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Social determinants of health are economic and social conditions that influence the health of people and communities. These conditions are shaped by the amount of money, power, and resources that people have, all of which are influenced by policy choices. Social determinants of health affect factors that are related to health outcomes. Factors related to health outcomes include:
  • How a person develops during the first few years of life (early childhood development)
  • How much education a persons obtains
  • Being able to get and keep a job
  • What kind of work a person does
  • Having food or being able to get food (food security)
  • Having access to health services and the quality of those services
  • Housing status
  • How much money a person earns
  • Discrimination and social support
Determinates of a healthy population
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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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Economic Model
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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. Additionally, decrease in affluence is increased by temperature increases damaging the global economy
Final Project 4 W/ Socio-Economic Factors - Investment+Temperature Degradation
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 Goodwin cycle IM-2010 with debt and taxes added, modified from Steve Keen. THis can be extended by adding the Ponzi effect of borrowing for speculative investment.

Minsky Financial Instability Model
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Urbanisation insight
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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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241004_economic growth model structure_SFD
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An initial study of the economics of single use coffee pods.
Nina Coffee Company Model *
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Laying out and testing before coupling to main model (which is Final Project)
Socio-Economic Factors
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This page provides a structural analysis of POTUS Candidate Rand Paul's economic policy based on the information at:  https://www.randpaul.com/issue/spending-and-debt and also   https://www.randpaul.com/issue/taxes  The method used is Integrative Propositional Analysis (IPA) available: ​ http://scipolicy.org/uploads/3/4/6/9/3469675/wallis_white_paper_-_the_ipa_answer_2014.12.11.pdf
DRAFT IPA of Rand Paul Economic Policy
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Overview of Part G Ch 27 to 30 of Mitchell Wray and Watts Textbook see IM-164967 for book overview
History of Macroeconomic Thought
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MONEY_People, Experts. Knowledge IPN_Model2_Oscillations_0.1.7
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Assignment 3 – Complex Systems

 Ryan Salvaggio - 43668070

 

The Model

This model conceptualizes the effects on a real-estate market-model utilizing agent based modelling. This model utilizes basic economic principles of supply and demand.

The model bases itself on two Agents - one being ‘Customers’ of the real estate market model, whilst the other being the Real estate itself, coined 'Houses'.

Consumers (Demand)

The Agent population, ‘Consumers’ specifies the total amount of people whom can potentially become buyers within the market. This is limited to 30 for conceptual purposes. The Agent ‘Consumer’ exists in two states, either being an ‘Active Customer’ (Active) or an ‘Inactive Customer’ (Inactive).  The transition from Inactive to Active occurs upon the basis that the ‘Budget’ of the Consumer meets the desired price of the marketplace, this is specified through the variable ‘Budget’ defining the probability that this transition will occur – this is adjustable by the user indicating a highly resistive or by accepting the market. ‘Budget’s probability in a real life scenario would be based upon numerous factors however conceptually utilizing the slider can present many of these various situations.

Upon transitioning into an active state an ‘Active consumer’ will attempt to find the closest ‘For sale household’, this is represented and carried out through the ‘Enter’ action.  Upon finding a household the consumer and house will both return to their respected inactive state thus repeating the process.

Demand – ‘Count of active customers – demand’ is then calculated by a count of Consumers transitioned and currently in the Active state. A high demand would be indicative through a high ‘Budget’ responsiveness whilst a low demand would be indicative of a low ‘Budget’ responsiveness. The increase in Price and hence supply of household thus reduces demand and vise versa.  

House (Supply)

The Agent population, ‘Houses’ specifies the total amount of households that can potentially become for sale within the market. This is limited to 112 for conceptual purposes. The Agent ‘House’ exists in two states, either being ‘For Sale’ (Active) or ‘Not for Sale’ (Inactive).  The transition from Inactive to Active occurs upon the basis that the ‘Motivation to Sell’ of the House is satisfied, this satisfaction is specified by a set probability that this transition will occur – this is adjustable by the user indicating a highly responsive or restricted house market. ‘Motivation to sell’ probability in a real life scenario would be based upon numerous factors however conceptually utilizing the slider can present many of these various situations.

Upon transitioning into an active state a ‘For Sale’ house will wait for an ‘Active Customer’ ‘this is represented and carried out through the ‘Search’ action. Upon completion of the action both states become inactive and the process continues.

Supply – ‘Count of houses for sale –supply’ is then calculated by a count of Houses ‘For Sale’ that are currently in the active state. Ultimately a high Motivation to sell would sharply increase supply, whilst a low motivation would have the adverse effects.  

Movement Speed

Movement speed – describes the base movement rate of Consumers. This variable describes the transition into the ‘Inactive’ state of a consumer, ultimately when a household is found and purchased. Movement speed affects both demand and supply in the sense that the transitioning of stages is quickened and more responsive. (Indicated by a more rigid demand and supply curve).

Market Price

In economics Price is a linear function (straight line) of the proportion of houses for sale (positive slope), and also a linear function of the proportion of buyers (negative slope).Therefore , the variable ‘Market Price’ is calculated by 10 * the portion of ‘House’ in the active state (which is the supply) over the portion of ‘Consumers’ in the active state (which is the demand) Ultimately this presents the economic principles  that as Supply is directly related to Price and demand is inversely related to Price.

Note

Each simulation (with the same settings) will present a different and unique simulation. I have set a Random Boolean to the active component that randomizes the amount of Customers or houses that begin in their active state. The probability is only 0.008 but is useful in describing the effects on the market from various position’s and seeing unique models.  

References

https://www.youtube.com/watch?v=ynuoZQbqeUg - Your First ABM/Part II

https://insightmaker.com/insight/35714/Foraging-Model

Assignment 3 - Ryan Salvaggio 43668070
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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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Ecological economics
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Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.
Lab 13: Future C Emissions
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COVID-19 Outbreak in Burnie Tasmania Simulation Model

Introduction:

This model simulates the COVID-19 outbreak situation in Burnie and how the government responses impact local economy. The COVID-19 pandemic spread is influenced by several factors including infection rate, recovery rate, death rate and government's intervention policies.Government's policies reduce the infection spread and also impact economic activities in Burnie, especially its tourism and local businesses.   

Assumptions: 

- This model was built based on different rates, including infection rate, recovery rate, death rate, testing rate and economic growth rate. There can be difference between 
this model and reality.

- This model considers tourism and local business are the main industries influencing local economy in Burnie.

- Government's intervention policies will positive influence on local COVID-19 spread but also negative impact on local economic activity.

- When there are more than 10 COVID-19 cases confirmed, the government policies will be triggered, which will brings effects both restricting the virus spread and reducing local economic growth.

- Greater COVID-19 cases will negatively influence local economic activities.

Interesting Insights:

Government's vaccination policy will make a important difference on restricting the infection spread. When vaccination rate increase, the number of deaths, infected people and susceptible people all decrease. This may show the importance of the role of government's vaccination policy.

When confirmed cases is more than 10, government's intervention policies are effective on reducing the infections, meanwhile local economic activities will be reduced.

BMA708-Tian Liang-586868-Model of COVID-19 Outbreak in Burnie, Tasmania
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WIP Summary of Mariana Mazzucato's 2018 book See also IM-901 MacroEc
The Value of Everything
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Better Business - Economic
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Farming_small vs large
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ESI6550 Group 6 (Model 2)
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Economic Effect