Urban Housing Markets

1. Urban Housing Markets Prof. Clark Week #12

2. Urban Housing Markets • Brief summary • Spatial patterns in the housing market • Recall insights of SUM regarding K-Land ratio as you move away from place of employment • Look at some of the characteristics associated with the housing good

3. Characteristics of the Housing Good • Uniqueness • Features, locational fixity. • There are neighborhood effects • Positive and negative externalities • Long-lived • Stock of housing generates a flow of services. • Housing deteriorates over time without maintenance. • Consumption and investment good • Has been seen as a hedge against inflation • More later

4. Characteristics - continued • Housing is typically the largest component of the household budgets • Requires financing. • There are tax advantages to owning housing. • Low income typically rent, whereas middle and upper class typically own.

5. Market Structure • Monopoly power on supply side of housing market? • Monopolistic Competition • Why? • Housing market is segmented. • What does this mean?

6. Housing Market Analysis • Use simple supply and demand analysis of market. • The stock of housing generates a flow of services to the consumer. • The stock of housing sells at the asset price, V. • The flow of services sells at the flow price, R. • The two prices are related by the user cost of housing,  R=*V

7. User Cost of Capital Defined • User cost represents costs associated with the holding of housing capital. • Think of this as the costs to the owner of housing. • Costs include the sum of mortgage expenses, maintenance, and property taxes, less any capital gains.

8. User Cost of Housing Capital • Components of  • nominal mortgage rate (i=r+ e) which is deductible at the federal income tax rate (t), property tax rate (p) which is also deductible, maintenance expense rate (m) which increases with age of property, capital gains (g=gr+ e) • [(r+ e)(1-t)+p*(1-t) + m - (gr+e)] • Simplifying: • [(r+p)(1-t)+ m - gr -e*t)

9. Factors that influence  • [(r+p)(1-t)+ m - gr -e*t) • Thus, • higher is r, p, or m, the higher is . • higher is gr, and e, the lower is . • Housing is often seen as a hedge against inflation (i.e., the user cost of housing falls with increases in e). • For rental housing, the maintenance expenses are also tax deductible: • renter[(r+p)(1-t)+ m(1-t) - gr -e*t]

10. User Cost for Owners & Rentersowner[(r+p)(1-t)+ m - gr -e*t]renter[(r+p)(1-t)+ m(1-t) - gr -e*t] • There are several reasons why we would not expect the same user cost of capital for rental vs. owner occupied housing • m higher for rental units ( renter • rental property riskier, thus higher r ( renter • m is tax deductible for owners of rental property ( rente • Another issue: • There is tax advantage to ownership in that the imputed rent from home ownership is not taxed.

11. Which is higher? owner or renter? • Use estimates of parameters. • If t=0.28, mo=0.02, mr=0.03, ro=0.05, rr=0.06, e=0.03, p=0.02 and gr=0.01 owner[(ro+p)(1-t)+ mo - gr -e*t] owner owner renter[(rr+p)(1-t)+ mr (1-t) - gr -e*t] renter renter

12. If V=$100,000, we can derive Rowner and Rrenter • Rowner=0.052*100000 =$5200 per year • Rrenter=0.0608*100000 =$6080 per year • Thus, on same valued property, renters pay about 17% more per year.

13. Distinguishing Features of Renters and Owners • Low income typically rent. Why? • Down payment constraints. • Value of t typically lower for low income households • High mobility households rent due to the high transactions costs associated with buying. • College students are highly mobile and have low income. Almost universally rent.

14. Housing Demand • Which price (V or R) is correct? • QD=f(R, Ipermanent, demographic char’s) • Problem with Q? • Given multidimensional nature of Q, what is a “unit” of housing? • Must somehow standardize. Techniques: • Isolate a class of housing • Use hedonic housing price technique to create constant quality unit of housing (more later).

15. Empirical Findings on Demand • There are numerous housing demand studies. General findings indicate: • Demand is slightly price inelastic to slightly elastic (usually 0.7 - 1.2) • Primary determinant of price elasticity? • What does SUM suggest income effect would be? • Housing is income inelastic (approx. 0.75) • Income elasticity is lower for renters than owner occupants. • Income elasticity increases with income. • 0.1-0.6 for low income, 0.7-1.1 for high income

16. The Hedonic Approach • Hedonic approach views housing as a bundle of attributes. • As noted earlier, technique can be used to derive measures of constant quality housing. • Derive hedonic price function. • P=f(Structural Chars, Neighborhood Chars, Fiscal) • Derive implicit prices for characteristics as =P/Attribute. • Derive value of constant quality housing as the sum of vector (*attribute).

17. Demand for Attributes • Can actually derive demand functions for attributes using hedonic approach. • Overview: • Estimate implicit prices (=P/Attribute) • Fresno data can be used to derive these • In second stage, run the following regression model: Attribute=f(,Income,Demographic) • Note, there is an interesting identification problem. • Overview of findings:

18. Demand for Attributes: Findings(Follain and Jimenez, 1985) • Demand for living space is income inelastic (elasticity is about 0.5). • Demand for structural quality is income elastic (ie., over 1.6) • Demand for neighborhood amenities is income elastic. • Also, Muth finds demand for standard (as opposed to substandard) housing is income elastic.

19. Supply side of housing market • Little evidence of monopoly power. • Sources of supply include new and used housing. • Housing deteriorates w/o maintenance, and thus quality adjustments may lead to a housing unit passing from one income class to another. • Older housing deteriorates faster.

20. Housing Supply Function • Qs=f(V, Pinput,technology,expectations,govt) • Determinents: • Price is the asset price of housing. • Higher input prices reduce supply. • Technological advancements increase supply. • Expectations concerning future prices influence supply. • (e.g., rent control can dampen supply) • Government regulation influences supply • e.g., zoning, min. square footage requirements, etc.

21. Empirical Supply Functions(Price elasticity<1.0) • Reasons: • New housing is a small fraction of the overall stock of housing. • Thus, it cannot lead to large quantity adjustments (for overall market) when price changes. • Deterioration of used buildings into the next lower quality classification. • Deterioration is slow. • Remodeling to upgrade quality. • Expensive.

22. R-Q space: (Map Supply curve) V-Q space: (Map Demand Curve) Housing Market Equilibrium S R V S Re Ve D D Q Q Qe Qe

23. Rent-Quantity Space What happens when increases?(suppose real interest rates increase) • As user cost increases, • the supply curve is • mapped to higher • values of R for the • same value of Q. • This is because the • suppliers command • higher rents when • their costs increase. S’ R S R’e Re D Q Q’e Qe

24. As user cost goes up, the demand curve is mapped to lower values of V for each Q. This is because as rents increase, housing of a given value is less desirable to consumers, and hence demand falls at each Q. Value-Quantity Space What happens when increases?(suppose real interest rates increase) V S Ve V’e D D’ Q Q’e Qe

25. Role of Demographic Characteristics on Housing Prices Mankiw and Weil published a paper in late 1980’s suggesting strong impact from baby-boom.

26. Mankiw and Weil Briefly • Cross-sectional relationship (1970 Census) between quantity of housing demanded (ie., dollar value) and demographic characteristics of household. • Specifically looked at age distribution of population. • Findings: Demand rises sharply between age of 20-30, and then declines after age 40 (by about 1% per year).

27. What is impact of Baby Boom? • Large cohort moving through population distribution. • Findings suggest predictable influence of baby boom on future values • They simulate impact, assuming housing demand of those in 1970 is stable. • Findings suggest housing markets are not efficient. • What might be the problem with their methodology?

28. Housing Durability and Filtering • We now know something about the demand & supply sides of housing market. • Furthermore, we know housing is durable. • This has several implications • First, as housing deteriorates, costs increase (due to maintenance) and revenues decrease (due to quality). • Second, housing may pass to different income class over time (i.e., filter down) • Examine both phenomena.

29. Suppose an apartment building gets older. Demand falls as quality declines. Thus TR falls. Costs go up as maintenance increases. Thus, TC rises. Quantity falls TR,TC Revenue and Cost Adjustments TC’ TR TR’ TC Q’ Q

30. Eventually, property falls out of this particular submarket. If this is not the lowest quality housing market, housing will filter to other users.

31. Filtering • Filtering: • A change over time in the position of a given dwelling unit within the distribution of housing rents and prices in the community as a whole. • As a dwelling ages, it provides less housing services per year, cet. par. • Materials deteriorate, and technology becomes dated.

32. Look at Filtering Process • Assume all housing rented. • Assume constant population. • Consider 3 housing quality categories, and 3 income groups. • Housing Quality: High, Medium, Low • Income Levels: High, Middle, Low • Assume an initial equilibrium. • Maximizing rents requires matching as follows:

33. Equilibrium Sorting of Households and Housing Housing Quality Low Medium High Low Middle High X X Income Group X

34. Assume Income Growth of Highest Income Group

35. Adjustment in Sorting Housing Quality Low Medium High Higher Low Middle High X X X X Income Group X X Low quality falls out of housing stock

36. Does this lead to permanently higher housing quality for poor? • There is an equilibrium level of maintenance for all income groups. • This will not increase as housing filters down. • Thus, improvement is temporary. • Depends on rate of depreciation. • If depreciation is slow, it can help. • If depreciation is rapid, it cannot. • This is an empirical issue. • Next time, we will look at the article by Weicher.