Economy | Insight Maker

Clone of Clone of Factors affecting Brazilian soy export growth

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.

Bank Deposit Money Multiplier

Joe Van Steen

4

Visão geral

O modelo mostra a conexão e o conflito da indústria entre o turismo florestal e o turismo de montanha em Derby, Tasmânia. O objetivo desta simulação é descobrir o ponto de equilíbrio para a coexistência.

Como funciona o modelo?

Ambas as indústrias podem fornecer contribuições económicas para a Tasmânia. Em primeiro lugar, a venda de madeira através da exploração madeireira geraria renda. Além disso, os gastos dos ciclistas de montanha gerariam renda. No entanto, a baixa taxa de regeneração das árvores não pode encobrir a exploração madeireira, o que influencia as belas vistas e as experiências dos ciclistas. Embora a satisfação e a expectativa dependam das opiniões e da experiência, a demanda pelo mountain bike também seria influenciada pelas visitas repetidas e pelo boca a boca.

Informações interessantes

Embora a silvicultura possa fornecer uma grande contribuição económica para a Tasmânia, o excesso de exploração madeireira vai contra a estrutura ESG, além de criar conflito com o turismo de montanha. Desde que o número de visitas de cavaleiros seja estável, o turismo pode sempre proporcionar uma maior contribuição económica em comparação com a silvicultura. Portanto, o governo deveria considerar o ponto de equilíbrio entre as duas indústrias.

Simulação de Mountain Bikes Derby versus Silvicultura

Douglas M.

This is a reconstruction of the SIMM model presented in Chapter 2 of Feedback Economics (Contemporary Systems Thinking)

@LinkedIn, Twitter, YouTube

Clone of Simple Macroeconomic Model (SIMM) (SFD)

Aykut Kibritçioğlu

This model shows the changing happened in forest industry and mountain tourism in Derby Tasmania. Logging will degrade mountain tourism while benefit the forestry industry. Simulation borrowed from the Easter Island simulation.

According to the analysis, logging does not reduce tourism income. With the increase of number of bike guide, tourism income will increase as well. Also, in forest industry, timber income is higher than the harvest spending which means the industry always gain profits from logging. Therefore, the main concern is that the logging should be balanced between the Mountain Tourism and the forest industry.

Simulation of Derby Mountain bikes versus logging

Mirai

A detailed description of all model input parameters is available here. These are discussed further here and here.

Update 14 December 2015 (v2.5): correction to net output basis LCOE calculation, to include actual self power demand for wind, PV and batteries in place of "2015 reference" values.

Update 20 November 2015 (v2.4): levelised O&M costs now added for wind & PV, so that complete (less transmission-related investments) LCOE for wind and PV is calculated, for both gross and net output.

Update 18 November 2015 (v2.3: development of capital cost estimates for wind, PV and battery buffering, adding levelised capital cost per unit net output, for comparison with levelised capital cost per unit gross output. Levelised capital cost estimate has been substantially refined, bringing this into line with standard practice for capital recovery calculation. Discount rate is user adjustable.

Default maximum autonomy periods reduced to 48 hours for wind and 72 hours for PV.

Update 22 October 2015 (v2.2): added ramped introduction of wind and PV buffering capacity. Wind and PV buffering ramps from zero to the maximum autonomy period as wind and PV generated electricity increases as a proportion of overall electricity supply. The threshold proportion for maximum autonomy period is user adjustable. Ramping uses interpolation based on an elliptical curve between zero and the threshold proportion, to avoid discontinuities that produce poor response shape in key variables.

Update 23 September 2015 (v2.1): added capital investment calculation and associated LCOE contribution for wind generation plant, PV generation plant and storage batteries.

**This version (v2.0) includes refined energy conversion efficiency estimates, increasing the global mean efficiency, but also reducing the aggressiveness of the self-demand learning curves for all sources. The basis for the conversion efficiencies, including all assumptions relating to specific types of work & heat used by the economy, is provided in this Excel spreadsheet.

Conversion of self power demand to energy services demand for each source is carried out via a reference global mean conversion efficiency, set as a user input using the global mean conversion efficiency calculated in the model at the time of transition commencement (taken to be the time for which all EROI parameter values are defined. A learning curve is applied to this value to account for future improvement in self power demand to services conversion efficiency.**

The original "standard run" version of the model is available here.

Clone of Energy transition to lower EROI sources (v2.5)

Tingyu

This is a reconstruction of the SIMM model presented in Chapter 2 of Feedback Economics (Contemporary Systems Thinking)

@LinkedIn, Twitter, YouTube

Clone of Simple Macroeconomic Model (SIMM) (SFD)

Kyra Evers

Clone of Factors affecting Brazilian soy export growth

Patricio Rodriguez Valiente

This is a reconstruction of the SIMM model presented in Chapter 2 of Feedback Economics (Contemporary Systems Thinking)

@LinkedIn, Twitter, YouTube

Simple Macroeconomic Model (SIMM) (SFD)

Gene Bellinger

9

British monetary policy

Karen Egan

This is a model that will simulate a medieval fantasy population with regular trades

Fantasy Simulation

Joris Slob

Simple mock-up model of how prioritizing various push-pull factors impacts the size of the immigrant population over time as well as economic benefits to the U.S. economy.

Clone of Immigrant Populations and Policy Implications

Nilo Guimaraes

Muhammad Firas Zahid Suryaatmaja

Compound Interest Rate Model

Compound Interest Rate

Muhammad Firas

Factors affecting Brazilian soy export growth

Ying Gao

Z414 from System Zoo 2

Bossel: Z414 Resource Discovery

Alfred Aenishaenslin

INTRODUCTION

This is a balanced loop model that demonstrates how COVID 19 outbreak in Burnie and the response of the government (e.g. by enforcing health policies: Lockdown; quarantine, non-necessary business closure; border closure) affect the local economy. This model has 13 positive loops and seven negative loops. Government response is dependent on the number of reported COVID-19 cases which in turn thought to be dependent on the testing rates less those who recovered from COVID 19 and dead. Economic activity is dependent on the economic growth rate, increased in online shopping, increased in unemployment, number of people who do not obey the rules, COVID 19 cases and health policies.

ASSUMPTIONS

· Both infection and economic growth is reduced by enforcing government policies

· However, the negative effect of government policies is reduced by the number of people who do not obey government health policies

· Govt policies are enforced when the reported COVID-19 case are 10 or greater.

· Number of COVID cases reported is dependent on the testing rates less those who recovered and dead.

· The higher number of COVID-19 cases have a negative effect on local economy. This phenomena is known as negative signalling.

· Government policies have a negative effect on economic activity because health policies limit both social and economic activities which directly or indirectly affect the economy in Burnie .

· This negative effect is somewhat reduced by the increase in online shopping and the number of people who do not obey heath rules.

INTERESTING INSIGHTS

The test ratings seem to play a vital role in controlling COVID-19 outbreak. Higher Rates of COVID testings decrease the number of COVID 19 deaths and number of infected. This is because higher rates of testing accelerate the government involvement (as the government intervention is triggered earlier, 10 COVID cases mark is reached earlier). Delaying the government intervention by reducing the COVID testing rates increases the death rates and number of infected.

Increased testing rates allow the figures (deaths, susceptible, infected) to reach a plateau quickly.

BMA708- Shakila Bethmage- 548351 - COVID 19 Outbreak in Burnie

Shakila Piyumi Perera Bethmage

Description:

This is a system dynamics model of COVID-19 outbreak in Burnie which shows the process of infections and how government responses, impact on the local economy.

First part is outbreak model, we can know that when people is infected, there are two situations. One is that he recovers from treatment, but even if he recovered, the immunity loss rate increase, makes him to become infected again. The other situation is death. In this outbreak, the government's health policies (ban on non-essential trips, closure of non-essential retailers, limits on public gatherings and quarantine ) help to reduce the spread of the COVID-19 new cases. Moreover, government legislation is dependent on number of COVID-19 cases and testing rates.

Second part: the model of Govt legislation and economic impact. Gov policy can help to reduce infection rate and local economy at same way. The increase of number of COVID-19 cases has a negative impact on local Tourism industry and economic growth rate. On the other hand, Govt legislation also can be change when reported COVID-19 case are less or equal to 10.

Model of COVID-19 outbreak in Burnie(Yafei Shi 489576)

Yafei Shi

Overview

A model which simulates the competition between logging versus adventure tourism (mountain bike ridding) in Derby Tasmania. Simulation borrowed from the Easter Island simulation.

How the model works.

Trees grow, we cut them down because of demand for Timber amd sell the logs.

With mountain bkie visits. This depends on past experience and recommendations. Past experience and recommendations depends on Scenery number of trees compared to visitor and Adventure number of trees and users. Park capacity limits the number of users.

Interesting insights

It seems that high logging does not deter mountain biking. By reducing park capacity, visitor experience and numbers are improved. A major problem is that any success with the mountain bike park leads to an explosion in visitor numbers. Also a high price of timber is needed to balance popularity of the park. It seems also that only a narrow corridor is needed for mountain biking

Clone of Simulation of Derby Mountain biking versus logging

James Ondari

this is economy as it is in reality.

economy

arkk

Simple mock-up model of how prioritizing various push-pull factors impacts the size of the immigrant population over time as well as economic benefits to the U.S. economy.

Immigrant Populations and Policy Implications

Kelsi Caywood

Simple SD version of Wheaton 1999 stock flow representation of DiPasquale-Wheaton 4 Quadrant steady state model (4QM) from Eskanasi 2014 and Zhang 2018 theses

Housing dynamics 1

Geoff McDonnell

5

Clone of Clone of Clone of Clone of Recycling and Waste Treatment in Vancouver

Miriam Rodrigues Da Costa

This is a reconstruction of the SIMM model presented in Chapter 2 of Feedback Economics (Contemporary Systems Thinking)

@LinkedIn, Twitter, YouTube

Clone of Clone of Simple Macroeconomic Model (SIMM) (SFD)

Joal Paiva

Overview

The model shows the industry connection and conflict between Forestry and Mountain Tourism in Derby, Tasmania. The objective of this simulation is to find out the balance point for co-exist.

How Does the Model Work?

Both industries can provide economic contribution to Tasmania. Firstly, selling timbers through logging would generate income. Also, spendings from mountain bike riders would generate incomes. However, low tree regrowth rate can not cover up logging, which influences the beautiful vistas and riders' experiences. While satisfaction and expectation depend on vistas and experience, the demand of mountain biking would be influenced through repeat visits and world of mouth as well.

Interesting Insights

Although forestry can provide a great amount of economic contribution to Tasmania, over logging goes against ESG framework as well as creating conflict with mountain tourism. As long as the number of rider visits is stable, tourism can always provide a greater economic contribution compared to forestry. Therefore, the government should consider the balance point between two industries.

Clone of Simulation of Derby Mountain Bikes versus Forestry

Douglas M.

Economy Models