IISER MOHALI

Drawing Causal inference assumes the central focus of any social science research. However, the reliability and credibility of causal inference require experimental data that allow for the random assignment of treatment. In social science, we mostly work with observed data in which treatment assignments are not random; rather, treatments happen due to selection. I will discuss these in two sessions. In the first session, I would like to show you how and when regression analysis can make sense and when it cannot.

About the Speaker: Dr. Sabuj Kumar Mandal is currently working as an Associate Professor of economics in the Department of Humanities and Social Sciences, Indian Institute of Technology Madras (IITM), Chennai. He completed his B.Sc (Economics) from the Scottish Church College, Kolkata, and M.Sc (Economics) from the University of Calcutta with a specialisation in Econometrics and Environmental and Resource Economics. He completed his doctoral degree in economics from the Institute for Social and Economic Change, Bangalore. His teaching and research interests include Applied Econometrics, Energy and Environmental Economics (efficiency analysis), Oil price shocks and stock market behaviour, Climate Change and Migration, Corporate Social Responsibility and Firm Performance, and behavioural and experimental economics. He has several national and international publications to his credit, including Energy Policy, World Development, Journal of Development Studies, Journal of Policy Modelling, Water Resources and Economics, Energy Efficiency, and Scientific Reports. He was awarded the Young Economist Award 2015 by the Indian Econometric Society for his contribution to quantitative economics. He was awarded the Fulbright Nehru Academic and Professional Excellence Award 2020-21 (research category) and was affiliated with Arizona State University for collaborative research.