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Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.
This Scenario has Affluence decreasing due to Anthropogenic climate change
Final Project 3 W/ Socio-Economic Factors - Temperature Degradation
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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.  



The environmental, social, and economic sustainability aspects of textiles donations
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Unfolding story based on Bogdanov's original A Short Course of Economic Science text and Pilyugina's 2019 article
Bogdanov Economic History of Societies
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Preliminary climate change conflict CLD 01.10.25
9 months ago
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• This model examines how sustainable consumerism is from social, economic, and environmental aspects.  

The environmental, social, and economic sustainability aspects of consumerism
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Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.
This Scenario hits Affluence (1% decrease per annum) to increase decarbonization of energy
Final Project 2 W/ Socio-Economic Factors - Reinvestment Scenario
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Implementation of the Solow model of economic growth with labor enhancing technology.

parameters: s, alpha, delta, n, gA
variables: Y. K, L, C, A
per capita variables: y, k, c, a
per capita and technology variables: y~, k~, c~
steady state variables: y~*, k~*, c~*
all variables come with relative growth rates g

Features:

+steady state from beginning
+one time labor shock
+permanent savings quote shock
+permanent technological growth rate shock

Decreasing steady state variables when starting in steady state are numeric artifacts.
Solow growth model v1.0
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Health Determinants
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Clone of Pesticide Use in Central America for Lab work


This model is an attempt to simulate what is commonly referred to as the “pesticide treadmill” in agriculture and how it played out in the cotton industry in Central America after the Second World War until around the 1990s.

The cotton industry expanded dramatically in Central America after WW2, increasing from 20,000 hectares to 463,000 in the late 1970s. This expansion was accompanied by a huge increase in industrial pesticide application which would eventually become the downfall of the industry.

The primary pest for cotton production, bol weevil, became increasingly resistant to chemical pesticides as they were applied each year. The application of pesticides also caused new pests to appear, such as leafworms, cotton aphids and whitefly, which in turn further fuelled increased application of pesticides. 

The treadmill resulted in massive increases in pesticide applications: in the early years they were only applied a few times per season, but this application rose to up to 40 applications per season by the 1970s; accounting for over 50% of the costs of production in some regions. 

The skyrocketing costs associated with increasing pesticide use were one of the key factors that led to the dramatic decline of the cotton industry in Central America: decreasing from its peak in the 1970s to less than 100,000 hectares in the 1990s. “In its wake, economic ruin and environmental devastation were left” as once thriving towns became ghost towns, and once fertile soils were wasted, eroded and abandoned (Lappe, 1998). 

Sources: Douglas L. Murray (1994), Cultivating Crisis: The Human Cost of Pesticides in Latin America, pp35-41; Francis Moore Lappe et al (1998), World Hunger: 12 Myths, 2nd Edition, pp54-55.

REM 221 - Causal Loop diagramming
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This model shows the operation of a simple economy. It demonstrates the effect of changes in the fractional rate of consumption (or the converse the fractional rate of saving.)

In summary, lower rates of consumption (based on production) result in higher rates of production and consumption in the long-run.
Simple Economy: Model 8
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Insur
7 months ago
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Peak oil occurs not when there are no more reserves, but when it is too expensive to bring them to the surface. The diagram describes a dynamic where peak oil leads to oil prices that are too low for oil companies to produce oil. There are two keys to understand this counterintuitive situation. First, it is important to realize that without energy (oil) no economic activity can take place. Second, when supplies of oil become scarce, non-elite workers  - because of the contraction of the economy - will lose their jobs or suffer salary cuts. This will make goods containing (or using) oil products too expensive for the masses. Demand for those products (most things on the market) will decline and with it demand for oil - oil prices will drop too low for oil companies to produce oil!

These ideas stem from Gail Tverberg's blog: 'Our Finite World'. https://ourfiniteworld.com/

PEAK OIL LEADS TO LOW OIL PRICES
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Summary of Ch1 of Mitchell Wray and Watts Textbook see IM-164967 for overview
Macroeconomics Introduction
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Nobody seems to notice bubbles until they burst. One possible reason is that those caught up in a bubble are completely blinded by the grip, the overpowering logic and force excerted by the positive feedback loop that drives it. Financial bubbles occur time and time again - and nobody seems to learn. Another example on a different time scale is an argument that spins out of control and ends in violence. The participants seem to be blind to the consequences; the immediate and imperative logic of the feedback loop imposes itself. The vortex created by the feedback loop even seems to draw in outsiders, such as new investors. Is this the reason why we don't notice bubbles? This explanation is meant to stimulate discussion!

Bubbles and Feedback Loops
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First pass at model depicting importance of Net Capital Accumulation on economic growth of firm - from firm's perspective

Economic Growth Rev 0
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Plan for CCP project completion see IM-102242  for WIP detail of the structures of the related models
CCP Project Scope Deliverables and Extensions
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On the occasion of th G20-meeting in Toronto, the German Economics minister Herr Schaüble said that without restoring confidence it would not be possible to get consumer spending and business investment going. Similar remarks were made by David Cameron and Señor Zapatero of Spain. All maintain that confidence is a pre-requisite to get growth going and that, therefore, it was imperative to reduce fiscal deficits. Reducing the fiscal deficit will restore confidence at first. However, reducing the deficit very quickly will introduce a dynamic that may cause the economy to decline - and perhaps depress  consumers demand even further.  It will actually destroy confidence: few businesses are inclined to invest in a shrinking economy. Cutting the deficit too rapidly or too steeply can lead to a confidence trap.

NOTE: A big experiment is now taking place in the UK - the government has cut public spending severely! Will this lead to hardship and, perhaps, social unrest? 

Confidence Trap and Growth
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Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.
Final Project
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From Jay Forrester 1988 killian lectures youtube video describing system dynamics at MIT. For Concepts See IM-185226. For more detailed biography See Jay Forrester memorial webpage For MIT HIstory see IM-184930
System Dynamics Applications
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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. 

BMA708 COVID-19 Outbreak in Burnie, Tasmania
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Explanation of the Model

The sample model demonstrate the COVID-19 outbreak in Burnie, Tasmania appearing how the government reacts by executing important health approaches and the impacts on the economy of the region

Assumptions

The economic growth rate is subordinate on the extent of the populace who can be exposed. The number of COVID-19 cases adversely impacts the economy. The government arrangement is activated when the COVID-19 cases are 10 or above

Interesting Insights

1. There is a positive relationship between exposure to COVID- 19 and economic growth rate. Since the more individuals go out, the more trade activity takes place and that ultimately results economic growth

2. Expanding the testing rate results
- Higher cases being recognized
- Strict  government intervention
- Less deaths

BMA708_Assignment3_Md Shihabul Islam_548056
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This simple model describes wealth accumulation. The value in income is described by the following simple equation:

simple wealth accumulation model
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My Insight