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.ipynb_checkpoints
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Agent.py
Oligopoly.pdf
OligopolyOutline.png
OligopolyOutline.tif
OligopolyOutline.tif.old
OligopolyOutline.txt
Oligopoly_poster.pdf
Oligopoly_poster.pptx
README.md
WorldState.py
_config.yml
agTypeFile.txt
commonVar.py
databaseWizard.ipynb
entrepreneurs.txt
from2to3.md
graphicDisplayGlobalVarAndFunctions.py
mActions.py
memoTwoImagesOnScreen.py
modPars.txt
modelActions.txt
my2to3
notesOnHayekianTransformation.md
oActions.py
observerActions no pause.txt
observerActions with pause.txt
observerActions with specialAction.txt
observerActions.txt
parameters.py
partial_corr.py
penPosition.py
readingCsvOutput.ipynb
readingCsvOutput_par_corr.ipynb
readingFirstStepOutputInHayekinaMarket.ipynb
schedule.xls
schedule0.xls
schedule1.xls
schedule2.xls
schedule3.xls
schedule4.xls
schedule5.xls
schedule6.xls
schedule_display_agents.xls
slides_of_a_presentazione_of_the_model.pdf
workers.txtx
workers.txtx.few
workers.txtx.many

README.md

Oligopoly

Marco Mazzoli, Matteo Morini, and Pietro Terna

The model and its construction are reported in Oligopoly.pdf.

A concise presentation of the simulation mechanism is reported in the following image:

We have also the slides of the presentation of the Oligopoly model at WEHIA 2017.

A recent paper (Business Cycle in a Macromodel with Oligopoly and Agents' Heterogeneity: An Agent-Based Approach, 2017) of M.Mazzoli, M.Morini, and P.Terna, discusses the model and its results (if you experience problems in reading, please use Firefox). [Look at Erratum below].

The Oligopoly model uses SLAPP as its agent-based modeling shell.


Erratum: in Table 1, the Expected employment ratio at t=1 is 0.9 and not 0.8.