WIP replication of Khalid Saeed's draft paper presented by the Economics chapter of the SD Society in Sept 2019 youtube video

WIP My Initial Book version compared with Gemini Causal Loop Summary of the 2025 Book, from my gemini interaction using Gene Bellinger's AI prompts See also Sorokin-Social-and-Cultural-Dynamics insight 

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

WIP  based on Where profits come from paper , Nathan Tankus blog and other historical sources

This is a toy model of fractional reserve banking.

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.

This model is designed to simulate the outbreak of Covid-19 in Burnie in Tasmania, death cases, the governmental responses and Burnie local economy. 

A model of the relationship among covid-19 outbreak and government policy and economic impacts. 

This is a reconstruction of the SIMM model presented in Chapter 2 of Feedback Economics (Contemporary Systems Thinking)

Assignment 3 – Complex Systems

 Ryan Salvaggio - 43668070

 

The Model

This model conceptualizes the effects on a real-estate market-model utilizing agent based modelling. This model utilizes basic economic principles of supply and demand.

The model bases itself on two Agents - one being ‘Customers’ of the real estate market model, whilst the other being the Real estate itself, coined 'Houses'.

Consumers (Demand)

The Agent population, ‘Consumers’ specifies the total amount of people whom can potentially become buyers within the market. This is limited to 30 for conceptual purposes. The Agent ‘Consumer’ exists in two states, either being an ‘Active Customer’ (Active) or an ‘Inactive Customer’ (Inactive).  The transition from Inactive to Active occurs upon the basis that the ‘Budget’ of the Consumer meets the desired price of the marketplace, this is specified through the variable ‘Budget’ defining the probability that this transition will occur – this is adjustable by the user indicating a highly resistive or by accepting the market. ‘Budget’s probability in a real life scenario would be based upon numerous factors however conceptually utilizing the slider can present many of these various situations.

Upon transitioning into an active state an ‘Active consumer’ will attempt to find the closest ‘For sale household’, this is represented and carried out through the ‘Enter’ action.  Upon finding a household the consumer and house will both return to their respected inactive state thus repeating the process.

Demand – ‘Count of active customers – demand’ is then calculated by a count of Consumers transitioned and currently in the Active state. A high demand would be indicative through a high ‘Budget’ responsiveness whilst a low demand would be indicative of a low ‘Budget’ responsiveness. The increase in Price and hence supply of household thus reduces demand and vise versa.  

House (Supply)

The Agent population, ‘Houses’ specifies the total amount of households that can potentially become for sale within the market. This is limited to 112 for conceptual purposes. The Agent ‘House’ exists in two states, either being ‘For Sale’ (Active) or ‘Not for Sale’ (Inactive).  The transition from Inactive to Active occurs upon the basis that the ‘Motivation to Sell’ of the House is satisfied, this satisfaction is specified by a set probability that this transition will occur – this is adjustable by the user indicating a highly responsive or restricted house market. ‘Motivation to sell’ probability in a real life scenario would be based upon numerous factors however conceptually utilizing the slider can present many of these various situations.

Upon transitioning into an active state a ‘For Sale’ house will wait for an ‘Active Customer’ ‘this is represented and carried out through the ‘Search’ action. Upon completion of the action both states become inactive and the process continues.

Supply – ‘Count of houses for sale –supply’ is then calculated by a count of Houses ‘For Sale’ that are currently in the active state. Ultimately a high Motivation to sell would sharply increase supply, whilst a low motivation would have the adverse effects.  

Movement Speed

Movement speed – describes the base movement rate of Consumers. This variable describes the transition into the ‘Inactive’ state of a consumer, ultimately when a household is found and purchased. Movement speed affects both demand and supply in the sense that the transitioning of stages is quickened and more responsive. (Indicated by a more rigid demand and supply curve).

Market Price

In economics Price is a linear function (straight line) of the proportion of houses for sale (positive slope), and also a linear function of the proportion of buyers (negative slope).Therefore , the variable ‘Market Price’ is calculated by 10 * the portion of ‘House’ in the active state (which is the supply) over the portion of ‘Consumers’ in the active state (which is the demand) Ultimately this presents the economic principles  that as Supply is directly related to Price and demand is inversely related to Price.

Note

Each simulation (with the same settings) will present a different and unique simulation. I have set a Random Boolean to the active component that randomizes the amount of Customers or houses that begin in their active state. The probability is only 0.008 but is useful in describing the effects on the market from various position’s and seeing unique models.  

References

https://www.youtube.com/watch?v=ynuoZQbqeUg - Your First ABM/Part II

https://insightmaker.com/insight/35714/Foraging-Model

WIP Summary of Mariana Mazzucato's 2018 book See also IM-901 MacroEc

THE NEW SCIENCE OF PLEASURE Daniel L. McFadden NBER Working Paper 18687

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

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

A system diagram for the Mojave Desert including example socio-economic factors for an assignment at OSU- RNG 341.

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

The upper diagram shows the principal factors that have an influence on the budget deficit and indicates what needs to be done to correct it. But this is not the full story. The diagram below shows that  cutting public expenditure reduces aggregate demand and  increases unemployment. The reduction of aggregate demand  reduces  economic activity which has the effect of reducing  tax revenue.  In addition, the state has to pay out funds as there is a need for more unemployment benefit payments.   The result of these austerity measures  is often the opposite of their intended purpose: they can increase rather than decrease the budget deficit.

There is plenty of empiric evidence to show that this has happened time and time again. For instance, a report from UNCTAD (United Nations Conference on Trade and Development) found that between 1990 and 2000 in all the  cases examined where cutbacks in public spending and tax increases were used, the fiscal situation did not only not improve but worsened. Despite such repeated evidence, unfortunately calls for  austerity measures continue to be heard. 

Fig.5 Generic resource allocation structure from Khalil Saeed and Oleg Pavlov's Dynastic Cycles SD model paper  See also  the SD Simulation Model Insight

WIP Social determinants of health from Michael Marmot's  ABC 2016 Boyer Lectures on Social Justice and the Health Gap See US Data website for data and AIHW website for concepts. See also IM-83417 Marmot Essay 2017

A simulation model that shows the relationship between the mountain biking trails in derby and the the effect it has on the tourism,