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Laying out and testing before coupling to main model (which is Final Project)

Socio-Economic Factors

Geoffrey Alan Chapman

MONEY_People, Experts. Knowledge IPN_Model2_Oscillations_0.1.7

Bruce.Beihoff

Assignment 3 – Complex Systems

Ryan Salvaggio - 43668070

The Model

This model conceptualizes the effects on a real-estate market-model utilizing agent based modelling. This model utilizes basic economic principles of supply and demand.

The model bases itself on two Agents - one being ‘Customers’ of the real estate market model, whilst the other being the Real estate itself, coined 'Houses'.

Consumers (Demand)

The Agent population, ‘Consumers’ specifies the total amount of people whom can potentially become buyers within the market. This is limited to 30 for conceptual purposes. The Agent ‘Consumer’ exists in two states, either being an ‘Active Customer’ (Active) or an ‘Inactive Customer’ (Inactive). The transition from Inactive to Active occurs upon the basis that the ‘Budget’ of the Consumer meets the desired price of the marketplace, this is specified through the variable ‘Budget’ defining the probability that this transition will occur – this is adjustable by the user indicating a highly resistive or by accepting the market. ‘Budget’s probability in a real life scenario would be based upon numerous factors however conceptually utilizing the slider can present many of these various situations.

Upon transitioning into an active state an ‘Active consumer’ will attempt to find the closest ‘For sale household’, this is represented and carried out through the ‘Enter’ action. Upon finding a household the consumer and house will both return to their respected inactive state thus repeating the process.

Demand – ‘Count of active customers – demand’ is then calculated by a count of Consumers transitioned and currently in the Active state. A high demand would be indicative through a high ‘Budget’ responsiveness whilst a low demand would be indicative of a low ‘Budget’ responsiveness. The increase in Price and hence supply of household thus reduces demand and vise versa.

House (Supply)

The Agent population, ‘Houses’ specifies the total amount of households that can potentially become for sale within the market. This is limited to 112 for conceptual purposes. The Agent ‘House’ exists in two states, either being ‘For Sale’ (Active) or ‘Not for Sale’ (Inactive). The transition from Inactive to Active occurs upon the basis that the ‘Motivation to Sell’ of the House is satisfied, this satisfaction is specified by a set probability that this transition will occur – this is adjustable by the user indicating a highly responsive or restricted house market. ‘Motivation to sell’ probability in a real life scenario would be based upon numerous factors however conceptually utilizing the slider can present many of these various situations.

Upon transitioning into an active state a ‘For Sale’ house will wait for an ‘Active Customer’ ‘this is represented and carried out through the ‘Search’ action. Upon completion of the action both states become inactive and the process continues.

Supply – ‘Count of houses for sale –supply’ is then calculated by a count of Houses ‘For Sale’ that are currently in the active state. Ultimately a high Motivation to sell would sharply increase supply, whilst a low motivation would have the adverse effects.

Movement Speed

Movement speed – describes the base movement rate of Consumers. This variable describes the transition into the ‘Inactive’ state of a consumer, ultimately when a household is found and purchased. Movement speed affects both demand and supply in the sense that the transitioning of stages is quickened and more responsive. (Indicated by a more rigid demand and supply curve).

Market Price

In economics Price is a linear function (straight line) of the proportion of houses for sale (positive slope), and also a linear function of the proportion of buyers (negative slope).Therefore , the variable ‘Market Price’ is calculated by 10 * the portion of ‘House’ in the active state (which is the supply) over the portion of ‘Consumers’ in the active state (which is the demand) Ultimately this presents the economic principles that as Supply is directly related to Price and demand is inversely related to Price.

Note

Each simulation (with the same settings) will present a different and unique simulation. I have set a Random Boolean to the active component that randomizes the amount of Customers or houses that begin in their active state. The probability is only 0.008 but is useful in describing the effects on the market from various position’s and seeing unique models.

References

https://www.youtube.com/watch?v=ynuoZQbqeUg - Your First ABM/Part II

https://insightmaker.com/insight/35714/Foraging-Model

Assignment 3 - Ryan Salvaggio 43668070

Ryan Salvaggio

4

Explanation

This model shows the COVID-19 outbreak in Burnie and how the government policy impacts the economy. The possible phases when the infectious disease spreads in Burnie can be labelled as Susceptible, Infection and Recovery, which are main factors in the model. It is concluded that the government policy can reduce the infectious disease and also the impact in the overall economy.

Assumption

The Government Healthy Policy will affect the decrease in the infection and economy growth rate at the same time.

The Government Health Policy is only triggered when there are more than 10 cases

The increase in number of COVID-19 cases can affect negatively towards the economic growth.

Interesting Insights:

The Government's vaccination promote will reduce the possibility of spreading the infectious disease.

When vaccination rate increase, the dead, infected people and susceptible group will all decrease. This reveals that the crucial role in government's vaccination promote program.

When there is more than 10 confirmed cases, the government policies can effectively reduce the infections and the overall economic activities.

BMA708_Assignment 3_Joleen Tanjaya

Joleen Tanjaya

GSGS4610_FastFashion_FinalModel

Lanier Ellison

4 months ago

241004_economic growth model structure_SFD

JF

Economic forecast model

Олександра Тризна

Green lines: positive relationships

Red lines: negative relationships

Spill

Julian Blanc

A system diagram for the Mojave Desert including example socio-economic factors for an assignment at OSU- RNG 341.

Mojave Desert System Diagram with SES

Abi Wells

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

Michael Sunjaya Jurenang

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

Geoffrey Alan Chapman

This model is comparing healthy and sick residents in Burnie, Tasmania after the Covid-19 Outbreak in 2020. It will also show how the Burnie economy is effected by the disease, how the Government Health Policies are implemented and how they are enforced.

This model is based on the SIR, Susceptible, Infection, Recovery (or Removed) These are the three possible states related to the members of the Burnie population when a contagious decease spreads.

The Government/Government Health Policy, played a big part in the successful decrease in Covid-19 infections. The Government enforced the following.
- No travel (interstate or international)
- Isolation within the residents homes
- Social distancing by 1.5m
- Quarantine
- Non essential companies to be temporarily closed
- Limitations on public gatherings
- And limits on time and kilometers aloud to travel from ones home within a local community

This resulted in lower reported infection rates of Covid-19 and higher recovery rates.

In my opinion: When the first case was reported the Government could have been even faster to enforce these rules to decrease the fatality rates further for the Burnie, population.

Assumption: Government policies were only triggered when 10 cases were recorded.
Also, more cases that had been recorded effected the economic growth during this time.

Interesting Findings: In the simulation it shows as the death rates increases towards the end of the week, the rate of testing goes down. You would think that the government would have enforced a higher testing rate over the duration of this time to decrease the number of infections, exposed which would increase the recovery rates faster and more efficiently.

Figures have been determined by the population of Burnie being 19,380 at the time of assignment.

Complex Systems How Burnie Tasmania dealt with Covid-19 Outbreak BMA708

Kate Elizabeth Craddock

Final

Akshat Bansal

Fig 4. The Casual Loop Diagram of the Socio-Political and Economic Subsystems

Rony Zhu

Urbanisation insight

Arshiya Sharma

Implementação do modelo Handy.

Referência:

Motesharrei, S.; Rivas, J.; Kalnay, E. "Human and nature dynamics (HANDY): Modelling inequality and use of resources in the collapse or sustainability of societies". Ecological Economics 101 (2014) 90-102

http://www.sciencedirect.com/science/article/pii/S0921800914000615

HANDY

Daniel Cunha

ISCI 360 Project - Stage 2

Our model examines the relationship between two straw types (plastic straws and biodegradable straws) and their impact on the environment and economics. Specifically, we are interested in figuring out whether biodegradable straws are a viable solution to plastic straws.

Our model is broken down into three aspects: Social, Environmental and Economic. Color coding is used to differentiate between the different aspects and is explained below:

Turquoise represents the social aspect.

Purple represents the economic aspects.

Green represents the environmental aspects.

Blue represents other crucial stocks and flows in the model that do not necessarily fit into the three aspects above.

In our model, the Canadian population is assumed to increase steadily until a carrying capacity is reached. This can be seen in the graph as the line increases linearly before plateauing indefinitely. We assumed that we will be able to maintain the population at our carrying capacity due to technological advances.

Social Aspect:

The social aspect refers to the impact that awareness of the detrimental costs of straws can have on the usage of straws. The two flows that contribute to awareness are word of mouth (i.e. your friends and family informing you about the effects of straws and influencing you to stop using them) and media coverage (i.e. the media highlights the effects of straws). Both of these flows are dependent on the Canadian population such that 25% of the Canadian population at any time will be impacted by word of mouth or media coverage. (Side note: since word of mouth and media coverage are dependent on the Canadian population, they will plateau when the population does.) This is an arbitrary number but was chosen to show what a change in perspectives of the Canadian population can do. These flows input into an 'awareness of detrimental effects of using plastic straws' stock that reduces the number of plastic straws being used.

Plastic Straws

According to data from the United States individuals usually use 1.6 straws everyday and thus, we have assumed that to be true in Canada as well. Plastic straws start at a base value (due to the previous straw usage) and grow with the Canadian population while subtracting the awareness component of the model.

Environmental Aspect

Since the decomposition of plastic versus paper is significantly different, the amounts that accumulate in the ocean and landfills can be monitored. In addition, the impact on the environment can be monitored. Since plastic straws take longer to decompose, they have a larger impact on wildlife in the ocean than biodegradable straws. Thus, as the plastic straw usage decreases, the amount of habitat loss occurring plateaus. We have also included the aspect of clean-up in which the plastic from the ocean can be moved to the landfill. You will notice that the habitat loss plateaus but does not decrease. This is because we cannot reverse the damage we have done (without additional rigorous clean-up) but can mitigate additional damage. (Please note that clean-up affects only the stock 'Plastic Straws in the ocean' and thus, does not affect the stock 'habitat loss.' Therefore, clean-up will reduce the number of plastic straws in the ocean and indirectly affect the stock 'habitat loss.' However, it will not clean up the plastic straws already impacting 'habitat loss.')

Economic Aspect

The economic aspect monitors the amount of money it takes to make plastic straws versus biodegradable straws and the amount of money the government needs to fund ocean clean-ups. It can be seen that a the usage of plastic straws decreases, the need for clean-up money from the government decreases. However, there is a base level of damage that has already been done by us and thus, larger scale clean-ups will be needed to reverse that. In other words, smaller clean-ups will mitigate the damage we are currently doing but not reverse the damage we have already done. We can also track the cost of making each straw; it can be seen that biodegradable straws are more expensive to make.

However, the energy required to make the straws is less for biodegradable straws than plastic straws. Thus, there are trade-offs for using biodegradable straws.

Although, biodegradable straws are more expensive, they require less energy to make, decompose faster, require less funding for clean-up and impact the wildlife in the ocean to a lesser degree.

Project Stage 2

Eisha Sharda

ESI6550 Group 6 (Model 2)

Brad D

Farming_small vs large

Paul

Ecological economics

Bertrand Nzomigni

EcoCinco_Deforestation_Land Changes

FU CHUANBAO _

10 months ago

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

Yanglin Hu

COVID-19 Outbreak in Burnie Tasmania Simulation Model

Introduction:

This model simulates the COVID-19 outbreak situation in Burnie and how the government responses impact local economy. The COVID-19 pandemic spread is influenced by several factors including infection rate, recovery rate, death rate and government's intervention policies.Government's policies reduce the infection spread and also impact economic activities in Burnie, especially its tourism and local businesses.

Assumptions:

- This model was built based on different rates, including infection rate, recovery rate, death rate, testing rate and economic growth rate. There can be difference between

this model and reality.

- This model considers tourism and local business are the main industries influencing local economy in Burnie.

- Government's intervention policies will positive influence on local COVID-19 spread but also negative impact on local economic activity.

- When there are more than 10 COVID-19 cases confirmed, the government policies will be triggered, which will brings effects both restricting the virus spread and reducing local economic growth.

- Greater COVID-19 cases will negatively influence local economic activities.

Interesting Insights:

Government's vaccination policy will make a important difference on restricting the infection spread. When vaccination rate increase, the number of deaths, infected people and susceptible people all decrease. This may show the importance of the role of government's vaccination policy.

When confirmed cases is more than 10, government's intervention policies are effective on reducing the infections, meanwhile local economic activities will be reduced.

BMA708-Tian Liang-586868-Model of COVID-19 Outbreak in Burnie, Tasmania

Tian Liang

Economic Prosperity

Rich Fruchterman