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241004_economic growth model structure_SFD
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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. Additionally, decrease in affluence is increased by temperature increases damaging the global economy
Final Project 4 W/ Socio-Economic Factors - Investment+Temperature Degradation
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My Insight - Housing and Social Cohesion
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This model shows the simulation of COVID-19 outbreaks when it hit Burnie, Tasmania. This model will show how government intervention will impact the total number in COVID 19 cases and the overall economic activity.

 

Assumptions

1.   The current Burnie population in 19550. Therefore, the susceptible population is equal to the current Burnie population.

2.       Since Burnie is just a regional city, the virus infection rate is 25% as 5000 people in Burnie went into quarantine during the outbreak last year.

3.       50% of people who are infected will recover.

4.       20% of people who are infected will die because Burnie population average is old.

5.       Government intervention and policy will reduce the Infection

6.       COVID-19 is only countable as a case if the infected people have been tested, and the percentage of testing depends on how many infected people have been tested.

7.       Following a recovery, there is a chance that people could lose their immunity, and also the immunity loss rate measures this.

8.       Government intervention will reduce the infection rate by 15%.

9.       Lockdown will cause tourism industry to shut down and affect the overall economic activity.

10.   Lockdown is one of the most effective way to prevent infection.

11.   Strict health protocol also contributes to reduce the infection.

12.   Vaccination will not make people fully immune to the virus. However, vaccinated people will reduce the immunity loss percentage.

13.   Economic growth rate percentage is based on year 2020.

Findings

1.       COVID-19 could be significantly reduced in number and the spread of the vaccine could make a significant impact on the epidemic.

2.       Economic activity will drop during the first phase of government intervention, However, it will steadily increase overtime

3.       Less people going to be susceptible as government imposed covid 19 rules.

BMA708 Michael Sunjaya Jurenang ID:547923
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Cornerstore Economic Model
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This model indicate indicates the modeling COVID-19 outbreaks and responses from government policies with the effect on the local economy. Model was occurred at Burnie, Tasmania. The model mainly contains three parts: COVID-19 pandemic outbreak, four differences government policies and what the impact on economy from those policies.

 

Assumptions:

(1) Various variables influence the model, which can result in varied outcomes. The following values are based on an estimate and may differ from actual values. Government initiatives are focused at reducing Covid-19 infections and, as a result, affecting (both positive and negative) economic growth.

 

(2) 42% of infected people will recovery. 10% of people who are infected will die and the rate relatively higher due to the much old people living in Burnie, Tasmania.

78% of cases get tested.

 

(3) Government policy will only be implemented when there are ten or more recorded cases. Four government policies have had influences on infection.  

 

(4) The rising number of instances will have a negative impact on Burnie's economic growth.

 

Insights:

1. As a result of the government's covid 19 rules, fewer people will be vulnerable. Less people going to be susceptible.

 

2. After the government policy intervention, there is a effectively reduce of infected people.

 

3. Overall, there is no big differences of economic performance from the graph, might due to the positive and negative effect of economy. And after two weeks, the economy maintained a level of development without much decline.

BMA708 Yanglin Hu
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Laying out and testing before coupling to main model (which is Final Project)
Socio-Economic Factors
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This page provides a structural analysis of POTUS Candidate Rand Paul's economic policy based on the information at:  https://www.randpaul.com/issue/spending-and-debt and also   https://www.randpaul.com/issue/taxes  The method used is Integrative Propositional Analysis (IPA) available: ​ http://scipolicy.org/uploads/3/4/6/9/3469675/wallis_white_paper_-_the_ipa_answer_2014.12.11.pdf
DRAFT IPA of Rand Paul Economic Policy
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Economic Prosperity
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Simulation of MTBF with controls

F(t) = 1 - e ^ -λt 
Where  
• F(t) is the probability of failure  
• λ is the failure rate in 1/time unit (1/h, for example) 
• t is the observed service life (h, for example)

The inverse curve is the trust time
On the right the increase in failures brings its inverse which is loss of trust and move into suspicion and lack of confidence.
This can be seen in strategic social applications with those who put economy before providing the priorities of the basic living infrastructures for all.

This applies to policies and strategic decisions as well as physical equipment.
A) Equipment wears out through friction and preventive maintenance can increase the useful lifetime, 
B) Policies/working practices/guidelines have to be updated to reflect changes in the external environment and eventually be replaced when for instance a population rises too large (constitutional changes are required to keep pace with evolution, e.g. the concepts of the ancient Greeks, 3000 years ago, who based their thoughts on a small population cannot be applied in 2013 except where populations can be contained into productive working communities with balanced profit and loss centers to ensure sustainability)

Early Life
If we follow the slope from the leftmost start to where it begins to flatten out this can be considered the first period. The first period is characterized by a decreasing failure rate. It is what occurs during the “early life” of a population of units. The weaker units fail leaving a population that is more rigorous.

Useful Life
The next period is the flat bottom portion of the graph. It is called the “useful life” period. Failures occur more in a random sequence during this time. It is difficult to predict which failure mode will occur, but the rate of failures is predictable. Notice the constant slope.  

Wearout
The third period begins at the point where the slope begins to increase and extends to the rightmost end of the graph. This is what happens when units become old and begin to fail at an increasing rate. It is called the “wearout” period. 
BATHTUB MEAN TIME BETWEEN FAILURE (MTBF) RISK
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An initial study of the economics of single use coffee pods.
K Collins Coffee Pods ISD Humanities v 1.02
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Figs 1 and 2 of David HArvey's Companion to Marx's Grundrisse illustrating the circulation of money and value in capitalism, dubbed as "value in motion" Also Waterstone and Chomsky Consequences of Capitalism Book
Marx and Circulation of Capital and Money
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Fig 17.15 p700 Causal structure of commercial real estate markets of Case Study from John Sterman's 2000 Business Dynamics Book 
Boom and bust in Commercial Real Estate
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Overview of Part E Ch 20 to 24 of Mitchell Wray and Watts Textbook see IM-164967 for book overview
Economic policy in an open economy
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Circular equations WIP for Runy.

Added several versions of the model. Added a flow to make C increase. Added a factor to be able to change the value 0.5. 
Circularity in Economic models 1
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Economic Effect
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ESI6550 Group 6 (Model 2)
11 months ago
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Overview of Part G Ch 27 to 30 of Mitchell Wray and Watts Textbook see IM-164967 for book overview
History of Macroeconomic Thought
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Format: Given pre-conditions when independent variables(s) then dependent variable

Given Earnings Decline (0.25), Spending Variance (55), Initial Investment (500) and Rate of Return (RandNormal(0.06, 0.12)) when one of these independent variables change then how sensitive is Investment (22) over a 30 year time period (-1,000)

H1: if you Earn more then Investment will last much longer => rejected

H2: if you Spend less then Investment will last much longer => accepted

H3: if your Initial Investment is higher then Investment will last much longer => accepted

H4: if you reduce your Spend when Investments are declining then Investment will last much longer => accepted

Given Earnings Decline (0.25), Spending Variance (55), Initial Investment (500) and Rate of Return (RandNormal(0.06, 0.12)) when one of these independent variables are optimised then Investment will last exactly 30 years by minimising the absolute investment gap

H1: if you set an appropriate Spending Base then remaining Investment is 0 => rejected

H2: if you set an appropriate Spending Reduction then remaining Investment is 0 => rejected

Source for investment returns: https://seekingalpha.com/article/3896226-90-year-history-of-capital-market-returns-and-risks
OrangeFortune | Wealth Management when Retiring
4 3 weeks ago
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THE 2020 MODEL (BY GUY LAKEMAN) EMPHASIZES THE PEAK IN POLLUTION BEING CREATED BY OVERPOPULATION.
WITH THE CARRYING CAPACITY OF ARABLE LAND NOW BEING 1.5 TIMES OVER A SUSTAINABLE FUTURE (PASSED IN 1990) AND NOW INCREASING IN LOSS OF HUMAN SUSTAINABILITY DUE TO SEA RISE AND EXTREME GLOBAL WATER RELOCATION IN WEATHER CHANGES IN FLOODS AND DROUGHTS AND EXTENDED TROPICAL AND HORSE LATTITUDE CYCLONE ACTIVITY AROUND HADLEY CELLS

The World3 model is a detailed simulation of human population growth from 1900 into the future. It includes many environmental and demographic factors.

THIS MODEL BY GUY LAKEMAN, FROM METRICS OBTAINED USING A MORE COMPREHENSIVE VENSIM SOFTWARE MODEL, SHOWS CURRENT CONDITIONS CREATED BY THE LATEST WEATHER EXTREMES AND LOSS OF ARABLE LAND BY THE  ALBEDO EFECT MELTING THE POLAR CAPS TOGETHER WITH NORTHERN JETSTREAM SHIFT NORTHWARDS, AND A NECESSITY TO ACT BEFORE THERE IS HUGE SUFFERING.
BY SETTING THE NEW ECOLOGICAL POLICIES TO 2015 WE CAN SEE THAT SOME POPULATIONS CAN BE SAVED BUT CITIES WILL SUFFER MOST. 
CURRENT MARKET SATURATION PLATEAU OF SOLID PRODUCTS AND BEHAVIORAL SINK FACTORS ARE ALSO ADDED

Use the sliders to experiment with the initial amount of non-renewable resources to see how these affect the simulation. Does increasing the amount of non-renewable resources (which could occur through the development of better exploration technologies) improve our future? Also, experiment with the start date of a low birth-rate, environmentally focused policy.

WORLD2020 to PLANET2020
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Casual Loop Diagram
CLD