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

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I made this model to simulate how a companies revenue will change depending on the lifetime of the appliances it manufactures, in combination with the ratio of repair costs and price. It also shows the accumulation of e-waste.

Appliances lifetime simulation with folder

Henny van Dongen

URBAN1_V1

Juan Camilo Pulgarin Carmona

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This insight includes a Limits to Success archetype. (Bubbles colored with a darker blue)

Economical Factor

Bruce Ree

This is Figure 6 from Lancastle, N. (2012) 'Circuit Theory Extended: The Role of Speculation in Crises' based on Keen, S. (2010). Solving the Paradox of Monetary Profits.

http://www.economics-ejournal.org/economics/journalarticles/2012-34

Banks expand their lending, which in this model leads to higher production, wages and spending. The result is an increase in total spending.

Keynesian Boost

Neil Lancastle

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.

BATHTUB MEAN TIME BETWEEN FAILURE (MTBF) RISK

Guy Lakeman

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Financial Economics Model - Explorer Lab V1

Chris Fortuin

economic

s sh

9 months ago

This page provides a structural analysis of POTUS Candidate Lindsey Graham's economic policy based on the information at: http://www.lindseygraham.com/issue/restore-fiscal-discipline/ http://www.lindseygraham.com/issue/ease-tax-and-regulatory-burdens/ http://www.lindseygraham.com/issue/achieve-energy-independence/ http://www.lindseygraham.com/issue/reform-entitlements/ 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 Lindsey Graham Economic Policy

Steve Wallis

Summary of Ch 17 of Mitchell Wray and Watts Textbook see IM-164967 for book overview

Unemployment and Inflation

Geoff McDonnell

The concept of 'CLOSING A FEEDBACK LOOP' means that a loop is closed to affect the person or agents that originally are responsible for an action so that they plainly feel its effects. This almost inevitable leads to corrective action. One of the reasons why climate change does not arouse passion and action is that it is largely invisible and most people are not aware of it, although extreme weather events are beginning to change this somewhat. The schematic representation shows how systems thinking might help to draw attention to such situations by graphically connecting the dots to promote understand and hopefully action when people realize that there is a price to be paid for inaction. Please note, however, that the loop does not describe dynamic behaviour in the normal system dynamics sense.

WHEN THIS LOOP CLOSES SOME WILL SUFFER BADLY

Hanns-Jürgen Hodann

The complex model reflects the COVID-19 outbreak in Burnie, Tasmania. The model explains how the COVID-19 outbreak will influence the government policies and economic impacts. The infected population will be based on how many susceptible, infected, and recovered individuals in Burnie. It influences the probability of infected population meeting with susceptible individuals.

The fatality rate will be influenced by the elderly population and pre-existing medical conditions. Even though individuals can recover from COVID-19 disease, some of them will have immunity loss and become part of the susceptible individuals, or they will be diagnosed with long term illnesses (mental and physical). Thus, these variables influence the number of confirmed cases in Burnie and the implementation of government policies.

The government policies depend on the confirmed COVID-19 cases. The government policies include business restrictions, lock down, vaccination and testing rate. These variables have negative impacts on the infection of COVID-19 disease. However, these policies have some negative effects on commercial industry and positive effects on e-commerce and medical industry. These businesses growth rate can influence the economic growth of Burnie with the economic

Most of the variables are adjustable with the slider provided below. They can be adjusted from 0 to 1, which illustrates the percentages associated with the specific variables. They can also be adjusted to three decimal points, i.e., from 0.1 to 0.001.

Assumptions

- The maximum population of Burnie is 20000.
- The maximum number of infected individuals is 100.
- Government policies are triggered when the COVID-19 cases reach 10 or above.
- The government policies include business restrictions, lock down, vaccination and testing rates only. Other policies are not being considered under this model.
- The vaccination policy implemented by the government is compulsory.
- The testing rate is set by the government. The slider should not be changed unless the testing rate is adjusted by the government.
- The fatality rate is influenced by the elderly population and pre-existing medical conditions only. Other factors are not being considered under this model.
- People who recovered from COVID-19 disease will definitely suffer form immunity loss or any other long term illnesses.
- Long term illnesses include mental illnesses and physical illnesses only. Other illnesses are not being considered under this model.
- Economic activities are provided with an assumption value of 1000.
- The higher the number of COVID-19 cases, the more negative impact they have on the economy of Burnie.

Interesting Insights

A higher recovery rate can decrease the number of COVID-19 cases as well as the probability of infected population meeting with susceptible persons, but it takes longer for the economy to recover compared to a lower recovery rate. A higher recovery rate can generate a larger number of people diagnosed with long term illnesses.

Testing rate triggers multiple variables, such as government policies, positive cases, susceptible and infected individuals. A lower testing rate can decrease the COVID-19 confirmed cases, but it can increase the number of susceptible people. And a higher testing rate can trigger the implementation of government policies, thus decreasing the infection rate. As the testing rate has a strong correlation with the government policies, it can also influence the economy of Burnie.

BMA708 COVID-19 Outbreak in Burnie, Tasmania

ching tung li

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Economic model

Tiziana Lembo

Based on a project I am working in [country]. The objective of the Insight is to describe the root causes of the binding constraint of water scarcity on economic growth.

Common Pool Resource Problem
Limits to Growth
Success to Successful

Common Pool Resource is evidenced by uncontrolled (illicit) groundwater abstraction and the declining water tables and water quality.

Groundwater resources are clearly finite (even if the exact limit in uncertain). As the limit is approached water quantity and quality declines rapidly. Groundwater is generally being overexploited beyond safe yields.

There is a pattern of success to successful (those with means are better positioned to adapt to increasing scarcity) but this growth in inequality results in social unrest which in turn inhibits reinvestment by the successful.

Green elements are the focus of project investments: Improved regulatory capacity, infrastructure investments, WUA capacity building, and strengthening cooperatives to support investment in small holders.

Groundwater Problem

Omar Hopkins

A sample model for class discussion modeling COVID-19 outbreaks and responses from government with the effect on the local economy. Govt policy is dependent on reported COVID-19 cases, which in turn depend on testing rates less those who recover

Assumptions

The government has reduced both the epidemic and economic development by controlling immigration.

Yuhao c, BMA708_Marketing insights into Big Data.