Michaela Gulemetova-Swan

PhD candidate
Department of Economics
University of Pennsylvania
160 McNeil Building
3718 Locust Walk
Philadelphia PA 19104-6297
Phone: (267) 240 7193
Email: gulemeto@econ.upenn.edu
Home
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- "Evaluating the impact of Oportunidades on timing of first sex, marriage and fertility among urban
adolescents" (job market paper).
This paper analyzes the effect of conditional cash transfers on adolescent decisions about
marriage and fertility. I use data from the 2002-2004 evaluation study of the urban Oportunidades
program which is a nationwide anti-poverty program in Mexico that aims to
improve education, health and nutrition through conditional cash transfers and health education.
To avoid the problem of selection bias on decision to participate in the program,
treatment is defined as the offer of Oportunidades, rather than actual participation, and
I focus on intent-to-treat parameters, measuring the program impact on outcomes related
to fertility and marriage. In contrast with previous evaluation studies, I adopt a multistate
hazard modeling approach to evaluate the program's effect on the timing of first sex, first
marriage, and first and second births by adolescents. Baseline duration dependence in this
model is captured by fexible splines transformation. The model allows for the timing of
events to depend on the timing of previous events and incorporates unobservables in the
form of a permanent unobserved component that enters into the different equations with
factor loadings. I find that the offer of the Oportunidades significantly delays the timing of
pre-marital sex as well as of marital sex. Young women living in intervention areas marry
much later and as a consequence delay significantly the first and second births. In general,
I find that a hazard modeling approach proves to be a useful way of discerning program
effects.
- "Fertility, Dropout and Graduation: Exploring the Impact of Teen Motherhood on Educational
Outcomes in Philadelphia" (joint with Liza Herzog and Elizabeth Farley-Ripple) 2008.
In 2006, the teen birth rate in the United States rose for the first time since 1991, demanding renewed efforts to examine the relationship between teen fertility and educational outcomes. This paper considers the relative timing of first birth, dropout, and high school completion, utilizing contemporary data drawn from the School District of Philadelphia, Philadelphia Educational Longitudinal Study, student medical records, and federal census data. We conduct hazard analyses to estimate the impact of childbearing on graduation while accounting for the continuity of students education—that is, whether or not they drop out of school. Findings suggest that although teen childbearing presents a challenge to completing high school, dropping out is the critical event determining teens likelihood of graduating.
- "Application of Sibling Differencing Estimator: Reform Impact on School Enrollment in Slovakia" 2006.
There is consensus in the literature of Eastern European Roma minorities high
vulnerability to poverty. Roma lower school enrollment and educational attainment are
shown to be a major determinant of their lower competitiveness on the labor market and
their high dependence on social welfare assistance. In order to address this problem and
to create new incentives to invest in education, the government of the Slovak Republic
implemented in 2004 a major reform which included a cut in child benefits compensated
by stipends conditional on school enrollment for low-income families. This paper
attempts to estimate an early program impact of this reform on school enrollment of poor
Roma in Slovakia by applying the within-family siblings differencing estimator of
Parker, Todd and Wolpin (2005). A simple behavioral model of parental schooling
decisions motivates a reduced-form model for estimation. The Slovak cross-sectional
data is augmented to a short panel by generating missing schooling histories, under
several assumptions. Despite the lack of a true panel, the empirical results show positive
treatment effect. For comparison purposes, the cross-section, the before-after and the
difference-in-difference estimators of program impact are computed as well.
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