1 

Can Service-Learning Programs at Anchor Institutions Contribute 

to Increasing Homebuyer Readiness through Financial Capability?

Kevin Giff, BA 

Habitat for Humanity of Orange County, NC 

Susan Kasteler, BS

The University of Alabama

Nicole B. Prewitt, EdD (contact author) 

The University of Alabama 

nbprewitt@ua.edu

Lydia Stanley, MS 

The University of Alabama 

December 14, 2020 

Abstract

We used the case study model including survey methods to assess the level of consumer 

financial capability among low- to moderate-income (LMI) individuals and families seeking 

first-time homeownership through a student-led service-learning program. In addition to 

assessing understanding of key elements of consumer homebuyer readiness (including savings, 

money management, access to banking, credit building, and debt reduction) we also gauged 

overall sentiment regarding the path to homeownership. Results show the capability of servicelearning programs at anchor institutions to deliver a financial coaching program. In future work, 

there is interest in exploring opportunities to expand the program in underserved and rural 

markets and focus on manufactured and affordable housing to promote the mission of Duty to 

Serve (DTS) to overcome significant challenges that impact LMI families’ ability to secure and

sustain homeownership.
2 

Introduction

First-time homeownership remains inaccessible for many Americans, particularly for 

those from low- to moderate-income households (LMI) (U.S Department of Housing and Urban 

Development (HUD), 2020). Homeownership is a pathway to building wealth, developing 

thriving neighborhoods, and creating sustainable communities. Potential impediments that 

individuals face include stagnant wages, low savings, and high living expenses combined with 

limited access to the mainstream financial system. Additionally, many individuals have limited 

awareness of community programs that aim to build financial literacy for first-time homebuyers. 

When individuals seek support there are some organizations with restricted funds and/or 

misaligned resources. These elements create an environment where LMI individuals and 

families are less likely to benefit from social and economic opportunities. The disconnect 

between financial capability and homebuyer readiness outlines the need for anchor institutions to 

partner with their community to create a sustainable program that educates individuals of the 

steps to homeownership so this dream can become a reality for all who desire it.

Owning a home is the primary vehicle for building long-term wealth. Homeownership 

contributes to improved health, child development, educational attainment, employment 

opportunities, greater community stability, and higher life satisfaction (Herbert & Belsky, 2008; 

Kane, 1994; Pollack, Griffin, & Lynch, 2010; Rohe & Lindbald, 2013; Shanks, 2007). Despite 

the importance of homeownership for long-term economic freedom, homeownership rates are at 

historic lows, particularly among LMI households and households of color. For example, in 

Alabama white homeownership surpasses homeownership by individuals of color by 150 percent 

(Prosperity Now, 2017). Similarly, the homeownership rate for households with very low 

incomes is more than forty percent lower than the rate for high-income households (U.S. 
3

Department of Housing and Urban Development (HUD), 2012).

Although the economy and housing market are improving nationwide, Alabama lags 

behind the rest of the country in homeownership. Alabama is the fifth poorest state in the United 

States, with 16.8 percent of the state living below the federal poverty line (noticeably higher than 

the national average of 13.1 percent). This equates to nearly 800,000 Alabamians living in 

poverty (Alabama Possible, 2020). Looking beyond monthly paychecks and observing what a 

family owns is even more startling. One in five Alabamians live in asset poverty, “meaning they 

do not have enough resources (i.e., net worth) to subsist at the federal poverty level for three 

months if their income were interrupted.” (Prosperity Now, 2020). These staggering disparities 

depict the obstacles that inhibit economic mobility for many Alabamians.

To better understand these issues, The University of Alabama (UA), an anchor institution 

(Dubb, McKinley and Howard, 2013) driven by its public service mission, developed HomeFirst,

a service-learning program and training curriculum that provides financial coaching, 

individualized support, and program referrals to low- to moderate-income individuals and 

families seeking first-time homeownership. The HomeFirst program seeks to convene Alabama 

residents, undergraduate college students, and community partners across the state to ensure 

every resident of Alabama has a decent, safe, and affordable place to call home. The primary 

objectives include: 1) executing effective best practices to reduce barriers that prevent low- to 

moderate-income individuals and families from building assets and attaining homeownership, 2) 

utilizing a primarily undergraduate student volunteer base to deliver financial coaching services, 

and 3) promoting collaboration and effective resource building by coordination among 

nonprofits, local government entities, and The University of Alabama. 

HomeFirst supports each participant’s path toward homeownership by focusing on core 
4

areas related to homebuyer readiness through financial capability, including savings, money 

management, access to banking, credit building, and debt reduction. HomeFirst uses a 

participant-driven process in which participants work through modules to improve their financial

capability by focusing on specific, personalized goals. Student coaches do not offer financial 

advice on their participant’s financial issues, but rather they serve as module guides and provide 

tools, resources, and motivation to participants as they work toward their goals. The modules 

provide the roadmap for each participant’s path toward homeownership, with each module being 

structured to provide a brief overview of important financial topics while allowing the participant 

to apply the skills to their own lives through a short activity and action plan. Modules also 

provide information on available resources or referrals. Information presented in modules is 

adapted from the Consumer Financial Protection Bureau’s Your Money Your Goals and FDIC’s 

MoneySmart curriculum.

We used the case-study model, including survey methods, to assess the level of consumer 

financial capability among low- to moderate-income individuals and families seeking first-time 

homeownership through this student-led service-learning program. In addition to assessing 

understanding of key elements of consumer homebuyer readiness through financial capability 

(including savings, money management, access to banking, credit building, and debt reduction) 

we also gauged overall sentiment regarding the path to homeownership. 

Results show anchor institutions, place-based entities such as universities and hospitals 

that are tied to their surroundings by a mission, invested capital, or relationships to customers, 

employees, and vendors (Dubb, McKinley and Howard, 2013), can deliver service-learning 

programs such as a financial coaching program with the potential to expand into underserved 

markets as designated by Duty to Serve (DTS), a housing initiative designed to tackle three of 
5

the country’s toughest markets, which include manufactured housing, rural housing, and the 

preservation of affordable housing (Federal Housing Finance Agency, 2020). The paper is 

organized as follows: Section 2 presents the literature, both on financial capability and 

homebuyer readiness, broadly, and on service-learning and anchor institutions, specifically. 

Section 3 describes the survey process and resulting data. Section 4 presents the results. Section 

5 concludes the key findings and avenues for further research.

Literature Review

To our knowledge, no service-learning program has involved consumers’ financial 

capability and homebuyer readiness; therefore, we first want to establish some baseline 

knowledge from the larger body of work on financial capability and homebuyer readiness. 

Financial Capability

There is abundant research on the relationship between financial capability and 

homebuyer readiness. Financial capability is broadly defined as the ability and opportunity for 

households to achieve financial well-being (Sherraden, 2013; Xiao et. al, 2016). According to

Sherraden’s financial capability framework, financial capability consists of both internal 

capabilities, such as financial knowledge, skills, and behaviors, and external conditions, such as 

access and inclusion in the financial market. Individuals must possess financial knowledge, 

skills, and behaviors to make informed decisions for their best interests. Individuals must also 

live in an inclusive financial market where they have access to safe financial products and 

services and where consumer protection policies exist. Together, internal capabilities and 

external conditions enable financial capability (Sherraden, 2013).

Financial capability moves beyond traditional financial literacy approaches, which solely 

emphasize changes in internal capabilities by acknowledging the external socioeconomic 
6

conditions that impact an individual’s financial opportunity to achieve financial well-being 

(Sherraden et al., 2015; Xiao et al., 2016). The financial capability approach recognizes the 

relationship between individuals and systems. Due to these factors, individuals have varying 

levels of financial capability. Research indicates households with lower financial capability are 

more likely to live in unstable housing, lack personal savings, or achieve their financial goals. 

(Sherraden et al., 2015). 

The goal of financial capability programs is to improve financial well-being among 

individuals and households (CFPB, 2015; Sherraden 2013; Xiao et al., 2016). Due to the limited 

ability or reach for individual programs to significantly impact the external conditions, many 

approaches focus primarily on improving internal capabilities. Numerous studies show a positive 

correlation between changing internal capabilities and overall financial capability (Mottola et al.,

2017; Rothwell et al., 2016; Xiao et al., 2016). Findings suggest that approaches aimed at 

increasing financial knowledge skills bolster an individual’s financial capability. Furthermore, 

Rothwell et al. (2016) discovered supporting internal capabilities requires an understanding of 

how they are each interrelated, and specifically improving financial self-efficacy is key to 

fostering the relationship between financial knowledge and positive saving behaviors. With this 

in mind, all financial capability approaches acknowledge and actively work to advocate for 

external conditions that improve financial capability (Sherraden 2013; Rothwell et al., 2016; 

Xiao et al., 2016).

Financial capability is essential to the homebuyer readiness of households. Financial 

knowledge, skills, and behaviors are positively correlated with the conditions necessary for 

obtaining homeownership, including money and debt management, savings patterns, and 

creditworthiness (Grinstead et al., 2011; Sherraden et al., 2015; Asset Funders Networks, 2011). 
7

Furthermore, access to safe and sound mortgage products and first-time homebuyer supports 

provide an opportunity for LMI households to attain homeownership. (Olsen, n.d.; Myhre & 

Watson, 2017).

Increasing sustainable homeownership among LMI individuals and families by 

increasing the pool of potential homebuyers who are ready to purchase a home is the goal of 

many homebuyer education programs. For many LMI individuals, being ready to purchase a 

home includes access to information about the home purchase process, access to resources, and 

financial literacy sufficient to make informed decisions about homeownership. The term we have 

chosen for this is homebuyer readiness.

Homebuyer Readiness Among Low- to Moderate-income (LMI) Individuals and Families

So, why does homebuyer readiness matter? Moulton et al. (2013), compared the selfassessments of participants in the Ohio Housing Finance Agency’s first-time homebuyer 

program to their administrative data (credit reports and mortgage loan applications). They found 

that 31.5% of homebuyers underestimated the amount of their non-mortgage debt by at least 

$5,000 and 11.5% overestimated their debt by at least $2,000. In their findings, homebuyers who 

underestimated their non-mortgage debt incurred larger mortgage debt and had higher front-end 

ratios. 

Homebuyers who misestimated their non-mortgage debt were also more likely to take up 

an offer of financial coaching. In a study of data from the National Financial Capability Study 

and a large mortgage dataset, An et al. (2015) found that borrowers with lower financial literacy 

scores were more likely to accept riskier loans, pay higher interest rates, and default more often 

than those with higher scores. An et al. (2015) stated that “our lower bound estimate suggests we 

would see at least $460 million in reduced annual payments from converting low literacy 
8

borrowers in California into high literacy borrowers.” (p. 26). 

Many homebuyer education programs focus on long-term outcomes for those receiving 

homebuyer education services. Brown (2016) reviewed data from the Tennessee Development 

Housing Agency’s down payment assistance program, which began in 2002. Homebuyer 

education services were not available during the first six months. This made for a natural 

comparison to homebuyers who received services during the following six months. Data from 

the seven-year study period found that those who received homebuyer education services were 

42% less likely to have experienced foreclosure as a terminal outcome at the end of the study 

period. One reason for the lower foreclosure rate could be that homebuyers who receive 

homebuyer education services are more likely to contact a lender if they will not be able to make 

a mortgage payment (DeMarco et al., 2016). In a study of data from HUD’s First-time 

Homebuyer Education and Counseling Demonstration, DeMarco et al. (2016) stated, “[t]he 

treatment group’s mortgage literacy, credit scores, and communication with lenders 

demonstrably improved, and all signal steps on the path to sustainable homeownership” (p. 31).

One way to increase the impact and use of homebuyer education services among LMI 

borrowers is to seek out LMI individuals and families before they begin the homebuying process. 

Often homebuyers don’t take up offers of homebuyer education until they are already shopping 

for a home or have a contract to purchase a home. Moulton et al. (2019) also examined data from 

HUD’s First-time Homebuyer Education and Counseling Demonstration. Of those offered free 

homebuyer education services, 55% initiated services. Services offered included in-person and 

remote services, as well as a general homebuyer education course and one-on-one counseling. 

Further analysis showed that men, those with co-borrowers, and those later in the home purchase 

process were less likely to initiate services. The most common factor cited by homebuyers in this 
9

study who did not initiate services was a scheduling conflict. Moulton et al. (2019) stated their 

findings “highlight the importance of early intervention in the home purchase process,” (p. 396)

and further suggested that service providers use these findings to better target their outreach to 

potential participants. 

A Brief History of Service-learning Programs 

Service-learning is a pedagogy of practice found within the history of community 

engagement (Boyer, 2016; Yates & Accardi, 2019) that can connect academics and research 

(Dodd, 2017), can be evaluated (Metzger, 2012), has a positive impact on students and the 

institutions (Vogel & Seifer, 2011), and can broker community-campus partnerships (Levkoe & 

Stack-Cutler, 2018).

Through a national scan on more than 100 universities nationwide, Yates and Accardi 

(2019) provide a historical background of higher education’s community engagement efforts. 

The authors segment this history into three distinct waves: civic engagement, service-learning, 

and anchor institutions. Beginning in the 1980s, colleges and universities started to recommit to 

their roles of strengthening democracy and educating students to be engaged citizens. Through 

the establishment of Campus Compact and other similar initiatives, colleges and universities 

promoted student volunteerism and civic engagement efforts across the nation.

Building on this commitment, the service-learning movement grew during the 1990s. The 

year 1996 was marked by Ernest Boyer (2016), former president of the Carnegie Foundation for 

the Advancement of Teaching, challenging the field of higher education in the United States of 

America to recommit itself to the scholarship of engagement. Accordingly, service-learning has 

its foundation in the scholarship of engagement. In his work, Boyer stated,

At one level, the scholarship of engagement means connecting the rich resources of the 
10

university to our most pressing social, civic, and ethical problems, to our children, to our 

schools, to our teachers, and to our cities, just to name the ones I am personally in touch 

with most frequently. You could name others. Campuses would be viewed by both 

students and professors not as isolated islands, but as staging grounds for action. (p. 27)

Service-learning programming, embedded within the work of community engagement, 

connects academic coursework with community service initiatives. Dodd (2017) credibly makes 

the case for universities to make efforts to engage with their community, as it can provide 

valuable research opportunities. Dodd states “[s]ervice-learning, when done effectively, can 

extend beyond teaching and service to incorporate research that addresses authentic and complex 

social issues of relevance to the community, and, therefore, the university it serves.” (p. 186).

Additionally, Dodd argues research and community engagement are interconnected. To offer 

benefits, universities must first research what exactly the community wants from them. In this 

article, Dodd points out that a particular service-learning program not only teaches students realworld skills, it also gives universities a real connection to the community, allowing them to learn 

about issues that matter to the community. The university can then research these specific issues.

Metzger (2012) contends service-learning programs can be effectively evaluated by 

demonstrating that students being exposed to real-world events was very impactful on students’

learning outcomes. Vogel and Seifer (2011) explore how service-based learning has a positive 

impact on students and institutions and that communities benefit from this approach. They found 

that long-term service-learning plans increase the amount of faculty engagement with the 

community and improve faculty attitudes to community partnerships. Accordingly, servicelearning may broker community-campus partnerships. Levkoe & Stack-Cutler (2018) focused on 

how academic institutions, such as colleges, work with community partners. These partnerships 
11

aim to be mutually beneficial. Additionally, these collaborative efforts aim to benefit society as a 

whole. The authors argue that to have a successful outcome, both sides must highlight their 

specific goals and the structure of the partnership.

The Role of Anchor Institutions and Proximity to Underserved Markets as Designated by DTS

Most recently, starting in the early 2000s, colleges and universities started moving 

beyond community service programs and toward larger community and economic development 

through adopting anchor missions (Yates and Accardi, 2019). Dostilio & Welch (2019) 

distinguish the new anchor institution phase of higher education from previous community 

engagement by approaches having the priority focus of community outcomes in addition to 

student development or academic research goals.

Over the past several decades, communities across the United States have felt the 

personal effects of a shifting global economy. Since the 1960s, the rise of deindustrialization and 

globalization have greatly altered the local economy. As the nation has shifted away from a 

manufacturing-based economy toward a knowledge-based one, cities, towns, and villages have 

witnessed long-standing for-profit corporations exit their communities (Dubb, McKinley & 

Howard, 2013; Green & Hanna, 2018; Harris & Holley, 2016; Taylor & Luter, 2013, Yates and 

Accardi, 2019). In addition, through the decline of public funding, many communities have 

experienced sustained instability through unemployment, weakened education systems, unstable 

neighborhoods, and concentrated poverty (Taylor and Luter, 2013). 

Meanwhile, large, place-based nonprofit entities such as colleges and universities and 

hospitals (commonly referred to as the “eds and meds”), due to the nature of their operations,

have remained and increased their presence. As a result, these entities play an increasingly 

important role in the social and economic well-being of their communities. (Dubb, McKinley, & 
12

Howard, 2013; Olinger, Reece & Usher, 2015). For many communities across the United States, 

hospitals and universities represent the area’s largest employer, landowner, and purchaser of 

goods and services (Green & Hanna, 2018; Harris & Holley, 2016; Taylor & Luter, 2013). 

The concept of anchor institutions derived in the literature as a result of the shifting roles 

that large, non-profit entities play in their communities. According to Dubb, McKinley, and

Howard (2013), “Anchor institutions are place-based entities such as universities and hospitals 

that are tied to their surroundings by mission, invested capital, or relationships to customers, 

employees, and vendors.” Through an extensive review of the literature, Taylor & Luter (2013) 

identified four common aspects defining anchor institutions: spatial immobility, corporate status, 

size, and the anchor mission. 

The first aspect, spatial immobility, refers to the fixed nature of anchor institutions. 

Anchor institutions have deep roots in their communities by mission, invested capital, or 

relationship to customers or employees (Webber and Karlstrom, 2007). Secondly, the corporate 

status of anchor institutions is that of non-profit entities. Taylor & Luter (2013) highlight the 

connection to corporate status with spatial immobility. Nonprofit entities such as universities and 

hospitals tend to remain rooted in place regardless of economic condition, whereas communities 

risk experiencing for-profit entities leaving as profits decline or when economic conditions 

weaken (Taylor and Luter, 2013).

Third, the size of anchor institutions must be substantial enough to impact a region’s 

economy. Anchor institutions must be large enough to impact their communities through 

activities such as employment, real estate holdings, purchasing power, and cultural influences. 

Most commonly referenced as anchor institutions are hospitals and universities, however, in 

some cases, libraries, social service agencies, community centers, and faith-based entities may 
13

also qualify as anchor institutions. 

The fourth and final aspect anchor institutions must have is an anchor mission. Dubb, 

McKinley, and Howard (2013) define the anchor mission as anchor institutions applying their 

place-based economic power with human and intellectual resources to better the communities in 

which they reside. Large, place-based non-profit entities must acknowledge their roles as anchors 

in their communities to fully serve as anchor institutions. 

Anchor institution approaches tend to be centered around economic development, 

education, and health (Dostilio & Welch, 2019). Ehlenz, Birch, and Agness (2014) discuss key 

findings from case studies from six urban universities. In their findings, the authors found a 

variety of anchor institution approaches, including neighborhood revitalization, downtown 

redevelopment, and cross-sector partnerships. To help anchor institutions to assess and measure 

their impact in their communities, particularly those encompassing low-income populations, the 

Democracy Collaborative at the University of Maryland developed a framework. This 

framework is comprised of 12 outcome measures, some examples include: affordable housing, 

local partners, and financially secure households. 

Related to the housing needs of communities, the most cited anchor approaches are 

employee-assisted housing (EAH) programs and Community Land Trusts (CLT). EAH programs 

typically assist employees of higher education entities to purchase or rent a home in a 

surrounding neighborhood to the university. CLT’s are entities that acquire land in order to sell 

or rent to families at an affordable rate (Greene & Hanna, 2018). These approaches have several 

positive benefits and have been successful in addressing the housing needs of many 

communities. However, these approaches are still not far-reaching or adopted by many anchor 

institutions. 
14

Therefore, there are a number of avenues colleges and universities can take in meeting 

community needs and building local economies. As previously mentioned, higher education 

institutions serve many important roles in their local economies. Colleges and universities are 

large employers, real estate owners, purchasers, educators, and workforce developers (Harris & 

Holley 2016). Although higher education still remains in early adoption of the anchor institution 

phase, there are many outstanding approaches being implemented nationwide.

Duty to Serve

The Housing and Economic Recovery Act of 2008 establishes a duty for Fannie Mae and 

Freddie Mac to serve three specified underserved markets – manufactured housing, affordable 

housing preservation, and rural markets (Housing and Economic Recovery Act, 2008). The

HomeFirst program began with a pilot located in Tuscaloosa County, Alabama. Tuscaloosa 

County is home to 208,911 residents (Tuscaloosa County, AL, 2020). Education, auto 

manufacturing, and healthcare are important industries in Tuscaloosa County. The University of 

Alabama is located in Tuscaloosa and is the county’s largest employer, followed by MercedesBenz U.S. International, Inc., and DCH Regional Medical Center (Economic Development 

Partnership of Alabama, 2019). The median family income in Tuscaloosa County is $66,903, and 

the median value of an owner-occupied housing unit is $173,800 (HUD, 2019). Sixty-two 

percent of occupied units are owner-occupied and 10% of housing units in Tuscaloosa County 

are mobile homes (U.S. Census Bureau, 2014–2018). Of adults 25 years of age and older, 59% 

reported having attended at least some college. Including residents who had received a high 

school diploma or equivalent, the rate increases to 90% (U.S. Census Bureau, 2014-2018). It is 

important to note that Tuscaloosa County is not a high-needs rural county under the DTS 

program, as designated by the Federal Housing Finance Agency; however, in 2017 when Fannie
15

Mae, The University of Alabama, and other parties came together to develop a pilot at an anchor

institution to help support the development of a financial capability program to consumers in the

Tuscaloosa area, the goal of the service-learning program was to expand financial capability 

service delivery to increase financial stability and homeownership in high-needs rural markets. 

In 2019 HomeFirst expanded to include additional rural counties and collaborated with key 

stakeholders to increase the number of participants served.

The pilot expanded to include underserved markets in two high-needs rural counties 

under the DTS program: Greene County and Hale County. Greene County is home to 8,426 

residents (Greene County, AL 2020). Manufacturing is a key industry in Greene County, 

followed by agriculture, forestry, fishing, and hunting (Economic Development Partnership of 

Alabama, 2019). The median family income in Greene County is $31,003 (HUD, 2019). The 

median value of an owner-occupied housing unit is $67,700 and 68% of occupied units are 

owner-occupied. Forty percent of housing units in Greene County are mobile homes. This is 

more than double the average for Alabama and the United States (U.S. Census Bureau, 2014–

2018). The percentage of Greene County residents age 25 and older who reported attending at 

least some college is 39% (U.S. Census Bureau, 2014–2018). 

Hale County is home to 14,887 residents (Hale County, AL, 2020). Manufacturing and 

healthcare are important industries in Hale County (Economic Development Partnership of 

Alabama, 2019). The median family income in Hale County is $66,903 (HUD, 2019). The 

median value of an owner-occupied housing unit is $88,800 and 75% of occupied units are 

owner-occupied. Thirty-six percent of housing units in Hale County are mobile homes (U.S. 

Census Bureau, 2014–2018). This is more than double the average for Alabama and the United 

States. The percentage of Hale County residents age 25 and older who reported attending at least 
16

some college is 41% (U.S. Census Bureau, 2014–2018). 

Research on anchor institutions is only a few decades old. As a result, gaps in the 

literature still exist. The majority of the research focuses on anchor institutional approaches in 

urban settings. Further examination into the role and approaches of anchor institutions with 

proximity to underserved markets as designated by DTS is needed. Additionally, there is sparse 

research on anchor institution approaches in the Southeastern U.S. Furthermore, there is minimal 

research on the role students play in anchor institution approaches, both as actors within higher 

education settings and their local economies.

Survey Methodology and Data

During July 1, 2018–June 30, 2020, we reviewed collected data of 100 participants to 

understand participant perceptions about financial capability and their perspectives toward 

homeownership in order to begin the process of developing a conceptual framework to identify 

existing assets in high-needs rural counties across the state of Alabama. Therefore, the findings, 

although deep and insightful, may not be projectable to all high-needs rural counties. In order to 

expand our reach to high-needs rural counties with proximity to The University of Alabama,

HomeFirst identified community resources, financial tools, and affordable housing programs to 

further support attainable and sustainable housing. HomeFirst established partnerships with local 

non-profit organizations, governmental agencies, and large employers to recruit participants. In 

addition to recruitment through community partners, recruitment flyers were posted in areas of 

high visibility such as libraries and community centers. Recruitment of participants in our initial 

expansion into high-needs rural counties was similar to the Tuscaloosa County cohort in which 

participants met in-person with HomeFirst staff to complete registration. In all three counties 

HomeFirst staff identified relevant community stakeholders to market the program to LMI 
17

individuals. However, program registration and the mode of service delivery in high-needs rural 

county cohorts varied from the Tuscaloosa County cohort. Community partners in Greene and 

Hale counties completed registration for some participants. Tuscaloosa County cohort 

participants met with a coach to complete registration. 

In addition to program data, this study utilizes program history generated under 

sponsored research agreements and deliverables developed during the pilot program. 

This study uses a mixed-methods research design in order to have both qualitative and 

quantitative research to gain breadth and depth of understanding to inform best practices that 

promote the financial and housing stability of Alabamians. In addition, this study explores the 

important and necessary role higher education institutions in Alabama have to partner as anchor 

institutions to advance effective best practices that promote the financial and housing stability of 

all Alabamians.

Participants’ involvement in the study occurred in one or both of the following ways: 1) a 

retrospective review of program artifacts completed by the participant throughout engagement 

with the HomeFirst program and/or 2) a semi-structured interview occurring at the conclusion of 

the individual’s engagement with the HomeFirst program. Each person entering the program was 

asked to sign a privacy statement. This privacy statement was designed to provide participants 

with information on privacy, inform participants about their rights, and inform participants how 

their information remains secure. We only had access to collect information that participants 

voluntarily gave us. The data collected, including demographic data, was self-reported by the 

participants. The data collected was provided to us orally, on the application or on other forms. 

We assured participants that all the information shared both orally and in writing would be 

managed within legal and ethical considerations, including not selling their personal information 
18

and only releasing their personal information to third parties with consent. All participants were 

informed that we may also collect, use, and share anonymous aggregated case file information to 

evaluate our services, to gather valuable research information, and to design future programs.

The retrospective review of program artifacts included a pre-, post- Financial Capability 

Scale (FCS) questionnaire, follow-up questionnaires, learning modules, and meeting notes. The 

FCS is a standardized evaluation of financial capability that demonstrates client impacts and is 

used by financial coaching programs presented in the financial literature (Collins & O’Rourke, 

2013). In 2013, the Center for Financial Security at the University of Wisconsin-Madison 

developed the FCS. This scale contains six questions with two optional alternative questions and 

is measured on an eight-point scale to assess financial well-being. Questions cover topics related 

to money management, financial behaviors, and confidence. Of the six standard questions, four 

questions focus on observable behaviors. An example of one of these questions’ states, “Do you 

currently have a personal budget, spending plan, or financial plan?” Two questions focus on the 

measurement of consumer confidence. An example of a question measuring confidence states,

“How confident are you in your ability to achieve a financial goal you set for yourself today?” 

The scale is intended to create a standardized method to observe participant progress in financial 

coaching programs (Cohen, Hoagland, & Wiedrich, 2017).

To better interpret data, the FCS can be broken down into three levels: Low (0–3); 

moderate (4–5); and high (6–8). Research shows these three FCS levels correlate with key 

elements of financial well-being, including level of debt, asset, stress and emergency savings. 

For example, once an individual’s assets and emergency savings increase, they tend to score 

higher on the FCS. Higher levels of financial stress and debt consistently are tied to a lower FCS 

level (Asset Funders Networks, 2011). 
19

For our purpose, the FCS allowed the measurement of changes in both behavior and 

confidence in participants’ ability to handle their finances in the future by calculating the preand post-FCS score based on the six standard questions. Participants were asked additional 

questions to understand the usage of payday loans and of mainstream banking services.

Participants were informed about the interview portion of the study at the conclusion of 

the HomeFirst program registration process. Publicity flyers detailing the study were shared to 

individuals participating in the HomeFirst program on the campus of The University of Alabama 

or at partner site locations. Participants were able to enroll in the study at any time during their 

involvement with the HomeFirst program. To prevent potential coercion that could have 

occurred with participation in the study versus engagement with the HomeFirst program, 

participants were explicitly informed that participation or non-participation in the study had no 

impact on the individuals’ ability to engage with the HomeFirst program. To further minimize 

possible coercion, individuals were informed of the study after registering into the HomeFirst 

program. Furthermore, interviews took place in a location that was removed from the HomeFirst 

service delivery location. 

Each person agreeing to participate in semi-structured interviews was asked to read and 

sign an informed consent document. The purpose of the informed consent document was to 

communicate to the participant the nature of the study, right to privacy, and reassure protection 

from harm. Semi-structured interviews were conducted with two participants to further enhance 

data interpretation. Interviews were via the phone. The interviews took 60 minutes each and were 

audio recorded. 

The semi-structured interview prompted participants to discuss goals of homeownership; 

housing stability before, and if applicable, after purchasing their home; perception of available 
20

supportive services and resources; and the role the HomeFirst program had, if any, on goals of

homeownership. Sample questions included “What does homeownership mean to you?”, “What 

resources and services do you feel are available to support you in becoming a homeowner?”, and 

“Did you feel comfortable discussing personal financial matters with your financial coach?”

Probing questions were then used as a strategy to obtain more information.

The results from each interview were transcribed by a member of the research team and a 

pseudonym assigned to each participant. Once transcribed, the electronic record of the interviews 

was destroyed. A key associating the pseudonym with the actual name and contact information 

of each participant will be kept in the Principle Investigator’s (PI) UA Box for six years after 

completion of the study, after which time, the key will be destroyed. Only the researchers will 

have access to the collected data during the study. At no point (before, during, or after the study) 

will the identity of the participant be revealed to anyone other than the research team and at any 

time during the interviews, the participants had the right to rescind their consent to participate. 

Upon completion of the study, only the PI will have access to the collected data, and all 

collected data will be stored in the PI’s UA Box for six years after completion of the study.

In addition, we gathered data through module completion and participant satisfaction with the 

HomeFirst program. The learning modules were a set of financial education lessons that were 

completed by the participant throughout HomeFirst program involvement. Meeting notes 

detailing participant activities with the program were recorded. Program artifacts were obtained 

in paper or electronically with the participant’s consent at the conclusion of the participant’s

involvement with the HomeFirst program.
21

Results 

We reviewed data from July 1, 2018–June 30, 2020 from 100 participants. Two 

participants were excluded due to missing registration and program data. Of the remaining 98

participants, 25 individuals participated in the 2018–2019 (July 1, 2018–June 30, 2019) program 

cohort and 73 individuals participated in the 2019–2020 (July 1, 2019–June 30, 2020) cohort.

Demographic information collected at program intake and outlined in Table 1 indicates

participants identified predominantly as female (93%), African American (98%), and range in 

age from 19 to 74 with an average age of 44. Participants were predominantly renters (81%), the 

majority of participants were employed full-time (59%), and over half (53%) had at least some 

postsecondary education. All participants maintained an income below the area median family 

income in the region (or $66,900 for a family of four) (HUD, 2019). There were on average 2.8 

individuals per household, with majority of households comprising single mothers with children. 

Participants resided in Tuscaloosa County (64%), Greene County (25%), and Hale County 

(10%). Participant engagement with the HomeFirst program primarily occurred during the threemonth program cycle in fall 2018 and fall 2019. During this time, participants met individually 

with a financial coach. Coaching meetings, as noted in Table 2, primarily focused on completing 

HomeFirst modules, which provided information and resources to prepare participants for 

homeownership. Participants completed 4.7 modules on average. As noted in Table 3, in total, 

341 financial coaching meetings were held during both three-month program cycles (110 

meetings in Fall 2018 and 231 in Fall 2019) and on average, participants attended 3.6 meetings.

The number of meetings offered in the high-needs rural counties was less than the 

number of meetings offered to the Tuscaloosa County cohort. Hale County cohort participants 

were offered three meeting times. The Greene County cohort participants were offered two 
22

meeting times. The Tuscaloosa County cohort participants had the opportunity to meet 6–8 

times. To offset the limited meetings offered in high-needs rural counties, the meeting times 

were extended to allow for more modules to be covered in a single meeting. This variation in 

service delivery is reflected in the data in Table 2, which shows an average meeting attendance 

in Greene County of .7 meetings and the average number of modules completed being over three 

times higher (2.9 modules). Compare this to the Tuscaloosa County cohort where the average 

number of meetings and average number of modules are nearly identical. The Hale County 

cohort numbers were affected by two Hale County participants who chose to travel to the 

Tuscaloosa County cohort site for additional meetings. This resulted in a higher average meeting 

attendance and average number of modules completed. 

HomeFirst participants completed a pre- and post- questionnaire incorporating the 

Financial Capability Scale before and after the three-month program engagement. Table 3 

presents financial capability scale data taken at program intake. Participants’ intake responses 

ranged from 0–7, with the average score being 4.0. Over half (57%) of participants had a 

personal budget or financial plan. Over half (60%) reported that total spending on living 

expenses was less than total income. Nearly three out of four (72%) participants had both 

checking and savings accounts. About one in five (17%) used a payday loan in the past three 

months. FCS data collected at program intake was consistent to baseline data of other financial 

coaching programs (Cohen et al., 2017). In efforts to deepen the statistical analysis of the 

HomeFirst impacts in the upcoming program year there is potential to incorporate the Consumer 

Financial Protection Bureau Financial Well-Being Scale (Bureau, Consumer Financial 

Protection, 2015). This scale incorporates IRT modeling (Knoll et. al, 2012) which is the method 

of choice for standardized educational testing and other domains in which score precision is 
23

critical (Prosperity Now, 2017). It allows the community organization to utilize classical test 

theory techniques to analyze the data collected through iterative surveys and create scores that 

are comparable to one another. Using IRT, we will be able to take into account certain properties 

of the questions themselves in order to assess individuals’ level of financial literacy (Knoll et. al, 

2012). This analysis includes a user guide provided by the Consumer Financial Protection 

Bureau for those not familiar with the dense technical aspects of statistical modeling, as well as a 

technical report to understand the elements that render the financial well-being.

Financial Capability and Homebuyer Readiness Impacts

Initial results suggest the HomeFirst program had positive effects on the financial 

capability of participants. Table 4 displays the FCS data for participants at program exit. 

Participants’ exit responses ranged from 1–8, with the average score of 5.8. Participants who 

completed both pre- and post- program assessments scored on average 1.7 points higher on the 

FCS compared to program intake data (5.8 points versus 4.1). Average changes in pre-, postFCS scores were consistent, and in some cases slightly higher than similar financial coaching

programs (Cohen, Hoagland, & Wiedrich, 2017).

Furthermore, exit data show the HomeFirst program had impacted participants’ 

homebuyer readiness. The average participant saved $652 over the three-month period. Over half 

(65%) noted that the frequency in which they saved increased over the past three months. 

Participants paid off an average of $662 in debt during the three-month program. The majority 

(85%) of participants reported making “some” progress toward reducing debt and over half 

(62%) reported seeing a positive change in their credit score over the past three months.

The path to sustainable homeownership can be intimidating for LMI families. This was

demonstrated in interviews with two participants. A participant from Tuscaloosa County (2019)
24

stated, “I was just scared because to be honest, I was afraid to sign something [loan for a 

mortgage] that I wasn’t sure I was going to be able to pay for. The Homebuying process is

stressful and that fear was my biggest barrier.” In efforts to gain knowledge about the 

homebuying process this participant stated she wanted to “see if there was a program I can utilize 

before I went the traditional route of going to the lender directly just because I knew that can be 

very, very complicated” (p. 3).

These statements demonstrate a level of discomfort with the homebuying process and a 

lack of confidence in knowledge of the process. This lack of knowledge and confidence could 

impact LMI borrowers’ decisions about when to apply for a mortgage and the lender or program 

the borrower chooses to use. An et al. (2015) found that lower financial literacy correlated to 

borrowers accepting riskier loans with higher payments. 

Research by Moulton et al. (2013) found that 43% of LMI borrowers misestimate their 

current debt level when compared to their credit reports and mortgage applications. In an 

interview, the participant from Tuscaloosa County described what she discovered when she 

reviewed her credit report as well as her credit score. She stated: “My credit I thought was a big 

problem until I got my credit report and looked at it for myself and it was not that I did not have 

good credit, I just did not have a lot of credit because I was not a person that financed,” 

(Tuscaloosa County participant, personal communication, 2019, p. 12).

Intake data from participants also show that confidence in their ability to achieve a 

financial goal (question 2 on the FCS) was significantly higher than confidence in their ability to 

pay their monthly expenses if faced with an unexpected expense (question 3 on the FCS). In 

addition, participants in 2019 were asked to describe their current credit record at intake. Only 

12% described their credit as good or very good. Moulton et al. (2013) noted this potentially 
25

shows that individuals are overconfident about their credit. Misestimation of current finances and 

overconfidence correlates to increased front-end ratios. 

Early homebuyer education leads to increased FCS scores. This increase should correlate 

favorably to borrowers’ ability to attain affordable mortgages with lower front-end ratios. Since 

homebuyer education correlates to lower foreclosure rates (Brown, 2016), and to the borrowers’

increased likelihood of contacting a lender (DeMarco et al., 2016), the reduction could also

correlate to higher FSC scores and better affordability ratios, thus increasing sustainability over 

the long-term. This effect is demonstrated by the Tuscaloosa County participant’s statement, “it 

was comforting just to know that okay we could definitely always keep the house no matter what 

our current financial status because the payment is so low” (p. 5).

Observing the financial capability and homebuyer readiness of participants in the threecounty service area provides insight into the unique needs and circumstances within each county. 

Initial results identify slight variations in the pre-, post- FCS between Tuscaloosa, Greene, and 

Hale County participants. At program enrollment, Tuscaloosa County participants scored 4.4 on 

average, followed by Hale County with 4.2, and Greene County with 3.5 points on average. At 

program exit, Tuscaloosa County participants scored 6.2 points (or a 1.8-point increase), 

followed by Greene County 5.2 (+1.7), and Hale County 4.5 (+0.3). Greene County participants 

experienced a 48.6% increase in FCS scores, the largest percent increase amongst the three 

counties. (Tables 3 and 4).

There were also slight variations in the homebuyer readiness of participants by county of 

residence. Tuscaloosa County participants saved $909 on average over the three-month program 

engagement, followed by $281 average saved for Greene County participants, and $63 saved for 

Hale County participants. There were differences in perceived progress toward paying off debt. 
26

Amongst the cohort, 100% of Greene County participants reported making “some” or “a lot” of 

progress toward reducing debt; followed by 96% of Tuscaloosa County and 75% of Hale County 

participants. Meanwhile, 78% of Tuscaloosa County participants reported a positive change in 

their credit score over the past three months compared to half of Hale County and one quarter of 

Greene County participants (UA HomeFirst Metrics Report 2019). 

Variations in program outcomes within the three-county cohort may point to differences 

in the external conditions within each of these counties. For instance, financial access varies 

greatly between the rural counties and Tuscaloosa County, and all three counties lag behind 

nationally. In 2017, the unbanked rate (or the percentage of households with neither a checking 

nor savings account) was 19.2% and 12.2% for Greene and Hale County residents respectively 

(compared to 8.7% in Tuscaloosa County). These rates are significantly higher than the 6.5% 

national average. (Prosperity Now 2020). These trends suggest the need for further research into 

how the external conditions facing high-needs rural counties impact financial capability and 

homebuyer readiness. 

Student-led Service-learning Approach

The HomeFirst service-learning program was designed to provide the primary source of 

coaching for participants by undergraduate students. The program was designed as Vogel and 

Seifer (2011) describe, to have a positive impact on students, institutions, and ultimately the 

larger communities. The author found that long-term service-learning plans increase the amount 

of faculty engagement with the community and improve faculty attitudes to community 

partnerships. When asked to reflect on the program, participants noted pace and the 

individualized nature of the program were beneficial. For example, a participant (2019) from 

Greene County, Alabama stated, “I’m glad it was just not rushed through like the other class I 
27

took. HomeFirst actually gave me the opportunity to take my time and do the modules one at a 

time. They didn’t try to rush you through it all in one day.” The participant from Tuscaloosa 

County stated, “There was a uniqueness to HomeFirst...it was very fluid. [Coaches would say] as 

far as [they] know we need to cover this module or if you’re ahead and [you] already know these 

things I can find you things specific to your experience” (p. 3).

Meeting clients where they were was important to the Tuscaloosa County participant who 

recalled, “And so, their goal is, of course, to help establish homeownership and to get 

[participants] ready for homeownership. But the homeowners have varying needs...including 

myself and everybody else who participated. So, I think HomeFirst really tries to embody 

partnership, uniqueness, individuality, and meeting the client where they truly are.” (p. 3)

Additionally, the Greene County participant stated, “... I think that was the best part, that you get 

to sit one-on-one with your coach and talk instead of in a group with 15 people and everybody’s 

not on the same level” (p.7).

The Role of Colleges and Universities as Anchor Institutions

Accordingly, service-learning is also known to broker community-campus partnerships. 

Levkoe & Stack-Cutler (2018) stated the ways in which academic institutions, such as colleges, 

work with community partners, and in this case, participants who saw themselves as partners 

with the HomeFirst program. A partnership was one way the program was described by the

participant from Tuscaloosa County who stated, “So it was a partnership... A lot of times...for a 

lot of programs, it is you meeting their expectations. And sometimes that’s because, I mean, 

[other programs are] grant program[s] and they have to have certain expectations, and sometimes 

it is just not available because of the agency culture....I think that HomeFirst really embodies 

true partnership where both parties feel heard and that their needs are being met” (pp. 2–3).
28

Levkoe & Stack-Cutler (2018) state these partnerships aim to be mutually beneficial. 

Additionally, these collaborative efforts aim to benefit society as a whole. The authors argue that 

in order to have a successful outcome, both sides must highlight their specific goals, and the 

structure of the partnership. This was apparent with the interactions of our coaches and 

participants. For example, an anonymous 2019 participant stated during a case study interview, 

“I actually felt more comfortable working with the college students because it’s something 

they’re working toward. I think their title doesn’t matter. I think that anyone can deliver the 

program if they’re truly committed to the mission. And they’re truly committed to cultural 

sensitivity, and they’re truly committed to going the extra mile and relationships. I think students 

are prime candidates for that because they typically are more open minded. And just, you know, 

[they are] freer thinkers and have more energy. Then, you know, some...professionals who’ve 

been in the field quite a while. [Students] have a fresh perspective. So, I think it’s a great 

addition and a new way to build relationships between communities and students” (p. 4).

In his work, Boyer (2016) echoes what this participant stated with acknowledgement of 

the wealth of resources anchor institutions have to share by stating “[a]t one level, the 

scholarship of engagement means connecting the rich resources of the university to our most 

pressing social, civic, and ethical problems, to our children, to our schools, to our teachers, and 

to our cities” (p. 27). This is mirrored in another personal recollection of the Tuscaloosa County 

participant who stated, “I think sometimes it’s easy to become separated from community needs 

especially in areas that are not so... you know... this is a college town, so some areas have 

institutions, but they’re not college towns. And so, I really appreciate how the university has 

taken charge and [addressed] homeownership in Tuscaloosa. [T]here’s something I really 

appreciate about the university and I’ve seen over my time here. They’re responsive to the need, 
29

they’re in a position with resources, with research abilities, with grant capabilities, with student 

bodies, literally, you know, to actually perform the work, and they respond to the call.”

Dodd (2017) echoes the sentiment regarding the ways in which Universities make efforts 

to engage with their community, as it can provide valuable research opportunities. Dodd states 

“[s]ervice-learning, when done effectively, can extend beyond teaching and service to 

incorporate research that addresses authentic and complex social issues of relevance to the 

community and, therefore, the university it serves” (p. 186).

Key Findings/Conclusions

Homebuyer readiness for our purposes consists of overcoming the barriers that prevent 

LMI individuals and families from accessing affordable, sustainable homeownership. The most 

common obstacles (within the scope of our financial coaching program) are access to 

conventional/mainstream banking system, savings, money management, debt management, and 

knowledge of credit. 

Our results show that participants enrolled in our program were able to increase access to 

banking as evidenced by opening new savings or checking accounts, reduced reliance on 

predatory lending products, such as payday or title loans, and fewer participants reported being 

unbanked. Participants increased the frequency and amount saved during the program, reported 

an increased use a of a budget or spending plan, high confidence in managing their money, an 

increase in credit scores and high confidence in their ability to increase their score in the future. 

Evidence from our pilot study shows that the gains made are significant and participants were 

able to maintain the gains after the program was over. 

One area of interest and possible future study is the seeming incongruence of 

participant’s confidence in their ability to set and achieve a financial goal and their perception of 
30

their credit history. The expectation might be for those who view their credit history negatively 

to also have less confidence in their ability to set and achieve financial goals. However, this is 

not the case in our study participants. In 2019 only 12% of participants described their credit as 

good or very good, conversely a majority of participants (62%) indicated they were very 

confident in their ability to set and achieve a financial goal. More than current perceptions of 

creditworthiness, this confidence could be a factor in whether a participant accepts the offer of 

financial coaching or a factor in successful completion of the program. This insight could inform 

how financial coaching is offered (marketed) to participants with less confidence. As was shown 

previously, misconceptions about credit history, how to improve credit scores, what is 

considered a good credit score, as well as overconfidence could lead participants to make less 

favorable financial decisions. 

The population of the participants in the HomeFirst program consists of a higher-thanexpected percentage of participants who reported attending at least some college. A recent report 

by the Pew Research Center documents a significant increase in college attendance by low- to 

moderate-income individuals (Pew Research Center, 2019), which could account for the higherthan-expected number. Future research is suggested in the area of college attendance, student 

loan debt, and the relationship to financial capability. 

Another area for future study includes whether LMI borrowers are more likely to accept 

an offer of financial coaching through an anchor institution compared to similarly structured 

programs conducted through a social service agency. Anecdotal evidence from study participants 

suggest that the student coaching model in an academic setting carries less stigma and therefore 

participants may be more willing to accept an offer of financial coaching. 

This study also determined financial capability is essential to the financial well-being of 
31

LMI households. Initial results over a two-year pilot program suggest the HomeFirst program 

had positive impacts on the financial capability of participants. Individuals in the program 

experienced a 1.7-point average increase in Financial Capability Scale scores through program 

involvement. Average changes in pre-, post- FCS scores were consistent and, in some cases 

slightly higher than similar financial coaching programs (Cohen, Hoagland, & Wiedrich, 2017). 

Participants who completed the HomeFirst program observed positive changes in their saving 

habits, money management, access to banking, credit profile, level of debt, and homebuyer 

readiness.

By offering a participant-centered, service delivery approach, the HomeFirst program 

was able to more effectively support households on their path toward homeownership. 

Individuals felt a heightened ability to achieve their financial goals. Through forming meaningful 

relationships among participants, undergraduate student coaches, The University of Alabama,

and asset-building organizations, the HomeFirst approach offers low- to-moderate income 

households the resources and support they need to enter the pool of potential successful, 

sustainable homeowners.

Furthermore, there is an increased need for anchor institutions to address the external 

structural conditions contributing to financial capability, to ensure every individual has the 

ability and opportunity to reach their financial goals in an inclusive financial market. Through 

continued partnership and increased collaboration with area nonprofits, local government 

entities, financial institutions, and community stakeholders, The University of Alabama is in a 

position to effectively build a strong infrastructure of support for all households seeking financial 

stability, including those underserved markets as designated by DTS.

Finally, colleges and universities have a long-standing history of serving as change 
32

agents in local communities and for helping to bolster economic development. Since the 

establishment of land-grant universities in 1862, the purpose of higher education has been to 

serve the community, primarily through research and education (Olinger, Reece, & Usher 2015). 

More recently, over the past three decades, colleges and universities have renewed this civic and 

social mission through the development of civic engagement initiatives, service-learning 

programs, and more recently through adopting the anchor mission.

There is additional opportunity for anchor institutions to work collaboratively with 

communities and social service agencies in order to fill gaps to build a more complete 

infrastructure of support. Participants expressed the true “sparkle” of the program was the dignity 

and self-worth the program offered participants. We have reason to believe there is an 

opportunity for this program to be a direct promoter of social justice and can help to break 

structural inequalities (e.g. generational poverty) while working on financial capability. 

Considering the conversations and actions occurring around our nation focused on racial justice 

and reconciliation, in its small way, this program, offered at an anchor institution, offers a 

helpful and collaborative way of combating historic disenfranchisement.

College students can be in the family of social service providers and can provide us 

insight on how to deliver services. We hope to have the opportunity in the future to explore the 

sense of community, respect, and facilitation in an inclusive environment that was experienced

by participants. However, for now, anchor institutions have a history in their local communities 

and can add value. Therefore, it is our position that service-learning programs at anchor 

institutions should get to work contributing to increasing homebuyer readiness through financial 

capability.
33

References 

Alabama Possible. (2020). Barriers to Prosperity Data Sheet. Retrieved from 

https://alabamapossible.org/programs/datasheet/.

An, X., Bostic, R.W., and Yao, V. (July 15, 2015). Financial Literacy and Mortgage Credit: 

Evidence from the Recent Mortgage Market Crisis. Retrieved from SSRN: 

https://ssrn.com/abstract=2631948.

Boyer, E.L. (2016). The Scholarship of Engagement. Journal of Higher Education Outreach and 

Engagement, 20(1), 15–27.

Brown, S.R. (2016). The influence of homebuyer education on default and foreclosure risk: a 

natural experiment. Journal of Policy Analysis and Management, 35(1), 145–172.

CFPB. (2015). Financial Well-Being: The Goal of Financial Education. Consumer Financial 

Protection Bureau. Washington, DC. 

CFPB. (2015). Measuring financial well-being: A guide to using the CFPB financial well-being 

scale. Washington, DC: Consumer Financial Protection Bureau. 

Cohen, P., Hoagland, E., and Wiedrich, K. (2017). Prosperity Now. Measuring Financial 

Capability and Well-Being in Financial Coaching Programs. Retrieved from 

https://prosperitynow.org/files/resources/Measuring%20Financial%20Capability%20and

%20Wellness%20in%20Financial%20Coaching%20Programs.pdf.

Collins, J.M. & O’Rourke, C. (2013). Finding a Yardstick: Field testing Outcome Measures for 

Community-based Financial Coaching and Capability Programs. University of 

Wisconsin-Madison Center for Financial Security. Retrieved from 

https://fyi.extension.wisc.edu/financialcoaching/files/2013/07/Report_Final.pdf.

Department of Housing and Urban Development (2019). Retrieved 

from https://www.huduser.gov/portal/datasets/il/il2019/select_Geography.odn.

Dodd, A. (2017). Finding the community in sustainable online community engagement: Not-forprofit organization websites, service-learning, and research. Gateways: International 

Journal of Community Research and Engagement, 10, 185–203.

Dubb, S., McKinley.S, & Howard, T. (2013). The anchor dashboard: Aligning institutional

practices to meet low-income community needs. Retrieved from 

http://www.aecf.org/resources/the-anchor-dashboard-1.

Economic Development Partnership of Alabama (2019). Retrieved from

http://www.advantagealabama.com.
34

Federal Housing Finance Agency (2020). Duty to Serve: Program Overview. Retrieved from

https://www.fhfa.gov/PolicyProgramsResearch/Programs/Documents/DTSProgramOverview.pdf.

Greene County, AL (2020). Retrieved from

https://censusreporter.org/profiles/05000US01063-greene-county-al/.

Grinstead, M.L., Mauldin, T., Sabia, J.J., Koonce, J., & Palmer, L. (2012). Saving for Success: 

Financial education and savings goal achievement in individual development accounts. 

Retrieved from: http://files.eric.ed.gov/fulltext/EJ952959.pdf.

Hale County, AL (2020). Retrieved from

https://censusreporter.org/profiles/05000US01065-hale-county-al/.

Herbert, C. & Belsky, E. (2008). The Homeownership Experience of Low-Income and Minority 

Households: A Review and Synthesis of the Literature. Cityscape. 

Housing and Economic Recovery Act of 2008, Public Law 110–289, July 30, 2008. (Section 

1129. Duty to Serve Underserved Markets, pp. 2703–2705). Authenticated U.S. 

Government Information GPO. Retrieved 

from https://www.congress.gov/110/plaws/publ289/PLAW-110publ289.pdf.

Kane, T.J. (1994). College Entry by Blacks since 1970: The Role of College Costs, Family 

Background, and the Returns to Education. Journal of Political Economy, 102(5), 878–

911. doi:10.1086/261958

Knoll, Melissa A.Z., and Houts, Carrie R., (2012). The financial knowledge scale: An 

application of item response theory to the assessment of financial literacy. Journal of 

Consumer Affairs, 46.3, 381–410. https://doi.org/10.1111/j.1745-6606.2012.01241.x

Levkoe, C., & Stack-Cutler, H. (2018). Brokering Community–campus Partnerships: An 

Analytical Framework. Gateways: International Journal of Community Research and 

Engagement, 11(1), 18–36. 

Metzger, J. (2012). Teaching civic engagement: Evaluating an integrative service-learning 

program. Gateways: International Journal of Community Research and Engagement, 5, 

98–114. 

Moulton, S.R, Loibl, C., Anya, S., & Collins, J.M. (2013). Borrowing Capacity and Financial 

Decisions of Low-to-Moderate Income First-Time Homebuyers, Journal of Consumer 

Affairs, 47(3), 375–403.

Moulton, S.R., Peck, L.R., Fiore, N., Gruenstein Bocian, D. & DeMarco, D. (2019). An 

Examination of Participation in Homebuyer Education and Counseling Services. Journal 

of Consumer Affairs, 53(3), 825–847. 
35

Mottola, G.R., & Kieffer, C.N. (2017). Understanding and Using Data from the National 

Financial Capability Study. Family and Consumer Sciences Research Journal, 46(1), 31–

39. 

Myhre, M.L., & Watson, N.E. (2017). Housing Counseling Works. U.S. Department of Housing 

and Urban Development | Office of Policy Development and Research. Retrieved from

https://www.huduser.gov/portal/sites/default/files/pdf/Housing-Counseling-Works.pdf.

Olsen, E.O. (n.d.). Promoting Homeownership among Low-Income Households. Retrieved from

https://www.urban.org/sites/default/files/publication/46626/411523-PromotingHomeownership-among-Low-Income-Households.PDF.

Pew Research Center, May 2019, A Rising Share of Undergraduates are From Poor Families, 

Especially at Less Selective Colleges. Retrieved from

https://www.pewsocialtrends.org/2019/05/22/a-rising-share-of-undergraduates-are-frompoor-families-especially-at-less-selective-colleges/.

Pollack, C.E., Griffin, B.A., & Lynch, J. (2010). Housing Affordability and Health Among

Homeowners and Renters. American Journal of Preventive Medicine, 39(6), 515–521. 

doi:10.1016/j.amepre.2010.08.002. 

Prosperity Now (2020). 2020 Prosperity Now Scorecard: Alabama. Retrieved from 

https://scorecard.prosperitynow.org/data-by-location#state/al.

Rohe, W.M. & Lindblad, M. (2013). Reexamining the Social Benefits of Homeownership after 

the Housing Crisis. Harvard University Joint Center for Housing Studies.

Rothwell, D.W., Khan M., & Cherney, K., (2016) Building Financial Knowledge Is Not Enough: 

Financial Self-Efficacy as a Mediator in the Financial Capability of Low-Income 

Families, Journal of Community Practice, 24(4), 368–388.

Shanks, T.R. (2007). The Impacts of Household Wealth on Child Development. Journal of 

Poverty, 11(2), 93–116. doi:10.1300/j134v11n02_05

Sherraden, M.S. (2013). Building blocks of financial capability. In J. Birkenmaier, M.S. 

Sherraden, & J. Curley (Eds.), Financial education and capability: Research, education, 

policy, and practice (pp. 3–43). New York, NY: Oxford University Press.

Sherraden, M.S., Huang, J., Frey, J.J., Birkenmaier, J., Callahan, C., Clancy, M.M., & Sherraden, 

M. (2015). Financial capability and asset building for all (Grand Challenges for Social 

Work Initiative Working Paper No. 13). Cleveland, OH: American Academy of Social 

Work and Social Welfare, 1–29.

The University of Alabama. (2019). HomeFirst Metrics Report 2019. Retrieved from

http://ccbp.ua.edu/homefirst/.
36

Tuscaloosa County, AL (2020). Retrieved from

https://censusreporter.org/profiles/05000US01125-tuscaloosa-county-al/.

U.S. Census Bureau (2018). Sex by Educational Attainment for the Population 25 Years and 

Over American Community Survey 1- year estimates. Retrieved from 

https://censusreporter.org.

U.S. Census Bureau (2014-2018). Tenure American Community Survey 5-year estimates.

Retrieved from https://censusreporter.org.

U.S. Census Bureau (2014-2018) Units in Structure American Community Survey 5-year 

estimates. Retrieved from https://censusreporter.org.

U.S. Department of Housing and Urban Development [HUD]. (2020). FY 2020 Income Limits 

Documentation System. Retrieved from 

https://www.huduser.gov/portal/datasets/il/il2020/2020MedCalc.odn.

U.S. Department of Housing and Urban Development [HUD]. (2019). Retrieved from 

https://www.huduser.gov/portal/datasets/il/il2019/select_Geography.odn.

U.S. Department of Housing and Urban Development [HUD]. (2012). Paths to Homeownership 

for Low Income and Minority Households. Evidence Matters. Washington, DC: U.S. 

Department of Housing and Urban Development. 

Vogel, A.L., & Seifer, S.D. (2011). Impacts of Sustained Institutional Participation in ServiceLearning: Perspectives from faculty, staff, and administrators. Gateways: International 

Journal of Community Research and Engagement, 4, 186–202. 

Xiao, J.J., & O’Neill, B. (2016). Consumer financial education and financial capability. 

International Journal of Consumer Studies, 40(6), 712–721. 

Yates, J.J., & Accardi, M. (2019). Field Guide for Urban University-Community Partnerships. 

Thriving Cities Lab: Institute for Advanced Studies in Culture, University of Virginia. 

Retrieved from https://iasculture.org/research/publications/thriving-cities-field-guide.
37

Appendix

Table 1.

Participant Demographics at Program Intake 

Cohort 2018 2019 Total

Median Age 44 43 43

Gender

 Female 84% 96% 93%

 Male 16% 4% 7%

Race

 Black/African American 100% 97% 98%

 White 0% 3% 2%

Marital Status 

Married

Single

16%

84%

12%

88%

13%

87%

Household Size 2.6 3.1 2.8

Education 

 Vocational/Technical Training 

 Have less than HS Diploma/GED

 Earned HS Diploma/GED

 Graduated or attended college 

4%

16%

24%

56%

3%

13%

32%

52%

3%

14%

30%

53%

Employment

 Unemployed 

 Part-time 

 Full-Time 

 Self-Employed 

 Retired 

 Student 

4%

8%

80%

0%

4%

4%

10%

13%

52%

1%

1%

1%

8%

12%

59%

1%

2%

2%

Housing Type

 Rental 

 Owner

 Other

County of Residence

 Greene 

 Hale

 Tuscaloosa 

 Other 

84%

4%

12%

0%

4%

92%

4%

80%

6%

14%

33%

12%

55%

0%

81%

5%

13%

25%

10%

64%

1%

Source: Administrative program data at intake

Note: Program intake data reported n=25 for 2018 and n=73 for 2019
38

Table 2.

Participant Program Involvement

Cohort 2018 2019

Total Meetings Attended

Meeting Attendance Average

 Greene 

 Hale 

 Tuscaloosa 

 Cohort 

110

-

-

4.6

-

231

0.7

2.3

4.9

3.2

Module Completion Average

 Greene 

 Hale 

 Tuscaloosa 

 Cohort

-

-

5.5

-

2.9

5.5

5

4.4

Source: HomeFirst administrative data

Note: Program administrative data reported for n=25 for 2018 and n=73 for 2019

Table 3.

Participant Financial Capability and Homebuyer Readiness at Program Intake 

Cohort 2018 2019

Pre-Program FCS Score (0–8)

 Greene County

 Hale County

 Tuscaloosa County

 Cohort Average

-

-

 3.8

-

3.5

4.2

4.4

4.1

Pre-FCS Responses 

 Currently have a personal budget, spending plan, or financial plan

 Very confident in ability to achieve a financial goal

 Very confident in ability to come up with enough money to

 cover an unexpected expense

 Had an automatic transfer to savings

 Spending on living expenses was less than total income

 Have been charged a late fee on a loan or bill in the last two

 months

24%

36%

8%

56%

52%

44%

30%

62%

34%

38%

48%

40%

Additional Financial Assessment Questions

 Have used a payday loan in the past three months?

 Have neither checking nor savings accounts?

28%

8%

22%

11%

Source: Administrative program data at intake

Note: Program intake data reported n=25 for 2018 and n=73 for 2019
39

Table 4.

Participant Financial Capability and Homebuyer Readiness at Program Exit 

Cohort 2018 2019

Post-Program FCS Score (0–8)

 Greene County

 Hale County

 Tuscaloosa County

 Cohort Average

-

-

5.5

-

5.2

4.5

6.2

5.8

Post-program FCS Responses 

 Currently have a personal budget, spending plan, or financial plan

 Very confident in ability to achieve a financial goal

 Very confident in ability to come up with enough money to

 cover an unexpected expense

 Had an automatic transfer to savings

 Spending on living expenses was less than total income

 Have been charged a late fee on a loan or bill in the last two

 months

85%

54%

15%

69%

31%

38%

80%

69%

37%

69%

66%

31%

Additional Financial Assessment Responses

 Have used a payday loan in the past three months

 Have neither checking nor savings accounts

 Average amount saved

 Average debt paid off

 

 Reported increased savings frequency

 Reported having a bit more or far more debt than is manageable

 Reported some or a lot of progress in paying off debt

 Reported credit score improvement

15%

8%

$814

$440

54%

15%

100%

69%

9%

2%

$591

$744

69%

40%

80%

60%

Source: Administrative program data at intake

Note: Program intake data reported n=25 for 2018 and n=73 for 2019

Note: This whitepaper was commissioned by Fannie Mae under a services agreement between 

Fannie Mae and The University of Alabama. The views expressed in this whitepaper are those of 

its authors and do not necessarily reflect those of Fannie Mae. The University of Alabama thanks 

Cheryl Peterson of Fannie Mae for her feedback and suggestions.