Find Insights | Insight Maker

Simplification of Prevention Investment Framework (private) IM See WIP integrating with economic view insight (private) and multiscale version IM private

HYPER Model Overview

Geoff McDonnell

3

ABOUT THE MODEL

This is a dynamic model that shows the correlation between the health-related policies implemented by the Government in response to COVID-19 outbreak in Burnie, Tasmania, and the policies’ impact on the Economic activity of the area.

ASSUMPTIONS

The increase in the number of COVID-19 cases is directly proportional to the increase in the Government policies in the infected region. The Government policies negatively impact the economy of Burnie, Tasmania.

INTERESTING INSIGHTS

1. When the borders are closed by the government, the economy is severely affected by the decrease of revenue generated by the Civil aviation/Migration rate. As the number of COVID-19 cases increase, the number of people allowed to enter Australian borders will also decrease by the government.

2. The Economic activity sharply increases and stays in uniformity.

3. The death rate drastically decreased as we increased test rate by 90%.

COVID-19 Outbreak in Burnie Tasmania (Rajaa Sajjad, 538837)

Rajaa Sajjad

3

Explanation:

Explanation:

This model presents the COVID-19 outbreak in Burnie and how the government reacts to it. Moreover, the model also illustrates how the economy in Burnie is impacted by the pandemic. The possible stages of residents when the infectious disease spreads in Burnie can be concluded as Susceptible, Infection and Recovery, which are used as the main data in this model. However, the improvement of decreasing of reported infection rates of this infectious disease and increasing of recovery rates are contributed by the implementation of the Government Health Policy.

Assumption

The decrease of both infection rate and economic growth are all influenced by the Government Health Policy simultaneously. The Government Health Policy is only triggered when there are 10 cases reported. However, the increase in reporting COVID-19 cases affects economic growth negatively.

Interesting Insights:

There are two interesting insights that have been revealed from the simulation. First, the death rate continuously increased even though the infection rate goes down. However, the increase in testing rates contributed to the stability of the death rate towards the end of the week. Moreover, higher testing rates also trigger faster government intervention, which can reduce infectious cases. Second, as the Government Health Policy limited the chance of going out and shopping, the economic growth is negative due to the higher cases.

BMA708, Assessment 3: Complex system, Burnie Covid-19 outbreak

Hanyong Li

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

Geoff McDonnell

BACKGROUND:

The following simulation model demonstrates the relationship between supply, demand and pricing within the real estate and housing world. I have based the model on a small city with a population of 100,000 residents as of 2015.

AXIS:

X-Axis

The X-Axis shows the time. It begins in 2015 in the month of October and continues for 36 consecutive years.

Y-Axis

There are 2 Y-Axis on this model. The left hand side relates to the price, demand, and supply, while the right hand side solely lists the population.

As you could see, this town has a population of 100,000 residents to-date. The bottom of the model shows a population loop that produces an exponential growth rate of 2.5%. This dynamic and growing city populates approximately 240,000 residents after 36 years.

MODEL

The model consists of 2 folders named: Buyers/Consumers & Suppliers/Producers. This first folder represents the 'Demand'. It includes a buyers growth rate, buyers interest increase and decrease, a price demand and the demand price. The formulas form an exponential rise in demand due to the rapid and continuous increase in population in this new city. As population increases, so does the demand from buyers.

The second folder conveys the supply of houses. It includes a sophisticated loop of real estate. Residents who own houses in the market decide to sell the home. This becomes the Houses for sale, also known as the 'supply'. Those houses are sold and the sold houses re-enter the market and the loop continues.

The supply has an inverse relationship with the price. When prices drop, supplies drop because the demand goes up. And when the price goes up, so does the supply. This will represent the growth of new houses in the market.

PRICE

Note: The price is based on monthly rent rates.

The price is dependant on many variables. Most importantly, the supply and demand. It also includes factors such as expectations & the economic value of the house. I have included a stable, 'good' economic value for all homes as this fictional town is in a stable and growing area.

Price fluctuates throughout the entire simulation, however it also goes up in price. Over the years houses continue to rise in price while they regularly fluctuate. For example, in 2018 (3 years later), the max price for a home was: $4254.7 and min price was: $852.98. On the other hand, in October 2051 (36 years later), the max price was: $14906 and the min price was: $7661. (This is based on the following data: Houses for Sale: 500, Houses that have sold: 100, Houses in the Market: 730).

SLIDERS

There are 3 sliders on the bottom that could be altered. The simulation would react accordingly. The 3 sliders include changeable data on:

- Houses for Sale.

- Houses that have Sold.

- Houses in the Market.

Real Estate Simulation Assignment - Mitchell Bassil 43290264

Mitchell Bassil

8

Like Model 6 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, government "spending" tends to slow growth of production and consumption.

Simple Economy: Model 7

Jim Berger

WIP based on Where profits come from paper , Nathan Tankus blog and other historical sources

Monetary Circuit Flows

Geoff McDonnell

last month

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

Final Project w/ socio-economic

Claire Murley

5

Healthcare Economic System

Rod Wallace

Commercial aviation economic activity in the EU

刘翱玮

This model shows the structure and operation of a simple economy. It can represent economic systems at different levels of abstraction (e.g. a single good, a group of goods, multiple groups, & an "economy.")

This model has one significant difference from Model 4. The fractional consumption rate table serves the purpose of demonstrating the effects of changes in the fractional consumption rate (or the converse the fractional rate of saving) from 100% to less-than 100% to more-than 100%.

It demonstrates dramatically the effects of significant changes in consumption rates.

Simple Economy: Model 5

Jim Berger

This model bases on the SIR model aims to indicate the relationship between the lockdown policy of the government for combating with COVID-19 and the economic activity in Burnie Tasmania during the pandemic.

This model assumes that more COVID-19 cases will lead to the more serious lockdown policy of the local government, which indirectly affect the economic activities and economic growth. The primary reason is that the lockdown policy force people to stay at home and reduce the chance to work and consume.

The simulation trend of the model is that the economy will keep a steady increase when the serious government policy reduces the COVID-19 spreading speed rate.

COVID-19 outbreak in Burnie model by LUJIN 517217

LU JIN

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

Agile Chris

4 2 months ago

WIP Ideas from Science Special Issue May 2014

The Science of Inequality

Geoff McDonnell

3

WIP Exttension of IM-172005 Simulation of Goodwin01 Minsky Model. Compare with Part3 slide 5 of presentation in patreon

Goodwin02 Minsky Simulation Keen Economic Dynamics Aug2019

Geoff McDonnell

Cutbacks can have a counterintuitive effect. The government knows precisely how much it custs in spending. However, it cannot know the extent to which tax revenues shrink in a non-linear complex economic system as the economy contracts. In addition, the treasury has to spend more as automatic stabilizers activate and payments are made to an increasing number of unemployed workers. The effect of this is that initially the deficit shrinks, but later it rises as tax revenues fall short of expectations and more spending takes place. The ironic part is that often the very indicator that promted austerity measurs, the defcit to GDP ratio, becomes worse than it was at the outset. We could observe this in Spain and Portugal where planned deficits have been repeatedly missed, as austerity measures (fiscal cutbacks) were introduced to deal with the effects of the 2008 financial crisis.

CUTBACKS OFTEN MAKE FISCAL DEFICITS WORSE

Hanns-Jürgen Hodann

About the Model

This model is a dynamic model which explains the relationship between the police of the government and the economy situation in Burnie Tasmania after the outbreak of Corona Virus.

This model is based on SIR model, which explains the dynamic reflection between the people who were susceptible, infected,deaths and recovered.

Assumptions

This model assumes that when the Covid-19 positive is equal or bigger than 10, the government policy can be triggered. This model assumes that the shopping rate in retail shops and the dining rates in the restaurants can only be influenced by the government policy.

Interesting Insights

The government police can have negative influence on the infection process, as it reduced the possibility of people get infected in the public environments. The government policy has a negative effect on shopping rate in retail shops and the dining rate in the restaurants.

However, the government policy would cause negative influence on economy. As people can not shopping as normal they did, and they can not dinning in the restaurants. The retail selling growth rate and restaurant revenue growth rate would be reduced, and the economic situation would go worse.

Corona virus outbreak in Burnie Tasmania (Xuexiao Zhang 538712)

Xuexiao Zhang

Microeconomic measures can produce counterintuitive 'emergent' effects at the macro or systemic level. The commendable act of saving money by individuals during uncertain economic times has the perverse macroeconomic effect of making a recession worse: in aggregate there will be less money available for spending, suppressing demand for goods and services. Economists call this effect 'the paradox of thrift'. Similarly, logical efforts by companies in such conditions to reduce their wage bill or their postponement of investment decisions will reduce spending in the economy and deepen the economic downturn.

What can be done to counteract this harmful dynamic? The missing spending can be replaced by government spending: governments have it within their power to effectively counter economic downturns!

Microeconomic Savings can convert to Macroeconomic Costs

Hanns-Jürgen Hodann

This Insight Maker model illustrates the complex relationships involved in the destruction of rainforests. The reinforcing loop emphasizes the destructive cycle where economic development leads to increased deforestation, while the balancing loop highlights the negative consequences on biodiversity, climate, and economic activities, attempting to counteract the destructive forces. The model serves as a simplified representation to better understand the interconnected factors contributing to rainforest destruction and the importance of considering feedback loops in addressing environmental issues.

Destruction of Rainforests

Sujhanan

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. According to Micheal Finke, house prices typically run 20x monthly rental rates.

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 1.9

Home buying simulation 1.9

Larry Lee

4 7 months ago

Green lines: positive relationships

Red lines: negative relationships

Spill

Julian Blanc

NATIONAL DEBT MODEL

David Percy

Economics Fast Fashion

Andhika

13 6 months ago

Overview

This model not only reveals the conflict between proposed logging of adjacent coups and Mountain bike in Derby but also simulates competition between them. The simulation model aims to investigate the potential coexistence opportunities between the mountain biking and forestry and find out the optimal point for coexistence to help improve Tasmania’s economy.

How the model works

It is recognized that the mountain biking and forestry industries can help support the Tasmanian community and strengthen the Tasmanian economy. The logging and forest sector in Derby can help the local community generate wealth and create more employment opportunities. The sector main source of income come from selling timber such as domestic and export sales. Nevertheless, the sector’s profit has decreased over the past few years on account of the weaker demand and reduced output. Accordingly, the profitability and output of the sector have fluctuated in response to the availability of timber, the timber price movements as well as the impact of changing demand conditions in downstream timber processing sectors. The slow growth rate for a timber has a negative impact on the profitability of the forestry industry and the economic contribution of this industry is set to grow slower, as there is a positive correlation between these variables. In addition, the mountain biking industry in Derby can bring a huge significant economic contribution to the local community. The revenue streams of the industry come from bike rental, accommodation, retail purchase and meals and beverages. These variables also influence the past experience which is positive correlation between reviews and satisfaction that can impact the demand for the mountain biking trails. More importantly, the low regeneration rate for a timber can have a negative impact on the landscape of the mountain biking and the tourist’s past experience that led to a decrease in the demand of tourists for the mountain biking, as the reviews and satisfaction are dependent on the landscape and past experience. It is evident that the industry not only helps the local community generate wealth through industry value addition but also creates a lot of employment opportunities. Therefore, the Mountain Bike Trails can be regarded as sustainable tourism that can help increase employment opportunities and economic contribution that can be of main economic significance to the Tasmania’s economy. Therefore, both industries can co-exist that can maximise the economic contribution to the local community and the Tasmanian economy.

Interesting Insights

It is interesting to note that the activity of cutting down trees does not influence the development of Mountain Biking industry. By lowering the prices of accommodation, food, bike rental and souvenirs, it can help increase the reviews and recommendations of Mountain Biking that will enhance the number of tourists. In this case, the Mountain Biking industry can achieve sustainable economic growth in the long-term while the economic growth rate of forestry industry will continue to decrease.

Simulation of Derby Mountain bikes versus logging

Charles Lau