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MIT Center for Real Estate Week 1: Introduction ã The space versus asset market: 4 Quadrant math. ã Real Estate Micro Economics: Hedonics, Location, density, government regulations. ã Real Estate Macro Economics: timing behavior (search,
MIT Center for Real Estate Week 1: Introduction • The space versus asset market: 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 Construction as a part of GDP (1990) $, in billions % of GDP $, in billions % of GDP Private Construction 338 6.1 Public Construction 109 2.0 Buildings 301 5.5 Buildings 46 0.8 Residential Buildings 183 3.3 Housing and Development 0.1 Nonresidential Buildings 118 2.1 Industrial 0.0 Industrial 24 0.4 Other 41 0.7 Office 29 0.5 Hotels/Motels 10 0.2 Nonbuilding Construction 63 1.1 Other Commercial 34 0.6 Infrastructure 55 1.0 All Other Nonresidential 21 0.4 All Other 0.1 Nonbuilding Construction 37 0.7 Total New Construction 446 8.1 Public Utilities 31 0.6 All Other 0.1 5,514 100.0 Adapted from DiPasquale and Wheaton (1996) Total GDP 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 8,777 100.0 Total U.S Real Estate 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 0.1 84 3.2 8,777 100.0 6,122 100.0 2,655 100.0 Total: % of All Real Estate Adapted from DiPasquale and Wheaton (1996) 100.0 69.8 30.2 Exhibit 2-3: The DiPasquale-Wheaton 4-Quadrant Diagram… Rent $ D Space Market: Rent Determination Asset Market: Valuation R* D Price $ Q* P* C* Asset Market: Construction Space Market: Stock Adjustment Construction (SF) Stock (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 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 quadrant 1) 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] 2) Demand = Stock = S 3) Hence: R = (S/α1E)–1/ β1 MIT Center for Real Estate 2nd and 3rd Quadrants 4) P = R/i i = all inclusive cap rate 5) 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 rent] MIT Center for Real Estate 4th Quadrant 6) Replacement version: E= fixed C= δS [Construction equals depreciation (δ is depreciation rate)] 7) Steady Demand growth version: ∆E/E = δ Hence: C= δS [what if S grows less or more than E?] MIT Center for Real Estate U.S Single-Family Market Completions Rate vs Home Price Appreciation 1980-81 1990-91 2001-02 7% 6% 5% 4% 3% 2% 1% 0% -1% -2% -3% -4% Completions Rate Employment Growth Home Price Index (2002 $) 2002 2001 2000 1999 1998 1997 1996 1995 1994 1993 1992 1991 1990 1989 1988 1987 1986 1985 1984 1983 1982 1981 1980 1979 1978 1977 1976 -5% MIT Center for Real Estate The Historic Supply of US Office Space Broken Ground Projects Construction as % of Stock 18% 16% 14% 12% 10% 8% 6% 4% 2% 0% -2% 1901 1910 1919 1928 1937 1946 1955 1964 1973 1982 1991 2000 Downtown Suburban Y ear 19 19 19 68 58 48 38 28 18 g 19 19 08 98 88 ( 19 19 18 78 68 58 48 38 28 18 08 98 88 Index of Historic Housing Prices in Amsterdam (Real Guilders) y 18 18 18 18 18 18 18 18 18 17 78 68 58 48 38 28 18 08 98 88 78 68 58 48 38 28 Price Index g 17 17 17 17 17 17 17 17 17 16 16 16 16 16 16 16 16 MIT Center for Real Estate ) 40 35 30 25 20 15 10 50 MIT Center for Real Estate Real Estate Micro-economics: Cities and Land Markets • No two properties are identical [complete product differentiation] • Properties are close if not perfect substitutes for each other – at some price differential • Price differentials are extremely large, and very predictable • Price differentials tend to be stable over time: local neighborhoods not have independent cyclic movements MIT Center for Real Estate House prices reflect both unit characteristics and location attributes MIT Center for Real Estate Repeat-Sale House price indices (CSW) for 15 submarkets within the greater Boston CMSA: 1982-2002 House Price Indexes, Eastern Massachusetts, by City/Town Location 300 Boston Southeast W estern Far North Shore 495 North 95 South 95 North W estern Lowell Area 495 W est North Shore South Shore W orcester Area Cambridge Area North Central 200 150 100 50 Year 2002 2001 2000 1999 1998 1997 1996 1995 1994 1993 1992 1991 1990 1989 1988 1987 1986 1985 1984 1983 1982 Price Index (1990=100) 250 MIT Center for Real Estate Home Prices within South California Median Home Price, Thousands ($ 2002.4) $400 $350 $300 $250 $200 $150 $100 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 Los Angeles Orange County Sources: OFHEO, Torto Wheaton Research Riverside Ventura San Diego MIT Center for Real Estate Office Rents Move together Cyclically but not always secularly TW Rent Index, 2003$ per sqft 40 Forecast 35 30 25 20 Los Angeles Orange County Ventura County Riverside 2005 2003 2002 2001 2000 1998 1997 1996 1995 1993 1992 1991 1990 1988 1987 1986 1985 1983 1982 1981 1980 15 San Diego MIT Center for Real Estate Closely Correlated Industrial Rent Rent Movements: few secular differences differences TW Rent Index, 2003$ per sqft 10.00 Forecast 9.00 8.00 7.00 6.00 5.00 Los Angeles Orange County Ventura County Riverside 2005 2004 2002 2001 1999 1998 1996 1995 1993 1992 1990 1989 1987 1986 1984 1983 1981 1980 4.00 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 Suburban Markets Manhattan 2001 2000 1998 1997 1996 1995 1993 1992 1991 1990 1988 1987 1986 1985 1983 1982 1981 1980 20 MIT Center for Real Estate Office Suburban Rents in Detail TW Index, $2002 per sqft 50 45 40 35 30 25 20 15 Northern New Jersey Long Island Stamford 2001 2000 1998 1997 1996 1995 1993 1992 1991 1990 1988 1987 1986 1985 1983 1982 1981 1980 10 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 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 Estate Metropolitan Housing Markets often move independently FIG U R E R epeat S ale H ouse P rice Indices for S elected "new " C ities: 1975-1999 (constant $) 250 230 210 170 150 130 110 90 70 Y ear At lanta D ennver H ouston Los Ange les P hoen ix 19 19 19 19 19 9 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 50 19 House Price 190 MIT Center for Real Estate Metropolitan Housing Markets have some similar movements FIGURE Repeat Sale House Price Indices for Selected "Traditional" Cities: 1975-1999 (constant $) 250 230 210 170 150 130 110 90 70 Boston Chicago New York Sanfrancisco W ashington D.C 19 19 Year 19 9 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 50 19 House Price 190 ... Warehouse 223 2.5 8,777 100.0 Total U.S Real Estate Adapted from DiPasquale and Wheaton (1996) MIT Center for Real Estate U.S Real Estate Ownership, 1990 All Real Estate Residential Only Nonresidential... cyclic movements MIT Center for Real Estate House prices reflect both unit characteristics and location attributes MIT Center for Real Estate Repeat-Sale House price indices (CSW) for 15 submarkets... 3.00% 1975 6.00 1973 4.00% 1971 5.00% Forecast 6.50 MIT Center for Real Estate National Multi-Housing Forecast Permits vs Real Rent 6.00% $ Per Sqft 750.00 Forecast 5.00% 700.00 4.00% 3.00% 650.00