Modeling Economic Activities and Random Catastrophic Failures of Financial Networks via Gibbs Random Fields
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Modeling Economic Activities and Random Catastrophic Failures of Financial Networks via Gibbs Random Fields Levent Onural1
· Mustafa Çelebi Pınar2 · Can Fırtına3
Accepted: 9 July 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract The complicated economic behavior of entities in a population can be modeled as a Gibbs random field (GRF). Even with simple GRF models, which restrict direct statistical interactions with a small number of neighbors of an entity, real life economic and financial activities may be effectively described. A computer simulator is developed to run empirical experiments to assess different coupling structures and parameters of the presented model; it is possible to test many economic and financial models and policies in terms of their transient and steady-state consequences. Keywords Economic networks · Financial networks · Gibbs random fields · Markov random fields · Metropolis algorithm
1 Introduction There is no doubt that the global network of economic activities is complicated. Individual decisions and actions at various levels combine at macro levels and thus determine the global activity patterns. Ever since the field of economics emerged there has been a debate over the mechanisms and drivers of economic interactions among different agents composing the economy as a whole and its impact on equilibrium aspects such as prices and interest rates. Two different conceptual views are present in the fields of macroeconomics and microeconomics. While macroeconomics is predominantly focused on the behavior of complete economies reacting to external stimuli, microeconomics is concentrated on the behavior of the smallest components of an economy, namely the various
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Levent Onural [email protected]
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Department of Electrical and Electronics Engineering, Bilkent University, 06800 Ankara, Turkey
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Department of Industrial Engineering, Bilkent University, 06800 Ankara, Turkey
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Department of Computer Engineering, Bilkent University, 06800 Ankara, Turkey
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actors contained within it, interacting to form an aggregate of economic behavior. The macroeconomic view sees the processes of economic behavior as being relatively static, with the belief that these processes inherently lead to an equilibrium state. A change in the economic environment will alter this equilibrium, once the change has concluded, the economy will return to another equilibrium position. Specific relationships between behavior and outcomes at a granular level may be ignored. The microeconomic view, in contrast, places utmost importance on individuals and their decision making, the core belief being that human behavior is not always rational and processes inherent in the working economy fluctuate depending on individual or firm behavior, and cannot therefore be considered in isolation from the behavior of other economic agents. The work presented here focuses on the results of the interaction of a set of economic agents, be it individuals, households or banks (or ot
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