WIP Dynamic map from Steve Keen's Minsky at 100 Lecture video and slides and later Emergent Macroeconomics papers

A simple model for cc adoption which depends on several condions.

This model shows the operation of an extremely simple economy. The system produces and consumes each item (or good) at a fixed rate.

When production exceeds consumption, consumer goods accumulate in stocks. Trading may occur between actors in this system. That will not, however, affect the quantities of the stocks of goods. It only affects ownership (not a concern of this model.)

The recent moratorium on deep-sea drilling will reduce the supply of oil. But the world-wide trend is an ever increasing demand for it. This simple CLD  tries to illustrate the dampening effect on demand and on economic activity of diminishing oil supplies and of rising prices: oil prices  affect virtually all products and especially agricultural production. As it becomes more and more difficult to extract oil, prices must rise. At the moment the global recession counteracts this effect, but the recession will not last forever. Is it too early to speak of Peak Oil?

A model of the potential impact on the elderly population (75+ years) from heat stress, which is increased by climate change in the UK.

Economic capital growth in a system constrained by a non-renewable resource, Figure 37 from Thinking in Systems by Donella H. Meadows

Buying and storing electricity when it is cheap, and selling it when it is expensive. What are the benefits, both public and private?

Introduction:

Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.

An attempt to combine ideas from Joe Stiglitz's Book The Price of Inequality, Peter Turchin's book Secular Cycles and Khalil Saeed and Oleg Pavlov's Dynastic Cycles SD model paper

This model shows the operation of a simple economy with two modifications made to Model 2 -- 1) feedback from production rate to consumption rate and 2) the use of a fractional rate input for calculating consumption rate. 

In summary, lower fractional rates of consumption (based on production) result in higher levels of Savings.

Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.

CLD exposition of Goodwin01 from Steve Keen's August 2019 course on Introduction to Economic Dynamics and Minsky software See video and powerpoint slides. Based on IM-2011 Minsky FIH and IM-168865 MacroEconomics CLDs. SeeIM-172005 for Simulation

Smithian growth model from Michael Joffe Fig. 3.7 p57 Ch3 Feedback Economics Book

This Model was developed from the SEIR Model (Susceptible, Exposed, Infected, Recovered) and it predicts the COVID-19 outbreak in Burnie, Tasmania. This pandemic outbreak contributes to diverse rates including infection rate, death rates and recovery rate, government policies and its economic impacts.    

Assumptions:

 This model is driven by its determined rates, e.g., incubation rate, morality rate, test rate and immunity loss rate and its recovery rate.

Government policies are involved in fully vaccination rate, social distance, national border closure, travel, and business restriction which effect Burnie’s economy.

There are three economic entities dimensions in Burnie Island, we can tell that the pandemic has negative impact on Brick-and-Mortar enterprises and tourism business to some extent, whereas, e commercial business plays a crucial role to stimulate the regional economic activities during the COVID-19 period.

 

Interesting Insights:

 The figure of susceptible changes significantly during the initial 3 weeks because of low recovery rate and high infection rate. On the other hand, the implementation and interventions of government policies is effective, because the number of patients who tested negative is increased and the majority of them release and go back home after medical follow-up. 

The complex model reflects the COVID-19 outbreak in Burnie, Tasmania. The model explains how the COVID-19 outbreak will influence the government policies and economic impacts. The infected population will be based on how many susceptible, infected, and recovered individuals in Burnie. It influences the probability of infected population meeting with susceptible individuals.

The fatality rate will be influenced by the elderly population and pre-existing medical conditions. Even though individuals can recover from COVID-19 disease, some of them will have immunity loss and become part of the susceptible individuals, or they will be diagnosed with long term illnesses (mental and physical). Thus, these variables influence the number of confirmed cases in Burnie and the implementation of government policies.

The government policies depend on the confirmed COVID-19 cases. The government policies include business restrictions, lock down, vaccination and testing rate. These variables have negative impacts on the infection of COVID-19 disease. However, these policies have some negative effects on commercial industry and positive effects on e-commerce and medical industry. These businesses growth rate can influence the economic growth of Burnie with the economic

Most of the variables are adjustable with the slider provided below. They can be adjusted from 0 to 1, which illustrates the percentages associated with the specific variables. They can also be adjusted to three decimal points, i.e., from 0.1 to 0.001.

Assumptions

- The maximum population of Burnie is 20000.
- The maximum number of infected individuals is 100.
- Government policies are triggered when the COVID-19 cases reach 10 or above.
- The government policies include business restrictions, lock down, vaccination and testing rates only. Other policies are not being considered under this model.
- The vaccination policy implemented by the government is compulsory.
- The testing rate is set by the government. The slider should not be changed unless the testing rate is adjusted by the government.
- The fatality rate is influenced by the elderly population and pre-existing medical conditions only. Other factors are not being considered under this model.
- People who recovered from COVID-19 disease will definitely suffer form immunity loss or any other long term illnesses.
- Long term illnesses include mental illnesses and physical illnesses only. Other illnesses are not being considered under this model.
- Economic activities are provided with an assumption value of 1000.
- The higher the number of COVID-19 cases, the more negative impact they have on the economy of Burnie. 

Interesting Insights

A higher recovery rate can decrease the number of COVID-19 cases as well as the probability of infected population meeting with susceptible persons, but it takes longer for the economy to recover compared to a lower recovery rate. A higher recovery rate can generate a larger number of people diagnosed with long term illnesses.

Testing rate triggers multiple variables, such as government policies, positive cases, susceptible and infected individuals. A lower testing rate can decrease the COVID-19 confirmed cases, but it can increase the number of susceptible people. And a higher testing rate can trigger the implementation of government policies, thus decreasing the infection rate. As the testing rate has a strong correlation with the government policies, it can also influence the economy of Burnie. 

Health specific Clone of Scott Page's Aggregation diagram from Complexity and Sociology 2015 article see also IM-9115 and SA IM-1163

​Farmers use intensive pesticides to harvest cotton, which is harmful to not only the health of the farmers using them, but also our environment as it pollutes rivers and groundwater that negatively interfere with the ecosystem. Even though these farmers know of the health and environmental risks, they still use harmful pesticides to produce cotton, but why is this so. This stock and flow map should explain what impacts farmers to use pesticides to grow cotton despite the risks and explain the cause and effect relationship their use has on the cotton industry and the environment.

Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.

IASAM