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
  • "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.