Does money matter? Spending to educate
Open to PhD students and faculty engaged in causal inference in education research.
From the speaker's bio:
Gaurav Khanna is a Ph.D. candidate in Economics at the University of Michigan with interests in Development Economics and Labor Economics. His most recent project studies the impact of affirmative action policies in India, and their effects on incentives for minority-group students; as well as on how the construction of roads allowed for the spread of spatial development. He also has a project that looks at how the Indian government uses public-works programs to tackle socio-political issues like insurgency-related violence.
Past work includes studying the impact of these programs on wages and employment on rural labor markets, and an investigation of seasonal famines in rural Bangladesh. In the US context, he is working with researchers on a project that looks at the labor market impacts of high-skilled immigration, and the influx of international students in US universities.
Prior to starting his Ph.D, Gaurav worked at the World Bank’s Poverty Reduction Unit, and studied the effects of the financial crisis on unemployment and wages across many different countries. He received his M.Sc in Development Economics from Oxford University, and his B.A in Economics from Delhi University.
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.