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    • MIT OpenCourseWarehttp://ocw.mit.edu11.433J / 15.021J Real Estate EconomicsFall 2008For 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 Value of New Construction Put in Place, 2002 $ (in Billions) % of GDP Private Construction 650 6.1 Buildings Residential buildings 422 4.0 Nonresidential buildings 167 1.6 Industrial 17 0.2 Office 38 0.4 Hotels/Motels 10 0.1 Other commercial 56 0.5 All other nonresidential 46 0.4 Nonbuilding construction Public utilities 54 0.5 All other 7 0.1 Public Construction 210 2.0 Buildings 102 1.0 Housing and development 6 0.1 Industrial 2 0.0 Other 94 0.9 Nonbuilding construction 108 1.0 Infrastructure 97 0.9 All other 11 0.1 Total new construction 861 8.1 Total GDP: 10,624 100.0 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 EstateThe Value of US Real Estate Assets (1990) $, in billions % of TotalResidential 6,122 69.8Single Family Homes 5,419 61.7Multifamily 552 6.3Condominiums/Coops 96 1.1Mobile Homes 55 0.6Nonresidential 2,655 30.2Retail 1,115 12.7Office 1,009 11.5Manufacturing 308 3.5Warehouse 223 2.5Total U.S. Real Estate 8,777 100.0 Adapted from DiPasquale and Wheaton (1996)
    • MIT Center for Real Estate U.S. Real Estate Ownership, 1990 All 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 30.2Adapted from DiPasquale and Wheaton (1996)
    • Exhibit 2-3: The DiPasquale-Wheaton 4-Quadrant Diagram… D Rent $ Space Market: Asset Market: Rent Determination Valuation R* D Price $ P* Q* Stock (SF) C*Asset Market:Construction Space Market: Stock Adjustment Construction (SF)
    • 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 employment R = rent per square foot β1 = rental elasticity of demand, %change in sqft per worker/% change in rent] α1 = sqft / E when R=$12). 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 losses ΔS/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 ?]
    • Effect of Demand Growth in Space Market: More MIT Center for Real Estate Jobs Asset Market: Rent $ Space Market: Valuation Rent Determination D0 D1 R*Price $ P* Q* Stock (SF) C*Asset Market:Construction Space Market: Stock Adjustment Construction (SF)
    • Effect of Demand Growth in Space Market: First phase… MIT Center for Real Estate Rent $ Space Market: Asset Market: Rent Determination Valuation D0 D1 Doesn’t form a rectangle. R* Excess (negative) vacancy…Price $ P* Q* Stock (SF) C*Asset Market:Construction Space Market: Stock Adjustment Construction (SF)
    • Effect of Demand Growth in Space Market: 2nd phase… MIT Center for Real Estate Asset Market: Rent $ Space Market: Valuation Rent Determination D0 D1 R1 Rents spike and get rid of excess (negative) vacancy R*Price $ P1 P* Q* Stock (SF) Can this be a long- run equilibrium result?… C*Asset Market: Doesn’t form aConstruction rectangle. Space Market: Stock Adjustment Construction (SF)
    • Effect of Demand Growth in Space Market: LR Equilibrium… MIT Center for Real Estate Asset Market: Rent $ Space Market: Valuation Rent Determination D0 D1 R1 R** R* P**Price $ P1 P* Q* Q** Stock (SF) In long run equilibrium new supply tempers C* initial rent spikeAsset Market:Construction C** Space Market: Stock Adjustment Construction (SF)
    • Effect of Demand Growth in Asset Market… MIT Center for Real Estate Asset Market: Rent $ Space Market: Valuation Rent Determination D0 11% CAPD1 R*8%CAP R** SR LR P1 Q** P* Q* Price $ P** Stock (SF) C*Asset Market:Construction Space Market: C** Stock Adjustment Construction (SF)
    • MIT Center for Real Estate Using the 4-Quadrant Model toassess 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 EstateCurrent 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 EstateReal 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 EstatePrefect Historic correlation between economic recessions and Housing Production – except for the last 5 years 5 3.2 Year-over-year change in total 4 2.8 employment, millions Total housing starts, 3 2.4 millions of units 2 2.0 1 1.6 0 1.2 -1 0.8 -2 0.4 -3 0.0 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 New Jobs (L) Total Housing Starts (R) Sources: BLS, BOC, TWR.
    • MIT Center for Real EstatePrefect Historic correlation between economic recessions and Housing Prices – except for the last 5 years Housing and U.S. Job Growth 6% 12% 5% 10% 4% 8% real median home prices 6% 3% 4%job growth 2% 2% 1% 0% 0% -2% -1% -4% based on 4-qtr -2% moving averages -6% -3% -8% 1 20 Q3 20 Q1 20 Q3 19 Q1 19 Q3 19 Q1 20 Q3 20 Q1 19 Q3 19 Q1 19 Q3 19 Q1 19 Q3 19 Q1 19 Q3 19 Q3 19 Q3 19 Q1 19 Q1 19 Q3 19 Q3 19 Q3 19 Q1 19 Q1 19 Q1 Q 04 05 07 95 96 98 99 01 02 87 89 90 92 93 80 81 83 84 86 69 71 72 74 75 77 78 19 Job Grow th Real Median Home Price Grow th (lagged)
    • MIT Center for Real EstateWith offices, building booms follow rents. The booms then generate falling rents = endogenous cycle? Office construction and rent growth (TWR sum of markets) 140 15 Forecast 120 Completions - 10 Historical average 100 5 80 60 0 40 -5 20 0 -10 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 Completions in msf (L) TWR rent inflation in % (R) Figure by MIT OpenCourseWare.
    • MIT Center for Real Estate National Office Market Completions Rate vs. Real Rent $ Per Sqft Forecast 34.00 8.00% 32.00 6.00% 30.00 28.00 4.00% 26.00 2.00% 24.00 0.00% 22.00 -2.00% 20.00 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 Total Employment Growth (L) Real Rent (R) Completion Rate (L)
    • MIT Center for Real Estate Historically: Rents over the “cycle”mean revert around Development costs PPI: Construction TWR Rent Index 200 31 190 29 180 27 170 25 160 150 23 140 21 130 19 120 110 17 100 15 20 1 20 1 1 19 1 19 1 20 1 20 1 20 1 20 1 20 1 20 1 20 1 19 1 19 1 19 1 19 1 19 1 19 1 19 1 19 1 19 1 Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q 06 07 08 99 03 04 05 00 01 02 91 92 93 94 95 96 97 98 88 89 90 19 PPI: Construction Materials and Components TWR Rent Index Source: BLS, TWR Office Outlook XL, Summer 2008
    • MIT Center for Real Estate Over the long run there also are: little cycles and Big cycles Broken Ground Projects Construction as % of Stock18%16%14%12%10%8%6%4%2%0%-2% 1901 1910 1919 1928 1937 1946 1955 1964 1973 1982 1991 2000 Downtown Suburban
    • Price Index 16 0 50 100 150 200 250 300 350 400 28 16 38 16 48 16 58 16 68 16 78 16 88 16 98 17 08 17 18 17 28 17 38 g 17 48 17 58 17 MIT Center for Real Estate 68 y 17 78 17 88 17 98 18 08Y ear 18 18 18 28 18 38 18 48 18 58 18 68 ( 18 78 18 88 18 98 19 g 08 19 18 19 Amsterdam (Real Guilders) 28 ) 19 38 19 48 19 58 Index of Historic Housing Prices in 19 68
    • MIT Center for Real Estate CPI Apartment Rent Indices for Selected "traditional" Cities: 1918-1999 (constant $) 400 350 300Apartment Rent 250 200 150 100 50 0 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 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 riskPrice Index 1899 = 1.0constant dollars/square ft. 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0 1899 1909 1919 1929 1939 1949 1959 1969 1979 1989 1999 Source: MIT 2002 Thesis
    • 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 In(sale) 8.52 5.71 In(sqrt) 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 $) House Price Indexes, Eastern M assachusetts, by City/Tow n Location 300 250 Boston Southeast W estern 1 200 Far North ShorePrice Index (1990=100) 495 North 95 South 95 N orth 150 W estern 2 Lowell Area 495 W est North Shore 100 South Shore W orcester Area Cam bridge Area North Central 50 0 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 Year
    • MIT Center for Real Estate Home Prices within South California Median Home Price, Thousands ($ 2002.4)$400$350$300$250$200$150$100 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 Los Angeles Orange County Riverside Ventura San Diego Sources: OFHEO, Torto Wheaton Research
    • MIT Center for Real Estate Office Rents Move together Cyclically but not always secularly TW Rent Index, 2003$ per sqft40 Forecast3530252015 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
    • MIT Center for Real Estate Closely Correlated Industrial Rent Movements: few secular differences TW Rent Index, 2003$ per sqft10.00 Forecast 9.00 8.00 7.00 6.00 5.00 4.00 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
    • MIT Center for Real Estate Manhattan Office Rents vs. NJ and Conn. Suburbs TW Index, $2002 per sqft 65 60 55 50 45 40 35 30 25 20 1980 1981 1982 1983 1985 1986 1987 1988 1990 1991 1992 1993 1995 1996 1997 1998 2000 2001 Suburban Markets Manhattan
    • MIT Center for Real Estate Office Suburban Rents in Detail TW Index, $2002 per sqft504540353025201510 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
    • 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 Markets – there can be huge differences in both long term growth and cyclic risk 1 9 8 0 = 1 0 0 (C o n s ta n t $ 2 0 0 5 ) 350 300 B o s to n 250 Los A n g e le s 200 Ch ic a g o 150 Na tio n 100 Da lla s 50 0 1980 1985 1990 1995 2000 2005
    • 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 $) 250 230 210 190 170House Price 150 130 110 90 70 50 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 Year Atlanta Dennver Houston Los Angeles Phoenix
    • MIT Center for Real EstateAlthough sometimes they are subject to a common economy wide Shock FIGURE 4. Repeat Sale House Price Indices for Selected "Traditional" Cities: 1975-1999 (constant $) 250 230 210 190 170 House Price 150 130 110 90 70 50 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 Year Boston Chicago New York Sanfrancisco Washington D.C.