Abstract
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 language | English |
---|---|
Title of host publication | 26th International World Wide Web Conference, WWW 2017 |
Publisher | International World Wide Web Conferences Steering Committee |
Pages | 73-81 |
Number of pages | 9 |
ISBN (Print) | 9781450349130 |
DOIs | |
State | Published - 2017 |
Event | 26th International World Wide Web Conference, WWW 2017 - Perth, Australia Duration: 3 Apr 2017 → 7 Apr 2017 |
Publication series
Name | 26th International World Wide Web Conference, WWW 2017 |
---|
Conference
Conference | 26th International World Wide Web Conference, WWW 2017 |
---|---|
Country/Territory | Australia |
City | Perth |
Period | 3/04/17 → 7/04/17 |
Bibliographical note
Publisher Copyright:© 2017 International World Wide Web Conference Committee (IW3C2).
Keywords
- Behavioral economics
- Cognitive biases
- Econometrics
- Regret
- Sponsored search auctions