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Ana Reynoso

Assistant Professor of Economics

Ana Reynoso is an applied economist interested in Labor Economics and Economic Development. Most of her research investigates how policy affects marital matching patterns and the gains from marriage for different groups in both developed and developing countries. She also studies the impact of policies affecting teaching practices and school schedules on children's academic and non-academic outcomes. 

For her doctoral dissertation, she received the George Timis Prize for Distinguished Dissertation from Yale University in 2018. This prize is awarded to students whose dissertations demonstrate exceptional and distinguished accomplishment. Her dissertation built upon her previous papers, “Marriage, marital investments, and divorce: theory and evidence on policy non neutrality,” and “The impact of divorce laws on the equilibrium in the marriage market.”

She also received the Ryoichi Sasakawa Young Leaders Fellowship for 2013-14. The fellowship supports students whose areas of concentration fall within the parameters of the social sciences and humanities. Additional academic achievements include receiving Yale University Cowles Foundation Fellowship, Yale University Graduate Fellowship, Full merit-based tuition award, Universidad de San Andres, Diploma de honor (magna cum laude) and UBACyT Graduate Fellowship, Universidad de Buenos Aires.

Ana has been drawn to teaching since high school. She began tutoring classmates so that they could develop a better understanding of the material and pass rigorous exams. With her continuing passion for education, she became a teaching fellow and advised seniors in economics on their undergraduate theses at Yale.  Joining the University of Michigan in the fall term of 2018, she will begin as an assistant professor, teaching Economics 420, Topics in Labor Economics: Analysis of Modern Labor Markets. One of the objectives will be learning how to use economic models to frame the relevant questions and obtain theoretical predictions, and to analyze real-life data to answer those questions and interpret the results.