PROGRAM ON RETIREMENT POLICY

RESEARCH REPORT

How Might Legal Recognition of 

Same-Sex Marriage Affect Retirement 

Incomes and Federal Programs? 

Final Report 

Karen E. Smith Stephen Rose Damir Cosic 

November 7, 2016 
ABOUT THE URBAN INSTITUTE 

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

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

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

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

Abstract

This paper uses the Urban Institute’s Dynamic Simulation of Income Model (DYNASIM) to estimate the 

impact of legal same-sex marriage on retirement incomes of lesbians and gays from 2015 to 2065. It 

also estimates the impact of legal same-sex marriage on government budgets. Legal same-sex marriage 

reduces government budgets (increases the deficit) but also increases retirement incomes for seniors in 

the bottom three-fifths of the income distribution. 

We find that legal same-sex marriage increases some components of net income while reducing others. 

Net per capita retirement income increases on average for lesbians and gays in the bottom three 

lifetime earnings quintiles, but falls for those in the top quintile and the change gets bigger over time.

Marriage provides an important financial cushion for partners during periods of unemployment, ill 

health, and in retirement. Poverty rates among gays and lesbians ages 62 and older are projected to fall 

from 18 percent in 2015 to 5 percent in 2065 after same-sex marriage becomes legal. Legal same-sex 

marriage is one factor contributing to this reduction.

Legal same-sex marriage on net lowers aggregate government budgets (increases the deficit) in the long 

run, but because lesbians and gays are a small share of the US population, the aggregate effect of legal 

same-sex marriage is small (about $3.5 billion (less than 1 percent) lower in 2065). The number of Social 

Security beneficiaries and benefit outlays increase with expanded access to spouse and survivor 

benefits. More Social Security beneficiaries will pay taxes on Social Security benefits, contributing to an 

increase in federal income taxes. The number of Medicare Part B and D participants falls slightly as 

some same-sex partners gain employer sponsored health insurance through a working spouse. On net, 

the savings from Medicare and higher revenue from taxes do not offset the increase in Social Security 

spending. 

Copyright © October 28, 2016. Urban Institute. Permission is granted for reproduction of this file, with attribution to 

the Urban Institute. Cover image by Tim Meko.
CONTENTS III

Contents

Abstract ii

Acknowledgments v

Executive Summary vi

Chapter 1: Introduction 1

Background 2

Report Plan 3

Chapter 2: Literature Review 5

Share of Lesbians, Gays, and Bisexuals 5

Potential Number of Same-Sex Marriages 7

Same-Sex Marriages, Individual Well-Being, and Government Finances 9

Chapter 3: Number and Characteristics of Same-Sex Cohabiting and Married Couples 12

Number of Married and Cohabiting Same-Sex Household Couples 13

Same-Sex Marriage 14

Chapter 4: Demographic Characteristics of Same-Sex Cohabiting and Married Couples 20

Age 21

Education 22

Race and Ethnicity 24

Individual Earnings 26

Housing Wealth of Same-Sex and Opposite-Sex Couples 28

Chapter 5: Estimation Models 32

Same-Sex Cohabitation 32

Mate-Matching 35

Same-Sex Marriage 39

Opposite-Sex Marriage 41

Chapter 6: Projection Results 42

Projections of Share of Same-Sex Marriages 43

Changes in Government Programs and Federal Revenues and Expenditures 46

Projected Retirement Income of Gays and Lesbians Ages 62 and Older 54

Chapter 7: Conclusions 61

Appendix A. Effective Date of Legal Same-Sex Marriage by State 64
I V CONTENTS

Appendix B. Same-Sex Cohabitation Hazard 69

Appendix C. Same-Sex Marriage Hazard Model 72

Appendix D. Heterosexual Cohabitation Hazard Model 75

Appendix E. Heterosexual Marriage and Separation Hazard Model, Cohabiting Couples 79

Appendix F. Heterosexual Separation from Marriage Hazard Model, Married Couples 83

Appendix G. Heterosexual Divorce Hazard Model for Separated Couples 86

Notes 88

References 89

About the Authors 92

Statement of Independence 93
ACKNOWLEDGMENTS V

Acknowledgments

This report was funded by US Department of Labor’s Employee Benefits Security Administration, under 

contract DOL-OPS-14-D-0020, order no. DOL-OPS-15-T-00194. We are grateful to them and to all our 

funders, who make it possible for Urban to advance its mission. 

The views expressed are those of the authors and should not be attributed to the Urban Institute, 

its trustees, or its funders. Funders do not determine research findings or the insights and 

recommendations of Urban experts. Further information on the Urban Institute’s funding principles is 

available at www.urban.org/support.

The authors thank Lynn Johnson and Samuel Tseng at the Department of Labor for their helpful 

comments and suggestions on our work plan and preliminary reports. We also thank Richard Johnson 

for his guidance and input on all elements of this research and Sasha Ruby for his assistance with the 

literature review. Finally, we thank Melissa Favreault and Doug Murray who have been instrumental in 

the development of the DYNASIM model for many years.
V I EXECUTIVE SUMMARY

Executive Summary 

The Defense of Marriage Act (DOMA), enacted in 1996, barred the federal government 

from recognizing same-sex marriages legalized by the states. On June 26, 2013 in United 

States v. Windsor, the U.S. Supreme Court ruled that DOMA violated the Fifth 

Amendment and that the federal government must recognize state-sanctioned samesex marriages. Exactly two years later, the U.S. Supreme court opened the gates to legal 

marriage for same-sex couples across the nation when it ruled 5 to 4 in Obergefell v. 

Hodgesthat the U.S. Constitution guarantees the right to same-sex marriage. These 

recent Supreme Court decisions significantly improve access to retirement benefits for 

today’s nearly 800,000 same-sex couples.

This study analyzes how many and to what extent older gay and lesbian Americans gain financially 

from the federal recognition of same-sex marriage. It also projects the impact of legalized same-sex 

marriage on federal government spending and revenues for the next 70 years.

While there is some uncertainty about the size of the gay and lesbian populations, survey results 

suggest that between 1.3 and 2.5 percent of Americans (about 4 to 8 million people) identify as lesbian 

or gay. Among those, about 1.6 million are living with a same-sex partner.

Survey data suggest that about 75 percent of gays and lesbians report wanting to marry someday, 

but the number of married-same-sex couples has been historically constrained for couples living in 

states that do not recognize same-sex marriage. Of the nearly 800,000 couples living with a same-sex 

partner in 2014, 42 percent were married, but the share of same-sex couples that are married is 

markedly higher in states that legalized same-sex marriage relatively early.

While about the same share of lesbians and gays partner and marry, lesbian women typically do so

at slightly younger ages than gay men. Nonmarital cohabitation is typically a transitory status for 

opposite-sex couples, with many transitioning to marriage. The absence of legal marriage for many 

same-sex couples means that nonmarital cohabitation is common among same-sex couples even at 

older ages. 

Same-sex couples are more likely to be white and well-educated than opposite-sex couples and 

tend to have higher earnings. However, same-sex couples are more likely than opposite-sex couples to 

partner with someone of a different age and racial group. A substantially higher share of women in 

heterosexual couples have no market earnings than women in same-sex couples, as more heterosexual 
EXECUTIVE SUMMARY VII

women remain at home to raise children. Family heads in the majority of working-age same-sex and 

opposite-sex couples have earnings that differ substantially from their partners, suggesting that Social 

Security spouse and survivor benefits will be an important financial resource for both same-sex and 

opposite-sex couples in the future.

The opportunity to marry will, on average, improve the financial security of older gays and lesbians. 

The average per capita annual retirement income of lesbians and gays in the middle income quintile was

approximately $2,000 higher when same-sex marriage was legal than under the baseline case in which 

same-sex marriage was not legal. For couples, then, the gain in this middle income range was $4,000. 

Poverty rates for gays and lesbians ages 62 and older are sharply higher than for all seniors. Poverty 

rates for gays and lesbians ages 62 and older are projected to decline from 18 percent in 2015 to 5 

percent in 2065. While poverty rates are projected to fall in general due to rising earnings, gays and 

lesbians will also benefit from the many advantages of combining incomes and access to additional 

retirement benefits. Legal same-sex marriage reduces poverty rates for gays and lesbians ages 62 and 

older by one to two percentage points per year.

The rise of middle quintile incomes for older gays and lesbians and decline in poverty rate are due to 

several factors. First, pooling of income reduces the number of gay and lesbian people with low family 

income and provides certain economies of scale (a slimmed down version of the old saying that “two can 

live as cheaply as one”). Second, married couples tend to have higher per capita incomes because people 

with responsibilities to other people tend to have higher earnings and are more likely to accumulate 

savings and become home owners. Third, couples can survive layoffs or other problems more easily 

than single people, because a spouse’s resources can provide a financial cushion. Fourth, they gain 

access to private and public spouse benefits, such as coverage by a spouse’s employer-sponsored health 

insurance, higher Social Security payments that are based on the employment history of a higherearning spouse, and Social Security survivor benefits.

Using our simulation model, we examined the impact of same-sex marriage on federal programs and 

tax revenues. Our projections showed the following: 

 A small increase in the number of people receiving OASDI benefits (0.03 percent in 2015); 

 An increase in the net cost of OASDI benefits of several billions of dollars per year (0.02 to 0.04 

percent increase) due to the increase in the number of beneficiaries and an increase in the 

number receiving spouse and survivor benefits that exceed their own worker benefits. This 

change is too small, however, to materially affect the Social Security Trust Fund;
VIII EXECUTIVE SUMMARY

 A small decrease in the number receiving SSI benefits (0.12 percent in 2015) that dissipates 

over time;

 A small decrease (0.02 percent) in the number of people receiving Medicare Part B and Part D 

benefits which slightly reduced Medicare costs, net of premiums (0.018 percent decline), 

because these programs are subsidized by the federal government;

 A small decrease in the amount of the Medicare surtax (0.17 to 0.9 percent); 

 More older people paying income taxes on their Social Security benefits (0.15 percent in 2015 

rising to 0.33 percent in 2065); 

 Small changes in federal income taxes paid that are not uniformly higher or lower as some 

couples get marriage bonuses and others get marriage penalties; and

 The combined effect of these changes is a reduction in the net federal budget (increase deficit) 

of between $3 billion to $6 billion dollars a year after 2030 (which represents about four onehundredths of one percent).
CHAPTER 1: INTRODUCTION 1

Chapter 1: Introduction

The Defense of Marriage Act (DOMA), enacted in 1996, barred the federal government from 

recognizing same-sex marriages legalized by the states. On June 26, 2013 in United States v. Windsor, the 

U.S. Supreme Court ruled that DOMA violated the Fifth Amendment and that the federal government 

must recognize state-sanctioned same-sex marriages. At that time, 15 states had legalized same-sex 

marriage. By June 25, 2015, same-sex marriage was legal in 36 states. On June 26, 2015, exactly two 

years after the Supreme Court ruled DOMA unconstitutional, the U.S. Supreme Court opened the gates 

to legal marriage for same-sex couples across the nation when it ruled 5 to 4 in Obergefell v. Hodgesthat 

the U.S. Constitution guarantees the right to same-sex marriage.

Because DOMA defined marriage for federal purposes as a relationship between a man and a 

woman, it denied married same-sex couples hundreds of federal benefits. At issue in the Windsor case 

was the federal income-tax exemption on estates granted to surviving spouses that was denied to Edith 

Windsor when her legal same-sex spouse died. In addition to the tax provisions considered in Windsor, 

Social Security spouse, divorced spouse, and survivor benefits are important benefits available to 

married heterosexual couples that were unavailable to legally married same-sex couples prior to 

Windsor. Also, employers were not required to make joint and survivor annuities available to employees 

in qualified defined benefit plans that were married to same-sex spouses (although some employers did 

extend these benefits to same-sex domestic partners). The Supreme Court’s rulings in Windsor and 

Obergefell significantly improved access to retirement benefits for the nearly 800,000 same-sex couples 

today.

This project uses the Urban Institute’s state-of-the-art DYNASIM microsimulation model to 

estimate Social Security and pension benefits newly available to legally married same-sex couples. We 

analyze how many and to what extent older gay and lesbian Americans gain financially from the federal 

recognition of same-sex marriage and project the impact of legalized same-sex marriage on Social 

Security solvency over the next 70 years.

This report addresses the following research questions:

1. How do the characteristics of same-sex couples who choose to marry differ from same-sex 

couples who remain partnered?

2. How do marriage rates compare for states that were early adopters of same-sex marriage and 

those that were late adopters? 
2 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

3. How many same-sex couples are likely to gain Social Security and other retirement income and 

what are their characteristics?

4. How large will the gains likely be? How do gains differ by the lifetime earnings of both married 

partners?

5. How are expanded benefits expected to impact Social Security solvency and government 

budgets?

The impact of the policy change will depend on the number of same-sex couples who choose to 

marry, on the earnings differentials of married same-sex couples, and on the duration of same-sex 

couple marriages. Because of the uncertainty of how high same-sex marriage rates will be, we present 

low, medium, and high estimates of how many same-sex marriages there will be in the future and how 

each of these estimates affect incomes, Social Security solvency, and government budgets.

Background

Employee benefits affected by the Supreme Court’s recent same-sex marriage rulings include 

retirement plans, health insurance, life insurance, and flexible spending accounts.1 In particular, the 

ruling requires defined benefit plans governed by ERISA to offer retiring employees the option of a joint 

and survivor annuity benefit that covers a same-sex spouse. Some employers may have offered joint 

and survivor annuities that cover same-sex domestic partners, but the court’s ruling now requires all 

qualified defined benefit plans to offer such annuities for all married couples. 

The same-sex marriage rulings also enable same-sex spouses and the qualifying children of samesex marriages to receive Social Security spouse and survivor benefits. Under Social Security program 

rules, a widow or widower is entitled to 100 percent of a deceased worker’s benefit amount. A spouse is 

entitled to half of a primary worker’s benefit amount. In both cases, beneficiaries must choose between 

a spouse or survivor benefit and the retirement benefit they could receive based on their own earnings. 

Divorced men and women are entitled to spouse and survivor benefits if their marriage lasted at least 

10 years. Social Security also pays benefits for dependent children and parents.

In 2015, Social Security provided spouse or survivor benefits to 48 percent of women ages 62 and 

older (or 12.9 million) (SSA 2016, Table 5.A14). For these women, spouse and survivor benefits provide 

higher Social Security benefits than what they could collect based on only their own earnings. While the 

share receiving these auxiliary benefits has fallen over time—from 61 percent in 1960—as women’s 

labor supply and earnings have increased and marriage rates have declined, auxiliary benefits remain an 
CHAPTER 1: INTRODUCTION 3

important source of retirement income for many older women today (Butrica and Smith 2012a, 2012b; 

Wu, Karamcheva, Munnell, Purcell 2013; Tamborini and Whitman 2007). These same benefits are likely 

to improve the retirement security of married same-sex couples who now qualify for spouse and 

survivor benefits as a result of the Supreme Court’s ruling. However, the impact will depend on the 

relative lifetime earnings of same-sex spouses. Couples with similar lifetime earnings will not gain much 

from access to spousal benefits because each spouse would be better off collecting retirement benefits 

based on his or her own earnings (although a lower-earning spouse who outlives a higher-earning 

spouse would gain somewhat from access to survivor benefits). However, couples with very different 

lifetime earnings could experience substantial gains in Social Security benefits from access to spousal 

benefits. Although these additional Social Security outlays would improve retirement security for samesex couples, they would at least somewhat worsen the long-term financial outlook for Social Security, 

which is now projected to lack sufficient revenue to fully pay scheduled benefits by 2034.

Report Plan

This report will consist of seven chapters, organized around the various tasks that we have set out to 

accomplish. 

Chapter 2 presents a literature review of prior work on same-sex demographics and same-sex 

marriage. The first section describes the various estimates of the share of lesbians, gays, bisexuals, and 

transgender people (LBGTs) in the United States. Other areas covered in this literature review include 

estimates of the number of same-sex marriages and divorces and attempts to estimate the fiscal effects 

of legalizing same-sex marriage.

Chapter 3 focuses on the numbers and demographic characteristics of lesbian and gay household 

couples. The American Community Survey (ACS) has reliable data on same-sex couples who are 

cohabiting and married from 2012 to 2014. The 2012 daily Gallup tracking polls include estimates of 

the LBGT share of the population independent of living arrangement in each state. 

These data sources provide reasonable estimates of the number of lesbian and gay couples in each 

state and in the country as a whole. Further, we compare the share married, share cohabiting, and share 

unattached for each state by age and sex. This shows that the national marriage share of opposite-sex 

people is considerably higher than that of same-sex people. Further, we present data showing the 

married share in states by year that same-sex marriage was legalized. A key finding here is that the 

same-sex married share rose rapidly after states legalized same-sex marriage.
4 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

Chapter 4 focuses on the demographics of same-sex couples by age, educational attainment, 

race/ethnicity, and personal earnings. In this chapter, we compare the distributions along each of these 

dimensions comparing lesbians and gays living in household couples to opposite-sex men and women in 

household couples. Further we examine a) how male same-sex couples differ from female same-sex 

couples, b) how same-sex couples differ from opposite-sex couples, and c) how married same-sex 

couples differ from unmarried cohabiting same-sex couples. 

Chapter 5 presents estimated cohabitation, marriage, separation, and divorce hazard models using 

1979 and 1997 National Longitudinal Survey of Youth (NLSY) data for heterosexual couples. We use 

these models to update DYNASIM’s year-to-year cohabitation, marriage, separation, and divorce 

projections. The heterosexual hazard models account for individual characteristics including age, sex, 

race, ethnicity, education, earnings, prior marital status, and economic factors that are available on the 

NLSY data. This chapter presents the parameters of the equations that determine each of these yearly 

transitions. This chapter also presents cohabitation and marriage hazard estimates for same-sex 

couples using data from the 2004-2014 ACS by age, sex, and race. The same-sex hazard models include 

a more limited set of explanatory variables that are observable on the ACS cross-sectional data.

Chapter 6 reports DYNASIM’s simulations of future federal revenues and expenditures, 

participation in government programs, and family incomes, comparing results under our baseline 

scenario that incorporated legalized same-sex marriage nationwide with an alternative scenario that 

assumed neither the federal government nor any of the states recognized same-sex marriage. Because 

the share of same-sex couples who will eventually marry is necessarily uncertain, we also ran 

simulations that varied the long-run same-sex marriage rate. We projected benefits from the Old Age, 

Survivors, and Disability Insurance (OASDI) program, better known as Social Security, because legalized 

same-sex marriage gives same-sex couples access to spouse and survivor retirement benefits, which 

could substantially improve their financial security at older ages. We also projected Supplemental 

Security Income (SSI), which provides cash benefits to older people (as well as people with disabilities) 

with very few resources. In addition, we simulated federal income tax payments, Medicare Part B and D 

participation, and Medicare premiums. Chapter 7 concludes.
CHAPTER 2: LITERATURE REVIEW 5

Chapter 2: Literature Review

This literature review first provides estimates of the share of lesbians, gays, and bisexuals (LGBs) in 

the United States. It then provides a brief history of the evolution of same-sex marriage and attempts to 

estimate the number of potential same-sex marriages in the future. It then summarizes the results of 

studies that examined individual well-being of same-sex couples and how legalization will impact 

government finances. Key findings in this section are that about 1.8 percent of Americans are lesbian or 

gay, defining the population at risk of same-sex marriage, and the fiscal impact of same-sex marriage is 

likely small.

Share of Lesbians, Gays, and Bisexuals

Table 1 shows the share of the population that reported being lesbian, gay, and bisexual from various 

survey data. Among the six surveys that are representative of the entire adult population—Gallup Daily 

Tracking Survey, General Social Survey (GSS), National Survey of Sexual Health and Behavior (NSSHB), 

National Health Interview Survey (NHIS), Pew US Religious Landscape Survey, and National Health and 

Nutrition Examination Surveys (NHNES)—the LGB share varies from 2.3 to 6.8 percent of the 

population and the gay and lesbian share ranges from 1.5 to 2.5 percent. 

With the exception of the NHIS, all surveys find that there are slightly more bisexuals than lesbians 

and gays. This is an important finding for our study because few bisexuals enter into long-term samesex relationships. Unpublished NHIS-based estimates from Gary Gates show that only 4 percent of 

bisexuals were in a cohabiting same-sex relationship, 42 percent were in an opposite-sex marriage or 

cohabitation relationship, and the remainder were not coupled. 

For this analysis, we will focus on the lesbian and gay share and use the 1.8 percent estimate of the 

population size in the United States. The 1.8 share is based on the largest and most recent nationally 

representative survey reporting sexuality and is consistent with estimates from Gary Gates of the 

Williams Institute at UCLA Law School (Gates 2011).
6 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

TABLE 1

Estimates of the Number of Lesbians, Gays, and Bisexuals in the U.S. and Selected Foreign Countries

Both Sexes, Share of Adult Population

Source Homosexual Bisexual Total LGB 

No Age Restrictions

Gallup, 2012 na na 3.4

General Social Survey, 2014 1.7 2.6 4.3

National Survey of Sexual Health and Behavior, 2009 2.5 3.1 5.6

National Health Interview Survey, 2013 1.6 0.7 2.3

U.S. Religious Landscape Study, 2014 1.8 2.8 4.6

National Health and Nutrition Examination 

Surveys, combined 2003-2010 1.5 2.3 3.8

With Age Restrictions

Gallop 2012 

Ages 18-29 na na 6.4

Ages 30-49 na na 3.2

Ages 50-64 na na 2.6

Ages 65+ na na 1.9

National Survey of Family Growth, 2002

Ages 20-44 1.8 2.3 4.1

National Survey of Family Growth, 2006-2008: Ages 20-44 1.7 2.2 3.9

National Survey of Family Growth, 2011-2013: Ages 18-44 1.3 5.5 6.8

Youth Risk Behavior Survey, 2001-09

Ninth to twelfth grade 1.3 3.7 5.0

International Surveys

 Australia, 2013 1.6 1.8 3.4

 Canada, 2015 1.7 1.3 3.0

 Netherlands, 2009 2.5 6.5 9.0

 Norway, 2010 0.7 0.5 1.2

 United Kingdom, 2010 1.0 0.5 1.5

Sources: Gallup: Gates and Newport (2012); General Social Survey: (authors’ tabulations from GSS Data Explorer); National 

Survey of Sexual Health and Behavior: CDC table 16 (Chandra, Mosher, Casey 2011); National Health Interview Survey: Ward, 

Dahlhamer, Galinsky, Joestl (2014); U.S. Religious Landscape Study (Pew Research Center [2015b]); National Health and 

Nutrition Surveys: Cochran et al (2013); National Survey of Family Growth: Chandra, Mosher, Copen, Sionean (2011); National 

Survey of Family Growth: Copen, Chandra, Febo-Vazquez (2016); Youth Risk Behavior Survey: Kann et al (2011). Australia: 

Richters et al 2014; Canada: Statistics Canada 2015; Netherlands: Sandfort, Graaf, Bijl, and Schnabel (2010); Norway: Gates 

(2011); United Kingdom: BBC News (2010).

Note: na=not available.
CHAPTER 2: LITERATURE REVIEW 7

Potential Number of Same-Sex Marriages 

The fight for same-sex marriage began in 1972 when a Minnesota same-sex couple sued the state for 

not issuing them a marriage certificate. In Baker v. Nelson, the U.S. Supreme Court affirmed the state 

court’s ruling upholding the government’s decision to refuse the couple a marriage license. Following 

that decision, a number of state legislatures passed laws banning same-sex marriages. The first victory 

for same-sex couples seeking to marry occurred in 1993 when the Hawaiian Supreme Court ruled in 

Baehr v. Lewin that denying three gay couples marriage licenses violated the equal protection clause of 

the state’s constitution. This victory was relatively short-lived, however, because the state amended its 

constitution in 1998 to prohibit same-sex marriages. To squelch any momentum on local actions 

promoting same-sex marriage, 32 state legislatures soon banned same-sex marriage, with some 

legislatures arguing that allowing same-sex marriage would harm traditional family formation 

(Trandafir 2015). By the end of 2000, 40 states had either statutory or constitutional bans on same-sex 

marriage (National Conference of State Legislatures 2015). 

In 1999, California passed a domestic partnership statute and Vermont passed a civil union act 

giving same-sex couples many—but not all—of the rights enjoyed by married couples. The next 

significant victory for same-sex marriage occurred in Massachusetts in 2004, which granted same-sex 

couples full marriage rights. In May 2008, the California Supreme Court ruled that the prohibition of 

same-sex marriage was unconstitutional. While some gays and lesbians immediately took advantage of 

their new right to marry, a statewide ballot initiative (Proposition 8) was passed in November 2008 that 

overturned this right. However, it became clear that the tide was turning in favor of same-sex marriage 

in 2009 when Connecticut, Iowa, and Maine legalized same-sex marriages. By June 26, 2015, when the 

Obergefell decision was announced, 37 states and the District of Columbia had already legalized samesex marriage. Although many of these actions were being challenged in court, the Obergefell decision 

settled the issue definitely and permanently. Appendix Table A1 shows the effective dates of legal 

same-sex marriage by state. 

Gates and Brown (2015) use data from the ACS and Gallup Daily Polls to show that the number of 

married same-sex couples has rapidly increased in response to the Supreme Court’s decisions and the 

spread of legalized same-sex marriage. In 2013, before Windsor opened up federal benefits to married 

same-sex couples by overturning the DOMA provisions, 23 percent of co-residing same-sex couples 

(230,000) were married. In June 2015, the date of the Obergefell decision, 38 percent of co-residing 

same-sex couples (390,000) were married. By October 2015—less than 4 months after the Obergefell

decision—the share of married same-sex couples grew to 45 percent (486,000). Many more same-sex 
8 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

couples may have been ready to marry in the months after the Obergefell decision but needed more time 

to plan their weddings.

Before these marriage data became available, several commentators speculated about the share of 

co-residing same-sex couples that would marry. Badgett and Sears (2005) projected that perhaps only 

50 percent of same-sex couples would marry. By contrast, Stevenson (2012) applied the demographic 

parameters from opposite-sex marriages to same-sex marriages and estimated that 85 percent of samesex couples would marry once all the restrictions were lifted. 

While it is possible that homosexuals will marry at much lower rates than heterosexuals, there are 

other indicators that homosexuals have as much desire to couple as heterosexuals. For example, 

Badgett (2010), in a review of surveys assessing LGB interest in marriage, concludes that there is “a 

very strong demand for marriage by same-sex couples.” A 2001 survey of self-identified LGB adults 

living in 15 major urban areas found that almost three quarters of respondents (74 percent) would like 

to marry someday. A 2003 survey of LGB adults found that more than three quarters of respondents 

(78 percent) would like to marry. 

In 2013, the Pew Research Center released a large study on lesbian, gay, bisexual, and transsexual

(LBGT) Americans’ attitudes towards many important life decisions including marriage and coupling 

(Pew Research Center 2013). While only 5 percent of lesbians and gays were married at the time, 56 

percent of single gay men and 58 percent of single lesbians said that they hoped to married “if given the 

opportunity.” The reasons for getting married included love, companionship, making a life-long 

commitment, and financial stability. The intensity of support for each of these motives was the same in 

the LGB community as in the general population. Wanting to marry because of children and religion, 

however, was much stronger among heterosexuals than LGBTs. By contrast, LGBT people felt strongly 

about legal rights and benefits, which heterosexuals took for granted.

Very little data exist on same-sex divorce. Badgett and Mallory (2014) tracked data in 23 states 

with same-sex civil unions or marriages and found that the divorce/dissolution rate of same-sex couples 

was slightly lower than the rate for opposite-sex couples. In the two states with data on divorce, 1.1 

percent of same-sex married couples and 1.6 percent of opposite-sex married couples divorced each 

year. These findings are only suggestive of the true divorce rate, however, because they are based only 

on the relatively few years that passed since these state-sanctioned arrangements became legal. By 

contrast, the divorce rate of opposite-sex marriages is based on dissolutions over a longer time period. 

Furthermore, many same-sex couples were in long-term relationships before marriage became legal. 
CHAPTER 2: LITERATURE REVIEW 9

Some earlier relationships may have dissolved before marriage was legalized, leaving more lasting 

relationships eligible for marriage.

Finally, Manning and Brown (2015) use the 2013 ACS to look at co-residing same-sex couples ages 

50 and older. Compared with opposite-sex married couples older than 50, same-sex couples are 

younger, more likely to be white and much more likely to have a college degree, raising household 

incomes and employment rates for same-sex couples. But the variation in economic circumstances 

among same-sex couples was greater than among opposite-sex married couples, with same-sex couples 

exhibiting a much higher poverty rates and likelihood of receiving food stamps.

Same-Sex Marriages, Individual Well-Being, and 

Government Finances

The Windsor and Obergefell decisions will undoubtedly impact both same-sex couples’ benefits and the 

federal budget. The Government Accountability Office counted 1,138 statutory provisions that would 

be affected by federal recognition of same-sex marriage (Crandall-Hollick, Pettit, and Sherlock 2015), 

but the literature concerning the effect of these decisions on same-sex couples is limited. While 

marriage opens up lots of benefits to same-sex partners, some companies had already offered benefits 

to unmarried domestic partners. The National Compensation Survey reported that 16 percent of samesex domestic partners had access to defined benefit retirement survivorship benefits and 36 percent 

had access to health care benefits (U.S. Labor Department 2015). 

The Congressional Budget Office issued a detailed analysis of the potential budgetary effects of 

federal recognition of same-sex marriage in 2004 (CBO 2004). In this analysis, CBO assumed that all 

states would legalize same-sex marriage and assumed that 0.6 percent of adults, or 600,000 same-sex 

couples, would initially enter into same-sex marriages. CBO estimated that federal recognition of samesex marriage would improve the federal budget’s bottom line by less than $1 billion in each of the next 

ten years. The federal budget would improve because same-sex marriage would raise federal revenues 

and depress federal outlays. According to CBO, individual income tax and estate tax revenues would 

rise by $200 million per year between 2005 and 2010 and by $500 million to $700 million per year 

between 2011 and 2014. CBO also determined that the legalization of same-sex marriage would 

change same-sex couples’ eligibility for federal benefits, raising outlays for Social Security and the 

Federal Employees Health Benefits (FEHB) program but reducing outlays for Supplemental Security 

Income (SSI), Medicaid, and Medicare. In total, CBO estimated that federal recognition of same-sex 

marriage would impact outlays, in either direction, by less than $50 million per year between 2005 and 
1 0 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

2009 and reduce federal outlays by between $100 million and $200 million per year between 2010 and 

2014.

Couples with more similar lifetime earnings will gain less from Social Security spouse and survivor 

benefits than couples with different lifetime earnings. Black, Sanders, and Taylor (2007) found that gay 

and lesbian couples were less likely than their heterosexual counterparts to have a stay-at-home 

partner. Having a stay-at-home partner was more common when children were present in the family. 

For both same-sex and opposite-sex couples, the stay-at-home partner tended to have less education 

than the working partner. Among two-earner couples, the earnings gap between the higher-earner and 

lower-earner was typically higher for opposite-sex couples than for same-sex couples, partly because 

men typically earn more than women.

Federal and state income taxes depend on income and filing status. Changing filing status from a 

single filer to a married filer can increase income tax liabilities (creating a marriage penalty) or reduce 

income tax liabilities (creating a marriage bonus). Pamerleau (2015) found that marriage bonuses 

typically occur when individuals with disparate incomes marry and that marriage penalties typically 

occur when individuals with similar incomes marry. Alm and Leguizamon (2015), using Current 

Population Survey (CPS) data, found substantial changes in marriage penalties and bonuses from 1969 

to 2010, with large marriage penalties prevalent during much of the 1990s and early 2000s and 

marriage bonuses becoming more common after 2003. Cruz (2013) shows that marriage rates declined 

in the 1990s when marriage penalties were more prevalent. Alm and Whittington (1997), using Panel 

Study of Income Dynamics (PSID) data, found a small positive probability of delaying marriage for 

couples facing marriage penalties compared to couples facing marriage bonuses. Pamerleau (2015) 

examined husband and wife income differentials and found that the majority of married households 

received tax bonuses and relatively few received tax penalties, suggesting that tax laws may affect 

marriage decisions.

Badgett (2010), using 2005-2007 ACS data, estimated federal income tax liability in 2009 for samesex couples in Massachusetts. He found that 66 percent of same-sex couples would pay less federal 

income tax if they filed as a married couple instead of as two single adults, 11 percent would face the 

same liability regardless of how they filed, and 23 percent would pay more if they filed as a married 

couple. Those facing a marriage bonus would save $2,325 on average, and those facing a marriage 

penalty would pay an additional $502 on average.

Alm, Leguizamon, and Leguizamon (2014), using 2010 ACS data, estimated the federal and state 

income revenue effect of legal same-sex marriage. Assuming that all same-sex couples living together in 
CHAPTER 2: LITERATURE REVIEW 1 1

the ACS married (526,452 couples), they found very small changes in state and federal revenues from 

allowing same-sex marriage. They estimated that legal recognition of same-sex marriage would reduce 

federal income tax revenue in 2010 by $187 million to $580 million, an average reduction per same-sex 

couple of about $316. They also found that it would increase state income tax revenue in 23 states, 

lower revenue in 21 states, and leave revenue unchanged in the remaining 7 states. For example, they 

found that California state income tax revenue would decrease by $29 million but New York state 

income tax revenue would increase by $16 million. The average change in annual tax liabilities per 

married same-sex couple differed across states, ranging from a decline of $381 to an increase of $323. 

They provided some sensitivity analysis using a 50 percent marriage rate, but noted that changes in 

legal status could also result in more same-sex marriages beyond the same-sex couples currently living 

together. Their high estimate assumed that 1 million same-sex couples married. Even with this high 

marriage rate, their results did not change much. 

Stevenson (2012), using 2003-2004 ACS data, also estimated how federal income taxes would 

change following the large expansion of same-sex marriage. He found that marriage penalties would 

roughly offset marriage bonuses. His preferred specification showed that tax revenues increasing by a 

paltry $34 million.

Fisher, Gee, and Looney (2016) use Internal Revenue Service (IRS) tax data to examine the number 

of same-sex married couples who filed joint tax returns. The number of same-sex couples filing joint 

income tax returns increased from 131,080 in 2013 to 183.280 in 2014 and these filers were generally 

younger, had higher income and fewer children than opposite-sex joint tax filers. They were also 

disproportionately located in metropolitan and coastal areas. The highest same-sex joint filer rates 

were in states that legalized same-sex marriage prior to 2013.
1 2 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

Chapter 3: Number and 

Characteristics of Same-Sex 

Cohabiting and Married Couples

We use ACS data to examine the number and characteristics of same-sex household couples in the 

United States. The ACS is a large ongoing nationally representative survey of American households that 

began in 2000. It collects demographic and income information for all household members from nearly 

2 million households per year.

Household couples refer to two adults living together who are either married or cohabiting. While 

married couples are easy to identify, the ACS identifies cohabiters as households with two primary 

adults in which the second person in the household lists his or her relationship to the household head as 

an “unmarried partner;” this category does not include people living apart who are dating. If the sexes of 

the two primary adults are the same, then this is a same-sex marriage or same-sex cohabiting couple. 

This method may overstate the number of same-sex marriages because of misreported sex on the ACS 

(Gates and Brown 2015). We make no adjustments to the ACS for potential misreports.

Before the 2013 Windsor ruling, the Census Bureau recoded same-sex couples that reported being 

married to unmarried. The Census Bureau stopped this practice in 2013 and coded same-sex couples 

who said they were married as married. In 2012, the ACS identified the same-sex married couples that 

Census Bureau converted into non-married cohabiters. We use this recode flag to identify married 

same-sex couples in 2012. Thus, for 2012, 2013, and 2014, we can identify same-sex married couples in 

the ACS.

Beginning in 2008, the ACS asked respondents if they got married, got divorced, or became 

widowed in the past year. Even before 2013, the ACS included positive new marriage responses among 

same-sex partners, even though the Census Bureau recoded their marital status to unmarried partners. 

We will use this information in estimating same-sex marriage hazards and for validating the 

cohabitation transitions that are modeled in Chapter 5. 
CHAPTER 3: NUMBER AND CHARACTERISTICS OF SAME-SEX COUPLES 1 3

Number of Married and Cohabiting Same-Sex 

Household Couples

The estimated number of same-sex household couples increased fairly sharply (nearly 40 percent) 

between 2008 and 2014 (figure 1). The victories in the Windsor and Obergefell Supreme Court cases 

were a clear sign that gays and lesbians could lead their lives more openly and partner without fear of 

negative consequences. Some of the increase in reported same-sex household couples likely results 

from a rising willingness of same-sex individuals to report their partner status given changing social 

attitudes. Despite the increase in the number of same-sex household couples, in 2014, same-sex 

household couples still account for only 1.2 percent of all household couples.

FIGURE 1

Weighted Number of Same-Sex Household Couples by Year

Regardless of Marital Status

Source: Authors’ tabulations from the American Community Survey.

Notes: The figure includes all households with a same-sex married or cohabiting partner.

We will start our computations of the effects of legalizing same-sex marriage with the nearly 

800,000 cohabiting same-sex couples estimated from the 2014 ACS. Our goal is to estimate the number 

of married same-sex couples, which we will determine by estimating the number of lesbians and gays 

that marry among those in same-sex household couples. We posit that the cohabiting same-sex couples 

reflect the size and characteristics of same-sex couples that are likely to marry after the Obergefell 

569,991 591,466 592,876 596,702

642,854

727,042

789,951

0

100,000

200,000

300,000

400,000

500,000

600,000

700,000

800,000

900,000

2008 2009 2010 2011 2012 2013 2014

Year

Number
1 4 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

decision. Because of the uncertainty surrounding this statistic, we will present estimates based on low, 

medium, and high marriage rates. 

Same-Sex Marriage 

The share of household couples who are married is sharply lower for same-sex couples than for 

opposite sex couples. In 2014, 89 percent of opposite-sex household couples were married (table A2), 

but only 36 percent of same-sex household couples were (table A3). Marriage has been historically 

constrained for same-sex couples living in states that did not have legal same-sex marriage. 

Among same-sex household couples, the number reporting having gotten married in the past 12 

months rose sharply in 2013 and 2014 as more states legalized same-sex marriage and the DOMA 

decision changed the financial incentives for marriage (figure 2). For example, 4,744 same-sex 

household couples reported getting married in the past 12 month in 2008 when same-sex marriage was 

legal only in Massachusetts and Connecticut, compared with 84,829 in 2014 when same-sex marriage 

was legal in 36 states. 

FIGURE 2

Number of Same-Sex Couples that Married in the Past 12 Months by Year

Source: Authors’ tabulations from the 2008-2014 American Community Survey.

Notes: The figure includes all households with a same-sex married or cohabiting partner that report a new marriage in the past 12 

months.

4,744 7,189 5,817 4,510 7,484

33,674

84,829

0

20,000

40,000

60,000

80,000

100,000

2008 2009 2010 2011 2012 2013 2014

Year

Number
CHAPTER 3: NUMBER AND CHARACTERISTICS OF SAME-SEX COUPLES 1 5

The share of same-sex household couples that are married is much higher in states that were early 

adopters of legal same-sex marriage than in states that were late-adopters. Same-sex marriage shares

were low in states before they legalized same-sex marriage, but not necessarily zero. Some couples 

could have married in a state with legal same-sex marriage. 2

We grouped ACS respondents by the year in which their state legalized same-sex marriage and 

compared same-sex married shares in 2012, 2013, and 2014 (figure 3). Because state-specific sample 

sizes are relatively small, random variation can cause substantial swings in the share of same-sex 

couples that are married each year. Nonetheless, in states that legalized same-sex marriage before 

2011, the share of same-sex household couples legally married reached at least 60 percent in at least 

one of the years we observed—2012, 2013, or 2014, and those states exhibit no particular trend in 

married shared from 2012 to 2014. By contrast, same-sex married shares are lower in states that 

legalized same-sex marriage in 2011 or later, and those married shares increased from 2012 to 2014. 

We will use the observed same-sex married shares in the early adopter states to generate a national 

estimate of the long-run share of same-sex household couples that will likely marry.

FIGURE 3

Share of Same-Sex household Couples that are Married in 2012, 2013, and 2014 by Year of State 

Legalization

Source: Authors’ tabulations from the 2004-2014 American Community Survey.

Notes: The figure includes all households with a same-sex married or cohabiting partner.

Another way to look at the data is to examine the shares of the population that are married, 

cohabiting, or unpartnered. Identifying the sexuality of ACS respondents is fairly straightforward for 

50%

61%

44%

61%

35%

22%

30%

24% 26%

60%

53%

41%

63%

46%

36% 37%

31% 30%

56%

67%

62%

52%

48%

54%

49%

39%

34%

0%

20%

40%

60%

80%

2004 2008 2009 2010 2011 2012 2013 2014 2015

Year of Same-Sex Marriage Legalization

2012 2013 2014 Percent
1 6 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

coupled people, because the survey identifies the sex of the partner. However, it is more difficult for 

unpartnered people. Box 1 describes our method for assigning sexuality to these respondents.

BOX1

Assigning Sexuality to Unpartnered People

Using population estimates from the 2014 U.S. Religious Landscape Study and 2002 National Survey of 

Family Growth, we classified 1.8 percent of the ACS sample as gay or lesbian. We estimated the number 

of unpartnered gays and lesbians by subtracting the observed number of married and cohabiting gays 

and lesbians from the calculated total number of gays and lesbian. We classified the remaining 

unpartnered people as heterosexual.

While there is uncertainty surrounding this calculation, the important information for this study is

the number of gays and lesbians who choose to marry or cohabit, which we observe on the ACS. We use 

the 1.8 percent lesbian and gay share to calculate lesbian and gay marriage and cohabitation rates at 

each age using the following relationships.

LG population = 1.8*total population

Unpartnered LG = LG population – married LG population – cohabiting LG population

Unpartnered heterosexual = total population – LG population – married heterosexual population –

cohabiting heterosexual population.

In chapters 5 and 6 we present estimates of the effect of legal same-sex marriage using both higher 

and lower gay and lesbian marriage rates based on the 1.8 percent lesbian and gay share assumption. In 

each of these simulations, the number of lesbians and gays remain unchanged. We simply increase or 

decrease the simulated number of same-sex married couples.

Figures 4 and 5 show these three statuses (married, cohabiting, unpartnered) by age for 

heterosexual men and women and for gays and lesbians, respectively based on pooled 2012-2014 ACS 

data. Before age 20, few people are living in household couples. This pattern changes dramatically as 

people age through their 20s, with some heterosexuals cohabiting and many marrying (figure 4). By age 

34, more than half of heterosexuals are married and another 9 percent are cohabiting. By age 50, 59 

percent are married and another 4 percent are cohabiting. The share married edges up 2 percentage 

points by age 65 and the share cohabitating edges down 2 percentage points. 
CHAPTER 3: NUMBER AND CHARACTERISTICS OF SAME-SEX COUPLES 1 7

FIGURE 4

Share of Heterosexuals that Are Married, Cohabitating, or Unpartnered by Age, 2012-2014

Source: Authors’ tabulations from the 2012-2014 American Community Survey.

Notes: The figure includes all people ages 15 to 65 whom we classify as heterosexual. 

FIGURE 5

Share of Gays and Lesbians that Are Married, Cohabitating, or Unpartnered by Age, 2012-2014

Source: Authors’ tabulations from the 2012-2014 American Community Survey.

Notes: The figure includes all people ages 15 to 65 whom we classify as gay or lesbian. 

0%

20%

40%

60%

80%

100%

15 20 25 30 35 40 45 50 55 60 65

Age

Percent

Unpartnered

Cohabit

Married

0%

20%

40%

60%

80%

100%

15 20 25 30 35 40 45 50 55 60 65

Age

Percent

Unpartnered

Cohabit

Married
1 8 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

Coupling status differs in four important ways between heterosexuals and gays and lesbians. First, 

many fewer gays and lesbians marry; the married share of that population peaks at 16 percent, 

compared with 62 percent for heterosexuals. Second, gays and lesbians tend to form household couples 

relatively late in life. Whereas the share of heterosexuals in household couples plateaus by about age 

40, the share of gays and lesbians in household couples rises sharply in their 40s and does not peak until 

age 50. Third, gays and lesbians are much less likely to form household couples than heterosexuals; at 

age 50, 64 percent of heterosexuals are in household couples, compared with only 49 percent of gays 

and lesbians. Fourth, the share of adults in household couples—married or unmarried—declines after 

age 50 declines for gays and lesbians but remains steady for heterosexuals. This difference may reflect 

the much more hostile environment that older gays and lesbians experienced when young, compared 

with gays and lesbians born a decade or more earlier. 

The relatively low share of same-sex household couples that are married in 2012-2014 partly 

reflects legal limitations on same-sex marriage. Figure 6 compares data on same-sex coupling in 2012-

2014, comparing outcomes in Massachusetts, which legalized same-sex marriage in 2004 and Texas, 

which only legalized same-sex marriage after the Supreme Court’s 2015 Obergefell decision. Marriage 

rates among gays and lesbians are considerably higher in Massachusetts than in Texas. 

Although gay men marry and form unmarried cohabitating households at about the same rate as 

lesbians, gays and lesbians tend to enter into these relationships at different ages (figure 7). Lesbians 

enter a household partnership (couple) and marry at younger ages than do gay men. While gay men 

couple at later ages than lesbians, gay men are more likely to enter or remain in a same-sex partnership 

after age 40 than lesbians.
CHAPTER 3: NUMBER AND CHARACTERISTICS OF SAME-SEX COUPLES 1 9

FIGURE 6

Share of Gays and Lesbians in Household Couples and Married by Age, 2012-2014

Massachusetts and Texas

Source: Authors’ calculations from the 2012-2014 American Community Survey.

Notes: Estimates are restricted to gays and lesbians ages 15 to 65 in Massachusetts and Texas. Couples include both cohabiting 

and married individuals in 2012-2014. 

FIGURE 7

Share of Gays and Lesbians that are Coupled and Married by Age

Source: Authors’ calculations from the 2012-2014 American Community Survey.

Notes: Estimates are restricted to gays and lesbians ages 15 to 65. The data are smoothed by including three observations per 

person: one at their reported age, one at their age minus one, and one at their age plus one. See text for details. 

0%

10%

20%

30%

40%

50%

60%

15 20 25 30 35 40 45 50 55 60 65

Age

Percent

MA Couples

TX Couples

MA Married

TX Married

0%

10%

20%

30%

40%

50%

60%

15 20 25 30 35 40 45 50 55 60 65

Age

Percent

Female Coupled

Male Coupled

Female Married

Male Married
CHAPTER 4: DEMOGRAPHIC CHARACTERISTICS OF SAME-SEX COUPLES 2 0

Chapter 4: Demographic 

Characteristics of Same-Sex 

Cohabiting and Married Couples

This chapter looks at the age, educational attainment, race and ethnicity, and personal earnings of

heterosexual and homosexual men and women in household couples. Along each of these four 

dimensions, we make three comparisons: gays and lesbians versus heterosexuals, men versus women, 

and married versus cohabiting couples. We also examine how age, education, race and ethnicity, and 

earnings differ between partners within same-sex and opposite-sex couples. These differences help 

determine the long-term stability of partnerships and the importance of Social Security spouse and 

survivor benefits to married couples. The expected duration of survivor benefits increases as the age 

difference between partners widens. The larger the earnings difference, the larger is the amount of 

Social Security spouse and survivor benefit to the lower-earner partner. 

The data presented below come from the ACS. When examining differences by marital status, we 

used 2014 data. We limited the data for same-sex couples to those living in states that had legalized 

marriage before January 1, 2013, allowing same-sex couples at least two years to legally marry within 

their state.

3 This restriction means that the demographic characteristics of married same-sex people 

were more likely to be closer to their long-run averages than if all states were included. When 

examining differences within couples, we used pooled 2012-2014 ACS data with no state restrictions. 

We limit the samples to adults ages 20 and older when most adults have completed high school and are 

beginning to couple.

The main findings from this section are that same-sex household couples are more likely to remain 

unmarried at older ages while cohabitation is largely a transitional state for opposite-sex couples who 

quickly move into marriage as they age. Same-sex household couples are more highly educated, more 

non-Hispanic white, and have higher earnings than opposite-sex household couples. Same-sex 

household couples are also more likely to be partnered with someone in a different race and age group 

than opposite-sex couples but are more likely to be partnered with someone with equal earnings.

Despite lower rates of marriage among same-sex household couples compared to opposite-sex 

household couples, cohabiting same-sex households own homes at rates similar to married couples, 

suggesting that these cohabiting partners are in committed relationships.
CHAPTER 4: DEMOGRAPHIC CHARACTERISTICS OF SAME-SEX COUPLES 2 1

Age

The age pattern of cohabitation is different for same-sex household couples than for opposite-sex 

household couples. Figure 8 shows the age distribution in 2014 of eight population groups of household

couples based on gender, sexual orientation, and marriage/cohabiting status. The most striking 

difference is the high share of people younger than age 35—the bottom two categories—among 

cohabiting opposite-sex couples. Because heterosexuals marry in such high numbers, opposite-sex 

cohabitation is generally confined to the young. Among same-sex couples, by contrast, people younger 

than 35 make only a slightly larger share of unmarried couples than married couples.

Opposite-sex couples are more likely to be partnered with someone in the same age group than are 

same-sex couples. Figure 9 shows the percentage of household heads that live with a partner in the 

same age categories among same-sex and opposite-sex household couples. For example, among 35 to 

44 year olds, 63 percent of heads of opposite-sex couples have a partner who is in the same age range; 

the comparable share for same-sex couples is 47 percent. At all ages, head and partner ages are more 

similar for opposite-sex couples than for same-sex couples.

FIGURE 8

Age Distribution of Married and Cohabiting Couples by Sexual Orientation and Sex, 2014

Source: Authors’ calculations from the 2014 American Community Survey.

Notes: Estimates are based on cohabiting or married individuals ages 20 and older in 2014. The same-sex sample is limited to 

married or cohabiting same-sex individuals living in states that legalized same-sex marriage by 2012.

1 2 5 5 2 1

15 9

17 12

20 24

15 12

36

20 35 21

23

23

21

20

20

23

28 32

27

28

23

22

15 16 17 14

16

15

21

22

9 10 18 20

9 5

19 24

5 6

0

20

40

60

80

100

Married

Women

Married

Men

Cohabiting

Women

Cohabiting

Men

Married

Women

Married

Men

Cohabiting

Women

Cohabiting

Men

Same-Sex Opposite-Sex

Percent

65+

55-64

45-54

35-44

25-34

20-24
2 2 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

FIGURE 9

Percentage of Married and Cohabiting Couples Ages 20 and Older within the Same Age Group by 

Sexual Orientation, 2012-2014

Source: Authors’ calculations from the 2012-2014 American Community Survey.

Notes: Estimates are based on cohabiting or married adults ages 20 and older in 2012-2014. 

Education

For those in household couples, married and cohabiting gays and lesbians have much higher rates of 

college attainment than married and cohabiting heterosexuals (figure 10). While at least 50 percent of 

married and cohabitating gays and lesbians have a college degree, the shares for heterosexuals range 

from 35 percent for married heterosexual women to 20 percent for cohabiting heterosexual men. 

Heterosexual cohabiters have much lower rates of college completion than married heterosexual 

people (partly because they are younger). Among gays and lesbians, the rates of college completion do 

not vary much, with women cohabiters having the lowest rate (50 percent). 

The higher educational attainment of same-sex couples is likely due to several factors, but the 

actual causes cannot be determined from our data. The observed differences may arise because gays 

and lesbians seek advanced education at higher rates than heterosexuals; more-educated gays and 

lesbians are more likely to partner than less-educated gays and lesbians; and more-educated individuals 

are more likely to report living with a same-sex partner than less-educated individuals.

45

66 63 63 65

93

40

58

47

55

48

77

0

20

40

60

80

100

20-24 25-34 35-44 45-54 55-64 65+

Husband (Head) Age

Percent of Household Couples

Opposite-Sex Couples Same-Sex Couples
CHAPTER 4: DEMOGRAPHIC CHARACTERISTICS OF SAME-SEX COUPLES 2 3

FIGURE 10

Educational Distribution of Married and Cohabiting Couples by Sexual Orientation and Sex, 2014

Source: Authors’ calculations from the 2014 American Community Survey.

Notes: Estimates refer to cohabiting or married adults ages 20 and older in 2014. The same-sex sample is limited to married or 

cohabiting same-sex individuals living in states that legalized same-sex marriage by 2012.

Figure 11 looks at the similarity of partners within same-sex and opposite-sex household couples. 

At lower education levels, same-sex couples are much less likely have a partner with the same 

education. This is partly driven by the high rate of college attainment among gays and lesbians. Yet 

another consequence of this high rate of college completion is that same-sex household heads are more 

likely to be partnered with another college graduate than heads of opposite-sex households. 

4 3 4 2 8 9 11 13

21 22 26

19

33 33 36

22 20 42

20

21

24 22

29

24

53 55 50 57

35 36

25 20

0

20

40

60

80

100

Married

Women

Married

Men

Cohabiting

Women

Cohabiting

Men

Married

Women

Married

Men

Cohabiting

Women

Cohabiting

Men

Same-Sex Opposite-Sex

Percent

College Graduate

Some College

High School

Graduate

Less Than High

School
2 4 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

FIGURE 11

Percentage of Married and Cohabiting Couples Ages 20 and Older with the Same Education by Sexual 

Orientation, 2012-2014

2012-2014

Source: Authors’ calculations from the 2012-2014 American Community Survey.

Notes: Estimates refer to cohabiting or married heads ages 20 and older in 2012-2014.

Race and Ethnicity

Among married and cohabiting adults in 2014, the non-Hispanic white share among same-sex couples is 

much higher than the comparable share among opposite-sex couples (figure 12). Polling data indicates 

that sexual orientation does not differ much by race and ethnicity (Pew 2013), so this difference is 

driven by racial and ethnic disparities in the transition from unpartnered status to cohabitation and 

marriage. 

Cohabiters are also slightly more likely than married people to be non-white: among heterosexual

cohabiters, 62 to 65 percent are white, compared with 73 percent of heterosexual married people. 

Among same-sex couples, the white share is higher and the racial and ethnic difference between 

cohabiters and married is smaller: 81 to 82 percent of same-sex cohabiters are white versus 84 to 86

percent of married gays and lesbians.

Figure 12 also shows that there are no large gender differences and only one small one: gay men are 

more likely to be white if they are married than cohabiting (86 versus 81 percent), whereas the racial 

55 55

35

66

32

42

37

76

0

20

40

60

80

Less than High School High School Graduate Some College College Graduate

Husband (Head) Educational Attainment

Percent Opposite-Sex Couples Same-Sex Couples
CHAPTER 4: DEMOGRAPHIC CHARACTERISTICS OF SAME-SEX COUPLES 2 5

and ethnic differences between married and cohabitating adults somewhat smaller among lesbians (84

versus 82 percent white).

Interestingly, Hispanics are more prevalent than blacks among married and cohabiting couples,

even though the overall adult population shares are very similar, reflecting blacks’ low marriage and 

cohabitation rates. Heterosexual Hispanics are also more prevalent among cohabiters (about 20 

percent) than married couples (13 percent).

FIGURE 12

Educational Distribution of Married and Cohabiting Couples by Sexual Orientation and Sex, 2014

Source: Authors’ calculations from the 2014 American Community Survey.

Notes: Estimates refer to cohabiting or married individuals ages 20 and older in 2014. The same-sex sample is limited to married 

or cohabiting same-sex individuals living in states that legalized same-sex marriage by 2012.

Same-sex household couples are less likely to be with a partner of the same race and ethnicity than 

opposite-sex household couples (figure 13). This difference partly reflects the relative dearth of nonwhites among same-sex household couples, making it difficult for gays and lesbians of color to find 

partners of color, and partly reflects the openness of gays and lesbians to relating to someone different 

from themselves. Among white household heads, there is only a small gap in the share with white 

partners between opposite-sex and same-sex couples.

84 86 82 81 73 73 65 62

5 3 7 5

7 7

11 14

7 7 8 10 13 13 20 21

5 5 3 4 7 6 4 3

0

20

40

60

80

100

Married

Women

Married

Men

Cohabiting

Women

Cohabiting

Men

Married

Women

Married

Men

Cohabiting

Women

Cohabiting

Men

Same-Sex Opposite-Sex

Percent

Other

Hispanic

Black NonHispanic

White NonHispanic
2 6 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

FIGURE 13

Percent of Married and Cohabiting Couples Ages 20 and Older in which Both Partners Belong to the 

Same Racial and Ethnic Group by Sexual Orientation, 2012-2014

Source: Authors’ calculations from the 2012-2014 American Community Survey.

Notes: Estimates refer to cohabiting or married couple heads ages 20 and older in 2012-2014.

Individual Earnings

Figure 14 shows the distribution of real earnings ($2015 price-adjusted dollars) across our eight

population groups. First, with just one exception, women are more likely to be out of the labor force 

(have no earnings) than men. The exception is among married same-sex couples in which 23 percent of 

women and 22 percent of men have zero earnings. In contrast, 38 of women and 25 percent of men in 

opposite-sex marriages have no earnings. Among opposite-sex cohabiters, 23 percent of women and 15 

percent of men have no earnings, while the comparable figures among same-sex cohabiters are 19 

percent for women and 14 percent for men. 

Second, the prevalence of high earnings (greater than $75,000 per year) varies quite a bit by gender 

and sexual orientation. Because gays and lesbians tend to have more education than heterosexuals, 

they are more likely to have high earnings. Consequently, the groups with the highest shares of high 

earners are gay men (36 percent for cohabiters and 34 percent for those who are married). By contrast, 

the share of high earners among heterosexual men is just 24 percentfor those who are married and 10 

percent for those cohabiting (who tend to be relatively young).

95 93

81

73

91

68

53

41

0

20

40

60

80

100

Non-Hispanic White Non-Hispanic Black Hispanic Other

Husband (Head) Race and Ethnicity

Percent of Couples Opposite-Sex Couples Same-Sex Couples
CHAPTER 4: DEMOGRAPHIC CHARACTERISTICS OF SAME-SEX COUPLES 2 7

FIGURE 14

Real Earnings Distribution of Married and Cohabiting Couples by Sexual Orientation and Sex, 2014

Source: Authors’ calculations from the 2014 American Community Survey.

Notes: Estimates refer to cohabiting or married individuals ages 20 and older in 2014. The same-sex sample is limited to married 

or cohabiting same-sex individuals living in states that legalized same-sex marriage by 2012.

Third, many lesbians have high earnings, including 24 percent of those who are married—the same 

share as for men in opposite-sex marriages—and 21 percent of those cohabiting—more than twice the 

rate as for men in opposite-sex cohabiting couples. A much lower share of heterosexual women are high 

earners—9 percent of those married and 5 percent of those cohabiting.

Despite strong differences by sexual orientation and marriage in earnings distributions among 

people in household couples, partners in same-sex couples are only somewhat more likely than partners 

in opposite sex couples to have similar earnings. In the middle of the earnings scale (between $25,000 

and $75,000), the share of couples in which partners have similar earnings is nearly identical in samesex and opposite-sex couples (figure 15). For household heads at the top and bottom of the earnings 

scale (those with less than $25,000 in earnings and those earning at least $75,000), same-sex couples 

are slightly more likely than opposite couples to be with someone with the same earnings level.

Whether married adults receive Social Security spouse and survivor benefits and how much they 

gain depends on how much their lifetime earnings differed from their spouse’s lifetime earnings. The 

relatively low share of same-sex household couples in which both partners have similar cross-sectional 

earnings suggests that many married gays and lesbians could eventually receive Social Security spouse 

22 23 19 14

38

25 23 15

15 15 20

17

24

15

37

31

22 14

26

16

20

21

26

31

17

13

14

17

10

16

9

13

24

34

21

36

9

24

5 10

0

20

40

60

80

100

Married

Women

Married

Men

Cohabiting

Women

Cohabiting

Men

Married

Women

Married

Men

Cohabiting

Women

Cohabiting

Men

Same-Sex Opposite-Sex

Percent

75K or more

50K-75K

25K-50K

1-25K

No Earnings
2 8 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

and survivor benefits and that the legalization of same-sex marriage could boost their future retirement 

incomes.

FIGURE 15

Percentage of Married and Cohabiting Couples Ages 20 and Older in which Both Partners Have 

Similar Earnings, 2012-2014

By Sexual Orientation and Household Head’s Earnings

Source: Authors’ calculations from the 2012-2014 American Community Survey.

Notes: Estimates refer to cohabiting or married heads ages 20 and older in 2012-2014.

Housing Wealth of Same-Sex and Opposite-Sex Couples

Among heterosexual household couples, married couples are much more likely to own their homes at all 

ages under 65 than unmarried couples (figure 16). By contrast, among same-sex couples, the home 

ownership rate is only slightly lower for cohabiters than for married couples (figure 17). This suggests

that many unmarried same-sex couples are in committed relationships and willing to pool resources and 

purchase a home together. 

42

26

33

27

46 48

32 33

26

50

0

20

40

60

None 0 - $25,000 $25,000 - $50,000 $50,000 - $75,000 $75,000 or More

Husband (Head) Earned Income

Percent Opposite-Sex Couples Same-Sex Couples
CHAPTER 4: DEMOGRAPHIC CHARACTERISTICS OF SAME-SEX COUPLES 2 9

FIGURE 16

Opposite-Sex Home Ownership, Married versus Cohabiting, 2012-2014

Source: Authors’ tabulations of 2012-2014 American Community Survey.

Notes: Estimates refer to opposite-sex married and cohabiting household heads ages 20 and older in 2012-2014.

FIGURE 17

Same-Sex Home Ownership, Married versus Cohabiting, 2012-2014

Source: Authors’ tabulations of 2012-2014 American Community Survey.

Notes: The figure includes same-sex married and cohabiting household heads ages 20 and older in 2012-2014.

0%

20%

40%

60%

80%

100%

20-29 30-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80-84

Age

Home Ownership Rate (percent) Married Cohabiting

0%

20%

40%

60%

80%

100%

20-29 30-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80-84 85+

Age

Homeownership Rate (percent) Married Cohabiting
3 0 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

Home ownership rates of married couples are almost identical across all ages for opposite-sex and 

same-sex couples (figure 18). This underscores the similarity of decision-making about this major 

purchase for same-sex couples with opposite-sex couples. In fact, same-sex married and same-sex 

cohabiters tend to own homes of greater value than opposite-sex married couples, while home values 

are lowest for opposite-sex cohabiters (figure 19). Higher home values among same-sex couples reflect 

their tendency to live in high-cost urban areas and to be college educated. The high homeownership 

rates and home values of cohabiting same-sex couples show that same-sex commitments are common 

and comparable to married opposite-sex couples.

FIGURE 18

Married Opposite-Sex and Same-Sex Couples, Home Ownership Rate, 2012-2014

Source: Authors’ tabulations of 2012-2014 American Community Survey.

Notes: Figure includes married opposite-sex and married same-sex household heads ages 20 and older in 2012-2014.

0%

20%

40%

60%

80%

100%

20-29 30-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80-84 85+

Age

Homeownership Rate (percent) Married Opposite-Sex Married Same-Sex
CHAPTER 4: DEMOGRAPHIC CHARACTERISTICS OF SAME-SEX COUPLES 3 1

FIGURE 19

Average Home Values among Homeowners among Opposite-Sex Married and Same-Sex Married and 

Cohabiting, by Age, 2012-2014

Source: Authors’ tabulations of 2012-2014 American Community Survey.

Notes: Figure includes opposite-sex married, same-sex married, and same-sex cohabiting household heads ages 20 and older in 

2012-2014 who own their home (with or without a mortgage). Home values are in nominal dollars.

$0

$50,000

$100,000

$150,000

$200,000

$250,000

$300,000

$350,000

$400,000

20-29 30-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80-84 85+

Age

Average Home Value (dollars)

Same-Sex Cohabiting Same-Sex Married Opposite-Sex Married
3 2 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

Chapter 5: Estimation Models

As people move through life, their marital status and living arrangements often change. In this chapter, 

we show the parameter estimates for hazard models describing these decisions. We estimated hazard 

models for individual transitions from 1) unpartnered to cohabitating, 2) from cohabitating to married 

or separated (i.e., leave the cohabitating relationship before marriage), 3) from married to separated, 

and 4) from separated to divorced. Some household couples transition directly from unpartnered to 

married—that is, the duration of their cohabitation spell when the marriage begins is zero years. These 

transitions are shown in figure 20. Individuals are subject to an annual mortality hazard. Widows enter 

the unpartnered pool the year after their spouse dies. 

Same-Sex Cohabitation

No longitudinal data exists for same-sex couples with sufficient sample size for estimating 

cohabitation, marriage, divorce, and separation hazards. We used cross-sectional ACS data to estimate 

cohabitation and marriage hazards for same-sex individuals. We used hazard models estimated with 

data on opposite-sex couples to generate divorce and separation probabilities for same-sex couples.

We calculated annual same-sex cohabitation rates by measuring the change in the share of the gay 

and lesbian population that transition from an unpartnered state to a partnered state at each age in 

pooled 2012-2014 ACS data. We calculated these hazards separately for men and women by single 

year of age and race using the following equations:

1. cohab(t+1) = cohab(t) - die(t+1) - marry(t+1) -sep(t+1) + newcohab(t+1)

2. newcohab(t+1) = cohab(t+1) - cohab(t) + die(t+1)+marry(t+1)+sep(t+1)

3. cohabitation rate = newcohab(t+1)/unpartnered(t)

where cohab is the number of gays and lesbians cohabiting, die is the number estimated to die using ageand gender-specific mortality probabilities, marry is the number who marry, sep is the number who 

separate using age- and gender-specific divorce probabilities from opposite-sex couples, and newcohab

is the number who enter a cohabitating union.
CHAPTER 5: ESTIMATION MODELS 3 3

FIGURE 20

Flowchart of Demographic Hazards

Source: Updated DYNASIM4 demographic hazard models.

Appendix B shows our estimated same-sex cohabitation hazards by sex, age, and race and ethnicity. 

Figures 21 and 22 show the cohabitation hazards for same-sex women and men respectively. NonHispanic whites cohabit at higher rates than same-sex individuals of color. Lesbians enter cohabitation 

at younger ages than gay men.
3 4 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

FIGURE 21

Cohabitation Hazard Rate by Age and Race for Lesbian Women

Source: Authors’ calculations from 2012-2014 American Community Survey.

FIGURE 22

Cohabitation Hazard Rate by Age and Race for Gay Men

Source: Authors’ calculations from 2012-2014 American Community Survey.

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

15 20 25 30 35 40 45 50 55 60

Age

Percent White Black Hispanic Other

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

20%

15 20 25 30 35 40 45 50 55 60

Age

Percent White Black Hispanic Other
CHAPTER 5: ESTIMATION MODELS 3 5

Mate-Matching

For each individual selected to transition from an unpartnered state to a partnered state, we 

imputed the characteristics of the desired partner using the distribution of observed characteristics of 

newly married couples in 2010-2014 ACS data. We did this separately for same-sex male couples, 

same-sex female couples, and opposite-sex couples. Ideally, we would have used the characteristics of 

new cohabitants to define the characteristics of newly coresiding couples, but we could not observe 

new cohabitation on the ACS. Instead we used the characteristics of couples that were married within 

the last 12 months.

Unlike the characteristics of all household couples described in Chapter 4, these partner 

characteristics are limited to newly married couples. This limitation is important mainly because the age 

difference between new partners tends to be larger for relationships that occur at older ages than at 

younger ages. Table 2 shows the distribution of the household head’s age by partner’s age for newly 

married same-sex female couples, same-sex male couples, and opposite-sex couples. Table 3 shows the 

distribution of the household head’s education by partner’s education for newly married female 

couples, same-sex male couples, and opposite-sex couples. Table 4 shows the distribution of the 

household head’s race and ethnicity by the partner’s race and ethnicity for newly married same-sex 

women, same-sex men, and heterosexual couples.
3 6 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

TABLE 2

Distribution of Household Head’s Age by Partner’s Age and Couple Type

Row Percent

15-24 25-34 35-44 45-54 55-64 65+

Partner Age Same-Sex Female Head Age

15-24 46 31 11 8 4 1

25-34 9 59 23 6 2 1

35-44 1 17 49 28 4 1

45-54 0 2 17 56 20 4

55-64 0 1 4 30 47 18

65+ 0 0 1 6 27 66

Same-Sex Male Head Age

15-24 36 37 15 9 3 1

25-34 5 55 25 11 3 1

35-44 1 13 43 33 8 2

45-54 0 2 18 51 22 6

55-64 0 1 6 28 45 20

65+ 0 0 1 10 30 58

Opposite-Sex Male Age

15-24 51 44 4 1 0 0

25-34 6 67 22 3 0 0

35-44 1 16 53 25 4 1

45-54 0 3 19 52 22 4

55-64 0 1 4 23 49 22

65+ 0 0 1 5 20 73

Source: Authors’ calculations from the 2010-2014 American Community Survey.

Notes: Estimates includes all opposite-sex couples ages 18 to 80 that were married in the past 12 months and same-sex couples 

ages 18 to 80 that were cohabiting or married in the past 12 months. Row percents may not add to 100 due to rounding.
CHAPTER 5: ESTIMATION MODELS 3 7

TABLE 3

Distribution of Household Head’s Education by Partner’s Education and Couple Type

Row Percent

Partner Education

Less than 

High 

School

High School 

Graduate

Some 

College

College 

Graduate

Post 

Graduate

Same-Sex Female Head Education

Less than High School 26 43 21 6 4

High School Graduate 7 43 29 14 8

Some College 3 22 37 25 14

College Graduate 1 10 19 40 30

Post Graduate 0 5 11 28 56

Same-Sex Male Head Education

Less than High School 30 35 20 10 5

High School Graduate 6 34 27 21 12

Some College 2 18 34 28 18

College Graduate 1 9 19 41 31

Post Graduate 0 6 14 31 49

Opposite-Sex Male Education

Less than High School 50 37 10 2 1

High School Graduate 15 57 20 6 2

Some College 7 41 36 12 3

College Graduate 2 22 26 39 12

Post Graduate 2 15 19 34 31

Source: Authors’ calculations from the 2010-2014 American Community Survey.

Notes: Estimates include all opposite-sex couples ages 18 to 80 that were married in the past 12 months and same-sex couples 

ages 18 to 80 that were cohabiting or married in the past 12 months. Row percents may not add to 100 due to rounding.
3 8 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

TABLE 4

Distribution of Household Head’s Race and Ethnicity by Partner’s Race and Ethnicity and Couple 

Type

Row Percent

Partner Race

White NonHispanicBlack NonHispanic Hispanic Other

Same-Sex Female Head Race

White Non-Hispanic 92 2 5 1

Black Non-Hispanic 21 72 6 2

Hispanic 36 4 58 2

Other 46 4 7 43

Same-Sex Male Head Race

White Non-Hispanic 89 2 6 3

Black Non-Hispanic 39 54 5 1

Hispanic 53 3 42 1

Other 67 1 8 24

Opposite-Sex Male Head Race

White Non-Hispanic 89 4 5 1

Black Non-Hispanic 7 90 3 1

Hispanic 16 4 78 1

Other 36 5 8 51

Source: Authors’ calculations from the 2010-2014 American Community Survey.

Notes: Estimates include all opposite-sex couples age 18 to 80 that were married in the past 12 months and same-sex couples 

ages 18 to 80 that were cohabiting or married in the past 12 months. Row percents may not add to 100 due to rounding.

For each individual projected to transition from an unpartnered state to a partnered state, 

DYNASIM used these distributions to impute the age, race, and education of the partner. For all 

heterosexual individuals seeking a partner, DYNASIM compared the woman’s characteristics with the 

man’s characteristics and found the best match using a minimum distance function. For gays and 

lesbians, men were matched with other men and women were matched with other women. In all cases, 

matched household couples were incrementally removed from the mate market until the market 

cleared (i.e., there were no partners left to choose). Anyone left in the mate market without a valid 
CHAPTER 5: ESTIMATION MODELS 3 9

match remained unmatched. The minimum distance function selected the best match among all valid 

choices, but the selected partner did not necessarily match on all desired characteristics. 

Same-Sex Marriage

We estimated a same-sex marriage hazard model using the 2012-2014 ACS data. We restricted the 

sample to individuals ages 15 and older living with a same-sex partner in states that legalized marriage 

before 2014. The sample includes all unmarried respondents and those married in the past 12 months. 

We estimated separate logistic hazard models for men and women (Appendix C includes summary 

statistics for the estimation samples and logistic parameter estimates).

We include age as a series of piece-wise linear splines with kinks at ages 20, 25, 30, 40, 50, and 55

(Barron and Kastberg 2016).The age splines include more inflection points at younger ages when the 

marriage rates change more quickly and fewer inflection points at older ages when marriage rates

flatten out. We estimated the probability of marriage relative to the year that same-sex marriage was 

legalized in each couples’ state of residence. We also examined marriage probabilities by race (omitting 

the non-Hispanic whites as the reference group) and education (omitting high school graduates as the 

reference group). We included the absolute value of the difference in partner ages and education and, 

for the female marriage model, the presence of children.

Figures 23 and 24 compare actual (report getting married in the last 12 months) and predicted 

marriage rates by age for same-sex female and male household couples, respectively. Marriage patterns 

differed substantially for men and women. Female same-sex marriage probabilities increased from ages

20 to 40 and then remained fairly level. Male same-sex marriage probabilities were lower than female 

probabilities at younger ages, but increased steadily with age through age 80. 
4 0 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

FIGURE 23

Actual and Predicted Probability of Marriage by Age among Female Same-Sex Household Couples

Source: Authors estimates from the 2012-2014 American Community Survey.

Notes: Estimates were based on a sample of women ages 20 and older living with a same-sex partner in a state that legalized 

same-sex marriage before 2014. The sample included all unmarried women and women married in the prior 12 months. .

FIGURE 25

Actual and Predicted Probability of Marriage by Age among Male Same-Sex Household Couples

Source: Authors estimates from the 2012-2014 American Community Survey.

Notes: Estimates were based on a sample of men ages 20 and older living with a same-sex partner in a state that legalized samesex marriage before 2014. The sample included all unmarried men and men married in the prior 12 months. 

0%

5%

10%

15%

20%

25%

30%

35%

19 24 29 34 39 44 49 54 59 64 69 74 79

Age

Probability of Marriage (percent)

Estimated Probability New Marriage

0%

5%

10%

15%

20%

25%

30%

35%

19 24 29 34 39 44 49 54 59 64 69 74 79

Age

Probability of Marriage (percent)

Estimated Probability New Marriage
CHAPTER 5: ESTIMATION MODELS 4 1

Opposite-Sex Marriage

For heterosexuals, we estimated demographic hazard probabilities using detailed information on 

changes in marital status and living arrangements available in the 1979 National Longitudinal Survey of 

Youth (NLYS79) and the 1997 National Longitudinal Survey of Youth (NLSY97).

The NLSY79 is a nationally representative sample of 12,686 young men and women who were ages 

14 to 22 when they were first surveyed in 1979. These individuals were interviewed annually through 

2002 and biennially thereafter. Currently, the NLSY79 includes data from ages 15 to 55 for years 1979 

to 2012. The NLSY97 consists of a nationally representative sample of approximately 9,000 youths who 

were ages 12 to 16 on December 31, 1996. Round 1 of the survey took place in 1997. These individuals 

were interviewed annually from 1997 to 2011 and again in 2013. Currently, the NLSY97 includes data 

from ages 13 to 33 for years 1997 to 2013. During the biennial survey periods, the survey collects 

annual retrospective data on coresidency, marriage, divorce, and separation.

Both NLSY79 and NLSY97 include basic demographic information including age, sex, education, 

marital status, and number and duration of marriages. They also include information on labor force 

participation and earnings, number and ages of children, relationship to all members of the family, and 

some parental information. In addition, they collect data on the current partner’s age, race, education, 

and labor force participation. 

Appendix D shows estimated logistic cohabitation hazard models for heterosexual men and women 

by race and ethnicity. Appendix E shows estimated logistic marriage and separation hazard models for 

opposite-sex cohabiting couples. Appendix F shows estimated logistic separation hazard models for 

married couples. Appendix G shows estimated logistic divorce models for separated married couples.
4 2 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

Chapter 6: Projection Results

This chapter describes our DYNASIM simulation results showing how legal recognition of same-sex 

marriage will affect government spending and revenues and family incomes. Same-sex marriage will 

provide some gays and lesbians with spouse and survivor Social Security benefits, raising retirement 

incomes and Social Security outlays. It will also affect federal income tax payments, as same-sex 

spouses pool their incomes and file tax returns jointly. In addition, same-sex marriage will change 

eligibility for SSI and affect take-up of Medicare Part B and Part D coverage, as some married gays and 

lesbians gain access to their spouse’s employer-sponsored health plans. 

We benchmarked DYNASIM’s starting number of same-sex couples (married or cohabiting) to data 

from the 2013 and 2014 ACS by age, sex, and state. We assigned lesbian and gay status to all cohabiting 

same-sex couples and imputed lesbian and gay status to unpartnered, never married individuals such 

that the lesbian and gay share was 1.8 percent at each age.

Because of the uncertainty of how high same-sex marriage rates will be, we simulated low, medium, 

and high estimates of number of same-sex marriages using benchmarks derived from current data. 

Nationally, 89 percent of opposite-sex household couples are now married, compared with only 59 

percent of same-sex household couples in Massachusetts, the state that first legalized same-sex 

marriage in 2004. We used the 89 percent figure for the high estimate of the share of same-sex 

household couples that will be married. We used the 59 percent figure for the moderate estimate of the 

married share among same-sex household couples. Finally, we used a 45 percent target for our low 

estimate based on the average same-sex married share among all states that legalized same-sex 

marriage before 2015. 

We used the Urban Institute’s DYNASIM microsimulation model to simulate four scenarios: one 

that assumed that neither the federal government nor any of the states recognized same-sex marriage, 

and three that assumed complete recognition of same-sex marriage by the federal government and all 

of the states, but which differed in the prevalence of same-sex marriage, corresponding to our low, 

medium, and high same-sex marriage prevalence rates. In all four scenarios, DYNASIM projected

outcomes from 2007 to 2065. We used the difference in the simulated outcomes compared to the nosame-sex marriage baseline to estimate the distributional impact of legal recognition of same-sex 

marriage under the low, medium, and high prevalence scenarios.

For each simulation, DYNASIM projects annual demographic transitions for all individuals including 

cohabitation, marriage, separation, divorce, birth, death, disability, retirement, and benefit claiming. It 
CHAPTER 6: PROJECTION RESULTS 4 3

also projects major sources of income and wealth, including pensions from employer-sponsored defined 

benefit (DB) plans, cash balance plans, and retirement accounts—defined contribution (DC) plans, 

individual retirement accounts (IRAs), and Keoghs. Using information about marital status, living 

arrangements, and partner characteristics, DYNASIM calculates Social Security benefits, payroll taxes, 

federal and state income taxes, and health insurance coverage and premiums. For more information 

about DYNASIM see Favreault, Smith, and Johnson (2016).

Many modeled outcomes in DYNASIM use marital status and spousal characteristics to predict 

demographic transitions and income and asset levels including fertility, death, employment, wealth, 

pensions, health insurance, Social Security benefit claiming, and joint and survivor pension selection. 

Adding same-sex marriage to DYNASIM alters these behaviors for same-sex couples who marry. For

our four simulations, however, we retained the medium-marriage rate simulation for fertility, mortality, 

employment, and earnings projections and allowed only wealth and pension accumulations and 

calculated taxes and benefits associated with legal marriage to vary across the different scenarios. 

We compare before- and after-tax retirement incomes in 2015, 2025, 2035, 2045, 2055, and 2065 

for gays and lesbians ages 62 and older for the four scenarios by age, sex, marital status, education, 

number of work years, lifetime earnings quintile, and retirement income quintile and compare them to 

the baseline scenario that excludes same-sex marriage. Differences in the low, medium, and high

scenarios compared with the baseline provide information on the size and direction of the impact of the 

Supreme Court’s recent same-sex marriage decisions on retirement income. 

Our output also includes annual Social Security trust fund balances, federal income tax revenue, 

Medicare surtax, and SSI benefits for the baseline and three scenarios. For each year, we estimate the 

impact of federal recognition of same-sex marriages on government budgets for the three prevalence 

scenarios compared with the no same-sex marriage scenario.

Projections of Share of Same-Sex Marriages

DYNASIM starts with an initial sample based on data from the 2004 and 2008 panels of the Survey of

Income and Program Participation aligned to start in 2006. It then mimics what happens in the real 

world: People get older, cohabit and marry, and, if they are cohabiting or married, they may separate 

and divorce. Children are born and people die. Figure 25 shows the evolution of the share of same-sex 

adults in household couples who are married for the low, medium, and high marriage simulations. Many 

states did not legalize same-sex marriage until 2015, although some same-sex couples in all states were 
4 4 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

married before 2015 because they were married in other states which already recognized same-sex 

marriage.

FIGURE 25

Share of Same-Sex Household Couples that are Married by Simulation, 2006-2065

Source: Authors’ calculations from DYNASIM4 ID 938.

Notes: Estimates includes all gay and lesbian household heads living with a same-sex partner.

Figure 25 reflects the reality that it takes time for same-sex people to take full advantage of their 

legal right to marry, partially because some gays and lesbians start out unpartnered and have to find 

someone whom they might marry. Our medium marriage rate simulation moves towards an equilibrium 

marriage rate of about 65 percent, slightly higher than the same-sex marriage rate observed in 

Massachusetts in 2012-2104 because the population is aging and marriage is becoming more stable. 

The alternative marriage rate simulations generate marriage shares among same-sex couples that are 

about 10 percentage points higher and 10 percentage points lower than in the medium scenario.

To project future outcomes, DYNASIM simulates what happens to people as they age. As a result, 

some people move from being single to cohabiting to married, while others separate, divorce, or 

become widowed, sometimes followed by recoupling and remarriage. Figure 26 compares the share of 

gays and lesbians who are in household couples (married and cohabiting) by age in 2012-2014 (from the 

ACS) and as projected by DYNASIM over the period 2031 to 2036.

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

2006 2011 2016 2021 2026 2031 2036 2041 2046 2051 2056 2061

Year

Percent

Low Marriage Medium Marriage High Marriage
CHAPTER 6: PROJECTION RESULTS 4 5

FIGURE 26

Share of Gays and Lesbians in Household Couples by Age and Year

Source: American Community Survey 2012-2014 and DYNASIM4 ID 938 medium same-sex marriage simulation.

Notes: The sample includes all cohabiting gays and lesbians ages 15 to 65. Individuals are coupled if they live with a same-sex 

partner.

The two lines in figure 26 substantially overlap but differ in a couple of age ranges. From about ages 

25 to 40, the share of gays and lesbians in household couples is slightly higher in 2012-2014 than in the 

simulations for 2031-2036. Although the difference is not large, this discrepancy is driven by a longterm trend away from marriage and cohabitation, regardless of sexual orientation. For ages 40 to 55, 

the 2031-2036 projections track closely with 2012-2014 ACS values. After age 58, however, the 2031-

2036 projections show a slightly higher rate of coupling than the 2012-2014 ACS. The simulations 

account for a number of factors, including lower separation rates as people age and lower death rates 

for people in couples than those who are unattached. 

Figure 27 shows the shares of gays and lesbians, by age, who are married in the low, medium, and 

high marriage rate simulations. The high marriage rate simulation has the largest impact on the married 

share for those under 55, while the low rate trails substantially below the medium rate after age 30. 

0%

10%

20%

30%

40%

50%

60%

15 20 25 30 35 40 45 50 55 60 65

Age

Percent 2012-2014 2031-2036
4 6 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

FIGURE 27

Share of Gays and Lesbians Who Are Married by Age and Marriage Rate Option, 2031-2035

Source: DYNASIM4 ID 938.

Notes: The sample includes all gays and lesbians ages 15 to 70 regardless of living arrangement or marital status.

Changes in Government Programs and Federal Revenues 

and Expenditures

A major goal of this project is to show how the legalization of same-sex marriage affects participation in

various government programs and the costs and revenues of those programs. We used the projection 

capacities of the DYNASIM model to examine these impacts through 2065 under three alternative 

same-sex marriage rates. All of our comparisons are made relative to the situation in which legal samesex marriage did not exist (which itself is a simulation). 

As table 5 shows, legalizing same-sex marriage is projected to slightly raise the number of OASI 

beneficiaries. Some gays and lesbians who marry in our projections would not qualify for Social Security 

benefits on their own because they lack 40 quarters of covered employment. Once they marry, they 

become entitled to spousal and survivor benefits. Divorced individuals are eligible for spouse and 

survivor benefits if their marriage lasted at least 10 year. However, this population is so small that the 

difference between the three marriage rates is not large. 

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

15 20 25 30 35 40 45 50 55 60 65 70

Age

Percent High Marriage Medium Marriage Low Marriage
CHAPTER 6: PROJECTION RESULTS 4 7

TABLE 5

Baseline Number and Change in the Number of OASI and SSI Beneficiaries by Marriage Rate 

Simulation, 2015-2065

Thousands of people

Baseline OASI 

Beneficiaries 

(thousands)

Change in OASI 

Beneficiaries 

(thousands)

Baseline SSI 

Beneficiaries 

(thousands)

Change in SSI 

Beneficiaries 

(thousands)

Marriage Rate Marriage Rate

Year Medium Low High Medium Low High

2015 44,971 13 13 13 5,680 -7 -6 -18

2020 53,626 16 15 17 5,519 -10 -8 -17

2025 61,947 16 16 17 5,662 -13 -10 -18

2030 69,401 15 14 16 5,244 -16 -11 -20

2035 74,731 16 14 17 4,970 -16 -12 -26

2040 77,621 16 14 17 4,636 -9 -5 -21

2045 79,864 19 15 21 4,346 5 10 -16

2050 82,431 16 14 18 4,108 15 20 -1

2055 85,783 18 15 20 3,905 -2 2 -7

2060 89,424 17 15 19 3,790 11 14 -19

2065 93,615 16 15 18 3,684 3 0 -38

Source: Authors’ calculations from DYNASIM4 ID 938, comparing the no same-sex marriage and low, medium, and high same-sex 

marriage simulations.

Notes: Table includes all individuals. Changes are in thousands of people compared with the no same-sex marriage simulation.

In contrast, the number eligible for SSI benefits is projected to mostly decrease because the 

legalization of same-sex marriage will make some gays and lesbians who would otherwise qualify for SSI 

ineligible, namely those with little income and assets in their own name who marry partners with higher 

income and assets, or who gain access to spousal Social Security or pension benefits. On the other hand, 

the legalization of same-sex marriage may make someone eligible for SSI, if their individual income and 

assets exceed the single-person eligibility threshold but their resources combined with the resources of 

their spouse fall below the higher eligibility threshold that applies to married couples. As the last three 

columns of Table 5 show, the number of people affected is small, but the higher marriage rate 

simulations generally generate the larger declines in SSI participation. 

Table 6 shows the change in benefits, measured in inflation-adjusted dollars, provided by OASDI 

and SSI. As marriage opens up opportunities for Social Security spousal and survivor benefits that did 
4 8 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

not exist before same-sex marriage was recognized by the federal government, OASDI payments 

increase. However, the overall impact is small, because married gays and lesbians will represent only a 

sliver of the total population and spousal and survivor benefits are less significant than worker benefits. 

The growth in OASDI benefits attributable to the legalization of same-sex marriage will account for no 

more than 0.04 percent of all OASDI spending. SSI payments will generally fall as a result of the 

legalization of same-sex marriage, but again the overall impact will be insignificant, equal to just a 

couple of tenths of one percent of overall SSI spending. 

TABLE 6

Baseline OASDI Benefits and SSI Benefits and Change in OASDI and SSI Benefits by Marriage Rate 

Simulation, 2015-2065

Billions of dollars

Baseline 

OASDI 

Benefits 

($billions)

Change in OASDI Benefits 

($billions)

Baseline SSI 

Benefits 

($billion)

Change in SSI Benefits 

($billions)

Marriage Rate Marriage Rate

Year Medium Low High Medium Low High

2015 914 0.15 0.16 0.14 39 -0.07 -0.07 -0.15

2020 1,186 0.22 0.22 0.23 40 -0.10 -0.08 -0.16

2025 1,580 0.35 0.34 0.37 44 -0.13 -0.10 -0.17

2030 2,074 0.53 0.48 0.55 46 -0.15 -0.10 -0.19

2035 2,630 0.76 0.68 0.80 50 -0.17 -0.13 -0.27

2040 3,254 1.10 0.94 1.18 54 -0.11 -0.06 -0.23

2045 3,982 1.44 1.24 1.54 58 0.14 0.23 -0.21

2050 4,933 1.94 1.67 2.11 63 0.38 0.45 -0.02

2055 6,164 2.64 2.24 2.96 70 -0.05 0.04 -0.11

2060 7,735 3.41 2.84 3.81 78 0.23 0.31 -0.53

2065 9,717 4.12 3.50 4.64 87 0.24 0.16 -0.89

Source: Authors’ calculations from DYNASIM4 ID 938, comparing the no same-sex marriage and low, medium, and high same-sex 

marriage simulations.

Notes: Table includes all individuals. Changes are in $billions nominal compared with the no same-sex marriage simulation.

Another important set of programs are Medicare Parts B and D. Married adults may have access to 

the private medical insurance of their spouse, thus allowing them to “opt out” of Parts B and D coverage. 

As more gays and lesbians marry, more people will have the opportunity to take advantage of their 

spouse’s coverage (table 7).
CHAPTER 6: PROJECTION RESULTS 4 9

TABLE 7

Baseline Medicare Part B and Part D Participants and Change in Number Receiving Medicare Parts B 

and D by Marriage Rate Simulation, 2015-2065

Thousands of adults

Baseline 

Medicare Part 

B Participant 

(thousands)

Change in Medicare Part 

B (thousands) Baseline 

Medicare 

Part D 

Participant 

(thousands)

Change in Medicare Part 

D (thousands)

Marriage Rate Marriage Rate

Year Medium Low High Medium Low High

2015 50,122 -9 -7 -14 39,666 -7 -6 -13

2020 58,027 -11 -8 -15 45,957 -10 -7 -13

2025 66,822 -15 -11 -18 52,891 -11 -7 -13

2030 74,252 -18 -14 -24 58,818 -12 -10 -17

2035 79,520 -12 -12 -15 62,971 -9 -9 -12

2040 83,037 -17 -13 -21 65,751 -14 -11 -18

2045 85,505 -21 -15 -23 67,669 -15 -11 -17

2050 88,289 -23 -19 -26 69,861 -18 -16 -21

2055 91,368 -18 -14 -21 72,255 -13 -11 -16

2060 95,318 -27 -22 -31 75,446 -20 -17 -24

2065 98,839 -22 -18 -26 78,252 -17 -13 -19

Source: Authors’ calculations from DYNASIM4 ID 938, comparing the no same-sex marriage and low, medium, and high same-sex 

marriage simulations.

Notes: Table includes all individuals. Changes are in thousands of people compared with the no same-sex marriage simulation.

Same-sex marriage and the income pooling that results will reduce revenues collected by the 

Medicare surtax, which applies to earnings and investment income in excess of $200,000 if single and 

$250,000 if married. The added income pooling generated by same-sex marriage leads more people to 

pay the surtax, while the $50,000 higher threshold for married couples than single individuals reduces 

surtax payments. Overall, our projections show that same-sex marriage reduces revenue for the 

Medicare surtax (table 8). While the loss of this tax revenue is less than $1 billion a year, the total surtax 

collected is also small, so the share of the loss reaches several tenths of a percentage point. 
5 0 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

TABLE 8

Baseline Medicare Surtax and Net Medicare Cost and Change in Medicare Surtax and Net Medicare 

Spending by Marriage Rate Simulation, 2015-2065

Billions of dollars

Baseline 

Medicare 

Surtax 

($billions)

Change in Medicare Surtax 

($billions) Baseline 

Net 

Medicare 

Cost 

($billions)

Change in Net Medicare 

Spending ($billions)

Marriage Rate Marriage Rate

Year Medium Low High Medium Low High

2015 21 -0.04 -0.03 -0.06 258 -0.05 -0.04 -0.08

2020 32 -0.05 -0.06 -0.05 375 -0.07 -0.05 -0.10

2025 44 -0.18 -0.15 -0.17 553 -0.10 -0.07 -0.13

2030 66 -0.58 -0.57 -0.55 786 -0.11 -0.09 -0.19

2035 91 -0.31 -0.27 -0.30 1071 -0.03 -0.05 -0.08

2040 129 -0.39 -0.43 -0.43 1425 -0.14 -0.11 -0.23

2045 180 -0.37 -0.43 -0.30 1875 -0.30 -0.21 -0.39

2050 258 -0.58 -0.52 -0.59 2459 -0.39 -0.33 -0.50

2055 357 -0.87 -0.88 -0.70 3204 -0.40 -0.32 -0.60

2060 486 -0.69 -0.72 -0.37 4177 -0.69 -0.58 -0.96

2065 637 -0.53 -0.37 -0.86 5387 -0.56 -0.36 -0.82

Source: Authors’ calculations from DYNASIM4 ID 938, comparing the no same-sex marriage and low, medium, and high same-sex 

marriage simulations.

Notes: Table includes all individuals. Changes are in $billions nominal compared with the no same-sex marriage simulation. Net 

Medicare spending is Medicare spending less Medicare premiums.

Same-sex marriage causes net Medicare spending, defined as Medicare expenditures minus 

premiums paid, to fall slightly over time. Gross spending falls because some gays and lesbians gain 

access to workplace health benefits through their same-sex spouses and thus do not receive Medicare 

benefits. Revenues from Part B and Part D premiums also fall because the number of enrollees drops, 

but premiums fall less than expenditures because Part B and Part D are subsidized by the federal 

government. In 2045, for example, premiums are projected to be down by about $34 million, while gross 

spending on the programs declines by $64 million. Of course, the relative size of these savings are very 

tiny—the cost savings from the medium marriage simulation never exceed two one-hundredths of one 

percent, and will not have an appreciable effect on Medicare’s trust fund.

A potential drawback of marrying and combining spousal incomes is that it could raise household 

income enough to require a married couple to pay federal income taxes on Social Security payments. As 

Table 9 shows, more people will pay federal taxes on Social Security as the same-sex marriage rate rises. 

However, as the last three columns show, the extra taxes are not particularly high because only a 
CHAPTER 6: PROJECTION RESULTS 5 1

portion of Social Security benefits are included in taxable income. Because the income thresholds for 

paying taxes on Social Security are not indexed, the impact grows over time under all three simulations, 

as inflation and wage growth raise nominal incomes.

TABLE 9

Baseline Number of People Who Pay Federal Income Tax on Social Security Benefits and Baseline 

Tax on Social Security Benefits and Change in the Number of People Paying Federal Income Tax on

Social Security Benefits and Amount of Tax Paid by Marriage Rate Simulation, 2015-2065

Baseline 

Number Pay 

Tax 

(thousands)

Change in Tax Payers 

(thousands) Baseline 

Tax on 

Social 

Security 

($billions)

Change in Taxes Paid 

($billions)

Marriage Rate Marriage Rate

Year Medium Low High Medium Low High

2015 27,031 40 35 80 52 0.04 0.05 0.08

2020 34,084 80 64 100 79 0.11 0.12 0.15

2025 40,124 112 91 136 113 0.17 0.19 0.22

2030 44,385 129 110 172 157 0.27 0.29 0.39

2035 46,500 143 117 177 203 0.39 0.39 0.52

2040 47,288 151 114 183 253 0.53 0.50 0.71

2045 47,804 175 137 213 307 0.70 0.65 0.93

2050 48,983 181 138 218 387 0.94 0.81 1.19

2055 51,121 169 127 194 497 1.16 0.93 1.48

2060 53,434 187 144 228 646 1.49 1.21 1.81

2065 55,871 186 147 214 827 2.06 1.71 2.55

Source: Authors’ calculations from DYNASIM4 ID 938, comparing the no same-sex marriage and low, medium, and high same-sex 

marriage simulations.

Notes: Table includes all individuals. Changes are in thousands of people and billions of dollars compared with the no same-sex 

marriage simulation.

Federal recognition of same-sex marriage also affects federal income tax payments. Married people 

filing jointly face a different tax schedule than single people. For example, a married couple can 

automatically exempt more income from taxes than a single person, and a couple is entitled to more 

standard deductions. In addition, the federal income tax is progressive, with marginal taxes that 

increase with income, and the income thresholds that set steeper marginal tax rates are higher for 

married joint filers than single filers. Marrying someone with very little income can reduce income tax 

payments, because the couple can claim more deductions and exemptions and is unlikely to be pushed 

into a higher tax bracket. However, marrying someone with similar income can push the couple into a 

higher tax bracket, raising tax payments. The impact of marriage on federal income tax payments, then, 
5 2 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

depends on how the incomes of the two spouses differ. Our DYNASIM projections show that legalizing 

same-sex marriage slightly reduces federal income tax revenue in most years, although it slightly raises 

revenue in 2065 (table 10). However, the impact is quite small. The annual loss, through 2065, never 

amounts to as much as a tenth of a percent of tax revenues.

TABLE 10

Baseline Federal Income Tax and Change in Federal Income Tax Receipts by Marriage Rate 

Simulation, 2015-2065

Baseline 

Federal 

Income

Tax 

($billions)

Change in Federal Income Tax 

Receipts ($billions)

Percentage Change in Federal 

Income Tax (%)

Marriage Rate Marriage Rate

Year Medium Low High Medium Low High

2015 1,098 0.00 0.00 -0.08 0.000% 0.000% -0.008%

2020 1,530 0.07 0.09 0.10 0.004 0.006 0.006

2025 2,007 -0.80 -0.56 -0.63 -0.040 -0.028 -0.031

2030 2,627 -2.26 -2.19 -1.81 -0.086 -0.084 -0.069

2035 3,314 -0.82 -0.68 -0.12 -0.025 -0.021 -0.003

2040 4,210 -1.63 -1.61 -1.56 -0.039 -0.038 -0.037

2045 5,328 -0.83 -1.20 -0.08 -0.015 -0.022 -0.002

2050 6,761 -1.72 -1.63 -0.02 -0.026 -0.024 0.000

2055 8,604 -2.47 -2.93 -3.64 -0.029 -0.034 -0.042

2060 10,911 -2.00 -2.19 -2.31 -0.018 -0.020 -0.021

2065 13,993 0.85 1.04 0.66 0.006 0.007 0.005

Source: Authors’ calculations from DYNASIM4 ID 938, comparing the no same-sex marriage and low, medium, and high same-sex 

marriage simulations.

Notes: Table includes all individuals. Changes are in billions of nominal dollars compared with the no same-sex marriage 

simulation.

Combining these fiscal effects, our projections show that the overall impact of legalizing same-sex 

marriage is to slightly raise federal spending net of revenues (table 11). Under our medium same-sex 

marriage rate assumption, the net position of the federal budget will be about $3.6 billion lower in 2065 

than it would have been if same-sex marriage had not been legalized, a trivial difference in a multitrillion dollar budget. Figure 28 summarizes each of the fiscal impacts in 2065. The change in OASDI 

benefits is the biggest impact of same-sex marriage, which is partially offset by increased income tax 

revenue. 
CHAPTER 6: PROJECTION RESULTS 5 3

TABLE 11

Baseline Net Federal Budget Balance and Change in the Net Balance of the Federal Budget

(Revenues-Expenditures) by Marriage Rate Simulation, 2015-2065

Billions of dollars

Baseline 

Net 

Federal 

Budget 

($billions)

Change in Net Federal Budget 

($billions)

Percentage Change in Net Federal 

Budget (%)

Marriage Rate Marriage Rate

Year Medium Low High Medium Low High

2015 981 -0.07 -0.09 -0.06 -0.007% -0.009% -0.006%

2016 983 -0.42 -0.45 -0.38 -0.043 -0.046 -0.039

2017 1,096 -0.20 -0.31 0.08 -0.019 -0.029 0.007

2018 1,167 -0.20 -0.15 0.06 -0.017 -0.013 0.005

2019 1,250 -0.23 -0.31 -0.06 -0.018 -0.025 -0.005

2020 1,320 -0.03 -0.05 0.08 -0.002 -0.004 0.006

2025 1,560 -1.10 -0.88 -0.87 -0.070 -0.057 -0.056

2030 1,860 -3.12 -3.06 -2.52 -0.168 -0.164 -0.136

2035 2,186 -1.70 -1.46 -0.87 -0.078 -0.067 -0.040

2040 2,723 -2.86 -2.82 -2.71 -0.105 -0.104 -0.100

2045 3,438 -2.49 -2.87 -1.33 -0.072 -0.084 -0.039

2050 4,298 -4.23 -3.94 -2.20 -0.098 -0.092 -0.051

2055 5,344 -5.53 -5.76 -6.59 -0.103 -0.108 -0.123

2060 6,538 -5.63 -5.48 -5.00 -0.086 -0.084 -0.076

2065 8,182 -3.48 -2.63 -3.13 -0.042 -0.032 -0.038

Source: Authors’ calculations from DYNASIM4 ID 938, comparing the no same-sex marriage and low, medium, and high same-sex 

marriage simulations.

Notes: Table includes all individuals. Changes are in billions of nominal dollars compared with the no same-sex marriage 

simulation.
5 4 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

FIGURE 28

Fiscal Impact of Legal Recognition of Same-Sex Marriage by Marriage Rate Simulation, 2065

Source: Authors’ calculations from DYNASIM4 ID 938, comparing the no same-sex marriage and low, medium, and high same-sex 

marriage simulations.

Notes: Table includes all individuals. Changes are in billions of dollars compared with the no same-sex marriage simulation.

Projected Retirement Income of Gays and Lesbians Ages

62 and Older

Federal recognition of same-sex marriage will also affect the retirement security of same-sex couples, 

as they gain access to Social Security spouse and survivor benefits and become subject to different 

federal income tax rules. We assume that married couples pool their finances and unmarried household 

couples do not. To assess the impact of same-sex marriage on income, then, our analysis splits the 

combined individual incomes from each married spouse equally between the spouses, and compares 

that per capita household income to each spouse’s individual income, representing their resources if 

same-sex marriage were not legalized. Net per capita income is computed as per capita income minus 

the federal income tax, state income tax, OASDI tax, HI tax, Medicare Surtax, and Medicare Part B and 

Part D premiums. All income amounts are reported in inflation-adjusted 2015 dollars. 

By 2045, average per capita income including Social Security, SSI, earnings, and other benefits for 

gays and lesbians ages 62 and older will be about $1,200 higher because of access to legal same-sex 

marriage than it would have been had same-sex marriage not been legalized (figure 29 and table 12). 

4.12

0.24

2.06

0.85

-0.53 -0.56

-3.48 -5

-3

-1

1

3

5

7

OASDI

benefits

SSI Tax on Social

Security

Total federal

income tax

Medicare

surtax

Net Medicare

Spending

Total federal

balance

Change ($billions) Low marriage Medium marriage High marriage
CHAPTER 6: PROJECTION RESULTS 5 5

Same-sex marriage raises Social Security benefits, as gays and lesbians gain access to spouse and 

survivor benefits. But, much of the increase stems from higher per capita earnings, which results 

primarily because some gays and lesbians ages 62 and older who are no longer working are married to a 

younger partner with earnings, raising per capita shared earnings for the nonworkers. We see an 

analogous reduction in asset income primarily from retirement account withdrawals that are now 

shared with a younger spouse.

Some of the income gains from same-sex marriage are offset by a decline in defined benefit (DB) 

pension income resulting from a shift from single life annuities to joint and survivor annuities. The total 

wealth in DB pensions is unchanged by marriage. 

Same-sex marriage also reduces per capita tax payments and Medicare premiums on average for 

gays and lesbians ages 62 and older, further improving their financial well-being (figure 30). The effects 

are largely driven by a drop in average federal income tax payments, which are only slightly offset by an 

increase in OASDI payroll taxes. 

FIGURE 29

Change in Average Per Capita Income by Income Source among Gays and Lesbians Ages 62 and Older 

in Selected Years

Source: Author’s tabulations from DYNASIM4 ID 938, comparing the no same-sex marriage and medium same-sex marriage 

simulations.

-2,500

-2,000

-1,500

-1,000

-500

0

500

1,000

1,500

2,000

2015 2025 2035 2045 2055 2065

Year

($2,015)

Social Security benefits

Other Income

Earned income

Asset Income

SSI

DB pension income
5 6 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

FIGURE 30

Change in Average Per Capita Tax and Medicare Premiums among Gays and Lesbians Ages 62 and 

Older for Selected Years

Source: Author’s tabulations from DYNASIM4 ID 938, comparing the no same-sex marriage and medium same-sex marriage 

simulations.

In generating our per capita measure, we split income and taxes of both partners. When one partner 

has more income than the other, marriage lowers the per capita income of the higher-income partner 

and increases the per capita income of the lower-income partner. In these cases, family formation 

reduces both income inequality and family poverty.

Net per capita income for gays and lesbians ages 62 and older will rise throughout most of the 

income distribution because of access to same-sex marriage (figure 31). Compared with projections 

that assume same-sex marriage was not legalized, projected 2065 net per capita income with legalized 

same-sex marriage show an annual gain for older gays and lesbians of about $1,350 at the 10th 

percentile of the income distribution, $1,990 at the 25th percentile, and $2,180 at the median. Net per 

capita incomes would be lower, however, for older gays and lesbians in the top 10 percent of the income 

distribution. 

-800

-700

-600

-500

-400

-300

-200

-100

0

100

2015 2025 2035 2045 2055 2065

Year

($2015)

OASDI tax

State income tax

Federal income tax

Other tax and premiums

Total tax and premium
CHAPTER 6: PROJECTION RESULTS 5 7

TABLE 12

Average Per Capita Income and Taxes and Average Charge under Medium Same-sex Marriage 

Simulation among Lesbian and Gay Individuals Age 62 and Older by Income and Tax Type and Year

Year

2015 2025 2035 2045 2055 2065

Baseline (No Same-Sex Marriage)

Total cash income 39,434 50,540 55,794 53,651 54,909 58,801

Social Security benefits 11,488 12,875 15,675 17,041 18,713 21,247

Earned income 12,831 18,224 19,303 17,419 18,228 19,606

SSI 384 325 184 117 71 66

DB pension income 8,600 7,236 5,855 3,719 2,339 1,706

Asset income 5,486 11,189 13,994 14,536 14,512 15,122

Other income 646 691 783 820 1,048 1,054

Total Taxes and Premiums 7,299 11,810 13,719 13,192 14,435 15,933

Federal income tax 3,960 6,934 7,731 6,791 7,044 7,282

State income tax 783 1,394 1,617 1,258 1,134 1,048

OASDI tax 674 904 935 878 982 1,078

HI tax 173 248 236 229 256 279

Medicare surtax 36 130 190 194 251 298

Medicare Part B premium 1,303 1,671 2,290 2,915 3,617 4,510

Medicare Part D premium 370 529 721 927 1,152 1,439

Net cash income 32,135 38,731 42,074 40,459 40,474 42,868

Average Change (medium marriage rate)

Total cash income -119 -1,132 -741 296 65 241

Social Security benefits -2 -23 92 230 375 480

Earned income 340 899 638 1,124 702 722

SSI -37 -38 -23 -23 -20 -18

DB pension income -129 -121 -93 -16 -18 -11

Asset income -297 -1,896 -1,421 -1,154 -1,105 -1,039

Other income 6 45 67 135 131 108

Total Taxes and Premiums -55 -689 -641 -194 -430 -205

Federal income tax -47 -542 -372 -54 -240 -25

State income tax -14 -149 -199 -98 -110 -53

OASDI tax 16 49 33 44 34 38

HI tax 4 13 10 16 9 10

Medicare surtax -2 -26 -24 -19 -33 -24

Medicare Part B premium -10 -25 -69 -67 -71 -116

Medicare Part D premium -3 -9 -22 -17 -19 -36

Net cash income -64 -443 -99 490 494 446

Source: Authors’ calculations from DYNASIM4 ID 938 no same-sex marriage and medium same-sex marriage simulations. 
5 8 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

Notes: Table includes all lesbian and gay individuals ages 62 and older in selected years. Dollar amounts are per capita values in 

$2015 price-adjusted dollars. Married couples split incomes and taxes in years they are married and own amounts in years 

individuals are unmarried. Net cash income is the sum of Social Security, earnings, SSI, DB pension income, asset income, and

other income, less federal income tax, state income tax, OASDI tax, HI tax, Medicare Surtax, Medicare Part B and Part D 

premiums.

FIGURE 31

Distribution of Change in Per Capita Net Income among Gays and Lesbians Ages 62 and Older in 

Selected Years

Source: Author’s tabulations from DYNASIM4 ID 938 and medium same-sex marriage simulations.

As figure 32 shows, the effect of same-sex marriage on incomes varies considerably with an 

individual’s shared lifetime earnings. The shared lifetime earnings measure splits couple earnings in 

years they are married and uses individual earnings in years they are single. We then calculate the 

average shared earnings from age 22 to age 62. For adults ages 62 and older in the bottom three shared 

lifetime earnings quintiles, the gains from same-sex marriage are substantial, reaching about $2,000 per

person by 2065. While those in the fourth income quintile have small gains in most years after 2025, 

these gains disappear in 2065. However, same-sex marriage significantly reduces net per capita income 

for lesbian and gay adults ages 62 and older in top shared lifetime earnings quintile, primarily because of 

income sharing. When same-sex marriage is available, some gay men and lesbians with high incomes 

marry people with less income, so the average per person income of the couple is lower than the highincome partner’s income alone. Income tax penalties associated with marriage also reduce the incomes 

for couples in the top shared lifetime earnings quintile. 

$446

$1,738 $1,350 $1,991 $2,178

$1,026

-$3,432

-$6,724 -8000

-7000

-6000

-5000

-4000

-3000

-2000

-1000

0

1000

2000

3000

Mean P5 P10 P25 P50 P75 P90 P95

Mean and Percentile Change in Per Capita Net Cash Income

($2015)

2015

2025

2035

2045

2055

2065
CHAPTER 6: PROJECTION RESULTS 5 9

FIGURE 32

Change in Average Per Capita Net Cash Income among Gays and Lesbians Ages 62 and Older by 

Shared Lifetime Earnings in Selected Years

Source: Author’s tabulations from DYNASIM4 ID 938, comparing the no same-sex marriage and medium same-sex marriage 

simulations.

Our projections show that these income shifts will lead to a dramatic decline in the poverty rate for 

older gays and lesbians. As figure 33 shows, there are two persistent trends. First, the poverty rate 

declines over time for everyone ages 62 and older, as productivity growth raises earnings and Social 

Security benefits. Second, the decline is much greater for older gays and lesbians than for the overall 

older population. In 2015, the poverty rate was 8 percent for all adults ages 62 and older, compared 

with just under 18 percent for older gays and lesbians under the medium marriage simulation and just 

over 18 percent under the no same-sex marriage simulation. DYNASIM projects that by 2065, the 

poverty rates of lesbians and gays ages 62 and older will fall sharply. The poverty rate declines by 13 

percentage points for older gays and lesbians with legal same-sex marriage and by 3 percentage points 

for all older adults. Compare to our no same-sex marriage simulation, legal same-sex marriage reduces 

the share of lesbians and gays ages 62 and older in poverty by one to two percentage points each year.

The gains are larger for lesbian women than for gay men.

-6000

-5000

-4000

-3000

-2000

-1000

0

1000

2000

3000

2015 2025 2035 2045 2055 2065

Year

($ 2015)

Bottom quintile

2nd quintile

3rd quintile

4th quintile

Top quintile
6 0 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

FIGURE 33

Poverty Rate among Adults Ages 62 and Older, by Sexual Orientation and Year

Source: Author’s tabulations from DYNASIM4 ID 938.

Notes: All 62 plus category includes all individuals age 62 and older

8% 8% 7% 7% 6% 5%

18%

14%

11%

9%

7%

5%

18%

15%

13%

11%

9%

7%

0%

5%

10%

15%

20%

2015 2025 2035 2045 2055 2065

Year

Percent with Family Income Below Poverty

All 62+ 62+ gays and lesbians No LG marriage
CHAPTER 7: CONCLUSION S 6 1

Chapter 7: Conclusions

In two landmark Supreme Court decisions in 2013 (Windsor) and 2015 (Obergefell), same-sex marriage 

went from being unrecognized by the federal government and most states to legal in every state and 

recognized by the federal government. One consequence of legalizing same-sex marriage is that it 

provides gay and lesbian couples access to spouse and survivor benefits from Social Security and family 

fringe benefits from employers.

Legalized same-sex marriage creates various pluses and minuses for individuals and for the federal 

government. For example, marriage has tax consequences that cause some couples to pay higher taxes 

and other couples to pay lower taxes. Some spouses will get more Social Security benefits and other 

couples will pay higher taxes on their Social Security benefits because their joint income will now 

surpass the cutoff for tax payments. Other spouses will choose to forgo Medicare Parts B and D to join 

the private health insurance plan of their working partner.

All of these changes affect the retirement incomes of older gays and lesbians in unpredictable ways. 

Similarly, the variety of added costs, saved costs, lower premiums, and changes in federal revenues 

makes the net effect on federal revenues and expenditures uncertain. This study used the Urban 

Institute’s state-of-the-art DYNASIM microsimulation model to estimate each of these impacts. The 

baseline for our comparisons simulated outcomes as if same-sex marriages were not recognized by the 

federal government or any of the states.

While there is some uncertainty about the size of the gay and lesbian populations, survey results 

suggest that between 1.3 and 2.5 percent of Americans (about 4 to 8 million people) identify as lesbian 

or gay. Among those, about 1.6 million are living with a same-sex partner.

Survey data suggest that about 75 percent of gays and lesbians report wanting to marry someday, 

but the number of married-same-sex couples has been historically constrained for couples living in 

states that do not recognize same-sex marriage. Of the nearly 800,000 couples living with a same-sex 

partner in 2014, 42 percent were married, but the share of same-sex couples that are married is 

markedly higher in states that legalized same-sex marriage relatively early. 

While about the same share of lesbians and gays partner and marry, lesbian women typically do so 

at slightly younger ages than gay men. Nonmarital cohabitation is typically a transitory status for 

opposite-sex couples, with many transitioning to marriage. The absence of legal marriage for many 
6 2 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

same-sex couples means that nonmarital cohabitation is common among same-sex couples even at 

older ages. 

Same-sex couples are more likely to be white and well-educated than opposite-sex couples and 

tend to have higher earnings. However, same-sex couples are more likely than opposite-sex couples to 

partner with someone of a different age and racial group. A substantially higher share of women in 

heterosexual couples have no market earnings than same-sex women, as more heterosexual woman 

remain at home to raise children. Family heads in the majority of working-age same-sex and oppositesex couples have earnings that differ substantially from their partners, suggesting that Social Security 

spouse and survivor benefits will be an important financial resource for both same-sex and opposite-sex 

couples in the future.

The opportunity to marry will improve, on average, the financial security of older gays and lesbians. 

The average per capita annual income of lesbians and gays in the middle income quintile was

approximately $2,000 higher when same-sex marriage was legal than under the baseline case in which 

same-sex marriage was not legal. For couples, then, the gain in this middle income range was $4,000. 

Poverty rates for gays and lesbians ages 62 and older are sharply higher than for all seniors. Poverty 

rates for gays and lesbians ages 62 and older are projected to decline from 18 percent in 2015 to 5 

percent in 2065. While poverty rates are projected to fall in general due to rising earnings (especially 

for women), gays and lesbians will also benefit from the many advantages of combining incomes and 

access to additional retirement benefits. Legal same-sex marriage reduces poverty rates for gays and 

lesbians ages 62 and older by one to two percentage points per year.

The rise of middle quintile incomes for older gays and lesbians and decline in poverty rate are due to 

several factors. First, pooling of income reduces the number of gays and lesbians with low family income 

and provides certain economies of scale (a slimmed down version of the old saying that “two can live as 

cheaply as one”). Second, married couples tend to have higher per capita incomes because people with 

responsibilities to other people tend to have higher earnings and are more likely to accumulate savings 

and become home owners. Third, couples can survive layoffs or other problems more easily than single 

people, because a spouse’s resources can provide a financial cushion. Fourth, they gain access to private 

and public spouse benefits, such as coverage by a spouse’s employer-sponsored health insurance, 

higher Social Security payments that are based on the employment history of a higher-earning spouse, 

and Social Security survivor benefits.

Using our simulation model, we examined the impact of same-sex marriage on federal programs and 

tax revenues, and family incomes. Our projections showed the following: 
CHAPTER 7: CONCLUSION S 6 3

 A small increase in the number of people receiving OASDI benefits (0.03 percent in 2015); 

 An increase in the net cost of OASDI benefits of several billions of dollars per year (0.02 to 0.04 

percent increase) due to the increase in the number of beneficiaries and an increase in the 

number receiving spouse and survivor benefits that exceed their own worker benefits. This 

change is too small, however, to materially affect the Social Security Trust Fund;

 A small decrease in the number receiving SSI benefits (0.12 percent in 2015) that dissipates 

over time;

 A small decrease (0.02 percent) in the number of people receiving Medicare Part B and Part D 

benefits which slightly reduced Medicare costs, net of premiums (0.018 percent decline), 

because these programs are subsidized by the federal government;

 A small decrease in the amount of the Medicare surtax (0.17 to 0.9 percent); 

 More older people paying income taxes on their Social Security benefits (0.15 percent in 2015 

rising to 0.33 percent in 2065); 

 Small changes in federal income taxes paid that are not uniformly higher or lower as some 

couples get marriage bonuses and others get marriage penalties; and

 The combined effect of these changes is a reduction in the net federal budget (increase deficit) 

of between $3 billion to $6 billion dollars a year after 2030 (which represents about four onehundredths of one percent). 
6 4 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

Appendix A. Effective Date of Legal 

Same-Sex Marriage by State

TABLE A1 

Effective Date of Legal Same-Sex Marriage by State

State Effective Date LGBT Share

Massachusetts 5/17/2004 4.4

Connecticut 11/12/2008 3.4

Iowa 4/3/2009 2.8

Vermont 9/1/2009 4.9

District of Columbia 12/18/2009 10

New Hampshire 1/1/2010 3.7

New York 7/24/2011 3.8

Washington 12/6/2012 4

Maine 12/29/2012 4.8

Maryland 1/1/2013 3.3

California 6/28/2013 4

Delaware 7/1/2013 3.4

Minnesota 8/1/2013 2.9

Rhode Island 8/1/2013 4.5

New Jersey 10/21/2013 3.7

Hawaii 12/2/2013 5.1

New Mexico 12/19/2013 2.9

Utah 12/20/2013 2.7

Oregon 5/19/2014 4.9

Pennsylvania 5/20/2014 2.7

Illinois 6/1/2014 3.8

Indiana 10/6/2014 3.3

Oklahoma 10/6/2014 3.4

Virginia 10/6/2014 2.9

Wisconsin 10/6/2014 2.8

Colorado 10/7/2014 3.2

Nevada 10/9/2014 4.2

West Virginia 10/9/2014 3.1

North Carolina 10/10/2014 3.3

Alaska 10/12/2014 3.4

Idaho 10/15/2014 2.7
APPENDIX A 6 5

Arizona 10/17/2014 3.9

Wyoming 10/21/2014 2.9

Kansas 11/4/2014 3.7

Montana 11/19/2014 2.6

South Carolina 11/20/2014 2.9

Alabama 1/1/2015 2.8

Florida 1/6/2015 3.5

Arkansas 6/26/2015 3.5

Georgia 6/26/2015 3.5

Kentucky 6/26/2015 3.9

Louisiana 6/26/2015 3.2

Michigan 6/26/2015 3.8

Mississippi 6/26/2015 2.6

Missouri 6/26/2015 3.3

Nebraska 6/26/2015 2.7

North Dakota 6/26/2015 1.7

Ohio 6/26/2015 3.6

South Dakota 6/26/2015 4.4

Tennessee 6/26/2015 2.6

Texas 6/26/2015 3.6

Source: National Conference of State Legislatures (2015); Pew Research Center (2015a); Wikipedia. LGBT shares from Gates and 

Newport (2012).
6 6 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

TABLE A2

Number and Percent of Married or Cohabiting Opposite-Sex Men and Women by Individual Characteristics among Adults Ages 20 and Older 

in 2014

Number (thousands) Column Percent Row Percent

ALL Married Cohabit ALL Married Cohabit ALL Married Cohabit

All 126,013 112,499 13,515 100 100 100 100 89 11

Age

20-24 3,130 1,524 1,606 2 1 12 100 49 51

25-34 20,131 15,273 4,858 16 14 36 100 76 24

35-44 25,763 22,830 2,933 20 20 22 100 89 11

45-54 27,239 25,116 2,123 22 22 16 100 92 8

55-64 25,287 24,035 1,251 20 21 9 100 95 5

65+ 24,464 23,721 743 19 21 5 100 97 3

Education

Less than high school 11,306 9,665 1,642 9 9 12 100 85 15

High school graduate 42,545 37,267 5,278 34 33 39 100 88 12

Some college 29,246 25,658 3,588 23 23 27 100 88 12

College graduate 42,916 39,909 3,007 34 35 22 100 93 7

Race Ethnicity

White non-Hispanic 90,685 82,083 8,602 72 73 64 100 91 9

Black non-Hispanic 9,505 7,863 1,642 8 7 12 100 83 17

Hispanic 17,839 15,089 2,750 14 13 20 100 85 15

Other 7,985 7,465 520 6 7 4 100 93 7

Real Earnings

No earnings 37,865 35,299 2,566 30 31 19 100 93 7

1-25K 26,249 21,677 4,572 21 19 34 100 83 17

25K-50K 26,520 22,700 3,820 21 20 28 100 86 14

50K-75K 16,238 14,726 1,512 13 13 11 100 91 9
APPENDIX A 6 7

Number (thousands) Column Percent Row Percent

ALL Married Cohabit ALL Married Cohabit ALL Married Cohabit

75K or more 19,141 18,097 1,044 15 16 8 100 95 5

Source: Authors' tabulations from the 2014 American Community Survey.

Notes: Table includes all opposite-sex men and women ages 20 and older cohabiting with or married to a same-sex partner in 2014. Earnings are in 2015 price-adjusted dollars.

TABLE A3

Number and Percent of Married or Cohabiting Same-Sex Men and Women by Individual Characteristics among Adults Ages 20 and Older in 

2012-2014

Number (thousands) Column Percent Row Percent

ALL Married Cohabit ALL Married Cohabit ALL Married Cohabit

All 4313 1535 2778 100 100 100 100 36 64

Sex

Men 2085 721 1364 48 47 49 100 35 65

Women 2227 813 1414 52 53 51 100 37 63

Age

20-24 188 25 164 4 2 6 100 13 87

25-34 779 190 589 18 12 21 100 24 76

35-44 899 284 616 21 18 22 100 32 68

45-54 1143 379 764 26 25 28 100 33 67

55-64 731 295 437 17 19 16 100 40 60

65+ 572 363 209 13 24 8 100 63 37

Education

Less than high School 227 122 105 5 8 4 100 54 46

High school graduate 1099 435 664 25 28 24 100 40 60

Some college 1047 307 739 24 20 27 100 29 71
6 8 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

Number (thousands) Column Percent Row Percent

ALL Married Cohabit ALL Married Cohabit ALL Married Cohabit

College graduate 1940 670 1269 45 44 46 100 35 65

Race Ethnicity

White non-Hispanic 3288 1162 2125 76 76 77 100 35 65

Black non-Hispanic 328 116 211 8 8 8 100 35 65

Hispanic 526 179 347 12 12 12 100 34 66

Other 171 77 95 4 5 3 100 45 55

Real Earnings

No earnings 969 478 491 22 31 18 100 49 51

1-25K 904 275 628 21 18 23 100 30 70

25K-50K 968 273 695 22 18 25 100 28 72

50K-75K 623 200 423 14 13 15 100 32 68

75K or more 849 309 540 20 20 19 100 36 64

Year State Legalized Same-Sex Marriage

2004 142 78 64 3 5 2 100 55 45

2008 49 29 20 1 2 1 100 59 41

2009 82 42 41 2 3 1 100 51 49

2010 22 13 9 1 1 0 100 58 42

2011 327 142 184 8 9 7 100 44 56

2012 158 60 98 4 4 4 100 38 62

2013 1022 398 625 24 26 22 100 39 61

2014 1158 367 791 27 24 28 100 32 68

2015 1352 407 945 31 27 34 100 30 70

Source: Authors' tabulations from the 2012-2014 American Community Survey.

Notes: Table includes all same-sex men and women ages 20 and older cohabiting with or married to a same-sex partner in 2012-2014. Earnings are in 2015 price-adjusted dollars.
APPENDIX B 6 9

Appendix B. Same-Sex Cohabitation Hazard

TABLE B1

Same-Sex Cohabitation Hazard Rate by Sex, Race, and Age

Female Same-Sex Male Same-Sex

Age ALL White Black Hispanic Other ALL White Black Hispanic Other

15 0.0096 0.0101 0.0075 0.0081 0.0005 0.0047 0.0047 0.0033 0.0050 0.0013

16 0.0181 0.0172 0.0235 0.0153 0.0019 0.0082 0.0078 0.0093 0.0084 0.0029

17 0.0241 0.0257 0.0285 0.0180 0.0045 0.0100 0.0107 0.0092 0.0097 0.0054

18 0.0371 0.0405 0.0480 0.0292 0.0097 0.0170 0.0187 0.0136 0.0183 0.0093

19 0.0456 0.0533 0.0477 0.0341 0.0241 0.0235 0.0262 0.0167 0.0247 0.0091

20 0.0579 0.0703 0.0616 0.0407 0.0398 0.0322 0.0365 0.0261 0.0325 0.0195

21 0.0637 0.0814 0.0513 0.0391 0.0444 0.0395 0.0457 0.0257 0.0389 0.0277

22 0.0681 0.0868 0.0602 0.0474 0.0748 0.0447 0.0533 0.0285 0.0426 0.0355

23 0.0649 0.0800 0.0548 0.0505 0.1010 0.0477 0.0553 0.0308 0.0477 0.0403

24 0.0633 0.0741 0.0647 0.0520 0.1137 0.0506 0.0603 0.0355 0.0410 0.0428

25 0.0583 0.0682 0.0511 0.0493 0.0955 0.0519 0.0640 0.0299 0.0419 0.0485

26 0.0550 0.0662 0.0453 0.0433 0.0792 0.0551 0.0683 0.0353 0.0409 0.0506

27 0.0589 0.0676 0.0484 0.0507 0.0591 0.0557 0.0667 0.0322 0.0463 0.0612

28 0.0591 0.0684 0.0443 0.0483 0.0220 0.0603 0.0698 0.0410 0.0507 0.0739

29 0.0599 0.0674 0.0441 0.0623 0.0111 0.0544 0.0653 0.0182 0.0467 0.0697

30 0.0548 0.0609 0.0347 0.0570 0.0164 0.0492 0.0593 0.0266 0.0472 0.0588

31 0.0639 0.0699 0.0536 0.0628 0.0621 0.0419 0.0528 0.0106 0.0326 0.0439

32 0.0613 0.0767 0.0442 0.0460 0.0730 0.0450 0.0552 0.0262 0.0354 0.0354

33 0.0706 0.0993 0.0604 0.0547 0.1234 0.0414 0.0557 0.0137 0.0308 0.0321
7 0 APPENDIX B

Female Same-Sex Male Same-Sex

Age ALL White Black Hispanic Other ALL White Black Hispanic Other

34 0.0716 0.1116 0.0447 0.0410 0.0994 0.0478 0.0600 0.0238 0.0420 0.0542

35 0.0747 0.1163 0.0544 0.0392 0.0902 0.0494 0.0611 0.0178 0.0380 0.0842

36 0.0607 0.1050 0.0188 0.0224 0.0527 0.0496 0.0602 0.0182 0.0396 0.0867

37 0.0529 0.0943 0.0126 0.0184 0.0300 0.0436 0.0599 0.0086 0.0270 0.0650

38 0.0498 0.0887 0.0026 0.0209 0.0177 0.0486 0.0713 0.0105 0.0257 0.0519

39 0.0515 0.0873 0.0168 0.0210 0.0196 0.0598 0.0874 0.0235 0.0291 0.0441

40 0.0594 0.0983 0.0228 0.0390 0.0383 0.0720 0.1072 0.0323 0.0453 0.0397

41 0.0638 0.1006 0.0297 0.0394 0.0223 0.0822 0.1217 0.0374 0.0568 0.0517

42 0.0695 0.1114 0.0283 0.0451 0.0423 0.0908 0.1363 0.0262 0.0576 0.0753

43 0.0659 0.1088 0.0213 0.0310 0.0269 0.0971 0.1442 0.0244 0.0614 0.0803

44 0.0745 0.1258 0.0257 0.0295 0.0453 0.0982 0.1553 0.0134 0.0529 0.0701

45 0.0780 0.1370 0.0304 0.0164 0.0271 0.1000 0.1620 0.0225 0.0574 0.0643

46 0.0869 0.1533 0.0432 0.0152 0.0420 0.1071 0.1807 0.0202 0.0519 0.0657

47 0.0885 0.1552 0.0385 0.0191 0.0248 0.1052 0.1783 0.0235 0.0532 0.0470

48 0.0881 0.1524 0.0359 0.0199 0.0184 0.1020 0.1744 0.0255 0.0516 0.0464

49 0.0732 0.1300 0.0157 0.0187 0.0222 0.0829 0.1379 0.0197 0.0418 0.0332

50 0.0558 0.1029 0.0053 0.0099 0.0299 0.0667 0.1075 0.0233 0.0450 0.0401

51 0.0432 0.0781 0.0000 0.0154 0.0315 0.0409 0.0645 0.0103 0.0214 0.0129

52 0.0337 0.0581 0.0000 0.0123 0.0150 0.0289 0.0426 0.0102 0.0214 0.0098

53 0.0282 0.0468 0.0003 0.0213 0.0322 0.0139 0.0207 0.0021 0.0002 0.0000

54 0.0220 0.0365 0.0000 0.0128 0.0070 0.0151 0.0219 0.0044 0.0059 0.0000

55 0.0256 0.0392 0.0053 0.0147 0.0101 0.0143 0.0220 0.0057 0.0049 0.0000

56 0.0213 0.0349 0.0000 0.0000 0.0000 0.0182 0.0251 0.0032 0.0177 0.0011
APPENDIX B 7 1

Female Same-Sex Male Same-Sex

Age ALL White Black Hispanic Other ALL White Black Hispanic Other

57 0.0198 0.0325 0.0032 0.0025 0.0040 0.0178 0.0273 0.0000 0.0064 0.0051

58 0.0139 0.0224 0.0006 0.0000 0.0000 0.0160 0.0246 0.0000 0.0020 0.0050

59 0.0188 0.0266 0.0073 0.0036 0.0000 0.0145 0.0229 0.0000 0.0000 0.0029

60 0.0163 0.0207 0.0043 0.0073 0.0000 0.0134 0.0193 0.0000 0.0038 0.0147

61 0.0178 0.0231 0.0063 0.0107 0.0000 0.0148 0.0203 0.0053 0.0000 0.0175

62 0.0120 0.0149 0.0060 0.0077 0.0014 0.0178 0.0213 0.0120 0.0061 0.0180

63 0.0134 0.0191 0.0088 0.0014 0.0000 0.0192 0.0209 0.0137 0.0134 0.0214

64 0.0099 0.0139 0.0052 0.0000 0.0000 0.0192 0.0224 0.0112 0.0083 0.0264

Source: Authors’ calculations from 2012-2014 American Community Survey data.
7 2 APPENDIX C

Appendix C. Same-Sex Marriage

Hazard Model

Tables C1 and C2 show summary statistics for male and female same-sex marriage estimation samples 

respectively. Age spline 15 is the maximum of 0 and age-15. Age spline 20 is the maximum of 0 and age20, and so on.

TABLE C1

Summary Statistics for Male Same-Sex Marriage Hazard Model Estimation

Variable Mean Standard 

Deviation

Minimum Maximum

New Marriage 0.14712 0.3543 0 1

Spline age - 15 31.83287 13.4984 4 79

Spline age - 20 26.83435 13.4954 0 74

Spline age - 25 21.90143 13.3789 0 69

Spline age - 30 17.28998 12.8113 0 64

Spline age - 40 9.57439 10.2987 0 54

Spline age - 50 4.02020 7.0579 0 44

Spline age - 55 2.34964 5.4038 0 39

Year-Legal Year=0 0.30350 0.4598 0 1

Year-Legal Year=1 0.36854 0.4825 0 1

Year-Legal Year=2 0.10080 0.3011 0 1

Year-Legal Year=3 0.09264 0.2900 0 1

Less than HS 0.02298 0.1498 0 1

High Grade=12 0.18640 0.3895 0 1

Some College 0.21883 0.4135 0 1

College Graduate 0.57180 0.4949 0 1

Non-Hispanic Black 0.04262 0.2020 0 1

Hispanic 0.13174 0.3382 0 1

Other Race 0.06374 0.2443 0 1

Source: Authors tabulations from the 2012-2014 American Community Survey.

Notes: Estimates were based on a sample of 5,402 men age 19 and older living with a same-sex partner in a state that legalized 

same-sex marriage before 2014. The sample included all unmarried men and men married in the prior 12 months.
APPENDIX C 7 3

TABLE C2

Summary Statistics for Female Same-Sex Marriage Hazard Model Estimation Sample

Variable Mean Standard 

Deviation

Minimum Maximum

New marriage 0.15194 0.359 0 1

Spline age - 15 31.40958 14.346 4 81

Spline age - 20 26.41206 14.342 0 76

Spline age - 25 21.54604 14.124 0 71

Spline age - 30 17.08960 13.374 0 66

Spline age - 40 9.68435 10.617 0 56

Spline age - 50 4.27973 7.221 0 46

Spline age - 55 2.52787 5.528 0 41

Year-legal year=0 0.29975 0.458 0 1

Year-legal year=1 0.35900 0.480 0 1

Year-legal year=2 0.11045 0.313 0 1

Year-legal Year=3 0.08154 0.274 0 1

Less than high school 0.03282 0.178 0 1

High grade=12 0.21305 0.410 0 1

Some college 0.22130 0.415 0 1

College graduate 0.53282 0.499 0 1

No children 0.86829 0.338 0 1

|Head age - partner age| 5.87221 6.112 0 49

Same education dummy 0.57370 0.495 0 1

Black 0.05615 0.230 0 1

Hispanic 0.11437 0.318 0 1

Other race 0.05244 0.223 0 1

Source: Authors tabulations from the 2012-2014 American Community Survey.

Notes: Estimates were based on a sample of 4,844 women ages 19 and older living with a same-sex partner in a state that 

legalized same-sex marriage before 2014. The sample includes all unmarried women and women married in the prior 12 months.

Table C3 shows logistic model parameter estimates, with standard errors, of marriage probabilities 

for unmarried men and women in same-sex household couples. Age splines for men are statistically 

significant as a group, but not significant separately. Age splines for women are more precisely 

estimated. College graduates were more likely to marry than people with less education. Marriage 

probabilities increased sharply in the first and second year after a state legalized same-sex marriage, 

suggesting some pent up demand for marriage among same-sex household couples. The marriage 

probability was higher for same-sex women with children, and when a female partner was of similar age 

and education level as the household head. These variables were not statistically significant for men.
7 4 APPENDIX C

TABLE C3

Male and Female Same-Sex Marriage Logistic Model Parameter Estimates and Standard Errors

Male Female

Parameter 

Estimate

Standard 

Error

Parameter 

Estimate

Standard 

Error

Intercept 2.5479 4.8155 6.1311 3.9503

Spline age - 15 -1.0264 1.0257 -1.6903 ** 0.8388

Spline age - 20 1.0315 1.1083 1.6561 * 0.9046

Spline age - 25 -0.0140 0.1783 0.2186 0.1560

Spline age - 30 0.0073 0.0726 -0.1787 ** 0.0704

Spline age - 40 0.0349 0.0358 -0.0445 0.0352

Spline age - 50 -0.0298 0.0441 0.0865 * 0.0485

Spline age - 55 0.0203 0.0359 -0.0683 * 0.0412

Year-legal year=0 -0.2525 0.1550 -0.4994 *** 0.1499

Year-legal year=1 0.8912 *** 0.1372 0.6129 *** 0.1292

Year-legal year=2 0.5688 *** 0.1707 0.7355 *** 0.1545

Year-legal year=3 0.4016 ** 0.1800 -0.0039 0.1917

Less than high school -0.3284 0.3241 -0.3496 0.3126

Some college 0.0779 0.1292 0.2639 * 0.1353

College graduate 0.2651 ** 0.1100 0.3890 *** 0.1190

Black -0.1736 0.2106 -0.0949 0.1933

Hispanic 0.0245 0.1236 -0.2104 0.1436

Other race -0.0573 0.1683 0.1411 0.1792

No children -0.6142 *** 0.1101

|Head age - partner age| -0.0086 0.0074

Same education dummy 0.2253 ** 0.0915

Number of observations 5397 4844

Source: Authors tabulations from the 2012-2014 American Community Survey.

Notes: Estimates were based on a sample of 5,397 men and 4,844 women ages 19 and older living with a same-sex partner in a 

state that legalized same-sex marriage before 2014. The sample includes all unmarried individuals and individuals married in the 

prior 12 months. 

***p < 0.01, **p < 0.05, *p < 0.1.
APPENDIX C 7 5

Appendix D. Heterosexual 

Cohabitation Hazard Model

TABLE D1 

Summary Statistics of the NLSY Cohabitation Estimation Dataset

Statistic Mean

Standard 

Deviation Min Max

Outcome 0.09355 0.29120 0 1

Female 0.46942 0.49907 0 1

Age-16 12.02239 9.67292 0 39

Age-19 9.29020 9.38333 0 36

Age-22 7.03827 8.72149 0 33

Age-30 3.25155 6.01431 0 25

School enrollment 0.27056 0.44425 0 1

Employment status 0.63779 0.48064 0 1

Live w/ parents 0.50998 0.49990 0 1

Children younger than 1 year 0.03543 0.18871 0 3

Children older than 1 year 0.56968 1.07602 0 11

Unemployment rate 6.40530 1.67345 4 9.7

NLSY79 0.70967 0.45392 0 1

First cohabitation 0.68650 0.46392 0 1

Log-real earnings 6.57213 4.58268 0 13

Earnings missing 0.21517 0.41094 0 1

White 0.68684 0.46378 0 1

Black 0.18991 0.39223 0 1

Hispanic 0.08229 0.27481 0 1

Asian 0.00866 0.09264 0 1

Other 0.03230 0.17678 0 1

Less than high school 0.35950 0.47985 0 1

High school 0.25831 0.43770 0 1

Some college 0.23346 0.42303 0 1

College diploma 0.09433 0.29228 0 1

Graduate school 0.05441 0.22683 0 1

Observations 272,809

Source: Authors’ tabulations from the 1979 and 1997 National Longitudinal Survey of Youth.

Notes: Table includes person-month data for individuals at risk of entering a cohabiting relationship.
7 6 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

TABLE D2: 

Cohabitation Model Logistic Parameter Estimated and Standard Errors for White, Black, and Hispanic Men and Women.

Women Men

White Black Hispanic White Black Hispanic

Intercept -3.0880*** -3.8677*** -2.2226*** -4.434*** -4.250*** -4.116***

(0.146) (0.253) (0.190) (0.212) (0.291) (0.289)

NLSY79 1.6394*** -0.9206 0.7395** 0.375 -2.812* 0.387

(0.239) (0.636) (0.350) (0.483) (1.504) (0.699)

Age splines

Age-16 0.5295*** 0.6555*** 0.3082*** 0.614*** 0.553*** 0.647***

(0.049) (0.087) (0.062) (0.074) (0.103) (0.100)

Age-19 -0.5119*** -0.6956*** -0.4115*** -0.423*** -0.370*** -0.547***

(0.065) (0.110) (0.088) (0.090) (0.129) (0.124)

Age-22 -0.0388 -0.0173 0.0869* -0.194*** -0.235*** -0.156***

(0.033) (0.050) (0.052) (0.037) (0.054) (0.055)

Age-30 -0.0713*** 0.0092 -0.0574** -0.090*** -0.092*** -0.060**

(0.016) (0.022) (0.027) (0.015) (0.020) (0.027)

Age-38 0.0484** 0.0072 0.0387 0.060*** 0.055** 0.062**

(0.019) (0.024) (0.029) (0.018) (0.022) (0.029)

NLSY79* Age-16 -0.3419*** 0.2088 -0.119 -0.073 0.476 -0.137

(0.083) (0.220) (0.125) (0.165) (0.511) (0.238)

NLSY79* Age-19 0.4301*** -0.0205 0.2561 0.251 -0.076 0.244

(0.102) (0.244) (0.158) (0.182) (0.535) (0.266)

NLSY79* Age-22 -0.1210*** -0.2214*** -0.1833** -0.203*** -0.352*** -0.09

(0.043) (0.070) (0.071) (0.049) (0.088) (0.078)

Education (omit high school graduate)

Some college -0.0448 0.0963* 0.0588 -0.114*** -0.086 -0.146**

(0.038) (0.051) (0.061) (0.038) (0.053) (0.063)

College diploma -0.0192 0.2321*** 0.3793*** -0.158*** 0.170** -0.332***
APPENDIX D 7 7

Women Men

White Black Hispanic White Black Hispanic

(0.047) (0.084) (0.102) (0.047) (0.084) (0.126)

Graduate school 0.1853*** 0.1553 0.3532*** 0.145** 0.250* 0.035

(0.061) (0.118) (0.135) (0.059) (0.132) (0.146)

School enrollment

Enrolled -0.9659*** -0.7273*** -0.8518*** -0.800*** -0.659*** -0.567***

(0.059) (0.094) (0.094) (0.071) (0.116) (0.111)

NLSY79* enrolled -0.3437*** -0.1206 -0.3647** -0.198** -0.12 -0.592***

(0.084) (0.138) (0.145) (0.094) (0.176) (0.175)

Unemployment rate -0.0596*** -0.0442** -0.0894*** -0.038*** -0.014 -0.026

(0.012) (0.017) (0.020) (0.011) (0.017) (0.020)

First cohabitation 0.0737* -0.2145*** 0.0293 -0.153*** -0.360*** -0.321***

(0.039) (0.051) (0.063) (0.037) (0.048) (0.060)

Number of children

Younger than 1 year 1.0753*** 0.7166*** 1.3261***

(0.089) (0.091) (0.101)

Older than 1 year -0.0843** -0.0356 0.0394

(0.037) (0.037) (0.048)

NLSY79* younger than 1 year 0.7615*** 0.2057* 0.2081

(0.108) (0.117) (0.131)

NLSY79* older than 1 year 0.2779*** 0.1146*** 0.1529***

(0.041) (0.041) (0.051)

Earnings

Log wage-adjust earnings 0.064*** 0.056*** 0.061*** 0.064*** 0.056*** 0.061***

(0.009) (0.009) (0.012) (0.009) (0.009) (0.012)

Missing 0.640*** 0.118 0.417*** 0.640*** 0.118 0.417***

(0.113) (0.134) (0.150) (0.113) (0.134) (0.150)

NLSY79*log wage-adjusted earnings -0.029** 0.019 0.003 -0.029** 0.019 0.003

(0.012) (0.016) (0.021) (0.012) (0.016) (0.021)
7 8 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

Women Men

White Black Hispanic White Black Hispanic

NLSY79* missing -1.432*** -0.288 -0.971*** -1.432*** -0.288 -0.971***

(0.148) (0.193) (0.241) (0.148) (0.193) (0.241)

Asian -0.5026*** -0.631***

(0.149) (0.146)

Number of observations 58551 45369 22708 71121 42658 24889

Source: Authors’ estimates from the 1979 and 1997 National Longitudinal Survey of Youth.

Notes: ***p < 0.01, **p < 0.05, *p < 0.1. Standard errors are in parenthesis. Table includes person-month data for individuals at risk of entering a cohabiting 

relationship.
APPENDIX E 7 9

Appendix E. Heterosexual Marriage and Separation 

Hazard Model, Cohabiting Couples

TABLE E1

Marriage and Separation Logistic Model Parameter Estimates and Standard Errors for Cohabiting Couples by Race

White Women Black Women Hispanic Women

Marriage Separation Marriage Separation Marriage Separation

Intercept -0.664*** 2.151*** -2.600*** 2.356*** -0.938*** 1.532***

(0.012) (0.020) (0.024) (0.032) (0.030) (0.047)

NLSY79 -2.497*** -0.293*** -0.641*** 0.839*** -2.849*** -0.431**

(0.051) (0.096) (0.067) (0.125) (0.089) (0.183)

Length of cohabitation

 Year 1 0.278*** 0.087* 1.714*** 0.058 1.313*** -0.288***

(0.042) (0.051) (0.086) (0.080) (0.083) (0.095)

 Year 2 -0.410*** 0.05 0.581*** 0.157* 0.184* -0.300***

(0.053) (0.057) (0.117) (0.086) (0.108) (0.102)

 Year 3 -0.430*** -0.087 0.344*** -0.313*** 0.12 -0.301***

(0.063) (0.068) (0.119) (0.104) (0.129) (0.113)

 Year 4 -0.364*** 0.013 0.332*** -0.382*** -0.143 -0.344***

(0.074) (0.077) (0.099) (0.116) (0.153) (0.128)

 Year>4 -0.163*** -0.097*** 0.056** -0.101*** -0.068*** -0.158***

(0.015) (0.015) (0.024) (0.019) (0.023) (0.022)

 NLSY79*Year 1 0.386*** 0.563*** -1.325*** -0.595*** -1.394*** 0.726***

(0.077) (0.083) (0.137) (0.108) (0.165) (0.148)

 NLSY79*Year 2 1.435*** 1.152*** 0.263 -0.182 0.219 0.997***
8 0 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

White Women Black Women Hispanic Women

Marriage Separation Marriage Separation Marriage Separation

(0.095) (0.094) (0.170) (0.119) (0.189) (0.167)

 NLSY79*Year 3 0.354*** 0.033 -0.197 -0.724*** -1.016*** 0.568***

(0.128) (0.137) (0.155) (0.163) (0.265) (0.203)

 NLSY79*Year 4 0.875*** 0.902*** 0.058 -0.079 0.176 0.612***

(0.134) (0.135) (0.080) (0.175) (0.265) (0.234)

 NLSY79*Year>4 0.133*** 0.064*** -0.068** -0.049** 0.005 0.121***

(0.019) (0.020) (0.030) (0.024) (0.032) (0.028)

Woman's age

 Age 0.009 -0.204*** 0.022* -0.200*** -0.015 -0.133***

(0.006) (0.006) (0.012) (0.010) (0.013) (0.014)

 Age squared -0.001*** 0.002*** -0.001*** 0.002*** -0.001** 0.001***

(0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

Man's age - Woman's age

 Less than 0 0.104* 0.454*** -0.032 0.455*** 0.051 0.039

(0.055) (0.060) (0.102) (0.079) (0.099) (0.102)

 Greater than 6 -0.150** -0.173** -0.609*** -0.126 -0.470*** -0.260**

(0.069) (0.077) (0.132) (0.093) (0.146) (0.132)

Woman's education

 Less than HS -0.465*** -0.05 -0.562*** 0.105 -0.602*** -0.138

(0.071) (0.068) (0.130) (0.088) (0.111) (0.104)

 Some college 0.249*** -0.136** 0.464*** 0.232*** 0.241** -0.300**

(0.059) (0.066) (0.103) (0.083) (0.109) (0.118)

 College diploma 0.617*** -0.444*** 1.103*** -0.028 0.598*** -0.572**

(0.070) (0.093) (0.146) (0.150) (0.166) (0.228)

 Graduate school 1.018*** -0.554*** 1.543*** -0.144 0.716*** -0.634**
APPENDIX E 8 1

White Women Black Women Hispanic Women

Marriage Separation Marriage Separation Marriage Separation

(0.092) (0.138) (0.192) (0.139) (0.215) (0.317)

Education delta: man's - woman's

 -2 or less -0.324*** 0.244** -0.550*** -0.024 -0.263 0.148

(0.087) (0.109) (0.170) (0.142) (0.185) (0.223)

 -1 -0.225*** 0.128** -0.294*** 0.041 -0.190* 0.073

(0.057) (0.063) (0.104) (0.081) (0.107) (0.110)

 1 0.150** 0.029 0.443*** 0.143 0.206* -0.048

(0.060) (0.067) (0.115) (0.091) (0.109) (0.109)

 2 or more 0.09 0.006 0.610*** 0.182 0.149 -0.267

(0.106) (0.114) (0.209) (0.166) (0.201) (0.219)

Asian -0.035 -0.594*** 0 0

(0.145) (0.178) 0

NLSY79*Asian 0.093*** 0.593*** 0 0

(0.031) (0.055) 0 0

Different races -0.345*** 0.314*** 0.111 0.017 -0.201* 0.536***

(0.076) (0.075) (0.135) (0.136) (0.104) (0.109)

NLSY79*different races 0.106 -0.232* -0.233** -0.2 0.748*** -0.281

(0.131) (0.123) (0.092) (0.251) (0.193) (0.178)

First cohabitation 0.133** -0.149** -0.145 -0.157* -0.044 -0.396***

(0.059) (0.063) (0.110) (0.092) (0.114) (0.114)

NLSY79*first cohabitation 2.327*** 0.067 1.467*** -0.02 3.067*** 0.086

(0.069) (0.122) (0.099) (0.144) (0.117) (0.209)

Previous marriage 2.876*** 0.083 2.269*** -0.013 3.596*** -0.027

(0.083) (0.111) (0.138) (0.137) (0.151) (0.181)

Number of children

 Younger than 1 year 0.021 -0.667*** 0.224* -0.497*** -0.414*** -1.165***
8 2 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

White Women Black Women Hispanic Women

Marriage Separation Marriage Separation Marriage Separation

(0.088) (0.110) (0.130) (0.127) (0.134) (0.188)

 Older than 1 year 0.069* -0.144*** 0.057 -0.041 -0.188*** -0.165***

(0.039) (0.045) (0.047) (0.042) (0.060) (0.063)

 

NLSY79*younger than 1 

year 0.244 0.348* -0.06 0.391** 0.525* 0.958***

(0.166) (0.196) (0.240) (0.197) (0.274) (0.283)

 NLSY79*older than 1 year -0.430*** 0.096* -0.202*** 0.024 0.094 0.066

(0.056) (0.057) (0.063) (0.051) (0.083) (0.079)

Number of Observations 15589 15589 7334 7334 5990 5990

Source: Authors’ estimates from the 1979 and 1997 National Longitudinal Survey of Youth. Source:

Notes: ***p < 0.01, **p < 0.05, *p < 0.1. Standard errors are in parentheses. Table includes parameter estimates from person month data for cohabiting couples at risk of marriage 

or separation.
APPENDIX F 8 3

Appendix F. Heterosexual 

Separation from Marriage Hazard 

Model, Married Couples

TABLE F1

Separation Logistic Hazard Model Parameter Estimated and Standard Errors by Race/Ethnicity

White Black Hispanic

Intercept -0.614 -0.966 -0.04

(0.503) (0.901) (0.748)

NLSY79 -0.392 1.082 -1.028

(0.411) (0.783) (0.626)

Length of marriage

 Year 1 0.053 0.255 -0.748*

(0.278) (0.645) (0.391)

 Year 2 0.212 0.287 -0.855**

(0.279) (0.649) (0.399)

 Year 3 0.02 0.333 -0.942**

(0.284) (0.652) (0.404)

 Year 4 -0.15 0.272 -1.059**

(0.291) (0.659) (0.413)

 Year>4 -0.098*** -0.093 -0.200***

(0.037) (0.090) (0.053)

 NLSY79*year 1 -0.139 -0.376 1.083**

(0.294) (0.660) (0.423)

 NLSY79*year 2 -0.111 -0.056 1.061**

(0.295) (0.663) (0.431)

 NLSY79*year 3 -0.255 -0.67 0.751*

(0.303) (0.670) (0.442)

 NLSY79*year 4 0.073 -0.269 0.898**

(0.308) (0.675) (0.451)

 NLSY79*year>4 0.028 0.008 0.115**

(0.037) (0.091) (0.053)

Woman's age

 Age -0.052** -0.049 -0.053
8 4 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

(0.026) (0.037) (0.041)

 Age squared 0.001 0 0.001

0.000 (0.001) (0.001)

Man's age - Woman's age

 Less than 0 0.249*** 0.19 0.304**

(0.089) (0.168) (0.139)

 Greater than 6 -0.092 0.288 0.188

(0.134) (0.233) (0.211)

 NLSY79*less than 0 -0.180* 0.115 -0.284*

(0.106) (0.186) (0.168)

 NLSY79*greater than 6 0.281* -0.22 -0.234

(0.150) (0.256) (0.243)

Woman's education

 Less than HS 0.603*** 0.274 0.107

(0.103) (0.225) (0.147)

 Some college -0.455*** -0.122 -0.503***

(0.100) (0.177) (0.162)

 College diploma -1.280*** -0.478* -1.064***

(0.144) (0.269) (0.303)

 Graduate school -1.848*** -1.287*** -1.548***

(0.203) (0.419) (0.449)

 NLSY79*less than HS -0.068 0.03 0.184

(0.119) (0.245) (0.169)

 NLSY79*some college 0.064 -0.034 0.086

(0.117) (0.193) (0.196)

 NLSY79*college diploma 0.259 -0.172 0.153

(0.165) (0.294) (0.372)

 NLSY79*graduate school 0.928*** 0.48 1.144**

(0.234) (0.481) (0.556)

Education delta: man's - woman's

 -2 or less 0.641*** 0.292* 0.477**

(0.100) (0.161) (0.192)

 -1 0.396*** 0.142* 0.242***

(0.054) (0.081) (0.093)

 1 -0.072 -0.052 -0.001

(0.054) (0.089) (0.086)

 2 or more -0.355*** -0.342* -0.239

(0.099) (0.177) (0.187)

Different races 0.191*** 0.058 0.182**
APPENDIX F 8 5

(0.062) (0.128) (0.080)

Cohabited -0.055 -0.390*** -0.266***

(0.048) (0.087) (0.094)

Number of Children

 Younger than 1 year -0.713*** -0.271*** -0.420***

(0.074) (0.102) (0.104)

 Older than 1 year -0.005 0.037 0.109***

(0.020) (0.024) (0.029)

Earnings

 Wife -0.018 0 0.046**

(0.012) (0.022) (0.019)

 Wife, missing -0.274** -0.305 0.154

(0.135) (0.268) (0.214)

 Husband -0.062*** -0.035 -0.103***

(0.019) (0.029) (0.028)

 Husband, missing -0.126 0.081 -0.197

(0.213) (0.320) (0.296)

 NLSY79*Wife 0.014 -0.003 -0.028

(0.017) (0.030) (0.028)

 NLSY79*wife, missing -0.071 0.19 -0.281

(0.188) (0.334) (0.292)

 NLSY79*husband -0.001 -0.086** 0.025

(0.025) (0.035) (0.039)

 NLSY79*husband, missing -0.276 -1.229*** -0.454

(0.275) (0.378) (0.414)

Asian -0.281

(0.285)

NLSY79*Asian 0.071

(0.374)

Number of Observations 75817 18819 21380

Source: Authors’ estimates from the 1979 and 1997 National Longitudinal Survey of Youth. Source:

Notes: ***p < 0.01, **p < 0.05, *p < 0.1. Standard errors are in parentheses

.
8 6 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

Appendix G. Heterosexual Divorce 

Hazard Model for Separated 

Couples

TABLE G1

Divorce Logistic Hazard Model Parameter Estimates and Standard Errors

Parameter Estimate Standard Error

Intercept -3.345 (1.659)**

NLSY79 3.916 (1.737)**

Length of separation

 Year 1 1.249 (0.623)**

 Year 2 1.13 (0.627)*

 Year 3 0.746 (0.635)

 Year 4 0.213 (0.652)

 Year>4 0.014 (0.091)

 NLSY79*year 1 -0.912 (0.640)

 NLSY79*year 2 0.07 (0.643)

 NLSY79*year 3 -0.754 (0.655)

 NLSY79*year 4 0.479 (0.671)

 NLSY79*year>4 -0.031 (0.092)

Woman's race

 Black -0.241 (0.333)

 Hispanic -0.681 (0.569)

 Asian -0.902 (0.322)***

Different races

 Different races -0.27 (0.104)***

 Black*different races 0.389 (0.227)*

 Hispanic*different races 0.876 (0.167)***

Woman's age

 Age 0.18 (0.118)

 Age squared -0.005 (0.002)**

 NLSY79*age -0.279 (0.122)**

 NLSY79*age squared 0.006 (0.002)**

Man's age - woman's age

 Less than 0 0.114 (0.064)*

 Greater than 6 -0.219 (0.079)***
APPENDIX G 8 7

Parameter Estimate Standard Error

Woman's education

 Less than HS -0.664 (0.098)***

 Some college 0.282 (0.097)***

 College diploma 0.2 (0.141)

 Graduate school 0.287 (0.179)

 Black*less than HS -0.319 (0.364)

 Black*high school -1.058 (0.343)***

 Black*some college -0.874 (0.353)**

 Black*college diploma 0.416 (0.438)

 Hispanic*less than HS 0.132 (0.580)

 Hispanic*high school -0.077 (0.575)

 Hispanic*some college -0.156 (0.584)

 Hispanic*college diploma 0.044 (0.675)

Education delta: man's - woman's

 -2 or less -0.349 (0.123)***

 -1 -0.25 (0.067)***

 1 0.066 (0.069)

 2 or more 0.139 (0.120)

Number of children

 Younger than 1 year -0.319 (0.095)***

 Older than 1 year -0.058 (0.020)***

Earnings

 Wife 0.046 (0.012)***

 Wife, missing 0.269 (0.122)**

 Husband 0.063 (0.019)***

 Husband, missing 0.601 (0.201)***

Observations 10,947

Source: Authors’ estimates from the 1979 and 1997 National Longitudinal Survey of Youth. Source:

Notes: ***p < 0.01, **p < 0.05, *p < 0.1. Standard errors are in parentheses. The model is estimated on all separated individuals.
8 8 HOW MIGHT RECENT SAME-SEX MARRIAGE DECISIONS AFFECT RETIREMENT INCOMES?

Notes

1. The General Accounting Office counted 1,138 federal provisions in which marital status a 

factor (Crandall-Hollick, Pettit, and Sherlock 2015).

2. State-level data are subject to change from year to year because of random variation due to the 

relatively small number of cases in each state.

3. These states include Massachusetts, Connecticut, Iowa, Vermont, District of Columbia, New 

Hampshire, New York, Washington, and Maine. 
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9 2 ABOUT THE AUTHORS

About the Authors

Stephen Rose is an affiliated scholar in the Income and Benefits Policy Center at the 

Urban Institute. He is a nationally recognized labor economist and has spent the last 35 

years researching and writing about the interactions between formal education, 

training, career movements, incomes, and earnings. His book, Social Stratification in 

the United States, was originally published in 1978, and the seventh edition was 

released in 2014. 

Karen E. Smith is a senior fellow in the Income and Benefits Policy Center at the Urban 

Institute, where she is an internationally recognized expert in microsimulation. Over 

the past 30 years, she has developed microsimulation models for evaluating Social 

Security, pensions, taxation, wealth and savings, labor supply, charitable giving, health 

expenditure, student aid, and welfare reform. Smith has played a lead role in the 

development of the Social Security Administration’s Modeling Income in the Near 

Term microsimulation model, Urban Institute’s Dynamic Simulation of Income 

microsimulation model, and the Social Security Administration’s Policy Simulation 

Model. 

Damir Cosic is a research associate in the Income and Benefits Policy Center at Urban 

Institute and part of a group that studies retirement income and benefits. His work 

focuses on policy evaluation using microsimulation models. Cosic holds a BS in 

electrical engineering from the University of Zagreb in Croatia and has extensive 

experience as a software engineer. He received an MA in economics from Hunter 

College in New York City and PhD in economics from the Graduate Center at the City 

University of New York. 
STATEMENT OF INDEPENDENCE

The Urban Institute strives to meet the highest standards of integrity and quality in its research and analyses and in 

the evidence-based policy recommendations offered by its researchers and experts. We believe that operating 

consistent with the values of independence, rigor, and transparency is essential to maintaining those standards. As 

an organization, the Urban Institute does not take positions on issues, but it does empower and support its experts 

in sharing their own evidence-based views and policy recommendations that have been shaped by scholarship. 

Funders do not determine our research findings or the insights and recommendations of our experts. Urban 

scholars and experts are expected to be objective and follow the evidence wherever it may lead.
1. The General Accounting Office counted 1,138 federal provisions in which marital status a factor (CrandallHollick, Pettit, and Sherlock 2015).

2. State-level data are subject to change from year to year because of random variation due to the relatively 

small number of cases in each state.

3. These states include Massachusetts, Connecticut, Iowa, Vermont, District of Columbia, New Hampshire, New 

York, Washington, and Maine. 

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