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GSGS_HW2_GREENING_THE_GHETTO
3 3 weeks ago
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Based on G.P. Cimellaro et al. Framework for analytical quantification of disaster resilience Engineering Structures 32 (2010) 3639–3649 paper

Facilities Disaster Resilience
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Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.
Q1 Final Project w/ socio-economic
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ESI6550 Group 6 (Model 2)
11 months ago
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This model is designed for the local government of Burnie, Tasmania, aiming to help with balancing COIVD-19 and economic impacts during a possible outbreak. 

The model has been developed based upon the SIR model (Susceptible, Infected, Recovered) model used in epidemiology. 

It lists several possible actions that can be taken by the government during a COVID-19 outbreak and provide the economic impact simulation. 

The model allow users to Change the government policies factors (Strength of Policies) and simulate the total economic impact.

Interestingly, the government plicies largely help with controlling the COVID outbreak. However, the stronger the policies are, the larger impact on local economy

Burnie Covid Model, Zilin Huang 533476
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Georgism
3 months ago
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Model description:

This model is designed to simulate the outbreak of Covid-19 in Burnie in Tasmania. It also tell us the impact of economic policies on outbreak models and economic growth.

 

Variables:

The simulation takes into account the following variables and its adjusting range: 

 

On the left of the model, the variables are: infection rate( from 0 to 0.25), recovery rate( from 0 to 1), death rate( from 0 to 1), immunity loss rate( from 0 to 1), test rate ( from 0 to 1), which are related to Covid-19.

 

In the middle of the model, the variables are: social distancing( from 0 to 0.018), lock down( from 0 to 0.015), quarantine( from 0 to 0.015), vaccination promotion( from 0 to 0.019), border restriction( from 0 to 0.03), which are related to governmental policies.

 

On the right of the model, the variables are: economic growth rate( from 0 to 0.3), which are related to economic growth.

 

Assumptions:

(1) The model is influenced by various variables and can produce different results. The following values based on the estimation, which differ from actual values in reality.

 

(2) Here are just five government policies that have had an impact on infection rates in epidemic models. On the other hand, these policies will also have an impact on economic growth, which may be positive or negative.

 

(3) Governmental policy will only be applied when reported cases are 10 or more. 

 

(4) This model lists two typical economic activities, namely e-commerce and physical stores. Government policies affect these two types of economic activity separately. They together with economic growth rate have an impact on economic growth.

 

Enlightening insights:

(1) In the first two weeks, the number of susceptible people will be significantly reduced due to the high infection rate, and low recovery rate as well as government policies. The number of susceptible people fall slightly two weeks later. Almost all declines have a fluctuating downward trend.

 

(2) Government policies have clearly controlled the number of deaths, suspected cases and COVID-19 cases.

 

(3) The government's restrictive policies had a negative impact on economic growth, but e-commerce economy, physical stores and economic growth rate all played a positive role in economic growth, which enabled the economy to stay in a relatively stable state during the epidemic.

Model of COVID-19 Outbreak in Burnie, Tasmania
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Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.
Lab 13 Question 1
3 3 months ago
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Since the mid-20th century, the number of people living without clean water has risen by 30% despite efforts to improve infrastructure and sanitation.
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Summary of Ch1 of Mitchell Wray and Watts Textbook see IM-164967 for overview
Macroeconomics Introduction
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Summary WIP of Thomas Palley's 2012 Book
From Financial Crisis to Stagnation
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The World Socio-Economics model is computer model to simulate the consequence of interactions between the earth and human systems based on the World3 model by the work of Club of Rome, The Limits to Growth[1].

The World3 model builds by system dynamics theory that is has an approach to understanding the nonlinear behaviour of complex systems over time using stocks, flows, feedback loops, table functions and time delays.

The Limits to Growth concludes that, without substantial changes in resource consumption, "the most probable result will be a rather sudden and uncontrollable decline in both population and industrial capacity". 

Since the World3 model was originally created, it has had minor tweaks to get to the World3-91 model used in the book Beyond the Limits[2], later improved to get the World3-03 model used in the book Limits to Growth: the 30 year update[3].

References;
[1] Meadows, Donella H., Meadows, Dennis L., Randers, Jørgen., Behrens III, William W (1972). The Limits to Growth. 

[2] Meadows, Donella H., Dennis L. Meadows, Randers, Jørgen., (1992). Beyond the limits: global collapse or a sustainable future.

[3] Meadows, Dennis., Randers, Jørgen., (2004). The limits to growth: the 30-year update.
World Socio-Economics model 2000-2100
47 10 months ago
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A system dynamics model to CBA of smart grid project
STATIC_Model_System dynamics approach to Isernia CBA Case
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This Insight is used for simulating growth of a company with specified parameters.
CompanyGrowth
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Brainstorming - Scoping constraints of tradeoff microanalysis
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This model simulates the economics of buying a home. It was created to compare buying a home against using investment returns to pay for rent.

Try cloning this insight, setting the parameter values for real-world scenarios, and then running sensitivity analysis (see tools) to determine the likely wealth outcomes. Compare buying a home to renting. Note that each run will keep the parameters the same while simulating market volatility.

version 1.8
Home buying simulation 1.8
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Socio-economic Cycle - Final Porjecy
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economic inequality
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dec 2h stock and flow model for stakeholder 2
11 months ago
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Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.
Final AF project
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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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Adam Smith's The Invisible Hand: The Feedback Structure of Markets. From Sterman JD Business Dynamics p170 Fig 5-26. A price-mediated resource allocation system..

Price control mechanism
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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