Like previous models, this model shows the operation of a simple economy, the influence of changes in the consumption rate, and the effect of government intervention. In addition, this model shows changes in the hypothetical general price level. It gives an idea of changes in price trends based on c
Like previous models, this model shows the operation of a simple economy, the influence of changes in the consumption rate, and the effect of government intervention. In addition, this model shows changes in the hypothetical general price level. It gives an idea of changes in price trends based on changes in the quantity of money. NOTE: No general price level exists. Prices provide information for the exchange of individual economic goods.
WIP Overview model structures of Khalid Saeed's 2014  WPI paper  Jay
Forrester’s Disruptive Models of Economic Behavior  See also General SD and Macroeconomics CLDs  IM-168865
WIP Overview model structures of Khalid Saeed's 2014 WPI paper Jay Forrester’s Disruptive Models of Economic Behavior  See also General SD and Macroeconomics CLDs IM-168865
3 months ago
The housing market is heavily dependent on two main factors; supply and demand. Both play a major role in determining an equilibrium price for both sellers and buyers in the real estate market.     Residents, or the general population of individuals, place significant reliance on financial instituti
The housing market is heavily dependent on two main factors; supply and demand. Both play a major role in determining an equilibrium price for both sellers and buyers in the real estate market. 

Residents, or the general population of individuals, place significant reliance on financial institutions to provide sources of capital i.e mortgages, to fund their purchases of homes. The rate of interest charged by these organisations in turn gives buyers (consumers) purchasing power, creating demand. 

Supply is made up of the number of houses in the market, and consequently, of these, the number of houses which are up for sale. As the prices of houses for sale increases, the demand for purchase of these properties decreases. Conversely, the lower price, the higher the demand. Once the market reaches an equilibrium point, to which buyers and sellers form an agreement, houses are sold accordingly. An underlying factor to consider is the cost of construction, which impacts producers, or suppliers in this instance, and thus the number of homes for sale, and the expected profit sellers hope to achieve. 

The simulated graph highlights the common scenario within the housing market, to which we see that as price increases, the total number for houses for sale decreases, generating an opposite slope to the price. As the price for houses increases, the demand for the houses decreases and vice versa. The equilibrium is evident at time 14 whereby the price of houses and the number of houses for sale overlaps which in turn creates a market to which both buyers and sellers are happy.
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
Simpler view  IM-70351  combined with Economic View IM-69774  in preparation for integrating with Prevention Investment Framework  (private) IM  Reworked at  Multiscale simpler view IM
Simpler view IM-70351 combined with Economic ViewIM-69774 in preparation for integrating with Prevention Investment Framework (private) IM
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. Older version cloned at  IM-46280
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. Older version cloned at IM-46280
Solow model without external factors.
Solow model without external factors.
4 5 months ago
Structure of model in Nathan Forrester's 1983 MIT Thesis comprising 4 models
Structure of model in Nathan Forrester's 1983 MIT Thesis comprising 4 models
WIP based mostly on Jan
Toporowski  2013 vol 1  and  2018 vol 2  books on Michal Kalecki: An Intellectual Biography   Layout Consistent with  David Wheat MacroEconomic model CLD Insight  by Gene Bellinger  
WIP based mostly on Jan Toporowski 2013 vol 1 and 2018 vol 2 books on Michal Kalecki: An Intellectual Biography  
Layout Consistent with David Wheat MacroEconomic model CLD Insight by Gene Bellinger  
Summary of Ch 27 of Mitchell Wray and Watts Textbook see  IM-164967  for book overview See  IM-169093  for added dynamic evolutionary economics history
Summary of Ch 27 of Mitchell Wray and Watts Textbook see IM-164967 for book overview See IM-169093 for added dynamic evolutionary economics history
 Wealth can be seen as the factories,
infrastructure, goods and services the population of a nation dispose of. According
to Tim Garrett,  a scientist who looks at
the economy from the perspective of physics, it is existing wealth that generates
economic activity and growth. This growth demands the

Wealth can be seen as the factories, infrastructure, goods and services the population of a nation dispose of. According to Tim Garrett,  a scientist who looks at the economy from the perspective of physics, it is existing wealth that generates economic activity and growth. This growth demands the use of energy as no activity can take place without its use. He also points out that the use of this energy unavoidably  leads to concentrations of CO2 in the atmosphere.  All this, Tim Garrett says,  follows from the second law of thermodynamics.  If wealth decreases then so does economic activity and growth. The CLD tries to illustrate how wealth, ironically, now generates the conditions and feedback loops  that  may cause it to decline. The consequences are  inevitably economic  stagnation (or secular recession?). 

You can read about the connection Tim Garrett makes between 'Wealth, Economic Growth, Energy and CO2  Emissions' simply by Googling 'Tim Garrett and Economy'.

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)
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,
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.