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Economic capital growth model, Figure 27 from Thinking in Systems by Donella H. Meadows
REM 221 – Figure 27 - Economic Capital Growth
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• This model examines how sustainable consumerism is from social, economic, and environmental aspects. The question in focus is "How will our second-hand clothing donations affect communities in developing countries, specifically Kenya?"

5 Stock Variables: 
• U.S. Consumers
• Multinational Corporations
• Overseas Factories
• Kenya

Highlight Findings: 
To sum up, there are 4 major problems associated to donations:
• 1. Source of problem is the consumer: Cheap deals attract hundreds of millions in revenue for fast fashion, and contribute to 100,000 tonnes of clothing to Kenya annually. 
• 2. Rapid consumerism leads to over-utilization of slowly-renewable resources, such as water.
• 3. Nearly 96% of textiles jobs are eradicated by the massive inflow of clothing donations to Kenya. 
• 4. The offshoring of textiles jobs enrages U.S. blue-collar workers, leading to the rise of protectionism.  



Environmental, social, and economic sustainability aspects of textiles donations
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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.")

In summary, lower rates of consumption (based on production) result in higher rates of production and consumption in the long-run. Rates of consumption over 100% of production will diminish the savings stock and eventually cause rates of production and consumption to fall.
Simple Economy: Model 6
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Deforestation and Economic Development in an Underdeveloped County
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​In a recent report, the World Economic Forum considered that the use of robots in economic activity will cause far more job losses in the near future than there will be new ones created. Every economic sector will be affected. The CLD tries to illustrate the dynamic effects of replacing human workers with robots. This  dynamic  indicates that if there is no replacement of the  income forgone by the laid off workers, then the economy will soon grind to a halt. To avoid disaster, there must be enough money in circulation, not parked in off-shore investments, to permit the purchase of all the goods and services produced by robots. The challenge for the government is to make sure that this is  case.  

ROBOTS AND A DISATROUS ECONOMIC DYNAMIC
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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.
Simple Economy: Model 9
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Solow model without external factors.
Solow Model
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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'.

ECONOMIC GROWTH WILL MAKE EVERYTHING WORSE
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economic capital has a reinforcing loop (investment of output) governing growth and a balancing loop (depreciation) governing decline.
2 months ago
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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.

Pesticide Use in Central America Model
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Method with the feedback loops
Dynamic_Model_System dynamics approach to Isernia CBA
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Taken from Saeed, Khalid. ‘Limits to Growth Concepts in Classical Economics’. In Feedback Economics: Economic Modeling with System Dynamics, edited by Robert Y. Cavana, Brian C. Dangerfield, Oleg V. Pavlov, Michael J. Radzicki, and I. David Wheat, 217–46. Cham: Springer International Publishing, 2021. https://doi.org/10.1007/978-3-030-67190-7_9.

Note that I haven't been able to reproduce the reported results!
Marxian economic growth
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Simpler view IM-70351 combined with Economic ViewIM-69774 in preparation for integrating with Prevention Investment Framework (private) IM
Reworked at Multiscale simpler view IM
Integrating Simple and Economic Views of Prevention
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Backup: MONEY_People, Experts. Knowledge IPN_Model2_Oscillations_R_0.2.2.B
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Economic capital growth model, Figure 27 from Thinking in Systems by Donella H. Meadows
Economic Capital Growth
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Do you like travelling? Find out how we can help make it more sustainable!

Images used:
Suitcase: 
http://vignette2.wikia.nocookie.net/animaljam/images/a/ab/Travel-suitcase_(1).png/revision/latest?cb=20140907211051
Fiji: http://cdn.newsapi.com.au/image/v1/91c1263a2a357b3673af8ff8362c0c8d?width=1024
Hotels:
https://taj.tajhotels.com/content/dam/luxury/hotels/taj-palace-delhi/images/master2/16x7/38849817-H1-Exterior_1-16x7.jpg
Poverty:
http://www.montana.edu/extensionecon/images/povertywordcloud.jpg
Leverage Point
https://image.slidesharecdn.com/genderinintegratedsystemsresearchbycynthiamcdougallseniorscientistgenderequitythemeleader-150311041710-conversion-gate01/95/gender-in-integrated-systems-research-by-cynthia-mcdougall-senior-scientist-gender-equity-theme-leader-25-638.jpg?cb=1426065542

Sources:
https://www.statista.com/statistics/270422/forecast-for-2020-arrivals-of-foreign-tourists-worldwide/

http://www.sustainabletourism.net

Week 10 Lecture- Dr. David Tindall Lecture pdf

https://www.adb.org/countries/fiji/poverty

Economic Impact of Tourism on Fiji's Economy: Empirical Evidence from Computable General Equilibrium Model by Paresh Kumar Narayan

https://www.wttc.org/-/media/files/reports/economic%20impact%20research/countries%202015/fiji2015.pdf

http://sustainabletravel.org/our-work/regional-alliances/pacific/hotel-sustainable-resources-pacific/

http://reusegraywater.com/about-us/

Rubin, K.E., The Valuation of Hotels and Motels for Assessment Purposes, 1984

https://en.wikipedia.org/wiki/Leverage-point_modeling

Meadows, D.H., & Wright, D. (2009). Thinking in systems: a primer, London: Earthscan.






Sustainable Tourism (Final)
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Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.
Wrong Q2 Final Project w/ socio-economic
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​BACKGROUND:

The following simulation model demonstrates the relationship between supply, demand and pricing within the real estate and housing world. I have based the model on a small city with a population of 100,000 residents as of 2015. 

AXIS:

X-Axis
The X-Axis shows the time. It begins in 2015 in the month of October and continues for 36 consecutive years. 

Y-Axis
There are 2 Y-Axis on this model. The left hand side relates to the price, demand, and supply, while the right hand side solely lists the population.

As you could see, this town has a population of 100,000 residents to-date. The bottom of the model shows a population loop that produces an exponential growth rate of 2.5%. This dynamic and growing city populates approximately 240,000 residents after 36 years.

MODEL

The model consists of 2 folders named: Buyers/Consumers & Suppliers/Producers. This first folder represents the 'Demand'. It includes a buyers growth rate, buyers interest increase and decrease, a price demand and the demand price. The formulas form an exponential rise in demand due to the rapid and continuous increase in population in this new city. As population increases, so does the demand from buyers. 

The second folder conveys the supply of houses. It includes a sophisticated loop of real estate. Residents who own houses in the market decide to sell the home. This becomes the Houses for sale, also known as the 'supply'. Those houses are sold and the sold houses re-enter the market and the loop continues. 

The supply has an inverse relationship with the price. When prices drop, supplies drop because the demand goes up. And when the price goes up, so does the supply. This will represent the growth of new houses in the market. 

PRICE

Note: The price is based on monthly rent rates.

The price is dependant on many variables. Most importantly, the supply and demand. It also includes factors such as expectations & the economic value of the house. I have included a stable, 'good' economic value for all homes as this fictional town is in a stable and growing area.

Price fluctuates throughout the entire simulation, however it also goes up in price. Over the years houses continue to rise in price while they regularly fluctuate. For example, in 2018 (3 years later), the max price for a home was: $4254.7 and min price was: $852.98. On the other hand, in October 2051 (36 years later), the max price was: $14906 and the min price was: $7661. (This is based on the following data: Houses for Sale: 500, Houses that have sold: 100, Houses in the Market: 730).

SLIDERS

There are 3 sliders on the bottom that could be altered. The simulation would react accordingly. The 3 sliders include changeable data on:
- Houses for Sale.
- Houses that have Sold.
- Houses in the Market.


Real Estate Simulation Assignment - Mitchell Bassil 43290264
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Implementação do modelo Handy.

Referência:

Motesharrei, S.; Rivas, J.; Kalnay, E. "Human and nature dynamics (HANDY): Modelling inequality and use of resources in the collapse or sustainability of societies". Ecological Economics 101 (2014) 90-102

http://www.sciencedirect.com/science/article/pii/S0921800914000615
HANDY
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Calculating EOQ using classical inventory model
Economic Order Quantity
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Overview of Part F Ch 25 and 26 of Mitchell Wray and Watts Textbook see IM-164967 for book overview
Economic Instability
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Semirara island Casual Loop Diagram
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This model attempts to illustrate a Strong Towns' perspective of municipal financing of our communities based on a development Growth Ponzi Scheme. http://www.strongtowns.org/the-growth-ponzi-scheme/ 

The communal economic investment by the community to help generate future economic prosperity and improve the community's quality of life. 

If the community generates greater economic prosperity as a result of the Near Term Cash either directly through increased Municipal Revenue or indirectly through the enhancement of Community Wealth Generators and Place Making improvements within the community then it is a desirable investment. 

If, however, it leads to ever increasing debt and the chasing of outside investments with the community as the means of collateral then it is a Growth Ponzi Scheme and the community needs to create some new paradigms to find a different path. 
Ponzi Growth Scheme Strong Towns
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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.)

In summary, lower rates of consumption (based on production) result in higher rates of production and consumption in the long-run.
Simple Economy: Model 8