Northwestern and Duke Universities will hold their 8th annual week-long workshop on Research Design for Causal Inference, at Northwestern University from June 19-23, 2017. Organized by Bernie Black (Northwestern) and Mat McCubbins (Duke), the workshop features an outstanding faculty and is an excellent and efficient way to become acquainted with contemporary approaches for making causal inferences from various kinds of observational and experimental data. Details and registration information can be found here. A brief overview follows:
"Research design for causal inference is at the heart of a 'credibility revolution' in empirical research. We will cover the design of true randomized experiments and contrast them to natural or quasi experiments and to pure observational studies, where part of the sample is treated in some way, the remainder is a control group, but the researcher controls neither the assignment of cases to treatment and control groups nor administration of the treatment. We will assess the causal inferences one can draw from a research design, threats to valid inference, and research designs that can mitigate those threats."
Monday, June 19 (Don Rubin): Introduction to Modern Methods for Causal Inference
Tuesday, June 20 (Alberto Abadie): Designs for “Pure” Observational Studies
Wednesday, June 21 (Alberto Abadie): Instrumental variable methods
Thursday, June 22 (Jens Hainmueller): Panel Data and Difference-in-Differences
Friday morning, June 23 (Jens Hainmueller): Regression Discontinuity
Friday afternoon: Feedback on your own research