THE IMPACT OF DIVERSITY ON HOMEOWNERSHIP
AND HOME EQUITY WITHIN RACIAL AND ETHNIC GROUPS
Jensen Dean Kile
B.A., California State University, Sacramento, 2006
THESIS
Submitted in partial satisfaction of
the requirements for the degree of
MASTER OF ARTS
in
SOCIOLOGY
at
CALIFORNIA STATE UNIVERSITY, SACRAMENTO
FALL
2009
THE IMPACT OF DIVERSITY ON HOMEOWNERSHIP
AND HOME EQUITY WITHIN RACIAL AND ETHNIC GROUPS
A Thesis
by
Jensen Dean Kile
Approved by:
__________________________________, Committee Chair
Charles Varano, Ph.D.
__________________________________, Second Reader
Randall MacIntosh, Ph.D.
____________________________
Date
ii
Student: Jensen Dean Kile
I certify that this student has met the requirements for format contained in the University
format manual, and that this thesis is suitable for shelving in the Library and credit is to
be awarded for the thesis.
__________________________, Graduate Coordinator
Amy Qiaoming Liu, Ph.D.
Department of Sociology
iii
___________________
Date
Abstract
of
THE IMPACT OF DIVERSITY ON HOMEOWNERSHIP
AND HOME EQUITY WITHIN RACIAL AND ETHNIC GROUPS
by
Jensen Dean Kile
Wealth inequality in the United States continues to widen year after year. However,
only recently has research addressed the relationship of race and wealth and few have
analyzed specific forms of wealth accumulation. Home equity is the most popular and
significant method of wealth accumulation, yet much about multiethnic equity
accumulation is unknown. Without research that explicitly identifies the most important
forms and causes of racial differences in homeownership and home equity, public policy
is less able to take appropriate and informed action against the most significant barriers to
equality. This study attempts to fill the gap in information and analyzes the role of racial
stratification within neighborhoods on the odds of homeownership and its effect on home
equity accumulation within the pan-ethnic racial groups.
This study uses hierarchical linear modeling and data from the American Housing
Survey National sample from 2005. Even while controlling for various factors in the
home equity accumulation process, this study finds discriminatory residential patterns are
constraining the market process and reducing the value appreciation of homes owned by
Hispanic and Black households. More specifically, a neighborhood level barrier exists
that is actively suppressing their wealth. Houses of Black and Hispanic homeowners in
segregated neighborhoods produce less wealth than houses in integrated neighborhoods.
Not only is the disparate access to equal housing contributing to the perpetuation of the
racial wealth divide in the United States. It is contributing to political and social
inequalities directly linked to wealth.
_______________________, Committee Chair
Charles Varano, Ph.D.
_______________________
Date
iv
To my mother, Audrey,
who has shown me that no one is ever too young to teach nor too old to learn;
To my father, Doug,
who has shown me the treasure of dedication and strong character.
v
ACKNOWLEDGMENTS
I would like express my appreciation to Professor Varano for taking me under his wing,
sharing his wealth of knowledge and insight, engaging me with ideas and concepts, and
consistently supporting my efforts with this thesis.
I would also like to express my deep gratitude to Professor MacIntosh. His many
uncounted hours of guidance, encouragement, and patience, troubleshooting and
reviewing made this thesis possible. He repeatedly went above and beyond to be of
service; for that, I cannot thank him enough.
vi
TABLE OF CONTENTS
Page
Dedication ................................................................................................................................. v
Acknowledgments.................................................................................................................... vi
List of Tables ........................................................................................................................ viii
Chapter
1. INTRODUCTION .............................................................................................................. 1
Statement of the Problem ............................................................................................ 1
Significance of the Study ............................................................................................. 3
2. LITERATURE REVIEW ................................................................................................... 8
Homeownership and Diversity .................................................................................. 10
Home Equity and Diversity ....................................................................................... 14
Theories on Wealth Accumulation ............................................................................ 17
3. METHODOLOGY ........................................................................................................... 35
Dataset ....................................................................................................................... 35
Measures .................................................................................................................... 37
Models and Estimations ............................................................................................. 45
Descriptive Statistics.................................................................................................. 47
Descriptive Statistics by Race.................................................................................... 50
4. FINDINGS AND INTERPRETATIONS ......................................................................... 56
Summary of Diversity Hypothesis Tests ................................................................... 56
Homeownership Results ............................................................................................ 57
Homeownership within Ethnic and Racial Groups .................................................... 62
Home Equity Results ................................................................................................. 68
Home Equity within Ethnic and Racial Groups ......................................................... 73
5. CONCLUSIONS............................................................................................................... 81
Review of Findings .................................................................................................... 82
Theoretical Implications ............................................................................................ 84
Strengths and Limitations .......................................................................................... 88
Implications of Findings ............................................................................................ 91
References ............................................................................................................................... 96
vii
LIST OF TABLES
Page
1.
Table 1: Descriptive Statistics of Homeowner and Equity Calculations ........... 49
2.
Table 2: Descriptive Statistics of Full Sample by Ethnic and Racial Groups ... 55
3.
Table 3: HLM Modeling of Homeownership .............................................. 58-59
4.
Table 4: Homeownership within Ethnic and Racial Groups ..............................63
5.
Table 5: HLM Modeling of Home Equity ......................................................... 69
6.
Table 6: Home Equity within Ethnic and Racial Groups .................................. 79
viii
1
Chapter 1
INTRODUCTION
Statement of the Problem
Race and wealth inequalities have long been problems in our society owing to a history
of segregation and the institutionalization of racial preferences. Due to the continued
widening of the wealth gap, the United States has had the highest level of wealth
inequality out of all post-industrial nations from the 1980’s onward (Wolff 1998; Keister
and Moller 2000; Lewin-Epstein and Semyonov 2000; Ross and Yinger 2002). In the
1990’s, several researchers estimated after more than 130 years out of slavery, African
Americans across all classes had amassed only one percent of the total U.S. wealth, while
the average net worth and median net wealth of African Americans were around one
quarter and one eighth of Whites, respectively (Blau and Graham1990; Conley 1999;
Gittleman and Wolff 2004). Other studies have focused on the Black-White gap and
found a variety of discrimination and difference from realtor and lending practices to the
quality of homes and their value increases (Henretta 1984; Parcel 1982; Oliver and
Shapiro 1995; Horton and Thomas 1998; Campbell and Kaufman 2006; Keister 2000).
However, only recently have researchers recognized the problem of studying only Black
and White in a multiethnic environment. As a result, they have studied across racial
groups and found that race inequalities in homeownership and home value differ among
racial and ethnic groups (Massey and Denton 1993; Campbell and Kaufman 2006;
Flippen 2001, 2004; Krivo and Kaufman 2004,). Despite a slow reduction of racial
2
income inequality over the past few decades as found by Gittleman and Wolff (2004),
they argue that income and wealth equality are still years away. In fact, income equality
has little effect on the racial and ethnic gap between high and low wealth (Keister and
Moller 2000; Flippen 2001; Avery and Rendall 2002; Krivo and Kaufman 2004). As the
wealth gap continues to widen we must acknowledge that the knowledge and policy
surrounding wealth is inadequate and lagging behind our understanding and efforts for
income equality. Of those researchers studying multiethnic wealth inequality, the
majority has focused on net wealth across racial groups, but few have focused on any
specific method of wealth accumulation.
Primary residences are principal factors in the growing trend of inequality, since
they are the most commonly shared asset, accounting for around forty percent of all
assets in the United States (Wolff 1998; U.S. Census Bureau 2001; Morrow-Jones 1993;
Boehm and Schlottmann 2004; Conley 1999; Ross and Yinger 2002). However, it should
not be assumed that the popularity of a wealth accumulation method is related to the
significance of that method in producing wealth. As Case and Marynchenko (2002)
demonstrate, wealth accumulation is distributed non-uniformly across markets,
socioeconomic classes and races. Likewise, Wolff (1998) finds that the majority of
wealth holdings of the nation’s wealthiest one percent are not primarily in home equity
but rather business equity, stocks and other financial investments. This is further
supported by the evidence that even as nation-wide homeownership rates continue to
decline, the top five percent of wealth holders, who have most of their investments
elsewhere, are the only group to have their wealth increase (Spillerman 2000). Despite
3
the differences between the classes, home equity through primary residences is where the
overwhelming majority of Americans, especially the middle and lower classes, invest
their wealth (Wolf 1998). Due to its popularity as a wealth accumulation method and its
significance for the majority of Americans, there is a need to understand home equity as
it relates to wealth inequality.
In addition, research has indicated that racial stratification affects the access of
minority groups to homeownership (Massey and Denton 1993; Rosenbaum1996;
González Wahl, Breckenridge and Gunkel 2007). It is also known that racial stratification
affects the value of homes differently according to race (Flippen 2004). Thus, an
understanding of wealth inequality through homeownership is twofold. It is necessary to
analyze the role of racial stratification among neighborhoods in providing access to
homeownership. In addition, once access to homeownership is controlled, the disparities
of racial stratification on home equity can be revealed. Thus, this study considers the
effect of residential diversity on racial disparities home ownership and in the values of
homes.
Significance of the Study
Homeownership and home equity appreciation are significant on many levels. The impact
of minority homeownership and home value appreciation being less than that of Whites is
important to social theories and public policy formation. Theoretically, the debate over
wealth accumulation has often resided in research concerning the role of socioeconomic
status, employment, and income. Until the past two decades, alternative methods of
4
wealth accumulation, including home equity and racial effects have generally been
ignored (Blau and Graham 1990; Flippen 2001; Krivo and Kaufman 2004). Without
research that specifically identifies the most important forms and methods of racial
differences in homeownership and home equity, many have argued that policy makers are
less able to take appropriate and informed action against the most significant barriers to
equality (Conley 1999; Castañeda, Díaz-Giménez, Ríos-Rill 2003; Krivo and Kaufman
2004; Flippen 2004).
Homeownership itself, aside from equity, is significant on many levels. Logan
and Molotch (1987) highlight the distinct ability of real estate to act simultaneously as a
commodity with an exchange value as well as a site with many use values. Many authors
have identified various use benefits of homeownership. These include; access to jobs,
schools, social and support networks, physical shelter, the social prestige and identity of
homeownership, as well as the psychological benefits of safety and solidarity (Logan and
Molotch 1987; Alba and Logan 1992; Morrow-Jones 1993). In an effort to highlight the
need for shared public space, Mitchell (2003) affirms the ability of property ownership to
serve as a protected place that simply allows one to exist. He goes further to suggest that
self-representation requires physical space. In agreement, many scholars have recounted
the historical correlation between the ownership of property and public voice and civic
rights (Boehm and Schlottmann 2004). Homeownership is more than a simple luxury and
financial nest egg; it is socially significant in reproducing inequality in experiences,
rights, and wealth.
5
Additionally, the existence of wealth inequality in a representative democracy
translates into to power and political inequality, wherein society stockpiles resources and
opportunities in favor of one group and fails to support the competitive potential, ideas,
skills, and abilities of the out-group (Massey and Denton, 1993; Conley 1999). Over each
generation, the perpetuation of inequality becomes more entrenched. Another significant
value of wealth is its ability to hedge against emergency financial needs that can often
cause a snowball effect for those without consumable wealth independent of income
(Spillerman 2000:500; Lewin-Epstein 2000). Home equity, although not as liquid as
other forms of wealth, can provide access to lines of credit for everything from
transportation to advanced education. The existence of inequalities in access to
homeownership is well documented by researchers regarding the impact of residential
segregation and the disparity in housing quality between Whites, Blacks, Hispanics and
Asians (Alba and Logan 1992; Massey and Denton 1993; Krivo 1995; Frey and Farley
1996; Logan and Stults 2000; Rosenbaum and Friedman 2001; Fischer 2003). Despite
many suggesting the relationship of equity to racial and ethnic stratification be studied
(Parcel 1982; Horton 1992; Alba and Logan 1992; Yinger 1995; Conley 1999; Flippen
2001), research regarding the relationship of race and home equity is merely in its
infancy (Blau and Graham1990; Flippen 2001; Krivo and Kaufman 2004). Out of these,
only Krivo and Kaufman (2004) have studied the interaction of institutional and social
contexts of the market and the neighborhood on equity accumulation.
A wide array of research has highlighted the failure of national programs and
federal policies at curbing inequality’s growth, mostly due to ignorance surrounding the
6
systematic disadvantage minority groups face due to the social and geographical
characteristics of mortgage and housing markets (Yinger 1995; Oliver and Shapiro 1999;
Ross and Yinger 2002; Krivo and Kaufman 2004). Similarly, other researchers suggest
that regional differences in market equality and racial intolerance are central to
understanding inequality (Kiel and Zabel 1995; Xiao Di and Liu 2004; Gonzales Wahl,
Breckenridge and Gunkel 2006). Multiple studies have revealed that cities and
neighborhoods are diversifying and segregating differently based on regional and racial
characteristics. Many regions and neighborhoods in the West have increased in diversity,
especially along Black, White, and Hispanic lines (Logan, Stults and Farley 2004).
Sandoval, Johnson and Tafoya (2002) report that between 1990 and 2000 diversity
indexes across California nearly tripled, which challenge many prior theories of racial
preferences in neighborhood selection (Massey and Denton 1993; Bobo and Zubrinsky
1996). Nevertheless, certain groups and locations face segregation increases, thus Logan,
Stults and Farley (2004) suggest more attention is needed on Hispanic and Asian
neighborhoods, which would include research on the role of diversity on homeownership
and equity.
Although it is a secondary focus of their research, Krivo and Kaufman (2004)
analyze the effects of mortgage characteristics and the ethno-racial context of
metropolitan housing in their study of equity inequality, and found them to be significant.
However, their study of metropolitan context is limited to percentages of specific
minorities in the region. Furthermore, only a Black-White dissimilarity index was used,
leaving out multi-group segregation and the wide variety of minority and majority
7
association and interaction. This leaves room for a more concentrated study on the role of
residential segregation and home equity.
Past research identifies a significant link between racial residential segregation
and inequality, yet virtually no research has studied the relationship of residential
diversity on home equity. Krivo and Kaufman (2004) took a crucial step in that direction,
but were unable to analyze the relational nuances of racial diversity and wealth through
home equity. Since home equity is a critical portion of wealth and directly tied to factors
affecting homeownership and racial inequality, it deserves continued inquiry within and
across racial groups. Furthermore, as cities and neighborhoods become more diverse, our
understanding of the role of diversity in homeownership and home equity is necessary to
fill a gap in academic knowledge as well as inform future social policy.
8
Chapter 2
LITERATURE REVIEW
An abundance of knowledge surrounding homeownership and wealth inequality has been
garnered by past research. However, most of it has focused on a monetary based
perspective that highlights the accumulation of life cycle characteristics such as length of
residency, income, and employment and often ignores racial and ethnic differences
(Mutchler and Krivo 1989; Krivo 1995; Alba and Logan 1992; Lewin-Eppstein 1997;
Rosenbaum 1996; Caroll 1997). Other studies have included assimilation characteristics
(Rosenbaum 1996; Alba and Logan 1992; Krivo and Kaufman 2004) and stratification
characteristics (Horton and Thomas 1998; Massey and Denton 1993; Bobo and
Zubrinsky 1996; Spillerman 2002; Krivo and Kaufman 2004) in relation to home equity.
Of those considering stratification, Black-White inequalities dominate past and current
knowledge (Parcel 1982, Blau and Graham 1990; Oliver and Shapiro 1995; Conley 1999;
Deng 2002; Freeman 2005). Only recently have other ethnic and racial groups, primarily
Asian and Hispanic and sometimes their subcategories, been the focus of studies
(Campbell and Kaufman 2006; Flippen 2001; Krivo and Kaufman 2004; Herbert and
Kaul 2005; Kim and White 2005). The few researchers who have addressed the need for
research reflecting the diversity of our nation have contributed immensely to the
modification of historic theories on race and produced significant knowledge that is
useful to new theories and public policy. For the purpose of this research, it is necessary
to review current literature on race and homeownership as well as the role of race on
9
equity1. Since past research has also identified the four significant theoretical areas
affecting homeownership equity, it is necessary to highlight research that has discussed
life cycle, assimilation, stratification and financial factors in order to be aware of their
established effects on homeownership and home equity.
Furthermore, only in the past decade has research addressed the effects of
diversity on social stratification (Charles 2000; Alba, Logan and Stults 2000a; Gonzales
Wahl, Breckenridge and Gunkel 2006; Freeman 2000; Kim and White 2005; Nyden,
Lukehart, Maly and Peterman 1998). What makes research on diversity difficult is that
the studies on diversity have often applied different definitions of diversity. Most
research defines diversity at the metropolitan or neighborhood level, usually defining the
percent of a minority group in relation to Whites (Krivo and Kaufman 2004; Deng 2002;
Charles 2000). Although the majority of studies focus on diversity along Black and White
racial lines, recent research has looked at multi-group diversity among the pan-ethnic
categories of White, Asian, Hispanic and Black (Kim and White 2005; Putnam 2007).
Diversity has also been defined as mixed or multiethnic individuals (Kim and White
2005). At an individual level, diversity continues to grow as more children come from
multiethnic families and as individuals self-identify as multiple ethnicities. Due to the
1
Although race is a classification based on physiological characteristics and ethnicity based on cultural
differences, racial and ethnic differences in both cases are usually related to traits that become powerful
symbols based on stereotypes connected with visible and linguistic identifiers. Since group differences
affect ethnic and racial groups regardless of their official categorization, the two terms are used as
synonyms in this study. Because ethnic titles are symbols, they can also oppress those who are labeled
since they do not adequately account for the great level of diversity within. This research will use the
survey terms “White,” “Black,” “Hispanic” and “Asian” to represent the pan-ethnic categories rather than
“African American,” “Hispanic American,” and “Asian American,” since they imply a distinction between
ethnicity and citizenship not applied to Whites.
10
changing trends and high levels of diversity in the Western states, one quarter of
California’s youth is now multiethnic (Kim and White 2005). Kim and White (2005)
research the pan-ethnic groups (White, Black, Latino and Asian), as well as the vast
majority of sub-ethnic groups within and have shown great diversity within the panethnic groupings. Asian ethnicities were found to have the widest range of diversity
between the sub-ethnic groups, while White ethnic group differences were the most
homogenous. This contrast suggests that Whites are more likely to experience similar
opportunities and events regardless of their ethnic background. More importantly, the
differences between the pan-ethnic groups overall are greater and more significant than
the differences within. Since this research focuses on household wealth, it is essential to
understand relevant research on metropolitan, neighborhood household diversity, and its
known effect on pan-ethnic racial groups.
Homeownership and Diversity
It does not take long to find research identifying the continued existence of
discriminatory processes towards minorities in mortgage lending practices such as,
redlining, racial and ethnic steering, predatory and subprime lending, or explicit denial
from brokers (Turner 1992; Massey and Denton 1993; Oliver and Shapiro 1995; Yinger
1995, 1997). Meanwhile, realtors are also found to screen properties, charge higher
lending costs, restrict information, and less enthusiastically pursue client relationships
based on race and ethnic differences (Yinger 1997). These practices influence the quality
and amenities of neighborhoods being shown to minority clients, or force minorities pay
11
more to seek better housing, resulting in lower loan to value ratios (Massey and Denton
1993; Bobo and Zubrinsky 1996; Alba, Logan and Stults 2000a; Charles 2000; Flippen
2001; Rosenbaum and Friedman 2001). The researchers who have explored the financial
factors leading to homeownership suggest that there is a “minority tax” or monetary
premium paid by minorities to achieve homeownership equal to that of Whites (Alba and
Logan 1992; Yinger 1995; Flippen 2001). It is further estimated that Blacks pay on
average $3,680 more than Whites for each time they take on a search for a new home
(Yinger 1997:364). This cost is measured by subtracting from the surplus gained from
purchasing a new house, the financial effects of minority discrimination; including the
estimated costs of redlining by mortgage brokers. In addition, reductions are made for the
lower volume and lower value of homes shown to minorities by real estate brokers, the
difficulty searching for and receiving loans, and the cost of switching lenders and brokers
due to discrimination (Yinger 1997). It is purely a higher cost based on race. Though past
research has also found that across racial groups and income levels, the desire to own a
home is generally similar; the act of pursuing homeownership is not equalized and does
not produce equivalent outcomes (Alba and Logan 1992; Conley 1999). Despite income
levels, minorities are less likely to own homes than Whites, even with their homes often
being of lower value and quality (Alba and Logan 1992; Conley 1999, Rosenbaum 1996;
Flippen 2001; Krivo and Kaufman 2004). Recently, Asians have slowed in their increase
in homeownership, yet they have maintained higher rates of homeownership above other
minority groups; even so, neither their rates, nor the value and quality of their homes
12
seem to be equivalent to Whites (Flippen 2001; Krivo and Kaufman 2004; Herbert and
Kaul 2005).
Initially most of the national housing policies from the Fair Housing Act in 1968
to the Federal Housing Enterprises Financial Safety and Soundness Act of 1992 produced
little discernable improvement, and at times often created homeownership that is more
segregated. However, recent research has linked the current increase in minority
homeownership to the Federal Housing Administration’s (FHA) approval of Fannie Mae
and Freddie Mac which have reached beyond traditional governmental loans to extended
homeownership opportunities to those living in “underserved” or low income areas
(Herbert and Kaul 2005; Freeman 2005). Still, Herbert and Kaul (2005) have identified
an unequal racial distribution of homeownership under these programs, wherein Asians
are more likely to gain homeownership using Fannie Mae and Freddie Mac than Blacks
and Hispanics regardless of income and underserved status. This suggests that without
adequate knowledge, public policies and programs are affected by racial discrimination,
causing further racial differences in homeownership.
Another racial difference in homeownership is found in the higher rates of
minorities than equivalent Whites who transition from owning back to renting. Over
thirty-seven percent of all homeowners transition back to renting, with Blacks and other
low-income minorities being the most likely to transition from homeownership to renting
(Marrow-Jones 1993; Boehm and Schlottmann 2004; Keister and Moller 2004). In terms
of wealth accumulation, the loss of homeownership results in a loss of wealth and denies
the household of using wealth accumulated from prior ownership towards future home
13
purchases. Equality in homeownership may be more significant for the wealth
accumulation of minority groups since their homeownership is less stable and therefore at
greater financial risk. This risk factor may be one of the many reasons why Blacks are
less likely to move from renters to owners.
Past researchers have debated over the influence of self-segregation by minorities
on residential locations versus systemic segregation. Many researchers have found that
Whites distance themselves from minority groups according to racial prejudice, as well as
economic and safety concerns (Grant and Parcel 1990; Farley et al 1994; Herbert and
Kaul 2005). After collecting neighborhood preferences between Whites and Blacks,
Farley and colleagues (1994) found that Blacks are much more likely to prefer to live in
mixed residential areas, while Whites overwhelmingly prefer homogeneity. This echoes
Massey and Denton (1993) in claiming that residential segregation, at least at some level,
is inevitable since interracial neighborhoods cannot stabilize due to racial differences in
comfortable levels of integration. Thus, as neighborhoods diversify, Whites “flight” to all
White neighborhoods, rendering the original neighborhood once again segregated.
Although “white flight” is a current practice, the popularity and instability observed in
the 1970’s and 1980’s have improved in recent decades (Yinger 1995, Nyden et al.
1998). Though diverse communities are often considered the future of urban America,
predominantly Black neighborhoods are the least likely to become integrated out of
minority neighborhoods (Herbert and Kaul 2005). The slight decline in Black-White
segregation suggests that racial stratification in American conscience and public policy
14
may be improving. However, the slight increase in Hispanic segregation implies that
racial perceptions may only be changing and in need of further research.
Although there may be slight variation by region and cities, research across racial
groups has found that there still exists a clear racial hierarchy in American society. One
in which Blacks are least desired neighbors by all racial groups, followed by Hispanics,
then Asians, with Whites as the most preferred group across the board (Massey and
Denton 1995; Nyden et al 1998; Zubrinsky 200; Krivo and Kaufman 1999). According to
this hierarchy, Blacks may benefit from living in mixed neighborhoods of any racial
group, since their status in society will only improve through association with groups
perceived to have higher status. Under this hierarchy, Asians would distance themselves
from predominantly Black, Hispanic and Asian areas, and seek residency in White
neighborhoods. In a similar manner, Hispanics prefer to avoid predominantly Hispanic
and Black communities for integrated White and Asian neighborhoods. The racial
hierarchy outlined here is evident in nearly all multiethnic research on wealth inequality,
wherein the Black-White wealth gap is much larger than the Asian-White gap.
Home Equity and Diversity
Although income inequality has often been the main argument against wealth inequality,
the recent decrease in the income gap across racial groups has had little effect on the
widening wealth gap (Avery and Rendall 2002; Gittleman and Wolff 2004; Xiao Di and
Liu 2004). Wealth inequality in the United States continues to grow exponentially along
class and racial lines (Straight 2002; Hurst, Lough, Stafford and Gayle 1998; Conley
15
1999; Xiao Di and Liu 2004). Researchers who have isolated the elements of net wealth
find that homeownership of primary residences accounts for the single most important
asset (44 percent) for the majority of Americans, and particularly so for minorities and
low income households who have over seventy percent of their wealth in home equity
(Yinger 1995; Wolff 1998; Spillerman 2000; Restinas and Belsios 2002). Because of the
use value of homes, they are the most commonly shared asset across race and class lines
(Yinger 1995; Conley 1999; Keister and Moller 2000; Flippen 2001). Thus, a primary
residence is usually the first wealth investment a household makes, leaving other types of
wealth, such as business equity and stocks, for later financial investments (Boehm and
Schlottmann 2004). Boehm and Schlottmann (2004) also recognize that homeownership
is not a guarantee for successful wealth accumulation, especially because many areas
may lose or gain property value at different rates based on factors beyond the
homeowner’s control. However, segregation by neighborhood tends to isolate value
difference for minority neighborhoods (Massey and Denton 1993). This practice
perpetuates the financial strength of White neighborhoods as well as negative stereotypes
for minorities.
In 1992, Oliver and Shapiro (1995) found that while a large proportion (25
percent) of Whites had zero or negative net wealth, an incredibly large number of Blacks
(60 percent) had zero or negative net wealth. Due to the racial gap and lower success in
wealth accumulation, many researchers have questioned the logic of the poor and
minorities who decide to invest in home equity. Whether or not it is the wisest
investment, the researchers have recognized that many poor and minorities do not have
16
access to alternative forms of wealth accumulation (Hurst et al. 1998; Chiteji and Stafford
1999; Spillerman 2000). Investments in other forms of wealth, such as those provided by
employers (IRA, 401K plans and pensions), may be limited by employment
opportunities, their reluctance or inability to invest in stocks, as well as the limitations of
asset ownership of the poor by state and federal poverty programs (Spillerman 2000).
Thus, except for the poorest of the poor who cannot invest in housing, it seems home
equity is one of the few investment options available to minorities and the lower classes
(Keister and Moller 2000; Spillerman 2000). The lack of alternative investment methods
is even more significant when the values of homes are compared across racial groups. Of
those able to achieve and maintain a significant investment in home equity, Blacks and
Hispanics end up with lower value and quality homes than Whites and Asians regardless
of their socioeconomic status (Bianchi, Farley and Spain 1982; Horton and Thomas 1998;
Flippen 2001; Krivo and Kaufman 2004; Gittleman and Wolff 2004). Research on Black
and White home values has also found that Blacks, and possibly all minorities, must
over-invest their financial assets to gain comparatively sized and similar quality homes as
Whites (Blau and Graham1990; Marrow-Jones 1993). The higher costs of adequate
housing and the lower value result in lower equity for many minority groups.
It is known that equity differences are related to discrimination and segregation,
and that higher percentages of Asians and Hispanics in an area are negatively associated
with equity accumulation (Krivo and Kaufman 2004). Likewise, it has been found that
predominantly White neighborhoods are associated with higher rates of equity growth
(Parcel 1982). However, the role of multiethnic neighborhood diversity on wealth
17
accumulation is unknown. Based on established findings of stratification, it is
hypothesized that Blacks and Hispanics will have higher equity gains than Asians and
Whites in an integrated multiethnic community than they would in a segregated
community. Alternatively, researchers who have done in-depth studies on integrated
neighborhoods have found that it takes a conscious effort by community groups, schools,
public organizations, real estate brokers and banks in order to maintain stable levels of
diversity and equality (Yinger 1995; Nyden, et al. 1998; Lopez 2001). This level of
conscious involvement may also indicate that in diverse neighborhoods, Whites and
Asians work in partnership with the more stigmatized groups to achieve collective
neighborhood quality and shared levels of equity accumulation. This would result in a
hypothesis that as diversity increases, wealth inequality decreases.
Theories on Wealth Accumulation
Life Cycle
In order to identify the most significant causes, past studies of wealth accumulation have
used a variety of theories. These theories have uncovered significant factors that affect
homeownership and wealth accumulation. Thus, it is imperative that their roles are
understood so that they can be accounted for whenever possible. The most commonly
studied theory is the Modigliani’s life cycle thesis, which suggests that net wealth is
accumulated in a bell-shaped curve, reaching its highest point right before retirement,
after which, wealth is spent or transferred (Keister and Moller 2000). This theory
predominantly considers age, income, steady employment and savings as factors leading
18
to stable increases in wealth. Researchers studying wealth have also included family size,
marital status, gender, and even length of residency as indicators of factors that will
increase or limit the accumulation of wealth. Most research has found that wealth is
significantly affected by the life cycle and demographic factors (Alba and Logan 1992;
Hurst et al 1998; Flippen 2001; Krivo and Kaufman 2004). However, the life cycle
analysis has also been critiqued for its inability to explain away the racial wealth gap.
Carroll (1997) concludes that the working class saves primarily for emergencies rather
than retirement. Instead of a target cumulative savings, most save and consume in
proportion to their income (Carroll 1997). Similarly, Mutchler and Krivo (1989) suggest
that political factors and economic conditions influence savings as well. Consequently, it
can be assumed that retirement and intergenerational transfers are not a primary focus of
all economic classes. Likewise, when all life cycle factors are controlled, race still has an
effect on stratifying wealth (Keister and Moller 2000; Flippen 2001; Krivo and Kaufman
2004). Due to their significance even when race is included, life cycle factors must be
considered and controlled in any study across racial groups. Yet, their weakened
significance once race is included suggests that alternative theories may also apply.
Assimilation
Just as the life cycle framework assumes that race is not significant after the proper
variables are controlled, assimilation theories assume that once human capital and life
cycle characteristics are controlled, race will be a non-significant factor (Rosenbaum
1996). Assimilation theory suggests that the racial differences left over after life cycle
19
characteristics are related to characteristics stemming from recent movement into the
American culture. The characteristics, such as language, immigration status, years in the
United States and relationships with non-immigrants, are assumed to have an effect on a
household’s understanding of the housing market and their financial options (Krivo and
Kaufman 2004). In short, assimilation theories presume racial differences are essentially
differences in knowledge and social capital (Alba and Logan 1992). Therefore,
appropriate assimilation would distribute home equity equally among racial groups.
Interestingly, among Asians and Hispanics, the rates of homeownership and equity of
immigrants tend to be higher than their native-born counterparts (Krivo and Kaufman
2004). This is likely due to immigrant movement into transitory neighborhoods until their
social networks are established (Massey and Denton 1993). It has also been suggested
that many immigrants may originate from the more affluent classes in their country of
origin. In their landmark study, Massey and Denton (1993) highlight the prevalence of
ghettoes as permanently confining areas, which have a stronger effect on Black
investment opportunities compared to Hispanics, and Asians who often live in more
transitional enclaves. Although Blacks have long history of legal and de jure
hypersegregation, they have had longer exposure to American culture than other minority
groups, which can explain why their perspectives and knowledge of homeownership and
equity accumulation are similar to that of Whites. However, Blacks as a group have the
least amount of combined wealth, suggesting that there are structures privileging Whites
over minorities beyond individual level control or simply a culture of poverty (Yinger
1995).
20
Stratification
Because of racial differences remaining after life cycle and assimilation factors are
controlled, theories of stratification have evolved to encapsulate the idea that stratified
racial groups in the United States are ranked according to their level of stigmatization in
the society (Alba and Logan 1992; Massey and Denton 1993; Avery and Rendall 2002;
Flippen 2004). These perceptions are also assumed to be embedded in society’s
institutions and are perpetuating inequality through their normal operation (Grant and
Parcel 1990; Massey and Denton 1993; Flippen 2004). A principle feature of American
residential segregation is that it is racial, wherein virtually all Blacks are segregated from
Whites regardless of income or class (Massey and Denton 1993; Farley, Steeh, Krysan,
Jackson and Reeves 1994; Avery and Rendall 2002). Thus, when Flippen (2004) finds
that Hispanics and Asians are less disadvantaged than Blacks are, it reflects the fact that
they are also less stigmatized by the dominant social structures. Stratification is evident in
residential segregation practices in American society and urban policies, which have
created or supported ghettoes rather than transitional enclaves especially among Blacks.
Since stratification elements are embedded in social life and institutions, they are likely to
influence ethnic groups even within diverse communities; however, their effect is
assumed to weaken.
21
Life Cycle Characteristics
Age
The age of adult householders is a significant factor in homeownership and home equity,
mostly due to the ability of older households to garner wealth and employment that
would support homeownership (Bianchi, Farley and Spain 1982; Alba and Logan 1992;
Hurst et al. 1998; Conley 1999). However, the inclusion of race significantly affects the
effect of age. Although the majority of wealth is concentrated in households over age 45,
the age of home owners is often more significant for Whites, since even at a young age, it
takes the median wealth of 18 Blacks to equal the medium wealth of one average White
home owner (Parcel 1982; Hurst et al. 1998; Gittleman and Wolff 2004). Age is also a
factor in homeownership stability and equity accumulation since the return of
homeowners to renting is most likely among young homeowners (Marrow-Jones 1993).
Education
Just as age is more significant among Whites than minorities, higher education is more
likely to increase homeownership for Whites than it does for minorities (Horton and
Thomas 1998). Flippen (2001) argues that the significance of education on
homeownership is debatable, yet it is highly significant in the accumulation of home
equity. There are two identified reasons for why education affects homeownership and
equity. In terms of homeownership, education is significantly linked with higher income
and perhaps an expectation to own (Conley 1999; Alba, Logan and Stults 2000a; Xiao Di
and Liu 2004). In terms of equity, studies on education and the racial preference of
22
neighborhoods show clear indications that higher education is associated with prudent
home acquisitions, as well as the increase of minorities in White neighborhoods (Bobo
and Zubrinsky 1996; Conley 1999; Alba, Logan and Stults 2000a). Though minorities
with higher education are more likely to be included in White neighborhoods, their
neighbors are more likely to have greater wealth (Alba, Logan and Stults 2000a). This
would suggest that education would positively affect homeownership odds and home
equity across racial groups.
Marital Status
Due to the reality that marriage combines two previously independent social networks
and asset accumulations, marriage is found to be significant in nearly every study (Parcel
1982; Krivo 1995, Myers and Woo Lee 1998; Conley 1999; Juster, Smith and Stafford
1999). However, research has long found disparities in the role of marriage in non-White
households. For instance, Krivo (1995) found marriage less significant for Hispanics than
Whites, while others have found marriage less significant for Blacks than Whites (Parcel
1982; Flippen 2001). A plausible cause of the insignificance is the lower amounts of
wealth available for minority households to merge as well as the lower rates of marriage
among Blacks (Parcel 1982). This study expects that marriage is significant towards
homeownership odds and home equity for all racial groups, yet it is expected to be most
significant for Whites.
23
Employment
Because income for the majority of Americans is dependent on their employment,
employment is significant in increasing wealth and providing a higher rate of
homeownership (Conley 1999; Juster, Smith and Stafford 1999). Though employment is
not necessary for having an income, it is assumed that the majority of the population
would not make an investment without a reliable source of income to back the
investment. Consequently, employment has been found to be a significant factor in
homeownership as well as home equity (Krivo and Kaufman 2004).
Household Income
Household income has a unique influence on wealth accumulation and homeownership,
since income not only has a hand in creating wealth but also derives from it (Keister and
Moller 2000). The direct effects of income are often difficult to study, since not all
income is consumed, nor is it saved as wealth at a consistent rate (Blau and Graham
1990). However, income is found to have a positive, non-linear effect on homeownership
and home equity across all racial groups (Alba and Logan 1992; Horton and Thomas
1998; Boehm and Schlottmann 2004; Xiao Di and Liu 2004). Although a clear income
threshold must be reached before homeownership is an option, racial minorities must
reach a higher threshold in order to purchase a home of similar value (Horton and
Thomas 1998; Myers and Woo Lee 1998; Boehm and Schlottmann 2004; Xiao Di and
Liu 2004; Herbert and Kaul 2005). Income has a direct effect on equity at higher income
levels, which is also associated with a higher likelihood to live in an affluent and less
24
segregated neighborhood (Blau and Graham, 1990; Alba and Logan 2000a; Logan, Stults
and Farley 2004a). Thus, it is likely that income above a certain threshold will provide
higher odds of homeownership and higher equity across all racial groups. Income should
be a control factor since it may influence inclusion in an integrated neighborhood as well
as higher home values within those neighborhoods.
Children
Children play an interesting role in homeownership and home equity. Researchers have
found that families with children are more apt to purchase a home and more likely to be
long-term residents in their neighborhood (Alba and Logan 1992; Conley 1999; Xiao Di
and Liu 2004; Crowder; South and Chavez 2006). The pan-ethnic groupings of Hispanics
and Blacks have been identified as groups with larger family size despite the stark
differences in family size when ethnic subcategories (such as Puerto Rican, Mexican and
Dominican) are compared to each other (Rosenbaum 1996). The effect of children on
wealth is opposite their effect on homeownership. Children consume liquid forms of
wealth throughout their younger years and reduce the amount of wealth available for
long-term investment (Flippen 2001). Though it is not certain, it is probable that children
positively influence homeownership odds and negatively influence home equity.
Length of Residence
Length of residence has obvious advantages to paying off mortgages and increasing
wealth. Central city neighborhoods are more likely to have shorter lengths of residences,
25
since Asians and Hispanics are more likely to move out of ethnic enclaves, while Blacks
move more often than Whites (Crowder, South and Chavez 2006). Having more time to
pay off mortgages and lower search and purchasing costs, would suggest that length of
residence is more significant for White equity than the equity of minority groups.
Sex
Although gender is not specifically a life cycle factor, it has been found significant in
affecting income as well as homeownership and wealth accumulation through life’s
course (Bianchi, Farley and Spain 1982; Jianakoplos and Menchik 1997; Horton and
Thomas 1998; Conley 1999). Jianakoplos and Menchik (1997) found that divorced and
single women are more likely to consume wealth at a higher rate than married
households. Furthermore, due to gender differences in income and expectations that
females play lesser roles in breadwinning, female-only headed households are less likely
to have the income necessary to increase homeownership (Bianchi, Farley and Spain
1982, Mulder and Smits 1999). When racial factors are considered, gender effects are
lessened for minorities who may often have non-spousal incomes supporting the
household (Krivo 1995; Jianakoplos and Menchik 1997). How single women affect home
equity is unknown.
Assimilation Characteristics
Specific factors have created differences between native-born citizens and immigrants
across racial groups. Although the theory assumes that assimilation factors would result
26
in equality once the following factors are controlled, research has found that White
immigrants most reflect theorized assumptions of assimilation, suggesting that minorities
have a harder time assimilating due to their racial classifications (Henretta 1984; Alba
and Logan 1992; Myers and Woo Lee 1998; Alba, Logan and Stults 2000b; Straight
2002). Although perspectives and strategies towards assimilation and home acquisition
are similar across the pan-ethnic groups, current social and historical locations suggest
assimilation has only minor success in a stratified society (Parcel 1982; Massey and
Denton 1993; Marrow-Jones 1993; Straight 2002; Rosenbaum 1996; Krivo 1995).
Factors affecting immigrant families include, inter-ethnically married households, nativeborn households, citizenship status, years in the United States and linguistic isolation.
Intermarried
Krivo and Kaufman (2004) assume that intermarried White households are more likely to
be discriminated against than non-intermarried White households. This is based upon
previous research that finds a correlation between the visual skin appearance and level of
stratification (Krivo 1995; Alba, Logan and Stults 2000b). Although Krivo and Kaufman
(2004) found a negative correlation between intermarried and home equity for WhiteBlack and White-Asian households, it was not statistically significant. There is relatively
little research on intermarried households, leaving little indication of its role on wealth.
27
Native-born / Naturalized Citizen
Homeownership as well as the quality of the property can be assumed a product of
socialization and different standards of living. As an alternative to race, researchers have
suggested that becoming socialized within the American housing market would affect
social capital and knowledge of the markets (Mulder and Smits 1999; Alba and Logan
2002; Ross and Yinger 2002). Similarly, as the percentage of foreign-born residents
increase, homeownership rates decline (Krivo 1995). However, race and length of
residence also have an effect on the role of nativity in assimilation. Foreign-born Blacks
and non-Black groups are often found to have better success in assimilation due to
residence in transitional enclaves rather than the ghettoes of native Blacks (Rosenbaum
and Friedman 2001; Wilkes and Iceland 2004; Alba and Logan 1992). A study in Canada
found that immigrants have a higher chance of assimilation when they are new to an area
before enclaves are formed (Myles and Hou 2004). As in Canada, the presence of new
immigrants is highly correlated with diversity in neighborhoods in the United States
(Putnam 2007; Friedman and Rousebaum 2004; Alba, Logan and Stults 2000b). This
agrees with further research in the U.S., which has found that immigrants often have
higher self-employment rates than their native counterparts (Conley 1999). Thus, nativity
is not a similar indicator of assimilation for all ethnic groups in all regions (Frey and
Farley 1996; Daly, Reed and Royer 2001; Krivo and Kauffman 2004). Residents who
have lived in the U.S. long enough to become naturalized citizens are more likely to have
gained the necessary social capital to improve odds of homeownership and home equity.
28
Therefore, it is expected that odds of homeownership and home equity will be lower
among non-native and non-naturalized residents.
Years in U.S.
Just as there are differences in the role of naturalization and nativity on homeownership
and home equity, the length of residency is significant for some immigrant groups
(Flippen 2001; Krivo and Kaufman 2001). For instance, Asian immigrants are able to
achieve homeownership and higher equity faster than Hispanic immigrants (Myers and
Woo Lee 1998). Meanwhile, due to changes in opportunities and immigration policies,
the effect of immigration differs also according to the immigration cohorts in which the
household arrived (Myers and Woo Lee 1998; Rosenbaum and Friedman 2001). Thus,
years in the U.S. might be related to the accruement of social capital across the panethnic groups. It is expected that even in diverse neighborhoods years in the U.S. may
still have an effect due to racial stratification.
Language Isolation
Linguistic isolation is determined if a household does not have a member who can speak
the dominant language. Although many immigrant groups are expected to have poor
English skills, linguistic isolation is more significant for Hispanics than for Asians
(Freeman 2000). This may be due to closer residential proximity of Asians to Whites,
linguistic education before immigrating, or stratified linguistic barriers that discriminate
specific accents. Since diverse neighborhoods should also have diverse levels of
29
linguistic abilities, the effect of linguistic isolation is expected to remain significant for
homeownership odds and home equity.
Stratification Characteristics
Racial stratification characteristics are expected to vary greatest between homogenous
and diverse communities. Theoretically, integrated neighborhoods should weaken the
role of racial stratification characteristics for homeownership and home equity. Although
residential segregation is the most obvious indicator of social stratification, other
indicators that must be considered are the residential and regional location of a home and
levels of overcrowding.
Residential Location
Racial segregation has been found to be strongest in the metropolitan areas, and despite a
recent decline, two thirds of metropolitan areas still had extremely high segregation
indexes (above 70) in 1992 (Bianchi, Farley and Spain 1982; Krivo and Kaufman 1999;
Yinger 1995:111; Alba and Logan 1992, 2000a). Diverse neighborhoods are more likely
to exist in metro areas since most suburbs and urban fringes are predominantly White
(Wilkes and Iceland 2004; Deng 2002). Yet, central city communities are more likely to
have poorer conditions, older, smaller and more overcrowded homes than their suburban
counterparts (Rosenbaum 1996; Collins, Crow and Caliner 2002; Deng, Ross and
Wachter 2002). Diverse central city communities, which are predominantly near highly
segregated and lower quality areas, may have lower values. However, diverse metro
30
communities are expected to have lower rates of discrimination and higher rates of
homeownership across the pan-ethnic groups than less diverse areas, thus increasing the
odds of homeownership and equity accumulation for minorities.
Overcrowding
Low housing quality and value is often associated with overcrowding; likewise, it may
also reflect residential segregation and discrimination in the form of limited alternatives
(Yinger 1995; Simmons 2002). Research has also found that minorities, such as
Hispanics, are more likely to live in overcrowded housing than Whites (Krivo 1995).
Nationwide, overcrowding continues to increase, especially in Western states, such as
California with one quarter of the nation’s overcrowded households (Simmons 2002).
Regionally, overcrowding is concentrated in the West where there is also much higher
cost of living. Thus, it is expected that overcrowding negatively affect the wealth of
homeowners, especially Hispanic homeowners.
Financial Characteristics
Since financial characteristics beyond income have a significant impact on the probability
of homeownership as well as the quality and value of the house, specific mortgage and
financial traits are controlled in this study. Unfortunately, no study has been able to
connect the relationship of wealth to credit across racial groups. Therefore, the next best
indicators of credit worthiness are the type of mortgage received by households.
31
Variable Term Mortgage
Variable term mortgages are byproducts of the subprime loan market usually offered to
low educated, low income, non-married and elderly households, as well as minorities and
women (Freeman and Hamilton 2002; Boehm, Thistle and Schlottmann 2006). The
variable rates are offered in exchange for the preferential fixed rates due to the higher
perceived risk of the applicant to default on the mortgage (Ross and Yinger 2002). A
variable term mortgage would likely increase the amount of interest paid out over the
course of the mortgage, thus reducing the amount of wealth gained through equity (Krivo
and Kauffmann 2004). Since variable term mortgages disproportionately target
minorities, I expect their significance towards wealth accumulation to have a greater
effect on minorities’ odds of homeownership and home equity.
FHA / VA / FmHA Mortgages and Loans
Federal Housing Administration (FHA), Department of Veteran Affairs (VA) and Federal
Farmers Home Administration (FmHA) loans are offered as alternatives to current
market loans in order to encourage first time homeownership among the poor groups in
rural areas of the United States (U.S. Government Accountability Office 1993). The
federal government insures these loans; therefore, they can offer standard interest rates
with lower down payments for eligible applicants. Unfortunately, at their original
implementation, FHA/VA/FmHA loans and mortgages systemically excluded poor and
property-less minorities, reducing their ability to increase wealth along with Whites
(Parcel 1982; Yinger 1995; Boehm, Thistle and Schlottmann 2006). This research
32
expects that households with FHA/ VA/FmHA loans will be able to achieve higher home
equity; however, this benefit is expected to be racially stratified.
Large Down Payment
Large down payments are influenced by the lender’s mortgage terms as well as the
savings of the applicant (Yinger 1995). The use of higher down payments will decrease
the amount of time necessary to pay off the loan, decrease the need for mortgage
insurance and may lower the interest rate (Krivo and Kaufman 2004). Thus, we expect
that large down payments will prematurely close the gap between the loan and the value
of the home, producing higher homeownership odds and home equity across all racial
groups.
Inherited Down Payment
Not only are parents influential in socializing children and transferring social status, they
are also highly responsible for transfers of financial assets that are often significant in
explaining a portion of the wealth gap (Chiteji and Stafford 1999; Jianakoplos and
Menchik 1997; Juster, Smith and Stafford 1999; Spillerman 2000; Deng, Ross and
Wachter 2002; Blau and Graham1990; Keister and Moller 2000). Since most inheritances
are received after the primary home is purchased, inherited down payments are expected
to have the most significant effect on home equity (Mulder and Smits 1999). Likewise,
intergenerational transfers may come in many forms from savings accounts and college
funds to direct transfers in times of need, financial transfers given at the right time in the
33
home purchasing process can shorten the period necessary for saving for a down payment
and lessen the impact of poor credit (Avery and Rendall 2002; Guiso and Jappelli 2002).
Despite the timing and multiple types of inheritances, Krivo and Kaufman (2004) still
found that inherited down payments at the time of purchase were strongly associated with
greater equity. Inherited wealth is also racially unequal with the significance being higher
for Whites than Blacks and Hispanics (Avery and Rendall 2002; Gittleman and Wolff
2004; Krivo and Kaufman 2004). Not only do Whites receive significantly more
inheritances in relation to Blacks, their inheritances tend to be of a much higher value.
Thus, inherited down payments may help increase homeownership for Blacks, but the
lower value of their inheritance will likely weaken the relationship of inheritance and
wealth compared to Whites (Henretta 1984; Conley 1999; Avery and Rendall 2002).
Krivo and Kaufman (2004) find that the significance of inherited down payments towards
increasing equity is racially stratified with most significance for Whites, followed by
Hispanics and with least significance for Blacks.
Prior Owner / Condominium Owner
Prior owners are found to have better odds of homeownership and higher equity across all
racial groups, especially Whites and Asians (Myers and Woo Lee 1998; Krivo and
Kaufman 2004). This is due to the reality that prior ownership provides higher initial
wealth. Alternatively, condominiums use shared ownership to lowering the level of
individual burden on homeownership. Condominiums are also expected to provide lower
wealth due to the property being split amongst multiple households. Krivo and Kaufman
34
(2004), found that prior ownership is most influential for Whites, followed by Asians,
Hispanics and Blacks in traditional stratification form. This is likely related to the earlier
recognition that Whites are less likely to move, resulting in their prior ownership most
likely having more equity. Interestingly, the effect of condominium ownership on home
equity is not stratified as usual. Instead, condominiums were most influential for Asians
and more equally influential at a much lower rate for Whites, Hispanics and Blacks. This
might be due to difference in condominium ownership across racial groups. In any case,
since both prior ownership and condominium ownership are significant for all groups,
they are expected to remain significant for odds of homeownership and home equity
regardless of the level of neighborhood diversity.
35
Chapter 3
METHODOLOGY
Dataset
This chapter outlines the survey and methods used to acquire a sample for this study.
Also included is a discussion of the variables and their means and standard deviations.
This research uses the 2005 American Housing Survey’s National data (AHS-N), which
was conducted by the U.S. Census Bureau in conjunction with the Department of
Housing and Urban Development. The AHS is a longitudinal survey that began in 1973
and has biannually tracked a panel of housing units at the national level since 1985.
Importantly, the AHS survey was originally created in order to monitor the effects of
legislation towards reducing housing inequality for minorities. Thus, this survey was
constructed to acquire the most detailed unit and household characteristics of any housing
survey, including perspectives on the neighborhood, the home’s costs and estimated
market value, mortgage and financing as well as detailed demographic data for each
household member. The AHS provides the essential information for a unit level analysis,
which is necessary since homeownership and home value are unit level characteristics
(Kiel and Zabel 1995). In addition, the AHS allows for more accurate analyses of
households because it collects individual level data on all occupants within the
household. The national sample includes 69,020 units before limiting or weighting. Out
of those, 34,248 households identified themselves as homeowners. Households living in
mobile homes and households self described as "other" races are excluded. After
36
adjustments to the race of the household, there are 28,804 Whites, 1,612 Asians, 4,972
Hispanics and 4,640 Blacks who participated in the study.
The AHS has been used by many researchers and is recognized for its strong
sampling methodology as well as accuracy and reliability (Collins, Crow and Caliner
2002; Morrow-Jones 1993; Kiel and Zabel 1996; Boehm, Thistle and Schlottmann 2006;
Deng, Ross and Wachter 2002; Rosenbaum 1996; Krivo and Kaufman 2004).
Furthermore, researchers such as Lam and Kaul (2003) have specifically analyzed the
AHS for reliability and consistency in the responses of mortgage and financial factors.
Though as assumed, time between purchase and survey causes a slight decline in
accuracy for some responses, they conclude that the responses are highly reliable and
relatively consistent. Therefore, the AHS is a useful dataset due to its comprehensive
survey, high response rate and the validity of those responses. In addition, the Census
Bureau provides weighting procedures to correct for sampling bias caused by nonresponse and housing unit coverage, which at 11 percent for the AHS, is higher than the
Census at 2.2 percent (U.S. Census Bureau 2005). Indexes of neighborhood diversity, at
the metropolitan level, are created using the Census Summary File 3, which includes
percentages of ethnic groups within census tracts. The census tracts closely approximate
neighborhoods.
A few limitations of the data comes from the lack of information of lenders and
lending types (prime and subprime) as well as household credit score information, which
are often attributed as significant factors in mortgage lending. Likewise, the racial and
ethnic categories, while collected broadly in 23 response types, are not over sampled for
37
minorities. Therefore, the inclusion of multiple ethnic groups is ineffective for much
analysis, and limits most analysis to the overarching pan-ethnic categories or high
population minority groups at the national and regional levels. Lastly, the AHS data
accessible by the public is not available with tract-level information, due to
confidentiality purposes. This will limit the capability of neighborhood diversity
comparisons to the use of aggregated neighborhood data at the metropolitan level.
Overall, the dataset contains many useful and reliable variables that provide high quality
data for research.
This study tests the following hypotheses:
1) The greater racial diversity within neighborhoods in a market will result in greater
homeownership rates across racial and ethnic groups.
2) The greater racial diversity within neighborhoods in a market will result in greater
equity among homeowners across racial and ethnic groups.
Measures
There are two dependent variables in this study, the first is homeownership and the
second is home equity. Homeownership was measured by asking respondents if their
housing unit is “Owned or being bought by someone in your household” (=1), “Rented
for cash rent” (=2), and “Occupied without payment of cash rent” (=3). Since equity is
accumulated only through homeownership, homeowners were recoded as “do not own”
(=0) and “own a home” (=1). The second dependent variable, home equity, was
calculated using many variables retrieved from the homeowners to determine the amount
38
owed on all mortgages including interest rates for the remaining years. The current value,
purchase price and all mortgage information is collected from the homeowners. This
information is then used to estimate the value of the home remaining after debts,
producing a wealth value of the house and property. For instance, each non-variablemortgage’s interest rate is multiplied by the estimated remaining length of the mortgage
then added to the mortgage’s remaining balance to get a mortgage sum. Then the
mortgage sums are added to each other, creating a total debt. The debt is subtracted from
the homeowner’s estimated current market value of the home, resulting in the current
total wealth accumulated by the homeowner through homeownership. In order to address
researchers’ concerns over the validity of the financial data in the AHS, Lam and Kaul
(2003) test the AHS for the validity of homeowner’s financial estimations through
corroboration with external sources as well as the reliability of their responses through
longitudinal analysis. Lam and Kaul (2003) found that AHS mortgage variables such as
the original mortgage amounts, interest rates, and the race of the homeowner are
consistent and reliable. Therefore, calculations based upon the homeowner responses can
be considered as reliable.
The first independent variable is diversity. Diversity was calculated from the
Census Data Summary File 3 2000, which provides racial characteristics of Metropolitan
Statistical Areas (MSA). Two multiethnic diversity indexes are usually used to obtain
scores of diversity and evenness within an MSA. Diversity scores are used to measure the
presence of groups within a defined area, such as the MSA, while entropy indexes
measures the evenness of the groups within the region. MSAs have been used as a
39
standard statistical area definition across federal datasets since the 1940’s. MSAs as
defined by the Census Bureau are used as a “reasonable approximations of housing
markets” (Iceland 2004:5). These approximations group residents into geographically
linked communities based on an urban core with a population over 50,000 and the outside
cities and counties that contribute workers (Federal Register 2000). As a result, there are
331 MSA’s in Summary File (3) for the year 2000. The benefit to using MSAs over
county statistics is the inclusion of the rural areas that have a direct link to the
metropolitan area under study. Although the AHS-N collects neighborhood level
information for each respondent, this information is not released for public use due to
privacy concerns. For this reason, the most logical and lowest level of geographic
analysis for a national population is at the MSA level. In the 2005 AHS-N, MSAs are
coded from 40 to 9340.
Although there are significant differences between individuals within race and
ethnic backgrounds, the second independent variable will combine all possible responses
into four pan-ethnic categories; White, Black, Asian and Hispanic, for an overarching
understanding of racial effects. Using pan-ethnic categories provides simplicity for
statistical relationships in data analysis, such as using the entropy index, as well as for
comparison to the greater majority of past research. Race and ethnicity was calculated at
the household level according to the respondent’s self reported race as well as the
question “is this person Hispanic or Spanish-American” in which they could answer
“yes”(=1) or “no”(=2). Households were recoded into four main categories of “White”
(=1), “Asian” (=2), “Hispanics” (=3), and “Blacks” (=4). Thus intermarried households
40
between minorities and non-minority Whites, as well as those reporting mixed Whiteminority races have been recoded to the respective minority group, assuming that
households with a minority person or mixed heritage is more likely to experience racial
prejudice. A dummy was created for racially intermarried households where (=1) will
include White households containing non-White spouses of different races and (=0) will
include households of the same race.
Lifecycle Controls
The first control variables come from the lifecycle thesis and include age, education,
marital status, employment, household income, number of children, sex (for single
occupants) and length of residency.
Household Age was captured as the highest reported age in years out of the
householder or spouse. Education was captured by asking “what is the highest level of
school education completed…?” ranging from (=31) Less than 1st grade to (=47)
Doctorate degree. For the purpose of accurate calculations, these categories have been
recoded into a new variable with new response categories for education in terms of
estimated years. For example, 12th grade with no diploma equals 11.5 years, high school
graduate equals 12 years. The household’s education is captured as the highest education
in years between the householder and spouse. Marital status is measured by respondent’s
answer to “married” and spouse present (=1), “married” and spouse absent (=2),
“Widowed” (=3), “Divorced” (=4), “Separated” (=5) or “Other” (=6). These categories
were recoded into a dummy variable with “Not Married” (=0) and “Married” (=1).
41
Employment Status has also been coded into a dummy variable if the householder or
spouse answered “yes” (=1) to the question “Did this person work at any time last
week?” Those who answered “no” to the question were recoded as (=0). Income for the
household was measured as a sum of all forms of household income from all unit
dwellers. Furthermore, since housing costs are not linearly distributed, and since income
does not have a linear effect on homeownership or wealth due to theoretical thresholds, a
variable has been created by splitting the reported income into groups to capture the
threshold levels. Income ranges from -$40,616 to $135,342. The responses have been
grouped into deciles; $9,600 and under (=1), $9,601 to $17,800 (=2), $17,801 to $26,000
(=3), $26,001 to $35,000 (=4), $35,001 to $45,000 (=5), $45,001 to $56,000 (=6),
$56,001 to $70,000 (=7), $70,001 to $90,000 (=8), $90,001 to $120,000 (=9), and
$120,001+ (=10). The number of children per household is calculated as any person
under the age of 18. A dummy was coded as (=1) if age is reported as less than or equal
to 18 and relationship was responded to as “Child of reference person” (= 22), all others
were be coded as (= 0). Gender for single, non-married households was captured using
the variable, which respondents replied either “male” (=1) or “female” (=2). A dummy
was recoded as single-owner “male” (=0) and single owner “female” (= 1). The length of
residence in the current dwelling was measured by asking for “the year the householder
moved in.” A new variable has been coded for length of residency by subtracting the year
moved in from the survey year of 2005.
42
Assimilation Controls
The second batch of control variables fall within the assimilation theories and include;
native household, naturalized household and years in the United States. The variable for
native household was recoded as citizen (=1) if the householder or spouse responded as a
native-born with the “United States” (=57) as their “country of birth,” if they answered
anything other than “United States” they were recoded as (=0). Naturalized citizens are
measured by asking respondents if they are “Native, born in US” (=1), “Native, born in
Puerto Rico or US outlying area” (=2), “Native-born abroad of US parent(s)” (=3),
“foreign born, US citizen by naturalization” (=4) or “Foreign born, not a US citizen”
(=5). This variable was recoded for the household as “native” (=1) if either the
householder or spouse answered as a native or naturalized citizen if they answered (=1)
through (=3) and “non native” (=0) if they answered “naturalized” (=4) or “not a citizen”
(=5). Another dummy has been created for naturalized citizens (=1) if they selected
“naturalize (=4) and non naturalized citizens (=0) if they selected (=1) through (=3) or
(=5). Years in the U.S. for non native-born citizens was captured as the highest number in
years reported between the homeowner and spouse using the variable.
Stratification Controls
The third category of controls stems from prior research in stratification and encompasses
regional location, residential location and overcrowding. Residential location was
measured at two levels. Regionally, the respondents location was automatically captured
by regional categories of “Northeast” (=1), “Midwest” (=2), “South” (=3), and “West”
43
(=4). Regions were recoded into three dummy variables, the first “Midwest” was coded
as (=1) if the respondent selected (=2) and all other responses will be recoded as (=0).
“South” was coded as (=1) if the respondent selected (=3) and all other responses will be
recoded as (=0). “West” was coded as (=1) if the respondent selected (=4) and all other
responses were recoded as (=0). Respondents were also categorized to their residential
location in relation to the central city of the nearby MSA. The respondent could answer
(=1 ) for “Central City” and (=2) through (=5) for variations of suburbs and rural MSA
locations. A dummy has been created for the “Central City” (=1) for those who answered
“Central City” (=1) All else was recoded as “non Central City” (=0). A second dummy
was created for “Suburban” (=1) if respondents answered (=2 through =5) and “Non
Suburban” (=0) for those who answered (=1). Overcrowding is defined by the U.S.
Census as more than one person per room. Overcrowding was measured by dividing the
respondents’ answers to the number of total persons living in the household by the
number of rooms used for living purposes (top coded at (=21)) in the unit.
Financial Controls
Financial variables are used to control for effects on equity and homeownership,
especially in reference to mortgages. Responses to variables concerning use of a variable
term mortgage, FHA/VA/FmHA loans, and prior ownership, ownership of a
condominium, large down payment and inherited down payment were used as the final
category of control variables. Variable Term Mortgage is measured if the respondent
answered “yes” (=X) when asked about the length of mortgage on the primary or
44
secondary mortgages. This was then recoded as “Variable Term Mortgage” (=1) and
others (=0). The type of mortgage is measured by asking if the mortgage is an “FHA”
(=1),”VA” (=2), “Farmers Home Administration Mortgage” (=3), or “some other type”
(=4). This variable was recoded to “FHA, VA, FmHA” (=1) and “other” (=0). Prior
ownership was measured by asking the respondents to reply “Yes” (=1) or “No” (=2) if
they “ever owned a home before.” This variable has been recoded into a dummy variable
(=0) if never owned before and (=1) if they are prior owners. The down payment is
estimated by subtracting the amount of the original mortgage from the total purchase
price. In addition, homeownership is differentiated by asking if the unit is “either Condo
or Cooperative” (=1) or “No, Neither one” (=3). Homeownership was recoded as those
who are “not owner” of a house or own a condominium (=0) and those who are “owner”
of a non-mobile unit (=1). The down payment amount was then divided by the purchase
price to obtain the percentage of the down payment. A dummy variable was then
constructed for all those with large down payments of 30 percent and above (=1) and all
those below 30 percent as (=0). Since large down payments and inherited down payments
will help households increase equity, a response of “inheritance or gift” (=5) to the
question “Was the main source of down payment the sale of a previous home, savings, or
something else?” was dummy coded as (=1) as a control for those with inheritance, while
all without were coded (=0).
45
Models and Estimations
This research uses hierarchical linear modeling (HLM) to link the two levels of data
under analysis. HLM is a necessary statistical method for incorporating higher-level
variables (such as the entropy index derived from the MSA level) with household level
data (in this case, homeownership, home equity and race). HLM is much more relevant
than aggregation and disaggregation used often in linear regression analyses since it is
statistically correct in differentiating between the effects of a variable at both levels (Bryk
and Raudenbush 1992). Furthermore, HLM does not need to aggregate data at one level
in order to combine it with another level, producing more accuracy across levels due to
less waste of relevant data than with aggregation (Bryk and Raudenbush 1992). Although
HLM still suffers from the weaknesses of assumed linear effects like other linear
statistics, it is clearly superior to other forms of linear analysis for multi-level data.
Unfortunately, the use of HLM does limit the ability to account for non-response
and truncated data since there is currently no way to link a Tobit model and HLM.
Authors considering home equity have often used Tobit and Probit analyses to include
the responses of those without equity data in their calculations (Krivo and Kaufman 2004,
Flippen 2001). However, since the purpose of this research is accurately assessing the
role of higher-level diversity on homeownership, HLM is more necessary than Tobit. The
result is data that more accurately reflects the relationship of diversity on equity and
homeownership rather than retain higher accuracy for the relationship of value or
homeownership to pan-ethnic categories.
46
A multi-group entropy score of MSA diversity (E) and neighborhood diversity
(Ei) is calculated as,
r
E =Σ (πr)ln[1/ r]
r =1
and
r
Ei =Σ (πri)ln[1/ ri]
r =1
The “πr” refers to the particular ethnic group’s proportion of the population, the “i’s”
refer to the census track (Iceland 2004; Reardon and Firebaugh, 2002). To achieve an
index where a low of 0 is equal complete neighborhood integration and a high of 1 is
reflective of complete segregation, the neighborhood diversity score was divided by the
MSA diversity score. This index was calculated as,
n
H= Σ [(ti(E-Ei)) / ET]
i=1
“where ti refers to the total population of tract i, T is the metropolitan area population”
and “n is the number of tracts” (Iceland 2004:8). Although research has highlighted
various forms of segregation such as Massey and Denton (1993), the concern here was to
capture the distribution of ethnic groups within neighborhoods without the influence of
the ethnic group size. This study assumes that neighbors often share equal access to
resources and should experience similar rates of equity accumulation. Multi-group
diversity in relation to home equity is also unique to this study. The only comparable
research on equity by Krivo and Kaufman (2004) controlled for only Black and White
dissimilarity. They found no significant effect on non-Black minorities, likely due to the
relative isolation of Black minorities from other groups. Since a diverse MSA may be
47
segregated at the neighborhood level, this research is interested in obtaining
neighborhood multiethnic entropy indexes at the MSA level.
Descriptive Statistics
Table 1 reports the mean and standard deviation for all the variables used in the
homeowner calculations. The multi-group entropy index referring to the displacement of
ethnic groups within neighborhoods suggests about 28 percent of neighborhoods are
more segregated than the metropolitan area they are within. In terms of race and
ethnicity, 72.0 percent of the households classify as White, 4.0 percent classify as Asian,
12.4 percent classify as Hispanic and 11.6 percent classify as Black. When looking
specifically at homeowners, 78.6 percent are White, 3.6 percent are Asian, 9.6 percent are
Hispanic and 8.2 percent are Black. Roughly 68 percent of the population own rather than
rent their home, while 44.7 percent currently own mortgages. This leaves 23.3 percent of
the population owning their homes outright. The average equity in 2005 dollars is
$176,486. When only homeowners are observed, the average home equity rises
considerably to $259,739. The mean age for households in the full sample is 50.6 years,
when looking at only homeowners, the mean age rises to 53.7 years. The mean education
achievement for households is 13.8 years, and rises slightly to 14.2 years for
homeowners. Regarding marital status, 51.1 percent of the sample population is married
with spouse present, 11.1 percent are widowed, 1.7 percent has an absent spouse and 36.1
percent are not married. Approximately 63 percent of homeowners are married, 11.6
percent are widowed or formerly married, 1.3 percent have an absent spouse and 24.2
48
percent are single or never married. Single female-headed households make up 20.1
percent of the sample population and 13.3 percent of homeowners. At the time of the
survey, 67.8 percent of the households had at least one member currently employed, and
69.0 percent of homeowners were currently employed. The average annual income is
$61,263.96 for the full sample, and $73,455.24 for homeowners. On average, households
have 1.9 children under age 18 currently living with them and have lived in their current
residence for 11.2 years. Homeowners have 0.65 children under age 18 on average and
have lived in their current residence for 14.4 years. Around 3.2 percent of non-White
households in the full sample are racially intermarried, while 3.8 percent of homeowners
are racially intermarried. 86.8 percent of the sample households and 90.4 percent of
homeowners are native-born citizens. About 30.4 percent of households live in central
cities, while 43.5 percent live in suburbs and 26.1 percent are rural residents. When
looking at homeowners, only 23.2 percent of the households live in the central city, while
44.6 percent live in suburban areas and 32.3 percent live in rural areas. About 9.6 percent
of homeowners have variable term mortgages. Nearly 10 percent of households are using
variable term mortgages to achieve homeownership. Households using FHA/VA/FmHA
mortgages make up 6.3 percent of the respondents and 9.3 percent of homeowners. A
small segment of the sample (1.5%) used inherited down payments as an advantage to
gain homeownership, which makes up 2.2 percent of homeowners. Just over 10 percent
of current homeowners used a large down payment when beginning their loan. In the
sample population, 58 percent have previously owned a home, while only 57.2 percent of
49
homeowners have previously owned a home. About 6.1 percent of homeowners own a
condominium.
Table 1: Descriptive Statistics of Homeowner and Equity Calculations
Homeownera
Mean
Std. Deviation
Multi-group Entropy Index
MEIc
Housing Characteristics
Home owner
Mortgage owner
Equity
Race-Ethnicity
White
Asian
Hispanic
Black
Lifecycle Characteristics
Age
Education
Married
Widowed
Spouse absent
Other not married
Employment
Household income
Children
Length of residence
Single female
Assimilation Characteristics
Intermarried
Native-born
Stratification Characteristics
Central City
Suburb
Rural
Financial Characteristics
Variable term mortgage
FHA/VA/FmHA loans
Large down payment
Inherited down payment
Prior owner
Condominium owner
Home Equityb
Mean
Std. Deviation
.277
.097
.278
.100
.680
.447
$176,486.029
.467
.497
$265,246.140
1.000
.658
$259,739.054
.000
.475
$286,217.390
.720
.040
.124
.116
.449
.200
.330
.320
.786
.036
.096
.082
.410
.187
.295
.274
50.642
13.760
.511
.111
.017
.361
.678
$61,263.960
1.870
11.227
.201
17.350
3.020
.500
.314
.131
.480
.467
$67,712.518
.974
13.082
.401
53.731
14.168
.630
.116
.013
.242
.690
$73,455.243
.645
14.349
.133
15.895
2.903
.483
.320
.113
.428
.463
$74,610.956
1.053
13.980
.340
.032
.868
.175
.338
.038
.904
.191
.295
.304
.435
.261
.459
.496
.439
.232
.446
.323
.422
.497
.468
.066
.063
.071
.015
.580
.041
.248
.243
.256
.120
.494
.199
.096
.093
.104
.022
.572
.061
.295
.290
.305
.145
.498
.238
a
= N 40,028
b
= N 27,198
c
0= Integrated 1= Segregated
50
Descriptive Statistics by Race
Table 2 highlights the means and medians within racial categories. The multi-group index
is relatively the same for each racial group. Black households are most isolated from
other racial groups in their neighborhoods with a mean index of .309 out of 1.00. In other
words, when only Black households are observed, the average neighborhood is 30.9
percent more racially segregated than in the region. White households are less isolated
and have a lower mean index of .275. Hispanic households follow with .263, while Asian
households are the most likely to live in neighborhoods with other racial groups with an
index of .255. Overall, the MSA's in the sample have neighborhoods that are
considerably more evenly integrated than segregated since all of the numbers are below
.500. However, looking at the MEI mean and median values shows that Black and
Hispanic households who are isolated from other racial groups are least likely to
experience change in their levels of isolation.
A large majority of White households own their homes 74.2 percent, while 47.7
percent are currently doing so through a mortgage. Similarly, 61.1 percent of Asians own
their homes and 48.8 percent currently have a mortgage. A surprisingly small majority of
Hispanics (52.6 percent) owns their home, and 38.9 percent currently have a mortgage.
The majority of Black households do not own their home. Only 47.8 percent of Black
households own a home, and 30.9 percent currently have a mortgage. In terms of wealth
through home equity, Asian households have the highest mean equity out of all the racial
groups with a mean of $140,614. However, the median suggests that at least 50 percent of
51
Asian households do not have any positive home equity. In contrast, white households
have a mean of $130,003 in home equity, but a median home equity of $60,000. Hispanic
households have a mean equity of $70,000 and like Asian and Black households, their
median home equity is $0. Black households have the lowest mean equity with only
$40,000 and a median of $0. Thus, the Black households who beat the odds and obtain
homeownership are still obtaining homes of significantly lower value than the other racial
groups.
Lifecycle Controls
In terms of lifecycle characteristics, White households tend to be older with a mean age
of 52.4 years. Black households come in next with a mean age of 47.9 years, followed by
Asian households with a mean age of 46.3 years and Hispanic households with 44.4
years. Marital status ranges across the groups. White households have the highest level of
widowed households (12.2 percent) and are followed closely by Black households who
have 12.1 percent. Asian and Hispanic households have much lower levels of widowed
households with 5.0 percent and 5.5 percent respectively. Though they have high levels
of widowed households, Whites have the lowest level of absent spouses with 1.4 percent.
An estimated 2.0 percent of Black households have absent spouses and 2.9 percent of
Hispanic households have absent spouses. Asian households have the highest amount of
absent spouses at 3.2 percent. The majority of Black households (55.7 percent) are single
or other non-married households. 35.4 percent of Hispanic households and 33.6 percent
of White households are single or non-married. Despite the younger mean household age,
52
Asians have the least amount of single households with only 25.8 percent. Black
households have the highest rate of single female-lead households at 38.0 percent. The
next closest is Hispanics with 20.5 percent, followed by Whites with 17.6 percent and
Asians with 13.4 percent. Asian households have the highest level of education with a
mean of 14.9 years of schooling, yet their median is only 12.0 years. In contrast, White
households have a mean of 14.1 years of education, while having as median of 14.0
years, suggesting that although some Asian households are likely to have exceptionally
high education, the majority are only completing high school, while the majority of
White households complete at least some college. The mean education for Black
households is 12.9 years and the mean for Hispanic households is 12.0 years. Asian
households are most likely to be employed with 78.0 percent of households currently
employed. They are followed by Hispanic households with 77.2 percent currently
employed, and White households with 66.5 percent currently employed. Black
households have the lowest level of current employment with only 61.8 percent
employed. As with education, Asian households have the highest mean income with
$74,876. However, they also have greatest variation in income with a mean of only
$38,400. White households have a mean of $65,547 per household, per year. Whites have
a median of $49,000, suggesting much less variation within the category. Hispanic
households follow with a mean income of $52,039 and a median of $38,400. Black
households have the lowest amount of income with a mean of only $39,831 and a median
of $28,000. The average number of children currently living in the home for Whites is .5,
Asians .8, Blacks .8 and Hispanics 1.1. White households are the most stationary with a
53
mean length of residency at 12.3 years, followed by Blacks at 9.8 years, Hispanics at 7.5
years and Asians at 6.9 years.
Assimilation Controls
In terms of assimilation characteristics, 18.0 percent of Hispanics are intermarried with
Whites. Similarly, 14.2 percent of Asians are intermarried, while only 3.1 percent of
Black households are intermarried. White households are most likely to be native-born
with 95.6 percent, followed closely by Black households at 91.2 percent. Only 50.5
percent of Hispanic households are native-born and only 28.7 percent of Asian
households are native-born.
Stratification Controls
In terms of residential stratification, minority groups are more likely to live in the central
city than Whites are. Black households are most likely to live in the inner city. Roughly,
52.1 percent of Black households reside in the central city, compared to 36.2 percent of
Blacks in the surrounding suburbs. In contrast, only 11.7 percent of Black households
live in rural areas. Hispanic households are split between the city and suburbs, with 44.8
percent of Hispanic households in the central city and a similar 43.3 percent living in the
suburbs. In contrast, only 11.9 percent of Hispanics live in rural areas. Asian households
are more likely to live in the suburbs than anywhere else, with 50.7 percent in the suburbs
compared to 39.8 percent in the central cities and only 9.5 percent living in rural areas.
Likewise, White households are most likely (44.3 percent) to be in the suburbs. Rural
54
areas come next with 31.9 percent of White households, followed by central cities with
23.8 percent of White households.
Financial Controls
Financial characteristics vary in use within the racial groups. About 7.9 percent of Asian
households have a variable term mortgage. Meanwhile, 6.7 percent of White households,
6.0 percent of Hispanic households and 4.2 percent of Black households have variable
term mortgages. Asians are least likely to have a FHA/VA/FmHA loan, with only 4.6
percent benefitting from one. Around 6.0 percent of Whites, 7.2 percent of Hispanics and
8.5 percent of Blacks are using FHA/VA/FmHA loans. At 10.4 percent, Asians have the
highest rate of large down payments when purchasing their home. White households
come in second highest with 7.8 percent, followed by Hispanic households with 5.2
percent and Black households with 3.4 percent. More than any other group, 1.7 percent of
White households have received an inheritance for their down payment. About 1.2
percent of Asian, 0.9 percent of Hispanic and 0.8 percent of Black households did
likewise. A large majority of White households (62.6 percent) have previously owned a
home, followed by a smaller majority of Asians (50.7 percent). Hispanic and Black
households are much less likely to have previously owned a home at 44.6 percent and
36.2 percent respectively. Condominium ownership is used to obtain homeownership for
6.1 percent of Asian households, 4.5 percent of White households, 3.2 percent of
Hispanic households and 2.2 percent of Black households.
Table 2: Descriptive Statistics of Full Sample by Ethnic and Racial Groups
White
Median
Mean
Multi-group Entropy Index
MEIa
Housing Characteristics
Home owner
Mortgage owner
Equity in $10,000's
Lifecycle Characteristics
Age
Widowed
Spouse Absent
Other not married
Education
Employment
Household income
Children
Length of residence
Single female
Assimilation Characteristics
Intermarried with Whites
Native-born
Stratification Characteristics
Central City
Suburb
Rural
Financial Characteristics
Variable term mortgage
FHA/VA/FmHA loans
Large down payment
Inherited down payment
Prior owner
Condominium owner
Asian
Median
Mean
Hispanic
Median
Mean
Black
Median
Mean
.275
.263
.255
.263
.263
.305
.309
------6.000
.742
.477
13.003
------.000
.611
.488
14.614
------.000
.526
.389
7.178
------.000
.478
.309
4.046
51.000
---------14.000
---49,000
---7.000
----
52.408
.122
.014
.336
14.133
.665
65,547
.532
12.338
.176
42.000
---------12.000
---38,400
---4.000
----
46.257
.050
.032
.258
14.893
.780
74,876
.802
6.845
.134
42.000
---------12.000
---38,400
---4.000
----
44.352
.055
.029
.354
12.012
.772
52,039
1.115
7.524
.205
46.000
---------13.000
---28,000
---4.000
----
47.940
.121
.020
.557
12.924
.618
39,831
.806
9.820
.380
-------
NA
.956
-------
.142
.287
-------
.180
.505
------
.031
.912
----------
.238
.443
.319
----------
.398
.507
.095
----------
.448
.433
.119
----------
.521
.362
.117
-------------------
.067
.060
.078
.017
.626
.045
N = 28,804
-------------------
.079
.046
.104
.012
.517
.061
N = 1,612
-------------------
.060
---.042
.072
---.085
.052
---.034
.009
---.008
.446
---.326
.032
---.022
N = 4,972
N = 4,640
a
0= Integrated 1= Segregated
55
.259
56
Chapter 4
FINDINGS AND INTERPRETATIONS
Summary of Diversity Hypothesis Tests
The first of this study's two hypotheses was that the greater diversity within
neighborhoods in a market would result in greater homeownership rates across all racial
groups. With all racial groups combined, a region's neighborhood racial segregation or
integration does not have the expected significant effect on homeownership (Table 3). It
was assumed that significance with in all racial groups would lead to significance when
all racial groups are combined. However, Table 4 indicates that the levels of
neighborhood integration are also not significant when looked at within any group. This
may be due to the increase in diversity indexes across many states over the past two
decades as suggested by Sandoval, Johnson and Tafoya (2002), or the increase of federal
housing programs in aiding underserved and often segregated neighborhoods such as
Fannie Mae and Freddie Mac (Herbert and Kaul 2005). Thus, it may be that
neighborhood segregation no longer has an effect on home acquisitions. However, as
Table 3 indicates, race is still significant for homeownership. It is plausible that
metropolitan neighborhood diversity has been aggregated too much to capture the
nuances of racial residential segregation at the neighborhood level.
The second hypothesis was that the greater diversity of neighborhoods in a market
would result in greater equity among homeowners across all racial groups. Again, the
assumption was that significance within all racial groups would lead to significance when
all racial groups are combined. Table 5 illustrates that there is no significance for
57
neighborhood diversity on home equity when all racial groups are combined. However,
Table 6 shows that neighborhood diversity is significant within the Hispanic and Black
homeowner categories. Meanwhile, Asian homeowners’ values are only approaching
significance. In this case, the hypothesis is correct for half of the groups. This also
suggests that the reason neighborhood diversity is not significant for home equity in
Table 5 is that it is not significant for the majority of the population, which is made of
White homeowners. The following paragraphs highlight the role and significance of the
control variables and some general interpretations of the results.
Homeownership Results
Table 3 indicates that 18 of the 24 hypothesized effects on homeownership are
statistically significant. The intra-class correlation coefficient for homeownership is
0.035; meaning about 3.5 percent of variation in homeownership occurs between
metropolitan areas. Approximately two-thirds of that variation is explained by all the
variables in the model. As stated above, household race is significant for Hispanic and
Black households. With all the other factors controlled, Hispanics and Black households
are approximately 2 percent less likely to own their homes compared to Whites. This
racial difference is found to be statistically significant (p <.05). Despite being less likely
to own a home and having higher rates of mortgages, Asian households in this study have
no significant difference in odds of homeownership than White households (p >.05).
Though Asians household coefficients were expected to be significant, the nonsignificance imitates some past findings, which have varied in results due to the large
58
heterogeneity of characteristics within the Asian racial category. As observed in Table 2,
some Asian households fare exceptionally well, while many do much worse, explaining
the large difference between medians and means. Their relatively small population in the
United States and this sample suggests the outliers may be creating non-significance for
all Asians when they are grouped together. It may be that if the Asian category were
subdivided, greater inequalities and levels of significance would be exposed.
Table 3: HLM Modeling of Homeownership
Final estimation of fixed effects
(with robust standard errors)
Fixed effects
Intercept 1
MEIa
Race-Ethnicity
(Omitted Non-Hispanic White)
Asian
Black
Hispanic
Lifecycle Characteristics (Omitted
Married and single owner male)
Age
Education
Widowed
Spouse absent
Other not married
Employment
Household Income
Children
Length of residence
Single female
Assimilation Characteristics
Intermarried
Native-born
Stratification Characteristics
Suburb
Ownership
B
(S.E.)
t
OR
0.159***
0.070
(0.021)
(0.061)
6.360
1.126
-----
0.006
-0.019*
-0.019*
(0.012)
(0.009)
(0.015)
0.495
-2.501
-1.232
--0.981
0.981
-0.001***
0.002*
-0.056***
-0.091***
-0.125***
0.002
0.033***
0.022***
0.014***
0.011
(0.0002)
(0.001)
(0.010)
(0.016)
(0.008)
(0.007)
(0.001)
(0.003)
(0.002)
(0.008)
-3.739
2.127
-5.500
-5.586
-11.372
0.361
28.943
7.288
31.401
1.331
0.999
1.002
0.946
0.913
0.882
--1.034
1.022
1.014
---
-0.017
0.002
(0.015)
(0.009)
1.081
0.190
-----
(0.006)
3.460
1.035
0.034***
59
Table 3: Continued
Rural
Financial Characteristics
Variable term mortgage
FHA/VA/FmHA loans
Large down payment
Inherited down payment
Prior owner
Condominium owner
Conditional ICC
Variance between level 2
Variance at level 2 explained
0.050*
(0.018)
2.526
1.051
0.209***
0.291***
0.163***
0.278***
0.352***
0.371***
(0.010)
(0.010)
(0.010)
(0.020)
(0.008)
(0.010)
22.713
25.228
17.229
13.643
43.838
11.211
1.232
1.338
1.177
1.320
1.422
1.449
.026
.035
.670
Odds ratios shown are significantly different from 1.0
*** p <.001, ** p <.01, * p <.05
a
0= Integrated 1= Segregated
Lifecycle Controls
Many lifecycle characteristics also play an interesting and statistically significant
role in homeownership. For each additional year of a household’s age, the household has
a 0.1 percent (p <.001) decrease in odds of homeownership. Each additional year of
education significantly increases the odds of homeownership by .2 percent (p <.05).
Despite household age, being widowed significantly decreases odds of homeownership
by 5.4 percent (p <.001), while having an absent spouse significantly decreases odds of
homeownership by 8.7 percent (p <.001) when compared to married households. A single
or non-married household has their odds of homeownership decreased by 11.8 percent (p
<.001) when compared to married households, suggesting that single dwellers are more
likely to rent than own their homes even when age is controlled. Employment has no
significance (p >.05) on homeownership odds. Employment values may be nonsignificant due to the high average household age in the population, which suggests many
homeowners may be retired. However, income is still significant, so it may also be that
60
current employment is not a defining factor for homeownership versus renting. Income
has a positive relationship with homeownership. The odds of homeownership increase by
a significant 3.4 percent (p <.001) for every decile increase in household income. As
hypothesized, the more children in a household, the more likely (2.2 percent) they are to
own versus not own a home (p <.001). Every additional year a household lives in their
current residence increases their odds of homeownership by 1.4 percent (p <.001). The
last life cycle characteristic is single female-headed households. Single female
households are found to have no significant difference in homeownership odds than
single male households (p >.05). It was expected that single female-headed households
would be less likely to own a home due to gender differences in wealth. However, it may
also be that single women are more likely to have custody over their children following a
divorce, thus the effect of children on homeownership may be insignificantly increasing
the single female's odds of owning a home.
Assimilation Controls
None of the assimilation characteristics were found to be significant for homeownership
(p >.05). Intermarried households have no significant difference from single race
households in homeownership. It may be that the effect of intermarrying is has different
effects for different groups and therefore not consistent enough to be significant.
Intermarried are found to have no significance on homeownership as a whole and within
racial groups. Households that are native-born have no significant difference (p >.05)
both on the whole and within racial groups, from those which are foreign-born. This may
61
also be due to the variation in immigration's impact on different racial groups; however,
when looked at within racial categories, native-born status remains non-significant.
Stratification Controls
Although neighborhood segregation is not found significant, residential characteristics
play a significant role in homeownership as expected. Living in a suburb increases
homeownership odds by 3.5 percent compared to those in the central city (p <.001); while
rural resident have a 5.1 percent increase in odds of homeownership over those in the
central city (p <.05). These are likely related to higher prices and less ownership options
available in the central city compared to those in the suburbs and outlying areas.
Financial Controls
As hypothesized, all of the financial characteristics play a highly significant (p <.001)
role in homeownership. The use of variable term mortgages increases odds of
homeownership by a 23.2 percent compared to those with standard mortgages.
Meanwhile, access to and the use of FHA/VA/FmHA loans increases odds of
homeownership by 33.8 percent. Using a large down payment increases the odds of
homeownership over those with a standard down payment by 17.7 percent. Inheriting a
down payment also increases odds of homeownership by 32.0 percent over those who do
not inherit their down payment. As discussed earlier, using the wealth from a previously
owned a home has a large impact on owning one's current home. Prior ownership
increases odds of ownership by 42.2 percent compared to those who did not previously
62
own a home. Lastly, as anticipated, owning a condominium highly increases odds of
ownership by 44.9 percent compared to those who own a house.
Homeownership within Ethnic and Racial Groups
Because race is significant for increasing and decreasing odds of homeownership, it
becomes necessary to see how each race uniquely interacts with the variables in the
study. Most importantly, the goal is to identify if neighborhood diversity indexes play a
significant role in access to homeownership within racial categories. Table 4 looks at
homeownership within racial groups, wherein 15 of 20 variables are significant for White
households, 10 of 21 are significant for Asian households, 13 of 21 are significant for
Hispanic households and 12 of 21 are found to be significant for Black households. In
terms of homeownership, neighborhood diversity is found to have no significant effect (p
>.05) for any racial category. As mentioned earlier, this may be due to changing
demographics across the nation, increased financial aid for segregated communities or
neighborhood data aggregation at the metropolitan level.
Lifecycle Controls
Many lifecycle characteristics are significant in all groups, with White households having
the most. As found in past research, household age is found to be significant (p <.001) for
White households, where each additional year of household age decreased odds of
homeownership by 0.2 percent. It was expected that age would increase the odds of
63
homeownership for Whites. Hispanics odds increased by 0.2 percent for every year of
age (p <.05). Asian and Black households are not significantly affected by age (p >.05).
Table 4: Homeownership within Ethnic and Racial Groups
Final estimation
(with robust standard errors)
Fixed effects
Intercept 1
MEIa
Lifecycle Characteristics
Age
Education
Widowed
Spouse absent
Other not married
Employment
Household Income
Children
Length of Residence
Single female
Assimilation Characteristics
Intermarriedb
Native-born
Stratification Characteristics
Suburb
Rural
Financial Characteristics
Variable term mortgage
FHA/VA/FmHA loans
Large down payment
Inherited down payment
Prior owner
Condominium owner
Whites
OR
Asians
OR
Hispanics
OR
Blacks
OR
1.293***
---
-----
-----
-----
0.998***
--0.939***
0.927***
0.874***
--1.029***
1.027***
1.014***
---
--------0.907*
--1.034***
1.048***
1.015***
---
1.002*
--0.940*
0.885**
0.886***
--1.042***
1.025***
1.013***
---
--1.008**
--0.906**
0.891***
---*
---
---
---
---
---
---
---
---
1.046***
1.078***
-----
-----
-----
1.215***
1.257***
1.129***
1.303***
1.425***
1.411***
1.204***
1.380***
1.259***
1.224***
1.480***
1.575***
1.270***
1.428***
1.302***
1.442***
1.426***
1.505***
1.240**
1.464***
1.327***
1.390***
1.445***
1.657***
.036*
Conditional ICC
.022
Variation between level 2
.500
Variation at level 2 explained
.717
Odds ratios shown are significantly different from 1.0
*** p <.001, ** p <.01, * p <.05
.057
.049
.440
1.034**
1.016***
1.016**
---*
.052
.059
.034
.572
.505
a
0= Integrated 1= Segregated
b
intermarried with Whites
64
Each year of additional education significantly (p <.05) increases the odds of
homeownership for Black households by 0.8 percent. White, Asian and Hispanic
households have no significant change based on education. Though the positive
relationship for Black households was as hypothesized, it was also hypothesized that
education would be significant for all racial groups. As expected, widowed household
have lower odds of homeownership than married households. However, the lower odds
are only significant for Whites (-6.1 percent, p <.001) and Hispanics (-6.0 percent, p
<.05). Being widowed is not significant for Asian and Black households (p >.05). Also as
expected, absent spouses significantly reduce odds of homeownership for White
households by 7.3 percent (p <.001), Hispanic households by 11.5 percent (p <.01) and
Black households by 9.4 percent (p <.001). Despite having higher percentage of absent
spouses, Asian household odds are found to be non-significant (p >.05). In agreement
with the hypothesis, being single or not married has a significant effect on all racial
groups. Whites who are single have their odds of homeownership reduced by a highly
significant (p <.001) 12.6 percent. Asian homeownership odds are reduced by a
significant (p <.05) 9.3 percent by not being married. Hispanics have a highly significant
(p <.001) reduction of 11.4 percent in odds of homeownership compared to their married
counterparts. Lastly, single Black households experience a highly significant (p <.001)
10.9 percent reduction in odds of homeownership compared to married Black
households. Contrary to expectations, current employment is found not significant for
homeownership odds of all racial groups (p >.05). Household income is highly
65
significant (p <.001) for all racial groups in increasing homeownership odds. As
expected, each increase by income decile leads to an increase in odds of homeownership
by 2.9 percent for Whites, 3.4 percent for Asians, 4.2 percent for Hispanics and 3.4
percent for Blacks. Likewise, the greater the number of children in a household leads to a
highly significant increase in homeownership odds across all racial groups. White
households increase their odds of homeownership by 2.7 percent (p <.001) per child in
their home. In the same way, Asians notice an odds increase of 4.8 percent (p <.001),
Hispanics notice an odds increase of 2.5 percent (p <.001) and Blacks notice an odds
increase of 1.6 percent (p <.01) per child. The length of residence significantly (p <.01)
increases the odds of homeownership across all racial groups. Each additional year of
residency leads to a highly significant (p <.001) increase in odds of homeownership, 1.4
percent for Whites, 1.5 percent for Asians, 1.3 percent for Hispanics and 1.6 percent for
Blacks. Unexpectedly, single female-led households have no significant affect on
homeownership for any racial group when compared to single male households (p >.05).
Assimilation Controls
None of the assimilation characteristics are found to be significant for any racial
category. Asian and Hispanic households were expected to have significant relationships
to the assimilation factors. The lack of significance follows some past research (Frey and
Farley 1996; Krivo and Kauffman 2004) that indicates that the racial stratification and
financial characteristics are more significant for racial minorities. Being intermarried
with a White partner has no effect on homeownership odds within any group. Being
66
native-born versus being foreign-born also has no significant effect on homeownership
odds for any racial group.
Stratification Controls
Interestingly, residential characteristics are only significant (p <.001) for the odds of
White households. Whites who lived in the suburbs have a 4.6 percent increase in odds of
homeownership compared to those who live in the central city. Whites who live in rural
areas experience a 7.8 percent increase in homeownership odds compared to Whites who
live in the central city. Residential location does not statistically influence (p >.05)
homeownership odds for racial minorities, but as discussed later, it significantly influence
their home equity. It is possible that minority groups have the same level of difficulty no
matter where they try to purchase a home, rendering the effect of location not significant.
Financial Controls
All financial variables are highly significant (p <.001) within all racial groups. The use of
variable term mortgages increases the odds of homeownership rather evenly for Whites
(21.5 percent), Asians (20.4 percent), Hispanics (27.0 percent) and Blacks (24.0 percent).
The use of FHA/VA/FmHA loans increases the odds of homeownership for Whites by
25.7 percent, Asians by 38.0 percent, Hispanics by 42.8 percent and Blacks by 46.4
percent. Using a large down payment significantly increases the odds of homeownership
by 12.9 percent for Whites, 25.9 percent for Asians, 30.2 percent for Hispanics and 32.7
percent for Blacks. Though these programs were known to have racial bias in terms of
67
access and funding when they first begun, it is important to realize how important they
remain for minority households in terms of access to homeownership. This follows the
pattern of stratification that suggests those most disadvantaged in a particular area will
experience the greatest increase once the barriers to their advancement are removed.
Using large down payments, the odds of homeownership increase significantly, in a
stratified form, with Whites at the lower end and Blacks at the greater end. Black
households gain an increase of 32.7 percent in odds of homeownership through the
assistance of a large down payment. Hispanic households follow with 30.2 percent, then
Asians with 22.4 percent and Whites with 12.9 percent. Only a small percentage of the
population has access to inheritance for down payments; however, it is highly significant
for increasing the odds of homeownership for Whites by 30.3 percent, Asians by 22.4
percent, Hispanics by 44.2 percent and Blacks by 39.0 percent. Despite the findings of
past research, which found minorities receive much lower valued inheritances than
comparable Whites, it seems as though the low valued inheritances have a great effect
(Henretta 1984; Conley 1999; Avery and Rendall 2002). Prior ownership leads to a large
increase of odds of homeownership for all groups. Whites who have previously owned a
home have an increase in odds of homeownership by 42.5 percent, while Asians gain
48.0 percent, Hispanics gain 42.6 percent and Blacks gain 44.5 percent compared to their
counterparts who have not previously owned. Lastly, owning a condominium increases
ownership odds by a significant 41.1 percent for Whites, 57.5 percent for Asians, 50.5
percent for Hispanics and 65.7 percent for Blacks. In all cases but inherited down
68
payments, minority groups benefit more through access to and use of these financial
elements.
Home Equity Results
Table 5 indicates that 12 of the 24 hypothesized effects on home equity are statistically
significant. About 34 percent of variation in home equity occurs between metropolitan
areas, with approximately a third of that variance explained by the control variables.
Contrary to the second main hypothesis, the diversity of neighborhoods within a
metropolitan area has no significant (p >.05) impact on the equity accumulated through
owning a house. However, when looked at within racial categories, neighborhood
diversity has a significant impact on Black and Hispanic home equity. Therefore, it may
be that the effects found for the Black and Hispanic subsamples are not large enough to
be detected when the minority racial groups are combined with the much larger White
subsample.
Even with all of the control variables, racial categories play a significant role in
wealth inequality through home equity. Asian households’ home equity is $48,342 less
than White households (p <.01). Hispanic households have $51,569 less home equity
than Whites (p <.05), and Black households have $79,345 less equity than Whites (p
<.001). Black households have the greatest disadvantage, followed by Hispanics and then
Asians. As with homeownership and prior research, the theories of racial stratification in
home equity are reinforced by the data.
69
Table 5: HLM Modeling of Home Equity
Final estimation
(with robust standard errors)
Fixed effects
Intercept 1
MEIa
Race-Ethnicity
(Omitted Non-Hispanic White)
Equity
B
(S.E.)
t
-271336.103***
-235294.908
(47716.148)
(140174.848)
-5.686
-1.679
-48342.090**
-51568.726*
-79344.547***
(16202.283)
(20556.727)
(11527.406)
-2.984
--2.509
-6.883
930.504***
14988.977***
-7346.300
-17378.133
-15984.133*
4234.076
119399.017***
16405.721***
-327.018
-2317.869
(211.120)
(1392.220)
(7353.138)
(23306.147)
(6271.163)
(7297.308)
(10139.273)
(2475.805)
(296.370)
(7079.868)
4.407
10.710
-0.999
-0.746
-2.549
0.580
11.776
6.626
-1.103
-0.327
11427.803
10736.227
(10776.382)
(10315.998)
1.060
1.041
Asian
Hispanic
Black
Lifecycle Characteristics
Age
Education
Widowed
Spouse absent
Other not married
Employment
Household Income
Children
Length of Residence
Single female
Assimilation Characteristics
Intermarried
Native-born
Stratification Characteristics
Suburb
Rural
Financial Characteristics
Variable term mortgage
FHA/VA/FmHA loans
Large down payment
Inherited down payment
Prior owner
Condominium owner
-4656.798
5223.114
(8209.342)
(22848.652)
-0.567
0.229
8996.524
-27874.320***
17611.384*
-9514.710
71879.131***
-101024.664***
(7291.098)
(5550.520)
(7338.960)
(12296.878)
(5732.053)
(16598.309)
1.234
-5.022
2.400
-0.774
12.540
-6.086
Conditional ICC
Variance between level 2
Variance at level 2 explained
.336
.310
.094
***p <.001, ** p <.01, *p <.05,
a
0= Integrated 1= Segregated
70
Lifecycle Controls
Many of the lifecycle characteristics are statistically significant, though not all, as
expected. Household age has a significant and positive effect (p <.001). For each
additional year of a household’s age, a household gained $931 in home equity. Education
was also found to be positively significant (p <.001). For each additional year of
education, households gained $14,989 in home equity. Marital status has mixed
significance for home equity. Unexpectedly, being widowed has no significant impact on
home equity (p >.05). Due to the high mean household age (53.7), many in the population
may be widowed population through death, which may not have the same fiscal effects as
becoming a widow through divorce. Having an absent spouse also has no significant
effect on home equity (p >.05). In this case, absent spouses may continue to share
ownership of the home despite being absent. However, being single is significant (p <.05)
in decreasing home equity by $15,984 regardless of age. As found with homeownership
odds, current employment plays a non-significant (p >.05) role in home equity. This may
be due to a weak link between current employment and stable income. Household income
is highly significant and increases home equity by $119,399 per decile increase (p <.001).
Likewise, each additional child in the home significantly (p <.001) increases the equity in
a home by $16,406. It was expected that children reduce the wealth of households by
increasing consumption; however, it may also be that children (who increase the odds of
homeownership) also lead parents into purchasing larger homes or homes in financially
superior areas. Contrary to the hypothesis, the length of residence has no significant
effect on home equity (p >.05). It was assumed that the longer one resides in their home,
71
the more of their debt can be paid off. However, it may be that areas where people settle
for longer periods are not necessarily increasing in value. Thus, long-term residents may
not be taking advantage of moving into faster appreciating areas. Alternatively, not all
mortgages are the same length, so length of time may not directly relate to the amount of
a mortgage one pays off. As with the homeownership model, being a single female has
no significant effect in the home equity model (p >.05). It may be that being single has a
stronger effect than being female.
Assimilation Controls
None of the assimilation characteristics are found to be significant on home equity.
Intermarried households have no significant impact on home equity (p >.05). Though
they had expected otherwise, Krivo and Kaufman (2004) also found the intermarried
household variable not significant in past research. However, when looked at within
racial groups, being intermarried has significant effects for Asians and Hispanics.
Likewise, being native-born compared to being foreign-born is not significant (p >.05).
When observed within racial groups, it is significant only for Asian households, which
will be discussed later. As suggested by past researchers, it may be that in a highly
stratified society, beneficial assimilation does not occur as effectively (Parcel 1982;
Massey and Denton 1993; Marrow-Jones 1993; Straight 2002; Rosenbaum 1996; Krivo
1995). Yet it may also be that assimilation factors are only significant for a small portion
of the population, in this case, the immigrant population.
72
Stratification Controls
Though the effect of race is stratified as expected, living in suburban and rural areas has
no significant impact on home equity compared to living in the central city (p >.05).
However, when residential location is observed within racial categories, Asians and
Hispanics experience significant effects. White and Black home equity seems to be less
tied to residential location as it is to race, income, education and other factors. Since the
majority of the population is non-Hispanic White, their insignificance is likely pushing
the overall significance out of an acceptable margin of error.
Financial Controls
Lastly, many financial characteristics have significant relationships with equity
accumulation. Though obtaining a FHA/VA/FmHA loan increases odds of
homeownership, it significantly (p <.001) decreases home equity by $27,874 compared to
those who do not have the loan, which was contrary to expectations. As expected, large
down payments significantly increase home equity by $17,611 (p <.05). Prior ownership
increases home equity significantly by $71,879 (p <.01). Also as expected, owning a
condominium significantly reduces home equity by $101,025. Variable term mortgages
and inherited down payments have no significant effect on home equity. Variable term
mortgages are significant towards homeownership, which suggests that variable term
mortgages create more opportunities to own homes, but those using variable term
mortgages may be purchasing homes of comparable value to those with standard
mortgages. Likewise, inherited down payments are significant for homeownership, but
73
seem to make no difference on home equity. This also suggests that the increased
opportunity to own a home is not necessarily related to the increased value of a home.
Home Equity within Ethnic and Racial Groups
When home equity is observed within racial groups, it is possible to isolate the variables
with significant impact on the wealth accumulation for each racial group. As observed in
Table 6, 10 of 20 factors are significant for White households, 11 of 21 factors are
significant for Asian households, 8 of 21 factors are significant for Hispanic households
and 7 of 21 factors are significant for Black households. Living in a region with racially
integrated neighborhoods has a significantly positive effect for Hispanic households and
Black households. Hispanics who live in regions with high neighborhood segregation
have $332,661 less in equity than Hispanics within regions of high integration (p <.05).
Black households also benefit from living in integrated neighborhoods and lose $255,897
in home equity in regions of high segregation (p <.05). Residing in a region with
segregated neighborhoods has no significant effect on Asian or White home equity (p
>.05). Residential segregation may not block odds of obtaining housing within racial
groups, but it seems to block access to comparable housing. Blacks and Hispanics who
are able to live outside of the cities with highly segregated ghettos and barrios have
substantial financial gains on their counterparts who are not able to escape. Also of
importance is the effect of change Hispanic households gain compared to Black
households. Stratification theories had suggested Hispanics would have larger gains than
Blacks would due to less stigma and difficulty while looking for a new home. This may
74
indicate shifting patterns of racial stratification. In short, greater racial integration in
neighborhoods helps minorities gain wealth more efficiently. It seems that areas with
more diversity have either higher valued housing or housing that increases in value faster
than segregated areas.
Lifecycle Controls
Lifecycle characteristics play varying roles depending upon a household's race. Age is
only significant for Whites (p <.001) and Hispanics (p <.01), where each additional year
of household age adds $978 and $1,165 to a household's equity respectively. Asian and
Black households have no significant effect (p >.05). Household education is significant
within every group. Each year of education increases home equity by $17,865 for Whites
(p <.001), $14,017 for Asians (p <.001), $5,915 for Hispanics (p <.05) and $11,407 for
Blacks (p <.001). Marital status has mixed effects within racial categories. A widowed
household has no effect on home equity for any racial group (p >.05). Having a spouse
absent is only significant for Asians who lose $99,702 in home equity (p <.001). The
home equity of Whites, Hispanics and Blacks are not affected by absent spouses (p >.05).
As expected, being single reduces home equity, however only White and Black
households have significant reductions (p <.05). Single White homeowners have $17,924
less home equity than married White homeowners. Single Black homeowners have
$27,269 less in home equity than married Black homeowners. As found with
homeownership, the effect of current employment on home equity is not significant
within any racial group (p >.05). As hypothesized, household income significantly
75
increases home equity within all racial categories. Though it is not a linear effect, roughly
every income decile increase leads to a gain of $123,613 (p <.001) for White households,
a gain of $83,474 (p <.001) for Asian households, a gain of $138,668 (p <.001) for
Hispanic households and a gain of $43,763 (p <.01) for Black households. This suggests
that income gains are less helpful for Black households in home equity accumulation and
most helpful for Hispanics and Whites. The number of children in a household
significantly increases home equity for Whites $22,172 (p <.001) and Asians $22,979 (p
<.05). The number of children is not significant in producing or reducing equity for
Hispanic and Black households (p >.05). Demographically, Hispanic and Black
households have the largest number of children so it was expected that they would also
have a significant relationship with home equity. However, other factors such as race and
income and education may be more influential for Hispanic and Black households. The
length of residence is not significant (p >.05) within any racial group. Again, it was
expected that years spent in one place would increase home equity, yet this may not
account for housing market trends or households who intentionally move into higher
appreciating areas. As found with homeownership, households headed by single females
also have no affect on home equity regardless of racial categories (p >.05).
Assimilation Controls
As expected, only Asian and Hispanic households notice a significant change in home
equity due to assimilation characteristics. A puzzling result is that Asians who intermarry
with Whites have a significantly negative change (p <.05) in home equity over those who
76
do not. Hispanics gain $41,985; however, Asians lose $73,707 in equity by intermarrying
with Whites. Intermarrying has no effect on Black home equity (p >.05). A positive
relationship was expected for all minorities. Native-born Asians have a significant
increase in home equity of $61,633 over non-native Asians (p <.05). However, all other
groups have no difference between native and foreign-born (p >.05). It was expected that
Asian and Hispanic households had a significant relationship, however Asian households
are the only group with more than 50 percent of households being foreign-born.
Therefore, this may just be a factor of the characteristics of the sample population.
Stratification Controls
Though moving out of the central city into the suburbs does not seem to change the odds
of homeownership for minority households, it does significantly increase the value of
their homes according to the expected levels of stratification. Asian households gain
more wealth the further they move from the central city. Asian household in the suburbs
had a statistically significant increase (p <.05) of $30,464 in home equity for living in the
suburbs compared to living in the central city. Asians also had a statistically significant
increase of $105,871for living in rural areas compared to the central city (p <.01).
Hispanics notice a significant (p <.05) increase of $25,059 for living in the suburbs, but
have no changes in rural areas (p >.05). Black households also notice a significant (p
<.05) increase of $22,507 in suburbs, yet rural areas compared to central cities have no
effect (p >.05). For Hispanics and Blacks this may be related to their lower odds of
homeownership in rural areas. White home equity is not affected by living in suburban or
77
rural areas compared to central cities (p >.05). Location is significant only for Whites in
odds of homeownership, suggesting home equity appreciates about the same regardless of
where White households reside.
Financial Controls
Financial characteristics play a varied role in home equity accumulation within racial
groups. Variable term mortgages are only significant (p <.05) for Asian households and
increased their home equity by $59,905. White, Hispanic and Black households had no
significant change in equity compared to households in their categories with standard
mortgages (p >.05). The use of FHA/VA/FmHA loans is highly significant (p <.001) for
White households, who have $31,087 less in home equity than White households with
normal loans. Asian, Hispanic and Black households all benefit significantly from these
loans for homeownership. However, they do not experience a significant change in home
equity by using FHA/VA/FmHA loans (p >.05). It was expected that the use of
government loans would increase home equity, however this indicates that homes
purchased with these loans did not purchase homes in areas of high value. Due to the
history of racism in these loan processes, it was expected that FHA/VA/FmHA loans
would be less significant for minorities. In this case, they are found completely nonsignificant for minorities. While significant for every group in odds of homeownership,
the use of a large down payment only significantly increased the home equity of White
households by $22,023 (p <.001). The use of large down payments does not have an
effect on Asian, Hispanic or Black home equity. Inheriting a down payment is not
78
significant towards gaining home equity for all racial categories (p >.05). Prior ownership
has significant positive effects within all racial groups. White households gain a highly
significant (p <.001) $77,330 on their current equity by having owned their previous
home. Asian households gain $112,689 (p <.001), Hispanic households gain $60,515 (p
<.001), and Black households gain $33,507 (p <.001), when compared to their racial
counterparts who did not previously own their home. The significances within racial
groups are found as expected; however, the results are not stratified as expected. In this
case, Asian households have a much larger gain than any other group. However, the
lower levels of past ownership by minorities indicated in Table 2, suggest racial barriers
to homeownership are still affecting all minorities more than Whites. Asians may have
greater pay offs due to prior homeownership, yet they still lag behind Whites in the
opportunity to own a home. Lastly, owning a condominium is significant within all
groups. Whites who own a condominium have a significant (p <.001) $99,517 less than
Whites who own houses. Asians have $139,936.41 less (p <.001) than Asians who own
houses; Hispanics who own condominiums have $85,580 less (p <.001) than Hispanics
who own houses, and Blacks have $34,103 less (p <.05) than Blacks who own houses.
The effects of condominium ownership are as expected. They raise the odds of
homeownership within all groups and lower the total equity within all groups. The
relatively small wealth gap between Blacks who own property and Blacks who jointly
own their property suggest that Black homeowners have considerably lower valued
homes than the rest of the racial groups.
Table 6: Home Equity within Ethnic and Racial Groups
Final estimation
(with robust standard errors)
Whites
B (S.E.)
Fixed effects
Intercept 1
-345274.59***
MEI
-229440.99
Age
978.36***
Education
17864.66***
Widowed
-8527.72
Spouse absent
-22827.83
Other not married
-17923.98*
Employment
8144.11
Household income
123612.83***
Children
22172.20***
Length of residence
-206.12
Single female
-4807.72
Intermarriedb
---Native-born
17734.29
Suburb
-8960.76
Rural
9996.48
Variable term
4983.60
mortgage
FHA/VA/FmHA
-31086.69***
Large down payment
22023.04***
Inherited down
-22385.76
payment
Prior owner
77330.10***
Condominium owner
-99516.49***
Conditional ICC
Variation between level 2
Variation at level 2 explained
*** p <.001, ** p <.01 ,* p <.05
(61150)
(147880)
(298)
(1842)
(10739)
(24290)
(8426)
(8798)
(11211)
(4693)
(336)
(8521)
---(17166)
(11863)
(22600)
(10185)
Asians
B (S.E.)
-200772.78
-353815.59
1390.93
14017.01***
-53930.81
-99702.13***
-9881.71
-11543.31
83473.94***
22978.78*
482.52
44350.33
-73707.30*
61633.21*
30463.68*
105870.67**
59904.66*
(129382)
(183257)
(1069)
(5375)
(43767)
(30139)
(48602)
(29305)
(20871)
(10530)
(1125)
(43052)
(37328)
(28755)
(14519)
(35487)
(25680)
Hispanics
B (S.E.)
207172.57**
-332660.56*
1165.01**
5915.26*
46899.78
41868.76
-7655.15
26876.11
138668.12***
346.83
-413.69
-657.17
41984.82*
-13303.51
25059.41*
9893.26
9294.80
Blacks
B (S.E.)
(64765)
(161889)
(366)
(2299)
(27547)
(58712)
(21340)
(16252)
(24753)
(4332)
(679)
(17234)
(18012)
(14438)
(11653)
(52934)
(13034)
-85512.67
-255896.84*
650.82
11407.25***
-27689.06
-36697.41
-27268.62*
-13304.94
43763.34**
3424.81
-352.26
11439.86
44798.60
-5124.53
22507.07*
-75552.16
-8059.89
(7795)
(7964)
(12130)
-57941.30
-14253.05
-15575.16
(41631)
(22273)
(81512)
-15978.05
-6753.26
54675.02
(12017)
(19616)
(38362)
-11926.13
8354.28
20752.93
(7359)
(18944)
.359
.337
.110
112688.72***
-139864.31***
(20099)
(21046)
.231
.235
.141
60514.96***
-85579.66***
(14553)
(17539)
.276
.267
.105
33507.28***
-34305.15*
(51330)
(112762)
(465)
(2467)
(16649)
(28584)
(12843)
(12142)
(12011)
(3360)
(386)
(9248)
(40656)
(16509)
(10595)
(63460)
(10505)
(7360)
(24913)
(26250)
(8360)
(17047)
.438
.425
.065
a
0= Integrated 1= Segregated
b
Intermarried with Whites
79
80
In review, the odds of homeownership are positively affected by years of education,
income, number of children, the use of variable term mortgages, the use of
FHA/VA/FmHA loans, the use of a large down payment, inheriting a down payment,
previously owning a home, owning a condominium, and for Whites, living in the suburbs
or rural areas. Odds of Homeownership are negatively affected by age, being single,
widowed or having an absent spouse, and race if the household is Hispanic or Black.
Home equity is increased by age, education, income, number of children, the use of a
large down payment, prior ownership, and living in the suburbs if the household is nonWhite. Meanwhile, Home equity is reduce by being Asian, Hispanic or Black compared
to being White, being single, using FHA/VA/FmHA loans, owning a condominium, and
neighborhood segregation if the household is Hispanic or Black.
81
Chapter 5
CONCLUSIONS
Although the United States continues to diversify and integrate, we have had the highest
level of racial and ethnic wealth inequality amongst all postindustrial nations from the
1980’s onward (Wolff 1998; Keister and Moller 2000; Lewin-Epstein and Semyonov
2000; Ross and Yinger 2002). This wealth inequality has contributed to power and
political inequality, where inequalities in opportunities, resources, political power and
rights continue to perpetuate. Most efforts and research have focused on improving
income inequality despite the relatively weak relationship of income to wealth equality
(Keister and Moller 2000; Flippen 2001; Avery and Rendall 2002; Krivo and Kaufman
2004). As the wealth gap continues to widen, there is a dire need to update past research
and improve our current understanding and efforts towards social equality. This thesis set
out to explore the role of neighborhood level diversity towards obtaining homeownership
and its effect on home equity, in order to understand a leading factor for the wealth gap in
the United States. Specifically, this thesis considers the effect of an improved index for
multi-group neighborhood segregation, rather than the more prevalent dual-group
dissimilarity indexes. In an attempt to provide research that is relevant to our multiethnic
society, this study also analyzes within pan-ethnic racial groups to observe the specific
impact of neighborhood diversity on wealth for each group. Lastly, this thesis introduces
hierarchical linear modeling as a more appropriate statistical method for incorporating
higher-level variables such as the multi-group entropy index. These approaches brought
82
advantages and disadvantages. However, the resulting statistics provide important
information for current policy and future research.
Review of Findings
This study tested two main hypotheses. The first was that the greater racial diversity
within neighborhoods in a market would result in greater homeownership gains rates
across racial groups. The second was similar, which hypothesized that the greater racial
diversity of neighborhoods in a market would result in greater home equity gains across
racial groups. The analysis of the data found no significant support for the first
hypothesis; however, two of the four racial groups support the second hypothesis. Black
and Hispanic households both experience an increase in home equity if they live in
regions with greater neighborhood diversity. Though no past research has analyzed the
role of multi-group entropy on equity, the former studies have indicated that Black and
Hispanic households are most affected by residential segregation (Bianchi, Farley and
Spain 1982; Massey and Denton 1993; Flippen 2001; Krivo and Kaufman 2004;
Gittleman and Wolff 2004). It was also known that Black and Hispanic households have
lower value and quality homes than Whites and Asians regardless of their socioeconomic
status (Bianchi, Farley and Spain 1982; Horton and Thomas 1998; Flippen 2001; Krivo
and Kaufman 2004; Gittleman and Wolff 2004). This study found that the level of
segregation in a neighborhood does not contribute to the odds of homeownership, nor to
the racial differences in homeownership. However, this study found that the level of
segregation in a neighborhood contributes to the racial differences in home equity.
83
Hispanic households lose $332,661 in wealth purely through living in an area with
racially isolated neighborhoods, compared to their peers in non-segregated
neighborhoods. Likewise, Black households also lose $255,897 by living in a racially
isolated neighborhood compared to Black households in integrated neighborhoods. If the
effect is linear, it relates to roughly a loss of $3,327 for each percent increase in
segregation for Hispanics, and a loss of $2,559 for each percent increase in segregation
for Blacks. The findings of this study are even more significant when paired with the data
suggesting minorities hold roughly 70 percent of their wealth in equity alone (Yinger
1995; Wolff 1998; Spillerman 2000; Restinas and Belsios 2002). Thus, every dollar of
home equity lost is more detrimental for a minority’s net wealth than it is for the average
White household.
As past research has identified, Blacks and Hispanics prefer to live in racially
diverse residential areas more than Whites (Grant and Parcel 1990; Farley et al 1994;
Herbert and Kaul 2005). The reality that many Black and Hispanic households are
residing in segregated neighborhoods despite their will, suggests a neighborhood level
barrier exists that is actively suppressing their wealth. Since no evidence was found to
suggest neighborhood segregation plays a role in opportunities of homeownership, what
was found indicates the homes available to Blacks and Hispanics in segregated
neighborhoods greatly differ in value from homes available to them in integrated
neighborhoods. These findings reinforce past findings in the differences of loan to value
ratios of Blacks and Hispanics from Whites (Massey and Denton 1993; Bobo and
Zubrinsky 1996; Alba, Logan and Stults 2000a; Charles 2000; Flippen 2001; Rosenbaum
84
and Friedman 2001). This invites the conclusion that regardless of income, education,
prior homeownership and the other controlled factors, disparate access to housing of
equal value (and consequently an equal opportunity to improve wealth) is further
perpetuating the wealth divide in the United States for Black and Hispanic households in
segregated neighborhoods.
Theoretical Implications
This thesis followed four major theoretical frameworks; life cycle, assimilation,
stratification and financial. Though most of the control variables test for life cycle and
financial characteristics, most of the guiding emphases on hypotheses were due to
stratification theories. Race was found significant in both models, which agrees with
much of the past research and theories regarding social inequality and racial wealth
inequality. Interestingly, the effect of race played various roles in homeownership and
home equity. When looked at within racial groups, Asian, Hispanic and Black households
generally had lower gains than White households. In relation to odds of homeownership,
Asians were not found to have significantly different odds of ownership than Whites,
while Hispanics and Blacks shared equally lower odds of homeownership compared to
Whites. However, in the home equity model found in Table 5, the effect of race is
stratified as expected, with Asians having the smallest loss in wealth compared to Whites
and Black households having the greatest loss. Hispanic households were found to be in
the middle. This clearly supports the conclusions of past research on racial hierarchy that
has documented wealth inequality (Krivo and Kauffman 2004; Herbert and Kaul 2005;
85
Kim and White 2005; Putnam 2007). When viewed by racial group, the equity model also
found many of the financial characteristics were not significant for the minority groups.
This is of great concern because of its implications towards the ideal that financial
characteristics should directly relate to wealth characteristics.
For the most part, many of the control factors, as well as the independent variable
were assumed to be stratified by race. In addition to specific stratification controls such
as residential location, racial stratification was observed through the independent
variable, neighborhood level racial segregation. However, only a few of the expected
stratification controls were found stratified across race in the models. For the
homeownership model this included FHA/VA/FmHA mortgages and loans, and large
down payments. Alternatively, in the case of residential location and homeownership,
where Whites find significance and no minority groups find significance, a broad level of
stratification can be assumed. In this case, White household’s have significant advantages
gained from the places they choose to live, but for minority households, there is no
advantage anywhere. For home equity, the results of residential stratification are less
clearly shown. For example, living in a suburb versus the central city does not affect the
equity of White households; however, the effect on Asians is greatest, followed by
Hispanics then Blacks. With the other factors, Black and Hispanic households were more
likely to follow the pattern of racial hierarchy than Asians, whose results would vary
greatly. Though the current theories proved helpful, the results of this thesis suggests
more research needs to be done to refine and update racial stratification theories.
86
The life cycle theory still holds much weight according to this study. The
demographic uniqueness of a home continues to play a strong role in both
homeownership and home equity. Age, education, marital status, income and number of
children were significant for homeownership odds and home equity. As with past
research, life cycle characteristics have more of an effect on White households than on
minority households. This is an indicator of social stratification, wherein the logical and
expected relationships are limited or invalidated by an underlying systemic structure that
favors White efforts for homeownership and wealth accumulation. An example is found
through the effect of education on home equity. An additional four-year degree can lead
to a payoff of $71,459 in home equity for a White household. However, an identical four
years of education only leads to a payoff of $56,068 for Asian households, $45,629 for
Black households and an unreasonably low $23,661 for Hispanics households. In terms
of theoretical significance, life cycle characteristics continue to play significant functions
in both homeownership and home equity. However, they may be most useful as
indicators exposing the existence of structural racial inequalities.
Hypotheses involving home equity that were aligned with assimilation theories
were partially substantiated through the data. Being native-born is significant for Asians
in the home equity model. It was also expected to be significant for Hispanics in both
models. Yet, the result of being native-born is only related to large home equity payoffs
for Asians. Past research has also found that Asians have benefitted the most from
housing policies aimed at minority homeownership, which may contribute to the effect of
neighborhood segregation being not significantly different from that of Whites (Herbert
87
and Kaul 2005). These policies may be more accessible to native-born populations, or
native-born populations may also have higher initial wealth. The data also indicates that
Asians are more likely to live in integrated neighborhoods than any other group,
especially with Hispanics and Whites. Therefore, it may be that Asians are benefitting
inadvertently from their nearness to the less stigmatized groups. However, the effect of
being intermarried plays a unique role for Asians compared to Hispanics in terms of
home equity. Asians who intermarry with Whites lose $73,707 in equity compared to
Asians who do not. Alternatively, Hispanics follow the hypothesis and gain about $9,295
by intermarrying with Whites. This may suggest that neighborhood integration is more
socially acceptable than relational assimilation. It also may indicate that Asians who
intermarry may wed Whites who have lower social and financial capital, or may live in
areas with lower home values. As with stratification theories, these anomalous outcomes
may be a result of the pan-ethnic categorization of Asians, or their relatively low numbers
in our national population. Due to the findings of this study, assimilation theories should
remain a focal point for future research involving Asian and Hispanic populations.
The financial characteristics show highly significant and positively correlated
results across the board for homeownership. Because of the strong relationships, it would
be easy to assume that financial effects would also directly relate to home equity.
However, only a few financial effects are significant for home equity, and not all are
positively correlated. As with life cycle characteristics, the theories and assumptions of
the financial factors reflect White results better than those of minorities. When it comes
to gains and losses, Hispanics and Blacks usually gain less and lose noticeably more than
88
Asians and Whites. In terms of Hispanic and Black households, their weak gains from
financial effects is likely due to their lower value and quality homes than Whites and
Asians, regardless of their socioeconomic status (Bianchi, Farley and Spain 1982; Horton
and Thomas 1998; Flippen 2001; Krivo and Kaufman 2004; Gittleman and Wolff 2004).
On the other hand, Asians seem to fare better than Whites in relation to the impact of
financial characteristics. As in this study, Krivo and Kaufman (2004) found large
financial gains for Asians despite the lower levels of homeownership and the presence of
racial stratification. They concluded that Asians might be operating in distinctive housing
markets due to residency in areas with higher homeownership demand and value. If this
were the case, then the results found here would indicate that those high demand areas
might have also benefitted the greatest from the housing market boom at the time of the
study, resulting in the exceptionally high equity gains found here. These results again
point toward the conclusion that there are strong barriers to wealth accumulation through
home equity for minorities that do not exist for White households.
Strengths and Limitations
There were a few limitations to this research known prior to the study, as well as a few
learned in retrospect. As discussed earlier, the use of HLM limits the ability to account
for non-response and truncated data. Though certainly more accurate at comparing multilevel data than in linear regression, the use of HLM paired with a dataset that did not
oversample for minorities nor require complete responses, lead to a loss of many
potential households. Though still above the numerical counts necessary for a relevant
89
national study, it would be beneficial if there were some way to link Tobit modeling and
HLM. Secondly, access to household-level neighborhood data is limited for nongovernment officials to the metropolitan level. This severely limited the ability of this
study to compare neighborhood level factors, forcing neighborhood level data to be
aggregated at the metropolitan level. Though this does not necessarily affect the outcome
of the study, it limits the scope of the study to regions rather than the nuances found in
segregated and integrated neighborhoods. Choosing not to run a longitudinal study makes
it impossible to tell if the disparities of wealth and the effects of neighborhoods are
moving towards racial wealth equality or away. It also limits the ability to study the
accumulation of assets and inheritances in relation to home equity. The inclusion of four
theoretical approaches was significant for a general understanding in the understudied
area of home equity. However, a stronger focus on stratification theories with controls for
demographic and financial elements may be more beneficial to future research.
A few issues learned in retrospect are not unique to this study. One such issue is
the difficulty of using racial and ethnic categories in previously collected data. This
required the research to focus on the four major pan-ethnic categories despite their great
internal diversity. In addition, some financial data, such as, information on lenders,
neighborhood housing values and household credit scores were unavailable. Another
significant limitation to this study is multicollinearity. Due to the shared characteristics of
some variables (such as number of children in a household and the level of overcrowding
in a household), many coefficient estimates were erratically affected until one of the
highly correlated control variables was removed. The occurrences of multicollinearity
90
lead to the removal of higher-level regional locations due to their relationship with the
lower-level MSA's. In addition, a few control variables that were highly correlated with
citizenship status, such as years in the United States, naturalization status, and linguistic
isolation were also removed. As mentioned above, the number of children in a home was
kept, however the control for overcrowding was dropped out of necessity. This, along
with the removal of regional locations limited the number of variables used as controls
for racial stratification. Though the presence of multicollinearities limited the range of
controls in the model, the removal of the collinear controls has provided results that are
more valid.
Despite the limitations and challenges mentioned above, this thesis has strong
indications of validity, both in practice and in results. In practice, the methods used
helped increase validity and reliability. The dataset comes from an effectively constructed
and administered national survey. When analyzed for accuracy and reliability, Lam and
Kaul (2003) found it to be reliable and consistent with parallel data. The use of MSA data
over county statistics helps correctly identify physically and socially connected housing
markets rather than political and geographic areas. Since the focus of this thesis was the
relationship of a higher-level factor on lower-level variables, the HLM model used is the
most accurate way to incorporate multi-level data in an analysis. As discussed earlier, the
identification and removal of collinear variables has also factored into the increased
validity of this study. In terms of the results mentioned above, the study reinforces much
of the prior research reviewed in the literature review. In addition, the results generally
followed the theoretical expectations used to guide this thesis.
91
Implications of Findings
Without alternative forms of wealth accumulation, even the recently declining levels of
residential segregation are making a negative impact on the wealth of Hispanic and Black
households. This cross-sectional analysis captures the impact of household wealth at its
peak strength before the current economic recession and housing market collapse.
Considering the large number of Hispanic and Black households using FHA/VA/FmHA
mortgages and loans compared to Whites, as well as their lower net wealth, the current
economic recession will certainly have a greater negative effect on these minority groups
since many of their homeownerships begun as high risk. What this study found indicates
that even at the peak of home equity gains, minority households experienced lower
returns on their investments than Whites, due to racial-ethnic stratification. More research
will need to focus on the role of neighborhood diversity, especially longitudinally, to
identify the direction of home equity inequality in relation to the changing demographics
of neighborhoods in the United States. A follow-up study would also be significant for
understanding the role of the current economic recession and housing market collapse in
relation to the economic boom during this survey.
Prior ownership is one of the greatest factors affecting home equity and odds of
homeownership. When looked at within racial groups, it is clear that once the initial
barrier to first-time homeownership has been overcome, minorities’ odds of future
ownership increase the greatest. This suggests that efforts and research concerned with
reducing the racial gap in homeownership, though increasingly successful, are still
92
necessary. However, the findings of this study indicate social policy needs to focus on
removing the racial barriers that are blocking the residential preferences of Hispanic and
Black households. Structurally prejudiced residential barriers are constraining the market
process and reducing the value and appreciation of homes owned by Hispanic and Black
households. Idealistically, there should be no significant difference between minorities in
segregated neighborhoods and minorities in integrated neighborhoods. Especially, once
we have controlled for the life cycle and financial factors as done in this study. In this
case, it is potentially a good thing that White and Asian households are found to have
non-significant results for home equity. Though it is uncertain, it suggests that wealth
through home equity can be obtained just as effectively, whether Asians and Whites live
in areas with segregated neighborhoods or not. Future research should continue to isolate
the factors of wealth accumulation significant for each group. There may be factors
unique to Black and Hispanic households that need to be attended to in order to negate
the effects of neighborhood segregation. Due to the results of this study, theories
addressing racial stratification should become more prominent in future research. Greater
focus should also be made towards the influential social and economic factors behind
racial stratification until data no longer finds race significant when financial and life
cycle factors are controlled. In terms of subjects of the study, more research must be done
on those grouped within the Asian category to explain why their data does not
consistently agree with current theories on race and stratification. In addition, future
research should also study within pan-ethnic groups to identify the exceptional
93
populations producing results contrary to current theories and to update current panethnic theories.
Though continued research will generate the information this study was unable to
produce, policy implications can be articulated through what this study has found. Tables
3 and 5 indicate that neighborhood segregation is not significant in limiting the odds of
homeownership; however, Table 6 identifies obvious limits to the value of homes
available to Hispanics and Blacks. Inhibitors to equality may be related to the high rates
of predatory or subprime lending being offered to these minority groups (Turner 1992;
Massey and Denton 1993; Oliver and Shapiro 1995; Yinger 1995, 1997). Alternatively,
they may also be related to property screenings, higher lending costs, information
restrictions and differences in realtor-client and lender-client relationships based solely
on race (Yinger 1997). If the true financial value of a home is not its purchase price, but
rather its ability to hold or increase wealth through equity, Hispanic and Black
homeowners in segregated areas are not obtaining homes of equal value to those in
integrated areas. When combined with their inability to move into desired residential
locations, the effect on the racial wealth gap becomes more pronounced. It is important to
recall the impact of wealth on communities as well as the social, economic and physical
impact of wealth on the households. Access to wealth provides economic and noneconomic wellbeing, ranging from increased civic and educational opportunities to better
healthcare and employment. Policy aimed at reducing the home equity inequalities found
in this thesis would greatly improve the current and future wellbeing of Hispanic and
Black households.
94
The provision of housing with equal appreciation rates is much more difficult to
manage than purely providing homeownership opportunities. Equity appreciation
involves regional economic factors, urban zoning policies, neighborhood stigmas, as well
as the broad range of financial and commercial factors unique to the neighborhood. In the
past, loans specifically designated for communities of “underserved status” have seemed
to improve the acquisition of homeownership for those systematically excluded. Yet, due
to their lack of significance on the equity of minority groups, these very loans are likely
promoting homeownership in underserved and segregated communities. Loans of this
sort may also contribute to the deepening segregation as the few who can afford
homeownership move out, leaving the community in greater financial depression.
Likewise, providing homes in segregated areas for Black and Hispanics has contributed
to the racial wealth gap. Although, simply providing loans to escape underserved
communities may help a few households overcome the hurdles of homeownership in
more segregated neighborhoods, it does not solve the root problem, the social stigma and
popular prejudice towards segregated minority communities versus the positive values
attributed to segregated White communities. The stigmas and the practices they reinforce
perpetuate the financial strength of White neighborhoods by isolating market demands.
Rather than fight discrimination one a case-by-case basis, more effective policies need to
address the practices that are producing the racially disparate outcomes in the housing
market. Possible solutions to home equity inequality would need to be more complex and
range from strengthening current laws against racist practice of realtors and banks, as
well as increasing enforcement on laws against redlining and the types of loans offered to
95
minority group households. However, the ultimate change would require the negative
prejudice and discrimination towards Hispanics and Blacks to reduce. Racially prejudiced
attitudes and actions have been improving gradually in recent decades, yet they have a
long way to go. Changes in stereotypes may be lead by the policy of governments
nationally and locally, however, the deepest change comes when individuals who work
within the various sectors of the homeownership and appreciation processes (realtors,
bankers, urban planners, and neighbors) begin to internalize the information and act
consciously and collectively in ways that promote social equality.
Although current social equity policies may be considered successful in negating
the effect of residential segregation on opportunities to own a home, there is much work
to do in terms of providing access to homes of equal value for Black and Hispanic
households. It is clear that the financial investment of Black and Hispanics in homes are
not returning wealth equal to those made by Whites and Asians. It is important that
research continues to identify and study the various methods of wealth accumulation to
determine if specific groups are systemically excluded. In terms of home equity, this
means greater enforcement of current laws helping minority Hispanic and Black
households obtain homes in areas of equal value to Whites and Asians. As well as an
increased awareness of the structural inequalities by those with the abilities to improve or
perpetuate the homeownership and equity-appreciation gaps.
96
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