IIMA - Course Catalogue
Quantitative Methods for Causal Inference in Social Policy
Prof. Ankur Sarin,
Prof. Ambrish Dongre
Course Description & Objectives
The search for causality in relationship between variables is as frustrating as it is necessary. As elusive as they might be, claims about causality form the basis of much policy advice and advance our understanding of factors influencing human development. Relatively recent advances in the development and application of quantitative methods in identifying and estimating causal relationships also make this an exciting and productive line of research.
The methods covered will include experiments, ‘natural’ experiments, instrument variables, regression discontinuity designs, propensity score matching and value-add models.
The course emphasizes a close reading and discussion of research papers that are generally considered to be good representatives of the application of these methods as well as those that lend themselves to ideas for future work.
The purpose of this course will be introduce, explain and study the application of these techniques in the specific context of gathering evidence on different dimensions of education. Specific goals would be:
Introduce participants to methods that are at the cutting edge of quantitative empirical research
Learn to critique and develop on existing research in the area
Learn to practically apply methods
Develop an independent research project based on the ideas in the course
In doing so, participants will also encounter literature on evidence on substantive issues in education, including the relationship between resources and outcomes, comparison between private and public schools , use of affirmative action, intergenerational transmission of inequality and data-driven methods to improve accountability.
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