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The World Socio-Economics model is computer model to simulate the consequence of interactions between the earth and human systems based on the World3 model by the work of Club of Rome, The Limits to Growth[1].

The World3 model builds by system dynamics theory that is has an approach to understanding the nonlinear behaviour of complex systems over time using stocks, flows, feedback loops, table functions and time delays.

The Limits to Growth concludes that, without substantial changes in resource consumption, "the most probable result will be a rather sudden and uncontrollable decline in both population and industrial capacity".

Since the World3 model was originally created, it has had minor tweaks to get to the World3-91 model used in the book Beyond the Limits[2], later improved to get the World3-03 model used in the book Limits to Growth: the 30 year update[3].

References;

[1] Meadows, Donella H., Meadows, Dennis L., Randers, Jørgen., Behrens III, William W (1972). The Limits to Growth.

[2] Meadows, Donella H., Dennis L. Meadows, Randers, Jørgen., (1992). Beyond the limits: global collapse or a sustainable future.

[3] Meadows, Dennis., Randers, Jørgen., (2004). The limits to growth: the 30-year update.

World Socio-Economics model 2000-2100

滑川英樹

47 10 months ago

Based on G.P. Cimellaro et al. Framework for analytical quantification of disaster resilience Engineering Structures 32 (2010) 3639–3649 paper

Facilities Disaster Resilience

Geoff McDonnell

Brainstorming - Scoping constraints of tradeoff microanalysis

Laura Anne Geronimo

A system dynamics model to CBA of smart grid project

STATIC_Model_System dynamics approach to Isernia CBA Case

Jose Angel L V

11

Model description:

This model is designed to simulate the outbreak of Covid-19 in Burnie in Tasmania. It also tell us the impact of economic policies on outbreak models and economic growth.

Variables:

The simulation takes into account the following variables and its adjusting range:

On the left of the model, the variables are: infection rate( from 0 to 0.25), recovery rate( from 0 to 1), death rate( from 0 to 1), immunity loss rate( from 0 to 1), test rate ( from 0 to 1), which are related to Covid-19.

In the middle of the model, the variables are: social distancing( from 0 to 0.018), lock down( from 0 to 0.015), quarantine( from 0 to 0.015), vaccination promotion( from 0 to 0.019), border restriction( from 0 to 0.03), which are related to governmental policies.

On the right of the model, the variables are: economic growth rate( from 0 to 0.3), which are related to economic growth.

Assumptions:

(1) The model is influenced by various variables and can produce different results. The following values based on the estimation, which differ from actual values in reality.

(2) Here are just five government policies that have had an impact on infection rates in epidemic models. On the other hand, these policies will also have an impact on economic growth, which may be positive or negative.

(3) Governmental policy will only be applied when reported cases are 10 or more.

(4) This model lists two typical economic activities, namely e-commerce and physical stores. Government policies affect these two types of economic activity separately. They together with economic growth rate have an impact on economic growth.

Enlightening insights:

(1) In the first two weeks, the number of susceptible people will be significantly reduced due to the high infection rate, and low recovery rate as well as government policies. The number of susceptible people fall slightly two weeks later. Almost all declines have a fluctuating downward trend.

(2) Government policies have clearly controlled the number of deaths, suspected cases and COVID-19 cases.

(3) The government's restrictive policies had a negative impact on economic growth, but e-commerce economy, physical stores and economic growth rate all played a positive role in economic growth, which enabled the economy to stay in a relatively stable state during the epidemic.

Model of COVID-19 Outbreak in Burnie, Tasmania

LILI LIU

This Insight is used for simulating growth of a company with specified parameters.

CompanyGrowth

Stanislav Kubis

Summary of Ch1 of Mitchell Wray and Watts Textbook see IM-164967 for overview

Macroeconomics Introduction

Geoff McDonnell

56

Causal loop diagram on an extension of the US budget because of corona in connection to the Chinese budget for the sake of a discussion (in Dutch)

Financiering VS lening

Henny van Dongen

Summary WIP of Thomas Palley's 2012 Book

From Financial Crisis to Stagnation

Geoff McDonnell

There are many reasons why reality does not alter doctrines. Some of the factors and their dynamics are shown in the CLD.

However, an unchanging doctrine may prompt actions that influence and change reality. Do ill-adapted doctrinal reactions not increase the complexity in the world, potentially making everything worse? Some Neoliberal economic remedies come to mind.

THE INALTERABILITY OF DOCTRINES TENDS TO INCREASE COMPLEXITY

Hanns-Jürgen Hodann

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

Abi Wells

This simple model describes wealth accumulation. The value in income is described by the following simple equation:

simple wealth accumulation model

Larry Lee

24

Michael Marmot's Eur J Epidemiol Essay 2017 See also IM-62760 Social determinants of health from Michael Marmot's ABC 2016 Boyer Lectures on Social Justice and the Health Gap

Social Justice, Epidemiology and Health Inequalities

Geoff McDonnell

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

Steve Conrad

369

ISCI 360 Project - Stage 2

Our model examines the relationship between two straw types (plastic straws and biodegradable straws) and their impact on the environment and economics. Specifically, we are interested in figuring out whether biodegradable straws are a viable solution to plastic straws.

Our model is broken down into three aspects: Social, Environmental and Economic. Color coding is used to differentiate between the different aspects and is explained below:

Turquoise represents the social aspect.

Purple represents the economic aspects.

Green represents the environmental aspects.

Blue represents other crucial stocks and flows in the model that do not necessarily fit into the three aspects above.

In our model, the Canadian population is assumed to increase steadily until a carrying capacity is reached. This can be seen in the graph as the line increases linearly before plateauing indefinitely. We assumed that we will be able to maintain the population at our carrying capacity due to technological advances.

Social Aspect:

The social aspect refers to the impact that awareness of the detrimental costs of straws can have on the usage of straws. The two flows that contribute to awareness are word of mouth (i.e. your friends and family informing you about the effects of straws and influencing you to stop using them) and media coverage (i.e. the media highlights the effects of straws). Both of these flows are dependent on the Canadian population such that 25% of the Canadian population at any time will be impacted by word of mouth or media coverage. (Side note: since word of mouth and media coverage are dependent on the Canadian population, they will plateau when the population does.) This is an arbitrary number but was chosen to show what a change in perspectives of the Canadian population can do. These flows input into an 'awareness of detrimental effects of using plastic straws' stock that reduces the number of plastic straws being used.

Plastic Straws

According to data from the United States individuals usually use 1.6 straws everyday and thus, we have assumed that to be true in Canada as well. Plastic straws start at a base value (due to the previous straw usage) and grow with the Canadian population while subtracting the awareness component of the model.

Environmental Aspect

Since the decomposition of plastic versus paper is significantly different, the amounts that accumulate in the ocean and landfills can be monitored. In addition, the impact on the environment can be monitored. Since plastic straws take longer to decompose, they have a larger impact on wildlife in the ocean than biodegradable straws. Thus, as the plastic straw usage decreases, the amount of habitat loss occurring plateaus. We have also included the aspect of clean-up in which the plastic from the ocean can be moved to the landfill. You will notice that the habitat loss plateaus but does not decrease. This is because we cannot reverse the damage we have done (without additional rigorous clean-up) but can mitigate additional damage. (Please note that clean-up affects only the stock 'Plastic Straws in the ocean' and thus, does not affect the stock 'habitat loss.' Therefore, clean-up will reduce the number of plastic straws in the ocean and indirectly affect the stock 'habitat loss.' However, it will not clean up the plastic straws already impacting 'habitat loss.')

Economic Aspect

The economic aspect monitors the amount of money it takes to make plastic straws versus biodegradable straws and the amount of money the government needs to fund ocean clean-ups. It can be seen that a the usage of plastic straws decreases, the need for clean-up money from the government decreases. However, there is a base level of damage that has already been done by us and thus, larger scale clean-ups will be needed to reverse that. In other words, smaller clean-ups will mitigate the damage we are currently doing but not reverse the damage we have already done. We can also track the cost of making each straw; it can be seen that biodegradable straws are more expensive to make.

However, the energy required to make the straws is less for biodegradable straws than plastic straws. Thus, there are trade-offs for using biodegradable straws.

Although, biodegradable straws are more expensive, they require less energy to make, decompose faster, require less funding for clean-up and impact the wildlife in the ocean to a lesser degree.

Project Stage 2

Eisha Sharda

Investigations into the relationships responsible for the success and failure of nations. This investigation was prompted after reading numerous references on the subject and perceiving that *Why Nations Fail: The Origins of Power, Prosperity, and Poverty* by Acemoglu and Robinson seem to make a great deal of sense.

@LinkedIn, Twitter, YouTube

Why Nations Fail

Gene Bellinger

18

Economics model

Arkadiy Simonov

Enunciado do ploblema do projeto:

https://docs.google.com/file/d/0B-QIzc4nqMvKdWJLdEZXSzJMTzA/edit?usp=sharing

Perquentas e problemas

https://docs.google.com/document/d/1-e5AFCR_wXCamHt_JJt_j045YCKeQ-woegZT7y3Fe80/edit

simulador economico

https://projetobiomassa.slack.com/messages/C02FPF8GF/files/F59249AKT/

NOME E DESCRIÇÃO

LINK

TAMANHO

Prova1.Investimento Fixo e Tomada de Decisões Rápidas

https://canvas.instructure.com/courses/780776/files/folder/provahtml?preview=51184101

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Prova.2.Investimento método Lang

https://canvas.instructure.com/courses/780776/files/folder/provahtml?preview=51184144

32 KB

Prova 3 Investimento Fixo método Chilton

ihttps://canvas.instructure.com/courses/780776/files/folder/provahtml?preview=51184169

33 KB

Prova4:Custo Fixo

https://canvas.instructure.com/courses/780776/files/folder/provahtml?preview=51184189

32 KB

Prova 5:Custo de mao de obra

customaohtm custo de mao de obra

33 KB

Prova 6 Custo de mat,comb e enegia

CustoMat prima , energia

34 KB

Prova 7 Custo total

custo de operacional de producao

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Prova 8 Ponto deEquilibrio

ponto de eqilibrioibrio

32 KB

Prova 9:Analise de lucro e beneficios

Fluxo de caixa

33 KB

Simulacao e otimizacao economica Miniemporesa

Pagandai V Pannir Selvam

40

This model is based on the article Dynamic modeling of Infectious Diseases, An application to Economic Evaluation of Influenza Vaccination Farmacoeconomics 2008, 26(1): 45-56 .

And EBOLA

Dynamic Modeling of Infectious Diseases

Guy Lakeman

4

A systems model of the relationships amongst economic situation, health situations and Covid-19 in Burnie, Tasmania.

Health situation

According to exposed and go out population decreases, the population of infected decreases after a stable high cases period.

Economic situation

When the infected population decreases, the population economic recovery increases over time, then become stable after a period of time.

BMA708 Assessment 3 Complex system

Jingyi Qiu

This is a reconstruction of the SIMM model presented in Chapter 2 of Feedback Economics (Contemporary Systems Thinking)

@LinkedIn, Twitter, YouTube

Simple Macroeconomic Model (SIMM) (SFD)

Gene Bellinger

9

Explanation of the Model

The sample model demonstrate the COVID-19 outbreak in Burnie, Tasmania appearing how the government reacts by executing important health approaches and the impacts on the economy of the region

Assumptions

The economic growth rate is subordinate on the extent of the populace who can be exposed. The number of COVID-19 cases adversely impacts the economy. The government arrangement is activated when the COVID-19 cases are 10 or above

Interesting Insights

1. There is a positive relationship between exposure to COVID- 19 and economic growth rate. Since the more individuals go out, the more trade activity takes place and that ultimately results economic growth

2. Expanding the testing rate results

- Higher cases being recognized

- Strict government intervention

- Less deaths

BMA708_Assignment3_Md Shihabul Islam_548056

Md Shihabul Islam

Adam Smith's The Invisible Hand: The Feedback Structure of Markets. From Sterman JD Business Dynamics p170 Fig 5-26. A price-mediated resource allocation system..

Price control mechanism

Geoff McDonnell

6

About the Model

This model is a dynamic model which explains the relationship between the police of the government and the economy situation in Burnie Tasmania after the outbreak of Corona Virus.

This model is based on SIR model, which explains the dynamic reflection between the people who were susceptible, infected,deaths and recovered.

Assumptions

This model assumes that when the Covid-19 positive is equal or bigger than 10, the government policy can be triggered. This model assumes that the shopping rate in retail shops and the dining rates in the restaurants can only be influenced by the government policy.

Interesting Insights

The government police can have negative influence on the infection process, as it reduced the possibility of people get infected in the public environments. The government policy has a negative effect on shopping rate in retail shops and the dining rate in the restaurants.

However, the government policy would cause negative influence on economy. As people can not shopping as normal they did, and they can not dinning in the restaurants. The retail selling growth rate and restaurant revenue growth rate would be reduced, and the economic situation would go worse.

Corona virus outbreak in Burnie Tasmania (Xuexiao Zhang 538712)

Xuexiao Zhang