Insight diagram
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
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Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.
Lab 13 Base Model
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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
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Final Loop
8 months ago
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CLD exposition of Goodwin01 from Steve Keen's August 2019 course on Introduction to Economic Dynamics and Minsky software See video and powerpoint slides. Based on IM-2011 Minsky FIH and IM-168865 MacroEconomics CLDs. SeeIM-172005 for Simulation

Goodwin cycle Minsky Keen August 2019
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A system diagram for the Mojave Desert including example socio-economic factors for an assignment at OSU- RNG 341.
Mojave Desert System Diagram with SES
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Causal loop representations of macroeconomics taken from the System Dynamics literature contrasted with Forrester's main analysis of social and business organization layers See also Saeed's Forrester Economics IM-183285
Macroeconomics causal loop diagrams
8 3 weeks ago
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An initial study of the economics of single use coffee pods.
Coffee Pods ISD Humanities - Anouk D 10.4
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Initial Stock & Flow of Energy Infrastructure Development, Climate Change Impacts, and Economic Activity
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Nobody seems to notice bubbles until they burst. One possible reason is that those caught up in a bubble are completely blinded by the grip, the overpowering logic and force excerted by the positive feedback loop that drives it. Financial bubbles occur time and time again - and nobody seems to learn. Another example on a different time scale is an argument that spins out of control and ends in violence. The participants seem to be blind to the consequences; the immediate and imperative logic of the feedback loop imposes itself. The vortex created by the feedback loop even seems to draw in outsiders, such as new investors. Is this the reason why we don't notice bubbles? This explanation is meant to stimulate discussion!

Bubbles and Feedback Loops
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Scott Page's Aggregation diagram from Complexity and Sociology 2015 article see also IM-9115 and SA IM-1163
Macro micro dynamics
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Clone of IM-91683 from jacqui and vincy Summary of paper map produced by participants at the compelling case for prevention workshop 6 june 2017. 

Current premier version containing Story Steps and text for vincy to update.
This is clone of 97129 via Vincy.
FINAL Clone of Concept Map produced by CCP Workshop 1
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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
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Socio-economic factors (kaya)
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Figs 1 and 2 of David HArvey's Companion to Marx's Grundrisse illustrating the circulation of money and value in capitalism, dubbed as "value in motion" Also Waterstone and Chomsky Consequences of Capitalism Book
Marx and Circulation of Capital and Money
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State Goverment Fiscal Policy model
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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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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
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An initial study of the economics of single use coffee pods.
3 variables-- ORIGINAL Coffee Pods ISD Humanities v 1.02
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Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.
Lab 13_All
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I made this as an illustration of a piece of text I read in Regenerative Economics, household economics.
Unpaid Care