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Cornerstore Economic Model

This is an economic growth and collapse model based on the Seneca model described by Ugo Bardi. In this implementation, however, direct positive feedback of existing pollution level on pollution increase is replaced with direct positive feedback of existing pollution level on economic loss (i.e. pollution drags down the economy)

Ugo's World

Brian Maschhoff

My InsightPublic Opinion Toward Immigration Reform: The Role of Economic Motivations

Luca Makarushka-Napp

economic inequality

Vo Thi Hoang Anh

Rhino poaching in South - Africa

Anneli Ritzell

Relationships between conceptual dimensions of economic development, based on the International Economic Development Council’s definition for economic development which states:

“Economic development can be defined as a program, group of policies, or activity that seeks to improve the economic wellbeing and quality of life for a community by creating and/or retaining jobs that facilitate growth and provide a stable tax base"

Economic Development

Laura Supple

5 months ago

A systems model of the relationships amongst economic situation, health situations and Covid-19 in Burnie, Tasmania.

Health situation

According to exposed and go out population decreases, the population of infected decreases after a stable high cases period.

Economic situation

When the infected population decreases, the population economic recovery increases over time, then become stable after a period of time.

BMA708 Assessment 3 Complex system

Jingyi Qiu

Vymazal Lukáš - seminární práce Finanční model

renyren

3 months ago

Model Explanation:

This system dynamics model visualises the impact on investment into policing and community engagement resources on the crime rates within the youth population of Bourke, NSW.
The model also adds in the variable of funding for safe houses. With a high rate of domestic violence, unfavorable home conditions and other socio-economic factors, many youth roam the streets with no safe place to go, which may lead to negative behaviour patterns.

Assumptions

Youth Population: 700
Total youth population in 2016 for Bourke LGA was 646 (ages 10-29). (Census, 2016) Figures rounded to 700 for purposes of this model simulation.

Constants:
70% registration and engagement rates for Community funded programs
30% attendance rate for Safe Houses
50% crime conviction rate

Variables

Positive and Negative Influences

The model shows a number of key variables that lead youth to become more vunerable to commit a crime (such as alienation, coming from households with domestic violence, boredom and socio-economic disadvantages such as low income), as well as the variables that enhance the youth's likelihood to be a contributing member of the community (developing trusted relationships and connections with others, and having a sense of self worth, purpose and pride in the community). These factors (positive and negative) are aggregated to a single rate of 50% each for the purposes of the simulation, however each individual situation would be unique.

Police Funding / Resources

Police funding and resources means the number of active police officers attending to criminal activities, as well as prevention tactics and education programs to reduce negative behaviour. The slider can be moved to increase or decrease policing levels to view the impact on conviction rates. Current policing levels are approx 40 police to a population of under 3000 in Bourke.

Crime Rate

Youth crime rates in Australia were 3.33% (2016). Acknowledging Bourke crime rates are much higher than average, a crime rate of 40% is set initially for this model, but can be varied using the sliders.

Community Program Funding / Resources

Community Program Funding and Resources means money, facilities and people to develop and support the running of programs such as enhancing employability through mentorship and training, recreational sports and clubs, and volunteering opportunities to give back to the community. As engagement levels in the community programs increase, the levels of crime decrease. The slider can be moved to increase or decrease funding levels to view the impact on youth registrations into the community programs.

Observations

Ideally the simulations should show that an increase in police funding reduces crime rates over time, allowing for more youth committing crimes to be convicted and subsequently rehabilitated, therefore decreasing the overall levels of youth at risk.

A portion of those youth still at risk will move to the youth not at risk category through increased funding of safe houses (allowing a space for them to get out of the negative behaviour loop and away), whom them may consider registering into the community engagement programs. An increase in funding in community engagement programs will see more youth become more constructive members of the community, and that may in turn encourage youth at risk to seek out these programs as well by way of social and sub-cultural influences.

Justice & Community Support Investment and the Impacts on Bourke Youth Population

Sarah Vassallo

5

Escalation (3) subsidies

Isabel Woods

A sample model for class discussion modeling COVID-19 outbreaks and responses from government with the effect on the local economy. Govt policy is dependent on reported COVID-19 cases, which in turn depend on testing rates less those who recover

Assumptions

Govt policy reduces infection and economic growth in the same way.

Govt policy is trigger when reported COVID-19 case are 10 or less.

Interesting insights

Higher testing rates seem to trigger more rapid government intervention, which reduces infectious cases.

Clone of Burnie COVID-19 outbreak demo model

LU JIN

Extremely basic stock-flow diagram of compound interest with table and graph output in interest and savings development per year. Initial deposit, interest rate, yearly deposit and withdrawal can all be modified in Dutch.

Stock-Flow diagram of savings account - compound interest

Henny van Dongen

Maine Lobster Monoculture cause by economic pressure

Anjar Adhiyoso

WFA4133 Graham-Schaefer model with variable F & Econmics

Michael Colvin

Final

Akshat Bansal

Pathways Causal Loop - Health

Mandy Ableidinger

9

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

Lab 13–Future Emissions–Baseline

Amanda Land

Tese CO2 Supply_CTCP - bloco A

SILVIO JOAQUIM DE SANTANA

4

An initial study of the economics of single use coffee pods.

Helene D. Coffee Pods ISD Humanities

Helene D.

HYSTERESIS
The lost energy associated with delay.
Hysteresis is the dependence of a system not only on its current environment but also on its past environment. This dependence arises because the system can be in more than one internal state. To predict its future development, either its internal state or its history must be known.[1] If a given input alternately increases and decreases, the output tends to form a loop as in the figure. However, loops may also occur because of a dynamic lag between input and output.
Hysteresis is produced by positive feedback to avoid unwanted rapid switching. Hysteresis has been identified in many other fields, including economics and biology.

Economic systems can exhibit hysteresis. For example, export performance is subject to strong hysteresis effects: because of the fixed transportation costs it may take a big push to start a country's exports, but once the transition is made, not much may be required to keep them going.

Hysteresis is used extensively in the area of labor markets. According to theories based on hysteresis, economic downturns (recession) result in an individual becoming unemployed, losing his/her skills (commonly developed 'on the job'), demotivated/disillusioned, and employers may use time spent in unemployment as a screen. In times of an economic upturn or 'boom', the workers affected will not share in the prosperity, remaining long-term unemployed (over 52 weeks). Hysteresis has been put forward[by whom?] as a possible explanation for the poor unemployment performance of many economies in the 1990s. Labor market reform, or strong economic growth, may not therefore aid this pool of long-term unemployed, and thus specific targeted training programs are presented as a possible policy solution.

One type of hysteresis is a simple lag between input and output. A simple example would be a sinusoidal input X(t) and output Y(t)that are separated by a phase lag φ:

Such behavior can occur in linear systems, and a more general form of response is

where χi is the instantaneous response and Φd(t-τ) is the response at time t to an impulse at time τ. In the frequency domain, input and output are related by a complex generalized susceptibility.[3]

HYSTERESIS

Guy Lakeman

A single resource is used with a constant rate and converted into products in use. After a while, these products become unusable because of aging. The recycling of these unusable products is imperfect, thus the amount of not recyclable resource grows (until a better recycling process is invented).

Resource 1

Mario

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

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

This model shows the negative effects of COVID 19 outbreak in Philippines which has impacted the economy and mortality. The relationship between COVID-19 to economic situation and death rate has been shown in the graph. Based on the model, lacking of government policy indicates an increased in COVID 19 cases. Thus, result in rapid increase of poverty caused by unemployment and disruption of business establishments which is are both indicator of economic crises. Moreover, rapid increased of COVID cases and suffering due to economic crisis results to an increased of death rate.

Ph_Covid19SDM_Orendain, Lloyd Lesther

Lloyd Lesther