There is a new type of economic model called a capital exchange model, in which the biophysical economy is abstracted away, and the interaction of units of money is studied. Benatti, Drăgulescu and Yakovenko described at least eight capital exchange models – now referred to collectively as the BDY models – which are replicated as models A through H in EiLab. In recent writings, Yakovenko goes on to show that the entropy of these monetarily isolated systems rises to a maximal possible value as the model approaches steady state, and remains there, in analogy of the 2nd law of thermodynamics. EiLab demonstrates this behaviour. However, it must be noted that we are NOT talking about thermodynamic entropy. Heat is not being modeled – only simple exchanges of cash. But the same statistical formulae apply.

In three unpublished papers and a collection of diary notes and conference presentations (all available with this model), the concept of “entropic index” is defined for use in agent-based models (ABMs), with a particular interest in sustainable economics. Models I and J of EiLab are variations of the BDY model especially designed to study the Maximum Entropy Principle (MEP – model I) and the Maximum Entropy Production Principle (MEPP – model J) in ABMs. Both the MEPP and H.T. Odum’s Maximum Power Principle (MPP) have been proposed as organizing principles for complex adaptive systems. The MEPP and the MPP are two sides of the same coin, and an understanding of their implications is key, I believe, to understanding economic sustainability. Both of these proposed (and not widely accepted) principles describe the role of entropy in non-isolated systems in which complexity is generated and flourishes, such as ecosystems, and economies.

EiLab is one of several models exploring the dynamics of sustainable economics – PSoup, ModEco, EiLab, OamLab, MppLab, TpLab, and CmLab.

Using chains of replicas of Atwood’s Machine, this model explores implications of the Maximum Power Principle. It is one of a series of models exploring the dynamics of sustainable economics – PSoup, ModEco, EiLab, OamLab, MppLab, TpLab, EiLab.

The purpose of this model is to analyze how different management strategies affect the wellbeing, sustainability and resilience of an extensive livestock system under scenarios of climate change and landscape configurations. For this purpose, it simulates one cattle farming system, in which agents (cattle) move through the space using resources (grass). Three farmer profiles are considered: 1) a subsistence farmer that emphasizes self-sufficiency and low costs with limited attention to herd management practices, 2) a commercial farmer focused on profit maximization through efficient production methods, and 3) an environmental farmer that prioritizes conservation of natural resources and animal welfare over profit maximization. These three farmer profiles share the same management strategies to adapt to climate and resource conditions, but differ in their goals and decision-making criteria for when, how, and whether to implement those strategies. This model is based on the SequiaBasalto model (Dieguez Cameroni et al. 2012, 2014, Bommel et al. 2014 and Morales et al. 2015), replicated in NetLogo by Soler-Navarro et al. (2023).

One year is 368 days. Seasons change every 92 days. Each step begins with the growth of grass as a function of climate and season. This is followed by updating the live weight of animals according to the grass height of their patch, and grass consumption, which is determined based on the updated live weight. Animals can be supplemented by the farmer in case of severe drought. After consumption, cows grow and reproduce, and a new grass height is calculated. This updated grass height value becomes the starting grass height for the next day. Cows then move to the next area with the highest grass height. After that, cattle prices are updated and cattle sales are held on the first day of fall. In the event of a severe drought, special sales are held. Finally, at the end of the day, the farm balance and the farmer’s effort are calculated.

Using webs of replicas of Atwood’s Machine, we explore implications of the Maximum Power Principle. This is one of a series of models exploring the dynamics of sustainable economics – PSoup, ModEco, EiLab, OamLab, MppLab, TpLab, CmLab.

In CmLab we explore the implications of the phenomenon of Conservation of Money in a modern economy. This is one of a series of models exploring the dynamics of sustainable economics – PSoup, ModEco, EiLab, OamLab, MppLab, TpLab, CmLab.

Overview

Purpose

Modeling an economy with stable macro signals, that works as a benchmark for studying the effects of the agent activities, e.g. extortion, at the service of the elaboration of public policies..
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System Narrative
How do rebel groups control territory and engage with the local economy during civil war? Charles Tilly’s seminal War and State Making as Organized Crime (1985) posits that the process of waging war and providing governance resembles that of a protection racket, in which aspiring governing groups will extort local populations in order to gain power, and civilians or businesses will pay in order to ensure their own protection. As civil war research increasingly probes the mechanisms that fuel local disputes and the origination of violence, we develop an agent-based simulation model to explore the economic relationship of rebel groups with local populations, using extortion racket interactions to explain the dynamics of rebel fighting, their impact on the economy, and the importance of their economic base of support. This analysis provides insights for understanding the causes and byproducts of rebel competition in present-day conflicts, such as the cases of South Sudan, Afghanistan, and Somalia.

Model Description
The model defines two object types: RebelGroup and Enterprise. A RebelGroup is a group that competes for power in a system of anarchy, in which there is effectively no government control. An Enterprise is a local civilian-level actor that conducts business in this environment, whose objective is to make a profit. In this system, a RebelGroup may choose to extort money from Enterprises in order to support its fighting efforts. It can extract payments from an Enterprise, which fears for its safety if it does not pay. This adds some amount of money to the RebelGroup’s resources, and they can return to extort the same Enterprise again. The RebelGroup can also choose to loot the Enterprise instead. This results in gaining all of the Enterprise wealth, but prompts the individual Enterprise to flee, or leave the model. This reduces the available pool of Enterprises available to the RebelGroup for extortion. Following these interactions the RebelGroup can choose to AllocateWealth, or pay its rebel fighters. Depending on the value of its available resources, it can add more rebels or expel some of those which it already has, changing its size. It can also choose to expand over new territory, or effectively increase its number of potential extorting Enterprises. As a response to these dynamics, an Enterprise can choose to Report expansion to another RebelGroup, which results in fighting between the two groups. This system shows how, faced with economic choices, RebelGroups and Enterprises make decisions in war that impact conflict and violence outcomes.

We present here MEGADAPT_SESMO model. A hybrid, dynamic, spatially explicit, integrated model to simulate the vulnerability of urban coupled socio-ecological systems – in our case, the vulnerability of Mexico City to socio-hydrological risk.

What policy measures are effective in redistributing essential resources during crisis situations such as climate change impacts? We model a collective action institution with different rules for designing and organizing it, and make our analysis specific to various societal contexts.

Our model captures a generic societal context of unequal vulnerability and climate change impact in a stylized form. We represent a community of people who harvest and consume an essential resource to maintain their well-being. However, their ability to harvest the resource is not equal; people are characterized by a ‘resource access’ attribute whose values are uniformly distributed from 0 to 1 in the population. A person’s resource access value determines the amount of resource units they are able to harvest, and therefore the welfare levels they are able to attain. People travel to the centralized resource region and derive well-being or welfare, represented as an energy gain, by harvesting and consuming resource units.

The community is subject to a climate change impact event that occurs with a certain periodicity and over a certain duration. The capacity of resource units to regenerate diminishes during the impact events. Unequal capacities to access the essential resource results in unequal vulnerability among people with regards to their ability to maintain a sufficient welfare level, especially during impact events.

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This is the model for a paper that is based on a simulation model, programmed in Netlogo, that demonstrates changes in market structure that occur as marginal costs, demand, and barriers to entry change. Students predict and observe market structure changes in terms of number of firms, market concentration, market price and quantity, and average marginal costs, profits, and markups across the market as firms innovate. By adjusting the demand growth and barriers to entry, students can […]