Find Insights | Insight Maker

Butterfly Effect
Sensitivity To Initial Conditions
(sensitive dependence on initial conditions)
Navier Stokes Equations
Lorenz Attractor
Chaos Theory, Disorder and Entropy

Although the butterfly effect may appear to be an esoteric and unlikely behavior, it is exhibited by very simple systems: for example, a ball placed at the crest of a hill may roll into any of several valleys depending on, among other things, slight differences in initial position. Similarly the direction a pencil falls when held on its tip, or an universe during its initial stages.

These attractors apply to social systems and economics showing jumps between potential wells, and showing the strategic scaling behavior of rotating and cyclic systems whether they be social, economic, or complex spin or rotation of planets affecting weather and climate or spin of galaxies or elementary particles, or even a rock on the end of a piece of string.

What Playing with numbers is all about :)

If M is the state space for the map , then displays sensitive dependence to initial conditions if for any x in M and any δ > 0, there are y in M, with such that

Clone of THE BUTTERFLY EFFECT

Ana Cristina Beja

Buying and storing electricity when it is cheap, and selling it when it is expensive. What are the benefits, both public and private?

Smart Grid: Electricity storage and variable energy pricing

Carlos

14

Economic contibution

Nienke

Based on chapter 14 of Modeling Dynamic Economic Systems

Quasi-competitive equilibrium model

Martín López Ramírez

213

This Model was developed from the SEIR Model (Susceptible, Exposed, Infected, Recovered) and it predicts the COVID-19 outbreak in Burnie, Tasmania. This pandemic outbreak contributes to diverse rates including infection rate, death rates and recovery rate, government policies and its economic impacts.

Assumptions:

This model is driven by its determined rates, e.g., incubation rate, morality rate, test rate and immunity loss rate and its recovery rate.

Government policies are involved in fully vaccination rate, social distance, national border closure, travel, and business restriction which effect Burnie’s economy.

There are three economic entities dimensions in Burnie Island, we can tell that the pandemic has negative impact on Brick-and-Mortar enterprises and tourism business to some extent, whereas, e commercial business plays a crucial role to stimulate the regional economic activities during the COVID-19 period.

Interesting Insights:

The figure of susceptible changes significantly during the initial 3 weeks because of low recovery rate and high infection rate. On the other hand, the implementation and interventions of government policies is effective, because the number of patients who tested negative is increased and the majority of them release and go back home after medical follow-up.

Xueli Huang 501514, BMA708 Model of COVID-19 Outbreak in Burnie, Tasmania

XUELI HUANG

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

Project Stage 2 (solution)

Student

Climate Sector Boundary Diagram By Guy Lakeman

Climate, Weather, Ecology, Economics, Population, Welfare, Energy, Policy, CO2, Carbon Cycle, GHG (green house gasses, combined effects)

As general population is composed of 85% with an education level of a 12 grader or less (a 17 year old), a simple block of components concerning the health of the planet needs to be broken down into simple blocks.

Perhaps this picture will show the basics on which to vote for a sustained healthy future

Democracy is only as good as the ability of the voters to FULLY understand the implications of the policies on which they vote., both context and the various perspectives. National voting of unqualified voters on specific policy issues is the sign of corrupt manipulation.

Climate Sector Boundary Diagram of Guy Lakeman

Guy Lakeman

3

I propose we grow this sim model (or similar) over time to help ourselves better understand the opposing investment and austerity strategies now being advocated for the U.S. government. The hope is to build as simple a model as possible that subsumes the major underlying feedback loops that probably exist in the mental models of proponents of each of these positions. Starting this model was inspired by this Investment vs. Austerity discussion http://www.linkedin.com/groups/Investment-vs-Austerity-How-can-4582801.S.157876413

20120908a_InvestmentVsAusterity

Paul Newton

Smithian growth model from Michael Joffe Fig. 3.7 p57 Ch3 Feedback Economics Book

Adam Smith's Growth through Division of labour

Geoff McDonnell

This model demonstrate how the exisitng tested COVID cases effects economic recovery via goverment intervenes.

Assumption:Goverment intervenes positively contribute on transmission, patients recovery, and death elimination. When existing cases equal or lower than 10 cases, economic growth will be soaring with helps of influencial elements.

Interesting points: even though there are certain amount of unknow cases, enhancing social restriction and increasing test rate ould still reduce amount of cases

Complex Model to Simulate How COVID Outbreak Influence Economic Recovery in Burnie

Youjia Xiao

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.) It also, unlike Models 2 & 3, shows the influence Savings has on the production rate.

In summary, lower rates of consumption (based on production) result in higher rates of both production and consumption in the long-run.

Simple Economy: Model 4

Jim Berger

4

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

Q2 Final Project w/ socio-economic

Claire Murley

Simulating Hyperinflation for 3650 days.

If private bond holdings are going down and the government is running a big deficit then the central bank has to monetize bonds equal to the deficit plus the decrease in private bond holdings. We don't show the details of the central bank buying bonds here, just the net results.

See blog at http://howfiatdies.blogspot.com for more on hyperinflation, including a hyperinflation FAQ.

Hyperinflation Simulation

Vincent Cate

14

Unfortunately, this model only produces the illusion of functioning, but I did manage to get it to give me the graph. However, because of the use of flows, if you change the time step to and the simulation length to anything other than the same numbers, you'll find the graph showing something that looks more exponential. This is due to the function referencing itself in regards to time, so inevitably each time consumption grows it changes the outcome on the other side of the equation. Still, this is a convincing mock up. I added a "45 degree" line so that one could conceivably see (and also change) the difference made by altering the level of autonomous consumption.

Keynesian Macroeconomics

Nicholas Lowe

4

Tourism Flow

Robert Luetkemeier

This page provides a structural analysis of POTUS Candidate Martin O'Malley based on the information at: https://martinomalley.com/vision/ 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 Martin O'Malley Economic Policy

Steve Wallis

Summary WIP of Thomas Palley's 2012 Book

From Financial Crisis to Stagnation

Geoff McDonnell

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

The government has reduced both the epidemic and economic development by controlling immigration.

Yuhao c, BMA708_Marketing insights into Big Data.

Yuhao Chen

Food Waste Part 2

Kiran Rashid

5

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.

Clone of REM 221 - Causal Loop diagramming

Brett van Poorten

108

Irving Fisher's Debt Deflation Theory from Michael Joffe Fig. 3.4 p54 Ch3 Feedback Economics Book with Private Credit Inflation boom added to the bust cycles

Irving Fisher's Debt Deflation Theory

Geoff McDonnell

How Pioneer Corn is Changing Farming in Ghana

BrownieH

HOW A NEW COMMUNITY ENGAGEMENT INITATIVE MAY IMPACT YOUTH CRIME IN THE TOWN OF BOURKE, NSW

MKT563 Assessment 4: Kari Steele

Aim of Simulation:

Bourke is a town in which Youth are involved in high rates of criminal behaviour (Thompson, 2016). This simulation focuses on how implementation of a community engagement initiative may impact crime patterns of youths in Bourke. The specific aim is to assess whether the town should initiate a program such as the Big Brothers Big Sisters Community-Based Mentoring (CBM) (Blueprints for Healthy Youth Development, 2018) program to reduce crime and antisocial behaviour (National Institute of Justice, n.d). Big Brothers Big Sisters is a community mentoring program which matches a volunteer adult mentor to an at-risk child or adolescent to delay or reduce antisocial behaviours; improve academic success, attitudes and behaviours, peer and family relationships; strength self-concept; and provide social and cultural enrichment (Blueprints for Healthy Youth Development, 2018).

Model Explanation:

An InsightMaker model is used to simulate the influence of Big Brothers Big Sisters Initiative on Criminal Behaviour (leading to 60% juvenile detention rates) with variables including participation rate and also drug and alcohol use.

Assumptions:

1/ ‘Youth’ are defined, for statistical purposes, as those persons between the ages of 15 and 24 (United Nations Department of Economic and Social Affairs, n.d).

2/ Youth population (15 – 24 years) makes up 14.1% of the total population of LGA Bourke which according to the most up-to-date freely available Census data (2008) is 3091 (Australian Bureau of Statistics, 2010). Therefore, youth population has been calculated as 435 individuals.

3/ Big Brothers Big Sisters Program is assumed to impact LGA Bourke in a similar manner that has been shown in previous studies (Tierney, Grossman, and Resch, 2000) where initiative showed mentored youths in the program were 46% significantly less likely to initiate drug use and 27 percent less likely to initiate alcohol use, compared to control. They were 32 less likely to have struct someone during the previous 12 months. Compared to control group, the mentored youths earned higher grades, skipped fewer classes and fewer days of school and felt more competent about doing their schoolwork (non-significant). Research also found that mentored youths, compared with control counterparts, displayed significantly better relationships with parents. Emotional support among peers was higher than controls.

Initial Values:

Youth Population = 435

Criminal Behaviour = 100

40% of youth population who commit a crime are non-convicted

60% of youth population who commit a crime are convicted

20% of youth involved in the Big Brothers Big Sisters Initiative are non-engaged

80% of youth involved in the Big Brothers Big Sisters Initiative are engaged

Variables:

The variables include ‘Participation Rate’ and ‘Drug and Alcohol Usage’. These variables can be adjusted as these levels may be able to be impacted by other initiatives which the community can assess for introduction; these variables may also change in terms of rate over time.

Interesting Parameters

As can be seen by increasing the rate of participation to 90% we can see juvenile detention rate decreases with engagement (even with the 20% non-engagement of youths involved in program). By moving the slider to 10% participation however you can see the criminal behaviour increase.

Conclusion:

From the simulation, we can clearly see that the community of Bourke would benefit in terms of the Big Brothers Big Sisters Initiative decreasing criminal behaviour in youths (15 – 24 years of age) over a 5-year timeframe. Further investigation regarding expenditure and logistics to implement such a program is warranted based on the simulation of impact.

References:

Australian Bureau of Statistics. (2010). Census Data for Bourke LGA. Retrieved from www.abs.gov.au/AUSSTATS/abs@.nsf/Previousproducts/LGA11150Population/People12002-2006?opendocument&tabname=Summary&prodno=LGA11150&issue=2002-2006

Blueprints for Healthy Youth Development. (2018). Big Brothers Big Sisters of America Blueprints Program Rating: Promising, viewed 26 May 2018, <www.blueprintsprograms.com/evaluation-abstract/big-brothers-big-sisters-of-america>

National Institute of Justice. (n.d.). Program Profile: Big Brothers Big Sisters (BBBS) Community-Based Mentoring (CBM) Program, viewed 26th May 2018, <https://www.crimesolutions.gov/ProgramDetails.aspx?ID=112>

Tierney, J.P., Grossman, J.B., and Resch, N.L. (2000). Making a Difference: An Impact Study of Big Brothers/Big Sisters. Philadelphia, Pa.: Public/Private Ventures.
http://ppv.issuelab.org/resource/making_a_difference_an_impact_study_of_big_brothersbig_sisters_re_issue_of_1995_study

Thompson, G. (2016) Backing Bourke: How a radical new approach is saving young people from a life of crime. Retrieved from < www.abc.net.au/news/2016-09-19/four-corners-bourkes-experiment-in-justice-reinvestment/7855114>

United Nations Department of Economic and Social Affairs (UNDESA). (n.d.). Definition of Youth, viewed 24th May 2018, www.un.org/esa/socdev/documents/youth/fact-sheets/youth-definition.pdf

Bourke Community Engagement Impact on Youth Detention

Kari Steele