An experimental evaluation of regret-based econometrics

Noam Nisan, Gali Noti

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Using data obtained in a controlled ad-auction experiment that we ran, we evaluate the regret-based approach to econometrics that was recently suggested by Nekipelov, Syrgkanis, and Tardos (EC 2015). We found that despite the weak regret-based assumptions, the results were (at least) as accurate as those obtained using classic equilibrium-based assumptions. En route we studied to what extent humans actually minimize regret in our ad auction, and found a significant difference between the “high types” (players with a high valuation) who indeed rationally minimized regret and the “low types” who significantly overbid. We suggest that correcting for these biases and adjusting the regret-based econometric method may improve the accuracy of estimated values.

Original languageAmerican English
Title of host publication26th International World Wide Web Conference, WWW 2017
Number of pages9
StatePublished - 2017
Event26th International World Wide Web Conference, WWW 2017 - Perth, Australia
Duration: 3 Apr 20177 Apr 2017

Publication series

Name26th International World Wide Web Conference, WWW 2017


Conference26th International World Wide Web Conference, WWW 2017


  • Behavioral economics
  • Cognitive biases
  • Econometrics
  • Regret
  • Sponsored search auctions

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Networks and Communications


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