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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.

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 1.8

Home buying simulation 1.8

Larry Lee

5

Test 2

Marco

3

Pathways Causal Loop - Health

Mandy Ableidinger

9

Decarbonization Stories

Dean M

12

Socio-economic

Taylor Gariepy

GSGS_HW2_GREENING_THE_GHETTO

Dennis Hadjimichael

3 6 months ago

This model is designed for the local government of Burnie, Tasmania, aiming to help with balancing COIVD-19 and economic impacts during a possible outbreak.

The model has been developed based upon the SIR model (Susceptible, Infected, Recovered) model used in epidemiology.

It lists several possible actions that can be taken by the government during a COVID-19 outbreak and provide the economic impact simulation.

The model allow users to Change the government policies factors (Strength of Policies) and simulate the total economic impact.

Interestingly, the government plicies largely help with controlling the COVID outbreak. However, the stronger the policies are, the larger impact on local economy

Burnie Covid Model, Zilin Huang 533476

Zilin Huang

Economic forecast model

Олександра Тризна

Scott Page's Aggregation diagram from Complexity and Sociology 2015 article see also IM-9115 and SA IM-1163

Macro micro dynamics

Geoff McDonnell

Case 1

April Rose Alpha

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

A framework exploring flood risk management in a developing city, under the old paradigm of control - characterised by narrowly defined goals and an over-reliance on hard-engineered structural solutions.

Urban flood risk (control paradigm)

Michael Meadows

13

From Oatley 2014 p214++

Balance-of-Payments Adjustment

Even though the current and capital accounts must balance each other, there is no assurancethat the millions of international transactions that individu- als, businesses, and governments conduct every year will necessarily produce this balance. When they don’t, the country faces an imbalance of payments. A country might have a current-accountdeficit that it cannotfully finance throughcapital imports, for example, or it might have a current-accountsur- plus thatis not fully offset by capital outflows. When an imbalancearises, the country must bring its payments back into balance. The process by which a country doessois called balance-of-payments adjustment. Fixed and floating exchange-rate systems adjust imbalances indifferent ways.

In a fixed exchange-rate system, balance-of-payments adjustment occurs through changes in domestic prices. We can most readily understand this ad- justmentprocess through a simple example. Suppose there are only two coun- tries in the world—the United States and Japan—and supposefurther that they maintain a fixed exchange rate according to which $1 equals 100 yen. The United States has purchased 800 billion yen worth of goods, services, and financial assets from Japan, and Japanhas purchased $4 billion of items from the United States. Thus, the United States has a deficit, and Japan a surplus, of $4billion.

This payments imbalance creates an imbalance between the supply of and the demandfor the dollar and yen in the foreign exchange market. American residents need 800 billion yen to pay for their imports from Japan. They can acquirethis 800 billion yen by selling $8 billion. Japanese residents need only $4 billion to pay for their imports from the United States. They can acquire the $4 billion by selling 400billion yen. Thus, Americanresidentsareselling $4 billion more than Japanese residents want to buy, and the dollar depreci- ates againstthe yen.

Because the exchangerateis fixed, the United States and Japan must prevent this depreciation. Thus, both governmentsintervenein the foreign exchange market, buying dollars in exchange for yen. Intervention has two consequences.First, it eliminates the imbalance in the foreign exchange mar- ket as the governments provide the 400billion yen that American residents need in exchange forthe $4 billion that Japanese residents do not want. With the supply of each currency equalto the demandin the foreign exchange mar- ket, the fixed exchangerate is sustained. Second, intervention changes each country’s money supply. The American moneysupply falls by $4 billion, and Japan’s moneysupplyincreases by 400billion yen.

The change in the money supplies alters prices in both countries. The reduc- tion of the U.S. money supply causes Americanpricesto fall. The expansion of the money supply in Japan causes Japanese prices to rise. As American prices fall and Japanese prices rise, American goods becomerelatively less expensive than Japanese goods. Consequently, American and Japaneseresidents shift their purchases away from Japanese products and toward American goods. American imports (and hence Japanese exports) fall, and American exports (and hence Japanese imports) rise. As American imports (and Japanese exports) fall and American exports (and Japanese imports) rise, the payments imbalanceis elimi- nated. Adjustment underfixed exchange rates thus occurs through changesin the relative price of American and Japanese goods brought about by the changes in moneysupplies caused by intervention in the foreign exchange market.

In floating exchange-rate systems, balance-of-payments adjustment oc- curs through exchange-rate movements. Let’s go back to our U.S.—Japan sce- nario, keeping everything the same, exceptthis time allowing the currencies to float rather than requiring the governments to maintain a fixed exchangerate. Again,the $4 billion payments imbalance generates an imbalancein the for- eign exchange market: Americansare selling more dollars than Japanese resi- dents want to buy. Consequently, the dollar begins to depreciate against the yen. Because the currencies are floating, however, neither governmentinter- venesin the foreign exchange market. Instead, the dollar depreciates until the marketclears. In essence, as Americans seek the yen they need, they are forced to accept fewer yen for each dollar. Eventually, however, they will acquire all of the yen they need, but will have paid more than $4 billion for them.

The dollar’s depreciation lowers the price in yen of American goods and services in the Japanese market andraises the price in dollars of Japanese goodsandservices in the American market. A 10 percent devaluation of the dollar against the yen, for example, reduces the price that Japanese residents pay for American goods by 10 percentandraises the price that Americans pay for Japanese goods by 10 percent. By making American products cheaper and Japanese goods more expensive, depreciation causes American imports from Japan to fall and American exports to Japan to rise. As American exports expand and importsfall, the payments imbalanceis corrected.

In both systems, therefore, a balance-of-payments adjustment occurs as prices fall in the country with the deficit and rise in the country with the surplus. Consumers in both countries respond to these price changes by purchasing fewer of the now-more-expensive goods in the country with the surplus and more of the now-cheaper goodsin the country with the deficit. These shifts in consumption alter imports and exports in both countries, mov- ing each of their payments back into balance. The mechanism that causes these price changes is different in each system, however. In fixed exchange- rate systems, the exchange rate remains stable and price changes are achieved by changing the moneysupplyin orderto alter prices inside the country. In floating exchange-rate systems, internal prices remain stable, while the change in relative prices is brought about through exchange-rate movements.

Contrasting the balance of payments adjustment process under fixed and floating exchangerates highlights the trade off that governments face between

exchangerate stability and domestic price stability: Governments can have a stable fixed exchangerate or they can stabilize domestic prices, but they cannotachieve both goals simultaneously. If a government wants to maintain a fixed exchangerate, it must accept the occasional deflation and inflation caused by balance-of-payments adjustment. If a governmentis unwilling to accept such price movements,it cannot maintain a fixed exchangerate. This trade-off has been the central factor driving the international monetary system toward floating exchange rates during the last 100 years. We turn now to examine howthis trade-off first led governmentsto create innovativeinter- national monetary arrangements following World WarII and then caused the system to collapse into a floating exchange-rate system in the early 1970s.

Oatley's balance of payments

Jan Baykara

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

Lab 13 Base Model

Jessica LeDuc

6

Description

Model of Covid-19 outbreak in Burnie, Tasmania

This model was designed from the SIR model(susceptible, infected, recovered) to determine the effect of the covid-19 outbreak on economic outcomes via government policy.

Assumptions

The government policy is triggered when the number of infected is more than ten.

The government policies will take a negative effect on Covid-19 outbreaks and the financial system.

Parameters

We set some fixed and adjusted variables.

Covid-19 outbreak's parameter

Fixed parameters: Infection rate, Background disease, recovery rate.

Adjusted parameter: Immunity loss rate can be changed from vaccination rate.

Government policy's parameters

Adjusted parameters: Testing rate(from 0.15 to 0.95), vaccination rate(from 0.3 to 1), travel ban(from 0 to 0.9), social distancing(from 0.1 to 0.8), Quarantine(from 0.1 to 0.9)

Economic's parameters

Fixed parameter: Tourism

Adjusted parameter: Economic growth rate(from 0.3 to 0.5)

Interesting insight

An increased vaccination rate and testing rate will decrease the number of infected cases and have a little more negative effect on the economic system. However, the financial system still needs a long time to recover in both cases.

Untitled Insight

NGUYEN DANG KHOA VO

Marine Tourism Task III - Great Blue Hole

Emma Malte Larsen

Investment with depreciation (good/bad economy Markov chain)

Karoly

5 4 weeks ago

Final

Akshat Bansal

Overview:

Overall, this analysis showed a COVID-19 outbreak in Burnie, the government policies to curtail that, and some of the impacts it is having on the Burnie economy.

Variables

The simulation made use of the variables such as; Covid-19: (1): Infection rate. (2): Recovery rate. (3): Death rate. (4): Immunity loss rate etc.

Assumptions:

From the model, it is apparent that government health policies directly affect the economic output of Burnie. A better health policy has proven to have a better economic condition for Burnie and verse versa.

In the COVID-19 model, some variables are set at fixed rates, including the immunity loss rate, recovery rate, death rate, infection rate, and case impact rate, as this is normally influenced by the individual health conditions and social activities.

Moving forward, we decided to set the recovery rate to 0.7, which is a rate above the immunity loss rate of 0.5, so, the number of susceptible could be diminished over time.

Step 1: Try to set all value variables at their lowest point and then stimulate.

Outcome: the number of those Infected are– 135; Recovered – 218; Cases – 597; Death – 18,175; GDP – 10,879.

Step 2: Try to increase the variables of Health Policy, Quarantine, and Travel Restriction to 0.03, others keep the same as step 1, and simulate

Outcome: The number of those Infected – 166 (up); Recovered – 249 (up); Cases – 554 (down); Death – 18,077 (down); GDP – 824 (down).

With this analysis, it is obvious that the increase of health policy, quarantine, and travel restriction will assist in increase recovery rate, a decrease in confirmed cases, a reduction in death cases or fatality rate, but a decrease in Burnie GDP.

Step 3: Enlarge the Testing Rate to 0.4, variable, others, maintain the same as step 2, and simulate

Outcome: It can be seen that the number of Infected is down to – 152; those recovered down to – 243; overall cases up to – 1022; those that died down to–17,625; while the GDP remains – 824.

In this step, it is apparent that the increase of testing rate will assist to increase the confirmed cases.

Step 4: Try to change the GDP Growth Rate to 0.14, then Tourism Growth Rate to 0.02, others keep the same as step 3, and then simulate the model

Outcome: what happens is that the Infected number – 152 remains the same; Recovered rate– 243 the same; Number of Cases – 1022 (same); Death – 17,625 (same); but the GDP goes up to– 6,632.

This final step made it obvious that the increase of GDP growth rate and tourism growth rate will help to improve the overall GDP performance of Burnie's economy.

The Recent COVID-19 Outbreak in Burnie Tasmania - Buchi Okafor 546792

Buchi Okafor

Model-SIM from Chapter 3 of Wynn Godley and Marc Lavoie's Monetary Economics, adapted for an open economy. The model is stock-flow consistent with only government money--no bills or bonds. No central bank and interest rates do not change. Government spends buying output from the production sector. The production sector is passive turning over all revenue over to households. Households save out of income and spend partially spend out of wealth. Imports and exports pass through the production sector illustrating the idea that consumer households buy from domestic businesses that which they have imported. The model also tracks the sectoral balance flows and changes in equity. Sectoral flows and equity balances match each other dollar for dollar to satisfy the sectoral balances accounting identity (Household Saving - Consumption) + (Business Saving - Expenditure) + (Taxes - Government Spending) - (Exports - Imports) = 0. Since business investment occurs internally to the Business Sector,

SFC_Model-SIM_open_economy

Aaron Medlin

3 months ago

Additional Research:

1. DuPont Renewably Sourced Materials Report - I learned how DuPont uses separation, fermentation and chemistry to create high performance crops.

No Author, No Date, Retrieved from: http://www2.dupont.com/Renewably_Sourced_Materials/en_US/assets/DuPont_Renewably_Sourced.pdf

2. The Science of Hybrid Crops - This article explains the history of hybrid crops.

Reinhart, K. (2003) Living History - Science of Hybrid Crops. Retrieved from: http://www.livinghistoryfarm.org/farminginthe30s/crops_03.html

Spencer Beane Final Assignment

Spencer Beane

Socio-economic factors (kaya)

Olivia Barber

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

Ben Boulanger

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

Geoff McDonnell