Webinar Series
The Efficiency of a Dynamic Decentralized Two-sided Matching Market
This paper studies a decentralized dynamic matching market by using data from a large ride-sharing platform to estimate a model of search and matching between drivers and passengers. The authors measure the preferences for trips and waiting costs of passengers and drivers. The authors assess whether and to what extent centralized algorithms that require different information sets can improve efficiency, and the authors show that information on agent preferences and search lengths are particularly important for the platform to implement algorithms that increase revenue and the total surplus of drivers and passengers.
2022
Session Chair: Mitsuru IGAMI
Associate Professor of Economics, Yale University
Speakers
Session Format
Each session lasts for 1 hour 10 minutes (25 minutes for the author, 25 minutes for the discussion and 20 minutes for participants' Q&A). Please note that this webinar will be governed by the Chatham House Rule.
Registration
Registration has closed. Please visit the main page for details on next webinar.