GIMS - The Graz-Innsbruck Market System
Published: 6 Sep 2016
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Version 19
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DOI: 10.17632/psjh4bf96r.19
Contributor(s):
Description of this data
GIMS is a z-Tree-based software for conducting asset market experiments.
Experiment data files
Related links
Description of this data
GIMS is a z-Tree-based software for conducting asset market experiments.
Experiment data files
Related links
Latest version
Statistics
Views: 680
Downloads: 164
Previous versions
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Version 33
2018-10-22
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Version 32
2018-02-27
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Version 31
2017-12-19
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Version 30
2017-12-19
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Version 29
2017-05-03
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Version 28
2017-04-27
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Version 27
2017-02-27
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Version 26
2017-02-04
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Version 25
2017-02-04
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Version 24
2017-02-03
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Version 23
2017-02-03
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Version 22
2017-01-25
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Version 21
2016-12-21
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Version 20
2016-11-02
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Version 19
2016-09-06
Published: 2016-09-06
DOI: 10.17632/psjh4bf96r.19
Cite this dataset
Palan, Stefan (2016), “GIMS - The Graz-Innsbruck Market System”, Mendeley Data, v19 http://dx.doi.org/10.17632/psjh4bf96r.19
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Version 18
2016-08-10
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Version 17
2016-06-01
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Version 16
2016-06-01
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Version 15
2016-06-01
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Version 14
2016-06-01
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Version 13
2016-06-01
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Version 12
2016-06-01
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Version 11
2016-06-01
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Version 10
2016-06-01
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Version 9
2016-06-01
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Version 8
2016-06-01
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Version 7
2016-06-01
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Version 6
2016-06-01
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Version 5
2016-06-01
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Version 4
2016-06-01
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Version 3
2016-06-01
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Version 2
2016-06-01
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Version 1
2016-06-01
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Institutions
Universitat Innsbruck,
Karl-Franzens-Universitat Graz
Categories
Economics,
Finance,
Asset Pricing
Licence
CC BY 4.0
Learn more
The files associated with this dataset are licensed under a Creative Commons Attribution 4.0 International licence.
What does this mean?
This dataset is licensed under a Creative Commons Attribution 4.0 International licence. What does this mean? You can share, copy and modify this dataset so long as you give appropriate credit, provide a link to the CC BY license, and indicate if changes were made, but you may not do so in a way that suggests the rights holder has endorsed you or your use of the dataset. Note that further permission may be required for any content within the dataset that is identified as belonging to a third party.