A model of the ebb and flow of agricultural societies, like China's history. From Khalil Saeed and Oleg Pavlov's WPI 2006  paper  See also the Generic structure  Insight Map
A model of the ebb and flow of agricultural societies, like China's history. From Khalil Saeed and Oleg Pavlov's WPI 2006 paper See also the Generic structure Insight Map
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 s
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
4 2 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.pd
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
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 cotto
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.

   Model description:     This model is designed to simulate the Covid-19 outbreak in Burnie, Tasmania by estimating several factors such as exposed population, infection rate, testing rate, recovery rate, death rate and immunity loss. The model also simulates the measures implemented by the governm

Model description: 

This model is designed to simulate the Covid-19 outbreak in Burnie, Tasmania by estimating several factors such as exposed population, infection rate, testing rate, recovery rate, death rate and immunity loss. The model also simulates the measures implemented by the government which will impact on the local infection and economy. 

 

Assumption:

Government policies will reduce the mobility of the population as well as the infection. In addition, economic activities in the tourism and hospitality industry will suffer negative influences from the government measures. However, essential businesses like supermarkets will benefit from the health policies on the contrary.

 

Variables:

Infection rate, recovery rate, death rate, testing rate are the variables to the cases of Covid-19. On the other hand, the number of cases is also a variable to the government policies, which directly influences the number of exposed. 

 

The GDP is dependent on the variables of economic activities. Nonetheless, the government’s lockdown measure has also become the variable to the economic activities. 

 

Interesting insights:

Government policies are effective to curb infection by reducing the number of exposed when the case number is greater than 10. The economy becomes stagnant when the case spikes up but it climbs up again when the number of cases is under control. 

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 rat
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.
  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 c
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. 

  A system dynamics model to CBA of smart grid project
A system dynamics model to CBA of smart grid project
11 9 months ago
     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 t

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 parameter: Background disease.

Adjusted parameters: Infection rate, recovery rate. 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.

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 from Michael Joffe Fig. 3.4 p54 Ch3 Feedback Economics Book with Private Credit Inflation boom added to the  bust cycles
 MODERN MONETARY THEORY SHOWS HOW FULL EMPLOYMENT CAN BE ACHIEVED!  POTENTIAL GDP is a level of overall spending - by the government and the non-government sector - at which there is full employment. If the economy is not operating at
its potential, then the  private sector
has failed to invested or

MODERN MONETARY THEORY SHOWS HOW FULL EMPLOYMENT CAN BE ACHIEVED!

POTENTIAL GDP is a level of overall spending - by the government and the non-government sector - at which there is full employment. If the economy is not operating at its potential, then the  private sector has failed to invested or spend enough to generate the necessary growth nor has income  from net exports contributed enough. This only leaves the government to close the spending gap. Conceptually, a government disposing of its own freely floating currency could act using two powerful tools -  spending in excess of tax revenue, and taxation - to ensure that the gap between the actual economic activity and potential GDP is quickly closed. Achieving the  full employment that prevailed for 30 years between 1945 and 1975 in western economies is definitely possible! 

This model is based off Meadows economic capital with reinforcing growth loop constrained by a renewable resource model.
This model is based off Meadows economic capital with reinforcing growth loop constrained by a renewable resource model.
I have tried to capture the unemployment benefits budget in a causal loop diagram. You can make this as extensive as you want, but I have tried to focus on how unemployment benefits are financed and on the main determinants of expenditures and income. I was not (yet) able to 'close te loop' - to bui
I have tried to capture the unemployment benefits budget in a causal loop diagram. You can make this as extensive as you want, but I have tried to focus on how unemployment benefits are financed and on the main determinants of expenditures and income. I was not (yet) able to 'close te loop' - to build the diagram up from feedback cycles. 
The diagram is in Dutch.
Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.
Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.
A simple budget planning system.  What additional complexities can you add?
A simple budget planning system.  What additional complexities can you add?
Eastern oyster growth model calibrated for Long Island Sound Developed and implemented by Joao G. Ferreira and Camille Saurel; growth data from Eva Galimany, Gary Wickfors, and Julie Rose; driver data from Julie Rose and Suzanne Bricker; Culture practice from the REServ team and Tessa Getchis. This
Eastern oyster growth model calibrated for Long Island Sound
Developed and implemented by Joao G. Ferreira and Camille Saurel; growth data from Eva Galimany, Gary Wickfors, and Julie Rose; driver data from Julie Rose and Suzanne Bricker; Culture practice from the REServ team and Tessa Getchis. This model is a workbench for combining ecological and economic components for REServ. Economic component added by Trina Wellman.

This is a one box model for an idealized farm with one million oysters seeded (one hectare @ a stocking density of 100 oysters per square meter)

1. Run WinShell individual growth model for one year with Long Island Sound growth drivers;

2. Determine the scope for growth (in dry tissue weight per day) for oysters centered on the five weight classes)
 
3. Apply a classic population dynamics equation:

dn(s,t)/dt = -d[n(s,t)g(s,t)]/ds - u(s)n(s,t)

s: Weight (g)
t: Time
n: Number of individuals of weight s
g: Scope for growth (g day-1)
u: Mortality rate (day-1)

4. Set mortality at 30% per year, slider allows scenarios from 30% to 80% per year

5. Determine harvestable biomass, i.e. weight class 5, 40-50 g (roughly three inches length)
Peak oil occurs not when there are
no more reserves, but when it is too expensive to bring them to the surface. The
diagram describes a dynamic where peak oil leads to oil prices that are too low
for oil companies to produce oil. There are two keys to understand this
counterintuitive situation. Firs
Peak oil occurs not when there are no more reserves, but when it is too expensive to bring them to the surface. The diagram describes a dynamic where peak oil leads to oil prices that are too low for oil companies to produce oil. There are two keys to understand this counterintuitive situation. First, it is important to realize that without energy (oil) no economic activity can take place. Second, when supplies of oil become scarce, non-elite workers  - because of the contraction of the economy - will lose their jobs or suffer salary cuts. This will make goods containing (or using) oil products too expensive for the masses. Demand for those products (most things on the market) will decline and with it demand for oil - oil prices will drop too low for oil companies to produce oil!

These ideas stem from Gail Tverberg's blog: 'Our Finite World'. https://ourfiniteworld.com/