Causal loop diagram illustrating a variety of feedback loops influencing the price of oil.
Causal loop diagram illustrating a variety of feedback loops influencing the price of oil.
This is a simplification of the Austerity vs Prosperity model in the hope that it will be easier to understand. @ LinkedIn ,  Twitter ,  YouTube
This is a simplification of the Austerity vs Prosperity model in the hope that it will be easier to understand.
Simulation of MTBF with controls   F(t) = 1 - e ^ -λt   Where    • F(t) is the probability of failure    • λ is the failure rate in 1/time unit (1/h, for example)   • t is the observed service life (h, for example)  The inverse curve is the trust time On the right the increase in failures brings its
Simulation of MTBF with controls

F(t) = 1 - e ^ -λt 
Where  
• F(t) is the probability of failure  
• λ is the failure rate in 1/time unit (1/h, for example) 
• t is the observed service life (h, for example)

The inverse curve is the trust time
On the right the increase in failures brings its inverse which is loss of trust and move into suspicion and lack of confidence.
This can be seen in strategic social applications with those who put economy before providing the priorities of the basic living infrastructures for all.

This applies to policies and strategic decisions as well as physical equipment.
A) Equipment wears out through friction and preventive maintenance can increase the useful lifetime, 
B) Policies/working practices/guidelines have to be updated to reflect changes in the external environment and eventually be replaced when for instance a population rises too large (constitutional changes are required to keep pace with evolution, e.g. the concepts of the ancient Greeks, 3000 years ago, who based their thoughts on a small population cannot be applied in 2013 except where populations can be contained into productive working communities with balanced profit and loss centers to ensure sustainability)

Early Life
If we follow the slope from the leftmost start to where it begins to flatten out this can be considered the first period. The first period is characterized by a decreasing failure rate. It is what occurs during the “early life” of a population of units. The weaker units fail leaving a population that is more rigorous.

Useful Life
The next period is the flat bottom portion of the graph. It is called the “useful life” period. Failures occur more in a random sequence during this time. It is difficult to predict which failure mode will occur, but the rate of failures is predictable. Notice the constant slope.  

Wearout
The third period begins at the point where the slope begins to increase and extends to the rightmost end of the graph. This is what happens when units become old and begin to fail at an increasing rate. It is called the “wearout” period. 
From William E. Novak and  Linda Levine CMU SEI Sept 2010 Success in Acquisition: Using Archetypes to Beat the Odds  paper  and  webpage
From William E. Novak and  Linda Levine CMU SEI Sept 2010 Success in Acquisition: Using Archetypes to Beat the Odds paper and webpage
Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.
Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.
This page provides a structural analysis of POTUS Candidate Jim Gilmore's
 economic policy based on the information at:  http://www.gilmoreforamerica.com/jims-growth-code/   The method used is Integrative 
Propositional Analysis (IPA) 
available: 
​
http://scipolicy.org/uploads/3/4/6/9/3469675/walli
This page provides a structural analysis of POTUS Candidate Jim Gilmore's economic policy based on the information at: http://www.gilmoreforamerica.com/jims-growth-code/  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
  Overview:
  

 The
COVID-19 Outbreak in Burnie Tasmania shows the process of COVID-19 outbreak,
the impacts of government policy on both the COVID-19 outbreak and the GDP
growth in Burnie.  

  Assumptions:  

 We set some
variables at fix rates, including the immunity loss rate, recovery rate, de

Overview:

The COVID-19 Outbreak in Burnie Tasmania shows the process of COVID-19 outbreak, the impacts of government policy on both the COVID-19 outbreak and the GDP growth in Burnie.

Assumptions:

We set some variables at fix rates, including the immunity loss rate, recovery rate, death rate, infection rate and case impact rate, as they usually depend on the individual health conditions and social activities.

It should be noticed that we set the rate of recovery, which is 0.7, is higher than that of immunity loss rate, which is 0.5, so, the number of susceptible could be reduced over time.

Adjustments: (please compare the numbers at week 52)

Step 1: Set all the variables at minimum values and simulate

results: Number of Infected – 135; Recovered – 218; Cases – 597; Death – 18,175; GDP – 10,879.

Step 2: Increase the variables of Health Policy, Quarantine, and Travel Restriction to 0.03, others keep the same as step 1, and simulate

results: Number of Infected – 166 (up); Recovered – 249 (up); Cases – 554 (down); Death – 18,077 (down); GDP – 824 (down).

So, the increase of health policy, quarantine and travel restriction will help increase recovery, decrease confirmed cases, decrease death, but also decrease GDP.

Step 3: Increase the variables of Testing Rate to 0.4, others keep the same as step 2, and simulate

results: Number of Infected – 152 (down); Recovered – 243 (down); Cases – 1022 (up); Death – 17,625 (down); GDP – 824 (same).

So, the increase of testing rate will help to increase the confirmed cases.

Step 4: Change GDP Growth Rate to 0.14, Tourism Growth Rate to 0.02, others keep the same as step 3, and simulate

results: Number of Infected – 152 (same); Recovered – 243 (same); Cases – 1022 (same); Death – 17,625 (same); GDP – 6,632 (up).

So, the increase of GDP growth rate and tourism growth rate will helps to improve the GDP in Burnie.

Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.
Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.
Clusters of interacting methods for improving health services network design and delivery. Includes Forrester quotes on statistical vs SD methods and the Modeller's dilemma. Simplified version of  IM-14982  combined with  IM-17598  and  IM-9773
Clusters of interacting methods for improving health services network design and delivery. Includes Forrester quotes on statistical vs SD methods and the Modeller's dilemma. Simplified version of IM-14982 combined with IM-17598 and IM-9773
34 9 months ago
Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.
Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.
A single resource is used​ with a constant rate and converted into products in use. After a while, these products become unusable because of aging. The recycling of these unusable products is imperfect, thus the amount of not recyclable resource grows (until a better recycling process is invented).
A single resource is used​ with a constant rate and converted into products in use. After a while, these products become unusable because of aging. The recycling of these unusable products is imperfect, thus the amount of not recyclable resource grows (until a better recycling process is invented).
​The law of supply and demand is a basic economic principle that explains the relationship between supply and demand for a good or service and how the interaction affects the price of that good or service. The relationship of supply and demand affects the housing market and the price of a house.
​The law of supply and demand is a basic economic principle that explains the relationship between supply and demand for a good or service and how the interaction affects the price of that good or service. The relationship of supply and demand affects the housing market and the price of a house.

A number of factors including government policy affects the law of demand and supply, which I hope my diagram illustrates

When there is a high demand for properties in a particular city or state and a lack of supply of good quality properties, the prices of houses tend to rise. When there is no demand for housing due to a weak economy and an oversupply of properties is available, the prices of houses tend to fall.
 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

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?