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<h1 itemprop="headline">The Implications of Marital History Change on Women's Eligibility for Social Security Wife and Widow Benefits, <span class="nobr">1990–2009</span></h1>
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<div id="hByline">by <span itemprop="author">Howard M. Iams and Christopher R. Tamborini</span><br>Social Security Bulletin, <abbr title="Volume">Vol.</abbr> 72, <abbr title="Number">No.</abbr> 2, 2012 (released May 2012)</div>
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<h4>Related Content</h4>
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<div class="rcItems">
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<p>Research Summary: <a href="/policy/docs/research-summaries/marriage-trends.html">Marriage Trends & Women's Benefits</a></p>
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<p>Research Summary: <a href="/policy/docs/research-summaries/marriage-trends-race-ethnicity.html">Marriage Trends, Women's Benefits, & Demographic Differences</a></p>
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<p>Research Summary: <a href="/policy/docs/research-summaries/womens-eligibility.html">Women's Eligibility Basis</a></p>
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</div>
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</div>
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<div class="introBox">
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<p id="synopsis" itemprop="description">Social Security retirement benefits in the United States (<abbr class="spell">US</abbr>) reflect marital histories and lifetime earnings of current and former married couples. Focusing on the link between marital history and benefit eligibility, this article examines women's marital patterns over the past two decades. Using the 1990 and 2009 Marital History Modules to the Census Bureau's Survey of Income and Program Participation, descriptive/regression analysis reveals substantial changes in women's marital patterns among baby boomers and generation Xers. Those changes have prompted a decline in qualifying marital histories for Social Security spouse and widow benefits. The findings also reveal substantial variation by race/ethnicity. Black women are significantly more likely to be potentially ineligible for a marriage-based benefit than white women, particularly in more recent cohorts. Hispanic women's marriage-based eligibility is between that of black and white women. <span class="nobr"><abbr class="spell">US</abbr>-born</span> Hispanic women had higher shares without a qualifying marital history compared with the foreign born.</p>
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<hr />
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<div class="eightypercent">
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<p>Howard Iams is a senior research advisor to the Office of Research, Evaluation, and Statistics, Office of Retirement and Disability Policy (<abbr class="spell">ORDP</abbr>), Social Security Administration (<abbr class="spell">SSA</abbr>). Christopher Tamborini is a social science research analyst with the Office of Retirement Policy, <abbr class="spell">ORDP</abbr>, <abbr class="spell">SSA</abbr>.</p>
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<p><i>Acknowledgments:</i> The authors thank Lionel P. Deang, Kimberly Burham, David Timmons, David Weaver, and Susan Grad for valuable comments. </p>
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<p>Contents of this publication are <a href="/policy/accessibility.html">not copyrighted</a>; any items may be reprinted, but citation of the <i>Social Security Bulletin</i> as the source is requested. The findings and conclusions presented in the <i>Bulletin</i> are those of the authors and do not necessarily represent the views of the Social Security Administration.</p>
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</div>
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</div>
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<h2>Introduction</h2>
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<div class="abbrtable">
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<table role="presentation">
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<caption>Selected Abbreviations</caption>
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<tr>
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<td><abbr title="Gen X">GenX</abbr></td>
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<td>generation X</td>
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</tr>
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<tr>
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<td><abbr class="spell">PIA</abbr></td>
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<td>primary insurance amount</td>
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</tr>
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<tr>
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<td><abbr>SIPP</abbr></td>
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<td>Survey of Income and Program Participation</td>
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</tr>
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</table>
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</div>
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<p>Over the six decades following World War <abbr title="two">II</abbr>, major sociodemographic changes occurred in the American family. An important research and public policy subject is to document those changes and their implications for retirement outcomes, particularly for the baby boom generation now entering retirement. In this article, we examine the change in women's marital patterns at different stages of the life course over the past two decades and its implications for women's eligibility status for Social Security spouse and survivor benefits at retirement age.</p>
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<p>Women's financial circumstance in old age is a longstanding concern among policymakers and researchers (Ekerdt 2010; Favreault and Steuerle 2007; Government Accountability Office 2007; Holden and Fontes 2009; Lusardi and Mitchell 2008; Weaver 1997, 2010). Although the retirement security of women has improved significantly over the past 30 years, women have higher poverty rates in old age than men, in large part because they earn less over a lifetime and live longer (Blau and Kahn 2006; Weinberg 2007; Bureau of Labor Statistics 2010). Greater longevity also means that many women will spend some time during their life course as widows. Estimates from the Current Population Survey show that the poverty rate for women aged 65 or older in 2008 was almost double (11.9 percent) that of men (6.7 percent), with the unmarried group being particularly vulnerable to poverty (16.9 percent of single women compared with 5.0 percent of married women); see <abbr class="spell">SSA</abbr> (2010, Table 11.1).</p>
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<p>A growing body of research has shown a connection between women's lifetime marital experiences and retirement outcomes (Couch and others 2011; Wilmoth and Koso 2002; Tamborini, Iams, and Whitman 2009; Zissimopoulos, Karney, and Rauer 2008). The main purpose of this study is to determine the implications of changing marital patterns on women's eligibility for Social Security marriage-based benefits at retirement. The Social Security program not only provides women with income as retired or disabled workers but also as spouses or widows of insured workers. Generally, a person must be currently married, widowed, or divorced from a <span class="nobr">10-year</span> marriage to qualify for a spouse or <span class="nobr">widow(er)</span> benefit. This link between marital history and benefit eligibility means that the distribution of women who have the option of claiming spouse or widow benefits at retirement is subject to fundamental changes in marriage behavior.</p>
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<p>In this article, we assess the evolution of women's potential eligibility for Social Security spouse and widow benefits over the past two decades. We draw from the 1990 and the recently released 2009 Marital History Modules to the Census Bureau's Survey of Income and Program Participation (<abbr>SIPP</abbr>). Our analysis compares the marital histories of women in their thirties, forties, and fifties in 2009 with similarly aged women in 1990 using descriptive and regression methods. Building on recent studies that have found declining eligibility for spouse and widow benefits because of changes in marriage patterns (Harrington Meyer, Wolf, and Himes 2006; Tamborini, Iams, and Whitman 2009), we consider how current marital trends may reshape women's potential eligibility for spouse or widow benefits and how those patterns vary across race and ethnic subgroups.</p>
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<p>The results contribute to the literature in several ways. First, by using more recent nationally representative data than previously available, we provide up-to-date evidence indicating how women's eligibility for spouse and widow benefits is changing because of changes in marital patterns. Second, we offer insight into the early life marital experiences of the generation X (<abbr title="Gen X">GenX</abbr>) cohorts.<sup><a href="#mn1" id="mt1">1</a></sup> Research has just begun to consider family trends in postboomer cohorts (Tamborini and Iams 2011), and no studies to date have examined marital trends in <abbr title="Gen X">GenX</abbr> cohorts as they relate to Social Security marriage-based benefits.</p>
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<p>A third contribution of the present study is that it advances understanding of how eligibility for Social Security marriage-based benefits varies across race and ethnic subgroups. Although the Social Security program is gender and race neutral and handles persons with identical earnings or marital histories in the same way, racial differences in marital patterns can result in differences in eligibility for marriage-based Social Security benefits. This article addresses whether the racial differentials in potential benefit eligibility resulting from differences in marital history have continued from those observed through 1995 by Harrington Meyer, Wolf, and Himes (2006) and those observed through 2004 by Tamborini, Iams, and Whitman (2009). We also estimate the eligibility patterns of Hispanic women, by nativity, which is a useful focus given the lack of research on this issue combined with their growing share of the population in the United States (<abbr class="spell">US</abbr>).</p>
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<p>The next section elaborates on the background guiding this study. We then present the data and methods, followed by the empirical results. Finally, a conclusion is provided with a summary of the findings and their broader implications.</p>
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<h2>Background</h2>
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<p>Social Security benefits are an important source of retirement income for women. According to the Current Population Survey, Social Security made up at least half of the family income for 58 percent of women aged 65 or older in 2008 (<abbr class="spell">SSA</abbr> 2010, Table 9.B1). Benefits are particularly important to the financial security of the single, elderly population. Among women aged 65 or older in beneficiary families in 2008, Social Security accounted for at least 90 percent of the family income of 35 percent of unmarried women compared with 21 percent of married women (ibid., Table 9.B3).</p>
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<p>Originally, Social Security benefits were based on a worker's own lifetime earnings covered by the program. In the 1939 Social Security Amendments, Congress established wife and widow benefits to provide monthly payments to qualified spouses and survivors of insured workers (Martin and Weaver 2005). As Berkowitz (2002) noted, the design of Social Security marriage-based benefits was essentially based on a family structure common to the Depression era, when the Social Security program began; see also Cherlin (2009, 69). Typical to that era would be a one-earner family with an employed husband supporting a wife and children in a marriage that continued until the death of one of the spouses. Over time, those benefits were extended to divorced spouses and divorced surviving spouses with 10 years in the marriage and to children.<sup><a href="#mn2" id="mt2">2</a></sup></p>
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<p>Potential eligibility for Social Security spouse or <span class="nobr">widow(er)</span> benefits reflects a person's past and present marital status. The amount reflects the work record of that person in relation to the record of their current or former <span class="nobr">spouse(s).</span> In other words, the amount of Social Security spouse or <span class="nobr">widow(er)</span> benefits is a function of the lifetime earnings of workers and their spouses (or former spouses), while eligibility is based on marital history. Table 1 provides a brief overview of current marital requirements.</p>
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<div class="table" id="table1">
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<table class="textTable">
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<caption><span class="tableNumber">Table 1. </span>Entitlement to retired-worker and marriage-based (spouse and survivor) benefits at retirement age, by marital status and history</caption>
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<colgroup span="1" style="width:20em"></colgroup>
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<colgroup span="2" style="width:25em"></colgroup>
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<thead>
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<tr>
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<th class="stubHeading" scope="col">Marital status and history</th>
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<th scope="col">Retired-worker benefit</th>
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<th scope="col">Marriage-based benefit</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<th class="stub0" scope="row">Currently married or separated</th>
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<td>Must have at least 40 quarters of covered employment.</td>
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<td>Yes, up to 50 percent of the spouse's <abbr class="spell">PIA</abbr> if the spouse is still living. <sup>a</sup></td>
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</tr>
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<tr>
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<th class="stub0" scope="row">Widowed</th>
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<td>Must have at least 40 quarters of covered employment.</td>
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<td>Yes, up to 100 percent of the deceased spouse's <abbr class="spell">PIA</abbr>. <sup>b</sup></td>
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</tr>
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<tr>
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<th class="stub0" scope="row">Divorced with 10 years of marriage to an insured former spouse</th>
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<td>Must have at least 40 quarters of covered employment.</td>
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<td>Yes, if the spouse is living, benefits for married or sepa-rated women apply; if the spouse is deceased, widow benefits apply.</td>
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</tr>
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<tr>
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<th class="stub0" scope="row">Divorced with less than 10 years of marriage</th>
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<td>Must have at least 40 quarters of covered employment.</td>
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<td>None.</td>
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</tr>
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</tbody>
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<tfoot>
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<tr>
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<td class="firstNote" colspan="3">SOURCE: Adapted from Tamborini, Iams, and Whitman (2009, Table 1.)</td>
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</tr>
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<tr>
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<td class="note" colspan="3">a. If the person is entitled to a spouse and retired-worker benefit, then that person is said to be dually entitled. If the spouse benefit exceeds the person's own retired-worker benefit, then the full retired-worker benefit is paid with the difference between the retired-worker and spouse benefit added to the benefit amount.</td>
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</tr>
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<tr>
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<td class="lastNote" colspan="3">b. Widows can also be dually entitled. To qualify for a survivor benefit, a person must be unmarried or have remarried at or after age 60.</td>
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</tr>
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</tfoot>
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</table>
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</div>
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<p>Under current law, an aged individual who is currently married to an insured worker is eligible for a spouse benefit equal to a maximum of half of his or her spouse's primary insurance amount (<abbr class="spell">PIA</abbr>), beginning at the early retirement age of 62.<sup><a href="#mn3" id="mt3">3</a></sup> Eligible spouses generally must be married to the retiring worker for at least 1 continuous year before they can receive benefits based on their entitled spouse's record. An aged divorced person may be eligible for a divorced spouse benefit equal to up to half of his or her <span class="nobr">ex-spouse's</span> <abbr class="spell">PIA</abbr> if the marriage was 10 years (120 months) in duration and the <span class="nobr">ex-spouse</span> is alive. If the aged person qualifies for his or her own retired-worker benefit and a spouse or divorced spouse benefit, that person will receive the higher amount of the two benefits. If the spouse benefit exceeds one's own retired-worker benefit, that person becomes dually entitled and will receive his or her full retired-worker benefit with the spouse benefit supplementing the difference. If the retired-worker benefit is higher than the spouse benefit, then that person will receive only his or her own worker benefit.</p>
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<p>Social Security also provides <span class="nobr">widow(er)</span> benefits. If a surviving spouse begins to receive benefits at the full retirement age, the <span class="nobr">widow(er)</span> benefit can equal up to 100 percent of a deceased spouse's <abbr class="spell">PIA</abbr>. A reduced benefit (from 71 percent to 99 percent of the deceased worker's <abbr class="spell">PIA</abbr>) is available as early as age 60 (age 50 if the survivor is disabled).<sup><a href="#mn4" id="mt4">4</a></sup> Divorced persons with a <span class="nobr">10-year</span> marriage may qualify for a surviving divorced spouse benefit if their <span class="nobr">ex-spouse</span> dies. If the <span class="nobr">widow(er)</span> benefit exceeds a person's own retired-worker benefit, that person is dually entitled and will receive his or her full retired-worker benefit with the <span class="nobr">widow(er)</span> benefit supplementing the difference.<sup><a href="#mn5" id="mt5">5</a></sup> If the retired-worker benefit is larger than the <span class="nobr">widow(er)</span> benefit, then that person would be eligible for only a retired-worker benefit.</p>
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<p>Over the past five decades, women increasingly receive their own earned benefits, but spouse and survivor benefits still constitute a major part of the Social Security program. To illustrate, Chart 1 compares the distribution of benefits among aged female Social Security beneficiaries from 1960 through 2009. Several noteworthy trends emerge. First, the majority of aged women receive at least part of their Social Security benefit as a wife or widow. In 1960, around 61 percent (4.1 million) of female beneficiaries aged 62 or older received some type of benefit as a wife or widow, and in 2009 this figure was 55 percent (12.9 million). Second, the share of retired-worker-only beneficiaries remained relatively constant over the period (at about 40 percent), until recently increasing in 2009 (to about 45 percent).</p>
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<div class="chartCenter">
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<div class="chart700" id="chart1">
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<div class="title">Chart 1.<br>Percentage distribution of female Social Security beneficiaries aged 62 or older, by type of benefit and dual-entitlement status, selected years <span class="nobr">1960–2009</span></div>
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<div class="scrollChart"><img src="v72n2p23-chart01.gif" alt="Stacked bar chart with tabular version below." width="700" height="344" /></div>
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<div class="table altTable"><a class="altToggle" href="">Show as table</a>
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<table>
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<caption><span class="tableNumber">Table equivalent for Chart 1. </span>Percentage distribution of female Social Security beneficiaries aged 62 or older, by type of benefit and dual-entitlement status, selected years <span class="nobr">1960–2009</span></caption>
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<colgroup span="1" style="width:20em"></colgroup>
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<colgroup span="10" style="width:5em"></colgroup>
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<thead>
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<tr>
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<th class="stubHeading" scope="col">Type of benefit and dual entitlement status</th>
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<th scope="col">1960</th>
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<th scope="col">1970</th>
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<th scope="col">1975</th>
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<th scope="col">1980</th>
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<th scope="col">1985</th>
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<th scope="col">1990</th>
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<th scope="col">1995</th>
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<th scope="col">2000</th>
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<th scope="col">2005</th>
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<th scope="col">2009</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<th class="stub0" scope="rowgroup">Retired-worker only benefit</th>
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<td>38.7</td>
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<td>42.1</td>
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<td>42.3</td>
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<td>41.0</td>
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<td>38.5</td>
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<td>36.9</td>
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<td>36.2</td>
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<td>38.0</td>
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<td>41.4</td>
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<td>45.1</td>
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</tr>
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<tr>
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<th class="stub0" scope="rowgroup">Spouse or widow benefit of some type</th>
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<td colspan="10"></td>
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</tr>
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<tr>
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<th class="stub1" scope="row">Spouse only</th>
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<td>32.8</td>
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<td>22.4</td>
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<td>19.6</td>
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<td>17.6</td>
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<td>16.4</td>
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<td>15.3</td>
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<td>14.3</td>
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<td>12.9</td>
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<td>11.4</td>
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<td>10.0</td>
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</tr>
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<tr>
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<th class="stub1" scope="row">Widow only</th>
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<td>23.4</td>
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<td>26.8</td>
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<td>26.1</td>
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<td>25.4</td>
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<td>24.9</td>
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<td>24.3</td>
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<td>23.6</td>
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<td>21.5</td>
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<td>19.3</td>
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<td>17.0</td>
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</tr>
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<tr>
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<th class="stub1" scope="row">Dually entitled spouse</th>
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<td>2.4</td>
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<td>3.4</td>
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<td>4.4</td>
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<td>6.2</td>
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<td>8.7</td>
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<td>10.4</td>
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<td>11.5</td>
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<td>12.0</td>
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<td>12.0</td>
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<td>12.0</td>
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</tr>
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<tr>
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<th class="stub1" scope="row">Dually entitled widow</th>
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<td>2.1</td>
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<td>5.0</td>
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<td>7.4</td>
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<td>9.6</td>
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<td>11.5</td>
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<td>13.0</td>
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<td>14.4</td>
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<td>15.6</td>
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<td>16.0</td>
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<td>15.4</td>
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</tr>
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</tbody>
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<tfoot>
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<tr>
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<td class="noNotes" colspan="11"> </td>
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</tr>
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</tfoot>
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</table>
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</div>
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<div class="firstNote">SOURCE: Social Security Administration, Master Beneficiary Record (<abbr class="spell">SSA</abbr> 2011a, Table 5.A14).</div>
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<div class="lastNote">NOTES: All data for 2005 and dual-entitlement data for 1995 and 2000 are based on a 10 percent sample of administrative records. All other years are 100 percent data. Benefits exclude special <span class="nobr">age-72</span> beneficiaries and disabled adult children. They include disabled workers. Widow-only beneficiaries include disabled widows and mothers. Totals may not sum to 100 because of rounding.</div>
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</div>
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</div>
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<p>Third, there has been a shift away from women's entitlement based solely on their husband's record to dual entitlement—retired-worker benefits that are supplemented by a higher auxiliary spouse or survivor benefit. Thus, the share of dually entitled women rose from 5 percent in 1960 to 20 percent in 1985 and to 27 percent in 2009. Rising female labor force participation has largely driven this trend. Because women usually have lower lifetime earnings than their spouses, partly because of family responsibilities (for example, child rearing or caretaking of other family members), many women who qualify for their own retired-worker benefit also are dually entitled to a spouse, or more likely, a widow benefit (Butrica, Iams, and Sandell 1999; Kingson and O'Grady-LeShane 1993).</p>
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<h2>Marital Trends, Race and Ethnicity, and Social Security</h2>
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<p>The present study focuses on the link between marital trends and women's eligibility for marriage-based Social Security benefits, while recognizing that women's lifetime workforce attachment will also influence the benefits they receive. A focus on marital trends is valuable given that fundamental changes in marriage behavior in the United States over the past decades will have important implications for women's retirement experience, including their Social Security benefits (Couch and others 2011).</p>
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<p>Briefly, recent analysis of marital history data has shown declining marriage rates after the mid-1970s to "the lowest level in recorded history" by 2004 (Stevenson and Wolfers 2007, 29; Goldstein and Kenney 2001; Tamborini 2007). Less than 90 percent of women were likely to ever marry among the late-1960s birth cohort, unlike women born in the late 1940s (Kreider and Ellis 2011, 6). The divorce rate increased dramatically in the 1970s, peaked in 1981, and gradually decreased over the next 25 years (Stevenson and Wolfers 2007). Together, these trends have resulted in a sharp reduction in the percentage of currently married women between 1980 and 2009 (Kreider and Ellis 2011).</p>
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<p>At the same time, empirical research has shown increasing heterogeneity in marital outcomes by race and ethnicity. Black women have had a "lower and slower" entry into marriage than white women, a reversal of previous patterns (Goldstein and Kenney 2001; Kreider and Ellis 2011, Table 1; Stevenson and Wolfers 2007). Research has also found black/white differentials in marital disruption (Sweeney and Phillips 2004). The trend for Hispanic women has been mixed; generally, the marital experiences of Hispanic women has been characterized as somewhere between those of black and white women (McNamee and Raley 2011). While Hispanic women's marriage rates were similar to those of white women, their divorce rates were closer to those of black women, depending on the cohort. Importantly, research has indicated substantial differences by nativity, with marriage rates being higher among foreign-born than <span class="nobr"><abbr class="spell">US</abbr>-born</span> Hispanics (McNamee and Raley 2011; Oropesa and Landale 2004).<sup><a href="#mn6" id="mt6">6</a></sup></p>
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<p>Recent empirical work by Tamborini, Iams, and Whitman (2009) and Harrington Meyer, Wolf, and Himes (2006) showed that changes in marriage patterns among recent birth cohorts would lead to a decline in women's eligibility for spouse and widow benefits when those cohorts reach retirement age. A key finding in both analyses was that lower marriage rates among black women would result in sharper declines in their potential eligibility for spouse or widow benefits compared with white women. Harrington Meyer, Wolf, and Himes's (2006) projections also showed fairly similar trends in potential eligibility between white and Hispanic women using Current Population Survey marital history data through 1995.</p>
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<p>Put together, prior research leads us to expect declines in potential eligibility for spouse or widow benefits among recent cohorts of women as a result of changing marital patterns. We also expect that the downward trend is sharper for black women than white women because of the widening racial gap in marriage rates among recent cohorts. Hispanic women are expected to show mixed patterns, with substantial differences by nativity.</p>
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<h2>Methods</h2>
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<p>The data for this analysis are from the 1990 and the recently released 2009 Marital History Topical Modules (Wave 2 of the 1990 and 2008 panels) to the Census Bureau's <abbr>SIPP</abbr>—a nationally representative household survey designed to measure program participation and the economic situation of persons, families, and households in the United States.</p>
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<p><abbr>SIPP</abbr>'s Marital History Topical Module, implemented once within each panel, collects retrospective marital histories for every person in the household aged 15 or older. The data include information on marital transitions in months and years, which permit precise estimates of whether a respondent has a <span class="nobr">10-year</span> marriage. Because comprehensive marital history data are no longer collected by the National Center for Health Statistics and the Current Population Survey, the Marital History Module represents the best current data sources of marital history for the <abbr class="spell">US</abbr> population. Moreover, because the Census Bureau is redesigning the <abbr>SIPP</abbr> for 2014, the 2009 <abbr>SIPP</abbr> marital history data will be the most recent source for comprehensive marital histories of individuals for some time. The Social Security Administration (<abbr class="spell">SSA</abbr>) has funded a supplement to the redesigned <abbr>SIPP</abbr> to collect <abbr>SIPP</abbr> respondent's marital histories in the fall of 2014 and release data in 2015.</p>
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<p>The current study relies on a restricted-use file of the 2009 <abbr>SIPP</abbr> Marital History Module. In contrast to 1990, marital transition dates in months are not provided in the 2009 public-use file. Because the inclusion of marital data in months allows for more precise estimates of length of marriage, particularly with respect to Social Security's <span class="nobr">10-year</span> marriage rule, we utilize a restricted-use file, which contains this information.<sup><a href="#mn7" id="mt7">7</a></sup> To protect respondent confidentiality, all users of restricted files must have authorization from the Census Bureau, and the data must be used only for research purposes. All statistics have also been reviewed by <abbr class="spell">SSA</abbr>'s disclosure review board.</p>
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<h3>Analytic Approach</h3>
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<p>Our study sample consists of women aged <span class="nobr">30–59</span> in the 1990 and 2009 Marital History Modules, corresponding to an unweighted sample size of 11,208 in 1990 and 20,936 in 2009. Descriptive statistics of the study sample appear in the Appendix, <a href="#tableA1">Table A-1</a>.</p>
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<p>A key aspect of our analytic approach is the stratification of the sample into three age groups: young adult (<span class="nobr">30–39</span>), middle age (<span class="nobr">40–49</span>), and late middle age (<span class="nobr">50–59</span>). Comparing those age-specific groups across the two survey years permits us to identify differences across period and birth cohorts. Table 2 illustrates the birth cohorts represented for each age group in our analysis. As shown in the table, women in their forties and fifties in 2009 approximated the late baby boom/early <abbr title="Gen X">GenX</abbr> and middle baby boom birth cohorts, while women in their thirties represented the <abbr title="Gen X">GenX</abbr> birth cohort. By contrast, women in their fifties constituted the pre–baby boom cohorts in 1990, while women in their forties represented a mix of pre– and early baby boomers, and women in their thirties reflected the middle of the baby boom cohort. We recognize that younger women, particularly in their thirties, are far from finishing their marital histories. However, taking stock of women's marital experiences at the early to midlife stages of their life course across nearly two decades provides important insights into the broad direction of marital changes that may affect women's Social Security eligibility for marriage-based benefits in the future.</p>
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<div class="table" id="table2">
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<table class="textTable">
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<caption><span class="tableNumber">Table 2. </span>Relationship between study period, birth cohort, and age group for the sample population, 1990 and 2009</caption>
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<colgroup span="1" style="width:12em"></colgroup>
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<colgroup span="2" style="width:20em"></colgroup>
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<thead>
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<tr>
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<th class="stubHeading" scope="col">Age group</th>
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<th scope="col">1990</th>
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<th scope="col">2009</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<th class="stub0" scope="row">Young adult (<span class="nobr">30–39</span>)</th>
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<td><span class="nobr">1950–1960</span> (middle baby boom)</td>
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<td><span class="nobr">1968–1978</span> (<abbr title="Gen X">GenX</abbr>)</td>
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</tr>
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<tr>
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<th class="stub0" scope="row">Middle age (<span class="nobr">40–49</span>)</th>
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<td><span class="nobr">1940–1950</span> (pre– and early baby boom)</td>
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<td><span class="nobr">1958–1968</span> (late baby boom/ early <abbr title="Gen X">GenX</abbr>)</td>
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</tr>
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<tr>
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<th class="stub0" scope="row">Late middle age (<span class="nobr">50–59</span>)</th>
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<td><span class="nobr">1930–1940</span> (pre–baby boom)</td>
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<td><span class="nobr">1948–1958</span> (middle baby boom)</td>
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</tr>
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</tbody>
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<tfoot>
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<tr>
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<td class="firstNote" colspan="3">SOURCE: Authors' calculations using 1990 and 2008 <abbr>SIPP</abbr> (Wave 2) data. </td>
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</tr>
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<tr>
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<td class="lastNote" colspan="3">NOTES: Birth cohorts slightly overlap because of the month in which the data was collected relative to the respondent's birth date. The second wave of the <abbr>SIPP</abbr> was collected from June through September of 1990 and from February through May of 2009.</td>
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</tr>
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</tfoot>
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</table>
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</div>
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<p>Our analysis uses descriptive and multivariate regression methods. Given prior research showing racial differences in eligibility for Social Security marriage-based benefits resulting from differential marital patterns, our analysis provides separate estimates by race and ethnicity. Among Hispanic women, we also consider outcomes between those who were born in the United States and those who were foreign born. Unless otherwise noted, descriptive differences discussed in the text are significant at the .05 level.</p>
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<p>The multivariate regression analysis employs a probit model to examine the probability of not having eligibility for Social Security spouse or widow benefits based on marital history, holding important variables constant. We estimate separate probit regressions for the three age-specific groups in 1990 and 2009. This allows us to better identify differences in potential eligibility between 1990 and 2009 among women at the same stage of the life cycle. The general model can be expressed as follows:</p>
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<div class="equation">
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<math>
|
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<mrow>
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|
<mi>Y</mi>
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|
<mo>=</mo>
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<mi>α</mi>
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<mo>+</mo>
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<msub>
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|
<mi>β</mi>
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<mn>1</mn>
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</msub>
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<mi>R</mi>
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<mi>E</mi>
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<mo>+</mo>
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<msub>
|
|
<mi>β</mi>
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<mn>2</mn>
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</msub>
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<mi>C</mi>
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<msub>
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<mo>+</mo>
|
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<mi>E</mi>
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</msub>
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</mrow>
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</math>
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</div>
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<p class="noindent">where <i>Y</i> is the estimated probability of having a marital history that would imply ineligibility for Social Security spouse or widow benefits net of other characteristics; α is the intercept, βs are the probit regression coefficients, and <i><sub>E</sub></i> is the error term. Vector <i>RE</i> reflects the dummy variables measuring race and ethnicity/nativity, and vector <i>C</i> refers to the control variables.</p>
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<p>The dependent variable is a dichotomous measure denoting "ineligible" for Social Security spouse or widow benefits based on marital history (1 = yes, 0 = no). In this case, <i>ineligible</i> refers to those women who were never married or currently divorced without any <span class="nobr">10-year</span> marriage at the time of the survey.</p>
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<p>The key independent variables are the set of five dummy variables indicating race and ethnicity/nativity for Hispanics: (1) white non-Hispanic, (2) black non-Hispanic, (3) <abbr class="spell">US</abbr>-born Hispanic, (4) foreign-born Hispanic, and (5) other. The omitted reference group is white non-Hispanic. When we use the identifier black or white, we refer to non-Hispanics. Comparing the marginal effects of the race and ethnicity dummy variables in the 1990 and 2009 estimates helps us to identify whether the association between potential eligibility and race and ethnicity has changed.</p>
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<p>Control variables are educational attainment and age at the time of the survey. Education is measured by four dummy variables: less than high school graduate, high school graduate, some college, and bachelor's degree. High school graduate is the reference group. We measure the respondent's age in years. Income is not controlled for given that income measures in the <abbr>SIPP</abbr> reflect a woman's income status at the time of the survey rather than over her lifetime. Current marital status is quite likely to affect family income; for example, married couples tend to have higher family incomes than single persons. This relationship may result in biased estimators if income was included in the equation.</p>
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<p>Throughout the analysis, we use Stata's <i>(<abbr class="spell">SVY</abbr>)</i> command to obtain standard error estimates that account for <abbr>SIPP</abbr>'s complex survey design (StataCorp 2009).<sup><a href="#mn8" id="mt8">8</a></sup> Our analysis also applies the appropriate survey person weights. For the probit regression, we report the marginal effects, which can be interpreted as the probability of ineligibility for spouse or widow benefits because of marital history, holding the other variables in the model constant. For ease of presentation, we do not report the estimates for the control variables, which are available upon request.</p>
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<h2>Findings</h2>
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<p>We begin with the descriptive analysis. Table 3 reports the marital history measures for women in 1990 and 2009 by the three age groups: young adult (<span class="nobr">30–39</span>), middle age (<span class="nobr">40–49</span>), and late middle age (<span class="nobr">50–59</span>). Separate estimates for white, black, and Hispanic women are provided.</p>
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<div class="table" id="table3">
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<table>
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<caption><span class="tableNumber">Table 3. </span>Marital status and history measures of women, by age group and race/ethnicity, 1990 and 2009 (in percent)</caption>
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<colgroup span="1" style="width:30em"></colgroup>
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<colgroup span="8" style="width:5em"></colgroup>
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<thead>
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<tr>
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<th rowspan="2" class="stubHeading" id="c1">Marital status and history</th>
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<th colspan="4" class="spanner" id="c2">1990</th>
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<th colspan="4" class="spanner" id="c3">2009</th>
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</tr>
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<tr>
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<th id="c4" headers="c2">All</th>
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<th id="c5" headers="c2">White</th>
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<th id="c6" headers="c2">Black</th>
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<th id="c7" headers="c2">Hispanic</th>
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<th id="c8" headers="c3">All</th>
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<th id="c9" headers="c3">White</th>
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<th id="c10" headers="c3">Black</th>
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<th id="c11" headers="c3">Hispanic</th>
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</tr>
|
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</thead>
|
|
<tbody>
|
|
<tr>
|
|
<td> </td>
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|
<th colspan="8" class="panel" id="r1">Young adult (<span class="nobr">30–39</span>)</th>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" id="r2" headers="r1 c1">Current status</th>
|
|
<td colspan="8"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r3" headers="r1 r2 c1">Married</th>
|
|
<td headers="r1 r2 r3 c2 c4">72.0</td>
|
|
<td headers="r1 r2 r3 c2 c5">74.7</td>
|
|
<td headers="r1 r2 r3 c2 c6">52.4</td>
|
|
<td headers="r1 r2 r3 c2 c7">72.7</td>
|
|
<td headers="r1 r2 r3 c3 c8">67.6</td>
|
|
<td headers="r1 r2 r3 c3 c9">71.0</td>
|
|
<td headers="r1 r2 r3 c3 c10">41.0</td>
|
|
<td headers="r1 r2 r3 c3 c11">71.0</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r4" headers="r1 r2 c1">Never married</th>
|
|
<td headers="r1 r2 r4 c2 c4">15.3</td>
|
|
<td headers="r1 r2 r4 c2 c5">12.9</td>
|
|
<td headers="r1 r2 r4 c2 c6">32.2</td>
|
|
<td headers="r1 r2 r4 c2 c7">16.0</td>
|
|
<td headers="r1 r2 r4 c3 c8">21.8</td>
|
|
<td headers="r1 r2 r4 c3 c9">17.6</td>
|
|
<td headers="r1 r2 r4 c3 c10">47.3</td>
|
|
<td headers="r1 r2 r4 c3 c11">21.0</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r5" headers="r1 r2 c1">Divorced</th>
|
|
<td headers="r1 r2 r5 c2 c4">11.9</td>
|
|
<td headers="r1 r2 r5 c2 c5">11.9</td>
|
|
<td headers="r1 r2 r5 c2 c6">13.9</td>
|
|
<td headers="r1 r2 r5 c2 c7">9.5</td>
|
|
<td headers="r1 r2 r5 c3 c8">10.0</td>
|
|
<td headers="r1 r2 r5 c3 c9">10.8</td>
|
|
<td headers="r1 r2 r5 c3 c10">11.2</td>
|
|
<td headers="r1 r2 r5 c3 c11">7.2</td>
|
|
</tr>
|
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<tr>
|
|
<th class="stub1" id="r6" headers="r1 r2 c1">Widowed</th>
|
|
<td headers="r1 r2 r6 c2 c4">0.9</td>
|
|
<td headers="r1 r2 r6 c2 c5">0.6</td>
|
|
<td headers="r1 r2 r6 c2 c6">1.5</td>
|
|
<td headers="r1 r2 r6 c2 c7">1.8</td>
|
|
<td headers="r1 r2 r6 c3 c8">0.6</td>
|
|
<td headers="r1 r2 r6 c3 c9">0.6</td>
|
|
<td headers="r1 r2 r6 c3 c10">0.5</td>
|
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<td headers="r1 r2 r6 c3 c11">0.9</td>
|
|
</tr>
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|
<tr>
|
|
<th class="stub0" id="r7" headers="r1 c1">Lifetime history—</th>
|
|
<td colspan="8"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r8" headers="r1 r7 c1">Among all women</th>
|
|
<td colspan="8"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub2" id="r9" headers="r1 r7 r8 c1">Ever married</th>
|
|
<td headers="r1 r7 r8 r9 c2 c4">84.7</td>
|
|
<td headers="r1 r7 r8 r9 c2 c5">87.1</td>
|
|
<td headers="r1 r7 r8 r9 c2 c6">67.8</td>
|
|
<td headers="r1 r7 r8 r9 c2 c7">84.0</td>
|
|
<td headers="r1 r7 r8 r9 c3 c8">78.2</td>
|
|
<td headers="r1 r7 r8 r9 c3 c9">82.4</td>
|
|
<td headers="r1 r7 r8 r9 c3 c10">52.7</td>
|
|
<td headers="r1 r7 r8 r9 c3 c11">79.0</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub2" id="r10" headers="r1 r7 r8 c1">Ever divorced</th>
|
|
<td headers="r1 r7 r8 r10 c2 c4">27.3</td>
|
|
<td headers="r1 r7 r8 r10 c2 c5">28.9</td>
|
|
<td headers="r1 r7 r8 r10 c2 c6">24.2</td>
|
|
<td headers="r1 r7 r8 r10 c2 c7">20.8</td>
|
|
<td headers="r1 r7 r8 r10 c3 c8">19.3</td>
|
|
<td headers="r1 r7 r8 r10 c3 c9">22.4</td>
|
|
<td headers="r1 r7 r8 r10 c3 c10">15.5</td>
|
|
<td headers="r1 r7 r8 r10 c3 c11">13.7</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub2" id="r11" headers="r1 r7 r8 c1">Currently divorced with less than 10 years in any marriage</th>
|
|
<td headers="r1 r7 r8 r11 c2 c4">8.6</td>
|
|
<td headers="r1 r7 r8 r11 c2 c5">8.6</td>
|
|
<td headers="r1 r7 r8 r11 c2 c6">10.2</td>
|
|
<td headers="r1 r7 r8 r11 c2 c7">7.1</td>
|
|
<td headers="r1 r7 r8 r11 c3 c8">8.0</td>
|
|
<td headers="r1 r7 r8 r11 c3 c9">8.6</td>
|
|
<td headers="r1 r7 r8 r11 c3 c10">9.4</td>
|
|
<td headers="r1 r7 r8 r11 c3 c11">5.3</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r12" headers="r1 r7 c1">Among ever-married women</th>
|
|
<td colspan="8"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub2" id="r13" headers="r1 r7 r12 c1">Divorced</th>
|
|
<td headers="r1 r7 r12 r13 c2 c4">32.2</td>
|
|
<td headers="r1 r7 r12 r13 c2 c5">33.2</td>
|
|
<td headers="r1 r7 r12 r13 c2 c6">35.7</td>
|
|
<td headers="r1 r7 r12 r13 c2 c7">24.8</td>
|
|
<td headers="r1 r7 r12 r13 c3 c8">24.6</td>
|
|
<td headers="r1 r7 r12 r13 c3 c9">27.2</td>
|
|
<td headers="r1 r7 r12 r13 c3 c10">29.5</td>
|
|
<td headers="r1 r7 r12 r13 c3 c11">17.3</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub2" id="r14" headers="r1 r7 r12 c1">Currently divorced with less than 10 years in any marriage</th>
|
|
<td headers="r1 r7 r12 r14 c2 c4">10.2</td>
|
|
<td headers="r1 r7 r12 r14 c2 c5">9.9</td>
|
|
<td headers="r1 r7 r12 r14 c2 c6">15.0</td>
|
|
<td headers="r1 r7 r12 r14 c2 c7">8.4</td>
|
|
<td headers="r1 r7 r12 r14 c3 c8">10.2</td>
|
|
<td headers="r1 r7 r12 r14 c3 c9">10.4</td>
|
|
<td headers="r1 r7 r12 r14 c3 c10">17.7</td>
|
|
<td headers="r1 r7 r12 r14 c3 c11">6.7</td>
|
|
</tr>
|
|
<tr class="shaded">
|
|
<th class="stub0" id="r15" headers="r1 c1">Unweighted N</th>
|
|
<td headers="r1 r15 c2 c4">4,802</td>
|
|
<td headers="r1 r15 c2 c5">3,487</td>
|
|
<td headers="r1 r15 c2 c6">620</td>
|
|
<td headers="r1 r15 c2 c7">522</td>
|
|
<td headers="r1 r15 c3 c8">6,469</td>
|
|
<td headers="r1 r15 c3 c9">4,051</td>
|
|
<td headers="r1 r15 c3 c10">837</td>
|
|
<td headers="r1 r15 c3 c11">993</td>
|
|
</tr>
|
|
<tr>
|
|
<td> </td>
|
|
<th colspan="8" class="panel" id="r16">Middle age (<span class="nobr">40–49</span>)</th>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" id="r17" headers="r16 c1">Current status</th>
|
|
<td colspan="8"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r18" headers="r16 r17 c1">Married</th>
|
|
<td headers="r16 r17 r18 c2 c4">74.2</td>
|
|
<td headers="r16 r17 r18 c2 c5">76.8</td>
|
|
<td headers="r16 r17 r18 c2 c6">57.2</td>
|
|
<td headers="r16 r17 r18 c2 c7">66.4</td>
|
|
<td headers="r16 r17 r18 c3 c8">68.8</td>
|
|
<td headers="r16 r17 r18 c3 c9">71.2</td>
|
|
<td headers="r16 r17 r18 c3 c10">48.5</td>
|
|
<td headers="r16 r17 r18 c3 c11">71.5</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r19" headers="r16 r17 c1">Never married</th>
|
|
<td headers="r16 r17 r19 c2 c4">6.6</td>
|
|
<td headers="r16 r17 r19 c2 c5">5.1</td>
|
|
<td headers="r16 r17 r19 c2 c6">14.7</td>
|
|
<td headers="r16 r17 r19 c2 c7">11.7</td>
|
|
<td headers="r16 r17 r19 c3 c8">13.0</td>
|
|
<td headers="r16 r17 r19 c3 c9">9.8</td>
|
|
<td headers="r16 r17 r19 c3 c10">31.0</td>
|
|
<td headers="r16 r17 r19 c3 c11">14.1</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r20" headers="r16 r17 c1">Divorced</th>
|
|
<td headers="r16 r17 r20 c2 c4">16.0</td>
|
|
<td headers="r16 r17 r20 c2 c5">15.4</td>
|
|
<td headers="r16 r17 r20 c2 c6">21.3</td>
|
|
<td headers="r16 r17 r20 c2 c7">17.9</td>
|
|
<td headers="r16 r17 r20 c3 c8">16.4</td>
|
|
<td headers="r16 r17 r20 c3 c9">17.5</td>
|
|
<td headers="r16 r17 r20 c3 c10">17.9</td>
|
|
<td headers="r16 r17 r20 c3 c11">12.1</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r21" headers="r16 r17 c1">Widowed</th>
|
|
<td headers="r16 r17 r21 c2 c4">3.3</td>
|
|
<td headers="r16 r17 r21 c2 c5">2.7</td>
|
|
<td headers="r16 r17 r21 c2 c6">6.8</td>
|
|
<td headers="r16 r17 r21 c2 c7">4.0</td>
|
|
<td headers="r16 r17 r21 c3 c8">1.8</td>
|
|
<td headers="r16 r17 r21 c3 c9">1.5</td>
|
|
<td headers="r16 r17 r21 c3 c10">2.6</td>
|
|
<td headers="r16 r17 r21 c3 c11">2.4</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" id="r22" headers="r16 c1">Lifetime history—</th>
|
|
<td colspan="8"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r23" headers="r16 r22 c1">Among all women</th>
|
|
<td colspan="8"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub2" id="r24" headers="r16 r22 r23 c1">Ever married</th>
|
|
<td headers="r16 r22 r23 r24 c2 c4">93.4</td>
|
|
<td headers="r16 r22 r23 r24 c2 c5">94.9</td>
|
|
<td headers="r16 r22 r23 r24 c2 c6">85.3</td>
|
|
<td headers="r16 r22 r23 r24 c2 c7">88.3</td>
|
|
<td headers="r16 r22 r23 r24 c3 c8">87.0</td>
|
|
<td headers="r16 r22 r23 r24 c3 c9">90.2</td>
|
|
<td headers="r16 r22 r23 r24 c3 c10">69.0</td>
|
|
<td headers="r16 r22 r23 r24 c3 c11">85.9</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub2" id="r25" headers="r16 r22 r23 c1">Ever divorced</th>
|
|
<td headers="r16 r22 r23 r25 c2 c4">34.8</td>
|
|
<td headers="r16 r22 r23 r25 c2 c5">35.8</td>
|
|
<td headers="r16 r22 r23 r25 c2 c6">36.0</td>
|
|
<td headers="r16 r22 r23 r25 c2 c7">29.3</td>
|
|
<td headers="r16 r22 r23 r25 c3 c8">31.0</td>
|
|
<td headers="r16 r22 r23 r25 c3 c9">34.8</td>
|
|
<td headers="r16 r22 r23 r25 c3 c10">25.1</td>
|
|
<td headers="r16 r22 r23 r25 c3 c11">20.3</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub2" id="r26" headers="r16 r22 r23 c1">Currently divorced with less than 10 years in any marriage</th>
|
|
<td headers="r16 r22 r23 r26 c2 c4">6.3</td>
|
|
<td headers="r16 r22 r23 r26 c2 c5">5.8</td>
|
|
<td headers="r16 r22 r23 r26 c2 c6">9.6</td>
|
|
<td headers="r16 r22 r23 r26 c2 c7">7.9</td>
|
|
<td headers="r16 r22 r23 r26 c3 c8">9.0</td>
|
|
<td headers="r16 r22 r23 r26 c3 c9">9.8</td>
|
|
<td headers="r16 r22 r23 r26 c3 c10">9.9</td>
|
|
<td headers="r16 r22 r23 r26 c3 c11">6.1</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r27" headers="r16 r22 c1">Among ever-married women</th>
|
|
<td colspan="8"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub2" id="r28" headers="r16 r22 r27 c1">Divorced</th>
|
|
<td headers="r16 r22 r27 r28 c2 c4">37.3</td>
|
|
<td headers="r16 r22 r27 r28 c2 c5">37.7</td>
|
|
<td headers="r16 r22 r27 r28 c2 c6">42.2</td>
|
|
<td headers="r16 r22 r27 r28 c2 c7">33.1</td>
|
|
<td headers="r16 r22 r27 r28 c3 c8">35.6</td>
|
|
<td headers="r16 r22 r27 r28 c3 c9">38.6</td>
|
|
<td headers="r16 r22 r27 r28 c3 c10">36.4</td>
|
|
<td headers="r16 r22 r27 r28 c3 c11">23.7</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub2" id="r29" headers="r16 r22 r27 c1">Currently divorced with less than 10 years in any marriage</th>
|
|
<td headers="r16 r22 r27 r29 c2 c4">6.8</td>
|
|
<td headers="r16 r22 r27 r29 c2 c5">6.1</td>
|
|
<td headers="r16 r22 r27 r29 c2 c6">11.3</td>
|
|
<td headers="r16 r22 r27 r29 c2 c7">8.9</td>
|
|
<td headers="r16 r22 r27 r29 c3 c8">10.3</td>
|
|
<td headers="r16 r22 r27 r29 c3 c9">10.8</td>
|
|
<td headers="r16 r22 r27 r29 c3 c10">14.3</td>
|
|
<td headers="r16 r22 r27 r29 c3 c11">7.1</td>
|
|
</tr>
|
|
<tr class="shaded">
|
|
<th class="stub0" id="r30" headers="r16 c1">Unweighted N</th>
|
|
<td headers="r16 r30 c2 c4">3,832</td>
|
|
<td headers="r16 r30 c2 c5">2,835</td>
|
|
<td headers="r16 r30 c2 c6">471</td>
|
|
<td headers="r16 r30 c2 c7">386</td>
|
|
<td headers="r16 r30 c3 c8">7,304</td>
|
|
<td headers="r16 r30 c3 c9">4,987</td>
|
|
<td headers="r16 r30 c3 c10">911</td>
|
|
<td headers="r16 r30 c3 c11">816</td>
|
|
</tr>
|
|
<tr>
|
|
<td> </td>
|
|
<th colspan="8" class="panel" id="r31">Late middle age (<span class="nobr">50–59</span>)</th>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" id="r32" headers="r31 c1">Current status</th>
|
|
<td colspan="8"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r33" headers="r31 r32 c1">Married</th>
|
|
<td headers="r31 r32 r33 c2 c4">73.6</td>
|
|
<td headers="r31 r32 r33 c2 c5">75.9</td>
|
|
<td headers="r31 r32 r33 c2 c6">58.7</td>
|
|
<td headers="r31 r32 r33 c2 c7">72.3</td>
|
|
<td headers="r31 r32 r33 c3 c8">67.4</td>
|
|
<td headers="r31 r32 r33 c3 c9">70.1</td>
|
|
<td headers="r31 r32 r33 c3 c10">47.2</td>
|
|
<td headers="r31 r32 r33 c3 c11">65.6</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r34" headers="r31 r32 c1">Never married</th>
|
|
<td headers="r31 r32 r34 c2 c4">4.5</td>
|
|
<td headers="r31 r32 r34 c2 c5">3.7</td>
|
|
<td headers="r31 r32 r34 c2 c6">7.8</td>
|
|
<td headers="r31 r32 r34 c2 c7">7.4</td>
|
|
<td headers="r31 r32 r34 c3 c8">9.1</td>
|
|
<td headers="r31 r32 r34 c3 c9">7.2</td>
|
|
<td headers="r31 r32 r34 c3 c10">21.5</td>
|
|
<td headers="r31 r32 r34 c3 c11">11.0</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r35" headers="r31 r32 c1">Divorced</th>
|
|
<td headers="r31 r32 r35 c2 c4">12.1</td>
|
|
<td headers="r31 r32 r35 c2 c5">11.6</td>
|
|
<td headers="r31 r32 r35 c2 c6">17.9</td>
|
|
<td headers="r31 r32 r35 c2 c7">11.7</td>
|
|
<td headers="r31 r32 r35 c3 c8">18.6</td>
|
|
<td headers="r31 r32 r35 c3 c9">18.3</td>
|
|
<td headers="r31 r32 r35 c3 c10">24.8</td>
|
|
<td headers="r31 r32 r35 c3 c11">17.4</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r36" headers="r31 r32 c1">Widowed</th>
|
|
<td headers="r31 r32 r36 c2 c4">9.8</td>
|
|
<td headers="r31 r32 r36 c2 c5">8.8</td>
|
|
<td headers="r31 r32 r36 c2 c6">15.7</td>
|
|
<td headers="r31 r32 r36 c2 c7">2.0</td>
|
|
<td headers="r31 r32 r36 c3 c8">4.9</td>
|
|
<td headers="r31 r32 r36 c3 c9">4.4</td>
|
|
<td headers="r31 r32 r36 c3 c10">6.5</td>
|
|
<td headers="r31 r32 r36 c3 c11">6.6</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" id="r37" headers="r31 c1">Lifetime history—</th>
|
|
<td colspan="8"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r38" headers="r31 r37 c1">Among all women</th>
|
|
<td colspan="8"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub2" id="r39" headers="r31 r37 r38 c1">Ever married</th>
|
|
<td headers="r31 r37 r38 r39 c2 c4">95.5</td>
|
|
<td headers="r31 r37 r38 r39 c2 c5">96.3</td>
|
|
<td headers="r31 r37 r38 r39 c2 c6">92.2</td>
|
|
<td headers="r31 r37 r38 r39 c2 c7">92.6</td>
|
|
<td headers="r31 r37 r38 r39 c3 c8">90.9</td>
|
|
<td headers="r31 r37 r38 r39 c3 c9">92.8</td>
|
|
<td headers="r31 r37 r38 r39 c3 c10">78.5</td>
|
|
<td headers="r31 r37 r38 r39 c3 c11">89.0</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub2" id="r40" headers="r31 r37 r38 c1">Ever divorced</th>
|
|
<td headers="r31 r37 r38 r40 c2 c4">28.7</td>
|
|
<td headers="r31 r37 r38 r40 c2 c5">29.3</td>
|
|
<td headers="r31 r37 r38 r40 c2 c6">30.4</td>
|
|
<td headers="r31 r37 r38 r40 c2 c7">24.5</td>
|
|
<td headers="r31 r37 r38 r40 c3 c8">37.3</td>
|
|
<td headers="r31 r37 r38 r40 c3 c9">39.3</td>
|
|
<td headers="r31 r37 r38 r40 c3 c10">38.2</td>
|
|
<td headers="r31 r37 r38 r40 c3 c11">26.9</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub2" id="r41" headers="r31 r37 r38 c1">Currently divorced with less than 10 years in any marriage</th>
|
|
<td headers="r31 r37 r38 r41 c2 c4">3.0</td>
|
|
<td headers="r31 r37 r38 r41 c2 c5">2.6</td>
|
|
<td headers="r31 r37 r38 r41 c2 c6">5.6</td>
|
|
<td headers="r31 r37 r38 r41 c2 c7">3.5</td>
|
|
<td headers="r31 r37 r38 r41 c3 c8">7.1</td>
|
|
<td headers="r31 r37 r38 r41 c3 c9">6.6</td>
|
|
<td headers="r31 r37 r38 r41 c3 c10">12.4</td>
|
|
<td headers="r31 r37 r38 r41 c3 c11">6.3</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r42" headers="r31 r37 c1">Among ever-married women</th>
|
|
<td colspan="8"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub2" id="r43" headers="r31 r37 r42 c1">Divorced</th>
|
|
<td headers="r31 r37 r42 r43 c2 c4">30.1</td>
|
|
<td headers="r31 r37 r42 r43 c2 c5">30.4</td>
|
|
<td headers="r31 r37 r42 r43 c2 c6">33.0</td>
|
|
<td headers="r31 r37 r42 r43 c2 c7">26.4</td>
|
|
<td headers="r31 r37 r42 r43 c3 c8">41.0</td>
|
|
<td headers="r31 r37 r42 r43 c3 c9">42.4</td>
|
|
<td headers="r31 r37 r42 r43 c3 c10">48.7</td>
|
|
<td headers="r31 r37 r42 r43 c3 c11">30.2</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub2" id="r44" headers="r31 r37 r42 c1">Currently divorced with less than 10 years in any marriage</th>
|
|
<td headers="r31 r37 r42 r44 c2 c4">3.1</td>
|
|
<td headers="r31 r37 r42 r44 c2 c5">2.7</td>
|
|
<td headers="r31 r37 r42 r44 c2 c6">6.1</td>
|
|
<td headers="r31 r37 r42 r44 c2 c7">3.8</td>
|
|
<td headers="r31 r37 r42 r44 c3 c8">7.9</td>
|
|
<td headers="r31 r37 r42 r44 c3 c9">7.1</td>
|
|
<td headers="r31 r37 r42 r44 c3 c10">15.8</td>
|
|
<td headers="r31 r37 r42 r44 c3 c11">7.0</td>
|
|
</tr>
|
|
<tr class="shaded">
|
|
<th class="stub0" id="r45" headers="r31 c1">Unweighted N</th>
|
|
<td headers="r31 r45 c2 c4">2,574</td>
|
|
<td headers="r31 r45 c2 c5">1,963</td>
|
|
<td headers="r31 r45 c2 c6">301</td>
|
|
<td headers="r31 r45 c2 c7">236</td>
|
|
<td headers="r31 r45 c3 c8">7,163</td>
|
|
<td headers="r31 r45 c3 c9">5,193</td>
|
|
<td headers="r31 r45 c3 c10">918</td>
|
|
<td headers="r31 r45 c3 c11">549</td>
|
|
</tr>
|
|
</tbody>
|
|
<tfoot>
|
|
<tr>
|
|
<td class="firstNote" colspan="9">SOURCE: Authors' calculations using 1990 and 2008 <abbr>SIPP</abbr> (Wave 2) data. </td>
|
|
</tr>
|
|
<tr>
|
|
<td class="lastNote" colspan="9">NOTE: Data are weighted.</td>
|
|
</tr>
|
|
</tfoot>
|
|
</table>
|
|
</div>
|
|
<p>Looking first at the late middle-aged group (<span class="nobr">50–59</span>), the data show a trend away from marriage. Compared with 1990, late middle-aged women in 2009 were more likely to be never married, ever divorced, currently divorced, and currently divorced without a <span class="nobr">10-year</span> marriage. The growth in the never-married subgroup was substantial over the period, more than doubling from 4.5 percent to 9.1 percent. The increase was particularly sharp for black women (from 7.8 percent to 21.5 percent, compared with from 3.7 percent to 7.2 percent for white women and 7.4 percent to 11.0 percent for Hispanic women). The data show significant increases in the proportion of women who were currently divorced without a <span class="nobr">10-year</span> marriage, from 3.1 percent to 7.9 percent (among the ever married). By race and ethnicity, black women aged <span class="nobr">50–59</span> had particularly sharp increases in the share who were divorced without a <span class="nobr">10-year</span> marriage (from 6.1 percent to 15.8 percent of ever-married black women, compared with from 2.7 percent to 7.1 percent for their white counterparts and from 3.8 percent to 7.0 percent for their Hispanic counterparts).</p>
|
|
<p>Among middle-aged women (<span class="nobr">40–49</span>), substantial marital changes also occurred. Compared with 1990, middle-aged women in 2009 were more likely to be never married or currently divorced without a <span class="nobr">10-year</span> marriage. The percentage ever divorced remained roughly constant between 1990 and 2009, very likely reflecting the leveling of divorce rates since the 1970s.</p>
|
|
<p>The data reveal sharp differences among middle-aged women by race and ethnicity. Between 1990 and 2009, the percentage of ever-married black women decreased 16.3 percentage points (to 69.0 percent) compared with white women who experienced a decline of 4.7 percentage points (to 90.2 percent). The comparable figure for Hispanic women reflected a 2.4 percentage point decline (to 85.9 percent). In terms of divorce, a higher proportion of ever-married, black middle-aged women were currently divorced without a <span class="nobr">10-year</span> marriage than white women, but this gap narrowed between 1990 and 2009. For Hispanics, the percentage of currently divorced women without a <span class="nobr">10-year</span> marriage slightly declined. Thus, racial differences in ever-married women aged <span class="nobr">40–49</span> seem to have expanded between 1990 and 2009, but those differences contracted in terms of the share currently divorced without a <span class="nobr">10-year</span> marriage.</p>
|
|
<p>The most substantial changes appear in the young-adult group (aged <span class="nobr">30–39</span>). A "retreat from marriage" was evident among all groups, but it was greatest for black women. Specifically, the percentage of never-married black women rose from 32.2 percent in 1990 to 47.3 percent in 2009, while the percentage currently married dropped from 52.4 percent to 41 percent. The proportion of ever-married black women currently divorced without a <span class="nobr">10-year</span> marriage also increased, from 15 percent in 1990 to 17.7 percent in 2009. Of course, women in their thirties are far from completing their lifetime marital histories, but the trend appears in the direction of less marriage and with increasing black/white disparities among more recent birth cohorts.</p>
|
|
<p>Chart 2 presents a summary measure showing the share of women in each age cohort and race/ethnic subgroup who lacked marital histories required for Social Security spouse or widow benefits. As previously noted, <i>ineligible</i> reflects the sum of never-married women and currently divorced women without a <span class="nobr">10-year</span> marriage. Overall, the results show that well over half of all women in each age group had qualifying marital histories in 1990 and 2009, but at the same time, a larger proportion in each age-specific group would be ineligible for Social Security marriage-based benefits in 2009 relative to 1990.</p>
|
|
<div class="chartCenter">
|
|
<div class="chart700" id="chart2">
|
|
<div class="title">Chart 2.<br>Percentage of women ineligible for Social Security spouse or widow benefits because of marital history, by age group and race/ethnicity, 1990 and 2009</div>
|
|
<div class="scrollChart"><img src="v72n2p23-chart02.gif" alt="Bar chart with tabular version below." width="700" height="377" /></div>
|
|
<div class="table altTable"><a class="altToggle" href="">Show as table</a>
|
|
<table>
|
|
<caption><span class="tableNumber">Table equivalent for Chart 2. </span>Percentage of women ineligible for Social Security spouse or widow benefits because of marital history, by age group and race/ethnicity, 1990 and 2009</caption>
|
|
<colgroup span="1" style="width:8em"></colgroup>
|
|
<colgroup span="2" style="width:8em"></colgroup>
|
|
<colgroup span="2" style="width:8em"></colgroup>
|
|
<colgroup span="2" style="width:8em"></colgroup>
|
|
<thead>
|
|
<tr>
|
|
<th rowspan="2" class="stubHeading" scope="colgroup">Race/ethnicity</th>
|
|
<th colspan="2" class="spanner" scope="colgroup">Young adult (<span class="nobr">30–39</span>)</th>
|
|
<th colspan="2" class="spanner" scope="colgroup">Middle age (<span class="nobr">40–49</span>)</th>
|
|
<th colspan="2" class="spanner" scope="colgroup">Late middle age (<span class="nobr">50–59</span>)</th>
|
|
</tr>
|
|
<tr>
|
|
<th scope="col">1990</th>
|
|
<th scope="col">2008</th>
|
|
<th scope="col">1990</th>
|
|
<th scope="col">2008</th>
|
|
<th scope="col">1990</th>
|
|
<th scope="col">2008</th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<th class="stub0" scope="row">All</th>
|
|
<td>24.0</td>
|
|
<td>29.8</td>
|
|
<td>12.9</td>
|
|
<td>22.0</td>
|
|
<td>7.5</td>
|
|
<td>16.2</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">White</th>
|
|
<td>21.5</td>
|
|
<td>26.0</td>
|
|
<td>10.9</td>
|
|
<td>19.6</td>
|
|
<td>6.3</td>
|
|
<td>13.8</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">Black</th>
|
|
<td>42.4</td>
|
|
<td>56.7</td>
|
|
<td>24.3</td>
|
|
<td>40.9</td>
|
|
<td>13.4</td>
|
|
<td>33.9</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">Hispanic</th>
|
|
<td>23.1</td>
|
|
<td>26.3</td>
|
|
<td>19.5</td>
|
|
<td>20.2</td>
|
|
<td>10.9</td>
|
|
<td>17.3</td>
|
|
</tr>
|
|
</tbody>
|
|
<tfoot>
|
|
<tr>
|
|
<td class="noNotes" colspan="7"> </td>
|
|
</tr>
|
|
</tfoot>
|
|
</table>
|
|
</div>
|
|
<div class="firstNote">SOURCE: Authors' calculations using 1990 and 2008 <abbr>SIPP</abbr> (Wave 2) data. </div>
|
|
<div class="lastNote">NOTE: Data are weighted.</div>
|
|
</div>
|
|
</div>
|
|
<p>Chart 2 also reveals important differences by race and ethnicity. Black women comprised the highest share ineligible for marriage-based benefits in all age groups. Moreover, black/white differences appear to have widened between 1990 and 2009. The percentage point difference between the share of black and white women who lacked potential eligibility in the middle-aged group was greater in 2009 (that is, the gap was about 21 percentage points in 2009, corresponding to 40.9 percent (black) and 19.6 percent (white); those figures are compared with about 13 percentage points in 1990, corresponding to 24.3 percent (black) and 10.9 percent (white)). Among the young-adult group, black/white differences in ineligibility grew because of the faster rate of increase in never-married black women.</p>
|
|
<p>Hispanic women's incidence of ineligibility because of marital history is more similar to white than black women (see Chart 2). However, thus far, we have discussed Hispanic women without distinguishing between those who were <abbr class="spell">US</abbr> born and foreign born, two subgroups thought to have differing marital behavior. To assess possible differences by nativity, Chart 3 shows the proportion of <abbr class="spell">US</abbr>- and foreign-born Hispanic women without a qualifying marital history for spouse or widow benefits. The results confirm clear differences in marriage-based eligibility by nativity, with <span class="nobr"><abbr class="spell">US</abbr>-born</span> Hispanic women having higher proportions of ineligible marital histories than those born outside the United States. For example, the percentage of ineligible foreign-born Hispanic women in late middle age (<span class="nobr">50–59</span>) in 2009 was 15 percent compared with 21 percent of those who were <abbr class="spell">US</abbr> born. Among the middle-aged group (<span class="nobr">40–49</span>), 28 percent of <span class="nobr"><abbr class="spell">US</abbr>-born</span> Hispanic women did not have a qualifying marital history compared with 13 percent of those who were foreign born. Among the young-adult group (aged <span class="nobr">30–39</span>), 31 percent of <span class="nobr"><abbr class="spell">US</abbr>-born</span> Hispanic women in 2009 had ineligible marital histories compared with 22 percent of those who were foreign born. These observed differences are driven by differences in marital patterns, which are shown in detail in the Appendix, <a href="#tableA2">Table A-2</a>. Briefly, we find higher rates of ever marrying among foreign-born Hispanic women compared with their <span class="nobr"><abbr class="spell">US</abbr>-born</span> counterparts, particularly in the young-adult group. In terms of marital dissolution, the likelihood of being divorced is substantially lower among foreign-born Hispanic women in the young-adult and middle-aged groups.</p>
|
|
<div class="chartCenter">
|
|
<div class="chart700" id="chart3">
|
|
<div class="title">Chart 3.<br>Percentage of <abbr class="spell">US</abbr>-born and foreign-born Hispanic women ineligible for Social Security spouse or widow benefits because of marital history, by age group, 1990 and 2009</div>
|
|
<div class="scrollChart"><img src="v72n2p23-chart03.gif" alt="Bar chart with tabular version below." width="700" height="375" /></div>
|
|
<div class="table altTable"><a class="altToggle" href="">Show as table</a>
|
|
<table>
|
|
<caption><span class="tableNumber">Table equivalent for Chart 3. </span>Percentage of <abbr class="spell">US</abbr>-born and foreign-born Hispanic women ineligible for Social Security spouse or widow benefits because of marital history, by age group, 1990 and 2009</caption>
|
|
<colgroup span="1" style="width:10em"></colgroup>
|
|
<colgroup span="2" style="width:8em"></colgroup>
|
|
<colgroup span="2" style="width:8em"></colgroup>
|
|
<colgroup span="2" style="width:8em"></colgroup>
|
|
<thead>
|
|
<tr>
|
|
<th rowspan="2" class="stubHeading" scope="colgroup">Birthplace</th>
|
|
<th colspan="2" class="spanner" scope="colgroup">Young adult (<span class="nobr">30–39</span>)</th>
|
|
<th colspan="2" class="spanner" scope="colgroup">Middle age (<span class="nobr">40–49</span>)</th>
|
|
<th colspan="2" class="spanner" scope="colgroup">Late middle age (<span class="nobr">50–59</span>)</th>
|
|
</tr>
|
|
<tr>
|
|
<th scope="col">1990</th>
|
|
<th scope="col">2008</th>
|
|
<th scope="col">1990</th>
|
|
<th scope="col">2008</th>
|
|
<th scope="col">1990</th>
|
|
<th scope="col">2008</th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<th class="stub0" scope="row"><abbr class="spell">US</abbr> born</th>
|
|
<td>29.3</td>
|
|
<td>31.3</td>
|
|
<td>23.2</td>
|
|
<td>28.3</td>
|
|
<td>7.2</td>
|
|
<td>20.6</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">Foreign born</th>
|
|
<td>17.3</td>
|
|
<td>21.6</td>
|
|
<td>16.5</td>
|
|
<td>12.8</td>
|
|
<td>15.3</td>
|
|
<td>14.1</td>
|
|
</tr>
|
|
</tbody>
|
|
<tfoot>
|
|
<tr>
|
|
<td class="noNotes" colspan="7"> </td>
|
|
</tr>
|
|
</tfoot>
|
|
</table>
|
|
</div>
|
|
<div class="firstNote">SOURCE: Authors' calculations using 1990 and 2008 <abbr>SIPP</abbr> (Wave 2) data. </div>
|
|
<div class="lastNote">NOTE: Data are weighted.</div>
|
|
</div>
|
|
</div>
|
|
<p>In sum, the descriptive data indicate substantial changes in the marital patterns of recent cohorts of women and in the distribution of women potentially eligible for Social Security spouse or widow benefits. There is significant differentiation by race, ethnicity, and nativity. The next section examines those trends in a multivariate context.</p>
|
|
<h3>Probit Regression Results</h3>
|
|
<p>Using probit regression, we estimated the probability of being ineligible for Social Security marriage-based benefits in the three age groups in 1990 and 2009. Our main focus was to determine whether women's likelihood of being ineligible for spouse or widow benefits based on marital history changed over time and how that pattern varied by race, ethnicity, and nativity among Hispanics, controlling for the variables in the model. Table 4 shows the results of separate regressions for 1990 and 2009 for the three age groups: young adult (<span class="nobr">30–39</span>), middle age (<span class="nobr">40–49</span>), and late middle age (<span class="nobr">50–59</span>). We report the marginal effects, their significance level (two-tailed tests), and the standard errors, which account for <abbr>SIPP</abbr>'s complex survey design.</p>
|
|
<div class="table" id="table4">
|
|
<table>
|
|
<caption><span class="tableNumber">Table 4. </span>Marginal effect estimates (probit) of the probability of women not being potentially eligible for Social Security spouse or widow benefits, by age group and race and ethnicity/nativity, 1990 and 2009 </caption>
|
|
<colgroup span="1" style="width:15em"></colgroup>
|
|
<colgroup span="4" style="width:8em"></colgroup>
|
|
<thead>
|
|
<tr>
|
|
<th rowspan="2" class="stubHeading" id="c1">Race and ethnic origin</th>
|
|
<th colspan="2" class="spanner" id="c2">1990</th>
|
|
<th colspan="2" class="spanner" id="c3">2009</th>
|
|
</tr>
|
|
<tr>
|
|
<th id="c4" headers="c2">Marginal effect</th>
|
|
<th id="c5" headers="c2">Standard error</th>
|
|
<th id="c6" headers="c3">Marginal effect</th>
|
|
<th id="c7" headers="c3">Standard error</th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<td> </td>
|
|
<th colspan="4" class="panel" id="r1">Model 1: Young adult (<span class="nobr">30–39</span>)</th>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" id="r2" headers="r1 c1">White (reference group)</th>
|
|
<td colspan="4"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" id="r3" headers="r1 c1">Black</th>
|
|
<td headers="r1 r3 c2 c4">0.217***</td>
|
|
<td headers="r1 r3 c2 c5">0.023</td>
|
|
<td headers="r1 r3 c3 c6">0.293***</td>
|
|
<td headers="r1 r3 c3 c7">0.022</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" id="r4" headers="r1 c1">Hispanic</th>
|
|
<td colspan="4"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r5" headers="r1 r4 c1"><abbr class="spell">US</abbr> born </th>
|
|
<td headers="r1 r4 r5 c2 c4">0.085* </td>
|
|
<td headers="r1 r4 r5 c2 c5">0.034</td>
|
|
<td headers="r1 r4 r5 c3 c6">0.033 </td>
|
|
<td headers="r1 r4 r5 c3 c7">0.023</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r6" headers="r1 r4 c1">Foreign born </th>
|
|
<td headers="r1 r4 r6 c2 c4">-0.046 </td>
|
|
<td headers="r1 r4 r6 c2 c5">0.029</td>
|
|
<td headers="r1 r4 r6 c3 c6">-0.077** </td>
|
|
<td headers="r1 r4 r6 c3 c7">0.024</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" id="r7" headers="r1 c1">Other</th>
|
|
<td headers="r1 r7 c2 c4">-0.031 </td>
|
|
<td headers="r1 r7 c2 c5">0.028</td>
|
|
<td headers="r1 r7 c3 c6">-0.048* </td>
|
|
<td headers="r1 r7 c3 c7">0.023</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" id="r8" headers="r1 c1">Observed probability</th>
|
|
<td headers="r1 r8 c2 c4">0.240 </td>
|
|
<td headers="r1 r8 c2 c5">. . .</td>
|
|
<td headers="r1 r8 c3 c6">0.298 </td>
|
|
<td headers="r1 r8 c3 c7">. . .</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" id="r9" headers="r1 c1">Predicted probability (at x-bar)</th>
|
|
<td headers="r1 r9 c2 c4">0.233 </td>
|
|
<td headers="r1 r9 c2 c5">. . .</td>
|
|
<td headers="r1 r9 c3 c6">0.290 </td>
|
|
<td headers="r1 r9 c3 c7">. . .</td>
|
|
</tr>
|
|
<tr class="shaded">
|
|
<th class="stub0" id="r10" headers="r1 c1">N of observations</th>
|
|
<td colspan="2">4,802</td>
|
|
<td colspan="2">6,469</td>
|
|
</tr>
|
|
<tr>
|
|
<td> </td>
|
|
<th colspan="4" class="panel" id="r11">Model 2: Middle age (<span class="nobr">40–49</span>)</th>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" id="r12" headers="r11 c1">White (reference group)</th>
|
|
<td colspan="4"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" id="r13" headers="r11 c1">Black</th>
|
|
<td headers="r11 r13 c2 c4">0.145***</td>
|
|
<td headers="r11 r13 c2 c5">0.030</td>
|
|
<td headers="r11 r13 c3 c6">0.206***</td>
|
|
<td headers="r11 r13 c3 c7">0.017</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" id="r14" headers="r11 c1">Hispanic</th>
|
|
<td colspan="4"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r15" headers="r11 r14 c1"><abbr class="spell">US</abbr> born </th>
|
|
<td headers="r11 r14 r15 c2 c4">0.139***</td>
|
|
<td headers="r11 r14 r15 c2 c5">0.032</td>
|
|
<td headers="r11 r14 r15 c3 c6">0.083** </td>
|
|
<td headers="r11 r14 r15 c3 c7">0.027</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r16" headers="r11 r14 c1">Foreign born </th>
|
|
<td headers="r11 r14 r16 c2 c4">0.071* </td>
|
|
<td headers="r11 r14 r16 c2 c5">0.028</td>
|
|
<td headers="r11 r14 r16 c3 c6">-0.082** </td>
|
|
<td headers="r11 r14 r16 c3 c7">0.025</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" id="r17" headers="r11 c1">Other</th>
|
|
<td headers="r11 r17 c2 c4">-0.022 </td>
|
|
<td headers="r11 r17 c2 c5">0.033</td>
|
|
<td headers="r11 r17 c3 c6">-0.050** </td>
|
|
<td headers="r11 r17 c3 c7">0.016</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" id="r18" headers="r11 c1">Observed probability</th>
|
|
<td headers="r11 r18 c2 c4">0.129 </td>
|
|
<td headers="r11 r18 c2 c5">. . .</td>
|
|
<td headers="r11 r18 c3 c6">0.220 </td>
|
|
<td headers="r11 r18 c3 c7">. . .</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" id="r19" headers="r11 c1">Predicted probability (at x-bar)</th>
|
|
<td headers="r11 r19 c2 c4">0.122 </td>
|
|
<td headers="r11 r19 c2 c5">. . .</td>
|
|
<td headers="r11 r19 c3 c6">0.214 </td>
|
|
<td headers="r11 r19 c3 c7">. . .</td>
|
|
</tr>
|
|
<tr class="shaded">
|
|
<th class="stub0" id="r20" headers="r11 c1">N of observations</th>
|
|
<td colspan="2">3,832</td>
|
|
<td colspan="2">7,304</td>
|
|
</tr>
|
|
<tr>
|
|
<td> </td>
|
|
<th colspan="4" class="panel" id="r21">Model 3: Late middle age (<span class="nobr">50–59</span>)</th>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" id="r22" headers="r21 c1">White (reference group)</th>
|
|
<td colspan="4"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" id="r23" headers="r21 c1">Black</th>
|
|
<td headers="r21 r23 c2 c4">0.075** </td>
|
|
<td headers="r21 r23 c2 c5">0.025</td>
|
|
<td headers="r21 r23 c3 c6">0.204***</td>
|
|
<td headers="r21 r23 c3 c7">0.018</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" id="r24" headers="r21 c1">Hispanic</th>
|
|
<td colspan="4"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r25" headers="r21 r24 c1"><abbr class="spell">US</abbr> born </th>
|
|
<td headers="r21 r24 r25 c2 c4">0.009 </td>
|
|
<td headers="r21 r24 r25 c2 c5">0.029</td>
|
|
<td headers="r21 r24 r25 c3 c6">0.073* </td>
|
|
<td headers="r21 r24 r25 c3 c7">0.032</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r26" headers="r21 r24 c1">Foreign born </th>
|
|
<td headers="r21 r24 r26 c2 c4">0.100* </td>
|
|
<td headers="r21 r24 r26 c2 c5">0.045</td>
|
|
<td headers="r21 r24 r26 c3 c6">-0.001 </td>
|
|
<td headers="r21 r24 r26 c3 c7">0.027</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" id="r27" headers="r21 c1">Other</th>
|
|
<td headers="r21 r27 c2 c4">0.037 </td>
|
|
<td headers="r21 r27 c2 c5">0.033</td>
|
|
<td headers="r21 r27 c3 c6">-0.041* </td>
|
|
<td headers="r21 r27 c3 c7">0.017</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" id="r28" headers="r21 c1">Observed probability</th>
|
|
<td headers="r21 r28 c2 c4">0.075 </td>
|
|
<td headers="r21 r28 c2 c5">. . .</td>
|
|
<td headers="r21 r28 c3 c6">0.163 </td>
|
|
<td headers="r21 r28 c3 c7">. . .</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" id="r29" headers="r21 c1">Predicted probability (at x-bar)</th>
|
|
<td headers="r21 r29 c2 c4">0.070 </td>
|
|
<td headers="r21 r29 c2 c5">. . .</td>
|
|
<td headers="r21 r29 c3 c6">0.156 </td>
|
|
<td headers="r21 r29 c3 c7">. . .</td>
|
|
</tr>
|
|
<tr class="shaded">
|
|
<th class="stub0" id="r30" headers="r21 c1">N of observations</th>
|
|
<td colspan="2">2,574</td>
|
|
<td colspan="2">7,163</td>
|
|
</tr>
|
|
</tbody>
|
|
<tfoot>
|
|
<tr>
|
|
<td class="firstNote" colspan="5">SOURCE: Authors' calculations using 1990 and 2008 <abbr>SIPP</abbr> (Wave 2) data. </td>
|
|
</tr>
|
|
<tr>
|
|
<td class="lastNote" colspan="5">NOTES: Estimates are from separate-year regressions. Reported estimates are weighted and correct for <abbr>SIPP</abbr>'s complex survey design. The models also control for educational attainment and age (estimates are available upon request). The marginal effect indicates the discrete change in the probability of not being potentially eligible by the change in the dummy variable from 0 to 1.
|
|
<div class="newNote">. . . = not applicable.</div>
|
|
<div class="newNote">* p < .05; ** p < .01; *** p < .001.</div>
|
|
</td>
|
|
</tr>
|
|
</tfoot>
|
|
</table>
|
|
</div>
|
|
<p>Overall, the models indicate that women in 2009, across all three age groups, had a substantially higher predicted probability of not meeting the marital requirements for spouse or widow benefits than the comparable model in 1990, holding race and the other variables constant. These results capture cohort differences in marriage patterns at the same stage of life, namely relative rises in never-married and currently divorced women without <span class="nobr">10-year</span> marriages.</p>
|
|
<p>In terms of race, being black was strongly and positively associated with higher probabilities of being ineligible for marriage-based benefits (p < .001) across all age groups in 1990 and 2009. The marginal effect of being black was higher in 2009 compared with 1990, across all age groups. In other words, black women in 2009, relative to comparable white women, had higher probabilities of being ineligible for marriage-based benefits than their age-specific counterparts in 1990, all else being equal. At ages <span class="nobr">30–39</span>, for example, the marginal effect of being black on the probability of not having a qualifying marital history, relative to being white, was 29 percent in 2009 compared with 22 percent in 1990. That pattern reflects the faster increase in never-married black women in the young-adult cohort from 1990 to 2009.</p>
|
|
<p>Among Hispanic women, we find sharp differences between those born in the United States and those who were not. <span class="nobr"><abbr class="spell">US</abbr>-born</span> Hispanic women in the young-adult (survey year 1990), middle-aged (survey years 1990 and 2009), and late middle-aged (survey year 2009) models were significantly more likely to have a nonqualifying marital history than their white counterparts. By contrast, the results for foreign-born Hispanic women were more mixed, with some models (for example, models 1 and 2 in 2009) showing significantly lower probabilities of those women having a nonqualifying marital history. Overall, then, Hispanic women, namely those who were born in the United States, have ineligible probabilities resulting from marital history that appear to lie between those of white and black women. Thus, <span class="nobr"><abbr class="spell">US</abbr>-born</span> Hispanic women were more likely to be ineligible because of marital history than white women in the middle- and late middle-aged groups in 2009, but the magnitude was less than black/white differentials at the same stage of life. Interestingly, the probability of ineligibility because of marital history appeared to decrease among foreign-born Hispanic women in the middle- and late middle-aged groups in 2009, shown by the changing sign in the marginal effect between 1990 and 2009. This outcome likely picks up, in part, different patterns of immigration waves over time (see <a href="#mn6">note 6</a>).</p>
|
|
<h2>Conclusions</h2>
|
|
<p>The majority of aged women currently receive a Social Security benefit at least partly based on the earnings record of a present or past spouse. The distribution of women's potential eligibility for Social Security spouse or widow benefits is, however, dynamic and subject to changes in marital trends. In this study, we used data from the Census Bureau's <abbr>SIPP</abbr> Marital History Modules in 1990 and 2009 to shed light on the implications of trends in women's lifetime marital experiences for Social Security spouse and widow benefit eligibility. Overall, we find that most women are approaching retirement age with marital histories that make them potentially eligible for spouse or widow benefits in the future. However, fundamental changes in marital patterns, starting with the leading edge of the baby boom cohort, will prompt a decline in the share of women potentially eligible to receive these benefits.</p>
|
|
<p>Our findings reveal considerable changes in the marital patterns of women aged <span class="nobr">30–59</span> between 1990 and 2009. Those changes have been marked by increasing proportions of women who were never married, ever divorced, and currently divorced with shorter marriages (less than 10 years). Such patterns very likely reflect a mix of period and birth cohort effects as the sample moves from the large baby boom generation (born in the <span class="nobr">1946–1964</span> period) through <abbr title="Gen X">GenX</abbr> (born in the <span class="nobr">1968–1979</span> period). The results also indicate important differences by race, ethnicity, and nativity among Hispanic women. We find a sharper <i>retreat from marriage</i> for black women among more recent birth cohorts (Goldstein and Kenney 2001; Harrington Meyer, Wolf, and Himes 2006; Tamborini, Iams, and Whitman 2009). Consistent with the literature, the marital histories of Hispanic women lie somewhere between their white and black counterparts. We also find distinct marital patterns among <abbr class="spell">US</abbr>- and foreign-born Hispanic women.</p>
|
|
<p>The observed changes in women's marital histories are associated with an increase in the share without a qualifying marriage for Social Security spouse and widow benefits. Thus, the increase in women's ineligibility for Social Security spouse or widow benefits found in past research (Harrington Meyer, Wolf, and Himes 2006; Tamborini, Iams, and Whitman 2009) continues among recent cohorts of women, including those in <abbr title="Gen X">GenX</abbr>. In short, <abbr title="Gen X">GenX</abbr> women, although just in their thirties, appear to be continuing the <i>retreat from marriage</i>. Although the direction of marital patterns among those women could change as they age, the postboomer cohort appears to be following the trend of increasing proportions of women with nonqualifying marital histories for spouse or widow benefits, at least in an earlier stage of the adult life course.</p>
|
|
<p>The results also document sharp differences in benefit ineligibility by race and ethnicity. Across all of the age groups, black women had substantially higher proportions without a qualifying marital history for Social Security spouse or widow benefits than comparable white women. Moreover, we find that the widening black/white differentials in potential ineligibility shown in previous studies (Tamborini, Iams, and Whitman 2009) continue in the young-adult (aged <span class="nobr">30–39</span>) cohorts. A key driver of this trend is the increase in never-married black women.</p>
|
|
<p>Among Hispanic women, a central finding is that eligibility for Social Security spouse and widow benefits based on marital history varies by nativity. The probability of not having a qualifying marriage was greater among <span class="nobr"><abbr class="spell">US</abbr>-born</span> Hispanic women than their foreign-born counterparts, particularly among the younger cohorts. However, differences between <span class="nobr"><abbr class="spell">US</abbr>-born</span> Hispanic women and comparable white women were not as wide as black/white differences. Hispanic women may assimilate over time to the increasing <i>retreat from marriage</i>, as suggested by Oropesa and Landale (2004), which may result in widening differences in the marital experiences between white and Hispanic women in future years. Complicating interpretation, Hispanic immigrants come from many countries with different cultures, and country of origin shifted across the time period examined in this study. Our sample size is not large enough to identify country of origin reliably for immigrants and parents of <span class="nobr"><abbr class="spell">US</abbr>-born</span> Hispanics. We also did not consider differences among Hispanics in terms of their immigration history (that is, first generation US born versus second or greater generations).</p>
|
|
<p>Put together, the changing distribution of women potentially eligible for spouse or widow benefits can have important consequences for their retirement resources and for the Social Security program as a whole. Recent microsimulation projections based on the Modeling Income in the Near Term (<abbr>MINT</abbr>) data system have shown that women in the baby boom and <abbr title="Gen X">GenX</abbr> cohorts will be more likely to receive retired-worker benefits when their spouse is alive, but most will continue to take up widow benefits (dually entitled) if they outlive their husband because of lower lifetime earnings (Butrica and Smith 2012a). However, as this study suggests, a smaller share of future female retirees will have the option of augmenting their retirement benefit based on the work record of a deceased spouse because of shifts in marital patterns. That trend will be particularly pronounced among future black female retirees.<sup><a href="#mn9" id="mt9">9</a></sup> There is some reason for concern that those women may be at higher risk of economic vulnerability in old age. Microsimulation projections of the retirement-age population in 2030, for example, have suggested disproportionately high rates of poverty and <span class="nobr">near-poor</span> status among divorced female retirees with less than 10 years of marriage (Tamborini and Whitman 2010) as well as the never married (Tamborini 2007).</p>
|
|
<p>Future empirical work could clarify the consequences of changing eligibility for Social Security spouse or widow benefits for women's retirement income security. For example, the extent to which declining eligibility is concentrated in minority or less-educated subgroups may influence the effect of those changes on economic outcomes. Additionally, a further <i>retreat from marriage</i> among <abbr title="Gen X">GenX</abbr> cohorts, if sustained over the life course, may have important consequences for women's retirement resources in future years. The relationship between marriage and retirement outcomes among Hispanic women may be a salient topic given the lack of research in this area.</p>
|
|
<h2>Appendix</h2>
|
|
<div class="table" id="tableA1">
|
|
<table>
|
|
<caption><span class="tableNumber">Table A-1. </span>Descriptive statistics for study sample: Women aged <span class="nobr">30–59</span> in 1990 and 2009 (in percent)</caption>
|
|
<colgroup span="1" style="width:18em"></colgroup>
|
|
<colgroup span="2" style="width:8em"></colgroup>
|
|
<thead>
|
|
<tr>
|
|
<th class="stubHeading" id="c1">Characteristic</th>
|
|
<th id="c2">1990</th>
|
|
<th id="c3">2009</th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr class="shaded">
|
|
<th class="stub0" id="r1" headers="c1">Age (mean years)</th>
|
|
<td headers="r1 c2">42.3</td>
|
|
<td headers="r1 c3">44.6</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" id="r2" headers="c1">Educational attainment</th>
|
|
<td colspan="2"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r3" headers="r2 c1">Less than high school graduate</th>
|
|
<td headers="r2 r3 c2">16.6</td>
|
|
<td headers="r2 r3 c3">8.5</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r4" headers="r2 c1">High school graduate</th>
|
|
<td headers="r2 r4 c2">37.0</td>
|
|
<td headers="r2 r4 c3">23.9</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r5" headers="r2 c1">Some college</th>
|
|
<td headers="r2 r5 c2">23.9</td>
|
|
<td headers="r2 r5 c3">24.8</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r6" headers="r2 c1">Bachelor's degree</th>
|
|
<td headers="r2 r6 c2">21.5</td>
|
|
<td headers="r2 r6 c3">31.8</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" id="r7" headers="c1">Race/ethnicity</th>
|
|
<td colspan="2"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r8" headers="r7 c1">White</th>
|
|
<td headers="r7 r8 c2">78.4</td>
|
|
<td headers="r7 r8 c3">66.8</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r9" headers="r7 c1">Black</th>
|
|
<td headers="r7 r9 c2">10.8</td>
|
|
<td headers="r7 r9 c3">12.4</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r10" headers="r7 c1">Hispanic</th>
|
|
<td colspan="2"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub2" id="r11" headers="r7 r10 c1"><abbr class="spell">US</abbr> born</th>
|
|
<td headers="r7 r10 r11 c2">3.7</td>
|
|
<td headers="r7 r10 r11 c3">6.6</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub2" id="r12" headers="r7 r10 c1">Foreign born</th>
|
|
<td headers="r7 r10 r12 c2">3.9</td>
|
|
<td headers="r7 r10 r12 c3">7.1</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r13" headers="r7 c1">Other</th>
|
|
<td headers="r7 r13 c2">3.3</td>
|
|
<td headers="r7 r13 c3">7.1</td>
|
|
</tr>
|
|
<tr class="shaded">
|
|
<th class="stub0" id="r14" headers="c1">Unweighted N</th>
|
|
<td headers="r14 c2">11,208</td>
|
|
<td headers="r14 c3">20,936</td>
|
|
</tr>
|
|
</tbody>
|
|
<tfoot>
|
|
<tr>
|
|
<td class="firstNote" colspan="3">SOURCE: Authors' calculations using 1990 and 2008 <abbr>SIPP</abbr> (Wave 2) data. </td>
|
|
</tr>
|
|
<tr>
|
|
<td class="lastNote" colspan="3">NOTE: Data are weighted. </td>
|
|
</tr>
|
|
</tfoot>
|
|
</table>
|
|
</div>
|
|
<div class="table" id="tableA2">
|
|
<table>
|
|
<caption><span class="tableNumber">Table A-2. </span>Marital status and history measures of Hispanic women, by nativity (<abbr class="spell">US</abbr> born and foreign born) and age group, 1990 and 2009 (in percent)</caption>
|
|
<colgroup span="1" style="width:20em"></colgroup>
|
|
<colgroup span="4" style="width:6em"></colgroup>
|
|
<thead>
|
|
<tr>
|
|
<th rowspan="2" class="stubHeading" id="c1">Marital status and history</th>
|
|
<th colspan="2" class="spanner" id="c2">1990</th>
|
|
<th colspan="2" class="spanner" id="c3">2009</th>
|
|
</tr>
|
|
<tr>
|
|
<th id="c4" headers="c2"><abbr class="spell">US</abbr> born</th>
|
|
<th id="c5" headers="c2">Foreign born</th>
|
|
<th id="c6" headers="c3"><abbr class="spell">US</abbr> born</th>
|
|
<th id="c7" headers="c3">Foreign born</th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<td> </td>
|
|
<th colspan="4" class="panel" id="r1">Young adult (<span class="nobr">30–39</span>)</th>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" id="r2" headers="r1 c1">Current status</th>
|
|
<td colspan="4"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r3" headers="r1 r2 c1">Married</th>
|
|
<td headers="r1 r2 r3 c2 c4">66.6</td>
|
|
<td headers="r1 r2 r3 c2 c5">78.3</td>
|
|
<td headers="r1 r2 r3 c3 c6">65.0</td>
|
|
<td headers="r1 r2 r3 c3 c7">76.5</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r4" headers="r1 r2 c1">Never married</th>
|
|
<td headers="r1 r2 r4 c2 c4">20.7</td>
|
|
<td headers="r1 r2 r4 c2 c5">11.7</td>
|
|
<td headers="r1 r2 r4 c3 c6">24.1</td>
|
|
<td headers="r1 r2 r4 c3 c7">18.1</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r5" headers="r1 r2 c1">Divorced</th>
|
|
<td headers="r1 r2 r5 c2 c4">11.9</td>
|
|
<td headers="r1 r2 r5 c2 c5">7.3</td>
|
|
<td headers="r1 r2 r5 c3 c6">9.8</td>
|
|
<td headers="r1 r2 r5 c3 c7">4.7</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r6" headers="r1 r2 c1">Widowed</th>
|
|
<td headers="r1 r2 r6 c2 c4">0.8</td>
|
|
<td headers="r1 r2 r6 c2 c5">2.7</td>
|
|
<td headers="r1 r2 r6 c3 c6">1.1</td>
|
|
<td headers="r1 r2 r6 c3 c7">0.7</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" id="r7" headers="r1 c1">Lifetime history—</th>
|
|
<td colspan="4"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r8" headers="r1 r7 c1">Among all women</th>
|
|
<td colspan="4"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub2" id="r9" headers="r1 r7 r8 c1">Ever married</th>
|
|
<td headers="r1 r7 r8 r9 c2 c4">79.3</td>
|
|
<td headers="r1 r7 r8 r9 c2 c5">88.3</td>
|
|
<td headers="r1 r7 r8 r9 c3 c6">75.9</td>
|
|
<td headers="r1 r7 r8 r9 c3 c7">81.9</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub2" id="r10" headers="r1 r7 r8 c1">Ever divorced</th>
|
|
<td headers="r1 r7 r8 r10 c2 c4">28.6</td>
|
|
<td headers="r1 r7 r8 r10 c2 c5">13.6</td>
|
|
<td headers="r1 r7 r8 r10 c3 c6">18.4</td>
|
|
<td headers="r1 r7 r8 r10 c3 c7">9.4</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub2" id="r11" headers="r1 r7 r8 c1">Currently divorced with less than 10 years in any marriage</th>
|
|
<td headers="r1 r7 r8 r11 c2 c4">8.6</td>
|
|
<td headers="r1 r7 r8 r11 c2 c5">5.6</td>
|
|
<td headers="r1 r7 r8 r11 c3 c6">7.2</td>
|
|
<td headers="r1 r7 r8 r11 c3 c7">3.5</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r12" headers="r1 r7 c1">Among ever-married women</th>
|
|
<td colspan="4"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub2" id="r13" headers="r1 r7 r12 c1">Divorced</th>
|
|
<td headers="r1 r7 r12 r13 c2 c4">36.0</td>
|
|
<td headers="r1 r7 r12 r13 c2 c5">15.4</td>
|
|
<td headers="r1 r7 r12 r13 c3 c6">24.2</td>
|
|
<td headers="r1 r7 r12 r13 c3 c7">11.4</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub2" id="r14" headers="r1 r7 r12 c1">Currently divorced with less than 10 years in any marriage</th>
|
|
<td headers="r1 r7 r12 r14 c2 c4">10.9</td>
|
|
<td headers="r1 r7 r12 r14 c2 c5">6.3</td>
|
|
<td headers="r1 r7 r12 r14 c3 c6">9.5</td>
|
|
<td headers="r1 r7 r12 r14 c3 c7">4.3</td>
|
|
</tr>
|
|
<tr class="shaded">
|
|
<th class="stub0" id="r15" headers="r1 c1">Unweighted N</th>
|
|
<td headers="r1 r15 c2 c4">246</td>
|
|
<td headers="r1 r15 c2 c5">276</td>
|
|
<td headers="r1 r15 c3 c6">470</td>
|
|
<td headers="r1 r15 c3 c7">523</td>
|
|
</tr>
|
|
<tr>
|
|
<td> </td>
|
|
<th colspan="4" class="panel" id="r16">Middle age (<span class="nobr">40–49</span>)</th>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" id="r17" headers="r16 c1">Current status</th>
|
|
<td colspan="4"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r18" headers="r16 r17 c1">Married</th>
|
|
<td headers="r16 r17 r18 c2 c4">58.7</td>
|
|
<td headers="r16 r17 r18 c2 c5">72.8</td>
|
|
<td headers="r16 r17 r18 c3 c6">62.5</td>
|
|
<td headers="r16 r17 r18 c3 c7">79.7</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r19" headers="r16 r17 c1">Never married</th>
|
|
<td headers="r16 r17 r19 c2 c4">12.0</td>
|
|
<td headers="r16 r17 r19 c2 c5">11.4</td>
|
|
<td headers="r16 r17 r19 c3 c6">19.8</td>
|
|
<td headers="r16 r17 r19 c3 c7">8.9</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r20" headers="r16 r17 c1">Divorced</th>
|
|
<td headers="r16 r17 r20 c2 c4">24.6</td>
|
|
<td headers="r16 r17 r20 c2 c5">12.4</td>
|
|
<td headers="r16 r17 r20 c3 c6">15.9</td>
|
|
<td headers="r16 r17 r20 c3 c7">8.5</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r21" headers="r16 r17 c1">Widowed</th>
|
|
<td headers="r16 r17 r21 c2 c4">4.7</td>
|
|
<td headers="r16 r17 r21 c2 c5">3.4</td>
|
|
<td headers="r16 r17 r21 c3 c6">1.9</td>
|
|
<td headers="r16 r17 r21 c3 c7">2.9</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" id="r22" headers="r16 c1">Lifetime history—</th>
|
|
<td colspan="4"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r23" headers="r16 r22 c1">Among all women</th>
|
|
<td colspan="4"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub2" id="r24" headers="r16 r22 r23 c1">Ever married</th>
|
|
<td headers="r16 r22 r23 r24 c2 c4">88.0</td>
|
|
<td headers="r16 r22 r23 r24 c2 c5">88.6</td>
|
|
<td headers="r16 r22 r23 r24 c3 c6">80.2</td>
|
|
<td headers="r16 r22 r23 r24 c3 c7">91.1</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub2" id="r25" headers="r16 r22 r23 c1">Ever divorced</th>
|
|
<td headers="r16 r22 r23 r25 c2 c4">36.0</td>
|
|
<td headers="r16 r22 r23 r25 c2 c5">23.7</td>
|
|
<td headers="r16 r22 r23 r25 c3 c6">24.7</td>
|
|
<td headers="r16 r22 r23 r25 c3 c7">16.3</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub2" id="r26" headers="r16 r22 r23 c1">Currently divorced with less than 10 years in any marriage</th>
|
|
<td headers="r16 r22 r23 r26 c2 c4">11.2</td>
|
|
<td headers="r16 r22 r23 r26 c2 c5">5.1</td>
|
|
<td headers="r16 r22 r23 r26 c3 c6">8.5</td>
|
|
<td headers="r16 r22 r23 r26 c3 c7">3.9</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r27" headers="r16 r22 c1">Among ever-married women</th>
|
|
<td colspan="4"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub2" id="r28" headers="r16 r22 r27 c1">Divorced</th>
|
|
<td headers="r16 r22 r27 r28 c2 c4">40.9</td>
|
|
<td headers="r16 r22 r27 r28 c2 c5">26.7</td>
|
|
<td headers="r16 r22 r27 r28 c3 c6">30.8</td>
|
|
<td headers="r16 r22 r27 r28 c3 c7">17.9</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub2" id="r29" headers="r16 r22 r27 c1">Currently divorced with less than 10 years in any marriage</th>
|
|
<td headers="r16 r22 r27 r29 c2 c4">12.7</td>
|
|
<td headers="r16 r22 r27 r29 c2 c5">5.8</td>
|
|
<td headers="r16 r22 r27 r29 c3 c6">10.6</td>
|
|
<td headers="r16 r22 r27 r29 c3 c7">4.3</td>
|
|
</tr>
|
|
<tr class="shaded">
|
|
<th class="stub0" id="r30" headers="r16 c1">Unweighted N</th>
|
|
<td headers="r16 r30 c2 c4">174</td>
|
|
<td headers="r16 r30 c2 c5">212</td>
|
|
<td headers="r16 r30 c3 c6">381</td>
|
|
<td headers="r16 r30 c3 c7">435</td>
|
|
</tr>
|
|
<tr>
|
|
<td> </td>
|
|
<th colspan="4" class="panel" id="r31">Late middle age (<span class="nobr">50–59</span>)</th>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" id="r32" headers="r31 c1">Current status</th>
|
|
<td colspan="4"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r33" headers="r31 r32 c1">Married</th>
|
|
<td headers="r31 r32 r33 c2 c4">76.6</td>
|
|
<td headers="r31 r32 r33 c2 c5">67.3</td>
|
|
<td headers="r31 r32 r33 c3 c6">60.9</td>
|
|
<td headers="r31 r32 r33 c3 c7">69.9</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r34" headers="r31 r32 c1">Never married</th>
|
|
<td headers="r31 r32 r34 c2 c4">5.5</td>
|
|
<td headers="r31 r32 r34 c2 c5">9.6</td>
|
|
<td headers="r31 r32 r34 c3 c6">13.3</td>
|
|
<td headers="r31 r32 r34 c3 c7">8.8</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r35" headers="r31 r32 c1">Divorced</th>
|
|
<td headers="r31 r32 r35 c2 c4">10.6</td>
|
|
<td headers="r31 r32 r35 c2 c5">13.1</td>
|
|
<td headers="r31 r32 r35 c3 c6">19.7</td>
|
|
<td headers="r31 r32 r35 c3 c7">15.2</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r36" headers="r31 r32 c1">Widowed</th>
|
|
<td headers="r31 r32 r36 c2 c4">7.3</td>
|
|
<td headers="r31 r32 r36 c2 c5">10.0</td>
|
|
<td headers="r31 r32 r36 c3 c6">6.1</td>
|
|
<td headers="r31 r32 r36 c3 c7">6.1</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" id="r37" headers="r31 c1">Lifetime history—</th>
|
|
<td colspan="4"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r38" headers="r31 r37 c1">Among all women</th>
|
|
<td colspan="4"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub2" id="r39" headers="r31 r37 r38 c1">Ever married</th>
|
|
<td headers="r31 r37 r38 r39 c2 c4">94.5</td>
|
|
<td headers="r31 r37 r38 r39 c2 c5">90.4</td>
|
|
<td headers="r31 r37 r38 r39 c3 c6">86.7</td>
|
|
<td headers="r31 r37 r38 r39 c3 c7">91.2</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub2" id="r40" headers="r31 r37 r38 c1">Ever divorced</th>
|
|
<td headers="r31 r37 r38 r40 c2 c4">22.2</td>
|
|
<td headers="r31 r37 r38 r40 c2 c5">27.1</td>
|
|
<td headers="r31 r37 r38 r40 c3 c6">32.2</td>
|
|
<td headers="r31 r37 r38 r40 c3 c7">21.9</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub2" id="r41" headers="r31 r37 r38 c1">Currently divorced with less than 10 years in any marriage</th>
|
|
<td headers="r31 r37 r38 r41 c2 c4">1.6</td>
|
|
<td headers="r31 r37 r38 r41 c2 c5">5.7</td>
|
|
<td headers="r31 r37 r38 r41 c3 c6">7.4</td>
|
|
<td headers="r31 r37 r38 r41 c3 c7">5.3</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r42" headers="r31 r37 c1">Among ever-married women</th>
|
|
<td colspan="4"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub2" id="r43" headers="r31 r37 r42 c1">Divorced</th>
|
|
<td headers="r31 r37 r42 r43 c2 c4">23.5</td>
|
|
<td headers="r31 r37 r42 r43 c2 c5">30.0</td>
|
|
<td headers="r31 r37 r42 r43 c3 c6">37.1</td>
|
|
<td headers="r31 r37 r42 r43 c3 c7">24.1</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub2" id="r44" headers="r31 r37 r42 c1">Currently divorced with less than 10 years in any marriage</th>
|
|
<td headers="r31 r37 r42 r44 c2 c4">1.7</td>
|
|
<td headers="r31 r37 r42 r44 c2 c5">6.4</td>
|
|
<td headers="r31 r37 r42 r44 c3 c6">8.5</td>
|
|
<td headers="r31 r37 r42 r44 c3 c7">5.8</td>
|
|
</tr>
|
|
<tr class="shaded">
|
|
<th class="stub0" id="r45" headers="r31 c1">Unweighted N</th>
|
|
<td headers="r31 r45 c2 c4">119</td>
|
|
<td headers="r31 r45 c2 c5">117</td>
|
|
<td headers="r31 r45 c3 c6">257</td>
|
|
<td headers="r31 r45 c3 c7">292</td>
|
|
</tr>
|
|
</tbody>
|
|
<tfoot>
|
|
<tr>
|
|
<td class="firstNote" colspan="5">SOURCE: Authors' calculations using 1990 and 2008 <abbr>SIPP</abbr> (Wave 2) data. </td>
|
|
</tr>
|
|
<tr>
|
|
<td class="lastNote" colspan="5">NOTE: Data are weighted.</td>
|
|
</tr>
|
|
</tfoot>
|
|
</table>
|
|
</div>
|
|
<div id="notes">
|
|
<h2>Notes</h2>
|
|
<p> <a href="#mt1" id="mn1">1</a> <abbr title="Gen X">GenX</abbr> generally denotes persons born between 1968 and 1979.</p>
|
|
<p> <a href="#mt2" id="mn2">2</a> The length of marriage required among divorced spouses was reduced from 20 years to 10 years in 1977 (Tamborini and Whitman 2007).</p>
|
|
<p> <a href="#mt3" id="mn3">3</a> <abbr class="spell">PIA</abbr> is the monthly benefit a person would receive if he or she retires at the applicable full retirement age. For retirement benefits, <abbr class="spell">PIA</abbr> is a function of <i>average indexed monthly earnings</i> (<abbr>AIME</abbr>), which is a computation based on the highest 35 years of covered earnings (<abbr class="spell">SSA</abbr> 2011a, <span class="nobr">4–16</span>).</p>
|
|
<p> <a href="#mt4" id="mn4">4</a> A <span class="nobr">widow(er)</span> benefit may be limited if the deceased spouse claimed early retirement benefits. The benefit is increased if the deceased spouse earned delayed retirement credits by waiting to collect his or her retirement benefit until after the applicable full retirement age.</p>
|
|
<p> <a href="#mt5" id="mn5">5</a> Qualifying <span class="nobr">widow(er)s</span> must have been married to the deceased spouse for at least 9 months and have not remarried before age 60 (50 for disabled persons); see <abbr class="spell">SSA</abbr> (2011b).</p>
|
|
<p> <a href="#mt6" id="mn6">6</a> The Hispanic population is heterogeneous, and the composition of that population has changed greatly from 1990 through 2009 with recent waves of immigration. Part of this heterogeneity relates to differences between <abbr class="spell">US</abbr>- and foreign-born Hispanics. There is also diversity in socioeconomic outcomes by national origin (Martin 2007; Oropesa and Landale 2004).</p>
|
|
<p> <a href="#mt7" id="mn7">7</a> Thanks to an agreement with the Census Bureau, <abbr class="spell">SSA</abbr> has access to <abbr>SIPP</abbr>'s restricted-use Marital History Module for the 2008 panel, which contains respondents' marital event dates in months.</p>
|
|
<p> <a href="#mt8" id="mn8">8</a> <abbr>SIPP</abbr>'s sampling methodology follows a complex survey design, which uses stratification and clustering. We adjusted for this design in our data analysis because most statistical software packages assume a simple random sample for variance estimation as the default. Recent versions of Stata provide a series of commands that correct standard error estimates for complex survey design features. Using the <abbr class="spell">SVY</abbr> command in Stata, we identify the stratification, sampling weights, and sampling units (clustering) for the <abbr>SIPP</abbr> panels.</p>
|
|
<p> <a href="#mt9" id="mn9">9</a> Recent projections using <abbr>MINT</abbr> show rising ineligibility of divorced women for benefits as spouses and widows, particularly black divorced women (Butrica and Smith 2012b).</p>
|
|
</div>
|
|
<div id="references">
|
|
<h2>References</h2>
|
|
<p>Berkowitz, Edward D. 2002. "Family Benefits in Social Security: A Historical Commentary." In <i>Social Security and the Family: Addressing Unmet Needs in an Underfunded System,</i> edited by Melissa M. Favreault, Frank J. Sammartino, and C. Eugene Steuerle, <span class="nobr">19–46</span>. Washington, <abbr class="spell">DC</abbr>: Urban Institute Press.</p>
|
|
<p>Blau, Francine D., and Lawrence M. Kahn. 2006. "The <abbr>U.S.</abbr> Gender Pay Gap in the 1990s: Slowing Convergence." <i>Industrial & Labor Relations Review</i> 60(1): <span class="nobr">45–66</span>.</p>
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|
<p>Bureau of Labor Statistics. 2010. "Women's-to-Men's Earnings Ratio by Age, 2009." <i>The Editor's Desk</i> (July 08). <a href="https://www.bls.gov/opub/ted/2010/ted_20100708.htm">http://www.bls.gov/opub/ted/2010/ted_20100708.htm</a>.</p>
|
|
<p>Butrica, Barbara A., Howard M. Iams, and Steven H. Sandell. 1999. "<a href="/policy/docs/ssb/v62n3/v62n3p20.pdf">Using Data for Couples to Project the Distributional Effects of Changes in Social Security Policy</a>." <i>Social Security Bulletin</i> 62(3): <span class="nobr">20–27</span>.</p>
|
|
<p>Butrica, Barbara A., and Karen E. Smith. 2012a. "<a href="/policy/docs/ssb/v72n1/v72n1p1.html">The Impact of Changes in Couples' Earnings on Married Women's Social Security Benefits</a>." <i>Social Security Bulletin </i>72(1): <span class="nobr">1–9</span>.</p>
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|
<p>———. 2012b. "<a href="/policy/docs/ssb/v72n1/v72n1p23.html">Racial and Ethnic Differences in the Retirement Prospects of Divorced Women</a>." <i>Social Security Bulletin</i> 72(1): <span class="nobr">23–36</span>.</p>
|
|
<p>Cherlin, Andrew J. 2009. <i>The Marriage-Go-Round: The State of Marriage and the Family in America Today.</i> New York: Knopf.</p>
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<p>Couch, Kenneth A., Christopher R. Tamborini, Gayle L. Reznik, and John W. R. Phillips. 2011. "Impact of Divorce on Women's Earnings and Retirement Over the Life Course." Paper presented at the Conference on Unexpected Lifecycle Events and Economic Well-Being: The Roles of Job Loss, Disability, and Changing Family Structure. Federal Reserve Bank of San Francisco, <abbr title="California">CA</abbr> (May 20).</p>
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<p>Ekerdt, D. J. 2010. "Frontiers of Research on Work and Retirement." <i>Journal of Gerontology: Social Sciences</i> 65B(1): <span class="nobr">69–80</span>.</p>
|
|
<p>Favreault, Melissa M., and C. Eugene Steuerle. 2007. "Social Security Spouse and Survivor Benefits for the Modern Family." The Retirement Project, Discussion Paper 07-01. Washington, <abbr class="spell">DC</abbr>: Urban Institute Press.</p>
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<p>Goldstein, Joshua R., and Catherine T. Kenney. 2001. "Marriage Delayed or Marriage Forgone? New Cohort Forecasts of First Marriage for <abbr>U.S.</abbr> Women." <i>American Sociological</i> Review 66(4): <span class="nobr">506–519</span>.</p>
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<p>Government Accountability Office. 2007. <i>Retirement Security: Women Face Challenges in Ensuring Financial Security in Retirement.</i> Report to Ranking Member, Special Committee on Aging, <abbr class="spell">US</abbr> Senate, <abbr class="spell">GAO</abbr>-08-105, Washington, <abbr class="spell">DC</abbr>.</p>
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|
<p>Harrington Meyer, Madonna, Douglas A. Wolf, and Christine L. Himes. 2006. "Declining Eligibility for Social Security Spouse and Widow Benefits in the United States?" <i>Research on Aging</i> 28(2): <span class="nobr">240–260</span>.</p>
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<p>Holden, Karen C., and Angela Fontes. 2009. "Employment and Economic Security in Retirement: How Changes in Employment Have Altered Retirement-Related Economic Risks for Women." <i>Journal of Women, Politics & Policy</i> 30(<span class="nobr">2–3</span>): <span class="nobr">173–197</span>.</p>
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|
<p>Kingson, Eric R., and Regina O'Grady-LeShane. 1993. "The Effects of Caregiving on Women's Social Security Benefits." <i>The Gerontologist </i>33(2): <span class="nobr">230–239</span>.</p>
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|
<p>Kreider, Rose M., and Renee Ellis. 2011. <i>Number, Timing, and Duration of Marriages and Divorces: 2009</i>. Current Population Reports, P70-125. Washington, <abbr class="spell">DC</abbr>: Census Bureau.</p>
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<p>Lusardi, Annamaria., and Olivia S. Mitchell. 2008. "Planning and Financial Literacy: How Do Women Fare?" <i>American Economic Review</i> 98(2): <span class="nobr">413–417</span>.</p>
|
|
<p>Martin, Patricia P. 2007. "<a href="/policy/docs/ssb/v67n2/v67n2p73.html">Hispanics, Social Security, and Supplemental Security Income</a>." <i>Social Security Bulletin </i>67(2): <span class="nobr">73–100</span>.</p>
|
|
<p>Martin, Patricia P., and David A. Weaver. 2005. "<a href="/policy/docs/ssb/v66n1/v66n1p1.html">Social Security: A Program and Policy History</a>." <i>Social Security Bulletin</i> 66(1): <span class="nobr">1–15</span>.</p>
|
|
<p>McNamee, Catherine B., and R. Kelly Raley. 2011. "A Note on Race, Ethnicity and Nativity Differentials in Remarriage in the United States." <i>Demographic Research </i>24(13): <span class="nobr">293–312</span>.</p>
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<p>Oropesa, R. S., and Nancy S. Landale. 2004. "The Future of Marriage and Hispanics." <i>Journal of Marriage and Family</i> 66(4): <span class="nobr">901–920</span>.</p>
|
|
<p>[<abbr class="spell">SSA</abbr>] Social Security Administration. 2010. <i>Income of the Population 55 or Older, 2008.</i> Washington, <abbr class="spell">DC</abbr>: Office of Retirement and Disability Policy, Office of Research, Evaluation, and Statistics. <a href="/policy/docs/statcomps/income_pop55/2008/index.html">http://www.socialsecurity.gov/policy/docs/statcomps/income_pop55/2008/index.html</a>.</p>
|
|
<p>———. 2011a. <i><a href="/policy/docs/statcomps/supplement/2010/index.html">Annual Statistical Supplement to the Social Security Bulletin, 2010</a>.</i> Washington, <abbr class="spell">DC</abbr>: Office of Retirement and Disability Policy, Office of Research, Evaluation, and Statistics.</p>
|
|
<p>———. 2011b. <i>Online Social Security Handbook</i>. <a href="/OP_Home/handbook/handbook.html">http://www.socialsecurity.gov/OP_Home/handbook/handbook.html</a>.</p>
|
|
<p>StataCorp. 2009. <i><abbr>STATA</abbr>/<abbr class="spell">MP</abbr> 101 for Windows.</i> College Station, <abbr title="Texas">TX</abbr>: Stata Corp <abbr class="spell">LP</abbr>.</p>
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|
<p>Stevenson, Betsey, and Justin Wolfers. 2007. "Marriage and Divorce: Changes and Their Driving Forces." <i>Journal of Economic Perspectives </i>21(2): <span class="nobr">27–52</span>.</p>
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<p>Sweeney, Megan M., and Julie A. Phillips. 2004. "Understanding Racial Differences in Marital Disruption: Recent Trends and Explanations." <i>Journal of Marriage and Family</i> 66(3): <span class="nobr">639–650</span>.</p>
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<p>Tamborini, Christopher R. 2007. "<a href="/policy/docs/ssb/v67n2/v67n2p25.html">The Never-Married in Old Age: Projections and Concerns for the Near Future</a>." <i>Social Security Bulletin</i> 67(2): <span class="nobr">25–40</span>.</p>
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<p>Tamborini, Christopher R., and Howard M. Iams. 2011. "Are Generation X'ers Different Than Late Boomers? Family and Earnings Trends Among Recent Cohorts of Women at Young Adulthood." <i>Population Research and Policy Review</i> 30(1): <span class="nobr">59–79</span>.</p>
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<p>Tamborini, Christopher R., Howard M. Iams, and Kevin Whitman. 2009. "Marital Histories, Race, and Social Security Spouse and Widow Benefit Eligibility in the United States." <i>Research on Aging</i> 31(5): <span class="nobr">577–605</span>.</p>
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<p>Tamborini, Christopher R. and Kevin Whitman. 2007. "<a href="/policy/docs/ssb/v67n4/v67n4p1.html">Women, Marriage, and Social Security Benefits: Revisited</a>." <i>Social Security Bulletin</i> 67(4): <span class="nobr">1–20</span>.</p>
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<p>———. 2010. "Lowering Social Security's Duration-of-Marriage Requirement: Distributional Effects for Future Female Retirees." <i>Journal of Women & Aging</i> 22(3): <span class="nobr">184–203</span>.</p>
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<p>Weaver, David A. 1997. "<a href="/policy/docs/ssb/v60n4/v60n4p3.pdf">The Economic Well-Being of Social Security Beneficiaries, With an Emphasis on Divorced Beneficiaries</a>." <i>Social Security Bulletin</i> 60(4): <span class="nobr">3–17</span>.</p>
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<p>———. 2010. "<a href="/policy/docs/ssb/v70n3/v70n3p89.html">Widows and Social Security</a>." <i>Social Security Bulletin</i> 70(3): <span class="nobr">89–109</span>.</p>
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<p>Weinberg, Daniel H. 2007. "Earnings by Gender: Evidence from Census 2000." <i>Monthly Labor Review </i>130(7): <span class="nobr">26–34</span>.</p>
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<p>Wilmoth, Janet, and Gregor Koso. 2002. "Does Marital History Matter? Marital Status and Wealth Outcomes Among Preretirement Adults." <i>Journal of Marriage and Family</i> 64(1): <span class="nobr">254–268</span>.</p>
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<p>Zissimopoulos, Julie, Benjamin Karney, and Amy Rauer. 2008. "Marital Histories and Economic Well-Being." Working Paper <abbr title="Number">No.</abbr> <abbr class="spell">WP</abbr> 2008-180. Ann Arbor, <abbr title="Michigan">MI</abbr>: University of Michigan Retirement Research Center.</p>
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