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During the 'big recession' many governments have deliberately repressed salaries, usually via structural reforms, in order to gain competitivity. However, repression of salaries increases inequality, social discontent and often has counterintuitive effects. Salaries are a cost for companies, but they are also the basis for the demand for the goods and services they offer: people with little income cannot afford them. Scientific studies have shown repeatedly that economic growth generated via salary increases does not endanger the creation of employment, but rather reinforces it. In most countries, the 'positive effect of salary increases' eclipses any possible negative effects on export competitivity and even any detrimental effect on investment. A good example of such a study is the work of ONARAN and OBST on Wage-led Growth in the EU15 Member States (2016).  This positive dynamic has been highlighted in the model by prominent arrows. The policy implications for governments are clear! 

Dynamik Linking Wage Increases to Higher Growth and Profits
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Book Summary of The Great Transformation by Karl Polanyi see Wikipedia . See also more Karl Polanyi ideas IM-181325
The Great Transformation
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Adam Smith's The Invisible Hand: The Feedback Structure of Markets. From Sterman JD Business Dynamics p170 Fig 5-26. A price-mediated resource allocation system..

Price control mechanism
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Supply-Demand Shortside Adjustment
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​BACKGROUND:

The following simulation model demonstrates the relationship between supply, demand and pricing within the real estate and housing world. I have based the model on a small city with a population of 100,000 residents as of 2015. 

AXIS:

X-Axis
The X-Axis shows the time. It begins in 2015 in the month of October and continues for 36 consecutive years. 

Y-Axis
There are 2 Y-Axis on this model. The left hand side relates to the price, demand, and supply, while the right hand side solely lists the population.

As you could see, this town has a population of 100,000 residents to-date. The bottom of the model shows a population loop that produces an exponential growth rate of 2.5%. This dynamic and growing city populates approximately 240,000 residents after 36 years.

MODEL

The model consists of 2 folders named: Buyers/Consumers & Suppliers/Producers. This first folder represents the 'Demand'. It includes a buyers growth rate, buyers interest increase and decrease, a price demand and the demand price. The formulas form an exponential rise in demand due to the rapid and continuous increase in population in this new city. As population increases, so does the demand from buyers. 

The second folder conveys the supply of houses. It includes a sophisticated loop of real estate. Residents who own houses in the market decide to sell the home. This becomes the Houses for sale, also known as the 'supply'. Those houses are sold and the sold houses re-enter the market and the loop continues. 

The supply has an inverse relationship with the price. When prices drop, supplies drop because the demand goes up. And when the price goes up, so does the supply. This will represent the growth of new houses in the market. 

PRICE

Note: The price is based on monthly rent rates.

The price is dependant on many variables. Most importantly, the supply and demand. It also includes factors such as expectations & the economic value of the house. I have included a stable, 'good' economic value for all homes as this fictional town is in a stable and growing area.

Price fluctuates throughout the entire simulation, however it also goes up in price. Over the years houses continue to rise in price while they regularly fluctuate. For example, in 2018 (3 years later), the max price for a home was: $4254.7 and min price was: $852.98. On the other hand, in October 2051 (36 years later), the max price was: $14906 and the min price was: $7661. (This is based on the following data: Houses for Sale: 500, Houses that have sold: 100, Houses in the Market: 730).

SLIDERS

There are 3 sliders on the bottom that could be altered. The simulation would react accordingly. The 3 sliders include changeable data on:
- Houses for Sale.
- Houses that have Sold.
- Houses in the Market.


Real Estate Simulation Assignment - Mitchell Bassil 43290264
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WIP based on Bill mitchell's blogs. 
Sectoral balances are relationships among money flows during an accounting period. Where we perceive accumulations of past imbalances to be accrued is another matter....
MMT Fiscal position
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Model description:

This model is designed to simulate the outbreak of Covid-19 in Burnie in Tasmania. It also tell us the impact of economic policies on outbreak models and economic growth.

 

Variables:

The simulation takes into account the following variables and its adjusting range: 

 

On the left of the model, the variables are: infection rate( from 0 to 0.25), recovery rate( from 0 to 1), death rate( from 0 to 1), immunity loss rate( from 0 to 1), test rate ( from 0 to 1), which are related to Covid-19.

 

In the middle of the model, the variables are: social distancing( from 0 to 0.018), lock down( from 0 to 0.015), quarantine( from 0 to 0.015), vaccination promotion( from 0 to 0.019), border restriction( from 0 to 0.03), which are related to governmental policies.

 

On the right of the model, the variables are: economic growth rate( from 0 to 0.3), which are related to economic growth.

 

Assumptions:

(1) The model is influenced by various variables and can produce different results. The following values based on the estimation, which differ from actual values in reality.

 

(2) Here are just five government policies that have had an impact on infection rates in epidemic models. On the other hand, these policies will also have an impact on economic growth, which may be positive or negative.

 

(3) Governmental policy will only be applied when reported cases are 10 or more. 

 

(4) This model lists two typical economic activities, namely e-commerce and physical stores. Government policies affect these two types of economic activity separately. They together with economic growth rate have an impact on economic growth.

 

Enlightening insights:

(1) In the first two weeks, the number of susceptible people will be significantly reduced due to the high infection rate, and low recovery rate as well as government policies. The number of susceptible people fall slightly two weeks later. Almost all declines have a fluctuating downward trend.

 

(2) Government policies have clearly controlled the number of deaths, suspected cases and COVID-19 cases.

 

(3) The government's restrictive policies had a negative impact on economic growth, but e-commerce economy, physical stores and economic growth rate all played a positive role in economic growth, which enabled the economy to stay in a relatively stable state during the epidemic.

Model of COVID-19 Outbreak in Burnie, Tasmania
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The model is built to demonstrates how Burnie Tasmania can deal with a new COVID-19 outbreaks, taking government policies and economic effects into account.
The susceptible people are the local Burnie residents. If residents were infected, they would either recovered or dead. However, even they do recover, there is a chance that they will get infected again if immunity loss occurs.
From the simulation result we can see that with the implementation of local government policies including travel ban and social distancing,  the number of infected people will decrease. The number of recovered people will increase in the first 5 weeks but then experience a decrease.
In addition, with the implementation of local government policy, the economic environment in Burnie will be relatively stable when the number of COVID-19 cases is stable.
How Burnie, Tasmania can deal with a new outbreak of COVID-19
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Clone of Wagdy Samir Macroeconomics work in progress IM-901 Additions and deletions based on Robert Skidelsky's description of Keynes general THeory from his Biography Vol2 p 549 -571

Keynes General Theory
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Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.
This Scenario has Affluence decreasing due to Anthropogenic climate change
Final Project 3 W/ Socio-Economic Factors - Temperature Degradation
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• This model examines how sustainable consumerism is from social, economic, and environmental aspects.  

The environmental, social, and economic sustainability aspects of consumerism
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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.
Solow growth model v1.0
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Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.
This Scenario hits Affluence (1% decrease per annum) to increase decarbonization of energy
Final Project 2 W/ Socio-Economic Factors - Reinvestment Scenario
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Unfolding story based on Bogdanov's original A Short Course of Economic Science text and Pilyugina's 2019 article
Bogdanov Economic History of Societies
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Initial Stock & Flow of Energy Infrastructure Development, Climate Change Impacts, and Economic Activity
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• This model examines how sustainable consumerism is from social, economic, and environmental aspects. The question in focus is "How will our second-hand clothing donations affect communities in developing countries, specifically Kenya?"

5 Stock Variables: 
• U.S. Consumers
• Multinational Corporations
• Overseas Factories
• Kenya

Highlight Findings: 
To sum up, there are 4 major problems associated to donations:
• 1. Source of problem is the consumer: Cheap deals attract hundreds of millions in revenue for fast fashion, and contribute to 100,000 tonnes of clothing to Kenya annually. 
• 2. Rapid consumerism leads to over-utilization of slowly-renewable resources, such as water.
• 3. Nearly 96% of textiles jobs are eradicated by the massive inflow of clothing donations to Kenya. 
• 4. The offshoring of textiles jobs enrages U.S. blue-collar workers, leading to the rise of protectionism.  



The environmental, social, and economic sustainability aspects of textiles donations
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System Model of Modern Warfare
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This model simulates the economics of buying a home. It was created to compare buying a home against using investment returns to pay for rent. According to Micheal Finke, house prices typically run 20x monthly rental rates. 

Try cloning this insight, setting the parameter values for real-world scenarios, and then running sensitivity analysis (see tools) to determine the likely wealth outcomes. Compare buying a home to renting. Note that each run will keep the parameters the same while simulating market volatility.

version 1.9
Home buying simulation 1.9
4 9 months ago
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Format: Given pre-conditions when independent variables(s) then dependent variable

Given Earnings Decline (0.25), Spending Variance (55), Initial Investment (500) and Rate of Return (RandNormal(0.06, 0.12)) when one of these independent variables change then how sensitive is Investment (22) over a 30 year time period (-1,000)

H1: if you Earn more then Investment will last much longer => rejected

H2: if you Spend less then Investment will last much longer => accepted

H3: if your Initial Investment is higher then Investment will last much longer => accepted

H4: if you reduce your Spend when Investments are declining then Investment will last much longer => accepted

Given Earnings Decline (0.25), Spending Variance (55), Initial Investment (500) and Rate of Return (RandNormal(0.06, 0.12)) when one of these independent variables are optimised then Investment will last exactly 30 years by minimising the absolute investment gap

H1: if you set an appropriate Spending Base then remaining Investment is 0 => rejected

H2: if you set an appropriate Spending Reduction then remaining Investment is 0 => rejected

Source for investment returns: https://seekingalpha.com/article/3896226-90-year-history-of-capital-market-returns-and-risks
OrangeFortune | Wealth Management when Retiring
4 4 months ago
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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.)

In summary, lower rates of consumption (based on production) result in higher rates of production and consumption in the long-run.
Simple Economy: Model 8
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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/

PEAK OIL LEADS TO LOW OIL PRICES
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Summary of Ch1 of Mitchell Wray and Watts Textbook see IM-164967 for overview
Macroeconomics Introduction
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Plan for CCP project completion see IM-102242  for WIP detail of the structures of the related models
CCP Project Scope Deliverables and Extensions