a

GAO

United States Government Accountability Office

Report to Congressional Committees

September 2006 EMPOWERMENT 

ZONE AND 

ENTERPRISE 

COMMUNITY 

PROGRAM

Improvements 

Occurred in 

Communities, but the 

Effect of the Program 

Is Unclear

GAO-06-727
What GAO Found

United States Government Accountability Office

Why GAO Did This Study

Highlights

Accountability Integrity Reliability

September 2006

EMPOWERMENT ZONE AND 

ENTERPRISE COMMUNITY PROGRAM 

Improvements Occurred in Communities, but 

the Effect of the Program Is Unclear 

Highlights of GAO-06-727, a report to 

congressional committees 

www.gao.gov/cgi-bin/getrpt?GAO-06-727. 

To view the full product, including the scope 

and methodology, click on the link above. To 

view the survey results, click on the following 

link: www.gao.gov/cgi-bin/getrpt?GAO-06-

734SP. For more information, contact 

William B. Shear at (202) 512-8678 or 

ShearW@gao.gov. 

The EZ/EC program is one of the 

most recent large-scale federal

effort intended to revitalize 

impoverished urban and rural 

communities. There have been 

three rounds of EZs and two 

rounds of ECs, all of which are 

scheduled to end no later than

December 2009. 

The Community Renewal Tax

Relief Act of 2000 mandated that

GAO audit and report in 2004, 2007, 

and 2010 on the EZ/EC program 

and its effect on poverty, 

unemployment, and economic

growth. This report, which focuses 

on the first round of the program 

starting in 1994, discusses program 

implementation; program 

oversight; data available on the use

of program tax benefits; and the 

program’s effect on poverty, 

unemployment, and economic

growth. In conducting this work,

GAO made site visits to all Round I 

EZs, conducted an e-mail survey of

60 Round I ECs, and used several 

statistical methods to analyze 

program effects. 

What GAO Recommends

While not making 

recommendations, GAO makes 

observations that should be

considered if these or similar 

programs are authorized in the 

future. HHS, HUD, and USDA 

provided comments. In particular, 

HUD disagreed with the

observation that there was a lack of

data to perform program oversight. 

Round I Empowerment Zones (EZ) and Enterprise Communities (EC) 

implemented a variety of activities using $1 billion in federal grant funding 

from the Department of Health and Human Services (HHS), and as of March 

2006, the designated communities had expended all but 15 percent of this 

funding. Most of the activities that the grant recipients put in place were 

community development projects, such as projects supporting education and 

housing. Other activities included economic opportunity initiatives such as 

job training and loan programs. Although all EZs and ECs also reported 

using the program grants to leverage funds from other sources, reliable data 

on the extent of leveraging were not available. 

According to federal standards, agencies should oversee the use of public 

resources and ensure that ongoing monitoring occurs. However, none of the 

federal agencies that were responsible for program oversight—including 

HHS and the departments of Housing and Urban Development (HUD) and 

Agriculture (USDA)—collected data on the amount of program grant funds 

used to implement specific program activities. This lack of data limited both 

federal oversight and GAO’s ability to assess the effect of the program. 

Moreover, because HHS did not provide the states and designated 

communities with clear guidance on how to monitor the program grant 

funds, the extent of monitoring varied across the sites. 

In addition, detailed Internal Revenue Service (IRS) data on the use of EZ/EC 

program tax benefits were not available. Previously, GAO cited similar 

challenges in assessing the use of tax benefits in other federal programs and 

stated that information on tax expenditures should be collected to ensure 

that these expenditures are achieving their intended purpose. Although GAO

recommended in 2004 that HUD, USDA, and IRS work together to identify 

the data needed to assess the EZ/EC tax benefits and the cost effectiveness 

of collecting the information, the three agencies did not reach agreement on 

an approach. 

Without adequate data on the use of program grant funds or tax benefits, 

neither the responsible federal agencies nor GAO could determine whether 

the EZ/EC funds had been spent effectively or that the tax benefits had in 

fact been used as intended. Using the data that were available, GAO 

attempted to analyze changes in several indicators—poverty and 

unemployment rates and two measures of economic growth. Although 

improvements in poverty, unemployment, and economic growth had 

occurred in the EZs and ECs, our econometric analysis of the eight urban 

EZs could not tie these changes definitively to the EZ designation. 
Page i GAO-06-727 Empowerment Zones and Enterprise Communities

Contents

Letter 1

Results in Brief 3

Background 6

Round I EZs and ECs Have Used Their Grant Funds to Implement a 

Wide Range of Program Activities 11

Oversight Was Hindered by Limited Program Data and Variation in 

Monitoring 21

Lack of Detailed Tax Data Made It Difficult to Assess the Use of 

Program Tax Benefits 25

In Aggregate, EZs and ECs Showed Some Improvements, but Our 

Analysis Did Not Definitively Link These Changes to the

Program 29

Observations 48

Agency Comments and Our Evaluation 49

Appendixes

Appendix I: Objectives, Scope, and Methodology 54

Methodology for Site Visits 55

Methodology for Survey of EC Officials 57

Methodology for Qualitative Analysis of Site Visit and EC Survey 

Data 59

Methodology for Review of Program Oversight 60

Methodology for Survey of EZ Businesses 61

Methodology for Assessing the Effect of the Program on Poverty, 

Unemployment, and Economic Growth 63

Appendix II: Methodology for and Results of Our Econometric Models 70

Description of Our Models 71

Results of Our Models for Poverty 72

Results of Our Models for Unemployment 74

Results of Our Models for Economic Growth 76

Other Variables Tested for Use in Our Econometric Models 80

Appendix III: List of Communities Designated in Round I of the EZ/EC 

Program 82

Appendix IV: Description of the Empowerment Zones and Enterprise 

Communities We Visited 85

Atlanta Empowerment Zone 85

Baltimore Empowerment Zone 90

Chicago Empowerment Zone 95

Detroit Empowerment Zone 100
Contents

Page ii GAO-06-727 Empowerment Zones and Enterprise Communities

New York Empowerment Zone 105

Philadelphia-Camden Empowerment Zone 116

Cleveland Empowerment Zone 127

Los Angeles Empowerment Zone 132

Kentucky Highlands Empowerment Zone 137

Mid-Delta Mississippi Empowerment Zone 142

Rio Grande Valley, Texas Empowerment Zone 147

Providence, Rhode Island Enterprise Community 152

Fayette-Haywood, Tennessee Enterprise Community 157

Appendix V: Comments from the Department of Health and Human 

Services 162

Appendix VI: Comments from the Department of Housing and Urban 

Development 165

Appendix VII: Comments from the U.S. Department of Agriculture 180

Appendix VIII: GAO Contact and Staff Acknowledgments 183

Tables Table 1: Round I EZ/EC Program Criteria and Benefits 8

Table 2: National Poverty, Unemployment, Economic Growth Data 

for 1990 to 2004 11

Table 3: Total EZ/EC Grant Funding Remaining as of March 31, 

2006 12

Table 4: Number of Stakeholders Interviewed for EZ and EC Site 

Visits, by Type 57

Table 5: Coding of Data Reliability of HUD and USDA Performance 

Systems 61

Table 6: Confidence Intervals for Average Household Income and 

Average Housing Value in Constant 2004 Dollars 64

Table 7: Factors Selected for Choosing Comparison Tracts 67

Table 8: Estimates of the Association between the EZ Program and 

the Change in Poverty Rate, 1990-2000 73

Table 9: Estimates of the Association between the EZ Program and 

the Change in Unemployment Rate, 1990-2000 75

Table 10: Estimates of the Association between the EZ Program and 

Economic Growth, Measured by the Change in the Number 

of Businesses, from 1995-1999 77

Table 11: Estimates of the Association between the EZ Program and 

Economic Growth, Measured by the Change in the Number 

of Jobs, 1995-1999 79

Table 12: Alternative Variables Considered in Our Analyses 80
Contents

Page iii GAO-06-727 Empowerment Zones and Enterprise Communities

Table 13: Changes in Selected Census Variables Observed in the 

Atlanta EZ and Its Comparison Area 88

Table 14: Changes in Selected Economic Growth Variables Observed 

in the Atlanta EZ and Its Comparison Area 89

Table 15: Changes in Selected Census Variables Observed in the 

Baltimore EZ and Its Comparison Area 93

Table 16: Changes in Selected Economic Growth Variables Observed 

in the Baltimore EZ and Its Comparison Area 94

Table 17: Changes in Selected Census Variables Observed in the 

Chicago EZ and Its Comparison Area 98

Table 18: Changes in Selected Economic Growth Variables Observed 

in the Chicago EZ and Its Comparison Area 99

Table 19: Changes in Selected Census Variables Observed in the 

Detroit EZ and Its Comparison Area 103

Table 20: Changes in Selected Economic Growth Variables Observed 

in the Detroit EZ and Its Comparison Area 104

Table 21: Changes in Selected Census Variables Observed in the New 

York EZ, the Bronx and Upper Manhattan (UM) Portions, 

and the EZ Comparison Area (Comp.) 112

Table 22: Changes in Selected Economic Growth Variables Observed 

in the New York EZ, the Bronx and Upper Manhattan (UM) 

Portions, and the EZ Comparison Area (Comp.) 114

Table 23: Changes in Selected Census Variables Observed in the 

Philadelphia-Camden EZ, the Camden (Cam.) and 

Philadelphia (Phila.) Portions, and the EZ Comparison 

Area (Comp.) 123

Table 24: Changes in Selected Economic Growth Variables Observed 

in the Philadelphia-Camden EZ, the Camden (Cam.) and 

Philadelphia (Phila.) Portions, and the EZ Comparison 

Area (Comp.) 124

Table 25: Changes in Selected Census Variables Observed in the 

Cleveland EZ and Its Comparison Area 130

Table 26: Changes in Selected Economic Growth Variables Observed 

in the Cleveland EZ and Its Comparison Area 130

Table 27: Changes in Selected Census Variables Observed in the Los 

Angeles EZ and Its Comparison Area 135

Table 28: Changes in Selected Economic Growth Variables Observed 

in the Los Angeles EZ and Its Comparison Area 135

Table 29: Changes in Selected Census Variables Observed in the 

Kentucky Highlands EZ 140

Table 30: Changes in Selected Economic Growth Variables Observed 

in the Kentucky Highlands EZ 141
Contents

Page iv GAO-06-727 Empowerment Zones and Enterprise Communities

Table 31: Changes in Selected Census Variables Observed in the 

Mid-Delta EZ 145

Table 32: Changes in Selected Economic Growth Variables Observed 

in the Mid-Delta EZ 146

Table 33: Changes in Selected Census Variables Observed in the Rio 

Grande Valley EZ 150

Table 34: Changes in Selected Economic Growth Variables Observed 

in the Rio Grande Valley EZ 151

Table 35: Changes in Selected Census Variables Observed in the 

Providence EC 155

Table 36: Changes in Selected Economic Growth Variables Observed 

in the Providence EC 156

Table 37: Changes in Selected Census Variables Observed in the 

Fayette-Haywood EC 160

Table 38: Changes in Selected Economic Growth Variables Observed 

in the Fayette-Haywood EC 161

Figures Figure 1: Oversight Responsibilities in Round I of the EZ/EC 

Program 10

Figure 2: Remaining Grant Funds by EZ as of March 31, 2006 13

Figure 3: Distribution of EZ and EC Activities by Key Program 

Principle 14

Figure 4: Types of Activities Implemented by Urban and Rural EZs 

and ECs, by Percent of Total Activities 16

Figure 5: Local Government Involvement in Decision Making in the 

Urban EZs 20

Figure 6: Changes in Poverty, Unemployment, and Two Measures 

of Economic Growth Observed in Round I EZs 32

Figure 7: Number and Percentage of EZs and ECs Experiencing a 

Decrease in Poverty from 1990 to 2000 34

Figure 8: Comparison of Decreases in Poverty in Urban and Rural 

Designated Areas and Comparison Areas from 1990 to 

2000 35

Figure 9: Number and Percentage of EZs and ECs that Experienced 

a Decrease in Unemployment from 1990 to 2000 38

Figure 10: Comparison of Decreases in Unemployment in Urban and 

Rural Designated Areas and Comparison Areas from 1990 

to 2000 40

Figure 11: Number and Percentage of EZs and ECs That 

Experienced an Increase in One or Both Measures of 

Economic Growth between 1995 and 2004 43
Contents

Page v GAO-06-727 Empowerment Zones and Enterprise Communities

Figure 12: Comparison of Changes in the Number of Businesses and 

the Number of Jobs in Urban and Rural Designated Areas 

and Comparison Areas between 1995 and 2004 45

Figure 13: Map of the Atlanta EZ and Its Comparison Area 85

Figure 14: Activities Implemented by the Atlanta EZ 87

Figure 15: Map of the Baltimore EZ and Its Comparison Area 90

Figure 16: Activities Implemented by the Baltimore EZ 92

Figure 17: Map of the Chicago EZ and Its Comparison Area 95

Figure 18: Activities Implemented by the Chicago EZ 97

Figure 19: Map of the Detroit EZ and Its Comparison Area 100

Figure 20: Activities Implemented by the Detroit EZ 102

Figure 21: Map of the New York EZ and Its Comparison Area 105

Figure 22: Activities Implemented by the Upper Manhattan portion 

of the New York EZ 108

Figure 23: Activities Implemented by the Bronx portion of the New 

York EZ 110

Figure 24: Map of the Philadelphia-Camden EZ and Its Comparison 

Area 116

Figure 25: Activities Implemented by the Philadelphia Portion of the 

Philadelphia-Camden EZ 119

Figure 26: Activities Implemented by the Camden Portion of the 

Philadelphia-Camden EZ 121

Figure 27: Map of the Cleveland EZ and Its Comparison Area 127

Figure 28: Activity Implemented by the Cleveland EZ 129

Figure 29: Map of the Los Angeles EZ and Its Comparison Area 132

Figure 30: Activity Implemented by the Los Angeles EZ 134

Figure 31: Map of the Kentucky Highlands EZ 137

Figure 32: Activities Implemented by the Kentucky Highlands 

EZ 139

Figure 33: Map of the Mid-Delta EZ 142

Figure 34: Activities Implemented by the Mid-Delta EZ 144

Figure 35: Map of the Rio Grande Valley EZ 147

Figure 36: Activities Implemented by the Rio Grande Valley EZ 149

Figure 37: Map of the Providence EC 152

Figure 38: Activities Implemented by the Providence EC 154

Figure 39: Map of the Fayette-Haywood EC 157

Figure 40: Activities Implemented by the Fayette-Haywood EC 159
Contents

Page vi GAO-06-727 Empowerment Zones and Enterprise Communities

Abbreviations

EC Enterprise Community 

EZ Empowerment Zone

HHS Department of Health and Human Services

HUD Department of Housing and Urban Development 

IRS Internal Revenue Service

USDA U.S. Department of Agriculture

This is a work of the U.S. government and is not subject to copyright protection in the 

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Page 1 GAO-06-727 Empowerment Zones and Enterprise Communities

United States Government Accountability Office

Washington, D.C. 20548

A

September 22, 2006 Letr

The Honorable Charles E. Grassley

Chairman

The Honorable Max Baucus

Ranking Minority Member

Committee on Finance

United States Senate

The Honorable William M. Thomas

Chairman

The Honorable Charles B. Rangel

Ranking Minority Member

Committee on Ways and Means

House of Representatives

The Empowerment Zone and Enterprise Community (EZ/EC) program is 

one of the most recent in a series of large-scale federal efforts intended to 

address one of the nation’s most persistent challenges—the revitalization 

of impoverished urban and rural communities. When it was enacted in 

1993, the EZ/EC program provided grants to public and private entities for 

social services and community redevelopment and tax benefits to local 

businesses to attract or retain jobs and businesses in distressed 

communities. The program differs from earlier initiatives with similar goals 

in that it emphasizes the role of local communities in identifying solutions 

and the use of public-private partnerships to attract the investment 

necessary for sustainable economic and community development. To date, 

Congress has authorized three rounds of EZs and two rounds of ECs. 

Communities designated under Round I of the program shared a total of $1 

billion in federal grant funding and also received tax and other benefits. 

The EZs received the bulk of this funding—$720 million in total—as well as 

more extensive tax benefits than the ECs. Communities designated in the 

two subsequent rounds of the program received a smaller amount of 

federal funding and more tax benefits. All three rounds of the EZ/EC 

program are scheduled to end no later than December 31, 2009. 

The Community Renewal Tax Relief Act of 2000 mandated that we audit 

and report in 2004, 2007, and 2010 on the EZ/EC program and a later 

initiative, the Renewal Community program, and their effect on poverty,
Page 2 GAO-06-727 Empowerment Zones and Enterprise Communities

unemployment, and economic growth.1 This report, the second of the 

mandated series, focuses on the first round of communities designated as 

EZs and ECs in 1994. It (1) describes how the designated communities 

implemented Round I of the EZ/EC program; (2) evaluates the extent of 

federal, state, and local oversight of the program; (3) examines the extent 

to which data are available to assess the use of program tax benefits; and 

(4) analyzes the effects that the Round I EZs and ECs had on poverty, 

unemployment, and economic growth in their communities. 

To address our first three objectives, we made site visits to all 11 Round I 

EZs and 2 of the 95 ECs—1 urban and 1 rural—to interview stakeholders 

and review documentation.2

 To gather information from the ECs, we 

administered an e-mail survey to officials from the 60 Round I ECs that 

were still in operation as of June 2005 and did not receive a subsequent 

designation.3

 We chose to exclude the 34 ECs that received subsequent 

designations, because we did not want their responses to be influenced by 

those programs. Because the states distributed the federal funding to the 

communities, we conducted telephone interviews with state officials in the 

13 states containing the EZs and ECs that we visited. In addition, we 

interviewed officials from the federal agencies with primary responsibility 

for the program—the Department of Health and Human Services (HHS), 

the Department of Housing and Urban Development (HUD), the Internal 

Revenue Service (IRS), and the U.S. Department of Agriculture (USDA). We 

also analyzed fiscal and program data from the agencies and assessed the 

reliability of these data.4

 To address our fourth objective, that is, the effect 

of the program on poverty, unemployment, and economic growth, we used 

several methods. First, we calculated the changes in the poverty and 

unemployment rates from 1990 to 2000 and measures of economic growth 

from 1995 to 2004 in the designated EZs and ECs and in comparison areas

1

Since its enactment in 2000, the Renewal Community program has focused on providing tax 

benefits to businesses in designated communities to attract or retain jobs and businesses.

2

For the purposes of this report, EZ/EC stakeholders include EZ/EC officials, board 

members, subgrantees, local chamber of commerce representatives, and other local 

officials recommended by EZ or EC officials as having a role in the program. See appendix I 

for information on the types of stakeholders we interviewed at each site.

3

Survey results can be viewed at www.gao.gov/cgi-bin/getrpt?GAO-06-734SP.

4

Program data include information on how activities were implemented and outputs.
Page 3 GAO-06-727 Empowerment Zones and Enterprise Communities

selected for their similarities to the designated communities. 5 Then, we 

used econometric models to assess the effects of the program. Finally, we 

used testimonial information gathered during our site visits and our survey 

results to help put these changes in context. 

We conducted our work between November 2004 and July 2006 in 

accordance with generally accepted government auditing standards. 

Appendix I lists the communities we visited. Appendixes I and II provide 

details on our methodology, and appendix III shows a list of communities 

designated in Round I of the EZ/EC program. Appendix IV provides details 

on each of the sites we visited.

Results in Brief Round I EZs and ECs used most of the $1 billion in program grant funds to 

implement a wide range of activities designed to help revitalize the 

designated communities. As of March 31, 2006, 20 percent of the $720 

million that EZs received and 2 percent of the $280 million that ECs 

received remained unspent, and some designees had received extensions 

of the original 10-year grant period that was set to expire in 2004. In 

general, EZs and ECs undertook more community development activities 

in areas such as education, housing, and infrastructure than they did 

economic opportunity activities such as job training and assistance to 

businesses. Although stakeholders from all EZs and ECs reported using the 

program grants to leverage funds from other sources and some said that 

they had required subgrantees to obtain other funds as a condition of 

receiving EZ/EC funds, reliable data on the extent of leveraging were not 

available. EZ and EC designees also reported other accomplishments and 

challenges and utilized a variety of governance structures to implement 

these activities.

Data were not collected on program benefits for specific activities, limiting 

the ability of federal agencies to oversee the program, and the monitoring 

performed at the state and local levels varied. According to our Standards 

for Internal Control in the Federal Government, federal agencies should 

oversee the use of public resources and ensure that ongoing monitoring

5

We calculated confidence intervals around estimates derived from Census data. In this 

report, all estimates shown for a percentage have a 95 percent confidence interval of less 

than plus or minus 5 percentage points, unless otherwise noted.
Page 4 GAO-06-727 Empowerment Zones and Enterprise Communities

occurs.6 However, the three agencies responsible for overseeing the 

program—HHS, HUD, and USDA—did not collect data on how program 

funds were used. For instance, HHS data show that EZs and ECs have used 

most of the EZ/EC grant funds but do not show the specific activities or 

types of activities for which the funds were used. And, although the 

performance reporting systems maintained by HUD and USDA do contain 

some information on activities that were carried out, they do not contain 

information on how much of the EZ/EC funds actually were used for 

specific activities or types of activities.7

 Further, HHS did not provide the 

states, EZs, and ECs with clear guidance on how to monitor the program 

grant funds, so the types and extent of monitoring performed by state and 

local participants varied. To some degree, the lack of reporting 

requirements may be an outcome of the program’s design, which was 

intended to give communities flexibility in using program funds and relied 

on multiple agencies for oversight. But the result has been that little 

information is available on the amount of funds spent on specific activities, 

hindering the agencies’ efforts to oversee the program.

Similarly, only limited data are available on the use of EZ/EC tax benefits, 

which were estimated to be much more substantial than the amount of 

program grant funds. We have stated that information on tax expenditures 

should be collected to ensure that these expenditures are achieving their 

intended purpose.8 In 2004, we reported that IRS collected data on some 

but not all of the program tax benefits and that the data could not be linked 

to the individual communities.9

 We also recommended that HUD, USDA, 

and IRS work together to identify the data needed to measure the use of 

EZ/EC tax benefits and the cost-effectiveness of collecting the information, 

but the three agencies did not reach agreement on a cost-effective

6

GAO, Standards for Internal Control in the Federal Government, GAO/AIMD-00-21.3.1

(Washington, D.C.: November 1, 1999).

7

HUD’s performance reporting system is known as Performance Measurement System while 

USDA’s is called the Benchmark Management System. For the purposes of this report, we 

refer to them as performance reporting systems.

8

GAO, Government Performance and Accountability: Tax Expenditures Represent a 

Substantial Federal Commitment and Need to Be Reexamined, GAO-05-690 (Washington, 

D.C.: September 23, 2005).

9

GAO, Community Development: Federal Revitalization Programs Are Being 

Implemented, but Data on the Use of Tax Benefits Are Limited, GAO-04-306, (Washington, 

D.C.: March 5, 2004).
Page 5 GAO-06-727 Empowerment Zones and Enterprise Communities

approach.10 During our work for this report, officials from some EZs and 

ECs told us that some local businesses were using the tax benefits. 

However, these testimonial data were neither sufficient to allow us to 

determine the actual amount of tax benefits used by EZs and ECs 

nationwide nor to assess the extent to which the program tax benefits 

contributed to the achievement of program goals.

Although improvements in poverty, unemployment, and economic growth 

had occurred in the EZs and ECs, our econometric analysis of the eight 

urban EZs could not tie these changes definitively to the EZ designation.11

As mentioned in our previous report, measuring the effect of initiatives 

such as the EZ/EC program is difficult for a number of reasons, such as 

data limitations and the difficulty of determining what would have 

happened in the absence of the program.12 Given these limitations, the 

effects of the EZ/EC program remain unclear. In some cases, communities 

did see decreases in poverty and unemployment and increases in economic 

growth. However, when we used econometric analyses to separate the 

effect of the program from other nonprogram factors we found that the 

comparison tracts we selected showed changes that were similar to those 

in the urban EZs. Further, EZ stakeholders and EC survey respondents said 

that program-related factors had influenced changes in their communities 

but noted that other unrelated factors had also had an effect. For example, 

stakeholders who observed a decrease in poverty in their communities 

believed that this change had resulted in part from EZ/EC activities, but 

they also noted that the population in their communities had changed, with 

original EZ/EC residents moving out of the area and individuals with higher 

incomes moving in. Ultimately, the evaluation techniques we developed 

were limited by the absence of data on the use of program grants and tax 

benefits. 

While all three rounds of the EZ/EC program are scheduled to end no later 

than December 31, 2009, we observe two limitations that should be 

considered if these or similar programs are authorized in the future. These 

10Our earlier recommendation was not directed to HHS because its role was limited to 

distribution and oversight of the EZ/EC grant funds.

11We were able to use statistical modeling techniques for the eight Round I urban EZs only, 

because the rural EZs were made up of too few census tracts to perform these analyses, and 

because the ECs received such small amounts of money over the 10-year period that we 

could not separate the program’s effects from those of other programs.

12GAO-04-306.
Page 6 GAO-06-727 Empowerment Zones and Enterprise Communities

include (1) oversight limitations that occurred because data were not 

collected on how program grant funds were used for specific activities and 

(2) the limited ability to evaluate the effect of the program due to the lack 

of data on the use of program grant funds, the extent of leveraging, and the 

extent to which program tax benefits were used. Given the magnitude of 

federal grant funds and tax benefits provided for the program, more should 

be done to better understand the extent to which these federal 

expenditures are having the desired effect. 

We provided a draft of this report to HHS, HUD, IRS, and USDA. We 

received comments from HHS, HUD, and USDA. HHS commented that a 

statement made in our report—that the agency did not provide guidance 

detailing the steps state and local authorities should take to monitor the 

program—unfairly represented the relationship between HHS and the 

other federal agencies that administered the EZ/EC program. However, we 

note in our report that the program’s design may have led to a lack of 

clarity in oversight since no single federal agency had sole oversight 

responsibility. Nonetheless, we believe that, in accordance with federal 

standards, each of the federal agencies that administered the program bore 

at least some responsibility for ensuring that public resources were being 

used effectively and that program goals were being met. HUD disagreed 

with our observation that there was a lack of data on the use of program 

grant funds, the amount of funds leveraged, and the use of tax benefits. 

However, although we found evidence that activities were carried out with 

program funds, information contained in HUD’s performance reporting 

system on the amounts of funds used and the amounts leveraged was not 

reliable. Both HUD and USDA provided suggestions for future evaluations 

of similar programs. The agencies’ comments are discussed later in the 

report and are reproduced in appendixes V through VII. HHS, HUD and 

USDA also provided technical comments that we incorporated into the 

report where appropriate.

Background The concept behind the EZ/EC program originated in Great Britain in 1978 

with the inception of the Enterprise Zone program. The main objective of 

the Enterprise Zone program was to foster an attractive business 

environment in specific areas where economic growth was lacking. In the 

United States, some states began to administer similar state Enterprise 

Zones in the 1980s. In 1993, the federal government established the federal 

EZ/EC program to help reduce unemployment and revitalize economically 

distressed areas. The authorizing legislation established the eligibility 

requirements and the package of grants and tax benefits for the EZ/EC 
Page 7 GAO-06-727 Empowerment Zones and Enterprise Communities

program (table 1). Multiagency teams from HHS, HUD, USDA, and other 

federal agencies reviewed the applications in Round I, and HUD and USDA 

issued designations based on the effectiveness of communities’ strategic 

plans, assurances that the plans would be implemented, and geographic 

diversity.13 In Round I, HUD designated a total of 8 urban EZs and 65 urban 

ECs, and USDA designated 3 rural EZs and 30 rural ECs.14

13Multiagency teams also included officials from the Department of Justice, the 

Environmental Protection Agency, and the Small Business Administration, among other 

agencies. 

14Two urban EZs—Cleveland and Los Angeles—were originally designated as Supplemental 

EZs and received a combination of Economic Development Initiative grants and Section 108 

Loan Guarantees, both of which could only be used for certain economic development or 

revitalization projects. The Supplemental EZs were given full Round I EZ status in 1998, and 

local businesses were allowed to use the program tax benefits starting in 2000. However, 

they did not receive the grants the other Round I EZs received. Four urban ECs also 

received Enhanced EC designations, which provided them with some Economic 

Development Initiative grants and Section 108 Loan Guarantees.
Page 8 GAO-06-727 Empowerment Zones and Enterprise Communities

Table 1: Round I EZ/EC Program Criteria and Benefits

Source: GAO.

a

This does not include two additional urban communities—Cleveland and Los Angeles—that initially 

received Supplemental EZ designations and received full Round I EZ status in 1998, because they did 

not receive EZ/EC grant funds.

HHS provided Round I EZs and ECs with a total of $1 billion in EZ/EC grant 

funds. EZs and ECs were allowed to use the EZ/EC grants for a broader 

range of activities than was generally allowed with those types of HHS 

funds. For instance, EZs and ECs could use funding for “traditional” 

activities, such as skills training programs for disadvantaged youth or drug 

and alcohol treatment programs, as well as for additional activities, such as 

the purchase of land or facilities related to an eligible program or the 

capitalization of a revolving loan fund. EZs and ECs were also permitted to 

use grant funds to cover some administrative costs and to change their 

goals and activities over time, with approval from HUD or USDA. In 

addition, HUD and USDA expected EZs and ECs to use the EZ/EC grant to 

leverage additional investment. 

Businesses operating in EZs and ECs were eligible for a substantial amount 

of program tax benefits. In 1993, the Joint Committee on Taxation 

Eligibility criteria To be considered for the program, communities were required to select census tracts that

• had above-average poverty according to 1990 Census data;

• had unemployment rates of at least the national average according to 1990 Census data;

• met certain 1990 population and area criteria; and

• exhibited other conditions of distress, such as high crime, deteriorating infrastructure, or population decline.

In addition, they were required to submit a strategic plan that addressed the four key principles of the program:

• economic opportunity,

• sustainable community development,

• community-based partnerships, and

• strategic vision for change.

EZ program benefits Round I EZs received Title XX Social Services Block Grants (EZ/EC grants). 

• Six urban EZs each received $100 million.a

• Three rural EZs each received $40 million.

Businesses located in EZs initially received three tax benefits:

• a tax credit for wages paid to employees who both live and work in an EZ,

• an increased expensing deduction for depreciable property, and 

• tax-exempt bonds that could be used to issue loans to qualified businesses for financing certain property.

By 2002, businesses in EZs also became eligible for two additional tax benefits related to the treatment of 

gains on the sale of EZ assets and stock. 

EC program benefits 95 Round I ECs each received $2.95 million in EZ/EC grants. 

Businesses located in ECs were eligible for one program tax benefit, the tax-exempt bond financing. 
Page 9 GAO-06-727 Empowerment Zones and Enterprise Communities

estimated that the tax benefits available to businesses in Round I 

communities would result in a $2.5 billion reduction in tax revenues 

between 1994 and 1998. In 2000, the committee estimated that the 

combination of EZ/EC program tax benefits and the Renewal Community 

tax benefits would reduce tax revenues by a total of $10.9 billion between 

2001 and 2010.15 The tax benefits for ECs expired in 2004, and the tax 

benefits for all EZs and Renewal Communities are currently set to expire at 

the end of 2009. 

Four federal agencies are responsible for administering the program in 

Round I. Oversight responsibilities for Round I were divided among three 

agencies, with HHS providing fiscal oversight and HUD and USDA 

providing program oversight (fig. 1). HHS issued grants to the states, which 

served as pass-through entities—that is, they distributed funds to 

individual EZs and ECs. According to their regulations, HUD and USDA are 

required to evaluate the progress each EZ and EC made on its strategic plan 

based on information gathered on site visits and on information reported to 

them by the designated communities. In addition, IRS is responsible for 

administering the program tax benefits.

15This number represents businesses’ use of tax benefits in all Round I EZs and ECs, as well 

as 20 Round II EZs, 10 Round III EZs, and 40 Renewal Communities. 
Page 10 GAO-06-727 Empowerment Zones and Enterprise Communities

Figure 1: Oversight Responsibilities in Round I of the EZ/EC Program

In assessing the extent of EZ/EC program improvements, it is useful to 

understand the overall national trends in poverty, unemployment, and 

economic growth. National trends in these indicators have varied since 

Round I of the program was established. As shown in table 2, the national 

poverty and unemployment rates showed improvements (i.e., declines) in 

2000 compared with 1990, but both were somewhat higher in 2004. In 1990, 

Round I EZs and ECs had poverty and unemployment rates that exceeded 

these national averages, as was required for program eligibility.

HHS HUD or USDA 

State 

EZ or EC 

Fiscal Program

Source: GAO analysis. 
Page 11 GAO-06-727 Empowerment Zones and Enterprise Communities

Table 2: National Poverty, Unemployment, Economic Growth Data for 1990 to 2004

Sources: Census Bureau and Bureau of Labor Statistics.

a

Data were not yet available for 2004.

In terms of economic growth, the table shows that the number of 

businesses increased gradually between 1990 and 2003, and the number of 

jobs increased from 1990 to 2000 but fell slightly between 2000 and 2003. 

Round I EZs and ECs 

Have Used Their Grant 

Funds to Implement a 

Wide Range of 

Program Activities

EZs and ECs used most of the program grant funds to implement a wide 

range of activities to carry out their respective revitalization strategies. In 

total, as of March 31, 2006, EZs and ECs had used all but 15 percent of the 

available grants. EZs and ECs implemented a variety of activities, but, in 

general, focused more on community development than economic 

opportunity. In addition, all designated communities reported leveraging 

additional resources, though a lack of reliable data prevented us from 

determining how much. Several designees also noted other 

accomplishments, such as increasing local coordination and capacity. The 

governance structures that Round I EZs and ECs established to implement 

these activities varied and included organizations to manage the day-to-day 

operations of the EZs, boards, and advisory committees. 

Most EZ/EC Grant Funds 

Have Been Expended, but 

Many EZs and Some ECs 

Received Grant Extensions

As of March 31, 2006, Round I EZs and ECs had spent all but 15 percent of 

the program grant funds they received. HHS data show that 20 percent of 

the program grant funds provided to EZs and 2 percent of the funds 

provided to ECs were unspent (table 3). In addition, HUD data show that 

the Cleveland and Los Angeles EZs, which originally received 

Supplemental EZ designations, had used significant portions of the 

Economic Development Initiative grants and Section 108 Loan Guarantees

Indicator 1990 1995 2000 2003 2004

Poverty 13.5% 13.8% 11.3% 12.5% 12.7%

Unemployment 5.6% 5.6% 4.0% 6.0% 5.5%

Number of 

businesses

6.1 million 6.6 million 7.1 million 7.3 million a

Number of jobs 93.4 million 100.3 million 114.1 million 113.4 million a
Page 12 GAO-06-727 Empowerment Zones and Enterprise Communities

that came with their designations.16 Specifically, each of them had spent 

slightly more than 70 percent of their grants; Cleveland had used 72 percent 

of its loan guarantees, but Los Angeles had used less—about 33 percent. 

Table 3: Total EZ/EC Grant Funding Remaining as of March 31, 2006

Source: GAO analysis of HHS data.

Most of the remaining $151 million in EZ/EC grants consists of the funds of 

four urban EZs: Atlanta, New York, Philadelphia-Camden, and Chicago, 

with Atlanta and New York accounting for the majority of the unspent 

funds (fig. 2). When the Atlanta EZ received a Renewal Community 

designation from HUD in 2002, the EZ designation was terminated, but HHS 

allowed the city of Atlanta to continue spending its remaining EZ grant 

funds through December 2009. The city of Atlanta elected to administer its 

remaining EZ grants in conjunction with its Renewal Community initiative, 

and prepared a strategic plan to address administration of both the 

remaining HHS funds and the HUD-designated Renewal Community. The 

Atlanta Renewal Community officials told us that they did not use the EZ 

funds for about 4 years after receiving the designation because of the time 

required for start-up but added that they planned to begin utilizing the 

funds soon. The New York EZ received matching funds from both the state 

and city governments, for a total of $300 million. New York EZ officials 

stated that they used equal parts of funding from these three sources for 

each activity, potentially explaining why they have drawn down funds at a 

slower rate than other EZs.

16The Cleveland EZ received $87 million in grants and an equal amount of loan guarantees, 

while the Los Angeles EZ received $125 million in grants and $325 million in loan 

guarantees. 

Total funding Amount remaining Percent remaining

EZs $720 million $146.6 million 20%

ECs $280 million $4.5 million 2%

Total $1 billion $151 million 15%
Page 13 GAO-06-727 Empowerment Zones and Enterprise Communities

Figure 2: Remaining Grant Funds by EZ as of March 31, 2006

Note: Two urban EZs—Philadelphia-Camden and New York—implemented the program through two 

separate entities that split the $100 million grant. These separate entities are represented above for 

Philadelphia-Camden, but separate data for the New York EZ were not available from HHS. The 

Cleveland and Los Angeles EZs did not receive EZ grant funds. 

Although the grant period for Round I EZs and ECs was originally 

scheduled to end December 21, 2004, several EZs and some ECs received 

extensions from HHS to continue drawing down their remaining funds. The 

recipients had to demonstrate a legitimate need to complete project 

activities outlined in their strategic plans. Eight of the 11 EZs (6 urban, 2 

rural) and 17 of the 95 ECs (11 urban and 6 rural) received extensions of 

their grants until December 31, 2009. In addition, 1 urban EZ and 9 ECs (6 

urban and 3 rural) received extensions for a shorter time frame, such as 

2005, 2006, or 2007. 

0 

20 

40 

60 

80 

100 

Amount remaining 

Amount spent

Kentucky 

Mid-Delta 

Highlands

Rio Grande 

Atlanta 

Valley 

New York 

PhiladelphiaCamden 

Philadelphia

Camden 

Chicago 

Detroit 

Baltimore 

Dollars in miilions

Source: GAO analysis of HHS data.
Page 14 GAO-06-727 Empowerment Zones and Enterprise Communities

EZs and ECs Implemented a 

Wide Variety of Activities, 

Most Related to Community 

Development 

The designated communities were encouraged to implement both 

community and economic development activities as part of their 

revitalization strategies. The EZ/EC program was designed to be tailored to 

address local needs, and the type of grant funds most EZs and ECs received 

from HHS allowed them to implement a wide range of activities. Overall, 

both EZs and ECs used the program grants to implement a larger number of 

community development activities—such as education, health care, and 

infrastructure—than economic opportunity activities—such as workforce 

development and providing assistance to businesses (fig. 3).17

Figure 3: Distribution of EZ and EC Activities by Key Program Principle

Note: This figure shows the percent of the total number of activities implemented, not the funds 

devoted to those activity types. The Cleveland and Los Angeles EZs are not included in this graphic 

because they did not receive EZ grant funds. The numbers do not always add up to 100 due to 

rounding.

The activities most often implemented by urban EZs and ECs were 

workforce development, human services, education, and assistance to 

businesses, which accounted for more than 50 percent of the activities in 

17EZs and ECs self-determined the categories for their activities, so it is possible that a 

similar activity implemented in two sites could be categorized differently.

Community-based partnership

Economic opportunity 

Community development 

Rural 

Urban 

ECs

EZs

ECs

EZs

Designation Type Percentage of the total number of activities

43

79 

57 

76 

28 29 

11 11 

35 7 

14 10 

Source: GAO analysis of HUD and USDA data.
Page 15 GAO-06-727 Empowerment Zones and Enterprise Communities

urban EZs and 60 percent of the activities in urban ECs (fig. 4). For 

example, the Baltimore EZ implemented a customized training program 

that provided EZ residents with individualized training and a stipend during 

the training period. In the Bronx portion of the New York EZ, stakeholders 

explained that they had funded an organization that trained women to 

become child care providers, a program that not only provided job skills 

and employment opportunities but also improved the availability of child 

care in the area. In addition, the Atlanta EZ and the Camden portion of the 

Philadelphia-Camden EZ implemented educational programs for EZ youth, 

such as after-school or summer programs. Also, stakeholders from the 

Upper Manhattan portion of the New York EZ mentioned contributing 

financial assistance to the business development of the Harlem USA 

project, a 275,000-square-foot retail development located in the EZ. 

Moreover, stakeholders from the Providence EC said they provided grants 

to a nonprofit that offered job training to youth and business development 

programs, such as “business incubators” that offered office space and 

technical assistance to new small businesses.
Page 16 GAO-06-727 Empowerment Zones and Enterprise Communities

Figure 4: Types of Activities Implemented by Urban and Rural EZs and ECs, by Percent of Total Activities

Note: This figure shows the percent of the total number of activities implemented, not the funds 

devoted to those activity types. The data reporting systems for urban and rural designees used slightly 

different categories of activities. The Cleveland and Los Angeles EZs are not included in this graphic 

because they did not receive EZ grant funds. 

Rural EZs and ECs implemented many of the same types of activities as 

urban designees, such as business development and job training, but often 

included activities related to health care and public infrastructure. For 

example, stakeholders from the Kentucky Highlands and Mid-Delta 

Mississippi EZs said that they had attracted businesses to the areas using 

EZ loans, grants, or tax benefits, and stakeholders from the Rio Grande 

Valley EZ reported funding job training for EZ residents. In addition, 

stakeholders from Kentucky Highlands said the EZ purchased ambulances 

0 5 10 15 20 25 

Tax incentive 

utilization 

Governance board 

Other programs/ 

projects

Health 

Environment 

Infrastructure 

Public safety 

Capacity building

Access to capital 

Housing

Businesses

asssisted 

Education 

Human services

Workforce 

development 

0 5 10 15 20 25 

Tourism and culture 

Housing

Environment and 

natural resources

Public safety 

Community/youth/ 

family resources

Capacity building

Public infrastructure 

Education 

Health care 

Business development/ 

job training

ECs

EZs

Source: GAO analysis of HUD and USDA data. 

Urban 

Percentage 

Percentage 

Rural 
Page 17 GAO-06-727 Empowerment Zones and Enterprise Communities

for an area that previously did not have those services. All three rural EZs 

reported using the EZ/EC grant to improve the water or sewerage 

infrastructure in their EZs, which some said was needed to foster 

additional economic development. Finally, stakeholders from the 

Fayette-Haywood EC reported having implemented several activities 

related to health care, such as recruiting doctors and providing funding to 

reopen a clinic that had been closed for several years. For more 

information on the types of activities implemented by the individual 

communities we visited, see appendix IV.

EZs and ECs Used Program 

Grants to Leverage Additional 

Funds, but Reliable Data on the 

Extent of Leveraging Are Not 

Available

HUD and USDA also expected designees to use their grants to leverage 

additional investment. Stakeholders from all EZs and ECs we visited and all 

EC survey respondents reported having used their EZ/EC grants to leverage 

other resources, including both monetary and in-kind donations. EZs and 

ECs developed different policies that may have affected the extent to 

which they leveraged funds. For example, the Mid-Delta EZ required that 

direct grant recipients obtain at least 65 percent of their funding from other 

sources. Some other communities, such as the Atlanta EZ, did not have 

similar requirements for subgrantees, although in some cases subgrantees 

did leverage funds on their own initiative. EC survey respondents reported 

using the EZ/EC grants to leverage additional resources for capital 

improvements, social services, and funding for businesses, among other 

things. Some EC survey respondents also mentioned that the designation 

had helped them to leverage funds to implement additional programs or to 

expand EC programs.

All EZs and ECs that provided us with a definition of leveraging said that 

they included all non-EZ/EC grant funds that were used in EZ/EC-funded 

programs. But only two of the four EZs that used the program tax-exempt 

bond included the amount of the bonds in their total leveraged funds. In 

addition, some EZs reported as leveraged funds other investments made in 

the EZ area, aside from those directly funded with the EZ/EC grant funds, 

although other designated communities did not. For example, the 

Baltimore EZ included all business investments made subsequent to 

infrastructure improvements the EZ made to an industrial park. 

USDA encouraged rural EZs and ECs to report all investment in the EZ as 

leveraged funds, not only those projects that received EZ/EC funds. For 

example, at USDA’s instruction, the Fayette-Haywood EC included funding 

from other USDA programs operating in the EC, even when EC funds were 

not involved. However, not all rural sites used this broad definition of 

leveraging. Similarly, at one HUD official’s instruction, the Cleveland EZ 
Page 18 GAO-06-727 Empowerment Zones and Enterprise Communities

included as leveraged funds other investments made within the EZ, such as 

city Community Development Block Grant funds invested in the area.18

However, there was no written guidance telling the Cleveland EZ to include 

other investments, and it no longer includes these other investments as 

leveraged funds in performance reports.19

Although communities reported using the EZ/EC grants to leverage 

additional resources, we could not verify the actual amounts. HUD’s and 

USDA’s performance reporting systems include information on the amount 

of funds leveraged for each activity, but for the sample of activities we 

reviewed, either supporting documentation showed an amount conflicting 

with the reported amount or documentation could not be found.20 In 

addition, the definition of “leveraged” varied across sites, as the federal 

agencies did not provide EZs and ECs with a consistent definition of what 

leveraged funds should include. As a result, designated communities 

included different types of funds in the amounts they reported as 

leveraged. 

Designees Reported Other 

Accomplishments

In addition to the activities that were implemented, EZ and EC 

stakeholders with whom we spoke mentioned other accomplishments that 

were not as easy to quantify and report in the performance systems. For 

example, one of the aims of the EZ/EC program was to increase 

collaboration among local governments, nonprofits, community members, 

and the business community. Stakeholders from several sites we visited 

commented on how the designation facilitated increased collaboration 

among different groups of people and organizations. For instance, several 

stakeholders from the Rio Grande Valley EZ noted the value of having 

different communities and people work together, something that had not 

happened prior to the EZ/EC program. Several EC survey respondents also 

mentioned the importance of collaboration and partnerships in carrying 

out the EC program. Stakeholders from some sites we visited mentioned 

that the EZ/EC program had helped to empower local residents by giving 

them a better understanding of how government worked. In addition, 

stakeholders from some EZs said that the EZ/EC program had helped to 

18The federal Community Development Block Grant program supports a wide array of local 

community development activities that are primarily to benefit low- and moderate-income 

individuals.

19However, past reported amounts remain in their performance data in HUD’s system.

20This finding is consistent with findings of the HUD and USDA Offices of Inspector General.
Page 19 GAO-06-727 Empowerment Zones and Enterprise Communities

build the capacity of local organizations. In Cleveland, local stakeholders 

said that the funding provided by the EZ had helped increase the 

organizational capacity of four local community development corporations 

and that participation in the governance of the EZ helped to foster 

communication between the groups. 

Designees Reported 

Implementation Challenges

EZ stakeholders also mentioned some issues that had made implementing 

the EZ/EC program more challenging. Stakeholders from some EZs noted 

that an initial lack of experience or expertise on the part of EZ officials had 

made it difficult to implement the program. In addition, stakeholders from 

the Camden portion of the Philadelphia-Camden EZ and the Rio Grande 

Valley EZ said that local subgrantee organizations generally had a low level 

of organizational capacity, which sometimes made it difficult to choose 

qualified applicants to implement EZ programs. Stakeholders from several 

sites also said that it was difficult to manage the expectations of both the 

EZ community and of residents and businesses that were not located in the 

zones and were not eligible for EZ/EC program benefits, especially when 

the individuals and businesses were located just across the street from the 

designated area. 

EZs and ECs Established a 

Variety of Governance 

Structures and Encouraged 

Community Participation

In addition to choosing the activities that their EZs or ECs implemented, 

designated communities were permitted to determine the structure they 

would use to govern and operate the program. Generally, these structures 

included an EZ/EC management entity—either a nonprofit organization or 

an entity that was part of the local government. Two urban EZs—New York 

and Philadelphia-Camden—became two separate entities that were 

managed by different types of organizations that split the $100 million EZ 

grant. In the Philadelphia-Camden EZ, for example, the Philadelphia 

portion was run by the city of Philadelphia and the Camden portion by a 

nonprofit organization. All designees had at least one board, and, in some 

cases, EZs included community advisory groups or separate “subzone” 

boards, which represented specific areas of the EZ in their governance 

structures. 

All three rural EZ boards made decisions about EZ activities without the 

direct involvement of local government entities. However, the extent of 

government involvement in urban EZ boards varied, regardless of whether 

the EZ was managed by a nonprofit or local government organization (fig. 

5). For example, in two EZs, Cleveland and Chicago, local government had 

extensive control of the program, but in other EZs, such as Detroit, the 

board of the nonprofit organization that managed the EZ shared partial 
Page 20 GAO-06-727 Empowerment Zones and Enterprise Communities

decision-making authority with the mayor and city council. Other EZs were 

operated with minimal local government involvement, with the boards 

determining which activities to implement, allocating resources, and 

deciding which entities would implement the programs. Appendix IV 

provides more details on the governance structures of the EZs we visited.

Figure 5: Local Government Involvement in Decision Making in the Urban EZs

a

The Los Angeles EZ was operated by a for profit organization—the Los Angeles Community 

Development Bank—until 2002 when it filed for bankruptcy. Since then, a Los Angeles city department 

has continued its operations; however, the mayor and city council are not directly involved.

Another program expectation was to encourage community participation 

within the designated communities. Regardless of the type of governance 

structure they used, EZs and ECs involved community participants in the 

planning and carrying out of program activities. According to stakeholders 

from all the EZs and the ECs we visited, residents were involved in 

meetings such as “visioning sessions” and town hall gatherings during the 

strategic planning process. Community groups, such as local colleges and 

universities, development corporations, and businesses, were also involved 

prior to designation. In addition, 56 out of 58 ECs responding to our survey 

reported that EC residents attended listening sessions, generated ideas for 

activities, or helped to establish priorities. Respondents also indicated that 

a variety of other groups participated in the strategic planning process for 

Level of local government involvement 

Minimal Partial Extensive 

Chicago 

Baltimore Cleveland 

Los Angelesa

Camden portion 

of Philadelphia-Camden

Upper Manhattan 

portion of New York 

Bronx portion 

of New York 

Philadelphia portion 

of Philadelphia-Camden 

Atlanta

Detroit

EZs: 

Source: GAO analysis of EZ documentation and interview data. 

Managed by local government 

Managed by another type of organization

Managed by nonprofit organization
Page 21 GAO-06-727 Empowerment Zones and Enterprise Communities

the ECs, including local government officials and representatives from 

community-based organizations. 

After designation, stakeholders from the EZs and ECs we visited said that 

residents often served on boards, and some stakeholders noted they relied 

on the boards to capture a wide range of viewpoints. Most EZs and ECs we 

visited also included as participants business representatives, officials 

from nonprofits, and clergy, among others. Some EZs and ECs also 

included residents from specific neighborhoods within the designated area 

or individuals with special expertise, such as in the areas of health care and 

housing. 

Oversight Was 

Hindered by Limited 

Program Data and 

Variation in Monitoring 

According to our federal standards, federal agencies should oversee the 

use of public resources and ensure that ongoing monitoring occurs.21

However, HHS, HUD, and USDA did not collect data on how program funds 

were spent. In addition, HHS did not provide the states, EZs, and ECs with 

clear guidance on how to monitor the program grant funds, and the types 

and extent of monitoring performed by state and local participants varied. 

The lack of reporting requirements may be related to the program’s design, 

which was intended to give communities flexibility in using program funds 

and relied on multiple agencies for oversight. However, these limitations 

have hindered the agencies’ efforts to determine whether the public 

resources are being used effectively and program goals are met.

Federal Agencies Are 

Required to Oversee the Use 

of Public Funds and Provide 

Ongoing Monitoring

According to federal standards established in the Standards for Internal 

Control in the Federal Government, program managers need both program 

and fiscal data to determine whether public resources are being used 

effectively and program goals are being met.22 In the case of the EZ/EC 

program, fiscal data would include not only the aggregate amount of 

program grant funding designated communities spent, but also data on the 

amount of funds spent on specific types of activities. Program data would 

include descriptions of the activities implemented and program outputs, 

such as the number of individuals trained in a job training program. The 

standards also state that federal agencies should ensure that ongoing 

21GAO/AIMD-00-21.3.1.

22GAO/AIMD-00-21.3.1.
Page 22 GAO-06-727 Empowerment Zones and Enterprise Communities

monitoring occurs in the course of normal operations. For instance, the 

federal agencies should provide guidelines on what monitoring should 

occur, including whether on-site reviews or reporting are required. For the 

EZ/EC program, HHS regulations require states, EZs, and ECs to maintain 

fiscal control of program funds and accounting procedures sufficient to 

enable them to prepare reports and ensure the funds were not used in 

violation of the applicable statute. 

The Federal Agencies’ 

Oversight Efforts Had 

Shortcomings in Data 

Collection

None of the federal agencies collected data showing how program funds 

had been spent. As we have noted, the EZ/EC grants were special Social 

Services Block Grants that gave recipients expanded flexibility in using the 

funds. The regulations for most grants of this type require states to report 

on, among other things, the amount of funding spent on each type of 

activity. However, because HHS did not require this level of reporting for 

the EZ/EC program, the agency’s data show how much of each grant was 

used but not how much was spent on specific activities or types of 

activities. Further, HHS’s data sometimes do not show how much of the 

grant a specific EC used, since states could aggregate drawdowns for 

multiple communities. For example, there are five urban ECs in Texas, but 

the data reported to HHS show only the aggregate amount of funds these 

ECs used, not the amount used by each.

Similarly, although HUD’s and USDA’s reporting systems contained some 

information on the amount of EZ/EC grants budgeted for specific activities, 

the systems did not account for the amounts actually spent on those 

activities. Moreover, we found that the data on the amount of EZ/EC grant 

funding were often not reliable, as some EZs and ECs reported budgeted 

amounts and others reported actual amounts spent. Further, in our 

assessments of the reliability of these data, we found documentation 

showing that the designated communities had undertaken certain activities 

with program funding, but we were often unable to find documentation of 

the actual amounts allocated or expended.23

23Because data on the amount of funds used for specific activities was not reliable, this 

report only includes information on the number of activities implemented. We were able to 

find complete documentation for our sample of activities for the amount of EZ grant funding 

reported by the Baltimore and Detroit EZs and the Camden portion of the 

Philadelphia-Camden EZ.
Page 23 GAO-06-727 Empowerment Zones and Enterprise Communities

Program Monitoring by 

State and Local Participants 

Varied

Although HHS regulations require states, EZs, and ECs to maintain fiscal 

control of program grant funds, the agency also did not provide guidance 

detailing the steps state and local authorities should take to monitor the 

program. In the absence of clear guidance, the type and level of monitoring 

conducted at the state and local levels varied. For example, some state and 

EZ/EC officials applied guidelines from other programs, such as the 

Community Development Block Grant program, or developed their own 

policies. Officials from almost all states we interviewed said they reviewed 

audits of the EZs and ECs and were required to submit aggregate data to 

HHS, and most had performed site visits at least once during the program. 

State officials also said they reviewed requests to draw down grant funds, 

approving expenditures if the requests met the goals outlined in the 

strategic plans. However, most states did not maintain records showing the 

types of activities designated communities undertook. Some states said 

that they had taken corrective actions, such as withholding payments when 

designated communities had not properly reported how funds were used. 

However, only a few states also completed program monitoring activities, 

such as reviewing whether a project took place or benefited EZ or EC 

residents, in conjunction with their fiscal reviews. Most of the EZs and ECs 

we visited conducted on-site monitoring of subgrantees and reviewed their 

financial and performance data, and some communities required annual 

audits of their subgrantees. For example, the Rio Grande Valley EZ 

assigned a program staff member to monitor each subgrantee activity and 

required annual audits. In contrast, the Fayette-Haywood EC did not 

perform any site visits and relied on other funding organizations to monitor 

subgrantees. 

Some instances of misuse of program funds did occur during the EZ/EC 

program. For example, officials at the Mid-Delta EZ reported two cases of 

embezzlement by EZ personnel.According to an EZ official, in one case 

that was discovered through an independent audit, an individual was 

prosecuted for embezzling $28,000 in 1996 (only $1,800 was recouped). The 

second case of embezzlement of $31,000 by two EZ staff, discovered when 

the staff turned themselves in, is currently under joint State of Mississippi 

and FBI investigation as part of a larger investigation of misuse of EZ funds 

starting as early as 1996. In addition, three audits by the state of Georgia 

found that almost all the administrative funds designated for the Atlanta EZ 

($4 million) had been used in the first 3 1⁄2 years of the program, including 

approximately $44,000 used for questionable costs related to personnel and 

travel expenditures. To address this issue, the Atlanta EZ repaid some of 

the costs in question, provided additional documentation, and instituted 
Page 24 GAO-06-727 Empowerment Zones and Enterprise Communities

better recordkeeping procedures. The city of Atlanta also initiated a 

restructuring of the EZ and fired the majority of EZ staff. 

Limitations in EZ/EC Oversight 

May Have Resulted from the 

Program Design 

As discussed earlier, the EZ/EC program was designed to give the 

designated communities increased flexibility in deciding how to use 

program funds and used states as pass-through entities for providing funds. 

Part of the philosophy behind the program was to relieve states and 

localities of the burden of excessive reporting requirements. Furthermore, 

no single federal agency had sole responsibility for oversight of Round I of 

the EZ/EC program, although federal standards require that agencies 

provide adequate oversight over public resources. In the beginning, the 

agencies made some efforts to share information, but these efforts were 

not maintained. For example, HUD officials said that they had received 

fiscal data from HHS and reconciled that information with their program 

data on the activities implemented in the early years of the program. 24

According to HUD, the agency made additional attempts to obtain data 

from HHS but only recently received a report. An HHS official said the 

agency no longer regularly shared detailed data with HUD and USDA, 

which the official said was likely due to a lack of program staff. 

These limitations do not necessarily apply to Rounds II and III of the EZ/EC 

program. For example, both fiscal and program oversight of the urban and 

rural EZs and ECs were provided directly through HUD and USDA in 

Round II because the program funding came directly through HUD and 

USDA appropriations. Officials from both agencies explained that 

information on the activity for which funds were used was linked to each 

drawdown of program funds. In addition, a HUD official said they had 

issued improved monitoring guidance in Round II, since designees receive 

funds directly from HUD. However, a USDA official said that they provided 

similar monitoring guidance to designees in Rounds I, II, and III. Because 

this report focuses on Round I of the program, we did not determine the 

effectiveness of the oversight of future rounds of the program. 

24Neither HHS nor USDA officials told us that they had made any efforts to reconcile fiscal 

and program data on the EZ/EC program.
Page 25 GAO-06-727 Empowerment Zones and Enterprise Communities

Lack of Detailed Tax 

Data Made It Difficult 

to Assess the Use of 

Program Tax Benefits

A lack of detailed tax data limited our ability to assess the extent to which 

businesses in the EZs and ECs used program tax benefits. We have 

previously reported that information on tax expenditures should be 

collected to ensure that these expenditures are achieving their intended 

purpose.25 IRS collects data on the use of some of the program tax benefits, 

but not all of them, and none of the data can be linked to the individual 

communities where the benefits were claimed. We also recommended that 

HUD, USDA, and IRS work together to identify the data needed to measure 

the use of EZ/EC tax benefits and the cost-effectiveness of collecting the 

information, but the three agencies did not reach agreement on a 

cost-effective approach.26 Officials from some EZs and ECs reported that 

some of the tax benefits were being used, but this information was not 

sufficient to allow us to determine the actual extent of usage. 

IRS Data on the Use of 

Program Tax Benefits Are 

Limited 

Previously, we have noted that information on tax expenditures should be 

collected in order to evaluate their effectiveness as a means of 

accomplishing federal objectives and to ensure that they are achieving their 

intended purpose.27 Inadequate or missing data can impede such studies, 

especially given the difficulties in quantifying the benefits of tax 

expenditures. Nevertheless, we have stated that the nation’s current and 

projected fiscal imbalance serves to reinforce the importance of engaging 

in such evaluations. 

However, as described in our 2004 report, the IRS collects limited data on 

the EZ/EC tax benefits. It does not collect data on benefits used in 

individual designated sites and for some benefits it does not have any 

data.28 For example, the IRS collects some information on EZ businesses’ 

use of tax credits for employing EZ residents. However, the data cannot be 

separated to show how much was claimed in individual EZs. In addition, 

IRS does not have data on the use of the increased expensing deduction for 

depreciable property, because taxpayers do not report this benefit as a 

separate line item on their returns. The lack of data on the use of program 

25GAO-05-690.

26GAO-04-306.

27GAO-05-690. 

28GAO-04-306.
Page 26 GAO-06-727 Empowerment Zones and Enterprise Communities

tax benefits is consistent with findings of other reports we prepared citing 

data challenges in other similar community and economic development 

programs, such as the Liberty Zone program.29

Our 2004 report recommended that HUD, IRS, and USDA collaborate to 

identify a cost-effective means of collecting the data needed to assess the 

use of the tax benefits.30 In response, HUD, IRS, and USDA identified two 

methods for collecting the information—through a national survey or by 

modifying the tax forms. However, the three agencies did not reach 

agreement on a cost-effective method for collecting additional data. Given 

the lack of information at the federal level, we, some EZs, and other 

researchers have tried to assess the use of EZ/EC tax benefits by surveying 

businesses.31 However, these surveys have had low response rates and a 

high number of undeliverable surveys, suggesting that the results might not 

be representative. Reasons associated with the low response rates were 

cited in previous reports, including the difficulty of locating someone at the 

businesses who knew whether the tax benefit had been claimed and issues 

associated with multiple business locations.32 In addition, some EZ officials 

said that businesses were not willing to share their tax information. 

Further, a high rate of small business closures was determined to be a 

contributing factor to the high number of undeliverable surveys. We 

initiated a survey of businesses as a part of the audit work for this 

engagement, but discontinued the survey due to a low response rate.33

29GAO-05-690; GAO, 21st Century Challenges: Reexamining the Case of the Federal 

Government, GAO-05-325SP (Washington, D.C.: February 1, 2005); and GAO, Tax Policy: 

Tax Expenditures Deserve More Scrutiny, GAO/GGD/AIMD-94-122 (Washington, D.C.: June 

3, 1994). The New York Liberty Zone was created in response to the September 11, 2001 

terrorist attacks and created seven tax benefits designed to assist in the recovery efforts, 

including a tax credit for hiring employees who are Liberty Zone residents.

30GAO-04-306. Our earlier recommendation was not directed to HHS because its role was 

limited to distribution and oversight of the EZ/EC grant funds.

31GAO, Community Development: Businesses’ Use of Empowerment Zone Tax Incentives, 

GAO/RCED-99-253 (Washington, D.C.: September 30, 1999) and Scott Hebert and others, 

Interim Assessment of the Empowerment Zones and Enterprise Communities (EZ/EC) 

Program: A Progress Report, prepared for the U.S. Department of Housing and Urban 

Development (Washington, D.C.: November 2001). 

32GAO/RCED-99-253 and Hebert and others, Interim Assessment.

33For more information on our survey methods, see appendix I.
Page 27 GAO-06-727 Empowerment Zones and Enterprise Communities

In the absence of other data, we relied on testimonial information to assess 

how often the EZ tax benefits were used and who used them. Although 

stakeholders from all EZs told us that they did not have any data on the 

extent to which EZ businesses had used program tax benefits, they 

provided us with some information that was consistent with the findings of 

past studies.34 For example, during our site visits, EZ stakeholders told us 

that they believed large businesses, which tend to use tax professionals 

who know and understand the benefits, were more likely to use the tax 

benefits than small businesses. They also noted that small businesses were 

less likely to make enough in profits to take advantage of the tax benefits.35

The stakeholders stated further that the credit for employing EZ residents 

was the most frequently used of the three original tax benefits. A few EZ 

officials commented that retail businesses were more likely to use the 

employment credit and manufacturing businesses were more likely to use 

the increased expensing deduction. 

Stakeholders from only 4 of the 11 EZs and 2 of the 58 ECs that responded 

to our EC survey told us that the tax-exempt bond benefit had been used in 

their communities. EZ stakeholders and EC survey respondents cited a 

variety of reasons that the tax-exempt bond financing had not been more 

widely used. For instance, some said that the bonds were not used because 

of the availability of the Industrial Development Revenue Bond, which EZ 

stakeholders explained had fewer restrictions and could be issued for 

larger amounts.36 In addition, some EZ stakeholders and one EC survey 

respondent said that it was difficult to find a large pool of qualified EZ 

residents to satisfy the employment requirement for the bond, which 

required that at least 35 percent of the workforce be EZ residents. Some EZ 

stakeholders also told us that the legal fees for an EZ bond were higher 

than for other types of bonds because the restrictions made the EZ bond 

more complex. For this reason, stakeholders explained, the cost of issuing 

the EZ bond was high relative to the bond cap, particularly early in the

34GAO/RCED-99-253 and Hebert and others, Interim Assessment.

35The EZ/EC tax benefits were nonrefundable, which means that a business can only claim 

them if it has a tax liability.

36An Industrial Revenue Bond is a bond used to finance the construction of manufacturing 

or commercial facilities for a private user. This bond is available to businesses in general 

and is not part of the EZ program benefits package.
Page 28 GAO-06-727 Empowerment Zones and Enterprise Communities

program.37 Finally, some EC survey respondents noted other reasons for 

not using the bond, such as the complicated nature of the bond or a lack of 

interested businesses or viable projects.

IRS Officials Reported that 

They Have Data Sufficient 

to Enforce the Tax Code, 

but This Information Is 

Insufficient for Assessing 

the Extent of Usage

IRS officials said that the limited data the agency collected did not affect its 

ability to enforce compliance with the tax code. They told us that IRS’s role 

is to administer tax laws and said that collecting more comprehensive data 

on the use of program tax benefits would not help the agency to achieve 

this objective. Further, they said that they allocate their resources based on 

the potential effect of abuse on federal revenue and noted that these tax 

benefits are not considered high risk, since the amount claimed is small 

compared with revenues collected from other tax provisions or the amount 

of potential losses from abusive tax schemes. Furthermore, both IRS 

officials and our previous reports have suggested that IRS generally does 

not collect information on the frequency of use or types of businesses 

claiming tax benefits unless legislatively mandated to do so.38

Although the total program tax benefits were estimated to be much larger 

than the federal grant funding—over $2.5 billion compared with the $1 

billion in EZ/EC grants—we do not, as we have noted, know the actual 

amount of tax benefits claimed by Round I EZs and ECs nationwide or the 

amounts used in individual communities.39 As a result, we could not assess 

differences in the rates of usage among the designated communities. 

Although we understand IRS’s concerns, the lack of data is likely to 

become increasingly problematic in light of the fact that future rounds of 

the EZ/EC program and the Renewal Community program rely heavily on 

tax benefits to achieve revitalization goals. It may also be a concern with

37A bond cap is the maximum dollar amount available for issuing the tax exempt bond. Prior 

to January 1, 2002, the cap for bonds was $3 million per borrower for activities in any EZ or 

EC, with a nationwide limit of $20 million per borrower. After 2002, the bond cap was 

removed for all EZs.

38GAO-05-690 and GAO-04-306.

39The Joint Committee on Taxation estimated that businesses in Round I communities 

would claim about $2.5 billion in tax benefits in the first four years of the program alone. 

Information for later years of the Round I program is not available because subsequent 

estimates by the committee did not separate benefits claimed by Round I communities from 

benefits claimed by later round communities.
Page 29 GAO-06-727 Empowerment Zones and Enterprise Communities

the Gulf Opportunity Zone Act, which provides tax benefits in counties and 

parishes affected by the 2005 Gulf Coast hurricanes.40

In Aggregate, EZs and 

ECs Showed Some 

Improvements, but Our 

Analysis Did Not 

Definitively Link These 

Changes to the 

Program

Although EZs and ECs showed some improvements in poverty, 

unemployment, and economic growth, we did not find a definitive 

connection between these changes and the EZ/EC program. As mentioned 

in our previous report, measuring the effect of initiatives such as the EZ/EC 

program is difficult for a number of reasons, such as data limitations and 

the difficulty of determining what would have happened in the absence of 

the program.41 In some cases, communities saw decreases in poverty and 

unemployment and increases in economic growth. But, we could not 

conclusively determine whether these changes were a response to the 

EZ/EC program or to other economic conditions. EZ stakeholders and EC 

survey respondents said that program-related factors had influenced 

changes in their communities but that other unrelated factors also had an 

effect. Although the overall effects of the EZ/EC program remain unclear, 

having data on the use of program grants and tax benefits would have 

allowed for a richer assessment of the program. 

A Number of Challenges 

Affected Our Efforts to 

Measure the Effects of the 

EZ/EC Program 

We attempted to assess the effects of the program on four indicators: 

poverty, unemployment, and two measures of economic growth—the 

number of businesses and the number of jobs.42 Although we used several 

quantitative and qualitative methods, including an econometric analysis to 

try to isolate the EZ/EC program’s effect, we could not differentiate 

between the effects of the program and other factors. Among the 

challenges we encountered were the following: 

• A lack of adequate data on the use of program benefits. As mentioned 

earlier, data on the use of EZ/EC grant funds and tax benefits were very 

limited.

40The Gulf Opportunity Zone Act of 2005 provides tax benefits to assist in the recovery and 

rebuilding of areas affected by Hurricanes Katrina, Rita, and Wilma. 

41GAO-04-306.

42The indicators of poverty, unemployment, and economic growth were specifically 

identified in our mandate.
Page 30 GAO-06-727 Empowerment Zones and Enterprise Communities

• Limited demographic data. We used poverty and unemployment data 

from the 1990 and 2000 censuses, but these dates do not correspond 

well to the program dates, as communities were designated in 1994 and 

in some cases are still operating. 

• Demonstrating what would have happened in the absence of the 

program. For example, we attempted to identify comparison areas that 

did not receive EZ or EC designations and that reflected similar 

community characteristics of EZs and ECs. 43 However, the designated 

communities sometimes had the highest poverty levels in the area, 

making it difficult to find exact matches among nearby census tracts. 

• Accounting for the spillover effects of the program to other areas, the 

effects of similar public and private programs, and the effects of 

regional and local economic trends.

• Accounting for bias in the choice of program areas. For example, if 

program officials tended to pick census tracts that were already 

experiencing gentrification prior to 1994, we may be overstating the 

effect of the EZ designation.44 Conversely, if officials tended to choose 

census tracts that were experiencing economic declines prior to 1994, 

such as areas affected by the loss of major employers, we may be 

understating the program’s impact. 

Several program-specific factors also limited our ability to assess the 

effects of the program. First, the program was designed to be tailored to the 

local sites, and each community was given broad latitude to determine its 

own needs and the program activities it thought would address those 

needs. Thus, each designee may or may not have selected program 

activities that directly related to the three factors—poverty, 

unemployment, and economic growth—mandated for our evaluation. 

Second, the time frame of actual program implementation may have varied 

among the designees. For instance, some EZ stakeholders mentioned that 

43We selected comparison areas through a statistical technique called the propensity score, 

which allowed us to identify the census tracts that were most similar to the census tracts 

selected in the original EZ and EC designations based on a set of factors, such as 1990 

poverty and unemployment rates. For more information on how we chose the comparison 

areas, see appendix I.

44Gentrification or economic displacement refers to the transformation of a relatively 

low-income neighborhood into a more affluent neighborhood through redevelopment, 

usually in conjunction with changing demographics and an influx of wealthier residents. 
Page 31 GAO-06-727 Empowerment Zones and Enterprise Communities

their programs took 2 or 3 years to get started, while others were able to 

begin drawing down funds in the first year. Third, the nature of the EZ/EC 

program, which focuses on changes in geographic areas rather than on 

individuals, makes it difficult to determine how the program affected 

residents who lived in an EZ/EC in 1994 but later moved. Stakeholders from 

most of the EZs and ECs we visited said that residents were moving out of 

the designated areas, often after finding a job. If true, this phenomenon 

may have masked some of the program’s effects on poverty and 

unemployment, since these individuals would not be captured in the 2000 

data.

In Some Cases, EZs and ECs 

Showed Improvements in 

Poverty, Unemployment, 

and Economic Growth

Some EZs and ECs saw improvements in poverty, unemployment, and 

economic growth. Four of the 11 EZs—Cleveland, Detroit, PhiladelphiaCamden, and Kentucky Highlands—showed improvements in both poverty 

and unemployment between 1990 and 2000 and at least one measure of 

economic growth between 1995 and 2004 (fig. 6). Some ECs also 

experienced similar improvements. For example, 25 out of 95 ECs saw 

positive changes in poverty and unemployment and at least one measure of 

economic growth.45 None of the EZs and ECs experienced negative 

changes in all three indicators, but many experienced negative changes in 

at least one. For instance, the Atlanta EZ experienced negative changes in 

unemployment and both measures of economic growth. However, the 

extent of these changes varied, particularly in our two measures of 

economic growth. For those EZs that saw improvements in the number of 

jobs, the increases ranged from a low of 2.6 percent in the PhiladelphiaCamden EZ to a high of 67.8 percent in the Kentucky Highlands EZ. Of 

those EZs that saw decreases in the number of businesses, the amount 

varied from 2.7 percent in the Detroit EZ to 20.8 percent in the Atlanta EZ. 

45Our analysis of changes in economic growth only included 94 ECs, since we did not have 

data for the Miami/Dade County, Florida EC.
Page 32 GAO-06-727 Empowerment Zones and Enterprise Communities

Figure 6: Changes in Poverty, Unemployment, and Two Measures of Economic Growth Observed in Round I EZs

Note: The changes in poverty and unemployment rates are based on the difference between 1990 and 

2000 Census data, and the changes in the number of businesses and jobs are based on the difference 

between 1995 and 2004 data from a private data vendor, Claritas. All poverty and unemployment 

estimates had 95 percent confidence intervals of plus or minus 5 percentage points or less. For the 

change in the number of businesses and jobs, we did not consider a change of plus or minus one 

percent or less as being significant.

Positive change (decrease in poverty/unemployment;

increase in businesses/jobs)

No statistically significant change

Negative change (increase in poverty/unemployment;

decrease in businesses/jobs)

Rio Grande Valley 

Mid-Delta 

Kentucky Highlands

(PA: Philadelphia

portion) 

(NJ: Camden portion) 

Philadelphia, PA/ 

Camden, NJ 

(NY: Upper 

Manhattan portion) 

(NY: Bronx portion) 

New York, NY 

Los Angeles, CA 

Detroit, MI 

Cleveland, OH 

Chicago, IL 

Baltimore, MD 

Atlanta, GA 

Total businesses

Total jobs

Unemployment 

Poverty 

Positive change

(decrease in poverty

/unemployment,

increase in 

businesses/jobs)

Negative change

(increase in poverty/

unemployment,

decrease in

businesses/jobs)

Percentage change Percentage change 

Overall positive or negative change Percentage change 

Rio Grande Valley 

Mid-Delta 

Kentucky Highlands

(PA: Philadelphia portion) 

(NJ: Camden portion) 

Philadelphia, PA/Camden, NJ 

(NY: Upper Manhattan portion) 

(NY: Bronx portion) 

New York, NY 

Los Angeles, CA 

Detroit, MI 

Cleveland, OH 

Chicago, IL 

Baltimore, MD 

Atlanta, GA 

Poverty 

Unemployment 

Economic growth

Jobs

Businesses

Source: GAO analysis of Census and Claritas data. 

40 30 20 10 0 0 10 20 30 40 50 60 70
Page 33 GAO-06-727 Empowerment Zones and Enterprise Communities

Most EZs and ECs Saw 

Some Decrease in the 

Poverty Rate, but These 

Changes Could Not Be Tied 

Definitively to the EZ/EC 

Program

In most of the 11 EZs and 95 ECs, both urban and rural, poverty rates fell 

between 1990 and 2000 (fig. 7).46 Most communities experienced 

statistically significant decreases in the poverty rate that ranged from 2.6 to 

14.6 percent. Specifically, our analysis showed the following:

• Almost all urban EZs experienced significant decreases ranging from a 

low of 4.1 percentage points in the New York EZ to 10.9 percentage 

points in the Detroit EZ. 

• All three rural EZs showed significant decreases—7.3 percentage points 

in the Rio Grande Valley EZ, 10.1 percentage points in the Kentucky 

Highlands EZ, and 10.7 percentage points the Mid-Delta EZ. 

• 44 out of the 65 urban ECs also saw significant decreases in poverty, 

with declines ranging from 2.6 percentage points in the Boston, 

Massachusetts EC to 14.6 percentage points in the Minneapolis, 

Minnesota EC. 

• Most rural ECs saw significant decreases, ranging from 3.4 percentage 

points in the Imperial County, California EC to 12.2 percentage points in 

the Eastern Arkansas EC.

46Changes in poverty rate are based upon percentage point differences.
Page 34 GAO-06-727 Empowerment Zones and Enterprise Communities

Figure 7: Number and Percentage of EZs and ECs Experiencing a Decrease in 

Poverty from 1990 to 2000

Note: All poverty estimates had 95 percent confidence intervals of plus or minus 5 percentage points 

or less. 

We also compared changes in poverty in designated areas and comparison 

areas and across urban and rural communities for both EZs and ECs. Our 

analysis showed the following:

• When combining urban and rural areas, the poverty rate in the 

designated areas fell more than in the comparison areas—5.4 

percentage points overall, compared with 3.9 percentage points in the 

comparison areas (fig. 8). 

• Rural designees experienced a larger significant decrease in poverty 

than urban designees—7.2 and 5 percentage points, respectively.

10 of 11 

7 of 8

3 of 3

91 

88

100 

73

68

83

Total

Urban

Rural

EZs

69 of 95 

44 of 65 

25 of 30 

Total

Urban

Rural

ECs

Number of designees Percentage of areas

Source: GAO analysis of Census data. 

All other designees

Designees with decrease in poverty
Page 35 GAO-06-727 Empowerment Zones and Enterprise Communities

• Urban and rural EZs experienced greater decreases in poverty than both 

their comparison areas and the ECs. 

Figure 8: Comparison of Decreases in Poverty in Urban and Rural Designated Areas 

and Comparison Areas from 1990 to 2000

Note: There are 1,557 census tracts in the designated areas and 1,504 in the comparison areas. All 

poverty estimates had 95 percent confidence intervals of plus or minus 5 percentage points or less.

Because we could not separate the program’s effects from other factors in 

these analyses, we developed an econometric model for the eight urban 

EZs and their comparison areas that considered a variety of factors related

Rural designated areas

Rural comparison areas

All

Urban

Rural

Source: GAO analysis of Census data. 

All designated areas (rural and urban) 

All comparison areas

Urban designated areas

Urban comparison areas

EZ 

EC 

Percentage decrease in poverty

0 2 4 6 8 10
Page 36 GAO-06-727 Empowerment Zones and Enterprise Communities

to the poverty rate.47 Among the nonprogram factors we considered were 

high school dropouts, the presence of households headed by females, and 

vacant housing units as reported in the 1990 Census. Our models indicated 

that the poverty rate in the comparison areas fell slightly more than in the 

EZs themselves (app. II). This result did not demonstrate that the declines 

in poverty in the EZs were directly associated with the EZ program. 

Finally, we conducted interviews of EZ stakeholders and surveyed EC 

officials to determine their views of the effects of the EZ/EC program on 

their communities. Their responses were consistent with the inconclusive 

results of our other analyses: in general, they believed that both the EZ/EC 

program and additional factors had affected the prevalence of poverty in 

their communities.48 Some EZ and EC stakeholders said that the EZ/EC 

designation and program activities had addressed poverty by bringing in 

jobs and helping to stabilize the area. For instance, stakeholders from 

several EZs, including the Chicago, Mid-Delta, and Kentucky Highlands 

EZs, mentioned the role of the EZ in job creation. In addition, stakeholders 

from other EZs, such as Detroit and Rio Grande Valley, mentioned the role 

of EZ programs that were related to housing. EC survey respondents 

commented that the EC designation gave them the opportunity to focus on 

initiatives that could improve poverty in the area, such as job creation, 

infrastructure and physical improvements, and housing.

However, EZ and EC stakeholders also mentioned external factors that 

may have affected the changes in poverty, such as changes in the local 

population when original residents moved away and gentrification. In 

addition, stakeholders from three EZs mentioned the positive effects of 

changes to welfare policy during the EZ/EC program.49 In ECs where our 

data showed that the poverty rate fell, some EC survey respondents also 

47We were able to use statistical modeling techniques only for the eight Round I urban EZs, 

because the rural EZs were made up of too few census tracts to perform these analyses and 

because the ECs received such small amounts of money that we could not separate the 

program’s effects from those of other programs. In addition, we could not isolate the effects 

of the program on individual EZs because the number of census tracts in some urban EZs 

was not large enough to provide reliable results. Appendix II describes our methodology 

and the results of the econometric analysis.

48These stakeholders did not comment on the changes that occurred in our comparison 

areas. 

49The Personal Responsibility and Work Opportunity Reconciliation Act of 1996 instituted a 

change in welfare policies, establishing work requirements and time limits for receiving 

benefits. 
Page 37 GAO-06-727 Empowerment Zones and Enterprise Communities

mentioned an increase in the availability of social services as a contributing 

factor. At EZs where stakeholders had mixed opinions on the changes in 

poverty, some cited a loss of industry or shifts in the national economy. Of 

the three EC survey respondents in areas where poverty either remained 

the same or increased, respondents mentioned the decrease in the number 

of jobs, increase in housing and utility costs, and the out-migration of 

residents with middle or high incomes. 

Decreases in the 

Unemployment Rate in 

Some Communities Also 

Could Not Be Definitively 

Tied to the EZ/EC Program

As we did for the poverty rate, we analyzed changes in the unemployment 

rate in EZs and ECs, using the same quantitative and qualitative methods. 

We found an overall decline in unemployment across communities; but, 

once again we could not tie the decrease definitively to the program’s 

presence. Further, fewer than half of the individual EZs and ECs 

experienced a decrease in unemployment (fig. 9), with declines ranging 

from 1.5 to 11.7 percentage points, and a number saw significant 

increases—up to 6.5 percentage points.50 Many communities did not 

experience a significant change. Specifically, our analysis showed the 

following:

• Four of the eight urban EZs saw unemployment fall, with rates declining 

from 2.9 percentage points in the Philadelphia-Camden EZ to 10 

percentage points in the Cleveland EZ. Two of the EZs saw 

unemployment rise—2 percentage points in New York and 6 percentage 

points in Atlanta—and two did not see a statistically significant change. 

• Changes in the unemployment rates of the rural EZs were also mixed. 

For example, unemployment in the Kentucky Highlands EZ fell 2 

percentage points, but it rose 3.1 percentage points in the Mid-Delta EZ 

and did not change significantly in the Rio Grande Valley EZ.

• Twenty-seven, or fewer than half, of the 65 urban ECs saw significant 

decreases from 1.5 percentage points (San Diego, California) to 8.7 

percentage points (Flint, Michigan). Eleven saw a significant increase of 

between 2.1 percentage points (Rochester, New York) and 6.5 

percentage points (Charlotte, North Carolina), while 27 did not 

experience a significant change.

50Changes in unemployment rate are based upon percentage point differences.
Page 38 GAO-06-727 Empowerment Zones and Enterprise Communities

• Almost half of the rural ECs saw significant decreases, with declines 

ranging from 2.7 percentage points (Fayette-Haywood, Tennessee) to 

11.7 percentage points (Lake County, Michigan). The unemployment 

rate remained about the same in 12 rural ECs, but 4 showed increases of 

between 2.8 and 3.5 percentage points (Williamsburg-Lake City, South 

Carolina and Central Savannah River Area, Georgia, respectively).

Figure 9: Number and Percentage of EZs and ECs that Experienced a Decrease in 

Unemployment from 1990 to 2000

Note: All unemployment estimates had 95 percent confidence intervals of plus or minus 5 percentage 

points or less.

Our analysis also looked at changes in unemployment across urban and 

rural communities and compared changes in designated areas and 

comparison areas for both EZs and ECs. The analysis showed the following 

results:

5 of 11 

4 of 8

1 of 3

45 

50 

33

43

42 

47 

All

Urban

Rural

EZs

41 of 95 

27 of 65 

14 of 30 

All

Urban

Rural

ECs

Number of designees Percentage of areas

Source: GAO analysis of Census data. 

All other designees

Designees with decrease in unemployment
Page 39 GAO-06-727 Empowerment Zones and Enterprise Communities

• The designated areas saw a statistically significant decrease in 

unemployment of 1.4 percentage points, compared with a decrease of 

just under 1 percentage point in the comparison areas (fig. 10). 

• In general, rural designees saw unemployment fall more than urban 

designees, although these differences were not as marked as those we 

identified in our analysis of the changes in poverty. 

• Urban EZs and ECs saw a greater decrease in unemployment than their 

comparison areas, where the rates did not show a statistically 

significant change. 

• Unemployment in rural EZs and their comparison areas remained about 

the same, while rural ECs and their comparison areas both experienced 

a significant decrease of about 2 percentage points. 
Page 40 GAO-06-727 Empowerment Zones and Enterprise Communities

Figure 10: Comparison of Decreases in Unemployment in Urban and Rural 

Designated Areas and Comparison Areas from 1990 to 2000

Note: Areas for which there was no statistically significant change are not shown. There are 1,557 

census tracts in the designated areas and 1,504 in the comparison areas. All unemployment estimates 

had 95 percent confidence intervals of plus or minus 5 percentage points or less.

Although our analyses of changes again showed that EZs experienced a 

larger decrease in unemployment than the comparison areas, these 

analyses did not separate the effect of the program from other factors. We 

again used an econometric model for the eight urban EZs that considered 

other factors, such as average household income and the presence of 

individuals with a high school diploma as reported in the 1990 Census. This 

analysis showed that the EZs experienced a decrease that was slightly 

greater than in the comparison areas, but the difference was not 

statistically significant (app. II).

Source: GAO analysis of Census data. 

Percentage decrease in unemployment

Rural

Urban

All

Rural designated areas

Rural comparison areas

All designated areas (rural and urban) 

All comparison areas

Urban designated areas

EZ 

EC 

Urban designated areas

EZ 

EC 

012 3 4 5 6 7 8 9 10
Page 41 GAO-06-727 Empowerment Zones and Enterprise Communities

We also looked at the observations of EZ stakeholders that we interviewed 

and the responses to our EC survey. Once again, these observations 

generally saw both program and external factors as affecting the changes in 

unemployment.51 Some EZ stakeholders cited EZ programs—such as 

providing financial assistance to EZ businesses, fostering job creation, and 

offering job training—as helping to reduce unemployment. For example, 

the Upper Manhattan and Bronx portions of the New York EZ and the 

Chicago EZ required subgrantees and borrowers to create a certain number 

of jobs based on the size of the EZ grant or loan received. Similarly, EC 

survey respondents also mentioned the EC’s involvement in creating jobs, 

attracting new businesses, and offering loans and technical assistance to 

businesses, along with a variety of social service programs designed to 

support employment. 

EZ stakeholders and EC survey respondents also noted additional factors 

that may have been associated with changes in unemployment. For 

example, some EZs cited the availability of social services not sponsored 

by the EZ as factors that influenced unemployment—for instance, daycare, 

transportation, and adult education or job placement programs. Some EZ 

stakeholders also suggested that changes in the national economy and in 

welfare policy had helped to reduce unemployment. Many survey 

respondents in ECs where unemployment fell reported that the decreases 

could be attributed to activities that may or may not have been part of the 

EC program, including adult educational services, higher skill levels among 

area residents, and social services such as childcare, programs for the 

homeless, and substance abuse treatment. Stakeholders from EZs where 

unemployment did not change or rose explained that EZ residents faced 

barriers to employment such as a lack of education or job skills, drug 

dependency, and criminal histories. 

Our Measures Showed that 

Some Economic Growth 

Occurred, but Results from 

Our Econometric Model 

Were Not Conclusive

A number of indicators can be used to measure economic growth, 

including data on the change in the number of local businesses, sales 

volumes, or home values. Our poverty and unemployment analyses used 

specific variables available in Census data, but to measure economic 

growth, we chose two measures—the number of businesses and the

51These stakeholders did not comment on the changes that occurred in our comparison 

areas. 
Page 42 GAO-06-727 Empowerment Zones and Enterprise Communities

number of jobs.52 Overall, our analysis showed that most EZs and ECs 

experienced an increase in at least one measure of economic growth 

between 1995 and 2004 (fig. 11). Specifically:

• Two of the eight urban EZs experienced significant increases in the 

number of both businesses and jobs, and three more experienced 

significant increases in one measure. The increases in businesses ranged 

from 4.2 percent in the Philadelphia-Camden EZ to 23.6 percent in the 

New York EZ. The increases in jobs ranged from 2.6 percent in the 

Philadelphia-Camden EZ to 30.5 percent in the Detroit EZ. However, 

some urban EZs experienced decreases in the number of businesses or 

jobs, some of which were large. Five experienced decreases in the 

number of businesses, ranging from 2.7 percent in the Detroit EZ to 20.8 

percent in the Atlanta EZ, and four experienced decreases in the number 

of jobs, from 5.2 percent in the Los Angeles EZ to 22.3 percent in the 

Atlanta EZ.

• All three rural EZs experienced increases in both businesses and jobs, 

with businesses increasing between 15.6 percent in the Mid-Delta EZ 

and 33 percent in the Kentucky Highlands EZ, and jobs rising between 5 

and 67.8 percent in the same two EZs, respectively.

• Fourteen of the 64 urban ECs experienced an increase in both economic 

growth measures, and an additional 24 saw an increase in one of the 

measures.53 However, 26 urban ECs saw a decrease in both measures.

• Like rural EZs, the majority of the rural ECs experienced an increase in 

both measures of economic growth. 

52We obtained these data for 1995, 1999, and 2004 from a private data vendor, Claritas. 

Changes in the number of businesses and number of jobs are based upon percent changes.

53Data were not available for the Miami/Dade County, Florida EC.
Page 43 GAO-06-727 Empowerment Zones and Enterprise Communities

Figure 11: Number and Percentage of EZs and ECs That Experienced an Increase in One or Both Measures of Economic Growth 

between 1995 and 2004

Note: We excluded establishments that were not eligible for program tax benefits, such as nonprofit 

and governmental organizations, from our analysis of the change in the number of businesses. 

However, we included jobs at those businesses in our analysis of the change in the number of jobs.

a

Data were not available for the Miami/Dade County, Florida EC. 

Like the analyses of poverty and unemployment, our analysis of the 

changes in economic growth compared urban and rural designees, 

designated and comparison areas, and EZs and ECs (fig. 12).

• In aggregate, both designated and comparison areas saw little change in 

the number of businesses, and both experienced an increase in the 

number of jobs of about 7 percent. 

5 of 11 

2 of 8

3 of 3

45 

25 

100 

39 

22 

77 

All

Urban

Rural

37 of 94 

14 of 64 

23 of 30 

3 of 11 

3 of 8

0 of 3

27of 94 

24 of 64 

3 of 30 

All

Urban

Rural

Number of designees Number of designees

Both measures–number of businesses and jobs Only one measure–number of businesses or jobs

Percentage 

of designees

Percentage 

of designees

Source: GAO analysis of Claritas data. 

All other designees

Designees with increase

27 

38

0

29 

38

10 

EZs

ECs

a

a

a

a
Page 44 GAO-06-727 Empowerment Zones and Enterprise Communities

• Overall, urban designees saw a decrease in the number of businesses, 

while rural designees saw a substantial increase. Both urban and rural 

designees saw an increase in the number of jobs, but the aggregate 

increase in rural areas was much greater (23.6 percent) than in urban 

areas (5.7 percent). Urban and rural comparison areas generally 

experienced changes similar to the designated areas.

• Urban EZs experienced a decrease in the number of businesses, while 

the number in comparison areas remained about the same. But urban 

EZs saw an increase in the number of jobs, while their comparison areas 

saw a decrease. 

• Rural EZs fared better than their comparison areas in both measures of 

economic growth. 
Page 45 GAO-06-727 Empowerment Zones and Enterprise Communities

Figure 12: Comparison of Changes in the Number of Businesses and the Number of 

Jobs in Urban and Rural Designated Areas and Comparison Areas between 1995 and 

2004

Percentage change in number of businesses

Businesses

Percentage change in number of jobs

Jobs

Rural designated areas

Rural comparison areas

All designated areas (rural and urban) 

All comparison areas

Urban designated areas

Urban comparison areas

EZ 

Rural designated areas

Rural comparison areas

All designated areas (rural and urban) 

All comparison areas

Urban designated areas

Urban comparison areas

EZ 

EC 

Source: GAO analysis of Claritas data. 

Rural

Urban

All

Rural

Urban

All

-5 0 5 10 15 20 25 30

-5 0 5 10 15 20 25 30
Page 46 GAO-06-727 Empowerment Zones and Enterprise Communities

Note: There are 1,557 census tracts in the designated areas and 1,504 in the comparison areas. We 

excluded establishments that were not eligible for program tax benefits, such as nonprofit and 

governmental organizations, from our analysis of the change in the number of businesses. However, 

we included jobs at those businesses in our analysis of the change in the number of jobs. These 

analyses do not include data for the Miami/Dade County, Florida EC. 

As explained earlier, our descriptive analyses could not isolate the effects 

of the EZ/EC program from other factors affecting the designated and 

comparison areas. We conducted an econometric analysis that 

incorporated other factors, such as the percentage of vacant housing units 

and population density as reported in the 1990 Census. However, the 

results of our models explained little of the relative changes in the number 

of businesses or jobs in the urban EZs with respect to their comparison 

areas (app. II). Because our proxy measures—the number of businesses 

and jobs—were not the only indicators representative of economic growth, 

we tested our models using different measures, such as the number of 

home mortgage originations, but found similar results. As a result, we 

could not determine with a reasonable degree of confidence the role that 

the EZs might have played in the changes in economic growth that we 

observed. 

We also reviewed the perceptions of EZ stakeholders interviewed and 

respondents to our survey of ECs on economic growth in their 

communities.54 These observations cited several aspects of the program 

that contributed to economic growth, including loan programs and other 

benefits that aided small businesses, infrastructure improvements, and tax 

benefits, especially when the tax benefits were combined with other 

federal, state, and local benefits. Additionally, several stakeholders 

mentioned that their EZ or EC had acted as a catalyst for other local 

development. EZ stakeholders also noted several external factors that 

affected the change in economic growth, such as the increase of jobs in 

businesses located within the EZ or EC, the role of other state and local 

initiatives in attracting businesses, and trends in the national economy. In 

ECs where our data showed an increase in the number of businesses or 

jobs, some survey respondents reported that the result was due to an 

increase in technical assistance for area businesses, such as 

entrepreneurial training programs, and others reported that financial 

assistance to businesses contributed to the growth, both of which may or 

may not have been EC programs. EZ stakeholders also mentioned 

challenges facing their communities, including the lack of infrastructure 

54These stakeholders did not comment on the changes that occurred in our comparison 

areas. 
Page 47 GAO-06-727 Empowerment Zones and Enterprise Communities

and residents with incomes that were not high enough to support local 

businesses. In ECs where our data showed a decrease in the number of 

businesses or jobs, survey respondents pointed to a decrease in the number 

of area businesses and downsizing of existing businesses as contributing 

factors.

Additional Program Data 

Could Facilitate Evaluations 

of the Effects of the EZ/EC 

and Similar Programs 

Our efforts to analyze the effects of Round I designation on poverty, 

unemployment, and economic growth were limited by the absence of data 

on the use of program grant funds, the amount of funds leveraged, and the 

use of tax benefits. Without these data, we could not account for the 

amount of funds EZs used to carry out specific activities, the extent to 

which they leveraged other resources, or how extensively businesses used 

the tax benefits. As a result, we could not assess differences in program 

implementation. In addition, as we reported in 2004, we could not evaluate 

the effectiveness of the tax benefits, although later rounds of the EZ/EC 

program have relied heavily on them.55

While we recognize, and discussed in our prior report on the EZ/EC 

program, the difficulties inherent in evaluating economic development 

programs, having more specific data would facilitate evaluations of this 

and similar programs.56 For example, the precision of our econometric 

models might have been improved by combining data on how program 

funds were used—such as the amounts used for assisting businesses—and 

the use of program tax benefits with other data we obtained, such as data 

on businesses and area jobs. Also, additional data would have allowed us to 

do in-depth evaluations of the extent to which various tax benefits were 

being used within each community, the size and type of businesses utilizing 

them, and the potential competitive advantages of using these benefits. Our 

previous reports have recommended that information on outlay programs 

and tax expenditures be collected to evaluate the most effective methods 

for accomplishing federal objectives.57

55GAO-04-306.

56GAO-04-306.

57GAO-05-690 and GAO/GGD/AIMD-94-122.
Page 48 GAO-06-727 Empowerment Zones and Enterprise Communities

Observations The EZ/EC program, one of the most recent large-scale federal programs 

aimed at revitalizing distressed urban and rural communities, resulted in a 

variety of activities intended to improve social and economic conditions in 

the nation’s high-poverty communities. As of March 31, 2006, all but 15 

percent of the $1 billion in program grant funds provided to Round I 

communities had been expended, and the program was reaching its end. All 

three rounds of the EZ/EC program are scheduled to end no later than 

December 31, 2009. However, given our findings from this evaluation of 

Round I EZs and ECs, the following observations should be considered if 

these or similar programs are authorized in the future. 

Based on our review, we found that oversight for Round I of the program 

was limited because the three agencies—HHS, HUD, and USDA—did not 

collect data on how program funds were used, and HHS did not provide 

state and local entities with guidance sufficient to ensure monitoring of the 

program. These limitations may be related in part to the design of the 

program, which offered increased flexibility in the use of funds and relied 

on multiple agencies for oversight. However, limited data and variation in 

monitoring hindered federal oversight efforts. 

In addition, the lack of data on the use of program grant funds, the extent 

of leveraging, and extent to which program tax benefits were used also 

limited our ability and the ability of others to evaluate the effects of the 

program. The lack of data on the use of tax benefits is of particular 

concern, since the estimated amount of the tax benefits was far greater 

than the amount of grant funds dedicated to the program. In response to 

the recommendation in our 2004 report, HUD, IRS, and USDA discussed 

options for collecting additional data on program tax benefits and 

determined two methods for collecting the information—through a 

national survey or the modification of tax forms. The three agencies, 

however, did not reach agreement on a cost-effective method for collecting 

the additional data. In our and others’ prior attempts to obtain this 

information using surveys, survey response rates were low and thus did not 

produce reliable information on the use of program tax benefits. 

We acknowledge that the collection of additional tax data by IRS would 

introduce additional costs to both IRS and taxpayers. Nonetheless, a lack 

of data on tax benefits is significant given that subsequent rounds of the 

EZ/EC program and the Renewal Community program rely almost 

exclusively on tax benefits, and other federal economic development 

programs, such as the recent Gulf Opportunity Zone initiative, involve 
Page 49 GAO-06-727 Empowerment Zones and Enterprise Communities

substantial amounts of tax benefits. Furthermore, the nation’s current and 

projected fiscal imbalance serves to reinforce the importance of 

understanding the benefits of such tax expenditures. If Congress 

authorizes similar programs that rely heavily on tax benefits in the future, it 

would be prudent for federal agencies responsible for administering the 

program to collect information necessary for determining whether the tax 

benefits are effective in achieving program goals.

Agency Comments and 

Our Evaluation

We provided a draft of this report for review and comment to HHS, HUD, 

IRS, and USDA. We received comments from HHS, HUD, and USDA. In 

general, the agencies provided comments related to the oversight of the 

program, the availability of data, and the methodology used to carry out the 

work. Their written comments appear in appendixes V through VII, 

respectively, and our responses to HUD’s more detailed comments also 

appear in appendix VI. HHS, HUD, and USDA also provided technical 

comments, which we have incorporated into the report where appropriate.

HHS commented that a statement made in our report—that the agency did 

not provide guidance detailing the steps state and local authorities should 

take to monitor the program—unfairly represented the relationship 

between HHS and the other federal agencies that administered the EZ/EC 

program. Specifically, HHS emphasized its responsibility for fiscal as 

opposed to programmatic oversight of the program. We note in our report 

that program design may have led to a lack of clarity in oversight, as no 

single federal agency had sole oversight responsibility. While this lack of 

clarity in oversight may be related in part to the design of the program, 

which offered increased flexibility in the use of funds and relied on 

multiple agencies for oversight, limited data and variation in monitoring 

hindered federal oversight efforts. Moreover, we believe that, in 

accordance with federal standards, each of the federal agencies that 

administered the program bore at least some responsibility for ensuring 

that public resources were being used effectively and that program goals 

were being met. 

HUD disagreed with GAO’s observation that there was a lack of data on the 

use of program grant funds, the amount of funds leveraged, and the use of 

the tax benefits. HUD indicated that we could obtain data on the use of 

program funds and the amount of funds leveraged from its performance 

reporting system. As we discussed in our report, we used information from 

HUD’s reporting system to report on the types of activities that designated 

communities implemented. We also noted that HUD maintained some 
Page 50 GAO-06-727 Empowerment Zones and Enterprise Communities

information on the amount of EZ/EC grants budgeted for specific activities. 

Although we found evidence that activities were carried out with program 

funds, information contained in the performance reporting system on the 

amounts of funds used and the amount leveraged was not reliable. For 

example, we found evidence that communities had undertaken certain 

activities with program funding, but we were often unable to find 

documentation of the actual amounts allocated or expended. HUD also 

indicated that it did not agree that data on the use of the tax benefits were 

lacking. However, HUD indicated that the agency itself had attempted to 

gather such data by collaborating with IRS in identifying ways to collect 

data on tax benefits, by developing a methodology to administer a survey to 

businesses, and by compiling anecdotal evidence of the use of program tax 

benefits. We continue to believe that the lack of data on program tax 

benefits limits the ability of the agencies to administer and evaluate the 

EZ/EC program. Further, the lack of such data is likely to become 

increasingly problematic in light of the fact that future rounds of the EZ/EC 

program and the Renewal Community program rely heavily on tax benefits 

to achieve revitalization goals.

HUD concurred that limitations in the oversight of the EZ/EC program may 

have resulted from the design of the program as no single federal agency 

had sole responsibility for oversight. HUD also recommended that we 

make clear that more oversight was not allowed in Round I and we include 

a statement that it met agency requirements to undertake periodic 

performance reviews and described some of its efforts to monitor the 

program according to applicable regulations. We do not believe that more 

oversight was not allowed. For example, early in the program HUD and 

HHS made some efforts to share information. Specifically, HUD officials 

said that they had received fiscal data from HHS and reconciled that 

information with their program data on the activities implemented, but 

these efforts to share information were not maintained. Further, as we 

previously stated, while we recognize that program design may have led to 

a lack of clarity in oversight, we believe that in accordance with federal 

standards, each of the federal agencies that administered the program bore 

at least some responsibility for ensuring that public resources were being 

used effectively and that program goals were being met. HUD also 

described changes it had made to ensure better oversight of program funds 

for Round II. We acknowledge HUD’s efforts to improve oversight of the 

program and, as discussed in our report, the oversight limitations that we 

identified in Round I of the program may not apply to later rounds. 
Page 51 GAO-06-727 Empowerment Zones and Enterprise Communities

HUD provided several comments related to the methodology we used to 

carry out our work. For example, HUD suggested that we measure the 

successes of the Round I program in meeting the four key principles of the 

program, which the designated communities were required to include in 

their strategic plans. Additionally, HUD commented that the indices we 

used to assess the effects of the EZ/EC program—poverty, unemployment 

and economic growth—were used in the application process for the 

program but were not intended to be used as performance measures. While 

we appreciate HUD’s suggestions on our methodology, our congressional 

mandate was to determine the effect of the EZ/EC program on poverty, 

unemployment and economic growth. In designing our methodology, we 

conducted extensive research on evaluations that had been conducted on 

the EZ/EC program, including HUD’s 2001 Interim Assessment, and spoke 

with several experts in the urban studies field. 

USDA stated that data and analyses on the effectiveness of programs such 

as EZ/EC were useful and offered areas to consider for future evaluations 

of economic development programs involving rural areas. For example, 

USDA mentioned issues involved in collecting data on rural areas, such as 

the limited availability of economic and demographic data for small rural 

populations, and discussed USDA’s efforts for developing a methodology 

that focuses on economic impacts using county-level economic data. USDA 

also said it is especially important in rural areas to have a clear and 

adequately funded data collection process for program evaluations. In 

addition, USDA noted that evaluations of the EZ/EC program could go 

beyond the indicators of poverty, unemployment and economic growth to 

include measures on economic development capacity and collaboration. 

We agree that collecting data for rural areas is a challenge and appreciate 

USDA’s effort to develop a methodology that focuses on economic impacts 

using county-level economic data and captures the short-term Gross 

Domestic Product changes in the impacted rural counties. Further, we 

appreciate USDA’s suggestion that additional measures be considered in 

future evaluations of economic development programs and that a broader 

perspective on program results might be useful. 

USDA also commented that its performance reporting system was intended 

to be used as a management tool for both USDA and the individual EZs and 

ECs. According to USDA, the system was not designed to be an accounting 

tool but has been useful for providing a picture of each designated 

community’s achievements. As we discussed in our report, we used 

information from USDA’s reporting system to report on the types of 

activities that designated communities implemented and also noted that 
Page 52 GAO-06-727 Empowerment Zones and Enterprise Communities

USDA maintained some information on the amounts of EZ/EC grants 

budgeted for specific activities. Moreover, while we recognize the system 

was not intended to be used as an accounting tool, we found that the data 

on the amounts of the EZ/EC grant funding were not reliable. For example, 

in our assessment of the reliability of data contained in USDA’s 

performance reporting system, we were often unable to find 

documentation of the actual amounts allocated or expended for specific 

activities. 

USDA further commented that it had encouraged designated communities 

to report all investment that contributed to the EZ or EC in accomplishing 

its strategic plan as leveraged funds. We recognize USDA’s efforts to 

encourage leveraging in the designated communities and to report such 

information in its performance reporting system. Our report notes that 

stakeholders from all EZs and ECs we visited and EC survey respondents 

reported having used their EZ/EC grants to leverage other resources. 

However, we were unable to evaluate the amounts of funds leveraged 

because the data contained in USDA’s performance reporting system were 

not reliable. For example, USDA’s performance reporting system included 

information on the amounts of funds leveraged for each activity, but for the 

sample of activities we reviewed, either supporting documentation showed 

an amount conflicting with the reported amount or documentation could 

not be found. Moreover, as we discuss in our report, the definition of 

leveraging used among the designated communities was inconsistent.

We are sending copies of this report to interested Members of Congress, 

the Secretary of Health and Human Services, the Secretary of Housing and 

Urban Development, the Secretary of Treasury, the Commissioner of the 

Internal Revenue Service, and the Secretary of Agriculture. We will make 

copies of this report available to others upon request. In addition, this 

report will be available at no charge on the GAO Web site at 

http://www.gao.gov. 
Page 53 GAO-06-727 Empowerment Zones and Enterprise Communities

Please contact me at (202) 512-8678 or ShearW@gao.gov if you or your staff 

have any questions about this report. Contact points for our Offices of 

Congressional Relations and Public Affairs may be found on the last page 

of this report. Key contributors to this report are listed in appendix VIII.

William B. Shear

Director, Financial Markets and 

 Community Investment 
Page 54 GAO-06-727 Empowerment Zones and Enterprise Communities

Appendix I

Objectives, Scope, and Methodology AAppenednxidexiIs

The objectives of this study were to (1) describe how Round I of the 

Empowerment Zone and Enterprise Community (EZ/EC) program was 

implemented by the designated communities; (2) evaluate the extent of 

federal, state, and local oversight of the program; (3) examine the extent to 

which data are available to assess the use of program tax benefits; and 

(4) analyze the effects the Round I EZs and ECs had on poverty, 

unemployment, and economic growth in their communities. To address 

each of our objectives, we completed site visits to all Round I EZs and two 

Round I ECs and administered a survey to all ECs that did not receive 

subsequent designations, such as a Round II EZ designation. At each site, 

we asked uniform questions on implementation, oversight, tax benefits, 

and changes observed in the EZ and ECs. We also surveyed 60 ECs that 

were in operation as of June 2005 and did not receive later designations and 

asked about similar topics. We performed a qualitative analysis to identify 

common themes from our interview data and open-ended survey 

responses. To address our second objective, we also interviewed federal 

and state program participants, reviewed oversight guidance and 

documentation, and verified a sample of reported performance data by 

tracing it to EZ and EC records. To address our third objective, we 

attempted to administer a survey of EZ businesses, but discontinued it due 

to a low response rate. To address our fourth objective, we obtained 

demographic and socioeconomic data from the 1990 and 2000 decennial 

censuses and business data for 1995, 1999, and 2004 from a private data 

vendor, Claritas. We used 1990 Census data to select areas similar to the EZ 

and EC areas for purposes of comparison. We then calculated the percent 

changes in poverty, unemployment, and economic growth observed in the 

EZs and ECs and their comparison areas. In addition, for the eight urban 

EZs, we used an econometric model to estimate the effect of the program, 

by controlling for certain factors, such as average household income, in the 

EZs and their comparison areas. Finally, we used information gathered 

from our qualitative analysis to provide context for the changes observed in 

the EZs and ECs. 
Appendix I

Objectives, Scope, and Methodology

Page 55 GAO-06-727 Empowerment Zones and Enterprise Communities

Methodology for Site 

Visits

To answer our objectives, we completed site visits to all 11 EZs and 2 of the 

95 ECs, one urban and one rural.1

 These EZs and ECs were located in:

• Atlanta, Georgia (EZ)

• Baltimore, Maryland (EZ)

• Chicago, Illinois (EZ)

• Cleveland, Ohio (EZ)

• Detroit, Michigan (EZ)

• Los Angeles, California (EZ)

• New York, New York (EZ)

• Philadelphia, Pennsylvania and Camden, New Jersey (EZ)

• rural Kentucky (Kentucky Highlands EZ)

• rural Mississippi (Mid-Delta EZ)

• rural Texas (Rio Grande Valley EZ)

• Providence, Rhode Island (EC)

• rural Tennessee (Fayette-Haywood EC)

We interviewed stakeholders from each site on the implementation, 

governance, oversight, and tax benefits of the EZ or EC and asked about 

the changes the stakeholders had observed in their communities. Using a 

standardized interview guide, we interviewed some combination of the 

following program stakeholders at each location: EZ/EC officials, board 

members (including some EZ/EC residents), representatives of subgrantee 

1

Of the 61 ECs that had not received additional designations, we selected a judgmental 

sample of 8 ECs, 4 urban and 4 rural, that represented geographic diversity and also factored 

in each EC’s combined poverty and unemployment rates in 1990. From this sample, we 

chose two ECs to visit—Providence, Rhode Island (urban) and Fayette-Haywood, 

Tennessee (rural)—that were similar in terms of their poverty and unemployment rates.
Appendix I

Objectives, Scope, and Methodology

Page 56 GAO-06-727 Empowerment Zones and Enterprise Communities

organizations, and Chamber of Commerce representatives or individuals 

able to provide the perspective of the business community (table 4).2

 We 

identified participants to interview at each site by soliciting opinions from 

EZ/EC officials and the current board chair. For each site, we reviewed 

strategic plans, organizational charts, and documentation on oversight 

procedures. In addition, we toured the EZ/EC to see some of activities 

implemented. 

2

In the New York and Philadelphia-Camden EZs, we implemented two separate site visit 

protocols, due to the split governance structures in those locations.
Appendix I

Objectives, Scope, and Methodology

Page 57 GAO-06-727 Empowerment Zones and Enterprise Communities

Table 4: Number of Stakeholders Interviewed for EZ and EC Site Visits, by Type

Source: GAO.

a

Includes local governmental officials, business owners, active community members, and other 

representatives.

b

Includes directors of subzones.

Methodology for 

Survey of EC Officials

To gather similar information from the ECs, we administered an e-mail 

survey to officials from the 60 Round I ECs that were still in operation as of 

June 2005 and did not receive a subsequent designation. We chose to 

exclude the 34 ECs that received subsequent designations, because we did 

not want their responses to be influenced by those programs. A version of 

the survey showing aggregated responses can be viewed at

www.gao.gov/cgi-bin/getrpt?GAO-06-734SP.

EZ/EC

EZ/EC 

officials

Board 

members

Representatives 

from subgrantee 

organizations

Representatives 

from the Chamber 

of Commerce or 

other business 

perspective

Officials from 

the state passthrough 

entities

Other 

representatives a

Urban

Atlanta EZ 2 2 6 2 4 10

Baltimore EZ 6 4 3 2 1 5

Chicago EZ 6 4 4 1 3 2

Cleveland EZ 5 4 3 0 4 8

Detroit EZ 7 4 3 1 2 9

Los Angeles EZ 1 2 2 0 0 12

New York EZ

Upper Manhattan 

portion 3 3 2 1 2 2

Bronx portion 2 4 3 1 2 1

Philadelphia/Camden EZ

Philadelphia portion 5 2 2 0 8 3

Camden portion 1 3 2 1 2 2

Providence EC 2 3 3 0 2 1

Rural

Kentucky Highlands EZ 4 6b 1 1 4 4

Mid-Delta Mississippi EZ 4 1 4 2 2 2

Rio Grande Valley EZ 4 3 3 1 3 1

Fayette Haywood EC 1 2 2 0 4 4
Appendix I

Objectives, Scope, and Methodology

Page 58 GAO-06-727 Empowerment Zones and Enterprise Communities

We developed survey questions from existing program literature and 

interview data collected from Department of Housing and Urban 

Development (HUD) and U.S. Department of Agriculture (USDA) 

headquarters officials as well as our site visits to Round I EZs and ECs. The 

questionnaire items covered the implementation of the program, the types 

of governance structures used, usage of the program tax-exempt bond, and 

stakeholders’ views of factors that influenced the changes they observed in 

poverty, unemployment, and economic growth in their ECs. We created two 

versions of the questionnaire, one for urban ECs and another for rural ECs, 

in order to tailor items to urban or rural sites. Department of Health and 

Human Services (HHS), HUD, and USDA officials reviewed the survey for 

content, and we conducted pretests at four urban and two rural ECs.3

 Since 

the survey was administered by e-mail, a usability pretest was conducted at 

one urban EC (Akron, Ohio) to observe the respondent answering the 

questionnaire as it would appear when opened and displayed on their 

computer screen. 

In administering the survey, we took the following steps to increase the 

response rate. To identify survey participants, we obtained contact 

information for the Round I ECs that did not receive a subsequent 

designation from HUD and USDA in April 2005.4

 We then sent a notification 

e-mail to inform the ECs of the survey, to identify the correct point of 

contact, and to ensure the e-mail account was active. Those who did not 

respond to the first e-mail received follow up e-mails and telephone calls. 

The questionnaire was e-mailed on August 25, 2005 to 27 rural ECs and 33 

urban ECs, and participants were given the option to respond via e-mail, 

fax, or post mail. Between September and December 2005, multiple follow 

up e-mails and calls were made to increase the response rate. When the 

survey closed on December 20, 2005, all of the rural ECs and 31 of the 33 

urban ECs had completed it. The overall response rate was high at 97 

percent, with the response rates for the rural ECs at 100 percent and urban 

ECs at 94 percent. We did not attempt to verify the respondents’ answers 

against an independent source of information. However, we used two 

techniques to verify the reliability of questionnaire items. First, we used in3

The four urban pretests were conducted in the Akron, Ohio EC; Bridgeport, Connecticut 

EC; Providence, Rhode Island EC; and the Albuquerque, New Mexico EC. The two rural 

pretests occurred in the Central Appalachia EC located in West Virginia and the 

Williamsburg/Lake City EC in South Carolina. 

4

There were 61 ECs that did not receive subsequent designations, but we excluded 1 urban 

EC from our sample because it was no longer in operation as of June 2005.
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Page 59 GAO-06-727 Empowerment Zones and Enterprise Communities

depth interviewing techniques to evaluate the answers of pretest 

participants, and interviewers judged that all the respondents’ answers to 

the questions were based on reliable information. Second, for the items 

that asked about changes to poverty, unemployment, and economic growth 

in the EC, we asked respondents to provide a source of data for their 

response. Responses to those questions that did not include a data source 

were excluded from our analysis of those items.

The practical difficulties of conducting any survey may introduce certain 

types of errors, commonly referred to as nonsampling errors. For example, 

differences in how a particular question is interpreted, the sources of 

information available to respondents, or the types of people who do not 

respond can introduce unwanted variability into the survey results. We 

sought to minimize these errors by taking the following steps: conducting 

pretests, making follow-up contacts with participants to increase response 

rates, performing statistical analyses to identify logical inconsistencies, and 

having a second independent analyst review the statistical analyses. 

Returned surveys were reviewed for consistency before the data were 

entered into an electronic database. All keypunched or inputted data were 

100-percent verified—that is, the data were electronically entered twice. 

Further, a random sample of the surveys was verified for completeness and 

accuracy. We used statistical software to analyze responses to close-ended 

questions and performed a qualitative analysis on open-ended questions to 

identify common themes. 

Methodology for 

Qualitative Analysis of 

Site Visit and EC 

Survey Data

To summarize the information collected at our site visits, we conducted a 

qualitative analysis of interview data. The goal of the analysis was to create 

a summary that would produce an overall “story” or brief description of the 

program as implemented in each site. In this process, we reviewed data 

from over 200 interviews to identify information pertaining to the following 

six broad topics: 

• strategic planning and census tract selection;

• goals, implemented activities, leveraging activities, and sustainability; 

• governance structure and process;

• program oversight;

• perceptions of the use of tax benefits; and 
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Page 60 GAO-06-727 Empowerment Zones and Enterprise Communities

• perceptions of poverty, unemployment, economic growth, and other 

changes within the zone. 

Based on initial reviews of the interview data, we produced general 

outlines for each topic. For example, a description of the governance 

structure and process included identifying the type of governance structure 

used, roles within the structure, opportunities for community involvement, 

the process for decision making, and successes and challenges related to 

governance. One reviewer was assigned to each of the six topics for an 

individual site. The reviewer examined all interviews completed at an 

individual site and created a topical summary based on interview data. 

Each summary was verified by (1) presenting the summaries to the group 

of six interview reviewers to ensure accuracy, clarity, and completeness 

and (2) having a second reviewer trace the summaries back to source 

documents.

We also performed a qualitative analysis of the open-ended responses in the 

EC survey to determine reasons why the tax-exempt bond was not more 

widely used; why poverty, unemployment, and economic growth may have 

remained the same over the designation; and what role the EC played in 

changes in poverty, unemployment and economic growth, as well as 

obtaining general comments about the program. Responses to these 

questions were first reviewed by an analyst to identify common categories 

within the responses and then independently verified by a second analyst.

Methodology for 

Review of Program 

Oversight 

We interviewed and obtained documentation from federal, state, and local 

program participants regarding program oversight. We interviewed officials 

from the federal agencies involved with the program and obtained and 

analyzed fiscal and program data from the agencies. In addition, since the 

states were the pass-through entities for grant funds provided to the EZs 

and ECs—that is, they distributed federal funding to the communities—we 

conducted telephone interviews with state officials and obtained relevant 

documents in the 13 states containing EZs and ECs we visited. Finally, we 

interviewed EZ and EC officials on their oversight of subgrantees as well as 

the oversight they received from federal and state entities. We did not 

perform financial audits of the EZs and ECs.

To determine the reliability of data in HUD and USDA Internet-based 

performance reporting systems, we randomly selected activities at each EZ 

and EC we visited and conducted a file review to determine the accuracy of
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Page 61 GAO-06-727 Empowerment Zones and Enterprise Communities

the data.5 In the files, we searched related documentation for the amounts 

reported in the system for certain categories, including EZ/EC grant 

funding, leveraged funds, and program outputs. We also determined 

whether, at a minimum, documentation existed to support that the activity 

was implemented. We then assigned each item we verified a code (table 5). 

Finally, we averaged the information for each site by category and 

calculated the average score for each urban and rural community.

Table 5: Coding of Data Reliability of HUD and USDA Performance Systems

Source: GAO.

We found sufficient documentation that most EZ/EC activities contained in 

the Internet-based reporting systems had occurred, with average codes of 

2.0 for urban areas and 1.9 for rural areas.6

 We found that data on EZ/EC 

grant funding, leveraged funds, and program outputs were not sufficiently 

reliable for our purposes because only weak or no documentation could be 

found at most sites. 

Methodology for 

Survey of EZ 

Businesses 

To assess the use of program tax benefits, we attempted to administer a 

survey to EZ businesses; however, we discontinued the survey due to a very 

low response rate. Based on past post-mailed and phone-administered 

surveys of EZ businesses, we knew that this would be a challenging 

population to survey. In fact, surveys we and Abt Associates conducted in

5

We selected the lesser of 10 activities or half of an EZ’s or EC’s activities using a systematic 

random sample. We use the term “activity” to describe the units of information reported in 

the HUD and USDA systems, called “implementation plans” in HUD’s system and 

“benchmarks” in USDA’s system.

Code Description

2 Items with strong documentation, meaning that exact documentation existed or 

could be easily inferred with the provided documentation.

1 Items with weak documentation, meaning that some evidence existed, but 

numbers did not match.

0 Items for which no documentation existed.

6

We excluded the Cleveland and Los Angeles EZs from our discussion, because they did not 

receive EZ/EC grant funds. 
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Page 62 GAO-06-727 Empowerment Zones and Enterprise Communities

1998 obtained response rates of only 42 and 35 percent, respectively.7 In 

addition, both surveys had a relatively high number of undeliverable 

surveys. In anticipation of these issues, we attempted to administer a 

concise, high-level survey via mail to a stratified random sample (n=517) of 

EZ businesses.8

 We implemented a sampling procedure using the 2004 

Claritas Business Facts dataset that stratified businesses located in the EZ 

by three strata: urban small businesses (less than 50 employees), urban 

large businesses (50 or more employees), and rural businesses. The survey 

was targeted to private businesses rather than public and nonprofit 

businesses, since these for-profit businesses were the ones eligible for the 

tax benefits.9

 Public and nonprofit businesses were excluded from the 

sample by the primary industry code identifier included in the Claritas data. 

A few of these types of businesses that were not initially excluded based on 

their industry code were later removed from the sample because the 

respondents said that they were not eligible for the tax benefits.

We developed our survey after reviewing surveys used in previous studies, 

interviewing business owners, and conducting pretests with EZ businesses. 

The questionnaire was brief—containing 21 closed-ended items and 1 

optional open-ended item—and took most pretest respondents 

approximately five minutes to complete. When we conducted pretests with 

10 businesses from Baltimore, Philadelphia, and rural Kentucky, all pretest 

participants found the survey to be easy to complete and said that it did not 

ask for sensitive information. These business owners, however, often 

lacked complete information about their company’s tax filings and were 

not always able to answer all of the survey questions. Several indicated that 

they would be unlikely to complete the survey because the topic was not 

relevant to them. 

We administered the survey according to standard survey data collection 

practices. We sent a letter notifying the 517 businesses of our survey about 

a week prior to the survey mailing, mailed a copy of the survey, and 

followed that mailing with a reminder postcard. We received a total of 63 

7

GAO/RCED-99-253 and Hebert and others, Interim Assessment.

8

Businesses in the Atlanta EZ were excluded from the analysis, since the same area received 

a Renewal Community designation in 2002 and we did not want businesses to confuse the 

different tax benefits available for each designation.

9

We also excluded private businesses that were not eligible for the tax benefits, such as 

gambling establishments and liquor stores.
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Page 63 GAO-06-727 Empowerment Zones and Enterprise Communities

responses after our initial mailing, a response rate of 12 percent. Our 

mailings to 104 businesses (20 percent) could not be delivered and were 

returned because of incorrect addresses or contact information. 

Methodology for 

Assessing the Effect of 

the Program on 

Poverty, 

Unemployment, and 

Economic Growth

To determine the effect of the EZ/EC program on changes in poverty, 

unemployment, and economic growth, we used a variety of quantitative 

methods that examined changes in the designated program areas and areas 

we identified as comparison areas. In addition, we incorporated interview 

data in our qualitative analysis to provide context for the changes 

observed. We calculated percent changes of demographic, socioeconomic, 

and business data between two points in time for the all Round I EZs and 

ECs.10 However, we used only urban EZs in our econometric analysis 

because of data limitations in rural areas and the amount of funds awarded 

to ECs. 

Description of Data Sources To assess the changes in poverty and unemployment, we used census tractlevel data on poverty rates and unemployment rates from the 1990 and 2000 

decennial censuses. To determine changes in economic growth in EZ and 

ECs, we defined economic growth in terms of the number of private 

businesses created and the total number of jobs in the areas.11 We obtained 

year-end data on these variables for years 1995, 1999, and 2004 from the 

Business-Facts Database maintained by Claritas, a private data processing 

company. We explored several public and private data sources that 

contained the number of businesses and jobs at the census tract level and 

selected Claritas because it (1) maintained archival data, (2) provided data 

with a high level of reliability at the census tract level, and (3) used 

techniques to ensure the representation of small businesses. We also 

explored a variety of other data options to enhance our analysis, but were 

ultimately not able to use them. For example, we tried to acquire data 

10The points in time for Census data were 1990 and 2000 and for the business data were 1995 

and 2004. 

11We determined this definition based on research done on the EZ program and similar 

programs, such as the state Enterprise Zone initiative. Similar to the EZ program, state 

Enterprise Zones are state run programs that offer certain tax benefits within an established 

area. We excluded establishments that were not eligible for program tax benefits, such as 

nonprofit and governmental organizations, from our analysis of the change in the number of 

businesses. However, we included jobs at those businesses in our analysis of the change in 

the number of jobs.
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Objectives, Scope, and Methodology

Page 64 GAO-06-727 Empowerment Zones and Enterprise Communities

throughout the period of the program, such as state unemployment data, 

local building permit and crime data, and data on students receiving free or 

reduced lunches. However, we were not able to use these data because 

they were not captured consistently across sites, not available at the 

census tract level, or not sufficiently reliable for our purposes.

The decennial census data used are from the census long form that is 

administered to a sample of respondents. Because census data used in this 

analysis are estimated based on a probability sample, each estimate is 

based on just one of a large number of samples that could have been 

drawn. Since each sample could have produced different estimates, we 

express our confidence in the precision of our particular sample’s results as 

a 95 percent confidence interval. For example, the estimated percent 

change in the poverty rate of EZs is a decrease of 6.1 percent, and the 95 

percent confidence interval for this estimate ranges from 4.9 to 7.2 percent. 

This is the interval that would contain the actual population value for 95 

percent of the samples that could have been drawn. As a result, we are 95 

percent confident that each of the confidence intervals in this report will 

include the true values in the study population. All Census variables based 

on percentages, such as poverty rate and unemployment rate, have 95 

percent confidence intervals of plus or minus 5 percentage points or less. 

The confidence intervals for average household income and average owneroccupied housing value are shown in table 6. 

Table 6: Confidence Intervals for Average Household Income and Average Housing Value in Constant 2004 Dollarsa 

95 percent confidence interval 95 percent confidence interval 95 percent confidence interval

1990 

estimate From To

2000 

estimate From To

Percent 

change From To

Average household income

Atlanta EZ $18,343 $17,466 $19,220 $28,552 $27,205 $29,899 55.66 55.4 55.91

 Comparison 30,567 29,741 31,393 39,500 38,328 40,672 29.23 28.99 29.46

Baltimore EZ 28,185 27,207 29,164 35,059 33,566 36,551 24.39 24.1 24.67

 Comparison 27,931 27,316 28,546 31,367 30,511 32,223 12.3 12.05 12.56

Chicago EZ 23,097 22,636 23,559 34,718 33,868 35,567 50.31 50.13 50.49

 Comparison 28,431 28,030 28,832 39,985 39,367 40,604 40.64 40.48 40.8

Detroit EZ 22,644 22,034 23,253 33,751 32,660 34,842 49.05 48.84 49.26

 Comparison 25,609 25,197 26,021 36,200 35,523 36,877 41.36 41.19 41.52
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Page 65 GAO-06-727 Empowerment Zones and Enterprise Communities

1990 

estimate From To

2000 

estimate From To

Percent 

change From To

New York EZ 26,518 25,981 27,054 33,557 32,833 34,280 26.54 26.34 26.75

 Comparison 26,993 26,714 27,272 31,247 30,872 31,622 15.76 15.59 15.93

 Upper Manhattan 26,559 25,971 27,147 34,041 33,239 34,844 28.17 27.96 28.39

 Bronx 26,294 24,983 27,606 30,842 29,238 32,446 17.29 16.95 17.64

PhiladelphiaCamden EZ 23,188 22,259 24,117 28,562 27,197 29,927 23.17 22.87 23.48

 Comparison 27,292 26,031 28,553 31,318 29,718 32,918 14.75 14.4 15.1

 Philadelphia 22,269 21,262 23,276 27,851 26,309 29,392 25.07 24.74 25.39

 Camden 26,742 24,465 29,018 31,158 28,228 34,088 16.52 16.05 16.98

Cleveland EZ 20,535 19,730 21,340 28,781 27,524 30,038 40.16 39.9 40.42

 Comparison 24,688 24,171 25,206 30,311 29,607 31,016 22.78 22.56 23

Los Angeles EZ 28,801 28,191 29,412 32,631 31,857 33,405 13.3 13.06 13.54

 Comparison 34,087 33,478 34,696 37,843 37,058 38,628 11.02 10.79 11.25

Kentucky Highlands 

EZ 23,304 22,043 24,565 31,064 29,520 32,608 33.3 32.99 33.61

Mid-Delta EZ 25,872 24,321 27,424 35,559 33,392 37,726 37.44 37.12 37.76

Rio Grande Valley EZ 25,093 23,626 26,560 32,763 30,920 34,606 30.57 30.24 30.9

Providence EC 28,593 27,525 29,661 32,616 31,229 34,004 14.07 13.75 14.39

Fayette-Haywood EC 32,560 31,008 34,111 45,353 43,249 47,457 39.29 39.01 39.57

Average owner-occupied housing value

Atlanta EZ $55,883 $52,688 $59,077 $117,869 $106,218 $129,519 110.92 110.68 111.17

 Comparison 74,063 72,446 75,680 101,774 96,312 107,236 37.42 37.15 37.68

Baltimore EZ 53,714 51,381 56,048 62,219 58,659 65,779 15.83 15.48 16.19

 Comparison 55,966 54,113 57,819 62,514 59,920 65,108 11.7 11.39 12.01

Chicago EZ 71,429 67,487 75,372 160,411 150,476 170,347 124.57 124.38 124.77

 Comparison 88,445 85,343 91,548 167,015 159,548 174,482 88.83 88.64 89.03

Detroit EZ 23,114 22,153 24,075 52,234 49,362 55,106 125.99 125.81 126.16

 Comparison 28,598 27,620 29,575 61,160 58,688 63,632 113.86 113.7 114.03

New York EZ 207,544 166,353 248,735 301,835 244,974 358,697 45.43 44.89 45.98

 Comparison 177,446 167,025 187,867 209,423 198,465 220,380 18.02 17.66 18.38

 Upper 

 Manhattan 238,864 188,845 288,882 384,155 308,848 459,462 60.83 60.32 61.33

 Bronx 99,728 71,856 127,600 124,588 100,021 149,155 24.93 24.23 25.63

PhiladelphiaCamden EZ 29,899 28,060 31,739 37,780 35,895 39,664 26.36 26.02 26.69

 Comparison 42,045 39,630 44,461 51,159 44,926 57,392 21.67 21.22 22.13

 Philadelphia 28,288 26,263 30,313 37,353 35,178 39,528 32.04 31.7 32.39

(Continued From Previous Page)

95 percent confidence interval 95 percent confidence interval 95 percent confidence interval
Appendix I

Objectives, Scope, and Methodology

Page 66 GAO-06-727 Empowerment Zones and Enterprise Communities

Source: GAO analysis of Census data.

a

Other variables used in the model and shown in the site visit descriptions that were based on 

percentages, such as the poverty rate, had confidence intervals of less than +/- 5 percentage points.

In addition to sampling errors, Census data (both sampled and 100 percent 

data) are subject to nonsampling errors that may occur during the 

operations used to collect and process census data. Examples of 

nonsampling errors are not enumerating every housing unit or person in 

the sample, failing to obtain all required information from a respondent, 

obtaining incorrect information, and recording information incorrectly. 

Operations such as field review of enumerator’s work, clerical handling of 

questionnaires, and electronic processing of questionnaires also may 

introduce nonsampling errors in the data. The Census Bureau discusses 

sources of nonsampling errors and makes attempts to limit them.

Choosing Comparison Areas 

Using the Propensity Score

To provide context for the changes we observed in the EZs and ECs, we 

calculated the percent change of the designated areas as well as areas, 

called comparison areas, that most closely resembled the EZ/EC program 

areas. To select comparison areas for our analysis, we used a statistical 

matching method called the propensity score. The propensity score 

predicts the probability that a tract could have been designated based on 

having characteristics similar to those found in the tracts selected for the 

program. We used five factors to calculate the propensity scores, as shown 

in table 7. 

1990 

estimate From To

2000 

estimate From To

Percent 

change From To

Camden 35,076 30,928 39,224 39,398 35,730 43,067 12.32 11.8 12.84

Cleveland EZ 38,071 36,277 39,866 75,186 71,537 78,835 97.49 97.29 97.69

 Comparison 46,972 45,966 47,979 70,161 68,649 71,674 49.37 49.19 49.54

Los Angeles EZ 141,665 138,933 144,397 156,492 151,907 161,078 10.47 10.21 10.72

 Comparison 160,090 157,393 162,787 165,180 161,599 168,761 3.18 2.94 3.42

Kentucky Highlands 

EZ 43,392 38,713 48,071 65,815 62,527 69,104 51.68 51.35 52

Mid-Delta EZ 50,061 47,323 52,800 66,872 59,968 73,777 33.58 33.19 33.97

Rio Grande Valley EZ 46,100 42,654 49,546 61,450 55,970 66,929 33.3 32.91 33.69

Providence EC 124,339 118,190 130,489 116,698 99,200 134,196 -6.15 -6.77 -5.52

Fayette-Haywood EC $68,945 $65,765 $72,125 $103,619 $97,144 $110,094 50.29 50.01 50.57

(Continued From Previous Page)

95 percent confidence interval 95 percent confidence interval 95 percent confidence interval
Appendix I

Objectives, Scope, and Methodology

Page 67 GAO-06-727 Empowerment Zones and Enterprise Communities

Table 7: Factors Selected for Choosing Comparison Tracts

Source: GAO.

a

Percent based on individuals for whom poverty status has been determined.

b

See Bondonio, Daniele and John Engberg (2000), “Enterprise Zones and Local Employment: 

Evidence from the States’ Programs,” Regional Science and Urban Economics, Vol. 30, No.5, pp. 519-

549.

c

Percent based on individuals 16 years of age or older.

d

Individuals per square mile.

e

Hebert and others, Interim Assessment.

f

For the purposes of this report, we calculated minority population by subtracting the percent of white 

population from the total population.

To ensure that our comparison areas were similar to the designated areas 

in terms of geography, we explored two selection methods, one that 

included tracts in the same county as the EZ/EC and in adjacent counties, 

and another that selected tracts within a 5-mile radius of the EZ/EC.12 We 

excluded tracts that received a subsequent designation in the EZ/EC or 

Renewal Community programs in 1998 and 2002 in order to remove the 

possibility of tracts that may have received similar benefits affecting our 

analysis. After mapping the resulting comparison tracts using these two 

methods, we decided to use tracts selected within a 5-mile radius of the 

EZs and ECs because this method provided more contiguous areas, while 

the results of the county and the adjacent counties method yielded 

Factor Reason selected

1990 poverty rate a • EZ/EC program eligibility criteria

• Factor considered in a similar studyb, e

1990 unemployment 

ratec

• EZ/EC program eligibility criteria

• Factor considered in a similar study b

1990 population 

density d

• Calculation based on two EZ/EC program eligibility criteria, 

population and area

• Factor considered in a similar studyb

1990 average 

household income

• Factor considered in similar studies b, e

Percentage of 

minority population 

in 1990f

• Factor considered in similar studies b, e

12Other researchers have used similar approaches, such as Greenbaum and Engberg in “The 

Impact of State Urban Enterprise Zones on Business Outcomes,” December 1998, Carnegie 

Melon University. p. 24.
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Objectives, Scope, and Methodology

Page 68 GAO-06-727 Empowerment Zones and Enterprise Communities

comparison tracts in other states where political structures and types of 

funds could differ. 

Using the computed propensity scores, we selected comparison tracts 

whose scores were greater than 0.1. This threshold was chosen because 

most EZ tracts had propensity scores of 0.1 or higher; therefore, 

comparison tracts with propensity scores of at least 0.1 were the most 

similar to the EZ tracts. This threshold also yielded approximately the same 

number of comparison tracts as EZ tracts in most of the eight urban EZs. In 

addition, we tested this threshold by running our models with comparison 

tracts whose propensity scores were greater than 0.05 or 0.15 and found 

that the results did not change significantly.

13 Some limitations exist with 

this method. For example, since many of census tracts chosen for the 

program may have had the highest level of poverty, it was difficult to find 

tracts with the same level of poverty.

Our Descriptive and 

Econometric Analyses

We calculated the percent changes at the program wide level for our four 

indicators of poverty, unemployment, and economic growth for both 

designated and comparison areas.14 We also calculated the changes for 

urban and rural designees and EZs and ECs separately, so that we could 

make comparisons between those groups. In addition, for the eight urban 

Round I EZs, we calculated the percentages separately for each EZ and EZ 

comparison area to show differences between zones. Although the 

comparison areas were sufficient to use in our program wide analyses, for 

rural EZs and urban and rural ECs, we did not use comparison areas for 

site-level analyses because there were too few comparison tracts. For 

13Generally, increasing the propensity score for selecting comparison tracts has the effect of 

reducing the sample of comparison tracts and decreasing the propensity score has the effect 

of increasing the sample of comparison tracts. 

14Due to changes in the census tract boundaries for some EZs and ECs from 1990 to 2000, we 

used the 2000 census block group to recreate the initial 1990 boundaries and ensure that our 

analysis remained consistent. For the census variables based on percentage characteristics, 

like poverty and unemployment rates, we calculated the change in percentage points by 

finding the difference between the 1990 sample estimate and the 2000 sample estimate. For 

census variables based on average characteristics, such as average household income, we 

calculated the percent change by finding the difference between the 1990 sample estimate 

and the 2000 sample estimate and then dividing the difference by the 1990 sample estimate. 

Census variables using dollar amounts like average household income were adjusted for 

inflation to 2004 dollars. We calculated the percent change for our economic growth 

measures. 
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Page 69 GAO-06-727 Empowerment Zones and Enterprise Communities

example, the Providence, Rhode Island EC consisted of 13 tracts, but the 

area had only four eligible comparison tracts. 

We also completed an econometric analysis of the eight urban EZs. We 

used a standard econometric approach, the weighted least squares model, 

which allowed us to analyze the change from 1990 to 2000 and compare it 

with the 1990 value of several explanatory variables. The benefit of this 

approach is that the program, officially implemented in 1994, would not 

affect the 1990 values of the explanatory variables. In addition, we spoke 

with several experts in the urban studies field on our methodology. For 

more information on the methods used in our econometric analysis and a 

full discussion of our results, please see appendix II.
Page 70 GAO-06-727 Empowerment Zones and Enterprise Communities

Appendix II

Methodology for and Results of Our 

Econometric Models ApendxiI

This appendix describes our efforts to isolate the effect of the EZ/EC 

program on the changes in poverty, unemployment, and economic growth, 

by conducting an econometric analysis of all urban EZ census tracts.1

 In 

our analysis of percent changes, we found that poverty and unemployment 

had decreased and that some economic growth had occurred. However, 

when we used the econometric models to control for other area 

characteristics, our results did not definitively suggest that the observed 

changes in poverty and unemployment were associated with the EZ 

program in urban areas. In addition, our models did not adequately explain 

the observed changes in the proxy measures we used for economic growth; 

thus, the results did not allow us to conclude whether there is an 

association between the EZ program and economic growth. 

As mentioned in the report, there were several challenges that limited our 

ability to determine the effect of the program. First, data at the census 

tract-level for the program years were limited. We used data from the 1990 

and 2000 decennial censuses to show the changes in poverty and 

unemployment. In addition, we primarily used two measures for economic 

growth—the number of businesses and the number of jobs from Claritas 

Business-Facts dataset for years 1995, 1999, and 2004—in our models of 

economic growth.2

 Second, we were not able to account for the spillover 

effects of EZ designation into their neighboring areas. For example, if the 

EZ/EC program affected comparison tracts as well as the designated 

communities, our analyses would not find any significant differences 

between the designated and comparison tracts. The result may be an 

obscuring of the extent of the statistical association between the urban EZ 

program and the study variables. Third, the analyses did not account for the 

confounding effects of other public or private programs, such as those 

intended to reduce poverty or unemployment or increase the number of 

area jobs. As a result, estimates for the EZ program in our analyses may 

under or overstate the extent of EZ program’s correlation with poverty, 

unemployment, and economic growth. Fourth, our estimations did not fully 

account for the economic trends that were affecting the choice of areas 

1

We completed econometric analyses of the eight urban EZs only, because the amount of 

program grant funding for ECs was too small to separate the program’s effects from other 

programs. In addition, we excluded the rural EZs because they are made up of too few 

census tracts to perform these analyses.

2

We excluded establishments that were not eligible for program tax benefits, such as 

nonprofit and governmental organizations, from our analysis of the change in the number of 

businesses. However, we included jobs at those establishments in our analysis of the change 

in the number of jobs.
Appendix II

Methodology for and Results of Our 

Econometric Models

Page 71 GAO-06-727 Empowerment Zones and Enterprise Communities

selected for the program. For example, if program officials tended to pick 

census tracts that were already experiencing gentrification prior to 1994, 

our estimations could overstate the effect of the EZ designation. 

Conversely, if officials tended to choose census tracts that were 

experiencing economic declines prior to 1994, such as those in which 

major employers had closed, we might understate the program’s impact. 

We did include a variable from Census data—new housing construction 

between 1990 and 1994—that measured one dimension of economic trends 

prior to EZ designation, but we did not include other dimensions, such as 

employment trends at the tract level, in the models. 

Description of Our 

Models

We used a weighted least square regression for our analyses.3 Our 

dependent variables were (1) the difference in the poverty rate between 

1990 and 2000, (2) the difference in the unemployment rate between 1990 

and 2000 (3) the difference in the number of businesses between 1995 and 

1999, and (4) the number of jobs between 1995 and 1999. For the basic 

model, we measured the difference in each dependent variable against the 

1990 value of some explanatory variables. The benefit of this approach is 

that 1990 values of the explanatory variables would not have been affected 

by the program, which was implemented in 1994. We also ran an expanded 

version of the model that included variables for each of the EZs to 

determine whether there were differences among the EZs, and we included 

variables for the EZs and their surrounding areas to account for economic 

trends at the metropolitan level, such as the growing or declining output of 

local industries.

Some of the explanatory variables for which we controlled included 

socioeconomic factors, such as percent of population with a high school 

diploma. In addition to these socioeconomic factors, we also considered 

the five factors we used to select the comparison tracts:

3

We also tested use of a fixed effect model, which allowed us to account for some tractspecific factors that may not vary over time but might be correlated with the designation of 

a tract, called “fixed effects.” Other researchers used fixed effects regression techniques to 

control for area-specific unchanging factors, such as industry composition. (See, for 

example, Leslie E. Papke, “What Do We Know About Enterprise Zones?” NBER Working 

Paper No. 4251. Cambridge, Mass., National Bureau of Economic Research, 1993.) The 

analysis in this report predicts first differences in the dependent variables, that is, the 

difference between the value in the 2000 Census and the value in the 1990 Census. When 

only 2 years of data are analyzed, regressions based on first differences are equivalent to 

fixed effect models. (See Zvi Griliches and Jerry Hausman, "Errors in Variables in Panel 

Data," Journal of Econometrics, 31 (1986), pp. 93-118.)
Appendix II

Methodology for and Results of Our 

Econometric Models

Page 72 GAO-06-727 Empowerment Zones and Enterprise Communities

• percent of minority population in 1990,

• average household income in 1990,

• population density in 1990,

• poverty rate in 1990, and

• unemployment rate in 1990. 

We included these variables because the comparison tracts may not be 

perfectly matched to the EZ tracts; including these factors allowed us to 

further account for differences between EZ and comparison tracts. 

Moreover, we weighted the estimations by the geometric mean of 1990 and 

2000 household counts of each tract to account for differences in the 

number of households in each tract. The purpose of this decision was to 

put more weight on the tracts with large numbers of households, because 

these tracts would tend to have smaller sampling errors.

The coefficients for the EZ program variables represent the EZs with 

respect to the comparison areas, and the positive or negative values 

suggest whether the EZs fared better or worse than the comparison areas. 

For instance, a positive coefficient in the models for poverty and 

unemployment would mean that the EZs did not fare as well as the 

comparison areas—that is, they had either a greater increase or a smaller 

decrease in poverty or unemployment. See our discussion of the results of 

each model for more information.

Results of Our Models 

for Poverty

Although our comparison of the percentage change between 1990 and 2000 

showed that poverty decreased in most urban EZs, the results of our 

models did not conclusively suggest that the change in poverty was 

associated with the EZ program. Our analysis of the percentage changes 

showed that the poverty rate fell more in the EZs than in the comparison 

areas. But, when we controlled for other factors in our models, we found in 

the basic model that poverty decreased less in the EZs than in the 

comparison areas, although the difference was very small (table 8). In 

addition, many of the variables used in selection of comparison tracts were 

significant, suggesting that the choice of areas selected for the program 

might have affected the differences between the urban EZs and the 

comparison areas in the change in poverty. When accounting for the 

different urban EZs and their comparison tracts, the poverty rate decreased 
Appendix II

Methodology for and Results of Our 

Econometric Models

Page 73 GAO-06-727 Empowerment Zones and Enterprise Communities

more in some urban EZs but less in others with respect to the comparison 

tracts, although the only significant result was in the Los Angeles EZ, which 

experienced a greater increase in poverty than the comparison areas. The 

differences among EZs may be a result of the local factors. In addition, one 

researcher found that there was a nationwide decrease in the number of 

people living in high poverty neighborhoods, defined as census tracts with 

poverty rates of 40 percent or higher, between 1990 and 2000—a trend that 

might be a factor affecting our results.4

Table 8: Estimates of the Association between the EZ Program and the Change in Poverty Rate, 1990-2000

4

Paul A. Jargowsky, Stunning Progress, Hidden Problems: The Dramatic Decline of 

Concentrated Poverty in the 1990s, (Washington, D.C.: The Brookings Institution, May 

2003).

Basic model Expanded model

Variables Coefficient Standard error Coefficient Standard error

EZ program 1.54 0.67

Atlanta EZ 3.41 2.69

Baltimore EZ -2.27 1.94

Chicago EZ 1.63 1.50

Cleveland EZ -2.43 2.10

Detroit EZ 2.25 1.54

Los Angeles EZ 3.07 1.20

New York EZ -1.87 1.23

Philadelphia-Camden EZ -1.10 2.70

Atlanta EZ areaa -5.50 2.61

Baltimore EZ areaa 0.60 2.49

Chicago EZ areaa -5.08 2.23

Cleveland EZ areaa -4.65 2.36

Detroit EZ areaa -7.73 2.35

Los Angeles EZ areaa 2.00 2.30

New York EZ areaa 0.56 2.40

Philadelphia-Camden EZ areaa b b

Percent of high school dropoutsc 0.080 0.026 0.017 0.024

Percent of vacant housing units -0.064 0.042 0.046 0.044

Percent of female-headed households with childrend 0.24 0.045 0.22 0.042
Appendix II

Methodology for and Results of Our 

Econometric Models

Page 74 GAO-06-727 Empowerment Zones and Enterprise Communities

Source: GAO analysis of Census data.

Notes: Coefficients significant at the 5 percent level are in bold. All variables are from the 1990 Census 

unless otherwise noted. We weighted the regressions by the geometric mean of 1990 and 2000 

household counts of each tract. 

a

We defined the EZ area to include both the EZ tracts and comparison tracts that were selected from 

within a 5-mile boundary of the EZ.

b

Results for the Philadelphia-Camden EZ area are not listed, because we used them as a reference 

group for the other seven EZs and their surrounding areas.

c

Percent based on the civilian population between ages 16 and 19 who are not enrolled in school and 

are not high school graduates.

d

Percent based on households headed by females without husbands present in which there are 

children under 18 years of age.

e

Percent based on individuals 16 and over. 

f

From the 2000 Census.

g

We calculated minority population by subtracting the percent of white population from the total 

population.

h

Individuals per square mile.

i

Percent based on individuals for whom poverty status has been determined.

j

Percent based on individuals 16 years of age or older in the labor force.

Results of Our Models 

for Unemployment

Like our models for poverty, our models for the unemployment did not 

conclusively suggest that the changes in unemployment were associated 

with the EZ program. The results of our basic model suggested that 

unemployment decreased more in the EZs than in the comparison areas, 

but the difference was very small and was not statistically significant (table 

9). All five of the variables we used to select comparison tracts were 

statistically significant, suggesting that the choice of areas selected for the 

program might have affected the difference in the change in unemployment 

Percent employed in retail industrye -0.0073 0.054 0.040 0.052

Percent housing units built between 1990 and 1994f -0.17 0.081 -0.29 0.082

Percent minority populationg 0.0045 0.022 -0.021 0.021

Average household income (in 2004 dollars) -0.00046 0.00085 -0.00060 0.000081

Population densityh 0.000047 0.0000087 0.000024 0.000013

Poverty ratei -0.71 0.052 -0.79 0.047

Unemployment ratej -0.047 0.046 0.085 0.054

Constant 30.39 4.29 40.79 4.83

Number of tracts 851 851

R-sq 0.40 0.47

(Continued From Previous Page)

 Basic model Expanded model

Variables Coefficient Standard error Coefficient Standard error
Appendix II

Methodology for and Results of Our 

Econometric Models

Page 75 GAO-06-727 Empowerment Zones and Enterprise Communities

rate between EZ and comparison tracts. Like the model for poverty, our 

model showed that the unemployment rate decreased more in some urban 

EZs but less in others, although the only EZ that experienced a significant 

change was the Cleveland EZ, which showed a significantly greater 

decrease in unemployment than the comparison areas. As with poverty 

rate, local factors may have accounted for the difference between the 

various urban EZs with respect to the comparison tracts.

Table 9: Estimates of the Association between the EZ Program and the Change in Unemployment Rate, 1990-2000

Basic model Expanded model

Variables Coefficient Standard error Coefficient Standard error

EZ program -0.065 0.50

Atlanta EZ 2.56 1.95

Baltimore EZ -0.71 1.77

Chicago EZ -0.68 1.07

Cleveland EZ -3.65 1.40

Detroit EZ 1.76 1.09

Los Angeles EZ 0.092 1.20

New York EZ -1.57 0.88

Philadelphia-Camden EZ -0.87 1.83

Atlanta EZ areaa -2.48 1.71

Baltimore EZ areaa 2.35 1.71

Chicago EZ areaa 2.66 1.57

Cleveland EZ areaa -1.89 1.58

Detroit EZ areaa -2.59 1.55

Los Angeles EZ areaa 3.61 1.62

New York EZ areaa 3.13 1.62

Philadelphia-Camden EZ areaa b b

Percent of population of working agec 0.068 0.072 0.093 0.068

Percent of population with a high school diplomad 0.11 0.039 0.20 0.044

Percent of housing units built between 1990 and 1994e -0.18 0.062 -0.23 0.062

Percent minority populationf 0.072 0.012 0.054 0.014

Average household income (in 2004 dollars) -0.00017 0.000068 -0.00032 0.000078

Population densityg 0.000032 0.0000066 0.0000064 0.000011

Poverty rateh 0.20 0.033 0.15 0.034

Unemployment ratei -0.90 0.039 -0.86 0.044

Constant -0.88 4.54 1.92 4.61
Appendix II

Methodology for and Results of Our 

Econometric Models

Page 76 GAO-06-727 Empowerment Zones and Enterprise Communities

Source: GAO analysis of Census data

Notes: Coefficients significant at the 5 percent level are in bold. All variables are from the 1990 Census 

unless otherwise noted. We weighted the regressions by the geometric mean of 1990 and 2000 

household counts of each tract. 

a

We defined the EZ area to include both the EZ tracts and comparison tracts that were selected from 

within a 5-mile boundary of the EZ.

b

Results for the Philadelphia-Camden EZ area are not listed, because we used them as a reference 

group for the other seven EZs and their surrounding areas.

c

We defined “working age” as between 16 and 64 years of age.

d

Percent based on population 25 years of age and over.

e

From the 2000 Census.

f

For the purposes of this report, we calculated minority population by subtracting the percent of white 

population from the total population.

g

Individuals per square mile.

h

Percent based on individuals for whom poverty status has been determined.

i

Percent based on individuals 16 years of age or older in the labor force.

Results of Our Models 

for Economic Growth

To estimate the statistical relationship between the EZ program and 

economic growth, we used two proxy measures: (1) the number of 

businesses excluding establishments that were not eligible for program tax 

benefits such as nonprofit and governmental organizations and (2) the 

number of jobs in the EZ. In order to be consistent with our analyses of 

poverty rate and unemployment, which covered the time period between 

1990 and 2000, we used 1995 and 1999 data for our models of economic 

growth.5

 We also tested the model using Home Mortgage Disclosure Act 

data on the number of loan originations for new home purchases and the 

mean loan amount for new home purchases as other possible measures of 

economic growth, but found consistent results, which are not presented 

here. 

On the basis of the results of our models, we were not able to determine 

whether there is a statistical association between the EZ program and 

Number of tracts 866 866

R-sq 0.53 0.57

(Continued From Previous Page)

Basic model Expanded model

Variables Coefficient Standard error Coefficient Standard error

5

We also tested the models using the longer time period of 1995 to 2004, but the results were 

consistent with those using the time period from 1995 to 1999. 
Appendix II

Methodology for and Results of Our 

Econometric Models

Page 77 GAO-06-727 Empowerment Zones and Enterprise Communities

economic growth because the explanatory variables we used explained 

little of the variation in the changes in the number of businesses or jobs 

between 1995 and 1999 (tables 10 and 11). 6

 Not surprisingly, most 

explanatory variables were also not significant. The low explanatory power 

of our models could be the result of not having considered the right 

variables; however, we explored many combinations of variables, all of 

which yielded consistent results. This lack of explanatory power might also 

be the result of the fact that our proxy measures—the number of 

businesses and jobs—were not strongly representative of economic 

growth. Nevertheless, similar to the models of the change in poverty and 

unemployment, the models of the change in economic growth reflect 

variation between the EZs with respect to the comparison areas, but none 

of the results were statistically significant. 

Table 10: Estimates of the Association between the EZ Program and Economic Growth, Measured by the Change in the Number 

of Businesses, from 1995-1999a

6

This low explanatory power is indicated in the low R-square statistics in tables 10 and 11. 

Basic model Expanded model

Variables Coefficient Standard error Coefficient Standard error

EZ program -22.58 18.84

Atlanta EZ 24.59 26.62

Baltimore EZ -0.84 12.12

Chicago EZ 12.80 14.80

Cleveland EZ 4.95 7.05

Detroit EZ 13.68 13.05

Los Angeles EZ -113.70 91.86

New York EZ 10.80 10.92

Philadelphia-Camden EZ 1.03 21.50

Atlanta EZ areab -12.32 22.13

Baltimore EZ areab -23.11 17.86

Chicago EZ areab -17.65 16.25

Cleveland EZ areab 11.51 29.68

Detroit EZ areab 8.64 25.45

Los Angeles EZ areab -38.46 27.71

New York EZ areab -15.84 20.05
Appendix II

Methodology for and Results of Our 

Econometric Models

Page 78 GAO-06-727 Empowerment Zones and Enterprise Communities

Source: GAO analysis of Census and Claritas data.

Notes: Coefficients significant at the 5 percent level are in bold. All variables are from the 1990 Census 

unless otherwise noted. We weighted the regressions by the geometric mean of 1990 and 2000 

household counts of each tract.

a

Excluding establishments that were not eligible for the program tax benefits, such as nonprofit and 

governmental organizations. 

b

We defined the EZ area to include both the EZ tracts and comparison tracts that were selected from 

within a 5-mile boundary of the EZ.

c

Results for the Philadelphia-Camden EZ area are not listed, because we used them as a reference 

group for the other seven EZs and their surrounding areas.

d

From the 2000 Census.

e

For the purposes of this report, we calculated minority population by subtracting the percent of white 

population from the total population.

f

Individuals per square mile.

g

Percent based on individuals for whom poverty status has been determined.

h

Percent based on individuals 16 years of age or older in the labor force.

Variables Coefficient Standard error Coefficient Standard error

Philadelphia-Camden EZ areab c c

Population -0.0027 0.0026 0.0011 0.0014

Percent vacant housing units 0.10 0.27 -1.09 1.01

Percent of housing units built between 1990 and 1994d 0.95 0.58 1.77 1.37

Percent minority populatione 0.74 0.69 0.80 0.69

Average household income (in 2004 dollars) 0.0044 0.0051 0.0056 0.006

Population densityf 0.00027 0.00014 0.000056 0.00011

Poverty rateg 1.67 2.21 2.31 2.61

Unemployment rateh 0.13 0.35 -0.22 0.59

Constant -253.01 278.86 -300.97 314.17

Number of tracts 860 860

R-sq 0.042 0.11

(Continued From Previous Page)

Basic model Expanded model
Appendix II

Methodology for and Results of Our 

Econometric Models

Page 79 GAO-06-727 Empowerment Zones and Enterprise Communities

Table 11: Estimates of the Association between the EZ Program and Economic Growth, Measured by the Change in the Number 

of Jobs, 1995-1999

Source: GAO analysis of Census and Claritas data.

Notes: Coefficients significant at the 5 percent level are in bold. All variables are from the 1990 Census 

unless otherwise noted. We weighted the regressions by the geometric mean of 1990 and 2000 

household counts of each tract.

a

We defined the EZ area to include both the EZ tracts and comparison tracts that were selected from 

within a 5-mile boundary of the EZ.

Basic model Expanded model

Variables Coefficient Standard error Coefficient Standard error

EZ program -68.86 196.83

Atlanta EZ 286.01 983.37

Baltimore EZ 1199.74 715.74

Chicago EZ -88.43 180.84

Cleveland EZ 102.85 293.30

Detroit EZ 199.16 181.98

Los Angeles EZ -438.63 632.33

New York EZ -288.08 231.26

Philadelphia-Camden EZ 197.87 631.54

Atlanta EZ areaa -318.84 883.10

Baltimore EZ areaa -819.50 810.54

Chicago EZ areaa 36.80 547.93

Cleveland EZ areaa 134.99 557.58

Detroit EZ areaa -61.44 576.67

Los Angeles EZ areaa -239.53 571.81

New York EZ areaa 270.91 553.59

Philadelphia-Camden EZ areaa b b

Percent of population of working aged -21.04 28.00 -19.59 29.65

Percent of population with a high school diplomad 10.36 8.39 4.06 11.77

Percent of housing units built between 1990 and 1994e 10.57 29.50 5.09 29.33

Percent minority populationf 3.41 4.63 3.23 5.36

Average household income (in 2004 dollars) 0.022 0.038 0.032 0.048

Population densityg 0.0016 0.0023 -0.0019 0.0029

Poverty rateh -1.30 20.33 2.99 20.34

Unemployment ratei 3.10 15.33 -0.95 14.30

Constant -56.23 1483.38 -200.97 1695.03

Number of tracts 859 859

R-sq 0.016 0.043
Appendix II

Methodology for and Results of Our 

Econometric Models

Page 80 GAO-06-727 Empowerment Zones and Enterprise Communities

b

Results for the Philadelphia-Camden EZ area are not listed, because we used them as a reference 

group for the other seven EZs and their surrounding areas.

c

We defined “working age” as between 16 and 64 years of age.

d

Percent based on population 25 years of age and over.

e

From the 2000 Census.

f

For the purposes of this report, we calculated minority population by subtracting the percent of white 

population from the total population.

g

Individuals per square mile.

h

Percent based on individuals for whom poverty status has been determined.

i

Percent based on individuals 16 years of age or older in the labor force.

Other Variables Tested 

for Use in Our 

Econometric Models

In addition to the variables presented in the models above, we explored 

many alternative dependent variables and explanatory variables to test the 

robustness of the models we used (table 12). In particular, we 

experimented with several alternative measures for economic growth. To 

test how our results might change in response to the selection of 

comparison tracts, we also reestimated the models using comparison tracts 

selected with different propensity scores. We also ran the models excluding 

the Los Angeles and Cleveland EZs, because these EZs received a slightly 

different package of benefits when they were initially designated as 

Supplemental EZs. These tests all yielded results consistent with our 

models, so they are not presented here. 

Table 12: Alternative Variables Considered in Our Analyses

Definition of variables Rationale Data sources

Dependent variables

Change in per-capita income between 1990 and 2000 An opposite measure of poverty 1990 and 2000 Census

Change in employment rate between 1990 and 2000 An opposite measure of unemployment 1990 and 2000 Census

Percent change in number of businesses between 

1995 and 1999

Alternative measure of economic growth Claritas 1995, 1999

Percent change in the number of jobs between 1995 

and 1999

Alternative measure of economic growth Claritas 1995, 1999

Percent change in number of businesses between 

1995 and 2004

Alternative measure of economic growth Claritas 1995, 2004

Percent change in the number of jobs between 1995 

and 2004

Alternative measure of economic growth Claritas 1995, 2004

Change in jobs per business between 1995 and 1999 Alternative measure of economic growth Claritas 1995, 1999
Appendix II

Methodology for and Results of Our 

Econometric Models

Page 81 GAO-06-727 Empowerment Zones and Enterprise Communities

Source: GAO.

Dependent variables

Change in aggregate sales volume of businesses at 

each tract between 1995 and 1999

Alternative measure of economic growth Claritas 1995, 1999

Percent change in number of loan originations for new 

home purchases between 1995 and 1999

Alternative measure of economic growth Home Mortgage 

Disclosure Act data 1995, 

1999

Percent change in mean loan amount for new home 

purchases between 1995 and 1999

Alternative measure of economic growth Home Mortgage 

Disclosure Act data 1995, 

1999

Explanatory variables

Percent foreign-born population Alternative indirect measure for minority population 1990 Census

Adjusted per capita income in 2004 dollars Alternative indirect measure household income 1990 Census

Percent of males aged 16 or greater Alternative measure for working population 1990 Census

Percent of housing units built last 5 years before 

census

Alternative measure to account for economic trend 1990 Census

Percent of persons aged 25 or greater with some 

college

Alternative measure for educational level 1990 Census

Percent of employment in manufacturing industry Alternative measure of industry characteristics 1990 Census

Percent of female-headed single households Alternative measure for household characteristics 1990 Census

(Continued From Previous Page)

Definition of variables Rationale Data sources
Page 82 GAO-06-727 Empowerment Zones and Enterprise Communities

Appendix III

List of Communities Designated in Round I of 

the EZ/EC Program ApendxiI

Round I Urban EZs (8)

Atlanta, Georgia

Baltimore, Maryland

Chicago, Illinois

Cleveland, Ohioa

Detroit, Michigan

Los Angeles, Californiaa

New York, New York

Philadelphia, Pennsylvania/Camden, New Jersey

Round I Urban ECs (65)

Akron, Ohio

Albany, Georgia

Albany/Schenectady/Troy, New York

Albuquerque, New Mexico

Birmingham, Alabama

Boston, Massachusettsb

Bridgeport, Connecticut

Buffalo, New York

Burlington, Vermont

Charleston, South Carolina

Charlotte, North Carolina

Cleveland, Ohioc

Columbus, Ohio

Dallas, Texas

Denver, Colorado

Des Moines, Iowa

East St. Louis, Illinois

El Paso, Texas

Flint, Michigan

Harrisburg, Pennsylvania

Houston, Texasb

Huntington, West Virginia

Indianapolis, Indiana

Jackson, Mississippi

Kansas City, Missouri/Kansas City, Kansasb

Las Vegas, Nevada

Little Rock/Pulaski, Arkansas

Los Angeles, California

Louisville, Kentucky

Lowell, Massachusetts

Manchester, New Hampshire

Memphis, Tennessee
Appendix III

List of Communities Designated in Round I of 

the EZ/EC Program

Page 83 GAO-06-727 Empowerment Zones and Enterprise Communities

Miami/Dade County, Florida

Milwaukee, Wisconsin

Minneapolis, Minnesota

Muskegon, Michigan

Nashville/Davidson, Tennessee

New Haven, Connecticut

New Orleans, Louisiana

Newark, New Jersey

Newburgh/Kingston, New York

Norfolk, Virginia

Oakland, Californiab

Ogden, Utah

Oklahoma City, Oklahoma

Omaha, Nebraska

Ouachita Parish, Louisiana

Phoenix, Arizona

Pittsburgh, Pennsylvania

Portland, Oregon

Providence, Rhode Island

Rochester, New York

San Antonio, Texas

San Diego, California

San Francisco, California

Seattle, Washington

Springfield, Illinois

Springfield, Massachusetts

St. Louis, Missouri

St. Paul, Minnesota

Tacoma, Washington

Tampa, Florida

Waco, Texas

Washington, District of Columbia

Wilmington, Delaware

Round I Rural EZs (3)

Kentucky Highlands, Kentucky

Mid-Delta, Mississippi

Rio Grande Valley, Texas

Round I Rural ECs (30)

Accomack and Northampton County, Virginia

Arizona Border Region, Arizona

Beadle/Spink Counties, South Dakota

Central Appalachia, West Virginia
Appendix III

List of Communities Designated in Round I of 

the EZ/EC Program

Page 84 GAO-06-727 Empowerment Zones and Enterprise Communities

Central Savannah River Area, Georgia

Chambers County, Alabama

City of East Prairie, Missouri

City of Lock Haven, Pennsylvania

City of Watsonville, California

Crisp/Dooly County, Georgia

East Arkansas, Arkansas

Fayette/Haywood County, Tennessee

Greater Portsmouth, Ohio

Greene-Sumter, Alabama

The Halifax/Edgecombe/Wilson Empowerment Alliance, North Carolina

Imperial County, California

Jackson County, Florida

Josephine County, Oregon

La Jicarita, New Mexico

Lake County, Michigan

Lower Yakima County, Washington

Macon Ridge, Louisiana

McDowell County, West Virginia

Mississippi County, Arkansas

North Delta Mississippi, Mississippi

Northeast Louisiana Delta, Louisiana

Robeson County, North Carolina

Scott, Tennessee/McCreary, Kentucky

Southeast Oklahoma, Oklahoma

Williamsburg-Lake City, South Carolina

Source: HUD and USDA data.

a

Initially designated as a Supplemental EZ

b

Also designated as an Enhanced EC 

c

Also designated as a Supplemental EZ
Page 85 GAO-06-727 Empowerment Zones and Enterprise Communities

Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited ApendxiIV

This appendix contains detailed information we gathered from our site 

visits to the 11 Round I EZs and 2 ECs. The appendix describes how the 

EZs and ECs were governed; the activities they implemented; changes in 

poverty, unemployment, and economic growth; and stakeholders’ 

perceptions of factors influencing those changes. It also includes the 

percent changes in variables used in the econometric model. 

Atlanta Empowerment 

Zone

Figure 13: Map of the Atlanta EZ and Its Comparison Area

EZ

Comparison areas

Atlanta city limits

Source: GAO analysis of Census and HUD data.

Georigia

0 3.5 

miles

7 

Atlanta

The Atlanta EZ was located

near downtown Atlanta.
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 86 GAO-06-727 Empowerment Zones and Enterprise Communities

How the EZ Was Governed The city of Atlanta established the nonprofit Atlanta Empowerment Zone 

Corporation to operate the EZ. The corporation had two boards: the 

Executive Board and the Community Empowerment Advisory Board, 

which included representatives of each of the EZ neighborhoods. 

According to EZ stakeholders we interviewed, the EZ Executive Board 

gave final approval on activities the EZ implemented. However, EZ 

stakeholders also mentioned that the intended process was not always 

followed and that the board was not always able to approve activities due 

to difficulties reaching consensus. 

Activities the EZ 

Implemented

According to HUD data, most of the Atlanta EZ’s activities related to 

community development, but the EZ also implemented some activities 

related to economic opportunity, such as making loans to EZ businesses. 

Initiatives involving housing, public safety, and assistance to businesses 

were the most frequently implemented types of activities (fig. 14). In our 

interviews, EZ stakeholders mentioned initiatives they saw as particularly 

useful, including housing programs for seniors and low-income EZ 

residents—for example, a program that helped to repair code violations in 

homes of senior citizens. Stakeholders also said that the EZ provided funds 

to after-school and health-related programs, such as one that provided 

children and adults with asthma with needed resources and education. 

Some EZ stakeholders suggested that the loan program lacked positive 

results, because many of the businesses that received the loans failed.1

1

In 2002, the Atlanta EZ was designated as a Renewal Community, and by 2003 the Atlanta 

EZ was no longer in operation. HHS transferred the remaining EZ/EC funds (over $53 

million) to the Renewal Community, but as of March 2006, these funds had not been used. 
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 87 GAO-06-727 Empowerment Zones and Enterprise Communities

Figure 14: Activities Implemented by the Atlanta EZ 

0

1

2

3

4

5

6

7

8

9

The Atlanta EZ provided funding for Operation P.E.A.C.E., an after-school tutoring organization, 

to purchase this bus. 

8% 

32% 

60% 

Atlanta, GA 

Community-based partnerships

Economic opportunity 

Community development 

Number of activities

Sources: GAO (photo); GAO analysis of HUD data (charts).

Activities

Health

Environment

Workforce

Education

development

Capacity

building

Access to

capital

Businesses

assisted

Public

safety

Housing
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 88 GAO-06-727 Empowerment Zones and Enterprise Communities

Changes in Poverty, 

Unemployment, and 

Economic Growth

Poverty declined in the Atlanta EZ, but unemployment did not, and 

measures of economic growth did not show improvement. Atlanta had the 

highest poverty rate of any EZ in 1990 (55 percent). By 2000, this rate had 

fallen by around 10 percentage points, while the rate of its comparison area 

remained the same. Conversely, the unemployment rate went from one of 

the lowest of the urban EZs in 1990 to one of the highest in 2000, and the 

increase was greater than in its comparison area. Similarly, the Atlanta EZ 

and its comparison area experienced a large decline—more than 20 

percent—in total number of businesses from 1995 to 2004. The Atlanta EZ 

had the second largest decline in the number of jobs of any EZ, which was 

also more than in its comparison area. Tables 13 and 14 show the changes 

in poverty, unemployment, and economic growth in the EZ and its 

comparison area. Table 13 also includes data on the changes in other 

variables included in our models. 

Table 13: Changes in Selected Census Variables Observed in the Atlanta EZ and Its Comparison Area

Source: GAO analysis of Census data.

Note: There are 23 census tracts in the designated area and 16 in the comparison area. Estimates for 

all census variables based on percentages had 95 percent confidence intervals of plus or minus 5 

percentage points or less. For the confidence intervals for average household income and average 

owner-occupied housing estimates, see appendix I.

1990 2000 Percent changea

EZ Comparison EZ Comparison EZ Comparison

Poverty rate (%) 54.67 30.15 44.82 28.02 -9.84b -2.12

Unemployment rate (%) 17.48 11.36 23.44 11.88 5.96b 0.52

Average household income $18,343 $30,567 $28,552 $39,500 55.66b 29.23b

Percentage of single female headed 

households with children 24.62 20.02 21.26 19.95 -3.36b -0.07

Total population 49,966 65,809 45,931 64,022 -8.07 -2.71

Total individuals per square mile 5,408 2,671 4,972 2,756 -8.07 3.16

Percentage of households that moved in the 

last 5 years 50.87 46.01 53.32 52.52 2.45b 6.51b

Percentage of population of working age 

(16-64) 60.16 61.68 63.42 64.59 3.26b 2.92b

Percentage of population with a high school 

diploma (or equivalent) 43.10 60.53 58.96 69.3 15.86b 8.78b

Percentage of high school dropouts 19.12 19.1 21.48 21.19 2.36b 2.08b

Percentage of vacant housing units 20.79 14.65 13.30 7.43 -7.48b -7.22b

Average owner occupied housing value $55,883 $74,063 $117,869 $101,774 110.92b 37.42b
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 89 GAO-06-727 Empowerment Zones and Enterprise Communities

a

Differences in poverty rate, unemployment rate, and other variables shown as percentages are based 

upon percentage point differences. Differences for average household income, population, individuals 

per square mile, and average housing value are calculated as percent changes. 

b

The change in estimates from 1990 to 2000 is statistically significant.

Table 14: Changes in Selected Economic Growth Variables Observed in the Atlanta EZ and Its Comparison Area

Source: GAO analysis of Claritas data.

Note: There are 23 census tracts in the designated area and 16 in the comparison area. We excluded 

establishments that were not eligible for program tax benefits, such as nonprofit and governmental 

organizations, from our analysis of the change in the number of businesses. However, we included 

jobs at those businesses in our analysis of the change in the number of jobs.

a

Differences for the number of businesses and the number of jobs are calculated as percent changes. 

Stakeholder Perceptions of 

the Factors Influencing 

Changes in Poverty, 

Unemployment, and 

Economic Growth

In our interviews, stakeholders said that changes in the poverty rate may 

have been due to changes in the EZ population and the demolition of public 

housing. They explained that residents with lower incomes had left the EZ 

and that households with higher incomes were moving in because of 

changes in the EZ as a result of development from the Olympics and the 

demolition of public housing through the HOPE VI program.2

Commenting on unemployment, stakeholders suggested that EZ residents 

had benefited from EZ job training and placement programs but that a 

mismatch still existed between residents’ skills and some of the new jobs 

available in the EZ. 

Although our economic growth data suggested a decrease in the number of 

businesses and number of jobs, stakeholders suggested that the EZ had 

helped to foster economic growth in some of the commercial corridors by 

helping to fund neighborhood plans. Two stakeholders also mentioned the 

1996 Olympics as a factor in bringing jobs and development to the EZ and 

1995 1999 2004

Percent change 1995-

2004a

EZ Comparison EZ Comparison EZ Comparison EZ Comparison

Number of 

businesses 1,930 3,980 1,549 3,380 1,529 3,248 -20.78 -18.39

Number of jobs 36,888 71,346 31,470 79,580 28,672 69,140 -22.27 -3.09

2

Congress established the HOPE VI program in 1992 to revitalize severely distressed public 

housing by demolition, rehabilitation, or replacement of sites.
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 90 GAO-06-727 Empowerment Zones and Enterprise Communities

the city of Atlanta, although one stakeholder noted that several businesses 

had closed down after the Olympics. This loss of businesses potentially 

helps explain the significant decrease in the number of businesses between 

1995 and 2004. 

Baltimore 

Empowerment Zone

Figure 15: Map of the Baltimore EZ and Its Comparison Area

EZ

Comparison areas

Baltimore city limits

Curtis Creek 

0 2 4 

miles

Patapsco 

River 

Baltimore 

Maryland 

The Baltimore EZ is located 

on both the East and West 

sides of downtown and in 

an industrial area in the 

Southeast corner of the city.

Source: GAO analysis of Census and HUD data.
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 91 GAO-06-727 Empowerment Zones and Enterprise Communities

How the EZ Was Governed The nonprofit Empower Baltimore Management Corporation was created 

specifically to manage Baltimore’s EZ program. The EZ was governed by a 

board composed of community leaders, three committees (one for each 

core strategic goal), an executive committee of the three committee chairs, 

and an advisory council of individuals from all areas of the EZ. Governance 

of the Baltimore EZ also included six “Village Centers”—community groups 

that applied to be the implementing agencies of EZ programs in their local 

communities. EZ activities were vetted through the advisory council and 

sent to the executive committee and full board for final approval. 

Activities the EZ 

Implemented

Unlike most EZs, the Baltimore EZ implemented a higher number of 

economic opportunity activities than community development activities. 

The three types of activities most often implemented were workforce 

development, access to capital, and assistance to businesses (fig. 16). Most 

stakeholders described the EZ’s workforce training activities, such as the 

customized training program that provided EZ residents with 

individualized instruction and a stipend during the training period. In 

addition, the EZ operated several loan funds and partially funded the Bank 

One check processing center and the Montgomery Park business incubator, 

two business developments. The EZ also ran a lead paint abatement 

program and a homeownership program. The Baltimore EZ received a 

grant extension through June 2006. 
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 92 GAO-06-727 Empowerment Zones and Enterprise Communities

Figure 16: Activities Implemented by the Baltimore EZ

The Baltimore EZ provided some funding for the renovation of the old Montgomery Ward building 

to create a “business incubator” that offers office space and technical assistance to new 

small businesses. 

7%

59%

34%

Baltimore, MD 

Community-based partnerships

Other

Economic opportunity

Community development

Number of activities

Sources: GAO (photo); GAO analysis of HUD data (charts).

Activities

Health

Environment

Education

Other

programs/

projects

Workforce

development

Capacity

building

Access to

capital

Businesses

assisted

Public

safety

Housing

Human

services

0

2

4

6

8

10
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 93 GAO-06-727 Empowerment Zones and Enterprise Communities

Changes in Poverty, 

Unemployment, and 

Economic Growth

Poverty decreased in the Baltimore EZ and economic growth improved 

somewhat, but unemployment stayed the same. The poverty rate in the EZ 

fell between 1990 and 2000, while its comparison area stayed about the 

same. However, the unemployment rate, which was one of the lowest of the 

urban EZs in 1990, stayed the same between 1990 and 2000, while the rate 

in its comparison area increased. In terms of economic growth, the results 

were mixed, with the EZ doing somewhat better than its comparison area. 

The number of businesses in the EZ fell from 1995 to 2004, but the number 

of jobs increased. In its comparison area, the number of businesses also 

fell, but the number of jobs fell substantially. Tables 15 and 16 show the 

changes in poverty, unemployment, and economic growth in the EZ and its 

comparison area. Table 15 also includes data on the changes in other 

variables included in our models.

Table 15: Changes in Selected Census Variables Observed in the Baltimore EZ and Its Comparison Area

Source: GAO analysis of Census data.

Note: There are 25 census tracts in the designated area and 41 in the comparison area. Estimates for 

all census variables based on percentages had 95 percent confidence intervals of plus or minus 5 

percentage points or less. For the confidence intervals for average household income and average 

owner-occupied housing estimates, see appendix I.

a

Differences in poverty rate, unemployment rate, and other variables shown as percentages are based 

upon percentage point differences. Differences for average household income, population, individuals 

per square mile, and average housing value are calculated as percent changes. 

b

The change in estimates from 1990 to 2000 is statistically significant.

1990 2000 Percent changea

EZ Comparison EZ Comparison EZ Comparison

Poverty rate (%) 41.81 41.17 35.66 39.74 -6.16 b -1.43

Unemployment rate (%) 15.00 14.55 16.48 17.58 1.49 3.03 b

Average household income $28,185 $27,931 $35,059 $31,367 24.39b 12.30b

Percentage of single female headed households with children 22.50 23.15 19.49 19.64 -3.01 b -3.51b

Total population 72,725 150,507 54,657 113,052 -24.84 -24.89

Total individuals per square mile 10,460 16,934 7,890 12,923 -24.57 -23.69

Percentage of households that moved in the last 5 years 41.07 42.98 41.00 44.90 -0.07 1.92b

Percentage of population of working age (16-64) 58.55 60.31 60.04 61.63 1.48 1.32

Percentage of population with a high school diploma (or 

equivalent) 45.69 49.86 56.44 58.50 10.74b 8.64b

Percentage of high school dropouts 32.36 26.43 19.55 20.61 -12.81 b -5.81b

Percentage of vacant housing units 17.59 12.67 26.22 23.63 8.62b 10.96b

Average owner occupied housing value $53,714 $55,966 $62,219 $62,514 15.83b 11.7b
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 94 GAO-06-727 Empowerment Zones and Enterprise Communities

Table 16: Changes in Selected Economic Growth Variables Observed in the Baltimore EZ and Its Comparison Area

Source: GAO analysis of Claritas data.

Note: There are 25 census tracts in the designated area and 41 in the comparison area. We excluded 

establishments that were not eligible for program tax benefits, such as nonprofit and governmental 

organizations, from our analysis of the change in the number of businesses. However, we included 

jobs at those businesses in our analysis of the change in the number of jobs.

a

Differences for the number of businesses and the number of jobs are calculated as percent changes. 

Stakeholder Perceptions of 

the Factors Influencing 

Changes in Poverty, 

Unemployment, and 

Economic Growth

In our interviews, several stakeholders from the Baltimore EZ said that 

changes in the population of the zone had influenced the change in poverty 

rate. They said that a local HOPE VI project had relocated many of the 

original EZ residents and that rising property values may have caused some 

original residents to move out of the zone. Four stakeholders also 

mentioned lower crime rates in the EZ, which three of them linked to the 

decrease in poverty. 

Two stakeholders mentioned trends in the national economy that 

influenced the change in unemployment, and some said that population 

changes in the zone had affected unemployment as well as poverty.

Stakeholders cited both EZ-related and external factors as affecting 

economic growth. For example, some said that the EZ created economic 

growth with its entrepreneurial programs, loan funds, and businesses 

developments, such as the Montgomery Park business incubator. 

Stakeholders offered mixed perceptions on the impact of the EZ tax 

benefits on economic growth. Some believed that tax benefits were helpful 

to economic growth, while others did not. In addition, one stakeholder said 

that the waterfront area of the EZ was a natural place for development and 

that the designated area might have experienced economic growth in the 

absence of the program. 

1995 1999 2004

Percent change 1995-

2004a

EZ Comparison EZ Comparison EZ Comparison EZ Comparison

Number of businesses 2,797 3,481 2,399 2,930 2,487 3,005 -11.08 -13.67

Number of jobs 41,837 61,519 53,732 35,268 47,504 36,860 13.55 -40.08
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 95 GAO-06-727 Empowerment Zones and Enterprise Communities

Chicago 

Empowerment Zone

Figure 17: Map of the Chicago EZ and Its Comparison Area

EZ

Comparison areas

Chicago city limits

Lake Michigan 

0 3.5 7 

miles

Indiana

Illinois

Chicago 

The Chicago EZ was

located in the Pilsen-Little 

Village, South Side, and 

West Side areas of Chicago.

Source: GAO analysis of Census and HUD data.
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 96 GAO-06-727 Empowerment Zones and Enterprise Communities

How the EZ Was Governed The city of Chicago operated its EZ program, incorporating an EZ 

coordinating council and advisory subgroups called “community clusters.” 

Both the coordinating council and community clusters were made up of EZ 

residents and local officials. All proposals for EZ activities were submitted 

through a request-for-proposal process, made available for comment by the 

coordinating council, and were reviewed and approved by the Chicago City 

Council. 

Activities the EZ 

Implemented

The Chicago EZ implemented more community development than 

economic opportunity activities. The activities it implemented most often 

were related to workforce development, education, and human services, 

and stakeholders said that the EZ was also active in the area of housing 

development (fig. 18). EZ stakeholders also noted that the EZ had helped to 

improve health care for individuals without insurance by contributing to 

the renovation or expansion of local medical facilities. In addition, 

businesses in the Chicago EZ used six program tax-exempt bonds. The 

Chicago EZ received a grant extension through 2009. 
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 97 GAO-06-727 Empowerment Zones and Enterprise Communities

Figure 18: Activities Implemented by the Chicago EZ

The Chicago EZ provided the initial funding for a subgrantee to build these mixed-income 

housing units in the South Side neighborhood. 

7%

37%

57%

Chicago, IL 

Community-based partnerships

Economic opportunity 

Community development 

Number of activities

Sources: GAO (photo); GAO analysis of HUD data (charts).

Activities

Health

Environment

Infrastructure

Workforce

Education

development

Human

services

Capacity

building

Access to

capital

Businesses

assisted

Other

programs/

projects

Public

safety

Housing

0

5

10

15

20

25

30

35

Other
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 98 GAO-06-727 Empowerment Zones and Enterprise Communities

Changes in Poverty, 

Unemployment, and 

Economic Growth

Our analyses showed improvements in the Chicago EZ in the poverty and 

unemployment rates, but not in economic growth. Both the EZ and its 

comparison area saw a decrease in poverty from 1990 to 2000. The EZ also 

experienced a decrease in unemployment that was considerably greater 

than that of its comparison area in that time period. In terms of economic 

growth, the Chicago EZ and its comparison area saw decreases in the 

numbers of businesses and jobs between 1995 and 2004, with the EZ seeing 

a larger decline in the number of jobs but less of a decline in the number of 

businesses than its comparison area. Tables 17 and 18 show the changes in 

poverty, unemployment, and economic growth in the EZ and its 

comparison area. Table 17 also includes data on the changes in other 

variables included in our models.

Table 17: Changes in Selected Census Variables Observed in the Chicago EZ and Its Comparison Area

Source: GAO analysis of Census data.

Note: There are 96 census tracts in the designated area and 146 in the comparison area. Estimates for 

all census variables based on percentages had 95 percent confidence intervals of plus or minus 5 

percentage points or less. For the confidence intervals for average household income and average 

owner-occupied housing estimates, see appendix I.

a

Differences in poverty rate, unemployment rate, and other variables shown as percentages are based 

upon percentage point differences. Differences for average household income, population, individuals 

per square mile, and average housing value are calculated as percent changes. 

b

The change in estimates from 1990 to 2000 is statistically significant.

1990 2000 Percent changea

EZ Comparison EZ Comparison EZ Comparison

Poverty rate (%) 49.10 40.38 39.32 33.49 -9.77 b -6.89b

Unemployment rate (%) 24.57 20.52 19.34 18.97 -5.23 b -1.54b

Average household income $23,097 $28,431 $34,718 $39,985 50.31b 40.64b

Percentage of single female headed households 

with children 25.64 23.07 21.59 19.69 -4.05b -3.38b

Total population 200,182 377,580 177,309 369,343 -11.43 -2.18

Total individuals per square mile 13,967 15,523 12,380 15,752 -11.36 1.47

Percentage of households that moved in the last 5 

years 37.52 40.03 39.21 39.68 1.69b -0.35

Percentage of population of working age (16-64) 53.51 57.87 55.63 59.53 2.12b 1.66b

Percentage of population with a high school diploma 

(or equivalent) 44.04 54.24 54.30 63.58 10.26b 9.35b

Percentage of high school dropouts 22.46 19.50 22.05 15.23 -0.41 -4.27 b

Percentage of vacant housing units 19.69 13.54 18.23 12.44 -1.45b -1.1b

Average owner occupied housing value $71,429 $88,445 $160,412 $167,015 124.57b 88.83b
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 99 GAO-06-727 Empowerment Zones and Enterprise Communities

Table 18: Changes in Selected Economic Growth Variables Observed in the Chicago EZ and Its Comparison Area

Source: GAO analysis of Claritas data.

Note: There are 96 census tracts in the designated area and 146 in the comparison area. We excluded 

establishments that were not eligible for program tax benefits, such as nonprofit and governmental 

organizations, from our analysis of the change in the number of businesses. However, we included 

jobs at those businesses in our analysis of the change in the number of jobs.

a

Differences for the number of businesses and the number of jobs are calculated as percent changes. 

Stakeholder Perceptions of 

the Factors Influencing 

Changes in Poverty, 

Unemployment, and 

Economic Growth

Asked about factors influencing the change in poverty, stakeholders 

pointed to both EZ activities and external factors. Among the EZ activities 

they cited were projects promoting homeownership or providing 

educational training. However, some stakeholders mentioned changes in 

the EZ population as an external factor that may have affected the changes 

in poverty, noting the demolition of several public housing buildings in the 

EZ and the addition of individuals with higher incomes moving into new 

housing built on those sites. 

Some stakeholders attributed a decrease in unemployment to the zone’s 

focus on creating jobs and the requirement that subgrantees demonstrate 

that they had created jobs for EZ residents. Some stakeholders also noted 

that the EZ’s provision of services, such as childcare, after-school 

programs, and job training, provided opportunities for more residents to 

obtain jobs. But some stakeholders believed that the decreases in 

unemployment were due to external economic forces, such as changes in 

the population of the EZ and more jobs available due to changes in the 

national economy. 

In terms of economic growth, some EZ stakeholders observed that the EZ 

had provided some initial investment in the zone and that private 

investment had followed. However, some stakeholders noted that the EZ 

had not done enough in the area of economic development. In addition, 

stakeholders said that not all the jobs from new businesses in the zone had 

gone to zone residents and that the number of new businesses did not meet 

the zone’s employment needs. 

1995 1999 2004

Percent change 1995-

2004a

EZ Comparison EZ Comparison EZ Comparison EZ Comparison

Number of businesses 5,089 10,567 4,614 9,582 4,496 9,211 -11.65 -12.83

Number of jobs 83,935 183,369 80,294 169,741 69,767 162,541 -16.88 -11.36
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 100 GAO-06-727 Empowerment Zones and Enterprise Communities

Detroit Empowerment 

Zone 

Figure 19: Map of the Detroit EZ and Its Comparison Area

How the EZ Was Governed The nonprofit Detroit Empowerment Zone Development Corporation ran 

the Detroit EZ and included an executive committee, a board made up of 

residents and other local officials, and three neighborhood review panels 

representing neighborhoods in the EZ. Each review panel had an advisory 

role in determining how a portion of the EZ funds would be spent. The EZ 

was required to obtain the approval of the Detroit City Council and Mayor 

for many EZ-funded activities. 

EZ

Comparison areas

Detroit city limits

Canada

Detroit River

Lake St. Clair

0 3.5 7

miles

Michigan 

Detroit 

The Detroit EZ 

encompassed three 

different areas in Detroit: 

Central, East, and 

Southwest.

Source: GAO analysis of Census and HUD data.
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 101 GAO-06-727 Empowerment Zones and Enterprise Communities

Activities the EZ 

Implemented

The Detroit EZ implemented mostly community development activities. 

The two most common types of activities were in the areas of human 

services and education (fig. 20). In addition, EZ stakeholders explained that 

the EZ had helped to spur housing development in the east and southwest 

areas of the zone by providing funds to community development 

corporations. Detroit EZ stakeholders also highlighted a business façade 

improvement program during our tour of the EZ. Although they focused 

mainly on community development, the Detroit EZ did implement some 

economic opportunity activities. Some EZ stakeholders said that the 

Financial Institutions Consortium, which set lending goals within the EZ, 

had helped EZ businesses. The Detroit EZ did not request a grant extension 

because it had used nearly all of the EZ grant funds.
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 102 GAO-06-727 Empowerment Zones and Enterprise Communities

Figure 20: Activities Implemented by the Detroit EZ

0

5

10

15

20

25

Bagley Housing, which participated in the EZ’s façade improvement program, 

also used EZ funds for new housing construction. 

4% 

11% 

85% 

Detroit, MI 

Community-based partnerships

Economic opportunity 

Community development 

Number of activities

Sources: GAO (photo); GAO analysis of HUD data (charts).

Activities

Health

Environment

Infrastructure

Education

Workforce

development

Human

services

Capacity

building

Businesses

assisted

Public

safety

Housing
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 103 GAO-06-727 Empowerment Zones and Enterprise Communities

Changes in Poverty, 

Unemployment, and 

Economic Growth

The Detroit EZ experienced positive changes in poverty, unemployment, 

and one measure of economic growth. Of the urban EZs, the Detroit EZ had 

the largest decrease in poverty and the second largest decrease in 

unemployment from 1990 to 2000. Although the decrease in the EZ was 

slightly greater than in its comparison area in poverty, the decrease in 

unemployment was less than in its comparison area. Between 1995 and 

2004, the EZ generally fared better than its comparison area in our 

measures of economic growth; however, the changes were not always 

positive. The number of businesses declined slightly, but the decrease was 

notably smaller than the decline in its comparison area. In addition, the EZ 

saw a greater increase in the number of jobs than in either its comparison 

area or most urban EZs. Tables 19 and 20 show the changes in poverty, 

unemployment, and economic growth in the EZ and its comparison area. 

Table 19 also includes data on the changes in other variables included in 

our models.

Table 19: Changes in Selected Census Variables Observed in the Detroit EZ and Its Comparison Area

Source: GAO analysis of Census data.

Note: There are 49 census tracts in the designated area and 86 in the comparison area. Estimates for 

all census variables based on percentages had 95 percent confidence intervals of plus or minus 5 

percentage points or less. For the confidence intervals for average household income and average 

owner-occupied housing estimates, see appendix I.

1990 2000 Percent changea

EZ Comparison EZ Comparison EZ Comparison

Poverty rate (%) 47.63 42.72 36.73 32.38 -10.90b -10.34b

Unemployment rate (%) 28.41 26.01 18.83 15.54 -9.58 b -10.47 b

Average household income $22,644 $25,609 $33,751 $36,200 49.05b 41.36b

Percentage of single female headed households with children 17.30 20.94 15.88 18.77 -1.43 -2.18b

Total population 103,346 256,371 88,707 229,536 -14.16 -10.47

Total individuals per square mile 5,547 6,923 4,762 6,200 -14.15 -10.45

Percentage of households that moved in the last 5 years 40.80 37.39 42.20 38.47 1.40 1.08

Percentage of population of working age (16-64) 57.65 56.96 60.34 57.01 2.69b 0.05

Percentage of population with a high school diploma (or 

equivalent) 49.34 53.63 58.06 60.87 8.72b 7.24b

Percentage of high school dropouts 23.29 20.47 20.83 18.89 -2.46b -1.57b

Percentage of vacant housing units 18.26 11.22 17.46 13.98 -0.79 2.76b

Average owner occupied housing value $23,114 $28,598 $52,234 $61,160 125.99b 113.86b
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 104 GAO-06-727 Empowerment Zones and Enterprise Communities

a

Differences in poverty rate, unemployment rate, and other variables shown as percentages are based 

upon percentage point differences. Differences for average household income, population, individuals 

per square mile, and average housing value are calculated as percent changes. 

b

The change in estimates from 1990 to 2000 is statistically significant.

Table 20: Changes in Selected Economic Growth Variables Observed in the Detroit EZ and Its Comparison Area

Source: GAO analysis of Claritas data.

Note: There are 49 census tracts in the designated area and 86 in the comparison area. We excluded 

establishments that were not eligible for program tax benefits, such as nonprofit and governmental 

organizations, from our analysis of the change in the number of businesses. However, we included 

jobs at those businesses in our analysis of the change in the number of jobs.

a

Differences for the number of businesses and the number of jobs are calculated as percent changes. 

Stakeholder Perceptions of 

the Factors Influencing 

Changes in Poverty, 

Unemployment, and 

Economic Growth

An EZ stakeholder said that the population of the zone had changed, 

possibly affecting the changes in the poverty rate. For example, the 

stakeholder noted that many of the initial EZ residents had moved out of 

the zone since designation, and that other individuals with higher incomes 

had moved into the zone. 

Stakeholders noted that EZ programs in job training, youth education, 

supportive services, and health care had helped some EZ residents to gain 

employment. However, some stakeholders also mentioned the lack of a 

skilled workforce in the EZ and the need for more job training. In addition, 

some stakeholders thought that the changes in the zone’s population might 

also have influenced the change in unemployment.

In terms of economic growth, EZ stakeholders noted that their façade 

improvement program had contributed to business growth in the EZ. One 

stakeholder also suggested that the EZ tax benefits and financing from the 

Financial Institutions Consortium had provided incentives to attract 

businesses to locate in the EZ. Another stakeholder mentioned external 

challenges to economic growth that included the loss of the automobile 

industry and the poor national economy over the time period of the EZ. 

1995 1999 2004

Percent change 1995-

2004a

EZ Comparison EZ Comparison EZ Comparison EZ Comparison

Number of businesses 3,723 5,343 3,650 5,282 3,621 4,770 -2.74 -10.72

Number of jobs 95,172 86,500 99,480 73,770 124,172 66,179 30.47 -23.49
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 105 GAO-06-727 Empowerment Zones and Enterprise Communities

New York 

Empowerment Zone 

Figure 21: Map of the New York EZ and Its Comparison Area

How the EZ Was Governed The New York EZ was governed by three boards: an overarching board and 

two subzone boards representing the Upper Manhattan and Bronx 

neighborhoods. The overarching board, which included officials from the 

EZ

Comparison areas

New York city limits

0 1.5 3

miles

East River 

Hudson River 

Bronx 

Brooklyn 

Upper 

Manhattan 

Queens

New York New York 

New Jersey 

The New York EZ was

made up of four 

neighborhoods in Upper 

Manhattan—East Harlem, 

Central Harlem, and 

Washington Heights and 

parts of Inwood—and the 

Southern portion of the 

Bronx borough. 

Source: GAO analysis of Census and HUD data.
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 106 GAO-06-727 Empowerment Zones and Enterprise Communities

city, state, and each subzone board, as well as local congressional 

representatives, provided final funding approval for all EZ projects.3

However, the program was managed locally by the two subzones, which 

had separate management organizations, boards, and budgets and made 

decisions about the activities that would be funded and the organizations 

that would implement them. The Upper Manhattan subzone received the 

bulk of the EZ grant ($83 million), and the Bronx portion received the 

remaining $17 million. The New York EZ also received matching funds from 

the city and state, bringing the total funding for the EZ to $300 million.

The EZ created the nonprofit Upper Manhattan Empowerment Zone to 

manage the Upper Manhattan portion of the zone. This EZ is governed by a 

board that includes community members, at-large members selected for 

their expertise, and representatives from city community planning boards. 

The board also has seven committees. Activities proposed in this portion of 

the EZ were reviewed by the committees, approved by the Upper 

Manhattan board, and finally approval by the overarching EZ board. 

The Bronx Overall Economic Development Corporation, a part of the 

Bronx Borough President’s office, managed the Bronx portion of the New 

York EZ. The board of the Bronx Overall Economic Development 

Corporation covered both EZ and non-EZ activities but included an EZ 

committee. Although the board did not include any EZ residents, an EZ 

stakeholder explained that it included some residents of other areas of the 

Bronx. In general, the board decided on activities, encouraged local 

nonprofits to submit proposals, and chose the organizations to implement 

the activities. Then the activities went before the New York EZ board for 

final approval. 

Activities the EZ 

Implemented 

Unlike most EZs, both portions of the New York EZ implemented more 

economic opportunity activities than community development activities. 

However, the Upper Manhattan and Bronx portions of the EZ differed 

somewhat in the types of activities they implemented. The New York EZ as 

a whole received a grant extension until 2009.

The types of activities most commonly implemented by the Upper 

Manhattan portion were assistance to businesses, workforce development, 

3

The overarching board also included a nonvoting HUD official.
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 107 GAO-06-727 Empowerment Zones and Enterprise Communities

access to capital, and infrastructure (fig. 22). Several EZ stakeholders 

mentioned the business developments in Harlem USA or along 125th Street 

as major accomplishments of their program. Stakeholders also noted that 

the EZ had assisted small businesses, successfully sponsored a restaurant 

initiative that provided local restaurants with loan capital and technical 

assistance, and facilitated the use of an EZ tax-exempt bond to finance a 

new car dealership. In addition, an EZ stakeholder said that the EZ fostered 

job growth by requiring recipients of EZ grants and loans to employ a 

certain number of EZ residents.
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 108 GAO-06-727 Empowerment Zones and Enterprise Communities

Figure 22: Activities Implemented by the Upper Manhattan portion of the New York EZ

0

3

6

9

12

15

Housing

The Upper Manhattan portion of the New York EZ provided the initial funding for Harlem USA, a

shopping mall located on 125th Street. EZ officials credit this project as being a catalyst for other 

investment in the area. 

5%

59%

37%

Upper Manhattan 

New York, NY 

Community-based partnerships

Economic opportunity 

Community development 

Number of activities

Sources: GAO (photo); GAO analysis of HUD data (charts).

Activities

Health

Governance

board

Infrastructure

Wor

Education

kforce

development

Capacity

building

Access to

capital

Businesses

assisted

Other

programs/

projects

Public

safety

Housing

Other
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 109 GAO-06-727 Empowerment Zones and Enterprise Communities

The types of activities most commonly implemented by the Bronx portion 

of the New York EZ included workforce development, education, access to 

capital, and human services (fig. 23). EZ stakeholders explained that the EZ 

had funded several workforce training activities, such as a program to train 

women to become childcare providers. However, several stakeholders also 

said that as the program progressed more funds were used to provide loans 

to EZ businesses, an activity that was felt to provide the best return on 

investment. 
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 110 GAO-06-727 Empowerment Zones and Enterprise Communities

Figure 23: Activities Implemented by the Bronx portion of the New York EZ

0

1

2

3

4

5

6

The Bronx portion of the New York EZ provided grants to this organization to provide training 

for EZ residents to become childcare providers. 

60% 

40% 

Bronx 

New York, NY 

Economic opportunity 

Community development 

Number of activities

Sources: GAO (photo); GAO analysis of HUD data (charts).

Activities

Wor

Education

kforce

development

Human

services

Access to

capital

Businesses

assisted

Other

programs/

projects

Other
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 111 GAO-06-727 Empowerment Zones and Enterprise Communities

Changes in Poverty, 

Unemployment, and 

Economic Growth

Overall, the New York EZ saw poverty fall and economic growth improve, 

but unemployment increase. The changes in the Upper Manhattan portion 

of the EZ followed this pattern, but the Bronx portion of the EZ also 

showed a decrease in one of the measures of economic growth, the number 

of total jobs. Tables 21 and 22 show the changes in poverty, unemployment, 

and economic growth in the EZ, the Upper Manhattan and Bronx portions 

of the EZ, and the EZ comparison area. Table 21 also includes data on the 

changes in other variables included in our models.

Indicators for the Upper Manhattan portion of the New York EZ were 

mixed compared with the New York comparison area. The poverty rate in 

the Upper Manhattan portion of the EZ fell between 1990 and 2000, while 

the unemployment rate stayed the same. The New York comparison area 

stayed about the same in poverty, and its unemployment rate rose. In 

economic growth, between 1995 and 2004 the Upper Manhattan portion of 

the EZ had the largest increase in total number of businesses and the 

second-largest increase in jobs of any urban EZ. The comparison area saw 

a slightly smaller increase in businesses and a larger increase in jobs.

Like the Upper Manhattan portion of the New York EZ, the Bronx portion 

showed mixed results relative to the New York comparison area. Its 

poverty rate stayed the same between 1990 and 2000 as did the New York 

comparison area. Between 1990 and 2000, it experienced a greater increase 

in unemployment than the New York comparison area. In terms of 

economic growth, the area did show an increase in the number of 

businesses from 1995 to 2004, but its comparison area showed a larger 

increase. However, in the same time period, the Bronx experienced a slight 

decrease in the number of jobs, while the comparison area experienced a 

large increase. 
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 112 GAO-06-727 Empowerment Zones and Enterprise Communities

Table 21: Changes in Selected Census Variables Observed in the New York EZ, the Bronx and Upper Manhattan (UM) Portions, 

and the EZ Comparison Area (Comp.)

Source: GAO analysis of Census data.

Note: There are 65 census tracts in the designated area and 160 in the comparison area. Estimates for 

all census variables based on percentages had 95 percent confidence intervals of plus or minus 5 

percentage points or less. For the confidence intervals for average household income and average 

owner-occupied housing estimates, see appendix I.

1990 2000 Percent changea

Entire 

EZ Bronx UM Comp.

Entire 

EZ Bronx UM Comp.

Entire 

EZ Bronx UM Comp.

Poverty rate (%) 42.68 44.2 42.38 42.5 38.62 41.59 38.02 41.75 -4.07b -2.61 -4.35b -0.75

Unemployment 

rate (%) 17.45 15.36 17.86 17.17 19.46 20.96 19.18 20.04 2.00b 5.6b 1.32 2.87b

Average 

household 

income $26,518 $26,294 $26,559 $26,993 $33,557 $30,842 $34,041 $31,247 26.54b 17.29b 28.17b 15.76b

Percentage of 

single female 

headed 

households with 

children 20.19 25.55 19.2 25.91 19.6 23.15 18.97 25.26 -0.59 -2.40b -0.23 -0.64

Total population 199,983 34,266 165,717 638,776 219,324 36,886 182,438 672,826 9.67 7.65 10.09 5.33

Total individuals 

per square mile 31,890 11,651 49,763 58,404 35,286 12,553 55,672 67,150 10.65 7.73 11.88 14.97

Percentage of 

households that 

moved in the last 

5 years 31.93 31.96 31.93 32.5 34.07 33.4 34.2 33.64 2.14b 1.45 2.28b 1.15b

Percentage of 

population of 

working age (16-

64) 59.67 60.09 59.59 58.97 61.3 60.36 61.49 58.49 1.63b 0.28 1.9b -0.48

Percentage of 

population with a 

high school 

diploma (or 

equivalent) 47.74 44.43 48.37 48.4 55.16 51.25 55.9 51.66 7.42b 6.82b 7.53b 3.26b

Percentage of 

high school 

dropouts 19.85 18.12 20.19 20.18 15.59 17.75 15.2 17.7 -4.26b -0.37 -4.99b -2.48b

Percentage of 

vacant housing 

units 8.81 3.24 9.77 3.99 11.09 7.35 11.73 5.99 2.28b 4.11 b 1.96b 2.00b

Average owner 

occupied 

housing value $207,544 $99,728 $238,864 $177,446 $301,835 $124,588 $384,155 $209,423 45.43b 24.93b 60.83b 18.02b
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 113 GAO-06-727 Empowerment Zones and Enterprise Communities

a

Differences in poverty rate, unemployment rate, and other variables shown as percentages are based 

upon percentage point differences. Differences for average household income, population, individuals 

per square mile, and average housing value are calculated as percent changes. 

b

The change in estimates from 1990 to 2000 is statistically significant.
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 114 GAO-06-727 Empowerment Zones and Enterprise Communities

Table 22: Changes in Selected Economic Growth Variables Observed in the New 

York EZ, the Bronx and Upper Manhattan (UM) Portions, and the EZ Comparison 

Area (Comp.)

1995

Entire EZ Bronx UM Comp.

Number of businesses 5,415 1,738 3,677 8,294

Number of jobs 96,228 32,243 63,985 108,785
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 115 GAO-06-727 Empowerment Zones and Enterprise Communities

Source: GAO analysis of Claritas data.

Note: There are 65 census tracts in the designated area and 160 in the comparison area. We excluded 

establishments that were not eligible for program tax benefits, such as nonprofit and governmental 

organizations, from our analysis of the change in the number of businesses. However, we included 

jobs at those businesses in our analysis of the change in the number of jobs.

a

Differences for the number of businesses and the number of jobs are calculated as percent changes. 

Stakeholder Perceptions of 

the Factors Influencing 

Changes in Poverty, 

Unemployment, and 

Economic Growth

Many Upper Manhattan stakeholders we interviewed attributed the change 

in poverty to the higher incomes from the jobs the EZ helped create. In 

addition, several stakeholders discussed changes in the zone’s population, 

as low-income residents were displaced by increases in property values 

and rental costs and employed residents with higher incomes moved into 

the area. One stakeholder attributed some of the decrease in poverty to 

welfare reform. 

For unemployment, some stakeholders said that it was difficult to improve 

the unemployment rate in the Upper Manhattan portion of the EZ due to a 

lack of residents with needed job skills. Stakeholders also noted that the 

change in the zone’s population had affected unemployment as well as 

poverty.

Several stakeholders observed that the Upper Manhattan EZ had helped 

foster economic growth, citing its role in the creation of retail areas and 

real estate development as examples. They also said that it had helped 

small businesses by providing technical assistance, training, and loans. 

Bronx stakeholders noted that the program had helped to influence poverty 

and unemployment through the resident employment requirements it had 

for businesses that received loans and the center it had created to match 

residents to jobs. However, some EZ stakeholders said that the EZ had had 

trouble getting EZ residents jobs, since there were few residents living in 

the Bronx portion of the EZ and many of them lacked necessary job skills. 

Further affecting the changes in poverty and unemployment, one 

1999 2004 Percent change 1995-2004a

Entire EZ Bronx UM Comp. Entire EZ Bronx UM Comp. Entire EZ Bronx UM Comp.

6,203 1,750 4,453 9,400 6,691 1,840 4,851 10,719 23.6 5.87 31.9 29.2

101,462 28,696 72,766 122,447 121,550 30,137 91,413 162,360 26.3 -6.53 42.9 49.3
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 116 GAO-06-727 Empowerment Zones and Enterprise Communities

stakeholder perceived that some original EZs residents had relocated and 

that new residents had moved into the EZ. 

Bronx stakeholders also said that access to capital for businesses resulted 

in an increase in businesses moving into the EZ, but one stakeholder noted 

that few jobs had been created. Another stakeholder said that some zone 

businesses were downsizing as a result of changes in the national economy.

Philadelphia-Camden 

Empowerment Zone

Figure 24: Map of the Philadelphia-Camden EZ and Its Comparison Area

0 2.5 5 

miles

Philadelphia 

Camden 

The Philadelphia-Camden 

EZ was made up of three 

Philadelphia

neighborhoods—American 

Street, North Central, 

and West Philadelphia—

and part of the city of 

Camden located near the 

Delaware River. 

New Jersey 

Pennsylvania

Delaware River 

EZ

Comparison areas

Philadelphia and Camden city limits

Source: GAO analysis of Census and HUD data.
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 117 GAO-06-727 Empowerment Zones and Enterprise Communities

How the EZ Was Governed Although Philadelphia and Camden were designated as one EZ and their 

original strategic plan envisioned a central board to oversee the EZ 

operations, the Philadelphia and Camden portions operated completely 

independently. Of the $100 million EZ grant, the Philadelphia portion of the 

EZ received about $79 million, and the Camden portion of the EZ received 

about $21 million.

The Philadelphia Empowerment Zone Office that oversees the EZ program 

is part of the city government. The EZ created three subzones, each of 

which had its own Community Trust Board to identify the needs of the 

community, select activities to implement, and allocate resources to the 

activities. However, the EZ did not create an overarching board to oversee 

the three Philadelphia subzones. To select entities to implement activities, 

the EZ issued requests for proposals. A panel of community members, 

experts, and officials selected the best applications, and the city approved 

the funding. The mayor required that more than half of EZ/EC grant be 

spent on economic development (including job training) and retained the 

right to veto decisions by the Community Trust Boards, although this rarely 

happened.

The Camden portion of the EZ was managed by a nonprofit entity called the 

Camden Empowerment Zone Corporation and was governed by a board, 

which included residents as well as “block captains” who were residents 

that had been elected to represent their communities, and other individuals 

from the business, cultural, religious, and nonprofit community.4

 Under the 

board, there was a subcommittee structure. The EZ issued requests for 

proposals to identify organizations to implement the programs, which were 

reviewed by a subcommittee and then forwarded to the full board for 

approval. 

Activities the EZ 

Implemented

Both portions of the Philadelphia-Camden EZ implemented more 

community development activities than economic opportunity activities. 

Officials from the Philadelphia portion of the EZ explained that, while they 

spent more than half of their program grant funding on economic 

development as required by their mayor, the number of community 

4

The Camden portion of the EZ was initially managed by the city of Camden, but HUD 

officials fostered the change to a nonprofit to deal with tensions between the city of Camden 

and state of New Jersey. 
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 118 GAO-06-727 Empowerment Zones and Enterprise Communities

development programs implemented was greater than the number of 

economic opportunity programs. In addition, both portions of the EZ 

received grant extensions until 2009. 

Activities related to education, access to capital, and assisting businesses 

were the most common in the Philadelphia portion of the PhiladelphiaCamden EZ (fig. 25). The two activities most often cited by stakeholders in 

our interviews were the program to clean up vacant lots and the 

community lending institutions. EZ stakeholders also noted that the EZ had 

helped to organize the business community in each neighborhood. 
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 119 GAO-06-727 Empowerment Zones and Enterprise Communities

Figure 25: Activities Implemented by the Philadelphia Portion of the Philadelphia-Camden EZ

The activities most frequently implemented in the Camden portion of the 

EZ were housing, capacity building, access to capital, and infrastructure 

(fig. 26). In addition, most EZ stakeholders described the U.S.S. New 

0

3

6

9

12

15

The American Street subzone of the Philadelphia-Camden EZ provided the business Cantol 

with a loan that enabled it to relocate to the city of Philadelphia. 

6%

28%

66%

Philadelphia, PA 

Community-based partnerships

Economic opportunity

Community development

Number of activities

Sources: GAO (photo); GAO analysis of HUD data (charts).

Activities

Health

Environment

Infrastructure

Education

Workforce

development

Governance

board

Human

services

Capacity

building

Access to

capital

Businesses

assisted

Other

programs/

projects

Public

safety

Housing

Other
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 120 GAO-06-727 Empowerment Zones and Enterprise Communities

Jersey, a new tourist attraction for which the EZ funded a portion of the 

application and the visitors’ center, as a success of the EZ program. During 

our interviews, stakeholders also pointed out activities such as a summer 

youth program, the refurbishing of a local park, physical improvements to 

the streets and sidewalks, and an EZ program designed to make loans and 

grants to EZ businesses. 
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 121 GAO-06-727 Empowerment Zones and Enterprise Communities

Figure 26: Activities Implemented by the Camden Portion of the Philadelphia-Camden EZ

Changes in Poverty, 

Unemployment, and 

Economic Growth

Overall, the Philadelphia-Camden EZ was the only urban EZ to see positive 

changes in poverty, unemployment, and both measures of economic 

growth. However, changes in the Philadelphia and Camden portions varied, 

0

2

4

6

8

10

The Camden portion of the Philadelphia-Camden EZ provided the initial funds for the application 

to attract the U.S.S. New Jersey to encourage tourism along the Camden waterfront. The EZ 

also provided funds to build the visitor’s center for the battleship. 

20%

22% 58%

Camden, NJ 

Community-based partnerships

Economic opportunity

Community development

Number of activities

Sources: GAO (photo); GAO analysis of HUD data (charts).

Activities

Health

Environment

Governance

board

Infrastructure

Education

Workforce

development

Human

services

Capacity

building

Access to

capital

Businesses

assisted

Public

safety

Housing
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 122 GAO-06-727 Empowerment Zones and Enterprise Communities

and were not always positive. Tables 23 and 24 show the changes in 

poverty, unemployment, and economic growth in the EZ, the Philadelphia 

and Camden portions of the EZ, and the EZ comparison area. Table 23 also 

includes data on the changes in other variables included in our models.

The Philadelphia portion of the EZ experienced decreases in poverty and 

unemployment and little change or a decrease in our measures of economic 

growth. Its declines in the poverty and unemployment rates from 1990 to 

2000 outpaced those in the Philadelphia-Camden comparison area.5

 In 

economic growth, the Philadelphia portion of the EZ experienced little 

change in the number of businesses between 1995 and 2004, while its 

comparison area experienced a large increase. Both the Philadelphia 

portion of the EZ and the EZ comparison area saw a similar decline in the 

number of jobs available. 

In contrast, the Camden portion of the Philadelphia-Camden EZ 

experienced little change in poverty or the unemployment rate, but it 

experienced positive changes in both measures of economic growth. Its 

poverty rate from 1990 to 2000 stayed about the same, while its comparison 

area decreased. Both the Camden portion of the EZ and the EZ comparison 

area saw little change in the unemployment rate. For economic growth, the 

Camden portion of the EZ had one of the highest increases in the number 

of businesses of any EZ from 1995 to 2004, slightly better than its 

comparison area. It also saw a large increase in the number of jobs. In 

contrast, the EZ comparison area experienced a large decline in number of 

jobs over the same time period.

5

All tracts that qualified as comparison tracts for Philadelphia-Camden were located in 

Philadelphia. 
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 123 GAO-06-727 Empowerment Zones and Enterprise Communities

Table 23: Changes in Selected Census Variables Observed in the Philadelphia-Camden EZ, the Camden (Cam.) and Philadelphia 

(Phila.) Portions, and the EZ Comparison Area (Comp.)

Source: GAO analysis of Census data.

Note: There are 18 census tracts in the designated area and 16 in the comparison area. Estimates for 

all census variables based on percentages had 95 percent confidence intervals of plus or minus 5 

percentage points or less. For the confidence intervals for average household income and average 

owner-occupied housing estimates, see appendix I.

a

Differences in poverty rate, unemployment rate, and other variables shown as percentages are based 

upon percentage point differences. Differences for average household income, population, individuals 

per square mile, and average housing value are calculated as percent changes. 

b

The change in estimates from 1990 to 2000 is statistically significant.

1990 2000 Percent change a

Entire 

EZ Cam. Phila. Comp.

Entire 

EZ Cam. Phila. Comp.

Entire 

EZ Cam. Phila. Comp.

Poverty rate (%) 50.14 43 52.1 43.07 42.98 40.55 43.68 37.97 -7.16b -2.45 -8.42b -5.1b

Unemployment rate 

(%) 22.21 18.09 23.6 18.81 19.3 19.08 19.38 17.91 -2.91b 0.99 -4.22b -0.9

Average household 

income $23,188 $26,742 $22,269 $27,292 $28,562 $31,158 $27,851 $31,318 23.17b 16.52b 25.07b 14.8b

Percentage of 

single female 

headed households 

with children 22.73 24.13 22.37 21.01 21.93 23.22 21.57 20.66 -0.81 -0.92 -0.8 -0.36

Total population 52,440 13,332 39,108 38,520 45,725 12,749 32,976 35,827 -12.81 -4.37 -15.68 -6.99

Total individuals per 

square mile 12,248 7,342 15,861 7,601 10,698 7,034 13,396 7,064 -12.66 -4.2 -15.54 -7.06

Percentage of 

households that 

moved in the last 5 

years 34.71 41.93 32.25 40.69 34.05 44.42 30.04 44.05 -0.66 2.49 -2.21 3.36b

Percentage of 

population of 

working age (16-64) 57.58 63.02 55.72 59.76 58.85 66.86 55.75 61.93 1.27 3.84b 0.03 2.17

Percentage of 

population with a 

high school diploma 

(or equivalent) 42.79 44.51 42.21 54.04 51.82 50.43 52.38 63.19 9.04b 5.92b 10.17b 9.15b

Percentage of high 

school dropouts 25.58 22.67 26.56 23.07 16.02 12.54 17.25 14.05 -9.56b -10.13b -9.3b -9.02b

Percentage of 

vacant housing 

units 21.45 22.37 21.21 14.48 24.94 25.7 24.73 14.91 3.49b 3.33b 3.52b 0.43

Average owner 

occupied housing 

value $29,899 $35,076 $28,288 $42,045 $37,780 $39,398 $37,353 $51,159 26.36b 12.32b 32.04b 21.7b
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 124 GAO-06-727 Empowerment Zones and Enterprise Communities

Table 24: Changes in Selected Economic Growth Variables Observed in the 

Philadelphia-Camden EZ, the Camden (Cam.) and Philadelphia (Phila.) Portions, and 

the EZ Comparison Area (Comp.)

1995

Entire EZ Cam. Phila. Comp.

Number of businesses 2,064 730 1,334 2,631

Number of jobs 35,867 14,430 21,437 55,071
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 125 GAO-06-727 Empowerment Zones and Enterprise Communities

Source: GAO analysis of Claritas data.

Note: There are 18 census tracts in the designated area and 16 in the comparison area. We excluded 

establishments that were not eligible for program tax benefits, such as nonprofit and governmental 

organizations, from our analysis of the change in the number of businesses. However, we included 

jobs at those businesses in our analysis of the change in the number of jobs.

a

Differences for the number of businesses and the number of jobs are calculated as percent changes.

Stakeholder Perceptions of 

the Factors Influencing 

Changes in Poverty, 

Unemployment, and 

Economic Growth

Stakeholders in the Philadelphia portion of the EZ mentioned the change in 

the zone’s population as having an effect on the changes in the poverty and 

unemployment rates. They noted that the number of poor households had 

decreased, in part due to the HOPE VI housing program, which had 

demolished some area public housing, and in part because some 

individuals who had obtained jobs had also moved out of the zone 

neighborhoods. In addition, some stakeholders noted that the change in 

welfare policy over the course of the EZ/EC program had an effect on 

poverty and unemployment by moving former welfare recipients into jobs. 

In describing the changes in economic growth, Philadelphia stakeholders 

said that community lending institutions had provided loans to businesses 

and that the vacant lot improvement program had helped retain and attract 

businesses to the EZ. However, one stakeholder noted that EZ lending had 

not resulted in many new jobs. 

EZ stakeholders in the Camden portion of the EZ said that EZ programs 

such as the Battleship New Jersey and housing and after school initiatives 

may have contributed to the slight decrease in poverty rate. They also 

noted that there had probably been a change in the EZ population, since 

Camden’s population was transient and individuals often left the area when 

they found a job. In addition, some stakeholders also mentioned changes in 

the national economy and a high homeless population as challenges to 

improving the area’s poverty and unemployment rates. 

1999 2004 Percent change 1995-2004a

Entire EZ Cam. Phila. Comp. Entire EZ Cam. Phila. Comp. Entire EZ Cam. Phila. Comp.

2,078 720 1,358 2,768 2,150 806 1,344 2,821 4.17 10.41 0.75 7.22

35,904 16,702 19,202 53,702 36,789 21,032 15,757 39,720 2.57 45.75 -26.5 -27.87
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 126 GAO-06-727 Empowerment Zones and Enterprise Communities

Camden stakeholders noted that the EZ had influenced economic growth 

through the improvements it had made to the physical appearance of 

certain commercial corridors, as well as through its loans and grants to 

small businesses. Stakeholders also said that the development of marketrate housing had helped to increase the customer base for local businesses. 

Finally, one stakeholder said that the state’s expansion of the light rail to 

Camden had influenced economic growth by improving transportation to 

the area. 
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 127 GAO-06-727 Empowerment Zones and Enterprise Communities

Cleveland 

Empowerment Zone

Figure 27: Map of the Cleveland EZ and Its Comparison Area

HUD initially designated Cleveland as a Supplemental EZ, which provided 

it with Economic Development Initiative grants and Section 108 Loan 

Guarantees rather than EZ/EC grant funds. The area received full Round I 

EZ status in 1998, and businesses in the EZ could claim the program tax 

benefits starting in 2000.

EZ

Comparison areas

Cleveland city limits

Source: GAO analysis of Census and HUD data.

The Cleveland EZ was

made up of four 

neighborhoods—Midtown, 

Fairfax, Hough, and 

Glenville. The EZ was also 

able to make loans in a

buffer area around the EZ. 

Lake Erie 

0 3 6 

miles

Ohio 

Cleveland 
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 128 GAO-06-727 Empowerment Zones and Enterprise Communities

How the EZ Was Governed The EZ was operated by the city of Cleveland Department of Economic 

Development and included the Community Advisory Committee, an 

advisory board made up of EZ residents, business owners, bank 

representatives, and representatives from four local community 

development corporations. Although the Community Advisory Committee 

was involved in the decision-making process, the mayor and Cleveland City 

Council made all final decisions about EZ funding. 

Activities the EZ 

Implemented

Cleveland EZ stakeholders said that they focused mainly on economic 

development activities, largely because of the type of benefits they 

received with the Supplemental EZ designation.6

 Stakeholders explained 

that most of their funds had been used to fund loans to EZ businesses. They 

also said that the EZ also worked to build the capacity of four community 

development corporations helping each of them complete a major project 

in their neighborhood—for example, the Quincy Place building in the 

Fairfax neighborhood (fig. 28). EZ stakeholders noted that the EZ had 

implemented some successful job training programs. The EZ received an 

extension of its grants and loan guarantees through 2009. 

6

The grants and loan guarantees the EZ received could only be used for certain economic 

development or revitalization projects. When Cleveland received the Supplemental EZ 

instead of the regular EZ designation, the officials modified their strategic plan. 
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 129 GAO-06-727 Empowerment Zones and Enterprise Communities

Figure 28: Activity Implemented by the Cleveland EZ

Note: We were not able to determine specific types of activities the Cleveland EZ implemented, 

because reliable data were not available. 

Changes in Poverty, 

Unemployment, and 

Economic Growth

The Cleveland EZ experienced positive changes in poverty, unemployment, 

and one measure of economic growth. From 1990 to 2000, Cleveland had 

one of the sharpest reductions in both poverty and unemployment of the 

urban EZs, and these changes outpaced those of its comparison area. 

Between 1995 and 2004, the EZ experienced an increase in economic 

growth as measured by the number of businesses, while its comparison 

area experienced a decrease. However, the EZ experienced a decrease in 

the number of jobs that was greater than the decrease experienced in its 

comparison area. Tables 25 and 26 show the changes in poverty, 

unemployment, and economic growth in the EZ and its comparison area. 

Table 25 also includes data on the changes in other variables included in 

our models.

The Cleveland EZ provided part of the financing package for the construction of this community 

center and county office building, which is managed by one of the four Cleveland community 

development corporations, Fairfax Renaissance Development Corporation. 

Cleveland, OH 

Source: GAO.
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 130 GAO-06-727 Empowerment Zones and Enterprise Communities

Table 25: Changes in Selected Census Variables Observed in the Cleveland EZ and Its Comparison Area

Source: GAO analysis of Census data.

Note: There are 32 census tracts in the designated area and 68 in the comparison area. Estimates for 

all census variables based on percentages had 95 percent confidence intervals of plus or minus 5 

percentage points or less. For the confidence intervals for average household income and average 

owner-occupied housing estimates, see appendix I.

a

Differences in poverty rate, unemployment rate, and other variables shown as percentages are based 

upon percentage point differences. Differences for average household income, population, individuals 

per square mile, and average housing value are calculated as percent changes. 

b

The change in estimates from 1990 to 2000 is statistically significant.

Table 26: Changes in Selected Economic Growth Variables Observed in the Cleveland EZ and Its Comparison Area

Source: GAO analysis of Claritas data.

Note: There are 32 census tracts in the designated area and 68 in the comparison area. We excluded 

establishments that were not eligible for program tax benefits, such as nonprofit and governmental 

1990 2000 Percent changea

EZ Comparison EZ Comparison EZ Comparison

Poverty rate (%) 46.85 39.41 36.03 35.70 -10.82b -3.71b

Unemployment rate (%) 25.44 20.63 15.48 17.29 -9.96b -3.34b

Average household income $20,535 $24,688 $28,781 $30,311 40.16b 22.78b

Percentage of single female headed 

households with children 19.07 23.24 18.24 23.19 -0.83 -0.05

Total population 50,724 153,578 43,694 141,465 -13.86 -7.89

Total individuals per square mile 8,319 7,231 7,168 6,532 -13.84 -9.66

Percentage of households that moved in the 

last 5 years 36.13 36.04 39.55 39.70 3.41b 3.66b

Percentage of population of working age

(16-64) 55.01 56.80 53.08 55.54 -1.93 -1.26

Percentage of population with a high school 

diploma (or equivalent) 47.14 54.84 61.82 65.13 14.68b 10.29b

Percentage of high school dropouts 18.35 14.83 13.30 16.38 -5.05b 1.55b

Percentage of vacant housing units 14.68 14.70 18.82 15.13 4.14b 0.43

Average owner occupied housing value $38,071 $46,972 $75,186 $70,164 97.49b 49.37b

1995 1999 2004

Percent change 1995-

2004a

EZ Comparison EZ Comparison EZ Comparison EZ Comparison

Number of businesses 1,766 4,883 2,067 4,889 1,899 4,602 7.53 -5.75

Number of jobs 42,087 87,334 58,679 102,996 38,023 84,064 -9.66 -3.74
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 131 GAO-06-727 Empowerment Zones and Enterprise Communities

organizations, from our analysis of the change in the number of businesses. However, we included 

jobs at those businesses in our analysis of the change in the number of jobs.

a

Differences for the number of businesses and the number of jobs are calculated as percent changes. 

Stakeholder Perceptions of 

the Factors Influencing 

Changes in Poverty, 

Unemployment, and 

Economic Growth

When asked about factors that had affected the changes observed in the 

Cleveland EZ, stakeholders said that factors related to poverty and 

unemployment were intertwined. For example, EZ stakeholders felt that 

EZ training programs had helped prepare residents for jobs, potentially 

affecting both poverty and unemployment. Stakeholders also cited changes 

in the zone population that had affected both factors, noting that as 

residents obtained jobs, they left the zone, and that some individuals with 

higher incomes had moved in, particularly in areas where new housing had 

been built. EZ stakeholders also mentioned the effect of general economic 

trends on poverty and unemployment. 

In terms of economic growth, EZ stakeholders noted that the majority of 

the businesses that had received EZ loans were still operating, that the 

number of businesses had increased in some areas of the EZ, and that these 

businesses had brought new jobs to the community. However, some EZ 

stakeholders commented that the EZ’s strict underwriting standards made 

it less successful in helping new or less sophisticated businesses. In 

addition, although the EZ had helped to create some jobs, some 

stakeholders felt that the jobs created were going to new residents rather 

than to original EZ residents. EZ staff also observed that regional trends 

such as the overall loss of jobs in the city of Cleveland had an effect on 

economic growth in the Cleveland EZ. 
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 132 GAO-06-727 Empowerment Zones and Enterprise Communities

Los Angeles 

Empowerment Zone 

Figure 29: Map of the Los Angeles EZ and Its Comparison Area

EZ

Comparison areas

Los Angeles city limits

The Los Angeles EZ 

covered a vast geographic 

region that included areas

located near the central city,

a separate area located in 

Los Angeles County, and an 

area in the San Fernando 

Valley portion of the city. 

The EZ was also able to 

make loans in a buffer area

around the EZ.

Source: GAO analysis of Census and HUD data.

Pacific Ocean 

0 5 10

miles

California

Los Angeles
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 133 GAO-06-727 Empowerment Zones and Enterprise Communities

HUD initially designated Los Angeles as a Supplemental EZ, which 

provided it with Economic Development Initiative grants and Section 108 

Loan Guarantees rather than EZ/EC grant funds. The area received full 

Round I EZ status in 1998, and businesses in the EZ could claim the 

program tax benefits starting in 2000.

How the EZ Was Governed The Los Angeles EZ created the Los Angeles Community Development 

Bank to administer its EZ program. The Community Development Bank 

was a “wholesale” rather than a conventional bank that entered into 

partnerships with other economic development entities that were already 

delivering services and operating loan programs. The EZ was autonomous 

from the city and had its own board of directors predominately made up of 

private sector members with one seat for a community representative. 

However, EZ stakeholders told us that this seat usually remained vacant. 

The board had a committee structure that included an audit committee, 

credit committee, and venture capital committee. The EZ board made all 

funding decisions. Any transaction over $1 million required full board 

approval, but smaller amounts could be approved by a committee of the 

board. In an effort to involve community members, the city created an 

advisory council called EZ Oversight Committee, which was filled through 

appointments made by the mayor and county board of supervisors. 

However, EZ stakeholders said that the EZ oversight committee never had 

a formal role in decision making or oversight. 

Activities the EZ 

Implemented

Los Angeles EZ stakeholders said that they focused mainly on economic 

development activities, largely due to the type of benefits they received 

with the Supplemental EZ designation.7

 Stakeholders noted that the job 

requirements attached to loans from the EZ and the six tax-exempt bonds 

had helped create jobs in the zone (fig. 30). In addition to providing loans to 

several businesses, the EZ helped fund a shopping complex and other 

development. One stakeholder felt the EZ did not lend enough funds to 

small businesses and pointed out that some of the loans to large 

businesses, such as a large dairy, had defaulted. The EZ bank filed for 

bankruptcy in 2002 due to a high level of loan defaults and the remaining 

7

When Los Angeles received the Supplemental EZ instead of the regular EZ designation, the 

officials modified their strategic plan from having some social service initiatives to focusing 

only on activities directly related to economic development. 
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 134 GAO-06-727 Empowerment Zones and Enterprise Communities

funds were transferred to the city of Los Angeles. The city of Los Angeles 

received an extension for the grant and loan guarantees through 2009.

Figure 30: Activity Implemented by the Los Angeles EZ

Changes in Poverty, 

Unemployment, and 

Economic Growth

Unlike the other EZs, both poverty and unemployment in the Los Angeles 

EZ largely remained the same between 1990 and 2000, and measures of 

economic growth declined from 1995 to 2004. The comparison area also 

saw little change in poverty and unemployment, but economic growth in 

the comparison area increased in that time period. Tables 27 and 28 show 

the changes in poverty, unemployment, and economic growth in the EZ and 

its comparison area. Table 27 also includes data on the changes in other 

variables included in our models.

The American Fish and Seafood Company used an EZ bond to help build a new facility. 

Los Angeles, CA 

Source: GAO.
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 135 GAO-06-727 Empowerment Zones and Enterprise Communities

Table 27: Changes in Selected Census Variables Observed in the Los Angeles EZ and Its Comparison Area

Source: GAO analysis of Census data.

Note: There are 41 census tracts in the designated area and 43 in the comparison area. Estimates for 

all census variables based on percentages had 95 percent confidence intervals of plus or minus 5 

percentage points or less. For the confidence intervals for average household income and average 

owner-occupied housing estimates, see appendix I.

a

Differences in poverty rate, unemployment rate, and other variables shown as percentages are based 

upon percentage point differences. Differences for average household income, population, individuals 

per square mile, and average housing value are calculated as percent changes. 

b

The change in estimates from 1990 to 2000 is statistically significant.

Table 28: Changes in Selected Economic Growth Variables Observed in the Los Angeles EZ and Its Comparison Area

Source: GAO analysis of Claritas data.

Note: There are 41 census tracts in the designated area and 43 in the comparison area. We excluded 

establishments that were not eligible for program tax benefits, such as nonprofit and governmental 

1990 2000 Percent changea

EZ Comparison EZ Comparison EZ Comparison

Poverty rate (%) 40.24 31.52 41.49 33.14 1.25 1.61

Unemployment rate (%) 18.39 15.07 18.61 15.47 0.22 0.40

Average household income $28,801 $34,087 $32,631 $37,843 13.30b 11.02b

Percentage of single female 

headed households with children 18.32 18.64 16.90 17.40 -1.43b -1.24

Total population 211,365 221,657 225,591 219,001 6.73 -1.20

Total individuals per square mile 11,082 12,918 11,836 13,170 6.81 1.95

Percentage of households that 

moved in the last 5 years 46.12 44.06 43.53 41.20 -2.59b -2.86b

Percentage of population of 

working age (16-64) 57.60 58.11 57.53 57.28 -0.06 -0.83

Percentage of population with a 

high school diploma (or equivalent) 38.40 50.30 37.46 49.53 -0.94 -0.77

Percentage of high school dropouts 32.14 23.50 23.09 17.04 -9.04b -6.46b

Percentage of vacant housing units 6.33 6.31 9.65 8.11 3.31b 1.80b

Average owner occupied housing 

value $141,665 $160,090 $156,493 $165,180 10.47b 3.18b

1995 1999 2004

Percent change 1995-

2004a

EZ Comparison EZ Comparison EZ Comparison EZ Comparison

Number of businesses 15,746 4,248 12,315 3,986 13,853 4,662 -12.02 9.75

Number of jobs 165,457 52,973 153,340 55,627 156,793 66,783 -5.24 26.07
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 136 GAO-06-727 Empowerment Zones and Enterprise Communities

organizations, from our analysis of the change in the number of businesses. However, we included 

jobs at those businesses in our analysis of the change in the number of jobs.

a

Differences for the number of businesses and the number of jobs are calculated as percent changes.

Stakeholder Perceptions of 

the Factors Influencing 

Changes in Poverty, 

Unemployment, and 

Economic Growth

Los Angeles EZ stakeholders we interviewed suggested that the EZ was not 

as likely as other factors to have effected changes in poverty and 

unemployment because they could not address those issues directly with 

the benefits they received. One stakeholder did not believe that the EZ had 

met its goals of increasing job training and employment opportunities, but 

other stakeholders believed that it had helped to assist and retain 

businesses and redevelop the area. Stakeholders mentioned external 

factors that influenced changes in poverty and unemployment, such as 

shifts in demographics with the influx of new immigrants and the 

outmigration of EZ residents as they obtained jobs or their incomes 

increased. In addition, some said that the EZ’s high concentration of 

homeless individuals and the lack of available public transportation in the 

EZ could be additional reasons that poverty and unemployment rates did 

not improve. 

One stakeholder noted that, because the original strategic plan was 

designed to focus on social services, the census tracts chosen were not 

well-suited for economic development. However, stakeholders mentioned 

that the EZ had helped to stabilize the area, since a large number of 

businesses had been leaving the Los Angeles area for advantages offered in 

other locations. 
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 137 GAO-06-727 Empowerment Zones and Enterprise Communities

Kentucky Highlands 

Empowerment Zone 

Figure 31: Map of the Kentucky Highlands EZ

How the EZ Was Governed The EZ was managed by the Kentucky Highlands Investment Corporation, 

a nonprofit that had been operating in the area for over 25 years. There 

were subzone boards in each of the three counties that became separate 

nonprofit entities and had funds to hire staff, manage the board, and 

conduct fiscal oversight. An overarching steering committee, which 

included representatives of the subzone boards, directed the EZ’s activities 

in the entire zone by providing oversight, making financial decisions, and 

implementing certain activities, such as the revolving loan fund. EZ 

stakeholders suggested that most of the decision making occurred at the 

subzone level, although the steering committee gave final approval to all 

projects. The EZ used about half of the available funds, and the rest was 

distributed among the three subzones. 

EZ 

Boundaries of counties partially included in the EZ

Virginia

Rockcastle 

McCreary 

Clay 

Cumberland 

Owsley 

Tennessee

Clay 

Clinton

Estill 

Jackson

Laurel 

Lee 

Madison 

Pulaski 

Russell 

Wayne

Pickett 

Scott 

Kentucky

Source: GAO analysis of USDA data.

The Kentucky Highlands

EZ is made up of two full 

counties (Jackson and 

Clinton) and one partial 

county (Wayne). 
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 138 GAO-06-727 Empowerment Zones and Enterprise Communities

Activities the EZ 

Implemented

Almost two-thirds of the EZ’s activities involved community development. 

Initiatives involving business development and job training; resources for 

communities, youth and families; and education were the most common 

activities (fig. 32). In addition, each county implemented different types of 

activities from the strategic plan. For example, stakeholders from the 

Clinton County subzone funded a library, a learning center, and health care 

initiatives—such as helping to fund the expansion of an emergency room 

and surgical wing at the local hospital—and attracted businesses from the 

houseboat industry. Stakeholders from the Jackson County subzone said 

that they had provided funds for a community center, which housed 

vocational training classes and a community theatre. Stakeholders from the 

Wayne County subzone said that they completed a water infrastructure 

project that they said was critical to attracting businesses and brought in 

jobs in the houseboat industry. The Kentucky Highlands EZ received a 

grant extension until 2009. 
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 139 GAO-06-727 Empowerment Zones and Enterprise Communities

Figure 32: Activities Implemented by the Kentucky Highlands EZ

0

1

2

3

4

5

6

The EZ provided the initial investment for the Jackson County Community Center, 

which included a vocational school and community theater. 

9%

27%

64%

Kentucky Highlands, KY 

Community-based partnerships

Economic opportunity

Community development

Number of activities

Sources: GAO (photo); GAO analysis of USDA data (charts).

Activities

Environment

and natural

resources

Education

Business

development/

job training

Community/

youth/family

resources

Capacity

building

Health

care

Public

infrastructure

Tourism

and culture

Public

safety
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 140 GAO-06-727 Empowerment Zones and Enterprise Communities

Changes in Poverty, 

Unemployment, and 

Economic Growth

Not only did the Kentucky Highlands EZ experience positive changes in all 

indicators, it experienced the largest decrease in unemployment between 

1990 and 2000 and the largest increases in the number of businesses and 

jobs between 1995 and 2004 of any rural EZ. Tables 29 and 30 show the 

changes in poverty, unemployment, and economic growth in the EZ. Table 

29 also includes data on the changes in other variables included in our 

models of the urban EZs.

Table 29: Changes in Selected Census Variables Observed in the Kentucky 

Highlands EZ 

Source: GAO analysis of Census data.

Note: There are seven census tracts in the designated area; we did not use comparison areas for rural 

EZs. For more information on our methodology, see appendix I. Estimates for all census variables 

based on percentages had 95 percent confidence intervals of plus or minus 5 percentage points or 

less. For the confidence intervals for average household income and average owner-occupied housing 

estimates, see appendix I.

a

Differences in poverty rate, unemployment rate, and other variables shown as percentages are based 

upon percentage point differences. Differences for average household income, population, individuals 

per square mile, and average housing value are calculated as percent changes. 

b

The change in estimates from 1990 to 2000 is statistically significant.

1990 2000 Percent changea

Poverty rate (%) 37.88 27.76 -10.12b

Unemployment rate (%) 9.76 7.75 -2.01b

Average household income $23,304 $31,064 33.3b

Percentage of single female headed 

households with children 4.64 5.73 1.09

Total population 27,212 30,464 11.95

Total individuals per square mile 36 40 11.96

Percentage of households that 

moved in the last 5 years 32.46 31.45 -1.01

Percentage of population of working 

age (16-64) 59.04 61.98 2.93b

Percentage of population with a high 

school diploma (or equivalent) 42.82 55.1 12.28b

Percentage of high school dropouts 15.80 16.47 0.67

Percentage of vacant housing units 16.74 18.97 2.23b

Average owner occupied housing 

value $43,392 $65,815 51.68b
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 141 GAO-06-727 Empowerment Zones and Enterprise Communities

Table 30: Changes in Selected Economic Growth Variables Observed in the 

Kentucky Highlands EZ 

Source: GAO analysis of Claritas data.

Note: There are seven census tracts in the designated area; we did not use comparison areas for rural 

EZs. For more information on our methodology, see appendix I. We excluded establishments that were 

not eligible for program tax benefits, such as nonprofit and governmental organizations, from our 

analysis of the change in the number of businesses. However, we included jobs at those businesses in 

our analysis of the change in the number of jobs.

a

Differences for the number of businesses and the number of jobs are calculated as percent changes.

Stakeholder Perceptions of 

the Factors Influencing 

Changes in Poverty, 

Unemployment, and 

Economic Growth

In our interviews, stakeholders said that changes in the poverty rate may 

have been the result of new jobs created by EZ projects, many of which 

offered benefits such as health insurance that helped to stabilize families. 

However, EZ staff and other stakeholders acknowledged that external 

factors, such as welfare reform and general economic trends, also could 

have contributed to poverty reduction. Stakeholders also attributed the 

reduction in unemployment to the job creation efforts, saying that the EZ 

had helped stabilize the area when a key employer, a sewing plant, closed 

prior to designation. 

In terms of economic growth, stakeholders felt that the EZ had played a 

role in the change in economic growth, citing infrastructure improvements 

and zone workshops on how to start new businesses. In addition, some EZ 

stakeholders noted that the economic growth that had occurred was due in 

part to the EZ program tax benefits, although not all stakeholders agreed. 

1995 1999 2004

Percent change 

1995-2004a

Number of businesses 609 691 810 33

Number of jobs 5,327 7,691 8,941 67.84
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 142 GAO-06-727 Empowerment Zones and Enterprise Communities

Mid-Delta Mississippi 

Empowerment Zone 

Figure 33: Map of the Mid-Delta EZ

How the EZ Was Governed The nonprofit Mid-Delta Empowerment Zone Alliance was created to 

manage the EZ. It included a board that consisted of city and county 

elected officials and representatives from community organizations, plus 

subzones boards in each of the six counties. Most decisions were made by 

the committees and brought to the full board for approval. However, 

EZ

Boundaries of counties partially included in the EZ

Coahoma

Issaquena

Madison 

Holmes

Chicot 

Desha

Mississippi 

Phillips

Attala

Bolivar 

Carroll 

Grenada

Humphreys

Leflore 

Sharkey 

Sunflower 

Tallahatchie 

Washington 

Yazoo 

Arkansas

Louisiana

Source: GAO analysis of USDA data.

The Mid-Delta EZ consisted 

of eight census tracts

located in six counties: 

Bolivar, Washington, 

Humphries, Holmes, 

Sunflower, and Leflore 

counties. 
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 143 GAO-06-727 Empowerment Zones and Enterprise Communities

several stakeholders noted that this formal process was not always 

followed and that some board decisions appeared to favor large businesses 

over community groups. 

Activities the EZ 

Implemented

Most of the activities the Mid-Delta EZ implemented were related to 

community development. Initiatives involving business development and 

job training; resources for communities, youth, and families; education; 

and housing accounted for the bulk of the activities (fig. 34). In our 

interviews, stakeholders noted that EZ funds were used for a variety of 

community- and family-oriented projects. These included helping a small 

municipality purchase needed police and fire equipment, partially funding a 

mortgage assistance program that moved 20 people into houses, and 

implementing some health care programs, such as a substance abuse 

treatment center for women. Also, one business in the Mid-Delta EZ used a 

program tax-exempt bond. In addition, stakeholders mentioned that EZ 

funds were used to attract major corporations, such as an automobile parts 

manufacturer and retail distribution center. However, several stakeholders 

also noted that some programs were unsuccessful, and an EZ official said 

that approximately 16 projects were under review for possible misuse of 

funds. The Mid-Delta EZ received a grant extension until 2009. 
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 144 GAO-06-727 Empowerment Zones and Enterprise Communities

Figure 34: Activities Implemented by the Mid-Delta EZ

0

1

2

3

4

5

6

The Mid-Delta EZ, along with the City of Mound Bayou, provided funding for the construction of 

this residential female substance rehabilitation facility.

8%

16%

76%

Mid-Delta, MS 

Community-based partnerships

Economic opportunity

Community development

Number of activities

Sources: GAO (photo); GAO analysis of USDA data (charts).

Activities

Housing

Environment

and natural

resources

Bu

Education

siness

development/

job training

Community/

youth/family

resources

Capacity

building

Health

care

Public

infrastructure

Public

safety
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 145 GAO-06-727 Empowerment Zones and Enterprise Communities

Changes in Poverty, 

Unemployment, and 

Economic Growth

The Mid-Delta EZ saw positive changes in two indicators: poverty and 

economic growth. Between 1990 and 2000, the poverty rate in the Mid-Delta 

EZ decreased more than any rural EZ. However, the Mid-Delta EZ 

experienced a small increase in unemployment over that time period. For 

economic growth, the EZ saw an increase in both measures from 1995 to 

2004, but the changes were significantly less than in the other two rural 

EZs. Tables 31 and 32 show the changes in poverty, unemployment, and 

economic growth in the EZ. Table 31 also includes data on the changes in 

other variables included in our models of the urban EZs.

Table 31: Changes in Selected Census Variables Observed in the Mid-Delta EZ 

Source: GAO analysis of Census data.

Note: There are eight census tracts in the designated area; we did not use comparison areas for rural 

EZs. For more information on our methodology, see appendix I. Estimates for all census variables 

based on percentages had 95 percent confidence intervals of plus or minus 5 percentage points or 

less. For the confidence intervals for average household income and average owner-occupied housing 

estimates, see appendix I.

a

Differences in poverty rate, unemployment rate, and other variables shown as percentages are based 

upon percentage point differences. Differences for average household income, population, individuals 

per square mile, and average housing value are calculated as percent changes. 

b

The change in estimates from 1990 to 2000 is statistically significant.

1990 2000 Percent changea

Poverty rate (%) 46.35 35.67 -10.68b

Unemployment rate (%) 14.31 17.38 3.07b

Average household income $25,872 $3,559 37.44b

Percentage of single female headed 

households with children 16.51 17.31 0.80

Total population 29,494 29,770 0.94

Total individuals per square mile 30.06 30.34 0.95

Percentage of households that moved 

in the last 5 years 34.75 31.00 -3.75b

Percentage of population of working 

age (16-64) 51.71 57.36 5.65b

Percentage of population with a high 

school diploma (or equivalent) 49.09 60.52 11.43b

Percentage of high school dropouts 14.66 12.62 -2.04b

Percentage of vacant housing units 8.08 9.41 1.33

Average owner occupied housing 

value $50,061 $66,872 33.58b
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 146 GAO-06-727 Empowerment Zones and Enterprise Communities

Table 32: Changes in Selected Economic Growth Variables Observed in the MidDelta EZ 

Source: GAO analysis of Claritas data.

Note: There are eight census tracts in the designated area; we did not use comparison areas for rural 

EZs. For more information on our methodology, see appendix I. We excluded establishments that were 

not eligible for program tax benefits, such as nonprofit and governmental organizations, from our 

analysis of the change in the number of businesses. However, we included jobs at those businesses in 

our analysis of the change in the number of jobs.

a

Differences for the number of businesses and the number of jobs are calculated as percent changes. 

Stakeholder Perceptions of 

the Factors Influencing 

Changes in Poverty, 

Unemployment, and 

Economic Growth

In our interviews, EZ stakeholders credited the EZ with improving poverty 

and unemployment by helping bring in higher paying jobs with benefits. 

However, some suggested that increases in unemployment were not the 

same for each county, and added that the Mississippi Delta region overall 

had a low educational level that limited some residents’ ability to 

participate in the workforce.

In terms of economic growth, EZ stakeholders noted the EZ’s efforts to 

attract large businesses through grants and loans had brought in new 

companies that provided jobs with relatively high wages and benefits. One 

stakeholder said that the EZ’s efforts helped to stabilize the area during a 

period when several large manufacturing plants relocated to other 

countries. 

1995 1999 2004

Percent change 

1995-2004a

Number of businesses 634 838 733 15.62

Number of jobs 9,415 12,694 9,884 4.98
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 147 GAO-06-727 Empowerment Zones and Enterprise Communities

Rio Grande Valley, 

Texas Empowerment 

Zone

Figure 35: Map of the Rio Grande Valley EZ

How the EZ Was Governed The EZ was managed by the nonprofit Rio Grande Valley Empowerment 

Zone, which was created specifically for the EZ. EZ stakeholders explained 

that the EZ board included an executive committee of members 

representing each of the four counties in the EZ and four subzone boards, 

one for each county. Both the EZ and the subzone boards were involved in 

selecting activities for implementation. Subzone members reviewed 

proposals and then forwarded their recommendations to a project review 

committee, which reviewed the activities for feasibility and sustainability. 

Once this process was complete, the activity was sent to the full board for 

approval. 

EZ 

Boundaries of counties partially included in the EZ

MEXICO 

Brooks

Cameron 

Hidalgo 

Jim Hogg 

Kenedy 

Starr 

Willacy 

Zapata

Texas

Gulf of 

Mexico 

Source: GAO analysis of USDA data.

The Rio Grande Valley EZ

included: (1) Hidalgo 

County, (2) Starr County, 

(3) the Delta Region in 

Willacy County, and (4) the 

city of Port Isabel in 

Cameron County.
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 148 GAO-06-727 Empowerment Zones and Enterprise Communities

Activities the EZ 

Implemented 

The Rio Grande Valley EZ implemented mostly community development 

activities, most commonly education, public infrastructure, and business 

development and job training initiatives (fig. 36). In our interviews, 

stakeholders mentioned that the EZ had provided funds to several projects 

sponsored by the school districts, focusing its funding on improving the 

well-being of children. For example, the EZ provided computers and 

technical assistance to local Boys and Girls Clubs. EZ stakeholders also 

cited several infrastructure improvements, such as a water plant, a water 

tower, the expansion of a fire department facility, and the creation of 

community centers. In terms of economic opportunity initiatives, three 

counties provided loans through a revolving loan program, and one county 

created a small business incubator. In addition, the EZ provided funding to 

a community-based organization to provide low-skilled workers with 

training for jobs in the health care field. 
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 149 GAO-06-727 Empowerment Zones and Enterprise Communities

Figure 36: Activities Implemented by the Rio Grande Valley EZ

0

1

2

3

4

5

6

7

8

In partnership with Hidalgo County, the EZ provided funds to expand the 

City of Edcouch Water Treatment Plant. 

10% 

15% 

75% 

Rio Grande, TX 

Community-based partnerships

Economic opportunity 

Community development 

Number of activities

Sources: GAO (photo); GAO analysis of USDA data (charts).

Activities

Housing

Environment

and natural

resources

Education

Business

development/

job training

Community/

youth/family

resources

Capacity

building

Health

care

Tourism

and culture

Public

infrastructure

Public

safety
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 150 GAO-06-727 Empowerment Zones and Enterprise Communities

Changes in Poverty, 

Unemployment, and 

Economic Growth

The Rio Grande Valley EZ experienced positive changes in poverty and 

economic growth. The EZ had the highest poverty and unemployment rates 

in 1990 of any of the rural EZs. Between 1990 and 2000, the EZ experienced 

a decrease in poverty; however, the unemployment rate did not show a 

significant change. For economic growth, the EZ experienced an increase 

in the number of businesses and jobs between 1995 and 2004. Tables 33 and 

34 show the changes in poverty, unemployment, and economic growth in 

the EZ. Table 33 also includes data on the changes in other variables 

included in our models of the urban EZs.

Table 33: Changes in Selected Census Variables Observed in the Rio Grande Valley 

EZ 

Source: GAO analysis of Census data.

Note: There are six census tracts in the designated area; we did not use comparison areas for rural 

EZs. For more information on our methodology, see appendix I. Estimates for all census variables 

based on percentages had 95 percent confidence intervals of plus or minus 5 percentage points or 

less. For the confidence intervals for average household income and average owner-occupied housing 

estimates, see appendix I.

a

Differences in poverty rate, unemployment rate, and other variables shown as percentages are based 

upon percentage point differences. Differences for average household income, population, individuals 

per square mile, and average housing value are calculated as percent changes. 

b

The change in estimates from 1990 to 2000 is statistically significant.

1990 2000 Percent changea

Poverty rate (%) 49.65 42.34 -7.31b

Unemployment rate (%) 14.94 13.82 -1.12

Average household income $25,093 $32,763 30.57b

Percentage of single female headed 

households with children 9.44 10.38 0.95

Total population 29,817 37,044 24.24

Total individuals per square mile 131 159 21.82

Percentage of households that moved 

in the last 5 years 30.11 34.41 4.29b

Percentage of population of working 

age (16-64) 55.47 55.48 0.01

Percentage of population with a high 

school diploma (or equivalent) 41.51 46.80 5.29b

Percentage of high school dropouts 20.1 16.38 -3.72b 

Percentage of vacant housing units 14.37 16.80 2.43b

Average owner occupied housing 

value $46,100 $61,450 33.3b
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 151 GAO-06-727 Empowerment Zones and Enterprise Communities

Table 34: Changes in Selected Economic Growth Variables Observed in the Rio 

Grande Valley EZ 

Source: GAO analysis of Claritas data.

Note: There are six census tracts in the designated area; we did not use comparison areas for rural 

EZs. For more information on our methodology, see appendix I. We excluded establishments that were 

not eligible for program tax benefits, such as nonprofit and governmental organizations, from our 

analysis of the change in the number of businesses. However, we included jobs at those businesses in 

our analysis of the change in the number of jobs.

a

Differences for the number of businesses and the number of jobs are calculated as percent changes. 

Stakeholder Perceptions of 

the Factors Influencing 

Changes in Poverty, 

Unemployment, and 

Economic Growth

In our interviews, EZ stakeholders suggested that EZ programs may have 

helped to improve residents’ quality of life through programs that provided 

employment opportunities or taught residents skills to improve their 

income. One stakeholder mentioned a health clinic that was partially 

funded by the EZ that had helped to provide additional jobs in the area. 

However, another stakeholder mentioned the large number of migrant farm 

workers in the area make tracking these changes difficult.

In terms of changes in economic growth, EZ stakeholders noted the initial 

lack of public infrastructure in the zone and mentioned that the EZ 

infrastructure development helped to prepare the area for future economic 

development and growth. Stakeholders credited EZ activities with helping 

to attract tourism to areas of the EZ and said that efforts to help businesses 

through revolving loan funds in some of the EZ counties had fostered 

economic growth. Some EZ stakeholders added that some of the growth of 

cities surrounding the EZ also might be due to an increase in trade across 

the border with Mexico.

1995 1999 2004

Percent change 

1995-2004a

Number of businesses 551 688 710 28.86

Number of jobs 6,025 6,548 7,427 23.27
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 152 GAO-06-727 Empowerment Zones and Enterprise Communities

Providence, Rhode 

Island Enterprise 

Community

Figure 37: Map of the Providence EC

How the EC Was Governed The Providence EC was managed by the nonprofit Providence Plan and 

included a board called the Oversight Committee that included EC 

residents from each neighborhood, small business owners, and two city 

council members. Unlike many of the EZs, the EC allocated most of its 

grant funds during the strategic planning process, so there were few funds 

for the board to approve during the course of the program. However, in 

those cases, the board reviewed background information on the 

organizations that requested funds, discussed the applicants at their 

EC 

Providence city limits

Narragansett 

Bay 

0 1 2 

miles

Rhode Island Massachusetts

Providence 

Source: GAO analysis of HUD data.

The Providence EC was

made up of three 

neighborhoods: the 

Olneyville, South Side, and 

Smith Hill. 
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 153 GAO-06-727 Empowerment Zones and Enterprise Communities

meetings, and then chose the applicants to fund. The board also reviewed 

the routine reporting by subgrantees and participated in site visits. 

Activities the EC 

Implemented

The Providence EC implemented four types of activities—workforce 

development, assistance to businesses, access to capital, and human 

services—most of which were related to economic opportunity (fig. 38). 

According to stakeholders, the EC’s largest subgrantee was a community 

development corporation, which implemented workforce training, a 

summer youth program, and business development programs. It also 

funded the renovation and development of some small business incubators 

that offered space and technical assistance to new small businesses. In 

addition, stakeholders noted that the EC implemented some Community 

Opportunity Zones, which were designed to provide integrated access to 

education, health, and social services for families with children. An EC 

official explained that most of the EC funds were spent in the first 5 years 

of the program and that all EC funds had been spent by June 2004. 
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 154 GAO-06-727 Empowerment Zones and Enterprise Communities

Figure 38: Activities Implemented by the Providence EC

0

1

2

3

4

5

6

7

8

The Providence EC provided funds that a subgrantee used to renovate some old Victorian homes

to create “business incubators” that offered office space and technical assistance to new small 

businesses, of which this is one example.

21%

50%

29%

Providence, RI 

Community-based partnerships

Economic opportunity 

Community development 

Number of activities

Sources: GAO (photo); GAO analysis of HUD data (charts).

Activities

Workforce

development

Human

services

Access to

capital

Businesses

assisted
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 155 GAO-06-727 Empowerment Zones and Enterprise Communities

Changes in Poverty, 

Unemployment, and 

Economic Growth

In the Providence EC, poverty and unemployment stayed about the same 

from 1990 to 2000 and the number of businesses and jobs decreased 

between 1995 and 2004.8

 Tables 35 and 36 show the changes in poverty, 

unemployment, and economic growth in the EC. Table 35 also includes 

data on the changes in other variables included in our models of the urban 

EZs.

Table 35: Changes in Selected Census Variables Observed in the Providence EC 

Source: GAO analysis of Census data.

Note: There are 13 census tracts in the designated area; we did not use comparison areas for 

individual ECs. For more information on our methodology, see appendix I. Estimates for all census 

variables based on percentages had 95 percent confidence intervals of plus or minus 5 percentage 

points or less. For the confidence intervals for average household income and average owneroccupied housing estimates, see appendix I.

a

Differences in poverty rate, unemployment rate, and other variables shown as percentages are based 

upon percentage point differences. Differences for average household income, population, individuals 

per square mile, and average housing value are calculated as percent changes. 

b

The change in estimates from 1990 to 2000 is statistically significant.

8

We did not use comparison areas for individual ECs. For more information on our 

methodology, see appendix I.

1990 2000 Percent changea

Poverty rate (%) 35.36 37.58 2.22

Unemployment rate (%) 13.63 11.90 -1.73

Average household income $28,593 $32,616 14.07b

Percentage of single female headed 

households with children 21.64 21.96 0.31

Total population 48,789 53,845 10.36

Total individuals per square mile 9,179 10,141 10.48

Percentage of households that moved in the 

last 5 years 52.23 50.85 -1.38

Percentage of population of working age (16-

64) 55.45 58.00 2.55b

Percentage of population with a high school 

diploma (or equivalent) 48.69 53.51 4.82b

Percentage of high school dropouts 26.17 19.16 -7.01b

Percentage of vacant housing units 14.55 10.43 -4.13b

Average owner occupied housing value $124,339 $116,698 -6.15b
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 156 GAO-06-727 Empowerment Zones and Enterprise Communities

Table 36: Changes in Selected Economic Growth Variables Observed in the 

Providence EC 

Source: GAO analysis of Claritas data.

Note: There are 13 census tracts in the designated area; we did not use comparison areas for 

individual ECs. For more information on our methodology, see appendix I. We excluded establishments 

that were not eligible for the program tax benefit, such as nonprofit and governmental organizations, 

from our analysis of the change in the number of businesses. However, we included jobs at those 

businesses in our analysis of the change in the number of jobs.

a

Differences for the number of businesses and the number of jobs are calculated as percent changes. 

Stakeholder Perceptions of 

the Factors Influencing 

Changes in Poverty, 

Unemployment, and 

Economic Growth

In our interviews, stakeholders cited several factors that they thought had 

influenced changes in poverty in the EC, including the increased costs of 

housing and utilities, growth in the foreign-born population, the loss of 

manufacturing jobs, and changes to welfare reform. In addition, one EC 

stakeholder noted that many residents were working but not earning high 

enough incomes to move them out of poverty. Although the EC 

experienced a decline in unemployment, stakeholders noted that barriers 

to employment remained, including limited job and language skills and 

records of incarceration. 

With respect to economic growth, EC stakeholders said that businesses 

began working together as a result of the EC. However, one stakeholder 

suggested that the EC was influenced by the slow Rhode Island economy 

and that the EC should have done more to foster economic growth.

1995 1999 2004

Percent change

1995-2004a

Number of businesses 2,714 2,426 2,200 -18.94

Number of jobs 37,724 34,763 33,545 -11.08
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 157 GAO-06-727 Empowerment Zones and Enterprise Communities

Fayette-Haywood, 

Tennessee Enterprise 

Community

Figure 39: Map of the Fayette-Haywood EC

How the EC Was Governed Three entities shared responsibility for operating the Fayette-Haywood EC. 

Haywood County administered the EC grant funds, a local development 

district was in charge of the EC’s reporting to USDA, and a board that 

represented both counties in the EC made funding decisions.9

 To make 

decisions about what activities to fund, each county held separate meetings 

to discuss projects that pertained to their community and sought final 

approval at a meeting of the full board. EC stakeholders mentioned that 

EC 

Boundaries of counties partially included in the EC

Source: GAO analysis of USDA data.

The EC included 

two counties, Fayette and 

Haywood, that had four 

census tracts in each. 

Alabama

Tennessee

Mississippi

Benton

Marshall

Crockett

Fayette

Hardeman

Haywood

Lauderdale

Madison

Shelby

Tipton

Arkansas

9

Local development districts are unique to the state of Tennessee, and the majority of their 

funding comes from the Tennessee General Assembly. 
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 158 GAO-06-727 Empowerment Zones and Enterprise Communities

USDA officials played an active role in the EC and attended most board 

meetings. 

Activities the EC 

Implemented

The majority of the activities implemented by the Fayette-Haywood EC 

were in community development, mainly in the areas of health care and 

housing (fig. 40). In our interviews, stakeholders mentioned benefits of the 

EC that included health care-related activities, such as recruiting doctors 

and nurses to the area and the reopening a medical clinic that had been 

closed for 10 years. Stakeholders also noted that new housing projects had 

been also built with the help of EC funds. The EC also conducted activities 

related to public infrastructure, such as helping to build a YMCA in 

Haywood County and other community centers in both counties. The EC 

did not request a grant extension, because it had used all of its grant funds. 
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 159 GAO-06-727 Empowerment Zones and Enterprise Communities

Figure 40: Activities Implemented by the Fayette-Haywood EC

0

0.5

1.0

1.5

2.0

2.5

3.0

The EC provided the initial funding for the construction of this YMCA in Haywood county.

10%

10%

80%

Fayette-Haywood, TN 

Community-based partnerships

Economic opportunity

Community development

Number of activities

Sources: GAO (photo); GAO analysis of USDA data (charts).

Activities

Health

care

Public

infrastructure

Bu

Education

siness

development/

job training

Community/

youth/family

resources

Capacity

building

Housing
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 160 GAO-06-727 Empowerment Zones and Enterprise Communities

Changes in Poverty, 

Unemployment, and 

Economic Growth

The Fayette-Haywood EC experienced positive changes in poverty and 

unemployment between 1990 and 2000 and both measures of economic 

growth between 1995 and 2004. Tables 37 and 38 show the changes in 

poverty, unemployment, and economic growth in the EC. Table 37 also 

includes data on the changes in other variables included in our models of 

the urban EZs.

Table 37: Changes in Selected Census Variables Observed in the Fayette-Haywood 

EC 

Source: GAO analysis of Census data.

Note: There are eight census tracts in the designated area; we did not use comparison areas for 

individual ECs. For more information on our methodology, see appendix I. Differences in poverty rate, 

unemployment rate, and other variables shown as percentages are based upon percentage point 

differences. Differences for average household income, population, individuals per square mile, and 

average housing value are calculated as percent changes. Estimates for all census variables based on 

percentages had 95 percent confidence intervals of plus or minus 5 percentage points or less. For the 

confidence intervals for average household income and average owner-occupied housing estimates, 

see appendix I.

1990 2000 Percent changea

Poverty rate (%) 28.37 19.30 -9.07b

Unemployment rate (%) 9.75 7.02 -2.73b

Average household income $32,560 $45,353 39.29b

Percentage of single female headed 

households with children 10.97 11.33 0.36

Total population 29,080 30,551 5.06

Total individuals per square mile 44 46 5.07

Percentage of households that moved 

in the last 5 years 34.49 36.48 1.99

Percentage of population of working 

age (16-64) 55.39 58.82 3.43b

Percentage of population with a high 

school diploma (or equivalent) 53.57 65.81 12.24b

Percentage of high school dropouts 18.26 12.77 -5.49b

Percentage of vacant housing units 6.46 6.85 0.39

Average owner occupied housing value $68,945 $103,619 50.29b
Appendix IV

Description of the Empowerment Zones and 

Enterprise Communities We Visited

Page 161 GAO-06-727 Empowerment Zones and Enterprise Communities

Table 38: Changes in Selected Economic Growth Variables Observed in the FayetteHaywood EC 

Source: GAO analysis of Claritas data.

Note: There are eight census tracts in the designated area; we did not use comparison areas for 

individual ECs. For more information on our methodology, see appendix I. We excluded establishments 

that were not eligible for the program tax benefit, such as nonprofit and governmental organizations, 

from our analysis of the change in the number of businesses. However, we included jobs at those 

businesses in our analysis of the change in the number of jobs.

a

Differences for the number of businesses and the number of jobs are calculated as percent changes.

Stakeholder Perceptions of 

the Factors Influencing 

Changes in Poverty, 

Unemployment, and 

Economic Growth

In our interviews, stakeholders said that changes in the poverty rate may 

have been due to changes in demographics as higher-income residents from 

neighboring counties moved into the EC, which had lower property taxes. 

In addition, stakeholders suggested that EC residents benefited from new 

affordable housing partially funded by the EC. 

When discussing changes in unemployment and economic growth, 

stakeholders mentioned that one factor was the designated area’s 

proximity to a growing city 25 miles away that provided additional job 

opportunities. In addition, stakeholders mentioned that the EC designation 

had helped the Haywood county government win grants to build 

infrastructure, such as a rail spur that attracted large industries to the EC. 

These industries offered jobs with higher wages and provided water lines 

with potable water for EC residents. 

1995 1999 2004

Percent change 

1995-2004a

Number of businesses 892 921 1,128 26.46

Number of jobs 9,556 10,128 11,240 17.62
Page 162 GAO-06-727 Empowerment Zones and Enterprise Communities

Appendix V

Comments from the Department of Health and 

Human Services ApendxiV
Appendix V

Comments from the Department of Health 

and Human Services

Page 163 GAO-06-727 Empowerment Zones and Enterprise Communities
Appendix V

Comments from the Department of Health 

and Human Services

Page 164 GAO-06-727 Empowerment Zones and Enterprise Communities
Page 165 GAO-06-727 Empowerment Zones and Enterprise Communities

Appendix VI

Comments from the Department of Housing 

and Urban Development ApendxiVI

Note: GAO comments 

supplementing those in 

the report text appear 

at the end of this 

appendix.
Appendix VI

Comments from the Department of Housing 

and Urban Development

Page 166 GAO-06-727 Empowerment Zones and Enterprise Communities
Appendix VI

Comments from the Department of Housing 

and Urban Development

Page 167 GAO-06-727 Empowerment Zones and Enterprise Communities

See comment 1.

See comment 2.

See comment 3.
Appendix VI

Comments from the Department of Housing 

and Urban Development

Page 168 GAO-06-727 Empowerment Zones and Enterprise Communities

See comment 4.

See comment 5.
Appendix VI

Comments from the Department of Housing 

and Urban Development

Page 169 GAO-06-727 Empowerment Zones and Enterprise Communities

See comment 6.

See comment 7.
Appendix VI

Comments from the Department of Housing 

and Urban Development

Page 170 GAO-06-727 Empowerment Zones and Enterprise Communities
Appendix VI

Comments from the Department of Housing 

and Urban Development

Page 171 GAO-06-727 Empowerment Zones and Enterprise Communities

See comment 8.

See comment 9.

See comment 10.
Appendix VI

Comments from the Department of Housing 

and Urban Development

Page 172 GAO-06-727 Empowerment Zones and Enterprise Communities

See comment 14.

See comment 13.

See comment 12.

See comment 11.
Appendix VI

Comments from the Department of Housing 

and Urban Development

Page 173 GAO-06-727 Empowerment Zones and Enterprise Communities

See comment 15.

See comment 16.

See comment 17.

See comment 18.

See comment 19.
Appendix VI

Comments from the Department of Housing 

and Urban Development

Page 174 GAO-06-727 Empowerment Zones and Enterprise Communities
Appendix VI

Comments from the Department of Housing 

and Urban Development

Page 175 GAO-06-727 Empowerment Zones and Enterprise Communities

The following are GAO’s comments on the Department of Housing and 

Urban Development’s letter dated August 17, 2006.

GAO Comments 1. HUD commented that GAO should include details on the amount of 

funding and tax incentives provided for Rounds II and III of the EZ/EC 

program. We noted in our report that communities designated in 

Rounds II and III received a smaller amount of funding and more tax 

benefits than those designated in Round I. Our statement does not 

provide further details on Rounds II and III because the focus of the 

report is Round I.

2. We recognize that Round I designees were required to address four key 

principles as part of their strategic plans. However, our mandate was to 

assess the effectiveness of the EZ/EC program on poverty, 

unemployment, and economic growth. Assessing the extent to which 

communities addressed the key principles would not have been useful 

in meeting our mandate because, among other things, there is not a 

clear relationship between the key principles and poverty, 

unemployment, and economic growth. Further, while the report did not 

evaluate the extent to which communities met the key principles, it 

included many examples of activities carried out under them. The 

report also indicated that communities had implemented a larger 

percentage of community development activities than economic 

opportunity activities but did not comment on the appropriateness of 

the distribution of activities. 

3. Our mandate was to assess the effects of the EZ/EC program on 

poverty, unemployment, and economic growth. Our report stated that 

communities were required to submit strategic plans that addressed the 

four key principles. However, because communities were able to 

modify their strategic plans over time, it would have been difficult to 

establish set criteria for assessing performance. Nonetheless, our 

report does contain numerous examples of activities undertaken by the 

communities, including examples mentioned in a separate appendix 

focusing on the 13 designated communities we visited. 

4. HUD commented that because GAO found that a lack of data on how 

program funds were used was a limiting factor in determining the 

effectiveness of the EZ/EC program, we should make use of 

information in the agency’s performance reporting system and in 

communities’ strategic plans. However, we reported that our file review 
Appendix VI

Comments from the Department of Housing 

and Urban Development

Page 176 GAO-06-727 Empowerment Zones and Enterprise Communities

to determine the accuracy of data in HUD’s performance reporting 

system found that the data were not sufficiently reliable for our 

purposes. For example, we found evidence that communities had 

undertaken certain activities with program funding, but we were often 

unable to find documentation of the actual amounts allocated or 

expended. As a result, we were unable to rely on information contained 

in the agency’s performance reporting system on the amounts of 

program funds allocated or expended on specific activities.

5. We found that data in HUD’s performance reporting system on the 

amounts of funds used and the amounts leveraged were not reliable. 

For example, we found that HUD’s system included information on the 

amount of funds leveraged. But for the sample of activities we 

reviewed, the supporting documentation either showed an amount 

conflicting with the reported amount or was not available. Moreover, 

we found that the definition of “leveraging” varied across EZ and EC 

sites. HUD further commented that Table 5 in the report showed that 

the agency’s performance reporting system received a code of 2.0, 

showing that leveraging data had strong documentation. However, 

HUD appears to have misinterpreted the information we presented on 

this matter. We found that HUD’s data on leveraging received an 

average code of 1.0, indicating that such information had weak 

documentation. Lastly, HUD recommended that it be allowed to 

alleviate GAO’s concerns about the reliability of its leveraging data by 

demonstrating how the data were tracked and recorded in its 

performance reporting system. However, the data reliability problems 

we found during the course of this work were due not to concerns 

about the system used to track and record the data, but rather to the 

frequent lack of supporting documentation for the data entered into the 

system. 

6. HUD commented that our report did not adequately address HUD’s 

performance reporting system and its role in HUD’s oversight of the 

urban Round I EZ and ECs. We acknowledge that HUD established the 

system in response to an earlier GAO recommendation and has since 

used it to oversee Round I EZs and ECs. Moreover, we agree that the 

system contains a variety of information and data elements, including 

activities implemented and program outputs. We also acknowledge that 

the performance reporting system is not intended to be a financial 

system for Round I. However, as discussed in our report, we found that 

because the system did not always contain information on what was 

spent on activities and did not always contain reliable information, 
Appendix VI

Comments from the Department of Housing 

and Urban Development

Page 177 GAO-06-727 Empowerment Zones and Enterprise Communities

HUD and the other federal agencies were limited in their ability to 

oversee the program. 

7. HUD commented that the program’s design was significant because it 

provided insight about the nature and extent of the federal, state, and 

local attitudes that existed at the time of the first Round of EZs/ECs. 

HUD also stated that it did not conduct monitoring of the SSBG funds 

because monitoring those funds was the responsibility of HHS. HUD’s 

statement further supports our discussion on the limitation in the 

oversight of the EZ/EC program that may have resulted from the 

program’s design. Although we found program oversight was hindered, 

we also reported that no single federal agency had sole responsibility 

for oversight. We do not agree with HUD’s recommendation that we 

make clear that more oversight was not allowed in Round I. For 

example, early in the program HUD and HHS made some efforts to 

share information. Specifically, HUD officials said that they had 

received fiscal data from HHS and reconciled that information with 

their program data on the activities implemented, but these efforts to 

share information were not maintained. Regarding the second 

recommendation, although HUD described some of its efforts to 

monitor the program according to applicable regulations, the oversight 

concerns we identified in the report remain. 

8. We reported that limitations in the oversight of the EZ/EC program may 

have resulted from the design of the program. 

9. We stated in the report that the concerns raised about program 

oversight for the Round I EZ/EC program may not apply to future 

rounds of the EZ/EC program. We also acknowledge that HUD may 

have made changes in its oversight of later rounds of the program. 

However, an evaluation of later rounds of the EZ/EC and Renewal 

Community programs is beyond the scope of this report.

10. In our report, we acknowledged HUD’s as well as the other agencies’ 

response to the recommendation in our 2004 report to identify a costeffective means of collecting the data needed to assess the use of the 

tax benefits. 

11. Our report acknowledged the collaboration among HUD, IRS, and 

USDA in addressing our previous recommendation and summarizes the 

outcome of their discussions, including the identification of two data 

collection methods—through a national survey or by modifying the tax 
Appendix VI

Comments from the Department of Housing 

and Urban Development

Page 178 GAO-06-727 Empowerment Zones and Enterprise Communities

forms. In addition, our report also acknowledged that IRS did not have 

any data for some program tax benefits. The lack of data on the use of 

tax benefits continues to be a source of concern that limits an 

assessment of the effect of the EZ/EC program. 

12. We agree that HUD’s efforts to develop a methodology to administer a 

survey to businesses to assess the use of the program tax benefits is a 

useful step in gathering such information. 

13. We recognize the efforts between HUD and Treasury on sharing 

national-level data on EZ businesses’ use of tax credits for employing 

EZ residents. However, as we mention in our report, data on the EZ 

employment tax benefit were limited because they could not be linked 

to the specific EZ claiming the benefit. 

14. In the absence of other data, we acknowledge HUD’s efforts to capture 

anecdotal information on the use of program tax benefits by EZ 

businesses.

15. We recognize HUD’s efforts to market the EZ/EC program tax benefits. 

16. We appreciate HUD’s suggestion on how to approach evaluations of 

later rounds of the EZ/EC and Renewal Community programs and 

welcome the opportunity to discuss these ideas. 

17. We appreciate HUD’s comments on the descriptive information on EZs 

and ECs we visited that are discussed in appendix IV.

18. HUD commented that the measures used in our report---poverty, 

unemployment and economic growth—were used in the application 

process and were not intended to be used as performance measures. 

However, as mentioned earlier our mandate was to assess the effects of 

the EZ/EC program on poverty, unemployment, and economic growth. 

19. HUD suggested that we consider additional methodologies for 

measuring the effects of the EZ/EC program, such as trend analysis 

using data from 1990 through 1995 and 1995 through 2000. To conduct 

our work, we used 1990 and 2000 data to measure changes in poverty 

and unemployment and 1995, 1999, and 2004 data to measure changes 

in economic growth. We chose these dates because data were available 

at the census tract level for these years. Moreover, in designing our 

methodology for our econometric analysis, we conducted a literature 
Appendix VI

Comments from the Department of Housing 

and Urban Development

Page 179 GAO-06-727 Empowerment Zones and Enterprise Communities

review and discussed our methodology with several experts in the 

urban studies field and determined that the approach presented in this 

report was effective in answering the objectives of our mandate. As 

mentioned in Appendix II, we also conducted different tests to ensure 

the robustness of our models, which all yielded results consistent with 

our models. The approach that HUD suggested controlled for trends 

that began before the EZs were designated in 1994. Because we did not 

have data on poverty or unemployment for 1995 we were unable to use 

this approach. However, our use of housing trends between 1990 and 

1994 in our econometric model controlled for some trends that were in 

place prior to EZ designation.

HUD also suggested a longitudinal case study approach might be the 

best way to assess the effectiveness of this type of program. Although a 

longitudinal case study approach would be informative, it is unlikely 

that a successful retrospective longitudinal study could be designed at 

the end of the program. As HUD noted, this intervention was intended 

to be implemented over a ten-year period. However, a longitudinal case 

study approach would necessitate data collection beginning at the 

inception of the program and continuing for the duration of the 

program as well as some period of time after it ends. 
Page 180 GAO-06-727 Empowerment Zones and Enterprise Communities

Appendix VII

Comments from the U.S. Department of 

Agriculture ApendxiVI
Appendix VII

Comments from the U.S. Department of 

Agriculture

Page 181 GAO-06-727 Empowerment Zones and Enterprise Communities
Appendix VII

Comments from the U.S. Department of 

Agriculture

Page 182 GAO-06-727 Empowerment Zones and Enterprise Communities
Page 183 GAO-06-727 Empowerment Zones and Enterprise Communities

Appendix VIII

GAO Contact and Staff Acknowledgments ApendxiVI

GAO Contact William B. Shear (202) 512-8678

Acknowledgments In addition to the individual named above, Charles Wilson, Jr., Assistant 

Director, Carl Barden, Mark Braza, Marta Chaffee, Emily Chalmers, Nadine 

Garrick, Kenrick Isaac, DuEwa Kamara, Austin Kelly, Terence Lam, John 

Larsen, Alison Martin, Denise McCabe, John McGrail, John Mingus, Jr., 

Marc Molino, Gretchen Maier Pattison, James Vitarello, and Daniel Zeno 

made key contributions to this report.

(250221)
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