Event Date: Thursday, November 8, 2018
Simplifying Matching Methods for Causal Inference
Gary King, Harvard University
Thursday, November 8, 2018 @ 2:00 pm
SSC 6210
We show how to use matching in causal inference to ameliorate model dependence -- where small, indefensible changes in model specification have large impacts on our conclusions. We introduce matching methods that are simpler, more powerful, and easier to understand than existing approaches. We also show that propensity score matching, an enormously popular method, often accomplishes the opposite of its intended goal -- increasing imbalance, inefficiency, model dependence, and bias -- and should not be used in applications. See http://bit.ly/causeI for papers and easy-to-use software to implement all methods discussed.
Gary King is the Albert J. Weatherhead III University Professor at Harvard University -- one of 26 with Harvard's most distinguished faculty title -- and Director of the Institute for Quantitative Social Science. King develops and applies empirical methods in many areas of social science research, focusing on innovations that span the range from statistical theory to practical application.