QUANTITATIVE RESEARCH METHODS WORKSHOP
Abstract: Social scientists often possess fragmented information about subsets and aspects of the complex causal processes they study. Research on police-civilian interactions, for example, is complicated not only by undocumented interactions, but inconsistent recording of events within documented interactions. These data constraints can lead to a proliferation of incompatible analytic approaches relying on contradictory unstated assumptions, impeding scientific progress on important questions like the severity of racial bias in policing. Nonparametric sharp bounds, or the tightest possible range of answers consistent with available data, offer a path forward: claims outside the bounds can be immediately rejected, and claims inside the bounds must explicitly justify the additional assumptions that enable tightening. However, we show proving sharpness is NP-hard for broad classes of data constraints and causal quantities, rendering this approach computationally infeasible for even moderately sized causal processes. We present an efficient spatial branch-and-bound procedure with a theoretical guarantee that we term “ε-sharpness,” indicating the worst-case looseness factor of the relaxed bounds relative to the (unknown) completely sharp bounds. The procedure is guaranteed to attain complete sharpness with sufficient computation time. We present results on asymptotic validity of and conservative statistical inference for ε-sharp bounds. The technique is illustrated using simulations using common research designs in the study of policing. Co-authored with Guilherme Duarte and Jonathan Mummolo.
Dean Knox is an assistant professor in Operations, Information, and Decisions at the Wharton School of the University of Pennsylvania. He studies policing, ethnic politics, and political communication. He also develops quantitative models and methods for new forms of social science data. These new sources include many forms of data previously thought to be too unstructured to study: audiovisual data conveying human emotion, path data for sequential decision-making, and mobile location data on movement and social interaction.
Dean’s research has appeared or is forthcoming in Science, the Journal of the American Statistical Association, the Proceedings of the National Academy of Sciences, and the American Political Science Review. It has received the Gosnell Prize for excellence in political methodology, the John T. Williams dissertation prize, and the best poster award by the Society for Political Methodology.
Please visit policingresearch.org for work by his group, Research on Policing Reform and Accountability, co-founded with Jonathan Mummolo. He is also a faculty fellow at Analytics at Wharton and an affiliate of the Quattrone Center for the Fair Administration of Justice.
This virtual workshop is open to the Yale community. To receive Zoom information, you must subscribe to the Quantitative Research Methods Workshop at this link: https://csap.yale.edu/quantitative-research-methods-workshop.
The series is sponsored by the ISPS Center for the Study of American Politics and The Whitney and Betty MacMillan Center for International and Area Studies at Yale with support from the Edward J. and Dorothy Clarke Kempf Fund.
This speaker is also being cosponsored with the Leitner Political Economy Seminar.