Learning in network games
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985998%3A_____%2F18%3A00490145" target="_blank" >RIV/67985998:_____/18:00490145 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.3982/QE688" target="_blank" >http://dx.doi.org/10.3982/QE688</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3982/QE688" target="_blank" >10.3982/QE688</a>
Alternative languages
Result language
angličtina
Original language name
Learning in network games
Original language description
We report the findings of experiments designed to study how people learn in network games. Network games offer new opportunities to identify learning rules, since on networks (compared to, e.g., random matching) more rules differ in terms of their information requirements. Our experimental design enables us to observe both which actions participants choose and which information they consult before making their choices. We use these data to estimate learning types using finite mixture models. Monitoring information requests turns out to be crucial, as estimates based on choices alone show substantial biases. We also find that learning depends on network position. Participants in more complex environments (with more network neighbors) tend to resort to simpler rules compared to those with only one network neighbor.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
50202 - Applied Economics, Econometrics
Result continuities
Project
<a href="/en/project/GA14-22044S" target="_blank" >GA14-22044S: Learning and Networks</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Quantitative Economics
ISSN
1759-7323
e-ISSN
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Volume of the periodical
9
Issue of the periodical within the volume
1
Country of publishing house
US - UNITED STATES
Number of pages
55
Pages from-to
85-139
UT code for WoS article
000430061200003
EID of the result in the Scopus database
2-s2.0-85045420059