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

A simple model for cc adoption which depends on several condions.

integratrated solar  energy  economics  for  northeast brazil depend   consultant engs

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

 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.

Smithian growth model from Michael Joffe Fig. 3.7 p57 Ch3 Feedback Economics Book

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.) It also, unlike Models 2 & 3, shows the influence Savings has on the production rate.

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

IASAM

This Model was developed from the SEIR Model (Susceptible, Exposed, Infected, Recovered) and it predicts the COVID-19 outbreak in Burnie, Tasmania. This pandemic outbreak contributes to diverse rates including infection rate, death rates and recovery rate, government policies and its economic impacts.    

Assumptions:

 This model is driven by its determined rates, e.g., incubation rate, morality rate, test rate and immunity loss rate and its recovery rate.

Government policies are involved in fully vaccination rate, social distance, national border closure, travel, and business restriction which effect Burnie’s economy.

There are three economic entities dimensions in Burnie Island, we can tell that the pandemic has negative impact on Brick-and-Mortar enterprises and tourism business to some extent, whereas, e commercial business plays a crucial role to stimulate the regional economic activities during the COVID-19 period.

 

Interesting Insights:

 The figure of susceptible changes significantly during the initial 3 weeks because of low recovery rate and high infection rate. On the other hand, the implementation and interventions of government policies is effective, because the number of patients who tested negative is increased and the majority of them release and go back home after medical follow-up. 

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

​Farmers use intensive pesticides to harvest cotton, which is harmful to not only the health of the farmers using them, but also our environment as it pollutes rivers and groundwater that negatively interfere with the ecosystem. Even though these farmers know of the health and environmental risks, they still use harmful pesticides to produce cotton, but why is this so. This stock and flow map should explain what impacts farmers to use pesticides to grow cotton despite the risks and explain the cause and effect relationship their use has on the cotton industry and the environment.

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

This model demonstrate how the exisitng tested COVID cases effects economic recovery via goverment intervenes.

An attempt to combine ideas from Joe Stiglitz's Book The Price of Inequality, Peter Turchin's book Secular Cycles and Khalil Saeed and Oleg Pavlov's Dynastic Cycles SD model paper

Based on chapter 14 of Modeling Dynamic Economic Systems

Clarify Purpose: To see forest rise/decline over 30 years. Reduce deforestation (decline). Identify the change driver, tipping points and leverage points.