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This is a first attempt to illustrate the interconnected nature of the economic assets of Roswell - Chaves County
RCC economic model
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This seeks to model increasing improvements in long run economic growth potential as the education level increases.
LR Economic Growth
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Economic growth model v.1
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Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.
This Scenario hits Affluence (1% decrease per annum) to increase decarbonization of energy
Final Project 2 W/ Socio-Economic Factors - Reinvestment Scenario
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​Climate Sector Boundary Diagram By Guy Lakeman
 Climate, Weather, Ecology, Economics, Population, Welfare, Energy, Policy, CO2, Carbon Cycle, GHG (green house gasses, combined effects)

As general population is composed of 85% with an education level of a 12 grader or less (a 17 year old), a simple block of components concerning the health of the planet needs to be broken down into simple blocks.
Perhaps this picture will show the basics on which to vote for a sustained healthy future
Democracy is only as good as the ability of the voters to FULLY understand the implications of the policies on which they vote., both context and the various perspectives.   National voting of unqualified voters on specific policy issues is the sign of corrupt manipulation.

Climate Sector Boundary Diagram of Guy Lakeman
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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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Output vs. depreciation from Meadows
Economic Loop
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Image Used;
Title: Industry Cliparts
Source: http://clipart-library.com/industry-cliparts.html
Creator: Clipart Library

Book: Meadows, D. H., & Wright, D. (2009). Thinking in systems: a primer. London: Earthscan.
Economic Capital
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Peak oil will occur when it is too expensive to bring oil to the surface and not when reserves reach their limit. Companies must make a profit to be able to extract oil and stay in the oil business.  However, that endeavour is becoming more and more difficult because of diminishing returns. They have to dig ever deeper to get to the oil  at ever increasing costs, and the oil they find deep down is of a lesser quality.  We have now reached a point where the price needed by oil companies to make a profit and stay in business is far higher than the price  the market can bear. That price is probably about $ 100 per barrel - and rising every year! A market price o $ 100 will almost certainly cause a sharp recession and cause the price of oil to fall back beyond the point of profitability. For example, the combined profit of ExxonMobile, Chevron and Conocophillips fell from 80.4 billion in 2011 to only 3.7 billon in 2016 - see URL below. What the market can bear depends on the spending power of the mass of non-elite workers. The CLD shows the negative feedback loops that prevent oil prices to rise above the level of  affordability. If non-elite workers cannot afford the goods and services offered,  then there will be no demand for them and by extension for oil.  In this situation the market price will not the cover the cost that oil companies need to extract oil. Oil supplies will decline and so will economic activity!

https://srsroccoreport.com/the-blood-bath-continues-in-the-u-s-major-oil-industry/

THE PRICE TRAP AND PEAK OIL
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An initial study of the economics of single use coffee pods.
Matilde's Coffee Pods ISD Humanities v 1.02
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Description
This model attempts to show the complex interactions between the youth population of Bourke, the justice system, and community engagement programs. This model takes into consideration 3 key variables; the current socio-economic climate of Bourke, the number of police officers, and government funding allocated for community engagement programs. The models goal is to simulate the effects of the above specified variables on the youth population of Bourke. 

Component Explanation 
Total Youth Population - The total youth population of Bourke, set to an initial value of 100 to represent 100% of the youth population. 

Stable Youth Population - Stable youth population is representing the proportion of youth in Bourke that have a stable upbringing and are not at risk of committing crime. Proportion can be altered by use of the socio-economic factors slider. 

At Risk Youth Population - At risk youth population is representing the proportion of youth in Bourke that have an unstable upbringing and are at risk of committing crime. Proportion can be altered by use of the socio-economic factors slider. 

Youth Crime - Is the amount of crime being committed by youth in Bourke. 

Youth Detention - Is the amount of youth being detained for criminal activity.  

Participants in Community Engagement Programs - The amount of the youth population that are being engaged to participate in community programs, such as football or netball clubs. 

Youth Run Community Programs - Youth that have been engaged by community programs who go that step further and become more heavily involved in there club, such as coaching or youth leadership roles. 
*NOTE* The goal of this stock is to attract at risk youth that are only involved as their friends are running it and take them out of that at risk population stock. 

Socio-Economic Factors - Takes into consideration the factors of government and economy to give a proportion of stable and at risk youth. Slider goes between 0 and 1, 0=100% at risk, 1= 100% stable. 

Police Officers - The amount of police officers present in Bourke. Slider goes between 2 and 53, 2 assuming 1 officer is  patrolling and 1 running the station. 53 as the average wage of a NSW police officer is $75000, so with $4000000 available 53 is the most that Bourke could pay. 

Program Funding - The funding for community engagement programs. The more higher funding for a the programs the higher the level of youth engagement. Slider values between $25000 and $3850000 as it shares the same $4000000 that the police wages come out of. 
*NOTE* program funding slider set step at $75000, which is the average annual salary of a police officer. 
*NOTE* when program funding goes up 1 slider step the police officer slider step must go down and vice versa. In order to maintain the $4000000 available for use.  

Interesting Results
- The populations follow a cyclic trend based on the 6 month detention youth offenders. 

-With a smaller amount of police officers and a higher funding for community programs a high proportion of at risk youth get involved with community programs instead of crime. 

- With a high amount of police officers and little funding for community programs. The stable youth population goes on a upward trend and the at risk youth population turn to crime and end up in detention. 

Bourke Justice Reinvestment Model (Ryan Tucker 44648995)
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This is a toy model of an investment market.

Households follow a simple ratio to invest in bonds or equities.  In part, the investment decision is stochastic, such that stock market returns are volatile, with equities more volatile than bonds and with a higher yield. As such, the system shows increasing volatility as the investment bubble grows.


Investment Markets
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WIP Exttension of IM-172005 Simulation of Goodwin01 Minsky Model. Compare with Part3 slide 5 of presentation in patreon

Goodwin02 Minsky Simulation Keen Economic Dynamics Aug2019
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• This model examines how sustainable consumerism is from social, economic, and environmental aspects.  

The environmental, social, and economic sustainability aspects of consumerism
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Estruturas dev  miniempresa  e  balanco de massa de calculadora de consumo paaso1 um de  projeto de sintese   de  fluxogramas  visando sintese  Gestao de viabilidade  tecnologicas via  diversos fluxogramasde blocos  ,procesos , Analise  de  fluxo materials  de  sistemas  miniempresa  industrial

https://docs.google.com/spreadsheets/d/1DIYxae_Cgpa3n53KTMrMdj8pBYCmNeJlVM_CB_xpUi4/edit#gid=9
Matches' 275 Equipment Cost Estimates.
www.matche.com/equipcost/Default.html
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Matches provides 275 process equipment conceptual capital costs estimates.
Exchanger, Heat · ‎Index of Process Equipment ... · ‎Tank · ‎Vessel
Equipment Costs for Plant Design and Economics for Chemical ...
www.mhhe.com/engcs/chemical/peters/data/
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Instructions for file “EQUIPMENT COSTS” accompanying Plant Design and Economics for Chemical ... When entries are complete, CLICK on CALCULATE.
Plant Design and Economics for Chemical Engineers | Cost Estimator
highered.mheducation.com/sites/.../student.../cost_estimator.html
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McGraw-Hill Online, Learning Center. Student Center | Instructor Center | Information Center | Home ...Cost Estimator. Please click here to use the Cost Estimator.
[PDF]
Passo 1 Projeto de eng de Estruturas empresa ,Balanco de massa e calculadora de consumos
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Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.
Q2 Final Project w/ socio-economic
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COVID-19 outbreak in Burnie Tasmania Simulation Model

Introduction

This model simulates how COVID-19 outbreak in Burnie and how the government responses influence the economic community.  Government responses are based on the reported COVID-19 cases amount, whcih is considered to be based on testing rate times number of people who are infected minus those recovered from COVID-19 and dead.
Government interventions include the implement of healthy policy, border surveillance, quarantine and travel restriction. After outbreak, economic activities are positively affected by the ecommerce channel development and normal economic grwoth, while the unemployement rate unfortunately increases as well. 

Assumption
  • Enforcing government policies reduce both infection and economica growth.                                                                                                         
  • When there are 10 or greater COVID-19 cases reported, the governmwnt policies are triggered.                                                          
  • Greater COVID-19 cases have negatively influenced the economic activities.                                                                                             
  • Government policies restict people's activities socially and economically, leading to negative effects on economy.                                          
  • Opportunities for jobs are cut down too, making umemployment rate increased.                                                                                   
  • During the outbreak period, ecommerce has increased accordingly because people are restricted from going out.                                  
Interesting insights

An increase in vaccination rate will make difference on reduing the infection. People who get vaccinated are seen to have higher immunity index to fight with COVID-19. Further research is needed.

Testing rate is considered as critical issue to reflect the necessity of government intervention. Higher testing rate seems to boost immediate intervention. Reinforced policies can then reduce the spread of coronvirus but absoluately have negative impacts on economy too.
Mengling Xue 561743 BMA708_Marketing insights into Big Data
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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
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Implementation of the Solow model of economic growth with labor enhancing technology.

parameters: s, alpha, delta, n, gA
variables: Y. K, L, C, A
per capita variables: y, k, c, a
per capita and technology variables: y~, k~, c~
steady state variables: y~*, k~*, c~*
all variables come with relative growth rates g

Features:

+steady state from beginning
+one time labor shock
+permanent savings quote shock
+permanent technological growth rate shock

Decreasing steady state variables when starting in steady state are numeric artifacts.
Solow growth model v1.0
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Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.
Final Project 1 W/ Socio-Economic Factors
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System Thinking and Modelling of Biophysical, Socio-economic and Cultural components of Barangay Iwahig - Judy Ann Simil
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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.

REM 221 - Causal Loop diagramming
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Based on the SIR (Susceptible, Infected, Recovered) model of disease, this is an upgraded model with more specifc vaeriables.
Insights:
When the growth rate and the number of the recovered is much larger than deaths, the economic activity remain steady growing.
Model of COVID-19 outbreak in Burnie Tasmania