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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.
The effect of Supply and Demand on the Housing Market Assignment 3 (43323871)
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The Logistic Map is a polynomial mapping (equivalently, recurrence relation) of degree 2, often cited as an archetypal example of how complex, chaotic behaviour can arise from very simple non-linear dynamical equations. The map was popularized in a seminal 1976 paper by the biologist Robert May, in part as a discrete-time demographic model analogous to the logistic equation first created by Pierre François Verhulst

Mathematically, the logistic map is written

where:

 is a number between zero and one, and represents the ratio of existing population to the maximum possible population at year n, and hence x0 represents the initial ratio of population to max. population (at year 0)r is a positive number, and represents a combined rate for reproduction and starvation.
For approximate Continuous Behavior set 'R Base' to a small number like 0.125To generate a bifurcation diagram, set 'r base' to 2 and 'r ramp' to 1
To demonstrate sensitivity to initial conditions, try two runs with 'r base' set to 3 and 'Initial X' of 0.5 and 0.501, then look at first ~20 time steps

The Logistic Map
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Simple model of the global economy, the global carbon cycle, and planetary energy balance.

The planetary energy balance model is a two-box model, with shallow and deep ocean heat reservoirs. The carbon cycle model is a 4-box model, with the atmosphere, shallow ocean, deep ocean, and terrestrial carbon. 

The economic model is based on the Kaya identity, which decomposes CO2 emissions into population, GDP/capita, energy intensity of GDP, and carbon intensity of energy. It allows for temperature-related climate damages to both GDP and the growth rate of GDP.

This model was originally created by Bob Kopp (Rutgers University) in support of the SESYNC Climate Learning Project.
Simple Climate-Carbon-Economic Model
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WIP of several books of Karl Polanyi's thoughts and papers around social science economic history and capitalism. . See also Summary of the Great Transformation IM-10640
Karl Polanyi Holistic thinking
3 3 months ago
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Simulation of Goodwin01 Minsky Model CLD in IM-172002 Compare with Part3 slide 3 of presentation in patreon. See extension Goodwin02 at IM-172145

Goodwin Minsky Simulation Keen Economic Dynamics Aug2019
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Map of SD work on Samuelson's 1939 model of the business cycle. See also D-memo D-2311-2 Gilbert Low 1976 and IM-165713. An alernative to the Ch 26 Macroeconomics textbook exposition.  From Gil Low's Multiplier Accelerator Model of Business Cycles, Ch 4 of Elements of the System Dynamics Method Book edited by Jorgen Randers 1976 (MIT Press) and 1980 (Productivity Press)
Samuelson multiplier accelerator model
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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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Deforestation and Economic Development in an Underdeveloped County
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climate change
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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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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
Circularity in Economic models including Exports and Imports
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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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Calculating EOQ using classical inventory model
Economic Order Quantity
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Method with the feedback loops
Dynamic_Model_System dynamics approach to Isernia CBA
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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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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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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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Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.
Wrong Q2 Final Project w/ socio-economic
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Simple model of the global economy, the global carbon cycle, and planetary energy balance.

The planetary energy balance model is a two-box model, with shallow and deep ocean heat reservoirs. The carbon cycle model is a 4-box model, with the atmosphere, shallow ocean, deep ocean, and terrestrial carbon. 

The economic model is based on the Kaya identity, which decomposes CO2 emissions into population, GDP/capita, energy intensity of GDP, and carbon intensity of energy. It allows for temperature-related climate damages to both GDP and the growth rate of GDP.

This model was originally created by Bob Kopp - https://insightmaker.com/user/16029 (Rutgers University) in support of the SESYNC Climate Learning Project.

Steve Conrad (Simon Fraser University) modified the model to include emission/development/and carbon targets for the use by ENV 221.
REM 221 Simple Climate-Carbon-Economic Model with Targets
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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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A clone of the Goodwin cycle IM-2010 with debt and taxes added, modified from Steve Keen's illustration of Hyman Minsky's Financial Instability Hypothesis "stability begets instability". This can be extended by adding the Ponzi effect of borrowing for speculative investment: http://www.jstor.org/stable/10.2307/4538470.

This model requires development and testing. Please contact the author if you are able to help.

Minsky Financial Instability Model