Brief Summary of Albert O Hirschman's Book with 2026 update

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

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 SD representation of Ch11 of their 2007 Monetary Economics book, as suggested by Adam K. Plan is to do a top down simple money flow SFC mmt model and successively split sectors. See also essence of MMT IM and simpler version Ch3 IM

A causal loop diagram illustrating solutions for the homelessness problem

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

not a mathematical model. just a general one

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

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.

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/

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

IASAM

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. 

Explanation of the Model

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.

MODERN MONETARY THEORY SHOWS HOW FULL EMPLOYMENT CAN BE ACHIEVED!

POTENTIAL GDP is a level of overall spending - by the government and the non-government sector - at which there is full employment. If the economy is not operating at its potential, then the  private sector has failed to invested or spend enough to generate the necessary growth nor has income  from net exports contributed enough. This only leaves the government to close the spending gap. Conceptually, a government disposing of its own freely floating currency could act using two powerful tools -  spending in excess of tax revenue, and taxation - to ensure that the gap between the actual economic activity and potential GDP is quickly closed. Achieving the  full employment that prevailed for 30 years between 1945 and 1975 in western economies is definitely possible! 

This model shows the operation of a simple economy with two modifications made to Model 2 -- 1) feedback from production rate to consumption rate and 2) the use of a fractional rate input for calculating consumption rate. 

In summary, lower fractional rates of consumption (based on production) result in higher levels of Savings.

This simple model describes wealth accumulation. The value in income is described by the following simple equation:

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

Eastern oyster growth model calibrated for Long Island Sound
Developed and implemented by Joao G. Ferreira and Camille Saurel; growth data from Eva Galimany, Gary Wickfors, and Julie Rose; driver data from Julie Rose and Suzanne Bricker; Culture practice from the REServ team and Tessa Getchis. This model is a workbench for combining ecological and economic components for REServ. Economic component added by Trina Wellman.

This is a one box model for an idealized farm with one million oysters seeded (one hectare @ a stocking density of 100 oysters per square meter)

1. Run WinShell individual growth model for one year with Long Island Sound growth drivers;

2. Determine the scope for growth (in dry tissue weight per day) for oysters centered on the five weight classes)
 
3. Apply a classic population dynamics equation:

dn(s,t)/dt = -d[n(s,t)g(s,t)]/ds - u(s)n(s,t)

s: Weight (g)
t: Time
n: Number of individuals of weight s
g: Scope for growth (g day-1)
u: Mortality rate (day-1)

4. Set mortality at 30% per year, slider allows scenarios from 30% to 80% per year

5. Determine harvestable biomass, i.e. weight class 5, 40-50 g (roughly three inches length)