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

Laying out and testing before coupling to main model (which is Final Project)

Based on oid 2016 report to be compared with the Just Justice Framework WIP insight

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. 

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

Ciclo 1 extra repair consturction errors rework

Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.

This model represents a repair contract to fix a group of houses with unresolved construction defects.

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

Social pressures create {Youth Alienation}, leading to youth developing bad behaviours and committing crimes. This attracts {Police Enforcement} who will, in turn, engage the {Community Leadership} where they introduce programs that are designed to assist youth to prevent re-offending through the development of {Community Clubs}, which then contributes to {Community Development}.

{Police Enforcement} collaborates with {Educational Institutions} to boost retention, which translates to socio-economic progress through {Community Development}. On the other hand, criminals are detained and put through the {Court} system, where the offenders are removed from the community through {Imprisonment}. This results in a stable and safe environment, which aid support for {Community Development).

The role of {Community Leadership} in the system, particularly at the grassroots will result is huge savings in the economy, aiding economic growth. The {Community Leadership} collaborates with the {Employment & Justice Agencies}, translating into socio-economic progress {Community Development}

The Community Development Model

This model provides an understanding into the relationships and links between a range of variable units and fixed units, and how {Community Development} is supported.

As {Youth Alienation} rate increases,  the {Crime} rate increases (both variables) demands police enforcement. {Police Enforcement} is a fixed variable as increase in police force is fixed over a period of time. 

To increase efficiency, engages or collaborate with:

•{Community Leadership} (fixed and variable) – is fixed for a certain period, and becomes variable as youth criminal activities increases

•{Court} (variable) – as youth criminal activities increase, the court resources reman fixed. It then removes some offenders from the community and imprison them, creating peace and stability in the community 

•{Educational Institutions} (variables) – as student retention increases, more institutions are needed.  

The key issue here (still an incomplete model) is that insight maker doesnt like the agent folder and the flows. I've solved the original problem where the flows couldn't go across agent boundaries (I did this simply by moving the stocks and their respective flows all OUTSIDE of the folder), but now the main issue is that the flows outside of the folder (particularly [Internal Factor Flow] don't pick up the links from the variables inside of the folder. A key variable, susceptability, has to connect to the previously mentioned flow. The problem is that it lies in the agent folder which means that the flow can't recognize the link. I even tried using a ghost of the Susceptability variable and placed it outside of the folder but that didn't work. 

An initial study of the economics of single use coffee pods.

On the occasion of th G20-meeting in Toronto, the German Economics minister Herr Schaüble said that without restoring confidence it would not be possible to get consumer spending and business investment going. Similar remarks were made by David Cameron and Señor Zapatero of Spain. All maintain that confidence is a pre-requisite to get growth going and that, therefore, it was imperative to reduce fiscal deficits. Reducing the fiscal deficit will restore confidence at first. However, reducing the deficit very quickly will introduce a dynamic that may cause the economy to decline - and perhaps depress  consumers demand even further.  It will actually destroy confidence: few businesses are inclined to invest in a shrinking economy. Cutting the deficit too rapidly or too steeply can lead to a confidence trap.

NOTE: A big experiment is now taking place in the UK - the government has cut public spending severely! Will this lead to hardship and, perhaps, social unrest? 

This model indicate indicates the modeling COVID-19 outbreaks and responses from government policies with the effect on the local economy. Model was occurred at Burnie, Tasmania. The model mainly contains three parts: COVID-19 pandemic outbreak, four differences government policies and what the impact on economy from those policies.

 

Assumptions:

(1) Various variables influence the model, which can result in varied outcomes. The following values are based on an estimate and may differ from actual values. Government initiatives are focused at reducing Covid-19 infections and, as a result, affecting (both positive and negative) economic growth.

 

(2) 42% of infected people will recovery. 10% of people who are infected will die and the rate relatively higher due to the much old people living in Burnie, Tasmania.

78% of cases get tested.

 

(3) Government policy will only be implemented when there are ten or more recorded cases. Four government policies have had influences on infection.  

 

(4) The rising number of instances will have a negative impact on Burnie's economic growth.

 

Insights:

1. As a result of the government's covid 19 rules, fewer people will be vulnerable. Less people going to be susceptible.

 

2. After the government policy intervention, there is a effectively reduce of infected people.

 

3. Overall, there is no big differences of economic performance from the graph, might due to the positive and negative effect of economy. And after two weeks, the economy maintained a level of development without much decline.