Housing Models

These models and simulations have been tagged “Housing”.

Related tagsDemandSupply

Based on Norbari APHA  presentation  2016 An agent-based model to examine the impact of unaffordable housing on obesity risk in early childhood, via Kurt Kreuger
Based on Norbari APHA presentation 2016 An agent-based model to examine the impact of unaffordable housing on obesity risk in early childhood, via Kurt Kreuger
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 instituti
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.
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
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
5 7 months ago
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 instituti
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.
  A stock-flow model of a Real Estate market.   A simple three-year, monthly, systems model.   Price  is a linear function  (straight line)  of the proportion of houses for sale  (positive slope) , and also a linear function of the proportion of buyers  (negative slope) .  Coefficients for the  Supp
A stock-flow model of a Real Estate market.
A simple three-year, monthly, systems model.
Price is a linear function (straight line) of the proportion of houses for sale (positive slope), and also a linear function of the proportion of buyers (negative slope).
Coefficients for the Supply Elasticity of Price and the Demand Elasticity of Price can be adjusted by the user using sliders.
Sales in each month are simply the lesser of the number of houses for sale and the number of buyers.
The number of houses for sale is a linear function of Price (positive slope) in the Flow "ToMarket".
Coefficient for Price Elasticity of Supply can be adjusted using a slider.
The number of buyers is a linear function of Price (negative slope) in the Flow "Motivation". Coefficient for Price Elasticity of Demand can be adjusted using a slider.
  A stock-flow model of a Real Estate market.   A simple three-year, monthly, systems model.   Price  is a linear function  (straight line)  of the proportion of houses for sale  (positive slope) , and also a linear function of the proportion of buyers  (negative slope) .  Coefficients for the  Supp
A stock-flow model of a Real Estate market.
A simple three-year, monthly, systems model.
Price is a linear function (straight line) of the proportion of houses for sale (positive slope), and also a linear function of the proportion of buyers (negative slope).
Coefficients for the Supply Elasticity of Price and the Demand Elasticity of Price can be adjusted by the user using sliders.
Sales in each month are simply the lesser of the number of houses for sale and the number of buyers.
The number of houses for sale is a linear function of Price (positive slope) in the Flow "ToMarket".
Coefficient for Price Elasticity of Supply can be adjusted using a slider.
The number of buyers is a linear function of Price (negative slope) in the Flow "Motivation". Coefficient for Price Elasticity of Demand can be adjusted using a slider.
Fig 17.15 p700 Causal
structure of commercial real estate markets of Case Study from John Sterman's 2000 Business Dynamics Book 
Fig 17.15 p700 Causal structure of commercial real estate markets of Case Study from John Sterman's 2000 Business Dynamics Book 
7 months ago
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 instituti
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 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 instituti
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.
Fig 2 to 14 Land Use added to 4 Quadrant Model SD Model from  Eskanasi 2014   thesis 
Fig 2 to 14 Land Use added to 4 Quadrant Model SD Model from Eskanasi 2014  thesis 
7 months ago
Initial qualitative causal loop diagram Fig 5.21 from Dianati, K. (2022) London’s Housing Crisis – A System Dynamics Analysis of Long-term Developments: 40 Years into the Past and 40 Years into the Future  UCL PhD Thesis  and see also  Video presentation  and  CLD 2 Insight  after Simulation experim
Initial qualitative causal loop diagram Fig 5.21 from Dianati, K. (2022) London’s Housing Crisis – A System Dynamics Analysis of Long-term Developments: 40 Years into the Past and 40 Years into the Future UCL PhD Thesis and see also Video presentation and CLD 2 Insight after Simulation experiments
7 months ago
  Miguel's Model of the Real Estate Market and Price Elasticity   This model represents the real-estate market, and the processes and variables in play which influence thatfocus on the effects of Price on the Elasticity of Supply and Demand.  The law of supply and demand states that when there is a

Miguel's Model of the Real Estate Market and Price Elasticity

This model represents the real-estate market, and the processes and variables in play which influence thatfocus on the effects of Price on the Elasticity of Supply and Demand.

The law of supply and demand states that when there is a high demand for a good or service. The price of the good or service rises. If there is a large supply of good or service but not enough demand for the good or service, the price falls. 

The price elasticity of supply is used to see how sensitive the supply of a good is to a price change. The higher the price elasticity the higher the sensitivity to price change. A Low price elasticity implies that changes in price have little influence on supply.

The price elasticity of Demand is used to see how sensitive the demand for a good is to a price change. The higher the price elasticity, the more sensitive to price changes. A Low price elasticity implies that changes in price have little influence on demand. 

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Important Variables and Stocks Involved

Old Quantity of Supply

%Change in Quantity Supply

HousesforSale

Old Quantity of Demand

%Change in Quantity Demand

WantingToBuy

Price Elasticity of Supply

Price Elasticity of Demand

%Change in Price

Old Price 

New Price


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Within this model to calculate the price elasticity of supply, the percentage change is first calculated using the Old quantity and New quantity (HousesForSale).

This percentage change is then divided by the percentage change of the Old Price and New Price to obtain the Price Elasticity of Supply.

Similarly to calculate the price elasticity of demand, the percentage change is calculated using the Old quantity of demand and New quantity of demand (WantingToBuy).

This percentage change is then divided by the percentage change in price to obtain the Price Elasticity of Demand.

With the slider variables that can be changed are the Old Price and New price which affect the percentage change in price.

The percentage change in price then affects the Price Elasticity of Supply and Demand as it is used in conjunction with the %Change in quantity of Supply and Demand to obtain a value.

If we set the settings and simulate to:

Old Price = 500('000)

New Price = 250('000)

Old Quantity of Supply = 100

HousesforSale (New Quantity of Supply) = 50

Old Quantity of Demand = 10

WantingToBuy (New Quantity of Demand) = 5

We can see that the Demand is a lot higher because the the houses are half the price than the old price.

If we use these settings:

Old Price = 250('000)

New Price = 500('000)

Old Quantity of Supply = 50

HousesforSale (New Quantity of Supply) = 25

Old Quantity of Demand = 25

WantingToBuy (New Quantity of Demand) = 10

We can see that the supply is a lot higher than demand as the new price is twice the amount of the old price. 

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With the sliders, these values can be adjusted to see the affect on the Price Elasticity of Supply and Demand. 

This Model should have included its effect on the price however, was not added due to problems finding the right equation. 

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 instituti
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.
4 months ago
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 instituti
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.
4 months ago
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 instituti
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.
2 months ago