Housing | Insight Maker

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)

Ryan Nakhle

32

Documentation

The Insight shown demonstrates how demand and supply in a real estate market can affect pricing.

Demand, Supply and Price have been represented by stocks. Each has an inflow where it has an increase in stock, and a corresponding outflow where stock is decreased.

Linking each stock and flow is a variable that changes that which it is linked to. These have been labelled appropriately. Each variable takes a decimal value and multiplies it with that it is linked to, such as the rate of demand affecting the price set as 0.001*Demand. This is to generate the loops required to show the rise and fall in price, demand and supply.

Adjustments can be made to the price, supply and demand stocks to simulate different scenarios. Price can be between 400 (400,000) and 1000 (1,000,000) in accordance to average housing prices. Demand and supply can be between 0 (0%) and 100 (100%), although having these set as realistic figures will demonstrate the simulation best.

Each simulation can be focused on how either demand and price interact over time or supply and price. These are shown in different tabs.

When the simulation is carried out, the way in which demand and supply rates affect pricing can be seen. Demand and supply are shown with price following shortly after with a slight delay, since changes in market behavior does not immediately affect prices of housing.

It should also be noted that the lines that represent each stock do not directly reflect the prices of housing in reality. Prices do not fluctuate so rapidly from 400 to near 0 like they do on the graph, however these are just representations of the interactions between each stock in a marketplace.

Zachary Chapman - 43309399 - Assignment 3 Final

Zachary Chapman

3

Macquarie University | MGMT220: Fundamentals of Business Analytics | Assignment Task #3: Complex Systems by Ying Chen (42151619)

This simple model uses the following key factors to demostrate the behaviour within the real estate market, bank's interest rates, median sale price, and listed sale price.

Sliders located below can be used to set values to simulate the affects over time.

Factors Affecting the Real Estate Market by 42151619

Ying Chen

4

A Complex System SD Model displaying the fluctuations and variables affecting the housing market.

Refer to storyboard for information of the SD Model

MGMT220 - Assignment 3 - 42845971 -Emma HASTINGS

Emma Hastings

A causal loop diagram illustrating solutions for the homelessness problem

Homelessness Model

Fred Nel

The law of supply and demand is a basic economic principle that explains the relationship between supply and demand for a good or service and how the interaction affects the price of that good or service. The relationship of supply and demand affects the housing market and the price of a house.

A number of factors including government policy affects the law of demand and supply, which I hope my diagram illustrates

When there is a high demand for properties in a particular city or state and a lack of supply of good quality properties, the prices of houses tend to rise. When there is no demand for housing due to a weak economy and an oversupply of properties is available, the prices of houses tend to fall.

Clone of 42988241 Leon Dhemba

Margarita Stergiou

A causal loop diagram illustrating solutions for the homelessness problem

Clone of Homelessness Model

HANNAH OLTMAN

The following is a complex system depicting the nature of real estate and showing the deciding factors of its activities.

House supply and house prices have a direct relationship (linear - positive). Buyers and house prices have an indirect relationship (linear - negative). Interest rate and desire are directly related (linear - positive).

Complex Systems - 43036317

Dileesha Sigera

The following model shows a real estate market created by a web-based modelling and simulation tool; Insight Maker. This model shows the relationships and links between many different players within the real estate market and how some changes are able to change the marketplace overall.

Information from Model

The information generated from this model includes "Wanting to Buy", "Houses for Sale" and "Price". "Wanting to Buy" refers to the players who demand or wish to buy houses, "Houses for Sale" refers to the total supply of houses within this marketplace whilst "Price" refers to the price an individual bought a house at a certain point in time.

Variables Included

All variables on the model are shown as ovals and are either fixed or can be adjusted. The fixed variables are shown in yellow, where fixed refers to not being able to be changed by non-editors viewing this model. These variables can not be adjusted as these variables are directly related from the information produced within the model. For example, the variable "Price" can not be adjusted as it would produce incorrect information when the model is simulated

All other variables shown in orange can be adjusted by moving the respective sliders. These variables are able to be adjusted according to what the view wishes.

Interesting Parameters

One adjusted that the user can make is to increase the "Demand Elasticity of Price" from 100 to 200. This increase in demand elasticity means a greater amount of individuals would be willing to purchases a house. As with the laws of supply and demand, an increase in demand will lead to a increase in price. Once simulated, this model shows that over time the price for a house increases.

One other interesting parameter that the user could do is to increase the level of "Destroy Houses" from 0.05 to 0.1. This increase would lead to a fall in the total amount of houses as the level of houses being destroyed (0.1) is greater than the level of houses being build (0.05). As shown in the simulation, this would lead to a fall in the total houses available in the marketplace.

Real Estate Market - Raymund Paradeza 43626491

Raymund Paradeza

4

This is a model that depicts the interactions between buyers and sellers in regards to the position of price to the median price.

This model works on the premise that when house prices drop below median price, buyers will increase and sellers will decrease, and vise versa.

When the values for Price, Buyers and Sellers are set to 50, the system will be in Equilibrium.

Delays have not been added in order to show how components instantly respond to changing parameters.

A more in-depth description is provided in the story.

Complex Systems Assignment #3 MGMT220 - Jeff Sun 42869129

Xu Jeff Sun

4

In the real-estate domain, buyers (demand) and sellers (supply) directly influence the price of houses. However, their motivation to buy and sell is directly influenced in respect to how the median price of houses is compared to the sensitivity (elasticity) of the actual prices and demand of houses.

This model will represent how the changes in price elasticity compared to the median price, affect the supply and demand within the real-estate domain.

1) Price and Demand Elasticity can be changed between 0-100 to show variances within the sensitivity of price in the market.

2) Buyers & Sellers are set to 75 however this can be fluctuated between 0-150 to represent variances within the demand & supply in the market.

3) Median Price is set to 75 since the total amount of buyers and sellers within the market is set to a maximum of 150. 75 is therefore the ‘median’.

4) Interest rates are also a factor in the demand of houses and influence the motivation for Buyers. If interest rates are high, Buyers are less motivated to buy due to increase in mortgages, therefore having a decrease in the demand and vice versa for when they are low. The following equation compares the price of houses to the median price, and if this condition is true, will apply Interest Rate(s) to the following logic.

if [Price]<[Median Price] Then

([Interest Rate]+[Demand Growth Ratio]-[Demand Growth Ratio])*[Buyers] end if

5) The price of houses is directly influenced by elasticity of demand and price within the market place. For example; if the elasticity of demand is relatively inelastic, the percentage change in the amount of houses demanded is smaller than that of the price. The following equation applies the logic listed above.

60-[Supply Elasticity of Price]/100*[Total Sellers]+[Demand Elasticity of Price]/100*[Total Buyers]+[Price Elasticity of Supply]/100*[Total Sellers]

Nicholas Clancy -Assignment 3- 43275796

Nicholas Clancy

The following model shows a real estate market created by a web-based modelling and simulation tool; Insight Maker. This model shows the relationships and links between many different players within the real estate market and how some changes are able to change the marketplace overall.

Information from Model

The information generated from this model includes "Wanting to Buy", "Houses for Sale" and "Price". "Wanting to Buy" refers to the players who demand or wish to buy houses, "Houses for Sale" refers to the total supply of houses within this marketplace whilst "Price" refers to the price an individual bought a house at a certain point in time.

Variables Included

All variables on the model are shown as ovals and are either fixed or can be adjusted. The fixed variables are shown in yellow, where fixed refers to not being able to be changed by non-editors viewing this model. These variables can not be adjusted as these variables are directly related from the information produced within the model. For example, the variable "Price" can not be adjusted as it would produce incorrect information when the model is simulated

All other variables shown in orange can be adjusted by moving the respective sliders. These variables are able to be adjusted according to what the view wishes.

Interesting Parameters

One adjusted that the user can make is to increase the "Demand Elasticity of Price" from 100 to 200. This increase in demand elasticity means a greater amount of individuals would be willing to purchases a house. As with the laws of supply and demand, an increase in demand will lead to a increase in price. Once simulated, this model shows that over time the price for a house increases.

One other interesting parameter that the user could do is to increase the level of "Destroy Houses" from 0.05 to 0.1. This increase would lead to a fall in the total amount of houses as the level of houses being destroyed (0.1) is greater than the level of houses being build (0.05). As shown in the simulation, this would lead to a fall in the total houses available in the marketplace.

Clone of Real Estate Market - Raymund Paradeza 43626491

sub cribed

Broadmoor Gentrification

Ryan Mast

This model aims to analyze how conservation from 2013 to 2017 needs improving in order to meet the needs to repopulate the Florida panther based on Acreage of conservation. Human population and housing development challenge conservation efforts, this model produces scenarios that test policy efforts in repopulate the Florida Panther. Our goal is to conserve 16 million acres for a habitat with 500 panthers.

SOS 212: Final Project

Christopher P Ryan

The law of supply and demand is a basic economic principle that explains the relationship between supply and demand for a good or service and how the interaction affects the price of that good or service. The relationship of supply and demand affects the housing market and the price of a house.

A number of factors including government policy affects the law of demand and supply, which I hope my diagram illustrates

When there is a high demand for properties in a particular city or state and a lack of supply of good quality properties, the prices of houses tend to rise. When there is no demand for housing due to a weak economy and an oversupply of properties is available, the prices of houses tend to fall.

42988241 Leon Dhemba

Leon Dhemba

Documentation

The Insight shown demonstrates how demand and supply in a real estate market can affect pricing.

Demand, Supply and Price have been represented by stocks. Each has an inflow where it has an increase in stock, and a corresponding outflow where stock is decreased.

Linking each stock and flow is a variable that changes that which it is linked to. These have been labelled appropriately. Each variable takes a decimal value and multiplies it with that it is linked to, such as the rate of demand affecting the price set as 0.001*Demand. This is to generate the loops required to show the rise and fall in price, demand and supply.

Adjustments can be made to the price, supply and demand stocks to simulate different scenarios. Price can be between 400 (400,000) and 1000 (1,000,000) in accordance to average housing prices. Demand and supply can be between 0 (0%) and 100 (100%), although having these set as realistic figures will demonstrate the simulation best.

Each simulation can be focused on how either demand and price interact over time or supply and price. These are shown in different tabs.

When the simulation is carried out, the way in which demand and supply rates affect pricing can be seen. Demand and supply are shown with price following shortly after with a slight delay, since changes in market behavior does not immediately affect prices of housing.

It should also be noted that the lines that represent each stock do not directly reflect the prices of housing in reality. Prices do not fluctuate so rapidly from 400 to near 0 like they do on the graph, however these are just representations of the interactions between each stock in a marketplace.

Clone of Zachary Chapman - 43309399 - Assignment 3 Final

YTHagakure

Documentation

The Insight shown demonstrates how demand and supply in a real estate market can affect pricing.

Demand, Supply and Price have been represented by stocks. Each has an inflow where it has an increase in stock, and a corresponding outflow where stock is decreased.

Linking each stock and flow is a variable that changes that which it is linked to. These have been labelled appropriately. Each variable takes a decimal value and multiplies it with that it is linked to, such as the rate of demand affecting the price set as 0.001*Demand. This is to generate the loops required to show the rise and fall in price, demand and supply.

Adjustments can be made to the price, supply and demand stocks to simulate different scenarios. Price can be between 400 (400,000) and 1000 (1,000,000) in accordance to average housing prices. Demand and supply can be between 0 (0%) and 100 (100%), although having these set as realistic figures will demonstrate the simulation best.

Each simulation can be focused on how either demand and price interact over time or supply and price. These are shown in different tabs.

When the simulation is carried out, the way in which demand and supply rates affect pricing can be seen. Demand and supply are shown with price following shortly after with a slight delay, since changes in market behavior does not immediately affect prices of housing.

It should also be noted that the lines that represent each stock do not directly reflect the prices of housing in reality. Prices do not fluctuate so rapidly from 400 to near 0 like they do on the graph, however these are just representations of the interactions between each stock in a marketplace.

Clone of Zachary Chapman - 43309399 - Assignment 3 Final

Isaiah Ritzmann

System Dynamics

Chan Kian Quan

Demographic change is driving need for housing which can be adapted to the needs of those with health conditions, domiciliary care and care home places. Forecasts are required to guide providers of housing and care homes, as well as health and social care services. This model provides a framework for identifying the drivers of demand and developing a consensus forecast.

Housing and care homes

David Plummer

41

Author: Brandon Sultana 43268080

This is a 3 year model that depicts the flows between Price, Supply and Demand in the real-estate market.

Throughout the model viewers can observe how the figures Price, Supply and Demand alter each other in an increasing or decreasing way.

Price is decreased by the growing supply of HousesForSale and increased by the growing demand of people wanting to buy. As Price decreases, HousesForSale increases and Price decreases as HousesForSale increase.

From the use of the graph it is evident that over 3 years the flow of house prices fluctuate and therefore more houses are sold at different times over 3 years.

The purpose of this insight is to help consumers and Businesses depict the best times to either buy or sell houses to maximize profits.

Additionally the market had to respect the number of possible consumers who are opting to build new houses, based on the rise and fall of house prices the real-estate analyses the new houses and residents in the area grow overtime.

Due to population growth, This cycle remains continuous so long as the real-estate company manages their resources effectively

Real-Estate Cycle Brandon Sultana 43268080

Brandon Luke Sultana

Retail Re-state Market

Insight Maker is a program that allows users to create complex interactions among industry or social factors. This program was used to model the relationships among different players in the real estate market.

This model shows the effects of changes in supply and demand, demand price and supply cost, availability of houses and houses prices on the Retail Re-state Market Demand, Demand Price, Supply, Supply Cost, Interest Rate, House Market and Houses Prices can be all adjusted by the user using the sliders [Slider Value 0-100 (000 000 value)]. Allowing the user to simulate different scenarios and view changes in the market.

For Example:

A slight change in House Prices will affect the Availability of Houses, House Price and the Supply and Demand dramatically.

When Supply increases, the availability of houses increases while Demand decreases.

Supply/Supply Cost has a direct relationship to one another as one variable increases the other one decreases.

Demand and Demand Price has a inversely relationship related to Price /

Availability of Houses is simply New houses and houses Sold, based on If statements, If Demand=>Supply or If Supply <= Demand, the quantity will adjusted to meet the Demand and Supply levels.

Houses Price is simply House Price Increase and Houses Price decrease, based on if statements, If Demand=>Supply Cost or If Supply Cost <= Demand Price, the price will be adjusted to meet the Demand and Supply price.

Clone of Ricky Su 43671942 (Assessment 3)

Duc Nguyen

A model that depicts the interactions between buyers and sellers in regards to the position of price to the median price.

This model works on the premise that when house prices drop below median price, buyers will increase and sellers will decrease, and vise versa.

Delays have not been added in order to show how components instantly respond to changing parameters.

Clone of Complex Systems Assignment #3 MGMT220

Duc Nguyen

Fig 17.15 p700 Causal structure of commercial real estate markets of Case Study from John Sterman's 2000 Business Dynamics Book

Boom and bust in Commercial Real Estate

Geoff McDonnell

The following model shows a real estate market created by a web-based modelling and simulation tool; Insight Maker. This model shows the relationships and links between many different players within the real estate market and how some changes are able to change the marketplace overall.

Information from Model

The information generated from this model includes "Wanting to Buy", "Houses for Sale" and "Price". "Wanting to Buy" refers to the players who demand or wish to buy houses, "Houses for Sale" refers to the total supply of houses within this marketplace whilst "Price" refers to the price an individual bought a house at a certain point in time.

Variables Included

All variables on the model are shown as ovals and are either fixed or can be adjusted. The fixed variables are shown in yellow, where fixed refers to not being able to be changed by non-editors viewing this model. These variables can not be adjusted as these variables are directly related from the information produced within the model. For example, the variable "Price" can not be adjusted as it would produce incorrect information when the model is simulated

All other variables shown in orange can be adjusted by moving the respective sliders. These variables are able to be adjusted according to what the view wishes.

Interesting Parameters

One adjusted that the user can make is to increase the "Demand Elasticity of Price" from 100 to 200. This increase in demand elasticity means a greater amount of individuals would be willing to purchases a house. As with the laws of supply and demand, an increase in demand will lead to a increase in price. Once simulated, this model shows that over time the price for a house increases.

One other interesting parameter that the user could do is to increase the level of "Destroy Houses" from 0.05 to 0.1. This increase would lead to a fall in the total amount of houses as the level of houses being destroyed (0.1) is greater than the level of houses being build (0.05). As shown in the simulation, this would lead to a fall in the total houses available in the marketplace.

Clone of Real Estate Market - Raymund Paradeza 43626491

PT

Housing Models