Housing | Insight Maker

Simplified Causal loop diagram (from CLD 1 Insight) after quantitative simulation experiments from Fig 5.20 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 Video presentation

London Housing Crisis CLD 2 (HSD 8)

Geoff McDonnell

3 weeks ago

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.

Clone of Simple Real Estate Market

PT

8 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 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.

Clone of The effect of Supply and Demand on the Housing Market Assignment 3 (43323871)

Tanwa Arpornthip

Haaglanden Social housing Fig 18 SD Model feedback structure from Eskanasi 2014 thesis Other models in the thesis include middle income households and mortgage debt

Housing system dynamics 5 Netherlands

Geoff McDonnell

3 weeks ago

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 3 weeks ago

Fig 9.5 Integrated China SD model from Zhang 2018 MIT Thesis Potential housing bubble with Chinese characteristics

Housing system dynamics 3

Geoff McDonnell

3 weeks 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 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.

Miguel Macaraeg 43267971

Miguel Macaraeg

Fig 23 Houdini Interaction between rental and owner occupied sectors SD Model from Eskanasi 2014 thesis

Housing system dynamics 4 Netherlands

Geoff McDonnell

3 weeks ago

Houdini SD Model from Eskanasi 2014 thesis including land and social housing

Housing system dynamics 6 Netherlands

Geoff McDonnell

3 4 weeks 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 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.

Clone of The effect of Supply and Demand on the Housing Market Assignment 3 (43323871)

Ni Nyoman Wulandari

5 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 experiments

London Housing Crisis CLD 1 (HSD 7)

Geoff McDonnell

3 weeks ago