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
This model is an attempt to simulate what is commonly
referred to as the “pesticide treadmill” in agriculture and how it played out
in the cotton industry in Central America after the Second World War until
around the 1990s.
The cotton industry expanded dramatically in Central America
after WW2, increasing from 20,000 hectares to 463,000 in the late 1970s. This
expansion was accompanied by a huge increase in industrial pesticide
application which would eventually become the downfall of the industry.
The primary pest for cotton production, bol weevil, became increasingly
resistant to chemical pesticides as they were applied each year. The
application of pesticides also caused new pests to appear, such as leafworms,
cotton aphids and whitefly, which in turn further fuelled increased application
of pesticides.
The treadmill resulted in massive increases in pesticide
applications: in the early years they were only applied a few times per season,
but this application rose to up to 40 applications per season by the 1970s;
accounting for over 50% of the costs of production in some regions.
The skyrocketing costs associated with increasing pesticide
use were one of the key factors that led to the dramatic decline of the cotton
industry in Central America: decreasing from its peak in the 1970s to less than
100,000 hectares in the 1990s. “In its wake, economic ruin and environmental
devastation were left” as once thriving towns became ghost towns, and once
fertile soils were wasted, eroded and abandoned (Lappe, 1998).
Sources: Douglas L. Murray (1994), Cultivating Crisis: The Human Cost of Pesticides in Latin America, pp35-41;
Francis Moore Lappe et al (1998), World
Hunger: 12 Myths, 2nd Edition, pp54-55.
A model of the ebb and flow of agricultural societies, like China's history. From Khalil Saeed and Oleg Pavlov's WPI 2006 paper See also the Generic structure Insight Map
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.
Residents, or the general population of individuals, place significant reliance on financial institutions to provide sources of capital i.e mortgages, to fund their purchases of homes. The rate of interest charged by these organisations in turn gives buyers (consumers) purchasing power, creating demand.
Supply is made up of the number of houses in the market, and consequently, of these, the number of houses which are up for sale. As the prices of houses for sale increases, the demand for purchase of these properties decreases. Conversely, the lower price, the higher the demand. Once the market reaches an equilibrium point, to which buyers and sellers form an agreement, houses are sold accordingly. An underlying factor to consider is the cost of construction, which impacts producers, or suppliers in this instance, and thus the number of homes for sale, and the expected profit sellers hope to achieve.
The simulated graph highlights the common scenario within the housing market, to which we see that as price increases, the total number for houses for sale decreases, generating an opposite slope to the price. As the price for houses increases, the demand for the houses decreases and vice versa. The equilibrium is evident at time 14 whereby the price of houses and the number of houses for sale overlaps which in turn creates a market to which both buyers and sellers are happy.
The effect of Supply and Demand on the Housing Market Assignment 3 (43323871)
ECONOMIC GROWTH feeds on itself, provided the growth engine is fed with materials and
finance. In this highly simplified representation some of the factors that influence economic growth
are show in the incircled green fields. Governments can influence economic growth positively
via investments and payouts. The most
obvious tool which governments can use to slow an overheated economy is
taxation.
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.
Wealth can be seen as the factories,
infrastructure, goods and services the population of a nation dispose of. According
to Tim Garrett, a scientist who looks at
the economy from the perspective of physics, it is existing wealth that generates
economic activity and growth. This growth demands the use of energy as no
activity can take place without its use. He also points out that the use of this
energy unavoidably leads to concentrations of CO2 in the
atmosphere. All this, Tim Garrett says, follows from the second law of thermodynamics.
If wealth decreases then so does economic activity and growth. The CLD tries to illustrate how wealth,
ironically, now generates the conditions and feedback loops that may cause it to decline. The consequences are inevitably economic stagnation (or secular recession?).
You can
read about the connection Tim Garrett makes between 'Wealth, Economic Growth,
Energy and CO2 Emissions' simply by
Googling 'Tim Garrett and Economy'.
A Tragedy of the Commons situation exists whenever two or more activities, each, which in order to produce results, rely on a shared limited resource. Results for these activities continue to develop as long as their use of the limited resource doesn't exceed the resource limit. Once this limit is reached the results produced by each activity are limited to the level at which the resource is replenished. As an example, consider multiple departments with an organization using IT resources, until they've exhausted IT capacity.
Environmental economics Niger Delta oil polluted case study
Simple model of the global economy, the global carbon cycle, and planetary energy balance.
The planetary energy balance model is a two-box model, with shallow and deep ocean heat reservoirs. The carbon cycle model is a 4-box model, with the atmosphere, shallow ocean, deep ocean, and terrestrial carbon.
The economic model is based on the Kaya identity, which decomposes CO2 emissions into population, GDP/capita, energy intensity of GDP, and carbon intensity of energy. It allows for temperature-related climate damages to both GDP and the growth rate of GDP.
This model was originally created by Bob Kopp - https://insightmaker.com/user/16029 (Rutgers University) in support of the SESYNC Climate Learning Project.
Steve Conrad (Simon Fraser University) modified the model to include emission/development/and carbon targets for the use by ENV 221.
REM 221 Simple Climate-Carbon-Economic Model with Targets
WIP SD representation of Ch11 of their 2007 Monetary Economics book, as suggested by Adam K. Plan is to do a top down simple money flow SFC mmt model and successively split sectors. See also essence of MMT IM and simpler version Ch3 IM
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
