Tasmania Models
These models and simulations have been tagged “Tasmania”.
These models and simulations have been tagged “Tasmania”.
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.
This model indicate indicates the modeling COVID-19 outbreaks and responses from government policies with the effect on the local economy. Model was occurred at Burnie, Tasmania. The model mainly contains three parts: COVID-19 pandemic outbreak, four differences government policies and what the impact on economy from those policies.
Assumptions:
(1) Various variables influence the model, which can result in varied outcomes. The following values are based on an estimate and may differ from actual values. Government initiatives are focused at reducing Covid-19 infections and, as a result, affecting (both positive and negative) economic growth.
(2) 42% of infected people will recovery. 10% of people who are infected will die and the rate relatively higher due to the much old people living in Burnie, Tasmania.
78% of cases get tested.
(3) Government policy will only be implemented when there are ten or more recorded cases. Four government policies have had influences on infection.
(4) The rising number of instances will have a negative impact on Burnie's economic growth.
Insights:
1. As a result of the government's covid 19 rules, fewer people will be vulnerable. Less people going to be susceptible.
2. After the government policy intervention, there is a effectively reduce of infected people.
3. Overall, there is no big differences of economic performance from the graph, might due to the positive and negative effect of economy. And after two weeks, the economy maintained a level of development without much decline.
ABOUT THE MODEL
This is a dynamic model that shows the correlation between the health-related policies implemented by the Government in response to COVID-19 outbreak in Burnie, Tasmania, and the policies’ impact on the Economic activity of the area.
ASSUMPTIONS
The increase in the number of COVID-19 cases is directly proportional to the increase in the Government policies in the infected region. The Government policies negatively impact the economy of Burnie, Tasmania.
INTERESTING INSIGHTS
1. When the borders are closed by the government, the economy is severely affected by the decrease of revenue generated by the Civil aviation/Migration rate. As the number of COVID-19 cases increase, the number of people allowed to enter Australian borders will also decrease by the government.
2. The Economic activity sharply increases and stays in uniformity.
3. The death rate drastically decreased as we increased test rate by 90%.
