Using Big Data to Solve Economic and Social Problems

This course provides an introduction to modern applied economics in a manner that does not require any prior background in economics or statistics. It is intended to complement traditional Principles of Economics (Econ 101) courses. Topics include equality of opportunity, education, health, the environment, and criminal justice. In the context of these topics, the course provides an introduction to basic statistical methods and data analysis techniques, including regression analysis, causal inference, quasi-experimental methods, and machine learning.

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Public Economics Lectures

This Ph.D. course covers basic issues in the optimal design of tax and social insurance policies, with emphasis on combining theoretical models with empirical evidence. Topics include efficiency costs and incidence of taxation, income taxation, transfer and welfare programs, public goods and externalities, optimal social insurance (excluding social security), welfare analysis in behavioral models, corporate taxation, and education policy.

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