Housing market and finance

Q: What is a market? A: Let s play a game Motivation THE APPLE MARKET The class is divided at random into two groups: buyers and sellers

Rules: Buyers: Each buyer receives a card containing a number (keep it to yourself) This number is the maximum price he/she is willing to pay for one unit Buyers cannot buy a unit at a price exceeding this number (would be happy to buy at any price below this number) Better buy one than leaving wants go unsatisfied Surplus : Difference between willingness to buy and the actual price paid If a buyer wants to make a bid, please raise your hand and say Buyer XXXX: Bid your bid price Each succeeding bid price must exceed the previous ones until a transaction occurs.

Rules: Sellers: Each seller receives a card containing a number (keep it to yourself) This number is the minimum price he/she is willing to sell for one unit Sellers cannot sell a unit at a price below this number (would be happy to sell at any price above this number) Better sell one than leaving wants go unsatisfied Surplus : Difference between selling price and the reservation price If a seller wants to sell a unit, please raise your hand and say Seller XXXX: Ask your ask price Each succeeding ask price must be below the previous ones until a transaction occurs.

I am the auctioneer and will record the bid, ask, and transacted prices on the board. Each buyer and seller is allowed to make one transaction. The buyer and seller making the deal drop out of the market (no longer a legitimate participant). A new trading period begins whenever a transaction is concluded.

Price THE APPLE MARKET Number of apples

OUR HYPOTHETICAL MARKET OF APPLES Price Supply Equilibrium price BUT THE HOUSING MARKET IS *VERY* DIFFERENT FROM THIS HYPOTHETICAL MARKET! Demand Equilibrium quantity Quantity

Characteristics of the housing market Housing is not an identical product! Homogeneity vs. heterogeneity What is price measuring? Participants are not identical! Tenure choice The Demographic housing market events is a lot more complex than the demand-supply diagram shown earlier! Housing is not easily malleable and purchasing it requires a large outlay! Financing Neighbourhood characteristics / externality Housing market is not a closed market! Search and uncertainty Household mobility

OUR HYPOTHETICAL MARKET OF APPLES Price Supply Equilibrium price Demand Equilibrium quantity Quantity

Estimating the market price of housing To fix ideas: Consider owner-occupied housing

Problem 1: What is quantity here? Solution: Notion of housing services: Standardized units of services; flow of services provided by each dwelling unit Horizontal axis: units of services Vertical axis: rent per unit of services Problem 2: What is price? Solution: Imputed rent owners pay rent to themselves Rent = Price * interest rate Price = Rent / interest rate Problem 3: How to measure units of services? Solution: Instead of observing rent per unit, we observe total expenditure (quantity times price per unit) = value of the dwelling

OUR HYPOTHETICAL MARKET OF APPLES Price Supply Equilibrium price Demand Equilibrium quantity Quantity

Estimating the market price of housing (continued) To fix ideas: Consider owner-occupied housing Approaches to estimating the market price: A. Hedonic price index B. Repeat sales C. Variants of the above two

Estimating the market price of housing (continued) A. Hedonic index Assumptions 1. Housing provides a flow of housing services bundle of property rights and enjoyment 2. Can decompose price into price per unit of services by attributes Physical Environmental Neighbourhood 3. Can use transacted prices to predict prices of similar housing units

Estimating the market price of housing (continued) Hedonic index Data requirements 1. A database of recently transacted properties 2. Observe: Selling price # of bedrooms # bathrooms Square footage / lot size Furnished basement? # kitchens Access to park / amenities / pollutants Distance to the CBD

Estimating the market price of housing (continued) Hedonic index Sample data 1998 transacted properties in Markham, Ontario ~900 observations from MLS (district N11) See map

Sample transacted properties from Multiple Listing Services, Markham (1999)

Estimating the market price of housing (continued) Hedonic index Sample data 1998 transacted properties in Markham, Ontario ~900 observations from MLS (district N11) See map Technique Statistical technique: Linear regression (log-log form) Results Interpretation See table

Hedonic pricing model, Markham (1999)

Estimating the market price of housing (continued) Hedonic index Sample data 1998 transacted properties in Markham, Ontario ~900 observations from MLS (district N11) See map Are similar dwelling units indeed comparable? Technique Statistical technique: Linear regression (log-log form) Results Interpretation See table

Estimating the market price of housing (continued) B. Repeat sales Assumptions 1. Concerns the regional house price index (aggregated at some geographic scale) 2. Changes in house prices of the SAME house would provide a quality-controlled index

Estimating the market price of housing (continued) B. Repeat sales Data requirements 1. A database of transacted properties over a long period of time Properties / stock of dwelling units in a region 2. Observe: Year of first transaction Year of second / subsequent transaction(s) Selling price of each transaction

Estimating the market price of housing (continued) B. Repeat sales Sample data 1985-2001 all properties in Philadelphia, Pennsylvania See map and table

Sample repeat sales data from Philadelphia, Pennsylvania (1980-2001)

Estimating the market price of housing (continued) B. Repeat sales Technique Statistical technique Assign -1 to year of first transaction Assign 1 to year of second transaction Assign 0 to years with no transaction Regress change in selling prices (log) on years (-1,0,1) Results and Interpretation See table

Repeat Sales House Price Index of Philadelphia, Pennsylvania (1980-2001)

Repeat Sales House Price Index of Philadelphia, Pennsylvania (1980-2001) Price index 2000=1 Years

Estimating the market price of housing (continued) B. Repeat sales Technique Statistical technique Assign -1 to year of first transaction Which dwelling units get sold most frequently? Market Assign 1 to year of second lemons! transaction Assign 0 to years with no transaction Regress change in selling prices (log) on years (-1,0,1) BE IT THE HEDONIC PRICE OR REPEAT SALES INDEX, WHAT IS ESTIMATED IS THE *MARKET* PRICE. IT IS NOT Results and Interpretation YOUR WILLINGNESS TO PAY! See table

OUR HYPOTHETICAL MARKET OF APPLES Price Supply Equilibrium price HOW TO ESTIMATE THE DEMAND FOR OWNER- OCCUPIED HOUSING? Equilibrium quantity Demand Quantity

Demand for owner-occupied housing Theory of demand: Shifts in demand may be caused by A. Income B. Price of substitutes / complements C. Preferences D. Population A. Income (see graph): Permanent income: Annuity equivalent of a person s life-time earnings Transitory income: How much a person s current earnings exceed or fall short of his / her permanent income Lifecycle Theory: Permanent income is important among owners because they borrow against their future income

Characteristics of the housing market Housing is not an identical product! Homogeneity vs. heterogeneity What is price measuring? Participants are not identical! Tenure choice Demographic events Housing is not easily malleable and purchasing it requires a large outlay! Financing Neighbourhood characteristics / externality Housing market is not a closed market! Search and uncertainty Household mobility

Demand for owner-occupied housing (continued) B. Price of substitutes (see graph): User cost of home ownership: Mortgage, tax, depreciation, maintenance, utilities, insurance, less capital gain

Price has decreased relative to rent

Demand for owner-occupied housing (continued) B. Price of substitutes (see graph): User cost of home ownership: Mortgage, tax, depreciation, maintenance, utilities, insurance, less capital gain C. D. Preferences / Population: Demographics: Household size, presence of child(ren), household composition (individuals or couples, lone parents), gender of household head

Demand for owner-occupied housing (continued) Data requirement: Microdata file (individuals) Income data Tenure data (owner vs. renter) Demographic and socioeconomic characteristics Statistics Canada publishes Public-use Microdata File (PUMF) for individuals / families / households Census (bicentennial) Statistics Canada also publishes another source: Household Incomes, Facilities and Equipments (HIFE) microdata file for households Annual Sample data: See SAS table

Demand for owner-occupied housing (continued) Technique: Statistical technique: Logit model of tenure choice Probability of being a home-owner, given income and all other variables Results and interpretation: See table for Ontario and Quebec

Logit model for tenure choice

Housing expenditure among young households in Ontario

OUR HYPOTHETICAL MARKET OF APPLES Price Supply Equilibrium price HOW TO ESTIMATE THE SUPPLY OF OWNER-OCCUPIED HOUSING? Equilibrium quantity Demand Quantity

Supply of housing space To fix idea: Consider new dwelling units (housing spaces) The four-quadrant diagram

The supply of housing space: The four-quadrant model Price = perpetuity of rent Rent $ Demand = Supply Price $ Stock (sq. ft.) Construction depends on price Construction (sq. ft.) Stock adjustment: Flow of space = new construction depreciation (demolition)

Supply of housing space To fix idea: Consider new dwelling units (housing spaces) The four-quadrant diagram NEW UNITS REPRESENT ABOUT 20% OF ALL HOUSING SALES IN A METROPOLITAN REGION; THE REMAINING SALES ARE REPEAT SALES!

Supply of housing space and vendor s search behavior Good news: We can recover information from transacted properties as long as we are willing to make some assumptions

OUR HYPOTHETICAL MARKET OF APPLES Price Supply Equilibrium price Demand Equilibrium quantity Quantity

Supply of housing space and vendor s search behavior (continued) Good news: We can recover information from transacted properties as long as we are willing to make some assumptions Suppose time-on-market and length-of-tenure affect only the reservation price of the vendor Suppose number of concurrent listings in the neighbourhood affects only the offer price of the potential buyer Example: Markham data

Predicted values of transacted properties, MLS records of Markham (1999)

Supply of housing space and vendor s search behavior (continued) Other considerations: Length of search also depends on vendor s equity position Risk aversion Fishing behavior Implications: Regional economic repercussion

Prices fluctuate in a much larger magnitude than ever before

OUR HYPOTHETICAL MARKET OF APPLES Price Supply Equilibrium price THIS DIAGRAM IS A STATIC DEPICTION OF A DYNAMIC MARKET! Demand Equilibrium quantity Quantity

Impact of increasing the standard deviation of housing values by $40,000, 1991 Source: Canada Census Enumeration Area, 1991. Map prepared by the author.

The risk of home-ownership Implications: Largest component of wealth of the typical household Macroeconomic repercussion Tenure choice and housing consumption often tie with demographic events Demographic structures Who is most vulnerable in economic shocks?

A HIDDEN COST IN THE HOUSING MARKET: THE RISK OF HOME-OWNERSHIP