Kathleen Li
Assistant Professor
Department: Marketing
Industry Areas: E-Commerce, Marketing Metrics
Research Areas: Clicks and Mortars, Empirical Methods, Marketing Models, Public Policy, Statistical Analysis
Kathleen (Kathy) Li is an assistant professor in the marketing department of the McCombs School of Business, the University of Texas at Austin. She is quantitative modeler whose research interests are both methodological and substantive. The methodological stream of her research includes developing and improving econometric methods for policy evaluation, and the asymptotic theory necessary for inference. The substantive stream of her research lies in emergent consumer behavior on the Internet and its interaction with offline environment, and how this affects patterns of demand for different products. Both research streams are reflected in her dissertation titled “Three Essays on Estimating Average Treatment Effects in Quasi-Experimental Panel Data.” Her research has been published in the Journal of the American Statistical Association and the Journal of Econometrics.
She received her MS and PhD in marketing from The Wharton School at the University of Pennsylvania and her BA in Economics, Mathematics and Statistics from Rice University.
ACADEMIC LEADERSHIP & AWARDS
2018 |
Professional Awards Wharton Marketing Graduate Fellowship, 2011-14, 2016-2018
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2018 |
John A. Howard / AMA Doctoral Dissertation Award, American Marketing Association
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2017 |
INFORMS Doctoral Consortium Fellow
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Publications
Kathleen Li, and Venkatesh Shankar. Two-Step Synthetic Control Approach for Estimating Casual Effects of Marketing Events. Management Science. Forthcoming.
Kathleen T Li and Garrett Sonnier. 2022. Statistical Inference for Factor Model Approach to Estimate Causal Effects in Quasi-Experimental Settings. Journal of Marketing Research, forthcoming.
Kathleen T Li and Christophe Van den Bulte. 2022. Augmented Difference-in-Differences. Marketing Science, forthcoming.
Kathleen T Li. 2020. Statistical Inference for Average Treatment Effects Estimated by Synthetic Control Methods. Journal of the American Statistical Association 115(532), 2068-2083.
Kathleen T Li and David R. Bell. 2017. Estimation of Average Treatment Effects with Panel Data: Asymptotic Theory and Implementation. Journal of Econometrics 197, 65-75.