Chapter 1 draft

Exploring the Effects of Generation X on the Gender Wealth Gap in the United States

Dissertation

Submitted to Northcentral University

Graduate Faculty of the School of Business and Technology Management in Partial Fulfillment of the

Requirements for the Degree of

DOCTOR OF PHILOSOPHY

by

DONNA L. DEMILIA

Prescott Valley, Arizona May 2011

UMI Number: 3459509

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Donna L. DeMilia

11

Approval Page

Exploring the Effects of Generation X on the Gender Wealth Gap in the United States

by

Donna L. DeMilia

Approved by:

*£L_ _ , A. £ -r U/ZJQ iair: James Neiman, Ph.D. -^ Date

Member: Kris Iyer, Ph.D.

Member: John Hannon, Ph.D.

Certified by:

j(

School Dean: Lee Smith, Ph.D. yib/&>/f

iii

Abstract

Women in the United States (U.S.) have less accumulated wealth than men, as evidenced

by more women living in poverty than men and less women being among the wealthy

than their male cohorts. The phenomenon of men having higher net worth than women,

known as the gender wealth gap, affects women's quality of life. The gender wealth gap

has narrowed for Generation X because factors that traditionally contributed to the gender

earnings gap do not affect members of this group as much as prior generations. The

problem was that it has been unknown whether Generation X women, in comparison to

women of prior generations, were accumulating as much wealth as their male cohorts.

The purpose of this quantitative trend analysis study was to examine the gender wealth

gap in the U.S. over the period 1992 - 2007 in order to determine whether Generation X

women, compared to women in prior generations, were accumulating as much wealth as

their male cohorts. The 8,676 participants in this quantitative trend analysis study were

respondents to the Survey of Consumer Finances (SCF), who were unmarried adult

taxpayers in the U.S. at the time of participation. The study period was 1992 through

2007, and the data for the study comes from the triennial SCF. The net worth values of

two groups, unmarried male respondents and unmarried female respondents, were

compared using Mann-Whitney U tests and ANOVA, which indicated that the two

groups were not similar, with/?<.001. Therefore, the gender wealth gap existed in the

U.S. throughout the study period. The trends in the gender wealth gap differed by

generational cohort throughout the study period. The gender wealth gap has narrowed for

Generation X over the study period, while the gender wealth gap for Traditionalists and

Baby Boomers continued to widen during the same period. It can be concluded that the

gender wealth gap will continue to narrow if future generations have similar

iv

characteristics to those of Generation X. It is recommended that future studies examine

specific factors that influence the gender wealth gap by generation, and identify ways to

promote financial equity within particular generations.

v

Acknowledgements

/ can do all things through Christ who strengthens me. -Philippians 4:13

It is with a grateful heart that I acknowledge my family and friends for supporting

me throughout my lifetime pursuit of academic advancement. I thank my parents, Joe

and Molly, for their guidance and encouragement, and for providing me with all of the

advantages that have led me to where I am today. Mom, you have listened to me

throughout this process, and for that I am so thankful. I thank my brothers, Joe and Dave,

for their friendship, and for each, in their own way, demonstrating a commitment to

excellence that I am so very proud of. I thank my niece Gracie for being a constant

reminder of all that is important in life, and I honor the memory of my GiGi, who first

inspired me to consider the differences between our generations. I give a special thanks

to Dean, for holding my hand, and always believing in me.

I would not have begun, nor completed, my doctoral studies without the support

of my colleagues at Grand Canyon University. I thank Dr. Kathy Player and Dr. Scott

Quatro, who first encouraged me to enroll in this doctoral program. Prof. Kim

Donaldson and Prof. Olivier Boucher have provided support and flexibility when I have

needed it. Dr. Kevin Barksdale's wisdom and guidance have helped me in my

completion of this milestone, and I am so very grateful.

The Northcentral community has provided the support that I have needed

throughout my doctoral studies. Dr. James Neiman, my Chairperson, has shared his

expertise as he has patiently guided me through the dissertation process. I acknowledge

vi

Dr. Linda Burrs, who first helped me to articulate this concept, Dr. Marilyn Simon, who

guided me as I took an idea and formulated it into a working study, and Jennifer Benacci,

who has answered my many questions throughout the past five years. I thank Dr. John

Hannon and Dr. Kris Iyer, for participating in my committee and providing me with

invaluable feedback that has shaped my dissertation.

I especially would like to thank my father, who has influenced my career more

than any other person has. My love, respect, and admiration for him are immeasurable. I

dedicate this work to my father, my friend, and my mentor, Joseph DeMilia. Thank you,

Dad, for everything.

vn

Table of Contents

Approval Page iii

Abstract iv

Acknowledgements vi

List of Tables x

List of Figures xii

Chapter 1: Introduction 1 Background 2 Problem Statement 5 Purpose 6 Theoretical Framework 7 Research Questions 8 Hypotheses 9 Nature of the Study 9 Significance of the Study 11 Definitions 12 Summary 13

Chapter 2: Literature Review 16 The Gender Wealth Gap 18 Women and Wealth Accumulation 29 The Survey of Consumer Finances 38 Generation X 45 Summary 55

Chapter 3: Research Method 58 Research Methods and Design 60 Participants 63 Materials/Instruments 66 Operational Definition of Variables 68 Data Collection, Processing, and Analysis 69 Methodological Assumptions, Limitations, and Delimitations 71 Ethical Assurances 73 Summary 74

Chapter 4: Findings 77 Results 79 Evaluation of Findings 117 Summary 121

Chapter 5: Implications, Recommendations, and Conclusions 123

vin

Implications 124 Recommendations 128 Conclusions 129

References 131

Appendices 139 Appendix A: Topics included in the 2007 Survey of Consumer Finances survey instrument 140

IX

List of Tables

Table 1 Number of Survey of Consumer Finances Respondents Selected for Study, by Year 65

Table 2 Number of Unmarried Respondents to the Survey of Consumer Finances, by Sex and Year 80

Table 3 Median Net Worth Statistics for Respondents to the Survey of Consumer Finances, by Year 81

Table 4 Mean Net Worth Statistics for Respondents to the Survey of Consumer Finances, by Year 81

Table 5 Net Worth Statistics for Unmarried Male Respondents to the Survey of Consumer Finances, by Year 82

Table 6 Net Worth Statistics for Unmarried Female Respondents to the Survey of Consumer Finances, by Year 83

Table 7 Mann-Whitney U Test Results Comparing Median Net Worth of Unmarried Male Respondents and Unmarried Female Respondents, by Year 85

Table 8 Regression Results Comparing Mean Net Worth of Unmarried Male Respondents and Unmarried Female Respondents, by Year 85

Table 9 Gender Wealth Gap, based upon Median Net Worth for Respondents to the Survey of Consumer Finances, by Year 86

Table 10 Gender Wealth Gap, based upon Mean Net Worth for Respondents to the Survey of Consumer Finances, by Year 87

Table 11 Gender Wealth Gap, Adjusted for Inflation, by Year 91 Table 12 Regression Output for the Trend in the Gender Wealth Gap, using Multiple

Measures 93 Table 13 Total Number of Unmarried Respondents, by Generational Cohort, by Year. 96 Table 14 Number of Male and Female Unmarried Respondents, by Generational Cohort,

by Year 96 Table 15 Gender Wealth Gap, based upon Median Net Worth, Traditionalist Generation

97 Table 16 Gender Wealth Gap, based upon Mean Net Worth, Baby Boomer Generation 98 Table 17 Gender Wealth Gap, based upon Median Net Worth, Generation X 98 Table 18 Gender Wealth Gap, based upon Median Net Worth, Generation Y 99 Table 19 Gender Wealth Gap, based upon Mean Net Worth, Traditionalist Generation

100 Table 20 Gender Wealth Gap, based upon Mean Net Worth, Baby Boomer Generation

101 Table 21 Gender Wealth Gap, based upon Mean Net Worth, Generation X. 102 Table 22 Gender Wealth Gap, based upon Mean Net Worth, Generation Y 103 Table 23 Equations of the Trend in the Gender Wealth Gap from 1992 - 2007, by

Generation 114 Table 24 Gender Wealth Gap, expressed as a percentage of Net Worth of Male

Respondents (W/X), based upon Median Net Worth Data 115 Table 25 Gender Wealth Gap, expressed as a percentage of Net Worth of Male

Respondents (W/X), based upon Mean Net Worth Data 116

x

Table 26 Gender Wealth Gap, expressed as a percentage of Net Worth of Male Respondents (W/X), based upon Mean Net Worth Data, excluding 1998 respondent #2192 and 2004 respondent #2529 117

XI

List of Figures

Figure 1. Ratio of women's earnings to men's earnings in the U.S. Data source: Bureau of Labor Statistics, 2009, Labor force statistics from the Current Population Survey - Women in the labor force: A Databook (2009 edition), Table 16 18

Figure 2. Gender wealth gap for the U.S. during the period 1992-2007, measured by median net worth statistics 88

Figure 3. Gender wealth gap for the U.S. during the period 1992-2007, measured by mean net worth statistics 89

Figure 4. Trend for the gender wealth gap for the U.S. during the period 1992-2007, measured by median net worth statistics, by generational cohort 104

Figure 5. Trend for the gender wealth gap for the U.S. during the period 1992-2007, measured by mean net worth statistics, by generational cohort 105

Figure 6. Trend for the gender wealth gap for Traditionalists in the U.S. during the period 1992-2007, measured by median net worth statistics 106

Figure 7. Trend for the gender wealth gap for Traditionalists in the U.S. during the period 1992-2007, measured by mean net worth statistics 107

Figure 8. Trend for the gender wealth gap for Baby Boomers in the U.S. during the period 1992-2007, measured by median net worth statistics 108

Figure 9. Trend for the gender wealth gap for Baby Boomers in the U.S. during the period 1992-2007, measured by mean net worth statistics 109

Figure 10. Trend for the gender wealth gap for Generation X in the U.S. during the period 1992-2007, measured by median net worth statistics 110

Figure 11. Trend for the gender wealth gap for Generation X in the U.S. during the period 1992-2007, measured by mean net worth statistics 111

Figure 12. Trend for the gender wealth gap percentage by generational cohort in the U.S. during the period 1992-2007, measured by median net worth statistics 112

Figure 13. Trend for the gender wealth gap percentage by generational cohort in the U.S. during the period 1992-2007, measured by mean net worth statistics 113

xii

1

Chapter 1: Introduction

Fisher (2010) reported that women in the United States (U.S.) have lower levels

of wealth and earnings than men. In fact, according to the Bureau of Labor Statistics

(2008b), U.S. women earn approximately 80% as much money as men, and have a much

greater likelihood of living in poverty than their male counterparts (Spraggins, 2005; U.S.

Census Bureau, 2008b). Despite the narrowing of the gender earnings gap (Bureau of

Labor Statistics, 2008b) and the elimination of the gender education gap (Bobbitt-Zeher,

2007) that have taken place since the U.S. Census Bureau first started tracking the ratio

of women's earnings to men's earnings in 1955, women in America continue to

experience less financial stability than men. The difference in wealth accumulated by

men and women, known as the gender wealth gap, persists in the U.S. (Raub, 2008).

Gender wealth disparity negatively affects women, as well as society as a whole. A

better understanding of the gender wealth gap, and whether Generation X women, in

comparison to women of prior generations, are accumulating as much wealth as their

male cohorts, may lead to societal changes that promote increased gender wealth equity.

This quantitative trend analysis study contains an examination of wealth statistics

as compiled through the triennial Survey of Consumer Finances (SCF). Through this

study, the gender wealth gap has been quantified, and generational differences in the

gender wealth gap over the period 1992 -2007 examined.

Chapter 1 contains background on the gender wealth gap and Generation X, a

statement of the problem examined in the study, the purpose of the study, a theoretical

framework for the study, the nature of the study, and the significance of the study. The

2

specific research questions and hypotheses analyzed throughout the study are presented,

along with definitions of key variables to be used throughout the study.

Background

The role of women in the U.S. workplace has changed significantly since the mid-

1970s. Women have historically made less money than men do, a situation often referred

to as the gender earnings gap (U.S. Census Bureau, 2009a). The gender earnings gap has

been attributed to women being less educated than men are and more likely to leave their

jobs to be homemakers or raise children (Bobbitt-Zeher, 2007). However, societal

changes have reduced or eliminated many factors that contributed to the gender earnings

gap. The necessities for dual-income households (Mackey, 2005) and the increased

education of women (Bobbitt-Zeher, 2007) have contributed to the narrowing of the

gender earnings gap. The narrowing of the gender earnings gap from .62 in 1979 to .80

in 2008 is reflective of this paradigm shift (Bureau of Labor Statistics, 2008).

Despite the narrowing of the gender earnings gap, there is evidence that women

are still accumulating less wealth than men are, an effect known as the gender wealth gap

(Raub, 2008). According to the U.S. Census Bureau, "women in the United States

outnumber men, but they are hampered by higher poverty rates and lower income" (U.S.

Census Bureau, 2001, p. 1). The U.S. Census Bureau conducts a formal census of the

U.S. population and analyzes it every 10 years. The most recent published data are from

2000. The 2010 census data has been gathered, but not all summaries and reports

regarding this data have been published yet. The reports prepared by the U.S. Census

Bureau, based upon 2010 data, will be released throughout 2011, 2012, and 2013.

Results from the U.S. Census Bureau's 2000 data indicated that women are more likely

3

than men are to be impoverished; families maintained by single women had lower

household incomes than those maintained by men, and adult women were more likely

than men are to live below the poverty level (Spraggins, 2005). In 2008, 31.4% of people

living in a female-headed household with no adult male present were below the poverty

level, compared to 14.2% of people living in a male-headed household with no adult

female present (U. S. Census Bureau, 2008b).

Not only are U.S. women more likely than men to live in poverty, they are also

less likely to be among the wealthy. Governmental data confirm that fewer women than

men in the U.S. are among the top wealth holders. On a triennial basis, the Internal

Revenue Service compiles Statistics of Income (SOI) and reports on the wealth of

American taxpayers (Federal Reserve Board, 2009, para. 1). In order to compile the SOI

data, information is used from the reporting year and the two subsequent years, as tax

returns are often filed on extension in later periods (Internal Revenue Service [IRS],

2009b). The most recent SOI data are for the 2004 reporting period, compiled from

2004, 2005, and 2006 data; the 2007 data will be compiled using 2007, 2008, and 2009

data, and cannot be estimated until after the 2009 data is submitted in 2010 (IRS, 2009b).

According to the 2004 SOI results, the top wealth holders in the U.S., people with over

$1.5 million in gross assets, were 57% male, and 43% female (IRS, 2009b). The SOI

results also indicate that, "male top wealth holders had a higher average net worth than

their female counterparts" (IRS, 2009b, para. 1).

When Generation Xers entered the workforce approximately 25 years after the

Equal Pay Act of 1963 was enacted, it was expected that the gender earnings gap, and

consequently the gender wealth gap, would be eradicated (Bohlander & Snell, 2010).

4

Members of Generation X, or Generation Xers, include persons born between 1968 and

1979 (U. S. Census Bureau, 2004). Women who are part of Generation X have not been

affected by the factors contributing to the gender earnings gap, including the gender gap

in education and familial factors that were barriers to women working in previous

decades, due to increased societal acceptance of females in the workplace (Steinsultz,

2006) and those women seeking post-secondary education (Bobbitt-Zeher, 2007).

Although Generation X women face many of the same career challenges and choices

faced by previous generations, the decisions that Generation X women make regarding

work are different from those made by their predecessors (DiNatale & Boraas, 2002).

Educational changes that began in the 1980s have resulted in more women

enrolling in college and attaining college degrees than men (Bobbitt-Zeher, 2007). The

increase in women enrolling in college and attaining degrees has substantially reduced or

eliminated the gender education gap. Generation X women were raised with the

expectation that they will balance careers and family responsibilities, and as such, more

women entered the workforce from Generation X than any prior generation (DiNatale &

Boraas, 2002). A woman's ability to enter and remain in the workforce is influenced by

her familial choices. More women are choosing to have fewer children, marry later in

life, or not to get married, than in prior decades (Steinsultz, 2006). In addition, more

Generation X women continue to work after having children than women of prior

generations (Steinsultz, 2006). As a result, more women are entering and remaining in

the workforce than in prior decades (Steinsultz, 2006). The U.S. Census Bureau

estimates that the median age for a first marriage for Generation X women ranged from

23.9 to 25.1 years old, compared with 20.8 to 22.1 years old for Baby Boomers (U.S.

5

Census Bureau, 2006). Many organizations have adopted family-friendly policies, such

as flexible work hours, childcare subsidies, and paid leaves for family care, that have

eliminated some of the barriers to work that women experienced in the past (Alkadry &

Tower, 2006). Generation Xers emphasize the importance of having a balance between

work and personal life concerns (Carley, 2008).

Problem Statement

The problem that was addressed in this study was whether Generation X women,

in comparison to women of prior generations, were accumulating as much wealth as their

male cohorts (Fisher, 2010). In fact, Fisher (2010) reported that U.S. women have lower

levels of wealth and earnings than men, as is evidenced by women being more likely to

live in poverty (U.S. Census Bureau, 2008b) and less likely to be among the wealthy

(IRS, 2009b) than their male cohorts are. The gender wealth gap has not been well

quantified by prior research and recent findings "have been mixed regarding whether a

wealth gap between male and female-headed households exists" (Fisher, 2010, p. 15). A

partial reason for the gender wealth gap is the gender earnings gap, a problem that has

been widely studied (Alkadry & Tower, 2006; Barbezat & Hughes, 2005). The factors

that traditionally contributed to the gender earnings gap, such as the education gap and

familial barriers to women working, do not affect members of Generation X as much as

prior generations (Bobbitt-Zeher, 2007). By quantifying the gender wealth gap and

examining the trends in the gender wealth gap by generational cohort, it has been

determined whether the gender wealth gap is improving for Generation X women in

comparison to prior generations. The results of this study have provided evidence

6

regarding whether the problems related to financial inequality are being eliminated, or

whether the gender wealth gap persists in the U.S.

Purpose

The purpose of this quantitative trend analysis study was to determine whether

Generation X women, in comparison to women of prior generations, were accumulating

as much wealth as their male cohorts. Examining the changes in the gender wealth gap in

the U.S. over the period 1992 - 2007 has provided information as to whether the overall

gender wealth gap has changed since Generation Xers have entered the workforce, and

whether the gender wealth gap is different for Generation X than for prior generations. A

narrowing of the gender wealth gap for Generation X indicates that the problems related

to wealth inequality are being eradicated for Generation X. A widening of the gender

wealth gap for Generation X indicates that the problems related to financial inequality,

such as higher levels of poverty and lower levels of wealth for women than men, are

being exacerbated. This quantitative trend analysis study has added to the body of

knowledge on the gender wealth gap and brought awareness to challenges in obtaining

gender financial equity.

The variables that have been examined as part of this quantitative trend analysis

study were net worth and the gender wealth gap. The gender wealth gap was assessed as

the difference between the net worth of men and the net worth of women. The data

analyzed was compiled through the Federal Reserve Board's triennial SCF for the survey

years 1992, 1995, 1998, 2001, 2004, and 2007. The SCF provides information regarding

the demographics, income, assets, and liabilities of approximately 4,500 households per

survey period (Bucks, et al., 2009). Interviewers collect the SCF data through face-to-

7

face and telephone interviews (Bucks, Kennickell, Mach & Moore, 2009). The total

number of SCF respondents selected for analysis in this study was 8,676, with a sample

size of 1,339 to 1,533 study participants from each of the six survey periods' data sets.

The sample size used for each study period far exceeded the minimum sample size of

176, required by a power analysis. An a priori power analysis was conducted using

G*Power software, to determine the necessary sample size for analyzing the difference

between the independent means of the two groups (net worth of male respondents and net

worth of female respondents), where d=.5, a=.05, and (l-/3)=.95. The minimum sample

size is 88 respondents for each of the two groups, for 176 total respondents, resulting in

an actual power of 0.95. All study participants are taxpayers within the U.S.

Theoretical Framework

Several theories were considered in examining the gender wealth gap. The

human capital theory indicates that economists consider expenditures on education,

training, and health as investments in human capital, since people cannot be separated

from their knowledge, skills, or health (Becker, 2008). Human capital theory suggests,

"Education and work experience are factors that decrease the likelihood of poverty"

(Steinsultz, 2006, p. 7). The individual model implies that investments in human capital

increase productivity, making individuals more attractive as employees and consequently

earning them higher pay (DuPuis, 2006). The gender model of income determination

argues, "Discrimination, harassment, and the unequal treatment of women workers force

women into lower paying jobs" (DuPuis, 2006, p. iv). "Gendered socialization that

discourages women from performing male typed jobs" may affect women's choices of

occupation, and ultimately their wealth accumulation (DuPuis, 2006, p. 7). The human

8

capital theory and gender model of income determination are intrinsically related to the

analysis of earnings and the gender earnings gap.

The analysis of the gender wealth gap by generational cohort was based upon

generational theory. Generational theory indicates that predictions of cohort belief and

behavior are based upon generational categorization (Asaro-Gonzalez, 2006). The

generational characteristics of Generation X women include a propensity to delay

marriage and childrearing, remain in the workforce after having children (Steinsultz,

2006), and pursue higher education (Bobbitt-Zeher, 2007). Generational characteristics

would indicate that more Generation X women would enter and remain in the workforce

than women of prior generations (Steinsultz, 2006). The generational characteristics of

Generation X would predict a narrowing of the gender earnings gap, as is evidenced by

the percentage of women's earnings to men's earnings increasing from .75 for Ql 1992 to

.80 for Q4 2007 (Bureau of Labor Statistics, 2010), the beginning and ending of the study

period.

Research Questions

The following questions have guided this quantitative trend analysis study to

determine whether the gender wealth gap in the U.S. has changed over the period 1992 -

2007, as Generation Xers entered the workforce. The gender wealth gap has been

measured based upon net worth statistics of unmarried men and women in the U.S., as

reported in the SCF over the period 1992 - 2007.

Q l : To what extent has the gender wealth gap changed during the period 1992 -

2007 in the U.S.?

9

Q2: How does the gender wealth gap in the U.S. differ by generational cohort

during the period 1992 - 2007?

Hypotheses

The following null and alternative hypotheses were associated with the two

research questions.

Hlo- There is no significant change observed in the gender wealth gap from 1992

until 2007.

Hl a . There is a significant change observed in the gender wealth gap from 1992

until 2007.

H2o. There are no significant differences between the trends in the gender wealth

gap observed for Generation X and the gender wealth gap observed for prior

generations for the period 1992 - 2007.

H2a. There are significant differences between the trends in the gender wealth

gap observed for Generation X and the gender wealth gap observed for prior

generations for the period 1992 - 2007.

Nature of the Study

The operational measure for analyzing the trends in the wealth accumulation of

women and men in the U.S. over the period 1992 - 2007 was net worth. Total assets,

total liabilities, and net worth were calculated based upon data reported in the triennial

SCF for the period 1992 - 2007. Net worth is the value of an individual's total assets

minus total liabilities. The Federal Reserve Board sponsors the SCF every three years.

Data regarding the demographics, income, assets, and liabilities of approximately 4,500

households is collected via face-to-face and telephone interviews (Bucks, et al., 2009).

10

The SCF has been selected as the database for the study because it provides respondent

level data, is comprehensive, and has reliable instrumentation that has been tested nine

times since 1983. The most recent six survey years, 1992, 1995, 1998, 2001, 2004, and

2007, were selected for inclusion in the study, to cover a 15-year period in the trend

analysis.

The dependent variable analyzed through this quantitative trend study was the

gender wealth gap, as assessed using data reported triennially in the SCF for the period

1992 - 2007. The gender wealth gap is the difference between the net worth of men and

the net worth of women. The gender wealth gap has been measured by survey year over

the study period, 1992 - 2007, in total and by generational cohort. The intent of

analyzing the gender wealth gap was to determine whether Generation X women, in

comparison to women of prior generations, were accumulating as much wealth as their

male cohorts in the U.S. for the period 1992 - 2007.

The population for the study was adult taxpayers in the U.S. The study sample

was chosen from the respondents to the SCF for 1992, 1995, 1998, 2001, 2004, and 2007,

that had the characteristics of being unmarried adults with annual earnings. Since the

delineation between the wealth accumulation of men and women would not be clear

within a married unit, only unmarried adults were included as part of the study sample. A

total of 8,676 respondents were included in the study sample, as this was the number of

unmarried respondents to the SCF over the study period that did not report cohabitating

and combining financial resources. Although the number of respondents, 8,676 in total,

appears large, this was the combined total from each of the six study periods' data sets.

Within each data set, a sample size of 1,339 to 1,533 was identified. A power analysis,

11

conducted using G*Power software, indicates that a minimum sample size of 176 is

necessary to achieve a=.05, and the sample size for the study far exceeded the minimum

required by the power analysis. The boundary for the study was the U.S., and all

respondents to the SCF whose data was used in the study were U.S. residents.

Significance of the Study

This quantitative trend analysis study of the gender wealth gap is significant in

that it has furthered the body of knowledge that potentially may lead to societal changes

that promote increased financial equity among the genders. There has been conflicting

evidence regarding the existence of the gender wealth gap in the literature (Fisher, 2010),

and this study has provided clarification as to the magnitude of and the trends in the

gender wealth gap over the period 1992 - 2007. In her 2010 study, Fisher identified the

need for future studies that categorize women and men into age cohorts in order to further

understanding on gender differences in savings behavior. This quantitative trend analysis

study has expanded upon Fisher's work by classifying women and men by generational

cohort and then examining their wealth accumulation.

The purpose of this quantitative trend analysis study was to determine whether

Generation X women, in comparison to women of prior generations, were accumulating

as much wealth as their male cohorts. Identifying the magnitude of the gender wealth

gap by generational cohort allows conclusions to be drawn about whether the increased

earnings and education experienced by the women of Generation X has led to increased

financial stability. A narrowing of the gender wealth gap for Generation X indicates that

the problems related to wealth inequality are less for Generation X than for prior

generations. A widening of the gender wealth gap for Generation X indicates that the

12

problems related to financial inequality, such as higher levels of poverty and lower levels

of wealth for women than men, still exist and may have increased. This quantitative

trend analysis study has furthered the body of knowledge on the gender wealth gap and

brought awareness to challenges that hinder financial equity among the genders. The

knowledge that has been gained from this study about the gender wealth gap trends

suggests that the conditions that lead to a gender wealth gap have changed with

generational changes in workforce composition.

Definitions

The following are terminologies that were used in this study as key operational

terms, words used in a unique way, or words that are not commonly known or have

meanings specific to this study and the data being analyzed. Each term is presented,

followed by a definition or explanation of how the term will be used throughout the

study.

Equity. Equity is defined as the "residual interest in the assets of an entity that

remains after deducting its liabilities" (Kieso, Weygandt & Warfield, 2008, p. 173).

Financial assets. Financial assets are defined as the aggregate asset category that

"includes all stocks, bonds, mutual funds, cash, and cash management accounts" (IRS,

2009c, para. 17).

Gender wage gap. The gender wage gap is the differential in earnings between

men and women (Burkhauser & Larrimore, 2009). The gender wage gap is also known

as the gender earnings gap or the gender pay gap.

13

Generation X. The term Generation X refers to individuals born during the 1960s

and the 1970s; those individuals are referred to as Generation Xers or Gen Xers (U.S.

Census Bureau, 2004).

Income. Income includes money received from the following sources: earnings,

unemployment compensation, workers' compensation, social security, supplemental

security income, public assistance, veterans' payments, survivor benefits, disability

benefits, pensions or retirement income, interest, dividends, rents, royalties, estates, and

trusts, educational assistance, alimony, child support, financial assistance from outside

the household, and other income sources (U.S. Census Bureau, 2008a, para. 25).

Net worth. According to the Internal Revenue Service, net worth refers to an

individual's financial position and is calculated as total assets minus total debts and

mortgages (IRS, 2009c, para. 23). In this study, net worth is used as a measure of wealth

accumulation.

Poverty threshold. The U.S. Census Bureau establishes, on an annual basis, a "set

of money income thresholds that vary by family size and composition to determine who

is in poverty", as authorized by the Office of Management and Budget's (OMB)

Statistical Policy Directive 14 (U.S. Census Bureau, 2009b, para. 1).

Summary

Women having higher poverty rates than men indicate that the gender wealth gap

persists in the U.S. (Spraggins, 2005; U.S. Census Bureau, 2008b). Gender wealth

inequality inhibits the growth of individuals and the evolution of societies, and

disadvantages both men and women. Generation X women are less affected by the

gender earnings gap than women of prior generations are. The problem was that it has

14

been unknown whether Generation X women, in comparison to women of prior

generations, were accumulating as much wealth as their male cohorts.

The purpose of this quantitative trend analysis study was to determine whether

Generation X women, in comparison to women of prior generations, were accumulating

as much wealth as their male cohorts. Examining the changes in the gender wealth gap in

the U.S. over the period 1992 - 2007 has provided information as to whether the overall

gender wealth gap has changed as Generation Xers entered the workforce, and whether

the gender wealth gap was different for Generation X than for prior generations. A

narrowing of the gender wealth gap for Generation X indicates that the problems related

to wealth inequality that have plagued women of prior generations are being eradicated

for Generation X. A widening of the gender wealth gap for Generation X indicates that

the problems related to financial inequality, such as higher levels of poverty and lower

levels of wealth for women than men, still exist. This quantitative trend analysis study

has furthered the body of knowledge on the gender wealth gap and has brought awareness

to challenges that still exist to obtain financial equity among the genders.

The quantitative trend analysis study included an analysis of data compiled

through the Federal Reserve Board's triennial SCF. By statistically analyzing the gender

wealth gap as reported by the SCF respondents over the period 1992 - 2007, the research

questions have been addressed and the hypotheses tested. A total of 8,676 SCF

respondents, who reside in the U.S. and were unmarried, have been included in this

analysis. Measures of central tendency were calculated for unmarried male respondents

and unmarried female respondents, and the gender wealth gap was quantified, for each of

the survey years within the study period of 1992 - 2007. The trends in the gender wealth

15

gap were analyzed to assess whether the gender wealth gap has changed since Generation

X entered the workforce. The gender wealth gap, by generational cohort, was quantified.

The gender wealth gaps were compared by generation in order to determine whether

Generation X has been less affected by the gender wealth gap than prior generations. The

results of this study have increased the body of knowledge regarding whether the gender

wealth gap will continue to persist in the U.S. Furthering the body of knowledge on the

gender wealth gap in the U.S. may lead to a better understanding, and ultimately the

minimization, of the circumstances leading to women being impoverished.

16

Chapter 2: Literature Review

The purpose of this quantitative trend analysis study was to determine whether

Generation X women, in comparison to women of prior generations, were accumulating

as much wealth as their male cohorts. Examining the changes in the gender wealth gap in

the U.S. over the period 1992 - 2007 has provided information as to whether the overall

gender wealth gap has changed as Generation Xers entered the workforce, and whether

the gender wealth gap was different for Generation X than for prior generations. A

narrowing of the gender wealth gap for Generation X indicates that the problems related

to wealth inequality that have plagued women of prior generations are being eradicated

for Generation X. A widening of the gender wealth gap for Generation X indicates that

the problems related to financial inequality, such as higher levels of poverty and lower

levels of wealth for women than men, are being exacerbated. This quantitative trend

analysis study has furthered the body of knowledge on the gender wealth gap and brought

awareness to challenges that still exist to obtain financial equity among the genders.

In order to gain an understanding of the existing body of knowledge, a detailed

study of books, articles, and dissertations was undertaken. The information provided in

the literature review was accumulated through accessing multiple online databases, as

well as public and university libraries. The literature review is organized into

information on the gender wealth gap, women and wealth accumulation, the Survey of

Consumer Finances, and Generation X.

The section on the gender wealth gap includes background on the gender earnings

gap. There is significantly more information available regarding the gender earnings gap

than the gender wealth gap. Since the gender earnings gap contributes to the gender

17

wealth gap, it is examined in depth as a basis for this study. This study is premised on

the hypothesis that the gender wealth gap should be closing as the gender earnings gap

narrows.

The section on women and wealth accumulation includes information regarding

studies done on women and wealth. The effects of marital status, children, education,

earnings, investing habits, and age on wealth and/or poverty were examined. There are

many studies on the wealth of older women (Joyce, 2005; Steinsultz, 2006), but fewer

studies encompass women of Generation X. This study was focused upon the gender

wealth gap for each generation, with specific focus on Generations X's gender wealth

gap-

The SCF has been the data set used for many studies (Cho, 2010; Evans, 2010).

The section on the Survey of Consumer Finances summarizes some of the findings from

studies that rely upon the SCF data sets. This study has used SCF data to develop a

quantitative trend analysis on the gender wealth gap in the U.S.

This quantitative trend analysis study was focused upon on the changes in the

gender wealth gap since Generation X entered the workforce. As such, it is important to

understand the characteristics of Generation X, in comparison to other generations

currently in the workforce, in order to assess how Generation X entering the workforce

may have influenced the gender wealth gap. There is an examination of the literature

regarding the differences between the Traditionalists, the Baby Boomers, Generation X,

and Generation Y presented in the section on Generation X. There is a specific focus on

comparing Generation X to the other generations.

18

The Gender Wealth Gap

The U.S. Census Bureau first began tracking the ratio of women's earnings to

men's in the 1950s (Weinberg, 2007). The gender earnings gap is the difference between

the salaries and wages of men and women. The gender earnings gap has been widely

studied since the U.S. Census Bureau first quantified it. The first time that the U. S.

Census Bureau tracked the ratio of women's earnings to men's earnings in the U.S. was in

1955, when the ratio was 0.64; this ratio has improved over 50 years, to 0.77, in 2005

(Weinberg, 2007). Figure 1 shows the ratios of women's earnings to men's earnings in

the U.S., as reported in the Current Population Survey of the Bureau of Labor Statistics,

from 1979 through 2008 (Bureau of Labor Statistics, 2009).

90.0%

80.0%

70.0%

60.0%

50 0%

40 0%

30 0%

20 0%

10.0%

0 0%

- • — • — • -

CT>o-*-c\icO'3-m(or^coa>o-<-CMcO''3-iocor^coa>o-<-c\i<o^-mcDr^co i ^ - c o c o c o c o c o c o c o c o c o c o a > a > a > a > C T > a > a > o > o > a } 0 0 o o o o o o o a i o c D O T o ^ c ^ o a i o o C T J O i o o o i o c D O O o ^ o o o o o o o o o o T - V - T - T - T - T - T - , - T - T - - l - * - T - T - T - T - T - T - . 1 - , - , - ( M C s ] C \ l C N C \ | C S J C M C \ I C N

Figure 1. Ratio of women's earnings to men's earnings in the U.S. Data source: Bureau

of Labor Statistics, 2009, Labor force statistics from the Current Population Survey -

Women in the labor force: A Databook (2009 edition), Table 16.

19

Gender pay inequality has traditionally been attributed to the glass ceiling, or the

perceived barriers to women moving into upper level management positions due to

gender (Alkadry & Tower, 2006). According to Alkadry and Tower (2006), more men

than women were in the higher-paying upper level positions within organizations, and

therefore made more money than their lower-level counterparts make. The glass ceiling

within organizations is usually based on unofficial policy, and is not as apparent as other

barriers to advancement such as limitations on education or experience (Coates, 2010).

Douse (2009) identified that women encounter structural, legal, and educational barriers

to moving into high-level management positions, and that the glass ceiling may be the

result of corporate tradition and prejudice, whereas Jones (2010) related society's current

attitude toward women in the workplace to America's historical patriarchal heritage.

The glass ceiling may be due, in part, to gender stereotypes (Brown, 2009).

Gender stereotypes are the main cause for gender discrimination in the workplace, and

may influence hiring and promotion decisions within an organization (Heilman, 2001).

Hiring managers may make decisions based upon occupational sex typing that may be

influenced by perceptions that managerial roles are considered masculine occupations,

since men hold a majority of managerial positions (Brown, 2009). Gender stereotypes, as

well as the hiring manager's attitude toward women, influence hiring decisions (Jones,

2010). Jones (2010) concluded that hiring managers with positive attitudes toward

women would hire a female applicant and hiring managers with negative attitudes toward

women would hire a male applicant, when those two applicants were equally qualified.

In addition to the external factors that may influence a woman's ability achieve

upward mobility on the corporate ladder, internal factors, such as a woman's self-

20

perception, may also be to blame for the glass ceiling. According to Brown (2009), a

partial explanation for the glass ceiling is self-perception, whereby "women may perceive

their own characteristics as different from those they attribute to a group of managers

traditionally dominated by men" (p. 2). Further, "some women may be raised with the

expectation that they will not be corporate leaders" (Brown, 2009, p. 4), and these

perceptions may psychologically influence women's choices, resulting in a self-fulfilling

prophecy.

Statistics regarding the number of women in upper management positions in

corporate America today support the contention that there is a continuing presence of the

glass ceiling in corporate America (Brown, 2009). Female employees made up

approximately 46.7% of the U.S. labor force for 2009, and held 51.4% of all managerial,

professional, and related positions in the U.S. for the same period (Catalyst, 2009).

Although women represented nearly half of the entire U.S. workforce, in 2009 women

held only 13.5% of the 5,161 executive officer positions at Fortune 500 companies

(Catalyst, 2009). There were 15 female Chief Executive Officers (CEOs) for the Fortune

500 for 2009, representing 3% of all CEOs for the group (Catalyst, 2010). However, the

number of women CEOs of Fortune 500 companies was five times more than just a

decade before, with only 0.6% of Fortune 500 companies having female CEOs in 1999

(Catalyst, 2010).

Coates (2010) examined the relationship between leadership styles and gender

through surveying the leaders at Fortune 500 companies that had women in positions of

leadership at the vice president level or higher. Coates (2010) found that there were no

statistically significant differences in gender attitudes about leadership style, critical

21

thinking skills, or active engagement skills, but that there was a difference in attitude

toward the importance of networking in attaining a senior level position, with male

respondents considering networking to be a more critical component of career

advancement than female respondents are.

Women are underrepresented on corporate boards, just as they are in corporate

management. According to Catalyst (2009), in 2009 women comprised 15.2% of all

directors that sat on the Boards of Fortune 500 companies. Almost 90% of all Fortune

500 companies had at least one female board member in 2009, but fewer than 20% of

these companies had three or more women directors (Catalyst, 2009).

Some studies indicate that women in leadership positions may help to eliminate

the glass ceiling. Douse (2009) suggested that women in management positions should

mentor other women to help to eliminate the effects of the glass ceiling in the corporate

world. Bilimoria (2006) found a positive correlation between the number of women on

the board of directors and the number of women in upper management positions of those

companies, so another potential way to minimize the glass ceiling is to include more

women on corporate boards. Since more men than women in senior management

positions focused upon networking, women might be able to better utilize networking

opportunities to foster career advancement (Coates, 2010).

There may be increasing opportunities for women in organizational leadership

positions. According to Coates (2010), today's organizations need a different leadership

style than has been necessary in the past, as today's leaders are more nurturing and

caring, traits that are generally associated with women rather than men. Coates (2010)

contends that if women were represented in organizational management in proportion to

22

their percentage of the general population, companies would be better prepared to market

to their customer base.

Recent studies have included the correlation of women's earnings to factors other

than the glass ceiling, such as age (Steinsultz, 2006), marital status (Joyce, 2005),

parenthood (Yamokoski, 2007), and education (Bobbitt-Zeher, 2007). Steinsultz (2006)

examined never married women 50 years of age and older in Canada, Germany, Sweden,

and the U.S. by analyzing demographic and wealth data compiled through the

Luxembourg Income Study. Steinsultz found that both income and accumulated wealth

decreased as age increased for never married and married women. The negative

correlation between age and income was strongest in the U.S., in comparison to Canada,

Germany, and Sweden (Steinsultz, 2006). Women over 50 years old tended to shift their

income sources from salaries and wages to government funded sources as they age

(Joyce, 2005), which accounts for at least part of the income decline observed by

Steinsultz in her study. A limitation of Steinsultz's study is that it does not examine

women under 50 to determine at which point women start this decline in earnings.

"Marital status is the strongest predictor of income security for older women",

according to Joyce (2005, p. 19). Recent studies, such as that undertaken by Joyce

(2005), have correlated marital status to women's earnings. Joyce conducted a secondary

analysis of the 2002-Rand Health and Retirement Study Data file in order to draw

conclusions regarding the effects of marital status on persons over 50 years of age in the

U.S., and found that married women had greater income and net worth than women that

were never married, were divorced, or were widowed. In contrast, Steinsultz (2006)

found that in the U.S., women who had never been married had higher income than

23

women who had been married. Steinsultz's study did not include an examination of

single women in categories other than having never been married, such as divorced or

widowed women, which may account for the contradiction with Joyce's study. Like

Steinsultz's study, Joyce's study is limited in that it only examines women over 50 years

of age. Joyce found that aging has a negative impact on income, regardless of marital

status, for women 50 years old and older. Most Americans get married at some point in

their lifetimes; as of the 2000 U.S. Census, 74% of adults up to the age of 35 had been

married before, and 95% of adults up to age 65 had married at least once (U.S. Census

Bureau, 2001). Just as there is a correlation between marital status and earnings, the

disruption of a marriage has a significant impact on earnings as well. Women who

experience a change in marital status that takes them from being married to being

divorced or widowed will "be at greater economic disadvantage than married women"

(Joyce, 2005, p. 1). Becoming divorced or widowed resulted in "negative and prolonged

consequences for women's economic well-being" (Joyce, 2005, p. 5). Economic

recovery is not observed for most women for at least five years after a divorce, unless

they remarry (Joyce, 2005). However, women who are widowed or divorced, and thus

fall into the study category of unmarried women, may have additional income over a

woman who has never been married. Divorced women may receive spousal support and

widowed women may receive survivor benefits that may give these women an equivalent

to dual incomes found in many married households. The economic impact of a spouse's

death on the widow's income is highly dependent upon whether the deceased had life

insurance in place and the age at which the spouse died, which will determine whether

24

the remaining spouse is eligible for Social Security survivor benefits, Social Security

retired-worker benefits, or other pension plans (Joyce, 2005).

Recent studies have explored the relationship between earnings and parenthood

(Yamokoski, 2007). Yamokoski (2007) conducted a secondary analysis of data from the

National Longitudinal Survey of Youth from 1979 through 2000 in order to assess the

effects of gender and parenthood on wealth accumulation. Yamokoski found that the

group that faced the most severe economic challenges was single mothers. Adults that

had become parents during their teenage years experienced significantly more economic

hardship than individuals that became parents as adults (Yamokoski, 2007). Single

mothers in particular have been the subjects of many studies on poverty (Steinsultz,

2006). Women who experience a marital disruption and have had children are more at

risk for becoming impoverished than women without children in similar circumstances

(Joyce, 2005).

Education is also directly linked to earning capacity. Bobbitt-Zeher's 2007

longitudinal study of data collected in 1972, 1982, and 1992 by the National Center for

Educational Statistics (NCES) examined the relationship between education and earnings.

Bobbitt-Zeher (2007) observed a direct correlation between income and education.

According to Bobbitt-Zeher, the "concurrent decline in the gender income gap and the

rise of women's participation in higher education is not coincidental" (p. 161). Further,

Bobbitt-Zeher observed gender pay differentials at all educational levels, supporting the

contention that the gender earnings gap is due to factors other than education. However,

the gender pay differential observed for men and women with equivalent levels of

education may be due in part to choice of major. The male participants in Bobbitt-

25

Zeher's 2007 study often chose to be educated in fields that historically resulted in higher

paying jobs than fields chosen by the female participants. Bobbitt-Zeher contended that

occupation, industry, and sector account for one-third of the gender earnings gap among

college-educated workers. Since women now outnumber men in their pursuit of college

educations, men separate themselves by continuing to choose professions that are

traditionally male dominated and high paying, perpetuating the overall gender earnings

gap (Bobbitt-Zeher, 2007).

Bobbitt-Zeher's (2007) findings about the relationship between education and

earnings are consistent with those of Steinsultz (2006) and Joyce (2005). Steinsultz

found that education had a direct correlation to levels of income for the respondents, in

that increased education is a strong predictor of increased income for older women in the

U.S. Steinsultz further found that the correlation between education and income was

stronger for never married women than for women who were married. In comparing the

relationship between education and earnings, there was a stronger correlation between

these factors for respondents from the U.S. than for the respondents from the other

countries studied by Steinsultz. According to Joyce, educational attainment relates to

work histories, and women who have higher levels of education have more continuous

work histories and work for a longer duration than women who are less educated.

Women should continue to narrow the gender earnings gap by "increasing their

participation in higher education and broadening their fields of study", according to

Bobbitt-Zeher (p. 162).

The choice of profession affects earnings capacity, and the overall gender

earnings gap relates to men's tendencies to go into higher paying professions than women

26

do (Bobbitt-Zeher, 2007). However, within many professions, there exists a gap in

earnings between the genders. The gender earnings gap, quantified by profession, is

highly documented. Weinberg (2007) compared median income of men and women

within different professions as reported in the 2000 U.S. Census, and the differences

calculated are significant. Weinberg's analysis of earnings distributions by occupation

identified that women's earnings at every percentile level of earnings were less than men's

earnings at the same percentile level. Weinberg reported that the median salary of a male

physician or surgeon was $140,000 in 1999, while the median salary for a woman in the

same field, that year was only $88,000. The median salary for a male lawyer was

$90,000, while female attorneys made a median annual income of $66,000 (Weinberg,

2007). Male judges, magistrates, or other judicial workers averaged $88,000 annually,

compared to females in similar positions earning only $50,000 (Weinberg, 2007). Male

economists made $73,000 compared to female economists at 60,000 (Weinberg, 2007).

Astronomers and physicists had a similar gender pay gap with males earning $71,000

compared to $51,000 for females (Weinberg, 2007).

Weinberg's (2007) comparisons of median earnings by gender, as reported in the

2000 U.S. Census, resulted in consistent findings for the lowest paying jobs as it did for

the highest: men make more than women do. The lowest paying job for both men and

women was as a dishwasher, with the median earnings at $14,000 for men and $12,000

for women (Weinberg, 2007). Men working as maids and housekeeping cleaners earned

an average of $4,000 more than women in similar positions, at $19,000 and $15,000,

respectively (Weinberg, 2007). The statistics on waiters and waitresses were identical to

those of maids and housekeeping cleaners, with men earning $19,000 and women earning

27

$15,000 (Weinberg, 2007). Male teaching assistants earned one-third more than their

female counterparts, at $20,000 compared to $15,000 (Weinberg, 2007).

The gender pay gap in the education field is well documented; Barbezat and

Hughes (2005) estimated the gender earnings gap for faculty at 20.7% in 1999, and

Umbach (2008) estimated this pay gap at 14% for 2003-2004 faculty earnings. Umbach

did more than to simply quantify the difference in pay by gender. Umbach further

factored out pay discrepancy based on education, experience, academic rank, and other

human capital factors, and still found a 6% gap in faculty pay that was unexplained,

except by gender.

Among the observations made by Barbezat and Hughes (2005) were that the

highest paying fields for both male and female academics were business, computer

science, economics, engineering, law, and medicine. Interestingly, the greatest

discrepancies in pay by gender were for economics professors and law professors, with

male economics professors earning more than females, and with female law professors

earning more than males (Barbezat & Hughes, 2005). The gender pay gap observed

among academics was greater at research universities than at liberal arts colleges,

according to Barbezat and Hughes' study.

Further studies have compared the behavior of the genders in the workplace and

related behavior to income. Keller (2008) studied absenteeism and related it to

demographic characteristics. Women have substantially higher absentee rates than men

do, according to Keller's 2008 study. Keller noted that the women studied had lower pay

rates than the male respondents, indicating that the absenteeism may be related not only

to gender but also to inadequate pay, lower levels of responsibility at work, or the

28

perception that they are being unfairly compensated. Spivey (2006) found that the

consequences of career interruptions were different for the genders, with men's

compensation being more drastically reduced upon return to the workforce than

women's, but women's time to recovery of earnings being substantially longer than

men's. One reason for the observed disparity in treatment of the genders upon

interruptions in their career may be that employers expect career interruptions for women

more so than for men (Spivey, 2006).

The trends in women's earnings should directly influence their accumulation of

wealth. The gender wealth gap is often attributed to men and women investing

differently, due to differences in levels of income and risk aversion (Foster, 2008). The

gender wealth gap, or the difference between the wealth of men and women, is more

difficult to analyze than the gender earnings gap, yet may be more significant that the

much-studied earnings gap. Wealth, as a measure, is more difficult to assess than

earnings, as it is a measure that requires calculation, yet is a more stable indicator of

financial health than income (Yamokoski, 2007). Wealth is the value of accumulated

assets less the outstanding debts owed, and is, along with total household income, a

measure of economic security (Joyce, 2005). In order to assess wealth, data must be

compiled from multiple sources, or be self-reported via surveys or other studies, whereas

earnings data are regularly reported to the U.S. government through census information

and income tax returns.

The gender wealth gap has become more apparent as the number of single persons

in the U.S. has grown over the last several decades. In 1970, 81% of all households in

the U.S. were families, whereas in 2000, that had declined sharply to only 69%> of

29

households (U.S. Census Bureau, 2001). Wealth of a married couple can be assessed, but

is not clearly attributed to either gender. Gender is an individual characteristic but wealth

is usually measured for a household, making it difficult to separate the assets of married

couples by gender (Yamokoski, 2007). In order to measure the gender wealth gap, only

the wealth of unmarried individuals should be compared. Due to declining marriage

rates, increasing divorce rates, and longer life expectancies, the number of unmarried

individuals in the U.S. is significantly higher than it was thirty years ago. This increase

in the number of single adults in the U.S. makes the gender wealth gap more obvious and

more quantifiable than it has been in the past. According to Steinsultz (2006), cultural

changes over the past three decades have affected women's attitudes about marriage.

Steinsultz contended that society should view the changing roles of women as positive

cultural shifts. Steinsultz identified that the number of women who are remaining or

becoming unmarried is growing, and that it is imperative to identify factors that affect the

wealth of this group of individuals.

Women and Wealth Accumulation

Wealth is a measure that is different from income. Income includes money

received from the following sources: earnings, unemployment compensation, workers'

compensation, social security, supplemental security income, public assistance, veterans'

payments, survivor benefits, disability benefits, pensions or retirement income, interest,

dividends, rents, royalties, estates, and trusts, educational assistance, alimony, child

support, financial assistance from outside the household, and other income sources (U.S.

Census Bureau, 2008a). Wealth is not a measure of current income, but represents the

total net worth accumulated to date. According to the Internal Revenue Service, net

30

worth refers to an individual's financial position and is calculated as total assets minus

total debts and mortgages (IRS, 2009c, para. 23).

Several factors that especially affect the wealth accumulation of women include

age, earnings, education, marital status, and number of children. Studies have

consistently shown that age, earnings, and education positively affect wealth

accumulation. Steinsultz (2006) and Yang (2006) both found that as people age, levels of

wealth increase. Age for respondents from the U.S. that participated in Steinsultz's study

significantly predicted wealth. Yang found that household wealth increased with age,

and specifically that there was "little evidence of decumulation of wealth at the end of the

life cycle" (p. 13). According to Yang, housing assets represent much of the wealth

accumulated at earlier ages, and non-housing assets increase as age increases. Further,

Yang identified that wealth in the U.S. is highly concentrated, with the mean net worth

exceeding the third quartile wealth level at all ages; this concentration increases for non-

housing assets in comparison to net worth. Yang's findings on wealth concentration may

support Steinsultz's contention that many older women live in poverty, in that this

population may not be showing the consistent asset growth that is indicated by the

averages. Since women have a longer life expectancy than men do, and single women

are more likely to live in poverty than married women or men, there is a greater

propensity for older women who have never been married or who are divorced or

widowed to live in poverty (Joyce, 2005). Steinsultz found that older women, especially

never married women, divorcees, and widows, who live alone have the highest chance of

living in poverty in all of the nations covered in her study, including Canada, Germany,

Sweden, and the U.S.

31

Foster (2008) found that lifetime earnings levels greatly affected retirement

savings wealth. Venti and Wise (1998) concluded that lifetime earnings affected total

wealth accumulated in dollars, but that wealth to earnings ratios are relatively constant

across eight often deciles of the population studied. Lower levels of lifetime wages and

participation in the labor force result in lower levels of retirement income, a problem that

is common amongst older women (Joyce, 2005). Women's patterns of work and family

responsibilities affect retirement wealth and affect retirement insecurity (Isaacs, 2010).

Isaacs (2010) hypothesized each generation of women would have had unique

expectations and life experiences that would ultimately affect retirement wealth. Prior

participation in the labor force and family responsibilities predict women's economic

outcomes in retirement (Isaacs, 2010).

Retired persons in the U.S. typically rely on Social Security, pensions, and other

investments to maintain their income and prevent poverty (Isaacs, 2010). The U.S.

Social Security system provides income to a vast majority of retired men and women

alike, but women are less likely than men are to have employer-sponsored pensions

(Isaacs, 2010). Isaacs (2010) challenged that the U.S. retirement system may not be

sufficient in providing economic security for elderly women, since there is a higher

percentage of elderly living in poverty in the U.S. than in other affluent countries, and the

percentage of elderly women in poverty is nearly double the percentage of elderly men in

America.

Education improves financial decision-making, which has a direct effect on

wealth attainment (Yamokoski, 2007). Yamokoski (2007) concluded that "at all income

levels, those who have completed more education save more, assume less debt, and make

32

decisions regarding investments that yield larger overall portfolios" (p. 14). Bobbitt-

Zeher examined the impact of education on earnings in her 2007 study. Bobbitt-Zeher

concluded that education level, and the choice of occupation, industry, and sector,

dramatically affect lifetime earnings. Other studies reinforce Bobbitt-Zeher's conclusion

that education has a positive relationship with income through demonstrating that

education ultimately affects levels of wealth attained. Joyce (2005) and Steinsultz (2006)

both studied women over 50 years old in America, and found that education positively

affected wealth accumulation for this demographic. Joyce found that "higher education

will result in greater income security" for women (p. 131). Completed years of education

was a strong positive predictor of both income and wealth for the women studied (Joyce,

2005). According to Joyce's findings, "education is a strong predictor of the majority of

the sources of income and components of wealth for the women, regardless of marital

status, which results in an increase in both the income security and access to accumulated

assets" (p. 125). Women with higher educational attainment tend to have more

continuous work histories and work for a longer duration of time, than those that are less

educated, leading to a lower risk of living in poverty later in life (Joyce, 2005). Older

women who experienced divorce or widowhood benefit economically after the marital

disruption in direct relation to their educational attainment (Joyce, 2005). Steinsultz's

2006 study found that education level significantly predicted wealth in the U.S.

Familial factors influence wealth accumulation, and there exists some conflict

within current research as to how family situations affect wealth. Schmidt and Sevak

(2006) found that "large differences in economic well-being by gender and marital status

exist" (p. 139). Joyce (2005), Steinsultz (2006), and Yamokoski (2007) found that

33

married couples accumulate significantly more wealth than single individuals do; it

should be noted that all three of these studies focused on individuals over 50 years of age.

Joyce found that "marriage enhances the lifetime probability of affluence" (p. 131).

According to Joyce, the economic security of married women is far greater than that of

single women due to married women having access to more sources of income, namely

spousal salaries and retirement benefits. In addition to the benefit of having spousal

income, "having a spouse directly influences the workforce behavior of married women

and, therefore, has a direct effect on their own wages over time" (Joyce, 2005, p. 5).

Housing equity is typically a significant component of net worth. Marital status

greatly affects homeownership, with never married adults being the least likely to own a

home (Yamokoski, 2007). Home values vary significantly based upon marital status, and

the values of homes owned by married couples were substantially higher than the values

of homes owned by single women that were never married, divorced, or widowed (Joyce,

2005).

Over the last three decades, cultural changes have affected women's attitudes

about marriage, with some women finding that "they are inharmonious with the roles

men have historically set for women, such as wife, mother and caregiver" (Steinsultz,

2006, p. 23). In 2005, 5 1 % of all adult women were unmarried (Yamokoski, 2007). Not

only is the overall number of unmarried women increasing, but the number of women

that have never been married is on the rise as well. Steinsultz (2006) contended that the

"threat of being alone and poor generated an atmosphere of insecurity and context of

vulnerability in the past" (p. 23), but that the paradigm shift that has taken place has made

more women comfortable with choosing to never marry. According to Steinsultz, women

34

who were never married tend to have greater wealth than married women do. In contrast

to Steinsultz's findings, Joyce (2005) found that women who were never married

accumulated less wealth than married women, although work consistency was higher and

total household income was only slightly less than that of the married women. This

growing demographic of the never married individual may have less of a family social

structure than a married person with a nuclear family, and as such, must be studied to

determine the impacts of age, gender, education, and ethnicity on the potential for wealth

accumulation (Steinsultz, 2006).

Divorce negatively affects a woman's ability to generate both earnings and wealth

(Foster, 2008). Foster (2008) identified that the decline in earnings and in wealth

generation was more drastic and longer lasting for women than for men in the U.S.,

following a divorce. Lyons (2001) revealed that divorced men have more access to credit

than divorced women do, although access to credit has been improving for divorced

households since 1989. Divorce is more economically devastating to women than

widowhood, as assets are generally divided in a divorce, whereas a widow typically

inherits the majority of marital assets (Joyce, 2005). Joyce (2005) found that widowed

women had more economic security than divorced or never married women did in older

age, but that this group still had less income and net worth than married cohorts.

Spivey (2006) explored the relationship between risk aversion and propensity to

marry. Spivey analyzed information on risk preferences collected through the 1979

National Longitudinal Survey of Youth and correlated income risk aversion with the

tendency to marry early in life. Spivey's findings were that women were slightly more

35

risk averse than men, and that individuals that were more risk averse were more likely to

marry at an earlier age than those that were more risk tolerant.

Gender tendencies toward risk aversion not only affect propensity to marry but

also investing habits. As more women have brought increasing amounts of income into

the household, they have taken a more active part in managing the family finances

(Evans, 2010). Women in the roles of family financial managers are expected to be more

risk averse than men, and exhibit more anxiety over finances than their male

counterparts; as such, women will more often seek professional financial advice than men

do (Evans, 2010). Current research does not support the assumption that, in order to

make investment decisions, the decision maker needs some financial knowledge (Leland,

2009). However, women are more likely to conduct simple information searches than

men are when engaging in investing activities, using fewer sources of information less

frequently (Evans, 2010). The inclination toward risk aversion may be physiological

rather than cultural. Financial risk-taking has been associated with higher levels of the

hormone testosterone in both males and females, indicating that, in general, men are more

likely to be risk tolerant than women (Sarpienza, Zingales, & Maestripieri, 2009).

Hryshko (2006) examined data compiled through the Panel Study of Income Dynamics to

analyze financial risk aversion, and determined that children who grew up under female

head-of-households tended to more risk averse than other groups, but did not conclude

that this means that females in general are more risk averse (Hryshko, 2006). Yao (2003)

found that females were consistently less risk tolerant than males, based upon a

longitudinal study of SCF data sets from 1983 through 2001.

36

Investing habits and tolerance for risk affect accumulation of wealth. According

to Leland (2009), there are conflicting opinions reported in the literature regarding the

influence of gender on financial knowledge. Leland conducted a study to explore the

factors that influence women in making investing decisions and using online investing

tools. Leland found that there is a significant correlation between women's attitudes

toward money and their propensity to invest online, specifically that women with a higher

tolerance for risk tended to invest online. Further, there is a strong positive correlation

between financial knowledge and the tendency to invest online for women, according to

Leland's study. Socioeconomic status influences the tendency for women to invest

online, in that the higher a woman's annual income, the greater the tendency to invest

online (Leland, 2009). Gender influences the exposure to and use of technology, with

males having an increased interest in and exposure to technology than females (Leland,

2009). There are differences in the perception of technological skills among the genders,

but no actual difference in user outcomes between the genders has been observed

(Leland, 2009).

Spivey (2006) also found that parents were more risk averse than individuals

without children, and that the most risk-averse parents were those with children between

6 and 13 years old. Spivey's hypotheses may partially explain the findings of Steinsultz

(2006); Steinsultz found that women who were never married accumulated more wealth

than married women, while making slightly less income, and this might be explained by

identifying never married women as risk tolerant while their married cohorts might be

described as risk averse, both in marriage and in investing habits.

37

Yamokoski (2007) found that single parenthood negatively affects wealth

accumulation. According to Yamokoski's (2007) findings, the younger the individual

was at the time he or she became a parent, the more dramatic the negative affect net

worth. A teenage mother is significantly more likely to have full custody of a child than

a teenage father is, and the teenage mother therefore has the primary burdens of being

caretaker and financial provider, causing a substantial decline in the ability for the teen

mother to achieve financial stability (Yamokoski, 2007).

The number of single parent households in the U.S. continues to climb; according

to Yamokoski (2007), by 2002, 23% of children lived in mother-only households and 5%

of children lived in father-only households. Single parenthood increases the risk for

living in poverty; this phenomenon clearly affects women more than men since the

number of mother-only households is more than 4 1/2 times the number of father-only

households. Yamokoski attributed at least part of the financial burden faced by single

mothers to insufficient government regulation of child support arrangements, and

identified that mothers who were never married are less likely to receive child support

than women who were divorced from their children's fathers.

In contrast to Yamokoski's (2007) findings that single parenthood significantly

affected wealth accumulation, Joyce (2005) found that the number of children did not

significantly affect the ultimate wealth levels of older women. Since the participants in

Joyce's study were women over 50, it is possible that the financial effects of raising

children were no longer as influential as they appeared in Yamokoski's study of women

of all ages. However, women with interrupted work histories are more likely to have

accumulated less assets and less retirement benefits than those that have consistently

38

worked throughout their lives, and interruptions in working for women is frequently

related to having children (Joyce, 2005). Schmidt and Sevak (2006) found that

households with young children did not necessarily have less wealth than households

without, but that households with children between the ages of 18 and 24 have less

wealth, usually due to higher education costs. Yilmazer (2002) found that parents

allocated a lesser percentage of overall wealth to retirement assets than households

without children.

Wealth concentrations have been a subject that has been studied in recent years;

Yang (2006) observed that wealth in the U.S. is highly concentrated. Foster (2008)

stated, "Wealth is much more unevenly distributed than income" (p. 3). Yang correlated

housing wealth and non-housing wealth with age and concluded that younger persons

were more likely to hold a significant portion of their equity in their homes, whereas

older persons accumulated more non-housing wealth than their younger counterparts did.

Juster, Lupton, Smith, and Stafford (2006) did a wealth analysis that was similar to

Yang's in that it divides housing and non-housing assets in their correlational study.

Joyce (2005) identified that married couples tend to have a greater home values than

unmarried women.

The Survey of Consumer Finances

The Survey of Consumer Finances (SCF) data sets have been used as a basis for

many studies, including journal articles, publications for the Federal Reserve Board, and

dissertations (Cho, 2009; Embry & Fox, 1997; Fisher, 2006). Arthur Kennickell (1995,

2006, 2009) has co-authored many studies based on the SCF. In addition to the many

working papers for the Federal Reserve Board that are written by Kennickell, he has

39

participated in writing numerous articles published as part of the Federal Reserve Bulletin

or finance or economic journals over the past two decades. In 1995, Kennickel

collaborated with Canner to review the increase in household debt in proportion to

increases in household income, based on the SCF data for 1983 through 1989. In 1999,

Kennickell and Woodburn analyzed the weighting system used in the survey to consider

the validity of the wealth distribution presented by the SCF for 1989, 1992, and 1995.

Bucks, Kennickell, and Moore (2006) found that household wealth increased 1.5% from

2001 to 2004, according to data from the SCF. Both mean and median net worth of U.S.

households increased significantly, at 13.0% and 17.7%, respectively, from 2004 to 2007,

according to a study on the SCF data by Bucks, Kennickell, Mach, and Moore (2009).

Embrey and Fox's 1997 study is closely related to this dissertation. Embrey and

Fox examined single male and single female household financial behaviors using data

from the 1995 SCF, and found significant differences in the life-cycle stages of single

men and single women. The average single male was younger, made more money, and

was less likely to have ever been married than the average single female (Embrey & Fox,

1997). Gender, age, income, and marital status influence investing patterns and wealth

accumulation, according to the Embrey and Fox's analysis of the 1995 SCF data.

Doctoral dissertations often reference data from the SCF. Savings habits (Cho,

2009; Fisher, 2006), spending habits (Tangsomchai, 2007), consumer debt behaviors

(Lee, 2009; Shand, 2008), risk aversion (Hu, 2002; Yao, 2003), and asset allocations

(Huang, 2007; Kyrychenko, 2007) have all been examined using data from the SCF. The

propensity for buying life insurance (Carman, 2003; Li, 2008), utilizing electronic

banking services (Huang, 2005), finding multiple sources of investment advice (Kwon,

40

2002), and using a financial planner (Evans, 2010) have been correlated to demographics

using SCF data.

Savings, or America's lack of savings, has been the subject of both Fisher's

(2006) and Cho's (2009) doctoral dissertations. Fisher (2006) examined savings patterns

based upon the 2004 SCF data set. Fisher found that having more than the expected per-

period income significantly affected saving, and that having less than the expected per-

period income negatively affected saving in a more significant way than having excess

income. Savings motive and savings horizon both significantly affected the likelihood of

savings (Fisher, 2006).

Cho (2009) focused on the problem that Americans have limited savings

accumulated. Cho used the 2007 SCF data to analyze the relationship between savings

behavior and savings goals. Using a logistic regression analysis of the SCF data, Cho

found that having savings goals significantly influenced the likelihood of savings, and

further deduced that the likelihood of saving increased if the savings goal was

prevention-related, rather than promotion-related.

Baek (2003) examined the 1992 and the 1998 SCF data sets as representative of

periods of economic recession and expansion, respectively. Baek analyzed the effects of

employment related factors on saving and the use of credit during economic recession

and expansion periods, and concluded that there was a significant correlation between

employment and savings and use of credit.

Savings habits, as they relate to having children, are the subject of Yilmazer's

(2002) dissertation. Taking information from the SCF, Yilmazer found that number of

children affects portfolio allocation, and specifically that homeowners decrease the share

41

of wealth invested in retirement assets based upon the number of children in the

household. Income uncertainty affects the decision to have a child, but ultimately does

not affect level of savings, when adjusted for family size, according to Yilmazer's 2002

study. Further, Yilmazer found that saving for children's education expenses increased

with the age of the head of household.

Consumer spending habits, and specifically consumer spending habits of

unconstrained households, were the subject of Tangsomchai's (2007) dissertation.

Tangsomchai used data from the SCF and the Survey of Income and Program

Participation (SIPP) to test the Life Cycle Permanent Income Hypothesis as it relates to

consumption of durable goods. The findings of this study were that financially

unconstrained households spent less than the model predicted (Tangsomchai, 2007).

Tangsomchai found that there were no significant differences in the consumption habits

of the genders, but spending habits were significantly different based upon race.

Household debt has been another widely studied subject using the Survey of

Consumer Finances data. Lee (2009) examined household debt repayment using data

sets from the SCF for 1992 through 2007. Lee's 2009 study was focused on relating

household debt repayment and delinquency patterns with racial and ethnic demographics.

Lee found that black, Hispanic and Asian households were less likely to have household

debt than white families, but that blacks were significantly more likely to be delinquent

than whites and Asians, who were more likely to be delinquent than Hispanics.

The impacts of early household debt, specifically student loan debt and credit card

debt, on decisions to marry, purchase a home, and have children, were the subject of

Shand's (2008) dissertation. Shand used the data sets from the SCF from 1992 through

42

2004 to examine the effect of having college loans, and found that educational debt

lowers the probability of home ownership, negatively correlates with marriage rates, and

causes a delay in fertility. Having credit card debt positively relates to homeownership,

as credit card debt may allow for flexibility in budget constraints (Shand, 2008).

Li (2004) examined the phenomenon of consumers having high levels of interest

bearing credit card debt while holding large quantities of liquid assets. Survey of

Consumer Finance (SCF) data indicated that risk aversion and precautionary savings

models predicted household behaviors (Li, 2004). Telyukova (2006) undertook a similar

study, and hypothesized that households may not pay down credit card debt because they

intend to use their liquid assets to purchase goods that they could not buy with credit

cards. Telyukova's findings support Li's (2004) findings in that they both conclude that

uncertainty affects the amount of liquid assets held by U.S. households, regardless of

existing credit card debt. The work of O'Hara (2003) further substantiates the findings of

Li (2004) and Telyukova. O'Hara used the 1995 and 1998 SCF data sets to examine

home equity borrowing patterns, and found that uncertainty affected the propensity to

save liquid assets while borrowing against home equity.

Lyons (2001) analyzed two decades of data provided by the SCF to examine how

access to desired credit had changed since 1983. Lyons (2001) found that in almost all

circumstances, access to desired credit improved over the period examined, regardless of

earnings, age, gender, or race. The most significant improvements in access to credit

observed were for black households and households with low income (Lyons, 2001).

Lyons further observed patterns in accessing credit for divorced individuals, and found

that access to credit increased since 1989 for divorced households. Divorced males had a

43

more dramatic increase in access to credit than divorced females over the period 1992

through 1998, according to SCF data (Lyons, 2001).

Risk aversion has been the subject of studies using SCF data. Of note is Yao's

(2003) dissertation that examined patterns of financial risk tolerance from 1983 through

2001 based on SCF data. Yao concluded that risk tolerance was a significant factor in

household financial decision-making. Age, race, and marital status all were predictors of

financial risk tolerance (Yao, 2003). Women are consistently less risk tolerant than men

(Yao, 2003).

Hu (2002) correlated risk aversion with homeownership, using Survey of

Consumer Finance data. Renters become more risk averse when they are considering

buying a home in the future, and homeowners hold less stock when they have a

substantial portion of their wealth invested in their homes (Hu, 2002).

Huang (2007) used data sets from the SCF for 1992 through 2004 to analyze the

relationship between race and household financial asset allocations. Huang (2007)

correlated race, age, education, gender, marital status, and number of children, socio-

economic variables, and risk tolerance, to financial assets held, and found that in general,

minorities were at financial disadvantage to white households.

Kyrychenko (2007) used five sets of data from the SCF (SCF) to examine asset

allocations, and found that U.S. stockholders have a propensity to hold stock in domestic

corporations over foreign stock. Further, households tend to follow popular financial

advice (Kyryshenko, 2007).

Li (2008) used the 2004 SCF to examine the types of life insurance purchased and

the amounts of life insurance held by households. Li (2008) found that insurance holders

44

that had cash value life insurance were older, more educated, more likely to have a home,

and more likely to expect to leave a bequest than term life insurance holders. Households

that did not have life insurance were younger, less educated, unmarried, renters with

lower income than households that include life insurance holders (Li, 2008). Carman

(2003) used the 1995 SCF data and found that life insurance is uncorrelated with

financial vulnerability at all stages of life cycle. However, there exists substantial gender

bias among married couples with regard to life insurance, with wives being substantially

more protected than husbands are (Carman, 2003).

Huang (2005) examined the use of electronic banking services. Through

examining data from the SCF, Huang (2005) found that age, gender, marital status, race,

education, and income all significantly affect the likelihood of using electronic banking

service, but employment status and financial assets do not.

Using the 1998 SCF data, Kwon (2002) examined the relationship between

demographics and the likelihood of using multiple sources of information when

investing. Kwon found that age, education, race/ethnicity, possession of financial assets,

and attitude toward risk all affected the use of multiple sources of information.

Evans (2010) used the SCF as the basis for a study that contained an examination

of the predisposition of women to use a financial planner in making savings and investing

decisions. Evans (2010) found that, based upon data from the 2004 SCF, gender did not

predispose the use of a financial planner so much as asset value, with households with

$100,000 or more in asset value being more likely to use a financial planner than those

with less money to invest. However, the needs of husbands and wives were clearly

different, with regard to managing the household finances (Evans, 2010).

45

Generation X

Generation X refers to the individuals born in the 1960s and 1970s in America,

with sources identifying the specific birth years of this cohort slightly differently.

Generation Xers have been identified as the 46 million people born between 1962 and

1977, who are between the ages of 33 and 48 in 2010 (Asaro-Gonzalez, 2006), and as

persons born between 1968 and 1979, who are between the ages of 31 and 43 in 2010

(U.S. Census Bureau, 2004). Scholars have studied the effects of Generation X on the

workplace extensively. The stereotypes about Generation Xers being disrespectful, lazy,

and fiercely independent (Mackey, 2005) have spurred research to explore those

characteristics. Generation Xers do not like to be micromanaged, like flexibility in their

working conditions, and prefer to receive timely feedback on their projects (Mackey,

2005). According to Mackey, members of former generations commonly perceive

members of Generation X as lacking company loyalty, because Xers will oftentimes

switch jobs for better working conditions or increased flexibility. Despite frequent job

movement, Generation Xers tend to have loyalty to their profession (Mackey, 2005).

Generation Xers are substantially different from other generations that are concurrently in

the workforce.

Generation Xers are working side by side with both older and younger

generations that have vastly different traits and values. The age span of workers

continues to increase as older workers remain in the workforce, creating challenges for

management who are overseeing up to four generations of employees working together

(Jones, 2010). The generations are divided by behaviors, attitudes, and beliefs that

"enable social scientists to identify social patterns and cultural trends in society within the

46

boundaries of each generation" (Asaro-Gonzalez, 2006, p. 27). The Traditionalists, the

Baby Boomers, Generation X, and Generation Y represent the vast majority of the

current workforce in the U.S.

The workplace is more complex today than it has been in prior decades because

there are multiple generations working together in organizations, oftentimes in team-

based environments rather than a traditional hierarchical structure (Moody, 2007).

Within these complex organizations, some employees have developed derogatory

stereotypes regarding the attitudes and behaviors of coworkers from other generations

(Moody, 2007). According to Moody (2007), age-based classifications in the modern

workplace are harmful. Members of each generation should not necessarily adapt to the

other generations, but should develop an understanding and acceptance of the

characteristics of their co-workers (Moody, 2007). Although defining persons as

members of a generation may lead to stereotyping, these generalizations are useful in

understanding the broad perspectives of different groups of individuals (Asaro-Gonzalez,

2006).

Generation Xers work with Traditionalists, Baby Boomers, and Generation Yers.

The specific birth years that classify each generation vary slightly by source, causing

some overlap and gaps in the generational cohorts. Traditionalists, also called the Mature

Generation, or the combination of the Silent Generation and the GI Generation, are those

individuals born between 1908 and 1945, who are between the ages of 65 and 102 in

2010 (Asaro-Gonzalez, 2006). Baby Boomers are those 78 million individuals born

between 1946 and 1964, who are between the ages of 46 and 64 in 2010 (U.S. Census

47

Bureau, 2006). Generation Yers are those 76 million individuals born between 1978 and

1984 who are between the ages of 26 and 32 in 2010 (Asaro-Gonzalez, 2006).

Generation Xers are outnumbered in the workforce, being the smaller than both

the Baby Boomers and Generation Y (Mackey, 2005). The growing number of aging

Baby Boomers, followed by a substantially smaller number of younger workers to

replace them are "creating a crisis in the workplace" (p. 3), according to Mackey (2005).

Managers must understand generational differences if they are to successfully lead this

diverse group of workers (Mackey, 2005). Each generation has their own characteristics

and expectations of their employers that influence the culture of the workplace (Mackey,

2005). Some of the conflicts that occur in the workplace regarding generational

differences include seniority versus merit-based promotions, rigid schedules versus

flextime, and how work is to be accomplished (Mackey, 2005). In order to manage such

age-diverse workgroups, the manager must understand the basic characteristics and

motivations for each generation.

Traditionalists, or the generation sometimes referred to as Matures (Janiszewski,

2004) or the Builder generation (Mackey, 2005), were born before the mid-1940s

(Janiszewski, 2004). The world events that affected the Traditionalists were the Great

Depression (Jones, 2010; Janiszewski, 2004), World War II, and Pearl Harbor (Jones,

2010). The Traditionalists "formed their view of the world during unstable and insecure

times and saw America triumph over them", creating an attitude that with dedication,

hard work, and sacrifice, they could make their lives better (Mackey, 2005, p. 7).

Traditionalists base their decisions about the future based upon the lessons learned in the

past (Mackey, 2005).

48

The gender roles of men and women in the Traditionalist generation were clear,

and men expected women to stay at home, support them, and raise the children (Mackey,

2005). Traditionalist workers have strong interpersonal skills, exhibit loyalty to their

employer, and believe that career advancement comes from job tenure (Jones, 2010).

The Traditionalists are the wealthiest generational group (Jones, 2010).

The Baby Boom generation was the first generation to have significantly different

political and social outlooks than their parents' generation, creating the first generation

gap (Love, 2005). The Baby Boomers' worldview was influenced by events such as

Woodstock (Janiszewski, 2004), Vietnam (Janiszewski, 2004; Jones, 2010), the Civil

Rights movement (Janiszewski, 2004; Jones, 2010), the assassinations of John F.

Kennedy and Martin Luther King, Jr. (Jones, 2010; Mackey, 2005), the Cold War

(Mackey, 2005), and feminism (Janiszewski, 2004). Watergate and the Vietnam War

strongly influenced the Baby Boomers views on authority (Love, 2005).

The Baby Boomers "grew up in an era of unprecedented prosperity and affluence

that followed World War II" (Mackey, 2005, p. 8). Since the Boomers grew up in

relative wealth, this allowed them to focus on social change instead of working to simply

meet their basic material needs (Love, 2005). Boomers looked for adventure and

considered the world full of possibilities (Mackey, 2005). Baby Boomers pursued

personal gratification, and unlike prior generations, would divorce or leave a job if

unhappy (Mackey, 2005).

The majority of Baby Boomers grew up in two-parent homes (Mackey, 2005).

Education became increasingly important, and Baby Boomers spent more time pursuing

higher education than prior generations had (Love, 2005). Boomers believed that

49

"getting a college education and working hard could provide a comfortable lifestyle that

surpassed that of their parents" (Mackey, 2005, p. 9).

Boomers went to work in a secure job environment, and represented

approximately two-thirds of the American labor force in 2009 (Mackey, 2005). Boomers

grew up having to cooperate and collaborate based upon the sheer number of them, and

brought that team environment to the workplace (Mackey, 2005). Baby Boomers

"believe that teamwork and relationship building are very important, and they evaluate

themselves and others based on work ethic" (Jones, 2010, p. 18). Baby Boomers are

often referred to as workaholics (Jones, 2010), and Boomers were willing to work long

hours and often left their children home alone (Mackey, 2005). Boomers have slowly

adjusted to the use of information and technology (Mackey, 2005).

Generation Xers were born into a "rapidly changing social climate and an

economic recession" (Mackey, 2005, p. 11). The major world events that influenced

Generation X were primarily negative ones, including the energy crisis (Mackey, 2005),

the Space Shuttle Challenger disaster (Asaro-Gonzalez, 2006; Jones, 2010; Mackey,

2005), the AIDS epidemic (Asaro-Gonzalez, 2006; Love, 2005), and corporate

downsizing (Asaro-Gonzalez, 2006). The Iran hostage crisis (Love, 2005), nuclear

threats (Love, 2005), the fall of the Berlin Wall (Jones, 2010; Mackey, 2005), and the

Gulf War (Jones, 2010; Love, 2005) were among the political events and conditions that

affected Generation Xers as they were growing up. Generation X is considered skeptical,

and this may be the result of them seeing "major American institutions called into

question", such as the Nixon Watergate scandal, the Iran-Contra conspiracy, massive

corporate layoffs, and the Stock Market Crash of 1987 (Mackey, 2005, p. 14).

50

Generation Xers were the first generation to grow up in a two-income family

(Mackey, 2005), which meant that they were often unsupervised as children of working

parents. Generation Xers relied upon themselves and their friends as they grew up, rather

than their parents, since they often came home to empty houses due to the increase in

dual-income households and the rise of divorce (Love, 2005). Known as latchkey

children since their Boomer parents would give them a key to the house to let themselves

in when they got home from school (Asaro-Gonzalez, 2006), Generation Xers became

self-reliant as a result of being the "most attention-deprived, neglected group of kids in a

long time" (Mackey, 2005, p. 14). The adult members of Generation X seek balance and

stability in their family and work lives because of this instability that they encountered at

an early age (Asaro-Gonzalez, 2006).

Since Generation X was the first generation to grow up in households that

predominantly had two working parents, Generation Xers grew up expecting that both

men and women would work (Mackey, 2005). According to Mackey, Generation Xers

tend to be more committed to balancing work and family lives than prior generations, in

reaction to growing up in homes with two working parents. Generation X looks for a

balanced lifestyle; they "work to live, not live to work" (Mackey, 2005, p. 11). Boomer

workaholics have criticized Generation Xers for their commitment to a balanced lifestyle,

and have stereotyped Generation Xers as being slackers in the workplace (Mackey,

2005). However, Asaro-Gonzalez (2006) concluded that Generation Xers do not have a

lower work ethic than Baby Boomers. Generation Xers place a higher value on balancing

work and personal life, which Boomers may interpret as having a lower work standard

51

(Asaro-Gonzalez, 2006). Generation Xers are not willing to sacrifice personal goals for

business goals (Janiszewski, 2004).

The Baby Boomers assumed that they would remain employed long-term when

they entered the workforce, whereas Generation X did not have the expectation of job

security (Janiszewski, 2004). Generation Xers were underemployed or unemployed upon

graduating college, due to the stock market crash of 1987, the economic recession of the

early 1990s, and corporate downsizing that was characteristic of this era (Love, 2005).

Many Generation Xers entered the workforce and received contractor positions, further

strengthening the generation's lack of reliance on organizations and institutions (Love,

2005). As such, Generation X members that are dissatisfied with their jobs will leave,

whereas Baby Boomers tend to stay with a company, intending to change to organization

for the better (Janiszewski, 2004). Generation X believes that they achieve financial gain

through changing roles or organizations rather than merit increases earned through one

organization (Jones, 2010).

Generation Xers tend to be more entrepreneurial and independent than Baby

Boomers (Janiszewski, 2004). However, many credit the Baby Boomers with having

transformed the business environment into a less hierarchical structure than what they

faced when they entered the workforce (Janiszewski, 2004). Generation Xers want to

work in informal but goal-focused organizations that provide recognition for achievement

and encourage innovation (Janiszewski, 2004). Generation Xers appreciate informality in

the workplace, and like casual dress days and the opportunity to have fun at work

(Mackey, 2005). Janizewski's (2004) statement, "Rigid constraints of any type

immediately alienate Generation X members" (p. 66) supports Mackey's (2005)

52

contention that Generation Xers dislike formal work environments. Generation Xers are

not being lazy, as their Boomer co-workers have often accused them of being, but simply

have a need for flexibility in how they accomplish tasks (Mackey, 2005). Generation

Xers are independent, like to be in control, and do not like to be closely supervised

(Mackey, 2005).

Generation Xers are strong at developing effective relationships (Mackey, 2005).

Generation Xers "value communication, respect production over tenure, value control of

their time, and look for a person to whom they can invest loyalty, not a company" (Jones,

2010, pp. 18-19). Generation Xers are known to "develop skills and apply them

effectively and therefore expect their employers to listen to their needs, create an

enabling environment and pay them fairly" (Mackey, 2005, p. 11). Generation Xers are

able to use technology effectively, since it was available to them throughout their

lifetimes (Mackey, 2005). According to Love (2005), the opinions about Generation

Xers in the workplace have been evolving over time from the negative viewpoint that

Generation Xers are lazy slackers that lack commitment, to valuing the positive impact

that Xers have had on organizations such as innovation, their ability to work

independently, and their adaptability.

Generation Xers are comfortable with change because they have experienced it

their whole lives, making them used to a fast pace and lack of stability (Mackey, 2005).

Generation Xers "can be corporate rovers", aggressively seeking new employment when

they are mismanaged and using employers for resume building purposes (Mackey, 2005,

p. 13). Generation Xers may not be loyal to their employers but are loyal to their

professions (Mackey, 2005).

53

Generation Xers grew up in a time when many minority groups were demanding

equal rights, and as such, value diversity (Mackey, 2005). Generation Xers entered a

diverse workforce, with women and minorities being more highly represented than in

prior generations, making Generation X the most diverse generation to date (Love, 2005).

Generation X women seek and find significant work flexibility through working

flex schedules, working from home, doing temporary work, or working as an independent

contractor, in order to accommodate a balance between work and family life (DiNatale &

Boraas, 2002). Keller (2008) studied the effects of flextime on absenteeism, and found

that the generations behaved differently. Younger employees reported that significantly

more use of unpaid leave than older employees did, according to Keller (2008). Keller

(2008) postulated that younger workers may "have less invested in their careers and feel

less loyal to the company" than older employees who may not wish to jeopardize their

positions through exhibiting excessive absenteeism (p. 57).

Financially, Generation Xers are self-reliant risk takers, but this the first

generation to have a lower standard of living than their parents (Mackey, 2005).

Generation Xers are not saving as much for retirement as Baby Boomers; although 7 in

10 Generation Xers started saving for retirement by the age of 25, they do not save

proportionately as much as the Baby Boomers did at a comparable age (Transamerica,

2004). However, Generation Xers value having a comfortable standard of living, and as

such, tend to be financial savers (Love, 2005).

Education became more available to Generation Xers than it had been to previous

generations, as standards of higher education decreased in the 1990s, which also led to

higher incurrence of student loan and credit card debt than previous generations (Love,

54

2005). Generation X is the most highly educated with approximately 60% of this cohort

having some college education (Mackey, 2005). Generation X women are highly

educated; 30% of Generation X women had 4-year college degrees by 2000, compared to

only 18%) of Baby Boomer women (DiNatale & Boraas, 2002). Generation X women are

slightly more likely to be college educated than their male counterparts are (DiNatale &

Boraas, 2002).

Through exposure to mass media, the younger generations in particular have had

their worldviews influenced by global events that have in turn influenced their beliefs and

workplace behaviors (Asaro-Gonzalez, 2006). The events that have shaped Generation Y

include the Gulf War (Mackey, 2005), the Oklahoma City Bombing (Mackey, 2005), the

Clinton scandals (Mackey, 2005), the September 11, 2001 terrorist attacks (Jones, 2010),

and the internet boom and use of technology (Jones, 2010).

Generation Yers are the most technologically advanced generation to date, and

possess strong self-images and confidence (Mackey, 2005). However, "because

members of the youngest generation have spent so much time in a virtual world, often

their social skills are not as developed, or not developed in such a way that is understood

by members of older generations" (Jones, 2010, p. 23).

Generation Yers are "idealistic and confident" (Jones, 2010, p. 19), and are both

"optimistic about the future and realistic about the present" (Mackey, 2005, p. 16).

Generation Yers are known to have been "raised in a period of unprecedented growth and

seemingly unlimited expansion in personal wealth" (Mackey, 2005, p. 15). Many

Generation Yers grew up in single-family homes where they felt wanted and accepted

(Mackey, 2005). Generation Y has a combination of characteristics that are taken from

55

generations prior, including loyalty like the Traditionalists, teamwork skills like the

Boomers, and skepticism like Xers (Mackey, 2005).

In the workplace, Generation Yers thrive on change and innovation (Jones, 2010;

Mackey, 2005), and use networking to gather new ideas and complete tasks (Mackey,

2005). Generation Y wants positive managerial reinforcement, personal fulfillment, and

ways to shed stress (Jones, 2010). Generation Y is, like Generation X, extremely tolerant

and welcoming of diversity (Mackey, 2005). Generation X and Generation Y seek

balance between work and personal life; Traditionalists and Baby Boomers work for the

common good despite individual wants or needs (Asaro-Gonzalez, 2006).

Summary

The literature related to the gender wealth gap, and how Generation X entering

the workforce may have affected the gender wealth gap, is broad, as has been

demonstrated through this literature review. The gender earnings gap, and changes to the

gender earnings gap, is highly documented (Alkadry & Tower, 2006; Weinberg, 2007).

The narrowing of the gender earnings gap should lead to a closing of the gender wealth

gap, but there is little quantification of the gender wealth gap to substantiate this

hypothesis.

There is substantial information regarding women and wealth accumulation. The

relationships between the accumulation of retirement assets and demographics such as

age, lifetime earnings, marital status, and number of children have been thoroughly

examined (Schmidt & Sevak, 2006; Yamokoski, 2007; Yilmazer, 2002). Most studies

have come to similar conclusions regarding demographic factors and wealth; however,

there are contradictory claims regarding the effects of having children on net worth.

56

Despite the significant volume of information on women and wealth accumulation, there

is little data regarding women and wealth accumulation across all life stages.

The SCF data have been the basis for many different types of studies, including

dissertations on savings, debt, asset allocation, and risk tolerance (Cho, 2009; Lee, 2009).

Many of these dissertations include analysis of one of the data sets of the SCF, but few

include longitudinal studies of trends that emerge over time. One of the advantages of

using the SCF as a basis for a doctoral study is the repetitive nature of the survey that

provides the opportunity for study trends over time.

Scholars have compared Generation X to other generations, with regard to their

characteristics, work patterns, and behaviors (Jones, 2010; Mackey, 2005). There is

significant research regarding how Generation Xers have different attitudes and actions

than prior generations. However, little information regarding the wealth accumulation

habits of Generation X is available, and there lacks information on the differences in

wealth accumulation patterns of the men and women of Generation X.

Prior research has not quantified the gender wealth gap, but studies, such as those

cited within this dissertation, provide a basis for the understanding that the gender wealth

gap may still exist. Women are more likely to live in poverty (Spraggins, 2005) and less

likely to accumulate significant wealth than men are (IRS, 2009b, para. 1), which are

evidence that there is a gender wealth gap and that it is a problem in the U.S. This

quantitative trend analysis study has provided a quantification of the gender wealth gap

observed for the sample. The majority of research regarding the gender wealth gap in the

U.S. involves older adults (Joyce, 2005; Steinsultz, 2006); researchers have studied the

wealth of older adults extensively, but the wealth of the population of adults under the

57

age of 50 years old has not been predominantly studied. This quantitative trend analysis

study contains an examination of the changes in the gender wealth gap by generational

cohort, bridging the gap in literature that relates to the gender wealth gap and younger

generations in the U.S.

58

Chapter 3: Research Method

The problem is that it was unknown whether Generation X women, in comparison

to women of prior generations, were accumulating as much wealth as their male cohorts

(Fisher, 2010). Overall, women in the U.S. have lower levels of wealth and earnings than

men have (Fisher, 2010), as is evidenced by women being more likely to live in poverty

(U.S. Census Bureau, 2008b) and less likely to be among the wealthy (IRS, 2009b) than

their male cohorts are. The phenomenon of men having higher net worth than women is

known as the gender wealth gap (Raub, 2008). The gender wealth gap is a problem

because it affects women's quality of life (Joyce, 2005; Steinsultz, 2006, Yang, 2006).

The gender wealth gap has not been well quantified by prior research and recent

findings "have been mixed regarding whether a wealth gap between male and female-

headed households exists" (Fisher, 2010, p. 15). A partial reason for the gender wealth

gap is the gender earnings gap, a problem that has been widely studied (Alkadry &

Tower, 2006; Barbezat & Hughes, 2005). Recent research efforts by Bobbitt-Zeher

(2007) found that Generation X is less affected by the education gap and familial barriers

to women working than prior generations have been. By quantifying the gender wealth

gap and examining the trends in the gender wealth gap by generational cohort, it may be

determined whether the gender wealth gap is improving for Generation X women in

comparison to prior generations. The results of this study may indicate whether the

problems related to financial inequality are lessening, or whether the gender wealth gap is

actually widening, either of which will indicate a need for further study.

The purpose of this quantitative trend analysis study was to determine whether

Generation X women, in comparison to women of prior generations, were accumulating

as much wealth as their male cohorts. Examining the changes in the gender wealth gap in

59

the U.S. over the period 1992 - 2007 has provided information as to whether the overall

gender wealth gap has changed as Generation Xers entered the workforce, and whether

the gender wealth gap is different for Generation X than for prior generations. A

narrowing of the gender wealth gap for Generation X indicates that the problems related

to wealth inequality that have plagued women of prior generations are being eradicated

for Generation X. A widening of the gender wealth gap for Generation X indicates that

the problems related to financial inequality, such as higher levels of poverty and lower

levels of wealth for women than men, still exist and are increasing. This quantitative

trend analysis study has furthered the body of knowledge on the gender wealth gap and

brought awareness to challenges that still exist to obtain financial equity among the

genders.

The following questions have guided the quantitative trend analysis study to

determine whether Generation X women, in comparison to women of prior generations,

were accumulating as much wealth as their male cohorts. The gender wealth gap has

been measured based upon net worth statistics of unmarried men and women in the U.S.,

as reported in the SCF over the period 1992 - 2007.

Q l : To what extent has the gender wealth gap changed during the period 1992 -

2007 in the U.S.?

Q2: How does the gender wealth gap in the U.S. differ by generational cohort

during the period 1992 - 2007?

The following null and alternative hypotheses are associated with the two

research questions.

60

Hlo. There is no significant change observed in the gender wealth gap from 1992

until 2007.

HI a . There is a significant change observed in the gender wealth gap from 1992

until 2007.

H20. There are no significant differences between the trends in the gender wealth

gap observed for Generation X and the gender wealth gap observed for prior

generations for the period 1992 - 2007.

H2a. There are significant differences between the trends in the gender wealth

gap observed for Generation X and the gender wealth gap observed for prior

generations for the period 1992 - 2007.

In this chapter, the research method and design are discussed. The study

participants, materials and instruments, and operational definitions of variables, are

detailed herein. Processes of collecting, processing, and analyzing data are outlined. The

limitations and delineations associated with the study are explained, and ethical

assurances are made.

Research Methods and Design

Trend analysis is a technique for evaluating a series of financial data over a period

of time (Kimmel, Weygandt, & Kieso, 2009). This quantitative trend analysis study will

contain an analysis of the triennial data collected through the SCF for the period 1992 -

2007. Trend analysis requires identifying an equation that approximates a line; the line

may be linear, calculated using a least-squares regression model or multiple regression

analysis, or curvilinear, calculated using a multiple regression analysis (Pedhazur, 1997).

61

Postpositive knowledge claims guide this study. The strategy of inquiry

employed in the study is non-experimental research accumulated via survey. The survey

instrument chosen as a basis for the study is the SCF. Researchers collect the SCF data

via structured interviews. The closed-ended, primarily numeric data accumulated

through the SCF has been analyzed using statistical methods to test the hypotheses

presented in this quantitative trend analysis study.

Four research methods were considered as the basis of the study: causal-

comparative research, correlational research, descriptive research, and trend analysis.

Causal-comparative research was rejected as a method since simply identifying the

relationship between gender and wealth would not encompass the entire study, as

proposed. Correlational research would not be an appropriate design for this study since

gender is not a quantifiable variable and correlation was not the goal of the study.

Descriptive research was considered a viable design type for this study. However,

descriptive research is very broad in scope, unlike the chosen study type, a quantitative

trend analysis.

Trend analysis research was selected as the research design for this study as the

study will contain an analysis of the changes in the gender wealth gap over the period

1992 - 2007. Trend analysis provides a basis for fully exploring the research questions.

The first research question addresses whether the gender wealth gap has changed over the

study period, which can only be analyzed through trend analysis. The second research

question addresses whether the gender wealth gap differs by generational cohort over the

study period. Since each research question requires examination of time based trends in

the gender wealth gap, a trend analysis is an appropriate research design available.

62

This quantitative trend analysis study was reliant upon data compiled through the

SCF. In choosing the research design, prior studies that have used data provided by the

SCF were considered. Dissertations such as those by Huang (2007), Lee (2009), Lyons

(2001), Shand (2008), and Yao (2003), all reported findings from examining SCF data

compiled over multiple periods, like this study. Lyons (2001) had research objectives

that were similar to this study in that they examined changes in gaps over time, and

utilized similar methods as chosen herein. Lyons (2001) conducted a trend analysis to

examine the gap between actual and desired borrowing of households, as reported in the

SCF from 1983 through 1998.

Many of the prior studies that utilized SCF data were correlation studies, rather

than trend analyses. The correlation studies conducted using SCF data for multiple

periods (Huang, 2007; Lee, 2009; Shand, 2008; Yao, 2003) had different research goals

than in this study. Although more dissertations that use SCF data for multiple periods are

correlation studies than trend analysis studies, trend analysis is the most appropriate

method of answering the research questions posed in this study. The focus of this study

was to determine trends in the gender wealth gap in order to assess the effects, if any, that

the entrance of Generation X into the workforce has had on the gender wealth gap. A

correlation study would not have accomplished the research goals in the manner that a

trend analysis did.

The design steps included an examination of data previously compiled via the

Federal Reserve Board's SCF for the years 1992, 1995, 1998, 2001, 2004, and 2007.

Based upon respondent data, the net worth of unmarried male and female study

participants were calculated. Measures of central tendency were calculated for the net

63

worth of unmarried male and female respondents for each of the survey years in the study

period, and the gender wealth gap was measured, in dollars, and as a percentage of male

net worth. Trends in the gender wealth gap were developed through linear regression

analysis in order to assess the first research question. To evaluate the second research

question, the respondents were classified by generational cohort. Measures of central

tendency were calculated for the net worth of male and female study participants within

each generational cohort, and the gender wealth gap by cohort was measured. The trend

in the gender wealth gap for each cohort was compared to the trend in the gender wealth

gap observed for Generation X in order to evaluate the second research question. This

design was sufficient to evaluate the specific research questions and hypotheses presented

in this quantitative trend analysis study.

Participants

The population for the SCF is the general population of individual taxpayers in

the U.S. Researchers use a standard multi-stage area-probability sample method for

selecting the sample for participation in the SCF interview process (Bucks et al., 2009).

The data collected by the National Opinion Research Center (NORC) as part of the SCF

is publicly available online as raw data or as weighted data. The Federal Reserve Board

commissions NORC to complete the SCF. Since the sample chosen for the SCF is not

always directly representative of the overall population of taxpayers in the U.S.,

researchers at NORC analyze the SCF data in a weighted fashion so that all

demographics of the population are proportionally represented in the sample (Bucks et

al., 2009).

64

All participants selected for the SCF study come from households with at least

one household member aged 18 or older; in 2008 this population size was approximately

139.9 million 1040 tax return filers (IRS, 2009a). Researchers selected the SCF sample

from the list of individual income tax filers for the previous year, as stratified by level of

income and types of income received, excluding those regarded as extremely wealthy.

Respondents who are listed on the Forbes 400 for each year were removed from the

population, and the respondents with net worth that would qualify them to be on the

Forbes 400 were identified and surveyed; their responses were not included in the survey

data, since these responses might greatly skew the sample means (Bucks et al., 2009).

Four respondents to the 2007 SCF reported net worth values comparable to the Fortune

400, and their responses were excluded from the 2007 data since their inclusion would

substantially skew the data results (Bucks et al., 2009).

In order to analyze the net worth of individuals by gender, this quantitative trend

analysis study contained an analysis of the wealth accumulation of unmarried adults,

since the delineation between the net worth of men and women would not be clear within

a married couple. Respondents were chosen for the study sample using non-statistical

sampling techniques, as the intention is not to draw a representative sample, but rather to

identify the respondents that fit the required profile for examination. A sample that is

representative of the U.S. population would not be feasible for this study, since net worth

of married couples must be excluded from the measurement of the gender wealth gap.

The Federal Reserve Board's website contains the publicly available SCF data, and

additional information is available upon request. The Federal Reserve Board presented

the raw SCF data in several file formats for ease of accessing and storing. The responses

65

to the SCF for the years 1992, 1995, 1998, 2001, 2004, and 2007, were isolated and

analyzed for all participants that fit the target profile of unmarried adult income earners.

The weighted survey data was analyzed as part of this study.

The study sample included SCF data from 8,676 respondents, as this was the

number of unmarried respondents to the SCF over the study period. This number was the

total of the unmarried respondents to the SCF that do not report cohabitating and

combining financial resources. Although the number of participants, 8,676 in total,

appears large, this is the combined total from each of the six study periods' data sets.

Within each data set, a sample size of 1,339 to 1,533 has been identified, as shown in

Table 1. A power analysis indicates that a minimum sample size of 176 is necessary to

achieve a=.05, and the sample size for the study far exceeds the minimum required by the

power analysis.

Table 1

Number of Survey of Consumer Finances Respondents Selected for Study, by Year

Year of Survey of Consumer Finances data accumulation

1992 1995 1998 2001 2004 2007

Number • of respondents 3,906 4,299 4,309 4,449 4,522 4,422

Number of respondents to be included in study sample

1,339 1,405 1,493 1,472 1,533 1,434

Total number of respondents in study sample 8,676

Note. Data source: Federal Reserve Board, 2009, About the Survey of Consumer Finances.

66

Materials/Instruments

This quantitative trend analysis study includes an examination of data previously

compiled via the Federal Reserve Board's SCF for the years 1992, 1995, 1998, 2001,

2004, and 2007. The Federal Reserve Board sponsors the SCF every three years,

whereby the National Organization for Research (NORC) at the University of Chicago

collects data from approximately 4,500 households, representing the general population

of the U.S., via face-to-face and telephone interviews (Bucks et al., 2009). The survey

contains detailed information regarding the demographics such as age and gender of

respondents, income, assets, liabilities, and net worth of the respondents. According to

the NORC, the SCF is the "only fully-representative source of information on the broad

financial circumstances of U.S. Households" (NORC, n.d., ][1).

The survey instrument used in the SCF study includes a detailed list of interview

questions regarding demographics, assets, liabilities, income, saving habits, investing

habits, and spending habits of the respondents. A listing of the topics covered by the

survey instrument is included in Appendix A. The Federal Reserve Board provides the

SCF survey instrument, instructions to interviewers, and prompt cards used in face-to-

face interviews, as well as detailed information regarding the testing of the survey

instrument and modifications made to the survey instrument, on its website (Federal

Reserve Board, 2009).

Researchers used the survey instrument in each of the nine SCF studies conducted

since 1983, and the instrument has been modified each period to improve validity and

reliability. There is no published data to support the overall validity and reliability of the

SCF survey instrument. However, Arthur Kennickell of the Federal Reserve Board has

67

been publishing various articles and working papers for the last 25 years that reference

the validity and/or reliability of particular aspects of the SCF, and many of these are

publicly available on the Federal Reserve Board's website (Federal Reserve Board,

2009).

The SCF is "expected to provide reliable information on components of wealth

that are broadly distributed in the population" (Fisher, 2006, p. 64). The repetitive nature

of the SCF, which has been conducted every three years since 1983, enhances the

assumption of reliability of data. NORC has conducted the SCF for the Federal Reserve

Board since 1992, and this consistency further enhances the assumption of reliability of

data (NORC, n.d.). The relative consistency of data gathered through the SCF indicates

reliability. Significant changes to the data collected through the SCF are reported upon

each survey period. Any changes that are made to SCF data after it is published are

reported on the Federal Reserve Board's website. No changes to the 2007 SCF data have

been reported, to date.

The use of human interviewers, who conduct face-to-face or telephone interviews

with respondents, challenges the validity and reliability of the SCF data collection

process. Human interviewers conduct the SCF, which makes it subject to inconsistent

measurements, or low inter-rater reliability (Trochim & Donnelly, 2008). The

interviewers submit an electronic debriefing questionnaire upon completion of each

interview in order to report any items that may potentially challenge the reliability of the

data collected (Kennickell, 2008).

Households are selected for inclusion in the SCF using a standard multi-stage

area-probability sample method (Bucks et al., 2009). The households that are invited for

68

inclusion in the SCF voluntarily participate in the survey, according to the Federal

Reserve Board (2009). If a selected household chooses not to participate, interviewers

are prohibited from conducting substitute interviews in order to maintain the validity of

the survey (Federal Reserve Board, 2009).

The overall validity of the SCF is not addressed through any published measure.

The frequent reference to the SCF in scholarly works such as technical papers

(Kennickell, 2008) and doctoral dissertations (Cho, 2009; Tangsomchai, 2007; Yilmazer,

2002) leads the reader to assume that there is at least minimal validity related to the SCF.

Operational Definition of Variables

The operational definitions that follow describe each variable that was analyzed in

this study, as associated with the two research questions and related null and alternative

hypotheses.

Net worth. Net worth is a measure of wealth accumulation and economic

security, calculated by taking the sum of the asset values (A) minus the sum of the present

value of all outstanding debts (L) reported for each respondent in the study sample. The

variable X will represent the net worth of male respondents and the variable Fwill

represent net worth for female respondents. Net worth is an interval measure expressed

in a monetary unit, the U.S. dollar, for the purposes of this study.

Gender wealth gap. The gender wealth gap (W) will be calculated by taking the

difference between the net worth of male respondents (X) and the net worth of female

respondents (Y). The gender wealth gap is an interval measure expressed in a monetary

unit, the U.S. dollar, for the purposes of this study.

69

Data Collection, Processing, and Analysis

The gender wealth gap (W) was measured based upon mean net worth and based

upon median net worth for each of the study years. Net worth was calculated by taking

the sum of the asset values (A) minus the sum of the present value of all outstanding

debts (L) reported for each respondent in the study sample, using the following equations:

l.X=Ax-Lx

Z.I JLy - Jby

3. W = X- Y

The intent of analyzing the trend in the gender wealth gap was to determine

whether Generation X entering the workforce affected the gender wealth gap in the U.S.

for the period 1992 - 2007. It was assumed, prior to completing the analysis, that the

gender wealth gap should narrow as Generation X enters the workforce because

Generation Xers are not subject to many of the factors that have historically caused the

gender earnings gap, such as a gender education gap, the glass ceiling, or familial barriers

to women working, that affected prior generations.

In order to assess the first research question, the differences between the sample

measures of central tendency for the net worth of group of male respondents and the net

worth of the group of female respondents was calculated, by year. The specific measures

of central tendency analyzed were the median and mean measures of net worth for the

two groups, unmarried male respondents and unmarried female respondents. The

differences between means of two groups, male respondents and female respondents,

were compared using t-tests, Mann-Whitney [/tests, and one-way ANOVA, utilizing

PASW software, at the 95% confidence level, to determine if the net worth of the groups

70

were statistically different. If the net worth figures for the groups were statistically

different, it would be assessed that the gender wealth gap (W) does exist.

The gender wealth gap (W) was quantified. The median and mean values of the

net worth of men (X) and the net worth of women (Y) for each of the survey years in the

study period were compared. The gender wealth gap (W) was equal to the difference

between X and Y. The gender wealth gap for the study period was plotted graphically and

the equation of the trend line determined using linear regression techniques. Regression

analyses were performed to determine if the gender wealth gap changed relative to time.

If there was not a significant correlation between time and the gender wealth gap in the

U.S. over the period 1992 - 2007, then the null hypothesis HIQ would not be rejected. If

there was a significant correlation between time and the gender wealth gap in the U.S.

over the period 1992 - 2007, then the null hypotheses HIQ would be rejected.

The gender wealth gap, by generational cohort, was calculated for each survey

year in the study period in order to evaluate the second research question. The median

and mean values of the net worth of men (X) and the net worth of women (Y) by

generational cohort for each of the survey years in the study period were compared. The

gender wealth gap (W) was calculated as the difference between Xand Y. The trends in

the gender wealth gap by generational cohort were plotted and the equations of the trend

lines calculated. The equations of the trend lines for the gender wealth gap for each

generation were compared to determine if the gender wealth gap was different for each

generational cohort. The slopes and intercepts of each trend line were compared to

determine if the trends in the gender wealth gap were different for each generational

cohort. If the trends in the gender wealth gap in the U.S. over the period 1992 - 2007

71

were not different for each generational cohort, then the null hypothesis H2o would not be

rejected. If there were a significant difference in the trends in the gender wealth gap in

the U.S. over the period 1992 - 2007 for Generation X in comparison to prior

generational cohorts, then the null hypotheses H2o would be rejected.

Methodological Assumptions, Limitations, and Delimitations

This quantitative trend analysis study was designed to determine whether

Generation X women, in comparison to women of prior generations, were accumulating

as much wealth as their male cohorts. While this information has provided insight into

the current state of the gender wealth gap, it does not necessarily help to alleviate the

problems associated with women accumulating less wealth than their male cohorts. The

study also cannot provide a determination of how future generations will be affected by

the gender wealth gap.

The study was based upon data compiled through the SCF. It is assumed that

participants in the SCF have answered questions truthfully and to the best of their

knowledge, regarding their income and wealth statistics. It is further assumed that the

data is properly collected and reported by interviewers, and that the data published is

representative of the data collected. It is assumed that the conclusions drawn about this

population can be extended to the general population of unmarried adults in the U.S. It is

assumed that the changes made to the survey instrument over the study period do not

change the validity of the data reported.

There are several limitations on this study. First, an examination of the gender

wealth gap requires that wealth be attributed to either males or females, and as such, the

wealth of married couples is not taken into consideration, as it cannot be segregated into

72

male or female generation and ownership. Second, the raw data collected by the SCF

may not be fully representative of the entire population of unmarried adults in the U.S.,

so weighted SCF data was used in this study. The weighted SCF data guarantees

representation of the population, but will not provide the most accurate detail for

analysis. Third, current studies, such as the 2010 U.S. Census and the 2010 SCF, were in

progress as this study was being conducted and therefore were not available for inclusion

in this report. The effects of the economic downturn that has taken place in the U.S.

since the collection of the 2007 SCF data was not included in this study. Finally, inherent

threats to validity, based upon the SCF study parameters, may limit this analysis, as

discussed in the following paragraphs.

External validity is the degree to which conclusions in a study would be valid for

other people, place, or times (Trochim & Donnelly, 2008). Since the SCF is weighted to

be representative of the population of U.S. taxpayers, data from the SCF, as well as

logical conclusions drawn from data analysis of the SCF, should have a high degree of

external validity. However, since only a select amount of the weighted data presented by

the SCF was used in this study, the study conclusions may not be completely transferable

to the overall population of unmarried adults in the U.S.

There are multiple threats to the validity of data compiled through the SCF that

involve the interview process, according to Kennickell (2008). Errors that relate to the

way that the interviewer conducts the live interview or telephone interview can affect the

validity of data compiled; in particular, Kennickell (2008) stated that the talent, training,

and motivation of the interviewer all potentially affect the validity of the data

accumulated through the SCF. The questions posed in the SCF are all factual in nature,

73

but some questions include technical terminology that the respondent might not clearly

understand, or require accumulation of information that a respondent may estimate

(Kennickell, 2008). Unanswered questions within the survey may contribute to a decline

in the validity of the survey data (Kennickell, 2008), but this should not affect this study

due to the large sample size being used for analysis. Social threats to construct validity,

such as hypothesis guessing, evaluation apprehension, and experimenter expectancies as

defined by Trochim and Donnelly (2008), may affect the validity of the SCF, as it is

administered in a face-to-face or telephone interview.

The greatest study delimitation that has been made was the choice to include data

regarding unmarried persons only. In order to consider the gender wealth gap, income

and wealth statistics must be attributed specifically to males or females, and therefore the

data collected from married couples has been excluded.

Another study delimitation that has been intentionally made is the exclusion of

research questions regarding the differences in the saving, spending, and investing habits

of men and women. These questions have been eliminated in order to narrow the scope

of the study. The literature review revealed limited information on the quantification of

the gender wealth gap, and this must first be identified prior to determining if the

differences in the saving, spending, and investing habits of men and women result in a

gender wealth gap that promotes the need for such study.

Ethical Assurances

Ethical issues in research include protection from harm, informed consent, right to

privacy, and honesty with professional colleagues. In this study, there was no direct

contact with study participants, limiting the possibility for ethical breaches. All data used

74

in this analysis has been taken from published data provided through the SCF. The SCF

has taken precautions to protect the identity of all participants, in that no information is

provided to the public regarding participant names or other known forms of

identification. Participants in the SCF are aware that data compiled through this survey is

made publicly available, and can therefore reasonably expect that data may be the subject

of secondary analyses such as this study. There are no possibilities for harm to study

participants, breach of consent, or lack of privacy because this is a secondary data

analysis. Due professional care will be taken to ensure that all data identified herein is

accurately reported, with a commitment to honesty with professional colleagues.

Prior to beginning the secondary analysis of data compiled through the SCF,

approval to complete the study from the IRB was sought. No data was collected nor

analyzed prior to IRB approval. The IRB approval was received as part of the proposal

phase of dissertation completion.

Summary

The research methods detailed herein have provided a basis for examining the

gender wealth gap in the U.S., as reported via the SCF, over the period 1992 - 2007.

There is evidence, such as higher poverty rates for women than men, that indicates that

the gender wealth gap persists in the U.S. (Spraggins, 2005; U.S. Census Bureau, 2008b).

The purpose of this quantitative trend analysis study was to determine whether

Generation X women, in comparison to women of prior generations, were accumulating

as much wealth as their male cohorts. If there was a narrower gender wealth gap for

Generation X than for prior generations, the problems related to gender wealth inequality

may be declining.

75

The quantitative trend analysis study included an examination of data compiled

through the Federal Reserve Board's triennial SCF. By statistically analyzing the gender

wealth gap and related trends as reported by the SCF respondents over the period 1992 -

2007, the two research questions were addressed and the related hypotheses tested. For

the 8,676 SCF respondents that were selected for inclusion in this study, net worth was

calculated. In order to evaluate the first research question, measures of central tendency

were calculated for unmarried male respondents and unmarried female respondents, for

each of the survey years during the study period 1992 - 2007. The gender wealth gap

was quantified by determining the difference between the average net worth of the male

respondents and the average net worth of the female respondents, for each of the survey

years throughout the study period. The changes to the gender wealth gap over the period

1992 through 2007 were measured by using linear regression analysis to develop a trend

line. The trends in the gender wealth gap were utilized to assess whether the gender

wealth gap has changed since Generation X entered the workforce, in response to the first

research question. The process was repeated with data categorized by the generational

cohort of the respondent so that it could be determined whether the gender wealth gap

was different for Generation X, in comparison to prior generations. The wealth data

measured by generational cohort was used to evaluate the second research question.

Gender wealth inequality inhibits the growth of individuals, and the evolution of

societies, and disadvantages both men and women. The results of this study have

increased the body of knowledge regarding the whether the gender wealth gap will

continue to persist in the U.S. Furthering the body of knowledge on the gender wealth

76

gap in the U.S. may lead to a better understanding, and ultimately the minimization, of

the circumstances leading to women being impoverished.

77

Chapter 4: Findings

In this study, the gender wealth gap in the U.S. during the period 1992 - 2007 was

examined. The problem was that it has been unknown whether Generation X women, in

comparison to women of prior generations, are accumulating as much wealth as their

male cohorts (Fisher, 2010). Overall, women in the U.S. have lower levels of wealth and

earnings than men have (Fisher, 2010), as evidenced by women being more likely to live

in poverty (U.S. Census Bureau, 2008b) and less likely to be among the wealthy (IRS,

2009b) than their male cohorts are. The gender wealth gap has not been quantified by

prior research, and this study quantified the gender wealth gap for the study period, based

upon SCF data collected for the years 1992, 1995, 1998, 2001, 2004, and 2007. The

gender wealth gap was quantified for each survey year, in total and by generational

cohort. The trends in the gender wealth gap by generational cohort over the study period

were examined in an attempt to determine whether the gender wealth gap has improved

for Generation X women in comparison to prior generations. The results of this study

have indicated that gender wealth gap has widened overall, but has narrowed for

Generation X, over the period 1992 - 2007.

The purpose of this quantitative trend analysis study was to determine whether

Generation X women, in comparison to women of prior generations, were accumulating

as much wealth as their male cohorts. Examining the changes in the gender wealth gap in

the U.S. over the period 1992 - 2007 has provided information as to how the overall

gender wealth gap has changed as Generation Xers entered the workforce, and how the

gender wealth gap differs for Generation X than for prior generations. The narrowing of

the gender wealth gap for Generation X would indicate that the problems related to

78

wealth inequality that have plagued women of prior generations were being minimized

for Generation X. In contrast, the overall widening of the gender wealth gap would

indicate that the problems related to financial inequality, such as higher levels of poverty

and lower levels of wealth for women than men, were worsening, especially for

generations prior to Generation X. This quantitative trend analysis study has furthered

the body of knowledge on the gender wealth gap and has brought awareness to challenges

that still exist to obtain financial equity among the genders.

The following questions have guided the quantitative trend analysis study to

determine whether Generation X women, in comparison to women of prior generations,

are accumulating as much wealth as their male cohorts. The gender wealth gap was

measured based upon net worth statistics of unmarried men and women in the U.S., as

reported in the SCF over the period 1992 - 2007.

Q l : To what extent has the gender wealth gap changed during the period 1992 -

2007 in the U.S.?

Q2: How does the gender wealth gap in the U.S. differ by generational cohort

during the period 1992 - 2007?

The following null and alternative hypotheses were associated with the two

research questions.

Hlo. There is no significant change observed in the gender wealth gap from 1992

until 2007.

H l a . There is a significant change observed in the gender wealth gap from 1992

until 2007.

79

H20. There are no significant differences between the trends in the gender wealth

gap observed for Generation X and the gender wealth gap observed for prior

generations for the period 1992 - 2007.

H2a. There are significant differences between the trends in the gender wealth

gap observed for Generation X and the gender wealth gap observed for prior

generations for the period 1992 - 2007.

In this chapter, the findings of the study are presented. The mean and median net

worth statistics for unmarried male and female respondents to the SCF over the period

1992 - 2007 have been calculated, and the gender wealth gap quantified. The

respondents were classified by generational cohort, and the gender wealth gap measured,

by generation, for each survey year. The trends in the gender wealth gap, by generational

cohort, were identified and compared. The results of this study, as well as an evaluation

of the findings, are presented in this chapter.

Results

Data from the SCF for the years 1992, 1995, 1998, 2001, 2004, and 2007, were

accessed and analyzed. The Federal Reserve Board makes data from the SCF available

to the public on their website. All respondents to the SCF were classified based upon

their marital status. The responses were isolated for participants that indicated that their

marital status was unmarried and that they did not cohabitate and combine financial

resources. The unmarried respondents to the SCF were categorized by sex for analysis

purposes. Table 2 shows the total SCF respondents and the number of unmarried SCF

respondents, in total and categorized by sex, for each survey year in the study period.

80

Only respondents that participated in the SCF and were not excluded from the public data

sets are shown in Table 2.

Table 2

Number of Unmarried Respondents to the Survey of Consumer Finances, by Sex and Year

Survey Year 1992 1995 1998 2001 2004 2007

Totals

Total Respondents

3,906 4,299 4,305 4,442 4,519 4,418

25,889

Total Unmarried

Respondents 1,339 1,405 1,493 1,472 1,533 1,434 8,676

Total Unmarried

Male Respondents

518 518 578 552 586 544

3,296

Total Unmarried

Female Respondent:

821 887 915 920 947 890

5,380

The net worth of each respondent was presented in the summary data for the SCF.

The survey participants did not self-report net worth. NORC has calculated respondent

net worth, based upon data that was self-reported by the respondents, and published this

measure as part of the summary SCF data. Net worth was measured as the difference

between the value of the assets owned by the respondents and their liabilities owed. The

calculation of net worth was based upon the reported assets and liabilities of the

respondents.

An examination of the gender wealth gap in the U.S. over the study period, 1992

through 2007, was necessary in order to address each of the research questions that

guided this study. To evaluate the existence of the gender wealth gap, the median and

mean net worth values for respondents, by sex, for each survey year, were calculated.

81

Tables 3 and 4 show the median and mean net worth values, by survey year, for three

groups: all unmarried SCF respondents in total, all unmarried male SCF respondents, and

all unmarried female SCF respondents.

Table 3

Median Net Worth Statistics for Respondents to the Survey of Consumer Finances, by

Year

1992

1995

1998

2001

2004

2007

All Respondents

118,690

131,000

153,900

191,115

214,200

303,870

Unmarried Respondents

33,101

37,340

32,390

39,800

41,150

63,100

Unmarried Male

Respondents

41,400

56,000

42,725

72,930

72,308

98,900

Unmarried Female

Respondents

27,750

31,080

28,210

27,150

28,370

52,295

The median net worth statistics, shown in Table 3, are substantially lower than the

mean net worth statistics, shown in Table 4, but are more representative of the general

population. In all survey years within the study period, the median net worth of

unmarried male respondents exceeded the mean net worth of unmarried female

respondents.

Table 4

Mean Net Worth Statistics for Respondents to the Survey of Consumer Finances, by Year

Unmarried Unmarried Unmarried Male Female

All Respondents Respondents Respondents Respondents

82

1992

1995

1998

2001

2004

2007

4,269,150

4,460,864

5,543,218

6,889,356

9,564,376

12,220,241

1,710,330

1,462,334

2,311,786

1,956,170

2,740,616

3,531,184

2,703,209

2,700,783

4,291,065

4,061,688

4,359,245

7,333,410

1,083,885

739,090

1,061,487

692,859

1,739,015

1,207,127

The mean net worth statistics, shown in Table 4, are substantially higher than the

median net worth statistics shown in Table 3, as they are greatly affected by high net

worth values of the top few participants. Like the median net worth statistics, the mean

net worth statistics show that the mean net worth for unmarried male respondents exceed

the mean net worth of unmarried female respondents for each of the survey years in the

study period. Based upon the data in Tables 3 and 4, the average net worth of male

respondents exceeded the average net worth of female respondents for each survey year

in the study period.

Median and mean net worth statistics provide a basis for analysis of the gender

wealth gap. Additional measures of net worth provide further insight into the dispersion

of wealth over the groups of unmarried male respondents and unmarried female

respondents. The 10th percentile, 25th percentile, median, 75l percentile, and 90th

percentile values of unmarried male respondents' net worth are shown in Table 5, and the

same measures for unmarried female respondents' net worth are shown in Table 6.

Table 5

Net Worth Statistics for Unmarried Male Respondents to the Survey of Consumer

Finances, by Year

83

1992

1995

1998

2001

2004

2007

P10

-

125

(25)

-

-

-

P25

4,740

7,800

4,700

6,740

8,700

9,790

Median

41,400

56,000

42,725

72,930

72,308

98,900

P75

281,700

305,300

309,200

386,000

459,400

655,500

P90

2,724,400

3,392,200

2,949,515

5,374,650

3,062,950

5,662,000

All of the net worth statistics for unmarried male respondents shown in Table 5

exceed the net worth values for unmarried female respondents, as shown in Table 6.

These additional net worth statistics, at the 10th percentile, 25th percentile, 75th percentile,

and 90th percentile of each group, support the assertion that the net worth of unmarried

male respondents exceeds the net worth of unmarried female respondents, as found

through examining the median and mean net worth values.

Table 6

Net Worth Statistics for Unmarried Female Respondents to the Survey of Consumer

Finances, by Year

1992

1995

1998

2001

2004

2007

P10

-

(300)

(400)

(150)

(1,500)

(1,099)

P25

1,800

2,300

1,400

1,810

1,650

3,115

Median

27,750

31,080

28,210

27,150

28,370

52,295

P75

119,070

129,100

128,400

146,900

148,200

285,000

P90

470,300

142,150

442,500

146,900

635,000

932,725

84

Although the median, mean, and percentile net worth values show that the net

worth of unmarried male respondents exceed the net worth of unmarried female

respondents, the hypothesis that the net worth values of the two independent groups are

not the same must be confirmed statistically. If the net worth values of the unmarried

male respondents and the unmarried female respondents were the same, there would be

no gender wealth gap. In order to establish that the gender wealth gap (W) existed

throughout the study period, a comparison of the net worth data for the unmarried male

and unmarried female respondents was undertaken.

To test for the equality of median net worth values of the independent groups,

unmarried male respondents and unmarried female respondents, Mann-Whitney U tests

were conducted. For each survey year in the study period, 1992, 1995, 1998, 2001, 2004,

and 2007, the statistical output of the Mann-Whitney [/tests were consistent. The null

hypothesis that the distribution of net worth values were the same for the independent

groups, unmarried male respondents and unmarried female respondents, was rejected, at

the significance level of less than .001, for each survey year in the study period. The null

hypothesis that the median net worth values were the same for the two independent

groups, unmarried male respondents and unmarried female respondents, was rejected, at

the significance level of less than .001, for each survey year in the study period. The

relevant statistical data from the Mann-Whitney [/tests are shown in Table 7.

85

Table 7

Mann-Whitney U Test Results Comparing Median Net Worth of Unmarried Male

Respondents and Unmarried Female Respondents, by Year

1992 1995 1998 2001 2004 2007

Independent Samples Mann-Whitney [/Test

Significance .000 .000 .000 .000 .000 .000

Independent Samples Median Test

Significance .000 .000 .000 .000 .000 .000

To test for the equality of means of the independent groups, unmarried male

respondents and unmarried female respondents, regression analysis and one-way

ANOVA tests were conducted for each survey year in the study period. Like the Mann-

Whitney U tests, the ANOVA confirmed that the net worth of the two groups, unmarried

male respondents and unmarried female respondents, were not statistically the same.

Based upon the statistical tests conducted, the net worth of unmarried male respondents

was not statistically the same as the net worth of unmarried female respondents at a

significance level of less than .001, for all survey years in the study period, indicating that

a gender wealth gap existed throughout the study period, 1992 - 2007. The relevant

regression results are shown in Table 8.

Table 8

Regression Results Comparing Mean Net Worth of Unmarried Male Respondents and

Unmarried Female Respondents, by Year

86

Summary Statistics ANOVA Coefficients

Survey Standard Error Year R2 of the Estimate df_ F t p_

1992 1995 1998 2001 2004 2007

0.004 0.009 0.008 0.015 0.004 0.013

12014608.552 10108942.240 17523506.698 ] 13231519.370 19414886.901 1 25742217.869 1

I 28.848 [ 61.574 1 60.16

111.822 L 32.967 [ 95.612

-5.371 -7.847 -7.756

-10.575 -5.742 -9.778

.000

.000

.000

.000

.000

.000

The gender wealth gap (W) was measured as the difference between the net worth

of unmarried male respondents (X) and the net worth of unmarried female respondents

(Y). The gender wealth gap has been expressed in dollars (W) and as a percentage of the

net worth of unmarried male respondents (W/X), by survey year, using both median and

mean net worth statistics, as is shown in Tables 9 and 10.

Table 9

Gender Wealth Gap, based upon Median Net Worth for Respondents to the Survey of

Consumer Finances, by Year

1992

1995

1998

2001

2004

2007

Median Net Worth,

Unmarried Male Respondents (X)

41,400

56,000

42,725

72,930

72,308

98,900

Median Net Worth,

Unmarried Female

Respondents (Y)

27,750

31,080

28,210

27,150

28,370

52,295

Gender Wealth Gap (W),

measured based upon Median Net

Worth (X-Y=W)

13,650

24,920

14,515

45,780

43,938

46,605

Gender Wealth Gap

percentage, based upon Median Net Worth (W/X)

32.97%

44.50%

33.97%

62.77%

60.76%

47.12%

87

The gender wealth gap (W), as well as the gender wealth gap percentage (W/X),

for each survey year in the study period are all positive numbers, indicating that median

net worth amounts for unmarried male respondents were higher than the median net

worth amounts for unmarried female respondents, as shown in Table 9. When the gender

wealth gap (W) and gender wealth gap percentage (W/X) are measured based upon mean

net worth amounts, as shown in Table 10, the mean net worth of unmarried male

respondents exceeded the mean net worth of unmarried female respondents in each of the

survey years in the study period. Therefore, the results are consistent regardless of

measure of central tendency: the average net worth of unmarried male respondents

exceeds the average net worth of female respondents for each survey year in the study

period.

Table 10

Gender Wealth Gap, based upon Mean Net Worth for Respondents to the Survey of

Consumer Finances, by Year

1992

1995

1998

2001

2004

Mean Net Worth, Unmarried Male Respondents (X)

2,703,209

2,700,783

4,291,065

4,061,688

4,359,245

Mean Net Worth, Unmarried

Female Respondents (Y)

1,083,885

739,090

1,061,487

692,859

1,739,015

Gender Wealth Gap (W),

measured based upon Mean Net

Worth (X-Y=W)

1,619,324

1,961,693

3,229,579

3,368,829

2,620,231

Gender Wealth Gap

percentage, based upon Mean Net

Worth (W/X)

59.90%

72.63%

75.26%

82.94%

60.11%

88

2007 7,333,410 1,207,127 6,126,283 83.54%

The first research question asked, "To what extent has the gender wealth gap

changed during the period 1992 - 2007 in the U.S.?" Since it had been established that

the gender wealth gap existed throughout the study period, the evaluation of the extent to

which the gender wealth gap has changed in the U.S. during the study period was

undergone. The gender wealth gap, as measured by both median and mean net worth

statistics, was plotted by survey year for study period, as shown in Figures 2 and 3.

Gender Wealth Gap (Median)

60,000

50,000

O 40,000

Z 30,000 c ro

"8 20,000

10,000

1992 1995 1998 2001 2004 2007

Figure 2. Gender wealth gap for the U.S. during the period 1992-2007, measured by

median net worth statistics.

The line of the gender wealth gap based upon median net worth statistics, as

shown in Figure 2, shows a general upward trend with a slight dip in 2004, and a more

significant valley in 1998. In comparison, the line of the gender wealth gap based upon

89

mean net worth statistics, as shown in Figure 3, shows a general upward trend, with a

slight dip in 2004.

Gender Wealth Gap (Mean)

7,000,000

6,000,000

x : 5,000,000 •c o 5 4,000,000 a> z c 3,000,000

0)

^ 2,000,000

1,000,000

1992 1995 1998 2001 2004 2007

Figure 3. Gender wealth gap for the U.S. during the period 1992-2007, measured by

mean net worth statistics.

The trend lines for the gender wealth gaps based upon median and mean net worth

statistics were calculated using linear regression. Using the median net worth statistics,

the trend line for the gender wealth gap (W) was expressed as follows:

y = 7,231.2x +6,528.7

The dependent variable (x) represents the sequence of survey years covered by the study,

where 1992=1, 1995=2, 1998=3, 2001=4, 2004=5, and 2007=6. The independent

variable (y) represents the gender wealth gap (W). The R statistic for the trend line of the

gender wealth gap was 0.740, indicating that 74.0% of the variability in the gender

wealth gap, as measured using median net worth statistics, was explained by time, and

90

the remaining 26.0% must be explained by other factors. Additional regression output

for the trend in the gender wealth gap, as measured using median net worth statistics, is

shown in Table 12.

Using the mean net worth statistics, the trend line that best represented the gender

wealth gap (W) has been expressed as follows:

y = 704,27 6x + 689,357

The dependent variable (x) represents the sequence of survey years covered by the study,

where 1992=1, 1995=2, 1998=3, 2001=4, 2004=5, and 2007=6. The independent

variable (y) represents the gender wealth gap (W). The goodness of fit of the line was

tested by calculating the coefficient of determination, R . The R value for the trend line

of the gender wealth gap was 0.670, indicating that 67.0% of the variability in the gender

wealth gap, as measured using mean net worth statistics, was explained by time, and the

remaining 33.0% must be explained by other factors. Additional regression output for

the trend in the gender wealth gap, as measured using mean net worth statistics, is shown

in Table 12.

The trends in the gender wealth gap (W) calculated by using median and mean net

worth statistics for unmarried male respondents (X) and unmarried female respondents

(Y) were different, but both trend lines had a positive slope. The positive slopes in the

trend lines indicate an increase in the gender wealth gap over the study period. Some of

the increase in the gender wealth gap may be due to inflation over the study period. As

such, the effects of inflation must be eliminated to assess whether the gender wealth gap,

expressed in 1992 dollars, changed over the study period.

91

To eliminate the effects of inflation on the gender wealth gap, the average annual

Consumer Price Index (CPI) for All Urban Consumers was accessed through the Bureau

of Labor Statistics (BLS) website for each of the survey years in the study period.

According to the BLS (2011), the CPI was 140.3 for 1992, 152.4 for 1995, 163 for 1998,

177.1 for 2001, 188.9 for 2004, and 207.3 for 2007, with a base year (100) of 1982

(Bureau of Labor Statistics, 2011). The median and mean gender wealth gap (W)

measures were adjusted to 1992 dollars to eliminate the effects of inflation, and the

adjusted values are shown in Table 11.

Table 11

Gender Wealth Gap, Adjusted for Inflation, by Year

1992 1995 1998 2001 2004 2007

CPI (base year 1982)

140.3 152.4 163.0 177.1 188.9 207.3

CPI (base year 1992)

100.0 108.6 116.2 126.2 134.6 147.8

Adjusted Gender Wealth Gap (Wadj),

measured based upon Median Net

Worth

13,650 22,941 12,494 36,267 32,634 31,542

Adjusted Gender Wealth Gap (Wad/).

measured based upon Mean Net

Worth

1,619,324 1,805,942 2,779,816 2,668,813 1,946,101 4,146,249

Upon examination of the adjusted gender wealth gap measures, it is apparent that

the increase in the gender wealth gap is not as substantial using numbers adjusted for

inflation as it is when the effects of inflation are included in the analysis. The trends in

the gender wealth gap, adjusted for inflation, were tested for significance and relevant

regression results included in Table 12.

92

To further examine the trends in the gender wealth gap, the gap has been

expressed as a percentage of male net worth (W/X). Expressing the gender wealth gap as

a percentage of net worth minimizes the effects of inflation from the analysis, since the

focus is not on the dollar difference between the net worth of the genders, but rather on

the relationship between the wealth gap and male net worth.

The gender wealth gap percentage (W/X), based on both median and mean net

worth values, increased over the study period. The positive slopes of the trend lines for

the gender wealth gap percentage (W/X) based upon median and mean net worth values,

respectively, are 0.0424 and 0.0252, indicating an increase in the gender wealth gap. The

trend lines for the gender wealth gap, based upon median and mean net worth statistics,

were calculated using linear regression. Using the median net worth statistics, the trend

line for the gender wealth gap percentage (W/X) was expressed as follows:

y = 0.0424x + .3218

The dependent variable (x) represents the sequence of survey years covered by the study,

where 1992=1, 1995=2, 1998=3, 2001=4, 2004=5, and 2007=6. The independent

variable (y) represents the gender wealth gap percentage (W/X). The R2 statistic for the

trend line of the gender wealth gap percentage was 0.388, indicating that 38.8% of the

variability in the gender wealth gap, as measured using median net worth statistics, was

explained by time, and the remaining 61.2% must be explained by other factors.

Additional regression output for the gender wealth gap percentage, as measured using

median net worth statistics, is shown in Table 12.

Using the mean net worth statistics, the trend line for the gender wealth gap

percentage (W/X) was expressed as follows:

93

y = 0.0252x + .6356

The dependent variable (x) represents the sequence of survey years covered by the study,

where 1992=1, 1995=2, 1998=3, 2001=4, 2004=5, and 2007=6. The independent

variable (y) represents the gender wealth gap percentage (W/X). The R2 statistic for the

trend line of the gender wealth gap percentage was 0.202, indicating that 20.2% of the

variability in the gender wealth gap, as measured using median net worth statistics, was

explained by time, and the remaining 79.8% must be explained by other factors.

Additional regression output for the gender wealth gap percentage, as measured using

mean net worth statistics, is shown in Table 12.

Table 12

Regression Output for the Trend in the Gender Wealth Gap, using Multiple Measures

Trend Measure

W, Median

W, Mean

W/X, Median

W/X, Mean

Wadj, Median

Wad,; Mean

Summary Statistics

R2

0.740

0.670

0.388

0.202

0.559

0.546

Standard Error of the Estimate df

8973.165 ]

1032954.957 ]

0.1114231 ]

.1047954 1

7551.84635 1

704855.37380 ]

ANOVA

F

[ 11.365

I 8.135

[ 2.532

L 1.015

L 5.073

4.818

Coefficients

t

3.371

2.852

1.591

1.007

2.252

2.195

P .028

.046

.187

.371

.087

.093

The six measures of the gender wealth gap calculated are the gender wealth gap

based upon median and mean net worth, gender wealth gap percentage based upon

median and mean net worth, and gender wealth gap based upon median and mean net

worth adjusted for inflation. All six measures of the gender wealth gap indicate that the

94

gender wealth gap has increased in the U.S. over the study period 1992 - 2007, but not all

six measures increased with statistical significance.

When evaluating the null hypothesis HI0, "There is no significant change

observed in the gender wealth gap from 1992 until 2007", the trends in the gender wealth

gap, as measured based upon median net worth data and mean net worth data, were both

examined and tested using regression analysis. The/?-values for the trend in the gender

wealth gap, based upon median net worth values and mean net worth values, respectively,

are .028 and .046, indicating that the change is significant at less than the .05 significance

level, indicating that the null hypothesis should be rejected. However, when adjusted for

inflation, the/>-values for the trend in the gender wealth gap, based upon median net

worth values and mean net worth values, respectively, are .087 and .093, indicating that

the change is significant at less than the .10 significance level. Therefore, at the .05

significance level, the null hypothesis should not be rejected.

The trends in the gender wealth gap percentages, like the trends in the adjusted

gender wealth gap, show changes that are not statistically significant at less than the .05

level. The/(-values for the trends in the gender wealth gap percentages (W/X), based

upon median and mean net worth values, respectively, are .187 and .371, indicating that

the changes in the gender wealth gap expressed as a percentage of male net worth are not

significant at the .05 level. The regression analysis of the gender wealth gap percentages

support the contention that the null hypothesis HIQ, "There is no significant change

observed in the gender wealth gap from 1992 until 2007", should not be rejected. It is

concluded that the change observed in the gender wealth gap over the study period is not

statistically significant, at a=.05, when adjusted for inflation.

95

The second research question asked, "How does the gender wealth gap in the U.S.

differ by generational cohort during the period 1992 - 2007?" In order to assess the

second research question, the respondents were categorized into generational cohorts

based upon birth year. The four generations examined as part of this study were the

Traditionalists, Baby Boomers, Generation X, and Generation Y. Various sources

identify different ranges of birth years associated with each generation, so for the

purposes of this study, the range of birth years used to identify each generation were as

follows: Traditionalists, 1908-1945; Baby Boomers, 1946-1961; Generation X, 1962-

1977; and Generation Y, 1978-1984.

Some respondents were eliminated from the generational analyses that were

included in the original study data. Respondents born prior to 1908 have been eliminated

from the analysis. There were 46 respondents excluded from the 1992 data set for the

analysis by generational cohort for being bom in 1907 or prior, 23 respondents excluded

from the 1995 data set, 15 respondents excluded from the 1998 data set, and six

respondents excluded from the 2001 data set. There were no respondents bom in 1907 or

prior that responded to the SCF in 2004 or 2007. NORC weighted the SCF responses to

be representative of the population of U.S. taxpayers. The weighting of the SCF data was

computed in five ways, so that each respondent was represented five times in the data

sets. A small number of respondents had their reported ages modified as part of the

weighting process; if this age modification affected the respondent's inclusion in a

generational cohort, the respondent was eliminated from the study. There were five

participants eliminated from the 2001 data set (participants #2081, #2461, #2663, #2868,

and #4161), and four participants eliminated from the 2004 data set (participants #971,

96

#1258, #1656, and #3077). The numbers of unmarried respondents that were assigned to

each generational cohort after these eliminations, by survey year, are shown in Table 13.

Table 13

Total Number of Unmarried Respondents, by Generational Cohort, by Year

Traditionalists Baby Boomers Generation Xers Generation Yers

1992

1995

1998

2001

2004

2007

647 587

604

511

473

433

411 450

448

479

499

439

235 343

387

397

401

367

- 2

39

74

156

195

Within each generational cohort, groups of unmarried male and unmarried female

respondents were identified. The numbers of unmarried male and female respondents

that were assigned to each generational cohort, by survey year, are shown in Table 14.

Table 14

Number of Male and Female Unmarried Respondents, by Generational Cohort, by Year

Traditionalists Baby Boomers Generation Xers Generation Yers

Male Female Male Female Male Female Male Female

1992

1995

1998

2001

2004

2007

212 183

189

179

159

126

435 404

415

332

314

307

183 169

199

181

188

184

228 281

249

298

311

255

111

158

167

157

166

151

124 185

220

240

235

216

0 1

19

31

72

83

0 1

20

43

84

112

In order to evaluate whether the gender wealth gap differs by generational cohort,

the mean and median net worth values for respondents by generational cohort were

97

calculated for each survey year. Tables 15 through 22 show the median and mean net

worth values for unmarried male and female respondents, by generational cohort, for

each survey year.

Table 15

Gender Wealth Gap, based upon Median Net Worth, Traditionalist Generation

1992

1995

1998

2001

2004

2007

Median Net Worth,

Unmarried Male Respondents (X)

187,500

305,300

267,000

247,800

337,950

608,400

Median Net Worth,

Unmarried Female

Respondents (Y)

67,842

89,415

96,800

97,290

107,350

177,200

Gender Wealth Gap (W),

measured based upon Median Net

Worth (X- Y= W)

119,658

215,885

170,200

150,510

230,600

431,200

Gender Wealth Gap

percentage, based upon Median Net Worth (W/X)

63.82%

70.71%

63.75%

60.74%

68.23%

70.87%

The gender wealth gap (W) based upon median net worth statistics for the

Traditionalist generational cohort, as shown in Table 15, was positive for each survey

year in the study period, indicating that median net worth of unmarried male respondents

exceeded the median net worth of female respondents in each survey year of the study

period for this generation. The gender wealth gap percentages (W/X) for the

Traditionalists were moderately high, ranging from 60.74% to 70.87% for the study

period.

98

Table 16

Gender Wealth Gap, based upon Mean Net Worth, Baby Boomer Generation

1992

1995

1998

2001

2004

2007

Median Net Worth,

Unmarried Male Respondents (X)

31,300

50,220

66,900

105,600

130,250

247,610

Median Net Worth,

Unmarried Female

Respondents (Y)

11,595

21,120

26,500

36,800

41,140

89,000

Gender Wealth Gap (W),

measured based upon Median Net

Worth (X- Y= W)

19,705

29,100

40,400

68,800

89,110

158,610

Gender Wealth Gap

percentage, based upon Median Net Worth (W/X)

62.96%

57.95%

60.39%

65.15%

68.41%

64.06%

The gender wealth gap (W) based upon median net worth statistics for the

Traditionalist generational cohort, as shown in Table 16, was positive for each survey

year in the study period, indicating that median net worth of unmarried male respondents

exceeded the median net worth of female respondents in each survey year of the study

period for this generation. The gender wealth gap percentages (W/X) for the Baby

Boomers were moderately high, ranging from 57.95% to 68.41% for the study period.

Table 17

Gender Wealth Gap, based upon Median Net Worth, Generation X

Generation X

99

1992

1995

1998

2001

2004

2007

Median Net Worth,

Unmarried Male Respondents (X)

7,300

8,890

6,700

12,000

27,190

32,320

Median Net Worth,

Unmarried Female

Respondents (Y)

800

2,930

1,400

2,960

5,710

13,345

Gender Wealth Gap (WO,

measured based upon Median Net

Worth (X- Y= W)

6,500

5,960

5,300

9,040

21,480

18,975

Gender Wealth Gap

percentage, based upon Median Net Worth (W/X)

89.04%

67.04%

79.10%

75.33%

79.00%

58.71%

The gender wealth gap (W) based upon median net worth statistics for Generation

X generational cohort, as shown in Table 17, was positive for each survey year in the

study period, indicating that median net worth of unmarried male respondents exceeded

the median net worth of female respondents in each survey year of the study period for

this generation. The gender wealth gap percentages (W/X) for the Generation X were

high, ranging from 58.71%) to 89.04% for the study period.

Table 18

Gender Wealth Gap, based upon Median Net Worth, Generation Y

1992

Median Net Worth,

Unmarried Male Respondents (X)

n/a

Generation Y

Median Net Worth,

Unmarried Female

Respondents (Y)

n/a

Gender Wealth Gap(ff),

measured based upon Median Net

Worth (X- 7 = W)

n/a

Gender Wealth Gap percentage, based upon Median Net Worth (W/X)

n/a

1995 125,330 101 125,229 99.92%

1998 -115.80%

100

2001

2004

2007

3,200

2,700

4,380

7,720

6,906

870

80

725

(3,706)

1,830

4,300

6,995

67.78%

98.17%

90.61%

The gender wealth gap (W) based upon mean net worth statistics for Generation Y

generational cohort, as shown in Table 18, was positive for four of the five survey years

in the study period that had Generation Y participants. The median net worth of

unmarried male respondents exceeded the median net worth of female respondents in

most survey years of the study period for Generation Y. The gender wealth gap

percentages (W/X) for Generation Y were varied, with one negative percentage and three

extremely high percentages, ranging from 90.61% to 99.92% for the study period.

Table 19

Gender Wealth Gap, based upon Mean Net Worth, Traditionalist Generation

1992

1995

1998

2001

2004

2007

Mean Net Worth, Unmarried Male Respondents (X)

4,631,987

6,344,033

11,289,710

8,166,937

11,569,444

18,837,970

Traditionalists

Mean Net Worth, Unmarried

Female Respondents (Y)

1,377,179

1,316,526

1,539,436

1,477,421

2,142,204

2,267,289

Gender Wealth G a p W ,

measured based upon Mean Net

Worth (X- Y= W)

3,254,808

5,027,508

9,750,274

6,689,516

9,427,240

16,570,681

Gender Wealth Gap

percentage, based upon Mean Net

Worth (W/X)

70.27%

79.25%

86.36%

81.91%

81.48%

87.96%

101

The gender wealth gap (W) based upon mean net worth statistics for the

Traditionalist generational cohort, as shown in Table 19, was positive for each survey

year in the study period, indicating that mean net worth of unmarried male respondents

exceeded the mean net worth of female respondents in each survey year of the study

period for this generation. The gender wealth gap percentages ( W/X) for the

Traditionalists were high, ranging from 70.27% to 87.96% for the study period.

Table 20

Gender Wealth Gap, based upon Mean Net Worth, Baby Boomer Generation

Baby Boomers

1992

1995

1998

2001

2004

2007

Mean Net Worth, Unmarried Male Respondents (A7)

739,789

1,019,883

899,956

3,890,948

3,607,526

7,452,799

Mean Net Worth, Unmarried

Female Respondents (Y)

517,636

120,502

1,304,437

457,469

2,911,588

1,268,445

Gender Wealth Gap(W),

measured based upon Mean Net

Worth (X- 7 = W)

222,153

899,381

(404,481)

3,433,479

695,938

6,184,355

Gender Wealth Gap percentage, based upon Mean Net

Worth (W/X)

30.03%

88.18%

-44.94%

88.24%

19.29%

82.98%

The gender wealth gap (W) based upon mean net worth statistics for the Baby

Boomer generational cohort, as shown in Table 20, was positive for each survey year

except for 1998, indicating that mean net worth of unmarried male respondents exceeded

the mean net worth of female respondents in most survey years of the study period for

102

this generation. In 1998, the mean net worth of unmarried female Baby Boomers

exceeded the mean net worth of unmarried male Baby Boomers. The gender wealth gap

percentages (W/X) based on mean net worth statistics for the Baby Boomers had a broad

range, from -44.94% to 88.24% for the study period.

Table 21

Gender Wealth Gap, based upon Mean Net Worth, Generation X

1992

1995

1998

2001

2004

2007

Mean Net Worth, Unmarried Male Respondents (X)

2,017,771

180,525

827,833

218,960

211,121

1,596,907

Mean Net Worth, Unmarried

Female Respondents (7)

52,164

16,009

16,134

41,287

283,162

183,610

Gender Wealth Gap (W),

measured based upon Mean Net

Worth (X- 7 = W)

1,965,607

164,517

811,698

177,673

(72,042)

1,413,297

Gender Wealth Gap percentage, based upon Mean Net

Worth (W/X)

97.41%

91.13%

98.05%

81.14%

-34.12%

88.50%

The gender wealth gap (W) based upon mean net worth statistics for the

Generation X, as shown in Table 21, was positive for each survey year in the study period

except for 2004, indicating that mean net worth of unmarried male respondents exceeded

the mean net worth of female respondents for most survey years of the study period. In

2004, the mean net worth value for unmarried female respondents exceeded the mean net

worth value of male respondents. The gender wealth gap percentages (W/X) for

103

Generation X were extremely high for all survey years except 2004, ranging from

81.14% to 98.05%.

Table 22

Gender Wealth Gap, based upon Mean Net Worth, Generation Y

1992

1995

1998

2001

2004

2007

Mean Net Worth, Unmarried Male Respondents (X)

n/a

123,530

20,331

440,880

23,375

40,277

Mean Net Worth, Unmarried

Female Respondents (7)

n/a

101

45,039

8,748

13,513

135,467

Gender Wealth Gap (W),

measured based upon Mean Net

Worth (X- Y= W)

n/a

123,429

(24,708)

432,132

9,861

(95,191)

Gender Wealth Gap percentage, based upon Mean Net

Worth (W/X)

n/a

99.92%

-121.53%

98.02%

42.19%

-236.34%

The gender wealth gap (W) based upon mean net worth statistics for the

Generation Y generational cohort, as shown in Table 22, is extremely varied throughout

the study period. There are three of the five survey years that Generation Y members

participated in the SCF that have positive gender wealth gap (W) values, indicating that

the mean net worth of unmarried male respondents exceeded the mean net worth of

female respondents in most survey years of the study period for this generation. The

gender wealth gap percentages (W/X) for Generation Y were widely varying, ranging

from -236.34% to 99.92% for the study period. It is important to note that for several of

the survey years included in the study, the sample size for Generation Y was very small:

104

there were two respondents in 1995, 39 respondents in 1998, 74 respondents in 2001, and

156 respondents in 2004 that were members of Generation Y. A power analysis

indicated that a sample size of 176 was necessary to achieve a=0.05, so the only survey

year that the Generation Y data can be considered significant is 2007, with a sample size

of 196 respondents. As such, Generation Y has been excluded from the generational

analysis.

The trend in the gender wealth gap for Generation X has been compared to the

trend in the gender wealth gap for the two prior generational cohorts, the Traditionalists

and the Baby Boomers. The trends in the gender wealth gap by generational cohort,

based upon median net worth and mean net worth amounts, respectively, are shown in

Figures 4 and 5.

Gender Wealth Gap (Median), by Generational Cohort

1992 1995 1998 2001 2004 2007

Traditionalists «•"•>•• Baby Boomers "> J-W» Generation X

Figure 4. Trend for the gender wealth gap for the U.S. during the period 1992-2007,

measured by median net worth statistics, by generational cohort.

105

The gender wealth gap based upon median net worth statistics, as shown in Figure

4, shows that each generational cohort has a larger gender wealth gap than the

generations that follow, as was expected. The gender wealth gap based upon mean net

worth statistics, as shown in Figure 5, indicates that there is some overlapping between

generational cohorts. The gender wealth gap based upon mean net worth of unmarried

Generation Xers exceeds the gender wealth gap based upon mean net worth of unmarried

Baby Boomers in survey years 1992 and 1998.

Gender Wealth Gap (Mean), by Generational Cohort

—•—Traditionalists «4fr- Baby Boomers •"»--»Generation X

Figure 5. Trend for the gender wealth gap for the U.S. during the period 1992-2007,

measured by mean net worth statistics, by generational cohort.

The average net worth for unmarried male respondents, average net worth for

female respondents, and gender wealth gap, by year, for each generational cohort, using

median net worth measures and mean net worth measures, were calculated and plotted, as

shown in Figures 6 through 11.

106

Gender Wealth Gap (Median), Traditionalists

Figure 6. Trend for the gender wealth gap for Traditionalists in the U.S. during the

period 1992-2007, measured by median net worth statistics.

The trend in the gender wealth gap ( W), measured using median net worth

statistics, for the Traditionalists was increasing over the study period, 1992 - 2007, as

shown in Figure 6. The slope of the trend in the median net worth of unmarried male

respondents (X) was significantly steeper than the slope of the trend in the median net

worth of unmarried female respondents (Y) for the Traditionalists over the study period.

107

Gender Wealth Gap (Mean), Traditionalists

1,000 -~

1,000

C-'X Mean

2=>Y Mean

W Mean

1992 1995 1998 2001 2004 2007

Figure 7. Trend for the gender wealth gap for Traditionalists in the U.S. during the

period 1992-2007, measured by mean net worth statistics.

The trend in the gender wealth gap (W), measured using mean net worth statistics,

for the Traditionalists was increasing over the study period, 1992 - 2007, as shown in

Figure 7. The slope of the trend in the mean net worth of unmarried male respondents

(X) was significantly steeper than the slope of the trend in the mean net worth of

unmarried female respondents (Y) for the Traditionalists over the study period.

108

Gender Wealth Gap (Median), Baby Boomers 300,000 r — —

CD . c "TO <D

5 CD

T3 C

CD

250,000

200,000

150,000

100,000

50,000

1992 1995 1998 2001 2004 2007

—̂ 4— X Median

•«•#-> Y Median

—•—W Median

Figure 8. Trend for the gender wealth gap for Baby Boomers in the U.S. during the

period 1992-2007, measured by median net worth statistics.

The trend in the gender wealth gap (W), measured using median net worth

statistics, for the Baby Boomers was increasing over the study period, 1992 - 2007, as

shown in Figure 8. The slope of the trend in the median net worth of unmarried male

respondents (X) was significantly steeper than the slope of the trend in the median net

worth of unmarried female respondents (Y) for the Baby Boomers over the study period.

109

Q . 03

CD

CO CD

CD

c <D

CD

Gender Wealth Gap (Mean), Baby Boomers

8,000,000

7,000,000

6,000,000

5,000,000

4,000,000

3,000,000

2,000,000

1,000,000

(1,000,000)

>X Mean

—EJ-Y Mean

•"/.. W Mean

Figure 9. Trend for the gender wealth gap for Baby Boomers in the U.S. during the

period 1992-2007, measured by mean net worth statistics.

The trend in the gender wealth gap (W), measured using mean net worth statistics,

for the Baby Boomers was increasing over the study period, 1992 - 2007, as shown in

Figure 9. The slope of the trend in the mean net worth of unmarried male respondents

(X) was significantly steeper than the slope of the trend in the mean net worth of

unmarried female respondents (Y) for the Baby Boomers over the study period.

110

Gender Wealth Gap (Median), Generation X 35,000

30,000 H

S- 25,000 CD £ 20,000 CD CD

15,000 —

-g 10,000 c CD CD 5,000

(5,000)

-X Median

~-e—Y Median

°W Median

1992 1995 1998 2001 2004 2007

Figure 10. Trend for the gender wealth gap for Generation X in the U.S. during the

period 1992-2007, measured by median net worth statistics.

The trend in the gender wealth gap (W), measured using median net worth

statistics, for Generation X was increasing over the study period, 1992 - 2007, as shown

in Figure 10. The slope of the trend in the median net worth of unmarried male

respondents (X) was steeper than the slope of the trend in the median net worth of

unmarried female respondents (Y) for Generation X over the study period.

I l l

Gender Wealth Gap (Mean), Generation X

2,500,000

2,000,000 -

CD

CD 1,500,000

(500,000)

1992 1995 1998 2001 2004 2007

Mean

Y Mean

,/""W Mean

Figure 11. Trend for the gender wealth gap for Generation X in the U.S. during the

period 1992-2007, measured by mean net worth statistics.

The trend in the gender wealth gap (W), measured using mean net worth statistics,

for Generation X was decreasing over the study period, 1992 - 2007, as shown in Figure

11. The slope of the trend in the mean net worth of unmarried male respondents (X) was

declining while the slope of the trend in the mean net worth of unmarried female

respondents (Y) was increasing for Generation X over the study period.

All of the trend lines for the gender wealth gap in U.S. over the period 1992 -

2007 by generational cohort had a positive slope, except for the trend for the gender

wealth gap measured by mean net worth values for Generation X. Although the trend for

the gender wealth gap measured by median net worth values for Generation X had a

positive slope, the declining trend in the mean net worth values may indicate that the

gender wealth gap is different for Generation X than it has been for prior generations.

Wealth accumulates over time, leading to the hypothesis that prior generations

should have higher net worth than later generations as they have had longer periods for

112

wealth to accumulate. In order to compare the gender wealth gap across generations, the

gender wealth gap cannot be expressed in dollars since each generation has had more

time for wealth to accumulate than the generations that follow. The gender wealth gap

has been expressed as a percentage of male net worth (W/X) in order to compare the

gender wealth gaps for multiple generational cohorts. The gender wealth gap expressed

as a percentage of male net worth (W/X), based upon median and mean net worth

statistics, respectively, for each generational cohort for the study period, are shown in

Figures 12 and 13.

Gender Wealth Gap Percentage (Median), by Generational Cohort

100.00% |

90.00% A

1992 1995 1998 2001 2004 2007

«—#—Traditionalists —•—Baby Boomers •-^•"•Generation X

Figure 12. Trend for the gender wealth gap percentage by generational cohort in the U.S.

during the period 1992-2007, measured by median net worth statistics.

113

Gender Wealth Gap Percentage (Mean), by Generational Cohort

—•—Traditionalists —•— Baby Boomers —ft Generation X

Figure 13. Trend for the gender wealth gap percentage by generational cohort in the U.S.

during the period 1992-2007, measured by mean net worth statistics.

The trends in the gender wealth gap percentage (W/X) that are illustrated in Figure

13 show significant valleys for Baby Boomers (1998, 2004) and Generation X (2004).

The trends in the gender wealth gap percentage (W/X) for all generational cohorts based

upon median net worth values, as shown in Figure 12, were substantially more constant

than when based upon mean net worth values.

The trend lines for the gender wealth gap were calculated using linear regression

analysis. The trend lines for the gender wealth gap for the Traditionalists and the Baby

Boomers, calculated based upon both median and mean net worth values, had positive

slopes, indicating a widening of the gender wealth gap. The trend lines for the gender

wealth gap for Generation X, calculated based upon both median and mean net worth

values, had negative slopes, indicating a narrowing of the gender wealth gap. The

114

equations for the trend lines of the gender wealth gap, expressed as a percentage of male

net worth, over the period 1992 - 2007, are shown in Table 23.

Table 23

Equations of the Trend in the Gender Wealth Gap from 1992 - 2007, by Generation

Gender Wealth Gap Percentage, Measured by Median Net Worth

Generation

Traditionalists

Baby Boomers

Generation X

Generation

Traditionalists

Baby Boomers

Generation X

The slopes of the trend lines for the gender wealth gap for each generation,

Traditionalists, Baby Boomers, and Generation X, were all different, as were the

intercepts of each of these lines. In particular, the negative slopes for the gender wealth

gap, measured by median net worth and mean net worth measures, for Generation X,

indicated that the trend in the gender wealth gap for this generation was substantially

different from the trends in the gender wealth gap for prior generations, which had

positive slopes. Since the trend lines for all three generations are equally affected by

inflation, there is no need to adjust the trends for inflation in order to determine whether

they are different. The null hypothesis H2Q, "There are no significant differences

Formula of Trend Line

y = 0.007 lx + 0.6387

y = 0.0119x + 0.5898

y = -0.0342% + 0.8666

R2

0.1005

0.3687

0.3657

centage, Measured by Mean Net Worth

Formula of Trend Line

y = 0.0259x + 0.7213

y = 0.0546x + 0.2484

y = -0.1249x + 1.1408

R2

0.5991

0.0369

0.255

115

between the trends in the gender wealth gap observed for Generation X and the gender

wealth gap observed for prior generations for the period 1992 - 2007", is rejected.

To substantiate the rejection of the null hypothesis, H2o, the gender wealth gap

expressed as a percentage of net worth of unmarried male respondents (W/X), was

examined by generational cohort. The gender wealth gap for the Traditionalists, Baby

Boomers, and Generation X, expressed as a percentage of the net worth of unmarried

male respondents (W/X), is summarized in Table 24 for median net worth data and Table

25 for mean net worth data. Generation Y data was excluded from these analyses

because of the limited sample size.

Table 24

Gender Wealth Gap, expressed as a percentage of Net Worth of Male Respondents

(W/X), based upon Median Net Worth Data

1992

1995

1998

2001

2004

2007

Average

Traditionalists

63.82%

70.71%

63.75%

60.74%

68.23%

70.87%

66.35%

Baby Boomers

62.96%

57.95%

60.39%

65.15%

68.41%

64.06%

63.15%

Generation Xers

89.04%

67.04%

79.10%

75.33%

79.00%

58.71%

74.70%

The gender wealth gap percentage (W/X) based upon median net worth values is

consistently positive, indicating that median male net worth is higher than median female

net worth for all generations for each survey year in the study period, as show in Table

24. The gender wealth gap, expressed as a percentage of net worth of male respondents

(W/X), based upon median net worth data is more consistent throughout the study period

116

than the same measured based upon mean net worth. When basing the gender wealth gap

percentage on mean net worth, there is one survey year for the Baby Boomers (1998) and

for Generation X (2004) that shows a negative wealth gap, indicating that the mean net

worth value of women is higher than the mean net worth value of men, as shown in Table

25.

Table 25

Gender Wealth Gap, expressed as a percentage of Net Worth of Male Respondents

(W/X), based upon Mean Net Worth Data

1992

1995

1998

2001

2004

2007

Average

Traditionalists

70.27%

79.25%

86.36%

81.91%

81.48%

87.96%

81.21%

Baby Boomers

30.03%

88.18%

-44.94%

88.24%

19.29%

82.98%

43.96%

Generation Xers

97.41%

91.13%

98.05%

81.14%

-34.12%

88.50%

70.35%

In two instances, the gender wealth gap (W), as measured by mean net worth

amounts, had negative values (Baby Boomers-1998, Generation X-2004), indicating that

the female mean net worth exceeded the male mean net worth. In both cases, the mean

net worth values for females were substantially inflated by the net worth of one female

respondent (1998 respondent #2192; 2004 respondent #2529); had this female respondent

been removed from the analysis, in each year, the gender wealth gap would have had a

positive value, as is shown in Table 26. The net worth for 1998 respondent #2192 ranged

from $136,374,640 to $219,403,400 under the five weighting models, and the net worth

for 2004 respondent #2529 ranged from $51,598,500 to $57,788,500 under the same five

117

weighting models. Had these two respondents not participated in the study, all measures

of the gender wealth gap would have been positive, indicating that unmarried male

respondents have a higher net worth than unmarried female respondents do.

Table 26

Gender Wealth Gap, expressed as a percentage of Net Worth of Male Respondents

(W/X), based upon Mean Net Worth Data, excluding 1998 respondent #2192 and 2004

respondent #2529

Traditionalists Baby Boomers Generation Xers 1992 1995 1998 2001 2004 2007 .verage

70.27% 79.25% 86.36% 81.91% 81.48% 87.96% 81.21%

30.03% 88.18% 33.29% 88.24% 19.29% 82.98% 57.00%

97.41% 91.13% 98.05% 81.14% 74.00% 88.50% 88.37%

Evaluation of Findings

Based upon the data analyzed, the gender wealth gap has clearly existed

throughout the study period, 1992 - 2007. The findings were consistent when measuring

the gender wealth gap based upon median net worth data and mean net worth data: the

gender wealth gap existed and, overall, was increasing throughout the study period, 1992

- 2007. The increases in the gender wealth gap observed based upon mean and median

net worth data were not steady increases, but the trend lines indicated a general widening

of the gender wealth gap in the U.S. over the study period. The first research question,

"To what extent has the gender wealth gap changed during the period 1992 - 2007 in the

U.S.?" was responded to in multiple ways. In each of the scenarios examined, the gender

118

wealth gap in the U.S. over the period 1992 - 2007 had increased, but it was not

statistically significant at the .05 level when adjusted for inflation.

The change in the gender wealth gap over the period had been measured in dollars

based upon median net worth data, as a percentage based upon median net worth data, in

dollars based upon mean net worth data, and as a percentage based upon mean net worth

data. The dollar values of the gender wealth gap (W) assessed based upon median net

worth values and mean net worth values changed by 241% and 278%, respectively, from

the beginning of the study period until the end of the study period. However, a

substantial portion of this change was due to inflation, so when tested for significance,

the change in the gender wealth gap was not considered significant at the .05 level.

When expressing the gender wealth gap, based upon median net worth data and mean net

worth data, as a percentage of the net worth of male respondents (W/X), the percentage

increase was 43% and 39%, respectively. However, due to variation in the increase over

the study period, this change was not considered significant at the .05 level. The null

hypothesis Hl0, "There is no significant change observed in the gender wealth gap from

1992 until 2007", is not rejected.

The second research question, "How does the gender wealth gap in the U.S. differ

by generational cohort during the period 1992 - 2007?" was examined through

identifying the gender wealth gap by generational cohort and analyzing the differences

between cohorts. To analyze the gender wealth gap by generational cohort, the wealth

gap was common sized to factor out differences in wealth between generations. Prior

generations have had more time for the accumulation and growth of wealth than later

generations, so the dollar values of the wealth gap were expressed as percentages in order

119

to compare the gaps of multiple generational cohorts. There was a general upward trend

in the gender wealth gap for the Traditionalists and the Baby Boomers, while there was a

general downward trend in the gender wealth gap for Generation X for the period 1992 -

2007. Although the overall gender wealth gap in the U.S. had increased, over the study

period, the gender wealth gap for Generation X had narrowed. The null hypothesis H20,

"There are no significant differences between the trends in the gender wealth gap

observed for Generation X and the gender wealth gap observed for prior generations for

the period 1992 - 2007", is rejected.

This study was predicated on human capital theory, the gender model of income

determination, and generational theory. The human capital theory proposes that

expenditures on education, training, and health are all investments in human capital

(Becker, 2008). Education is a factor that decreases the likelihood of poverty (Steinsultz,

2006), so as more women increase their education, fewer women should live in poverty.

The recent changes in the gender education gap should have resulted in changes in the

gender wealth gap. Generation X women have a greater likelihood of pursuing higher

education than women of prior generations (Bobbitt-Zeher, 2007). Generation X, a

generation that is substantially less affected by the gender education gap than prior

generations, is increasingly less affected by a gender wealth gap, confirming human

capital theory.

Although the gender wealth gap has narrowed for Generation X, it still clearly

existed throughout the study period. One explanation for the persistence of the gender

wealth gap in the U.S. across generations may be the gender model of income

determination. The gender model of income determination indicates that women may

choose lower paying jobs than their male counterparts due to discrimination and gendered

socialization (DuPuis, 2006). Further studies relating occupation to the gender wealth

gap may indicate whether the choice of occupation has a significant affect upon the

wealth accumulation of women.

Generational theory indicates that predictions of cohort belief and behavior are

based upon generational categorization (Asaro-Gonzalez, 2006). The characteristics of

Generation X are quite different from prior generations with relation to attitudes toward

work and family roles. Generation X women are more likely to delay marriage and

childrearing than women of prior generations, and often remain in the workforce after

having children (Steinsultz, 2006). The generational characteristics of Generation X

predict a narrowing of the gender earnings gap, and ultimately a narrowing of the gender

wealth gap for this generational cohort, as has been observed through this study.

The results of this study are consistent with many other studies (Isaacs, 2010;

Steinsultz, 2006), and expand upon prior findings. Isaacs (2010) hypothesized that

generational characteristics should affect wealth accumulation, as has been confirmed by

this study. Steinsultz (2006) and Yang (2006) both found that wealth increases with age;

this study confirms that hypothesis by identifying that mean and median net worth values

are higher for prior generations than for Generation X. Bobbitt-Zeher (2007) identified

the direct correlation between higher education and increased income, which can be

transferred to the assumption of increased wealth accumulation that was shown for

women of Generation X. The current body of knowledge includes substantial

hypothesizing regarding generational patterns in wealth accumulation and net worth,

which this study has now quantified.

121

Summary

The gender wealth gap in the U.S. has been examined over the study period, 1992

- 2007, through an analysis of the net worth of 8,676 respondents to the triennial SCF.

For each survey year in the study period, 1992, 1995, 1998, 2001, 2004, and 2007, SCF

data regarding the net worth of unmarried male and unmarried female respondents were

compared. Statistical analysis indicated that the median and mean net worth values of the

two groups, unmarried male respondents and unmarried female respondents, were not the

same in each of the survey years, with/?<.001. The differences in the net worth values of

unmarried male respondents and unmarried female respondents indicated that the gender

wealth gap in the U.S. existed in each of the survey years throughout the study period,

1992-2007.

The gender wealth gap in the U.S. was measured for each of the survey years

using six measures: median net worth, mean net worth, percentage of male net worth

based upon median net worth data, percentage of male net worth based upon mean net

worth data, median net worth adjusted for inflation, and mean net worth adjusted for

inflation. The trends in the gender wealth gap in the U.S. were examined over the study

period using all six measures. Although there was an increase in the gender wealth gap

when measured based upon median and mean net worth data in real dollars, the increase

was not as profound when measured using percentages or dollars adjusted for inflation.

The slight increase in the gender wealth gap over the study period was not statistically

significant at a=.05 when the effects of inflation were eliminated. Overall, it has been

concluded that the gender wealth gap in the U.S. did not substantially change over the

study period, 1992-2007.

The overall increase in the gender wealth gap observed was minimized due to the

downward trend in the gender wealth gap experienced by Generation X. When examined

by generational cohort, there were significant differences observed in the trend in the

gender wealth gap for Generation X in comparison to the trends in the gender wealth gap

for prior generational cohorts, the Traditionalists and the Baby Boomers. The gender

wealth gap for Generation X narrowed, as the gender wealth gaps for the Traditionalists

and Baby Boomers both increased over the study period. Isaacs (2010) hypothesis that

generational characteristics should affect wealth accumulation has been affirmed through

this study. Bobbitt-Zeher's (2007) contention that the narrowing of the education gap

should affect wealth parity has been supported by this study, as Generation X women are

less affected by an education gap than women of prior generations. The narrowing of the

gender wealth gap for Generation X indicates a possible correlation between increased

earning parity and educational equality, and the accumulation of net worth.

By identifying the trends in the gender wealth gap by generation, the findings of

this study add to the body of knowledge regarding gender differences in wealth

accumulation. Through examining how and why the gender wealth gap differs by

generation, the gender wealth gap may become better managed so that it might be

eradicated in the future.

Chapter 5: Implications, Recommendations, and Conclusions

The problem examined in this study was that it has been unknown whether

Generation X women, in comparison to women of prior generations, were accumulating

as much wealth as their male cohorts. The purpose of this quantitative trend analysis

study was to determine whether Generation X women, in comparison to women of prior

generations, were accumulating as much wealth as their male cohorts. A quantitative

trend analysis study was conducted on data compiled through the SCF for the survey

years 1992, 1995, 1998, 2001, 2004, and 2007. The gender wealth gap was measured for

each survey year and trends identified in total, and by generational cohort, for the study

period. The trends in the gender wealth gap were examined to determine how the gender

wealth gap differed for Generation X in comparison to prior generations. There were

limitations on the study based upon the methodology employed in gathering the SCF

data, but overall the SCF data is considered reliable and valid. The study delimitations

include the choice to exclude all married couples and Generation Yers from the analysis.

The study is further limited by lack of current information, as the SCF data for 2010 will

not be available until 2012. The effects of the economic downturn experienced in the

U.S. since the 2007 SCF data was compiled are not taken into account in this study.

There were no significant ethical implications regarding this study since there was no

direct contact with study participants. All data used in this study was publicly available

through the Federal Reserve Board's website, and the identities of all participants have

been protected as part of the SCF survey.

In this chapter, the implications of the study are discussed. Recommendations for

application of the new knowledge attained through this study are presented, along with

recommendations for future study. Final conclusions are drawn with regard to exploring

the effects of Generation X on the gender wealth gap in the United States.

Implications

The problem addressed in this study was whether Generation X women, in

comparison to women of prior generations, were accumulating as much wealth as their

male cohorts. It was determined that women in the U.S. have not accumulated as much

wealth as men, but that this trend has changed with Generation X. Although women in

the U.S. have lower levels of wealth and earnings than men (Fisher, 2010), and are more

likely to live in poverty (U.S. Census Bureau, 2008b) and less likely to be among the

wealthy (IRS, 2009b) than their male cohorts are, women of Generation X are narrowing

the gender wealth gap. Prior research has not quantified the gender wealth gap, and

recent findings "have been mixed regarding whether a wealth gap between male and

female-headed households exists" (Fisher, 2010, p. 15). This study has provided

quantification of the gender wealth gap, in total and by generational cohort, so that the

gender wealth gap can be better understood. This research supports Fisher's (2010)

statement that the findings on the gender wealth gap have been conflicting, but provides

the explanation that the trends in the gender wealth gap differ by generational cohort.

When examining the gender wealth gap by generation, it is clear that the gender wealth

gap has narrowed for Generation X, while it continued to widen for prior generations.

The first research question Ql, "To what extent has the gender wealth gap

changed during the period 1992 - 2007 in the U.S.?" has been addressed through

measuring the gender wealth gap using data collected as part of the SCF for survey years

1992, 1995, 1998, 2001, 2004, and 2007. The gender wealth gap was measured for each

125

survey year using median and mean net worth measures for groups of unmarried male

and female respondents. Although the trends in the gender wealth gap show an overall

increase in the U.S. over the study period, the increase was not significant at the .05 level

when the gender wealth gap measures were adjusted for inflation. The gender wealth gap

expressed as a percentage of male net worth (W/X), also increased over the study period,

but again the increases were not significant at the .05 level. In light of this data, the null

and alternative hypotheses were evaluated. The null hypothesis HIQ, "There is no

significant change observed in the gender wealth gap from 1992 until 2007" is not

rejected.

The second research question Q2, "How does the gender wealth gap in the U.S.

differ by generational cohort during the period 1992 - 2007?", was evaluated through

analyzing the SCF data for the survey years 1992, 1995, 1998, 2001, 2004, and 2007 by

generational cohort. Generational cohorts were established by birth year for

Traditionalists (1908-1945), Baby Boomers (1946-1961), Generation X (1962-1977), and

Generation Y (1978-1984). The gender wealth gap was measured for Generation X and

the two prior generations (Traditionalists and Baby Boomers) using mean and median net

worth measures for the groups of unmarried male (X) and unmarried female respondents

(Y), by generation, for each survey year. Trend lines were developed for the gender

wealth gap (W) measures for each generational cohort. The trend lines for the

Traditionalists and Baby Boomers had positive slopes, indicating a widening of the

gender wealth gap for these generational cohorts over the period 1992 - 2007. The trend

lines for Generation X had negative slopes, indicating a narrowing of the gender wealth

gap for this generational cohort over the period 1992 - 2007. The opposing slopes of the

trend lines for Generation X and prior generations proves that there is a difference in the

gender wealth gap for Generation X in comparison to prior generations. The null

hypothesis H2Q, "There are no significant differences between the trends in the gender

wealth gap observed for Generation X and the gender wealth gap observed for prior

generations for the period 1992 - 2007" is, therefore, rejected.

There are several limitations on this study that must be acknowledged when

evaluating the research findings. There are limitations on the study that are related to the

SCF data. The study relies upon the validity and reliability of the SCF data, which is

self-reported and collected via face-to-face or telephone interviews. The inherent

possibility of inaccurate data reporting exists due to the nature of the SCF. The

weighting process used in the SCF data reporting further limits the study. The SCF

weighted data includes five weightings of financial data per respondent in order to make

the sample representative of the population of U.S. taxpayers. The weighting of financial

data makes the overall net worth data representative, but there is no guarantee of

representativeness within each generational cohort. The respondents that had their date

of birth altered as part of the SCF weighting were eliminated from the study. In addition,

only the unmarried respondents were included in the study, which may also potentially

change the representativeness of the sample. Finally, Generation Y was excluded from

the generational analysis. The purpose of the study was to compare Generation X to prior

generations, but inclusion of Generation Y data may have added value to the findings.

The purpose of this quantitative trend analysis study was to determine whether

Generation X women, in comparison to women of prior generations, were accumulating

as much wealth as their male cohorts. While Generation X women were not yet

127

accumulating as much wealth as their male cohorts, the gender wealth gap for this

generation has narrowed over the study period. Women of prior generations, the

Traditionalists and Baby Boomers, continued to be affected by a widening gender wealth

gap. Generation X women are reversing the trends in the gender wealth gap that have led

to women experiencing less financial stability and having a higher likelihood of living in

poverty than their male cohorts.

The significance of this study is that it provides further knowledge on the gender

wealth gap that may lead to increased financial equity among genders. Through

clarifying the magnitude of the gender wealth gap and identifying changes in the trends in

the gender wealth gap by generation, the body of knowledge has been furthered. It may

be concluded that the increased earnings and education of Generation X women, in

comparison to prior generations, has led to increased financial stability as measured by

accumulation of net worth.

The challenges that still exist to securing financial equity among the genders need

to be addressed by generation, rather than for society in general. This study has shown

that the gender wealth gap does differ by generation, and therefore must be examined in

more depth by generational cohort.

Assuming that the generational changes in attitudes toward working, gender roles,

and wealth accumulation continue to shift in ways that promote increased equality, the

conditions that have led to the gender wealth gap may be eliminated with continued

changes in workforce composition. The examination of the gender wealth gap for

Generation Y and future generations will confirm this assumption that the gender wealth

gap may eventually be eliminated.

128

Recommendations

This study has shown that the gender wealth gap has narrowed for Generation X,

but was still widening for members of prior generations, including the Traditionalists and

the Baby Boomers. Recognition of the generational differences that affect the wealth

accumulation of women in particular may provide a basis for minimizing the gender

wealth gap for all generations. Since generational characteristics and attitudes may affect

the trends in the gender wealth gap, the gender wealth gap might need to be addressed

from a generational standpoint, rather than as a societal problem.

The conditions that have led to the gender wealth gap must be analyzed by

generation so that the gender wealth gap may be minimized for each generation.

Although the gender wealth gap has narrowed for Generation X, it continued to exist

throughout the study period. Future studies may search for correlations between wealth

accumulation and other factors, such as income, education, and familial status, by gender,

for Generation X. Since Generation X is the only generation that is currently in the

workforce with a proven trend of narrowing the gender wealth gap, this generation should

be studied in depth so that the specific factors related to increased wealth parity might be

promoted for other generations. Although this study conjectures that the gender wealth

gap has narrowed for Generation X due to increases income and educational equity, this

has not been specifically proven. The correlations between income, education, and net

worth of Generation Xers are suggested as topics for future study.

It is unlikely that Traditionalist and Baby Boomer women will be able to make

sufficient changes in their education and income level to be able to match the wealth

achieved through the accumulated lifetime earnings of their male counterparts since

many are at or near retirement age. However, some barriers to women's wealth

accumulation, such as the gender income gap and the gender education gap, have been

narrowed or eliminated for Generation X women. Generation Y and future generations

should maintain the educational equity and the increased income parity experienced by

Generation X. Future studies might incorporate an analysis of the gender wealth gap for

Generation Y. A future replication of this study that includes data on Generation Y may

provide new insight into the trends in the gender wealth gap. The 2010 SCF data should

become available in 2012, and should have a sufficient number of respondents from the

Generation Y cohort to make analysis significant.

The SCF data included responses to questions on the saving, investing, and

spending habits of participants. Saving, investing, and spending habits have a direct

impact on wealth accumulation and net worth. A recommendation for future study would

include a correlation analysis between saving, investing, and spending habits, and net

worth. Examining the correlation between financial management habits and wealth

accumulation, by gender and by generational cohort, may provide more insight into the

causes of the gender wealth gap.

Conclusions

Generation X has affected the gender wealth gap in the U.S. since their entrance

into the workforce. The gender wealth gap in the U.S. has widened slightly over the

period 1992 - 2007. However, Generation X's gender wealth gap has shown a narrowing

trend, whereas the trends in the gender wealth gap for prior generations have widened.

The effect of Generation X on the gender wealth gap is that the gap is narrower than it

would have been had this generation not entered the workforce.

130

While it is encouraging that the gender wealth gap has narrowing for Generation

X, it is important to note that the gender wealth gap still persisted throughout the study

period. The gender wealth gap in the U.S. remains a societal problem as the number of

women living in poverty continues to increase and the wealth levels of Traditionalist and

Baby Boomer women fail to grow at the rate of their male counterparts' net worth. The

gender wealth gap is narrowing for Generation X women, but they remain at risk for

financial inequity.

This study has provided an initial exploration into the effects of Generation X on

the gender wealth gap. Future studies that examine the saving, investing, and spending

habits of men and women, by generational cohort, may further the body of knowledge so

that the gender wealth gap may eventually be eradicated.

131

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Appendices

Appendix A:

Topics included in the 2007 Survey of Consumer Finances survey instrument

Household Listing

Economic Expectations and Financial Institutions

Credit Attitudes and Credit Cards

Principal Residence and Lines of Credit

Real Estate and Loans to Others

Businesses

Vehicles

Education Loans

Other Loans

Attitudes about Saving and Investing

Financial Assets

Work and Pensions: Respondent/Spouse/Partner

Income, Taxes, Income Expectations, and Support

Inheritances and Charity

Demographics, Health, Independent HH Members