| 研究課題/領域番号 |
17K03634
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| 研究機関 | 早稲田大学 |
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研究代表者 |
Veszteg Robert 早稲田大学, 政治経済学術院, 准教授 (30597753)
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| 研究分担者 |
船木 由喜彦 早稲田大学, 政治経済学術院, 教授 (50181433)
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| 研究期間 (年度) |
2017-04-01 – 2020-03-31
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| キーワード | decentralization / bargaining / matching / learning / experiments / axioms |
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| 研究実績の概要 |
We have conducted a series of experiments related to the main goal of this research project, to test some of the key assumptions behind economic models by analyzing decentralized human interaction. Motivated by the lack of conclusive results on bargaining in spite of more than half a century of academic research, we turned back to axiomatic models and tested seven axioms in the experimental laboratory (in Tokyo and in Paris). Our data support efficiency, symmetry, independence of irrelevant alternatives and monotonicity, and reject scale invariance. Individual rationality and midpoint domination are violated by a significant fraction of the observed agreements. Interestingly, our results are robust to the cultural differences between Japan and France. Our detailed findings have been summarized in a research paper and recently submitted for possible publication to an academic journal.
A related, somewhat earlier project of ours on decentralized matching markets has reached an important milestone as we have been invited to revise and resubmit our results for possible publication.
As for the third pillar of our project, learning and information aggregation in decentralized environments, we have conducted a number of experimental sessions and are currently working on exploring the collected data. One preliminary result that we have found is that human behavior can not satisfactorily be described by any of the two theoretical models that very often appear both in the theoretical and empirical literature (that is, perfect Bayesian learning, and completely naive learning).
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| 現在までの達成度 (区分) |
現在までの達成度 (区分)
2: おおむね順調に進展している
理由
We are doing our best to make progress in our research project as expected. We have finalized the design of a number of experiments and even run the first experimental sessions to gather observations to be used for testing our research hypotheses. Our experimental laboratory and the relatively large number of potential participants at Waseda University guarantee a smooth progress in data collection. We have already implemented enough experimental sessions (to be able to start the data analysis of the collected data) on the following topics:
* decentralized matching markets,
* decentralized bargaining, and
* decentralized learning in networks.
While we continue running further experimental sessions, we have also started presenting our findings at academic workshops and conferences, and writing them up in the form of academic journal articles.
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| 今後の研究の推進方策 |
The current state of our research allows us to feel optimistic. As for the immediate future, first of all, we must do our best to make sure that the two completed research papers related to this project are published as soon as possible in international academic journal. At the same time, we continue collecting data through additional experimental sessions based on the current, and also updated and new experimental designs. Our next experiments are going to explore:
* the empirical success of axioms for bargaining in a direct way, with the help of an environment in which participants are required to discuss and collectively choose a set of properties (instead of bargaining outcomes), and
* learning and information aggregation in large networks, in which participants do not have precise information about the structure of the entire network.
We also believe that it is important to communicate with the research community, therefore we are planning to participate both in domestic and international conferences before submitting our newest findings for publication.
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| 次年度使用額が生じた理由 |
We have decided to run some experiments during the 2018 academic year (instead of 2017). That is the main reason for not spending the entire budget initially allocated to the first year of this research project.
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