Duncan Simester

About

Duncan Simester is a Professor at the MIT Sloan School of Management where he holds the NTU Chair in Management Science and serves as the Chair of the MIT Evening MBA Task Force. He is an expert on how economics and artificial intelligence can contribute to the understanding and practice of marketing and strategy. His work is widely published in the academic literature, often relying on industry participation and large-scale field experiments conducted with cooperating firms. Prior to joining MIT, Duncan was a professor at the University of Chicago’s Graduate School of Business. He is also a qualified lawyer and a member of the bar in New Zealand. Duncan holds a PhD from MIT and has received notable honors including the 2020 Weitz-Winer-O’Dell Award from the American Marketing Association and the 2022 INFORMS Society for Marketing Science Fellow Award, recognizing his significant contributions to marketing research, theory, methodology, and practice.

Research topics

• Computer Science
• Economics
• Business
• Management science
• Computer Security
• Political Science
• Mathematics
• Marketing
• Process management
• Monetary economics

Selected publications

• Belief Disagreement and Portfolio Choice

  The Journal of Finance · 2022 · 181 citations

  Senior authorCorresponding

  ABSTRACT Using proprietary financial data on millions of households, we show that likely‐Republicans increased the equity share and market beta of their portfolios following the 2016 presidential election, while likely‐Democrats rebalanced into safe assets. We provide evidence that this behavior was driven by investors interpreting public information based on different models of the world. We use detailed controls to rule out the main nonbelief‐based channels such as income hedging needs, prefer…

  PublisherDOI

• Targeting Prospective Customers: Robustness of Machine-Learning Methods to Typical Data Challenges

  Management Science · 2019-11-15 · 131 citations

  article1st authorCorresponding

  We investigate how firms can use the results of field experiments to optimize the targeting of promotions when prospecting for new customers. We evaluate seven widely used machine-learning methods using a series of two large-scale field experiments. The first field experiment generates a common pool of training data for each of the seven methods. We then validate the seven optimized policies provided by each method together with uniform benchmark policies in a second field experiment. The findin…

  PublisherDOI

• Belief Disagreement and Portfolio Choice

  National Bureau of Economic Research · 2018-09-01 · 88 citations

  reportSenior author

  Using proprietary portfolio data on millions of households, we show that (likely) Republicans increase the equity share and market beta of their portfolios following the 2016 presidential election, while (likely) Democrats rebalance into safe assets.We provide evidence that this behavior is driven by investors interpreting public information using different models of the world, by ruling out the main non-belief-based channels (like income hedging needs, preferences, local economic exposure) usin…

  PublisherDOI

• Informational rigidities and the stickiness of temporary Sales

  Journal of Monetary Economics · 2017-06-22 · 88 citations

  articleOpen access
  PublisherOA PDFDOI

• Efficiently Evaluating Targeting Policies: Improving on Champion vs. Challenger Experiments

  Management Science · 2020 · 55 citations

  1st authorCorresponding

  Champion versus challenger field experiments are widely used to compare the performance of different targeting policies. These experiments randomly assign customers to receive marketing actions recommended by either the existing (champion) policy or the new (challenger) policy, and then compare the aggregate outcomes. We recommend an alternative experimental design and propose an alternative estimation approach to improve the evaluation of targeting policies. The recommended experimental design…

  PublisherOA PDFDOI

Frequent coauthors

• Eric T. Anderson

  Northwestern University

  33 shared

• John R. Hauser

  Massachusetts Institute of Technology

  21 shared

• Florian Zettelmeyer

  16 shared

• Meghan R. Busse

  14 shared

• Birger Wernerfelt

  Massachusetts Institute of Technology

  13 shared

• Erik Brynjolfsson

  National Bureau of Economic Research

  13 shared

• Spyros I. Zoumpoulis

  Decision Sciences (United States)

  11 shared

• Olivier Toubia

  Columbia University

  8 shared

Awards & honors

• 2020 Weitz-Winer-O’Dell Award from the American Marketing As…
• 2022 INFORMS Society for Marketing Science (ISMS) Fellow Awa…

Similar researchers at Massachusetts Institute of Technology

• Catherine Tuckerh-60
• Drazen Prelech-43