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Model description: 

This model is designed to simulate the Covid-19 outbreak in Burnie, Tasmania by estimating several factors such as exposed population, infection rate, testing rate, recovery rate, death rate and immunity loss. The model also simulates the measures implemented by the government which will impact on the local infection and economy. 

 

Assumption:

Government policies will reduce the mobility of the population as well as the infection. In addition, economic activities in the tourism and hospitality industry will suffer negative influences from the government measures. However, essential businesses like supermarkets will benefit from the health policies on the contrary.

 

Variables:

Infection rate, recovery rate, death rate, testing rate are the variables to the cases of Covid-19. On the other hand, the number of cases is also a variable to the government policies, which directly influences the number of exposed. 

 

The GDP is dependent on the variables of economic activities. Nonetheless, the government’s lockdown measure has also become the variable to the economic activities. 

 

Interesting insights:

Government policies are effective to curb infection by reducing the number of exposed when the case number is greater than 10. The economy becomes stagnant when the case spikes up but it climbs up again when the number of cases is under control. 

Sample Model of COVID-19 outbreak in Burnie Tasmania by Yim Fong Ng (544885)
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The model is built to demonstrates how Burnie Tasmania can deal with a new COVID-19 outbreaks, taking government policies and economic effects into account.
The susceptible people are the local Burnie residents. If residents were infected, they would either recovered or dead. However, even they do recover, there is a chance that they will get infected again if immunity loss occurs.
From the simulation result we can see that with the implementation of local government policies including travel ban and social distancing,  the number of infected people will decrease. The number of recovered people will increase in the first 5 weeks but then experience a decrease.
In addition, with the implementation of local government policy, the economic environment in Burnie will be relatively stable when the number of COVID-19 cases is stable.
How Burnie, Tasmania can deal with a new outbreak of COVID-19
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WIP based on Bill mitchell's blogs. 
Sectoral balances are relationships among money flows during an accounting period. Where we perceive accumulations of past imbalances to be accrued is another matter....
MMT Fiscal position
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Model of employee engagement and leverage point
Employee Engagement Cycle
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Introduction:
This model aims to show that how the Tasmania government's COVID-19 policy can address the spread of the pandemic and in what way these policies can damage the economy.

Assumption:
Variables such as infection rate, death rate and the recovery rate are influenced by the actual situation.
The government will implement stricter travel bans and social distant policies as there are more cases.
Government policies reduce infection and limit economic growth at the same time.
A greater number of COVID-19 cases has a negative effect on the economy.

Interesting insights:
A higher testing rate will make the infection increase and the infection rate will slightly increase as well. 
Government policies are effective to lower the infection, however, they will damage the local economy. While the higher number of COVID-19 cases also influences economic activities.
Model of COVID-19 outbreak in Burnie_Guoyu Shen
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Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.
Adaptive Lab 13: Future C Emissions
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Final SSM Lionfish Management PT2 revised with Storytelling
yesterday
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WIP  based on Where profits come from paper , Nathan Tankus blog and other historical sources
Monetary Circuit Flows
4 weeks ago
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Buying and storing electricity when it is cheap, and selling it when it is expensive. What are the benefits, both public and private?

Smart Grid: Electricity storage and variable energy pricing
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This is to support a discussion on money flows and growth. Money as a lubricant for the flow of embodied energy in human systems.
See also A Prosperous Way Down website
Odum Money and Energy Flows
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Based on the SIR (Susceptible, Infected, Recovered) model of disease, this is an upgraded model with more specifc vaeriables.
Insights:
When the growth rate and the number of the recovered is much larger than deaths, the economic activity remain steady growing.
Model of COVID-19 outbreak in Burnie Tasmania
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This is a protoype of the bahai high level economic model in accordance to the bahai-economic principles.
Bahai high level economic model
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Zadlženosť domácností predstavuje významný ekonomický a sociálny problém, ktorý je ovplyvňovaný viacerými faktormi, ako sú výška príjmu, výdavky domácnosti, úrokové sadzby, inflácia a schopnosť splácať záväzky.

Simulácia zadlženosti domácnosti
3 months ago
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Community Economic Impact
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Any activity  requires the use of energy. Economic activity is not possible without energy,  especially fossil fuels. An increase in economic activity necessarily leads to an increase in the use  fossil fuels and greenhouse gas emissions. In addition there will   be a commensurate increase in waste products, pollution and heat. This is dictated by the laws of physics and unavoidable.  A problem arise when the cost of this degeneration caused by continual economic growth surpasses the benefit society derives from it. The ecological economist Professor Herman Daly (2014) explained that when the impact on the ecosystem is correctly measured, global growth has reached a point where the total private and social costs of economic growth outweigh the private and social benefits. In other words, more economic growth is making global society worse off overall - growth has become uneconomic! The model shows that eventually pressures will build up that counteract the perennial belief that all social ills can be solved with economic growth. 

The dynamic of UNECONOMIC growth
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VA - socio-economic
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​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.
According to Clevo Wilson and Clem Tisdell article, "Why farmer continue to use pesticides despite environmental, health and sustainable costs,"

Pesticide use by farmers:
  • "used to reduce yield losses to pests"
  • "avoid economic losses to ensure economical survival"
  • "increase supply market and reduce market prices"
  • "ignorance of sustainable use"
  • "integral part of commercially grow high yielding varieties so without use, high yields may not be sustained"
  • "damage to agriculture land from the use occurs over long period of time so costs may not look serious short term, but reduces economic welfare in long term"
  • "environmental damage: pollutes rivers and groundwater, destroys beneficial predators and interferes with ecosystem overall"
  • "health risks underestimated"
  • "chemical companies selling it have incentive to push their use by advertising and promotion" (1,9).
Farmer Pesticide Use On Cotton
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This model analyzes the interaction between climate change mitigation and adaptation in the land use sector using the concept of forest transition as a framework.
Forest Transition
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Simple model of the global economy, the global carbon cycle, and planetary energy balance.

The planetary energy balance model is a two-box model, with shallow and deep ocean heat reservoirs. The carbon cycle model is a 4-box model, with the atmosphere, shallow ocean, deep ocean, and terrestrial carbon. 

The economic model is based on the Kaya identity, which decomposes CO2 emissions into population, GDP/capita, energy intensity of GDP, and carbon intensity of energy. It allows for temperature-related climate damages to both GDP and the growth rate of GDP.

This model was originally created by Bob Kopp - https://insightmaker.com/user/16029 (Rutgers University) in support of the SESYNC Climate Learning Project.

Steve Conrad (Simon Fraser University) modified the model to include emission/development/and carbon targets for the use by ENV 221.
Clone of REM 221 Simple Climate-Carbon-Economic Model with Targets
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From Schluter et al 2017 article A framework for mapping and comparing behavioural theories in models of social-ecological systems COMSeS2017 video. See also Balke and Gilbert 2014 JASSS article How do agents make decisions? (recommended by Kurt Kreuger U of S)
Modelling human behaviour (MoHuB)
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Introduction:
This simulation model demonstrates the outbreak of Covid-19 in Burnie, Tasmania and how the corresponding government’s responses affect the spreading of Covid-19. Meanwhile, this model also shows how the economy in Burnie is influenced by the impacts of both Covid-19 and government policies.

Variables: 
This simulation contains some relevant variables as follow:

Variables in Covid-19 outbreaks: (1) Infection rate, (2) Recovery rate, (3) Death rate, (4) Immunity loss rate

Variables in Government policies: (1) Vaccination rate, (2) Lockdown, (3) Travel ban, (4)Quarantine

Variables in Economy: (1) E-commerce business, (2) Unemployment rate, (3) Economic growth rate.

Assumption:
Government responses would be triggered when reported Covid-19 cases are at least 10.

The government policies reduce the spreading of Covid-19, but they would also limit economic development at the same time due to the negative impact of the policies on the economy is greater than the positive impact.

The increase in reported Covid-19 cases would negatively affect economic growth.

Interesting Insights:
The first finding is that the death number would keep increasing even though the infection rate has decreased, but with stronger government policies (such as implementing a coefficient over 25%), no more death numbers will occur caused by Covid-19.

The second finding is that as government policies limit business activities, with the increasing number of reported Covid-19 cases, economic growth will suffer a severe blow even if e-commerce grows, it can’t make up for this economic loss.
BMA 708 assignment 3 - simulation model of Covid-19 Outbreak in Burnie, Tasmania
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• This model examines how sustainable consumerism is from social, economic, and environmental aspects. The question in focus is "How will our second-hand clothing donations affect communities in developing countries, specifically Kenya?"

5 Stock Variables: 
• U.S. Consumers
• Multinational Corporations
• Overseas Factories
• Kenya

Highlight Findings: 
To sum up, there are 4 major problems associated to donations:
• 1. Source of problem is the consumer: Cheap deals attract hundreds of millions in revenue for fast fashion, and contribute to 100,000 tonnes of clothing to Kenya annually. 
• 2. Rapid consumerism leads to over-utilization of slowly-renewable resources, such as water.
• 3. Nearly 96% of textiles jobs are eradicated by the massive inflow of clothing donations to Kenya. 
• 4. The offshoring of textiles jobs enrages U.S. blue-collar workers, leading to the rise of protectionism.  



Environmental, social, and economic sustainability aspects of textiles donations
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This paper aims at describing a case where system dynamics modeling was used to evaluate the effects of information and material supply lead-time variation on sales contributions margins and operating cash conversion cycle of a commodity export business.  An empirical dynamic model, loaded with econometric theory of price effect on competitive demand, was used to describe the input data.  The model simulation outputs proved themselves relevant in analyzing the complex interconnections of multiple variables affecting  the profitability in a commercial routine, supporting the decision process among sales managers.

SDR Case study System dynamic modelling
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Irving Fisher's Debt Deflation Theory from Michael Joffe Fig. 3.4 p54 Ch3 Feedback Economics Book with Private Credit Inflation boom added to the  bust cycles
Irving Fisher's Debt Deflation Theory