Upload
nguyentruc
View
219
Download
0
Embed Size (px)
Citation preview
MIT OpenCourseWare http://ocw.mit.edu
11.433J / 15.021J Real Estate EconomicsFall 2008
For information about citing these materials or our Terms of Use, visit: http://ocw.mit.edu/terms.
MIT Center for Real Estate
Week 1: Introduction• The space versus asset market: 4 Quadrant
math.• Real Estate Micro Economics: Hedonics,
Location, density, government regulations.• Real Estate Macro Economics: timing
behavior (search, moving, contracts), cycles, regional growth.
MIT Center for Real Estate
The Role of Real Estate in the Economy
• Construction [6% of GDP]• Service flow, “Shelter”, rent plus imputed
rent [20% + of GDP]• Assets [55-60% of total national wealth]• Land? Not part of GDP (we don’t make
land), but it is part of wealth.• Accounting, measurement difficulties [book
versus market value]
MIT Center for Real Estate
$ (in Billions) % of GDP
Private Construction 650
Public Construction 210 2.0
Total new construction 861
Total GDP: 10,624
Buildings
Buildings
IndustrialHousing and development
Other
Nonbuilding constructionPublic utilitiesAll other
547
Nonbuilding constructionInfrastructureAll other
102
26
94108
9711
Residential buildingsNonresidential buildings
422167
IndustrialOfficeHotels/MotelsOther commercialAll other nonresidential
1738105646
6.1
8.1
100.0
0.50.1
1.0
0.00.1
0.91.00.90.1
4.01.60.20.40.10.50.4
Value of New Construction Put in Place, 2002
Source: Current Construction Reports, Series C30, U.S. Census Bureau. Gross Domestic Product from Economic Report of the President, 2004
Figure by MIT OpenCourseWare.
MIT Center for Real Estate
The Value of US Real Estate Assets (1990)
$, in billions % of Total
Residential 6,122 69.8
Single Family Homes 5,419 61.7
Multifamily 552 6.3
Condominiums/Coops 96 1.1
Mobile Homes 55 0.6
Nonresidential 2,655 30.2
Retail 1,115 12.7
Office 1,009 11.5
Manufacturing 308 3.5
Warehouse 223 2.5
Total U.S. Real Estate 8,777 100.0
Adapted from DiPasquale and Wheaton (1996)
MIT Center for Real EstateU.S. Real Estate
Ownership, 1990All Real Estate Residential Only Nonresidential Only
$, in billions % $, in billions % $, in billions %
Individuals 5,088 58.0 5,071 82.8 17 0.6
Corporations 1,699 19.4 66 1.1 1,633 61.5
Partnerships 1,011 11.5 673 11.0 338 12.7
Nonprofits 411 4.7 104 1.7 307 11.6
Government 234 2.6 173 2.8 61 2.3
Institutional Investors 128 1.5 14 0.2 114 4.3
Financial Institutions 114 1.3 13 0.2 101 3.8
Other (Including Foreign 92 1.0 8 0.1 84 3.2
Total: 8,777 100.0 6,122 100.0 2,655 100.0
% of All Real Estate 100.0 69.8 30.2
Adapted from DiPasquale and Wheaton (1996)
Exhibit 2-3: The DiPasquale-Wheaton 4-Quadrant Diagram…
Rent $
Stock (SF)Price $
Construction (SF)
Space Market:Stock Adjustment
Asset Market:Construction
Space Market:Rent Determination
Asset Market:Valuation
Q*
R*
P*
C*
D
D
MIT Center for Real Estate
Systems of Economic Equations• Parameters: Constants that reflect underlying
behavior, α, β, δ.• Endogenous variables: values that the model
“determines: C, S, R, P.• Exogenous variables: values that determine the
model’s variables, but which the models variables in turn do not influence: i, E.
• Equilibrium: Solution to the endogenous variables given exogenous values and parameters.
• Comparative Statics: How changes in exogenous variables change equilibrium endogenous ones.
MIT Center for Real Estate
1st quadrant1). Office Demand = α1ER-β1
E= office employmentR = rent per square footβ1 = rental elasticity of demand, %change
in sqft per worker/% change in rent]α1 = sqft / E when R=$1
2). Demand = Stock = S3). Hence: R = (S/α1E)–1/ β1 {downward sloping schedule}
MIT Center for Real Estate
2nd and 3rd Quadrants4). P = R/i
i = all inclusive cap rate5). Office Construction rate:
C/S = α2Pβ2
P = Asset Price per square foot[“Q” theory?]β2 = Price elasticity of supply:[% change in construction rate/% change in price]
MIT Center for Real Estate
4th Quadrant6). Replacement version (graph):
E= fixed, δS = building lossesΔS/S = C/S - δ [Construction rate – loss
rate equals net additions = 0 in equilibrium]7). Steady Demand growth version:
ΔE/E = δ, no losses Hence: ΔS/S - ΔE/E = C/S - δ[what happens to S/E if C/S >< δ ?]
MIT Center for Real EstateRent $
Stock (SF)Price $
Construction (SF)
Space Market:Stock Adjustment
Asset Market:Construction
Space Market:Rent Determination
Asset Market:Valuation
Q*
R*
P*
C*
D0D1
Effect of Effect of Demand GrowthDemand Growth in Space Market: More in Space Market: More JobsJobs
MIT Center for Real EstateRent $
Stock (SF)Price $
Construction (SF)
Space Market:Stock Adjustment
Asset Market:Construction
Space Market:Rent DeterminationAsset Market:
Valuation
Q*
R*
P*
C*
D0D1
Effect of Demand Growth in Space Market:Effect of Demand Growth in Space Market:
First phaseFirst phase……
Excess (negative) vacancy…
Doesn’t form a rectangle.
MIT Center for Real EstateRent $
Stock (SF)Price $
Construction (SF)
Space Market:Stock Adjustment
Asset Market:Construction
Space Market:Rent Determination
Asset Market:Valuation
Q*
R*
P*
C*
D0D1
R1
P1
Effect of Demand Growth in Space Market: Effect of Demand Growth in Space Market:
2nd phase2nd phase……
Can this be a long-run equilibrium result?…
Doesn’t form a rectangle.
Rents spike and get rid of excess (negative) vacancy
MIT Center for Real EstateRent $
Stock (SF)Price $
Construction (SF)
Space Market:Stock Adjustment
Asset Market:Construction
Space Market:Rent Determination
Asset Market:Valuation
Q*
R*
P*
C*
D0D1
R1
P1
Effect of Demand Growth in Space Market: Effect of Demand Growth in Space Market: LR EquilibriumLR Equilibrium……
R**
P**
C**
Q**
In long run equilibrium new supply tempers initial rent spike
MIT Center for Real EstateRent $
Stock (SF)Price $
Construction (SF)
Space Market:Stock Adjustment
Asset Market:Construction
Space Market:Rent Determination
Asset Market:Valuation
Q*
R*
P*
C*
11% CAP
8%CAP
D0
D1
P1
P**
R**
Q**
C**
SR
LR
Effect of Demand Growth in Effect of Demand Growth in AssetAsset MarketMarket……
MIT Center for Real Estate
Using the 4-Quadrant Model to assess the impact of other changes.
• What happens if Construction costs rise or the supply schedule shifts?
• Suppose depreciation speeds up (functional obsolescence dictates shorter life spans of buildings)?
• How to interpret owner occupied space (e.g. Single Family Housing)?
• EXERCISE #1.
MIT Center for Real Estate
Current Issues: using the diagram• Zero (or negative) population and labor force
growth in: Japan, Germany, Italy, Spain…? • Increasing use of the Internet for retail
shopping? • Expanded availability of (subprime) mortgage
credit to households previously ineligible? • Continued global saving glut from growth in
Asia – where savings rates are 20%+
MIT Center for Real Estate
Real Estate Macro-economics: Real Estate Cycles and Secular Trends• What are real estate cycles? Truly independent
oscillations or just reactions to the economy.• Cycles vary with Property type. • Cycles are related to broader capital markets. • Secular trend: growth rates of the stock
(construction) slow as economy matures. • Secular trend: Prices adjusted for inflation rise
over time?
MIT Center for Real Estate
Sources: BLS, BOC, TWR.
-3
-2
-1
0
1
2
3
4
5
1960
1962
1964
1966
1968
1970
1972
1974
1976
1978
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
Year
-ove
r-ye
ar c
hang
e in
tota
l em
ploy
men
t, m
illio
ns
0.0
0.4
0.8
1.2
1.6
2.0
2.4
2.8
3.2
Tota
l hou
sing
sta
rts,
mill
ions
of u
nits
New Jobs (L) Total Housing Starts (R)
Prefect Historic correlation between economic recessions and Housing Production – except for the last 5 years
MIT Center for Real Estate
Housing and U.S. Job Growth
-3%
-2%
-1%
0%
1%
2%
3%
4%
5%
6%
1969
Q319
71Q1
1972
Q319
74Q1
1975
Q319
77Q1
1978
Q319
80Q1
1981
Q319
83Q1
1984
Q319
86Q1
1987
Q319
89Q1
1990
Q319
92Q1
1993
Q319
95Q1
1996
Q319
98Q1
1999
Q320
01Q1
2002
Q320
04Q1
2005
Q320
07Q1
job
grow
th
-8%
-6%
-4%
-2%
0%
2%
4%
6%
8%
10%
12%
real
med
ian
hom
e pr
ices
Job Grow th Real Median Home Price Grow th (lagged)
based on 4-qtr moving averages
Prefect Historic correlation between economic recessions and Housing Prices – except for the last 5 years
MIT Center for Real Estate
With offices, building booms follow rents. The booms then generate falling rents = endogenous cycle?
140
120
100
80
60
40
20
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
0
15
10
5
0
-5
-10
Office construction and rent growth (TWR sum of markets)
Completions - Historical average
Forecast
Completions in msf (L) TWR rent inflation in % (R)
Figure by MIT OpenCourseWare.
MIT Center for Real Estate
-2.00%
0.00%
2.00%
4.00%
6.00%
8.00%
1971
1973
1975
1977
1979
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
2001
2003
2005
2007
20.00
22.00
24.00
26.00
28.00
30.00
32.00
34.00
Total Employment Growth (L) Real Rent (R) Completion Rate (L)
$ Per Sqft
National Office MarketCompletions Rate vs. Real Rent
Forecast
MIT Center for Real Estate
Historically: Rents over the “cycle”mean revert around Development costs
100
110
120
130
140
150
160
170
180
190
200
1988
Q119
89Q1
1990
Q119
91Q1
1992
Q119
93Q1
1994
Q119
95Q1
1996
Q119
97Q1
1998
Q119
99Q1
2000
Q120
01Q1
2002
Q120
03Q1
2004
Q120
05Q1
2006
Q120
07Q1
2008
Q1
15
17
19
21
23
25
27
29
31
PPI: Construction Materials and Components TWR Rent Index
PPI: Construction TWR Rent Index
Source: BLS, TWR Office Outlook XL, Summer 2008
MIT Center for Real Estate
-2%0%2%4%6%8%
10%12%14%16%18%
1901 1910 1919 1928 1937 1946 1955 1964 1973 1982 1991 2000
Downtown Suburban
Construction as % of Stock
Over the long run there also are:little cycles and Big cycles Broken
Ground Projects
MIT Center for Real Estate
Index of Historic Housing Prices in Amsterdam (Real Guilders)
g y ( g )
0
50
100
150
200
250
300
350
400
16281638164816581668167816881698170817181728173817481758176817781788179818081818182818381848185818681878188818981908191819281938194819581968
Year
Pric
e In
dex
MIT Center for Real Estate
CPI Apartment Rent Indices for Selected "traditional" Cities: 1918-1999 (constant $)
0
50
100
150
200
250
300
350
400
1918
1921
1924
1927
1930
1933
1936
1939
1942
1945
1948
1951
1954
1957
1960
1963
1966
1969
1972
1975
1978
1981
1984
1987
1990
1993
1996
Year
Apa
rtm
ent R
ent
NEW YORK BOSTON CHICAGO WASHINGTON D. C. SANFRANCISCO
MIT Center for Real Estate
Long run Appreciation? Just inflation (3.5%) for 100 years in NYC, but lots of decade risk
Price Index 1899 = 1.0 constant dollars/square ft.
Source: MIT 2002 Thesis
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1899 1909 1919 1929 1939 1949 1959 1969 1979 1989 1999
MIT Center for Real Estate
Real Estate Micro-economics: Cities and Land Markets
• No two properties are identical [complete product differentiation]
• Properties are close if not perfect substitutes for each other – at some price differential.
• Price differentials are extremely large, and very predictable.
• Price differentials tend to be stable over time: local neighborhoods do not have independent cyclic movements.
MIT Center for Real EstateHouse prices reflect both unit characteristics and
location attributes
17.19
8.525.71 In(sqrt)
In(s
ale)
9.34
Sale amount against square feet, Phoenix
Figure by MIT OpenCourseWare.
MIT Center for Real Estate
Repeat-Sale House price indices (CSW) for 15 submarkets within the greater Boston CMSA: 1982-2002 (current $)
House Price Indexes, Eastern Massachusetts, by City/Town Location
0
50
100
150
200
250
300
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
Year
Pric
e In
dex
(199
0=10
0)
BostonSoutheastW estern 1Far North Shore495 North95 South95 NorthW estern 2Lowell Area495 W estNorth ShoreSouth ShoreW orcester AreaCam bridge AreaNorth Central
MIT Center for Real Estate
Median Home Price, Thousands ($ 2002.4)
Sources: OFHEO, Torto Wheaton Research
Home Prices within South California
$100
$150
$200
$250
$300
$350
$400
77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02
Los Angeles Orange County Riverside Ventura San Diego
MIT Center for Real Estate
Office Rents Move together Cyclically but not Office Rents Move together Cyclically but not
Forecast
15
20
25
30
35
40
1980
1981
1982
1983
1985
1986
1987
1988
1990
1991
1992
1993
1995
1996
1997
1998
2000
2001
2002
2003
2005
Los Angeles Orange County Ventura County Riverside San Diego
TW Rent Index, 2003$ per sqft
always secularlyalways secularly
MIT Center for Real Estate
Closely Correlated Industrial Rent
Forecast
4.00
5.00
6.00
7.00
8.00
9.00
10.00
1980
1981
1983
1984
1986
1987
1989
1990
1992
1993
1995
1996
1998
1999
2001
2002
2004
2005
Los Angeles Orange County Ventura County Riverside San Diego
Movements: few secular differencesMovements: few secular differencesTW Rent Index, 2003$ per sqft
MIT Center for Real Estate
20
25
30
35
40
45
50
55
60
65
1980
1981
1982
1983
1985
1986
1987
1988
1990
1991
1992
1993
1995
1996
1997
1998
2000
2001
Suburban Markets Manhattan
Manhattan Office Rents vs. NJ and Conn. Suburbs
TW Index, $2002 per sqft
MIT Center for Real Estate
10
15
20
25
30
35
40
45
50
1980
1981
1982
1983
1985
1986
1987
1988
1990
1991
1992
1993
1995
1996
1997
1998
2000
2001
Northern New Jersey Long Island Stamford Westchester
Office Suburban Rents in DetailTW Index, $2002 per sqft
MIT Center for Real Estate
Prices and Development• Prices bring forth development: of any urban land
use..• Development occurs so as to maximize the
residual value between: Price-capital costs (construction).
• This residual is “land value”. Development maximizes land value.
• Land Development is a natural real option: incur heavy capital costs to realize an income stream –or- wait (to do the same later) ?
MIT Center for Real Estate
What is a real Estate Market?• Within “markets” all properties should
move together: high substitutability, easy mobility.
• Between markets there exists frictions, transportation costs, immobility of resources and low substitutability.
• MSA as “market”? CMSA?
MIT Center for Real EstateBetween MarketsBetween Markets –– there can be huge differences in there can be huge differences in
both long term growth and cyclic riskboth long term growth and cyclic risk
0
5 0
1 0 0
1 5 0
2 0 0
2 5 0
3 0 0
3 5 0
1 9 8 0 1 9 8 5 1 9 9 0 1 9 9 5 2 0 0 0 2 0 0 5
B o s ton
L osA n ge lesCh ic a go
Na tio n
Da lla s
1 9 8 0 = 1 0 0 (C o n s ta n t $ 2 0 0 5 )
MIT Center for Real Estate
Metropolitan Housing Markets can even move independently
FIGURE 5. Repeat Sale House Price Indices for Selected "new" Cities: 1975-1999 (constant $)
50
70
90
110
130
150
170
190
210
230
250
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
Year
Hou
se P
rice
Atlanta Dennver Houston Los Angeles Phoenix
MIT Center for Real Estate
Although sometimes they are subject to a common economy wide Shock
50
70
90
110
130
150
170
190
210
230
250
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
Year
Hou
se P
rice
Boston Chicago New York Sanfrancisco Washington D.C.
FIGURE 4. Repeat Sale House Price Indices for Selected "Traditional" Cities: 1975-1999 (constant $)