Northwestern University, University of Southern California, and the Society for Empirical Legal Studies is holding the third (annual) workshop on Research Design for Causal Inference, August 6-10, 2012, at Northwestern University.
Note: Registration is almost full (as of April 13).
QUESTIONS ABOUT THE WORKSHOP: Please email Bernie Black (bblack[@]northwestern.edu) or Mat McCubbins (mmccubbins[@]law.usc.edu) for substantive questions or fee waiver requests, and Michael Cooper (causalinference[@]law.northwestern.edu) for logistics and registration. im
Overview: 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 simulations and quasi-experiments, where part of the sample is “treated” in some way, and 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 kinds of causal inferences one can and cannot draw from a research design, threats to valid inference, and research designs that can mitigate those threats.
Most empirical methods courses begin with the methods. They survey how each method works, and what assumptions each relies on. We will begin instead with the goal of causal inference, and discuss how to design research to come closer to that goal. The methods reflect the goal and are often adapted to the needs of a particular study. Some of the methods we will discuss are covered in PhD programs, but rarely in depth, and rarely with a focus on causal inference and on which methods to prefer for messy, real-world datasets with limited sample sizes.
Each day will include a Stata “workshop” where we illustrate selected methods with real data and Stata code.
TARGET AUDIENCE: Quantitative empirical researchers (faculty and graduate students) in social science, including law, political science, economics, many business-school
