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.

Taken from Saeed, Khalid. ‘Limits to Growth Concepts in Classical Economics’. In Feedback Economics: Economic Modeling with System Dynamics, edited by Robert Y. Cavana, Brian C. Dangerfield, Oleg V. Pavlov, Michael J. Radzicki, and I. David Wheat, 217–46. Cham: Springer International Publishing, 2021. https://doi.org/10.1007/978-3-030-67190-7_9.

WIP Dynamic map from Steve Keen's Minsky at 100 Lecture video and slides and later Emergent Macroeconomics papers

Summary of UNEP ecosystems services CBA 2011 article by Wegner and Pascual

• This model examines how sustainable consumerism is from social, economic, and environmental aspects. The question in focus is "How will our second-hand clothing donations affect communities in developing countries, specifically Kenya?"

Unfolding story based on Bogdanov's original A Short Course of Economic Science text and Pilyugina's 2019 article

Sandbox for testing InsightMaker features using pipeline Construction & ROW land conversion as a driver of changes in ecosystem service value.

Economic capital growth in a system constrained by a non-renewable resource, Figure 37 from Thinking in Systems by Donella H. Meadows

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

From Jay Forrester 1988 killian lectures youtube video describing system dynamics at MIT. For Concepts See IM-185226. For more detailed biography See Jay Forrester memorial webpage For MIT HIstory see IM-184930

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

• This model examines how sustainable consumerism is from social, economic, and environmental aspects.  

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

CLD exposition of Goodwin01 from Steve Keen's August 2019 course on Introduction to Economic Dynamics and Minsky software See video and powerpoint slides. Based on IM-2011 Minsky FIH and IM-168865 MacroEconomics CLDs. SeeIM-172005 for Simulation

Peak oil occurs not when there are no more reserves, but when it is too expensive to bring them to the surface. The diagram describes a dynamic where peak oil leads to oil prices that are too low for oil companies to produce oil. There are two keys to understand this counterintuitive situation. First, it is important to realize that without energy (oil) no economic activity can take place. Second, when supplies of oil become scarce, non-elite workers  - because of the contraction of the economy - will lose their jobs or suffer salary cuts. This will make goods containing (or using) oil products too expensive for the masses. Demand for those products (most things on the market) will decline and with it demand for oil - oil prices will drop too low for oil companies to produce oil!

These ideas stem from Gail Tverberg's blog: 'Our Finite World'. https://ourfiniteworld.com/

Clone of Pesticide Use in Central America for Lab work

A model of the potential impact on the elderly population (75+ years) from heat stress, which is increased by climate change in the UK.

Implementation of the Solow model of economic growth with labor enhancing technology.

parameters: s, alpha, delta, n, gA
variables: Y. K, L, C, A
per capita variables: y, k, c, a
per capita and technology variables: y~, k~, c~
steady state variables: y~*, k~*, c~*
all variables come with relative growth rates g

Features:

+steady state from beginning
+one time labor shock
+permanent savings quote shock
+permanent technological growth rate shock

Decreasing steady state variables when starting in steady state are numeric artifacts.

This model shows the operation of a simple economy. It demonstrates the effect of changes in the fractional rate of consumption (or the converse the fractional rate of saving.)

In summary, lower rates of consumption (based on production) result in higher rates of production and consumption in the long-run.

Implementation of a DSGE Model solved in a Macroeconomics class by Harald Uhlig (link), using Rational Expectations, in this case, the Hansens Real Business Cycle Model.

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. 

Plan for CCP project completion see IM-102242  for WIP detail of the structures of the related models