Melissa S. Kearney is an Associate Professor of Economics at the University of Maryland and a Research Associate at the National Bureau of Economic Research. Phillip B. Levine is the A. Barton Hepburn and
Catherine Koman Professor of Economics at Wellesley College and a Research Associate at the National Bureau of Economic Research. The authors thank Liz Ananat and Serkan Ozbeklik for comments on an
earlier version. They also acknowledge helpful comments from seminar participants at the Harris School at the University of Chicago, the Harvard Labor Workshop, Middlebury College, the Maryland Population
Research Center, University of British Columbia, Wharton, University of Wisconsin IRP, Northwestern IPR, and participants at the conferences, “Public Policy and the Economics of Fertility” at Mount Holyoke
and “Labor Markets, Children, and Families” at the University of Stavanger. They thank Erin Moody and Lisa Dettling for very capable research assistance. They are grateful to Christopher Rogers at the National
Center for Health Statistics for facilitating access to confi dential data. These data are available from the National Center for Health Statistics. The authors can guide other scholars wishing to acquire the data.
For assistance, please contact Phillip B. Levine, Wellesley College, 106 Central Street, Wellesley, MA 02481, plevinewellesley .edu.
[Submitted January 2012; accepted December 2012] ISSN 0022- 166X E- ISSN 1548- 8004 © 2014 by the Board of Regents of the University of Wisconsin System
T H E J O U R N A L O F H U M A N R E S O U R C E S • 49 • 1
Income Inequality and Early Nonmarital Childbearing
Melissa S. Kearney Phillip B. Levine
A B S T R A C T
Using individual- level data from the United States, we empirically investigate the role of lower- tail income inequality in determining rates
of early nonmarital childbearing among low socioeconomic status SES women. We present robust evidence that young low- SES women are more
likely to have a nonmarital birth when they live in places with larger lower- tail income inequality, all else held constant. We calculate that differences in
the level of inequality are able to explain a sizeable share of the geographic variation in teen fertility rates. We propose a model of adolescent decision-
making that facilitates the interpretation of our results.
I. Introduction
Rates of early nonmarital childbearing vary tremendously across coun- tries and across states. The United States is consistently at the high end of this distribu-
tion, with a rate of teen childbearing that greatly exceeds that of other developed coun- tries. Within the United States, the experience is far from uniform. Some states have
teen childbearing rates that are roughly comparable to those found in Europe, but others have rates that are over three times that level. Figure 1 shows that the teen birth rate of
41.5 per 1,000 females age 15–19 in the United States is a multiple of the level that ex- ists in other developed countries. For example, the rate is 25.9 in the United Kingdom,
14.1 in Canada, and 4.3 in Switzerland. Figure 2 shows that tremendous variation exists across states as well. Some states have rates that are comparable to those in other devel-
oped countries, but others have extremely high rates. For example, the rates in Texas, New Mexico, and Mississippi over 60 per 1,000 are more than three times the rates in
New Hampshire, Massachusetts, and Vermont.
1
Why is it that teenagers in the United States are so much more likely than their counterparts in other countries to give birth
when young and unmarried? Why are teens in some parts of the United States so much more likely to have a teen birth than their counterparts in other parts of the country?
We consider these geographic patterns to pose both a challenge and a potential clue to understanding the determinants of early nonmarital childbearing. Year- to- year and
even decade- to- decade, the states that have relatively high rates of teen childbear- ing remain the high teen childbearing states, and the states that have relatively low
rates of teen childbearing remain the low teen childbearing states. The teen population weighted correlation between the 1980 and 2010 teen childbearing rate—averaged
across states—is 0.74.
1. This cross- state variation in teen birth rates does not simply refl ect cross- state variation in overall birth rates. The highest birth rates to women age 15–44 are found in Alaska, Idaho, and Utah, which rank 35, 28,
and 19, respectively, in terms of teen birth rates Martin et al. 2010. In addition, this cross- section variation is substantially larger than recent time- series variation, which has garnered so much attention. Between 1991
and 2008, the national teen birth rate fell from a peak of 62 to 42.
Figure 1 International Comparison of Teen Birth Rates, 2008
Source: United Nations Economic Commission for Europe 2011 and United Nations 2008.
These patterns suggest that longstanding differences across states are critical. What are the persistent conditions of states that drive the decisions of young women in this
regard? One potential culprit among many is income inequality, which tends to be fairly persistent within a place and shows a strong correlation with rates of early nonmarital
childbearing. Figures 3 and 4 display the sizable, positive correlation between income inequality and teen childbearing across developed countries and across states.
2
This cor- relation is noteworthy, but it does not necessarily imply a causal positive relationship.
Various theories exist for why income inequality, as distinct from absolute income, might affect individual- level behavior.
3
Social scientists, particularly political scien- tists and sociologists, have emphasized the role of relative, as distinct from absolute
deprivation—in leading to acts of social unrest. In an economics paper on the issue, Luttmer 2005 documents that people are less happy when they live around people
who are richer than themselves. Watson and McLanahan 2011 present evidence that relative income matters for the marriage decision of low- income men.
4
They inter- pret their model within the idea of an identity construct, whereby low- income men
2. Similar fi gures appear in Wilkinson and Pickett 2009. 3. Mayer 2001 provides a thoughtful review of these and other explanations in her paper on income in-
equality and educational attainment. 4. Loughran 2002 and Gould and Passerman 2003 consider the effect of male wage inequality on the mar-
riage decisions of women within a search model framework whereby women search for husbands based on male wages. Both papers use data from the 1970, 1980, and 1990 U.S. Census samples. Loughran 2002 tests
whether changes in male wage inequality within geographically, racially, and educationally defi ned marriage
Figure 2 Variation in Teen Birth Rates Across States, 2008
Source: Martin, et al. 2010
Figure 3 Income Inequality and Teen Birth Rates Across Countries
Sources: Gini Coeffi cient—United Nations 2009. Teen Birth Rate—United Nations 2008
Figure 4 Income Inequality and Teen Birth Rates Across States
Source: Gini Coeffi cient—Webster 2007. Teen Birth Rate—Martin, et al. 2010
postpone marriage with the goal of waiting until they achieve a higher economic sta- tus, and that status is determined by a peer reference group. Another possible mech-
anism through which income inequality affects outcomes is through the effects of segregation.
5
To the extent that greater levels of income inequality are associated with increased levels of residential and institutional segregation, individuals at the bottom
of the income distribution might feel a heightened sense of social marginalization, which links to the theories of Wilson 1987 and relates to the model we propose.
We propose an additional mechanism that is contextually specifi c through which income inequality might affect teen childbearing rates. A girl who views herself as
having little to lose by having a baby when young and unmarried is more likely to make that choice, rather than choosing to delay. If feelings of economic hopelessness
among the poor are heightened by greater disparities in income, leading economically disadvantaged young women to view the opportunity costs of early childbearing as
suffi ciently low, then this could generate a causal link between income inequality and rates of early nonmarital childbearing. This idea draws heavily on the existing ethno-
graphic and sociological literature on the topic, including the work of Clark 1965, Lewis 1969, Wilson 1987, and Edin and Kefalas 2005, among others. These ideas
motivate our empirical analysis.
To empirically investigate whether the observed aggregate relationship between income inequality and teen childbearing holds at the individual level, we conduct an
empirical examination of individual level data from the National Survey of Family Growth NSFG.
6
A key to our empirical strategy is to determine whether any effect of inequality is concentrated among those most likely to be adversely affected by it,
namely those at the bottom of the income distribution. Individual level data also al- lows us to control for individual- level demographics and other state characteristics.
We focus on lower- tail income inequality, defi ned as the ratio of household income at the 50
th
percentile to the 10
th
percentile of the distribution. We choose this measure of inequality to be our baseline measure because the economic and cultural disparities
resulting from this gap are more relevant to the lives of the poor, than say, the gap between those at the 90
th
percentile and the median. We fi nd that women who grow up in low socioeconomic circumstances have more
teen, nonmarital births when they live in higher inequality locations, all else equal. The proximate mechanism driving this is less frequent use of abortion, meaning that
low- SES girls in more unequal places are more likely to “keep the baby” when they become pregnant. Our analysis controls for individual demographic characteristics and
a broad array of state- level public policies including welfare and abortion policies.
markets affect the propensity to marry among females. The estimates suggest that for white women and for highly educated black women, rising within- group male wage inequality had a sizable negative impact on
the female propensity to marry between 1970 and 1990. Gould and Passerman 2003 conduct a similar study examining how intercity variation in male inequality affects the marital decisions of white women. They also
fi nd a strong positive relationship between male wage inequality and the probability of a woman being single and interpret their fi ndings in the context of a search model. Note that unlike the Watson and McLanahan
2011 paper on marriage, these papers are not focused on low- income populations. 5. Watson 2009 presents evidence that as income inequality has increased over time, cities have become
increasingly segregated along income lines. 6. An earlier version of this paper additionally considered cross- country comparisons using individual- level
data from the Family and Fertility Surveys FFS collected by the United Nations. We refer the interested reader to that paper Kearney and Levine 2011.
We also consider a large set of potentially confounding state- level factors, and con- fi rm that our fi ndings are not driven by these alternative explanations. For example,
we directly test the role of income inequality against absolute income levels, poverty concentration rates, minority concentration rates, as well as other potentially important
environmental factors such as social capital measures, religious composition, or politi- cal climate. Though we could never completely rule out the existence of an omitted
factor, the robustness of the relationship is striking.
7
Our scholarly contribution is twofold. First, we present empirical evidence sup- porting the role of income inequality in driving rates of early nonmarital childbear-
ing among those at the bottom of the income distribution. Our estimates suggest that inequality can explain a sizable share of the variation in teen childbearing rates across
states. To date, no other explanation can come close to explaining as much of the geo- graphic variation.
8
Second, we believe our proposed economic model of young adult decision- making in the face of short- versus long- term payoffs constitutes an impor-
tant contribution to the literature in economics that considers adolescent behaviors such as juvenile crime, teen childbearing, and high school noncompletion. In our con-
ceptualization, such so- called “risky behaviors” might be more appropriately consid- ered “drop out” behaviors, and our model suggests that adolescents will be more likely
to choose to drop out of the mainstream climb to socioeconomic success when they view their chances of success as suffi ciently low. Though this paper is focused entirely
on early nonmarital childbearing, we believe our model is applicable to a number of other contexts that involve current benefi ts and future economic costs.
II. Review of Previous Research on Early Nonmarital Childbearing
