Date & time
Open to PhD students and faculty engaged in causal inference in education research.
From the speaker's bio:
Joshua Hyman is an Assistant Professor in the Department of Public Policy at the University of Connecticut, with a joint appointment in the Department of Educational Leadership in the Neag School of Education. Hyman’s fields of interest are in labor economics, public finance, and the economics of education. His research examines the effects of education policies implemented during primary and secondary school on reducing economic inequality in educational attainment. In past and current work, he has examined the effects on educational attainment of a variety of policies, such as class size during elementary school, Michigan’s requirement that all high school students take the ACT college entrance exam, and Michigan’s 1995 school finance reform. Prior to joining the faculty at the University of Connecticut, Hyman was a Postdoctoral Research Fellow in the Gerald R. Ford School of Public Policy at the University of Michigan. Hyman earned his PhD in Economics and Public Policy and his MA in Economics from the University of Michigan. He earned his BA in Quantitative Economics from Tufts University. Prior to graduate school, he worked as a research assistant at Abt Associates in Cambridge, Massachusetts.
The objective of the Causal Inference in Education Research Seminar (CIERS) is to engage students and faculty from across the university in conversations around education research using various research methodologies.
This seminar provides a space for doctoral students and faculty from the School of Education, Ford School of Public Policy, and the Departments of Economics, Sociology, Statistics, and Political Science to discuss current research and receive feedback on works-in-progress. Discourse between these schools and departments creates a more complete community of education scholars, and provides a networking opportunity for students enrolled in a variety of academic programs who share common research interests. Open to PhD students and faculty engaged in causal inference in education research.