The Effect of Teen Pregnancy on Siblings’ Sexual
Behavior
Priyanka Anand and Lisa B. Kahn
April 22, 2013
Abstract
A number of studies have found long-term negative economic consequences for teen
parents. As a result, there is substantial policy interest in reducing the occurrence
of teen pregnancy by targeting high-risk individuals. In this paper, we test whether
experiencing an older sibling’s teen pregnancy impacts the younger sibling’s sexual
behavior. To identify this effect, we exploit the timing of the teen pregnancy by analyzing the change in sexual behavior just after the sibling’s teen pregnancy compared
to just before, relative to the change in behavior of a control group over the same
time window. We also explore whether the sibling peer effects vary with the gender
composition and age gap of the sibling pair. The data are from the National Longitudinal Study of Adolescent Health (Add Health). Our results show that after an older
sibling’s teen pregnancy, younger siblings are more likely to be sexually active, have
more sexual partners and are more likely to have a teen pregnancy themselves. We find
no effects on birth control use. These effects vary little by gender or by characteristics
of the sibling pair. Our work suggests that sibling peer effects in sexual behavior are
strong and these younger siblings could be a particularly well-targeted group for teen
pregnancy prevention campaigns.
1
1
Introduction
The United States has the highest teen birth rate of any country in the industrialized world
[Kearney and Levine, 2012]. As a result, there is substantial policy interest in understanding
the causes of teen pregnancy and, more generally, risky sexual adolescent behaviors.1 Previous work has investigated the role of race, religion, education, and income on teen pregnancy
and childbearing [Kearney and Levine, 2010, An et al., 1993, Thornberry et al., 1997, Zavodny, 2001]. The general consensus is that characteristics such as growing up with a single
parent, having parents with lower educational attainment and/or being in a family that receives welfare increase the probability of teen pregnancy. While a large number of papers
have looked at the impact of policies regarding sex education, welfare, access to abortion,
and mandatory schooling on teenage childbirth [Oettinger, 1999, Lundberg and Plotnick,
1995, Kane and Staiger, 1996, Black et al., 2008], only a small number have examined the
role of peer influence on sexual behavior [Fletcher and Yakusheva, 2011, Evans et al., 1992].
In this paper, we explore whether the sexual behavior of an individual is affected by the teen
pregnancy experience of an older sibling and whether this influence varies by the gender
composition and age gap of the sibling pair.
Peer effects among siblings have been shown to play an important role in the risky
behaviors of teenagers. Past literature has presented evidence that younger siblings are more
likely to emulate the alcohol, marijuana and cigarette use of their older siblings [Altonji et al.,
2010, Ouyang, 2004]. Teen pregnancy as an influence on a sibling is particularly interesting
because it occurs at a specified point in time and may have large, visible consequences. We
therefore have a well-defined shock to a younger sibling’s environment and can measure his
or her reactions in terms of sexual behavior. The effect of this shock could operate in two
directions. On the one hand, a teen might mimic his or her sibling’s behavior if he or she
admires the older sibling or desires the same attention and engage in riskier sexual actions.
On the other hand, directly observing the negative consequences of a pregnancy, abortion
or baby might make an individual more cautious, deterring him or her from engaging in
risky sexual behaviors.2 Previous findings that a teen pregnancy in the family [Monstad
1
The educational and economic consequences of early child-bearing are a source of long-standing debate.
Early studies that primarily relied on cross-sectional OLS estimates found large negative effects of teen
pregnancy on educational attainment, income, and marriage stability [Card, 1981, Card and Wise, 1978,
Trussell, 1976, Waite and Moore, 1978]. More recent papers are conflicted regarding the validity of these
results. Geronimus and Korenman [1992], Hoffman et al. [1993], Ashcraft and Lang [2006] and Hotz et al.
[2005] argue that the original OLS estimates of the consequences of teen pregnancy were greatly overstated
due to their insufficient controls for family heterogeneity, while findings by Fletcher and Wolfe [2008, 2012]
upheld the negative educational and economic consequences of teen pregnancy even after controlling for
family heterogeneity with their use of miscarriages as a control group. Overall, there does not seem to be
consensus on the long-term educational and economic effects of teen pregnancy.
2
East et al. [2009] analyzes data from a survey of younger siblings of Latina girls that have had teen
2
et al., 2011] or friend group [Fletcher and Yakusheva, 2011] positively impacts one’s own
probability of a teen pregnancy, suggest that the former effect will outweigh the latter.3
However, measuring only the stark, discrete outcome of a teen pregnancy may miss some
of the nuance of these effects. We therefore study a range of sexual behaviors including
sexual activity, number of partners and birth control use, in addition to the impact on teen
pregnancy, to better characterize the younger sibling’s reactions.
Identifying the causal impact of an older sibling’s teen pregnancy on a younger sibling’s
sexual behavior presents quite the challenge given that environmental factors contributing
to sexual behavior will be highly correlated across the siblings.4 In fact, McHale et al. [2009]
finds that siblings have correlated sexual behavior in terms of risk, particularly for those with
close relationships and of the same gender. Furthermore, younger siblings tend to engage in
risky behavior [Argys et al., 2006, Averett et al., 2007] and are sexually active at a younger
age than their older siblings [Rodgers et al., 1992]. It will be important to control for both
of these factors.
Our approach in this paper is to isolate the timing of the teen pregnancy and compare
sexual behavior of younger siblings just after an older sibling’s teen pregnancy to those just
before. As a control group, we use the change in sexual behavior of younger siblings who did
not have a teen pregnancy in the family over a similar time period. Thanks to the extremely
rich National Longitudinal Study of Adolescent Health dataset, which includes a rich set of
family background variables, we can exactly time and characterize all sexual relationships.
We can therefore control for mean differences in sexual behavior across different types of
families. Importantly, however, we cannot control for diverging trends.
We further explore whether the influence of an older sibling’s teen pregnancy varies with
characteristics of the sibling pair. We ask whether same-gendered pairs or those that are
closer in age more strongly impact each other. Much of the literature that analyzes sibling
gender composition focuses on its effect on the educational achievement of younger siblings
[Conley, 2000, Kaestner, 1997, Butcher and Case, 1994]. However, gender composition might
also play an important role in whether there are sibling peer effects on risky behavior. Ouyang
[2004] finds a larger influence of the older sibling’s alcohol and marijuana use on the younger
pregnancies and finds that two-thirds of the respondents perceived that early parenting is not a hardship.
Interestingly, all but one of these same respondents reported an increased motivation to avoid early parenting.
3
Furthermore, Kuziemko [2006] focuses on adult sibling pairs and shows that individuals are more likely
to have a child in the two years after one’s sibling has a child.
4
There are various strategies that have been implemented in other papers to address this challenge.
For example, several papers use the absence of a miscarriages as an instrument for the probability of teen
childbearing [Ashcraft and Lang, 2006, Fletcher and Wolfe, 2008, 2012]. Monstad et al. [2011] use a change
in compulsory school laws in Norway as a source of variation in teen pregnancy. Altonji et al. [2010] identify
whether teenagers are influenced by the behavior of older siblings by exploiting restrictions on the timing
and direction of the sibling influence.
3
sibling’s for same-gender pairs. Since the experience of a teen pregnancy varies by gender of
the parent, we might expect to find a larger influence of an older sibling’s teen pregnancy
on a younger sibling’s sexual behavior for same-gendered pairs. Similarly, the age difference
between the siblings could also affect the degree to which the younger sibling is influenced by
the teen pregnancy of their older sibling. A much younger sibling may not be as aware of the
consequences of the older sibling’s teen pregnancy as a younger sibling who is closer in age.
Indeed, Monstad et al. [2011] find teen births are more highly correlated when siblings are
closer in age for families in Norway. We examine the extent to which gender composition and
age differences affect the response of an individual to their older sibling’s teen pregnancy.
We find that the sexual behavior of younger siblings is affected by exposure to a sibling
teen pregnancy. In particular, we find that individuals who are exposed to a teen pregnancy
are more likely to be sexually active in the period immediately after the teen pregnancy, have
more sexual partners and are more likely to have a teen pregnancy themselves, conditional
on their sexual behavior immediately before the sibling teen pregnancy. These effects do not
seem to vary much by the gender of either sibling, though we do find some evidence that
the effects may be stronger among same-gendered siblings and those who are closer in age.
Overall, our results indicate that there are strong peer effects on sexual behavior between
older and younger siblings.
The organization of the paper is as follows. Section 2 describes the data and provides
some summary statistics. Section 3 presents the empirical strategy used to identify the
effect of teen pregnancy on the sexual behavior of younger siblings and how these effects
differ by gender composition and age differences. Section 4 presents the empirical results
and discussion. Section 5 concludes.
2
Data
The dataset used in this paper is from the National Longitudinal Study of Adolescent Health
(Add Health). The Add Health survey, first administered to students in 132 schools across
the United States, drew a sample of nearly 21,000 students to participate in a series of four
in-home surveys conducted from 1994-2008. These surveys contain detailed questions about
sexual behavior and pregnancy history, substance abuse, and criminal activities. Table 1
shows the ages, sample sizes and years for each wave of the survey. By wave 4, all individuals
have completed their teenage years and are in their mid-twenties to mid-thirties.
Importantly for this study, siblings living in the same household as students selected for
the in-home survey were oversampled. This resulted in over 3,000 sibling pairs in the first
4
wave of the survey.5 We obtain demographic and family background information from wave
1, including race, region of residence, urbanicity, household income, food stamp participation,
and household composition. Key variables of interest for this study are whether the older
sibling has been pregnant as a teenager or has gotten their partner pregnant, and the exact
date of the pregnancy. For these variables, we primarily use information from waves 3 and
4, in which individuals are asked to create a roster of all pregnancies and the date each
pregnancy ended (whether it was a live birth, abortion, or other outcome), resulting in 670
older siblings who had a pregnancy before the age of 20 (out of the 3,909 sibling pairs), or
17% of the sample and 25% of older sisters.6 This teen pregnancy rate is similar to the
corresponding measures reported in other papers. Fletcher and Yakusheva [2011] show that
20% of females report a pregnancy before age 20 using the entire Add Health sample (not
only sibling pairs) until wave 3, and Kearney and Levine [2012] report that 20% of women
in the National Survey of Family Growth have given birth by the time they are twenty.
However, we expect our number to be higher because our sample is selected on larger family
size, and we include all pregnancies (not just births, as in the Kearney and Levine paper).
Table 2 shows summary statistics for the sibling pairs based on the older sibling’s teen
pregnancy status, as well as the difference in means across groups in the third column where
statistical significance is also indicated. As can be seen, families with a teen pregnancy look
disadvantaged relative to the rest of the sample. They are more likely to be minority, earn
roughly $9,000 less per year, are 11 percentage points more likely to be on food stamps and
are 17 percentage points less likely to have a father in the household. All of these differences
are statistically significant at the 99%-level. These differences in family background motivate
our event study analysis as a method of controlling for unobserved factors correlated with
family background that would cause siblings to behave similarly.
Table 2 also shows that 72% of the teen pregnancies are to older sisters. One concern
is that boys may be unaware of a pregnancy or unwilling to acknowledge their role as the
father and thus underreport their instances of teen pregnancies. We explore this type of
measurement error by asking how many teen pregnancies would occur among boys if we
solely relied on information from girls and the reported age of their partners. Table 3
5
The restricted-use AddHealth data links each student with the survey information for their sibling,
resulting in 3,139 sibling pairs. 17 pairs are dropped because they do not have information on the date of
birth of at least one sibling. Our unit of analysis is the younger sibling. For twin pairs, each twin has one
observation as the “younger” sibling. The result is 3,909 sibling pairs in the sample. Results are robust to
the exclusion of twins from the sample.
6
In waves 1 and 2, individuals were asked whether each romantic relationship included a pregnancy;
however, the date of the pregnancy is not recorded. This adds 256 older siblings who experienced a teen
pregnancy whose pregnancy dates we can approximate based on their dates of sexual activity. Our results
are robust to the inclusion of these pregnancies. However, our prefered specification uses only information
from waves 3 and 4, so as to not introduce additional measurement error in dating the pregnancy.
5
reports this counterfactual distribution of teen pregnancies, in which we find that 63% of
teen pregnancies would go to girls (1,967 out of the 3,099 pregnancies reported by girls).
The age composition of partnerships (where young girls tend to have older partners) can
rationalize a large amount of the disproportionate number of teen pregnancies reported by
girls, compared to boys.7 Furthermore, Fletcher and Wolfe [2012] provide evidence from
various data sources (including the Add Health data) that the fertility information reported
by men is not systematically biased across race and family background characteristics.
Our key dependent variables will be sexual behaviors of the younger sibling in a period of
time after the older sibling’s teen pregnancy, including whether the individual was sexually
active, the number of sexual partners the individual has conditional on sexual activity,
and whether the individual always used birth control during this period conditional on
sexual activity.8 We choose the twelve months after the end date of the older sibling’s teen
pregnancy as the relevant period. We use the end date instead of the date of conception
because the survey did not collect information on the conception date, which is difficult
to impute for miscarriages or abortions. Furthermore, the family may not be aware of
the pregnancy immediately after the date of conception, whereas the end date is a clearly
defined shock to the pregnant teen. Results are robust to reasonable changes to this window
of analysis. For those who do not have a teen pregnancy, we use the median date among
those with a sibling teen pregnancy as the window during which sexual behavior variables
are measured. We also ask whether the younger sibling experienced a teen pregnancy at any
point after the older sibling’s pregnancy.
By isolating the timing of the sibling’s pregnancy, we can also control for behaviors in
the period before this window of time. We define the “before” period as the individual’s
behavior during partnerships that occurred between 18 months before the end date of the
sibling’s teen pregnancy until 6 months before the end date. We chose this window to be
7
As mentioned above, our results are robust to including teen pregnancies listed in waves 1 or 2 when
we cannot accurately date the pregnancy. When these pregnancies are included, we find that 59% of older
sibling teen pregnancies are to girls. This aligns much more closely to the 63% counterfactual share we get
when we use the self-reported age of partners among the females.
8
These variables were created from the relationship rosters completed by respondents during each wave
of the survey. For each romantic relationship, respondents were asked whether they were sexually active in
that relationship and the first and most recent date of sexual intercourse. In waves 1 and 2, respondents were
asked whether they used any type of birth control every time they had sex in the relationship; in waves 3 and
4, they were asked whether they used birth control the first and most recent time of sexual intercourse in the
relationship. A respondent is considered sexually active if the dates of sexual activity within any relationship
overlapped with the period of interest. The respondent is considered using birth control during the period
of interest if they reported always using birth control in any sexual relationship recorded in waves 1 and
2 that occurred during that period; for relationships reported in waves 3 and 4, they are considered using
birth control if they used birth control the first and most recent time of intercourse. Finally, the number
of sexual partners is the number of relationships for which the dates of sexual activity overlapped with the
period of interest.
6
the same length of time as the “after” period and allow a gap during most of the actual
pregnancy so that it hopefully does not influence behavior. For those who did not have a
sibling with a teen pregnancy, we again use the median date from the sample of those with
a teen pregnancy.9
Table 4 presents the average behavior in the before and after periods for those that had
a sibling with a teen pregnancy and those that did not. As indicated by the difference
columns, which are again starred for statistical significance, individuals on average increase
their sexual activity, number of sexual partners and use of birth control in the “after” period,
due to the fact that the individuals are getting older over this period of time. However, the
far right column, showing the difference in mean differences between groups, indicates that
those with siblings who have experienced a teen pregnancy tend to increase these behaviors
more than those whose siblings did not have a teen pregnancy and are also more likely to have
a teen pregnancy themselves. For example, those with a sibling teen pregnancy increase their
rate of sexual activity by 19 percentage points more than those without a teen pregnancy,
and increase the number of sexual partners by almost half a partner. These differences are
statistically significant at the 1% level. This suggests that younger siblings may respond to
their older siblings’ teen pregnancies, wishing to mimic their behavior. However, we see no
significant difference in means for birth control use. We will investigate these relationships in
a regression framework, described in the next section, where we also control for characteristics
of individuals and their family backgrounds, as well as their sexual behavior in the period
before their sibling’s teen pregnancy.
3
Empirical Strategy
In our analysis, we exploit the timing of the sibling teen pregnancy and measure the younger
sibling’s response to this shock, controlling for their behaviors beforehand. We estimate
regressions of the following form:
outcome afteri = α0 + α1 Sib Pregi + γbeforei + I yob + Xi β + εi
where Sib preg is an indicator that an older sibling experienced a teen pregnancy, and beforei
is a vector of sexual behaviors in the before period, including whether the teen is sexually
active, the number of sexual partners in the before window and whether the teen always used
birth control during sexual relationships that occurred in the before window. We also control
for year of birth indicators (I yob ), and a vector of control variables (Xi ) that includes indi9
The before variables for number of partners and birth control use are coded to 0 for those who were not
sexually active, so we can include them as control variables for all observations.
7
cators for the age at the sibling’s teen pregnancy (or age at the median teen pregnancy date
for those whose sibling did not have a teen pregnancy), the age at sibling’s teen pregnancy
interacted with whether the sibling had a teen pregnancy, race, gender, geographic region,
urban status, wave participation, household income, food stamp participation, and family
composition.10 Our key outcome variables (outcome after) are whether the teen is sexually
active, the total number of sexual partners conditional on sexual activity, and contraception
usage conditional on sexual activity, all measured during the after window, and whether the
younger sibling has a teen pregnancy themselves. We estimate these regressions on the full
sample, as well as sub-samples based on gender of younger or older sibling. For the binary
outcomes of interest (whether the teen is sexually active, contraception usage, and whether
the younger sibling has a teen pregnancy themselves), we use a logit specification of the
model to account for any non-linearities in the model.11
Analyzing the probability of having a teen pregnancy after observing the teen pregnancy
of a sibling is complicated by the existence of younger siblings who already have a teen
pregnancy by the time their older sibling gets pregnant. As can be seen in table 4, this is
true for approximately one-quarter of the siblings where both siblings have a teen pregnancy.
To deal with this issue, we drop the 75 sibling pairs where the younger sibling has a teen
pregnancy before their older sibling. For those whose sibling did not have a teen pregnancy,
we also drop the 140 sibling pairs where the younger sibling has a teen pregnancy before the
median teen pregnancy date.12
Finally, we look at whether the effect of sibling pregnancy varies depending on the characteristics of the sibling pair. In particular, we are interested in measuring whether the effect
is larger if the siblings are of the same-sex or have a smaller difference in age. To examine the
role of the gender composition of siblings, we interact sibling’s teen pregnancy with whether
the sibling is of the same gender:
outcome afteri = α0 + α1 Sib Pregi + γbeforei + α2 same genderi
+ α3 (Sib pregi ∗ same genderi ) + I yob + Xi β + εi
The coefficient of interest is α3 , which is the effect of a sibling teen pregnancy on the individual’s behavior if the sibling is the same gender. To examine the role of the age difference
between the two siblings, we interact having a sibling’s teen pregnancy with the age differ10
The age at sibling’s teen pregnancy is normalized around the average age at sibling’s teen pregnancy for
the sample of sibling pairs.
11
Results are robust to the use of a linear probability model instead of a logit.
12
An additional four observations that are born in 1975 are dropped because they perfectly predict the
outcome in the logit specification. One of these observations is also dropped from the contraception usage
and two from the sexual activity analysis for younger brothers for the same reason.
8
ence:
outcome afteri = α0 + α1 Sib Pregi + γbeforei + α2 age diffi
+ α3 (Sib pregi ∗ age diffi ) + I yob + Xi β + εi
Again, the coefficient of interest is α3 , which is the additional effect of a sibling teen pregnancy
on the individual’s behavior for each year of difference in age between the siblings.
4
Results
In this section, we present the results from the empirical analysis described above. Table
5 summarizes regression results for the full sample of younger siblings for four dependent
variables in the after period: sexual activity, the probability of ones’s own teen pregnancy,
number of partners and birth control use, where the latter two are measured conditional
on sexual activity. Columns labeled “I” control for all the family background variables
listed above, columns labeled “II” additionally control for the sexual behavior in the before
period, and columns labeled “III” include an interaction between the age at the sibling’s
teen pregnancy (or the median age for those whose sibling did not have a teen pregnancy)
and whether the sibling had a teen pregnancy.
Turning first to sexual activity, we see younger siblings are 18 percentage points more
likely to be sexually active immediately following a sibling’s teen pregnancy, relative to
those without a sibling teen pregnancy in the default window. The second column shows that
sexual behavior in the “before” period does significantly predict sexual behavior in the “after”
period. Including these variables increases the main coefficient of interest, whether the older
sibling has had a teen pregnancy, to a 19.5 percentage point increase in the probability of
being sexually active and is statistically significant at the 1% level. The coefficient is quite
large, given the overall sample mean is about 30%. Including an interaction between the
age at the sibling’s teen pregnancy (or the median age for those whose sibling did not have
a teen pregnancy) and whether the sibling had a teen pregnancy increases the coefficient to
20.6 percentage points.
The next set of columns in table 5 reports results on the probability of having a teen
pregnancy, where those who had a pregnancy before their older sibling are dropped from the
sample. As can be seen, younger siblings are approximately 6 to 10 percentage points more
likely to have a teen pregnancy after their sibling’s teen pregnancy, relative to those without
a sibling teen pregnancy. The coefficient is quite a large effect considering about 19% of our
sample of younger siblings have a teen pregnancy (excluding pregnancies that occur before
9
an older sibling’s).
The next set of columns in table 5 reports the impact on number of sexual partners in
the after window, conditional on being sexually active. Here the impact of a sibling’s teen
pregnancy is roughly a 1/5 increase in the number of sexual partners, statistically significant
at the 1% level. This result increases slightly we control for behaviors in the before period
and interact the age at the sibling’s teen pregnancy with whether the sibling had a teen
pregnancy.
Finally, the last set of columns in table 5 show that birth control usage is not statistically
significantly impacted by a sibling’s teen pregnancy, though somewhat large standard errors
mean that we cannot rule out sizeable impacts. Thus, on the whole, we do see evidence of
peer effects in that younger siblings seem to mimic their older sibling’s sexual behavior. We
do not see any evidence of more careful behavior in response to a sibling’s teen pregnancy.
We turn next to heterogeneity in these effects by gender of the younger and older sibling,
summarized in tables 6 and 7, respectively, where all regressions control for sexual behavior
in the before period. These tables show gender has little impact on sexual activity. We see
that the increased probability of one’s own teen pregnancy is concentrated among younger
sisters as opposed to younger brothers, as well as those that have older sisters as opposed
to older brothers. The magnitude on the birth control coefficient is also quite sizeable and
negative, though not statistically significant, for sisters compared to brothers.
Next we look at whether the effects differ depending on the gender composition of the
siblings. As discussed earlier, siblings of the same gender may have a larger impact on each
other, either because they are closer, or the consequences of teen pregnancy are the same for
both siblings. In table 8, we present the results for all four outcomes using the sample of all
sibling pairs. The only outcome that is significantly affected by the gender of the siblings is
the number of partners conditional on being sexually active. Younger siblings actually have
0.35 fewer partners, on average, after their sibling has a teen pregnancy if the sibling is the
same gender as them. Though not shown here, this effect is largely robust across gender of
older and younger sibling. For the probability of being sexually active, the point estimate
on the same gender interaction is sizeable and positive, though not statistically significant.
Lastly, we examine the role of the age difference between two siblings. In table 9, we
show the results from regressing the four sexual behavior outcomes on the interaction of
the sibling age difference with the sibling teen pregnancy. Here we see the probability of
being sexually active in the “after” period is affected by the age difference; being further
in age decreases the probability of sexual activity after exposure to a teen pregnancy, and
this effect is significant at the 10% level. We also see that being further in age decreases the
probability of the younger sibling having a teen pregnancy. The coefficient on the age gap
10
interaction term is not statistically significant for the other dependent variables. However,
as a whole, these results suggest that sexual behavior increases more following a sibling’s
teen pregnancy among those who are closer in age. Though not reported, these results are
similar by gender.
5
Conclusions
In this paper, we seek to understand the impact of a sibling’s teen pregnancy on one’s own
sexual behavior. The AddHealth data allows us to exploit the timing of the teen pregnancy
and analyze the behavior of the younger sibling just after a pregnancy, controlling for the
behavior just before. We also measure the differential impact of having a same-gendered
sibling with a teen pregnancy and the impact by the age difference of the siblings.
We find that sexual behavior is indeed impacted by exposure to a teen pregnancy. In particular we find that younger siblings with an older sibling who experiences a teen pregnancy
are more likely to be sexually active after the teen pregnancy, have more sexual partners,
and have a teen pregnancy themselves.
These findings are relevant for policy makers who would like to reduce pregnancy among
teenagers by targeting those who are at risk. Our findings indicate that younger siblings
tend to be influenced by the actions of their older siblings, which means younger siblings are
a particularly vulnerable group when it comes to teen pregnancy and risky sexual behavior.
11
References
Joseph G. Altonji, Sarah Cattan, and Iain Ware. Identifying sibling influence on teenage
substance. April 2010.
Chong-Bum An, Robert Haveman, and Barbara Wolfe. Teen out-of-wedlock births and
welfare receipt: The role of childhood events and economic circumstances. The Review of
Economics and Statistics, 75(2):195–208, May 1993.
Laura M. Argys, Daniel I. Rees, Susan L. Averett, and Benjama Witoonchart. Birth order
and risky adolescent behavior. Economic Inquiry, 44(2):215–233, April 2006.
Adam Ashcraft and Kevin Lang. The consequences of teenage childbearing. NBER Working
Paper 12485, August 2006.
Susan L. Averett, Laura M. Argys, and Daniel I. Rees. Older siblings and adolescent risky
behavior: Does parenting play a role? Economic Inquiry, 44(2):215–233, March 2007.
Sandra E. Black, Paul J. Devereux, and Kjell G. Salvanes. Staying in the classroom and out
of the maternity ward? the effect of compulsory schooling laws on teenage births. The
Economic Journal, 118, 2008.
Kristin F. Butcher and Anne C. Case. The effect of sibling sex composition on women’s
education and earnings. The Quarterly Journal of Economics, 109(3), August 1994.
Josefina J. Card. Long-term consequences for children of teenage parents. Demography, 18
(2):137–156, May 1981.
Josefina J. Card and Lauress L. Wise. Teenage mothers and teenage fathers: The impact
of early childbearing on the parents’ personal and professional lives. Family Planning
Perspectives, 10(4):199–205, July/August 1978.
Dalton Conley. Sibship sex composition: Effects on educational attainment. Social Science
Research, 29, 2000.
Patricia L. East, Ashley Slonim, Emily J. Horn, Cyndy Trinh, and Barbara T. Reyes. How an
adolescent’s childbearing affects siblings’ pregnancy risk: A qualitative study of mexican
american youths. Perspectives on Sexual and Reproductive Health, 41(4), December 2009.
William N. Evans, Wallace E. Oates, and Robert M. Schwab. Measuring peer group effects:
A study of teenage behavior. The Journal of Politcal Economy, 100(5):966–991, October
1992.
Jason M. Fletcher and Barbara L. Wolfe. Education and labor market consequences of
teenage childbearing. The Journal of Human Resources, 44(2), 2008.
Jason M. Fletcher and Barbara L. Wolfe. The effects of teenage fatherhood on young adult
outcomes. Economic Inquiry, 50(1):182–201, January 2012. Memo.
12
Jason M. Fletcher and Olga Yakusheva. Peer effects on teenage fertility. Memo, November
2011.
Arline T. Geronimus and Sanders Korenman. The socioeconomic consequences of teen childbearing reconsidered. The Quarterly Journal of Economics, 197(4):1187–1214, November
1992.
Saul D. Hoffman, E. Michael Foster, and Frank F. Furstenberg Jr. Reevaluating the costs of
teenage childbearing. Demography, 30(1):1–13, February 1993.
V. Joseph Hotz, Susan Williams McElroy, and Seth G. Sanders. Teenage childbearing and
its life cycle consequences: Exploiting a natural experiment. Journal of Human Resources,
40(3), 2005. NBER Working Paper 7397.
Robert Kaestner. Are brothers really better? sibling sex composition and educational
achievement revisted. The Journal of Human Resources, 32(2), 1997.
Thomas J. Kane and Douglas Staiger. Teen motherhood and abortion access. The Quarterly
Journal of Economics, 111(2):467–506, May 1996.
Melissa S. Kearney and Phillip B. Levine. Why is the teen birth rate in the united states so
high and why does it matter? Journal of Economic Perspectives, 26(2), 2012.
Melissa S. Kearney and Phillip B. Levine. Socioeconomic disadvantage and early childbearing. In Jonathan Gruber, editor, The Problems of Disadvantaged Youth: An Economic
Perspective. University of Chicago Press, 2010.
Ilyana Kuziemko. Is having babies contagious? estimating fertility peer effects between
siblings. Memo, June 2006.
Shelly Lundberg and Robert D. Plotnick. Adolescent premarital childbearing: Do economic
incentives matter? Journal of Labor Economics, 13(2):177–200, April 1995.
Susan M. McHale, Joanna Bissell, and Ji-Yeon Kim. Sibling relationship, family, and genetic
factors in sibling similarity in sexual risk. Journal of Family Psychology, 23(4), 2009.
Karin Monstad, Carol Propper, and Kjell G. Salvanes. Is teenage motherhood contagious?
evidence from a natural experiment. July 2011.
Gerald S. Oettinger. The effects of sex education on teen sexual activity and teen pregnancy.
The Journal of Politcal Economy, 107(3):606–644, June 1999.
Lijing Ouyang. Sibling effects on teen risky behaviors. Memo, November 2004.
Joseph Lee Rodgers, David C. Rowe, and David F. Harris. Sibling differences in adolescent
sexual behavior: Inferring process models from family composition patterns. Journal of
Marriage and the Family, 54(1):142–152, February 1992.
Terence P. Thornberry, Carolyn A. Smith, and Gregory J. Howard. Risk factors for teenage
fatherhood. Journal of Marriage and the Family, 59(3):505–522, August 1997.
13
T. James Trussell. Economic consequences of teenage childbearing. Family Planning Perspectives, 8(4):184–190, July/August 1976.
Linda J. Waite and Kristin A. Moore. The impact of an early first birth on young women’s
educaitonal attainment. Social Forces, 56(3):845–865, March 1978.
Madeline Zavodny. The effect of partners’ characteristics on teenage pregnancy and its
resolution. Family Planning Perspectives, 33(5), September/October 2001.
14
6
Tables
Table 1: Add Health sample
Wave 1 Wave 2
Year
1994-95
1996
Age Range
11-21
12-22
Observations 20,745 14,738
15
size and ages
Wave 3 Wave 4
2001-02 2007-08
18-28
24-35
15,197
15,701
Table 2: Summary statistics
Sibling teen pregnancy?
No
Yes
Diff’ce
(n=3,239) (n=670)
Twin
0.40
0.40
0.00
Younger sibling female
0.49
0.60
0.11 ∗ ∗
Older sibling female
0.45
0.72
0.27 ∗ ∗
Same gender
0.62
0.65
0.03
Age difference
1.33
1.30
−0.03
Age at sib’s pregnancy/default 17.07
16.80
−0.27 ∗ ∗
Hispanic
0.15
0.15
0.00
Asian
0.07
0.03
−0.04 ∗ ∗
Black
0.20
0.35
0.15 ∗ ∗
Other
0.05
0.06
0.01
Missing race
0.00
0.01
0.01 ∗ ∗
Urban
0.26
0.27
0.01
Suburban
0.49
0.48
−0.01
West
0.23
0.19
−0.04 ∗ ∗
Midwest
0.24
0.25
0.01
South
0.35
0.38
0.03+
Missing geographic area
0.07
0.11
0.04 ∗ ∗
Household income (wave 1)
35.37
26.24
−9.13 ∗ ∗
Missing household income
0.24
0.25
0.01
Foodstamps
0.12
0.23
0.11 ∗ ∗
Missing foodstamps
0.15
0.16
0.01
Lives with mother (wave 1)
0.90
0.84
−0.06 ∗ ∗
Lives with father (wave 1)
0.68
0.51
−0.17 ∗ ∗
Missing HH roster
0.00
0.01
0.01 ∗ ∗
** denotes significance at the .01 level, * at the 0.05 level, and + at the 0.1 level.
16
Table 3: Ratio of pregnancies by the age of the mother and father as reported by the mothers
Age of father
13 14 15 16 17 18 19 19+ Total Teen father
by age
total
13
1 1 1 0
2
0
0
0
5
14
0 3 1 3
0
2
3
5
17
15
1 2 17 13 21
3
13
26
96
16
0 3 8 27 39 34
5
68
184
17
0 0 3 15 66 66 72 121
343
Age of mother
18
0 0 1 13 45 80 125 300
564
19
1 0 1 2 20 57 126 551
758
19+
0 2 3 5 21 51 157
Total by age 3 11 35 78 214 293 501
1132
Teen mother
1967
total
17
Table 4: Sexual behavior before and after teen pregnancy
Sibling teen pregnancy?
No
Yes
(n=3,239)
(n=670)
Before After Diff’ce Before After Diff’ce
Sexually active
0.18
0.29 0.11**
0.14
0.44 0.30**
1
N partners conditional on sex
0.46
1.41 0.95**
0.29
1.67 1.39**
0.08
0.49 0.41***
BC conditional on sex1
0.13
0.52 0.39**
Teen pregnancy ever
0.17
0.33
Teen pregnancy after
0.12
0.22
1
Diff-in-Diff
0.19**
0.43**
0.01
0.16**
0.09**
Observations are conditional on being sexually active in the after period. Before values for N partners and
birth control are equal to zero if not sexually active in the before period.
** denotes significance at the .01 level, * at the 0.05 level, and + at the 0.1 level.
18
19
# Partners1
Birth control1
(I)
(II)
(III)
(I)
(II)
(III)
b/se
b/se
b/se
b/se
b/se
b/se
0.205** 0.233** 0.254** -0.034
-0.038
-0.042
(0.072) (0.071) (0.074) (0.042) (0.042) (0.044)
0.247** 0.270** 0.295** -0.029
-0.035
-0.041
(0.094) (0.094) (0.097) (0.055) (0.056) (0.058)
0.140
0.142
-0.119+ -0.119+
(0.111) (0.111)
(0.065) (0.065)
0.126* 0.125*
-0.006
-0.005
(0.058) (0.058)
(0.035) (0.035)
-0.223* -0.225*
0.198** 0.198**
(0.096) (0.096)
(0.050) (0.050)
-0.067* -0.069* -0.094* -0.022
-0.025
-0.020
(0.029) (0.029) (0.038) (0.017) (0.017) (0.023)
0.044
-0.009
(0.044)
(0.026)
1238
1238
1238
1237
1237
1237
pairs
2
Observations are conditional on being sexually active
Variables equal zero if not sexually active in the before window.
** denotes significance at the .01 level, * at the 0.05 level, and + at the 0.1 level.
Logit coefficients for binary outcomes reflect marginal effects. All regressions control for the age of the younger sibling at the time of the older siblings
teen pregnancy, age of younger sibling interacted with whether older sibling had teen pregnancy, gender of both siblings, year, race, geographic region,
household income in wave 1, foodstamps in wave 1, lives with mother in wave 1 and lives with father in wave 1.
1
N
w34 tp age int
w34 tp age norm
BC Before2
N Partners Before2
Sexually Act Bef
Sib Preg, No Baby
Sibling Baby
Table 5: Regressions including all sibling
Sexual Activity
Own teen preg
(I)
(II)
(III)
(I)
(II)
(III)
b/se
b/se
b/se
b/se
b/se
b/se
0.178** 0.195** 0.206** 0.060** 0.063** 0.096**
(0.034) (0.037) (0.040) (0.020)
(0.020)
(0.026)
0.166** 0.172** 0.185** 0.058*
0.060*
0.099**
(0.040) (0.043) (0.045) (0.027)
(0.026)
(0.034)
0.134** 0.134**
0.130** 0.131**
(0.051) (0.051)
(0.040)
(0.040)
0.045+ 0.045+
0.020
0.019
(0.025) (0.025)
(0.014)
(0.014)
0.096* 0.096*
-0.025
-0.025
(0.044) (0.044)
(0.018)
(0.018)
0.036** 0.030** 0.022+ -0.021** -0.022** -0.036**
(0.011) (0.011) (0.013) (0.005)
(0.005)
(0.008)
0.013
0.019*
(0.013)
(0.008)
3908
3908
3908
3689
3689
3689
20
Birth
control1
b/se
0.015
(0.074)
0.004
(0.098)
-0.125
(0.107)
0.011
(0.061)
0.222**
(0.085)
0.019
(0.043)
-0.027
(0.037)
516
2
Observations are conditional on being sexually active
Variables equal zero if not sexually active in the before window.
** denotes significance at the .01 level, * at the 0.05 level, and + at the 0.1 level.
Logit coefficients for binary outcomes reflect marginal effects. All regressions control for the age of the younger sibling at the time of the older siblings
teen pregnancy, age of younger sibling interacted with whether older sibling had teen pregnancy, gender of older siblings, year, race, geographic region,
household income in wave 1, foodstamps in wave 1, lives with mother in wave 1 and lives with father in wave 1.
1
N
w34 tp age norm
w34 tp age int
BC Before2
N Partners Before2
Sexually Active Before
Sibling Pregnant, No Baby
Sibling Baby
Table 6: Regressions by gender of younger sibling
Younger Sister
Younger Brother
Sexual
Own
# Partners1
Birth
Sexual
Own
# Partners1
Activity Teen Preg
control1 Activity Teen Preg
b/se
b/se
b/se
b/se
b/se
b/se
b/se
0.205**
0.161**
0.187+
-0.089
0.213**
0.031
0.328**
(0.041)
(0.051)
(0.100)
(0.058) (0.055)
(0.036)
(0.115)
0.197**
0.148*
0.200
-0.056
0.187**
0.069
0.466**
(0.053)
(0.062)
(0.131)
(0.077) (0.065)
(0.064)
(0.147)
0.214**
0.284**
0.124
-0.123
0.061
0.013
0.185
(0.071)
(0.082)
(0.150)
(0.086) (0.059)
(0.031)
(0.168)
0.054
0.006
0.157*
-0.012
0.035
0.030
0.053
(0.038)
(0.025)
(0.076)
(0.044) (0.031)
(0.027)
(0.092)
0.100
-0.043
-0.168
0.198**
0.089
-0.015
-0.294*
(0.063)
(0.035)
(0.131)
(0.064) (0.056)
(0.022)
(0.142)
0.023
0.031*
0.039
-0.027
-0.000
0.010
0.038
(0.019)
(0.016)
(0.060)
(0.035) (0.018)
(0.011)
(0.065)
0.014
-0.058**
-0.114*
-0.014
0.030+
-0.022
-0.031
(0.018)
(0.019)
(0.053)
(0.030) (0.018)
(0.019)
(0.056)
1995
1845
722
721
1911
1844
516
21
Birth
control1
b/se
0.030
(0.077)
0.003
(0.110)
-0.088
(0.096)
-0.015
(0.052)
0.257**
(0.069)
0.043
(0.044)
-0.050
(0.038)
583
2
Observations are conditional on being sexually active
Variables equal zero if not sexually active in the before window.
** denotes significance at the .01 level, * at the 0.05 level, and + at the 0.1 level.
Logit coefficients for binary outcomes reflect marginal effects. All regressions control for the age of the younger sibling at the time of the older siblings
teen pregnancy, age of younger sibling interacted with whether older sibling had teen pregnancy, gender of younger siblings, year, race, geographic
region, household income in wave 1, foodstamps in wave 1, lives with mother in wave 1 and lives with father in wave 1.
1
N
w34 tp age norm
w34 tp age int
BC Before2
N Partners Before2
Sexually Active Before
Sibling Pregnant, No Baby
Sibling Baby
Table 7: Regressions by gender of older sibling
Older Sister
Older Brother
Sexual
Own
# Partners1
Birth
Sexual
Own
# Partners1
Activity Teen Preg
control1 Activity Teen Preg
b/se
b/se
b/se
b/se
b/se
b/se
b/se
0.179**
0.098**
0.273**
-0.087
0.263**
0.118*
0.259*
(0.048)
(0.034)
(0.098)
(0.057) (0.055)
(0.054)
(0.125)
0.192**
0.120**
0.349**
-0.092
0.159*
0.082
0.228
(0.055)
(0.046)
(0.122)
(0.072) (0.070)
(0.059)
(0.173)
0.181*
0.189**
0.316*
-0.116
0.093
0.087+
-0.037
(0.076)
(0.069)
(0.160)
(0.094) (0.061)
(0.051)
(0.157)
0.037
0.021
0.050
-0.012
0.048
0.015
0.212*
(0.036)
(0.022)
(0.082)
(0.049) (0.032)
(0.018)
(0.084)
0.070
-0.033
-0.256+
0.159*
0.134*
-0.018
-0.235+
(0.063)
(0.027)
(0.143)
(0.077) (0.057)
(0.024)
(0.132)
0.000
0.032**
0.094
-0.050
0.032
0.008
-0.003
(0.018)
(0.011)
(0.059)
(0.035) (0.022)
(0.012)
(0.072)
0.034+
-0.058**
-0.143**
0.013
0.010
-0.011
0.008
(0.018)
(0.011)
(0.052)
(0.030) (0.020)
(0.012)
(0.061)
1941
1801
655
654
1965
1876
583
22
Birth control1
(I)
(II)
b/se
b/se
0.051
0.051
(0.036) (0.036)
0.096
0.095
(0.087) (0.088)
-0.166
-0.165
(0.119) (0.120)
-0.106
-0.107
(0.074) (0.074)
0.087
0.084
(0.108) (0.111)
-0.030+ -0.027
(0.017) (0.023)
-0.004
(0.026)
1237
1237
Observations are conditional on being sexually active
** denotes significance at the .01 level, * at the 0.05 level, and + at the 0.1 level.
Logit coefficients for binary outcomes reflect marginal effects. All regressions control for the age of the younger sibling at the time of the older siblings
teen pregnancy, age of younger sibling interacted with whether older sibling had teen pregnancy, year, race, geographic region, household income in
wave 1, foodstamps in wave 1, lives with mother in wave 1, lives with father in wave 1, and sexual behavior in the before period.
1
Table 8: Impact of sibling’s teen pregnancy by gender composition
All siblings
Sexual Activity
Own teen preg
# Partners1
(I)
(II)
(I)
(II)
(I)
(II)
b/se
b/se
b/se
b/se
b/se
b/se
Same Gender
-0.012
-0.012
-0.004
-0.003
-0.012
-0.011
(0.018) (0.018) (0.012)
(0.012) (0.060) (0.060)
Same*Sib Baby
0.037
0.035
0.005
0.002
-0.357* -0.352*
(0.052) (0.052) (0.031)
(0.030) (0.149) (0.149)
Same*Sib Preg, No baby 0.089
0.084
0.018
0.014
-0.072
-0.088
(0.077) (0.076) (0.045)
(0.043) (0.213) (0.214)
Sibling Baby
0.168** 0.179** 0.059+
0.094* 0.475** 0.491**
(0.051) (0.052) (0.033)
(0.040) (0.123) (0.124)
Sibling Preg, No Baby
0.106
0.121+
0.044
0.085
0.324+ 0.358+
(0.065) (0.068) (0.043)
(0.054) (0.185) (0.189)
w34 tp age norm
0.030** 0.023+ -0.022** -0.036** -0.060* -0.083*
(0.011) (0.013) (0.005)
(0.008) (0.029) (0.038)
w34 tp age int
0.011
0.018*
0.040
(0.013)
(0.008)
(0.044)
N
3908
3908
3689
3689
1238
1238
Table 9: Impact of sibling’s teen pregnancy by age difference
All Siblings
Sexual Activity Teen Pregnancy # Partners1
b/se
b/se
b/se
Age Difference
0.007
0.007+
0.011
(0.007)
(0.004)
(0.025)
Age Diff*Sib Baby
-0.032+
-0.026**
-0.022
(0.019)
(0.010)
(0.058)
Age Diff*Sib preg, no baby
-0.040
-0.026*
-0.101
(0.024)
(0.012)
(0.073)
Sibling Baby
0.240**
0.123**
0.257**
(0.046)
(0.034)
(0.093)
Sibling Pregnant, No Baby
0.227**
0.120**
0.365**
(0.054)
(0.044)
(0.116)
N
3908
3689
1238
1
Use of Birth Control1
b/se
-0.008
(0.015)
0.003
(0.034)
0.043
(0.044)
-0.043
(0.055)
-0.076
(0.069)
1237
Observations are conditional on being sexually active
** denotes significance at the .01 level, * at the 0.05 level, and + at the 0.1 level.
Logit coefficients for binary outcomes reflect marginal effects. All regressions control for the age of the
younger sibling at the time of the older siblings teen pregnancy, age of younger sibling interacted with
whether older sibling had teen pregnancy, gender of both siblings, year, race, geographic region, household
income in wave 1, foodstamps in wave 1, lives with mother in wave 1, lives with father in wave 1, and sexual
behavior in the before period.
23