Northwestern and Duke law schools, along with the Society for Empirical Legal Studies, will co-sponsor the 9th annual Research Design for Causal Inference workshops. Co-organized by Bernie Black (Northwestern) and Matthew McCubbins (Duke) and hosted at Northwestern's Pritzker School of Law, in Chicago, IL, the Main workshop is set for June 18-22, 2018, with an Advanced workshop following on June 25-27, 2018 (also in Chicago).
As the workshop overview notes, "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." To these ends, the Main workshop will cover the basics of causal inference, including potential outcomes, matching; difference-in-differences, instrumental variables, and regression discontinuity designs. The Advanced workshop will focus on principal stratification (a generalization of causal IV analysis), advanced matching with panel data, and application of machine learning to causal inference.
Both workshops feature an outstanding faculty and provide an excellent and efficient way to become acquainted with contemporary approaches for making causal inferences from various kinds of observational and experimental data. For those seeking additional registration information click here.