Calculating EOQ using classical inventory model

WIP based mostly on Jan Toporowski 2013 vol 1 and 2018 vol 2 books on Michal Kalecki: An Intellectual Biography  

A simple model of economic growth where a government taxes the economy, and spends it on capital and revenue goods.

Summary of Ch 27 of Mitchell Wray and Watts Textbook see IM-164967 for book overview See IM-169093 for added dynamic evolutionary economics history

https://www.bilibili.com/video/BV11Q4y1Z7at/

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

The statement that there can be no economic activity without  energy and that fossil fuels are finite contrasts with the fact that money is not finite and can be created by governments via their central banks at zero marginal cost whenever needed.

An important fact about COAL, GAS and OIL (especially when produced via fracking) is that their net energy ratios are falling rapidly. In other words the energy needed to extract a given quantity of fossil fuels is constantly increasing. The falling ratio 'EROI' (Energy Return on Energy Invested ) provides yet another warning that we can no longer rely on fossil fuels to power our economies. In 1940 it took the energy of only one barrel of oil to extract 100. Today the energy of 1 barrel of oil will yield only 15. We cannot wait until the ratio falls to 1/1 before we invest seriously in alternative sources of energy, because by then industrial society as we know it doday will have ceased to exist. An EROI of 1:1 means that it takes the energy of one barrel of oil to extract one barrel of oil - oil production would simply stop! 

Stephen P Dunn 2010 Book summary including Technostructure MMT PCT critical realist and managing perceptions links

IM-168155 Summary of Ch 27 of Mitchell Wray and Watts Textbook see IM-164967 for book overview with simplified Mike Radzicki's 2003 Evolutionary Economics history article added

Investigations into the relationships responsible for the success and failure of nations. This investigation was prompted after reading numerous references on the subject and perceiving that *Why Nations Fail: The Origins of Power, Prosperity, and Poverty* by Acemoglu and Robinson seem to make a great deal of sense.

The World3 model is a detailed simulation of human population growth from 1900 into the future. It includes many environmental and demographic factors.

Use the sliders to experiment with the initial amount of non-renewable resources to see how these affect the simulation. Does increasing the amount of non-renewable resources (which could occur through the development of better exploration technologies) improve our future? Also, experiment with the start date of a more environmentally focused policy.

To maintain economic wealth (roads, hospitals, power lines, etc.) power needs to be consumed. The same applies to economic activity, since any activity requires the consumption of energy. According to the Environmental Protection Agency, the burning of fossil fuels was responsible for 79 percent of U.S. greenhouse gas emissions in 2010. So whilst economic activity takes place fossil fuels will be burned and CO2 emissions are unavoidable - unless we use exclusively renewable energy resources, which is not likely to occur very soon. However, the increasing CO2 concentrations in the atmosphere will have negative consequences, such droughts, floods, crop failures, etc. These effects represent limits to economic growth. The CLD illustrates some of the more prominent negative feedback loops that act as a break on economic growth and wealth.  As the negative feedback loops (B1-B4) get stronger, an interesting question is, 'will a sharp reduction in economic wealth and unavoidable recession lead to wide-spread food riots and disturbances?'

How education causes the gap between socio-economic status?

Goodwin business cycle model, modified from Keen and Blatt

Butterfly Effect
Sensitivity To Initial Conditions
(sensitive dependence on initial conditions)
Navier Stokes Equations
Lorenz Attractor
Chaos Theory, Disorder and Entropy



If M is the state space for the map , then  displays sensitive dependence to initial conditions if for any x in M and any δ > 0, there are y in M, with  such that

A simple implementation of a Dynamic ISLM model as proposed by Blanchard (1981), and taken from An introduction to economic Dynamics - Shone (1997) - chapter 5. This model might serve as a framework to evaluate economic policies over GDP growth.

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

The housing market is heavily dependent on two main factors; supply and demand. Both play a major role in determining an equilibrium price for both sellers and buyers in the real estate market. 

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