY

New Data Grant

5,943

726

2,034

3,183

B

Change (%)

0.2

-22.0

-5.4

11.6

FY 2011 Grant

709

138

169

402

A

NJ

LAKEWOOD

TOWNSHIP

New Data Grant

979

179

289

511

A

Change (%)

38.0

29.8

71.2

27.0

FY 2011 Grant

465

110

80

275

B

NJ

LONG BRANCH

New Data Grant

468

82

104

282

B

Change (%)

0.6

-25.4

30.0

2.6

FY 2011 Grant

1,747

744

478

525

A

NJ

MIDDLESEX

COUNTY

New Data Grant

1,779

764

416

599

A

Change (%)

1.8

2.8

-13.0

14.0

93

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

260

43

0

217

B

NJ

MIDDLETOWN

New Data Grant

234

45

0

189

B

Change (%)

-10.2

4.4

-13.0

FY 2011 Grant

264

85

0

179

B

NJ

MILLVILLE

New Data Grant

284

106

1

177

B

Change (%)

7.6

24.6

-1.0

FY 2011 Grant

2,729

504

0

2,225

B

NJ

MONMOUTH

COUNTY

New Data Grant

2,521

445

0

2,076

B

Change (%)

-7.6

-11.6

-6.6

FY 2011 Grant

2,049

286

0

1,762

B

NJ

MORRIS COUNTY New Data Grant

1,768

240

0

1,527

B

Change (%)

-13.8

-16.0

-13.4

FY 2011 Grant

725

100

223

403

A

NJ

NEW

BRUNSWICK

New Data Grant

787

106

342

339

A

Change (%)

8.4

6.6

53.4

-16.0

FY 2011 Grant

7,836

1,567

4,126

2,143

B

NJ

NEWARK

New Data Grant

7,450

1,159

4,054

2,237

B

Change (%)

-5.0

-26.0

-1.8

4.4

FY 2011 Grant

695

135

110

450

B

NJ

NORTH BERGEN

TOWNSHIP

New Data Grant

539

108

30

401

B

Change (%)

-22.4

-20.2

-72.4

-11.0

FY 2011 Grant

273

22

0

251

B

NJ

OCEAN CITY

New Data Grant

347

20

0

327

B

Change (%)

27.2

-6.4

30.2

FY 2011 Grant

1,112

529

107

476

A

NJ

OCEAN COUNTY New Data Grant

1,161

506

155

500

A

Change (%)

4.4

-4.2

44.4

5.0

FY 2011 Grant

294

127

77

90

A

NJ

OLD BRIDGE

TOWNSHIP

New Data Grant

261

126

64

71

A

Change (%)

-11.4

-1.2

-16.8

-21.2

FY 2011 Grant

255

98

89

67

A

NJ

PARSIPPANY-

TROY HILLS TWP

New Data Grant

235

103

81

51

A

Change (%)

-7.8

5.0

-9.2

-24.4

FY 2011 Grant

1,116

301

176

639

B

NJ

PASSAIC

New Data Grant

1,467

135

779

554

A

Change (%)

31.4

84.2

FY 2011 Grant

950

126

0

824

B

NJ

PASSAIC

COUNTY

New Data Grant

903

131

0

772

B

Change (%)

-5.0

4.0

-6.4

94

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

2,684

685

874

1,125

B

NJ

PATERSON

New Data Grant

2,712

676

843

1,193

B

Change (%)

1.0

-1.2

-3.6

6.0

FY 2011 Grant

646

173

105

369

B

NJ

PERTH AMBOY

New Data Grant

569

155

73

341

B

Change (%)

-12.0

-10.4

-30.6

-7.4

FY 2011 Grant

206

82

58

67

A

NJ

SAYREVILLE

New Data Grant

223

82

67

74

A

Change (%)

8.0

0.8

16.2

9.8

FY 2011 Grant

1,133

179

0

954

B

NJ

SOMERSET

COUNTY

New Data Grant

1,011

147

0

864

B

Change (%)

-10.8

-18.4

-9.4

FY 2011 Grant

409

187

47

175

A

NJ

TOMS RIVER

TOWNSHIP

New Data Grant

392

176

77

140

A

Change (%)

-4.2

-6.2

64.2

-20.4

FY 2011 Grant

2,771

363

1,102

1,306

B

NJ

TRENTON

New Data Grant

2,623

339

1,058

1,227

B

Change (%)

-5.4

-6.8

-4.0

-6.0

FY 2011 Grant

1,269

301

205

763

B

NJ

UNION CITY

New Data Grant

974

128

479

367

A

Change (%)

-23.2

22.0

FY 2011 Grant

4,869

425

1,937

2,507

B

NJ

UNION COUNTY New Data Grant

4,475

389

1,813

2,274

B

Change (%)

-8.0

-8.6

-6.4

-9.4

FY 2011 Grant

635

47

296

292

B

NJ

UNION

TOWNSHIP

New Data Grant

514

48

250

216

B

Change (%)

-19.0

3.0

-15.6

-25.8

FY 2011 Grant

497

114

117

266

A

NJ

VINELAND

New Data Grant

438

117

99

222

A

Change (%)

-11.8

2.2

-15.2

-16.4

FY 2011 Grant

166

101

12

53

A

NJ

WASHINGTON

TOWNSHIP

New Data Grant

164

94

17

54

A

Change (%)

-1.0

-7.0

42.8

1.2

FY 2011 Grant

173

104

19

51

A

NJ

WAYNE

TOWNSHIP

New Data Grant

182

105

23

53

A

Change (%)

4.6

1.2

26.4

4.0

FY 2011 Grant

650

96

257

297

B

NJ

WOODBRIDGE

New Data Grant

594

95

223

276

B

Change (%)

-8.8

-1.6

-13.0

-7.2

95

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

3,996

1,023

876

2,098

A

NM ALBUQUERQUE

New Data Grant

4,233

1,052

861

2,319

A

Change (%)

6.0

2.8

-1.6

10.6

FY 2011 Grant

389

84

98

208

A

NM FARMINGTON

New Data Grant

395

88

121

185

A

Change (%)

1.4

5.4

24.0

-10.8

FY 2011 Grant

916

181

145

591

A

NM LAS CRUCES

New Data Grant

836

188

104

543

A

Change (%)

-8.8

4.2

-28.0

-8.0

FY 2011 Grant

301

160

50

92

A

NM RIO RANCHO

New Data Grant

386

169

61

156

A

Change (%)

28.2

5.6

23.6

69.6

FY 2011 Grant

525

143

120

262

A

NM SANTA FE

New Data Grant

569

131

134

303

A

Change (%)

8.4

-8.6

12.0

16.0

FY 2011 Grant

396

107

116

173

A

NV CARSON CITY

New Data Grant

398

107

90

201

A

Change (%)

0.6

-0.2

-22.2

16.2

FY 2011 Grant

5,799

1,651

1,925

2,222

A

NV CLARK COUNTY

New Data Grant

6,501

1,721

2,114

2,666

A

Change (%)

12.2

4.2

9.8

20.0

FY 2011 Grant

1,042

496

203

344

A

NV HENDERSON

New Data Grant

1,247

497

236

514

A

Change (%)

19.6

0.2

16.4

49.6

FY 2011 Grant

4,632

1,097

1,563

1,971

A

NV LAS VEGAS

New Data Grant

4,638

1,125

1,480

2,033

A

Change (%)

0.2

2.6

-5.4

3.2

FY 2011 Grant

1,532

434

509

590

A

NV NORTH LAS

VEGAS

New Data Grant

1,880

418

780

682

A

Change (%)

22.8

-3.6

53.2

15.6

FY 2011 Grant

1,847

425

641

782

A

NV RENO

New Data Grant

1,971

434

604

932

A

Change (%)

6.6

2.2

-5.8

19.2

FY 2011 Grant

567

173

208

186

A

NV SPARKS

New Data Grant

643

174

201

268

A

Change (%)

13.6

0.8

-3.2

44.2

FY 2011 Grant

3,364

397

1,261

1,705

B

NY ALBANY

New Data Grant

3,361

396

1,185

1,781

B

Change (%)

0.0

-0.4

-6.0

4.4

96

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

525

223

55

247

A

NY AMHERST TOWN New Data Grant

549

236

39

274

A

Change (%)

4.6

5.6

-28.8

11.0

FY 2011 Grant

984

91

325

568

B

NY AUBURN

New Data Grant

915

85

308

522

B

Change (%)

-7.0

-7.2

-5.2

-8.0

FY 2011 Grant

1,161

427

245

489

A

NY BABYLON TOWN New Data Grant

1,025

412

248

366

A

Change (%)

-11.8

-3.6

1.4

-25.2

FY 2011 Grant

2,111

231

870

1,011

B

NY BINGHAMTON

New Data Grant

1,942

212

816

914

B

Change (%)

-8.0

-8.2

-6.2

-9.6

FY 2011 Grant

14,541

1,585

6,614

6,341

B

NY BUFFALO

New Data Grant

14,974

1,361

6,607

7,006

B

Change (%)

3.0

-14.2

-0.2

10.4

FY 2011 Grant

971

128

484

359

B

NY CHEEKTOWAGA

TOWN

New Data Grant

991

136

460

395

B

Change (%)

2.0

6.8

-5.0

9.8

FY 2011 Grant

258

114

27

117

A

NY CLAY TOWN

New Data Grant

213

112

14

87

A

Change (%)

-17.2

-1.2

-48.6

-25.6

FY 2011 Grant

356

75

0

281

B

NY COLONIE TOWN New Data Grant

360

78

0

281

B

Change (%)

1.0

4.6

0.0

FY 2011 Grant

521

62

191

268

B

NY DUNKIRK

New Data Grant

517

59

181

277

B

Change (%)

-0.8

-4.2

-5.4

3.4

FY 2011 Grant

1,330

236

0

1,093

B

NY DUTCHESS

COUNTY

New Data Grant

1,334

237

0

1,097

B

Change (%)

0.2

0.2

0.4

FY 2011 Grant

1,238

133

506

599

B

NY ELMIRA

New Data Grant

1,147

121

498

528

B

Change (%)

-7.4

-9.0

-1.6

-11.8

FY 2011 Grant

2,761

295

533

1,933

B

NY ERIE COUNTY

New Data Grant

2,551

317

422

1,812

B

Change (%)

-7.6

7.4

-20.8

-6.2

FY 2011 Grant

510

45

175

289

B

NY GLEN FALLS

New Data Grant

477

36

161

280

B

Change (%)

-6.4

-19.4

-8.2

-3.4

97

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

376

181

37

158

A

NY GREECE

New Data Grant

422

185

40

197

A

Change (%)

12.4

2.6

8.2

24.4

FY 2011 Grant

451

53

76

322

B

NY HAMBURG

TOWN

New Data Grant

420

67

58

295

B

Change (%)

-6.8

26.2

-24.0

-8.4

FY 2011 Grant

815

391

112

312

A

NY HUNTINGTON

TOWN

New Data Grant

795

138

0

658

B

Change (%)

-2.4

-56.0

FY 2011 Grant

922

59

415

448

B

NY IRONDEQUOIT

New Data Grant

852

78

382

392

B

Change (%)

-7.6

32.0

-8.0

-12.4

FY 2011 Grant

1,850

653

464

733

A

NY ISLIP TOWN

New Data Grant

1,629

647

456

527

A

Change (%)

-12.0

-0.8

-1.8

-28.2

FY 2011 Grant

743

184

165

393

B

NY ITHACA

New Data Grant

789

187

160

442

B

Change (%)

6.2

1.6

-3.2

12.4

FY 2011 Grant

1,272

128

418

726

B

NY JAMESTOWN

New Data Grant

1,120

115

387

619

B

Change (%)

-12.0

-10.6

-7.4

-14.8

FY 2011 Grant

742

75

269

398

B

NY KINGSTON

New Data Grant

744

68

245

431

B

Change (%)

0.2

-9.4

-9.2

8.6

FY 2011 Grant

527

92

117

318

B

NY MIDDLETOWN

New Data Grant

517

85

86

347

B

Change (%)

-2.0

-8.4

-26.4

9.0

FY 2011 Grant

1,737

365

0

1,372

B

NY MONROE

COUNTY

New Data Grant

1,777

425

0

1,352

B

Change (%)

2.4

16.4

-1.4

FY 2011 Grant

1,651

203

566

881

B

NY MOUNT VERNON New Data Grant

1,506

146

571

789

B

Change (%)

-8.8

-27.8

0.8

-10.4

FY 2011 Grant

14,136

1,383

6,545

6,208

B

NY NASSAU

COUNTY

New Data Grant

13,833

1,102

6,568

6,163

B

Change (%)

-2.2

-20.4

0.4

-0.8

FY 2011 Grant

1,519

155

513

851

B

NY NEW ROCHELLE

New Data Grant

1,470

139

465

866

B

Change (%)

-3.2

-10.6

-9.4

1.8

98

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

163,359

35,217

41,200

86,942

B

NY NEW YORK

New Data Grant 168,010

27,435

42,510

98,065

B

Change (%)

2.8

-22.0

3.2

12.8

FY 2011 Grant

768

148

229

391

B

NY NEWBURGH

New Data Grant

771

123

215

433

B

Change (%)

0.4

-16.6

-6.4

10.8

FY 2011 Grant

2,287

226

1,279

782

B

NY NIAGARA FALLS

New Data Grant

2,386

193

1,270

923

B

Change (%)

4.4

-14.4

-0.8

18.0

FY 2011 Grant

2,061

281

315

1,466

B

NY ONONDAGA

COUNTY

New Data Grant

1,882

296

220

1,366

B

Change (%)

-8.8

5.2

-30.2

-6.8

FY 2011 Grant

1,569

287

0

1,282

B

NY ORANGE

COUNTY

New Data Grant

1,562

258

0

1,304

B

Change (%)

-0.4

-10.0

1.6

FY 2011 Grant

934

140

350

445

B

NY POUGHKEEPSIE

New Data Grant

878

121

303

454

B

Change (%)

-6.0

-13.0

-13.4

2.0

FY 2011 Grant

8,718

1,155

3,386

4,177

B

NY ROCHESTER

New Data Grant

8,808

1,047

3,279

4,482

B

Change (%)

1.0

-9.2

-3.2

7.4

FY 2011 Grant

1,888

565

503

819

A

NY ROCKLAND

COUNTY

New Data Grant

2,136

584

697

855

A

Change (%)

13.2

3.2

38.6

4.4

FY 2011 Grant

1,089

100

551

438

B

NY ROME

New Data Grant

1,026

95

536

394

B

Change (%)

-5.8

-4.4

-2.6

-10.2

FY 2011 Grant

334

45

0

289

B

NY SARATOGA

SPRINGS

New Data Grant

379

37

0

342

B

Change (%)

13.4

-17.6

18.2

FY 2011 Grant

2,317

259

764

1,294

B

NY SCHENECTADY

New Data Grant

2,165

216

690

1,259

B

Change (%)

-6.6

-16.6

-9.8

-2.6

FY 2011 Grant

3,335

1,442

530

1,364

A

NY SUFFOLK

COUNTY

New Data Grant

3,209

1,407

548

1,253

A

Change (%)

-3.8

-2.4

3.6

-8.2

FY 2011 Grant

5,586

791

2,321

2,474

B

NY SYRACUSE

New Data Grant

5,288

703

2,193

2,391

B

Change (%)

-5.4

-11.2

-5.4

-3.4

99

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

1,723

112

1,074

537

B

NY TONAWANDA

TOWN

New Data Grant

1,624

127

1,029

468

B

Change (%)

-5.8

13.8

-4.2

-12.8

FY 2011 Grant

1,869

183

672

1,014

B

NY TROY

New Data Grant

1,793

189

626

979

B

Change (%)

-4.0

3.2

-6.8

-3.6

FY 2011 Grant

1,292

132

535

625

B

NY UNION TOWN

New Data Grant

1,190

122

492

575

B

Change (%)

-7.8

-7.0

-8.0

-8.0

FY 2011 Grant

2,634

299

1,158

1,177

B

NY UTICA

New Data Grant

2,456

278

1,084

1,093

B

Change (%)

-6.8

-7.0

-6.4

-7.2

FY 2011 Grant

320

45

85

191

B

NY WEST SENECA

New Data Grant

302

51

68

184

B

Change (%)

-5.8

13.2

-20.2

-3.6

FY 2011 Grant

5,379

544

749

4,085

B

NY WESTCHESTER

COUNTY

New Data Grant

5,072

440

723

3,910

B

Change (%)

-5.6

-19.2

-3.6

-4.2

FY 2011 Grant

828

108

230

490

B

NY WHITE PLAINS

New Data Grant

929

98

228

602

B

Change (%)

12.2

-9.2

-0.4

23.0

FY 2011 Grant

3,390

635

1,065

1,690

B

NY YONKERS

New Data Grant

3,302

488

1,094

1,720

B

Change (%)

-2.6

-23.2

2.8

1.8

FY 2011 Grant

6,191

780

2,862

2,549

B

OH AKRON

New Data Grant

6,248

813

2,903

2,532

B

Change (%)

1.0

4.2

1.4

-0.6

FY 2011 Grant

627

81

258

288

B

OH ALLIANCE

New Data Grant

632

68

255

309

B

Change (%)

0.8

-16.4

-1.0

7.2

FY 2011 Grant

685

77

303

305

B

OH BARBERTON

New Data Grant

675

94

296

285

B

Change (%)

-1.6

21.8

-2.4

-6.6

FY 2011 Grant

271

56

13

203

A

OH BOWLING

GREEN

New Data Grant

290

58

12

220

A

Change (%)

7.0

4.0

-5.6

8.4

FY 2011 Grant

1,048

483

87

478

A

OH BUTLER COUNTY

New Data Grant

1,246

497

134

615

A

Change (%)

19.0

2.8

54.6

28.6

100

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

2,617

316

1,152

1,149

B

OH CANTON

New Data Grant

2,775

356

1,195

1,225

B

Change (%)

6.0

12.6

3.8

6.6

FY 2011 Grant

11,752

1,471

5,266

5,015

B

OH CINCINNATI

New Data Grant

12,502

1,451

5,607

5,444

B

Change (%)

6.4

-1.4

6.4

8.6

FY 2011 Grant

21,655

2,584

11,039

8,031

B

OH CLEVELAND

New Data Grant

22,540

2,338

11,271

8,931

B

Change (%)

4.0

-9.6

2.2

11.2

FY 2011 Grant

1,602

111

592

898

B

OH CLEVELAND

HEIGHTS

New Data Grant

1,625

147

571

907

B

Change (%)

1.4

32.2

-3.6

1.0

FY 2011 Grant

5,845

1,487

745

3,613

A

OH COLUMBUS

New Data Grant

7,061

1,517

1,133

4,410

A

Change (%)

20.8

2.0

52.2

22.0

FY 2011 Grant

3,874

603

1,083

2,188

B

OH CUYAHOGA

COUNTY

New Data Grant

3,386

753

621

2,012

B

Change (%)

-12.6

24.8

-42.6

-8.0

FY 2011 Grant

643

63

261

319

B

OH CUYAHOGA

FALLS

New Data Grant

661

86

270

304

B

Change (%)

2.6

36.6

3.6

-4.8

FY 2011 Grant

5,742

754

2,998

1,990

B

OH DAYTON

New Data Grant

5,781

779

3,094

1,908

B

Change (%)

0.6

3.2

3.2

-4.2

FY 2011 Grant

1,022

180

409

433

B

OH EAST CLEVELAND New Data Grant

1,268

165

481

623

B

Change (%)

24.0

-8.4

17.6

43.6

FY 2011 Grant

636

135

135

365

B

OH ELYRIA

New Data Grant

656

157

133

365

B

Change (%)

3.2

16.4

-1.4

0.0

FY 2011 Grant

974

107

595

273

B

OH EUCLID

New Data Grant

985

132

558

295

B

Change (%)

1.0

23.8

-6.2

8.0

FY 2011 Grant

236

61

21

153

A

OH FAIRBORN

New Data Grant

240

62

10

168

A

Change (%)

1.8

1.6

-52.2

9.4

FY 2011 Grant

1,658

798

170

690

A

OH FRANKLIN

COUNTY

New Data Grant

2,023

806

344

873

A

Change (%)

22.0

1.0

102.6

26.6

101

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

1,338

168

574

596

B

OH HAMILTON CITY

New Data Grant

1,441

224

563

655

B

Change (%)

7.8

33.0

-1.8

9.8

FY 2011 Grant

2,914

572

227

2,115

B

OH HAMILTON

COUNTY

New Data Grant

3,047

663

332

2,053

B

Change (%)

4.6

15.8

46.2

-3.0

FY 2011 Grant

271

54

19

198

A

OH KENT

New Data Grant

296

56

6

234

A

Change (%)

9.2

3.2

-66.6

18.2

FY 2011 Grant

524

56

354

114

B

OH KETTERING

New Data Grant

513

79

310

123

B

Change (%)

-2.2

41.6

-12.2

8.0

FY 2011 Grant

1,281

211

363

707

B

OH LAKE COUNTY

New Data Grant

1,338

272

367

700

B

Change (%)

4.4

28.8

1.0

-1.0

FY 2011 Grant

2,018

105

613

1,300

B

OH LAKEWOOD

New Data Grant

1,930

132

577

1,222

B

Change (%)

-4.4

26.0

-6.0

-6.0

FY 2011 Grant

510

78

96

337

B

OH LANCASTER

New Data Grant

488

97

72

319

B

Change (%)

-4.4

25.4

-24.8

-5.4

FY 2011 Grant

1,125

180

487

459

B

OH LIMA

New Data Grant

1,064

195

463

406

B

Change (%)

-5.4

8.6

-5.0

-11.4

FY 2011 Grant

1,129

244

416

469

B

OH LORAIN

New Data Grant

1,265

306

480

479

B

Change (%)

12.0

25.2

15.4

2.2

FY 2011 Grant

903

159

271

473

B

OH MANSFIELD

New Data Grant

869

147

282

440

B

Change (%)

-3.8

-7.6

4.2

-7.0

FY 2011 Grant

401

47

140

214

B

OH MARIETTA

New Data Grant

378

56

137

185

B

Change (%)

-5.6

20.2

-2.2

-13.6

FY 2011 Grant

660

69

198

393

B

OH MASSILLON

New Data Grant

654

83

199

372

B

Change (%)

-0.8

21.4

0.6

-5.4

FY 2011 Grant

159

100

10

48

A

OH MENTOR

New Data Grant

186

91

11

84

A

Change (%)

17.0

-9.4

2.0

75.4

102

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

627

136

146

345

B

OH MIDDLETOWN

New Data Grant

735

196

175

364

B

Change (%)

17.4

44.4

19.8

5.6

FY 2011 Grant

1,642

641

173

827

A

OH MONTGOMERY

COUNTY

New Data Grant

1,875

661

218

996

A

Change (%)

14.2

3.0

26.0

20.4

FY 2011 Grant

775

124

192

460

B

OH NEWARK

New Data Grant

797

168

183

447

B

Change (%)

2.8

35.8

-4.8

-2.8

FY 2011 Grant

944

88

589

267

B

OH PARMA

New Data Grant

862

96

520

247

B

Change (%)

-8.6

9.2

-11.8

-7.6

FY 2011 Grant

747

89

280

378

B

OH SANDUSKY

New Data Grant

759

103

272

384

B

Change (%)

1.6

16.4

-3.0

1.6

FY 2011 Grant

1,813

223

776

813

B

OH SPRINGFIELD

New Data Grant

1,765

260

778

727

B

Change (%)

-2.6

16.4

0.2

-10.6

FY 2011 Grant

1,329

255

32

1,042

B

OH STARK COUNTY

New Data Grant

1,182

322

0

860

B

Change (%)

-11.2

26.2

-100

-17.4

FY 2011 Grant

678

80

376

222

B

OH STEUBENVILLE

New Data Grant

637

83

369

185

B

Change (%)

-6.0

4.8

-1.8

-16.8

FY 2011 Grant

909

500

77

331

A

OH SUMMIT COUNTY New Data Grant

1,056

516

94

446

A

Change (%)

16.2

3.2

21.4

34.6

FY 2011 Grant

7,048

1,159

2,438

3,452

B

OH TOLEDO

New Data Grant

7,682

1,244

2,733

3,706

B

Change (%)

9.0

7.4

12.0

7.4

FY 2011 Grant

1,220

187

577

456

B

OH WARREN

New Data Grant

1,200

208

587

404

B

Change (%)

-1.6

11.6

1.8

-11.4

FY 2011 Grant

649

390

52

207

A

OH WARREN

COUNTY

New Data Grant

830

396

84

350

A

Change (%)

27.8

1.6

59.8

69.2

FY 2011 Grant

3,640

404

2,221

1,016

B

OH YOUNGSTOWN

New Data Grant

3,758

404

2,250

1,104

B

Change (%)

3.2

0.0

1.4

8.6

103

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

370

157

44

169

A

OK EDMOND

New Data Grant

410

157

37

216

A

Change (%)

11.0

0.2

-15.8

27.8

FY 2011 Grant

519

142

130

246

B

OK ENID

New Data Grant

454

152

106

196

B

Change (%)

-12.4

6.6

-18.4

-20.4

FY 2011 Grant

779

176

129

474

A

OK LAWTON

New Data Grant

765

187

137

441

A

Change (%)

-1.8

6.0

6.6

-6.8

FY 2011 Grant

437

111

64

262

A

OK MIDWEST CITY

New Data Grant

425

105

69

251

A

Change (%)

-2.8

-5.2

8.4

-4.4

FY 2011 Grant

259

104

47

108

A

OK MOORE CITY

New Data Grant

311

106

86

118

A

Change (%)

20.0

2.2

83.4

9.4

FY 2011 Grant

778

211

92

475

A

OK NORMAN

New Data Grant

828

214

98

516

A

Change (%)

6.6

1.4

6.6

8.8

FY 2011 Grant

4,771

1,083

906

2,781

A

OK OKLAHOMA CITY New Data Grant

4,878

1,118

953

2,806

A

Change (%)

2.2

3.2

5.2

1.0

FY 2011 Grant

364

101

75

188

B

OK SHAWNEE

New Data Grant

337

114

80

144

B

Change (%)

-7.2

13.0

6.0

-23.4

FY 2011 Grant

3,323

753

666

1,903

A

OK TULSA

New Data Grant

3,595

756

698

2,142

A

Change (%)

8.2

0.4

4.8

12.6

FY 2011 Grant

1,172

504

177

491

A

OK TULSA COUNTY

New Data Grant

1,367

511

280

577

A

Change (%)

16.6

1.2

58.2

17.4

FY 2011 Grant

186

41

19

127

A

OR ASHLAND

New Data Grant

184

67

0

118

B

Change (%)

-1.0

-47.2

FY 2011 Grant

554

181

165

209

A

OR BEAVERTON

New Data Grant

639

173

197

269

A

Change (%)

15.2

-4.2

19.4

28.6

FY 2011 Grant

400

149

61

189

A

OR BEND

New Data Grant

397

148

59

190

A

Change (%)

-0.8

-1.2

-2.8

0.2

104

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

1,931

750

406

775

A

OR CLACKAMAS

COUNTY

New Data Grant

2,189

733

451

1,006

A

Change (%)

13.4

-2.4

11.0

29.8

FY 2011 Grant

490

100

68

322

A

OR CORVALLIS

New Data Grant

516

105

42

369

A

Change (%)

5.4

5.4

-37.8

14.4

FY 2011 Grant

1,254

296

159

799

A

OR EUGENE

New Data Grant

1,356

301

161

894

A

Change (%)

8.2

1.6

1.2

12.0

FY 2011 Grant

801

198

212

391

A

OR GRESHAM

New Data Grant

972

204

302

467

A

Change (%)

21.4

3.0

42.2

19.4

FY 2011 Grant

602

185

195

223

A

OR HILLSBORO

New Data Grant

731

177

240

314

A

Change (%)

21.2

-4.4

23.0

41.0

FY 2011 Grant

562

142

116

304

A

OR MEDFORD

New Data Grant

617

144

148

325

A

Change (%)

9.8

1.6

27.8

6.8

FY 2011 Grant

281

113

55

113

A

OR MULTNOMAH

COUNTY

New Data Grant

324

88

89

147

A

Change (%)

15.2

-21.8

61.4

29.6

FY 2011 Grant

9,032

1,424

1,509

6,099

B

OR PORTLAND

New Data Grant

8,637

1,557

1,278

5,802

B

Change (%)

-4.4

9.4

-15.2

-4.8

FY 2011 Grant

1,313

301

336

676

A

OR SALEM

New Data Grant

1,326

298

358

670

A

Change (%)

1.0

-0.8

6.6

-1.0

FY 2011 Grant

553

111

112

330

A

OR SPRINGFIELD

New Data Grant

507

115

85

308

A

Change (%)

-8.2

3.4

-24.2

-6.6

FY 2011 Grant

1,819

670

441

708

A

OR WASHINGTON

COUNTY

New Data Grant

2,071

664

493

914

A

Change (%)

13.8

-0.8

11.8

29.0

FY 2011 Grant

783

42

371

370

B

PA

ABINGTON

New Data Grant

718

35

346

337

B

Change (%)

-8.2

-16.6

-6.6

-9.0

FY 2011 Grant

14,918

1,409

6,232

7,277

B

PA

ALLEGHENY

COUNTY

New Data Grant

14,110

1,367

5,959

6,783

B

Change (%)

-5.4

-3.0

-4.4

-6.8

105

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

2,506

398

686

1,422

B

PA

ALLENTOWN

New Data Grant

2,182

445

540

1,197

B

Change (%)

-13.0

11.8

-21.4

-15.8

FY 2011 Grant

1,815

179

724

912

B

PA

ALTOONA

New Data Grant

1,642

153

709

781

B

Change (%)

-9.6

-14.8

-2.0

-14.4

FY 2011 Grant

3,535

342

1,562

1,631

B

PA

BEAVER COUNTY New Data Grant

3,308

316

1,549

1,443

B

Change (%)

-6.4

-7.6

-0.8

-11.6

FY 2011 Grant

340

114

75

152

A

PA

BENSALEM

TOWNSHIP

New Data Grant

322

117

80

125

A

Change (%)

-5.4

2.6

6.8

-17.4

FY 2011 Grant

2,442

285

0

2,156

B

PA

BERKS COUNTY

New Data Grant

2,336

342

0

1,994

B

Change (%)

-4.4

19.8

-7.6

FY 2011 Grant

1,526

210

502

814

B

PA

BETHLEHEM

New Data Grant

1,343

182

464

697

B

Change (%)

-12.0

-13.6

-7.4

-14.4

FY 2011 Grant

620

88

437

94

B

PA

BRISTOL

TOWNSHIP

New Data Grant

592

78

419

94

B

Change (%)

-4.4

-11.6

-4.0

0.2

FY 2011 Grant

2,147

381

0

1,766

B

PA

BUCKS COUNTY

New Data Grant

1,874

384

0

1,490

B

Change (%)

-12.8

0.6

-15.6

FY 2011 Grant

385

46

80

259

B

PA

CARLISLE

New Data Grant

327

33

76

218

B

Change (%)

-15.0

-29.0

-5.4

-15.6

FY 2011 Grant

1,285

195

730

359

B

PA

CHESTER

New Data Grant

1,322

224

755

343

B

Change (%)

2.8

14.6

3.4

-4.6

FY 2011 Grant

2,488

465

0

2,023

B

PA

CHESTER

COUNTY

New Data Grant

2,348

530

0

1,818

B

Change (%)

-5.6

14.0

-10.2

FY 2011 Grant

1,229

231

0

999

B

PA

CUMBERLAND

COUNTY

New Data Grant

1,123

214

0

909

B

Change (%)

-8.6

-7.4

-9.0

FY 2011 Grant

1,367

248

0

1,118

B

PA

DAUPHIN

COUNTY

New Data Grant

1,284

271

0

1,013

B

Change (%)

-6.2

9.0

-100

-9.4

106

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

3,830

505

1,028

2,296

B

PA

DELAWARE

COUNTY

New Data Grant

3,530

487

987

2,055

B

Change (%)

-7.8

-3.6

-4.0

-10.6

FY 2011 Grant

868

79

270

519

B

PA

EASTON

New Data Grant

812

80

258

473

B

Change (%)

-6.6

0.4

-4.4

-8.8

FY 2011 Grant

3,201

391

1,303

1,507

B

PA

ERIE

New Data Grant

3,130

411

1,297

1,423

B

Change (%)

-2.2

5.0

-0.4

-5.6

FY 2011 Grant

1,877

250

902

725

B

PA

HARRISBURG

New Data Grant

2,093

247

859

987

B

Change (%)

11.4

-1.4

-4.8

36.2

FY 2011 Grant

904

37

409

458

B

PA

HAVERFORD

New Data Grant

836

24

397

414

B

Change (%)

-7.6

-35.0

-2.8

-9.6

FY 2011 Grant

864

69

330

465

B

PA

HAZLETON

New Data Grant

713

70

278

364

B

Change (%)

-17.4

2.2

-15.6

-21.8

FY 2011 Grant

1,419

123

743

554

B

PA

JOHNSTOWN

New Data Grant

1,339

116

737

486

B

Change (%)

-5.6

-5.4

-0.8

-12.4

FY 2011 Grant

1,628

236

453

939

B

PA

LANCASTER CITY New Data Grant

1,575

241

393

941

B

Change (%)

-3.2

2.2

-13.2

0.2

FY 2011 Grant

3,042

515

0

2,527

B

PA

LANCASTER

COUNTY

New Data Grant

2,812

543

0

2,269

B

Change (%)

-7.6

5.6

-10.2

FY 2011 Grant

762

82

261

419

B

PA

LEBANON

New Data Grant

697

93

240

364

B

Change (%)

-8.6

13.4

-8.2

-13.2

FY 2011 Grant

1,313

163

0

1,150

B

PA

LEHIGH COUNTY New Data Grant

1,278

177

0

1,101

B

Change (%)

-2.6

8.4

-4.2

FY 2011 Grant

1,093

53

398

642

B

PA

LOWER MERION

New Data Grant

1,016

59

382

575

B

Change (%)

-7.0

12.0

-4.0

-10.4

FY 2011 Grant

4,567

440

1,169

2,957

B

PA

LUZERNE

COUNTY

New Data Grant

4,296

418

1,104

2,775

B

Change (%)

-6.0

-5.2

-5.6

-6.2

107

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

1,103

112

577

414

B

PA

MCKEESPORT

New Data Grant

1,091

112

596

382

B

Change (%)

-1.0

0.4

3.2

-7.6

FY 2011 Grant

218

101

12

105

A

PA

MILLCREEK

TOWNSHIP

New Data Grant

219

103

11

105

A

Change (%)

0.6

2.0

-10.0

0.6

FY 2011 Grant

3,333

460

0

2,873

B

PA

MONTGOMERY

COUNTY

New Data Grant

3,212

525

0

2,688

B

Change (%)

-3.6

14.2

-6.4

FY 2011 Grant

911

111

331

470

B

PA

NORRISTOWN

New Data Grant

852

104

294

454

B

Change (%)

-6.4

-6.0

-11.0

-3.4

FY 2011 Grant

1,624

172

0

1,452

B

PA

NORTHAMPTON

COUNTY

New Data Grant

1,624

167

0

1,456

B

Change (%)

0.0

-2.8

0.4

FY 2011 Grant

686

74

416

196

B

PA

PENN HILLS

New Data Grant

770

83

427

259

B

Change (%)

12.2

13.4

2.8

32.0

FY 2011 Grant

46,187

7,094

18,235

20,858

B

PA

PHILADELPHIA

New Data Grant

43,091

6,485

18,096

18,510

B

Change (%)

-6.8

-8.6

-0.8

-11.2

FY 2011 Grant

15,038

1,348

7,439

6,251

B

PA

PITTSBURGH

New Data Grant

14,651

1,146

7,379

6,126

B

Change (%)

-2.6

-15.0

-0.8

-2.0

FY 2011 Grant

2,805

436

830

1,538

B

PA

READING

New Data Grant

2,622

485

723

1,414

B

Change (%)

-6.6

11.2

-12.8

-8.0

FY 2011 Grant

3,098

228

1,191

1,678

B

PA

SCRANTON

New Data Grant

2,788

232

1,117

1,440

B

Change (%)

-10.0

1.4

-6.2

-14.2

FY 2011 Grant

627

59

290

279

B

PA

SHARON

New Data Grant

599

48

293

258

B

Change (%)

-4.6

-18.8

1.2

-7.4

FY 2011 Grant

644

77

110

457

A

PA

STATE COLLEGE

New Data Grant

568

81

108

379

A

Change (%)

-11.8

5.0

-2.0

-17.0

FY 2011 Grant

1,776

157

762

857

B

PA

UPPER DARBY

New Data Grant

1,531

172

696

663

B

Change (%)

-13.8

9.6

-8.6

-22.6

108

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

3,899

412

1,357

2,130

B

PA

WASHINGTON

COUNTY

New Data Grant

3,620

377

1,327

1,917

B

Change (%)

-7.2

-8.6

-2.2

-10.0

FY 2011 Grant

4,155

530

1,104

2,522

B

PA

WESTMORELAND

COUNTY

New Data Grant

3,890

503

1,025

2,362

B

Change (%)

-6.4

-5.0

-7.2

-6.4

FY 2011 Grant

1,752

149

680

923

B

PA

WILKES-BARRE

New Data Grant

1,736

163

660

913

B

Change (%)

-1.0

9.6

-3.0

-1.2

FY 2011 Grant

1,151

128

421

601

B

PA

WILLIAMSPORT

New Data Grant

1,112

130

411

570

B

Change (%)

-3.4

1.8

-2.2

-5.2

FY 2011 Grant

1,531

204

517

810

B

PA

YORK

New Data Grant

1,359

230

465

663

B

Change (%)

-11.2

13.2

-10.0

-18.2

FY 2011 Grant

2,365

330

0

2,035

B

PA

YORK COUNTY

New Data Grant

2,205

393

0

1,812

B

Change (%)

-6.8

19.2

-11.0

FY 2011 Grant

1,681

131

318

1,232

A

PR

AGUADILLA

MUNICIPIO

New Data Grant

1,351

118

163

1,071

A

Change (%)

-19.6

-10.2

-48.8

-13.0

FY 2011 Grant

2,472

199

505

1,767

A

PR

ARECIBO

MUNICIPIO

New Data Grant

1,809

186

179

1,444

A

Change (%)

-26.8

-6.4

-64.6

-18.2

FY 2011 Grant

4,109

423

992

2,694

A

PR

BAYAMÓN

MUNICIPIO

New Data Grant

3,009

401

575

2,033

A

Change (%)

-26.8

-5.2

-42.0

-24.6

FY 2011 Grant

1,122

106

243

774

A

PR

CABO ROJO

MUNICIPIO

New Data Grant

992

98

148

745

A

Change (%)

-11.6

-7.0

-39.0

-3.8

FY 2011 Grant

3,054

277

729

2,048

A

PR

CAGUAS

MUNICIPIO

New Data Grant

2,252

275

353

1,624

A

Change (%)

-26.2

-0.6

-51.6

-20.8

FY 2011 Grant

1,207

93

289

825

A

PR

CANOVANAS

MUNICIPIO

New Data Grant

838

92

174

573

A

Change (%)

-30.6

-1.2

-40.0

-30.6

FY 2011 Grant

3,502

362

943

2,198

A

PR

CAROLINA

MUNICIPIO

New Data Grant

2,731

341

757

1,633

A

Change (%)

-22.0

-5.8

-19.6

-25.8

109

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

1,178

91

255

832

A

PR

CAYEY

MUNICIPIO

New Data Grant

864

93

159

612

A

Change (%)

-26.6

1.8

-37.6

-26.4

FY 2011 Grant

1,073

95

278

700

A

PR

CIDRA

MUNICIPIO

New Data Grant

846

84

146

616

A

Change (%)

-21.2

-12.0

-47.4

-12.0

FY 2011 Grant

873

82

191

599

A

PR

FAJARDO

MUNICIPIO

New Data Grant

741

71

146

524

A

Change (%)

-15.2

-13.0

-23.8

-12.6

FY 2011 Grant

1,112

88

230

794

A

PR

GUAYAMA

MUNICIPIO

New Data Grant

915

87

186

642

A

Change (%)

-17.6

-0.2

-19.4

-19.0

FY 2011 Grant

1,727

199

462

1,066

A

PR

GUAYNABO

MUNICIPIO

New Data Grant

1,229

189

201

840

A

Change (%)

-28.8

-5.2

-56.6

-21.2

FY 2011 Grant

1,413

118

321

974

A

PR

HUMACAO

MUNICIPIO

New Data Grant

1,202

113

251

838

A

Change (%)

-15.0

-4.4

-21.8

-14.0

FY 2011 Grant

1,183

94

226

863

A

PR

ISABELA

MUNICIPIO

New Data Grant

1,000

88

96

816

A

Change (%)

-15.6

-6.2

-57.6

-5.4

FY 2011 Grant

1,433

103

327

1,002

A

PR

JUANA DIAZ

MUNICIPIO

New Data Grant

1,202

98

294

810

A

Change (%)

-16.2

-5.4

-10.0

-19.2

FY 2011 Grant

1,194

97

271

825

A

PR

MANATI

MUNICIPIO

New Data Grant

1,020

85

202

732

A

Change (%)

-14.6

-12.6

-25.4

-11.2

FY 2011 Grant

2,562

178

597

1,787

A

PR

MAYAGÜEZ

MUNICIPIO

New Data Grant

1,877

172

239

1,466

A

Change (%)

-26.8

-3.6

-60.0

-18.0

FY 2011 Grant

4,648

345

962

3,342

A

PR

PONCE

MUNICIPIO

New Data Grant

3,436

321

546

2,569

A

Change (%)

-26.0

-7.0

-43.2

-23.2

FY 2011 Grant

1,293

111

334

849

A

PR

RIO GRANDE

MUNICIPIO

New Data Grant

1,007

105

233

670

A

Change (%)

-22.0

-5.4

-30.2

-21.2

FY 2011 Grant

942

73

231

638

A

PR

SAN GERMÁN

MUNICIPIO

New Data Grant

748

68

110

570

A

Change (%)

-20.6

-6.0

-52.6

-10.6

110

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

9,328

813

2,412

6,103

A

PR

SAN JUAN

MUNICIPIO

New Data Grant

6,975

2,827

3,448

700

B

Change (%)

-25.2

-53.6

FY 2011 Grant

1,250

94

267

890

A

PR

SAN SEBASTIÁN

MUNICIPIO

New Data Grant

1,017

82

101

834

A

Change (%)

-18.6

-12.8

-62.0

-6.2

FY 2011 Grant

1,407

163

369

875

A

PR

TOA ALTA

MUNICIPIO

New Data Grant

1,321

143

220

959

A

Change (%)

-6.0

-12.4

-40.4

9.6

FY 2011 Grant

1,912

183

425

1,304

A

PR

TOA BAJA

MUNICIPIO

New Data Grant

1,549

173

329

1,048

A

Change (%)

-19.0

-5.8

-22.6

-19.6

FY 2011 Grant

1,420

171

355

894

A

PR

TRUJILLO ALTO

MUNICIPIO

New Data Grant

1,091

144

194

753

A

Change (%)

-23.2

-15.4

-45.4

-15.8

FY 2011 Grant

1,553

126

326

1,100

A

PR

VEGA BAJA

MUNICIPIO

New Data Grant

1,229

115

151

963

A

Change (%)

-20.8

-8.6

-53.8

-12.4

FY 2011 Grant

1,322

94

307

921

A

PR

YAUCO

MUNICIPIO

New Data Grant

1,081

81

178

822

A

Change (%)

-18.2

-13.8

-42.0

-10.8

FY 2011 Grant

1,012

115

252

645

B

RI

CRANSTON

New Data Grant

1,049

104

238

708

B

Change (%)

3.8

-9.6

-5.8

9.8

FY 2011 Grant

749

87

181

481

B

RI

EAST

PROVIDENCE

New Data Grant

756

82

192

482

B

Change (%)

1.0

-6.2

6.6

0.2

FY 2011 Grant

1,891

256

621

1,014

B

RI

PAWTUCKET

New Data Grant

1,985

213

615

1,157

B

Change (%)

5.0

-17.0

-0.8

14.2

FY 2011 Grant

5,143

985

1,745

2,413

B

RI

PROVIDENCE

New Data Grant

5,274

740

1,628

2,905

B

Change (%)

2.6

-24.8

-6.6

20.4

FY 2011 Grant

864

106

227

531

B

RI

WARWICK

New Data Grant

971

112

242

617

B

Change (%)

12.4

5.8

6.4

16.2

FY 2011 Grant

1,219

173

341

704

B

RI

WOONSOCKET

New Data Grant

1,278

161

360

757

B

Change (%)

4.8

-7.2

5.4

7.6

111

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

195

57

16

123

A

SC

AIKEN

New Data Grant

211

57

15

139

A

Change (%)

7.8

-0.2

-3.2

13.0

FY 2011 Grant

652

104

435

113

B

SC

ANDERSON

New Data Grant

632

103

433

96

B

Change (%)

-3.0

-0.8

-0.6

-14.4

FY 2011 Grant

965

370

0

596

B

SC

CHARLESTON

New Data Grant

960

337

0

623

B

Change (%)

-0.6

-9.0

4.6

FY 2011 Grant

1,853

479

268

1,106

A

SC

CHARLESTON

COUNTY

New Data Grant

1,724

481

219

1,024

A

Change (%)

-7.0

0.6

-18.0

-7.4

FY 2011 Grant

1,128

250

147

731

A

SC

COLUMBIA

New Data Grant

973

366

199

408

B

Change (%)

-13.8

-49.8

FY 2011 Grant

305

62

42

200

A

SC

FLORENCE

New Data Grant

252

71

27

153

A

Change (%)

-17.4

14.8

-35.6

-23.4

FY 2011 Grant

927

178

470

278

B

SC

GREENVILLE

New Data Grant

923

180

499

244

B

Change (%)

-0.4

1.2

6.2

-12.6

FY 2011 Grant

2,207

775

318

1,114

A

SC

GREENVILLE

COUNTY

New Data Grant

2,596

774

337

1,486

A

Change (%)

17.6

-0.2

6.0

33.4

FY 2011 Grant

1,403

462

192

749

A

SC

HORRY COUNTY

New Data Grant

2,081

478

555

1,048

A

Change (%)

48.4

3.6

188.6

40.0

FY 2011 Grant

1,370

509

167

694

A

SC

LEXINGTON

COUNTY

New Data Grant

1,516

519

198

798

A

Change (%)

10.6

2.2

19.0

15.0

FY 2011 Grant

1,265

431

196

638

A

SC

RICHLAND

COUNTY

New Data Grant

1,316

453

140

723

A

Change (%)

4.0

5.0

-28.6

13.2

FY 2011 Grant

435

134

68

233

A

SC

ROCK HILL

New Data Grant

544

128

79

337

A

Change (%)

25.2

-4.6

16.6

44.6

FY 2011 Grant

678

184

328

166

B

SC

SPARTANBURG

New Data Grant

696

145

361

190

B

Change (%)

2.8

-21.4

10.2

14.8

112

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

1,183

408

177

598

A

SC

SPARTANBURG

COUNTY

New Data Grant

1,298

417

181

701

A

Change (%)

9.8

2.2

2.2

17.2

FY 2011 Grant

203

87

26

90

A

SC

SUMMERVILLE

New Data Grant

225

84

41

101

A

Change (%)

10.6

-4.4

57.6

11.6

FY 2011 Grant

338

74

39

224

A

SC

SUMTER

New Data Grant

348

78

33

237

A

Change (%)

3.0

5.2

-17.6

6.0

FY 2011 Grant

452

130

64

258

A

SD

RAPID CITY

New Data Grant

522

131

80

312

A

Change (%)

15.6

1.0

24.2

20.8

FY 2011 Grant

768

305

111

352

A

SD

SIOUX FALLS

New Data Grant

905

297

153

455

A

Change (%)

17.8

-2.8

37.8

29.6

FY 2011 Grant

216

77

8

132

B

TN

BRISTOL

New Data Grant

175

51

14

110

A

Change (%)

-18.8

42.8

FY 2011 Grant

1,594

566

300

727

B

TN

CHATTANOOGA

New Data Grant

1,822

600

325

896

B

Change (%)

14.4

6.0

8.4

23.2

FY 2011 Grant

739

241

129

369

A

TN

CLARKSVILLE

New Data Grant

869

256

128

484

A

Change (%)

17.6

6.4

-0.6

31.0

FY 2011 Grant

304

78

29

197

A

TN

CLEVELAND

New Data Grant

373

80

58

236

A

Change (%)

22.8

2.2

102.2

19.4

FY 2011 Grant

253

117

38

98

A

TN

FRANKLIN CITY

New Data Grant

255

120

19

115

A

Change (%)

0.8

2.8

-50.4

18.0

FY 2011 Grant

529

123

66

339

A

TN

JACKSON

New Data Grant

595

126

56

413

A

Change (%)

12.6

2.0

-14.6

21.8

FY 2011 Grant

445

122

32

291

A

TN

JOHNSON CITY

New Data Grant

496

122

47

326

A

Change (%)

11.2

-0.2

46.6

12.2

FY 2011 Grant

366

87

19

261

A

TN

KINGSPORT

New Data Grant

375

93

36

246

A

Change (%)

2.4

7.4

89.2

-5.6

113

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

937

445

69

423

A

TN

KNOX COUNTY

New Data Grant

1,069

449

123

497

A

Change (%)

14.2

1.0

77.6

17.6

FY 2011 Grant

1,694

358

139

1,197

A

TN

KNOXVILLE

New Data Grant

1,751

345

105

1,301

A

Change (%)

3.4

-3.6

-24.0

8.6

FY 2011 Grant

7,320

1,308

1,403

4,609

A

TN

MEMPHIS

New Data Grant

7,387

1,247

1,319

4,821

A

Change (%)

1.0

-4.6

-6.0

4.6

FY 2011 Grant

266

54

43

168

A

TN

MORRISTOWN

New Data Grant

267

56

37

174

A

Change (%)

0.6

3.6

-14.6

3.4

FY 2011 Grant

589

203

67

319

A

TN

MURFREESBORO

New Data Grant

755

210

99

446

A

Change (%)

28.0

3.0

47.0

40.0

FY 2011 Grant

4,508

1,229

783

2,496

A

TN

NASHVILLE-

DAVIDSON

New Data Grant

4,778

1,208

753

2,817

A

Change (%)

6.0

-1.6

-4.0

12.8

FY 2011 Grant

237

62

163

12

B

TN

OAK RIDGE

New Data Grant

254

75

139

41

B

Change (%)

7.4

20.0

-15.0

252.8

FY 2011 Grant

906

471

106

328

A

TN

SHELBY COUNTY New Data Grant

1,055

541

95

419

A

Change (%)

16.6

15.0

-10.4

27.6

FY 2011 Grant

984

227

185

572

A

TX

ABILENE

New Data Grant

982

226

192

564

A

Change (%)

-0.2

-0.4

3.6

-1.4

FY 2011 Grant

241

163

32

46

A

TX

ALLEN

New Data Grant

305

162

60

82

A

Change (%)

26.6

-0.2

90.0

78.2

FY 2011 Grant

1,624

366

382

876

A

TX

AMARILLO

New Data Grant

1,627

368

349

911

A

Change (%)

0.2

0.4

-8.8

4.0

FY 2011 Grant

2,876

735

999

1,143

A

TX

ARLINGTON

New Data Grant

3,229

705

1,007

1,518

A

Change (%)

12.2

-4.2

0.8

32.8

FY 2011 Grant

6,878

1,520

2,105

3,252

A

TX

AUSTIN

New Data Grant

7,503

1,524

2,116

3,864

A

Change (%)

9.0

0.2

0.4

18.8

114

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

749

137

250

362

A

TX

BAYTOWN CITY

New Data Grant

687

138

235

313

A

Change (%)

-8.4

1.0

-5.8

-13.6

FY 2011 Grant

1,654

459

860

334

B

TX

BEAUMONT

New Data Grant

1,461

409

736

316

B

Change (%)

-11.6

-11.0

-14.4

-5.4

FY 2011 Grant

1,592

485

386

722

A

TX

BEXAR COUNTY

New Data Grant

1,712

702

327

683

A

Change (%)

7.6

44.8

-15.2

-5.4

FY 2011 Grant

1,706

438

505

763

A

TX

BRAZORIA

COUNTY

New Data Grant

1,886

434

646

806

A

Change (%)

10.6

-1.0

27.8

5.8

FY 2011 Grant

2,966

342

876

1,748

A

TX

BROWNSVILLE

New Data Grant

3,337

337

1,120

1,879

A

Change (%)

12.6

-1.4

27.8

7.6

FY 2011 Grant

853

144

211

497

A

TX

BRYAN

New Data Grant

938

147

232

558

A

Change (%)

10.0

1.8

10.0

12.2

FY 2011 Grant

723

250

260

213

A

TX

CARROLLTON

New Data Grant

835

230

302

304

A

Change (%)

15.4

-8.0

16.0

42.6

FY 2011 Grant

1,029

168

110

752

A

TX

COLLEGE

STATION

New Data Grant

1,097

181

73

843

A

Change (%)

6.6

8.0

-34.0

12.2

FY 2011 Grant

529

113

171

245

A

TX

CONROE

New Data Grant

620

108

219

292

A

Change (%)

17.2

-4.0

28.0

19.4

FY 2011 Grant

3,055

556

816

1,683

A

TX

CORPUS CHRISTI

New Data Grant

2,906

588

726

1,592

A

Change (%)

-4.8

5.8

-11.2

-5.4

FY 2011 Grant

15,882

2,512

6,072

7,297

A

TX

DALLAS

New Data Grant

16,139

2,309

5,630

8,200

A

Change (%)

1.6

-8.0

-7.2

12.4

FY 2011 Grant

1,923

681

566

676

A

TX

DALLAS COUNTY New Data Grant

2,203

695

547

961

A

Change (%)

14.6

2.0

-3.2

42.2

FY 2011 Grant

334

69

125

139

B

TX

DENISON

New Data Grant

336

78

139

119

B

Change (%)

0.8

13.0

11.0

-14.2

115

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

803

237

152

414

A

TX

DENTON

New Data Grant

932

219

134

579

A

Change (%)

16.0

-8.0

-11.8

39.8

FY 2011 Grant

848

140

225

483

A

TX

EDINBURG

New Data Grant

1,042

149

304

590

A

Change (%)

22.8

6.2

34.8

22.0

FY 2011 Grant

7,676

1,200

2,105

4,371

A

TX

EL PASO

New Data Grant

7,780

1,251

1,969

4,560

A

Change (%)

1.4

4.4

-6.4

4.4

FY 2011 Grant

343

103

127

112

A

TX

EULESS CITY

New Data Grant

451

99

181

171

A

Change (%)

31.6

-4.2

42.4

52.4

FY 2011 Grant

198

136

18

45

A

TX

FLOWER MOUND

TOWN

New Data Grant

204

125

17

63

A

Change (%)

3.0

-8.2

-6.6

40.6

FY 2011 Grant

1,818

706

511

601

A

TX

FORT BEND

COUNTY

New Data Grant

2,138

775

539

823

A

Change (%)

17.6

9.8

5.6

37.0

FY 2011 Grant

6,153

1,407

1,826

2,921

A

TX

FORT WORTH

New Data Grant

6,536

1,429

1,702

3,405

A

Change (%)

6.2

1.6

-6.8

16.6

FY 2011 Grant

267

198

29

40

A

TX

FRISCO

New Data Grant

368

226

43

99

A

Change (%)

37.8

14.0

49.2

148.8

FY 2011 Grant

1,317

259

559

499

B

TX

GALVESTON

New Data Grant

1,411

215

650

546

B

Change (%)

7.2

-17.0

16.2

9.4

FY 2011 Grant

1,887

429

788

669

A

TX

GARLAND

New Data Grant

1,971

437

661

872

A

Change (%)

4.4

2.0

-16.0

30.4

FY 2011 Grant

1,264

316

455

493

A

TX

GRAND PRAIRIE

New Data Grant

1,395

338

392

665

A

Change (%)

10.4

7.0

-14.0

34.8

FY 2011 Grant

236

99

67

70

A

TX

GRAPEVINE

New Data Grant

248

89

58

100

A

Change (%)

4.8

-9.6

-13.4

42.8

FY 2011 Grant

864

126

248

490

A

TX

HARLINGEN

New Data Grant

905

125

208

572

A

Change (%)

4.8

-1.0

-16.2

16.8

116

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

9,860

3,062

3,143

3,655

A

TX

HARRIS COUNTY New Data Grant

11,688

3,401

3,431

4,856

A

Change (%)

18.6

11.0

9.2

32.8

FY 2011 Grant

7,639

776

2,141

4,722

A

TX

HIDALGO

COUNTY

New Data Grant

8,641

810

3,095

4,736

A

Change (%)

13.2

4.4

44.6

0.2

FY 2011 Grant

27,343

4,365

9,998

12,979

A

TX

HOUSTON

New Data Grant

27,161

4,048

9,601

13,512

A

Change (%)

-0.6

-7.2

-4.0

4.2

FY 2011 Grant

2,056

397

947

712

A

TX

IRVING

New Data Grant

2,104

417

789

898

A

Change (%)

2.4

5.0

-16.6

26.2

FY 2011 Grant

884

231

262

391

A

TX

KILLEEN

New Data Grant

1,039

247

236

557

A

Change (%)

17.6

6.8

-10.0

42.6

FY 2011 Grant

3,291

437

1,042

1,811

A

TX

LAREDO

New Data Grant

3,753

455

1,410

1,888

A

Change (%)

14.0

4.2

35.2

4.2

FY 2011 Grant

269

139

55

75

A

TX

LEAGUE CITY

New Data Grant

345

161

68

116

A

Change (%)

28.4

16.2

24.4

54.0

FY 2011 Grant

525

203

159

163

A

TX

LEWISVILLE

New Data Grant

613

184

178

251

A

Change (%)

16.6

-9.6

12.2

54.0

FY 2011 Grant

692

151

142

399

A

TX

LONGVIEW

New Data Grant

712

155

192

365

A

Change (%)

2.8

2.8

34.4

-8.4

FY 2011 Grant

2,100

437

426

1,237

A

TX

LUBBOCK

New Data Grant

2,238

443

512

1,284

A

Change (%)

6.6

1.4

20.0

3.8

FY 2011 Grant

381

107

146

128

B

TX

MARSHALL

New Data Grant

338

93

149

96

B

Change (%)

-11.2

-13.2

1.8

-24.6

FY 2011 Grant

1,619

256

486

878

A

TX

MCALLEN

New Data Grant

1,795

250

521

1,024

A

Change (%)

10.8

-2.0

7.2

16.6

FY 2011 Grant

499

247

93

159

A

TX

MCKINNEY CITY

New Data Grant

738

253

161

324

A

Change (%)

47.8

2.4

72.4

103.8

117

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

813

258

261

295

A

TX

MESQUITE

New Data Grant

910

270

252

389

A

Change (%)

11.8

4.4

-3.6

32.0

FY 2011 Grant

830

210

196

424

A

TX

MIDLAND

New Data Grant

784

214

182

388

A

Change (%)

-5.6

2.0

-7.0

-8.6

FY 2011 Grant

765

133

200

432

A

TX

MISSION

New Data Grant

965

149

321

495

A

Change (%)

26.0

11.4

60.6

14.6

FY 2011 Grant

271

145

65

61

A

TX

MISSOURI CITY

New Data Grant

413

130

96

187

A

Change (%)

52.2

-10.2

46.8

205.6

FY 2011 Grant

1,690

703

341

647

A

TX

MONTGOMERY

COUNTY

New Data Grant

2,194

718

513

963

A

Change (%)

29.8

2.2

50.4

48.8

FY 2011 Grant

319

108

73

138

A

TX

NEW BRAUNFELS New Data Grant

361

111

84

165

A

Change (%)

13.2

3.0

16.4

19.4

FY 2011 Grant

299

128

79

92

A

TX

NORTH

RICHLAND HILLS

New Data Grant

317

122

52

142

A

Change (%)

6.0

-4.4

-34.0

54.4

FY 2011 Grant

1,028

195

251

582

A

TX

ODESSA

New Data Grant

896

193

245

459

A

Change (%)

-12.8

-1.2

-2.4

-21.2

FY 2011 Grant

382

87

235

60

B

TX

ORANGE

New Data Grant

366

79

243

44

B

Change (%)

-4.2

-8.8

3.2

-26.6

FY 2011 Grant

1,733

282

659

792

A

TX

PASADENA

New Data Grant

1,780

287

672

820

A

Change (%)

2.6

2.0

2.0

3.6

FY 2011 Grant

277

167

49

61

A

TX

PEARLAND

New Data Grant

319

176

48

95

A

Change (%)

15.2

5.4

-1.0

54.8

FY 2011 Grant

1,016

128

304

584

A

TX

PHARR

New Data Grant

1,333

136

481

716

A

Change (%)

31.2

6.0

58.4

22.6

FY 2011 Grant

1,142

529

279

334

A

TX

PLANO

New Data Grant

1,195

501

219

475

A

Change (%)

4.6

-5.2

-21.4

42.2

118

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

1,235

303

722

210

B

TX

PORT ARTHUR

New Data Grant

1,194

233

742

219

B

Change (%)

-3.4

-23.0

2.8

4.0

FY 2011 Grant

581

200

181

200

A

TX

RICHARDSON

New Data Grant

633

191

168

273

A

Change (%)

9.0

-4.2

-7.2

36.4

FY 2011 Grant

386

204

99

83

A

TX

ROUND ROCK

New Data Grant

541

193

163

185

A

Change (%)

40.2

-5.6

65.0

122.4

FY 2011 Grant

192

110

36

46

A

TX

ROWLETT

New Data Grant

251

108

58

85

A

Change (%)

30.6

-1.2

60.0

83.0

FY 2011 Grant

809

178

164

467

A

TX

SAN ANGELO

New Data Grant

782

180

148

454

A

Change (%)

-3.4

0.8

-9.4

-2.8

FY 2011 Grant

13,226

2,656

3,741

6,830

A

TX

SAN ANTONIO

New Data Grant

12,959

2,559

3,174

7,226

A

Change (%)

-2.0

-3.6

-15.2

5.8

FY 2011 Grant

456

49

136

271

A

TX

SAN BENITO

New Data Grant

447

47

150

250

A

Change (%)

-2.0

-4.6

10.8

-7.8

FY 2011 Grant

480

103

86

290

A

TX

SAN MARCOS

New Data Grant

642

87

77

479

A

Change (%)

33.8

-15.8

-11.2

64.8

FY 2011 Grant

293

74

64

155

A

TX

SHERMAN

New Data Grant

324

74

58

192

A

Change (%)

10.6

0.0

-9.0

23.8

FY 2011 Grant

307

158

66

83

A

TX

SUGAR LAND

New Data Grant

347

152

58

136

A

Change (%)

13.0

-3.8

-11.0

63.4

FY 2011 Grant

2,448

935

617

897

A

TX

TARRANT

COUNTY

New Data Grant

2,859

964

667

1,227

A

Change (%)

16.8

3.2

8.2

36.8

FY 2011 Grant

467

116

93

258

A

TX

TEMPLE

New Data Grant

434

127

79

227

A

Change (%)

-7.0

9.6

-14.4

-12.0

FY 2011 Grant

415

72

63

281

A

TX

TEXARKANA

New Data Grant

332

127

121

84

B

Change (%)

-19.8

-54.6

119

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

386

85

89

212

A

TX

TEXAS CITY

New Data Grant

405

87

114

204

A

Change (%)

4.8

2.2

28.2

-4.0

FY 2011 Grant

790

350

204

236

A

TX

TRAVIS COUNTY

New Data Grant

1,001

345

259

398

A

Change (%)

26.8

-1.4

26.8

68.2

FY 2011 Grant

859

191

186

481

A

TX

TYLER

New Data Grant

976

187

210

580

A

Change (%)

13.6

-2.2

12.4

20.4

FY 2011 Grant

566

122

139

306

A

TX

VICTORIA

New Data Grant

588

121

158

309

A

Change (%)

3.8

-1.2

14.0

1.2

FY 2011 Grant

1,511

244

288

980

A

TX

WACO

New Data Grant

1,524

241

278

1,005

A

Change (%)

0.8

-1.4

-3.4

2.6

FY 2011 Grant

1,285

273

643

369

B

TX

WICHITA FALLS

New Data Grant

1,219

266

584

369

B

Change (%)

-5.2

-2.6

-9.2

-0.2

FY 2011 Grant

993

516

197

280

A

TX

WILLIAMSON

COUNTY

New Data Grant

1,242

526

279

437

A

Change (%)

25.0

2.0

41.4

56.0

FY 2011 Grant

210

55

45

110

A

UT

CLEARFIELD

New Data Grant

243

58

49

136

A

Change (%)

16.0

5.8

9.2

24.0

FY 2011 Grant

673

375

112

186

A

UT

DAVIS COUNTY

New Data Grant

832

382

208

243

A

Change (%)

23.6

1.8

85.0

30.4

FY 2011 Grant

311

129

66

116

A

UT

LAYTON

New Data Grant

315

130

62

124

A

Change (%)

1.2

0.6

-6.8

6.6

FY 2011 Grant

536

96

115

325

A

UT

LOGAN

New Data Grant

548

93

98

358

A

Change (%)

2.4

-3.0

-15.2

10.2

FY 2011 Grant

1,007

262

277

468

B

UT

OGDEN

New Data Grant

1,029

306

271

452

B

Change (%)

2.2

17.0

-2.2

-3.4

FY 2011 Grant

556

184

125

247

A

UT

OREM

New Data Grant

664

170

151

343

A

Change (%)

19.6

-7.6

21.0

39.2

120

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

1,542

232

371

939

A

UT

PROVO

New Data Grant

1,719

217

395

1,107

A

Change (%)

11.4

-6.4

6.6

17.8

FY 2011 Grant

3,688

576

1,267

1,845

B

UT

SALT LAKE CITY

New Data Grant

3,599

531

1,191

1,877

B

Change (%)

-2.4

-7.8

-6.0

1.8

FY 2011 Grant

2,257

906

530

820

A

UT

SALT LAKE

COUNTY

New Data Grant

2,553

898

653

1,002

A

Change (%)

13.2

-0.8

23.2

22.2

FY 2011 Grant

359

188

53

118

A

UT

SANDY CITY

New Data Grant

402

169

71

162

A

Change (%)

12.0

-10.2

33.6

37.4

FY 2011 Grant

439

140

100

199

A

UT

ST GEORGE

New Data Grant

512

141

160

211

A

Change (%)

16.6

0.2

60.8

6.0

FY 2011 Grant

334

114

101

119

A

UT

TAYLORSVILLE

New Data Grant

382

113

102

166

A

Change (%)

14.2

-1.0

1.4

39.4

FY 2011 Grant

1,143

605

215

323

A

UT

UTAH COUNTY

New Data Grant

1,417

580

351

486

A

Change (%)

24.0

-4.2

63.2

50.8

FY 2011 Grant

450

203

107

140

A

UT

WEST JORDAN

New Data Grant

497

200

129

168

A

Change (%)

10.4

-1.4

20.6

20.0

FY 2011 Grant

845

242

274

329

A

UT

WEST VALLEY

New Data Grant

1,049

250

408

392

A

Change (%)

24.2

3.2

48.6

19.2

FY 2011 Grant

1,143

290

456

397

A

VA

ALEXANDRIA

New Data Grant

760

270

187

303

A

Change (%)

-33.4

-7.0

-59.0

-23.6

FY 2011 Grant

1,610

444

646

521

A

VA

ARLINGTON

COUNTY

New Data Grant

1,370

267

442

661

B

Change (%)

-15.0

-48.6

FY 2011 Grant

580

83

26

471

A

VA

BLACKSBURG

New Data Grant

494

82

11

402

A

Change (%)

-14.8

-0.8

-59.6

-14.6

FY 2011 Grant

259

57

101

101

B

VA

BRISTOL

New Data Grant

284

68

96

120

B

Change (%)

9.6

18.6

-4.8

19.2

121

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

479

210

25

244

B

VA

CHARLOTTESVILLE New Data Grant

477

84

57

336

A

Change (%)

-0.6

59.8

FY 2011 Grant

1,108

430

176

501

A

VA

CHESAPEAKE

New Data Grant

981

428

145

408

A

Change (%)

-11.4

-0.4

-17.8

-18.8

FY 2011 Grant

1,136

593

136

407

A

VA

CHESTERFIELD

COUNTY

New Data Grant

1,319

610

188

521

A

Change (%)

16.2

2.8

38.8

28.0

FY 2011 Grant

94

38

6

50

A

VA

CHRISTIANSBURG New Data Grant

121

41

13

68

A

Change (%)

28.2

6.8

102.8

34.8

FY 2011 Grant

78

34

12

32

A

VA

COLONIAL

HEIGHTS

New Data Grant

78

34

10

34

A

Change (%)

-1.0

-2.6

-15.4

6.0

FY 2011 Grant

973

198

427

348

B

VA

DANVILLE

New Data Grant

924

183

431

310

B

Change (%)

-5.0

-7.4

1.0

-11.0

FY 2011 Grant

5,418

2,054

1,796

1,569

A

VA

FAIRFAX COUNTY New Data Grant

4,949

2,129

1,241

1,578

A

Change (%)

-8.6

3.6

-30.8

0.6

FY 2011 Grant

209

56

0

154

B

VA

FREDERICKSBURG New Data Grant

156

54

0

102

B

Change (%)

-25.2

-2.8

-33.4

FY 2011 Grant

973

279

164

531

A

VA

HAMPTON

New Data Grant

1,148

265

329

553

A

Change (%)

18.0

-5.0

101.2

4.2

FY 2011 Grant

488

87

48

352

A

VA

HARRISONBURG

New Data Grant

536

94

109

332

A

Change (%)

9.8

8.0

125.2

-5.8

FY 2011 Grant

1,335

573

202

560

A

VA

HENRICO

COUNTY

New Data Grant

1,564

592

219

753

A

Change (%)

17.2

3.2

8.2

34.6

FY 2011 Grant

197

69

47

81

B

VA

HOPEWELL

New Data Grant

230

87

51

92

B

Change (%)

16.6

26.0

8.0

13.8

FY 2011 Grant

870

582

125

163

A

VA

LOUDOUN

COUNTY

New Data Grant

1,018

602

181

236

A

Change (%)

17.0

3.4

44.4

44.6

122

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

746

198

105

444

B

VA

LYNCHBURG

New Data Grant

716

239

76

401

B

Change (%)

-4.0

21.0

-27.4

-9.6

FY 2011 Grant

1,469

373

251

845

A

VA

NEWPORT NEWS New Data Grant

1,287

348

189

750

A

Change (%)

-12.4

-6.8

-24.8

-11.2

FY 2011 Grant

4,718

862

2,804

1,052

B

VA

NORFOLK

New Data Grant

4,373

660

2,625

1,088

B

Change (%)

-7.4

-23.4

-6.4

3.4

FY 2011 Grant

620

136

277

206

B

VA

PETERSBURG

New Data Grant

672

104

277

290

B

Change (%)

8.4

-23.8

0.0

41.2

FY 2011 Grant

1,641

326

912

402

B

VA

PORTSMOUTH

New Data Grant

1,600

264

937

399

B

Change (%)

-2.4

-19.0

2.8

-0.8

FY 2011 Grant

1,758

827

408

523

A

VA

PRINCE WILLIAM

COUNTY

New Data Grant

2,116

875

555

686

A

Change (%)

20.4

5.8

36.0

31.2

FY 2011 Grant

185

31

9

144

A

VA

RADFORD

New Data Grant

160

32

4

124

A

Change (%)

-13.6

1.2

-52.6

-14.2

FY 2011 Grant

4,394

848

1,573

1,973

B

VA

RICHMOND

New Data Grant

4,396

764

1,534

2,099

B

Change (%)

0.0

-10.0

-2.4

6.4

FY 2011 Grant

1,671

312

642

717

B

VA

ROANOKE

New Data Grant

1,651

307

592

752

B

Change (%)

-1.2

-1.8

-7.8

4.8

FY 2011 Grant

505

162

53

291

A

VA

SUFFOLK

New Data Grant

479

163

59

258

A

Change (%)

-5.2

0.8

10.8

-11.4

FY 2011 Grant

2,196

838

402

955

A

VA

VIRGINIA BEACH New Data Grant

1,991

844

267

879

A

Change (%)

-9.4

0.8

-33.4

-8.0

FY 2011 Grant

229

63

0

166

B

VA

WINCHESTER

New Data Grant

251

68

0

183

B

Change (%)

9.6

7.4

10.4

FY 2011 Grant

812

148

184

480

B

VT

BURLINGTON

New Data Grant

703

151

131

421

B

Change (%)

-13.4

2.0

-28.8

-12.4

123

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

96

24

0

72

B

WA ANACORTES

New Data Grant

102

22

0

81

B

Change (%)

6.8

-9.4

12.0

FY 2011 Grant

419

123

92

204

A

WA AUBURN

New Data Grant

523

135

136

252

A

Change (%)

25.0

10.2

48.8

23.2

FY 2011 Grant

655

245

189

221

A

WA BELLEVUE

New Data Grant

640

236

164

241

A

Change (%)

-2.2

-3.6

-13.6

9.0

FY 2011 Grant

766

271

0

495

B

WA BELLINGHAM

New Data Grant

797

302

0

496

B

Change (%)

4.2

11.4

0.2

FY 2011 Grant

512

140

103

269

B

WA BREMERTON

New Data Grant

445

122

67

257

B

Change (%)

-13.0

-13.4

-35.2

-4.4

FY 2011 Grant

1,236

525

217

494

A

WA CLARK COUNTY

New Data Grant

1,476

519

328

630

A

Change (%)

19.4

-1.2

51.0

27.4

EAST

FY 2011 Grant

104

24

22

58

A

WA WENATCHEE

New Data Grant

117

25

31

61

A

CITY

Change (%)

12.4

4.6

40.6

5.0

FY 2011 Grant

837

192

239

405

A

WA EVERETT

New Data Grant

864

199

232

433

A

Change (%)

3.2

3.4

-3.0

6.8

FY 2011 Grant

652

166

211

274

A

WA FEDERAL WAY

New Data Grant

646

172

167

307

A

Change (%)

-0.8

3.8

-20.8

11.8

FY 2011 Grant

528

131

145

252

A

WA KENNEWICK

New Data Grant

574

143

145

287

A

Change (%)

8.8

8.6

0.6

13.6

FY 2011 Grant

710

165

223

321

A

WA KENT CITY

New Data Grant

801

178

257

366

A

Change (%)

12.8

7.8

15.0

14.0

FY 2011 Grant

4,047

1,595

1,015

1,437

A

WA KING COUNTY

New Data Grant

4,209

1,555

945

1,709

A

Change (%)

4.0

-2.4

-6.8

19.0

FY 2011 Grant

1,034

395

190

449

A

WA KITSAP COUNTY

New Data Grant

968

409

140

419

A

Change (%)

-6.4

3.4

-26.4

-6.6

124

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

578

112

152

314

A

WA LAKEWOOD

New Data Grant

528

112

118

298

A

Change (%)

-8.6

0.6

-22.6

-5.2

FY 2011 Grant

329

71

59

200

A

WA LONGVIEW

New Data Grant

344

71

48

225

A

Change (%)

4.2

0.2

-18.8

12.6

FY 2011 Grant

294

62

90

143

A

WA MOUNT VERNON New Data Grant

328

61

117

150

A

Change (%)

11.4

-1.6

30.2

5.0

FY 2011 Grant

353

105

0

248

B

WA OLYMPIA

New Data Grant

365

119

0

246

B

Change (%)

3.2

13.0

-0.8

FY 2011 Grant

563

113

191

258

A

WA PASCO

New Data Grant

652

115

201

336

A

Change (%)

15.8

1.6

5.2

30.0

FY 2011 Grant

2,707

1,027

565

1,115

A

WA PIERCE COUNTY

New Data Grant

2,847

1,022

519

1,305

A

Change (%)

5.2

-0.4

-8.0

17.0

FY 2011 Grant

420

120

130

169

A

WA RENTON CITY

New Data Grant

499

175

130

194

A

Change (%)

18.8

46.2

-0.4

14.4

FY 2011 Grant

248

92

45

111

A

WA RICHLAND

New Data Grant

247

93

28

126

A

Change (%)

-0.2

0.8

-38.2

14.4

FY 2011 Grant

10,729

1,352

2,751

6,626

B

WA SEATTLE

New Data Grant

10,400

1,274

2,753

6,374

B

Change (%)

-3.0

-5.8

0.0

-3.8

FY 2011 Grant

313

102

83

127

A

WA SHORELINE

New Data Grant

269

102

44

123

A

Change (%)

-13.8

0.2

-47.2

-3.2

FY 2011 Grant

2,792

1,116

680

995

A

WA SNOHOMISH

COUNTY

New Data Grant

2,882

1,141

566

1,175

A

Change (%)

3.2

2.2

-16.8

18.0

FY 2011 Grant

3,439

641

869

1,929

B

WA SPOKANE

New Data Grant

3,192

658

767

1,766

B

Change (%)

-7.2

2.6

-11.6

-8.4

FY 2011 Grant

1,406

513

207

685

A

WA SPOKANE

COUNTY

New Data Grant

1,451

506

196

749

A

Change (%)

3.2

-1.4

-5.4

9.4

125

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

2,639

631

284

1,725

B

WA TACOMA

New Data Grant

2,502

586

276

1,640

B

Change (%)

-5.2

-7.2

-2.6

-4.8

FY 2011 Grant

1,219

320

288

610

A

WA VANCOUVER

New Data Grant

1,264

312

254

698

A

Change (%)

3.8

-2.6

-11.8

14.4

FY 2011 Grant

304

58

96

149

A

WA WENATCHEE

New Data Grant

226

62

38

127

A

Change (%)

-25.6

5.4

-60.4

-15.2

FY 2011 Grant

1,073

166

340

567

A

WA YAKIMA

New Data Grant

995

176

297

523

A

Change (%)

-7.2

5.8

-12.6

-7.8

FY 2011 Grant

565

78

23

463

B

WI

APPLETON

New Data Grant

545

126

0

419

B

Change (%)

-3.6

61.2

-100

-9.6

FY 2011 Grant

615

90

160

365

B

WI

BELOIT

New Data Grant

547

123

149

276

B

Change (%)

-11.0

36.2

-6.8

-24.4

FY 2011 Grant

1,032

195

0

837

B

WI

DANE COUNTY

New Data Grant

1,097

474

194

430

A

Change (%)

6.2

120.0

FY 2011 Grant

578

164

0

414

B

WI

EAU CLAIRE

New Data Grant

579

205

0

374

B

Change (%)

0.2

25.2

-9.8

FY 2011 Grant

531

63

85

383

B

WI

FOND DU LAC

New Data Grant

502

85

72

346

B

Change (%)

-5.4

35.2

-16.0

-9.8

FY 2011 Grant

925

221

144

561

B

WI

GREEN BAY

New Data Grant

962

274

99

589

B

Change (%)

4.0

23.8

-31.0

5.0

FY 2011 Grant

488

80

0

408

B

WI

JANESVILLE

New Data Grant

459

123

0

336

B

Change (%)

-6.0

53.8

-17.6

FY 2011 Grant

966

176

52

738

B

WI

KENOSHA

New Data Grant

945

253

29

664

B

Change (%)

-2.2

43.6

-43.8

-10.2

FY 2011 Grant

925

171

253

502

B

WI

LA CROSSE

New Data Grant

961

211

243

507

B

Change (%)

3.8

23.4

-3.8

1.0

126

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

1,798

618

0

1,180

B

WI

MADISON

New Data Grant

2,044

450

321

1,273

A

Change (%)

13.6

106.0

FY 2011 Grant

15,282

2,609

6,349

6,324

B

WI

MILWAUKEE

New Data Grant

16,159

2,578

6,328

7,253

B

Change (%)

5.8

-1.2

-0.4

14.6

FY 2011 Grant

1,537

219

72

1,245

B

WI

MILWAUKEE

COUNTY

New Data Grant

1,419

281

79

1,059

B

Change (%)

-7.6

28.2

9.2

-15.0

FY 2011 Grant

195

27

20

148

B

WI

NEENAH

New Data Grant

200

33

18

150

B

Change (%)

2.4

18.8

-11.8

1.2

FY 2011 Grant

775

120

50

606

B

WI

OSHKOSH

New Data Grant

750

142

21

587

B

Change (%)

-3.2

18.8

-57.4

-3.2

FY 2011 Grant

1,786

235

648

903

B

WI

RACINE

New Data Grant

1,813

256

670

886

B

Change (%)

1.6

9.2

3.4

-1.8

FY 2011 Grant

982

87

262

633

B

WI

SHEBOYGAN

New Data Grant

891

96

235

560

B

Change (%)

-9.2

10.8

-10.2

-11.6

FY 2011 Grant

784

74

295

415

B

WI

SUPERIOR

New Data Grant

726

71

283

372

B

Change (%)

-7.4

-3.6

-4.2

-10.4

FY 2011 Grant

387

70

0

317

B

WI

WAUKESHA

New Data Grant

412

103

0

309

B

Change (%)

6.2

46.6

-2.6

FY 2011 Grant

920

607

92

221

A

WI

WAUKESHA

COUNTY

New Data Grant

990

613

89

288

A

Change (%)

7.6

1.0

-3.2

30.0

FY 2011 Grant

640

89

157

394

B

WI

WAUSAU

New Data Grant

598

82

144

372

B

Change (%)

-6.6

-7.8

-8.4

-5.4

FY 2011 Grant

1,086

37

501

548

B

WI

WAUWATOSA

New Data Grant

972

40

477

455

B

Change (%)

-10.6

7.6

-4.8

-17.0

FY 2011 Grant

1,253

83

523

647

B

WI

WEST ALLIS

New Data Grant

1,262

125

511

626

B

Change (%)

0.8

50.6

-2.2

-3.4

127

Grant Allocation Change Due to:

Grant

Overcrowded Persons in

Pre-1940

State Grantee Name

Amount Population

Units

Poverty

Growth Lag Housing

Formula

($000)

($000)

($000)

($000)

($000)

($000)

Type

FY 2011 Grant

1,678

183

981

514

B

WV CHARLESTON

New Data Grant

1,555

165

948

442

B

Change (%)

-7.4

-9.8

-3.4

-14.0

FY 2011 Grant

1,876

254

955

667

B

WV HUNTINGTON

New Data Grant

1,804

257

936

611

B

Change (%)

-3.8

1.0

-2.0

-8.4

FY 2011 Grant

351

62

71

218

B

WV MARTINSBURG

New Data Grant

274

56

67

152

B

Change (%)

-21.8

-10.6

-5.6

-30.4

FY 2011 Grant

486

186

43

257

B

WV MORGANTOWN New Data Grant

393

148

48

197

B

Change (%)

-19.2

-20.2

11.2

-23.4

FY 2011 Grant

954

135

445

374

B

WV PARKERSBURG

New Data Grant

898

154

438

306

B

Change (%)

-5.8

14.2

-1.6

-18.0

FY 2011 Grant

106

18

44

44

B

WV VIENNA CITY

New Data Grant

104

19

40

44

B

Change (%)

-2.0

7.8

-9.0

1.4

FY 2011 Grant

453

44

303

106

B

WV WEIRTON

New Data Grant

410

45

283

83

B

Change (%)

-9.4

1.6

-6.6

-21.4

FY 2011 Grant

1,338

113

642

583

B

WV WHEELING

New Data Grant

1,262

92

634

536

B

Change (%)

-5.6

-18.6

-1.2

-8.0

FY 2011 Grant

387

117

62

208

B

WY CASPER

New Data Grant

291

88

50

152

B

Change (%)

-24.8

-24.6

-18.4

-27.0

FY 2011 Grant

483

96

115

272

B

WY CHEYENNE

New Data Grant

420

91

84

246

B

Change (%)

-13.0

-5.6

-27.0

-9.8

U.S. Department of Housing and Urban Development

Office of Policy Development and Research

131

Washington, DC 20410-6000

December 2011

Document Outline

Untitled

TABLE OF CONTENTS

EXECUTIVE SUMMARY

CHAPTER 1 INTRODUCTION

CHAPTER 2 REDISTRIBUTIVE EFFECTS OF NEW DATA ON COMMUNITY DEVELOPMENT BLOCK GRANT ENTITLEMENT COMMUNITIES

CHAPTER 3 REDISTRIBUTIVE EFFECTS OF NEW DATA ON COMMUNITY DEVELOPMENT BLOCK GRANT NONENTITLEMENT COMMUNITIES

CHAPTER 4 CONFIRMING KEY TRENDS

CONCLUSION

ACKNOWLEDGEMENTS

REFERENCES

ADDITIONAL READING

APPENDIX 1: HUD ADMINISTRATIVE REGIONS

APPENDIX 2: ALL FY 2011 ENTITLEMENT JURISDICTIONS