Moving to Work

Retrospective

A Picture of Moving to Work

Agencies’ Housing Assistance

Housing Choice and Self-

Sufficiency Outcomes at

Moving to Work Agencies

The Impact of the Moving to

Work Demonstration on the

Per Household Costs of

Federal Housing Assistance

Evaluating the Effects of

Santa Clara County Housing

Authority’s Rent Reform

Moving to Work Agencies’

Use of Project-Based

Voucher Assistance

U.S. Department of Housing and Urban Development | Office of Policy Development and Research

Visit PD&R’s website

www.huduser.gov

to find this report and others sponsored by HUD’s Office of Policy Development and Research (PD&R). Other services of HUD USER, PD&R’s research information service, include listservs, special interest reports, bimonthly publications (best practices, significant studies from other sources), access to public use databases, and a hotline (800-245-2691) for help accessing the information you need.

Moving to Work Agencies’

Use of Project-Based

Voucher Assistance

Prepared for:

U.S. Department of Housing

and Urban Development

Prepared by:

Martha M. Galvez

Daniel Teles

Alyse D. Oneto

Matthew Gerken

URBAN INSTITUTE

April 2021

A

cknowledgments

Acknowledgments

This report was funded by the U.S. Department of Housing and Urban Development (HUD). We are grateful to HUD and to all our funders, who make it possible for Urban to advance its mission.

The views expressed are those of the authors and should not be attributed to the Urban Institute, its trustees, or its funders. Funders do not determine research findings or the insights and recommendations of Urban experts. Further information on the Urban Institute’s funding principles is available at urban.org/fundingprinciples.

Many people reviewed and contributed to this report. The authors appreciate the feedback and support that Elizabeth Rudd, the government technical representative for the Moving to Work (MTW) Retrospective Evaluation, provided throughout the course of the study. Noah Strayer provided valuable research assistance and Emily Peiffer provided editorial support. In addition, the authors thank leadership from Boulder Housing Partners, the Columbia (Missouri) Housing Authority, the Charlotte Housing Authority, the Housing Authority of the City of Pittsburgh, Home Forward (Portland, Oregon), the San Antonio Housing Authority, the San Diego Housing Commission, the San Mateo County Housing Department, the Seattle Housing Authority, and

the Housing Authority of Tulare County for taking the time to speak with us. We also thank MTW

Program Office and other HUD staff, including Lynn Rodgers, Lydia Taghavi, Alison Christensen, John Concannon, Debra Hamblin, Nick Miele, Marianne Nazarro, and many others, for their

assistance in understanding administrative data sources. HUD staff, including Mark Shroder and Kurt Usowsksi, also provided helpful feedback on our research design. Jason Casterline helped us to understand administrative financial data. We thank our reviewers, Doug Wissoker and Martin Abravanel, along with Diane Levy and Martha Galvez, for providing input throughout the research process. Other members of Urban’s MTW Evaluation team provided insights, data, and comments on this study along the way. Final y, we thank the 39 MTW agencies for their review of an early version of this report.

Disclaimer

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

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

Foreword

Foreword

The Moving to Work (MTW) demonstration, launched in 1996, is intended to promote innovation in housing assistance.

Participating public housing agencies (PHAs) may implement new ways of providing housing assistance intended to achieve the statutory objectives of cost effectiveness, self-sufficiency of assisted households, and increased housing choice for low-income families. This study, one of six reports produced by the U.S. Department of Housing and Urban Development’s (HUD’s) retrospective evaluation of MTW, focuses on project-based voucher (PBV) assistance, that is, a rental subsidy for low-income households tied to specific units through a long-term contract with a property manager or private owner. The amount of housing choice voucher funding that a PHA may al ocate to PBVs is limited by law.

Agencies participating in the MTW demonstration, however, may al ocate all their voucher funding to PBVs with HUD

approval. MTW agencies’ uses of PBVs, then, offer insight into the potential uses of expanded authority to al ocate voucher funding to PBVs and consequences of expanding the MTW demonstration.

This is the first study to describe the extent to which MTW agencies1 have used their expanded authority to allocate voucher funding to project-based units, and it presents several new analyses of PBV locations. PBV use is more common among MTW agencies than traditional PHAs, but extensive PBV use is not the norm. PBV use among both MTW and traditional PHAs is higher in expensive markets with increasing rents because PBVs come with long-term contracts. MTW agencies with lower-quality public housing were more likely to use the Rental Assistance Demonstration (RAD) to convert public housing to PBVs. Notably, approximately one-quarter of MTW agencies’ PBVs were located in LIHTC properties, which demonstrates how blended subsidies are used to create affordable housing.

In exploring concerns about the neighborhood quality of PBVs, the study shows that MTW agencies’ PBVs are located in areas with higher education levels and lower transportation costs, but also higher poverty areas with worse air quality than areas in which their tenant-based vouchers (TBVs) are located. Among both MTW and traditional agencies, more racial y segregated areas were more likely to have PBV units in higher-poverty neighborhoods. Because PBVs are anchored to a particular neighborhood, more research is needed to understand how PHAs decide where to locate PBVs.

This report also showcases how three MTW agencies have used PBVs to pursue local y-defined policy goals. In Boulder, Colorado, for instance, the MTW agency converted public housing to PBVs in a partnership with service providers focused on improving the educational attainment of children in assisted households. In Cambridge, Massachusetts, PBVs are a critical tool for preserving affordable housing. In Seattle, Washington, the housing authority uses PBVs to add housing assistance to services for people experiencing homelessness. But more research is needed on local partnerships to uncover whether there are innovative practices and partnerships that can be replicated elsewhere.

Given the findings in the previous paragraph, it would be beneficial to understand whether there are models that are more successful in locating PBVs in high-opportunity neighborhoods.

PBVs are an important component within the suite of federal rental assistance programs. This study highlights the power of PBVs, but also indicates where the program has room to improve. Improvements, including those featured in the local case studies, are critical to ensuring that as many households as possible receive rental assistance.

Todd Richardson

General Deputy Assistant Secretary

U.S. Department of Housing and Urban Development

1 The data in this report references MTW agencies that were designated as of December 15, 2015.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

Contents

Contents

Executive Summary ...............................................................................................................................ix

Findings ................................................................................................................................................................................ix

Limitations ...........................................................................................................................................................................xi

Implications for Policy and Research ...........................................................................................................................xi

1. Introduction ........................................................................................................................................ 1

2. Background .......................................................................................................................................3

Existing Evidence on Project-Based Voucher Assistance ...................................................................................... 5

Interaction with the Rental Assistance Demonstration and Low-Income Housing Tax Credit Programs ...7

3. Research Questions and Study Design ...............................................................................................9

Research Question 1: How extensively do Moving to Work agencies use project-based vouchers? ........ 9

Research Question 2: What factors are associated with Moving to Work and traditional

agencies’ use of project-based voucher assistance? .............................................................................................10

Research Question 3: To what extent are Moving to Work agencies’ project-based vouchers

located in Rental Assistance Demonstration or Low-Income Housing Tax Credit properties? ....................11

Research Question 4: Are Moving to Work agency project-based vouchers in lower-poverty, higher-

quality neighborhoods? Do project-based voucher locations vary by household race or ethnicity? ........13

Research Question 5: What factors are associated with variations in project-based voucher

locations? ............................................................................................................................................................................14

Research Question 6: What are the agencies’ motivations for project-based voucher use? ......................15

Data ......................................................................................................................................................................................16

4. Quantitative Results ......................................................................................................................... 18

Research Question 1: How extensively do Moving to Work agencies use project-based vouchers? ......19

Variation Across Moving to Work Agencies .....................................................................................................20

Research Question 2: What factors are associated with Moving to Work and traditional agencies’

use of project-based voucher assistance? ................................................................................................................21

Research Question 3: To what extent are Moving to Work agencies’ project-based vouchers

located in Rental Assistance Demonstration or Low-Income Housing Tax Credit properties? ..................24

Rental Assistance Demonstration Use at Moving to Work Agencies ........................................................24

Moving to Work Project-Based Vouchers in Low-Income Housing Tax Credit Properties ..................25

Variation Across Moving to Work Agencies .....................................................................................................26

Research Question 4: Are Moving to Work agency project-based vouchers in lower-poverty, higher-

quality neighborhoods? Do project-based voucher locations vary by household race or ethnicity? .......26

Project-Based Voucher Neighborhoods at Moving to Work Agencies ..................................................... 27

Moving to Work Project-Based Voucher Locations Compared With Traditional Public Housing

Agencies’ Project-Based Voucher Locations ..................................................................................................29

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

iv

Contents

Project-Based Voucher Location Patterns by Race and Ethnicity ..............................................................30

The Relationship Between Rental Assistance Demonstration, Low-Income Housing Tax

Credit, and Project-Based Voucher Locations .................................................................................................31

Research Question 5: What factors are associated with variations in Moving to Work project-

based voucher locations? ............................................................................................................................................. 33

5. Case Studies of Three Moving to Work Agencies’ Project-Based Voucher Use.................................36

Common Perspectives on Project-Based Voucher Use .......................................................................................36

Project-Based Vouchers and Neighborhood Location ..........................................................................................38

Boulder Housing Partners: Public Housing Conversion and Local Partnerships ...........................................39

Cambridge Housing Authority: Preserving Affordable Housing with Project-Based Vouchers ..................41

Seattle Housing Authority: Using Project-Based Vouchers to Serve People Exiting Homelessness ...... 43

6. Conclusions .....................................................................................................................................47

Limitations .........................................................................................................................................................................48

Policy Implications and Future Research ..................................................................................................................49

Appendix A: Data and Methodology ....................................................................................................A-1

Data Sources ................................................................................................................................................................... A-1

HUD Administrative Data ..................................................................................................................................... A-1

Other Data Sources .............................................................................................................................................. A-2

Measures and Sampling .............................................................................................................................................. A-4

Public Housing Agency Characteristics........................................................................................................... A-4

Neighborhood Characteristics ........................................................................................................................... A-5

Regional and Market Characteristics ................................................................................................................ A-6

File Construction .............................................................................................................................................................A-7

Project-Based Voucher-Assisted Households (2009, 2016) .......................................................................A-7

Merging the Office of Public and Indian Housing Information Center, National Housing

Preservation Database, and Rental Assistance Demonstration Data .......................................................A-7

Neighborhood-Level Dataset ............................................................................................................................. A-8

Public Housing Agency-Level Dataset............................................................................................................. A-8

Traditional Public Housing Agency Comparison Group...................................................................................... A-8

Defining Housing Markets........................................................................................................................................... A-9

Appendix B: Additional Results ...........................................................................................................B-1

Research Question 1: How extensively do Moving to Work agencies use project-based

vouchers? ...................................................................................................................................................................B-1

Research Question 2: What factors are associated with Moving to Work and traditional

agencies’ use of project-based voucher assistance? ...................................................................................B-4

Research Question 3: To what extent are Moving to Work agencies’ project-based vouchers

located in Rental Assistance Demonstration or Low-Income Housing Tax Credit properties? ........ B-6

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

v

Contents

Research Question 4: Are project-based vouchers at Moving to Work agencies in lower-

poverty, higher-quality neighborhoods? Do project-based voucher locations vary by

household race or ethnicity? .............................................................................................................................. B-9

Analysis of Correlation Between Neighborhood Measures....................................................................... B-9

Supplemental Exhibits .........................................................................................................................................B-10

Research Question 5: What factors are associated with variation in Moving to Work project-

based voucher locations? ...................................................................................................................................B-16

Appendix C: Interview Protocol ...........................................................................................................C-1

Appendix D. Moving to Work Agencies ...............................................................................................D-1

Appendix E. Inventory of Project-Based Voucher-Related Activities for Case Study Moving to

Work Agencies .................................................................................................................................... E-1

Appendix F. Inventory of Moving to Work Agencies with an Activity Related to the Family

Right to Move ...................................................................................................................................... F-1

Appendix G. Low-Income Housing Tax Credit Matching Sensitivity Analysis .......................................G-1

Appendix H: References ......................................................................................................................H-1

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

vi

Exhibits

Exhibits

Exhibit 1.1 The Moving to Work Retrospective Evaluation .............................................................................2

Exhibit 2.1 Assisted Rental Housing Programs ................................................................................................3

Exhibit 2.2 Average Poverty Rate of Census Tracts Containing Assisted Households

by Program Type for Moving to Work and Comparison Traditional Public Housing

Agencies, 2016 ........................................................................................................................................................ 7

Exhibit 3.1 Data Sources Used for Each Research Question ..................................................................... 16

Exhibit 4.1 Project-Based Voucher Use at Moving to Work and Comparison Traditional Public

Housing Agencies ................................................................................................................................................. 19

Exhibit 4.2 Moving to Work Agencies’ Project-Based Vouchers as Percent of Assisted

Households, 2016 ................................................................................................................................................. 21

Exhibit 4.3 Summary Statistics for Moving to Work and Comparison Traditional Public

Housing Agencies ................................................................................................................................................ 22

Exhibit 4.4 Model Results: Factors Related to the Percent of Assisted Households Assisted

by Project-Based Vouchers in 2016 .................................................................................................................23

Exhibit 4.5 Rental Assistance Demonstration Use at Moving to Work and Comparison

Traditional Public Housing Agencies, 2016 ................................................................................................... 25

Exhibit 4.6 Moving to Work Project-Based and Tenant-Based Vouchers in Rental Assistance

Demonstration and Low-Income Housing Tax Credit Properties, 2016 ................................................. 26

Exhibit 4.7 County-Normalized Measures of Neighborhood Quality for Assisted Households

at Moving to Work Agencies by Program, Averages and Differences, 2016 ........................................27

Exhibit 4.8 County-Normalized Measures of Neighborhood Quality for Project-Based

Vouchers at Moving to Work and Traditional Public Housing Agencies, 2016 .................................... 29

Exhibit 4.9 County-Normalized Measures of Neighborhood Quality for Assisted Households

at Moving to Work Agencies by Program and Race/Ethnicity, 2016 ....................................................... 30

Exhibit 4.10 County-Normalized Measures of Neighborhood Quality for Project-Based

Vouchers at Moving to Work Agencies in Rental Assistance Demonstration and Low-Income

Housing Tax Credit Properties, 2016 ...............................................................................................................32

Exhibit 4.11 Model Results: Factors Related to Neighborhood Poverty of Project-Based

Vouchers at Moving to Work and Traditional Public Housing Agencies ................................................33

Exhibit 4.12 Model Results: Factors Related to Neighborhood Poverty of Project-Based

Vouchers at Moving to Work Agencies ...........................................................................................................34

Exhibit 5.1 Boulder, Colorado and Boulder Housing Partners (BHP) ....................................................... 40

Exhibit 5.2 Cambridge, Massachusetts and the Cambridge Housing Authority (CHA) ......................42

Exhibit 5.3 Seattle, Washington and the Seattle Housing Authority (SHA) ............................................44

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

vi

Exhibits

Exhibit B.1 Project-Based Voucher Use at Moving to Work Agencies, by Agency .............................B-1

Exhibit B.2 Model Results: Factors Related to the Use of Any Project-Based Vouchers and

to the Percent of Assisted Households With Project-Based Vouchers at Agencies with Any

Project-Based Vouchers ....................................................................................................................................B-4

EXHIBIT B.3 Project-Based and Tenant-Based Voucher Assistance at Moving to Work

Agencies by Location in Rental Assistance Demonstration or Low-Income Housing Tax

Credit Properties, 2016 ......................................................................................................................................B-6

Exhibit B.4 Correlation Matrix for Neighborhood Quality Measures .....................................................B-9

Exhibit B.5 County-Normalized Average Poverty Rate for Project-Based Voucher Locations

by Moving to Work Agency, 2016 ...................................................................................................................B-11

Exhibit B.6 Qualities of Project-Based Voucher Neighborhoods in Relation to Tenant-Based

Voucher and Public Housing Neighborhoods at Moving to Work and Traditional Public

Housing Agencies Displayed as Net Differences .....................................................................................B-13

Exhibit B.7 Supplemental County-Normalized Measures of Neighborhood Quality for

Assisted Households at Moving to Work Agencies by Program and Race/Ethnicity, 2016 ...........B-14

Exhibit B.8 Difference in County-Normalized Measures of Neighborhood Quality for

Assisted Households at Moving to Work Agencies by Program and Race/Ethnicity,

2009 and 2016 .................................................................................................................................................. B-15

Exhibit B.9 Model Results: Modeling the Average County-Normalized Poverty Rate of

Project-Based Voucher Locations with Additional Explanatory Variables ......................................... B-16

Exhibit B.10 Model Results: Modeling the Percent of Project-Based Vouchers in High-

Poverty Neighborhoods with Additional Explanatory Variables ............................................................B-17

Exhibit E.1 Inventory of Mobility-Related Initiatives at Moving to Work Agencies ............................... E-1

Exhibit F.1 Inventory of Activities Related to the Family Right to Move at Moving to

Work Agencies ...................................................................................................................................................... F-1

Exhibit G.1 Identifying Co-Location of Project-Based Vouchers in Rental Assistance

Demonstration and Low-Income Housing Tax Credit Properties Using Varying Spatial

Buffers at Moving to Work Agencies ..............................................................................................................G-1

Exhibit G.2 Identifying Co-Location of Tenant-Based Vouchers in Rental Assistance

Demonstration and Low-Income Housing Tax Credit Properties Using Varying Spatial

Buffers at Moving to Work Agencies ..............................................................................................................G-1

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

vi i

Executive Summary

Executive Summary

MTW agencies have more access to PBVs

and flexibility in how they administer them,

but PBVs have also become more available

The U.S. Department of Housing and Urban

to traditional PHAs through RAD and recent

Development (HUD), through the Moving

regulatory changes. For some PHAs, PBVs

to Work (MTW) demonstration, provides

may be an appealing alternative to portable

a small group of public housing agencies

TBVs, which can be difficult to use in tight

(PHAs) with policy and funding flexibilities

rental markets or where landlords refuse

to test assistance models that further this

to participate in the voucher program. It

program’s three statutory objectives, which

is difficult to predict, however, how PHAs

are to increase housing choice for low-income

may respond to expanded PBV opportunity

families, encourage families to become

areas or the potential implications of

economical y self-sufficient, and reduce

additional PBV use. Because PBVs limit

costs and achieve greater cost-effectiveness.

assisted households’ neighborhood options,

MTW flexibilities extend to various aspects

policymakers worry that expanded PBV use

of PHA administrative policies and housing

will mean more households are exposed to

assistance programs, including project-based

high-poverty neighborhoods. Understanding

voucher (PBV) assistance. In contrast to

MTW agencies’ PBV use can shed light

portable tenant-based vouchers (TBVs), which

on the potential chal enges, opportunities,

households use to find private market rental

and tradeoffs of expanded PBV use among

housing, PBVs are attached to specific units

traditional PHAs.

through long-term contracts with property

managers or owners.

Findings

This report explores the extent to which the

MTW PHAs are more likely to use PBVs than

39 agencies with the MTW designation as of

traditional agencies, but extensive PBV use is

2016 used PBVs and how they applied their

not the norm. Just nine MTW agencies’ PBV-

MTW flexibilities in relation to PBVs. This is the

use exceeded 20 percent of their HCV budget

first comprehensive look at PBV use among

authority in 2016, while a larger number used

MTW agencies. It examines several questions

PBVs at levels closer to the norm for the

about what drives PBV use and locations

comparison traditional PHAs (0 to 5 percent of

and the PBV program’s interaction with the

their budget authority). Even among the case

Rental Assistance Demonstration (RAD) and

study agencies with extensive PBV use, staff

the Low-Income Housing Tax Credit (LIHTC)

discussed the importance of maintaining TBVs

program. MTW agencies’ motivations for using

and the residential mobility opportunities

PBVs are revealed through three case studies

they offer.

of agencies with extensive PBV portfolios.

We use a combination of HUD administrative

PBVs are used more in tighter housing

data, publicly available neighborhood-level

markets. Both the quantitative and qualitative

data, MTW plans and reports, and qualitative

findings suggest local housing market

data col ected from three MTW agencies. We

characteristics play an important role in PBV

focus on MTW agencies but include a group

use and agency decisions. PHAs in higher-

of similarly sized, traditional PHAs in certain

rent markets increased their PBV use more

analyses to expand our sample sizes and as a

than agencies in more affordable markets.

point of comparison for MTW agencies.

The three case study agencies described

PBV costs as more predictable than TBV

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

ix

Executive Summary

costs in expensive markets with rapidly

There is little evidence that PBVs reach lower-

rising rents. These agencies discussed the

poverty, opportunity-rich neighborhoods.

challenges facing TBV holders in the private

The typical PBV-assisted household at an

market as motivating their agencies’ PBV use.

MTW agency lives in a neighborhood in which

Across MTW agencies, PBV use increased

poverty is 85 percent higher than the average

more in the Northeast than in relatively more

in the agency’s county. At both MTW and

affordable regions of the South and Midwest.

comparison agencies, PBV units are in census

tracts with higher poverty rates than TBV

PBV use increased more among agencies

units and more closely resemble tracts where

that had more distressed public housing.

public housing is located. Additional measures

For MTW and large comparison traditional

of neighborhood quality provide similar

PHAs, receiving five fewer points on a

results, with two exceptions: MTW-assisted

Physical Assessment Subsystem (PASS)

PBV households live in neighborhoods with

score in 2008 is associated with having an

better-than-average access to affordable

additional 0.7 percent of households in PBV

transportation within their county and live

units—amounting to an 18-percent increase

in neighborhoods with higher educational

in PBVs by 2016. This effect appears to be

attainment than either TBV or public housing

driven more by which agencies use PBVs at

households. We found no statistical y

all than by the extent of PBV use. A statistical

significant differences in neighborhood

model with only MTW agencies did not detect

poverty rates between MTW and comparison

a statistically significant relationship between

agencies’ PBVs, or in location patterns by race

distressed developments and PBV use, but

or ethnicity for PBVs compared with other

the small sample size of MTW agencies makes

housing assistance programs. Although MTW

it difficult to detect results.

agencies use RAD more than traditional PHAs,

MTW agencies use RAD more frequently

we did not find any association between RAD

than the comparison traditional PHAs and are

use and PBV locations.

more likely to convert to PBVs versus project-

The three case study agencies discussed

based rental assistance (PBRA). Among MTW

their PBV use as consistent with goals to

agencies, 39 percent had used RAD as of

ensure low-income households have access

2016, compared with 12 percent of traditional

to opportunity-rich neighborhoods, but

PHAs. Both MTW agencies and traditional

neighborhood location was not the driving

agencies were more likely to convert to PBVs

motivation.

than to PBRA, and this was more so for MTW

agencies—which retain MTW flexibilities for

In more racially segregated counties,

PBVs but not for PBRA. In total, as of 2016,

PBV households live in higher-poverty

77 percent of MTW RAD conversions were

neighborhoods. On average, a 10-point

to PBVs versus 55 percent among traditional

difference in the dissimilarity index

PHAs.

corresponds to 8.6 percent more PBV

households living in high-poverty

There is a significant overlap between PBVs

neighborhoods. PBV locations also appeared

and LIHTC properties. More than one-fourth

more sensitive to racial segregation than

of MTW agencies’ PBVs were in LIHTC

TBVs in the same jurisdictions. It may be

properties in 2016. Very few of the PBVs in

that in highly segregated cities, developing

LIHTC properties are RAD conversions (about

PBV properties outside of higher-poverty

1 percent of all MTW PBVs).

neighborhoods is more difficult than renting in

those neighborhoods with a TBV.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

x

Executive Summary

The three case studies underscore the

needed to ensure PBVs offer access to lower-

diverse ways that MTW agencies use PBVs

poverty, opportunity-rich neighborhoods.

to pursue the MTW program’s statutory

Additional research is needed to understand

objectives. The case studies also highlight

the relationship between PBV locations

the importance of local contexts and priorities

and racial segregation and ways to address

in agency decision-making about PBV use.

barriers to affordable housing production in

The three agencies’ primary PBV goals were

low-poverty neighborhoods.

to preserve and expand affordable housing

opportunities—particularly in tight housing

Second, this work exposes the need for more

markets—and to improve cost efficiency. PBV

information that describes how MTW agencies

use was tied to specific local priorities and

use PBVs to identify promising practices and

partnerships.

replicable models. The case study agencies

were testing novel approaches to using PBVs

and were engaged in unique partnerships

Limitations

to address homelessness or to support

This report was based primarily on a

educational or economic mobility. To reveal

combination of HUD administrative data and

programs or practices that can be applied in

publicly available MTW plans and reports,

other settings, such as with smal er PHAs and

which can be imprecise or inconsistent

those located in weaker housing markets,

and lack some key information about PBV

more work is needed.

use. For example, we were not able to

Third, this work begins to reveal the

answer questions about PBVs connected to

relationships between the HCV and LIHTC

supportive services or used for high-need

programs. Future work is needed to ful y

groups that may be less successful with

document and understand these relationships,

tenant-based assistance. No administrative

including more precise estimates of PBV and

data source identifies housing or households

TBV co-location in LIHTC properties for both

connected to supportive services. In addition,

MTW and traditional PHAs.

our analyses were limited by the availability of

data identifying PBV use in LIHTC properties.

Finally, future work should examine supportive

We were able to map PBVs and LIHTC

service provision among MTW agencies

properties for MTW agencies, but extending

and traditional PHAs. More comprehensive

this analysis to traditional PHAs was beyond

administrative data are needed—from

the project’s scope. Final y, the small sample

MTW and traditional PHAs—that identify

size of 39 MTW agencies was a limiting factor

units connected to supportive services and

for regression analyses. To increase our

households served through programs that

sample size and statistical power, we include

combine housing and services.

larger traditional PHAs in several of our

analyses.

Implications for Policy and

Research

This work surfaced several policy implications

and areas for future research. First, our

analyses raise concerns about PBV locations

and suggest more deliberate attention will be

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

xi

1. Introduction

1. Introduction

fulfil ing the program’s statutory objectives

(see exhibit 1.1).

MTW agencies’ PBV use—and PBV use by

This report explores how Moving to Work

traditional PHAs—is relevant to HUD and

(MTW) agencies use project-based voucher

policymakers for several reasons. First, PBVs

(PBV) assistance. It is the first comprehensive

have become more available to PHAs. Recent

look at PBV use among MTW agencies

legislation and the RAD program discussed

and examines several questions about

below al ow traditional PHAs to project

PBV locations and the roles of the Rental

base a larger share of their total voucher

Assistance Demonstration (RAD) and the

al ocations than was previously permitted and

Low-Income Housing Tax Credit (LIHTC)

ease some of the chal enges to using PBVs.

programs in the PBV program. MTW agency

In some markets, PBVs may be appealing

motivations for using PBVs are revealed

because portable tenant-based vouchers

through three case studies of agencies

(TBVs) are difficult to use—whether due to

with extensive PBV portfolios. We use a

tight rental markets or landlords refusing to

variety of methodological approaches and a

accept them. It is difficult to predict, however,

combination of U.S. Department of Housing

whether PHAs will shift from TBVs to PBVs

and Urban Development (HUD) administrative

and the implications of expanded PBV use.

data, document review, and interviews with

Notably, PBVs limit assisted households’

staff at three MTW agencies. We focus on

neighborhood options, raising concerns about

MTW but, wherever possible, also examine

PBV households’ exposure to high-poverty

PBV use among comparably sized traditional

neighborhoods. MTW agencies’ PBV activities

public housing agencies (PHAs).2

and locations can shed light on potential

The MTW demonstration al ows a smal

challenges, opportunities, and tradeoffs of

group of PHAs to test funding and policy

expanded PBV use. Similarly, documenting the

flexibilities to find innovative approaches to

extent to which PBVs are tied to the RAD or

providing HUD-funded housing assistance.3

LIHTC programs can help policymakers and

It has three statutory objectives: to increase

practitioners understand potential constraints

housing choice for low-income families, to

on PBV locations.

encourage families to become economical y

self-sufficient, and to reduce costs and

achieve greater cost-effectiveness in federal

expenditures.4 As of 2019, 39 agencies had

active MTW designation (see appendix D for

a list of MTW agencies). This report is one of

several studies completed through the HUD-

sponsored retrospective evaluation of MTW

to understand how MTW agencies provide

housing assistance and their progress in

2 Throughout this report we refer to housing agencies with MTW designation as MTW agencies and housing agencies without MTW designation as traditional PHAs or comparison traditional PHAs.

3 See HUD’s Moving to Work Demonstration website for more information: https:/ www.hud.gov/mtw

4 See Public Law Section 204 C(3) (A-E): http:/ www.gpo.gov/fdsys/pkg/PLAW-104publ134/pdf/PLAW-104publ134.pdf (p 283 of PDF). Agencies participating in MTW must also fol ow several programmatic statutes. These include requirements to have at least 75 percent of admitted families be very-low income; create a rent policy encouraging self-sufficiency and employment; assist “substantially” the same number of low-income families and maintain a similar family mix that they would have otherwise; and ensure housing meets HUD housing quality standards. (For more details, see https://

www.hud.gov/sites/documents/PIH2013-02.PDF.) Moving to Work Agencies’ Use of Project-Based Voucher Assistance

1

1. Introduction

Exhibit 1.1 The Moving to Work Retrospective Evaluation

The HUD-sponsored Moving to Work (MTW) Retrospective Evaluation includes six reports and an online data feature that examine different aspects of the MTW program and MTW agencies’ activities and performance under the program’s three statutory objectives.

A Picture of Moving to Work Agencies’ Housing Assistance describes MTW agencies, the assistance they provided, and the characteristics of the households they served in 2008 and 2016. A related online data feature provides access to MTW agency-level data.

Moving to Work Agencies’ Use of Funding Flexibility examines how agencies have used MTW funding flexibility, alone and with regulatory waivers, and categorizes funding flexibility activities by their primary objectives—cost-effectiveness, self-sufficiency of assisted households, or increased housing choice for low-income families. The study includes an indepth examination of funding shifts for a subgroup of eight agencies.

Housing Choice and Self-Sufficiency Outcomes at Moving to Work Agencies examines the extent to which MTW agencies meet two of the program’s three statutory objectives, increasing housing choice and promoting self-sufficiency for assisted households.

The Impact of the Moving to Work Demonstration on the Per Household Costs of Federal Housing Assistance examines how MTW

status affects the costs, to HUD, of providing housing assistance to households in the public housing and Housing Choice Voucher (HCV) programs.

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform examines the impacts on work, earnings, and housing subsidies among assisted households of Santa Clara’s unique rent reform, which increased the proportion of income that households must pay toward rent.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance examines multiple aspects of MTW agencies’ use of project-based voucher (PBV) assistance, including the share of assistance and HCV budget authority devoted to PBVs, the relationships between PBVs and the Low-Income Housing Tax Credit and Rental Assistance Demonstration programs, the locations of PBV-assisted units, and case studies of three agencies’ MTW goals and activities.

The report first describes what is known

about PBV assistance and its interaction

with the RAD and LIHTC programs, and then

explains the research design and questions

for the study reported here. Answers fol ow.

A final section of the report showcases

three different MTW agencies and how they

have used PBVs to pursue particular local y

defined goals. A concluding section sums

up the study’s findings. Several appendixes

provide additional information. Appendix A

describes the data and measures used to

answer the research questions. Appendix

B contains additional detailed results from

the quantitative analyses. Materials related

to the qualitative case studies appear in

appendixes C, E, and F. Appendix D lists the

MTW agencies active as of 2016. A sensitivity

analysis related to the LIHTC analysis is

included in appendix G.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

2

2. Background

2. Background

and the voucher covers the difference. In

both programs, at least 75 percent of families

admitted must have extremely low incomes,

The Project-Based Voucher (PBV) program

using HUD’s income limits, when they are

was enacted by Congress in 1998 through

admitted to the program. Unlike tenant-based

the Quality Housing and Work Responsibility

vouchers (TBVs), however, PBVs are attached

Act, as a component of the Housing Choice

to specific housing units or properties and

Voucher (HCV) program (see exhibit 2.1 for

administered through contracts with property

descriptions of the HUD housing programs

owners for specified periods of time. When

referenced in this report). Households pay up

a household moves out of a PBV unit, the

to 30 percent of their income towards rent and

assistance remains with the unit for the length

utilities in the project-based HCV program and

of the PBV contract.

up to 40 percent in the tenant-based program,

Exhibit 2.1 Assisted Rental Housing Programs

Public Housing. Originating in 1937, public housing is the nation’s oldest housing subsidy program. Approximately 1.035 million public housing units are owned and managed by public housing agencies (PHAs), and tenants pay rent directly to a PHA each month.

Households must have income below 80 percent of the area median income (AMI) to qualify, but PHAs are required to target at least 40 percent of new admissions to households that meet HUD’s definition of extremely low income (ELI). Additionally, housing agencies often give preference to households that are homeless, elderly and/or disabled, or working families. Most families pay 30 percent of their income in rent or a minimum rent of up to $50 per month.

Housing Choice Vouchers (HCVs). The HCV program provides rental assistance to approximately 2.3 million low-income households annually. HUD requires that not less than 75 percent of families admitted to a PHA’s HCV program in a year have incomes at or below the ELI limit. The program includes tenant- and project-based voucher assistance. For both types of vouchers, households typically pay 30 percent of their income or a minimum rent of up to $50 per month.

Tenant-Based Vouchers (TBVs): TBVs are provided to individuals or households to enable them to rent privately owned housing. Once a household receives a voucher from their local PHA, they have a minimum of 60 days to find a unit that meets federal quality standards and whose landlord will accept the voucher. When an HCV holder leases a unit, the HCV

holder (such as the tenant) pays a portion of the gross rent (rent plus any tenant-paid utilities), and the PHA pays a portion of the gross rent. The program allows households to rent housing in any jurisdiction where a PHA administers an HCV

program and a landlord will accept a voucher.

Project-Based Vouchers (PBVs): PBVs are attached to specific units and properties through contracts with property managers or owners who rent units to eligible families. The rent is subsidized by the PHA through the PBV. Like with a TBV, the tenant pays a portion of the rent, and the PHA pays a portion of the rent. In some cases, PHAs own the PBV properties.

Section 8 Project-Based Rental Assistance (PBRA). PBRA subsidizes housing for 1.2 million households. The program provides long-term contracts to private for-profit or nonprofit owners (including PHA owners) who rent some or all the units in the properties to low-income families. Costs of maintaining and operating the units with low-income tenants are covered by a monthly Section 8 PBRA payment to the private owner. Households must have income below 80 percent of the AMI to qualify, but at least 40 percent of units in each development must go to ELI households. Households pay the higher of 30 percent of income or $25 in rent.

Local, Non-Traditional Programs. MTW agencies can implement local, non-traditional activities that fall outside of the traditional HCV

and public housing programs. Local, non-traditional programs may include programs that use MTW funds to provide a rental subsidy to a third-party entity (such as, other than a landlord or tenant) who manages intake and administration of the subsidy program (known as sponsor-basing); in which a PHA uses MTW funds to act as a mortgager; to acquire, renovate and/or build units that are not public housing or HCV units (for example, tax credit partnerships); and to provide services not otherwise permitted or that are provided to nonresidents.

Rental Assistance Demonstration (RAD). Congress authorized RAD in 2012 to stem the loss of public housing units due to a lack of funding for repairs. RAD allows PHAs to convert public housing to project-based Section 8 contracts, to provide a predictable long-term funding stream and allow PHAs to use a wide range of public and private funding sources to pay for property rehabilitation.

PHAs using RAD choose Section 8 contracts that are PBVs or PBRA.

Low-Income Housing Tax Credits (LIHTC). The LIHTC program was created by the Tax Reform Act of 1986. Since then, it has placed more than 3 million housing units in service and become the largest federal program that directly promotes building affordable housing. The federal government allocates tax credits to states based on a per-capita formula. States award credits to developers, who sell credits to investors and use the proceeds to pay for construction. Investors who buy the LIHTCs claim the credits starting in the first year that the building is occupied by low-income tenants paying affordable rents, and each year thereafter for up to 10 years.

The LIHTC buildings must maintain income and rent restrictions for a minimum of 15 years.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

3

2. Background

There are several reasons that Moving to

agencies can project base an additional 10

Work (MTW) agencies or traditional public

percent of vouchers if they are connected

housing agencies (PHAs) might choose to

to supportive services, serve vulnerable

convert a portion of their TBV assistance to

populations, or if the property is located in a

PBVs (CBPP, 2017; Cunningham and Scott,

low-poverty census tract. Second, no more

2010). PBVs might be attractive to PHAs in

than 25 units or 25 percent of all units in a

tight or expensive markets and offer more

development (whichever is greater) may be

predictable rent costs compared with TBVs.

assisted through PBVs unless the property

For example, long-term PBV contracts set rent

is in a census tract with a poverty rate below

increases over time, even in places where

20 percent (in which case the cap is 40

private market rents are rising rapidly. Or,

percent of all units). Third, the maximum PBV

PBVs may be a promising option in places

contract term is capped at 20 years, with the

where voucher holders have difficulty finding

option to renew for an additional 20 years.

voucher-affordable units or landlords that will

Finally, to retain neighborhood and housing

accept vouchers—recent research suggests

choice for families in the PBV program, HUD’s

that landlords commonly refuse to rent to

Family Right to Move requirement al ows

TBV holders (Cunningham et al., 2018). PBVs

households to request tenant-based rental

may also al ow agencies to serve higher-

assistance once they have lived in their PBV

need households by co-locating supportive

unit for 1 year.6 PHAs must provide the family

services. Or, they may provide a consistent

with either the next available TBV or other

revenue stream to help agencies finance new

comparable tenant-based rental assistance.

housing or rehabilitate existing affordable

housing—including through the Rental

In contrast, with approval from HUD’s MTW

Assistance Demonstration (RAD) program,

program office, MTW agencies may waive

which al ows PHAs to renovate and preserve

these restrictions and apply additional

public housing units by converting them

flexibilities related to PBVs and/or the HCV

to PBVs or project-based rental assistance

program more broadly. Specifical y related to

(PBRA). Final y, although there is no technical

PBVs, MTW agencies are permitted to:

requirement for it, PHAs might view PBVs

• Devote more than 20 percent of HCV

as an opportunity to create or preserve

program funds/al ocations to PBVs;

affordable housing in high-opportunity

neighborhoods. As discussed below, HUD

• Devote more than 25 percent of the units in

provides incentives to traditional PHAs for

a single project to PBVs;

project-basing in lower-poverty areas.

• Create initial PBV contract terms that extend

beyond 20 years;

There are several constraints on traditional

PHAs’ PBV use.5 First, PHAs may not al ocate

• Establish a “local MTW PBV program,”7

more than 20 percent of their total authorized

using simplified or existing local property

number of HCVs to PBVs. RAD PBVs, however,

selection processes for project-basing units;

are exempt from this 20-percent cap, and

and

5 Some of the current restrictions were revised or relaxed from previous program regulations through the Housing Opportunity Through Modernization Act of 2016 (HOTMA). For more information, see https:/ www.hud.gov/sites/dfiles/PIH/documents/PIH-2017-21.pdf. For example, prior to HOTMA a PHA could use up to 20 percent of its total HCV program funding to PBVs. HOTMA changed the limit to 20 percent of a PHA’s authorized number of vouchers, which represented an increase in allowable PBVs for most PHAs.

6 See 24 CFR 983.261 for more information on the Family Right to Move provision: https:/ www.govinfo.gov/content/pkg/CFR-2017-title24-vol4/pdf/CFR-

2017-title24-vol4-part983.pdf.

7 For more information on the creation of an agency MTW Section 8 project-based program, see Section D.7 “Attachment C” of the Standard MTW

agreement (https:/ www.hud.gov/sites/documents/DOC_10242.PDF).

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

4

2. Background

• Waive or revise the Family Right to Move

Existing Evidence on Project-

requirement.

Based Voucher Assistance

Additional HCV program flexibilities include

the ability to waive or revise:

Prior research has established that MTW

agencies use PBVs more than traditional

• Operational policies and procedures, such

agencies (Mast and Hardiman, 2017) and

as the terms of Housing Assistance Payment

that MTW agencies’ use of PBVs increased

(HAP) contracts and portability processes;

between 2008 and 2016 (Galvez, Gourevitch,

• Rent policies and term limits;

and Docter, forthcoming). Galvez, Simington,

and Treskon’s (2017) review of MTW agency

• Requirements for participants, such as

plans and reports found that nearly all (36

verification procedures;

of the 39) MTW PHAs were engaged in at

• Waitlist policies, such as procedures

least one PBV activity as of 2015. In 2016,

for maintaining waiting lists, and tenant

PBVs represented about 12 percent of al

selection procedures and criteria;

units at MTW agencies compared with

• Housing Quality Standards (HQS)

about 4 percent of all units at comparably

certification and inspection procedures; and

large traditional PHAs serving 750 or more

households annually (Galvez, Gourevitch, and

• Processes to determine what types of funds

Docter, forthcoming). The share of MTW PBV

may be used to rehabilitate or construct

assistance increased by roughly 8 percentage

units, and changes to procedures to

points from 2008 to 2016 (from about 4 to 12

determine a unit’s eligibility for PBVs.

percent), while the share of PBVs at traditional

MTW agencies document their activities and

PHAs increased by only 2 percentage points

use of MTW flexibilities in annual plans and

over the same period (from about 2 to 4

reports, but reporting and the level of detail

percent). Mast and Hardiman (2017) had similar

vary by agency, and they may bundle activities

findings and attributed MTW agencies’ more

for the purpose of reporting. For example,

frequent use of PBVs to their ability to use

Boulder Housing Partners has implemented

their MTW flexibilities.

one activity that covers eight elements of

their PBV program and uses a combination

Prior research also suggests that MTW and

of PBV-specific and HCV authorizations. The

traditional agencies serve similar populations

flexibilities include waiving the 20-percent

through their PBV programs, with negligible

cap on their HCV-authorized units; using a

differences in terms of the share of work-able

local definition of exception units; waiving

household heads, head of household average

the competitive bidding process; establishing

age, household composition and size, and the

local rent limits and reasonableness; allowing

share of households headed by a person with

owners or service providers to hold the

disabilities. PBVs at both types of agencies

waitlist for their property; allowing Boulder

tend to serve more elderly households and

Housing Partners staff to conduct their HQS

fewer disabled households or households

inspections rather than an independent entity;

with children compared with TBVs or public

and allowing tenants without HAP payments

housing (Galvez, Gourevitch, and Docter,

to stay on their voucher.

forthcoming; Mast and Hardiman, 2017). At

both MTW and traditional agencies, PBV-

assisted household heads were slightly more

likely to be White and to be male and slightly

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

5

2. Background

less likely to be work-able than public housing

their respective PHAs’ own jurisdictions. If

or TBV-assisted household heads (Galvez,

PBVs originate primarily through RAD public

Gourevitch, and Docter, forthcoming).

housing conversions, their neighborhoods wil

most likely resemble those of higher-poverty

There is no systematic evidence on how PHAs

public housing. Given that MTW agencies

make decisions about PBV use. Prior literature

tend to be in higher-poverty central city

suggests PHAs may use PBVs to preserve

jurisdictions, compared with traditional PHAs,

or finance new affordable housing stock,

they may perform relatively better within

to overcome challenges finding landlords

their local markets than when compared with

that will accept TBVs, or to pair housing

traditional agencies.

with supportive services (CBPP, 2017). No

research has directly examined what generally

There is no research examining PBV location

motivates PHAs, or MTW agencies specifical y,

patterns by race/ethnicity to determine if

to use PBVs.

PBVs may offer different neighborhood

opportunities for Black or Latino households

A limited body of research examines PBV

compared with TBVs or public housing. In

locations and finds that, on average, PBVs

tighter or more racial y segregated housing

tend to be in higher-poverty neighborhoods

markets, for example, where it may be

and are less dispersed (for example, found in

challenging for low-income or non-White

fewer census tracts) compared with TBVs—

households to find housing that wil accept

but reach lower-poverty, more dispersed

vouchers, PBVs could provide a mechanism

neighborhoods compared with public housing

for PHAs to identify more promising location

(Devine et al., 2003; McClure, Schwartz, and

options than might be feasible with TBVs.

Taghavi, 2015). Mast and Hardiman (2017)

look specifical y at households with children

and find the median-tract poverty rate for

PBVs was marginally higher than the median

for TBVs (28 percent for PBVs versus 24

percent for TBVs). Galvez, Gourevitch, and

Docter (forthcoming) find that MTW PBVs

and TBVs were in neighborhoods with nearly

identical poverty rates (exhibit 2.2). There is

no systematic evidence on MTW agencies’

efforts to use PBVs to reach high-opportunity

neighborhoods, but Galvez, Simington,

and Treskon (2017) found that only four

MTW agencies were explicitly using MTW

flexibilities to reach low-poverty or high-

opportunity areas with PBVs.8

None of these analyses examines the role of

public housing conversions in PBV locations

(as discussed below) or those locations

relative to the average poverty rate for

8 The MTW agencies were Cambridge, Holyoke, Reno, and King County.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

6

2. Background

Exhibit 2.2 Average Poverty Rate of Census Tracts Containing Assisted Households by Program Type for Moving to Work and Comparison Traditional Public Housing Agencies, 2016

34%

35%

33%

29%

30%

28%

27%

28%

27%

25%

25%

20%

15%

10%

5%

0%

Total

Public housing

Project-based vouchers Tenant-based vouchers

MTW Agencies

Comparison Traditional PHAs

MTW = Moving to Work. PHA = Public Housing Agency

Notes: Excludes households with missing geographic-tract identifiers in HUD Office of Public and Indian Housing Information Center data.

Sources: Urban Institute analysis of HUD Office of Public and Indian Housing Information Center data; 2011–2015 American Community Survey, 5-year data Interaction with the Rental

housing to either PBVs or PBRA. Because

Assistance Demonstration

RAD is a housing preservation program,

and Low-Income Housing Tax

HUD waives the PBV program’s poverty

deconcentration goal. The Act initial y

Credit Programs

authorized up to 60,000 units, and as of 2019,

The RAD and Low-Income Housing Tax Credit

Congress has raised the cap to 455,000

(LIHTC) programs should be considered

units. An interim evaluation identified 39,042

when examining PBV use, particularly as

RAD conversions (in 359 projects) as of

they relate to PBV locations (see exhibit 2.1

2016 (Econometrica, Inc., 2016), and as of

for descriptions of HUD housing programs).

2019, approximately 113,540 public housing

Both scenarios typical y involve layering PBVs

units have been converted. For both MTW

onto existing affordable housing properties—

and traditional PHAs, the extent to which

potentially in higher-poverty neighborhoods.

PBV-assisted units are in converted public

There is no research, however, documenting

housing properties may be important in

the extent to which PBVs are connected to

explaining PBV locations. If a large proportion

RAD conversions or are co-located in LIHTC

of PBV units national y are in former public

properties.

housing properties, PBV locations will very

likely resemble public housing locations. If

RAD was authorized under the Consolidated

MTW agencies use RAD more frequently

and Further Continuing Appropriations Act

than traditional agencies, MTW PBVs may

of 2012 to help PHAs preserve and improve

be in higher-poverty areas than traditional

public housing in need of major rehabilitation.

agencies’ PBVs.

Through RAD, PHAs can convert public

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

7

2. Background

The LIHTC program gives private investors

a federal income tax credit in return for

making equity investments in affordable

rental housing.9 Additional tax credits are

awarded to projects in areas with higher

poverty and/or a large number of low-income

households (Qualified Census Tracts) or areas

with particularly high development costs

(Difficult Development Areas).10 Research

and anecdotal evidence suggest there is

considerable overlap between the two

programs (Climaco et al., 2009; O’Regan

and Horn, 2013), although no data source

comprehensively overlays voucher and

LIHTC assistance or differentiates TBVs from

PBVs.11 Prior research also shows that LIHTC

properties are more likely to be found in

suburban areas compared with HCVs (El en,

O’Regan, and Voicu, 2009; McClure, 2006;

Freeman, 2004), which could suggest lower-

poverty locations compared with other place-

based assistance programs. As with RAD,

the degree of overlap between the PBV and

LIHTC programs could have implications for

PBV neighborhood locations, but it is difficult

to estimate whether co-location of PBV units

in LIHTC properties might expand or impede

access to lower-poverty neighborhoods.

9 See Scal y, Gold, and DuBois (2018) for information on the LIHTC program.

10 HUD defines Qualified Census Tracts as tracts where at least one-fourth of the population lives in poverty or where at least one-half of the population have income below 60 percent of area median income. The LIHTC statute defines Difficult Development Areas as areas with high development costs, specifically land, construction, and utility costs, and is intended to provide low-income housing in higher-income areas.

11 For example, O’Regan and Horn (2012) had access to subsidy information for LIHTC properties in one state and estimated that roughly 23 to 26 percent of households in LIHTC properties had vouchers.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

8

3. Research Questions and Study Design

3. Research

data used to answer them. The data sets

are summarized in exhibit 3.1, and additional

Questions and Study details about the quantitative analyses are

in appendix A. We discuss the findings in

Design

Section 4.

Research Question 1: How

This study answers six research questions:

extensively do Moving to

Work agencies use project-

1. How extensively do Moving to Work

agencies use project-based vouchers?

based vouchers?

2. What factors are associated with Moving

The first research question quantifies

to Work and traditional agencies’ use of

MTW agencies’ PBV activity using HUD

project-based voucher assistance?

administrative data and a database of MTW

activities developed for the evaluation.

3. To what extent are Moving to Work

Specifically, we examine:

agencies’ project-based vouchers located

in Rental Assistance Demonstration or Low-

• How many MTW agencies report PBV-

Income Housing Tax Credit properties?

assisted households in HUD administrative

4. Are Moving to Work agency project-based

data?

vouchers in lower-poverty, higher-quality

• Which MTW agencies have the most active

neighborhoods? Do project-based voucher

PBV programs?

locations vary by household race or

• How frequently do MTW agencies use their

ethnicity?

PBV flexibilities?

5. What factors are associated with variations

We identify six measures of PBV activity as

in project-based voucher locations?

of 2016. For the measures calculated using

6. What are the agencies’ motivations for

HUD administrative data, we contrast PBV use

project-based voucher use?

by MTW agencies to that of the comparison

For the quantitative analyses (questions

group of similarly large traditional PHAs.

1 through 5), we contrast Moving to Work

1. The number and percent of MTW agencies

(MTW) project-based voucher (PBV) use to

with PBV-assisted households.

that of a group of similarly large traditional

public housing agencies (PHAs) (defined as

2. The number and percent of all MTW-

serving 750 or more households through

assisted households served through PBVs.

any assistance program in 2016). These

3. The percent of housing choice voucher

larger PHAs more closely resemble MTW

(HCV) budget authority that MTW agencies

agencies in terms of size, the mix of housing

devoted to PBVs.

assistance provided, and local housing market

4. The total number of PBV activities requiring

characteristics than do smaller traditional

MTW flexibilities.

agencies (see Galvez, Gourevitch, and Docter,

forthcoming, and appendix A of this report

5. The total number of MTW activities that

for a discussion of the comparison traditional

involve or impact PBVs.

PHAs). Below, we describe each research

6. The number and percent of agencies that

question and summarize the methods and

used their MTW flexibilities to exceed the

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

9

3. Research Questions and Study Design

cap of 20 percent of HCV budget authority

• Logged average rental prices measured with

al ocated to PBVs.12

the Zillow Rent Index (ZRI)14 in 2016;

Relevant MTW PBV activities include any

• The percentage change in the ZRI over

active and ongoing activities that (1) explicitly

5 years prior to our analysis year (2011 to

involve MTW PBV flexibilities (for example,

2016);

exceeding PBV caps, extending initial contract

• The Real Estate Assessment Center (REAC)

terms, or establishing a local MTW PBV

Physical Assessment Subsystem (PASS)

program) or (2) implicitly involve PBVs in some

scores for 2008;

way.

• The percent of the PHA’s assisted

households that lived in public housing in

Research Question 2: What

2009;

factors are associated

• The percent of the PHA’s assisted

with Moving to Work and

households served by PBVs in 2009; and

traditional agencies’ use

• Indicator variables for PHA regional

of project-based voucher

location (South, Midwest, or West), using

assistance?

U.S. Census Bureau regions and the

Northeast as the reference region.

After determining MTW agencies’ PBV

Drawing on prior literature (CBPP, 2017)

use, we use linear regression to explore

and discussions with HUD and PHA staff,

factors associated with PBV use. To increase

our analysis examines whether PBV use is

our sample size and statistical power, the

associated with the need to overcome the

regression model is estimated using a sample

chal enges of finding units that will accept

of MTW agencies only (N=34) as well as a

tenant-based vouchers (TBVs) and/or preserve

larger sample that includes large PHAs and

deteriorating affordable housing stock.

MTW agencies (N=446).13 We use data from

the HUD PIH (Office of Public and Indian

We use high and rising rents as a sign of tight,

Housing) Information Center (PIC) and other

competitive housing markets where demand

sources. See exhibit 3.1 and appendix A for

for rental housing is growing faster than the

additional detail on data sources and analyses.

supply, and it may be more chal enging for

low-income households to find housing with a

The regression model estimates the

TBV.15 If MTW agencies view PBVs as a useful

relationship between the share of assisted

tool mainly in competitive, expensive markets,

households reported in PIC that were

we would expect to see higher PBV use in

assisted through PBVs in 2016 and the

places with high or rapidly rising rents. We

following measures:

measure rents using the ZRI and differentiate

12 Prior to HOTMA’s implementation in 2017, traditional PHAs were able to al ocate 20 percent of their budget authority to PBVs, which is the measure included in this analysis. HOTMA shifted the formula and cap to 20 percent of agencies’ voucher allocations.

13 The full sample of 39 MTW agencies with MTW designation as of 2019 is reduced to 34 agencies because of a combination of data limitations. The housing authorities of the County of Santa Clara and the City of San Jose report data jointly into the HUD PIH (Office of Public and Indian Housing) Information Center (PIC) and were entered into our analysis as a single PHA. Second, missing Physical Assessment Subsystem (PASS) and Zil ow data required removing the Massachusetts Department of Housing and Community Development, the Alaska Housing Finance Corporation, the Holyoke Housing Authority and the Housing Authority of Champaign County. The analysis includes 412 comparison PHAs for whom PIC, PASS, and Zil ow data were available.

14 Zil ow Rent Index and Zil ow Home Value Index data were acquired from www.zil ow.com/data on November 28, 2018. Aggregated data on this page is made freely available by Zillow for noncommercial use.

15 An alternative measure of a competitive or tight rental market is vacancy rates. We elect to use rising rents because it is more likely to be salient to the PHAs. As PHAs make decisions about the use of PBVs, they are likely more sensitive to changes in rents than in vacancy rates.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

10

3. Research Questions and Study Design

between markets with rising, fal ing, or stable

Research Question 3: To

rents using the change in ZRI between 2011

and 2016.

what extent are Moving to

Work agencies’ project-based

We also expect that PHAs with more

distressed public housing would be more

vouchers located in Rental

motivated to take advantage of HUD

Assistance Demonstration

programs such as the Rental Assistance

or Low-Income Housing Tax

Demonstration (RAD) or Section 18 Demolition

and Disposition that would al ow them to

Credit properties?

improve and convert their public housing

Three measures capture the extent to which

stock and transition units to PBVs. We

MTW agencies’ PBV programs interact with

measure public housing distress prior to the

the RAD and Low-Income Housing Tax Credit

RAD launch in 2012 using REAC PASS scores

(LIHTC) programs as of 2016:

from 2008.

1. The number and share of each MTW and

The model also includes indicator variables

traditional agency’s PBV units that were

for PHA regions, the percent of households in

former public housing units converted

PBVs and in public housing in 2009, to control

to PBVs through RAD (regardless of

for conditions that pre-date our outcome

occupancy status) as of 2016.

measures.

2. The number and share of each MTW

A notable limitation of this analysis is that

agency’s PBV-assisted households living

we are unable to explore the relationship

in former public housing units converted to

between PBVs and supportive services.

PBVs through RAD as of 2016.

Traditional agencies are permitted to dedicate

up to 10 percent more of their HCV al ocations

3. The number and share of each MTW

to PBVs above the 20-percent cap if the

agency’s PBV-assisted households living in

housing provides access to supportive

LIHTC properties in 2016.

services or serves vulnerable populations.

HUD administrative data do not directly

MTW agencies may have unique opportunities

identify which PBV units were converted

and motivation to provide supportive services

from public housing, so it is necessary to

through local partnerships or local, non-

use a combination of administrative data

traditional housing assistance. No data source

sets to differentiate the RAD-converted

identifies housing connected with services,

PBVs from other vouchers and to identify

however, so it is not possible to measure how

households living in those units in 2016. We

often MTW or traditional PHAs take advantage

first identified all MTW agency public housing

of these incentives.

addresses reported in PIC in 2012 through

In analyses presented in appendix B (exhibit

2016 to create an inventory of properties in

B.2), we explore additional factors that could

existence immediately prior to the availability

be related to PBV use through models that

of RAD (which was enacted in 2012). We

use the combined sample of MTW agencies

then matched the MTW public housing

and traditional PHAs and include (or control)

addresses to RAD “First Component” address

for a range of regional characteristics.

data16 for more than 44,000 units converted

16 RAD’s First Component al ows PHAs to convert public housing properties to either PBV or PBRA; the Second Component al ows the conversion of tenant protection vouchers funded under the Rent Supplement, Rental Assistance Payment, and Moderate Rehabilitation programs (see PIH Notice 2012-32). HUD program staff suggested the First Component data were the most relevant to this study because MTW Second Component conversions have been infrequent and TBV-assisted households or units are not consistently identified in HUD administrative data.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

11

3. Research Questions and Study Design

and “closed” through 2016 to identify the

analysis for MTW TBV-assisted households for

properties converted during the first 4 years

comparison.

of the program.17 We then use 2016 PIC data

to identify all households reported as living

This approach is not precise. For example,

in PBV-assisted units and to identify those in

we could incorrectly match a PBV-assisted

PBVs that were converted through RAD.

address to a LIHTC property if it is near but

not actual y in the same development. It is also

There are limitations to this approach.

possible that a mix of LIHTC-subsidized and

Because our study period ended in 2016,

unsubsidized units exist at any given property,

we only include RAD units closed by the end

although it is often the case that most or

of that year—which omits units still in the

all units in a LIHTC property are subsidized

lengthy RAD conversion process. The RAD

(Scal y, Gold, and DuBois, 2018). Alternatively,

program tripled between 2016 and 2019, to

if some LIHTC developments span more than

more than 113,000 units. To account for this,

our estimate of a typical city block, we may

we also identify the total number of units at

omit PBVs located in the larger properties.

MTW agencies that were in the process of

More precise estimates would require

conversion as of March 2018. Our approach

research on local variations in LIHTC property

may also undercount occupied RAD PBVs as

characteristics. In addition, we only examine

of 2016 due to lags in PHA reporting or any

the overlap between LIHTC properties and

inconsistencies in how MTW PHAs reported

PBVs for MTW agencies. Including traditional

RAD conversions to HUD. Nevertheless, our

agencies in these analyses would have been

approach provides the most comprehensive

computational y difficult and beyond the

accounting possible of MTW public housing

scope of this project.

units converted through RAD and reported as

occupied in our study period.

To identify the overlap between PBVs and

LIHTC properties, we used ArcGIS to map

the addresses of all MTW PBV-assisted

households in 2016 PIC data, and all LIHTC

properties active as of 2015 in the National

Housing Preservation Database.18 We drew

a radius of 200 feet around each LIHTC

property—the equivalent of about one city

block—and defined all PBV addresses that

fell within that radius as located in the LIHTC

property.19 We then determined the share of

each MTW agency’s PBV-assisted households

located in LIHTC properties. We repeated this

17 The RAD process involves several stages. First, a PHA submits a RAD application to HUD. If accepted, HUD awards a Commitment to Enter into a Housing Assistance Payment Contract (CHAP). The PHA then submits a Financing Plan to HUD detailing the type of conversion (PBV or PBRA), a physical condition assessment, its plans for rehab or new construction, project operating and maintenance costs, and more. If the plan is accepted, HUD issues a RAD Conversion Commitment (RCC) until work is complete and the property is “closed” and formal y leaves the public housing program with a new PBV or Section 8 PBRA contract in place.

18 We use all properties placed in service between 1987 and 2015 with active LIHTC program tax credits as of 2015.

19 City block sizes vary widely across the country (Handy, Paterson, and Butler, 2003), and can be as small as 200 feet to 800 feet or more (for example, the average city block in New York City is 1,500 feet, see: https://escholarship.org/uc/item/04b2d8xp. We use a radius of 200 feet since existing studies treat 200 feet as a lower bound for the size of an average city block (Galvez et al., 2014). We conducted a sensitivity analysis using varying radii for the LIHTC matching, which we include in appendix G.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

12

3. Research Questions and Study Design

Research Question 4: Are

from the 2012–2016 American Community

Moving to Work agency

Survey (ACS) 5-year sample. The average

county-normalized neighborhood poverty rate

project-based vouchers in

for MTW PBV households is compared with

lower-poverty, higher-quality

that of:

neighborhoods? Do project-

• Households assisted through TBVs by the

based voucher locations

same MTW agency, and

vary by household race or

• Households in public housing assisted by

ethnicity?

the same MTW agency.

We then examine how PBV locations differ

To answer these questions, we first assess

between MTW agencies and comparison

whether PBV-assisted households are in

traditional PHAs. Specifical y, we compare:

higher- or lower-poverty neighborhoods

(census tract) relative to three comparison

• The county-normalized neighborhood

points: (1) other neighborhoods in their same

poverty levels of MTW PBV locations to

housing markets; (2) households assisted

that of comparison traditional PHAs’ PBV

by the same PHA but with TBVs or living in

locations;

public housing; and (3) the locations of PBV

• The difference between PBV and TBV

units at traditional agencies. We also compare

county-normalized neighborhood poverty

differences in neighborhood characteristics for

levels for MTW agencies and that of

PBV, TBV, and public housing locations by the

comparison traditional PHAs; and

race/ethnicity of the assisted households.

• The difference between PBV and public

Previous research shows that in the

housing county-normalized neighborhood

aggregate, neighborhood poverty rates for

poverty levels at MTW agencies with that of

PBVs are roughly the same at MTW and

comparison traditional PHAs.

traditional agencies (Mast and Hardiman,

Each comparison is repeated using six

2017; Galvez, Gourevitch, and Docter,

additional county-normalized measures of

forthcoming). But this comparison does

neighborhood (census tract) quality drawn

not consider variations in local contexts or

from a combination of ACS and HUD’s

voucher holder race/ethnicity. To account for

Affirmatively Furthering Fair Housing (AFFH)

regional variation, we construct indicators of

data. The measures are:

neighborhood quality that are normalized by

• Labor force participation rate (2012–2016

county, which al ow us to compare location

ACS 5-year estimates);

outcomes across MTW agencies while

accounting for the poverty levels or other

• The percent of adults with a bachelor’s

degree (2012–2016 ACS 5-year estimates);

characteristics of the housing markets that

each agency serves.

• Labor Market Engagement Index (HUD

AFFH data);

Neighborhood poverty rates relative to

• Environmental Health Index (HUD AFFH

the county average is the main indicator of

data);

overall neighborhood quality. The county-

normalized neighborhood poverty rate of

• School Proficiency Index (HUD AFFH data);

each household is calculated by dividing the

and

poverty rate of the household’s census tract

• Low Transportation Cost Index (HUD AFFH

by the county poverty rate, using estimates

data).

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

13

3. Research Questions and Study Design

Correlation analysis for these six measures is

To this end, we take the fol owing steps:

included and discussed in appendix B, exhibit

B.4. General y, there is a positive relationship

• We test for differences in county-normalized

between the population with a bachelor’s

neighborhood poverty between RAD and

degree, labor force participation rate, labor

non-RAD PBV properties within the same

market engagement index, environmental

MTW agency.

health index, and school proficiency index.

• We test for differences in county-normalized

Poverty and transportation costs tend to be

neighborhood poverty levels between

negatively correlated with the other measures.

LIHTC and non-LIHTC PBV properties within

The AFFH labor market engagement,

the same MTW agency.

environmental health, and low-cost

• We examine the extent to which our initial

transportation indices are percentile ranks

calculations of differences between PBV and

national y. The school proficiency index is a

public housing locations change with RAD

percentage rank by state. For all four indices,

or LIHTC PBV units removed.

a higher score represents a more desirable

• We examine the extent to which our initial

or higher-quality area. That is, higher values

calculations of differences between PBV and

mean more labor market engagement, fewer

TBV locations change with RAD or LIHTC

environmental hazards, better schools,

PBV units removed.

or lower transportation costs. A county-

normalized value of 1 means that the assisted

households are in neighborhoods that are

Research Question 5: What

typical for the county.

factors are associated with

We then examine locations for Black or

variations in project-based

African-American (non-Hispanic/Latino),

voucher locations?

Hispanic/Latino, and White households. For

To understand the factors associated with

example, we compare neighborhood poverty

variation in MTW and traditional agency

levels for Hispanic/Latino households in PBV

PBV locations, we estimate the relationships

units to neighborhood poverty levels for

Hispanic/Latino households in TBV and public

between local housing market characteristics

housing units at the same MTW or traditional

and PBV locations. We estimate these

PHA. These analyses al ow us to examine

relationships using a combined sample of

whether assisted households’ race or ethnicity

MTW agencies (35) and comparison large

is associated with differential access to

PHAs (411), as well as with a sample of only

lower-poverty, higher-quality neighborhoods

MTW agencies.20

depending on the form of housing assistance.

We define PBV locations using two measures:

Final y, we test whether being associated

• The average (county-normalized)

with LIHTC or RAD influences neighborhood

neighborhood poverty rate for PBVs; and

poverty rates. If RAD or LIHTC units are

in higher-poverty areas, PBVs that are not

• The share of PBVs in high-poverty

associated with those programs may reach

neighborhoods.

lower-poverty areas.

Both measures are calculated using data

20 The full sample of 39 MTW agencies with MTW designation as of 2019 is further reduced because of a combination of data limitations. This analysis focuses only on agencies with PBVs reported in PIC (for MTW PHAs, this excludes the Delaware State, Lawrence-Douglas County, and Home Forward

[Portland, Oregon] housing authorities). The housing authorities of the County of Santa Clara and the City of San Jose report data jointly into PIC

and enter our analysis as a single PHA. Missing PASS and Zil ow data required removing the Massachusetts Department of Housing and Community Development, the Alaska Housing Finance Corporation, and the Holyoke and Champaign County housing authorities. Among the comparison traditional PHAs, 415 reported PBV units, and four were excluded because they lacked data necessary to calculate the dissimilarity index. There are 31

MTW agencies and 261 comparison PHAs that appear in analyses for both research questions 2 and 5.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

14

3. Research Questions and Study Design

from 2016. High-poverty neighborhoods

The estimates produced from these models

are defined as those with poverty rates that

are exploratory and noncausal. They attempt

are more than double the average for their

to uncover factors associated with differences

county.21 The models estimate the relationship

between PHAs in PBV locations. Essential y,

between each outcome measure and the

the models quantify the average differences

following factors:

in local factors between PHAs that have

PBV units in lower-poverty neighborhoods

• Income inequality in the PHA’s primary

(measured relative to the poverty levels in the

county (Gini Index for 2012–2016);

areas they serve) and PHAs that have units in

• Racial segregation in the PHA’s primary

higher-poverty neighborhoods.

county, using the Dissimilarity Index (2010);

• The poverty rate in the PHA’s primary county

Research Question 6: What

(2012–2016);

are the agencies’ motivations

• The fraction of PBV units in RAD properties

for project-based voucher

in 2016 (MTW models only); and

use?

• The fraction of PBV units in LIHTC properties

in 2016 (MTW models only).

To explore MTW agencies’ motivations and

The models that include the comparison

goals for PBV use, we select three agencies

PHAs do not include the fraction of PBV units

known to have extensive or innovative PBV

in LIHTC or RAD properties because we

programs. The agencies selected are Boulder

only calculated those measures for the MTW

Housing Partners, the Cambridge Housing

agencies.

Authority, and the Seattle Housing Authority.

These case studies are not exhaustive, but

We are also interested in understanding

they identify common themes across a subset

whether these factors affect PBV locations

of agencies with substantial PBV use.

above and beyond any influence that

they have on TBV locations and individual

To understand the agencies’ PBV efforts,

voucher holders’ housing options. To this

we reviewed publicly available documents

end, we estimate the models described

such as MTW annual reports and plans22

above with a control variable that accounts

and agency strategic or administrative plans.

for TBV locations. Specifical y, in the

Each of the PHAs reviewed and verified PIC

model that examines the average (county-

data summarizing their PBV use. We also

normalized) neighborhood poverty rate

conducted group phone interviews with three

for PBVs, we add the (county-normalized)

to four people in senior leadership roles at

average neighborhood poverty rate for

each agency who were knowledgeable about

TBV-assisted households, and in the model

the origin and priorities of the agencies’ PBV

that examines the share of PBVs in high-

programs. These group phone interviews

poverty neighborhoods, we add the share of

included executive directors, HCV program

TBV-assisted households in high-poverty

directors, asset management directors, or

neighborhoods.

policy staff.

21 The average poverty rate across counties in the sample is 16 percent, meaning the definition of high poverty on average is 32 percent. Ninety percent of PHAs are in counties with poverty rates between 10 and 27 percent—with the definition of high poverty thus fal ing between 20 and 46 percent, depending on the jurisdiction.

22 MTW housing agency plans and reports are available on HUD’s website. See “Moving to Work (MTW)–Participating Sites,” HUD, https:/ www.hud.gov/

program_offices/public_indian_housing/programs/ph/mtw/mtwagencies

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

15

3. Research Questions and Study Design

In total, six interviews and fol ow-up cal s

cal s and emails, additional document review,

were conducted with MTW agency staff in fal

and analysis of HUD administrative data for

2018. Interview topics focused on an overview

each agency.

of the agencies’ PBV programs, agencies’

motivations and goals for using PBVs, benefits

and tradeoffs of PBV use, and how PBVs

Data

help meet MTW statutory objectives or other

Across the six research questions, we use

goals. We also discussed the specific MTW

five HUD administrative data sources, MTW

PBV flexibilities that were the most useful

annual plans and reports, data describing ZIP

and local partnerships that involve PBVs.

Code and census tract characteristics from

See appendix C for interview protocols. For

three public datasets, and qualitative and

the Cambridge Housing Authority, we also

administrative data collected from the three

had access to information col ected through

MTW agencies. Exhibit 3.1 shows the data

interviews conducted for the companion study

sources. Data sources and the methodology

to this report focusing on the use of MTW fund

for constructing key measures and outcomes

flexibility (Levy, Long, and Edmonds, 2019). We

are described in detail in appendix A.

supplemented these discussions with fol owup

Exhibit 3.1 Data Sources Used for Each Research Question

Research Question

Data Sources

Year(s)

Measures

Number and percent of MTW agencies with PBVs

Number and percent of MTW-assisted households with

PBVs

PIC, VMS, RAD

Percent of MTW agency HCV budget authority devoted

1. How extensively do

Resource Desk,

to PBVs

MTW agencies use PBVs? MTW Plans, and

2016

evaluation data-

Number of PBV activities requiring MTW PBV flexibilities

base

Number of MTW activities that involve or impact PBVs

Number and percent of agencies that use MTW flex-

ibilities to exceed the PBV cap of 20 percent of HCV

budget authority

Percent of PBV-assisted households (2009, 2016)

2. What factors are

Outcome Variables:

Percent of households in public housing (2009)

associated with MTW and PIC, ACS, AFFH,

2016

traditional agencies’ use

REAC, Zillow

REAC Physical Inspection (PASS) scores (2008)

Explanatory Variables:

of PBV assistance?

2008–2016

Zillow Rent Index (ZRI) in 2016

Change in Zillow Rent Index (2011–2016) Region

Number and share of PBV units converted from PH

through RAD (includes unoccupied units)

3. To what extent are

MTW agencies’ PBVs

PIC, RAD Resource

Number and share of each MTW agency’s PBV-assisted

located in RAD or LIHTC

Desk, NHPD

2016

households living in units converted from PH through

properties?

RAD

Number and share of each MTW agency’s PBVs located

in LIHTC properties

(continued)

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

16

3. Research Questions and Study Design

Exhibit 3.1 Data Sources Used for Each Research Question (continued)

Research Question

Data Sources

Year(s)

Measures

County-normalized:

-Neighborhood poverty rate

4. Are MTW agency PBVs

in lower-poverty, higher-

-Labor force participation rate

quality neighborhoods?

PIC, RAD Resource

-Percent of adults with a bachelor’s degree

Do PBV locations vary

Desk, NHPD, ACS,

2009, 2016

-Labor market engagement index

by household race or

AFFH

ethnicity?

-Environmental health index

-School proficiency index

-Low transportation cost index

County-normalized neighborhood poverty rate of PBV

locations

Share of PBVs in high-poverty neighborhoods (2.0 times

the county average)

Characteristics of PHA’s primary county:

Outcome Variables:

5. What factors are

-Income inequality

2016

associated with variations PIC, ACS, AFFH,

-Racial segregation

in PBV locations?

REAC

Explanatory Variables:

2012–2016

-County poverty rate

Average neighborhood poverty rate for TBV households

Percent of TBV households in high-poverty

neighborhoods

Share of PBV units in RAD properties

Share of PBV units in LIHTC properties

MTW Plans and

Annual Plans:

annual reports,

2015 to 2019

MTW evaluation

Annual Reports:

6. What are the agencies’ database, Staff

2012 to 2018

motivations for PBV use?

interviews, findings

Not applicable

from research

MTW evaluation

questions 1, 2,

database: 2015

and 4.

Interviews: 2018

ACS = American Community Survey. AFFH = Affirmatively Furthering Fair Housing. LIHTC = Low-Income Housing Tax Credit. MTW = Moving to Work. NHPD =

National Housing Preservation Database. PASS = Physical Assessment Subsystem. PBV = project-based voucher. PH = public housing. PHA = public housing agency. PIC = PIH (Office of Public and Indian Housing) Information Center. RAD = Rental Assistance Demonstration. REAC = Real Estate Assessment Center. VMS =

Voucher Management System.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

17

4. Quantitative Results

4. Quantitative

percent of households in PBV units, an

18-percent increase, 8 years later. This

Results

effect appears to be driven more by

which agencies use PBVs at all than by

the extent of PBV use. A model with only

This section presents findings for our five

MTW agencies did not detect a statistical y

quantitative research questions. As has been

significant relationship. The small sample

noted elsewhere in the Moving to Work (MTW)

size, however, prevents us from ruling out

evaluation (Levy, Long, and Edmonds, 2019;

the possibility that the same relationship

Galvez, Gourevitch, and Docter, forthcoming;

between public housing quality and PBV use

Treskon, Gerken, and Galvez, forthcoming),

applies to MTW agencies.

MTW agencies are diverse—which is also

• As of 2016, MTW agencies used Rental

evident in their project-based voucher

Assistance Demonstration (RAD) more

(PBV) use. There is considerable variation

frequently than the comparison traditional

across MTW agencies for every measure we

PHAs (39 percent of MTW agencies versus

examined. Considered together, however, our

12 percent of traditional PHAs) and were

findings show that:

more likely to convert to PBVs versus

project-based rental assistance (PBRA) (77

• MTW agencies are more likely to use PBVs

percent of MTW RAD conversions were to

than traditional agencies, but extensive

PBV versus 55 percent at traditional PHAs).

PBV use is not the norm. Just nine MTW

agencies’ PBV use exceeded 20 percent of

• There is a significant overlap between PBVs

their housing choice voucher (HCV) budget

and Low-Income Housing Tax Credit (LIHTC)

authority in 2016.

properties. More than one-fourth of MTW

agencies’ PBVs were in LIHTC properties

• PBV use was associated with being in a

in 2016. Very few of the PBVs in LIHTC

higher-rent housing market. Across MTW

properties are also RAD conversions (about

agencies, PBV use increased more in the

1 percent of all MTW PBVs).

Northeast than in relatively more affordable

regions of the South and Midwest. After

• PBVs do not reach lower-poverty,

control ing for geographic region and the

opportunity-rich neighborhoods; there

rate at which rents were rising, a 10-percent

was no statistically significant difference

difference in rent prices is associated with a

in neighborhood poverty rates of PBV

0.4-percentage-point difference in the share

locations between MTW and comparison

of households served with PBVs.

agencies. At both MTW and comparison

agencies, PBV-assisted households live

• PBV use increased more among agencies

in higher-poverty neighborhoods than

that had more distressed public housing.

the typical tenant-based voucher (TBV)

Between 2009 and 2016, public housing

assisted household at the same PHA.

agencies (PHAs) with lower-quality public

The typical MTW PBV-assisted household

housing increased their use of PBVs more

lives in a neighborhood in which poverty

than agencies with higher-quality public

is 85 percent higher than the average for

housing. A statistical model of MTW and

the agency’s county. At both MTW and

comparison PHAs shows that receiving

comparison traditional agencies, PBV

five fewer points on a Physical Assessment

units are in census tracts with higher

Subsystem (PASS) score in 2008 is

poverty rates than TBV units, with PBV

associated with having an additional 0.7

neighborhoods more closely resembling

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

18

4. Quantitative Results

public housing locations. Using additional

Research Question 1: How

measures of neighborhood quality

provides generally similar results, with two

extensively do Moving to

exceptions. MTW-assisted PBV households

Work agencies use project-

live in neighborhoods with better-than-

based vouchers?

average access to affordable transportation

within their county and in neighborhoods

MTW agencies are more likely to administer

with higher educational attainment than

PBVs compared with traditional PHAs and,

either TBV or public housing households.

on average, dedicate a larger share of their

RAD was not associated with statistically

housing assistance to PBVs (exhibit 4.1). Nearly

significant differences in neighborhood

all MTW PHAs reported at least one PBV-

quality for PBV units.

assisted household in the HUD PIH (Office of

Public and Indian Housing) Information Center

• The concentration of PBV-assisted

(PIC) data in 2016, versus 56 percent of the

households in high-poverty neighborhoods

comparison traditional PHAs. MTW agencies

is greater at PHAs that serve counties with

served more than 41,000 PBV households that

greater racial segregation. This relationship

year, representing almost 1 in 10 MTW-assisted

holds after accounting for TBV locations,

households. The comparison traditional

which implies that racial segregation has a

agencies served slightly more than 105,000

greater influence on PBV locations than on

PBV households that year, accounting for

TBV locations.

about 4 percent of their overall housing

• As is the case with other types of housing

assistance.

assistance, White households receiving

PBV assistance reach lower-poverty, higher-

quality neighborhoods compared with Black

or Hispanic/Latino families.

Exhibit 4.1 Project-Based Voucher Use at Moving to Work and Comparison Traditional Public Housing Agencies Measures

MTW Agencies

Comparison Traditional PHAs

Total PBV households (2016)

41,270

105,669

Percent of PBV assisted households (2016)

9.7%

4.0%

Percent of PHAs with any PBVs (2016)

92.1%

56.1%

Average budget authority to PBVs (January 2017)

13.1%

5.4%

Average number of activities using MTW PBV flexibilities (2015)

2

N/A

Average number of activities involving PBVs (2015)

3

N/A

MTW = Moving to Work. N/A = not applicable. PBV = project-based voucher. PHA = public housing agency.

Notes: We exclude Moderate Rehabilitation units. Comparison traditional PHAs served more than 750 total households in 2016. The average percent of budget authority devoted to PBVs includes agencies with zero budget authority devoted to PBVs.

Sources: 2016 HUD Office of Public and Indian Housing Information Center data; January 2017 Voucher Management System data; 2015 MTW Annual Plans On average, the MTW agencies devoted 13

PHAs, and extensive use of PBVs among MTW

percent of their budget authority to PBVs,

agencies was rare. As of January 2017, only 9

compared with 5 percent at comparison

of the 39 MTW agencies devoted more than

traditional PHAs. Nevertheless, most MTW

20 percent of their budget authority to PBVs.

agencies’ PBV use fal s below the 20-percent

budget authority cap applied to traditional

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

19

4. Quantitative Results

Variation Across Moving to Work

reported five or more activities in 2015, while

Agencies

others—such as Boulder Housing Partners—

There is considerable variation in PBV

had just one or two activities despite having

use across MTW agencies. We summarize

relatively robust PBV portfolios. The four

that variation here and provide results for

MTW agencies (Atlanta, Oakland, Baltimore

individual MTW agencies in appendix B,

City, and County of San Mateo) with relatively

exhibit B.1.

large numbers of activities requiring PBV

flexibility (between 4 and 12) and related to

In 2016, 12 MTW agencies used PBVs

PBVs general y (between 6 and 12) had PBV

relatively sparingly (fewer than 5 percent of

assistance ranging from less than 1 percent to

their assisted households), and three MTW

30 percent of their overall household counts.

agencies had no PBV-assisted units (exhibit

4.2). At the other extreme, four MTW PHAs

served more than one-fourth of their assisted

households through PBVs. One of these

agencies—Cambridge Housing Authority—

provided over one-half of their housing

assistance through PBVs in 2016. The MTW

agencies with the next highest shares of PBV

assistance were Keene Housing (48 percent

of all assisted households), Boulder Housing

Partners (32 percent), and the Atlanta Housing

Authority (30 percent). These four agencies

combined represent 9,554 units, or 23

percent, of all MTW PBVs.

The MTW agencies with larger shares of

households assisted with PBVs also devoted

greater shares of their HCV budget authority

to PBVs. Cambridge Housing Authority

devoted the largest share—two-thirds of its

total HCV budget authority—to PBVs. Other

MTW PHAs with high shares of budget

authority in PBVs include Boulder Housing

Partners (41 percent), Seattle Housing

Authority (33 percent), and Charlotte Housing

Authority (26 percent).

The number of MTW activities requiring MTW

PBV flexibility or involving PBVs also varied

across PHAs and was not a good indicator of

the intensity of agencies’ PBV use. As noted

previously, agencies may consolidate multiple

PBV-related activities or flexibilities into a

single reported activity or report activities

separately. Some PHAs, such as the Atlanta,

Oakland, and Baltimore housing agencies,

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

20

4. Quantitative Results

Exhibit 4.2 Moving to Work Agencies’ Project-Based Vouchers as Percent of Assisted Households, 2016

14

12

10

8

6

4

Number of Moving to Work Agencies

2

0

No PBVs

Fewer than

5 to 10%

10 to 15%

15 to 20%

20 to 25%

More than

5%

25%

Percent of Assisted Households in Project-Based Vouchers

MTW = Moving to Work. PHA = public housing agency.

Notes: Sample excludes Moderate Rehabilitation and includes only project-based vouchers. The Housing Authority of the County of Santa Clara and the Housing Authority of the City of San Jose jointly report data into the HUD Office of Public and Indian Housing Information Center (for a total of 38 MTW observations).

Source: Urban Institute analysis of HUD Office of Public and Indian Housing Information Center data, 2016

Research Question 2: What

A statistical model of PBV use clarifies which

factors are associated

factors are associated with the growth in PBV

with Moving to Work and

use across agencies. The model predicts PBV

use in 2016 using the agency’s region, the

traditional agencies’ use

quality and size of the agency’s public housing

of project-based voucher

stock in 2008 and 2009, the extent of PBV

assistance?

use in 2009, the level of rents in the agency’s

service area in 2016, and the growth of rents

MTW agencies’ use of PBVs grew substantial y

between 2011 and 2016.

between 2009 and 2016, from approximately

3 percent of their total assisted households to

11 percent (see exhibit 4.3).23 During this time,

10 additional MTW agencies began offering

PBV units. Among the comparison traditional

PHAs, the increase in PBV use was more

modest: from about 1 percent of all assisted

households in 2009 to approximately 4

percent in 2016.

23 We use a different calculation of total PBV use for the regression analysis compared with the descriptive assessment of MTW agencies’ PBV use in research question 1, resulting in a slightly different share of PBV use. For the regression analyses we calculate an average of the percent PBV use at each MTW PHA. That is, the average of each PHA’s share of households served by PBVs.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

21

4. Quantitative Results

Exhibit 4.3 Summary Statistics for Moving to Work and Comparison Traditional Public Housing Agencies Standard

Number of

Mean

Min

Max

Deviation

PHAs

MTW Agencies

Percent PBVs in 2016

10.9%

0.0%

50.2%

12%

38

Percent PBVs in 2009

2.8%

0.0%

20.6%

5%

38

Percent in Public Housing in 2009

25.9%

0.0%

53.0%

13%

38

Physical Inspection (PASS) Score in 2008

24

14

30

3.8

37

Rent Index in 2016

$1,805

$860

$4,443

$786

36

5-Year Change in Rent Index

19.7%

-8.3%

63.4%

14%

35

Northeast

18.4%

0

1

39%

38

South

28.9%

0

1

45%

38

Midwest

15.8%

0

1

36%

38

West

36.8%

0

1

48%

38

Comparison Traditional PHAs

Percent PBVs in 2016

3.9%

0.0%

58.9%24

7%

765

Percent PBVs in 2009

0.9%

0.0%

20.6%

3%

751

Percent in Public Housing in 2009

25.1%

0.0%

100.0%

22%

751

Physical Inspection (PASS) Score in 2008

24

11

30

3.5

646

Rent Index

$1,463

$605

$4,616

$601

638

5-Year Change in Rent Index

13.3%

-29.8%

63.4%

13%

588

Northeast

22.1%

0

1

42%

751

South

37.2%

0

1

48%

751

Midwest

19.7%

0

1

40%

751

West

19.7%

0

1

40%

751

MTW = Moving to Work. PASS = Physical Assessment Subsystem. PBV = project-based voucher. PHA = public housing agency.

Notes: The number of PHAs included varies based on data availability. Comparison PHAs are those that assisted at least 750 households in 2016. PASS scores are unavailable for the Massachusetts Department of Housing and Community Development in 2008. Zillow Rent Index data are unavailable for the state of Alaska (Alaska Housing Finance Corporation) and Holyoke, Massachusetts (Holyoke Housing Authority) in 2016 and for Champaign, Illinois (Housing Authority of Champaign County) in 2011. The Housing Authority of the City of San Jose and Housing Authority of the County of Santa Clara are reported jointly in the HUD Office of Public and Indian Housing Information Center (PIC) data and listed here as a single PHA.

Sources: Authors’ calculations based on PIC, Real Estate Assessment Center, and Zillow data Using a sample of both MTW and

of total assisted households, considering that

comparison traditional PHAs (exhibit 4.4,

the average large PHA (MTW or traditional)

column 1), we find that PHAs with more

relied on PBVs to support only 4 percent of

distressed public housing in 2009 used

households, it represents a nearly 18 percent

more PBVs in 2016. The model shows that

increase in PBV units.

receiving five fewer points on a PASS score in

2008 is associated with having an additional

0.7 percent of households in PBV units 8

years later. While that is a small percentage

24 The traditional PHA that had 58.9 percent PBVs in 2016 was a small PHA that had converted two public housing developments to PBVs through RAD.

Under most other circumstances traditional PHAs could not have more the 20 percent of their voucher funding in PBVs at that time.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

22

4. Quantitative Results

Exhibit 4.4 Model Results: Factors Related to the Percent of Assisted Households Assisted by Project-Based Vouchers in 2016

MTW and

Comparison Traditional PHAs

MTW PHAs

-0.011

-0.019

Percent Public Housing (2009)

(0.018)

(0.232)

-0.002*

0.000

REAC PASS Score (2008)

(0.001)

(0.006)

0.040***

0.093

Rent Index (2016)

(0.013)

(0.091)

-0.036

-0.264

Change in Rents (2011 to 2016)

(0.028)

(0.206)

-0.009

-0.169*

South

(0.010)

(0.093)

-0.008

-0.173*

Midwest

(0.010)

(0.100)

-0.000

-0.131

West

(0.011)

(0.113)

1.181***

1.019***

Percent of Households in PBVs in 2009

(0.143)

(0.365)

-0.027

0.001

Constant

(0.033)

(0.300)

Observations

446

34

* p<0.10, ** p<0.05, *** p<0.01.

HH = households. MTW = Moving to Work. PASS = Physical Assessment Subsystem. PBV = project-based voucher. PHA = public housing agency. REAC = Real Estate Assessment Center.

Notes: Samples include MTW PHAs and traditional PHAs with at least 750 households in 2016 and for whom both REAC and Zillow data were available. For MTW

PHAs, this excludes Alaska Housing Finance Corporation; Massachusetts Department of Housing and Community Development; Holyoke Housing Authority; and Housing Authority of Champaign County. Standard errors are heteroskedastic robust and displayed in parentheses. The Housing Authority of the City of San Jose and Housing Authority of the County of Santa Clara household counts in the HUD Office of Public and Indian Housing Information Center data are reported jointly and listed here as a single PHA.

Using the sample of MTW and comparison

The model lacks precision when it uses the

PHAs, the model shows that PHAs in higher-

smaller sample of only MTW agencies (exhibit

rent areas use PBVs more extensively. Even

4.4, column 2). It is unable to determine

after control ing for geographic region and

whether the estimated relationships between

the rate at which rents are rising, we find that

PBV use and public housing quality and the

a 10-percent difference in the price of rent

cost of rent are applicable to MTW agencies

is associated with a 0.4-percentage-point

specifically. Yet, the model shows that

difference in the share of households served

among MTW agencies, PBVs are used more

with PBVs.

extensively in the Northeast than in the South

or the Midwest, with smaller differences

The model does not identify a relationship

between the Northeast and the West.

between the percent of assisted households

in public housing in 2009 and the percent in

Additional models appear in appendix B

PBVs in 2016 or any regional differences in

(exhibit B.2). We examine separately how the

the expansion of PBV use between 2009

factors listed in exhibit 4.4 affect whether

and 2016.

agencies use PBVs at all and the share of

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

23

4. Quantitative Results

PBV-assisted households. Using the sample

by 97 of the traditional PHAs (12 percent of

of MTW and comparison PHAs, we find that

788 PHAs). In total, MTW RAD conversions

PHAs in areas with higher rents are more

represented over one-fourth of all RAD

likely to use PBVs and to use them more

conversions among our sample of PHAs.

extensively. PHAs that had a greater share

of households in public housing in the past

The MTW agencies were more likely than the

(2009) were less likely to have any PBVs in

traditional PHAs to convert units to PBVs than

2016, but agencies with lower PASS scores in

to PBRA. MTW agencies converted about 77

the past (2008) were more likely to have PBVs

percent of their RAD units to PBVs, whereas

in 2016. Neither factor (the share of public

traditional agencies converted 55 percent of

housing assistance and PASS scores) strongly

their RAD units to PBVs. The average number

predicted the share of households assisted

of units per RAD property converted to PBVs

with PBVs in 2016 among agencies with PBVs.

was similar for MTW agencies and comparison

These results suggest that distressed public

traditional PHAs (105 units on average versus

housing is affecting which PHAs use PBVs, but

107).

not the extent to which they use them.

Differences in RAD use remain if conversions

that are still in progress as of March 2018 are

Research Question 3: To

included in the analysis: 22 of the 39 MTW

what extent are Moving to

agencies (about 56 percent) had RAD projects

Work agencies’ project-based

in progress or completed as of March 2018,

compared with 183 of the 788 traditional PHAs

vouchers located in Rental

(23 percent).

Assistance Demonstration

Among the 15 MTW agencies with RAD

or Low-Income Housing Tax

conversions in 2016:

Credit properties?

• Eleven reported PBV-assisted households in

MTW agencies frequently use RAD, and

PIC who were living in former public housing

there is considerable overlap between MTW

converted through RAD. The share of these

agencies’ PBVs and LIHTC properties (exhibits

agencies’ PBV-assisted households that

4.5 and 4.6). In 2016, almost 40 percent of

were living in RAD conversions varied from

all MTW occupied PBVs, representing 16,331

12 percent (Tacoma Housing Authority) to 98

households, were former public housing units

percent (Lexington-Fayette Urban County

converted through RAD and/or located at

Housing Authority).

LIHTC properties (exhibit 4.6). The remaining

• Three agencies—Atlanta Housing Authority,

60 percent of PBVs (24,939 households) were

Holyoke Housing Authority, and Philadelphia

not associated with RAD or LIHTC properties.

Housing Authority—had RAD-converted

PBV units by the end of 2016 but did not

Rental Assistance Demonstration Use at

report PBV-assisted households living in

Moving to Work Agencies

those units in that year. RAD units are not

Exhibit 4.5 summarizes MTW agencies’

occupied immediately after closing, and

RAD use compared with that of similarly

RAD-converted units at these three PHAs

large traditional PHAs. Fifteen of the MTW

may have been unoccupied for these

agencies (39 percent) converted 11,272 public

reasons, or there may have been lags in

housing units through RAD by the end of

reporting newly occupied units into PIC.

2016, compared with 32,996 units converted

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

24

4. Quantitative Results

• One PHA—the Housing Authority of

through RAD (about 5,700 MTW PBV-assisted

Baltimore City—converted public housing

households).25

properties exclusively to PBRAs instead of

PBVs by the end of 2016 (2,553 units).

Exhibit 4.5 presents MTW and traditional

agencies’ RAD properties that had completed

In total, in 2016, about 14 percent of all MTW

the RAD process by the end of 2016.

PBV-assisted households reported in PIC

were living in public housing converted

Exhibit 4.5 Rental Assistance Demonstration Use at Moving to Work and Comparison Traditional Public Housing Agencies, 2016

MTW Agencies

Comparison Traditional PHAs

N=15

N=97

Total RAD RAD PBV RAD PBRA Total RAD RAD PBV RAD PBRA

Number of RAD Properties

97

83

13

302

170

132

# Units Converted to RAD

11,272

8,719

2,553

32,996

18,215

14,781

% Converted RAD Units

100%

77.4%

22.6%

100%

55.2%

44.8%

Average Units per RAD Property

117

105

196

109

107

112

% PHAs Participating in RAD

38.5%

35.9%

2.6%

12.3%

7.6%

5.5%

MTW = Moving to Work. PBRA = project-based rental assistance. PBV = project-based voucher. PHA = public housing agency. RAD = Rental Assistance Demonstration.

Notes: Comparison traditional PHAs are those that serve more than 750 total households in 2016. Includes conversions closed by December 2016. Shares of PHAs participating in RAD are out of 39 MTW PHAs and 788 comparison traditional PHAs.

Source: RAD First Component data downloaded from the RAD Resource Desk (https://www.RADresource.net) in March 2018

Moving to Work Project-Based Vouchers

LIHTC properties. Some anecdotal evidence

in Low-Income Housing Tax Credit

suggests the RAD process can be difficult to

Properties

coordinate with LIHTC, which may explain the

Exhibit 4.6 presents the relationships between

low RAD/LIHTC overlap in the relatively early

PBVs, RAD, and LIHTC properties. More than

years of the RAD program.26

one-fourth of all MTW agencies’ PBVs (about

27 percent, or 10,984 households) were in

LIHTC properties in 2016, using addresses

within 200 feet of a LIHTC property address

as a proxy for co-location. The share was

substantial y smal er for TBVs: about 8 percent

of MTW TBVs, or 21,334 households, were in

LIHTC properties.

A small number of the MTW agency PBVs

(387 of all PBVs, or about 1 percent) were

RAD-converted public housing units located in

25 A small number of MTW RAD units were identified in PIC data as TBVs, likely due to PIC data entry or reporting errors. We omit these units from our analyses.

26 See for example, Lessons from RAD https:/ www.huduser.gov/portal/pdredge/pdr-edge-featd-article-010818.html.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

25

4. Quantitative Results

Exhibit 4.6 Moving to Work Project-Based and Tenant-Based Vouchers in Rental Assistance Demonstration and Low-Income Housing Tax Credit Properties, 2016

MTW PBVs

MTW TBVs

Count

Percent

Count

Percent

Not RAD or in LIHTC property

24,939

60.4%

252,723

92.1%

RAD only

5,347

13.0%

n/a

n/a

In LIHTC property only

10,597

25.7%

21,324

7.8%

RAD and in LIHTC property

387

0.9%

10

0.004%

RAD and/or in LIHTC property

16,331

39.6%

21,716

7.9%

Total

41,270

100%

274,439

100%

LIHTC = Low-Income Housing Tax Credit. MTW = Moving to Work. PBV = project-based voucher. RAD = Rental Assistance Demonstration.

TBV = tenant-based voucher.

Notes: Includes RAD conversions that closed by December 2016 and LIHTC properties active as of 2015.

Sources: 2016 HUD Office of Public and Indian Housing Information Center data; RAD Resource Desk; National Housing Preservation Database address data Variation Across Moving to Work

Research Question 4: Are

Agencies

Moving to Work agency

RAD use and the extent of overlap between

project-based vouchers in

the PBV and RAD or LIHTC programs varied

considerably across MTW agencies for every

lower-poverty, higher-quality

measure calculated. Exhibits B.1 and B.3 in

neighborhoods? Do project-

appendix B provide agency-level results.

based voucher locations

Examples of variation across agencies include

the fol owing:

vary by household race or

ethnicity?

• Among the MTW agencies with closed

RAD PBV units by the end of 2016, the total

We calculate county-normalized measures

number of units ranged from 88 (Holyoke

of neighborhood quality to describe the

Housing Authority) to 2,083 (Chicago

neighborhoods accessed by assisted

Housing Authority).

households. First, within MTW agencies, we

compare the neighborhoods of households

• Twenty-four of the 35 MTW agencies with

assisted with PBVs to the neighborhoods

any PBV-assisted households reported in

of households with TBVs and those of

2016 had PBVs located in LIHTC properties.

households in public housing. Second, we

The overlap ranged from 3 percent of their

compare the neighborhoods of MTW PBV

PBV-assisted households (Housing Authority

households to the neighborhoods of PBV

of the City of Reno) to 65 percent (San Diego

households at traditional PHAs. Third, we

Housing Commission). All MTW agencies

describe and examine the neighborhoods

had at least some TBVs located in LIHTC

accessed by Black (non-Hispanic), Hispanic/

units, ranging from about 0.3 percent of al

Latino, and White (non-Hispanic/Latino)

TBV units (Housing Authority of Champaign

households. Normalized measures al ow us

County) to slightly more than one-fourth

to compare locations while accounting for

(Seattle Housing Authority).

differences in local contexts.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

26

4. Quantitative Results

Project-Based Voucher Neighborhoods

As is typical y the case with MTW agencies,

at Moving to Work Agencies

there is significant variation in outcomes

PBV neighborhood poverty rates relative to

across PHAs. Exhibit B.5 displays the

that of their county average are presented in

average county-normalized neighborhood

exhibit 4.7.

poverty measures for the 35 MTW PHAs

that provided any PBVs in 2016, as per PIC

MTW agency PBV-assisted households

data. Neighborhood poverty rates for PBVs

lived in neighborhoods with poverty rates

ranged from 1.09 times the county average

nearly twice that of their county average in

for the Tulare County Housing Authority to

2016. Relative to the average neighborhood

2.95 times the county average for the Tacoma

in the county, the PBV neighborhoods also

Housing Authority. Meaning that PBVs served

had lower levels of educational attainment,

by the Tulare County Housing Authority are

lower labor market engagement, lower

in neighborhoods that are fairly similar to the

environmental quality (more potential

typical county census tract, while Tacoma

exposure to environmental toxins), and

Housing Authority PBVs are in neighborhoods

lower-performing schools. The fraction of the

with poverty rates 2.95 times the average in

population with a bachelor’s degree in PBV

Pierce County, Washington.

neighborhoods is 17 percent lower than the

county average, while labor force participation

To provide greater local context, we compare

is only 4 percent lower than the county

MTW PBV locations in 2016 with those of

average.

households assisted through TBV or public

housing at the same PHA. Differences in

PBV-assisted households, however,

neighborhood measures between PBV and

tend to live in neighborhoods with lower

TBV and between PBV and public housing

transportation costs (better access to public

appear in exhibit 4.7, with p-values in

transit)—which is consistent with being in

parentheses.

central-city neighborhoods versus suburban

or exurban locations.

Exhibit 4.7 County-Normalized Measures of Neighborhood Quality for Assisted Households at Moving to Work Agencies by Program, Averages and Differences, 2016

MTW PHAs with PBVs and TBVs

MTW PHAs with PBVs and PH

Means

Differences

Means

Differences

(p-value)

(p-value)

PBV

TBV

PBV-TBV

PBV

PH

PBV-PH

1.85

1.58

0.27***

1.87

2.03

-0.16

Poverty Rate

(0.001)

(0.124)

0.83

0.74

0.10**

0.82

0.71

0.11

Percent with Bachelor’s Degree

(0.029)

(0.064)

0.96

0.97

-0.02

0.96

0.94

0.01

Labor Force Participation

(0.123)

(0.334)

0.67

0.69

-0.01

0.66

0.60

0.05

Labor Market Engagement Index

(0.729)

(0.202)

(continued)

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

27

4. Quantitative Results

Exhibit 4.7 County-Normalized Measures of Neighborhood Quality for Assisted Households at Moving to Work Agencies by Program, Averages and Differences, 2016 (continued)

MTW PHAs with PBVs and TBVs

MTW PHAs with PBVs and PH

Means

Differences

Means

Differences

(p-value)

(p-value)

PBV

TBV

PBV-TBV

PBV

PH

PBV-PH

0.61

0.77

-0.15***

0.60

0.64

-0.05

Environmental Health index

(0)

(0.383)

0.71

0.67

0.03

0.69

0.66

0.03

School Proficiency Index

(0.232)

(0.416)

1.24

1.14

0.10***

1.23

1.22

0.02

Transportation Cost Index

(0.001)

(0.58)

Agencies

35

32

* p<0.10, ** p<0.05, *** p<0.01.

MTW = Moving to Work. PBV = project-based voucher. TBV = tenant-based voucher.

Notes: All statistics are normalized to the county mean. Raw values for the labor market engagement index, environmental health index, and transportation cost index are national percentile ranks with higher values signifying better outcomes. School proficiency index is percentile ranked at the state level. This exhibit excludes Delaware State Housing Authority, Lawrence-Douglas County Housing Authority, and Home Forward (Portland, Oregon), who do not have any PBV units.

The Housing Authority of the City of San Jose and Housing Authority of the County of Santa Clara household counts in the HUD Office of Public and Indian Housing Information Center data are reported jointly; they are listed here as a single public housing agency.

At MTW agencies, PBVs are in

Compared with both TBV and public housing

neighborhoods with higher poverty rates

households, PBV households at MTW

than TBVs. The difference in county-

agencies live in neighborhoods with higher

normalized poverty rates is 27 percent

educational attainment. The average MTW

of the regional average. For example, for

PBV household lives in a neighborhood in

MTW agencies in metropolitan areas with

which the share of adults with a bachelor’s

an average poverty rate of 14 percent, this

degree is 17 percent below the county

average. Yet, the typical MTW household

translates into an average PBV neighborhood

assisted with TBVs is in a neighborhood in

poverty rate of about 26 percent and an

which the share of adults with a bachelor’s

average TBV neighborhood poverty rate

degree is 26 percent below the county

of about 22 percent. This difference is

average, and the typical MTW household

statistical y significant (p=0.001).

in public housing lives in a neighborhood in

which the share of adults with a bachelor’s

MTW agencies’ PBVs are in neighborhoods

degree is 29 percent below the county

with similar poverty rates as public

average (exhibit 4.7).

housing neighborhoods. Public housing

neighborhoods have higher poverty rates

Compared with TBV households, PBV

than PBV neighborhoods (an average of 2.0

households live in neighborhoods with lower

times the county average compared with 1.85

transportation costs. Transportation costs

for PBVs). The difference is not statistical y

were measured using HUD’s AFFH data.

significant, however.

Lower transportation costs were expected

because census-tract poverty rates and

the transportation cost index are inversely

correlated.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

28

4. Quantitative Results

Moving to Work Project-Based Voucher

Both MTW and comparison traditional

Locations Compared With Traditional

PHAs’ PBVs are in neighborhoods with

Public Housing Agencies’ Project-Based

higher poverty relative to the average for

Voucher Locations

their counties . PBV households at the typical

Differences in PBV locations between MTW

comparison PHA live in neighborhoods that

agencies and comparison PHAs are presented

have poverty rates 67 percent higher than

in exhibit 4.8.

the county average. This is somewhat lower

than the average normalized poverty rate for

MTW-assisted PBVs (85 percent higher than

the county average), but the difference is not

statistical y significant (p=0.175).

Exhibit 4.8 County-Normalized Measures of Neighborhood Quality for Project-Based Vouchers at Moving to Work and Traditional Public Housing Agencies, 2016

Means

Difference

(p-value)

MTW PBV

Traditional PBV

MTW PBV - Traditional PBV

1.85

1.67

0.17

Poverty Rate

(0.175)

0.83

0.74

0.05

Percent with Bachelor’s Degree

(0.424)

0.96

0.97

0.00

Labor Force Participation

(0.855)

0.67

0.69

-0.02

Labor Market Engagement Index

(0.768)

0.61

0.77

-0.16***

Environmental Health Index

(0.003)

0.71

0.67

-0.01

School Proficiency Index

(0.856)

1.24

1.14

-0.03

Transportation Cost Index

(0.604)

* p<0.10, ** p<0.05, *** p<0.01.

MTW = Moving to Work. PBV = project-based voucher.

Notes: All statistics are normalized to the county mean. Raw values for the labor market engagement index, environmental health index, and transportation cost index are national percentile ranks with higher values signifying better outcomes. School proficiency index is percentile ranked at the state level. This exhibit excludes Delaware State Housing Authority, Lawrence-Douglas County Housing Authority, and Home Forward (Portland, Oregon), who do not have any PBV units.

The Housing Authority of the City of San Jose and Housing Authority of the County of Santa Clara household counts in HUD Office of Public and Indian Housing Information Center data are reported jointly; they are listed here as a single public housing agency.

After accounting for regional differences,

average. The index ranks census tracts based

MTW PBVs are in neighborhoods with poorer

on potential exposure to harmful toxins as

air quality than PBVs at traditional PHAs.

measured in the 2005 National Air Toxins

At both MTW and traditional agencies, PBVs

Assessment. At comparison agencies, the

are in neighborhoods that score lower on the

typical PBV household lives in a neighborhood

Environmental Health Index than the county

that ranks 23 percent lower than the county as

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

29

4. Quantitative Results

a whole. At MTW agencies, this difference is

Project-Based Voucher Location Patterns

39 percent. The gap in normalized measures

by Race and Ethnicity

of environmental health between MTW and

Differences in PBV locations by race/ethnicity

comparison agencies is statistical y significant

and assisted housing program are in exhibit

(exhibit 4.8).

4.9.

At both MTW and comparison PHAs, the

White families reach lower-poverty, higher-

average PBV-assisted household lives in a

quality neighborhoods than Black or

neighborhood with a higher poverty rate

Hispanic/Latino families, across PBVs and

than TBV-assisted households and a lower

other types of housing assistance. Across

poverty rate than public housing residents.

all assistance types, households headed by

We compare the differences between PBV

a non-Hispanic White person tend to live in

neighborhoods and TBV and public housing

census tracts with lower poverty and higher

neighborhoods at MTW agencies (shown

education attainment than households

in exhibit 4.8) with the same differences at

headed by people who identify as Hispanic/

traditional PHAs. Along most measures,

Latino or as non-Hispanic Black or African-

there is no statistical y significant difference

American (exhibit 4.9). PBV-assisted

between MTW and comparison agencies

households live in neighborhoods with worse

at even the 10-percent level (appendix

air quality than TBV households of the same

exhibit B.6). The one exception is that the

race and ethnicity, but in areas with higher

gap in air quality between PBV and TBV

education attainment and better access to

neighborhoods—with PBV households in

transportation than TBV households of the

neighborhoods with worse air quality—is

same ethnicity (exhibit 4.9).

greater at MTW agencies.

Exhibit 4.9 County-Normalized Measures of Neighborhood Quality for Assisted Households at Moving to Work Agencies by Program and Race/Ethnicity, 2016

Means

Differences

Number Differences

Number

(p-value)

of PHAs

(p-value)

of PHAs

PBV

TBV

PH

PBV – TBV

PBV – PH

Poverty Rate

1.88

1.61

2.10

0.27***

35

-0.18

31

Black (non-Hispanic)

(0.002)

(0.136)

1.81

1.53

1.97

0.29***

34

-0.16

31

Hispanic/Latino

(0.007)

(0.241)

1.70

1.43

1.80

0.27***

33

-0.08

30

White (non-Hispanic)

(0.004)

(0.494)

Percent with Bachelor’s Degree

0.84

0.73

0.69

0.11**

35

0.13**

31

Black (non-Hispanic)

(0.011)

(0.027)

0.84

0.73

0.76

0.11**

34

0.07

31

Hispanic/Latino

(0.038)

(0.272)

1.01

0.88

0.86

0.14**

33

0.15*

30

White (non-Hispanic)

(0.045)

(0.083)

(continued)

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

30

4. Quantitative Results

Exhibit 4.9 County-Normalized Measures of Neighborhood Quality for Assisted Households at Moving to Work Agencies by Program and Race/Ethnicity, 2016 (continued)

Means

Differences

Number Differences

Number

(p-value)

of PHAs

(p-value)

of PHAs

PBV

TBV

PH

PBV – TBV

PBV – PH

Environmental Health Index

0.60

0.76

0.65

-0.16***

33

-0.07

28

Black (non-Hispanic)

(0.001)

(0.249)

0.60

0.74

0.63

-0.14***

34

-0.05

30

Hispanic/Latino

(0.001)

(0.395)

0.57

0.75

0.63

-0.18***

31

-0.08

27

White (non-Hispanic)

(0.000)

(0.252)

Transportation Cost Index

1.26

1.14

1.22

0.12***

35

0.04

31

Black (non-Hispanic)

(0.001)

(0.283)

1.24

1.14

1.24

0.10***

34

-0.01

31

Hispanic/Latino

(0.004)

(0.823)

1.25

1.17

1.24

0.08***

33

0.01

30

White (non-Hispanic)

(0.003)

(0.771)

* p<0.10, ** p<0.05, *** p<0.01.

MTW = Moving to Work. PBV = project-based voucher. PH = public housing. PHA = public housing agency. TBV = tenant-based voucher.

Notes: All statistics are normalized to the county mean. Raw values for the environmental health index and transportation cost index are national percentile ranks with higher values signifying better outcomes. School proficiency index is percentile ranked at the state level. Additional measures appear in appendix exhibit B.7.

This exhibit excludes Delaware State Housing Authority, Lawrence-Douglas County Housing Authority, and Home Forward (Portland, Oregon), who do not have any PBV units. The Housing Authority of the City of San Jose and Housing Authority of the County of Santa Clara household counts in HUD Office of Public and Indian Housing Information Center data are reported jointly; they are listed here as a single PHA.

The Relationship Between Rental

PBV properties. Among the MTW agencies

Assistance Demonstration, Low-Income

with LIHTC-financed PBV properties, only

Housing Tax Credit, and Project-Based

two measures showed statistical y significant

Voucher Locations

differences: households in LIHTC-financed

Exhibit 4.10 summarizes county-normalized

PBV properties live in neighborhoods with

neighborhood quality measures for PBV

somewhat better access to transportation and

households in properties financed by RAD and

somewhat worse air quality. Otherwise, PBVs

LIHTC for MTW PHAs that have households

in LIHTC-financed properties were in similar

both in RAD and non-RAD PBV units, or PBVs

neighborhoods as other PBV households with

in both LIHTC and non-LIHTC properties.

regards to poverty, educational attainment,

labor force participation, and school

Among MTW agencies with RAD

proficiency.

conversions, we found no statistical y

significant differences in neighborhood

We also examined differences between MTW

quality measures between RAD and non-

PBV, TBV, and public housing neighborhoods,

RAD PBV units. MTW households in RAD

with RAD and LIHTC units removed from

and LIHTC-financed PBV properties live in

the analyses, to determine if the RAD or

similar neighborhoods to households in other

LIHTC units were driving location outcomes.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

31

4. Quantitative Results

We found few notable differences within

The difference in normalized average

MTW agencies or between MTW and

neighborhood poverty rates between PBVs

comparison agencies when these units were

and public housing is slightly larger when

removed. PBV-assisted households live in

LIHTC and RAD units are excluded, however,

higher-poverty neighborhoods than TBV-

and statistical y significant at the 5-percent

assisted households and in lower-poverty

level.

neighborhoods than public housing residents.

Exhibit 4.10 County-Normalized Measures of Neighborhood Quality for Project-Based Vouchers at Moving to Work Agencies in Rental Assistance Demonstration and Low-Income Housing Tax Credit Properties, 2016

Means

Differences

(p-value)

All PBV

RAD PBV Non-RAD LIHTC PBV Non-LIHTC

RAD –

LIHTC –

PBV

PBV

non-RAD

non-LIHTC

1.85

1.79

1.88

1.80

1.81

-0.08

-0.01

Poverty Rate

(0.707)

(0.926)

Percent with Bachelor’s

0.83

1.02

0.85

0.86

0.84

0.17

0.02

Degree

(0.281)

(0.704)

0.96

0.98

0.95

0.95

0.96

0.03

0.00

Labor Force Participation

(0.431)

(0.756)

Labor Market

0.67

0.83

0.68

0.67

0.74

0.15

-0.07

Engagement Index

(0.215)

(0.138)

0.61

0.57

0.65

0.60

0.68

-0.08

-0.08**

Environmental Health Index

(0.275)

(0.015)

0.71

0.61

0.74

0.67

0.72

-0.13

-0.06

School Proficiency Index

(0.314)

(0.136)

1.24

1.31

1.23

1.23

1.16

0.08

0.07**

Transportation Cost Index

(0.187)

(0.018)

Observations

35

10

24

10

24

* p<0.10, ** p<0.05, *** p<0.01.

LIHTC = Low-Income Housing Tax Credit. MTW = Moving to Work. PBV = project-based voucher. RAD = Rental Assistance Demonstration.

Notes: All statistics are normalized to the county mean. Raw values for the labor market engagement index, environmental health index, and transportation cost index are national percentile ranks with higher values signifying better outcomes. School proficiency index is percentile ranked at the state level. This exhibit excludes Delaware State Housing Authority, Lawrence-Douglas County Housing Authority, and Home Forward (Portland, Oregon), who do not have any PBV units.

The Housing Authority of the City of San Jose and Housing Authority of the County of Santa Clara household counts in HUD Office of Public and Indian Housing Information Center data are reported jointly; they are listed here as a single public housing agency. Observations are limited to agencies with LIHTC or RAD and PBV units.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

32

4. Quantitative Results

Research Question 5: What

poverty rate and (2) the share of PBV-

factors are associated with

assisted households that live in high-poverty

variations in Moving to

neighborhoods (exhibit 4.11, columns 1 and

3). On average, a 10-point difference in the

Work project-based voucher

dissimilarity index corresponds to 8.6 percent

locations?

more PBV households living in high-poverty

neighborhoods (exhibit 4.11, column 3).

We use statistical models to estimate the

relationship between local factors and

Adding the measure of TBV neighborhood

PBV locations. The models estimate the

poverty to the model estimates the extent to

relationship between income inequality,

which racial segregation in the county might

racial segregation, and poverty rates in

correspond to PBV locations differently than

the PHA’s primary county and (1) county-

TBV locations. The relationship between racial

normalized average poverty rate of the

segregation and the share of PBV households

PBV-assisted households’ or (2) the share

remains positive and significant (p=0.01) after

of PBV households that live in high-poverty

accounting for the share of TBV households

neighborhoods. For MTW agencies, the

in high poverty neighborhoods (exhibit 4.11,

models also account for any relationship

column 4). This implies that PBV household

between PBVs, RAD, and LIHTCs.

locations in highly racial y segregated counties

are more sensitive to segregation patterns

In more racial y segregated counties,

than are TBV locations at the same PHA.

PBV households live in higher-poverty

The models do not have enough precision

neighborhoods. There is a positive

to determine whether these relationships

relationship between racial segregation in

hold using the smal er sample of only MTW

the PHA’s county and both (1) PBV-assisted

agencies (exhibit 4.12).

households’ average county-normalized

Exhibit 4.11 Model Results: Factors Related to Neighborhood Poverty of Project-Based Vouchers at Moving to Work and Traditional Public Housing Agencies

Average County-Normalized

Percent of PBVs in High-Poverty

Neighborhood Poverty Rate of PBV

Neighborhoods

Locations

(1)

(2)

(3)

(4)

-1.853

-1.392

-0.865

-0.430

Income Inequality

(1.432)

(1.133)

(0.659)

(0.584)

1.457***

0.342

0.856***

0.360***

Racial Segregation (Dissimilarity Index)

(0.290)

(0.223)

(0.130)

(0.114)

-3.894***

0.138

-2.320***

-0.700**

County Poverty Rate

(0.674)

(0.554)

(0.310)

(0.312)

Average Neighborhood Poverty Rate of TBV

1.131***

Households

(0.079)

Percent of TBV Households in High-Poverty

0.942***

Neighborhoods

(0.077)

(continued)

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

33

4. Quantitative Results

Exhibit 4.11 Model Results: Factors Related to Neighborhood Poverty of Project-Based Vouchers at Moving to Work and Traditional Public Housing Agencies (continued)

Average County-Normalized

Percent of PBVs in High-Poverty

Neighborhood Poverty Rate of PBV

Neighborhoods

Locations

(1)

(2)

(3)

(4)

2.544***

0.438

0.729***

0.252

Constant

(0.584)

(0.454)

(0.268)

(0.238)

Observations

446

446

446

446

* p<0.10, ** p<0.05, *** p<0.01.

PBV = project-based voucher. TBV = tenant-based voucher.

Notes: Average neighborhood poverty is the average county-adjusted poverty rate of the census tracts of PBV households. High poverty neighborhoods are census tracts with poverty rates of at least 2.0 times the county average. Samples include public housing agencies (PHAs) with PBV units and at least 750

households in 2016 and for whom both American Community Survey and Affirmatively Furthering Fair Housing data were available. For Moving to Work PHAs, this excludes Delaware State Housing Authority, Lawrence-Douglas County Housing Authority, and Home Forward (Portland, Oregon), who do not have any PBV units.

Standard errors, displayed in parentheses, are heteroskedastic robust. The Housing Authority of the City of San Jose and Housing Authority of the County of Santa Clara household counts in HUD Office of Public and Indian Housing Information Center data are reported jointly and listed here as a single PHA.

PBV locations tend to mirror TBV locations.

4.12). This implies that differences between

PBV-assisted households were more likely to

PBV and TBV neighborhoods are generally

live in high-poverty neighborhoods at PHAs

consistent across PHAs. Additional y, the

with more TBV households living in high-

estimated relationships between poverty and

poverty neighborhoods (exhibits 4.11 and 4.12).

racial segregation at the county level and PBV

The estimated relationship between PBV and

neighborhood poverty are closer to zero in the

TBV location outcomes is close to one in al

model that accounts for TBV locations. This

four versions of the model (columns 2 and 4

implies that these factors are associated with

of exhibit 4.11 and columns 2 and 4 of exhibit

both PBV and TBV locations.

Exhibit 4.12 Model Results: Factors Related to Neighborhood Poverty of Project-Based Vouchers at Moving to Work Agencies Average County-Normalized

Percent of PBVs in High-Poverty

Neighborhood Poverty Rate of PBV

Neighborhoods

Locations

(1)

(2)

(3)

(4)

-2.515

-1.433

-1.296

-0.842

Income Inequality

(3.810)

(3.677)

(2.014)

(1.950)

0.517

-0.895

0.451

-0.432

Racial Segregation (Dissimilarity Index)

(0.719)

(0.801)

(0.511)

(0.547)

-2.203

1.757

-1.657*

0.787

County Poverty Rate

(1.821)

(2.006)

(0.925)

(1.176)

0.266

0.233

-0.045

-0.134

Fraction of PBV Units in RAD Properties

(0.346)

(0.335)

(0.206)

(0.196)

0.619

0.562

0.249

0.230

Fraction of PBV Units in LIHTC Properties

(0.455)

(0.412)

(0.307)

(0.259)

Percent of TBV Households in High-Poverty

0.966***

1.118***

Neighborhoods

(0.235)

(0.280)

(continued)

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

34

4. Quantitative Results

Exhibit 4.12 Model Results: Factors Related to Neighborhood Poverty of Project-Based Vouchers at Moving to Work Agencies

(continued)

Average County-Normalized

Percent of PBVs in High-Poverty

Neighborhood Poverty Rate of PBV

Neighborhoods

Locations

(1)

(2)

(3)

(4)

2.976*

0.948

1.042

0.544

Constant

(1.594)

(1.619)

(0.793)

(0.784)

Observations

35

35

35

35

* p<0.10, ** p<0.05, *** p<0.01.

LIHTC = Low-Income Housing Tax Credit. MTW = Moving to Work. PBV = project-based voucher. RAD = Rental Assistance Demonstration. TBV = tenant-based voucher.

Notes: High-poverty neighborhoods are census tracts with poverty rates of at least 2.0 times the county average. Samples include public housing agencies (PHAs) with PBV units and at least 750 households in 2016 and for whom both American Community Survey and Affirmatively Furthering Fair Housing data were available. For Moving to Work PHAs, this excludes Delaware State Housing Authority, Lawrence-Douglas County Housing Authority, and Home Forward (Portland, Oregon), who do not have any PBV units. Standard errors, displayed in parentheses, are heteroskedastic robust. The Housing Authority of the City of San Jose and Housing Authority of the County of Santa Clara household counts in HUD Office of Public and Indian Housing Information Center data are reported jointly and listed here as a single PHA.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

35

5. Case Studies of Three Moving to Work Agencies’ Project-Based Voucher Use 5. Case Studies of

Common Perspectives on

Three Moving to Work Project-Based Voucher Use

Several common themes emerged about

Agencies’ Project-

how and why the three agencies use PBV

assistance. Appendix E summarizes the

Based Voucher Use

specific MTW activities and waivers related

to each agency’s PBV use, as documented in

MTW plans and recorded in the database of

MTW activities created for the broader MTW

In this section, we summarize findings from

evaluation.

research question 6, our review of three public

housing agencies’ (PHAs’) project-based

The three PHAs maximize their MTW

voucher (PBV) programs. The three agencies

flexibilities to pursue MTW housing choice

included are Boulder Housing Partners,

and cost-effectiveness objectives. As

Cambridge Housing Authority, and the Seattle

summarized in the overview of the MTW PBV

Housing Authority. We first discuss common

flexibilities section above, there are five main

themes that emerged from the three agencies

PBV flexibilities available to MTW agencies.

about how and why they use PBV assistance.

Agencies may exceed the PBV funding cap;

We then present summaries of each agency’s

exceed the cap on the share of PBV units in

PBV activities along with additional detail on

a single property; establish contracts longer

each agency.

than 15 years; use flexibilities related to

selecting properties for PBVs; and waive or

These agencies were selected because they

revise the Family Right to Move requirement

are among the highest users of PBVs among

for PBV units. All three agencies included

all PHAs national y. For example, the average

in our case studies use at least two of the

Moving to Work (MTW) agency with any PBV

PBV flexibilities, combined with flexibilities

units devotes approximately 13 percent of

available for HCV program administration

their housing choice voucher (HCV) budget

general y. In MTW plans and reports, all three

authority to PBVs, while these three agencies,

agencies tie their PBV activities and waivers

on average, devote 47 percent (see exhibit

to the housing choice and cost-effectiveness

B.1). Combined, the PBVs of these three

objectives—although each agency noted in

agencies represent approximately 18 percent

interviews that PBVs can also indirectly impact

of all MTW PBV assistance in 2016. All three

the MTW self-sufficiency objective.

agencies also operate in tight, expensive

housing markets that have experienced

Specifically, all three agencies waive the cap

rapidly increasing rental costs. For example,

on the share of HCV budget authority that

rental vacancy rates were below 4 percent in

may be applied to PBVs and the cap on the

2016 in all three jurisdictions as per 2013–2017

number of PBV units that may be in a single

American Community Survey (ACS) 5-year

property. Among the three agencies, the

sample data, compared with 10 percent on

share of budget authority applied to PBVs in

average for MTW agencies and 15 percent for

2016 was the lowest for Seattle (31 percent)

all traditional agencies. Exhibits 5.1, 5.2, and

and highest for Cambridge (67 percent). Each

5.3 summarize key characteristics for each

of the agencies subsidizes properties that are

agency, including PBV use and local market

100 percent PBVs. Cambridge does not use

characteristics.

additional MTW PBV flexibilities, while Boulder

uses one of the remaining flexibilities related

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

36

5. Case Studies of Three Moving to Work Agencies’ Project-Based Voucher Use to property selection but does not waive the

contexts. For example, all three noted that

15-year maximum contract term. Seattle uses

PBVs provide opportunities to preserve or

all four flexibilities. Each of the agencies also

secure affordable units in areas with high

applies additional HCV program flexibilities to

or rapidly rising rents, whereas TBV families

their PBVs, such as adjusting unit or income

have difficulty finding voucher-affordable

eligibility requirements, waitlist policies,

housing or landlords that accept vouchers.

or Housing Quality Standards inspection

Boulder Housing Partners and the Cambridge

processes. Each of the agencies retains partial

Housing Authority discussed their local

or full ownership in at least one property with

housing markets as challenging for TBV

PBVs. Additional y, both Cambridge Housing

holders citywide, whereas the Seattle Housing

Authority and Seattle Housing Authority

Authority said specific neighborhoods or

use their flexibility to limit the Family Right

submarkets were difficult for TBV-assisted

to Move requirement in some capacity:

households to enter.

the Seattle Housing Authority waives the

requirement completely, and the Cambridge

Staff from each of the agencies also said that

Housing Authority extends the timeframe

year-to-year increases in housing assistance

when assisted households become eligible to

payment costs could be more predictable for

request a mobile voucher from 1 to 2 years.

PBVs compared with TBVs in areas where

rents are rising quickly. Whereas individual

Agencies use PBVs to facilitate partnerships.

landlords may raise rents substantial y at the

PBVs were described by each of the three

end of a lease period—triggering increased

PHAs as facilitating a variety of partnerships

housing assistance payments, a move by the

with community stakeholders (for example,

assisted family, or increased rent burdens,

city or county officials, housing providers, or

PBV Housing Assistance Payments (HAPs),

service providers) to further local affordable

and annual increases are established in

housing priorities or initiatives. For example,

PBV contracts. This al ows agencies to

this included a longstanding partnership

build increases in their longer-term financial

between the Seattle Housing Authority and

planning. For example, PBV contract rents

the city of Seattle to use PBVs to augment

are determined by the lowest of the fol owing:

local Housing Tax Levy funds to address

up to 110 percent of the fair market rent,

homelessness. In Boulder, the housing

reasonable rent, or rent requested by the

authority launched a multi-partner, place-

owner.27 In Cambridge, between 2011 and

based education initiative in several PBV-

2016, the fair market rent for a two-bedroom

assisted communities. The ability to pursue

unit increased about 16 percent. In contrast,

common goals with local partners and be

the average rent of a two-bedroom unit

responsive to local housing needs was noted

in Cambridge increased about 31 percent

as a key motivation for all three agencies’ PBV

between 2011 and 2016 (Zil ow Rental

use.

Index data). A tradeoff for this increased

predictability is that PBV program costs are

PBVs allow the PHAs to be more effective

comparatively difficult to reduce in the short-

in tight housing markets. As noted, each of

to medium-term in times of financial constraint

the three agencies is in expensive housing

because PBVs are tied to contracts ranging

markets with low vacancy rates. Agency staff

from 15 to 40 years across the agencies. TBV

noted advantages to PBVs compared with

costs can be reduced in the shorter term by

tenant-based vouchers (TBVs) in such market

27 See 24 CFR 983.301, subpart G, for more information: https:/ www.govinfo.gov/content/pkg/CFR-2017-title24-vol4/pdf/CFR-2017-title24-vol4-part983.

pdf.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

37

5. Case Studies of Three Moving to Work Agencies’ Project-Based Voucher Use slowing voucher issuances or not re-issuing

Neither the Seattle Housing Authority nor

vouchers after normal program attrition, but

Boulder Housing Partners has documented a

both options involve serving fewer assisted

maximum PBV target in MTW annual plans or

households.

reports, and neither agency had immediate

plans to expand substantial y over their current

PBVs offer opportunities for administrative

use (about 33 and 41 percent of HCV budget

efficiency. Agency staff said the MTW

PBV flexibilities offered opportunities for

authority in 2016, respectively). Boulder

administrative efficiencies—and subsequent

Housing Partners described an opportunistic

cost offsets for the agencies—that TBVs do

or entrepreneurial approach to PBV expansion

not. For example, Boulder Housing Partners’

decisions and suggested that shifting to more

staff discussed site-based waiting lists

PBV units could be appropriate if the right

administered by individual property owners

partnership or strategic opportunity emerged

and managers as al owing the PHA to free up

that would benefit from PBV use. Staff also

staff time for other tasks, in addition to helping

noted the housing authority’s board would

the agency efficiently connect households

not support a transition to 100 percent PBV

to suitable units and properties. The Seattle

use, and there would be limitations on their

Housing Authority staff also noted that

expansion. In Seattle, a primary consideration

conducting inspections at properties with

for assessing the appropriate level of PBV

multiple PBV-assisted units is more efficient

use was described as the need to maintain

than inspecting geographically dispersed

a balanced portfolio of housing assistance

units or units that require interacting and

available to meet the needs of different

coordinating with multiple owners or

populations. The PBV program and Seattle

managers. In addition, by al owing owners

Housing Tax Levy partnership tends to serve

to conduct their own turnover inspections

primarily single adults, which contrasts with

for mid-year vacancies, the Seattle Housing

the pressing need for housing assistance

Authority reduced the number of annual staff

among low-income families on the TBV

hours spent conducting inspections.

waitlist.

Maintaining a balance of TBVs and PBVs.

Each of the PHAs discussed the need to

Project-Based Vouchers and

maintain a portfolio of TBVs as well as

Neighborhood Location

PBVs, and the limitations on PBV use. None

expected to transition to 100 percent PBVs,

None of the three agencies explicitly use PBVs

and all acknowledged the importance

to target low-poverty or high-opportunity

of maintaining the residential mobility

neighborhoods. Each of the agencies,

opportunities that TBVs offer. Agency

however, tied their PBV activities to a broad

leadership said they periodical y discuss the

definition of housing choice—emphasizing

appropriate balance of HCV use and whether

that PBVs increase local affordable housing

to expand PBVs. The Cambridge Housing

options for low-income people citywide and

Authority, with the most aggressive PBV use

the benefits associated with their current PBV

among the three agencies, said they had

locations.

maximized their PBV use. Their 2017 MTW

Annual Report documented a benchmark

For example, the Cambridge Housing

of 70 percent of their HCV budget authority

Authority and Boulder Housing Partners

to be applied to PBVs, and as of 2016, PBVs

described their jurisdictions as general y

accounted for 67 percent of their budget

wealthy and opportunity-rich. The Cambridge

authority.

Housing Authority staff viewed the city

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

38

5. Case Studies of Three Moving to Work Agencies’ Project-Based Voucher Use as a whole—which is only 7 square miles

Authority PBV-assisted households lived

and is home to Harvard University and the

in slightly higher (4 to 5 percentage points)

Massachusetts Institute of Technology—as a

poverty areas than the agencies’ TBV-assisted

resource-rich environment that is difficult for

households.

TBV holders to access. This characterization

of their PBV efforts as general y offering

Notably, two of the three agencies revise

access to opportunity areas is reflected in

or waive the PBV program family right to

the MTW activities reported to HUD. Galvez,

move requirement. The Cambridge Housing

Simington, and Treskon (2017) found that the

Authority requires PBV-assisted households

Cambridge Housing Authority was one of only

to remain in their unit for 2 years (instead of 1)

four PHAs that reported PBV activities related

before they are eligible for a portable voucher,

to neighborhood mobility outcomes. Boulder

and the Seattle Housing Authority waives the

Housing Partners similarly highlighted the

requirement entirely. A preliminary scan of the

city’s relatively low poverty rates as a reason

MTW activities database for activities related

for not explicitly prioritizing low-poverty

to the family right to move requirement found

neighborhood locations. In addition, many of

that, as of 2015, at least 15 agencies reported

the Boulder Housing Partners and Cambridge

an activity that mentioned waiving or revising

Housing Authority PBV units are former public

the requirement (see appendix F). This is

housing units converted through RAD and tied

likely an undercount since agencies may have

to the original public housing locations.

started an activity after 2015, may report

policy changes separately from an activity (as

The Seattle Housing Authority staff noted the

does the Boulder Housing Partners), or use

city’s downtown area, where many of their

different terminology in their reporting (for

PBV units are located, was identified as an

example, “exit vouchers”) that would require

opportunity area by a Kirwan Institute and

a more thorough document review to identify.

Puget Sound Regional Council analysis—

The most common change listed in the

in part because of the proximity to public

activities database was to extend the length of

transportation and social services.28,29 For

time a household must live in a PBV-assisted

formerly homeless PBV residents, who

property before being eligible for a TBV to 2

account for most of their PBV occupants,

years instead of 1.

access to these resources can be essential to

helping them be successful.

Boulder Housing Partners:

PIC data show that the three agencies’ PBVs

Public Housing Conversion

tend to be in neighborhoods with moderate

and Local Partnerships

poverty rates: the average neighborhood

poverty rate for PBVs was 21 percent for the

They’re bringing their services and we’re bringing

Cambridge and the Seattle Housing Authority,

the housing, so it’s a match made in heaven.

and 23 percent for Boulder Housing Partners.

—Boulder Housing Partners

For the Seattle Housing Authority, average

PBV neighborhood poverty rates were similar

Since receiving MTW designation in 2011, the

across the TBV, PBV, and public housing

Boulder Housing Partners has focused their

programs (close to 20 percent). The Boulder

PBV efforts on converting their public housing

Housing Partners and Cambridge Housing

stock to PBVs and transitioning ful y to HCV

28 For more information, see the Puget Sound Regional Council’s “Opportunity Mapping”: https:/ www.psrc.org/opportunity-mapping.

29 Seattle Housing Authority is also piloting a neighborhood mobility program using TBVs to support moves to opportunity-rich neighborhoods. For more information, see: https:/ www.seattlehousing.org/creating-moves-to-opportunity-seattle-king-county-pilot-project-fact-sheet.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

39

5. Case Studies of Three Moving to Work Agencies’ Project-Based Voucher Use assistance. (See exhibit 5.1.) They also have

PBV flexibilities specifical y are central to

partnered with local housing and service

pursuing the agency’s goals. Waivers to the

providers to pursue a comprehensive place-

PBV budget authority and units per property

based education initiative and in their 2015

caps were included in the agency’s first MTW

MTW plan committed to contributing 2,000

Annual Plan after receiving MTW designation

new affordable units to Boulder’s permanently

(BHP Annual Plan, 2012). The agency’s 2018

affordable inventory by 2025.

annual plan specifically calls out “strategic use

of project-based vouchers” among the MTW

Staff said in interviews that MTW PBV

flexibilities and approaches needed to achieve

flexibilities were a motivation for pursuing

their 2,000-unit production goal.

MTW status. MTW status general y and MTW

Exhibit 5.1 Boulder, Colorado and Boulder Housing Partners (BHP)

• Boulder had a population of about 106,000 people in 2017—an increase of nearly 10 percent since 2010. HUD’s estimate of the median family income for 2018 was $108,594.

• Median rent for a two-bedroom unit in Boulder was $2,650 in 2016 and, between 2011 and 2016, the average rent increased by about 18 percent. The rental vacancy rate was 3.5 percent in 2017.

• BHP received Moving to Work (MTW) designation in 2011.

• BHP served 1,288 households in 2016, primarily through housing choice voucher (HCV) assistance:

» 417 project-based voucher (PBV) households (32 percent);

» 822 tenant-based voucher households (64 percent); and

» 49 public housing units (4 percent).

• BHP applied 41 percent of its HCV budget authority to PBVs in 2016 and operates 10 sites with PBV units. PBV use increased from 32 units in 2011 to 417 in 2016 (from 3 to 32 percent of all BHP assistance).

• BHP’s PBV-assisted households were more likely to be families with children compared with their typical assisted households (46 percent of PBV households versus 38 percent of all assisted households). They also were less likely to be White (57 percent compared with 67 percent) and more likely to be Hispanic/Latino (37 percent compared with 26 percent).

Sources: 2013–2017 American Community Survey, 5-year estimates; HUD Fiscal Year 2018 Median Family Income Documentation System: https://www.huduser.

gov/portal/datasets/il/il2018/2018MedCalc.odn; HUD Office of Public and Indian Housing Information Center dataset; Zillow Rental Index: https://www.zillow.com/

research/data/

Boulder Housing Partners formal y ties its

Staff described how PBVs and the

PBV use to the housing choice and cost-

combination of PBV flexibilities help

effectiveness MTW statutory objectives,

the agency impact the MTW statutory

although staff said in interviews that their

objectives. For example, site-based waiting

PBV program also addresses family self-

lists can help the agency more efficiently

sufficiency. In 2018, the agency consolidated

place households into properties and

MTW activities enacted in previous years

units that meet their needs and offer more

into a single PBV program activity. In addition

housing choices. Staff said that converting

to waiving the PBV caps, the activity al ows

units to PBVs as opposed to TBVs also

Boulder Housing Partners to project base 100

allowed Boulder Housing Partners to

percent of units in a single project and to use

maintain the same demographic mix in

site-based waitlists. The activity also modifies

their properties as in their traditional

several administrative policies for their HCV

public housing. The Bringing School Home

program, including local rent reasonableness

initiative, located at five former public

tests, rent limits, HQS inspections, and income

housing communities converted to 100

requirements.

percent PBVs, is intended to help close gaps

in educational achievement for low-income

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

40

5. Case Studies of Three Moving to Work Agencies’ Project-Based Voucher Use children and support long-term economic

Bringing School Home. Bringing School

self-sufficiency.

Home is a place-based initiative currently

operating in five former public housing

Agency staff identified three specific

properties that were converted to 100 percent

programmatic efforts they believe have been

PBVs. Local partners manage the PBV

supported by MTW PBV flexibilities.

communities and provide a variety of on-site

Partnerships. Strong partnerships with local

services for children up to 6 years old through

service providers are central to Boulder

a variety of educational and enrichment

Housing Partner’s organizational goals. Staff

supports for them and their families. The

noted that the re-naming of the organization

Emergency Family Assistance Association

in 2001 from the Housing Authority of the

manages the waitlist for these properties

City of Boulder to Boulder Housing Partners

and is responsible for the screening and

reflects a longstanding emphasis on service

admission. An example of services offered

partnerships that predates their MTW status.

to residents includes the “I Have a Dream”

These partnerships do not usual y come with

Foundation’s programming. The program

additional service dol ars attached; rather, staff

seeks to reduce the gap in educational

emphasized that both the Boulder Housing

outcomes between low-income students and

Partners and their affiliates see the value in

their peers by maximizing the amount of time

connecting families already receiving services

children spend in educationally enriching

to Boulder Housing Partners-assisted units.

activities.30

For example, Boulder Housing Partners joins

with the Boulder Shelter for the Homeless,

Cambridge Housing Authority:

which provides case management for

homeless individuals and families and helps

Preserving Affordable

them transition into PBV-assisted housing.

Housing with Project-Based

Vouchers

Project Renovate. Completed in 2017, Project

Renovate converted 279 public housing

“The Project-Based Voucher (PBV) Program is

units in 6 properties to PBV units using RAD

considered a community resource, both to support

and Section 18 (Demolition and Disposition).

and preserve existing housing, and to expand

Boulder Housing Partners converted units to

affordable housing development in Cambridge.”

PBVs instead of PBRAs through RAD to retain

—Administrative Plan for the Federal HCV

the use of MTW PBV flexibility for these units.

Program

Staff said that a goal for the conversions was

Cambridge Housing Authority (2013)

to retain the same households, demographic

mix, and level of affordability for the converted

Rapidly rising rents and extreme pressure on

properties as in their original public housing

the affordable housing stock in and around

portfolio. The housing authority has converted

the city of Cambridge provides the motivating

135 units to PBVs through RAD, amounting to

context for the PHA’s MTW and PBV program

about 33 percent of their PBV-assisted units.

priorities. In 2014, only 54 units of housing

Two additional PBV public housing property

were available to every 100 extremely low-

conversions have been completed through

income households in Middlesex County; 35

the Section 18 Demolition and Disposition

of these units were HUD-subsidized (Poethig

program (2018 annual report).

et al., 2017). Approximately 30 percent of

Cambridge’s population is students, which

30 For more information about the Bringing School Home program, see: https:/ boulderhousing.org/bringing-school-home.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

41

5. Case Studies of Three Moving to Work Agencies’ Project-Based Voucher Use places additional demands on the lower end

out of the jurisdiction. TBV holders who

of the rental housing market.31 Rents have

remain in Cambridge may face annual rent

been rising rapidly in the Cambridge area

increases beyond the TBV voucher payment

since 1994, when rent control ended in the

standard—set at 126 percent of fair market

state of Massachusetts. (see exhibit 5.2)

rent—potential y triggering a move, higher

HAPs, or additional rental costs and higher

The housing authority’s MTW and PBV

rent burdens for assisted households.

programs center on creating and preserving

affordable units in Cambridge. In interviews,

Agency staff identified three specific

staff emphasized that TBVs are difficult to

programmatic efforts that they believe are

use local y, with 47 percent of TBVs porting

facilitated by MTW PBV flexibilities.

Exhibit 5.2 Cambridge, Massachusetts and the Cambridge Housing Authority (CHA)

• Cambridge’s population is approximately 111,000.

• The median family income is $107,845.

• Median rent for a two-bedroom unit in Cambridge was $2,930 in 2016. The rental vacancy rate was 3.4 percent.

• CHA received Moving to Work designation in 1999.

• CHA served 6,431 households in 2016:

» 3,240 project-based voucher (PBV) households (50 percent);

» 1,742 tenant-based voucher (TBV) households (33 percent); and

» 970 public housing units (15 percent).

• Since 2008, the PBV program expanded from 99 households to 3,240. This includes 1,150 public housing units converted through the Rental Assistance Demonstration (28 percent of the CHA PBV-assistance). The Cambridge Housing Authority applied about 67

percent of its Housing Choice Voucher budget authority to PBVs in 2016.

• CHA PBV households were more likely to be headed by a man and to be single adults compared with CHA’s public housing or TBV-assisted households. The Cambridge Housing Authority does not target a specific population with PBVs.

Sources: 2013–2017 American Community Survey, 5-year estimates; HUD Fiscal Year 2018 Median Family Income Documentation System: https://www.huduser.

gov/portal/datasets/il/il2018/2018MedCalc.odn; HUD Office of Public and Indian Housing Information Center dataset; Zillow Rental Index: https://www.zillow.com/

research/data/

The Expiring-Use Preservation Program.

Voucher,32 which al ows them to remain in

About one-half of the Cambridge Housing

their unit; however, if the resident leaves their

Authority PBVs—about 1,800 vouchers in 18

original unit, the Enhanced Voucher converts

properties—were issued through the Expiring-

to a mobile voucher, and the original unit

Use Preservation Program, which focuses on

becomes unsubsidized and likely converted

preserving units in and around Cambridge.

to a market-rate unit. Through the Expiring-

Through this program, the Cambridge Housing

Use Preservation Program and their MTW

Authority identifies units in the private rental

authority, the Cambridge Housing Authority is

market with an existing subsidy that are

able to work with the owner to preserve the

nearing their expiration date (for example, the

tenancies of the existing residents in addition

prepayment or expiration of a Section 236

to preserving the long-term affordability of

mortgage, HUD legacy programs like Rent

these units. While initial y used solely in the

Supplement program and Rental Assistance

city of Cambridge, the Cambridge Housing

Payment). Upon expiration of these subsidies,

Authority has expanded this program to

eligible residents may receive an Enhanced

owners in surrounding cities, including

31 “Demographics and Statistics FAQ.” Cambridge Development Department, accessed February, 2019, https:/ www.cambridgema.gov/CDD/

factsandmaps/demographicfaq.

32 For more information about HUD’s Enhanced Vouchers, see: https:/ www.hud.gov/sites/documents/ENHANCED_VOUCHERS_ENG.PDF.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

42

5. Case Studies of Three Moving to Work Agencies’ Project-Based Voucher Use Lynn, Southbridge, Worcester, and several

that their development partners could

neighborhoods of Boston. The preservation

access properties or neighborhoods that the

program relies on partnerships between the

housing authority may not be able to access

PHA, property owners, residents, community

alone. They also stated that most of their

stakeholders, and, if outside of Cambridge,

partnerships are long-standing and formalized

the local PHAs.

through Memoranda of Understanding and

were formed when organizations approach

Public housing conversion through RAD.

the PHA with col aboration ideas.

Just under 30 percent of the agency’s PBV-

assisted units are in former public housing

properties converted through RAD. The

Seattle Housing Authority:

Cambridge Housing Authority converted

Using Project-Based Vouchers

units to PBVs rather than PBRAs to retain

to Serve People Exiting

MTW flexibilities for rent simplification and to

retain voucher administrative fees, providing

Homelessness

additional cash flow to leverage debt for

“Our primary interest in the project-based voucher

capital improvements. Staff asserted that

has been in the population that it serves and the

it was a priority to retain the same assisted

services that come with it.”

households through the conversion and avoid

disrupting their experience with the housing

—Seattle Housing Authority

authority—including building management

Since the early 2000s, the Seattle Housing

and recertification staff. According to agency

Authority has partnered closely with the city,

staff, few residents, if any, have taken

county, and local service providers to address

advantage of Choice Mobility TBVs because

homelessness and support service-enriched

of the challenges finding housing with a

housing for high-need populations. Most of

mobile voucher in Cambridge.

the Seattle Housing Authority’s 3,600 PBVs

Partnerships. The Cambridge Housing

are connected to these efforts, with a smal

Authority has several partnerships with

share going to replacement vouchers in

service providers and housing developers

their HOPE VI communities. Seattle Housing

that incorporate PBV assistance to develop

Authority staff stated that to date, their use

or preserve affordable units. Many of

of PBVs has, in large part, been guided

these partners provide services on site in

by community priorities identified by local

PBV-assisted properties. For example, the

partners.

Cambridge Housing Authority partners with

The Seattle Housing Authority applies the

Just-A-Start to place their PBV-assisted units.

smal est share of its HCV units and budget

As a community development corporation,

authority to PBVs among the PHAs included

Just-A-Start provides resident services in

in the case studies in this report (33 percent),

al their affordable rental developments,

but is the largest of the three agencies and

including supportive services and education

supports the largest number of PBV vouchers

programs.33 In Levy, Long, and Edmonds

(see exhibit 5.3). The Seattle Housing

(2019), the Cambridge Housing Authority

Authority is also the only agency that uses al

similarly identified MTW fund flexibility as

four MTW PBV flexibilities, along with applying

a tool to preserve and develop affordable

several HCV general flexibilities to their PBV

housing and partner with other local entities.

program.

The Cambridge Housing Authority noted

33 For more information on Just-A-Start, see: https:/ www.justastart.org/.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

43

5. Case Studies of Three Moving to Work Agencies’ Project-Based Voucher Use A tradeoff discussed by the Seattle Housing

and staff stated that PBVs may be used if

Authority staff of the focus on homeless and

promising opportunities emerge, but they

high-need households is that the Seattle

are not currently planning to expand its PBV

Housing Authority’s PBVs disproportionately

portfolio substantial y. This is based on both

house White, single adult men compared with

the demand for family housing through their

their TBV program. The PBV population mix

TBV program and budget considerations.

is driven by priorities set through the city’s

Additional y, the use of PBVs necessarily

Housing Tax Levy efforts and the county’s

impacts the agency’s ability to issue TBVs

10-Year Plan to End Homelessness, and

because PBV HAP contracts require a long-

not by explicit Seattle Housing Authority

term financial commitment that cannot be

targets. Although staff said that single adults

broken without placing housed families at

can inherently carry some cost efficiencies

risk of instability. Staff stated that the PBV

because they tend to live in studios that have

commitments must be considered carefully

lower HAP costs than larger units, it has also

before entering, while if necessary, TBV

meant serving fewer families than might be

savings can be found by temporarily freezing

expected through the TBV program. Unlike

new issuances without directly harming

the PBV population, staff said, roughly half of

existing assisted households. Staff said that

the TBV waiting list tends to be families with

the Seattle Housing Authority leadership is in

children.

the early stages of assessing their current PBV

portfolio and agency priorities for future PBV

The Seattle Housing Authority has not formal y

use.

established a maximum PBV allocation,

Exhibit 5.3 Seattle, Washington and the Seattle Housing Authority (SHA)

• Seattle’s population is approximately 690,000. The population increased by more than 15 percent between 2010 and 2017.

• The median family income is $103,447.

• Median rent for a two-bedroom unit in Seattle was about $2,550 in 2016. The rental vacancy rate was 4 percent.

• SHA received Moving to Work designation in 1998.

• Between 2008 and 2016, SHA added nearly 1,700 new households to their programs. In 2016, SHA served 15,141 households:

» 3,603 project-based voucher (PBV) households (24 percent);

» 4,937 tenant-based voucher (TBV) households (33 percent); and

» 6,054 in public housing (40 percent).

• About 33 percent of SHA’s Housing Choice Voucher budget authority was applied to PBVs in 2016. Since 2008, their PBV program increased marginally, from 3,026 to 3,603 households.

• SHA’s PBV households are more likely to be single adults and to be White compared with households assisted through TBVs (72

percent single adults compared with 53 percent, and 43 percent White compared with 34 percent). This is a decrease from 2008

when PBV-assisted households were 81 percent single adults and 53 percent White.

Sources: 2013–2017 American Community Survey, 5-year estimates; HUD Fiscal Year 2018 Median Family Income Documentation System: https://www.huduser.

gov/portal/datasets/il/il2018/2018MedCalc.odn; HUD Office of Public and Indian Housing Information Center dataset; Zillow Rental Index: https://www.zillow.com/

research/data/

Staff discussed their PBV efforts and MTW

in other forms of assistance. The Seattle

flexibilities as al owing them to pursue both

Housing Authority’s PBV units also tend to

housing choice and cost-effectiveness

be located close to social and health service

goals. In meeting housing choice goals,

providers in Seattle’s downtown area or

staff emphasized that PBVs provide deeply

offer supportive services. This proximity to

subsidized housing options for high-need

services was described as providing high-

populations who might not be successful

need and formerly homeless residents

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

44

5. Case Studies of Three Moving to Work Agencies’ Project-Based Voucher Use access to the resources they need to be

Staff said that prior to the Tax Levy

successful.

collaboration and through to approximately

2009, additional ad hoc partnerships were

Examples of cost-effectiveness efforts tied to

formed that account for the balance of

PBV efforts, described in more detail below,

the Seattle Housing Authority PBV units.

included administrative efficiencies such

Many centered on the county’s Plan to End

as streamlined inspections and admissions

Homelessness and efforts to braid housing

processes, site-based waiting lists, waiving

assistance with service dol ars from the

PBV exit vouchers, and noncompetitive PBV

county or other sources to serve high-need

al ocation processes, among others. Staff

populations. For example, in 2000, the Seattle

noted the efficiencies gained through these

Housing Authority committed 400 PBVs to

efforts, as well as challenges reporting or

the Sound Families Program, which provided

monetizing the value of the administrative

transitional housing for homeless families.36

efficiencies that flexibilities al ow.

Sound Families was described as one of the

Agency staff identified two main programmatic

few PBV partnerships to focus on families.

efforts as facilitated by MTW PBV flexibilities.

Cost-effectiveness through PBVs. The

Local partnerships to end homelessness.

Seattle Housing Authority has made several

Two main partnerships were discussed as

efforts to pursue efficiencies through its

driving the Seattle Housing Authority PBV use:

PBV program specifical y and HCV program

the Seattle Housing Tax Levy34 and the King

general y. Staff highlighted two PBV flexibilities

County 10-Year Plan to End Homelessness.35

as particularly useful to sustaining service-

The Housing Tax Levy raises funds to support

enriched housing: waiving the PBV exit

affordable housing creation and preservation.

voucher requirements37 and site-based waiting

The first levy was passed in 1986, and Seattle

lists. Waiving exit vouchers was described

residents vote every 7 years to provide

as al owing continuity and predictability for

funding to create and preserve affordable

service partners and removing pressure from

housing. The Seattle Housing Authority

the TBV waitlist to absorb households exiting

leadership said that for each levy process,

PBV units. Staff said that site-based waiting

they determine whether to participate and at

lists in partner owned or operated sites

what scale. The Seattle Housing Authority has

maintained by partners allowed high-need

contributed PBVs to each of the levies passed

populations to be connected to properties that

since they received MTW status—in 2002,

offered appropriate services. Additional y, the

2009, and 2016—committing 500, 500, and

Seattle Housing Authority has implemented

300 new PBVs, respectively. In total, roughly

combined program management and LEAN

one-half of the Seattle Housing Authority

processes38 within the HCV program. The

PBVs are units connected to the levy.

combined program management activity

enables the Seattle Housing Authority to

34 For more information on the Seattle Housing Levy, see: https:/ www.seattle.gov/housing/levy.

35 For more information on the King County 10-year Plan to End Homelessness, see: http:/ www.cehkc.org/plan.html.

36 “Administrative Plan for the Seattle Housing Authority Housing Choice Voucher Program,” Seattle Housing Authority, approved 2003 and updated 2015, https:/ www.seattlehousing.org/sites/default/files/housing_choice_voucher_administrative_plan.pdf.

37 As a part of the “Family Right to Move,” a traditional PBV household can move from the PBV unit and keep their rental assistance by requesting another voucher or comparable tenant-based rental assistance (referred to as an “exit voucher”). Through their PBV MTW activity, the Seattle Housing Authority provides housing choice at the beginning of the PBV process through site-specific waiting lists and have waived the “exit voucher.”

38 Lean Six Sigma is a process improvement methodology, aimed at reducing waste and improving operations. The Seattle Housing Authority tailored the Washington State Auditor’s office program to fit the needs of their HCV program. To learn more about Lean methodology, see: https:/ www.sao.wa.gov/

improving-government/learn-to-be-lean/; https:/ goleansixsigma.com/what-is-lean-six-sigma/.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

45

5. Case Studies of Three Moving to Work Agencies’ Project-Based Voucher Use streamline management and policies for

PBV and public housing units that are co-

located at the same property, which reduces

administrative redundancies. It also allows

the Seattle Housing Authority to ensure that

their residents don’t see a difference in their

services or program management, no matter

what kind of assistance they receive. The

LEAN process is focused on creating a culture

of accountability and collaboration. This

has allowed the Seattle Housing Authority’s

leadership to identify areas where the

program was succeeding and areas where

streamlining or other improvements are

needed.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

46

6. Conclusions

6. Conclusions

markets. Staff at the three case study agencies

stated that PBV costs—which are tied to long-

term contracts with gradual rent increases—

This study documents various aspects of

are more predictable than TBV costs when

the use of project-based vouchers (PBVs)

rents are rising quickly. All three agencies

by Moving to Work (MTW) agencies and

discussed the chal enges TBV holders face

a group of comparably sized traditional

finding private market housing citywide or in

agencies through analysis of administrative

specific submarkets as motivating their PBV

data and case studies of three MTW agencies

use.

with large PBV portfolios. We examine PBV

Our results also show a relationship between

locations in detail to explore concerns about

distressed public housing and PBV use. MTW

PBVs concentrating in high-poverty areas and

and traditional agencies with lower-quality

whether MTW agencies may use PBVs as a

public housing in 2008 (measured as Physical

tool to reach opportunity-rich places.

Assessment Subsystem [PASS] scores) were

PBV use is more common among MTW

more likely to increase their PBV use by the

agencies than among traditional public

end of our study period (2016). The MTW

housing agencies (PHAs), but extensive PBV

agencies were more likely than the traditional

use is not the norm. Most MTW agencies used

agencies to use the Rental Assistance

PBVs to some extent as of 2016 and reported

Demonstration (RAD) to convert public

activities requiring MTW PBV flexibilities. Yet,

housing—and to convert to PBVs. This may

only nine agencies exceeded the 20-percent

reflect MTW agencies’ ability to use funding

budget authority cap on PBV use in 2016,

or other flexibilities to navigate the RAD

and only four of those agencies used PBVs

conversion process and that MTW agencies

for more than 25 percent of the assisted

can retain their funding and other flexibilities

housing they provided. More MTW agencies

for converted PBV units (but not for project-

used PBVs and their flexibilities sparingly, at

based rental assistance, or PBRA).

a level closer to the norm for the comparison

We find no evidence that PBVs are used as

traditional PHAs (0 to 5 percent of their

a tool to improve access to low-poverty or

budget authority). Even among the three case

opportunity-rich neighborhoods by MTW

study agencies with extensive PBV use, in

agencies or our sample of traditional PHAs.

markets where tenant-based vouchers (TBVs)

For both sets of agencies, PBVs are in more

are chal enging to use, staff discussed the

distressed neighborhoods compared with

importance of maintaining a portfolio of TBVs

TBVs and tend to be in areas that more closely

and the residential mobility opportunities they

resemble public housing neighborhoods.

offer.

Also, on average, both MTW and traditional

Local housing markets play an important

PHAs’ PBV-assisted households live in

role in PBV use and agency decisions, which

more distressed neighborhoods than the

was evident in both the quantitative and

typical neighborhood in their counties.

qualitative findings. Across MTW agencies,

The RAD conversions did not explain PBV

PBV use increased more in the Northeast than

neighborhood locations.

in relatively more affordable regions of the

Results were similar across neighborhood

South and Midwest. And, our analysis of MTW

quality measures, with two exceptions:

and traditional PHAs shows that agencies in

MTW PBVs were in neighborhoods with

areas with higher rents increased their PBV

better access to affordable transportation

use more than agencies in more affordable

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

47

6. Conclusions

compared with the average for their counties,

There was considerable variation across MTW

most likely because MTW agencies tend to

agencies in the extent and nature of their PBV

serve dense central cities with better public

use for every measure we examined. The

transportation compared with other parts of

three case studies underscore the diverse

their counties. And, MTW agencies’ PBVs are

and creative ways that MTW agencies may

in neighborhoods with higher educational

use PBVs to pursue the MTW program’s

attainment than TBVs or public housing.

statutory objectives and the importance

of local contexts and priorities in agency

We did not find any differences in location

decisionmaking.

patterns by race or ethnicity for PBVs

compared with other assistance programs.

As is the case for the TBV program, non-

Limitations

White PBV-assisted households tend to

A significant limitation of this report is that it

live in higher-poverty, more distressed

does not examine the extent to which PBVs

neighborhoods than White PBV-assisted

are combined with supportive services or

households. We found that racial segregation

house high-need households. MTW agencies

was associated with PBV locations—with

have unique opportunities to provide

agencies in more racial y segregated

supportive services by making creative use

areas more likely to have PBV units in the

of funding or policy flexibilities—and staff

higher-poverty neighborhoods. Notably,

from the case study agencies discussed

PBV locations appeared more sensitive

tying supportive services to PBV properties

to racial segregation than TBVs in the

for veterans, homeless people, and others.

same jurisdictions. It may be that, in highly

HUD also encourages traditional PHAs to

segregated cities, developing PBV properties

use PBVs to provide supportive services and

outside of high-poverty neighborhoods is

serve “hard to house” families. No data source

more difficult than renting in those same

documents whether PBVs house high-need

neighborhoods with a TBV.

families or are linked to services, however.

The case study agencies, although not

MTW annual plans and reports provide some

representative of all MTW agencies, did not

relevant information, but the scale or nature of

approach PBVs as a tool to create housing

services cannot be determined consistently.

in opportunity-rich neighborhoods. The

Our analysis of the relationships between

agencies’ primary PBV goals were to preserve

the PBV and Low-Income Housing Tax Credit

and expand housing opportunities more

(LIHTC) programs was also limited by available

broadly and to improve cost efficiency—

data. Administrative data do not identify

and PBV use tended to be tied to specific

vouchers used in LIHTC properties. We

local priorities, partnerships, and market

estimate the intersection of these programs

considerations. The agencies discussed their

for MTW agencies based on addresses, but

PBV use as consistent with neighborhood

these estimates are sensitive to assumptions

choice goals in that PBVs were in areas that

about property and block sizes and could

likely offered tangible benefits to assisted

be improved by adjusting for local contexts.

households—but neighborhood location was

Future research could also expand this

not driving PBV decisionmaking. Notably, the

analysis to traditional PHAs.

agencies each waived or revised the Family

Right to Move requirement to some degree,

The small number of MTW agencies itself was

citing cost concerns and the potential impact

a limiting factor for cross-agency analysis of

on their TBV waiting lists.

PBV use or locations. We include comparison

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

48

6. Conclusions

traditional PHAs in regression analyses to

to make it more feasible for agencies to

increase our sample sizes and ability to

implement it in the way HUD intends.

detect statistical relationships, but the extent

to which our findings are representative

Second, the case studies identified examples

of MTW agencies, specifical y, could not

of unique approaches to PBV use and of

be determined. Similarly, we include case

productive local partnerships from three high-

studies of just three MTW agencies that are

capacity agencies, but a rigorous investigation

not typical of the average PHA because they

of promising MTW agency activities was not

are the highest PBV users among all PHAs

possible. More information about innovative

national y and in some of the nation’s most

practices and partnerships from a diversity

competitive rental markets. Their insights are

of agencies could help identify replicable

useful to understand the benefits of PBVs

models. Future case studies or qualitative

in tight markets and ways that PBVs can be

work should include a range of MTW PHA

used to facilitative partnerships or increase

sizes, local market characteristics, and

administrative efficiencies—but they tell us

agencies with different levels of PBV use to

little about PBV use in weaker markets or

understand the challenges and opportunities

decisionmaking among agencies that do not

that PBVs present to pursue MTW’s

use PBVs.

objectives.

Third, our analyses begin to document

Policy Implications and Future

the relationships between the Housing

Research

Choice Voucher (HCV) program and LIHTC

properties, but more work is needed to ful y

Our findings have implications for PBV

understand the extent to which the HCV and

policy and raise new questions for additional

LIHTC programs are mutual y dependent. A

research. First, our findings suggest some

more precise estimate of PBV and TBV co-

cause for concern about PBV locations and

location in LIHTC properties at both MTW

PBV-assisted households’ access to low-

and traditional PHAs would shed light on the

poverty, opportunity-rich neighborhoods.

role that LIHTC properties play in the HCV

More research is needed to understand ways

program.

to improve PBV neighborhood locations,

including the mechanisms driving PBV location

Finally, future work should examine the extent

options and MTW agency decisionmaking.

to which MTW agencies and traditional PHAs

For example, more qualitative research with

combine PBVs with supportive services or

MTW and traditional agencies could shed light

use PBVs to support high-need households.

on how agencies select PBV properties and

HUD should consider ways to strengthen

identify opportunities for HUD to encourage

data and reporting from both MTW and

improved locations. More work is also needed

traditional agencies to support research on

to examine the relationship between PBV

the availability of supportive services and

locations and racial segregation—for example,

examine outcomes for households with access

to understand whether local opposition to

to services.

affordable housing development contributes

to PBVs’ concentration in high-poverty areas.

Final y, research is needed to ful y document

how often MTW agencies waive or revise

the PBV Family Right to Move requirement,

the agencies’ reasons for doing so, and ways

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

49

Appendix A: Data and Methodology

Appendix A: Data and dataset. We also used tract-level racial

composition from the dataset to construct a

Methodology

county-level dissimilarity index.

Office of Public and Indian Housing

This appendix provides additional information

Information Center Data (2009, 2016)

about the data sources used to create this

For the retrospective MTW evaluation, HUD

report and summarizes the methods deployed

provided detailed household-level PIC data for

to clean and analyze the data. A companion

1995 through 2016 (see Galvez, Gourevitch,

study to this report, “A Picture of Moving to

and Docter, forthcoming, for information

Work Agencies’ Housing Assistance” (Galvez,

on the MTW retrospective evaluation PIC

Gourevitch, and Docter, forthcoming), provides

data). For this study, we use data for 2009

additional detailed information about how the

and 2016. The PIC data extracts identify

HUD PIH (Office of Public and Indian Housing)

the PHA that provided housing assistance

Information Center (PIC) data were cleaned

to each household, whether the household

and processed for the Moving to Work (MTW)

lived in public housing or received a housing

evaluation.

choice voucher (HCV), the specific type of

HCV received (project-based, tenant-based,

Data Sources

homeownership, certificates, or moderate

rehabilitation), relevant dates of each action

HUD Administrative Data

and other program milestones (for example,

program admission date, exit date, dates

We use five HUD administrative data sources,

of unit inspection), head of household

as noted in exhibit 3.1 in the Study Design

demographics (age, race and ethnicity,

section.

income, and marital status of householders,

disability status), income information for the

Affirmatively Furthering Fair Housing

households (monthly contributions toward

Data

rent, income, sources of income) and the

HUD published the Affirmatively Furthering

household’s Federal Information Processing

Fair Housing (AFFH) dataset, last updated

Standards (FIPS) census tract, county, and

in September of 2017, for public housing

state codes. HUD also provided address

agencies (PHAs) to use to conduct the fair

information for public housing households and

housing analysis required as part of the

HCV households at MTW PHAs for 2012–

Assessment of Fair Housing (Mast and Abt

2016.

Associates, 2017). The dataset includes a

series of indices developed at the census-tract

Rental Assistance Demonstration (2013–

level and designed to inform communities

2018)

about segregation and disparities in access

The First Component of the Rental Assistance

to opportunity. Data and documentation

Demonstration (RAD) al ows PHAs to convert

were retrieved from the HUD Exchange.39

public housing properties to one of two

We retrieved the Low Transportation Cost

forms of project-based assistance: project-

Index, the School Proficiency Index, the

based vouchers (PBVs) or project-based

Environmental Health Index, and the Labor

rental assistance (PBRA). A PHA fol ows

Market Engagement Index from the AFFH

several steps in the RAD conversion process.

39 AFFH Data and Mapping Tool, Published September 2017 https:/ egis.hud.gov/affht/.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

A-1

Appendix A: Data and Methodology

First, the PHA submits an application to

Real Estate Assessment Center data

HUD, and if accepted, HUD awards the

(2008)

PHA a Commitment to Enter into a Housing

HUD’s Real Estate Assessment Center (REAC)

Assistance Payment Contract (CHAP). The

monitors and provides data on HUD’s real

PHA then adds information on the RAD

estate portfolio. REAC’s Physical Assessment

conversion to its Annual or 5-Year Plan and

Subsystem (PASS) coordinates inspections

submits a Financing Plan to HUD detailing

for PHAs and provides scores of the physical

the type of conversion (PBV or PBRA), a

condition of public housing. REAC determines

physical condition assessment, plans for

PASS scores for both individual developments

rehab or new construction, operating and

and for PHAs’ public housing portfolio as

maintenance costs, and more. Once HUD

a whole. We use 2008 data because data

accepts the Financing Plan, HUD issues the

quality is poor prior to 2008.

PHA a RAD Conversion Commitment (RCC),

and the PHA’s property moves toward closing,

Voucher Management System (2002–

or full conversion, which is when the property

2017)

formally leaves the public housing program

and when either the new PBV Housing

HUD provided Voucher Management System

Assistance Payment (HAP) or Section 8 PBRA

(VMS) monthly data from August 2002

contract becomes effective.

through November 2017. The VMS data

identify, for each PHA in every month of the

We downloaded publicly available First

year, the number of vouchers of various types

Component RAD data on March 20, 2018,

and spending on those vouchers. HUD also

from the RAD Resource Desk.40 The data

provided PHA-level VMS Storyboard data for

include information for each RAD property

2002–2017, which includes similar information

national y: the PHA name and size, the

as the other VMS data, but also includes

development name and PIC Development

information on annual budget authority.

Number of each converted public housing

property, the type of conversion (PBV or

Other Data Sources

PBRA), the number of units converting, the

For regression analyses related to MTW

property’s stage in the RAD conversion

agencies’ use of PBVs and unit locations, we

process (CHAP Awarded, Financing Plan

link administrative data to information included

Submitted, or Closed), the date the CHAP

in publicly available datasets. The included

was issued, whether the RAD conversion

data sources are as fol ows.

entails new construction and the estimated

construction costs, whether the RAD

Moving to Work Evaluation Database of

conversion used Low-Income Housing Tax

Moving to Work Agency Activities

Credit (LIHTC) financing and the tax credit

amount, whether the RAD conversion is

For the MTW Retrospective Evaluation, we

insured by the Federal Housing Administration

created an agency-level database of MTW

(FHA), and the anticipated or actual closing

activities and flexibilities based on information

date of the RAD conversion.41

in the publicly available 2015 MTW annual

40 First Component RAD data are publicly available at http:/ www.radresource.net/.

41 Private owners of projects funded by the Office of Multifamily Housing at HUD, including Rent Supplement, Rental Assistance Payment, and Mod Rehab, can convert tenant protection vouchers through RAD’s Second Component to either PBVs or PBRA once contracts expire or are terminated.

These programs are tracked using contract numbers reported separately in the Tenant Rental Assistance Certification System (TRACS).

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

A-2

Appendix A: Data and Methodology

plans and reports.42 The database includes

or Inconclusive), the tax credit type (9 percent,

information on all MTW activities implemented

4 percent, and others), the tax credit start

by the 39 agencies, including activity name,

date, the number of LIHTC-subsidized units,

activity status, year proposed, implementation

and the tax credit construction type (New

year, the authorization(s) involved, activity

Construction, Both New Construction and

description, and the statutory objectives that

Acquisition and Rehab, Existing, or Acquisition

the activity addresses.

and Rehab), and other property-level

information, such as latitude and longitude

• MTW Annual Plans. MTW agencies must

coordinates, the property’s address, manager,

submit an annual plan that describes

and owner.

general housing authority operating

information, proposed MTW activities,

There are lags in reporting in the HUD

previously approved MTW activities and

LIHTC database (Scal y et al., 2018). Before

their status, sources and uses of funds, and

properties are formerly “placed in service”

any administrative updates for the upcoming

and entered into the HUD LIHTC database

year.

and the NHPD, they must meet strict legal

• MTW annual reports. MTW agencies

requirements that typical y take 3 to 4 years to

must submit an annual report that outlines

meet. Therefore, the most recent years of the

MTW reporting compliance, housing stock

HUD LIHTC database and the NHPD may not

information, leasing information, waiting

reflect the full set of LIHTC properties or units.

list information, progress on proposed and

LIHTC units cannot be occupied, however,

approved MTW activities, and administrative

until they are formerly placed in service, so

information for the current year.

these lags do not impact our analysis of the

overlap between the LIHTC program and PBV

National Housing Preservation Database

and TBV assistance at MTW PHAs.

(1987–2015)

The National Housing Preservation Database

American Community Survey data

(NHPD)43 was created by the Public and

The Integrated Public Use Microdata Series

Affordable Housing Research Corporation and

(IPUMS)44 from the National Historical

the National Low Income Housing Coalition.

Geographic Information System (NHGIS)

It is a property-level database that pul s

provides free online access to summary

from the HUD LIHTC database and other

statistics from the U.S. Census Bureau

sources to determine the subsidies attached

and American Community Survey (ACS)

to properties receiving LIHTCs, Project-

(Manson et al., 2018).45 We retrieved ACS

Based Section 8, Section 202, State Housing

5-year average data on poverty, educational

Finance Agency financed Section 236,

attainment, labor force participation, and

Section 515, Section 538, HOME, and others.

inequality at the census tract level for 2005

NHPD provides information on up to the two

to 2009 and 2012 to 2016. We also retrieved

most recent subsidies of each subsidy type

ACS 5-year average Gini Indices at the

on a property. For LIHTC tax credits, NHPD

county-level for 2012 to 2016.

provides the tax credit status (Active, Inactive,

42 MTW housing authority plans and reports are available on HUD’s website. See “Moving to Work (MTW)–Participating Sites,” HUD, accessed December 15, 2016, https:/ www.hud.gov/program_offices/public_indian_housing/programs/ph/mtw/mtwagencies 43 NHPD data are publicly available at https:/ preservationdatabase.org/.

44 https:/ ipums.org/what-is-ipums.

45 IPUMs data are available at: https:/ www.nhgis.org/.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

A-3

Appendix A: Data and Methodology

Zillow Data

The percent of households in public housing

We use publicly available data from Zil ow,

is calculated as the number of public housing

an online real estate database company, to

households divided by the sum of a PHA’s

measure the property values and rental costs

households.

of the PHA service area.46 We specifically

The number of activities using MTW PBV

draw from two time-series: the Zil ow Home

flexibility (2015) is calculated as activities

Value Index (ZHVI) for all homes (ZHVI Al

listed in 2015 MTW annual plans that explicitly

Homes: Single Family, Condo/Co-op) and the

use MTW PBV flexibilities and are identified

Zil ow Rent Index (ZRI) for all homes (ZRI Time

as such in the unpublished database of MTW

Series: Multifamily, Single Family Residential,

activities constructed for the retrospective

Condo/Co-op). Both indices are described in

MTW evaluation.

the fol owing section.

The number of activities that involve PBVs

(2015) is calculated as activities listed in

Measures and Sampling

2015 MTW annual plans that rely on PBVs,

Below we describe how we constructed

regardless of whether MTW flexibility is

key measures and the comparison group of

required. Information is drawn from the

database of MTW plans that were created for

traditional PHAs.

the MTW evaluation.

Public Housing Agency Characteristics

The percent HCV Budget Authority Applied

We use VMS data, PIC data, RAD First

to PBVs. We use January 2017 VMS data to

Component data, NHPD data, and MTW

calculate the total number of PBVs by PHA for

Annual Plans and Reports to describe

that month. After consultation with HUD, we

characteristics of PHAs related to PBV use.

include leased, not leased, and vacant PBV

vouchers in the PBV voucher count. We then

PBV households are defined as any

calculate the per-unit costs (PUC) for voucher

household listed in PIC with the “PBV”

units, dividing the HAP field for MTW PHAs

program type. We exclude Mod-Rehab units

by unit-months leased (UML). We then pull in

from our analyses.

budget authority information from the VMS

Storyboard January 2017 data and multiply

Public housing households are defined

by 12 to get annual budget authority. To

as any household in PIC with the “public

determine the percent of overall HCV budget

housing” program type.

authority devoted to PBVs, we multiply the

number of PBV vouchers by the PUC, multiply

TBV households are defined as any

by 12 to convert from monthly to yearly, and

household in PIC with the “tenant-based

then divide by the calculated annual budget

voucher” program type. We exclude

authority.

“certificate” program types from our sample of

TBV-assisted households.

Total RAD PBV units and properties. We

use RAD First Component data to sum the

The percent of PBV assisted households is

number of units and the number of properties

calculated as the number of PBV households

converting to PBV through RAD, separately for

divided by the sum of a PHA’s total

MTW PHAs and comparison traditional PHAs.

households.

We only consider Closed properties as of the

end of 2016.

46 Aggregated data are available at https:/ www.zillow.com/research/data/ and are freely available from Zillow for noncommercial use.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

A-4

Appendix A: Data and Methodology

Total RAD PBRA units and properties. We

housing to PBV units. Specifical y, we look at

use RAD First Component data to sum the

the relationship between the PASS scores in

number of units and the number of properties

2008 and the percent of households assisted

converting to PBRA through RAD, separately

with PBVs in 2016. 2008 is the earliest year for

for MTW PHAs and comparison traditional

which there is broad coverage and data are of

PHAs. We only consider Closed properties as

high quality.

of the end of 2016.

Neighborhood Characteristics

Total PBVs and TBVs in RAD properties.

We use the PIC extract and addresses along

We calculate county-normalized neighborhood

with RAD data to identify the number of MTW

characteristics. We begin with census tract

PBV and MTW TBV households living in RAD

level measures as described below. We then

properties in 2016. We only consider Closed

normalize measures to the county. The county-

RAD properties as of the end of 2016.

normalized measures al ow us to compare

location outcomes across PHAs while

Total PBVs and TBVs in LIHTC units. We

accounting for large regional differences. We

use the PIC extract and PIC addresses along

define these relative measures by dividing

with data on LIHTC properties in NHPD to

the tract-level value of each characteristic

determine the number of MTW PBV and MTW

by the county average. For example, we

TBV households living in LIHTC properties

define county-normalized rate such that a

in 2016. We rely primarily on active LIHTC

value of 2.0 signifies a poverty rate of twice

properties for the purposes of this analysis.

the regional (county) average, and a value of

NHPD contains information on up to the two

0.5 signifies a poverty rate that is half of the

most recent LIHTC tax credits on a property.

regional average.

A LIHTC property is considered active if it has

at least one active LIHTC program tax credit.

Poverty Rate is calculated from ACS data. It is

A LIHTC program tax credit is considered

the population with total family income below

active if its affordability period, which in most

the poverty line divided by the population

circumstances is 30 years, occurs after the

for whom poverty status is determined. Total

date of the most recent refresh of NHPD,

population with family income below the

suggesting the property the tax credit is

poverty line was calculated by adding the

attached to must still meet affordability

population below 50 percent of the poverty

requirements (Gold et al., 2018). We map al

line to the population between 50 and 99

2016 MTW PBV addresses in 2016 PIC data

percent of the poverty line. Calculations

and all LIHTC properties active as of 2015,

use data from the 2012–2016 ACS 5-year

using ArcGIS. We draw a radius of 200 feet

estimates retrieved from NHGIS.

around each LIHTC property and flag all PBV

We also create variables signifying low-

addresses that fall within that radius as located

poverty and high-poverty neighborhoods.

in the LIHTC property.

We define low poverty neighborhoods as

REAC Physical Inspection (PASS) scores for

those with a county-normalized rate at or

2008 are calculated by REAC. Where data

below 0.5 and high poverty neighborhoods as

for 2008 were unavailable, we use the score

those with county-normalized of at least 2.0.

from the closest earlier year. We use 2008

Percent with a bachelor’s degree is calculated

PHA-level PASS scores to understand whether

as the population of adults age 25 or older

PHAs with more distressed public housing are

with bachelor’s degree, master’s degree,

more likely to shift their portfolio from public

professional school degree, or doctoral

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

A-5

Appendix A: Data and Methodology

degree divided by the total population of

with shorter commutes and strong public

adults age 25 or over. Calculations use data

transportation infrastructure.

from the 2012–2016 ACS 5-year estimates

retrieved from NHGIS.

Regional and Market Characteristics

Labor force participation is calculated as

Dissimilarity Index is a measure of segregation

the total number of people age 16 or older in

that represents the extent to which the

the labor force divided by the total number

distribution of two groups differs by level of

of people age 16 or older. Calculations use

geography. We use an index that compares the

data from 2012–2016 ACS 5-year estimates

share of White and non-White residents in a

retrieved from NHGIS.

census tract (in 2010) to the share of White and

non-White residents in the county. A score of 0

Labor market engagement index is an AFFH

represents equal distribution across all tracts. A

index based upon the level of employment,

score of 100 represents complete segregation.

labor force participation, and educational

For research question 5, we divide by 100 to

attainment in a census tract using data from

rescale the dissimilarity index to run from 0 to 1.

2006–2010 ACS 5-year estimates. The index

is normalized as a national percentile rank.

Gini Index is a measure of distribution

Higher values represent greater labor force

frequently used to describe the income

participation and human capital.

distribution in an area. The index runs from 0

to 1 with a score of zero representing equal

Environmental health index is an AFFH index

incomes across all households. We use

that summarizes the potential exposure to

county-level estimates from the 2012–2016

harmful toxins in a census block group using

ACS retrieved from NHGIS.

data from the National Air Toxins Assessment

(2005). The index is normalized as a national

Rent Index is the ZRI for all homes (ZRI Time

percentile rank. Higher values represent

Series: Multifamily, SFR, Condo/Co-op). The

better environmental quality.

ZRI is a smoothed measure of the median

estimated market-rate rent for a given home

School quality is measured using the

type, region, and year. We col ect this data at

AFFH School Proficiency Index. The index

the ZIP Code by month level. We then create

uses school-level data on fourth-grade

an annual measure by taking a simple twelve-

performance in 2011–2012 from Great Schools

month average. ACS population estimates

and geographic data from Common Core of

are used to create a weighted average for

Data and the School Attendance Boundary

each PHA. Prior to including the rent index in

Information System (SABINS). The index is

regressions, we scale by dividing it by 100 so

normalized as state percentile ranks. Higher

coefficients can be interpreted as the change

values represent greater school performance

associated with a $100 increase or decrease

in the area.

in monthly rents.

Transportation cost index is an AFFH index

Property Values are measured using the ZHVI

based upon estimates of transportation costs

for all homes (ZHVI All Homes: Single Family,

for a three-person, single-parent family with

Condo/Co-op). The ZHVI is a smoothed,

income at 50 percent of the median income

seasonal y adjusted measure of the median

for renters in the county. Estimates use

estimated home value for a given home type,

Location Affordability Index (2008–2012) data.

region, and year. We use the index for al

The index is normalized as national percentile

homes, by ZIP Code, for the years 2009 to

ranks. Low transportation costs are associated

2016. We col ect this data at the ZIP Code

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

A-6

Appendix A: Data and Methodology

by month level. We then create an annual

PHAs: the MTW PIC data include a single

measure by taking a simple 12-month average.

variable indicating program type for each

ACS population estimates are used to create

household (MTW 50058 field 1c), while

a weighted average for each PHA. Prior to

traditional PHA data include a variable

including the rent index in regressions, we

identifying whether households received

scale by dividing it by 1000 so coefficients can

a voucher of any type or lived in a public

be interpreted as the change associated with

housing unit, as well as a separate sub-code

a $1000 increase or decrease in the value of a

for the type of voucher received (50058

“typical” home.

section 11 and section 12). For the MTW

evaluation, we create a single program

Change in Rents is calculated by taking the as

identification variable that reconciles these

the percentage (from 0 to 1) increase in the ZRI

two different reporting approaches and allows

(al homes) from December 2011 to December

us to identify all PBV-assisted households at

2016. This calculation occurs at the ZIP Code

each agency.

level. ACS population estimates are used to

create a weighted average for each PHA.

Merging the Office of Public and Indian

Housing Information Center, National

File Construction

Housing Preservation Database, and

For some research questions, we combine

Rental Assistance Demonstration Data

elements from various sources to construct

Taking this PIC extract from 2009 and 2016,

analytic files. We construct three files for

we merge in address information from HUD

analysis. The discussion of specific measures

for PBV- and TBV-assisted households at

constructed for analysis is discussed in the

MTW PHAs to identify, for 2016 only, al

Data Analysis section.

households at MTW PHAs living in RAD-

converted properties and in LIHTC properties.

Project-Based Voucher-Assisted

Households (2009, 2016)

Identifying the overlap of assistance with

RAD. We use the RAD First Component data

We create a household-level dataset of al

to gather the PIC Development Numbers

households who received PBV assistance

of all RAD PBV properties that had closed

through the HCV program in 2009 and 2016,

or finished the RAD conversion process

as recorded in the PIC dataset provided by

by the end of 2016. We then use address

HUD for the retrospective MTW evaluation.

information for 2012 to 2016 for public housing

The file includes information on the

households at MTW PHAs. The address

characteristics of assisted households and the

information has latitude and longitude

census tracts in which they lived. We calculate

coordinates of public housing households,

total households receiving PBV assistance in

along with the PIC Development Number for

those years by PHA for MTW agencies and

the properties where they are housed. We use

comparison traditional agencies.

the PIC data and the RAD data, linking by PIC

PIC data indicate whether a household was

Development Number, to create a full list of

served through public housing, PBVs, TBVs,

latitude and longitude coordinates of public

Section 8 rental certificates, homeownership

housing properties that converted to PBV

vouchers, or the moderate rehabilitation

through RAD and had closed by the end of

program. Program assistance is documented

2016. We then combine this list of latitude and

in PIC differently for MTW and traditional

longitude coordinates of RAD properties with

2016 PIC addresses for MTW PBV and MTW

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

A-7

Appendix A: Data and Methodology

TBV households to identify which households

ZIP Codes to PHAs using the PIC dataset

were living in RAD properties in 2016.

provided by HUD. We then aggregate the

Zil ow and SAFMR data to the PHA level by

Identifying the overlap of assistance with

taking a population-weighted average. Next,

LIHTC. We map MTW PBV and MTW TBV

we aggregate the neighborhood-level dataset,

households in 2016, using PIC address

described above, to the PHA-level with

information, with all LIHTC properties between

neighborhood characteristics weighted by the

1987 and 2015 with active LIHTC tax credits

number of households in each census tract.

using the NHPD. We then use radius matching

to identify all households within a 200-foot

The PHA-level dataset is used to answer

radius of LIHTC properties. We identify

research questions 2 and 5. It includes PIC

households located within the radius as living

data on 765 PHAs. Of these, 31 MTW agencies

in an LIHTC property.

and 261 comparison PHAs are included in both

the research question 2 and research question

Neighborhood-Level Dataset

5 analyses. These agencies had PBVs in

To understand location outcomes (research

2016 and are covered by the Zil ow, REAC,

questions 4 and 5), we create a dataset in

and AFFH datasets. These 292 agencies are

which the unit of observation is the census

included in the regressions for both research

tract. The analytic sample begins with the

question 2 and research question 5. The

dataset of PBV-assisted households for the

analysis for research question 2 includes

years 2009 and 2016, aggregated to the

three MTW agencies and 151 comparison with

census-tract level. We combine these data

no PBVs in 2016 that are not included in the

with neighborhood characteristics from the

analysis for research question 5. The analysis

ACS and AFFH. The ACS and AFFH data are

for research question 5 includes 4 MTW

defined at the census-tract-level; we also

agencies and 150 comparison agencies that

aggregate these data to county. The resulting

have PBVs but were not included in research

dataset contains all census tracts with

question 2 because either REAC or Zil ow data

assisted households in 2009 and 2016, the

was unavailable.

characteristics of both the census tract and

county and the number of households in each

Traditional Public Housing

tract by both assistance type and race and

Agency Comparison Group

ethnicity. As a next step, we exclude from our

analysis all traditional PHAs with fewer than

As discussed in detail in “A Picture of Moving

750 assisted households.

to Work Agencies’ Housing Assistance,”

MTW PHAs appear to have more in common

The neighborhood-level dataset is used to

with the 788 traditional PHAs who assisted

answer research question 4. These data are

750 or more households in 2016 than with

then aggregated to the PHA-level for use in

the remaining, smal er traditional PHAs (see

research question 5.

exhibit B.1 for characteristics of MTW agencies

and traditional PHAs with 750 or more

Public Housing Agency-Level Dataset

assisted households). Actual sample sizes may

To identify PHA housing market

vary for individual analyses based on data

characteristics, we create a PHA-level dataset

quality and availability. Second, ZIP Code-level

using a combination of PIC, Zil ow, and smal -

housing market data and tract-level ACS and

area fair market rent (SAFMR) data. Zil ow and

AFFH data were not available for all PHAs.

SAFMR data describing local housing markets

Sample sizes are included in all tables.

are defined at the ZIP Code-level. We mapped

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

A-8

Appendix A: Data and Methodology

Defining Housing Markets

PIC household data includes both census tract

and ZIP Code for each assisted household.

From this data, we create lists of ZIP Codes

served by each PHA. Characteristics of the

housing market from Zil ow are defined by ZIP

Code. Because these market characteristics

define the entire jurisdiction, we weight ZIP

Codes using population estimates drawn from

the ACS.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

A-9

ctivity

Vs**

4

6

2

4

1

3

5

0

0

1

Using

12

PB (2016)

Any A

(continued)

ctivities

xibility*

3

12

6

1

1

1

0

2

0

0

1

V Fle (2015)

# of A Using MTW PB

?

Units

0

0

0

0

0

0

0

0

0

0

(up to

2,533

RAD PBRA

12/2016)

V

Units

0

0

0

0

(up to

149

135

1,150

145

1,350

2,083

783

ns.

RAD PB

12/2016)

ssistance

uestio

Vs

1%

7%

.4%

1%

.1%

.2%

7%

0

oucher A

Budget

to PB

3.

(1/2017)

25.

10

41.

67

17

26.4%

8.6%

21.

14.6%

esults

arch q

Authority

ese

.2%)

1%)

0

.03%)

0

1,687 (2.5%)

479 (2.5%)

roject-Based V

dditional R

Other (2016)

111 (1.6%)

35 (0

422 (1.6%)

119 (1.9%)

20 (1.0%)

3 (0

80 (2.

f P

B-1

se o

1%)

uantitative r

ork agencies use project-based vouchers

.5%)

PH

.7%)

798

195

,183

7%)

1%)

(2016)

1,375 (19

4,290

849

554

(23.5%)

8, (33.5%)

2, (23.2%) 17 (26.0%)

(22.

(36.4%)

6,860 (36.

Appendix B: A

49 (3.8%)

he q

gency

970 (15.

401 (19

gencies’ U

esults

1%)

.5%)

7%)

.6%)

ork A

rom t

,273

o W

lts f

TBV

(2016)

43,235 (65.3%)

10 (54.0%)

gencies, by A

125 (57

102 (32.

5,351 (76.5%)

8,411 (46.

15,

822 (63.8%)

2,

1,486 (72.3%)

5,453 (57

969 (63.6%)

esu

2,376 (63.5%)

Moving t

ork A

.2%)

7%)

PBV

.3%)

.4%)

.3%)

105

0

(2016)

5,527

1,950 (7.4%)

417

3,240

1,824 (19

4, (6.2%)

1,408 (7.4%)

etailed r

160 (2.2%)

(30

(32.4%)

(50

148 (7

436 (11.

dditional R l d

na

xtensively do Moving to W

: A

Total

741

1,288

6,431

3,

1,523

,020

dditio

(2016)

6,997

18,263

26,295

2,055

9,475

66,210

19

Households

nts a

oucher Use at Moving to W

dix B rese

uthority

uthority

artners

uthority

pen

uthority of

uthority of

uthority of

tate Housing

ppendix p

1 Project-Based V

Ap This a Research Question 1: How e Exhibit B.

PHA

Alaska Housing Finance Corporation

Atlanta Housing A

Housing A Baltimore City

Boulder Housing P

Cambridge Housing Authority

Housing A Champaign County

Charlotte Housing A

Chicago Housing A

Housing A Columbus, Georgia

Delaware S Authority

District of Columbia Housing Authority

ctivity

Vs**

1

3

4

6

0

0

1

0

4

2

5

11

0

0

0

1

Using PB (2016)

Any A

(continued)

ctivities

xibility*

0

1

2

2

0

0

1

0

2

0

3

9

0

0

0

1

V Fle (2015)

# of A Using MTW PB

Units

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

(up to

RAD PBRA

12/2016)

V

Units

0

88

0

0

0

206

0

0

0

0

516

0

0

789

0

0

RAD PB

(up to 12/2016)

ssistance

Vs

1%

7.1%

0

0

0

0

0

.8%

.5%

oucher A

Budget

to PB (1/2017)

13.

23.6%

6.6%

2.0%

12.8%

9.8%

14.5%

10

7.4%

10

esults

Authority

.2%)

1%)

7

.8%)

.6%)

.9%)

0

0

0

8 .1%)

(0

323 (2.2%)

1,020 (4.3%)

307 (2.5%)

935 (2.9%)

(0

roject-Based V

dditional R

Other (2016)

11 (0

123 (5.2%)

34 (0

111 (1.9%)

318 (2.2%)

110 (2.

168 (7

f P

B-2

se o

.7%)

1%)

(continued)

.4%)

PH

.9%)

0

0

(2016)

1,065 (19

2,299 (15.3%)

1,103 (26.4%)

4,499 (31.2%)

6,620 (53.3%)

2,036 (34.0%)

1,633 (11.4%)

1,471 (28.3%) 13,463 (42.0%) 4,040 (41.2%)

Appendix B: A

938 (39

406 (32.

357 (9

337 (15.2%)

gency

gencies’ U

7%)

.9%)

.1%)

.8%)

ork A

.9%)

,528 .2%)

.9%)

774 .2%)

o W

TBV

(2016)

10 (70

9,593 (66.5%)

3,569

5,385

,314 (81.9%)

2,989 (49

(68.6%)

15, (49

(54.9%)

gencies, by A

3,829 (71.

,239 (71.4%)

1,242 (52.6%)

402 (51.6%)

857 (67

2,834 (67

3,399 (89

19

4,697 (37

10

1,522 (68.8%)

Moving t

ork A

1%)

1%)

PBV

.5%)

164

0

.01%)

7%)

159

(2016)

370

2,

3,236 (13.

854

2,

1,864 (5.8%)

434 (8.

58 (2.5%)

(47

(14.4%)

(14.3%)

(15.0%)

201 (4.8%)

58 (1.5%)

1 (0

801 (6.4%)

56 (1.

377 (3.8%)

186 (8.4%)

Total

172

(2016)

5,339

2,361

779

14,991

1,263

4,

3,814

14,416

23,570

12,425

5,990

14,349

5,206

32,036

9,810

2,213

Households

oucher Use at Moving to W

uthority

uthority

uthority

uthority

uthority

uthority

uthority

uthority

uthority of the City

uthority of the City

uthority

1 Project-Based V

e Housing A

PHA

Fairfax County Redevelopment and Housing A

Holyok

Keene Housing

King County Housing Authority

Lawrence-Douglas County Housing A

Lexington-Fayette Urban County Housing A

Lincoln Housing A

Louisville Metropolitan Housing A

Massachusetts Department of Housing and Community Development

Minneapolis Public Housing Authority

Housing A of New Haven

Oakland Housing A

Orlando Housing A

Philadelphia Housing Authority

Housing A of Pittsburgh

Portage Metropolitan Housing A

Exhibit B.

ctivity

Vs**

1

5

1

1

6

7

7

2

2

y on

0

2

Using

110

PB (2016)

N/A

V = tenant-

Any A

, moderate

ctivities

xibility*

1

2

1

1

3

4

3

1

1

0

2

67

N/A

V Fle (2015)

# of A Using MTW PB

ental Assistance Demonstration. TB

V, and PH across MTW PHAs and traditional

781

Units

0

0

0

0

0

0

0

0

0

0

0

(up to

2,553

14,

. RAD = R

V, TB

RAD PBRA

12/2016)

ercent PB

V

Units

0

0

0

657

0

0

0

0

456

0

212

7198,

RAD PB

(up to 12/2016)

18,215

ssistance

Other” includes households with a homeownership certificate

Vs

0

0

.6%

7%

7%

0

1%

oucher A

Budget

to PB (1/2017)

25.2%

19

3.

24.8%

7.0%

33.0%

16.

13.3%

13.

5.4%

esults

Authority

xclude local, non-traditional households. P

ystem data; 2013–2016 RAD first component data; MTW 2015 plans

.7%)

.5%)

.3%)

.5%)

. PH = public housing. PHA = public housing agency

597

.03%)

0

5 .2%)

,499

(4.8%)

547 (3.6%)

(0

8,257 (1.9%)

(1.4%)

roject-Based V

dditional R

Other (2016)

1 (0

310 (1.5%)

76 (0

72 (0

15 (0

82 (0

121 (2.3%)

37

f P

B-3

se o

1%)

(continued)

.7%)

.8%)

otal households e

PH

176 .6%)

.02%)

.0%)

0

,366

(2016)

2, (17

6,562 (31.9%)

oucher Management S

176 (1.

6,054 (40

101.452 (23.8%)

750 (28.8%)

Appendix B: A

816 (25.0%)

592 (5.3%)

30 (0

4 (0

425 (8.2%)

826 (19

Vs for all MTW PHAs averages across PHAs. “

gency

V = project-based voucher

xibilities and identified as such in the unpublished database of MTW activities. **Includes any activities in MTW plans that rel gencies’ U

. PB

V fle

.6%)

.9%)

.8%)

ork A

.

o W

TBV

(2016)

13,678 (66.5%)

15,039 (94.8%)

4,406 (98.9%)

14,594 (91.0%)

274,439 (64.5%)

1,715,911 (65.8%)

gencies, by A

9,585 (77

2,379 (73.0%)

8,819 (78.6%)

4,937 (32.6%)

3,371 (65.3%)

3,341 (79

2,514 (79

Moving t

ork A

.1%)

1%)

.4%)

xplicitly using MTW PB

PBV

0

.04%)

.0%)

.7%)

(2016)

1,731

1,354 (8.4%)

3,603

1,246

630

64 (2.0%)

21 (0

(15.4%)

(23.8%)

(24.

41,270 (9

570 (3.6%)

2 (0

15 (0

(20

105,669 (4.0%)

141

,445

. PBRA = project-based rental assistance

Total

,571

163

182

149

(2016)

12,358

3,260

20

11,218

15,857

4,453

16,034

15,

5,

4,

3,

425,418

Households

2,609

xibility is required.

oucher Use at Moving to W

ortland,

uthority

uthority

raditional

ork. N/A = data not available

uthority of the City

uthority of the

uthority of the

uthority of the

uthority of the City

. *Includes activities listed in MTW plans as of 2015 e

1 Project-Based V

2016 HUD Office of Public and Indian Housing Information Center data; January 2017 V

eno

Comparison traditional PHAs are those that served more than 750 total households in 2016. T

PHA

Home Forward (P OR)

Housing A of R

San Antonio Housing Authority

Housing A County of San Bernardino

San Diego Housing Commission

Housing A County of San Mateo

Housing A County of Santa Clara/ Housing A of San Jose

Seattle Housing A

Tacoma Housing A

Tulare County Housing Authority

Vancouver Housing Authority

MTW PHAs

Comparison T PHAs

Vs, regardless of whether MTW fle

Exhibit B.

MTW = Moving to W

based voucher

PB

Notes:

PHAs in the last two rows are out of total assisted households. Budget authority devoted to PB

rehabilitation, or voucher undefined program type and those with no program type

Sources:

Appendix B: Additional Results

Research Question 2: What factors are

assisted with PBVs. Using the sample of

associated with Moving to Work and

Moving to Work (MTW) and comparison public

traditional agencies’ use of project-based

housing agencies (PHAs), we find that PHAs in

voucher assistance?

areas with higher rents are more likely to use

Exhibit B.2 presents results of alternative

PBVs at all and to use PBVs more extensively.

versions of the model described in our

PHAs with a greater share of households in

discussion of research methods in the body

public housing in 2009 are less likely to have

of the report. For comparison, the results from

had any PBVs in 2016, but agencies with

exhibit 4.4 are provided here in columns 1 and

lower Physical Assessment Subsystem (PASS)

4 of exhibit B.2.

scores in 2008 were more likely to have PBVs

in 2016. Neither factor (the share of public

To examine project-based voucher (PBV)

housing assistance and PASS scores) strongly

use, we create an indicator variable equal

predicted the share of households assisted

to 1 if an agency has any PBV units and zero

with PBVs.

otherwise. Results appear in columns 2 and

5. To examine the intensity of PBV use among

We find that PHAs in areas with higher rents

agencies with any PBV units, we use the same

are more likely to use PBVs at all and to use

model presented in our discussion of study

PBVs more extensively. PHAs with a greater

design in the body of the report but limit the

share of households in public housing in 2009

sample to agencies with PBVs (columns 3 and

are less likely to have had any PBVs in 2016,

6).

but agencies with lower PASS scores in 2008

were more likely to have PBVs in 2016. Neither

We separately examine how the factors listed

factor (the share of public housing assistance

in exhibit 4.4 affect whether agencies use

and PASS scores) were predictive of the share

PBVs at all and the share of assisted families

of households assisted with PBVs.

Exhibit B.2 Model Results: Factors Related to the Use of Any Project-Based Vouchers and to the Percent of Assisted Households With Project-Based Vouchers at Agencies with Any Project-Based Vouchers

MTW and Comparison Traditional PHAs

MTW Agencies

Percent of

Percent of

Percent of

Households

Percent of

Households

Assisted

with a PBV if

Assisted

Agency

with a PBV if

Households

Agency

Agency Uses

Households

Uses Any

Agency Uses

with a PBV

Uses Any PBV

Any PBVs

with a PBV

PBV

Any PBVs

(1)

(2)

(3)

(4)

(5)

(6)

Percent Public

-0.011

-0.317***

0.007

-0.019

-0.528

0.003

Housing (2009)

(0.018)

(0.116)

(0.033)

(0.232)

(0.446)

(0.248)

REAC PASS Score

-0.002*

-0.023***

-0.000

0.000

-0.024

0.002

(2008)

(0.001)

(0.006)

(0.001)

(0.006)

(0.015)

(0.007)

0.040***

0.163**

0.047***

0.093

-0.049

0.098

Rent Index (2016)

(0.013)

(0.074)

(0.017)

(0.091)

(0.110)

(0.096)

Change in Rents

-0.036

0.113

-0.059

-0.264

-0.408

-0.248

(2011 to 2016)

(0.028)

(0.203)

(0.040)

(0.206)

(0.429)

(0.225)

-0.009

-0.151***

-0.004

-0.169*

-0.131

-0.159

South

(0.010)

(0.056)

(0.014)

(0.093)

(0.117)

(0.094)

(continued)

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

B-4

Appendix B: Additional Results

Exhibit B.2 Model Results: Factors Related to the Use of Any Project-Based Vouchers and to the Percent of Assisted Households With Project-Based Vouchers at Agencies with Any Project-Based Vouchers (continued)

MTW and Comparison Traditional PHAs

MTW Agencies

Percent of

Percent of

Percent of

Households

Percent of

Households

Assisted

with a PBV if

Assisted

Agency

with a PBV if

Households

Agency

Agency Uses

Households

Uses Any

Agency Uses

with a PBV

Uses Any PBV

Any PBVs

with a PBV

PBV

Any PBVs

(1)

(2)

(3)

(4)

(5)

(6)

-0.008

-0.146**

-0.005

-0.173*

-0.152

-0.171

Midwest

(0.010)

(0.068)

(0.013)

(0.100)

(0.206)

(0.106)

-0.000

-0.082

0.002

-0.131

-0.063

-0.128

West

(0.011)

(0.065)

(0.014)

(0.113)

(0.084)

(0.116)

Percent of

1.181***

4.436***

0.979***

1.019***

1.862

0.908**

Households in PBVs

in 2009

(0.143)

(0.657)

(0.147)

(0.365)

(1.195)

(0.413)

-0.024

0.937***

-0.059

0.001

1.886***

-0.054

Constant

(0.033)

(0.277)

(0.047)

(0.300)

(0.621)

(0.322)

446

446

292

34

34

31

* p<0.10, ** p<0.05, *** p<0.01.

MTW = Moving to Work. PBV = project-based voucher. PHA = public housing agency. REAC = Real Estate Assessment Center.

Notes: Samples include MTW agencies and traditional PHAs with at least 750 households in 2016, and for whom both REAC and Zillow data were available.

For MTW PHAs, Alaska Housing Finance Corporation, Massachusetts Department of Housing and Community Development, and the Holyoke and Champaign County housing authorities are excluded. The housing authorities of the City of San Jose and County of Santa Clara report jointly into Public and Indian Housing Information Center and are listed here as a single PHA. Standard errors are heteroskedastic robust and displayed in parentheses.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

B-5

C

ax

0

0

0

0

1

0

2

0

0

0

0

0

0

LIHT

.05%)

.04%)

(0

(0

Location in RAD and

(continued)

.7%)

C Only

1%)

272

7%)

4

(5.

363

.3%)

83

.0%)

(4.3%)

560 (3.

66

92

(8.0%)

180 (8.6%)

(0

162 (3.0%)

(3.9%)

(8.6%)

924 (9

319 (8.3%)

ental Assistance

Location in LIHT

703 (6.3%)2,

133 (10

ow-Income Housing T

Vs

0

0

0

0

14 .7%)

4 .3%)

7%)

0

0

0

0

0

(0

42

(0

255 (4.

(1.8%)

MTW TB

Location in RAD Only

C

7%)

.7%)

.5%)

7%)

.3%)

ocation

,532 7%)

LIHT

5,079 (94.9%)

14,565 (96.3%)

5,034 (92.3%)

40 (93.

2,242 (94.4%)

No L in RAD or

8,048 (95.

756 (92.0%)

1,907 (90

1,478 (99

886 (91.4%)

9,349 (91.0%)

3,510 (91.

1,109 (89

V

ental Assistance Demonstration or L

125

102

ssistance

5,351

8,411

822

2,

1,486

,273

5,453

2,376

969

1,242

Total TB

(2016)

15,

43,235

10

3,829

Households

oucher A

ocation in R

esults

’ project-based vouchers located in R

C

0

0

0

0

0

17

0

0

0

0

0

LIHT

63

.4%)

(1.9%)

(0

Location in RAD and

282 (15.5%)

roject-Based V

?

6

dditional R

gencies by L

f P

B-

1%)

se o

ork A

1%)

ork agencies

C Only

0

23

9

12 .7%)

0

0

27

0

(5.5%)

(6.

(0

(6.2%)

Location in LIHT

661 (33.9%)

785 (24.2%)

1,277 (31.

265 (18.8%)

Appendix B: A

1,839 (33.3%)

gencies’ U

Vs

1%)

1%)

1%)

ork A

0

0

0

38 7%)

0

0

0

0

o W

(25.

ax Credit properties

MTW PB

Location in RAD Only

136 (32.6%)

847 (26.

1,060 (58.

1,452 (35.4%)

227 (52.

Moving t

C

7%)

1%)

.7%)

1%)

.9%)

ocation

0

LIHT

58 (100%)

xtent are Moving to W

oucher Assistance at Moving to W

No L in RAD or

160 (100%)

3,688 (66.

1,289 (66.

258 (61.9%)

1,545 (47

101 (68.2%)

470 (25.8%)

1,359 (33.

209 (47

1,143 (81.2%)

407 (93.8%)

V

o what e

105

0

enant-Based V

160

5,527

1,950

417

3,240

148

1,824

4,

436

1,408

434

58

Total PB

(2016)

ow-Income Housing T

Households

-

-

-

-

-

uthority

uthority

artners

uthority

uthority

edevel

uthority of Balti

uthority of Cham

uthority of Co

tate Housing

gency Name

e Housing A

uthority

Research Question 3: T Demonstration or L

EXHIBIT B.3 Project-Based and T Credit Properties, 2016

MTW A

Alaska Housing Finance Corporation

Atlanta Housing A

Housing A more City

Boulder Housing P

Cambridge Housing Authority

Housing A paign County

Charlotte Housing A

Chicago Housing A

Housing A lumbus, Georgia

Delaware S Authority

District of Columbia Hous ing A

Fairfax County R opment and Housing Authority

Holyok

C

0

0

0

0

0

0

0

0

7

0

0

0

0

0

0

LIHT

.2%)(0

ax Credit

Location in RAD and

(continued)

1%)

7%)

.0%)

C Only

31 (7.7%) 929

36

63

.0%)

80

(8.8%)

(4.2%)

(2.2%)

163 (5.5%) 610 (6.0%) 322 (9 501 (3.2%) 216 (4.0%)

(5.3%)

Location in LIHT

509 (15.0%)

785 (8.2%)

1,185 (6.

692 (14.

1,824 (19

ow-Income Housing T

Vs

0

0

0

3 .1%)

0

0

0

0

0

0

14 .1%)

0

0

0

(0

12 .4%)(0

(0

MTW TB

Location in RAD Only

C

.7%)

7%)

ocation

129

7%)

LIHT

2,890 (85.0%)

18, (93.9%)

4,005 (85.3%)

2,807 (93.9%)

9,629 (94.0%)

15,259 (96.

No L in RAD or

371 (92.3%)

768 (97

169 (96.0%)

9,599 (91.2%)

821 (95.8%)

2,

8,808 (91.8%)

3,247 (91.0%)

5,

1,442 (94.

7,761 (81.0%)

V

,314

774

ssistance

ental Assistance Demonstration or L

402

,528

857

,239

2,834

3,399

9,593

19

4,697

1,522

Total TB

(2016)

10

2,989

10

3,569

15,

5,385

9,585

Households

oucher A

esults

ocation in R

C

0

0

0

0

0

0

0

0

0

0

0

0

0

0

LIHT

25 (2.9%)

Location in RAD and

roject-Based V

dditional R

f P

B-7

gencies by L

1%)

.2%)

.7%)

se o

ork A

C Only

0

0

0

0

0

57 7%)

0

47

.7%)

0

(6.

33

(12.5%)

(17

Location in LIHT

326 (15.

770 (23.8%)

242 (30

613 (28.4%)

759 (40

Appendix B: A

gencies’ U

Vs

.5%)

1%)

ork A

0

0

0

0

0

0

0

0

0

0

0

0

0

o W

MTW PB

Location in RAD Only

196 (97

223 (26.

Moving t

C

.8%)

.3%)

.5%)

ocation

0

5

1

0

LIHT

58

56

(2.5%)

(100%)

(100%)

2,466 (76.2%)

(100%)

oucher Assistance at Moving to W

No L in RAD or

370 (100%)

1,838 (84.9%)

559 (69

549 (64.3%)

1,546 (71.6%)

1,105 (59

330 (87

153 (82.3%)

V

370

164

0

1

159

0

2,

201

58

3,236

801

854

2,

56

1,864

377

186

enant-Based V

Total PB

(2016)

Households

-

uthority

uthority

uthority

uthority

ortland,

(continued)

uthority

uthority

uthority of the

uthority of the

gency Name

uthority

MTW A

Keene Housing

King County Housing Authority

Lawrence-Douglas County Housing A

Lexington-Fayette Urban County Housing A

Lincoln Housing A

Louisville Metropolitan Housing A

Massachusetts Department of Housing and Community Development

Minneapolis Public Housing Authority

Housing A City of New Haven

Oakland Housing A

Orlando Housing A

Philadelphia Housing Authority

Housing A City of Pittsburgh

Portage Metropolitan Hous ing A

Home Forward (P OR)

Exhibit B.3 Project-Based and T Properties, 2016

C

0

0

0

0

0

0

0

0

0

0

ax Credit

LIHT

10 .004%)

Location in RAD and

(0

.1%)

.7%)

.9%)

.8%)

C Only

237 7%)

7%)

7%)

(2.

294 (8.

288 (8.6%)

168 (6.

Location in LIHT

241 (10

1,053 (7

1,486 (9

618 (14.0%)

1,886 (12.9%)

1,246 (25.2%)

21,324 (7

ow-Income Housing T

Vs

0

0

12 .1%)

0

0

0

0

0

0

.1%)

(0

26 (1.0%) 382 (0

MTW TB

Location in RAD Only

C .9%)

.2%)

.1%)

.

households at MTW

ocation

.1%)

723 1%)

LIHT

12,625 (92.3%)

13,553 (90

708 (87

2,320 (92.3%)

252, (92.

No L in RAD or

138 (892,

8,570 (97

788 (86.0%)3,

12,

3,691 (74.8%)

3,077 (91.3%)

3,053 (91.4%)

V

sing Preservation Database data

ssistance

ental Assistance Demonstration or L

2,379

8,819

4,937

3,371

3,341

2,514

Total TB

(2016)

13,678

15,039

4,406

14,594

274,439

V = tenant-based voucher

Households

oucher A

esults

ocation in R

C

0

0

0

0

0

0

0

0

0

0

LIHT

387 .9%)(0

Location in RAD and

roject-Based V

dditional R

gencies by L

f P

B-8

.1%)

.1%)

se o

ork A

C Only

2 1%)

0

0

1 .0%)

0

7%)

ental Assistance Demonstration. TB

(3.

77

,597

(50

(12.2%)

10 (25.

Location in LIHT

372 (65.3%)

407 (30

1,697 (47

296 (23.8%)

Appendix B: A

. RAD = R

gencies’ U

Vs

7%)

ork A

0

0

0

0

0

0

0

o W

MTW PB

Location in RAD Only

751 (43.4%)

146 (11.

271 (43.0%)

5,347 (13.0%)

Moving t

C

7%)

.9%)

V = project-based voucher

ocation

21

1 .0%)

15

.4%)

LIHT

62 (96.9%)

(100%)

(50

(100%)

24,939 (60

ork. PB

oucher Assistance at Moving to W

No L in RAD or

980 (56.6%)

198 (34.

947 (69

1,906 (52.9%)

804 (64.5%)

282 (44.8%)

V

64

21

1,731

570

2

1,354

15

3,603

1,246

630

enant-Based V

Total PB

(2016)

41,270

Households

C properties between 1987 and 2015 with active tax credits. Overlap for all MTW public housing agencies (PHAs) is out of total

-

ax Credit. MTW = Moving to W

u-

uthority

uthority

(continued)

uthority of the

uthority of the

uthority of the

uthority of the

uthority of the

gency Name

eno

C counts only include LIHT

ow-Income Housing T

2016 HUD Office of Public and Indian Housing Information Center data; 2013–2016 RAD First Component data; 1987–2015 National Hou

LIHT

C = L

MTW A

Housing A City of R

San Antonio Housing Authority

Housing A County of San Bernardino

San Diego Housing Com mission

Housing A County of San Mateo

Housing A County of Santa Clara/ Housing A City of San Jose

Seattle Housing A

Tacoma Housing A

Tulare County Housing Authority

Vancouver Housing A thority

MTW Agencies

Exhibit B.3 Project-Based and T Properties, 2016

LIHT

Notes:

PHAs, rather than averages across PHAs.

Sources:

Appendix B: Additional Results

Research Question 4: Are project-

participation and labor market engagement.

based vouchers at Moving to Work

There is also a strong relationship between

agencies in lower-poverty, higher-quality

percent with a bachelor’s degree and school

neighborhoods? Do project-based

proficiency Index.

voucher locations vary by household

race or ethnicity?

The relationships between these metrics and

the environmental health index are weaker,

Analysis of Correlation Between

ranging from -0.01 to 0.18. We also find a

Neighborhood Measures

positive relationship between the poverty

Exhibit B.4 displays the results of a

rate and transportation costs index (0.40).

correlation analysis of the county-normalized

This likely reflects the prevalence of high-

neighborhood measures and shows that

poverty neighborhoods within the urban

the indices provide unique information;

core of cities and therefore providing shorter

correlations have absolute values as low as

commutes and better access to public transit.

0.01.

Poverty and transportation costs tend to be

negatively correlated with other measures

Generally, we find positive relationships

of neighborhood quality. The lone exception

between the fraction of the population with

is a marginal y positive (0.01) correlation

a bachelor’s degree, labor force participation

between percent with a bachelor’s degree

rate, labor market engagement index,

and transportation costs. Gourevitch, Greene,

environmental health index, and school

and Pendall (2018) note that the people living

proficiency index. The relationships between

below the poverty line tend to live in census

percent with a bachelor’s degree, labor force

tracts that score better on the transportation

participation, and labor market engagement

cost index and that the transportation cost

are relatively strong, with correlations

index is strongly associated with being in a

ranging from 0.29 to 0.82. Not surprisingly,

metropolitan area and is inversely correlated

neighborhoods with higher levels of education

with the environmental hazards.

tend to have higher levels of labor force

Exhibit B.4 Correlation Matrix for Neighborhood Quality Measures

Percent

Poverty

with

Labor Force Labor Market Environmental

School

Transportation

Rate

Bachelor’s Participation Engagement Health Index Proficiency

Cost Index

Degree

Index

Index

Poverty Rate

1.00

Percent with Bachelor’s

Degree

-0.51

1.00

Labor Force Participation

-0.37

0.29

1.00

Labor Market Engagement

Index

-0.62

0.82

0.46

1.00

Environmental Health Index

-0.29

0.009

-0.01

0.13

1.00

School Proficiency Index

-0.47

0.53

0.19

0.54

0.18

1.00

Transportation Cost Index

0.40

-0.04

-0.05

-0.15

-0.39

-0.17

1.00

Note: Table displays the correlation between neighborhood quality measures at the census tract level.

Source: Authors’ calculations based on data from American Community Survey and Affirmatively Furthering Fair Housing Moving to Work Agencies’ Use of Project-Based Voucher Assistance

B-9

Appendix B: Additional Results

Supplemental Exhibits

Exhibit B.5 displays the calculation of

county-normalized poverty rates for MTW

agencies. The county normalized poverty

rate is calculated as the ratio of the average

neighborhood poverty rate across PBV-

assisted households divided by the average

poverty rate in the county in which the

plurality of assisted households lives. For

example, row 1 shows the poverty rate in the

consolidated city-borough of Anchorage,

Alaska, was 8.1 percent in 2016. The average

PBV-assisted household lived in a census

tract with a poverty rate of 17.4 percent.

The county-normalized poverty measure is

(0.174/0.081)=2.148.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

B-10

Appendix B: Additional Results

Exhibit B.5 County-Normalized Average Poverty Rate for Project-Based Voucher Locations by Moving to Work Agency, 2016

Average Poverty for

PBV Locations

County Average

MTW Agency

Poverty Rate

Poverty Rate

County-Normalized

Alaska Housing Finance Corporation

8%

17%

2.15

Atlanta Housing Authority

19%

36%

1.84

Housing Authority of Baltimore City

23%

27%

1.18

Boulder Housing Partners

13%

23%

1.72

Cambridge Housing Authority

8%

21%

2.00

Housing Authority of Champaign County

20%

26%

1.30

Charlotte Housing Authority

15%

22%

1.44

Chicago Housing Authority

17%

33%

1.90

Housing Authority of Columbus, Georgia

21%

50%

2.36

Delaware State Housing Authority

13%

n/a

n/a

District of Columbia Housing Authority

18%

32%

1.79

Fairfax County Redevelopment and

Housing Authority

6%

8%

1.41

Holyoke Housing Authority

18%

26%

1.47

Keene Housing

11%

16%

1.45

King County Housing Authority

11%

14%

1.34

Lawrence-Douglas County Housing Authority

19%

n/a

n/a

Lexington-Fayette Urban County

Housing Authority

22%

41%

1.88

Lincoln Housing Authority

15%

43%

2.90

Louisville Metropolitan Housing Authority

17%

41%

2.41

Massachusetts Department of Housing and

Community Development

18%

20%

1.52

Minneapolis Public Housing Authority

12%

29%

2.32

Housing Authority of the City of New Haven

13%

28%

2.18

Oakland Housing Authority

12%

28%

2.27

Orlando Housing Authority

18%

47%

2.67

Philadelphia Housing Authority

26%

36%

1.39

Housing Authority of the City of Pittsburgh

13%

35%

2.71

Portage Metropolitan Housing Authority

15%

23%

1.51

Home Forward (Portland, OR)

17%

n/a

n/a

Housing Authority of the City of Reno

15%

19%

1.26

San Antonio Housing Authority

19%

31%

1.67

Housing Authority of the County of San

Bernardino

20%

28%

1.41

San Diego Housing Commission

14%

28%

2.02

Housing Authority of the County of San Mateo

8%

14%

1.89

(continued)

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

B-11

Appendix B: Additional Results

Exhibit B.5 County-Normalized Average Poverty Rate for Project-Based Voucher Locations by Moving to Work Agency, 2016

(continued)

Average Poverty for

PBV Locations

County Average

MTW Agency

Poverty Rate

Poverty Rate

County-Normalized

Housing Authority of the County of Santa

Clara/Housing Authority of the City of San

Jose

9%

13%

1.40

Seattle Housing Authority

11%

21%

2.02

Tacoma Housing Authority

13%

38%

2.95

Tulare County Housing Authority

28%

31%

1.09

Vancouver Housing Authority

11%

20%

1.84

MTW = Moving to Work. PBV = project-based voucher.

Note: Table compares county poverty rate, the average poverty rate of census tracts with PBV units (weighted by the number of units), and the county normalized poverty rate for PBV units.

To understand whether differences between

PBV and tenant-based voucher (TBV) or PBV

and public housing location fol owed a similar

pattern at MTW and comparison agencies, we

calculated net differences that are displayed

in exhibit B.6. In general, the differences in

location characteristics between programs are

the same at MTW and comparison agencies.

The difference between the average

environmental health index in TBV and in PBV

neighborhoods is greater at MTW agencies,

however.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

B-12

Appendix B: Additional Results

Exhibit B.6 Qualities of Project-Based Voucher Neighborhoods in Relation to Tenant-Based Voucher and Public Housing Neighborhoods at Moving to Work and Traditional Public Housing Agencies Displayed as Net Differences Means

Net Differences

(p-values)

MTW PBV

Traditional

(MTW PBV - TBV) -

(MTW PBV - PH) -

PBV

(Traditional PBV - TBV)

(Traditional PBV - PH)

1.85

1.67

0.12

0.08

Poverty Rate

(0.228)

(0.539)

Percent with Bachelor’s

0.83

0.74

0.08

0.01

Degree

(0.197)

(0.927)

0.96

0.97

0.01

0.00

Labor Force Participation

(0.492)

(0.976)

Labor Market Engagement

0.67

0.69

0.02

-0.05

Index

(0.792)

(0.547)

Environmental

0.61

0.77

-0.11**

-0.04

Health Index

(0.016)

(0.458)

0.71

0.67

0.04

0.00

School Proficiency Index

(0.397)

(0.979)

Transportation

1.24

1.14

0.03

0.02

Cost Index

(0.412)

(0.737)

* p<0.10, ** p<0.05, *** p<0.01.

MTW = Moving to Work. PBV = project-based voucher. PH = public housing. TBV = tenant-based voucher.

Notes: Tables display the net difference in county-normalized rates-poverty rates normalized by the average poverty rate in the region (county). The Housing Authority of the City of San Jose and Housing Authority of the County of Santa Clara household counts in the HUD Office of Public and Indian Housing Information Center data are reported jointly and listed here as a single public housing agency. Household race and ethnicity are determined by the household head.

Exhibit 4.9 displays average neighborhood

characteristics for PBV locations by race/

ethnicity and assisted housing program,

specifically displaying the poverty rate,

share of the population with a bachelor’s

degree, environmental health index, and

transportation cost index. Exhibit B.7 provides

a supplement. It displays the labor force

participation rate, labor market engagement

index, and school proficiency index by

program and race/ethnicity.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

B-13

Appendix B: Additional Results

Exhibit B.7 Supplemental County-Normalized Measures of Neighborhood Quality for Assisted Households at Moving to Work Agencies by Program and Race/Ethnicity, 2016

Differences

Differences

Means

PHAs

PHAs

(p-value)

(p-value)

PBV

TBV

PH

PBV - TBV

PBV - PH

Labor force participation

0.96

0.97

0.93

-0.01

35

0.03

31

Black (non-Hispanic)

(0.293)

(0.088)

0.96

0.99

0.96

-0.03

34

-0.01

31

Hispanic

(0.009)

(0.655)

0.97

1.00

0.97

-0.02

33

0.00

30

White (non-Hispanic)

(0.095)

(0.937)

Labor market engagement index

0.68

0.68

0.56

0.00

35

0.09

31

Black (non-Hispanic)

(0.893)

(0.041)

0.70

0.71

0.67

-0.01

34

0.02

31

Hispanic

(0.741)

(0.632)

0.81

0.84

0.76

-0.03

33

0.04

30

White (non-Hispanic)

(0.551)

(0.552)

School Proficiency Index

0.69

0.65

0.64

0.04

35

0.02

31

Black (non-Hispanic)

(0.373)

(0.661)

0.83

0.82

0.75

0.01

33

0.07

30

Hispanic

(0.868)

(0.207)

0.70

0.68

0.70

0.01

34

-0.02

31

White (non-Hispanic)

(0.75)

(0.759)

* p<0.10, ** p<0.05, *** p<0.01.

PBV = project-based voucher. PH = public housing. PHA = public housing agency. TBV = tenant-based voucher.

Notes: All statistics are normalized to the county mean. Raw values for the labor market engagement index are national percentile ranks with higher values signifying better outcomes; school proficiency index is percentile ranked at the state level. Additional measures appear in appendix B.9. This exhibit excludes Delaware State Housing Authority, Lawrence-Douglas County Housing Authority, and Home Forward (Portland, Oregon), who do not have any PBV units. The Housing Authority of the City of San Jose and Housing Authority of the County of Santa Clara household counts in the HUD Office of Public and Indian Housing Information Center data are reported jointly; they are listed here as a single PHA.

Exhibit B.8 provides a comparison of PBV

served with PBVs grew from an average of 3

neighborhood characteristics in 2009 and

percent in 2009 to an average of 11 in 2016.

2016, by race and ethnicity. Among the

Between 2009 and 2016, the average county-

24 MTW PHAs with PBVs in both 2009

normalized neighborhood poverty fell from 2.1

and 2016, PBVs are in lower-poverty

to 1.8.

neighborhoods in 2016 than they were in

2009. The share of MTW-assisted households

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

B-14

Appendix B: Additional Results

Exhibit B.8 Difference in County-Normalized Measures of Neighborhood Quality for Assisted Households at Moving to Work Agencies by Program and Race/Ethnicity, 2009 and 2016

Means

Differences

Number of MTW

2009

2016

(p-value)

Agencies

Poverty Rate

2.07

1.81

-0.26**

24

All Households

(0.032)

2.09

1.89

-0.20

23

Black (non-Hispanic)

(0.137)

1.98

1.72

-0.26**

22

Hispanic/Latino

(0.03)

1.94

1.61

-0.33**

23

White (non-Hispanic)

(0.012)

Percent with Bachelor’s Degree

0.79

0.85

0.07

24

All Households

(0.105)

0.76

0.84

0.08

23

Black (non-Hispanic)

(0.312)

0.76

0.85

0.08

22

Hispanic/Latino

(0.174)

0.97

1.08

0.11

23

White (non-Hispanic)

(0.123)

Labor Force Participation

0.90

0.95

0.05***

24

All Households

(0.005)

0.89

0.96

0.07**

23

Black (non-Hispanic)

(0.017)

0.91

0.96

0.05**

22

Hispanic/Latino

(0.018)

0.92

0.98

0.05**

23

White (non-Hispanic)

(0.020)

* p<0.10, ** p<0.05, *** p<0.01.

MTW = Moving to Work.

Note: The table displays differences in statistics that have been normalized to the county mean. This exhibit excludes Delaware State Housing Authority, Lawrence-Douglas County Housing Authority, and Home Forward (Portland, Oregon), who do not have any project-based voucher units. The Housing Authority of the City of San Jose and Housing Authority of the County of Santa Clara household counts in the HUD Office of Public and Indian Housing Information Center data are reported jointly; they are listed here as a single public housing agency. P-values are derived from paired t-tests. Household race and ethnicity are determined by the household head.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

B-15

Appendix B: Additional Results

Research Question 5: What factors are

costs measured using the Affirmatively

associated with variation in Moving to

Furthering Fair Housing (AFFH) Low Cost

Work project-based voucher locations?

Transportation index.

We explored alternative versions of the model

Sample sizes are reduced due to data

presented in exhibits 4.10 and 4.11. Specifical y,

availability. For this reason, we only

we add the fol owing to the model: identifier

examined this larger set of factors using the

variables for census geographic region;

larger sample that includes both MTW and

average rental prices measured with the

comparison agencies. Results appear in

Zil ow Rent Index (ZRI) in 2016; the percentage

exhibits B.9 and B. 10 in columns 3 and 4, with

change in the ZRI over the 5 years prior to

results from exhibits 4.10 and 4.11 repeated in

our analysis year (2011 to 2016); residential

columns 1 and 2 for comparison.

property values measured by the Zil ow Home

Value Index (ZHVI) in 2016, and transportation

Exhibit B.9 Model Results: Modeling the Average County-Normalized Poverty Rate of Project-Based Voucher Locations with Additional Explanatory Variables

(1)

(2)

(3)

(4)

-1.853

-1.392

0.727

-1.783

Income Inequality

(1.432)

(1.133)

(1.902)

(1.574)

1.457***

0.342

1.787***

0.976***

Segregation (Dissimilarity Index)

(0.290)

(0.223)

(0.357)

(0.279)

-3.894***

0.138

-6.065***

-0.634

County Poverty Rate

(0.674)

(0.554)

(1.283)

(1.083)

Percent of TBV households in high

poverty neighborhoods

1.131***

1.152***

Fraction of PBV units in RAD Properties

(0.079)

(0.102)

0.343

-0.0810

Increase in Rents (2011–2016)

(0.337)

(0.280)

Property Values (Zillow Home Value

-0.000292

0.0000286

Index 2016)

(0.000)

(0.000)

0.000360

-0.00197

Transportation Cost Index

(0.003)

(0.003)

-0.0356

0.181*

South

(0.116)

(0.095)

-0.110

0.0985

Midwest

(0.140)

(0.109)

0.0870

0.232**

West

(0.132)

(0.097)

2.544***

0.438

2.880***

0.447

Constant

(0.584)

(0.454)

(0.927)

(0.780)

(continued)

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

B-16

Appendix B: Additional Results

Exhibit B.9 Model Results: Modeling the Average County-Normalized Poverty Rate of Project-Based Voucher Locations with Additional Explanatory Variables (continued)

(1)

(2)

(3)

(4)

Observations

446

446

343

343

* p<0.10, ** p<0.05, *** p<0.01.

PBV = project-based voucher. RAD = Rental Assistance Demonstration. TBV = tenant-based voucher.

Notes: Outcome variable is the county-normalized poverty rate of PBV neighborhoods in 2016. Samples include public housing agencies (PHAs) with at least 750

households in 2016 and for whom both Real Estate Assessment Center and Zillow data were available. For Moving to Work PHAs, this excludes Alaska Housing Finance Corporation; Massachusetts Department of Housing and Community Development; Holyoke Housing Authority; and Housing Authority of Champaign County. The Housing Authority of the City of San Jose and Housing Authority of the County of Santa Clara household counts in the HUD Office of Public and Indian Housing Information Center data are reported jointly; they are listed here as a single PHA. Standard errors are heteroskedastic robust and displayed in parentheses.

Exhibit B.10 Model Results: Modeling the Percent of Project-Based Vouchers in High-Poverty Neighborhoods with Additional Explanatory Variables

(1)

(2)

(3)

(4)

-0.865

-0.430

0.229

-0.308

Income Inequality

(0.659)

(0.584)

(0.878)

(0.748)

0.856***

0.360***

1.001***

0.646***

Segregation (Dissimilarity Index)

(0.130)

(0.114)

(0.163)

(0.145)

-2.320***

-0.700**

-3.467***

-1.567***

County Poverty Rate

(0.310)

(0.312)

(0.564)

(0.517)

Percent of TBV households in high

0.942***

0.930***

poverty neighborhoods

(0.077)

(0.096)

0.148

-0.0448

Increase in Rents (2011–2016)

(0.169)

(0.153)

Property Values (Zillow Home Value

-0.000120

0.0000286

Index 2016)

(0.000)

(0.000)

0.000472

-0.000767

Transportation Cost Index

(0.001)

(0.001)

0.0174

0.102**

South

(0.058)

(0.051)

0.00192

0.0759

Midwest

(0.065)

(0.056)

0.0818

0.148***

West

(0.064)

(0.054)

0.729***

0.252

0.902**

0.375

Constant

(0.268)

(0.238)

(0.431)

(0.372)

(continued)

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

B-17

Appendix B: Additional Results

Exhibit B.10 Model Results: Modeling the Percent of Project-Based Vouchers in High-Poverty Neighborhoods with Additional Explanatory Variables (continued)

(1)

(2)

(3)

(4)

Observations

446

446

343

343

* p<0.10, ** p<0.05, *** p<0.01.

TBV = tenant-based voucher.

Notes: Outcome variable is the county-normalized poverty rate of project-based voucher neighborhoods (2016). Samples include public housing agencies (PHAs) with at least 750 households in 2016 and for whom both Real Estate Assessment Center and Zillow data were available. For Moving to Work PHAs, this excludes Alaska Housing Finance Corporation; Massachusetts Department of Housing and Community Development; Holyoke Housing Authority; and Housing Authority of Champaign County. The Housing Authority of the City of San Jose and Housing Authority of the County of Santa Clara household counts in the HUD Office of Public and Indian Housing Information Center data are reported jointly; they are listed here as a single PHA. Standard errors are heteroskedastic robust and displayed in parentheses.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

B-18

Appendix C: Interview Protocol

Appendix C:

Motivation

Interview Protocol

• To start, can you tell us a little about your

PBV program? (e.g., the size, planning, long

term goals)

• How are you using your PBVs?

Introduction and Consent

» How would you describe your

Hel o, my name is [NAME], and this is my

agency’s primary motivation(s) or goals

colleague [NAME], and we are members of

for using PBVs?

the Urban Institute (Urban) research team that

» We know that MTW activities need to

is conducting the HUD-sponsored evaluation

meet one of three statutory objectives:

of the MTW Program. The Urban Institute is

cost-effectiveness, housing choice,

a non-profit research organization based in

and self-sufficiency.

Washington, DC.

» What is the relationship to your

As part of the assessment, we are speaking

activities and the MTW objectives?

with staff from 3 PHAs with substantial PBV

» How does your PBV program help you

activity to better understand how MTW

meet the statutory objectives for the

agencies use PBVs.

MTW demonstration? Which objectives

does it help you meet?

[NAME OF NOTE TAKER] will be taking

notes and with your permission, it will also

» Does your PBV program help you to

be recorded. Your participation, and your

meet other goals?

agency’s participation, in this discussion

» (e.g. targeting opportunity

is completely voluntary and we will not be

neighborhoods, preserving affordable

evaluating any particular initiative or effort –

housing, serving specific populations,

but rather describing your activities, goals,

providing supportive services, or

opportunities, and challenges using PBVs.

improving housing quality?

The information col ected from these

• Has your agency experienced any

discussions will be used for research purposes

constraints in using PBVs?

only.

» Financing challenges (e.g., property

costs, acquiring financing)?

Before we get started, do you agree/consent

to this interview, and to recording?

» HUD’s PBV caps?

» Any other concerns?

Do you have any questions before we begin?

• How does the agency determine whether to

We appreciate your wil ingness to participate.

use PBVs versus other housing programs?

» What factors influence this decision?

Background

» Who is responsible for these

• Can you confirm your title/position?

decisions?

• How long you have been in this position?

» Did the implementation of HOTMA

[compare date with agency MTW entry]

impact your use of PBVs?

• How long have you worked at the agency?

• How do you measure the impact of your

PBV program?

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

C-1

Appendix C: Interview Protocol

• Has your PBV program made an impact on

• ( If applicable) We see from our data that

your agency’s overall goals?

you have XX RAD conversions. Why did

» [If so, how?]

you choose to use PBVs over PBRAs? (not

applicable for Seattle Housing Authority)

MTW Flexibilities

» Has the use of PBVs with RAD

specifically impacted housing quality?

• We are trying to understand how MTW

flexibilities and PBV programs and activities

• ( If applicable) Has the use of LIHTC

are related. Can you tell me about the

helped to increase access to opportunity

process for implementing an MTW PBV

neighborhoods?

activity?

» Prompt: Do you look at the flexibilities

Partnerships

first and then plan an activity around

• Have you developed partnerships with

them? Or do you have an activity

other local organizations to leverage PBV

you want to do and make it fit the

assistance? If so, with whom?

flexibility?

• Have these partnerships helped you to

• What MTW flexibilities have helped your

meet mobility, supportive service, special

agency regarding the use of project-basing?

population, or other local y-relevant goals?

(ex. waiving either of the PBV caps, waitlist

• How do these partnerships function?

options)?

» Do you have MOUs?

• How have MTW flexibilities influenced

decisions to expand PBV use?

• Have you encountered any difficulty

partnering with other local organizations?

» Have they al owed you to serve

If so, did that impact your decision to

households with more complex needs

implement PBV activities?

through your PBV program?

 Are you using PBVs to serve

Wrap Up

homeless populations?

• Is there anything else that we aren’t asking

 Are you using PBVs to provide

that we should be asking? Anything else you

supportive services?

would like to share with us?

» Are you are trying to target other

• Are there any fol ow up conversations we

populations with your PBV program

should have with partners or other staff

(or vouchers, generally) (e.g., family

members?

composition, age, gender, or race/

Thank you for taking this time to meet with us.

ethnicity)?

If there’s anything you think of later that you’d

» Would these activities have been

like to share, please don’t hesitate to e-mail or

possible without the use of MTW PBV

call us.

flexibilities?

• Have you considered implementing any

activities that you decided not to? Why?

• Have you encountered any challenges in

implementing your PBV activities?

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

C-2

Appendix D. Moving to Work Agencies

Appendix D. Moving Oakland Housing Authority

to Work Agencies

Orlando Housing Authority

Philadelphia Housing Authority

Housing Authority of the City of Pittsburgh

Alaska Housing Finance Corporation

Portage Metropolitan Housing Authority

Atlanta Housing Authority

Home Forward (Portland, Oregon)

Housing Authority of Baltimore City

Housing Authority of the City of Reno

Boulder Housing Partners

San Antonio Housing Authority

Cambridge Housing Authority

Housing Authority of the County of

Housing Authority of Champaign County

San Bernardino

Charlotte Housing Authority

San Diego Housing Commission

Chicago Housing Authority

Housing Authority of the County of San Mateo

Housing Authority of Columbus, Georgia

Housing Authority of the County of Santa Clara*

Delaware State Housing Authority

Housing Authority of the City of San Jose*

District of Columbia Housing Authority

Seattle Housing Authority

Fairfax County Redevelopment and

Tacoma Housing Authority

Housing Authority

Tulare County Housing Authority

Holyoke Housing Authority

Vancouver Housing Authority

Keene Housing

King County Housing Authority

Lawrence-Douglas County Housing Authority

*The housing authorities of the County of Santa

Lexington-Fayette Urban County

Clara and the City of San Jose submit joint Moving

Housing Authority

to Work plans and reports.

Lincoln Housing Authority

Louisville Metropolitan Housing Authority

Massachusetts Department of Housing

and Community Development

Minneapolis Public Housing Authority

Housing Authority of the City of New Haven

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

D-1

-

-

-

-

-

-

Vs;

(continued)

artners,

V rules, as

ent limits and

ousing P

V units; Allow participants

.

, but we want to be able to project

oulder H

aive the 20 percent cap on PB

gencies

or B

.

ork A

cies

Description

uthority to establish appropriate rent limits in

lans f

.

) p

aive the competitive bidding process; R

xpand its Project-Based portfolio beyond the 20-per

V Communities where the developer is required, or has

gen

tandards inspections at our PB

et study

TWM

tudy Moving to W

oucher-Related

ork (

ssistance

xcepted units; W

o W

s main objective is to reduce cost, eliminate redundancy and increase

, which will provide for a quick turn around on a vacant unit and choos

oucher A

ork A oving t

This activity will combine several approved activities related to the PB well as implementing three new elements: W Definition of e rent reasonableness; Allow owner/service partner to hold waitlist; Allow BHP staff to conduct Housing Quality S who are no longer receiving HAPs to remain on the voucher; Allow participant fami lies to continue to pay rent according to their income This initiative will project base 100 percent of replacement vouchers at family prop erties. The goal is to provide services at each site base in advance of such programs being finalized This activity’ efficiency by allowing the Housing A project-based voucher projects and conduct its own rent reasonableness proce dures for setting rents at PB chosen, to conduct a mark This initiative allows applicants to be chosen by the service provider or the owner of the property ing an applicant who will fit the community and benefit from the services provided.

This program allows CHA to e cent HUD threshold and allows property owners to project base a building beyond the 25-percent HUD threshold. Property owners may coordinate with CHA to proj ect base up to 100 percent of a property ctivities for Case S

o W

roject-Based V

nnual M

Year

2018

2012

2014

2015

2001

f P

E-1

elated A

se o

018 a rity.

oucher-R

he 2 utho

Status

Closed

Closed

Closed

gencies’ U

roject-Based V oving t

gencies

Ongoing

Ongoing

rom t g A

ork A

f P

ork A

re f sin

o W

dy M

ou

.1 a

PHA

Moving t

tory o tu

Boulder

Boulder

Boulder

Boulder

Cambridge

xhibit E eattle H S

ase S n e d the

xibility

xibility

xibility

Appendix E. Inventory of Project-Based V

. Inven or C rovided i rity, an elated Initiatives at Moving to W

V fle

V fle

V fle

ns p

PB

Development

PB

PB

utho

Activity Category

Admissions policy

dix E

riptio g A

-ea

esc sin

-

V

ou

Vs

ent R

pen

ge H

ocal Proj

1 Inventory of Mobility-R

Ap Activities f nitiative d brid

aivers

V W

Vs to cover 100

V Applicant Process

The i Cam

Exhibit E.

Initiative

PB

Allow BHP to commit PB percent of the units at converted public housing developments

Rent Limits and R sonableness for PB

PB

Implement L ect-Based Assistance Leasing Program/HC

-

-

-

’s public housing

Vs and low-in

ow Income Housing Program, es sense and reduces costs by

e public housing subsidized units in . This streamlined approach includes

gencies

Vs for private affordable properties with

Vs.

ork A

Description

.

treamlined L

ork.

ouchers to PB

xibility to apply similar public housing policies and procedures

e project-based programs financially feasible for owners, and

Vs to be operated just lik

tudy Moving to W

’s project-based activities include a large number of MTW strategies

ssistance

. SHA

. MTW = Moving to W

’s current implementation of this activity allows for all units subsidized

, units) within the same community mak

oucher A

CHA converts Enhanced V maturing mortgages

This initiative focuses on increasing the supply of hard units in CHA portfolio and through an increase in PB

Similar to the biennial recertification policy in Public Housing, a biennial recertifica tion schedule would apply to households living in project-based units CHA will use MTW fle to residents in project-based units.

SHA uses MTW to develop and implement a local project-based program, providing vouchers to subsidize units in SHA-owned and nonprofit-owned properties through out Seattle to reduce costs, mak to provide housing choice in Seattle In some of its communities, SHA co-locates units funded through PB come public housing. Combining program management and policies for both of these types of units (referred to as S or SLIHP eliminating redundancies, including duplicative rent reviews and inspections. It also avoids unnecessary disparities between tenants of the two different types of units. SHA by project-based HC communities that receive both types of subsidy acceptance of slight differences (generally less than $1) in rent calculation caused by different data systems of record for vouchers and public housing.

ctivities for Case S

roject-Based V

Year

2012

2000

2014

2014

2000

2008

V = housing choice voucher

f P

E-2

elated A

se o

(continued)

oucher-R

ayment. HC

Status

Closed

gencies’ U

Ongoing

Ongoing

Ongoing

Ongoing

Ongoing

gencies

ork A

ork A

o W

PHA

Seattle

Seattle

Moving t

Cambridge

Cambridge

Cambridge

Cambridge

. HAP = Housing Assistance P

uthority

.

uthority

xibility

xibility

Appendix E. Inventory of Project-Based V

elated Initiatives at Moving to W

V fle

V fle

Development

Development

Rent reform

PB

PB

Development

Activity Category

-

-

-

. SHA = Seattle Housing A

erma

- V

artners. CHA = Cambridge Housing A

ears for

ecertifica

1 Inventory of Mobility-R

ffordable Hard

V in Public Housing

Initiative

Expiring Use Preservation Program

Expand Supply of P nently A Units of Housing

Implement R tions Every 2 Y Households in Proj ect-Based Units/HC

PB

Project-Based Program

Combined Program Man agement

V = project-based voucher

Exhibit E.

BHP = Boulder Housing P

PB

Appendix F. Inventory of Moving to Work Agencies with an Activity Related to the Family Right to Move Appendix F. Inventory The initiative descriptions here are taken from

or based upon those found in the Moving

of Moving to Work

to Work (MTW) Plans47 and MTW evaluation

database.

Agencies with an

Activity Related to

the Family Right to

Move

Exhibit F.1 Inventory of Activities Related to the Family Right to Move at Moving to Work Agencies Activity

Description of Impact on

Initiative

Category

PHA

Status

Year

Family Right to Move

PBV – Waiver

of Tenant-

PBV flexi-

Alaska Housing Fi-

Based Require-

bility

nance Corporation

Ongoing

2011

Waive the requirement to provide a TBV to a

family upon termination of PBV assistance.

ment

Implement

Local Proj-

ect-Based

PBV flexi-

Cambridge Housing

Assistance

bility

Authority

Ongoing

2001

Extends the time-frame for requesting mobile

vouchers, from 1 to 2 years.

Leasing Pro-

gram/HCV

2-Year Require-

Chicago Housing Authority reduces the

ment for PBV

turnovers in PBV developments by allowing

Participant

Occupancy

Chicago Housing

families only to receive an HCV after 2 years of

Transition to

policy

Authority

Ongoing

2011

occupancy rather than 1 year, except for tenants

HCV

currently residing in a supportive housing unit.

Modify PBV

Fairfax County

PBV holders are able to go on the waitlist after a

Choice Mobility

PBV flexi-

Redevelopment and Not yet imple-

year but will not receive preference or automati-

Criteria

bility

Housing Authority

mented

2016

cally receive a voucher after 1 year.

Local PBV

PBV flexi-

Housing Authority of

Elimination of the automatic conversion to

Program

bility

Champaign County

Ongoing

2011

tenant-based assistance after 1 year in the proj-

ect-based unit.

For our fiscal year 2015 Plan, Home Forward is

proposing a change to this activity. Under exist-

Local PBV

PBV flexi-

Housing Authority of Not yet imple-

ing regulations, PHAs are limited to project-bas-

Program

bility

Portland

mented

2015

ing up to 20 percent of the amount of budget

authority allocated to the agency by HUD in the

voucher program. We are proposing to eliminate

this cap on PBV allocations.

(continued)

47 “Moving to Work (MTW) – Participating Sites,” US Department of Housing and Urban Development. Retrieved from: https:/ www.hud.gov/program_

offices/public_indian_housing/programs/ph/mtw/mtwagencies

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

F-1

Appendix F. Inventory of Moving to Work Agencies with an Activity Related to the Family Right to Move Exhibit F.1 Inventory of Activities Related to the Family Right to Move at Moving to Work Agencies (continued)

Activity

Description of Impact on

Initiative

Category

PHA

Status

Year

Family Right to Move

HACSB has implemented a local PBV program

to increase the availability of quality housing

Local PBV

PBV

Housing Authority of

units. The expansion of our housing authority

Program

flexibility

the County of San

Ongoing

2009

and/or our affiliate nonprofit owned housing

Bernardino

stock will allow us to continue to reinvest net

income into the acquisition of additional afford-

able housing units.

Expand the

Housing Authority of

Requires participating families to stay at least 24

Section 8 PBV

PBV

the County of San

Ongoing

2011

months in a PBV unit before they are eligible to

Program

flexibility

Mateo

move with continued assistance

Minimum 2-Year

Housing Authority

This initiative requires project-based participants

Occupancy in

Occupancy

of the County of

Not yet

to remain in their PBV units for a minimum of 2

Project-Based

policy

Santa Clara/Housing

implemented

2014

years prior to becoming eligible to request a

Unit

Authority of the City

of San Jose

TBV to move with continued assistance.

Massachusetts De-

PBV Discretion-

PBV

partment of Housing

DHCD modified its PBV program guidelines

ary Moves

flexibility

and Community

Ongoing

2012

to establish reasonable limits on discretionary

Development

moves.

This activity increases cost-effectiveness by

removing the automatic provision of a TBV to a

Modified PBVs

PBV

San Antonio Hous-

Not yet

flexibility

ing Authority

implemented

2015

household who wishes to relocate from a unit

associated with local project-based set-aside

voucher.

2-year occu-

Requires PBV holders to complete 2 years of

pancy term for

Occupancy San Diego Housing

occupancy before becoming eligible to receive

PBV tenants

policy

Commission

Ongoing

2011

a TBV.

Project-Based

PBV

Seattle Housing

Offers site-specific waiting lists maintained by

Program

flexibility

Authority

Ongoing

1999

providers (and, therefore, does not issue exit

vouchers)

Local PBV

PBV

Tacoma Housing

Tacoma Housing Authority waived the mobility

Program

flexibility

Authority

Ongoing

2011

option that allows PBV tenants to automatically

receive a TBV after 1 year of occupancy.

Alternative PBV

PBV

Vancouver Housing

Program

flexibility

Authority

Ongoing

2014

Requirement for a move voucher after 1 year

waived.

DHCD = Department of Housing and Community Development. HACSB = Housing Authority of the County of San Bernardino. HCV = housing choice voucher. PBV =

project-based voucher. PHA = public housing agency. TBV = tenant-based voucher.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

F-2

Appendix G. Low-Income Housing Tax Credit Matching Sensitivity Analysis

Appendix G. Low-

assign households to properties.

Income Housing

Existing studies suggest that 200 feet is a

suitable lower bound for the size of a standard

Tax Credit Matching

city block. We used a radius of 200 feet for

our analysis and then conducted a sensitivity

analysis using larger and smaller radii. We

Sensitivity Analysis

repeated our analysis by changing the radius

in 50-foot increments to a minimum of 50 feet

and a maximum of 350 feet and show how

The size of the standard city block varies

the co-location changes in exhibits F.1 and

widely across the United States, ranging

F.2. There is some tapering in the additional

from as small as 200 feet long to 800 feet or

increase in location in Rental Assistance

more. This variation complicates the task of

Demonstration or Low-Income Housing Tax

linking households to properties that applies

Credit for radii above 200 feet for both Moving

the same radius across jurisdictions of

to Work (MTW) project-based vouchers and

varying geographies. Research focused on

tenant-based vouchers. Future research could

a single jurisdiction can tailor the radius to

tailor the radius to more closely match each

the local context and, if necessary, manually

MTW agency’s jurisdiction and local context.

Exhibit G.1 Identifying Co-Location of Project-Based Vouchers in Rental Assistance Demonstration and Low-Income Housing Tax Credit Properties Using Varying Spatial Buffers at Moving to Work Agencies

50 feet

100 feet

150 feet

200 feet

250 feet

300 feet

350 feet

Not RAD or in LIHTC

76.8%

69.5%

64.6%

60.4%

58.0%

55.0%

52.7%

PBV RAD Only

13.9%

13.8%

13.4%

13.0%

12.9%

12.9%

12.4%

PBVs in LIHTC Only

9.3%

16.6%

21.5%

25.7%

28.1%

31.2%

33.4%

PBV RAD and in LIHTC

0.02%

0.1%

0.5%

1.0%

1.0%

1.0%

1.5%

Total

41,270

41,270

41,270

41,270

41,270

41,270

41,270

LIHTC = Low-Income Housing Tax Credit. PBV = project-based voucher. RAD = Rental Assistance Demonstration.

Notes: Active LIHTC properties as of 2015 are included.

Source: 2016 HUD Office of Public and Indian Housing Information Center (PIC) data for counts of Moving to Work PBVs and tenant-based voucher households, and National Housing Preservation Database data for LIHTC addresses in conjunction with PIC addresses for LIHTC household counts Exhibit G.2 Identifying Co-Location of Tenant-Based Vouchers in Rental Assistance Demonstration and Low-Income Housing Tax Credit Properties Using Varying Spatial Buffers at Moving to Work Agencies

50 feet

100 feet

150 feet

200 feet

250 feet

300 feet

350 feet

Not RAD or LIHTC

97.6%

95.4%

93.7%

92.1%

90.6%

89.1%

87.7%

TBV RAD only

0.1%

0.1%

0.1%

0.1%

0.1%

0.1%

0.1%

TBV in LIHTC only

2.3%

4.4%

6.2%

7.8%

9.3%

10.7%

12.2%

TBV RAD and LIHTC

0.0004%

0.001%

0.003%

0.004%

0.004%

0.01%

0.01%

Total

274,439

274,439

274,439

274,439

274,439

274,439

274,439

LIHTC = Low-Income Housing Tax Credit. TBV = tenant-based voucher. RAD = Rental Assistance Demonstration.

Notes: Active LIHTC properties as of 2015 are included.

Source: 2016 HUD Office of Public and Indian Housing Information Center (PIC) data for counts of Moving to Work project-based voucher and TBV households, and National Housing Preservation Database data for LIHTC addresses in conjunction with PIC addresses for LIHTC household counts Moving to Work Agencies’ Use of Project-Based Voucher Assistance

G-1

Appendix H: References

Appendix H:

Ellen, Ingrid Gould, Katherine O’Regan, and

Ioan Voicu. 2009. “Siting, Segregation, and

References

Spil overs: A Re-examination of the Low

Income Housing Tax Credit Program” in

Housing Markets and the Economy: Risk,

Regulation, Policy; Essays in Honor of Karl

Center on Budget and Policy Priorities (CBPP).

Case. Edited by Edward Glaeser and John

2017. Policy Basics: Project-Based Vouchers.

Quigley. Cambridge, MA: Lincoln Institute for

Washington, DC: Center of Budget and Policy

Land Policy.

Priorities.

Freeman, Lance. 2004. Siting Affordable Housing:

Climaco, Carissa, Meryl Finkel, Bulbul Kaul, Ken

Location and Neighborhood Trends of Low

Lam, and Chris Rodger. 2009. Updating the

Income Housing Tax Credit Developments in

Low-Income Housing Tax Credit (LIHTC)

the 1900s. Washington, DC: The Brookings

Database: Projects Placed in Service Through

Institution.

2006. Washington, DC: US Department of

Housing and Urban Development, Office of

Galvez, Martha, Ruth Gourevitch, and Benny

Policy Development and Research.

Docter. Forthcoming. A Picture of Moving

to Work Agencies’ Housing Assistance.

Cunningham, Mary K., Martha M. Galvez, Claudia

Washington, DC: U.S. Department of Housing

L. Aranda, Robert Santos, Douglas Wissoker,

and Urban Development.

Alyse Oneto, Rob Pitingolo, and James

Crawford. 2018. A Pilot Study of Landlord

Galvez, Martha, Jasmine Simington, and

Acceptance of Housing Choice Vouchers.

Mark Treskon. 2017. Moving to Work and

Washington, D.C.: U.S. Department of

Neighborhood Opportunity. Washington, DC:

Housing and Urban Development. https://

The Urban Institute.

www.huduser.gov/portal/pilot-study-landlord-

acceptance-hcv.html.

Gold, Amanda, Matthew Gerken, Carl Hedman,

and Corianne Payton Scal y. 2018. Technical

Cunningham, Mary, and Mol y M. Scott. 2010.

Documentation for the Low-Income Housing

The Resident Choice Option: Reasons Why

Tax Credit: Past Achievements, Future

Residents Change from Project-Based

Chal enges. Washington, DC: Urban Institute.

Vouchers to Portable Housing Vouchers.

Washington, DC: The Urban Institute.

Gourevitch, Ruth, Solomon Greene, and Rolf

Pendal . 2018. Place and Opportunity:

Devine, Deborah J., Robert W. Gray, Lester Rubin,

Using Federal Fair Housing Data to

and Lydia B. Taghavi. 2003. Housing Choice

Examine Opportunity across US Regions

Voucher Location Patterns: Implications for

and Populations. Washington, DC: Urban

Participants and Neighborhood Welfare.

Institute.

Washington, DC: U.S. Department of Housing

and Urban Development.

Handy, Susan, Robert G. Paterson, and Kent Butler.

2003. Planning for Street Connectivity: Getting

Econometrica, Inc. 2016. Evaluation of

from Here to There. Chicago, IL: American

HUD’s Rental Assistance Demonstration

Planning Association.

(RAD): Interim Report. Washington, DC:

U.S. Department of Housing and Urban

Levy, Diane K., David Long, and Leiha Edmonds.

Development. https:/ www.huduser.gov/portal/

2019. Moving to Work Agencies’ Use of

sites/default/files/pdf/RAD-InterimRpt.pdf.

Funding Flexibility. Unpublished manuscript.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

H-1

Appendix H: References

Manson, Steven, Jonathan Schroeder, David

Scal y, Corianne Payton, Amanda Gold, Carl

Van Riper, and Steven Ruggles. 2018. IPUMS

Hedman, Matt Gerken, and Nicole DuBois.

National Historical Geographic Information

2018. The Low-Income Housing Tax Credit:

System: Version 13.0 [Database]. Minneapolis,

Past Achievements, Future Challenges.

MN: University of Minnesota. http://doi.

Research Report . Washington, DC: Urban

org/10.18128/D050.V13.0.

Institute.

Mast, Brent D., and Abt Associates. 2017.

Stacy, Christina, Josh Leopold, Daniel Teles,

Affirmatively Furthering Fair Housing Data and

Ruth Gourevitch, Alyse D. Oneto, Yipeng Su,

Mapping Tool (AFFH-T) Data Documentation.

and Matthew Gerken. 2020. The Impact of

Washington, DC: Department of Housing and

the Moving to Work Demonstration on the

Urban Development.

Per Household Costs of Federal Housing

Assistance. Washington, DC: U.S. Department

Mast, Brent D., and David Hardiman. 2017. “Project-

of Housing and Urban Development.

Based Vouchers,” Cityscape: A Journal of

Policy Development and Research 19 (2):

Treskon, Mark, Matt Gerken, and Martha Galvez.

301–322.

Forthcoming. Housing Choice and Self-

Sufficiency Outcomes at Moving to Work

McClure, Kirk. 2006. “The low-income housing tax

Agencies. Washington, DC: U.S. Department of

credit program goes mainstream and moves

Housing and Urban Development.

to the suburbs,” Housing Policy Debate 17 (3):

419–446.

McClure, Kirk, Alex F. Schwartz, and Lydia B.

Taghavi. 2015. “Housing choice voucher

location patterns a decade later,” Housing

Policy Debate 25 (2): 215–233.

O’Regan, Katherine M., and Keren M. Horn. 2013.

“What Can We Learn About the Low-Income

Housing Tax Credit Program by Looking at

the Tenants?” Housing Policy Debate 23 (3):

597–613.

Poethig, Erika, Liza Getsinger, Josh Leopold,

Graham MacDonald, Lily Posey, Pamela

Blumenthal, Reed Jordan, and Katya

Abazajian. 2017. “Mapping America’s Rental

Housing.” Urban Institute, updated 2017.

https:/ apps.urban.org/features/rental-housing-

crisis-map/.

Scal y, Corianne Payton, Amanda Gold, and Nicole

DuBois. 2018. The Low-Income Housing

Tax Credit: How it Works and Who it Serves.

Research Report. Washington, DC: Urban

Institute.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance

H-2

U.S. Department of Housing and Urban Development

Office of Policy Development and Research

Washington, DC 20410-6000

April 2021

Document Outline

Executive Summary

Findings

Limitations

Implications for Policy and Research

1. Introduction

2. Background

Existing Evidence on Project-Based Voucher Assistance

Interaction with the Rental Assistance Demonstration and Low-Income Housing Tax Credit Programs

3. Research Questions and Study Design

Research Question 1: How extensively do Moving to Work agencies use project-based vouchers?

Research Question 2: What factors are associated with Moving to Work and traditional agencies’ use of project-based voucher assistance?

Research Question 3: To what extent are Moving to Work agencies’ project-based vouchers located in Rental Assistance Demonstration or Low-Income Housing Tax Credit properties?

Research Question 4: Are Moving to Work agency project-based vouchers in lower-poverty, higher-quality neighborhoods? Do project-based voucher locations vary by household race or ethnicity?

Research Question 5: What factors are associated with variations in project-based voucher locations?

Research Question 6: What are the agencies’ motivations for project-based voucher use?

Data

4. Quantitative Results

Research Question 1: How extensively do Moving to Work agencies use project-based vouchers?

Variation Across Moving to Work Agencies

Research Question 2: What factors are associated with Moving to Work and traditional agencies’ use of project-based voucher assistance?

Research Question 3: To what extent are Moving to Work agencies’ project-based vouchers located in Rental Assistance Demonstration or Low-Income Housing Tax Credit properties?

Rental Assistance Demonstration Use at Moving to Work Agencies

Moving to Work Project-Based Vouchers in Low-Income Housing Tax Credit Properties

Variation Across Moving to Work Agencies

Research Question 4: Are Moving to Work agency project-based vouchers in lower-poverty, higher-quality neighborhoods? Do project-based voucher locations vary by household race or ethnicity?

Project-Based Voucher Neighborhoods at Moving to Work Agencies

Moving to Work Project-Based Voucher Locations Compared With Traditional Public Housing Agencies’ Project-Based Voucher Locations

Project-Based Voucher Location Patterns by Race and Ethnicity

The Relationship Between Rental Assistance Demonstration, Low-Income Housing Tax Credit, and Project-Based Voucher Locations

Research Question 5: What factors are associated with variations in Moving to Work project-based voucher locations?

5. Case Studies of Three Moving to Work Agencies’ Project-Based Voucher Use

Common Perspectives on Project-Based Voucher Use

Project-Based Vouchers and Neighborhood Location

Boulder Housing Partners: Public Housing Conversion and Local Partnerships

Cambridge Housing Authority: Preserving Affordable Housing with Project-Based Vouchers

Seattle Housing Authority: Using Project-Based Vouchers to Serve People Exiting Homelessness

6. Conclusions

Limitations

Policy Implications and Future Research

Appendix A: Data and Methodology

Data Sources

HUD Administrative Data

Other Data Sources

Measures and Sampling

Public Housing Agency Characteristics

Neighborhood Characteristics

Regional and Market Characteristics

File Construction

Project-Based Voucher-Assisted Households (2009, 2016)

Merging the Office of Public and Indian Housing Information Center, National Housing Preservation Database, and Rental Assistance Demonstration Data

Neighborhood-Level Dataset

Public Housing Agency-Level Dataset

Traditional Public Housing Agency Comparison Group

Defining Housing Markets

Appendix B: Additional Results

Research Question 1: How extensively do Moving to Work agencies use project-based vouchers?

Research Question 2: What factors are associated with Moving to Work and traditional agencies’ use of project-based voucher assistance?

Research Question 3: To what extent are Moving to Work agencies’ project-based vouchers located in Rental Assistance Demonstration or Low-Income Housing Tax Credit properties?

Research Question 4: Are project-based vouchers at Moving to Work agencies in lower-poverty, higher-quality neighborhoods? Do project-based voucher locations vary by household race or ethnicity?

Analysis of Correlation Between Neighborhood Measures

Supplemental Exhibits

Research Question 5: What factors are associated with variation in Moving to Work project-based voucher locations?

Appendix C: Interview Protocol

Appendix D. Moving to Work Agencies

Appendix E. Inventory of Project-Based Voucher-Related Activities for Case Study Moving to Work Agencies

Appendix F. Inventory of Moving to Work Agencies with an Activity Related to the Family Right to Move

Appendix G. Low-Income Housing Tax Credit Matching Sensitivity Analysis

Appendix H: References

Exhibit 1.1 The Moving to Work Retrospective Evaluation

Exhibit 2.1 Assisted Rental Housing Programs

Exhibit 2.2 Average Poverty Rate of Census Tracts Containing Assisted Households by Program Type for Moving to Work and Comparison Traditional Public Housing Agencies, 2016

Exhibit 3.1 Data Sources Used for Each Research Question

Exhibit 4.1 Project-Based Voucher Use at Moving to Work and Comparison Traditional Public Housing Agencies

Exhibit 4.2 Moving to Work Agencies’ Project-Based Vouchers as Percent of Assisted Households, 2016

Exhibit 4.3 Summary Statistics for Moving to Work and Comparison Traditional Public Housing Agencies

Exhibit 4.4 Model Results: Factors Related to the Percent of Assisted Households Assisted by Project-Based Vouchers in 2016

Exhibit 4.5 Rental Assistance Demonstration Use at Moving to Work and Comparison Traditional Public Housing Agencies, 2016

Exhibit 4.6 Moving to Work Project-Based and Tenant-Based Vouchers in Rental Assistance Demonstration and Low-Income Housing Tax Credit Properties, 2016

Exhibit 4.7 County-Normalized Measures of Neighborhood Quality for Assisted Households at Moving to Work Agencies by Program, Averages and Differences, 2016

Exhibit 4.8 County-Normalized Measures of Neighborhood Quality for Project-Based Vouchers at Moving to Work and Traditional Public Housing Agencies, 2016

Exhibit 4.9 County-Normalized Measures of Neighborhood Quality for Assisted Households at Moving to Work Agencies by Program and Race/Ethnicity, 2016

Exhibit 4.10 County-Normalized Measures of Neighborhood Quality for Project-Based Vouchers at Moving to Work Agencies in Rental Assistance Demonstration and Low-Income Housing Tax Credit Properties, 2016

Exhibit 4.11 Model Results: Factors Related to Neighborhood Poverty of Project-Based Vouchers at Moving to Work and Traditional Public Housing Agencies

Exhibit 4.12 Model Results: Factors Related to Neighborhood Poverty of Project-Based Vouchers at Moving to Work Agencies

Exhibit 5.1 Boulder, Colorado and Boulder Housing Partners (BHP)

Exhibit 5.2 Cambridge, Massachusetts and the Cambridge Housing Authority (CHA)

Exhibit 5.3 Seattle, Washington and the Seattle Housing Authority (SHA)

Exhibit B.1 Project-Based Voucher Use at Moving to Work Agencies, by Agency

Exhibit B.2 Model Results: Factors Related to the Use of Any Project-Based Vouchers and to the Percent of Assisted Households With Project-Based Vouchers at Agencies with Any Project-Based Vouchers

EXHIBIT B.3 Project-Based and Tenant-Based Voucher Assistance at Moving to Work Agencies by Location in Rental Assistance Demonstration or Low-Income Housing Tax Credit Properties, 2016

Exhibit B.4 Correlation Matrix for Neighborhood Quality Measures

Exhibit B.5 County-Normalized Average Poverty Rate for Project-Based Voucher Locations by Moving to Work Agency, 2016

Exhibit B.6 Qualities of Project-Based Voucher Neighborhoods in Relation to Tenant-Based Voucher and Public Housing Neighborhoods at Moving to Work and Traditional Public Housing Agencies Displayed as Net Differences

Exhibit B.7 Supplemental County-Normalized Measures of Neighborhood Quality for Assisted Households at Moving to Work Agencies by Program and Race/Ethnicity, 2016

Exhibit B.8 Difference in County-Normalized Measures of Neighborhood Quality for Assisted Households at Moving to Work Agencies by Program and Race/Ethnicity, 2009 and 2016

Exhibit B.9 Model Results: Modeling the Average County-Normalized Poverty Rate of Project-Based Voucher Locations with Additional Explanatory Variables

Exhibit B.10 Model Results: Modeling the Percent of Project-Based Vouchers in High-Poverty Neighborhoods with Additional Explanatory Variables

Exhibit E.1 Inventory of Mobility-Related Initiatives at Moving to Work Agencies

Exhibit F.1 Inventory of Activities Related to the Family Right to Move at Moving to Work Agencies

Exhibit G.1 Identifying Co-Location of Project-Based Vouchers in Rental Assistance Demonstration and Low-Income Housing Tax Credit Properties Using Varying Spatial Buffers at Moving to Work Agencies

Exhibit G.2 Identifying Co-Location of Tenant-Based Vouchers in Rental Assistance Demonstration and Low-Income Housing Tax Credit Properties Using Varying Spatial Buffers at Moving to Work Agencies

HUDII-043 MTW PB Report - H-3 (cdc)1.6.pdf

OLE_LINK1

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Executive Summary

Findings

Limitations

Implications for Policy and Research

1. Introduction

2. Background

Existing Evidence on Project-Based Voucher Assistance

Interaction with the Rental Assistance Demonstration and Low-Income Housing Tax Credit Programs

3. Research Questions and Study Design

Research Question 1: How extensively do Moving to Work agencies use project-based vouchers?

Research Question 2: What factors are associated with Moving to Work and traditional agencies’ use of project-based voucher assistance?

Research Question 3: To what extent are Moving to Work agencies’ project-based vouchers located in Rental Assistance Demonstration or Low-Income Housing Tax Credit properties?

Research Question 4: Are Moving to Work agency project-based vouchers in lower-poverty, higher-quality neighborhoods? Do project-based voucher locations vary by household race or ethnicity?

Research Question 5: What factors are associated with variations in project-based voucher locations?

Research Question 6: What are the agencies’ motivations for project-based voucher use?

Data

4. Quantitative Results

Research Question 1: How extensively do Moving to Work agencies use project-based vouchers?

Variation Across Moving to Work Agencies

Research Question 2: What factors are associated with Moving to Work and traditional agencies’ use of project-based voucher assistance?

Research Question 3: To what extent are Moving to Work agencies’ project-based vouchers located in Rental Assistance Demonstration or Low-Income Housing Tax Credit properties?

Rental Assistance Demonstration Use at Moving to Work Agencies

Moving to Work Project-Based Vouchers in Low-Income Housing Tax Credit Properties

Variation Across Moving to Work Agencies

Research Question 4: Are Moving to Work agency project-based vouchers in lower-poverty, higher-quality neighborhoods? Do project-based voucher locations vary by household race or ethnicity?

Project-Based Voucher Neighborhoods at Moving to Work Agencies

Moving to Work Project-Based Voucher Locations Compared With Traditional Public Housing Agencies’ Project-Based Voucher Locations

Project-Based Voucher Location Patterns by Race and Ethnicity

The Relationship Between Rental Assistance Demonstration, Low-Income Housing Tax Credit, and Project-Based Voucher Locations

Research Question 5: What factors are associated with variations in Moving to Work project-based voucher locations?

5. Case Studies of Three Moving to Work Agencies’ Project-Based Voucher Use

Common Perspectives on Project-Based Voucher Use

Project-Based Vouchers and Neighborhood Location

Boulder Housing Partners: Public Housing Conversion and Local Partnerships

Cambridge Housing Authority: Preserving Affordable Housing with Project-Based Vouchers

Seattle Housing Authority: Using Project-Based Vouchers to Serve People Exiting Homelessness

6. Conclusions

Limitations

Policy Implications and Future Research

Appendix A: Data and Methodology

Data Sources

HUD Administrative Data

Other Data Sources

Measures and Sampling

Public Housing Agency Characteristics

Neighborhood Characteristics

Regional and Market Characteristics

File Construction

Project-Based Voucher-Assisted Households (2009, 2016)

Merging the Office of Public and Indian Housing Information Center, National Housing Preservation Database, and Rental Assistance Demonstration Data

Neighborhood-Level Dataset

Public Housing Agency-Level Dataset

Traditional Public Housing Agency Comparison Group

Defining Housing Markets

Appendix B: Additional Results

Research Question 1: How extensively do Moving to Work agencies use project-based vouchers?

Research Question 2: What factors are associated with Moving to Work and traditional agencies’ use of project-based voucher assistance?

Research Question 3: To what extent are Moving to Work agencies’ project-based vouchers located in Rental Assistance Demonstration or Low-Income Housing Tax Credit properties?

Research Question 4: Are project-based vouchers at Moving to Work agencies in lower-poverty, higher-quality neighborhoods? Do project-based voucher locations vary by household race or ethnicity?

Analysis of Correlation Between Neighborhood Measures

Supplemental Exhibits

Research Question 5: What factors are associated with variation in Moving to Work project-based voucher locations?

Appendix C: Interview Protocol

Appendix D. Moving to Work Agencies

Appendix E. Inventory of Project-Based Voucher-Related Activities for Case Study Moving to Work Agencies

Appendix F. Inventory of Moving to Work Agencies with an Activity Related to the Family Right to Move

Appendix G. Low-Income Housing Tax Credit Matching Sensitivity Analysis

Appendix H: References

Exhibit 1.1 The Moving to Work Retrospective Evaluation

Exhibit 2.1 Assisted Rental Housing Programs

Exhibit 2.2 Average Poverty Rate of Census Tracts Containing Assisted Households by Program Type for Moving to Work and Comparison Traditional Public Housing Agencies, 2016

Exhibit 3.1 Data Sources Used for Each Research Question

Exhibit 4.1 Project-Based Voucher Use at Moving to Work and Comparison Traditional Public Housing Agencies

Exhibit 4.2 Moving to Work Agencies’ Project-Based Vouchers as Percent of Assisted Households, 2016

Exhibit 4.3 Summary Statistics for Moving to Work and Comparison Traditional Public Housing Agencies

Exhibit 4.4 Model Results: Factors Related to the Percent of Assisted Households Assisted by Project-Based Vouchers in 2016

Exhibit 4.5 Rental Assistance Demonstration Use at Moving to Work and Comparison Traditional Public Housing Agencies, 2016

Exhibit 4.6 Moving to Work Project-Based and Tenant-Based Vouchers in Rental Assistance Demonstration and Low-Income Housing Tax Credit Properties, 2016

Exhibit 4.7 County-Normalized Measures of Neighborhood Quality for Assisted Households at Moving to Work Agencies by Program, Averages and Differences, 2016

Exhibit 4.8 County-Normalized Measures of Neighborhood Quality for Project-Based Vouchers at Moving to Work and Traditional Public Housing Agencies, 2016

Exhibit 4.9 County-Normalized Measures of Neighborhood Quality for Assisted Households at Moving to Work Agencies by Program and Race/Ethnicity, 2016

Exhibit 4.10 County-Normalized Measures of Neighborhood Quality for Project-Based Vouchers at Moving to Work Agencies in Rental Assistance Demonstration and Low-Income Housing Tax Credit Properties, 2016

Exhibit 4.11 Model Results: Factors Related to Neighborhood Poverty of Project-Based Vouchers at Moving to Work and Traditional Public Housing Agencies

Exhibit 4.12 Model Results: Factors Related to Neighborhood Poverty of Project-Based Vouchers at Moving to Work Agencies

Exhibit 5.1 Boulder, Colorado and Boulder Housing Partners (BHP)

Exhibit 5.2 Cambridge, Massachusetts and the Cambridge Housing Authority (CHA)

Exhibit 5.3 Seattle, Washington and the Seattle Housing Authority (SHA)

Exhibit B.1 Project-Based Voucher Use at Moving to Work Agencies, by Agency

Exhibit B.2 Model Results: Factors Related to the Use of Any Project-Based Vouchers and to the Percent of Assisted Households With Project-Based Vouchers at Agencies with Any Project-Based Vouchers

EXHIBIT B.3 Project-Based and Tenant-Based Voucher Assistance at Moving to Work Agencies by Location in Rental Assistance Demonstration or Low-Income Housing Tax Credit Properties, 2016

Exhibit B.4 Correlation Matrix for Neighborhood Quality Measures

Exhibit B.5 County-Normalized Average Poverty Rate for Project-Based Voucher Locations by Moving to Work Agency, 2016

Exhibit B.6 Qualities of Project-Based Voucher Neighborhoods in Relation to Tenant-Based Voucher and Public Housing Neighborhoods at Moving to Work and Traditional Public Housing Agencies Displayed as Net Differences

Exhibit B.7 Supplemental County-Normalized Measures of Neighborhood Quality for Assisted Households at Moving to Work Agencies by Program and Race/Ethnicity, 2016

Exhibit B.8 Difference in County-Normalized Measures of Neighborhood Quality for Assisted Households at Moving to Work Agencies by Program and Race/Ethnicity, 2009 and 2016

Exhibit B.9 Model Results: Modeling the Average County-Normalized Poverty Rate of Project-Based Voucher Locations with Additional Explanatory Variables

Exhibit B.10 Model Results: Modeling the Percent of Project-Based Vouchers in High-Poverty Neighborhoods with Additional Explanatory Variables

Exhibit E.1 Inventory of Mobility-Related Initiatives at Moving to Work Agencies

Exhibit F.1 Inventory of Activities Related to the Family Right to Move at Moving to Work Agencies

Exhibit G.1 Identifying Co-Location of Project-Based Vouchers in Rental Assistance Demonstration and Low-Income Housing Tax Credit Properties Using Varying Spatial Buffers at Moving to Work Agencies

Exhibit G.2 Identifying Co-Location of Tenant-Based Vouchers in Rental Assistance Demonstration and Low-Income Housing Tax Credit Properties Using Varying Spatial Buffers at Moving to Work Agencies

HUDII-043 MTW PB Report i (sm)1.8_508.pdf

OLE_LINK1

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_Hlk536215328

_Hlk25762854

_Hlk19900963

_Hlk19900967

_Hlk19900975

_Hlk19900980

_Hlk19900987

Executive Summary

Findings

Limitations

Implications for Policy and Research

1. Introduction

2. Background

Existing Evidence on Project-Based Voucher Assistance

Interaction with the Rental Assistance Demonstration and Low-Income Housing Tax Credit Programs

3. Research Questions and Study Design

Research Question 1: How extensively do Moving to Work agencies use project-based vouchers?

Research Question 2: What factors are associated with Moving to Work and traditional agencies’ use of project-based voucher assistance?

Research Question 3: To what extent are Moving to Work agencies’ project-based vouchers located in Rental Assistance Demonstration or Low-Income Housing Tax Credit properties?

Research Question 4: Are Moving to Work agency project-based vouchers in lower-poverty, higher-quality neighborhoods? Do project-based voucher locations vary by household race or ethnicity?

Research Question 5: What factors are associated with variations in project-based voucher locations?

Research Question 6: What are the agencies’ motivations for project-based voucher use?

Data

4. Quantitative Results

Research Question 1: How extensively do Moving to Work agencies use project-based vouchers?

Variation Across Moving to Work Agencies

Research Question 2: What factors are associated with Moving to Work and traditional agencies’ use of project-based voucher assistance?

Research Question 3: To what extent are Moving to Work agencies’ project-based vouchers located in Rental Assistance Demonstration or Low-Income Housing Tax Credit properties?

Rental Assistance Demonstration Use at Moving to Work Agencies

Moving to Work Project-Based Vouchers in Low-Income Housing Tax Credit Properties

Variation Across Moving to Work Agencies

Research Question 4: Are Moving to Work agency project-based vouchers in lower-poverty, higher-quality neighborhoods? Do project-based voucher locations vary by household race or ethnicity?

Project-Based Voucher Neighborhoods at Moving to Work Agencies

Moving to Work Project-Based Voucher Locations Compared With Traditional Public Housing Agencies’ Project-Based Voucher Locations

Project-Based Voucher Location Patterns by Race and Ethnicity

The Relationship Between Rental Assistance Demonstration, Low-Income Housing Tax Credit, and Project-Based Voucher Locations

Research Question 5: What factors are associated with variations in Moving to Work project-based voucher locations?

5. Case Studies of Three Moving to Work Agencies’ Project-Based Voucher Use

Common Perspectives on Project-Based Voucher Use

Project-Based Vouchers and Neighborhood Location

Boulder Housing Partners: Public Housing Conversion and Local Partnerships

Cambridge Housing Authority: Preserving Affordable Housing with Project-Based Vouchers

Seattle Housing Authority: Using Project-Based Vouchers to Serve People Exiting Homelessness

6. Conclusions

Limitations

Policy Implications and Future Research

Appendix A: Data and Methodology

Data Sources

HUD Administrative Data

Other Data Sources

Measures and Sampling

Public Housing Agency Characteristics

Neighborhood Characteristics

Regional and Market Characteristics

File Construction

Project-Based Voucher-Assisted Households (2009, 2016)

Merging the Office of Public and Indian Housing Information Center, National Housing Preservation Database, and Rental Assistance Demonstration Data

Neighborhood-Level Dataset

Public Housing Agency-Level Dataset

Traditional Public Housing Agency Comparison Group

Defining Housing Markets

Appendix B: Additional Results

Research Question 1: How extensively do Moving to Work agencies use project-based vouchers?

Research Question 2: What factors are associated with Moving to Work and traditional agencies’ use of project-based voucher assistance?

Research Question 3: To what extent are Moving to Work agencies’ project-based vouchers located in Rental Assistance Demonstration or Low-Income Housing Tax Credit properties?

Research Question 4: Are project-based vouchers at Moving to Work agencies in lower-poverty, higher-quality neighborhoods? Do project-based voucher locations vary by household race or ethnicity?

Analysis of Correlation Between Neighborhood Measures

Supplemental Exhibits

Research Question 5: What factors are associated with variation in Moving to Work project-based voucher locations?

Appendix C: Interview Protocol

Appendix D. Moving to Work Agencies

Appendix E. Inventory of Project-Based Voucher-Related Activities for Case Study Moving to Work Agencies

Appendix F. Inventory of Moving to Work Agencies with an Activity Related to the Family Right to Move

Appendix G. Low-Income Housing Tax Credit Matching Sensitivity Analysis

Appendix H: References

Exhibit 1.1 The Moving to Work Retrospective Evaluation

Exhibit 2.1 Assisted Rental Housing Programs

Exhibit 2.2 Average Poverty Rate of Census Tracts Containing Assisted Households by Program Type for Moving to Work and Comparison Traditional Public Housing Agencies, 2016

Exhibit 3.1 Data Sources Used for Each Research Question

Exhibit 4.1 Project-Based Voucher Use at Moving to Work and Comparison Traditional Public Housing Agencies

Exhibit 4.2 Moving to Work Agencies’ Project-Based Vouchers as Percent of Assisted Households, 2016

Exhibit 4.3 Summary Statistics for Moving to Work and Comparison Traditional Public Housing Agencies

Exhibit 4.4 Model Results: Factors Related to the Percent of Assisted Households Assisted by Project-Based Vouchers in 2016

Exhibit 4.5 Rental Assistance Demonstration Use at Moving to Work and Comparison Traditional Public Housing Agencies, 2016

Exhibit 4.6 Moving to Work Project-Based and Tenant-Based Vouchers in Rental Assistance Demonstration and Low-Income Housing Tax Credit Properties, 2016

Exhibit 4.7 County-Normalized Measures of Neighborhood Quality for Assisted Households at Moving to Work Agencies by Program, Averages and Differences, 2016

Exhibit 4.8 County-Normalized Measures of Neighborhood Quality for Project-Based Vouchers at Moving to Work and Traditional Public Housing Agencies, 2016

Exhibit 4.9 County-Normalized Measures of Neighborhood Quality for Assisted Households at Moving to Work Agencies by Program and Race/Ethnicity, 2016

Exhibit 4.10 County-Normalized Measures of Neighborhood Quality for Project-Based Vouchers at Moving to Work Agencies in Rental Assistance Demonstration and Low-Income Housing Tax Credit Properties, 2016

Exhibit 4.11 Model Results: Factors Related to Neighborhood Poverty of Project-Based Vouchers at Moving to Work and Traditional Public Housing Agencies

Exhibit 4.12 Model Results: Factors Related to Neighborhood Poverty of Project-Based Vouchers at Moving to Work Agencies

Exhibit 5.1 Boulder, Colorado and Boulder Housing Partners (BHP)

Exhibit 5.2 Cambridge, Massachusetts and the Cambridge Housing Authority (CHA)

Exhibit 5.3 Seattle, Washington and the Seattle Housing Authority (SHA)

Exhibit B.1 Project-Based Voucher Use at Moving to Work Agencies, by Agency

Exhibit B.2 Model Results: Factors Related to the Use of Any Project-Based Vouchers and to the Percent of Assisted Households With Project-Based Vouchers at Agencies with Any Project-Based Vouchers

EXHIBIT B.3 Project-Based and Tenant-Based Voucher Assistance at Moving to Work Agencies by Location in Rental Assistance Demonstration or Low-Income Housing Tax Credit Properties, 2016

Exhibit B.4 Correlation Matrix for Neighborhood Quality Measures

Exhibit B.5 County-Normalized Average Poverty Rate for Project-Based Voucher Locations by Moving to Work Agency, 2016

Exhibit B.6 Qualities of Project-Based Voucher Neighborhoods in Relation to Tenant-Based Voucher and Public Housing Neighborhoods at Moving to Work and Traditional Public Housing Agencies Displayed as Net Differences

Exhibit B.7 Supplemental County-Normalized Measures of Neighborhood Quality for Assisted Households at Moving to Work Agencies by Program and Race/Ethnicity, 2016

Exhibit B.8 Difference in County-Normalized Measures of Neighborhood Quality for Assisted Households at Moving to Work Agencies by Program and Race/Ethnicity, 2009 and 2016

Exhibit B.9 Model Results: Modeling the Average County-Normalized Poverty Rate of Project-Based Voucher Locations with Additional Explanatory Variables

Exhibit B.10 Model Results: Modeling the Percent of Project-Based Vouchers in High-Poverty Neighborhoods with Additional Explanatory Variables

Exhibit E.1 Inventory of Mobility-Related Initiatives at Moving to Work Agencies

Exhibit F.1 Inventory of Activities Related to the Family Right to Move at Moving to Work Agencies

Exhibit G.1 Identifying Co-Location of Project-Based Vouchers in Rental Assistance Demonstration and Low-Income Housing Tax Credit Properties Using Varying Spatial Buffers at Moving to Work Agencies

Exhibit G.2 Identifying Co-Location of Tenant-Based Vouchers in Rental Assistance Demonstration and Low-Income Housing Tax Credit Properties Using Varying Spatial Buffers at Moving to Work Agencies