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Regular version of the site
Article
The impact of pandemic-driven care redesign on hospital efficiency

Jakovljević M., Timofeyev Y., Zhuravleva T.

Risk Management and Healthcare Policy. 2024. Vol. 17. P. 1477-1491.

Book chapter
Veto Core Consistent Preference Aggregation

Aleksei Y. Kondratev, Ianovski E.

In bk.: AAMAS '24: Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems. Auckland: International Foundation for Autonomous Agents and Multiagent Systems, 2024. P. 1020-1028.

Working paper
Equilibrium existence and uniqueness in additive trade models

Slepov Fedor, Kokovin S. G.

Basic research program. WP BRP. National Research University Higher School of Economics, 2023. No. 262/EC/2023.

Professor Svetlana Boyarchenko

We are glad to announce forthcoming open research seminar of St Petersburg School of Economics and Management with support from European University in St Petersburg. Professor Svetlana Boyarchenko (The University of Texas at Austin) will present his paper «STRATEGIC EXPERIMENTATION WITH ERLANG BANDITS». The seminar will take place on March, 10, 2017, at 17:30, at Kantemirovskaya 3A, room 343.
If you would like to attend the seminar, please send your name and affiliation to: ykaprova@hse.ru.
Abstract:

While risks related to events that arrive randomly play important role in many real life decisions, models of learning and experimentation based on twoarmed Poisson bandits remain mostly abstract theoretical models with few economic applications. We suggest a new class of models of strategic experimentation which are almost as tractable as exponential models, but incorporate such realistic features as dependence of the expected rate of news arrival on the time elapsed since the start of an experiment and judgement about the quality of a “risky” arm based on evidence of a series of trials as opposed to a single evidence of success or failure as in exponential models with conclusive experiments. We demonstrate that, unlike in the exponential models, players may stop experimentation before the first breakdown happens. Moreover, ceteris paribus, experimentation in a model with breakthroughs may last longer than experimentation in the corresponding model with breakdowns.