KIER 京都大学経済研究所 Kyoto Institute of Economic Research

JP

Events

Microeconomics and Game Theory

Category
Date
Title
Presenter/Location
Details
Micro/Game
2025/03/17 Mon
17:00〜18:30
Constitutional Rules, Government Formation, and Cabinet Survival (joint with Daniel Diermeier, Chris Li, and Jun Zhao)
Tong Li (Vanderbilt University)
本館1階会議室
Micro/Game
2025/01/30 Thu
17:00〜18:30
A model of job-stress and burnout
Kieron Meagher (Australian National University)
本館1階会議室
Micro/Game
2025/01/17 Fri
11:00〜12:30
[応用ミクロ経済学セミナーと共催]
Designing an Immigrant Social Integration Policy
Yujung Hwang (Johns Hopkins University)
法経東館1階 108演習室
Micro/Game
2025/01/09 Thu
17:00〜18:30
Coalitional Stability in Games with Additive Dyadic Social Interactions (with Michel Le Breton and Shlomo Weber)
Hideo Konishi (Boston College)
本館1階会議室
Micro/Game
2024/12/26 Thu
17:00〜18:30
Who gets the bonus? Affirmative Action Reforms in High School Admissions in China
Tong Wang (Ritsumeikan University)
本館1階会議室
Micro/Game
2024/12/25 Wed
12:00〜13:00
From Behavioral Economicus (BE) to Intelligence Economicus (IE)
Soo Hong Chew (National University of Singapore)
本館1階会議室
Micro/Game
2024/12/23 Mon
12:00〜13:00
The Taxation Principle(s) with Unobservable Actions
Bruno Strulovici (Northwestern University)
本館1階会議室
Micro/Game
2024/12/19 Thu
17:00〜18:30
Certainty equivalent and uncertainty premium of time-to-build (with Michi Nishihara)
Haejun Jeon (Tokyo University of Science)
本館1階会議室
Micro/Game
2024/12/12 Thu
17:00〜18:30
Signaling in repeated delegation
Wing Suen (The University of Hong Kong)
本館1階会議室

Abstract: In one-shot delegation the principal optimally imposes an upper bound on actions when the agent is possibly upward-biased. In repeated delegation a biased type has greater incentive to signal her honesty in the early period than an honest type to induce the principal to relax the upper bound in the later period. Both types are locked in a signaling race and pool at downward-distorted actions in equilibrium. The optimal delegation set in the early period imposes a binding action lower bound despite the agent’s upward bias. The optimal action upper bound is less restrictive than that in a one-shot game.

Micro/Game
2024/12/05 Thu
17:00〜18:30
Using Big Data and Machine Learning to Uncover How Players Choose Mixed Strategies
Akira Matsushita (Kyoto University)
本館1階会議室
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