H O U S I N G A N D H O U S I N G F I N A N C E

RE S E AR C H RE P O R T 

Affordable Homeownership 

An Evaluation of Shared Equity Programs 

Brett Theodos Rob Pitingolo Sierra Latham Christina Stacy

Rebecca Daniels Breno Braga

March 2017
AB O U T T H E U R BA N I N S T I T U TE 

The nonprofit Urban Institute is dedicated to elevating the debate on social and economic policy. For nearly five 

decades, Urban scholars have conducted research and offered evidence-based solutions that improve lives and 

strengthen communities across a rapidly urbanizing world. Their objective research helps expand opportunities for 

all, reduce hardship among the most vulnerable, and strengthen the effectiveness of the public sector. 

Copyright © March 2017. Urban Institute. Permission is granted for reproduction of this file, with attribution to the 

Urban Institute. Cover image by from Mountainlands Community Housing Trust.
AB O U T C A P I T AL I MP AC T P A R TN E RS

Capital Impact Partners transforms underserved communities into strong, vibrant places of opportunity. A leading 

nonprofit Community Development Financial Institution, Capital Impact Partners delivers strategic financing, 

incubate social innovation programs and support capacity building and policy reforms that create social change and 

deliver financial impact nationwide. Over a 30-year history, Capital Impact Partners has disbursed more than $2 

billion to help ensure access to quality health care and education, healthy foods, affordable housing, cooperative 

development, and the ability to age independently. 

AB O U T G R O UN DE D S OL U T I ON S N E TW O R K 

Grounded Solutions Network works nationally, connecting local experts with the networks, knowledge and support 

they need to build inclusive communities. Grounded Solutions Network helps promote housing solutions that will 

stay affordable for generations so communities can stabilize and strengthen their foundation, for good. Grounded 

Solutions Network was formed by the integration of the National Community Land Trust Network and 

Cornerstone Partnership (formerly a program of Capital Impact Partners) to better support their members, funders 

and partners to build and preserve communities where everyone can live. 

AB O U T T H E S OC IA L I N N OV A TI ON F UN D 

This report is based upon work supported by the Social Innovation Fund (SIF) which unites public and private 

resources to evaluate and grow innovative community-based solutions with evidence of results. The Social 

Innovation Fund is a program of the Corporation for National and Community Service, a federal agency that 

engages millions of Americans in service through its AmeriCorps, Senior Corps, Social Innovation Fund, and 

Volunteer Generation Fund programs, and leads the President's national call to service initiative, United We Serve. 

AB O U T T H E F O R D F O UN D A T I ON 

The Ford Foundation is an independent, nonprofit grant-making organization. For more than 75 years it has 

worked with courageous people on the frontlines of social change worldwide, guided by its mission to strengthen 

democratic values, reduce poverty and injustice, promote international cooperation, and advance human 

achievement.
Contents 

Acknowledgments vi

Executive Summary vii

Study Design and Program Applicants vii

Shared Equity Home Purchases viii

Shared Equity Buyer Outcomes viii

Implications for Policy and Practice ix

Chapter 1. Introduction and Background 1

Background 2

Shared Equity Homeownership 3

The Cornerstone Homeownership Innovation Program 5

Research Approach 6

Chapter 2. Shared Equity Program Models 8

Overview of Shared Equity Program Model Components 8

Establishing and Maintaining Affordability over Time 9

Participant Engagement 11

Lender Engagement 12

Marketing to Potential Buyers 12

Shared Equity Program Profiles 13

HomeBase Texas (Austin, Texas) 13

Hello Housing (San Francisco Bay Area, California) 13

Champlain Housing Trust (Burlington, Vermont) 14

Long Island Housing Partnership (Long Island, New York) 15

The Housing Fund (Nashville, Tennessee) 15

Mountainlands Community Housing Trust (Park City, Utah) 16

Homestead Community Land Trust (Seattle, Washington) 17

South Florida Consortium (South Florida) 17

City First Homes (Washington, District of Columbia) 18

Chapter 3. Data and Methodology 20

Data 20

Application Data 20

Homekeeper Administrative Data on Shared Equity Purchase Transactions 21

Baseline and Follow-up Credit Bureau Data 21

Secondary Data 22

Empirical Methodology 22
C O N T E N T S V

Program Applicants 22

Shared Equity Purchases 22

Shared Equity Buyer Outcomes 23

Chapter 4. Program Applicants 28

Demographics 29

Education and Employment 30

Finances and Creditworthiness 31

Neighborhood Characteristics 34

Chapter 5. Shared Equity Home Purchases 35

Home Purchasers 36

Shared Equity Transactions 40

Chapter 6. Shared Equity Buyer Outcomes 45

Shared Equity Purchasers versus All Other Applicants 45

Shared Equity Purchasers versus Other Applicant Purchasers 48

Shared Equity Purchasers versus Other Credit Bureau Purchasers 51

Chapter 7. Implications for Practice and Policy 56

Future Research 57

A Growing Field 58

Appendix A. Codebook 60

Appendix B. Baseline Medians by Purchase Status 63

Appendix C. Minimum Detectable Effects 64

Appendix D. Regional Demographic Characteristics, by Site 67

Notes 69

References 71

About the Authors 73

Statement of Independence 74
V I A C K N O W L E D G M E N T S

Acknowledgments 

This report was funded by Capital Impact Partners, with support from the Social Innovation Fund, the 

Ford Foundation, and the Annie E. Casey Foundation. We are grateful to them 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 www.urban.org/support. 

This report was supported and managed by Grounded Solutions Network. We thank the Grounded 

Solutions staff who contributed to the development of this report by providing feedback, expertise, and 

research support: Tiffany Eng, Elizabeth Haney, Jenee Kresge Gaynor, Hong Ly, Rachel Silver, and Emily 

Thaden. We also thank Thane Maxwell and Rick Jacobus, independent consultants. A tremendous thank 

you to the staff and applicants at the shared equity programs for their support of the evaluation. And 

finally, thanks to Ellen Seidman and Douglas Wissoker for serving as technical reviewers for this report. 

We also add a special mention to Ken Temkin, a coauthor on the baseline report for this study, and 

esteemed colleague who contributed substantively to this research and will be greatly missed.
E X E C U T I V E S U M M A R Y VII

Executive Summary 

Owning a home has long been a meaningful milestone in many Americans’ lives. Yet, because home 

prices continue to rise during the current economic recovery and since lending standards remain tight 

by historical standards, many renters view homeownership as an unattainable goal. Shared equity is a 

homeownership model that allows income-eligible families to purchase homes at below-market prices. 

In return for the subsidized purchase price, the owner’s potential capital gains from home resale are 

restricted. 

With the support of the Social Innovation Fund and the Ford Foundation, Capital Impact 

established the Cornerstone Homeownership Innovation Partnership (CHIP) in 2011. CHIP identifies 

and supports a set of leading nonprofit stewards of long-term affordable homeownership units, and 

helps build the evidence base around shared equity. Capital Impact commissioned the Urban Institute 

to evaluate housing outcomes for buyers under CHIP. 

To date, there has been little empirical research on shared equity homeownership that evaluates 

results for homeowners. This study helps bridge this gap by examining the CHIP grantees, allowing us to 

explore what types of households they enable to buy homes, as well as financial and neighborhood 

outcomes. 

Study Design and Program Applicants 

In this study, we evaluated 9 shared equity programs made up of 683 people who applied to the 

programs and consented to participate in the research between June 2012 and June 2014. The 

programs are located in Austin, Texas; the Bay Area in California; Burlington, Vermont; Long Island, 

New York; Nashville, Tennessee; Park City, Utah; Seattle, Washington; South Florida (Broward and 

Palm Beach Counties); and Washington, DC. From intake application data, we learned that applicants 

share the following characteristics: 

 An overwhelming share of applicants (96 percent) were not homeowners at the time of 

application, a requirement for many programs. 

 Half of applicants had a bachelor’s degree and roughly one-fifth had an associate’s degree. 

These education levels were higher than for the overall US population. 
VIII E X E C U T I V E S U M M A R Y

 However, applicants had incomes that were on average 51 percent of their area’s median 

family incomes—far lower than for many homeownership supports, which often target families 

at or above 80 percent of area incomes. Nearly half of all applicants were housing cost 

burdened, defined as spending more than 30 percent of their income on housing and utility 

expenses. 

 Applicants had little net worth at the median, $712, but their credit scores were “good,” with a 

median of 696. 

Shared Equity Home Purchases 

Many applicants in this study’s sample purchased a shared equity home (36 percent). Some applicants 

who did not purchase through shared equity also purchased homes; about one-third of applicants who 

did not purchase a shared equity home (and 20 percent of all applicants) opted to purchase a home 

without participating in a CHIP program. The remaining 44 percent of applicants did not purchase a 

home during the study period. 

At baseline, applicants who purchased a shared equity home during the study looked comparable to 

“other” purchasers who bought apart from the programs. Shared equity purchasers tended to be better 

off financially at baseline than those who did not purchase a home, however. For example, they were 

less likely to have nonmortgage delinquencies, accounts in collections, or past foreclosures. Their credit 

scores were higher and they had roughly twice as much saved for a home purchase. 

Those who bought a home through a shared equity program received, relative to the unsubsidized 

market price of their home, on average the equivalent of 39 percent of its value in subsidies. The 

average unrestricted market value of purchased shared equity homes was roughly $241,000, with over 

$94,000 in subsidy. Borrowers contributed down payments worth an average of roughly $11,000 (5 

percent of the unrestricted market value) and the remaining balance was financed by buyers (on 

average, approximately $138,000 and 57 percent of the unrestricted market value). 

Shared Equity Buyer Outcomes 

Using credit bureau data, we compared applicants who purchased a shared equity home with applicants 

who did not purchase a shared equity home. We also compared applicants who purchased a shared 
E X E C U T I V E S U M M A R Y I X

equity home with the subset of applicants who purchased “other” non–shared equity homes. We made 

these comparisons at two different times: before the potential buyer applied to the program (June 2012 

or June 2013) and at follow-up (June 2016). Finally, we also compared outcomes between shared equity 

buyers and a comparison group of nonapplicants who purchased a home during the study period, also 

using credit bureau data. 

We found that shared purchasers had smaller mortgages than other applicant purchasers and that 

they had lower monthly payments on all credit accounts. There were no other differences in 

nonmortgage, mortgage, or neighborhood outcomes when comparing shared equity buyers to other 

applicants, or the subset of other applicants that purchased homes outside of the shared equity 

programs. When comparing shared equity purchasers to nonapplicant purchasers with similar 

observable characteristics, we again found that shared equity purchasers had smaller mortgages and 

had smaller monthly payments on all credit accounts. We also saw that they were less likely to have 

home equity lines of credit, and had higher accounts in collections. All these results were robust to 

adjustments accounting for tests of multiple outcomes. After making such adjustments, we did not see 

differences in other financial and neighborhood metrics. Apart from accessing smaller mortgages, more 

time may be needed to understand whether and how shared equity purchasers are better or worse off 

financially compared with other buyers. 

Implications for Policy and Practice 

Many applicants in this study’s sample were able to buy shared equity homes, the average subsidies for 

the shared equity homes were sizeable, and shared equity buyers had incomes at baseline well below 

area medians. Together, these facts indicate that shared equity programs were serving their core 

mission of linking low- and moderate-income people with affordable owner-occupied housing. 

A fairly high share of those who did not buy a shared equity home ended up purchasing a home 

outside the programs. This may be appropriate sorting: people who do not need all the help shared 

equity gives should not accept it, because they would be trading a sizable portion of the upside of their 

investment. The remainder of applicants who did not buy any home were no longer interested in 

purchasing a home or were not able to buy. It may be that some applicants would have benefited from 

greater help, for example, through financial coaching (Theodos, Simms et al. 2015).

Assessing the impacts of homeownership can be a challenging endeavor because randomization is 

rarely possible and a high degree of personal choice is involved in the decision to buy a home. However, 
X E X E C U T I V E S U M M A R Y

by combining all of these comparisons groups into one study and using a robust set of baseline controls, 

we have tested for links between shared equity programs and buyer outcomes.

Some important questions remain unanswered by this research, and warrant further study. Most 

important in our minds is whether the benefits of reduced mortgage costs redound in meaningful ways 

to owners over time. It is possible that these buyers will subsequently differentiate themselves from 

other buyers in their levels savings, debt, financial stress, and mortgage delinquency and foreclosure. 

This study was only able to observe buyers through June 2016; longer-term follow-ups would be useful.

Further, neighborhood outcomes also merit further investigation. For some programs, it is plausible 

that shared equity approaches allow for low- and moderate-income households to buy homes in more 

expensive neighborhoods than they could otherwise afford. However, some programs in this study 

brought homes online through funding sources that may not have prioritized more affluent 

neighborhoods, or even that actively targeted distressed neighborhoods, such as the Neighborhood 

Stabilization Program.

Although questions about the long-term effects of shared equity remain, this study offers evidence 

that shared equity models provide homeownership opportunities to lower-income households with 

debt levels less than they could otherwise achieve. With the homeownership rate having fallen to its 

lowest level since 1965, exploring how to sustain and expand these models can be a part of making 

homeownership available to more American families.
A F F O R D A B L E H O M E O W N E R S H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S 1

Chapter 1. Introduction and 

Background 

Determining how to create affordable, sustainable homeownership opportunities for low- and 

moderate-income households has been a critical policy issue for decades, both for ideological reasons—

homeownership is part of the American Dream—and to promote household financial stability and 

wealth creation. Owning a home has long been a meaningful milestone in many American’s lives. Yet as 

home prices continue to rise during the current economic recovery, many renters view homeownership 

as an unattainable goal. Shared equity programs aim to satisfy this unmet demand by maintaining a 

stock of affordable housing for generations of new homebuyers. 

Shared equity is a homeownership model that allows income-eligible families to purchase homes at 

below-market prices. In return for the subsidized purchase price, the owner’s potential capital gains 

from home resale are restricted. Nonprofit and municipal shared equity programs—the focus of this 

report—create a stock of homes that will remain priced within reach of lower-income households over 

successive resales, thereby serving more families per dollar of grants or forgivable loan subsidy. Such 

programs retain a portion of the property’s capital gains when owners resell. These programs differ 

from the market-driven shared equity models that are beginning to emerge. In market-driven 

approaches, investors use private money to pay a share of the purchase price, and in exchange, the 

homeowner gives the investor a share in the appreciation of the home.1

This report is based upon work supported by the Social Innovation Fund, a program of the 

Corporation for National and Community Service. The Social Innovation Fund combines public and 

private resources to grow the impact of innovative, community-based solutions that show compelling 

evidence of improving the lives of people in low-income communities throughout the United States. 

Capital Impact Partners received a grant from the Social Innovation Fund to establish the Cornerstone 

Homeownership Innovation Program (CHIP). This effort supports the expansion of shared equity 

homeownership programs in nine sites located throughout the United States. Capital Impact Partners 

engaged the Urban Institute to analyze the programs funded by the Social Innovation Fund. 

To date, there has been little empirical research on shared equity homeownership that evaluates 

results for homeowners. Most research simply describes the concept in theory, describes consumer 

attitudes toward shared equity programs, or uses formula-based projections. Two studies have 

measured outcomes from Vermont’s Champlain Housing Trust, and a previous study by the Urban 
2 A F F O R D A B L E H O M E O W N E RS H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S

Institute measured outcomes among seven affordable homeownership programs (Davis and Stokes 

2009; Temkin, Theodos, and Price 2013). None of these studies uses a comparison group, however, and 

therefore do not provide insights into outcomes for shared equity buyers relative to the counterfactual 

of the experience of other similar households not participating in these programs. 

The shared equity programs evaluated here received funding and technical assistance from CHIP to 

expand homeownership to families who may otherwise be unable to buy a home at market prices. Using 

both applicant and nonapplicant comparison groups, we examine these programs, exploring questions 

relating to the households who were able to use the program to buy homes, as well as these households’ 

mortgage, financial, and neighborhood outcomes. 

Background 

At most recent count, 10 million renters are severely cost burdened; that is, they spend half or more of 

their monthly income on housing.2 Making the transition from renter to owner, always difficult, is 

currently especially hard as the prices of starter homes, the most affordable in the market, have risen by 

32 percent from 2012 to 2016, a growth rate higher than for “trade-up” or “premium” homes.3

Homeowners in some markets who purchased their homes prior to the recession have been reluctant to 

move because they would take a loss on their home at its current market value, while others may be 

limited by an inability to support higher mortgage costs on relatively stagnant incomes.4 Investor owned 

and real estate owned properties (the latter being a home owned by a lender after foreclosure) further 

limit the supply of starter homes available for purchase. 

Following the end of the most recent economic recession in 2009, real median household income in 

the United States has begun to increase—although incomes are still below 2007 levels, and Latinos and 

Asians have done better than black and white households. Even so, homeownership remains stubbornly 

out of reach for many families because home prices have been increasing even more rapidly. To further 

exacerbate barriers to homeownership, rents have been growing much faster than wages in many cities, 

hindering renters’ ability to save for a down payment (Ault, Sturtevant, Viveiros 2015). These recent 

trends are particularly problematic for families in high-cost markets, and for first-time homebuyers, 

who may also be burdened by student debt (Jacobus 2015). 

Though a hypothetical homebuyer earning the national median income may be a convenient way to 

illustrate general trends, growing income inequality creates different realities among prospective 

homebuyers. Incomes for high-income households have grown more rapidly than for low-income ones. 
A F F O R D A B L E H O M E O W N E R S H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S 3

Relative to current homeowners, first-time homebuyers tend to have lower incomes and less 

accumulated wealth. Homebuyers in the market for starter homes can expect to dedicate a 

substantially larger share of their income to mortgage payments than those in the market for trade-up 

and premium homes.5

Perhaps most important, potential buyers face possibly the tightest mortgage credit requirements 

in the past generation. By one estimate, there are over one million fewer owners each year since 2009 

solely as a result of historically tight credit standards.6 The median FICO credit score for new buyers is 

739, 34 points higher than it was a decade ago (Urban Institute 2016). All this adds up to a falling 

homeownership rate—from a high of 69.2 percent in Q4 2004 to 63.5 percent in Q3 2016—a level not 

seen since 1965.7

Another trend is that the nonwhite share of the US population is growing and will continue to 

increase in coming years. Yet, differences in ownership by race/ethnicity are stark. Homeownership 

rates are appreciably lower for non-Hispanic black (41.5 percent), Hispanic (45.3 percent), and 

Asian/Native Hawaiian/Pacific Islander (55.7 percent) households than they are for non-Hispanic 

whites (72.1 percent).8 And without policy changes, these differences are projected to continue 

(Goodman, Pendall, and Zhu 2015). 

The confluence of these trends motivates policy and practice to support affordable homeownership 

for new buyers. 

Shared Equity Homeownership 

Barriers to home buying, such as down payments and closing costs, have made it difficult for families 

with limited financial resources to become homeowners. Maintaining a stock of affordable homes for 

purchase over time can open homeownership more broadly, preventing homeownership opportunities 

from being concentrated among communities’ wealthier residents and encouraging economic 

integration. 

Shared equity programs, which are usually administered by a nonprofit organization or a 

municipality, have three important features: (1) they lower the initial cost of purchasing a home; (2) they 

limit the gain a homebuyer can receive on resale, thus generating a relatively affordable price for a 

subsequent buyer; and (3) they frequently provide stewardship to maintain community values and help 

homeowners retain and maintain their homes. For example, community land trusts (CLTs) retain 
4 A F F O R D A B L E H O M E O W N E RS H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S

ownership of the land on which a home is located, thus substantially lowering the initial cost of the 

property. This structure also protects subsequent owners from the effects of increasing land prices, an 

especially important benefit in fast-developing or gentrifying areas.

Shared equity homeownership, sometimes called long-term affordable homeownership, represents 

a small, innovative segment of the current housing market. Rather than providing homebuyers a onetime cash grant, these programs recycle subsidies over time, thus cost-effectively promoting 

homeownership for a greater number of low- and moderate-income homebuyers. Nonprofit or 

municipal organizations and agencies administer this homeownership model, making homes more 

affordable for generations of first-time buyers, who may have a poor credit history or lack the 

necessary down payment or monthly income to afford a market-rate home.

Shared equity programs provide homebuyers a way to bridge the gap between the mortgage they 

can afford and the actual market cost to own a home. The entity administering the program and the 

buyer split the market cost of the home, and the program keeps a share of the equity. The buyer is able 

to access a share of any appreciation, but the program will limit the resale price so the house remains

affordable to other low-income homebuyers, passing the benefit of any initial subsidy to subsequent 

owners. Shared equity is a broad designation that includes the following types of programs:

 Deed restrictions, also called deed covenants, are written into the deed that conveys a 

property. These restrictions bind subsequent as well as current owners (Abromowitz and 

White 2006). Inclusionary zoning programs, which require new developments to allocate a set 

share of units as affordable, often employ deed-restricted mortgage.

 Community land trusts (CLTs) are private nonprofit organizations with a commitment to 

providing affordable housing. CLTs lease their land to homeowners who own the units on the 

land (Davis 2006). 

 Limited equity cooperatives are typically multi-household developments in which occupants 

purchase shares in the cooperative rather than the units outright (as in a condominium). Prices 

for shares are determined by the cooperative’s bylaws and can be structured to include 

affordability restrictions (Davis 2006).

Although each shared equity model is unique in its structure, all share the same goal of providing 

homeownership options to low- and middle-income communities and include mechanisms to preserve 

the affordability of these homes over time. Research into shared equity programs is limited, but results 

so far have been promising. A 2013 study of seven programs found that shared equity homebuyers 
A F F O R D A B L E H O M E O W N E R S H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S 5

earned competitive returns on their housing investment while complying with long-term affordability 

restrictions. And as the homes were resold, they remained affordable to low-income homebuyers. 

Shared equity homebuyers also had low delinquency and foreclosure rates, and those who moved did so 

at rates near the national average, using the sales proceeds to purchase market-rate homes (Temkin, 

Theodos, and Price 2013). A 2009 performance evaluation of a shared equity program in Burlington, 

Vermont, found that this program was an effective asset-building strategy for lower-income households 

and that, compared with buyers of unrestricted market-rate homes, these buyers had lower foreclosure 

rates and were able to sustain homeownership longer (Jacobus and Davis 2010).

The Cornerstone Homeownership Innovation Program 

In 2010 Capital Impact Partners created the Cornerstone Partnership. Between 2010 and 2015, 

Cornerstone Partnership worked with over 3,000 housing professionals to develop high-level 

guidelines for implementing effective shared equity homeownership programs, as well as to launch a 

series of tools, resources and technical assistance opportunities to support practitioners in the field. 

With the support of the Social Innovation Fund and the Ford Foundation, Capital Impact Partners 

established CHIP in 2011. CHIP was designed to identify and support leading nonprofit stewards of 

affordable homeownership units by providing them with resources to help them build their 

organizational capacity and thereby support the expansion of shared equity homeownership. A twin 

goal was to use CHIP programs to help build the evidence base around shared equity, the function of 

this research. From 46 organizations, CHIP selected 10 partners that met baseline criteria9 and 

underwent a comprehensive assessment.10 One original program—a consortium led by the Community 

Asset Preservation Corporation in Newark, New Jersey—exited CHIP before the end of the baseline 

data collection period. Therefore, this research is based on 9 of the original 10 selected partners. CHIP 

grantees received funding from 2012 through 2016. 

In 2014, Capital Impact Partners and its long-time partners at the National Community Land Trust 

Network began conversations about the best ways to leverage their work supporting affordable 

homeownership practitioners and policymakers in an expanding coalition. As a result of these 

conversations, Capital Impact released its Cornerstone Partnership initiative to join with the National 

Community Land Trust Network. As of January 2016, Cornerstone Partnership and the National 

Community Land Trust Network began operating as Grounded Solutions Network. As Grounded 

Solutions Network, the organization’s expanded mission is to “cultivate communities—equitable, 
6 A F F O R D A B L E H O M E O W N E RS H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S

inclusive and rich in opportunity—by advancing affordable housing solutions that last for 

generations.”11

Research Approach 

In this study, we estimate outcomes for homebuyers participating in the CHIP shared equity programs. 

To so do, we rely on intake surveys, program administrative data, and credit bureau records. Some 

program applicants purchased a home through the programs; others did not. Using credit bureau data, 

we compare buyers who purchased a shared equity home with those who did not (although some non–

shared equity buyers may have purchased a home elsewhere). We make these comparisons at two 

different times: when the potential buyer applied to the program between June 2012 and June 2014 

and at follow-up in 2016—with both baseline and follow-up measures coming from credit bureau 

records. We also compare shared equity buyers with other buyers to further explore mortgage 

performance, using the same time periods. In this way, we are estimating relatively near-term outcomes 

for shared equity participants 

Between the start of data collection in June 2012 and the conclusion of the study enrollment period 

in June 2014, the programs received 683 applications. The participating shared equity programs 

received a greater number of applicants during this time period, but not all of them agreed to 

participate in this study. Further, the 683 applicants who consented to participating in this research 

were not screened for program eligibility, and therefore some applicants included may not have been 

qualified to purchase a home through the program. 

As of July 2016, 244 of these applicants had purchased a shared equity home. We use information 

on applicants (program buyers versus other applicants) and on a separate comparison group to inform 

the following research questions: 

 What portion of shared equity program applicants purchased shared equity homes? What 

portion of applicants purchased homes apart from these programs? As such, what can be said 

about whether those who bought shared equity homes were appreciably more likely to buy 

than other applicants? 

 What were the baseline characteristics of applicants who purchased shared equity homes as 

compared with those who purchased homes apart from these programs and those who did not 

purchase homes at all? 
A F F O R D A B L E H O M E O W N E R S H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S 7

 How did applicants who bought shared equity homes fare with regard to nonmortgage financial 

characteristics (e.g., credit score and revolving debt), relative to: a) applicants who did not 

purchase shared equity homes, b) applicants who bought homes apart from these programs, 

and c) a comparable group of nonapplicants who recently bought homes?

 How did applicants who bought shared equity homes fare with regard to mortgage

characteristics (e.g., any 90- to 180-day mortgage delinquencies and having a home equity line 

of credit), relative to: a) applicants who bought homes apart from these programs and b) a 

comparable group of nonapplicants who recently bought homes?

 How did applicants who bought shared equity homes compare with regard to neighborhood

characteristics (e.g. neighborhood median occupied home value), relative to: a) applicants who 

did not purchase shared equity homes, b) applicants who bought homes apart from these 

programs, and c) a comparable group of nonapplicants who recently bought homes?
8 A F F O R D A B L E H O M E O W N E RS H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S

Chapter 2. Shared Equity Program 

Models 

In this chapter we describe key elements of shared equity models, and then profile the nine shared 

equity programs (or groups of programs in South Florida) included in the study (table 2.1). The 

information in this section draws from interviews with program staff, as described in our baseline 

report (Theodos, Temkin et al. 2015).12 We synthesize key program information here. Please see the 

baseline report for expanded detail about each approach used by the shared equity organizations in this 

study. 

TABLE 2.1

Shared Equity Programs

Location Organization

Austin, TX HomeBase

Bay Area (San Francisco), CA Hello Housing

Burlington, VT Champlain Housing Trust

Long Island (Hauppauge), NY Long Island Housing Partnership

Nashville, TN The Housing Fund Inc.

Park City, UT Mountainlands Community Housing Trust

Seattle, WA Homestead Community Land Trust

South Florida

Community Land Trust of Palm Beach County

Delray Beach Community Land Trust

Heartfelt Florida Housing of South Palm Beach County

Community Land Trust

Housing Partnership Inc.

South Florida Community Land Trust

Washington, DC City First Homes

Overview of Shared Equity Program Model Components 

Shared equity programs are designed to establish and maintain an affordable stock of homes for 

purchase by low- and moderate-income residents. Programs can manage shared equity units in their 

own portfolios, on behalf of third parties, or some combination of the two. Some programs complement 

these tasks by offering down payment assistance to homebuyers, providing technical assistance to 

other affordable housing organizations, or advocating on behalf of affordable housing locally. 
A F F O R D A B L E H O M E O W N ER S H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S 9

Programs that steward the units in their portfolios first access them in a variety of ways. They may 

purchase and rehabilitate existing units. Or they may develop homes through new construction. Or, 

they may access homes that are set aside for the program, for example through inclusionary zoning or 

other efforts. 

Any shared equity program operates within a specific local context and requires political and 

financial support from state and local policymakers. Local housing market conditions also influence 

program efficacy. For instance, shared equity homes may not appear to be an attractive alternative in 

markets where home prices are not appreciating or where market-rate homes are relatively affordable 

to low- and moderate-income buyers. And opportunities to acquire newly constructed units are 

especially limited in hot markets, unless developers have a regulatory motivation or financial incentive 

to construct homes for sale below market prices. 

Establishing and Maintaining Affordability over Time 

The primary goal of a shared equity program is to provide homeownership opportunities to low- and 

moderate-income households. They often limit participation to these intended beneficiaries by 

restricting eligibility to households earning less than a specified share of area median family income, for 

example, those earning below 80 percent of the area median. The program maintains a stock of homes 

that remain affordable to this population by subsidizing the initial sales price, and creating rules for how 

resale values are determined. 

The initial sales price for a shared equity home requires a trade-off between making a unit 

affordable and using available subsidy dollars as efficiently as possible. This means establishing an initial 

sales price affordable to buyers with a particular income based on assumptions regarding down 

payments, interest rates, and loan terms. However, because of the restrictions placed on potential 

profit on resale of these homes, the difference between the price of a shared equity home and a marketrate home must be large enough to attract potential buyers. 

Resale formulas establish the maximum proceeds that a shared equity owner can realize when 

selling his or her unit. Any shared equity program, in establishing the resale formula, must balance two 

competing objectives: allowing sellers to build equity (which facilitates wealth creation and encourages 

property maintenance) and maintaining the home’s affordability to subsequent buyers. Five general 

types of resale formulas are introduced below, all of which are used by programs within this study. 
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Although there are important administrative differences among them, it is possible to arrive at similar 

rates of return and similar levels of affordability preservation using different resale formulas.

 Fixed rate. The maximum resale price is established by applying a fixed annual percentage 

growth rate to the initial purchase price. Under fixed-rate formulas, the maximum resale price 

for homes increases without regard to changes in area house prices or incomes.

 Indexing to changes in the national price of household goods. The maximum resale price is 

established by increasing the initial affordable price by a percentage equal to the percentage 

increase in the Consumer Price Index during the reseller’s tenure. Like properties governed by 

fixed-rate formulas, the maximum resale price for homes with resale formulas indexed to the 

Consumer Price Index increases without regard to changes in area house prices or incomes.

 Indexing to changes in area incomes. The maximum resale price is established by increasing 

the initial affordable price by a percentage equal to the percentage increase in the area median 

family income during the reseller’s tenure. The maximum resale price for homes with resale 

formulas indexed to the area median family income increases with regard to changes in 

incomes rather than to changes in area house prices.

 Indexing to changes in area home values. The maximum resale price is established by 

increasing the initial affordable price by a percentage equal to the percentage increase in area 

home value during the reseller’s tenure. Changes in area home values may be measured by 

median sales prices or real estate price indices.

 Appraisal based. The change in a home’s market value is determined by the difference in 

appraisals conducted at the time of purchase and resale. The reseller is allowed to retain a 

portion of the change in appraised market value. For example, the reseller might keep 25 

percent of the appreciation. The home then resells at a price equal to the initial affordable price 

plus the reseller’s share of the change in appraised value. Homes with appraisal-based resale 

formulas increase in price with regard to changes in home values and without regard to changes 

in area incomes.

It is important to bear in mind that the proceeds realized by owners at resale for each type of 

formula offer the potential (although not a guarantee) for substantial returns on investment, as most 

shared equity owners purchase their homes with a small down payment. For example, in programs with 

a flat percentage rate (the fixed-rate resale formula described above), this percentage (e.g., 2 percent) is 

applied to the purchase price of the home, which can be 20 times the down payment amount (assuming 
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a 5 percent down payment). Therefore, even a relatively modest allowable rate of 2 percent per year 

will result in allowable appreciation in excess of the buyer’s down payment within 2.5 years (assuming 

no compounding). 

One potential drawback of the shared equity approach is that owners, because they do not realize 

all of a unit’s appreciation, may have fewer incentives to invest in capital improvements. Some programs 

address this by allowing owners to recover the some or all of the cost of capital improvements they’ve 

made. (And the program may depreciate the value of the expenses that can be credited over time.) 

Many programs require that owners receive approval before starting major capital improvements to 

ensure that units remain affordable at resale. 

Participant Engagement 

Because shared equity homes are priced below market, the concept is attractive to potential low- to 

moderate-income homebuyers; however potential homebuyers are often unfamiliar with shared equity. 

Organizations that operate shared equity programs work with local realtors and developers to improve 

awareness of shared equity buying opportunities and local knowledge of how the programs operate. In 

addition to referrals from these real estate professionals, some organizations also maintain websites or 

use social media to advertise their programs and homes. 

Because many shared equity buyers are first-time homeowners, programs frequently require that 

prospective buyers complete a prepurchase homebuyer counseling program. Shared equity programs 

that provide their own counseling typically teach attendees about their program policies 

simultaneously. If the program does not provide buyer counseling, it can refer clients to counseling 

organizations, such as those approved by the US Department of Housing and Urban Development 

(HUD). 

Many organizations that operate shared equity homeownership programs provide services to 

buyers after purchase. These stewardship services have the potential to improve the performance of 

shared equity mortgages and ease the transition from rental housing. Owners will have a point of 

contact if they have trouble paying the mortgage or have questions related to maintaining their home. 

Indeed, all the programs take steps to remain in contact with their buyers after purchase; thus, buyers 

are aware of resources if they require assistance. In some cases, the organizations operating shared 

equity programs will also assist owners in selling their homes. 
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Lender Engagement 

Although shared equity housing has been in place for more than 30 years, many lenders are unfamiliar 

with such housing. Moreover, given the restrictions on homes purchased under these programs, 

whether shared appreciation, deed restrictions, or only a leasehold interest in the underlying land, 

standard Federal Housing Administration (FHA) are unavailable to shared equity homebuyers. During 

this period, conventional mortgages were difficult to access in some of the sites, though this has 

improved of late with Fannie Mae’s changes in 2015 that allow lenders to use Desktop Underwriter for 

these loans.13 Lenders often struggle to understand their own risks or what happens to a shared equity 

home in the event of default or foreclosure. As a result, shared equity program managers must typically 

work to educate local lenders about their particular shared equity program for these lenders to develop 

products that can be used for permanent mortgage financing. 

However, only a limited number of lenders have been willing to work with shared equity buyers, 

mainly because the difficulty of accessing FHA or the secondary market meant that lenders generally 

had to hold the loans on their balance sheets, and hold capital against them. (As referenced, with 

changes in 2015, Fannie Mae began purchasing these loans.) In addition to these factors, many loans 

under these programs are relatively small, which reduces lender profit, and thus, interest in serving the 

market. Programs have overcome these impediments by providing loans themselves; partnering with 

local lenders and credit unions; or coordinating with other public organizations, such as state housing 

finance authorities. 

Marketing to Potential Buyers 

Shared equity as an approach for providing affordable housing is unfamiliar to many potential buyers 

and also some real estate market participants. To alleviate this problem, many programs work with local 

realtors and developers to foster familiarity with shared equity programs and create a valuable source 

of referrals. This can include holding periodic meetings with local real estate professionals to ensure 

that key market participants are aware of shared equity buying opportunities. In addition to working 

directly with local realtors and developers, shared equity programs often maintain websites and use 

social media to advertise their programs. Some also receive word-of-mouth referrals as community 

members spread news of their programs. 
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Shared Equity Program Profiles 

HomeBase Texas (Austin, Texas) 

Founded in 2008, HomeBase Texas (also known as HomeBase) manages a portfolio of 650 deedrestricted homes in the City of Austin and Travis County, including properties they manage as a 

subsidiary for the local Habitat for Humanity affiliate and on behalf of the Mueller Foundation. 

(However, after study enrollment, management of the Mueller Foundation portfolio was transferred to 

another organization.) Beyond a shared equity homeownership program, HomeBase can also provide 

down payment assistance throughout greater Texas. 

Source of homes. HomeBase acquires new units by developing relationships with volume builders 

that may have lots for development and by building homes on acquired land. 

Prepurchase services provided to homebuyers. All buyers must participate in a one-on-one session 

that covers shared equity homeownership, and take a class that uses the NeighborWorks prepurchase 

curriculum. 

Sources for mortgage financing. HomeBase works with credit unions, some of which offer 100 

percent financing. Loans are either portfolio products or sold to Fannie Mae. In some cases, developers 

offer permanent financing. 

Resale proceeds. HomeBase allows 2 percent per annum appreciation on the sales price and offers 

no credits for capital improvements. 

Hello Housing (San Francisco Bay Area, California) 

Founded in 2005, Hello Housing operates in the greater Bay Area, which includes Alameda, Contra 

Costa, Marin, and San Mateo counties. Their portfolio of 540 deed-restricted homes includes units 

managed for the cities of Novato, Alameda, Concord, and Menlo Park. In addition to a shared equity 

program, Hello Housing provides down payment assistance. 

Source of homes. Hello Housing develops homes, sells inclusionary units on behalf of private 

developers, and manages homes already constructed through inclusionary zoning or other “below 

market rate” programs in municipalities contracting with Hello Housing. 
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Prepurchase services provided to homebuyers. In most cases, homebuyers are required to take a 

four- to eight-hour class from a HUD-certified counseling agency before purchase. 

Sources for mortgage financing. PNC Mortgage and Boston Private Capital are Hello Housing’s 

preferred lenders. 

Resale proceeds. Hello Housing operates in multiple jurisdictions in the Bay Area and applies 

different resale formulas based on the jurisdiction. One resale formula applies the change in area 

median family income to the original purchase price (not the appraised value) of the home, plus the 

depreciated value of capital improvements. In another, the resale formula takes the percentage change 

in Consumer Price Index (CPI) plus a quarter of a percent for every three months the owner has been in 

the home, plus capital improvements. 

Champlain Housing Trust (Burlington, Vermont) 

Founded in 1984, the Champlain Housing Trust operates in Chittenden, Franklin, and Grand Isle 

counties. It has a portfolio of roughly 570 homes, which it manages using a CLT model. 

Source of homes. Champlain Housing Trust has acquired properties in various ways, including 

through the Neighborhood Stabilization Program (NSP) and the Vermont Housing and Conservation 

Board, and also manages units constructed through Burlington’s inclusionary zoning program. In 

addition, the organization will, through its buyer-driven program, provide subsidies on a home already 

being purchased in exchange for resale restrictions. 

Prepurchase services provided to homebuyers. Champlain Housing Trust provides homebuyer 

education and prepurchase counseling, and requires all buyers to participate. 

Sources for mortgage financing. Champlain Housing Trust homebuyers access first mortgage 

financing through four local credit unions, three local banks, and USDA Rural Development. Mortgages 

are salable to Fannie Mae through the state housing finance agency or directly by local lenders. 

Resale proceeds. Champlain Housing Trust allows sellers to retain 25 percent of appreciation as 

measured by the change in the appraised value of a home between initial purchase and resale. Owners 

receive 100 percent of the increased value resulting from capital improvements.
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Long Island Housing Partnership (Long Island, New York) 

Founded in 1989, Long Island Housing Partnership, Inc. operates in Nassau and Suffolk counties. Their 

portfolio consists of more than 1,250 deed-restricted homes, which include units managed on behalf of 

local municipalities on Long Island. 

Source of homes. Long Island Housing Partnership’s largest source of homes during this study was 

through NSP funding, but the program uses other sources as well. In addition to organization-developed 

homes retained in its portfolio, it also manages acquisitions of tax-default properties. 

Prepurchase services provided to homebuyers. Long Island Housing Partnership’s shared equity 

program is restricted to first-time homebuyers, all of whom are required to attend mortgage counseling. 

The program also offers a down payment assistance program and a matched savings program in 

partnership with local banks. 

Sources for mortgage financing. Long Island Housing Partnership participates in a local coalition of 

mortgage lenders that includes Citibank, JP Morgan Chase, Capital One, Bank of America, HSBC, 

Astoria, M&T, and the State of New York Mortgage Agency. The following credit unions also originate 

shared equity loans: Suffolk Federal Credit Union, Teachers Credit Union, Bethpage Federal Credit 

Union, as does the Municipal Credit Union. 

Resale proceeds. Long Island Housing Partnership uses the Consumer Price Index to limit the 

resale price, but caps resale prices so that homes are affordable to families whose incomes are the same 

percentage of area median family income as the original buyers. There are provisions for sellers to 

recover the cost of capital improvements. 

The Housing Fund (Nashville, Tennessee) 

Founded in 1996, The Housing Fund Inc. operates state-wide in Tennessee. The Housing Fund’s 

portfolio currently consists of 20 deed-restricted homes, but the organization also assists in the 

development of new, affordable homes to be sold to low- or moderate- income families. In addition to 

their shared equity program, the Housing Fund provides owners with down payment assistance. 

Source of homes. During of this study, the Housing Fund used NSP funds to acquire lots in a 

foreclosed suburban subdivision and build townhomes on the vacant land. In addition, it acquired a few 

existing homes, some at the request of buyers. 
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Prepurchase services provided to homebuyers. The Housing Fund works with buyers throughout 

the process, including helping the buyer work with the lender, title, and real estate agents. In addition, 

all buyers are required to receive homebuyer counseling from a third-party provider. If needed, the 

Housing Fund will refer some potential buyers to credit repair agencies. 

Sources for mortgage financing. The Housing Fund works primarily with Pinnacle Bank for its 

mortgage financing products. The Tennessee Housing and Development Agency offers first mortgages, 

and it can modify the terms of its normal first mortgage product to mirror the Housing Fund's 

underwriting. The state housing agency holds these notes, and several banks originate these products, 

acting as broker for the housing agency. 

Resale proceeds. Through year 3, resellers receive 25 percent of appreciation as measured by 

changes to appraised value. For years 3 to 30, appreciation is split 50-50. After year 30, resellers 

receive 100 percent of the appreciation. Major improvements that change a unit’s footprint require the 

Housing Fund’s approval. The value of capital improvements the owner makes is added to the resale 

formula–dictated sales price. 

Mountainlands Community Housing Trust (Park City, Utah) 

Founded in 1993, Mountainlands operates in Summit and Wasatch counties. Their portfolio of roughly 

180 homes includes units developed by Mountainlands and under Summit County’s inclusionary zoning 

requirements. A small share of units are managed using a CLT model. 

Source of homes. Mountainlands manages deed-restricted homes on behalf of the county. In 

addition, Mountainlands sometimes requests lots from developers with inclusionary zoning 

requirements or purchases them to build homes. 

Prepurchase services provided to homebuyers. Mountainlands provides prepurchase services to 

potential homeowners. 

Sources for mortgage financing. Mortgage lenders at Mountainlands are Academy Mortgage 

Corporation, Intermountain Mortgage Company, Key Bank Mortgage, Mountain Valley Financial, and 

USDA Rural Development. 

Resale proceeds. Mountainlands allows a maximum of 3 percent per annum appreciation on 

purchase price. With varying limits, resellers receive 100 percent of capital improvements approved by 

Mountainlands. 
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Homestead Community Land Trust (Seattle, Washington) 

Founded in 1992, Homestead Community Land Trust provided its first shared equity subsidy in 2002 

and manages a portfolio of 183 homes (at year end 2015) in the City of Seattle and King County. 

Source of homes. Homestead’s acquisition strategies from 2012 to 2015 included new 

construction infill homes, acquisition rehab of single-family detached homes, partnerships with other 

nonprofit developers and purchase and completion of a distressed condominium development. 

Prepurchase services provided to homebuyers. Homestead’s shared equity program is limited to 

first-time homebuyers, who are required to participate in a first-time homebuyer class. Homestead also 

provides one-on-one financial counseling tailored to each family’s budget and purchasing power, as well 

as additional support throughout the purchase process as needed on an individual basis. 

Sources for mortgage financing. Mortgage lenders at Homestead are Washington Federal, Guild 

Mortgage, and HomeStreet Bank. 

Resale proceeds. Homestead allows resellers to realize 1.5 percent per annum appreciation on the 

restricted resale price. Owners can receive 100 percent of qualified capital improvements. 

South Florida Consortium (South Florida) 

CHIP awarded a single grant to a consortium of South Florida shared equity programs, all of which use a 

CLT model. We collectively refer to these groups as the “South Florida consortium.”

TABLE 2.2 

Shared Equity Programs in the South Florida Consortium 

Program Geographic footprint Founding year Portfolio size

Community Land Trust of Palm Beach County

Delray Beach Community Land Trust

Heartfelt Florida Housing of South Palm Beach 

County Community Land Trust

Housing Partnership Inc.

South Florida Community Land Trust

Palm Beach County

City of Delray Beach

Palm Beach County

Palm Beach County

Broward County

2008

2006

2010

1986

2006

28

56

20

32

8

Source of homes. Programs in the South Florida consortium acquire properties by purchasing 

never-occupied, real estate owned, or foreclosed homes; developing on land the local government 

donates; assuming ownership of NSP properties; and partnering with local Low-Income Housing Tax 

Credit developers. 
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Prepurchase services provided to homebuyers. CLT of Palm Beach County and Delray Beach CLT 

are both restricted to first-time homeowners. CLT of Palm Beach County and South Florida CLT both 

require buyers to attend HUD-approved prepurchase counseling, and a CLT orientation. Delray CLT 

only requires buyers to attend a CLT orientation, and Heartfelt Florida Housing of South Palm Beach 

County CLT requires buyers to attend at least one program-provided workshop. Housing Partnership 

offers prepurchase group classes, provides down payment assistance, and offers financial coaching. 

Sources for mortgage financing. The South Florida consortium is served by six lenders. 

Additionally, Heartfelt Florida Housing of South Palm Beach County CLT originates loans for qualifying 

homebuyers earning under 80 percent of the area median family income. 

Resale proceeds. CLT of Palm Beach County, Heartfelt Florida Housing of South Palm Beach 

County CLT, and South Florida CLT allow resellers to receive up to 25 percent of any appreciation. 

Delray Beach CLT’s resale formula is based on purchase price plus change in area median family income, 

and owners receive credits for capital improvements and capital systems replacements. 

City First Homes (Washington, District of Columbia) 

Founded in 2010, City First Homes manages a portfolio of 242 deed-restricted homes in Washington, 

DC. 

Source of homes. City First Homes uses several methods to create permanently affordable homes. 

One method of creation is by providing developers with flexible and subordinate capital in 

consideration for their agreement to record covenants that secure permanently affordable units. City 

First Homes also works with renters in multifamily buildings that are interested in purchasing their 

buildings and converting them to housing cooperatives. City First Homes provides these groups with 

lending capital and technical assistance to create shared equity units. 

Prepurchase services provided to homebuyers. Before purchase, City First introduces buyers to 

the shared equity model in a two-hour course. Buyers are also referred to third parties for general 

housing and homeownership counseling with a requirement for 8 hours of pre-purchase training. 

Sources for mortgage financing. City First Homes refers buyers to Industrial Bank, Citibank, and 

Monarch Bank. 
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Resale proceeds. City First allows the owner to retain 25 percent of allowable appreciation. The 

owner is allowed to recover 100 percent of the value of capital improvements made to the property as 

estimated by the appraiser at resale.
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Chapter 3. Data and Methodology 

This chapter describes the data and analysis techniques used in this paper. Four types of data support 

the analysis: baseline surveys provided at the point of application to the programs, program data about 

purchase transactions for shared equity buyers, baseline and follow-up financial information from a 

large credit bureau about all applicants and a nonapplicant comparison group, and secondary data 

about the neighborhoods where applicants and nonapplicants live. A complete data dictionary can be 

found in appendix A. Funding was not available to support a follow-up survey as included in the original 

study design, and as a result this report reflects outcome analysis relying only on credit bureau and 

program data.14

To analyze the data, we first estimate the characteristics that contributed to the likelihood that an 

applicant would purchase a home through a shared equity program. We then estimate the relationship 

between the shared equity program and financial outcomes of shared equity purchasers. To do so, we 

compare shared equity purchasers to other applicants who did not purchase a shared equity home. 

Next, we compare shared equity purchasers to other applicants who purchased a home outside of the 

program. Finally, we compare shared equity purchasers to similar purchasers who were not applicants 

to the shared equity program but who lived in the metro region of the purchaser. (We explain each 

group in further detail later in this chapter.)

Data 

Application Data 

Programs provided detailed information about applicants who agreed to participate in this research. 

Study enrollment ran from June 2012 through June 2014. To be considered an applicant, a potential 

homebuyer had to express an interest in purchasing a shared equity home, complete the program’s 

required intake form, and comply with any eligibility criteria (e.g., relating to household income). Each 

organization had a limited number of homes available for sale in their portfolio at any given time, 

though the number of applicants was not restricted. 

Program staff then informed potential buyers about the research study and asked them to sign an 

informed consent form indicating their willingness to participate in the evaluation. Buyers unwilling to 
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participate in the research study were still able to pursue a home through the program; this report does 

not contain information on those individuals, and we do not know how many people are in this category. 

The programs then collected baseline data on these individuals, either through their normal intake 

forms if they contained all questions we needed, or if they preferred, using a supplemental 

questionnaire in addition to their normal intake process. In either case, sites shared the same set of 

baseline data points with us. 

The baseline data contain information about applicants’ demographic and financial characteristics, 

their housing expenses, self-reported credit history, and living arrangements. Applicants also provided 

identifying information. 

Homekeeper Administrative Data on Shared Equity Purchase Transactions 

The shared equity programs then provided us data on study participants who applied to a program and 

purchased a shared equity home. The programs shared these data via HomeKeeper, a web-based 

Saleforce.com application.15 By combining shared equity purchase and baseline application data (and 

credit data, as discussed in the next section), we are able to identify the characteristics of applicants 

who purchased homes through the programs. We present this analysis in chapter 4: Program 

Applicants. These data also include information about the shared equity purchases, such as information 

on the physical characteristics of the new home, its location, and buyer financing. These are described in 

chapter 5. 

Baseline and Follow-up Credit Bureau Data 

To understand the relationship between shared equity programs and participant finances, we use 

information from a large credit bureau about credit scores, overall debt, revolving debt, student loans, 

mortgage debt, home equity lines of credit (HELOCs), and delinquencies. We also purchased from the 

credit bureau age and estimated wage data, as well as information on which census tract each person 

lived in before and after the study period. For each individual, we purchased data for coinciding with 

baseline (June 2012 or June 201316) and follow-up (June 2016) periods. The credit bureau was able to 

match 91 percent of applicants (623 of 683). 

We purchased these credit data for individuals who applied to the shared equity programs—both 

those who purchased homes through the programs and those who did not. We also purchased credit 
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data for individuals who did not apply to the shared equity program but who lived in the same metro 

areas as shared equity applicants, so that we could have a second comparison group for the shared 

equity purchasers. We selected this outside comparison group based on their similarity to program 

applicants in terms of credit score and geographic location, and required that they be first time home 

buyers at baseline, and recent buyers by the follow-up period. 

Secondary Data 

Finally, we incorporate demographic data on neighborhoods from the American Community Survey 

(2010–2014) and area median family income data from HUD. We use these data to identify differences 

in neighborhood characteristics between where purchasers were living at the time of application and 

where their new home is located. We used home price and median family income data to evaluate 

purchased homes’ affordability relative to the local market. These analyses are located in chapter 4: 

Program Applicants. 

Empirical Methodology 

Program Applicants 

To analyze baseline data, we first explored descriptive characteristics of program applicants, including 

their demographics, finances and creditworthiness, and the neighborhoods in which they live (chapter 

4). 

Shared Equity Purchases 

Next, we estimated the differences in these average characteristics between shared equity purchasers 

those applicants who did not purchase a shared equity home (chapter 5). We also segmented the latter 

group into applicants who purchased a home outside of the program and applicants who did not 

purchase a home at all, comparing both groups with shared equity purchasers. (We refer to those who 

purchased a home not through a shared equity home as “other” purchasers, not “market” or 
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“conventional” purchasers, as they may have used other public or philanthropic supports to purchase 

homes, and we do not observe these attributes of the transactions.) 

To more closely examine what types of characteristics make an applicant more or less likely to 

purchase a shared equity home, we then estimated a linear probability of the likelihood of purchasing a 

shared equity home.17 This allowed us to determine which characteristics were associated with a shared 

equity home purchase, holding other variables constant. 

Shared Equity Buyer Outcomes 

To estimate the relationship between shared equity programs and financial outcomes, we compared 

follow-up credit bureau data for shared equity purchasers with data for those applicants who did not 

purchase a shared equity home. (We provide these estimates in chapter 6 and minimum detectable 

effects in appendix C). We also compared shared equity purchasers with just those applicants who 

purchased a home outside of the program. Finally, as a check against these findings, we used credit 

bureau data to compare shared equity purchasers with a de-identified group of nonapplicants who 

purchased outside of the shared equity programs but within the same MSAs as program purchasers. 

It is important to note that we do not make causal claims about any differences found between 

shared equity and nonapplicants’ outcomes because we cannot fully control for unobservable 

characteristics that might be related to program participation such as motivation or expected future 

earnings.18 Such differences, to the extent they exist, would lead to selection bias. With this research 

approach, we can detect meaningful differences on the average outcomes for individuals with similar 

pre-program observable characteristics. And it is worth noting that the baseline controls we include are 

consistent with existing literature assessing homeownership using matching approaches, for example, 

as in Aratani 2011; Grinstein-Weiss et al. 2011; Manturuk, Lindblad and Quercia 2012; and Roskruge at 

al. 2013.

Selection for participation into shared equity programs may occur at two levels (figure 3.1). In the 

first level, individuals select to become applicants into the program. These are low and moderateincome individuals and households living in areas where the program is available who demonstrate 

some interest in buying house using a shared equity approach. 

In the second level, shared equity applicants select into purchasing a house using a shared equity 

program or not. And shared equity programs elect to approve or reject applicants as home purchasers. 

Some shared equity applicants will be unable to qualify for conventional mortgages, and do not 
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purchase a home. Some applicants will purchase homes via other programs, for example, using down 

payment assistance. Some applicants will opt to purchase homes with conventional mortgages, though 

perhaps at a home value lower than they could access via a shared equity program. Some applicants 

who are mortgage-eligible have life circumstance changes, or otherwise have shifts in their priorities 

that mean they do not buy a home at all. Applicants may be rejected by a program if their incomes or 

asset levels are too high, or they do not complete the necessary counseling requirements. Given all 

these possibilities, it is possible that those applicants who purchase shared equity homes differ in nonobservable ways from applicants who do not, but we do not have good insights into the magnitude and 

direction of a bias, if one exists. 

FIGURE 3.1 

Program Selection 

We therefore estimated the differences in outcomes using three different comparison groups 

(applicants who did not purchase a shared equity home, applicants who purchased outside of the 

program, and non–shared equity applicants) to get as robust a picture as possible. None of these 

comparisons is ideal, but together they give us a picture of the relationship between shared equity and 

outcomes. Each comparison method is described in detail below. 

Population 

Shared equity 

applicants 

"Other" home 

purchasers 

Nonpurchasers 

Shared equity 

home purchasers 

Nonapplicants 

"Other" home 

purchasers 

Nonpurchasers 
A F F O R D A B L E H O M E O W N ER S H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S 2 5

SHARED EQUITY PURCHASERS VERSUS ALL OTHER APPLICANTS 

To estimate the relationship between shared equity home purchase and a number of nonmortgage 

financial and neighborhood outcomes, we first compared shared equity purchasers to shared equity 

applicants who did not purchase a shared equity home. Some of the latter group of applicants purchased 

a home outside of the program and others did not purchase a home at all. 

To make this comparison, we estimated the following model: 

Yim2016 = β0 + β1Tim + β2Yim2012 + β2Xim2012 + δm + εim2016

where Yim2016 was the outcome of interest for individual i in site m in year 2016, Tim was an indicator 

whether individual i is a shared equity purchaser, Yim2012 was the outcome measured before the 

program implementation (baseline), Xim2012 was a set of covariates also measured at baseline, δm were 

site fixed effects, and εim2016 was the idiosyncratic error. For the set of characteristics Xim2012, we 

included information from the application data, such as asset level, race, income and education; from 

the credit bureau data, such as past credit history; and characteristics about the neighborhood (census 

tract) where an applicant resided at baseline from the American Community Survey. We estimated the 

model using linear least squares with standard errors clustered at the site level. 

The coefficient of interest is β1, which compares the outcomes of program applicants who were 

shared equity purchasers and those who are not, controlling for a set of pre-program characteristics 

and the baseline variable of the outcome variable. While we cannot draw causality from these 

estimations since selection to purchase a shared equity home might be based on other unobservable 

characteristics, β1 represents the average difference in outcomes for individuals net of difference in 

observed pre-program characteristics. 

SHARED EQUITY PURCHASERS VERSUS OTHER APPLICANT PURCHASERS 

Next, we compared shared equity purchasers to the other shared equity applicants who purchased a 

home outside of the program. In addition to nonmortgage financial and neighborhood outcomes, this 

allowed us to compare mortgage performance, since both groups opened a mortgage during the study 

period. 

To do so, we used the same model above, but restricted the sample to applicants who purchased a 

home during the study period (both through the program and outside of it), and we examined mortgage 

and home purchase related outcome measures, such as total mortgage amount, and also nonmortgage 

and neighborhood characteristics. 
2 6 A F F O R D A B L E H O M E O W N E RS H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S

SHARED EQUITY PURCHASERS VERSUS NONAPPLICANT PURCHASERS

Finally, we compared shared equity purchasers to purchasers who were not shared equity applicants 

but who lived in the same metro area at the time the study began. This group was selected to be within 

the credit score range of the shared equity applicants in the sample. The group was also limited to 

individuals who were first time homeowners at the baseline data pull, to ensure that length of tenure of 

ownership was comparable across the two groups.

To draw this sample, we used data from a major credit bureau. Since we could not observe, in 

advance, a desire to purchase a home in the general population, we have no way of comparing 

“interested buyers” to all shared equity applicants. We did, however, examine recent home purchasers. 

However, as before, this comparison group has limitations: some shared equity purchasers likely were 

unable to purchase outside of the programs, and may not have had an adequate match in the general 

pool of nonapplicants.

To draw a comparison group from these outside purchasers, we use a propensity score matching 

approach. This method relies on selecting a group of home purchasers from the pool of nonapplicants 

who have similar baseline characteristics to the shared equity purchasers. The decision to use 

propensity score matching approach for the comparison between the share equity purchasers versus 

nonapplicants and linear square for the other groups is based on the number of individuals in the 

comparison group with similar observable characteristics (there are only 139 applicants who purchased 

a home outside the program).

We implemented the model in two steps. First, we estimated the probability that each individual i

will purchase a shared equity home based on his or her baseline characteristics – the “propensity” to 

enroll. To do so, we used a Probit model to predict each individual i′s probability of being a shared

equity purchaser:

Pi = p(Yim2012, Xim2012, δm),

where Yim2012 was the outcome measured before the program implementation (baseline), Xim2012 was a 

set of baseline characteristics from the credit bureau data including age and credit history 

characteristics, and average characteristics of the census tract where individual i lived at baseline (e.g. 

median income level, share African American, share Latino, share bachelor’s degree, etc.) from the 

American Community Survey, and δm were site dummies.

Second, we used this estimated propensity score to match individuals in the treatment group to 

those in the comparison group with a similar likelihood of selecting to participate in the program. To do 
A F F O R D A B L E H O M E O W N ER S H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S 2 7

so, we used a nearest neighbor matching with replacement approach, where an individual in the control 

group can be matched to more than one individual in the treatment group. The statistic of interest is

then the difference in the average outcomes between the shared equity purchasers and the matched 

comparison group:

τ̂Y = Y̅

T,2016 − Y̅MC,2016,

where Y̅

T,2016 is the average of outcome Y for shared equity purchasers at follow up and Y̅MC,2016 is the 

average of outcome Y for individuals in the comparison group who are matched to individuals in the 

treatment group based on their observable characteristics. To test whether τ̂Y is statistically different 

from zero, we estimated its standard errors using the expression derived by Abadie and Imbens (2006).

We also adjusted the results from the propensity score matching for multiple comparisons. For this 

purpose we group the outcome variables in five families: financial (credit score, credit utilization rate, 

and revolving debt); loan performance (any 90- to 180-day nonmortgage delinquencies and at least one 

account in collections); debt amounts (monthly payment on credit accounts and credit on open 

mortgage trades); mortgage type and performance (any open HELOCs reported in the last 6 months, 

any 90-180 day mortgage delinquencies and any foreclosure); and neighborhood (percent of 

neighborhood with a bachelor’s degree or more and neighborhood median occupied home value). We 

used the Bonferroni adjustment.
2 8 A F F O R D A B L E H O M E O W N E RS H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S

Chapter 4. Program Applicants 

In this chapter we provide baseline information about individuals who applied to a shared equity 

program. In total, 683 individuals applied through the shared equity organizations to purchase a home 

in the study period and consented to participate in the research study. The 683 applicants who 

consented to participate in this research were not screened for program eligibility, and therefore some 

applicants included may not have been qualified to purchase a home through the programs, for example 

if they were over-income. Table 4.1 summarizes the number of applicants by site. The number of 

applicants participating in the study ranged from a high of 136 in Burlington (Champlain Housing Trust) 

to a low of 25 in the Bay Area (Hello Housing). 

TABLE 4.1 

Shared Equity Program Applicants by Site 

Organization headquarters Organization 

Applicants 

study 

in 

Austin, TX 

Bay Area (San Francisco, CA) 

Burlington, VT 

Long Island (Hauppauge, NY) 

Nashville, TN 

Park City, UT 

Seattle, WA 

South Florida 

South Florida (Lake Worth, FL) 

South Florida (Delray Beach, FL) 

South Florida (Delray Beach, FL) 

South Florida (Riviera Beach, FL) 

South Florida (Fort Lauderdale, FL) 

Washington, DC 

HomeBase 

Hello Housing 

Champlain Housing Trust 

Long Island Housing Partnership 

The Housing Fund 

Mountainlands Community Housing Trust 

Homestead Community Land Trust 

Community Land Trust of Palm Beach 

County 

Delray Beach Community Land Trust 

Heartfelt Florida Housing of South Palm 

Beach County Community Land Trust 

Housing Partnership Inc. 

South Florida Community Land Trust 

City First Homes 

111

25

136

48

29

68

102

114

50

Total 683

Source: CHIP application data. 

In the remainder of this chapter, we report on the combined set of all applicants. For a breakdown 

of program applicant characteristics by site, see our baseline study (Theodos, Temkin et al. 2015). 
A F F O R D A B L E H O M E O W N ER S H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S 2 9

Demographics 

Across all sites, the median applicant was 37 years old with more than a third in the 30-39 age category 

(table 4.2). This is somewhat older than the 31-year median age of all first-time homebuyers during this 

time, according to the National Association of Realtors (2014). The programs attracted greater interest 

from women than from men: 69 percent of all applicants were female. When a couple applies for 

housing, one is considered the applicant and the other a coapplicant. Across all sites, nearly two-thirds 

of applicants applied for a shared equity program on their own, not with a coapplicant. Marital status 

was married for half of all applicants. Understandably, unmarried applicants were more represented 

among sole applicants than coapplicants. But 30 percent of all sole applicants were married, while 

conversely 14 percent of coapplicants were single. 

The programs attracted applicants from a mix of races/ethnicities. Forty-four percent of applicants 

were white non-Hispanic (white), 23 percent were black non-Hispanic (black), 19 percent were 

Hispanic, and 14 percent were from another or multiple races. While not shown, racial and ethnic 

composition of applicants varies widely across the sites. A majority of applicants to the programs in 

Burlington Vermont and Park City Utah were white, with black applicants the majority in Nashville and 

South Florida, and Hispanics the majority for the Austin site. 

An overwhelming share of applicants (96 percent) were not homeowners at the time of application. 

This includes renters and those who have other living arrangements, such as living with friends or 

family. This finding is consistent with many shared equity organizations requiring applicants to be firsttime homebuyers to qualify for a shared equity home. Nearly 85 percent of applicants were first-time 

buyers, classified following HUD’s definition of those who have not owned a home in the previous three 

years. 

At the time of application, applicants lived primarily in two-bedroom homes (43 percent) or those 

with three or more bedrooms (32 percent), with the remaining 26 percent in zero- or one-bedroom 

units. 
3 0 A F F O R D A B L E H O M E O W N E RS H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S

TABLE 4.2

Demographic Characteristics of Shared Equity Program Applicants

Demographic characteristics N Percent

Less than 30 years old

683

21

30–39 years 38

40–49 years 19

50–59 years 13

60 years and older 10

Female 643 69

Married 659 50

Sole applicant 681 64

White non-Hispanic

661

44

Black non-Hispanic 23

Hispanic 19

Other non-Hispanic 14

Renter

624

80

Other/lives with family 16

Homeowner 4

Lives in studio or 1 bedroom home

595

26

Lives in 2 bedroom home 43

Lives in 3+ bedroom home 32

Source: CHIP application data.

Education and Employment 

Half of applicants had a bachelor’s degree and roughly one-fifth had an associate’s or technical degree 

(table 4.3). This is more education than for the overall US population. For example, by comparison, 30 

percent of the US population 25 and older have at least a bachelor’s degree.19 It is not clear from our 

study why these programs attracted a more educated applicant pool. Looking to the other applicants, 

we see that 30 percent of all applicants lacked an associate’s or bachelor’s degree, though only a small 

share did not graduate from high school. 

About 82 percent of applicants reported working full time and another 14 percent were working 

part time or were self-employed. Applicants were employed in diverse occupations. About 30 percent 

were in office administration or health care. No other single occupation category accounted for more 

than 15 percent of applicants. 
A F F O R D A B L E H O M E O W N ER S H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S 3 1

TABLE 4.3 

Education, Employment, and Occupation Characteristics of Shared Equity Applicants 

Education and employment characteristics N Percent

HS diploma or less 20

Technical certification

Some college

572 9

21

College graduate 50

Full time 82

Part time

Self employed

453 9

5

Other 4

Office administration 15

Health care 15

Maintenance/repair/building and grounds 8

Sales/retail 8

Education 6

Food services 6

Community/social services 5

Transportation/material moving 4

Production/manufacturing

Financial

453 4

3

IT/technology 3

Legal 2

Construction 1

Management 1

Hospitality 1

Research 1

Architecture/engineering 1

Other 14

Source: CHIP application data. 

Finances and Creditworthiness 

Across the sites, applicants’ incomes were generally between 45 percent and 60 percent of the median 

family income for their surrounding area (table 4.4). These values were quite low compared with 

conventional homeownership targets of either 80 or even 120 percent of the area’s median family 

income. However, they were consistent with targets set by the shared equity organizations and with the 
3 2 A F F O R D A B L E H O M E O W N E RS H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S

buyers they wished to recruit. Of course, median incomes are different across metros. For example, in 

South Florida, the median family income is just 60 percent of that in Washington, DC. 

Applicants’ low incomes were somewhat surprising, given that the typical applicant was a college 

graduate, older, and with a full-time job. We hypothesize that this is the result, to a large degree, of the 

field that these individuals are working in. Many occupations require a college degree but are not 

necessarily high paying, which puts a particularly strain on buying a home in areas with a high cost of 

living. Given the demographic data, which show most shared equity applicants had college degrees, 

were in their late 30s at the median, and worked full time, their low incomes are not likely the result of 

life cycle patterns (being young and starting a career). Rather, many shared equity applicants worked in 

jobs like office administration and healthcare that, though stable, may not be sufficiently lucrative to 

support their purchasing a market rate home.

At intake, applicants who owned or rented had a median monthly housing expense of $835; in

addition, some applicants paid separate utilities that had a median monthly cost of $150 (table 4.4). 

Across all sites, 49 percent of applicants were housing cost burdened, defined as spending more than 30 

percent of their income on housing and utility expenses. This share was close to the national figure for 

renters: roughly half are cost burdened at this level.

In addition to having incomes roughly 45 to 60 percent of median family income across the sites, 

applicants had little net worth. Homeownership (even with resale restrictions) provided an opportunity 

for applicants to begin building wealth. The all-site median applicant net worth was $712. The mean was 

nearly $13,000. The median and mean statistics reported in table 4.4 show considerable differences for 

a select number of measures. Mean statistics can be inflated due to a small number of applicants with 

extremely high levels of assets or debts.

On the debt side of the balance sheet, total debts outstanding in the last 6 months as recorded on 

their credit record averaged $6,144 for all applicants. At baseline, roughly four in five applicants had 

revolving debt (for example, via a credit card), with a median of balance of $1,393 (for those with such 

debt). Roughly one-third had an auto loan, with a median balance of $11,276 and roughly one-fifth had 

student loan debt, with the median balance of $16,006. With respect to debt in collections, 35 percent 

of applicants had at least one collection outstanding on their credit record. This was the same as the 

share of all Americans with debt in collections (Ratcliffe et al. 2014).

The median asset level was $6,500 for all applicants. Most applicants had checking or savings 

accounts, and the median balance of those who did was $1,141 and $2,844 respectively. For the quarter 

of applicants with retirement accounts, the median amount was $10,000. Fewer applicants had 
A F F O R D A B L E H O M E O W N ER S H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S 3 3

investment accounts; those who did had a median balance of $7,651 (table 4.4). Although applicants’ 

net worth was low, the typical applicant saved some money to purchase a home. As of the program 

intake date, roughly two-thirds reported they had saved for a home purchase. When asked specifically 

how much of their assets were set aside to purchase a home, the median amount was $5,500. 

One key constraint in obtaining a mortgage is meeting lenders’ creditworthiness standards. The 

median borrower FICO score of all originated mortgages has hovered around 740 since June 2012 

(Urban Institute 2016). The median baseline credit score for applicants as reported by a major credit 

bureau was 696. While this is close to the median credit score for FHA borrowers (at roughly 680), 

buyers through these programs cannot make use of FHA-insured mortgages, per FHA’s implementation 

of its rules on shared equity loans. 

Also of interest, programs asked applicants at baseline to report their credit score if they knew it. 

Just over sixty percent of applicants reported a credit score, with the remaining indicating they did not 

know it. (Knowing ones credit score may indicate, among other things, that the applicant is further along 

in the mortgage finance process, and has checked his or her credit report.) 

TABLE 4.4 

Financial and Creditworthiness Characteristics of Shared Equity Program Applicants 

Financial characteristics N Mean Median

Household income 624 $42,743 $41,415

Household income / median family income 624 51%

Monthly housing costs 603 $837 $835

Monthly utilities 384 $175 $150

Housing cost burdened 468 49%

Net worth 605 $12,856 $712

Total debt 605 $ 20,495 $6,144

Revolving debt 456 $2,950 $1,393

Auto loan debt 208 $12,519 $11,276

Student loan debt 128 $22,805 $16,006

Credit utilization rate 605 26%

Any 90-to 180-day nonmortgage delinquencies 605 16%

At least one account in collections 605 35%

Total assets 683 $32,269 $6,500

Checking + savings balance 487 $12,264 $3,719

Retirement account balance 184 $30,139 $10,000

Investment account balance 66 $24,665 $7,651

Past foreclosure 683 2%

Savings for home purchase 500 $15,699 $5,500

Credit score 599 682 696

Credit score self-reported 680 61%

Sources: CHIP application data; credit bureau data. 

Notes: Data are given only for applicants with the type of account or debt specified. 
3 4 A F F O R D A B L E H O M E O W N E RS H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S

Neighborhood Characteristics 

The neighborhoods in which applicants lived varied across the sites with respect to poverty rate and 

median income. Among applicants, the average poverty rate for their baseline census tracts was 13

percent (table 4.5). The median income of tracts in which applicants lived was $61,125. 

On average, non-Hispanic whites accounted for about 55 percent of residents in applicant 

neighborhoods yet this proportion differed quite a bit by site. For example, Burlington stood out for its 

high share of white applicants. This was also the case for its surrounding MSA, as shown in appendix D. 

Washington DC; Nashville, and South Florida applicants lived in neighborhoods that had significantly 

higher shares of black residents than did their surrounding MSAs. Austin applicants lived in 

neighborhoods with greater shares of Hispanic residents than the overall MSA, but in South Florida 

applicants lived in neighborhoods with lower shares of Hispanics than the MSA. 

Shared equity applicants lived in neighborhoods where more one-third (34 percent) had a 

bachelor’s degree or higher (table 4.5). Applicants in Washington, DC, lived in neighborhoods with the 

highest percentage of college degree holders (51 percent) while the lowest was in South Florida (19 

percent). 

TABLE 4.5 

Characteristics of Shared Equity Program Applicants’ Neighborhoods

Neighborhood characteristics N Mean

Poverty rate 607 13%

Median household income 607 $61,125

Median occupied home value 602 $296,441

Homeownership rate 607 55%

White non-Hispanic 607 59%

Black non-Hispanic 607 15%

Hispanic 607 17%

Other non-Hispanic 607 3%

Bachelor’s degree or higher 607 34%

Sources: CHIP application data; US Census Bureau, American Community Survey (2010–14). 

Note: As a point of reference, these characteristics are displayed at the MSA-level, by site in appendix D. 
A F F O R D A B L E H O M E O W N ER S H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S 3 5

Chapter 5. Shared Equity Home 

Purchases 

In this chapter we describe “take-up” rates for the program and the baseline characteristics of 

applicants who purchased shared equity homes. We compared these shared equity buyers, at baseline, 

with those who did not purchase shared equity homes—a group comprised of nonpurchasers and 

people who bought homes, but not through the programs. Finally, we describe the financial 

characteristics of the shared equity transactions themselves. 

This study’s first research question is whether shared equity programs resulted in households being 

more likely to purchase homes than they would otherwise. Over one-third (36 percent) of shared equity 

applicants completed the process and purchased a home through the program. However, some 

applicants who did not purchase through a shared equity program ultimately purchased a home—about 

20 percent of all applicants (and 32 percent of those not buying through shared equity programs). These 

“other” purchases may have involved other subsidy or homeownership supports, or buyers may have 

used conventional mortgages without any external assistance. About 44 percent of applicants did not 

purchase a home at all. 

Not purchasing a home through the program is not necessarily a negative outcome. In some cases, 

an applicant being able to purchase a home through conventional means may be preferable because full 

appreciation accrues to the purchaser. Similarly, certain applicants may be better off not purchasing a 

home at all if they are not financially ready. Indeed, one benefit of a shared equity homeownership 

program may be helping applicants to determine when they should not purchase a home, thereby saving 

them from financial stress, delinquency, and foreclosure. 

Rates of purchasing shared equity homes varied by site from 21 percent in Austin to 52 percent in 

Nashville (table 5.1). Although Nashville had the highest rate, it also had one of the fewest numbers of 

applicants (29). South Florida, alternatively, had one of the highest numbers of applicants (114) but one 

of the lower rates of purchasing shared equity homes (22 percent). Burlington had the highest number 

of applicants (136) and one of the highest shared equity purchase rates, at 50 percent. It is worth 

acknowledging that the rate at which applicants purchased shared equity homes could vary according 

to several factors, including those having to do with the potential pool of applicants, but also 

programmatic ones like whether sites ask people to officially apply early or late in the process, and 

whether sites allow buyers to bring homes into the program (“buyer-driven” approaches).
3 6 A F F O R D A B L E H O M E O W N E RS H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S

TABLE 5.1 

Shared Equity Program Purchases by Site 

Applicants % Purchasers

Site N N % of Applicants

Austin, TX 111 23 21

Bay Area (San Francisco), CA 25 12 48

Burlington, VT 136 68 50

Long Island (Hauppauge), NY 48 15 31

Nashville, TN 29 15 52

Park City, UT 68 20 29

Seattle, WA 102 49 48

South Florida 114 25 22

Washington, DC 50 17 34

Total 683 244 36

Source: CHIP HomeKeeper administrative data. 

Home Purchasers 

To understand which applicants chose to purchase a home through a shared equity program and which 

did not, we first look at the baseline mean characteristics of shared equity purchasers, “other” 

purchasers, and nonpurchasers (table 5.2). We test for statistical differences in baseline characteristics 

controlling for site fixed effects, as more applicants purchased homes in some sites than in others. 

As shown below, shared equity purchasers were similar at baseline to the combined group of other 

purchasers and nonpurchasers. We observed no differences in age, gender, marital status, soleapplicant status, race, living arrangement, employment, income, housing costs, housing burden, net 

worth, debt levels, assets, credit scores, or neighborhood characteristics. Shared equity purchasers did 

pay less for utilities at baseline, were less likely to have at least one account in collections or a past 

foreclosure, were more likely to have completed a technical certification, and were more likely to selfreport their credit score. (Net worth and assets appear higher on average for shared equity purchasers 

than for all other applicants, but the differences were not statistically significant. The differences are 

driven by a few high asset applicants who purchased homes. We present the median values in appendix 

B.) 

Similarly, shared equity purchasers did not differ much from other purchasers on observable 

characteristics at baseline. There were no meaningful differences in most demographic or residential 

characteristics. So too with incomes, assets, debts, delinquencies, collections, foreclosures, credit 

scores, and several neighborhood attributes. The “other purchaser” group did have somewhat higher 
A F F O R D A B L E H O M E O W N ER S H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S 3 7

monthly utility costs, were somewhat more likely to be housing cost burdened, and lived in 

neighborhoods with lower home values, but higher homeownership rates. 

Shared equity purchasers and nonpurchasers who applied to shared equity programs also had 

similar demographic characteristics, incomes, debts, and neighborhood attributes at baseline. However, 

other measures showed that nonpurchasers were less ready to buy homes than those who bought 

shared equity homes (and those who bought homes apart from a shared equity program). For example 

19 percent of nonpurchasers had a nonmortgage 90- to 180-day delinquency at baseline, compared 

with 11 percent of shared equity purchasers. Fifty percent of nonpurchasers had an account in 

collections versus 23 percent of shared equity purchasers. Nonpurchasers had roughly half the amount 

saved for a home as shared equity purchasers. Nonpurchasers were also more likely to have had a 

foreclosure (3 percent versus 0.4 percent). 

TABLE 5.2 

Baseline Characteristics of Shared Equity Program Applicants by Home Purchase Status (Averages) 

Other Purchasers and Nonpurchasers

Shared

equity Other Non 

Statistic purchaser Combined purchaser purchaser

Demographics (%)

Age

Less than 30 20 21 24* 20

30–39 41 36 42 33

40–49 16 21 18 22

50–59 12 13 14 12

60 years or older 12 9 1*** 12

Female 55 61 51 66

Married 38 34 33 34

Sole applicant 60 67 65 67

Race

White non-Hispanic 54 39 50 34

Black non-Hispanic 22 23 19 25

Hispanic 9 24 17 28

Other non-Hispanic 15 14 15 13

Renter 81 80 82 79

Other/lives with family 15 17 14 19

Homeowner 4 3 4 2

Livesin studio or 1-bedroom home 25 21 23 20

Lives in 2-bedroom home 35 38 37 39

Lives in 3-bedroom home or larger 40 41 40 41

Educational Attainment

HS diploma or less 16 18 16 19

Technical certification 5 9*** 4 12***

Some college 16 18 22 17
3 8 A F F O R D A B L E H O M E O W N E RS H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S

Other Purchasers and Nonpurchasers

Shared

Statistic

equity

purchaser

Other Non 

Combined purchaser purchaser

College graduate 48 38 52 32

Employment

Fulltime 83% 81% 88% 77*

Parttime 8% 9% 6% 11**

Self employed

Other

4%

5%

6%

4%

4%

2%

6

6

Finances

Household income $44,192 $41,089 $44,190 $39,435

Household income/median family income (%)

Monthly housing costs

Monthly utilities

Housing cost burdened (%)

Net worth

54

$838

$98

37

$29,968

51

$838

$139**

49

$2,725

54

$893

$142**

48*

$7,641

49

$809

$137

49

-$79

Total debt $21,501 $19,900 $26,875 $15,923

Revolving debt

Auto loan debt

$2,444

$3,646

$2,094

$4,694

$2,759

$4,561

$1,714**

$4,769

Student loan debt $4,386 $5,085 $4,856 $5,216

Credit utilization rate (%)

Any 90-to 180-day nonmortgage delinquencies 

(%)

At least one account in collections (%)

Total assets

25

11

23

$49,101

27

18

43**

$22,915

27

17

31

$35,491

27

19*

50***

$17,088

Checking + savings balance

Retirement account balance

$4,088

$14,815

$2,685

$10,000

$2999

$12,830

$2,510

$8,191

Investment account balance $37,121 $12,941** $11,448** $13,756

Savings for home purchase

Past foreclosure (%)

Credit score

$20,406

0.4

704

$12,535

2*

669

$15,752

1

698

$10,552*

3*

653**

Credit score self-reported (%) 81 50** 71 41**

Census Tract Characteristics

Poverty rate (%)

Median household income

14

$62,448

13

$60,346

12

$62,868

13

$58,920

Median occupied home value

Homeownership rate (%)

White non-Hispanic (%)

Black non-Hispanic (%)

Hispanic (%)

Bachelor’s degree or higher (%)

$315,677

54

61

14

14

38

$285,204

56

57

16

18

33

$296,286*

58*

60

14

17

38

$278,956

54

56

17

19

30

Number of individuals 244 439 139 300

Sources: CHIP application data; CHIP HomeKeeper administrative data; US Census Bureau, American Community Survey (2010–

14); credit bureau data. 

Notes: Sample restricted to primary applicant only. T-stats are based on standard errors clustered at the site level. Sixty 

applicants were not matched to credit bureau data. Figures presented above are means. 

*** = significantly different from shared equity purchasers at 1 percent, ** = significantly different from shared equity purchasers 

at 5 percent, * = significantly different from shared equity purchasers at 10 percent. 
A F F O R D A B L E H O M E O W N ER S H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S 3 9

We next looked at a linear probability model to estimate which characteristics are associated with 

home purchase through a shared equity program rather than apart from the program or not at all (table 

5.3). We find that when we hold other variables constant, participants age 60 and older were 14.6 

percentage points more likely to purchase a home through a shared program than those younger than 

30. Participants who reported their credit score at baseline (an indication that they had checked their 

score recently, which may also be a proxy for readiness to buy) were also more likely to purchase a 

home through the program, this time by 23.8 percentage points. Conversely, applicants with a past 

foreclosure were 24.3 percentage points less likely to purchase a shared equity home, and those with a 

student loan were 7.4 percentage points less likely to purchase a shared equity home. Similarly, a ten 

percent increase in income was associated with a 19 percentage point decrease in probability of 

purchasing a shared equity home indicating that higher income individuals were less likely to purchase. 

Participants who applied to the program in 2012 were 18.1 percentage points more likely to purchase a 

home than those who applied in 2013, though the reasons for this are not clear. 

TABLE 5.3 

Predictors of Shared Equity Home Purchase Using Baseline Characteristics 

Characteristic Shared equity purchase

Age

Less than 30 [omitted]

30–39 0.0521

(0.0390)

40–49 -0.037

(0.055)

50–59 -0.010

(0.052)

60 or older 0.146*

(0.077)

Gender

Female -0.020

(0.035)

Marital status

Married 0.038

(0.047)

Race

White non-Hispanic [omitted]

Black non-Hispanic 0.002

(0.072)

Hispanic -0.099

(0.069)

Other -0.069

(0.050)

Educational Attainment b HS diploma or less [omitted]
4 0 A F F O R D A B L E H O M E O W N E RS H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S

Characteristic Shared equity purchase

Technical certificationb

b Some college

b College graduate

-0.080

(0.049)

0.010

(0.037)

-0.006

(0.047)

Financial characteristicsb Log of household income

b Log of monthly housing costs

Student loan

a Log of total assets

Past foreclosure

b Credit score

Credit score self-reported

-0.019***

(0.004)

0.001

(0.010)

-0.074*

(0.034)

0.011

(0.008)

-0.243***

(0.065)

0.000

(0.000)

0.238***

(0.053)

Neighborhood characteristics b Log of median occupied home value

b Percent with a bachelor’s degree or more

0.019

(0.059)

-0.078

(0.097)

Applied in 2012 0.181***

(0.045)

Observations

R-squared

Adjusted R-squared

610

0.239

0.191

Sources: CHIP application data; CHIP HomeKeeper administrative data; US Census Bureau, American Community Survey (2010–

14); credit bureau data.

Notes: Robust standard errors clustered at the site level are reported in parentheses. Site fixed effects are included. 

a

 dummy for zero included. 

b

 dummy for missing included. 

*** p<0.01, ** p<0.05, * p<0.1 

Shared Equity Transactions 

Shared equity home purchases are financed through a combination of subsidies, mortgage financing, 

and buyer cash investment (down payment), as illustrated in figure 5.1. The deployment of subsidies 

varies across organizations, but in all cases shared equity programs enable buyers to purchase homes 
A F F O R D A B L E H O M E O W N ER S H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S 4 1

for below the market value ensuring the home sells at a discount to the market value. This is done by 

capping the resale price or providing cash grants to the buyer, or some combination of the two. In either 

case, a portion of the shared equity subsidies remain with the home due to the resale restrictions. In 

addition to the shared equity subsidies, programs may provide, or buyers may access, other cash 

subsidies like grants and forgivable loans to make their homes more affordable. Combined, these forms 

of assistance represent the total subsidy in each sale. 

As a point of reference, we consider shared equity home purchases in the context of what the home 

would have sold for in the absence of a shared equity program. We refer to this hypothetical price as the 

“unrestricted market value.” This value is an estimate derived using available information about the 

home and other homes in the immediate area. For example, the home may be assessed by municipal 

assessors and assigned a value for tax purposes. Or “comp sales” of nearby homes may be used by the 

program to estimate the market value of a shared equity home.

As a share of the unsubsidized market price of their home, those who bought a home through a 

shared equity program received the equivalent of 37 percent of the home’s value in subsidies. The 

remaining 64 percent was paid for using a combination of cash investment and mortgage financing. 

Buyer subsidies are transfers to the homebuyer to support the home purchase, and include the 

following:

1. Grants, which can reduce the price of the home, serve as down-payment assistance, or serve as 

closing cost assistance;

2. Deferred loans, which do not accrue interest for a specified period;

3. Forgivable loans, which homebuyers only need to repay if they sell their home within a 

specified period, after which the forgivable loan behaves as a grant; and

4. Equity held by the program, which allows the program to maintain the below-market price of 

the home for future qualified homebuyers.20
4 2 A F F O R D A B L E H O M E O W N E RS H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S

FIGURE 5.1 

Shared Equity Purchase Financing 

Note: “Cash subsidy” includes additional buyer grants, forgivable mortgages, and deferred mortgages. 

Table 5.4 presents how shared equity purchasers in this study financed their purchases. The 

average unrestricted market value of homes purchased through shared equity programs was 

approximately $241,000. Buyer subsidies reduced the homebuyer’s price by 39 percent, worth on 

average roughly $94,000. After investing an average of about $11,000 in a down payment, homebuyers 

used mortgage financing to pay the remaining amount, roughly $138,000, or 57 percent of the 

unrestricted market value of homes. 

TABLE 5.4 

CHIP Purchaser Funding Sources 

Share of unrestricted 

Average amount market value (%)

Unrestricted market value $240,676 100

Buyer subsidy $94,292 39

Buyer cash investment $10,792 5

Buyer financing $137,864 57

Source: CHIP HomeKeeper administrative data. 
A F F O R D A B L E H O M E O W N ER S H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S 4 3

There were some notable differences by site (table 5.5). Some sites provided subsidy by discounting 

homes relative to the market value, while others made up the difference by offering grants directly to 

buyers. We found that some programs like in the Bay Area and Washington DC sold homes at a 

discount to market value and offered subsidies of 37 percent and 51 percent respectively. They paid for 

their homes through a combination of down payments and financing. On Long Island, on the other hand, 

buyers purchased homes primarily with grants and paid at or close to the market value. This type of 

program still allowed buyers to purchase homes at about 68 percent of their unrestricted value. 

The average first lien mortgage interest rate21 for shared equity homebuyers was 4.13 percent. For 

context, since 2010 average 30-year fixed mortgage rates have ranged from a high of 5.21 in April 

2010, to a low of 3.35 in May of 2013.22
4 4 A F F O R D A B L E H O M E O W N E RS H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S

TABLE 5.5 

CHIP Purchaser Funding Sources, by Site 

Bay Area, 

All Sites Austin, TX CA

Burlington, 

VT

Long 

Island, 

NY

Nashville, 

TN

Park 

City, UT

Seattle, 

WA

South 

Florida

Washington, 

DC

Unrestricted 

market value $240,676 $194,840 $496,163 $196,265 $282,080 $140,167 $256,583 $283,126 $207,011 $263,344

Buyer

subsidy 

% of 

unrestricted 

market value

$94,292

39.2

$78,153

40.1

$183,401

37.0

$59,918

30.5

$91,478

32.4

$27,509

19.6

$60,703

23.7

$147,379

52.1

$97,329

47.0

$134,479

51.1

Buyer cash 

investment

% of 

unrestricted 

market value

$10,792

4.5

$286

0.1

$62,539

12.6

$8,600

4.4

$12,377

4.4

$1,403

1.0

$34,120

13.3

$3,521

1.2

$1,461

0.7

$12,163

4.6

Buyer 

financing

% of 

unrestricted 

market value

$137,864

57.3

$116,401

59.7

$250,221

50.4

$135,433

69.0

$178,224

63.2

$111,254

79.4

$161,760

63.0

$132,226

46.7

$108220

52.3

$116,702

44,3

Source: CHIP HomeKeeper administrative data. 

Note: Unrestricted market value was recorded in

estimated market the value using square footage 

 HomeKeeper. H

of the home and

owever for reco

 price per square 

rds in Austin, B

foot data for t

ay Area, and So

he metro area.

uth Florida where unrestricted values were not available, we 
A F F O R D A B L E H O M E O W N ER S H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S 4 5

Chapter 6. Shared Equity Buyer 

Outcomes 

Shared equity programs may produce near-term financial benefits for those who would otherwise be 

unable to buy a home. And these programs may lead to financial gains over time, especially if they result 

in more manageable monthly payments. Programs may also help individuals purchase homes in 

neighborhoods with higher home values and education levels than they would have been able to 

otherwise. 

The approach typically considered most rigorous for understanding program effects is a 

randomized controlled trial (Theodos et al. 2014). In well-designed randomized control trials, those 

receiving an intervention are comparable in observable and unobservable ways to a control group of 

people not receiving the intervention. The shared equity programs could not randomize access to their 

homes, however. We thus needed to create comparison groups without the assurance that these 

individuals are comparable to shared equity buyers in the characteristics we cannot observe. 

As described in chapter 3, to get as full a picture as possible, we estimated outcomes for shared 

equity purchasers in three ways. First, we compared financial outcomes for shared equity purchasers 

with all program applicants who did not purchase a shared equity home. We also compared shared 

equity purchasers to applicants who purchased outside the program, looking at mortgage outcomes in 

addition to nonmortgage and neighborhood outcomes. Last, we compared shared equity purchasers to 

an entirely different group of purchasers who were not shared equity applicants but had similar 

observable characteristics at baseline; we examined mortgage, nonmortgage, and neighborhood 

outcomes for these groups. 

We found that shared purchasers had smaller mortgages than other applicant purchasers and that 

they had lower monthly payments on all credit accounts. There were no other differences in 

nonmortgage, mortgage, or neighborhood outcomes when comparing shared equity buyers to other 

applicants, or the subset of other applicants that purchased homes outside of the shared equity 

programs. When comparing shared equity purchasers to nonapplicant purchasers with similar 

observable characteristics, we again found that shared equity purchasers had smaller mortgages and 

had smaller monthly payments on all credit accounts. We also saw that they were less likely to have 

HELOCs, and had higher accounts in collections. All these results were robust to adjustments 
4 6 A F F O R D A B L E H O M E O W N E RS H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S

accounting for tests of multiple outcomes. After making such adjustments, we did not see differences in 

other financial and neighborhood metrics. 

Shared Equity Purchasers versus All Other Applicants 

We first compared shared equity purchasers with all other applicants who did not purchase a shared 

equity home. This group consists of both applicants who purchased a home outside of a program, and 

applicants who did not purchase at all. 

These findings are displayed in table 6.1. The first row “shared equity purchaser” displays the 

regression derived estimate of the association between shared equity purchasers (versus all other 

applicants) and the outcome in question, controlling for other factors. The second row displays the 

estimate of the association between the outcome variable measured at baseline and the outcome 

variable at follow-up. These estimates show that the model is working, at least in the sense that the 

baseline measures are strongly correlated with the outcome measure of interest. (Several other 

variables noted in the table, but not shown, were included as control variables in each model.) 

We found that shared equity purchasers showed no detectable differences in post-purchase credit 

score, credit utilization rate, revolving debt, nonmortgage delinquencies, or collections compared with 

all other applicants. In other words, the shared equity purchasers did no worse and no better, that we 

could detect, than applicants who did not purchase shared equity homes. There were also no detectable 

differences in the share of adults with a bachelor’s degree living in an applicant’s census track or the 

median occupied home value in the census tract, indicating that shared equity applicants did not move 

to neighborhoods that differed greatly from those in which non–shared equity purchasers lived at the 

end of the study. 
A F F O R D A B L E H O M E O W N E R S H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S 4 7

TABLE 6.1 

Financial Characteristics of Purchasers versus All Other Applicants 

Any 90-to 

Credit 180-day 

utilization Revolving nonmortgage 

Credit score rate debta delinquencies

At least one 

account in 

collections

% of 

neighborhood 

with a bachelor’s 

degree or more

Neighborhood 

median 

occupied home 

value

Shared equity 

purchaser

Dependent variable 

measured at 

baseline

2.136

(6.804)

0.662***

(0.034)

-0.038

(0.042)

0.219***

(0.058)

$182.5

($576.2)

$0.55***

($0.15)

-0.006

(0.033)

0.127*

(0.065)

0.009

(0.027)

0.384***

(0.061)

-0.018

(0.021)

0.495***

(0.044)

-$7,792

($9,649)

$79,513**

($32,780)

Observations

R-squared

574

0.591

568

0.251

568

0.219

568

0.214

568

0.540

610

0.570

567

0.605

Sources: CHIP HomeKeeper administrative data; US Census Bureau, American Community Survey (2010–14); credit bureau data. 

Notes: Robust standard errors clustered by site in parentheses for most variables. However, due to concerns about the small number of clusters, we report unclustered standard 

errors for the few cases in which those standard errors were larger. The regression-adjusted models include the following control measures: gender, age, race, education attainment, 

marital status, site dummies, log of total assets at baseline, whether applicant reported credit score on application, whether applicant had a past foreclosure, log of total monthly 

rent and utilities, baseline credit score, whether applicant had a student loan at baseline, log of household income, percent of baseline neighborhood with a bachelor's degree or 

more, log of baseline neighborhood median occupied home value, whether the applicant appeared as a purchaser in HomeKeeper data but not in credit bureau data, and whether 

the applicant applied in 2012 (versus later). 

a. Revolving debt does not include HELOCs. 

*** p<0.01, ** p<0.05, * p<0.1. 
4 8 A F F O R D A B L E H O M E O W N E RS H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S

Shared Equity Purchasers versus Other Applicant 

Purchasers 

We next compared shared equity purchasers to shared equity applicants who purchased outside of a 

program, the “other purchasers” described in chapter 4.23 These outside purchases could have included 

other forms of subsidy such as down payment assistance, or they could have been funded through 

traditional mortgages with no additional assistance. 

As in the above analysis, we did not detect that shared equity purchasers had higher or lower credit 

scores, credit utilization rates, revolving debt, or nonmortgage delinquencies than other applicant 

purchasers. These results are shown in table 6.2, which can be interpreted in a manner similar to table 

6.1. 

Turning to mortgage outcomes, we found that purchasing a shared equity home was associated 

with, on average, $36,346 less credit on open mortgage trades compared with other purchasers, 

indicating that shared equity purchasers were taking out smaller mortgages than applicants who 

purchased outside a program (table 6.2). Additionally, on average, shared equity purchasers paid $235

less on all credit accounts each month (including mortgages). These results were robust to the 

Bonferroni correction for multiple comparisons (which is described further in the following section). We 

found no differences between shared equity purchasers and all other purchasers on 90- to 180-day 

delinquencies on mortgages or number of open HELOCs. 

We also found no differences in neighborhood characteristics such as percentage with a bachelor’s 

degree and median occupied home value (table 6.2). Thus, while shared equity purchasers were getting 

smaller mortgages, we found they moved into similar neighborhoods as outside purchasers. 
A F F O R D A B L E H O M E O W N E RS H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S 4 9

TABLE 6.2 

Nonmortgage, Mortgage, and Neighborhood Characteristics of Shared Equity Purchasers versus Other Applicant Purchasers 

Any 90-to 180-day 

nonmortgage At least one account 

Credit score Credit utilization rate Revolving debta delinquencies in collections

Shared equity purchaser 2.121 -0.064 $-720.70 0.013 0.009

(8.694) (0.040) ($898.70) (0.036) (0.037)

Dependent variable 

measured at baseline 0.624*** 0.263** $0.53*** 0.197* 0.390***

(0.0637) (0.102) ($0.14) (0.0918) (0.036)

Observations 345 342 342 342 342

R-squared 0.580 0.360 0.260 0.273 0.571

Sources: CHIP HomeKeeper administrative data; US Census Bureau, American Community Survey (2010–14); credit bureau data. 

Notes: Robust standard errors clustered by site in parentheses for most variables. However, due to concerns about the small number of clusters, we report un-clustered standard 

errors for the few cases in which those standard errors were larger. The regression-adjusted models include the following control measures: gender, age, race, education attainment, 

marital status, site dummies, log of total assets at baseline, whether applicant reported credit score on application, whether applicant had a past foreclosure, log of total monthly 

rent and utilities, baseline credit score, whether applicant had a student loan at baseline, log of household income, percent of baseline neighborhood with a bachelor's degree or 

more, log of baseline neighborhood median occupied home value, whether the applicant appeared as a purchaser in HomeKeeper data but not in credit bureau data, and whether 

the applicant applied in 2012 (versus later). 

a. Revolving debt does not include HELOCs. 

*** p<0.01, ** p<0.05, * p<0.1 
5 0 A F F O R D A B L E H O M E O W N E RS H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S

TABLE 6.2 CONTINUTED 

Nonmortgage, Mortgage, and Neighborhood Characteristics of Shared Equity Purchasers versus Other Applicant Purchasers 

Any open % of 

Monthly HELOCs Any 90-to 180- neighborhood Neighborhood 

payment on Credit on open reported in the day mortgage with a bachelor’s median occupied 

credit accounts mortgage trades last 6 months delinquencies degree or more home value

Shared equity purchaser -$235** -$36,346** -0.008 0.001 -0.001 $12,072 

($94) ($13,848) (0.019) (0.015) (0.020) ($11,554)

Dependent variable

measured at baseline $0.35** $0.21 0.312*** -0.179 0.390*** $53,914 

($0.11) ($0.17) (0.0491) (0.0966) (0.0426) ($31,822)

Observations 342 342 342 342 350 343

R-squared 0.438 0.499 0.249 0.172 0.522 0.659

Sources: CHIP HomeKeeper administrative data; US Census Bureau, American Community Survey (2010–14); credit bureau data. 

Notes: Robust standard errors clustered by site in parentheses for most variables. However, due to concerns about the small number of clusters, we report un-clustered standard 

errors for the few cases in which those standard errors were larger. The regression-adjusted models include the following control measures: gender, age, race, education attainment, 

marital status, site dummies, log of total assets at baseline, whether applicant reported credit score on application, whether applicant had a past foreclosure, log of total monthly 

rent and utilities, baseline credit score, whether applicant had a student loan at baseline, log of household income, percent of baseline neighborhood with a bachelor's degree or 

more, log of baseline neighborhood median occupied home value, whether the applicant appeared as a purchaser in HomeKeeper data but not in credit bureau data, and whether 

the applicant applied in 2012 (versus later). The indicator “any foreclosures” was not able to run in this model given the lack of observations with a foreclosure. 

*** p<0.01, ** p<0.05, * p<0.1 
A F F O R D A B L E H O M E O W N E RS H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S 5 1

Shared Equity Purchasers versus Nonapplicant 

Purchasers 

Finally, we compared shared equity purchasers to nonapplicant home purchasers using a propensity 

score matching approach. Effective matching will balance observable baseline characteristics between 

the shared equity purchasers and the matched comparison group. In table 6.3, we explored how 

effectively this study matched shared equity home purchasers with the unmatched comparison group 

by comparing baseline characteristics. After restricting the analysis to individuals who were credit 

bureau home purchasers, the sample consisted of 186 shared equity purchasers, 301 individuals in the 

unmatched comparison group and 93 in the matched comparison group.24

In table 6.3, “Shared Equity Purchasers,”, “Unmatched Comparison Group,” shared equity 

purchasers,” “unmatched comparison group,” and “matched comparison group” show average 

characteristics of shared equity purchasers, unmatched nonapplicant home purchasers, and matched 

nonapplicant home purchasers, respectively, before the program intervention. For example, the share 

of individuals who had a credit score between 650 and 700 at baseline was 23.1 percent among the 

shared equity purchasers, 14.3 percent within the unmatched comparison group, and 21.5 percent 

within the matched comparison group. 

“Statistical differences: shared equity purchasers vs. unmatched group” tests whether shared 

equity purchasers and the unmatched comparison group had different baseline characteristics. Shared 

equity purchasers had significantly lower credit scores, were younger on average, had lower incomes, 

and had lower revolving debt than the unmatched group of home purchasers. This difference most likely 

reflected that the programs targeted less well-off populations with limited access to mortgages. In 

addition, shared equity purchasers were more likely to live in areas that have higher shares of nonHispanic blacks. 

“Statistical differences: shared equity purchasers vs. matched group” tests whether shared equity 

purchasers and the matched comparison group had different baseline characteristics. We observed that 

the matched group was not statistically different from the shared equity group in all baseline 

characteristics.25
5 2 A F F O R D A B L E H O M E O W N E RS H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S

TABLE 6.3 

Test of Balancing Covariates 

Baseline 

Shared Unmatched Matched 

Baseline means

equity

purchasers

comparison 

group

Statistical 

difference

comparison 

group

Statistical 

difference

Individual characteristics

Credit score distribution (%)

<650 17.7 19.3 20.4

650–699 23.1 14.3 ** 21.5

700–749 23.1 20.6 19.9

750–799 26.3 27.2 24.7

≥800 9.7 18.6 *** 13.4

Age 36.1 41.9 *** 36.5

Household income $40.516 $49,192 *** $39,037

Credit utilization rate (%) 24.4 27.2 20.0

Revolving debt $2,731 $4,651 *** $2,178

Any 90-to 180-day 

delinquencies(%)

nonmortgage 9.7 10.3 10.2

Monthly payment on credit accounts $332 $438 $330

Student loan (Y/N) 21.5% 20.9% 26.3%

At least one account in collections 19.4% 21.3% 19.9%

Neighborhood characteristics (census tract level)

% of neighborhood with a 25.9 bachelor's degree or more 27.0 27.1

Neighborhood median occupied $326,576 home value $307,133 $314,737

Neighborhood racial/ethnic 

Black non-Hispanic

composition (%)

12.1 6.7 *** 14.0

Hispanic 12.6 11.1 9.2

Observations 186 301 93

Sources: CHIP HomeKeeper administrative data; US Census Bureau, American Community Survey (2010–14); credit bureau 

data. 

Notes: Propensity score is estimated using a Probit model with the following control variables at baseline: credit score, age and 

income as reported by the credit bureau, credit utilization rate, revolving debt, nonmortgage delinquency debt, indicator of 

student loans, at least one account in collections, monthly payment on credit accounts, any open home equity line, credit amount 

on open mortgage, mortgage delinquency, share of adults at each education level, share of population that is black, share of 

population that is Hispanic, median occupied home value, and site dummies. We used a nearest neighbor matching with 

replacement matching approach. 

*** p<0.01, ** p<0.05, * p<0.1 

Table 6.4 compares the outcomes of shared equity purchasers and the matched comparison group. 

In terms of mortgage outcomes, shared equity purchasers have on average significantly less mortgage 

credit than their matched counterparts. Though participants have on average $143,988 in credit on 
A F F O R D A B L E H O M E O W N E RS H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S 5 3

open mortgage type trades, home purchasers in the matched comparison group have on average 

$224,780. This result most likely reflects the design of CHIP programs, in which shared equity 

applicants have access to subsidized housing and therefore lower housing costs. We did not observe 

any statistically significant difference in delinquency or rates of foreclosures on mortgages between 

these two groups, meaning that shared equity purchasers paid their mortgage debts as regularly as the 

matched comparison group. We found that shared equity purchasers were appreciably less likely to 

have a HELOC than the matched comparison group. Only 1 percent of shared equity purchasers had an 

open HELOC reported in their credit files compared to 17 percent of individuals in the matched 

comparison group. Several shared equity programs do not allow participants to take out HELOCs or 

other additional financing on their purchased homes.

While shared equity purchasers had on average $1,304 in monthly payments on credit accounts, 

purchasers in the matched comparison group had $1,950 in monthly payments on credit accounts. The

lower monthly payments by shared equity applicants can be explained by smaller mortgage amounts 

since mortgage payments are included in credit account payments.

Beyond these outcomes, we also compared measures of financial standing for shared equity 

purchasers and the matched group. We did not observe any statistical difference between these two 

groups in their revolving debt, and nonmortgage delinquencies. While the average credit score of 

shared equity purchasers increased from baseline to follow-up, it did so by less than did the matched 

comparison group, meaning that at follow-up, credit scores were lower for shared equity purchasers 

than other purchasers. However, credit utilization rates—an indicator of how much debt consumers use 

relative to the debt they have available—were lower at follow-up for shared equity buyers than the 

matched comparison group. Like with credit scores, the share of shared equity purchasers with at least 

one account in collections went down from baseline to follow-up, but less than the matched comparison 

group, meaning that at follow-up, shared equity purchasers were more likely to have an account in 

collections.

We also compared the average characteristics of neighborhoods (census tracts) of shared equity 

purchasers and the matched comparison group and did not find that neighborhood education levels or 

neighborhood home values were significantly different between the two groups. Shared equity 

applicants lived, on average, in neighborhoods where 23 percent of adults had a bachelor’s degree or 

more and the median home value was about $293,000. The matched comparison group lived, on 

average, in areas where 25 percent of adults had at least a bachelor’s degree and the median home 

value was about $270,000. These results were not statistically different. The results indicate that the 
5 4 A F F O R D A B L E H O M E O W N E RS H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S

restriction on housing supply for program participants did not make them more likely to live in lowerincome neighborhoods than their counterparts. 

TABLE 6.4 

Follow-up Outcomes for Shared Equity Purchasers versus a Matched Comparison Group 

Shared Matched 

equity comparison Standardized 

Means purchasers group Difference Effect Size

Credit score

Credit utilization rate (%)

Revolving debt

Any 90-to180-day nonmortgage 

delinquencies (%)

At least one account in collections (%)

Monthly payment on credit accounts

Credit on open mortgage trades

Any open HELOCs reported in the last 6 

months (%)

Any 90-to180-day mortgage delinquencies 

(%)

Any foreclosure (%)

% of neighborhood with a bachelor’s degree

or more

Neighborhood median occupied home value

724

22.5

$4,475

7.0

13.44

$1,304

$144,042

1.1

2.2

0.0

23.3

$292,639

737

27.0

$5,444 

10.2

4.30

$1,950 

$224,780 

17.2

2.2

0.5

24.6

$269,797

-13.48*

(7.85)

-4.63**

(2.25)

-$969

($871)

-3.23

(3.29)

9.14***

(2.07)

-$646***

($117)

-

$80,738***

($13,019)

-16.13***

(4.37)

0.0

(2.02)

-0.54

(0.54)

-1.41

(1.33)

$22,780

($17,406)

-0.13

-0.17 

-0.14

-0.11

0.32

-0.71

-0.74

-0.56

0.00

-0.10

-0.15

-0.06

Observations 186 93

Sources: CHIP HomeKeeper administrative data, US Census Bureau, American Community Survey (2010–14); credit bureau 

data. 

Notes: Propensity score is estimated using a Probit model with the following control variables at baseline: credit score, age and 

income as reported by the credit bureau, credit utilization rate, revolving debt, nonmortgage delinquency debt, indicator of 

student loans, at least one account in collections , monthly payment on credit accounts, any open home equity line, credit amount 

on open mortgage, mortgage delinquency, share of adults at each education level, share of population is black, share of population 

that is Hispanic, median occupied home value, and site dummies. We used a nearest neighbor matching with replacement 

matching approach. Standard errors are estimated using the expression derived in Abadie and Imbens (2006). 

*** p<0.01, ** p<0.05, * p<0.1 
A F F O R D A B L E H O M E O W N E RS H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S 5 5

It is possible to detect statistical significance errantly by chance, all the more when conducting 

multiple statistical tests. As the number of outcomes increases, so too does the likelihood of a Type I 

error, or incorrectly finding significance when it does not exist. To account for this, we estimated 

significance levels of these same outcomes using the Bonferroni correction for multiple comparisons, 

which corrects for the number of variables within larger groups of outcomes (table 6.5).

Using this correction, we found that shared equity purchasers had lower credit on open mortgage 

trades, lower monthly payments on credit accounts and, and lower likelihood of having a home equity 

line of credit. However, the relationship between shared equity and credit score was no longer 

significant, nor was utilization rate. But, the likelihood of having at least one account in collections was 

still significant for shared equity purchasers. Of course, all these outcomes were measured in the 

relatively near-term, and a longer-term study will be needed to investigate whether the lower mortgage 

costs for shared equity buyers translate into more secure financial standing relative to other buyers. 

TABLE 6.5 

Multiple Comparisons Analysis for Shared Equity Purchasers versus a Matched Comparison Group 

Outcomes

Unadjusted P- Bonferroni correction 

value significance level

Financial

Credit score

Credit utilization 

Revolving debt

rate (%)

0.086

0.040

0.266

Loan Performance 

Any 90-to180-day nonmortgage delinquencies 

At least one account in collections (%)

(%) 0.327

0.000 ***

Mortgage Amount 

Monthly payment on credit accounts

Credit on open mortgage trades

0.000

0.000

***

***

Mortgage Performance 

Any open HELOCs reported in the last 6 months 

Any 90-to180-day mortgage delinquencies (%)

Any foreclosure (%)

(%) 0.000

1.000

0.321

***

Neighborhood 

% of neighborhood with a bachelor’s degree or 

Neighborhood median occupied home value

more 0.287

0.191

Sources: CHIP HomeKeeper administrative data, US Census Bureau, American Community Survey (2010–14); credit bureau 

data. 

Notes: P-values from estimated using a Probit (propensity score) model. Control variables described in table 6.4. We used a 

nearest neighbor matching with replacement matching approach. 
5 6 A F F O R D A B L E H O M E O W N E RS H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S

Chapter 7. Implications for Practice 

and Policy 

Shared equity homeownership has the potential to create affordable and sustainable ownership 

opportunities for low- and moderate-income families. Many applicants in this study’s sample were able 

to buy shared equity homes (36 percent). The subsidies for the shared equity homes were sizeable—an 

average of $94,292, or 39 percent of the homes’ value. Shared equity buyers had average incomes at 

baseline of 51 percent of the area median family income, lower than many homeownership supports. 

Together, these facts indicate that shared equity programs were serving their core mission of linking 

low- and moderate-income people with affordable owner-occupied housing. 

The finding most notable across the different comparisons was that shared equity purchasers had 

lower mortgages and lower monthly payments than comparable buyers. At the point of follow-up, we 

found that shared equity purchasers performed largely the same as other applicants and the matched 

comparison group in terms of their other financial and neighborhood outcomes. Apart from accessing 

smaller mortgages, more time may be needed to understand whether and how shared equity 

purchasers are better or worse off financially compared with other buyers. 

A fairly high proportion of those who did not buy a shared equity home purchased a home outside 

of the program (20 percent of all applicants). This may be appropriate sorting: people who do not need 

all the help shared equity gives should not accept it because they would be trading a sizable portion of 

the upside of their investment. The outside purchasers might suggest that the trade-offs between the 

subsidy and the long term equity are working. If no one had purchased outside of the programs, we 

might worry that the subsidy is actually too large, and that some of those households should have been 

purchasing on the conventional market. Some applicants did purchase outside of the programs and 

shared equity purchasers had low incomes as a percentage of median family income, suggesting that the 

programs are appropriately targeting those who need it. 

The remaining applicants who did not buy any home were not able to buy, or their circumstances 

changed, and they were no longer interested. This may actually be a positive effect; discouraging people 

who are not ready to purchase a home from doing so, thus preventing future financial distress. 

Alternatively, it may well be the case some applicants would have benefited from greater help. 

In particular, potential buyers might have benefitted from additional counseling. The credit market 

for mortgages is quite tight by historical standards. In 2015, lenders failed to make about 1.1 million 
A F F O R DA B L E H O M E O W N E R S H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S 5 7

mortgages that they would have if conventional lending standards had been in place.26 Shared equity 

helps lower monthly payments, but does not typically decrease credit standards for first mortgages. In 

this sample, about 29 percent of applicants at intake had a credit score below 680—a level below which 

conventional mortgages were not widely available during this time. This suggests that credit counseling 

or credit-repair services may broaden the pool of potential homebuyers. Recent research shows that 

financial coaching can help individuals increase savings, pay off debt, and raise their credit scores, 

suggesting that this approach could help shared equity applicants prepare for home purchase as well 

(Theodos, Simms et al. 2015). 

Future Research 

Assessing the impacts of homeownership can be a challenging endeavor because randomization is 

rarely possible and personal choice is involved in the decision to buy a home. For example, researchers 

have long been trying to determine what effect homeownership has on child outcomes, and they still 

disagree in many respects. Several studies found that homeownership was associated with positive 

youth outcomes such as increased years of schooling, reductions in teenage pregnancies, higher 

cognitive test scores, fewer behavioral problems, and higher income later in life (Boehm and 

Scholttmann 1999; Boyle 2002; Green and White 1997; Haurin, Parcel, and Haurin 2002). However, 

other studies have found that once other factors are controlled for, the benefits of homeownership 

disappear (Barker and Miller 2009; Holupka and Newman 2012; Mohanty and Raut 2009). 

Here too determining the true causal effect of shared equity programs on buyer outcomes is 

difficult, as shared equity buyers may differ in unobservable ways from applicants who chose not to buy 

and those who bought apart from the programs. However, by combining all these comparisons into one 

study, we investigated the relationships between shared equity programs and buyer outcomes. We 

could control for a robust set of baseline conditions, including baseline measures of the outcome 

variables of interest, thus removing some of our concerns about bias. Our study also followed the Great 

Recession, and thus does not reflect that atypical period in the housing market. And the study included 

a wide range of programs and housing markets. 

More research is needed, though, to explore the causal relationship between shared equity and 

buyer outcomes, such as via a randomized controlled trial. A promising approach would be to leverage 

the opening of a large development for which demand exceeds supply and for which a lottery 

represents the fairest means of distributing the scarce resource of shared equity housing subsidies. This 
5 8 A F F O R D A B L E H O M E O W N E RS H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S

sort of approach would be especially helpful in establishing the extent to which these programs create 

more homeowners than would happen absent the existence of this form of subsidy. 

Other questions remain as well. Most important in our minds is whether the benefits of reduced 

mortgage costs redound in meaningful ways to owners over time. It is possible that these buyers will 

subsequently differentiate themselves from other buyers in their levels of savings, debt, financial stress, 

and mortgage delinquency and foreclosure. This study was only able to observe buyers through June 

2016; longer-term follow-ups would be useful. 

Neighborhood outcomes also merit further investigation. For some programs, it is plausible that 

shared equity approaches allow for low- and moderate-income households to buy homes in more 

expensive neighborhoods than they could otherwise afford. However, some programs in this study 

brought homes online through funding sources that may not have prioritized more affluent 

neighborhoods, or even that actively targeted distressed neighborhoods, such as the Neighborhood 

Stabilization Program. 

A Growing Field 

Through this study, and as recorded in our baseline report (Theodos, Temkin, et al. 2015), we heard staff 

articulate that shared equity programs must become larger to be more financially sustainable. Across 

the country, many shared equity programs manage or own only a few units. Representatives of the 

shared equity programs in this sample estimated they require about 300 units in portfolio to generate 

sufficient revenue to cover annual operating expenses. But scaling up requires additional subsidy and 

subsidy remains a challenge. Bringing homes into a shared equity program while preserving 

affordability is expensive. Inclusionary zoning is growing, and remains a good tool for hot-market cities. 

But this approach is not likely to be sufficient in these rapidly appreciating markets, nor will it be the 

solution for mid- and cool-market cities. Thus, accessing sufficient subsidy will be critical, but it is hard 

to imagine such funding emerging at large levels in a constrained spending environment. 

Moreover, although shared equity programs have been in place for more than 30 years, the concept 

is still unfamiliar to many real estate agents, lenders, and prospective buyers. As a result, real estate 

agents may be hesitant to list shared equity properties or show them to their clients. Buyers are largely 

unaware of these approaches. And historically, lenders could not use their standard mortgage products 

for shared equity transactions, and such loans were not salable to the secondary market. Most can now 

use Fannie Mae’s Desktop Underwriter, however, and are purchased by Fannie Mae. Further, with the 
A F F O R DA B L E H O M E O W N E R S H I P : A N E V A L U A T I O N O F S H A R E D E Q U I T Y P R O G R A M S 5 9

recently proposed Duty to Serve regulatory language including shared equity mortgages as “affordable 

housing preservation” lending, borrowers may be even more able to access financing for these loans. 

Given challenges of scale, are other approaches available? Wall Street has shown increasing 

interest in creating privately financed equity-sharing models.27 Such developments could quickly enable 

far more people purchase homes than will be possible through community land trusts, inclusionary 

zoning, limited equity cooperatives, and the like. But, these market-driven approaches will not preserve 

affordability over successive borrowers and questions remain about whether and how they can be 

established and sustained in a manner that best serves consumers while generating a reasonable return 

for investors. 

Homeownership has fallen to its lowest level since 1965. Although important questions remain, this 

study offers evidence that shared equity models provide homeownership opportunities to lowerincome households with less debt than they could otherwise achieve.
6 0 A P P E N D I X A

Appendix A. Codebook 

TABLE A.1 

Codebook for the Cornerstone Homeownership Innovation Partnership Evaluation 

Variable Description Source

Date Date of application CHIP application data 

Applied in 2012

1 Applicant applied to 

2012

a shared equity program in 

CHIP application data

Application street Baseline address - street CHIP application data 

Application city Baseline address - city CHIP application data 

Application state Baseline address - state CHIP application data 

Application zip Baseline address - zip code CHIP application data 

Sole applicant Applicant did not apply with co-applicant CHIP application data 

1. Renter

Tenure status

2. Other/live with family

3. Homeowner CHIP application data 

1. Studio or 1 bedroom 

Number of bedrooms in 2. 2 bedrooms home

current home 3. 3 bedrooms or more CHIP application data 

Monthly housing costs Self-reported monthly housing costs CHIP application data 

Housing cost burdened

Monthly 

monthly 

housing 

income

cost greater than 30 percent of gross 

CHIP application data

Monthly utilities Self-reported monthly utilities cost CHIP application data 

Log of monthly costs Log(monthly housing and utility costs CHIP application data 

1. Less than 30 

2. 30-39 

3. 40-49 

4. 50-59 

Age 5. 60 or older CHIP application data 

Female Applicant is female CHIP application data 

Race

1. White non-Hispanic 

2. Black non-Hispanic 

3. Hispanic

4. Other non-Hispanic (American Indian, Alaska 

Native, Asian, Native Hawaiian, or Pacific Islander) CHIP application data 

Ethnicity

1.

2.

Hispanic

Not Hispanic CHIP application data 

Marital status

1 if applicant is married 

separated, or widowed)

(not single, divorced, 

CHIP application data 

1. HomeBase, Austin, TX

2. Champlain Housing Trust, Burlington, VT

3. City First Homes, Washington, DC

4. South Florida Consortium, FL

Site

5. Hello Housing, Bay Area (San Francisco), CA

6. Long Island Housing Partnership, Long Island 

(Hauppauge), NY

7. Mountain Lands Community Housing Trust, Park 

City, UT

8. The Housing Fund, Nashville, TN

9. Homestead CLT, Seattle, WA CHIP application data 

Employment status 1. Fulltime CHIP application data 
A P P E N D I X A 6 1

Variable Description Source

2. Parttime

3. Self employed

4. Other

Occupation

Self-reported occupation, manually 

industry codes

matched to 

CHIP application data 

Household income Self-reported gross annual household income CHIP application data 

Household income divided by 

median family income Household income divided by median family income CHIP application data 

Total assets

Self-reported checking account balance plus savings 

account balance, plus retirement account balance, plus 

investment account balance, plus real estate assets, 

plus CDs, plus other assets CHIP application data 

Checking + savings balance

Self-reported checking 

account balance

account balance plus savings 

CHIP application data 

Retirement account balance Self-reported retirement account balance CHIP application data 

Investment account balance Self-reported investment account balance CHIP application data 

Net worth Total assets − total debts

CHIP application data; 

credit bureau data

Credit score self-reported 1 if applicant reported credit score on application CHIP application data

Savings for home purchase

Self-reported amount saved specifically 

home (down payment, closing costs)

for buying a 

CHIP application data 

1.

2.

High school diploma or 

Technical certification

less

Education attainment

3.

4.

Some college

College graduate CHIP application data 

Past foreclosure

reported)

(self- 1 if applicant has ever been 

process (self-reported)

involved in the foreclosure 

CHIP application data 

Shared equity purchaser

1 if the individual purchased a home through 

equity program during the study period

a shared CHIP HomeKeeper 

administrative data

Value of the home if it were available on the 

Unrestricted market value

unrestricted open market; estimated using list price 

per square foot data in Austin, the Bay Area, and South 

Florida

CHIP HomeKeeper 

administrative data

Noncash subsidy

The amount of home equity held by the shared equity 

organization; the difference between the purchase 

price and the home’s appraised unrestricted market 

value

CHIP HomeKeeper 

administrative data

Noncash subsidy percentage

Noncash subsidy 

market value

as a percentage of unrestricted CHIP HomeKeeper 

administrative data

Cash subsidy

Cash transfers to the homebuyer to support the 

purchase, to include grants, deferred loans, and 

forgivable loans

home 

CHIP HomeKeeper 

administrative data

Cash subsidy percentage

Cash subsidy 

value

as a percentage of unrestricted market CHIP HomeKeeper 

administrative data

Buyer cash investment

The amount that the homebuyer 

home's down payment

contributed to the CHIP HomeKeeper 

administrative data

Buyer cash 

percentage

investment Buyer’s cash investment as 

unrestricted market value

a percentage of CHIP HomeKeeper 

administrative data

Buyer financing

The amount of mortgage and other financing used by 

the buyer to purchase the home (not including 

forgivable and deferred mortgages)

CHIP HomeKeeper 

administrative data

Buyer financing percentage

Buyer’s 

value

financing as a percent of unrestricted market CHIP HomeKeeper 

administrative data

Median family income Median family income of the metropolitan statistical HUD
6 2 A P P E N D I X A

Variable Description Source

area

2010–2014 American 

Percent white non-Hispanic Share of tract population that is non-Hispanic, white Community Survey

2010–2014 American 

Percent black non-Hispanic Share of tract population that is non-Hispanic, black Community Survey

2010–2014 American 

Percent Hispanic Share of tract population that is Hispanic Community Survey

2010–2014 American 

Median occupied home value Median occupied home value in tract Community Survey

2010–2014 American 

Homeownership rate Share of occupied homes that are owner occupied Community Survey

Percentage with a 

degree or more

bachelor’s Share of tract population over age 25 whose 

level of education is a bachelor's degree

highest 2010–2014 

Community 

American 

Survey

Poverty rate

Share 

level

of families in tract below the federal poverty 2010–2014

Community 

American 

Survey

2010–2014 American 

Median household income Median household income in tract Community Survey

Credit score

Vantage V3 score. When individuals are scoreable 

using both models, Vantage and FICO scores are 

generally comparable. Credit bureau data

Home purchaser

1 if observation’s mortgage debt increased by more 

than $10,000 during the study period, if their months 

since an opened mortgage at the end of the study was 

less than the study period, or if their number of 

mortgage trades increased by at least 1 during the 

study period. Credit bureau data

Total debt

Total balance on 

six months

credit accounts reported in the last 

Credit bureau data

Any 90-to180-day 

nonmortgage delinquencies

1 if the individual showed one or more occurrence of 

90-to 180-day delinquencies on nonmortgage trades Credit bureau data

Monthly payment on 

accounts

credit Total monthly payment on credit accounts

the last six months (including mortgages)

reported in 

Credit bureau data

At least one account in 

collections 1 if one or more trades are in collections Credit bureau data

Number of open home 

line of credit in last six

equity 

months

Total number of open home equity 

reported in the last 6 months

line of credit trades 

Credit bureau data

Any 90-to 180-day 

delinquencies

mortgage 

1 if one or more occurrence of 90-to 180-day 

delinquency in the last 24 months on mortgage 

trades (excluding unsatisfied derogatory)

type 

Credit bureau data

Credit on open mortgage 

trades in last six months

Total credit amount on open mortgage 

reported in the last six months

type trades 

Credit bureau data

Any foreclosures 1 if foreclosed first mortgage trades Credit bureau data

Revolving debt

Total balance on open revolving trades reported in the 

last six months minus total balance on open HELOC

trades reported in the last six months Credit bureau data

Credit on open revolving 

in last six months

trade Total credit amount on 

in the last six months

open revolving trades reported 

Credit bureau data

Credit utilization rate Revolving debt/credit on open revolving trades Credit bureau data

Student loan debt

Total balance on open nondeferred student trades 

reported in the last six months Credit bureau data

Auto loan debt

Total balance on open auto loan 

reported in the last six months

or lease trades 

Credit bureau data
A P P E N D I X B 6 3

Appendix B. Baseline Medians by 

Purchase Status 

TABLE B.1 

Baseline Characteristics of Shared Equity Program Applicants by Home Purchase Status (Medians) 

Other Purchasers and Nonpurchasers

Sh. Eq. Other 

Statistic purchaser Combined purchaser Nonpurchaser

Finances

Household income $42,449 $40,000 $43,690 $38,400

Household income / median family income 

(%) 52 50 52 48

Monthly housing costs $825 $845 $878 $800

Monthly utilities $75 $119 $120 $117

Net worth $1,945 $0 $1,376 $0

Total debt $5,440 $7,224 $10,713 $4,961

Revolving debt $795 $681 $1,062 $480

Auto loan debt $0 $0 $0 $0

Student loan debt $0 $0 $0 $0

Credit utilization rate (%) 12 15 19 11

Total assets $9,059 $5,200 $10,300 $2,450

Checking/savings $1,361 $1,000 $1,247 $1,000

Retirement account $3,788 $2,080 $4,248 $1,398

Investment account $11,040 $5,928 $5,928 $6,463

Savings for home purchase $7,000 $5,000 $8,000 $3,000

Credit score 713 683 707 655

Census tract characteristics

Poverty rate (%) 10 9 8 10

Median household income $60,000 $57,804 $58,666 $57,049

Median occupied home value $279,700 $254,800 $266,600 $246,900

Homeownership rate (%) 54 57 60 57

White non-Hispanic (%) 70 66 67 64

Black non-Hispanic (%) 5 6 6 6

Hispanic (%) 7 11 11 11

Bachelor’s degree or higher (%) 39 32 39 29

Number of individuals 244 439 139 300

Sources: CHIP application data; CHIP HomeKeeper administrative data; US Census Bureau, American Community Survey (2010–

14); credit bureau data. 

Notes: Sample restricted to primary applicant only. T-stats are based on standard errors clustered at the site level. Sixty 

applicants were not matched to credit bureau data. Figures presented above are means. 
6 4 A P P E N D I X C

Appendix C. Minimum Detectable 

Effects 

In this appendix, we present the minimum detectable effects we can obtain in our estimations given a 

power level, significance level, sample size, and mean and standard deviation of the comparison group. 

The minimum detectable effect tells us the smallest effect on the outcome detectable for a given level of 

power and statistical significance. The power of the test is the probability that we will be able to reject 

the hypothesis of zero effect for a given effect size and a given statistical significance level. Sample 

sizes, as well as other design choices, will affect the power of a statistical test. 

We present this power analysis for a few example metrics as illustrations: credit utilization rate, 

revolving debt, and any 90- to 180-day nonmortgage delinquency. The same logic would apply to all 

outcomes we analyze; we expect these three will provide the reader with a general sense of our ability 

to detect effects in this study. We conduct power calculations for a 10 percent significance level and 80 

percent power level. 

We first calculate the minimum detectable effects for the sample used in table 6.1. The estimation 

compares the outcomes between shared equity purchasers and all other applicants. Given the sample 

size and characteristics of the comparison group, we would be able to detect statistical difference 

greater than 6.9 percent for credit utilization rate, $1,161 for revolving debt, and 7.5 percent for any 

90- to 180-day nonmortgage delinquency at a 10 percent significance level (table C.1). All differences 

estimated in table 6.1 are lower in magnitude than these minimum detectable effects, and therefore are 

not statistically significant. 

TABLE C.1 

Minimum Detectable Effects, Shared Equity Purchasers versus All Other Applicants 

Number of 

Observations Comparison Group

Comparison/ Std. 

treatment Mean deviation Minimum detectable effect

Credit utilization rate 380/225 0.295 0.329 0.069

Revolving debt 380/225 $3,690 $5,544 $1,161

Any 90-to 180-day 

nonmortgage delinquency 380/225 0.153 0.360 0.075

Source: Credit bureau data. 

Note: We use a 10 percent significance level and 80 percent power level in the minimum detectable effects calculations. 
A P P E N D I X C 6 5

We now turn to the sample used in the estimations presented in tables 6.2 and 6.3, which compare 

the outcomes between shared equity purchasers and other applicant purchasers. From this power 

analysis, we would be able to detect statistical difference greater than 8.5 percent for credit utilization 

rate, $1,778 for revolving debt, and 7.0 percent for any 90- to 180-day nonmortgage delinquency at a 

10 percent level between these two groups (table C.2). All differences estimated in table 6.2 are lower 

in magnitude than these minimum detectable effects, and therefore are not statistically significant at a 

10 percent level. 

TABLE C.2 

Minimum Detectable Effects, Shared Equity Purchasers versus Other Applicant Purchasers 

Number of 

Observations Comparison Group

Comparison/ Minimum 

treatment Mean Std. deviation detectable effect

Credit utilization rate 138/225 0.322 0.317 0.085

Revolving debt 138/225 $5,455 $6,600 $1,778

Any 90-to 180-day 

nonmortgage 

delinquency 138/225 0.073 0.260 0.070

Source: Credit bureau data. 

Note: We use a 10 percent significance level and 80 percent power level in the minimum detectable effects calculations. 

Finally, we calculate minimum detectable effects for the sample used for the estimations in table 

6.5. In this estimation we compare outcomes between shared equity purchasers and a matched 

comparison group of nonapplicant purchasers. Given the sample size and characteristics of the 

comparison group, we would be able to detect statistical difference greater than 8.5 percent for credit 

utilization rate, $2,199 for revolving debt, and 8.8 percent for any 90- to 180-day nonmortgage 

delinquency at a 10 percent level (table C.3). All differences estimated in table 6.5 are lower in 

magnitude than these minimum detectable effects and therefore are not significant. 
6 6 A P P E N D I X C

TABLE C.3 

Minimum Detectable Effects, Shared Equity Purchasers versus Matched Comparison Group 

Number of 

Observations Comparison Group

Comparison/ Minimum detectable 

treatment Mean Std. deviation effect

Credit utilization 

rate 186/186 0.270 0.290 0.085

Revolving debt 186/186 $5,444 $7,551 $2,199

Any 90-to 180-day 

nonmortgage 

delinquency 186/186 0.102 0.304 0.088

Source: Credit bureau data. 

Note: We use a 10 percent significance level and 80 percent power level in the minimum detectable effects calculations. 

Individuals in the matched comparison group are weighted by the numbers of matched shared equity home purchasers. For 

example, an individual in the comparison group matched to three shared equity home purchasers receives a weight of three in the 

statistical calculations. 
Appendix D. Regional Demographic 

Characteristics
6 8 A P P E N D I X D

TABLE D.1 

Characteristics of Regional Demographic Characteristics, by Site 

Neighborhood 

characteristics

Austin, 

TX

(AustinRound 

Rock, TX 

Metro 

Area)

Bay Area, Burlington, Long Island, 

CA (San VT NY (New 

Francisco- (Burlington- YorkOakland- South NewarkHayward, Burlington, Jersey City, 

CA Metro VT Metro NY-NJ-PA 

Area) Area) Metro Area)

Nashville, TN

(NashvilleDavidsonMurfreesboro

-Franklin, TN 

Metro Area)

Park 

City, UT

(Summit 

Park, UT 

Micro 

Area)

Seattle, 

WA

(SeattleTacomaBellevue, 

WA 

Metro 

Area)

South Florida

(Miami-Fort 

LauderdaleWest Palm 

Beach, FL 

Metro Area)

Washington, 

DC

(WashingtonArlingtonAlexandria, 

DC-VA-MDWV Metro 

Area)

Poverty Rate (%) 15 11 11 14 14 8 12 17 8

Median 

Household 

Income $61,900 $80,008 $62,175 $66,902 $52,805 $89,886 $68,969 $48,435 $91,756

Median occupied 

home value $196,500 $592,000 $252,000 $400,000 $171,700 $496,800 $315,700 $188,700 $373,300

Homeownership 

rate (%) 58 54 68 52 66 76 60 62 64

White nonHispanic (%) 54 42 91 48 74 85 67 34 48

Black nonHispanic (%) 7 8 2 16 15 0 5 20 25

Hispanic (%) 32 22 2 23 7 12 9 42 14

Other nonHispanic (%) 9 33 7 14 6 4 23 5 16

Bachelor’s 

degree or higher 

(%) 41 45 42 37 31 50 38 29 48

Source: US Census Bureau, American Community Survey (2010–14). 
N O T E S 6 9

Notes 

1. See Brett Theodos, Ellen Seidman, and Laurie Goodman, “11 questions you should ask before sharing your 

home equity with Wall Street,” Urban Wire (blog), Urban Institute, December 14, 2016, 

http://www.urban.org/urban-wire/11-questions-you-should-ask-sharing-your-home-equity-wall-street. 

2. Authors’ calculation of 2015 American Community Survey data. 

3. Ralph McLaughlin, “House Arrest: How Low Inventory is Slowing Home Buying,” Trulia’s Blog, March 21, 2016, 

http://www.trulia.com/blog/trends/inventory-price-watch-q116/, and “Rich City, Poor City: How Housing 

Supply Drives Regional Economic Inequality,” Trulia’s Blog, August 31, 2016, 

http://www.trulia.com/blog/trends/rich-city-poor-city/. 

4. See Zillow Research blog posts by Svenja Gudell: “The US Housing Affordability Crisis: How a Rent and LowIncome Problem is Becoming Everyone’s Problem,” April 11, 2016, http://www.zillow.com/research/housingaffordability-q4-2015-12111/; “Q1 2016 Market Report: Tight Inventory, Rapid Price Growth Represent Real 

Headwinds for the Market’s Core,” April 21, 2016, http://www.zillow.com/research/inventory-by-tier-march12226/; “Housing Highs and Lows: How the Home Affordability Gap between the Rich and Poor Is Widening,” 

July 10, 2016, http://www.zillow.com/research/affordability-2016q1-12763/; and “A Wealth of Problems: 

How the Housing Bust Widened the Rich-Poor Gap,” July 12, 2016, 

http://www.zillow.com/research/foreclosures-and-wealth-inequality-12523/. Also see McLaughlin: “House 

Arrest” and “Rich City, Poor City.”

5. Ibid. 

6. Laurie Goodman, Jun Zhu. And Bai, Bing, “Overly tight credit killed 1.1 million mortgages in 2015,” Urban Wire

(blog), Urban Institute, November 21, 2016, http://www.urban.org/urban-wire/overly-tight-credit-killed-11-

million-mortgages-2015. 

7. Data from the US Census Bureau Housing Vacancies and Homeownership, 

https://www.census.gov/housing/hvs/data/histtabs.html. 

8. Ibid. 

9. Capital Impact developed a set of baseline eligibility criteria for CHIP that required applicants to (1) be 

classified as nonprofit organizations, (2) provide stewardship services to homeowners, (3) serve predominantly 

low-income homebuyers, (4) have a commitment to outcomes tracking and a willingness to participate in the 

evaluation component, and (5) meet a 1:1 matching funds requirement (Capital Impact Partners 2011). 

10. The comprehensive assessment was a multistage process that allowed each finalist and CHIP staff to get to 

know one another better and assess whether the program would be a good fit for CHIP funding (Capital Impact 

Partners 2011). 

11. See Grounded Solutions Network, “About,” accessed December 27, 2016, 

http://groundedsolutions.org/about/. 

12. Program profiles are current as of our interviews and later updates reflected in Theodos, Temkin et al. 2015; 

they may not reflect the status as of 2016. 

13. Also, note that the Federal Housing Finance Authority included shared equity mortgages as “affordable 

housing preservation” lending in the Duty to Serve rule proposed December 2016.

14. Funding was discontinued one year earlier than anticipated. To accommodate this shorter timeline and 

decrease in funding, this report includes outcome analyses relying only on credit bureau and program data, not 

survey data as originally designed. 

15. HomeKeeper is a data collection and workflow management tool. More information is available at 

www.myhomekeeper.org. 
7 0 N O T E S

16. Since enrollment took place over two years, we purchased two separate baseline data points and assigned 

purchasers to 2012 if they purchased before or during June 2013, and 2013 if they purchased after June 2013. 

This allowed us to ensure that baseline data was as close to the point of application as possible.

17. Linear Probability models have the advantage that the parameter estimates can be directly interpreted as the 

“mean marginal effect” of covariates on the outcome and site dummies can be interpreted as unobservable 

fixed-effects (Angrist and Pischke, 2008). As a sensitive test, we also estimate average marginal effects using a 

Probit model and the results were very similar. 

18. We tried and failed to use the distance of baseline residence to the centroid of the supply of shared equity 

homes in each site as an instrumental variable for shared equity purchase. However, the instrument proved to 

be weak making this estimation approach invalid. 

19. Authors’ calculation of 2013 American Community Survey data. 

20. This equity may never be expressly included in the transaction (i.e., the home may be sold at the resale 

restricted price). Alternatively, the home could sell at the market price, with a program providing an equivalent 

amount of cash upon sale (with resale restrictions still applying). 

21. For the 199 shared equity buyers for whom we had detailed funding source data. 

22. Freddie Mac, “30-Year Fixed Rate Mortgage Average in the United States© [MORTGAGE30US],” FRED, 

Federal Reserve Bank of St. Louis, accessed December 29, 2016, 

https://fred.stlouisfed.org/series/MORTGAGE30US. 

23. Credit bureau data captured 192 out of the 244 shared equity purchasers as home buyers. Reasons for the 

credit bureau not identifying shared equity purchasers as home buyers include purchasing the home with cash 

or purchasing through a program that does not report mortgage to credit bureau agencies. For example, the 

Habitat for Humanity programs in this study do not report about the mortgages they originate to credit 

bureaus. 

24. Because of the matching procedure with repetition, individuals of the matched comparison group were 

weighted by the number of matches for statistical calculation purposes. For example, an individual in the 

comparison group matched to three shared equity home purchasers receives weight of three in the statistical 

calculations. 

25. We also estimated the distribution of propensity scores in the treatment and comparison groups. Our visual 

analysis shows significant overlap between those distributions and therefore the common support assumption 

is likely to hold. 

26. Laurie Goodman, Jun Zhu. And Bai, Bing, “Overly tight credit killed 1.1 million mortgages in 2015,” Urban Wire

(blog), Urban Institute, November 21, 2016, http://www.urban.org/urban-wire/overly-tight-credit-killed-11-

million-mortgages-2015. 

27. Theodos, Seidman, and Goodman, “11 questions you should ask before sharing your home equity with Wall 

Street.” 
R E F E R E N C E S 7 1

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A B O U T T H E A U T H O R S 7 3

About the Authors 

Brett Theodos is a senior research associate with the Metropolitan Housing and Communities Policy 

Center at the Urban Institute. Rob Pitingolo, Sierra Latham, Christina Stacy, and Rebecca Daniels are 

research associates with the Metropolitan Housing and Communities Policy Center at the Urban 

Institute. Breno Braga is a research associate with the Center on Labor, Human Services, and 

Population at the Urban Institute. 
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