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creditcrunch

by Peter Thompson (Submitted: 03/21/2010)

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WHAT IS IT?

I have decided to model the credit crunch from its early stages where the banks signed many irresponsible loans in order to boost its profits, through to where these loans defaulted, to where the bank's collapse because of the worsening economy and weakening of the pound. The dynamic model allows for many input scenarios where the culprits that caused the credit crunch can be identified and focussed on, to find solutions as to how the crisis could have been prevented, or indeed can be prevented from a specific moment onwards.

HOW IT WORKS

The model view shows people and their banks interacting, red arrows showing withdrawals and green arrows showing deposits, blue arrows are loan agreements. If a person takes out a loan, they get a label of "loan" until this is paid off; the loan period is 30 days.
Should a person become bankrupt, their figure becomes grey and no longer interacts with a bank, any loans they may have default.
Bank can collapse when they run out of reserves, and their patch colour (background) becomes red, there will be no more transactions with people once the bank has collapsed.
Although the term people has been used throughout the report, agents can be referred to as families or even companies, which can be pushed into administration when their account is empty. Every one of these entities has a bank account with a specific starting value, they have a mentality to import food or buy British made food, their mentality can also be altered in terms of engaging in bank runs.

HOW TO USE IT

Select the sliders to the desired position, click setup and go (loop).

THINGS TO NOTICE

Fine tuning can provide many different models for the credit crunch.

THINGS TO TRY

People: 309
Banks: 24
Import percentage: 50%
Starting: 2500
Self Interested: 82%
Duration: 6000 days

EXTENDING THE MODEL

We could extend the model by showing a recovery after the credit crunch. I would have like to have made the actions of agents more transparent to other agents, effectively modelling the credit crunch is a more effective manner as it is argued that the media and word of mouth played a big part in the crisis, resulting in problems such as less spending, spending on cheaper and imported goods, leading to less money being pumped into the economy, and engaging in bank runs collapsing many banks.

CREDITS AND REFERENCES

[1] Anand S. Rao Australian Artificial Intelligence Institute
Michael P. George. BDI Agents From Theory to Practice http://www.agent.ai/doc/upload/200302/rao95.pdf

[2] Ilias Sakellariou NetLogoBDI Extension http://users.uom.gr/\~iliass/projects/NetLogo/

[3] Wilensky, U. (1999). NetLogo. http://ccl.northwestern.edu/netlogo. Center for Connected Learning and Computer-Based Modeling. Northwestern University, Evanston, IL.

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