A toy model to see what happens to employment when people must move through various states to get to certain jobs

'Efficiencyism’  can be described as a blind belief in the effectiveness of efficiency measures without taking into account circumstances and the wider context.   The graph on the left shows how the frequent use of the term 'efficiency' at the level of local interactons can lead to the emergence of  'efficiencyism' through upward causation, denoted by the arrows pointing upwards.  However, there is also downward causation from the global level depicted by the red arrows which can increase the blind application of efficiency measures at the local level. In other words, efficiency for the sake of efficiency becomes a dominant idea.  The tyrannical influence of 'eficiencyism' affects all of us to varying degrees and unfortunately can often have very negative side effects, such as an increase in unemployment, social injustice and even increase inequality.  Of  course, well thought out efficiency improvements can also bring great  benefits.   I recommend reading an excellent article by Dr. Charles Chandler, who explains the term 'efficiencyism' with some excellent examples and also points to some  of its undesirable effects.

http://www.ageofoe.com/010-efficiencyism-holds-us-back/

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

Model supporting research of investment vs. austerity implications. Please refer to additional information on the SystemsWiki Focus Page and Modern Money & Public Purpose Video.

国連が公表している人口の将来推計とOECDが公表している各種経済統計を参考にして、2000年から2100年までの人口・経済見通しを作成するためのダイナミクスモデル。

The significance of reduced energy return on energy invested (EROI) in the transition from fossil fuel to renewable primary energy sources is often disputed by both renewable energy proponents and mainstream economists.​ This model is a first attempt to illustrate the impact of EROI in large-scale energy transition using a system dynamics approach. The variables of primary interest here are: 1) net energy available to "the rest of the economy" as renewable penetration increases [Total final energy services out to the economy]; and 2) the size of the energy sector as a proportion of overall economic activity, treating energy use as a very rough proxy for size [Energy services ratio].
This model aggregates energy use in the form of fuels and electricity as a single variable, total final energy services, and treats the global economy as a single closed system.
The model includes all major incumbent energy sources, and assumes a transition to wind, PV, hydro and nuclear generated electricity, plus biomass electricity and fuels. Hydro, biomass and nuclear growth rates are built into the model from the outset, and wind and PV emplacement rates respond to the built-in retirement rates for fossil energy sources, by attempting to make up the difference between the historical maximum total energy services out to the global economy, and the current total energy services out. Intermittency of PV and wind are dealt with via Li-ion battery storage. Note, however, that seasonal variation of PV is not addressed i.e. PV is modeled using annual and global average parameters. For this to have anything close to real world validity, this would require that all PV capacity is located in highly favourable locations in terms of annual average insolation, and that energy is distributed from these regions to points of end use. The necessary distribution infrastructure is not included in the model at this stage.
It is possible to explore the effect of seasonal variation with PV assumed to be distributed more widely by de-rating capacity factor and increasing the autonomy period for storage.

This version of the model takes values for emplaced capacities of conventional sources (i.e. all energy sources except wind and PV) as exogenous inputs, based on data generated from earlier endogenously-generated emplaced capacities (for which emplacement rates as a proportion of existing installed capacity were the primary exogenous input).

Peak oil will occur when it is too expensive to bring oil to the surface and not when reserves reach their limit. Companies must make a profit to be able to extract oil and stay in the oil business.  However, that endeavour is becoming more and more difficult because of diminishing returns. They have to dig ever deeper to get to the oil  at ever increasing costs, and the oil they find deep down is of a lesser quality.  We have now reached a point where the price needed by oil companies to make a profit and stay in business is far higher than the price  the market can bear. That price is probably about $ 100 per barrel - and rising every year! A market price o $ 100 will almost certainly cause a sharp recession and cause the price of oil to fall back beyond the point of profitability. For example, the combined profit of ExxonMobile, Chevron and Conocophillips fell from 80.4 billion in 2011 to only 3.7 billon in 2016 - see URL below. What the market can bear depends on the spending power of the mass of non-elite workers. The CLD shows the negative feedback loops that prevent oil prices to rise above the level of  affordability. If non-elite workers cannot afford the goods and services offered,  then there will be no demand for them and by extension for oil.  In this situation the market price will not the cover the cost that oil companies need to extract oil. Oil supplies will decline and so will economic activity!

https://srsroccoreport.com/the-blood-bath-continues-in-the-u-s-major-oil-industry/

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 (even 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. This ratio (Energy Invested on Energy Returned - EIOER) provides yet another warning that we can no longer rely on fossil fuels to power our economies. 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. 

PS: A link between growth in energy consumption and GDP growth is clearly illustrated on slide 13 of Gail Tverberg's presentaion entitled ''Oops! The world economy depends on an energy-related bubble''. In fact, the slide shows that growth in energy consumption usually precedes GDP growth.

https://gailtheactuary.files.wordpress.com/2015/10/oops-debt-bubble-10_30_15.pdf

How the 4-H club became a marketing thingy for DuPont

Fig 9.5 Integrated China SD model from Zhang 2018 MIT Thesis Potential housing bubble with Chinese characteristics

Overview

This model simulates logging and mountain biking competition in Derby, Tasmania. The Simulation is referenced to simulate Derby mountain biking with logging.

 

Model Work

The tourism industry is represented on the model's left side, and the logging industry is on the right side. Interactions between these two industries generate tax revenues. Logging and tourism have different growth rates regarding people working/consuming. The initial values of these two industries in the model are not fixed but increase yearly due to inflation or economic growth.

 

Detail Insights

From the perspective of tourism, as the number of tourists keeps growing, the number of people who choose to ride in Derby City also gradually increases. And the people who ride rate the ride. The negative feedback feeds back into the cycling population. Similarly, positive cycling reviews lead to more customer visits. And all the customers will create a revenue through tourism, and a certain proportion of the income will become tourism tax.

From a logging perspective, it is very similar to the tourism industry. As the number of people working in the industry is forecast to increase, the industry's overall size is predicted to grow. And as the industry's size continues to rise, the taxes on the logging industry will also continue to rise. Since logging is an industry, the tax contribution will be more significant than the tourism excise tax.

 

This model assumption is illustrated below:

1. The amount of tax reflects the level of industrial development.

2. The goal of reducing carbon emissions lets us always pay attention to the environmental damage caused by the logging industry.

3. The government's regulatory goal is to increase overall income while ensuring the environment.

4. Logging will lead to environmental damage, which will decrease the number of tourists.

 

This model is based on tourism tax revenue versus logging tax revenue. Tourism tax revenue is more incredible than logging tax revenue, indicating a better environment. As a result of government policy, the logging industry will be heavily developed in the short term. Growth in the logging industry will increase by 40%. A growth rate of 0.8 and 0.6 of the original is obtained when logging taxes are 2 and 4 times higher than tourism taxes.

 

Furthermore, tourism tax and logging tax also act on the positive rate, which is the probability that customers give a positive evaluation. The over-development of the logging industry will lead to the destruction of environmental resources and further affect the tourism industry. The logging tax will also affect the tourism Ride Rate, which is the probability that all tourism customers will choose Derby city.

 

This model more accurately reflects logging and tourism's natural growth and ties the two industries together environmentally. Two ways of development are evident in the two industries. Compared to tourism, logging shows an upward spiral influenced by government policies. Government attitudes also affect tourism revenue, but more by the logging industry. 

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?'

Model showing the effect of bank lending of deposited money as a multiplier in the creation of new money. Multiplier effect is shown as related to the bank reserve requirement on deposited funds.

The Cred System is an alternative to traditional currency that increases community resiliency and reduces participant's dependence on traditional dollars. This model is a basic description of the Cred System, involving four people and two loops.

Model supporting research of investment vs. austerity implications. Please refer to Modern Money & Public Purpose Video.

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Overview
This model is a working simulation of the competition between the mountain biking tourism industry versus the forestry logging within Derby Tasmania.

Modern Monetary theory (MMT) has shown how modern monetary systems actually work. It has shown  that governments that issue their own currency, such as the US, can never run out of money or be forced to default on debt issued in their own currency. It has also demonstrated that government spending to stimulate the economy is logical and that the resulting deficit is irrelevant - the government always has the monetary means to eliminate it. This directly contradicts neoliberal doctrine that wants to limit government spending and posits that deficits destabilize the economy. Neoliberalism often constitutes a 'worldview' and 'personal identity'. Those who hold such strong beliefs cannot be persuaded to abandon them using rational arguments and facts - psychological reasons usually impede it as research has shown. The worldwide dominance of the doctrine, vested interests and psychologically grounded opposition suffocate MMT and rational arguments showing its superiority are seemingly of no avail. 

Model showing the effect of bank lending of deposited money as a multiplier in the creation of new money. Multiplier effect is shown as related to the bank reserve requirement on deposited funds.

Model showing the effect of bank lending of deposited money as a multiplier in the creation of new money. Multiplier effect is shown as related to the bank reserve requirement on deposited funds.

Microeconomic measures can produce counterintuitive 'emergent' effects at the macro or systemic level. The commendable act of saving money by individuals during uncertain economic times has the perverse macroeconomic effect of making a recession  worse: in aggregate there will be less money available for spending, suppressing demand for goods and services. Economists call this effect 'the paradox of thrift'. Similarly, logical efforts by companies in such conditions to reduce their wage bill or their postponement of investment decisions will reduce spending in the economy  and deepen the economic downturn.

What can be done to counteract this harmful dynamic? The missing spending can be replaced by government spending: governments have it within their power to effectively counter economic downturns!