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Kim et al. Receive Journal of Marketing Research 2020 Green Award

Kim et al. Receive Journal of Marketing Research 2020 Green Award

Sungjin Kim, Clarence Lee, and Sachin Gupta have been selected to receive the Paul E. Green Award for their article “Bayesian Synthetic Control Methods,” which appeared in the October issue (Volume 57, No. 5) of Journal of Marketing Research (JMR).

The Paul E. Green Award recognizes the article in JMR that demonstrates the greatest potential to contribute to the theory, methods, and practice of marketing.  It honors the S.S. Kresge Professor Emeritus of Marketing at the Wharton School at the University of Pennsylvania. On behalf of the AMA, this year’s Green Award selection process was managed by Professor Michel Wedel, Distinguished University Professor at the Robert H. Smith School of Business at the University of Maryland. The committee overseeing the selection process consisted of Russ Winer (New York University), Kusum Ailawadi (Dartmouth College)and Mary Frances Luce (Duke University). ​In recognizing the winning paper, the committee made the following comment:


In their paper, “Bayesian Synthetic Control Methods,” Kim et al. significantly improve the application of synthetic control methods (SCMs) to marketing and other social science problems where the lack of a randomized control group inhibits the ability to estimate the treatment effect.  SCMs are very useful tools for such quasi-experimental research that creates a “synthetic” control unit as a weighted average of a set of controls where the weights are determined by getting as close as possible to the pre-treatment outcome in the treatment unit.  It has three limitations: restrictive constraints on the weights, no formal theory for statistical inference, and what is called the “large p, small n” sparsity problem, in which there are more parameters than observations.

The significant contribution of this paper is the use of Bayesian methods to address these three limitations. It relaxes the constraints on the weights, provides exact statistical inference, and uses shrinkage priors to solve the sparsity problem.  In addition, the authors’ methods incorporate analogs of the frequentist SCM variants used in prior research.  The authors provide computer code for their SCM approach so that it can be implemented by practitioners and other academics.  With respect to the practical applications, the example in the paper of the impact of a soda tax imposed on Washington State consumers in 2010 illustrates how their method can be applied in the real world.  Thus, the paper makes important advances both methodologically and substantively as it gives analysts a new tool to improve the measurement of the causal effects of a variety of marketing, policy, and other interventions where randomized controlled tests are either infeasible or expensive.

In addition to the winning paper, the three other excellent finalists for the award were as follows: