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A list of all the posts and pages found on the site. For you robots out there, there is an XML version available for digesting as well.
Pages
Posts
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publications
Measuring Long-Run Marketing Effects and Their Implications for Long-Run Marketing Decisions
Bronnenberg, B., Dubé, J. P., Mela, C., Albuquerque, P., Erdem, T., Gordon, B. R., Hanssens, D., Hitsch, G., Hong, H., & Sun, B. (2008). "Measuring Long-Run Marketing Effects and Their Implications for Long-Run Marketing Decisions." Marketing Letters. 19, 367-382.
A Dynamic Model of Consumer Replacement Cycles in the PC Processor Industry
Gordon, B. R. (2009). "A Dynamic Model of Consumer Replacement Cycles in the PC Processor Industry." Marketing Science. 28(5), 846-867.
Drs. Muth and Mills Meet Dr. Tiebout: Integrating Location-Specific Amenities into Multi-Community Equilibrium Models
Epple, D., Gordon, B. R., & Sieg, H. (2010). "Drs. Muth and Mills meet Dr. Tiebout: Integrating Location-Specific Amenities into Multi-Community Equilibrium Models." Journal of Regional Science. 50(1), 381-400.
A New Approach to Estimating the Production Function for Housing
Epple, D., Gordon, B. R., & Sieg, H. (2010). "A New Approach to Estimating the Production Function for Housing." American Economic Review. 100(3), 905-924.
Competitive Strategy for Open Source Software
Kumar, V., Gordon, B. R., & Srinivasan, K. (2011). "Competitive Strategy for Open Source Software." Marketing Science. 30(6), 1066-1078.
Revisiting the Workshop on Quantitative Marketing and Structural Econometrics
Gordon, B. R., Thomadsen, R., Bradlow, E. T., Dubé, J. P., & Staelin, R. (2011). "Revisiting the Workshop on Quantitative Marketing and Structural Econometrics." Marketing Science. 30(6), 945-949.
Does AMD Spur Intel to Innovate More?
Goettler, R. L. & Gordon, B. R. (2011). "Does AMD spur Intel to innovate more?." Journal of Political Economy. 119(6), 1141-1200.
Download Paper | Preprint (PDF)
Marketing and Politics: Models, Behavior, and Policy Implications
Gordon, B. R., Lovett, M., Shachar, R., Arceneaux, K., Moorthy, S., Peress, M., Rao, A., Sen, S., Soberman, D., & Urminsky, O. (2012). "Marketing and Politics: Models, Behavior, and Policy Implications." Marketing Letters. 23(2), 391-403.
Advertising Effects in Presidential Elections
Gordon, B. R. & Hartmann, W. (2013). "Advertising Effects in Presidential Elections." Marketing Science. 32(1), 19-35.
Does Price Elasticity Vary with Economic Growth? A Cross-Category Analysis
Gordon, B. R., Goldfarb, A., & Li, Y. (2013). "Does Price Elasticity Vary with Economic Growth? A Cross-Category Analysis." Journal of Marketing Research. 50(1), 4-23.
Competition and Product Innovation in Dynamic Oligopoly
Goettler, R. L. & Gordon, B. R. (2014). "Competition and Product Innovation in Dynamic Oligopoly." Quantitative Marketing and Economics. 12(1), 1-42.
A Dynamic Model of Rational Addiction: Evaluating Cigarette Taxes
Gordon, B. R. & Sun, B. (2015). "A Dynamic Model of Rational Addiction: Evaluating Cigarette Taxes." Marketing Science. 34(3), 452-470.
Multiplicity of Equilibria and Information Structures in Empirical Games: Challenges and Prospects
Borkovsky, R., Ellickson, P., Gordon, B. R., Aguirregabiria, V., Gardete, P., Grieco, P., Gureckis, T., Ho, T. H., Mathevet, L. & Sweeting, A. (2015). "Multiplicity of Equilibria and Information Structures in Empirical Games: Challenges and Prospects." Marketing Letters. 26(2), 115-125.
Advertising Competition in Presidential Elections
Gordon, B. R. & Hartmann, W. R. (2016). "Advertising Competition in Presidential Elections." Quantitative Marketing and Economics. 14(1), 1-40.
LETTER: Field studies of psychologically targeted ads face threats to internal validity
Eckles, D., Gordon, B. R., & Johnson, G. A. (2018). "LETTER: Field studies of psychologically targeted ads face threats to internal validity." Proceedings of the National Academy of Sciences. 115(23), E5254-E5255.
An Empirical Study of National vs. Local Pricing by Chain Stores under Competition
Li, Y., Gordon, B. R., & Netzer, O. (2018). "An Empirical Study of National vs. Local Pricing by Chain Stores under Competition." Marketing Science. 37(5), 812-837.
A Comparison of Approaches to Advertising Measurement: Evidence from Big Field Experiments at Facebook
Gordon, B. R., Zettelmeyer, F., Bhargava, N., & Chapsky, D. (2019). "A Comparison of Approaches to Advertising Measurement: Evidence from Big Field Experiments at Facebook." Marketing Science. 38(2), 193-225.
Inefficiencies in Digital Advertising Markets
Gordon, B. R., Jerath, K., Katona, Z., Narayanan, S., Shin, J., & Wilbur, K. C. (2021). "Inefficiencies in Digital Advertising Markets." Journal of Marketing. 85(1), 7-25.
Digitization and Flexibility: Evidence from the South Korean Movie Market
Yang, J., Anderson, E. T., & Gordon, B. R. (2021). "Digitization and Flexibility: Evidence from the South Korean Movie Market." Marketing Science. 40(5), 821-843.
Disentangling Ad Tone Effects on Voter Turnout and Candidate Choice in Presidential Elections
Gordon, B. R., Lovett, M. J., Luo, B., & Reeder, J. C. (2023). "Disentangling Ad Tone Effects on Voter Turnout and Candidate Choice in Presidential Elections." Management Science. 69(1), 220-243.
Close Enough? A Large-Scale Exploration of Non-experimental Approaches to Advertising Measurement
Gordon, B. R., Moakler, R., & Zettelmeyer, F. (2023). "Close Enough? A Large-Scale Exploration of Non-experimental Approaches to Advertising Measurement." Marketing Science. 42(4), 768-793.
Predicted Incrementality by Experimentation (PIE) for Ad Measurement
Gordon, B. R., Moakler, R., & Zettelmeyer, F. (2025). "Predicted Incrementality by Experimentation (PIE) for Ad Measurement." arXiv preprint arXiv:2304.06828.
Multicell experiments for marginal treatment effect estimation of digital ads
Waisman, C. & Gordon, B. R. (2025). "Multicell experiments for marginal treatment effect estimation of digital ads." Management Science. (forthcoming).
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Personalization and Targeting: How to Experiment, Learn & Optimize
Lemmens, A., Roos, J., Gabel, S., Ascarza, E., Bruno, H., Gordon, B. R., Israeli, A., Feit, E. M., Mela, C., & Netzer, O. (2025). "Personalization and Targeting: How to Experiment, Learn & Optimize." International Journal of Research in Marketing, forthcoming.
Amazon Ads Multi-Touch Attribution
Lewis, R., Zettelmeyer, F., Gordon, B. R., Garib, C., Hermle, J., Perry, M., Romero, H. and Schnaidt, G. (2025). "Amazon Ads Multi-Touch Attribution." arXiv preprint arXiv:2508.08209.
Characterizing and Minimizing Divergent Delivery in Meta Advertising Experiments
Burtch, G., Moakler, R., Gordon, B. R., Zhang, P., and Hill, S. (2025). "Characterizing and Minimizing Divergent Delivery in Meta Advertising Experiments." arXiv preprint arXiv:2508.21251.
teaching
Retail Analytics and Pricing (MKTG-462-0)
MBA course, Kellogg School of Management, 1900
This course will teach you how to use analytics and data to address decisions faced by retailers and manufacturers. Pricing and promotion decisions are emphasized, with additional coverage on topics such as private labels, product assortment, trade funding, shopper marketing, and more. The course is organized around a hierarchy of topics. We spend roughly one week understanding pricing and promoting to an individual customer. This analysis provides the foundation as we move to more aggregate decisions, such as setting regular and promoted prices at the product level, managing category pricing, and understanding the drivers of store traffic. As we progress through this hierarchy of decisions, we illustrate how different types of data can—or can’t—be used to answer managerial questions. A key part of the class is understanding the limitations of different types of data and how better planning can both simplify the analytics and increase your confidence in the findings. This class is very practical and hands-on. Most of the data we analyze is from real-world managerial problems, through collaborations with leading retailers and consulting firms who have brought problem-driven challenges to the classroom. Weekly homework assignments, both individual and group, are paired with in-class cases. There is no final exam.