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

The Logistic Map is a polynomial mapping (equivalently, recurrence relation) of degree 2, often cited as an archetypal example of how complex, chaotic behaviour can arise from very simple non-linear dynamical equations. The map was popularized in a seminal 1976 paper by the biologist Robert May, in part as a discrete-time demographic model analogous to the logistic equation first created by Pierre François Verhulst. 

Mathematically, the logistic map is written

where:

 is a number between zero and one, and represents the ratio of existing population to the maximum possible population at year n, and hence x0 represents the initial ratio of population to max. population (at year 0)r is a positive number, and represents a combined rate for reproduction and starvation.
For approximate Continuous Behavior set 'R Base' to a small number like 0.125To generate a bifurcation diagram, set 'r base' to 2 and 'r ramp' to 1
To demonstrate sensitivity to initial conditions, try two runs with 'r base' set to 3 and 'Initial X' of 0.5 and 0.501, then look at first ~20 time steps

This is a first attempt to illustrate the interconnected nature of the economic assets of Roswell - Chaves County

Description:

This page provides a structural analysis of POTUS Candidate Jim Gilmore's economic policy based on the information at: http://www.gilmoreforamerica.com/jims-growth-code/  The method used is Integrative Propositional Analysis (IPA) available: ​ http://scipolicy.org/uploads/3/4/6/9/3469675/wallis_white_paper_-_the_ipa_answer_2014.12.11.pdf

This model was proposed in a regulatory framework in Brazil. Its main idea is the obtainment of a dynamic control model to avoid the related parties issues on regulated public services over contract extensions. As the terminal condition of these contract extensions is NPV=0, the firms would have an incentive to contract related parties to inflate costs, and diminish their profits, in order to request a larger time extension. So, this system creates a stable "shadow" based on the 5 years before these extensions, where the company did not have such incentives.

Description

 

The model shows Covid-19 situations in Burnie, Tasmania. Under such circumstances, how the state government deals with the pandemic and how economy changes will be illustrated. The relationship between government policy and economic activities under Covid-19 outbreaks will be explained through different variables.

Assumptions

 

Government policy negatively affects Covid-19 outbreaks and economic activities.

Covid-19 outbreaks also has negative effects on economic growth.

 

Parameters

 

There are several fixed and adjusted variables.

 

1.     COVID-19 Outbreaks

Fixed variables: infection rate, recovery rate

Adjusted variables: immunity loss rate

 

2.     Government Policy

Adjusted variables: lockdown, social distancing, testing, vaccination

3.     Economic impact

Fixed variables: tourism

Adjusted variables: economic growth rate

 

Interesting Insights

 

Tourism seems to be the most effective way to bring back economic growth in Tasmania, and it takes time to recover from Covid-19.

 

Government policies tend to have negative influences on economic growth.

This is a simplification of the Austerity vs Prosperity model in the hope that it will be easier to understand.

economic model

Nobody seems to notice bubbles until they burst. One possible reason is that those caught up in a bubble are completely blinded by the grip, the overpowering logic and force excerted by the positive feedback loop that drives it. Financial bubbles occur time and time again - and nobody seems to learn. Another example on a different time scale is an argument that spins out of control and ends in violence. The participants seem to be blind to the consequences; the immediate and imperative logic of the feedback loop imposes itself. The vortex created by the feedback loop even seems to draw in outsiders, such as new investors. Is this the reason why we don't notice bubbles? This explanation is meant to stimulate discussion!

WIP Summary of Davies 2017 article from special Theory Culture and Society issue on Elites and Power after Financialization

This paper aims at describing a case where system dynamics modeling was used to evaluate the effects of information and material supply lead-time variation on sales contributions margins and operating cash conversion cycle of a commodity export business.  An empirical dynamic model, loaded with econometric theory of price effect on competitive demand, was used to describe the input data.  The model simulation outputs proved themselves relevant in analyzing the complex interconnections of multiple variables affecting  the profitability in a commercial routine, supporting the decision process among sales managers.

Overview of Part E Ch 20 to 24 of Mitchell Wray and Watts Textbook see IM-164967 for book overview