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MIT Center for Real Estate

The Housing recovery is here!

Should you buy a house?

William Wheaton

Department of Economics Center for Real Estate

MIT

January, 2014 IAP

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MIT Center for Real Estate

1). Why there will be a recovery.

- Household Formation unusually low - But construction is also

- Both have to increase

2). What kind of recovery (tenure). - Permanent shift to renting?

- Multi versus Single family construction. 3). Where.

- Boom states (CANFLAZ)? - The keys to appreciation: - supply elasticities,

- LT demand growth

- current prices relative to trend

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MIT Center for Real Estate

The Outlook for Population, jobs and Households: Aging = more HH/pop, fewer Jobs/pop

-0.50 0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 1950 1960 1970 1980 1990 2000 2010 2020

households employment population

Cyclic recovery In HH formation ?

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MIT Center for Real Estate

1a). The recovery in Household Formation.

- 2000-2007 Household formation: 1,285,000 yearly - Then 950,000 in 2008, 750,000 in 2009, 600,000 in

2010.

- In 2011 it recovered to 730 and up to 960,000 in 2012. But dropped back to 850,000 in 2013 (est.) - It has to return to 1,200,000 range plus make up

for lost formation of 2m during the downturn!

1b). Could there be a permanent shift in HH formation (headship rate). What determines formation?

- Rising Rents (-)

- Mediocre Job prospects (-) - Divorce (+), marriage(-)

- Aging (+, headship)

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MIT Center for Real Estate

1c). Some additional sources of housing unit “demand”

- Annual demolitions average between 75,000 and

100,000, but there are “episodes”: urban

redevelopment in the 1960’s, Failed developments today?

- 2nd home demand. The Census identifies homes

that are vacant and for sale or rent, vacant and

uninhabitable, and then homes that are “seasonal, usual residence elsewhere,…”

- This latter category has grown from 8% of the stock in 1970 to 16% of the stock in 2010. Annual average growth is about 200,000.

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MIT Center for Real Estate

Forecast: still excess demand for new units during the next 5 years – even if construction recovers to 1.4m!

1997-2008 6.5 Mil

Sources: Bureau of the Census, Moody’s Economy.com, Torto Wheaton Research.

Housing Starts Less New Households

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MIT Center for Real Estate

In the aggregate Residential Construction must recover: When it does - watch GDP growth

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MIT Center for Real Estate

2a). Will there be a recovery in the ownership rate? - Homeownership driven to unsustainable levels by

easy credit – 69-70%. Underwriting or rates?

- Foreclosures have dropped ownership to 65.3%. - Base case: economic recovery prevents further

foreclosures due to job losses. Price recovery

encourages under water owners to hang in there.

- Ownership still desired, result: ownership stabilizes at 65%

2b). Downside: strategic defaults – walking.

- Recent evidence of widespread underwater loans

- Great resistance by Banks to principal reductions - Massive walking defaults? Ownership drops to

62-63% (later)

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MIT Center for Real Estate

Scenarios for unwinding Home Ownership

(+): Economic Recovery, mortgage modification

(-) : Strategic Defaults 62 63 64 65 66 67 68 69 70 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 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 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

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MIT Center for Real Estate 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 198 6 199 0 199 4 199 8 200 2 200 6 200 7. 3 200 8. 3 200 9. 3 201 0. 3 201 1. 3 201 2. 3

Delinquency Rate Transition to foreclosure

Source: Mortgage Bankers Association

Mortgage Delinquency dropping: transition to foreclosure is also (All Loans)

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MIT Center for Real Estate

A once-in-a-lifetime opportunity! Why isn’t everyone

buying? Credit rationing must be back

3.0 4.5 6.0 7.5 9.0 10.5 12.0 13.5 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 19 86 19 87 19 88 19 89 19 90 19 91 19 92 19 93 19 94 19 95 19 96 19 97 19 98 19 99 20 00 20 01 20 02 20 03 20 04 20 05 20 06 20 07 20 08 20 09 20 10 20 11 20 12 20 13

P/R and i*P/R Ratios, 2013q2=1 30-year fixed mortgage rate, %

P/R ratio

i*P/R ratio

Mortgage rate

Sources: BLS, FHFA, CBRE EA.

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MIT Center for Real Estate Base Case: Ownership: 65% HH formation 1.2m Owners: 800k yearly Renters: 400k

HH formation - Job growth

DHH GEM P 1980 1985 1990 1995 2000 2005 2010 2015 2020 0 500 1000 1500 2000 2500 3000 3500 -0.06 -0.04 -0.02 0.00 0.02 0.04 0.06 Renter - Owner HH HO DRHH DOHH 1980 1985 1990 1995 2000 2005 2010 2015 2020 63 64 65 66 67 68 69 -500 0 500 1000 1500 2000

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MIT Center for Real Estate

Multi Single-Family Linkages: Supply

• Virtually all new Single Family housing is built for ownership.

• Between 70% and 90% of multifamily construction is for built rental occupancy.

•Historically single family construction exceeds owner household growth.

•Historically multi-family construction is less than renter household growth.

•All of this is possible because of steady flow unit conversions.

•The main type of unit converted is older single family.

•“Filtering” single family units constitute an enormous source of net rental supply. A “buffer” for changes in ownership .

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MIT Center for Real Estate Renters MF construction DRHH MCMP 1980 1985 1990 1995 2000 2005 2010 2015 2020 - 400 - 200 0 200 400 600 800 1000 1200 1400 Owners - SF construction DOHH S CM 1980 1985 1990 1995 2000 2005 2010 2015 2020 - 500 0 500 1000 1500 2000 Base Case: SF construction 1.1m MF construction .3m Gaps: conversions And demolitions }? }?

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MIT Center for Real Estate

Conversions responsible for most of ∆ rental

Stock (Investors: 1998-2005 vs. 2006-2011)

-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 19 98 19 99 20 00 20 01 20 02 20 03 20 04 20 05 20 06 20 07 20 08 20 09 20 10 20 11

new completions demolitions conversions total Year-over-year change in rental stock, mil units

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MIT Center for Real Estate

Supply keeps prices moving with rents (their “fundamental”) – except for 2001-2006. Back

moving together in the last 3-4 years

(rents leading prices up, but not for long…)e

?

80 90 100 110 120 130 140 150 160 170

Home Price Rent

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MIT Center for Real Estate

Sales Duration (inventory/sales) recovers: Prices set to rise significantly

4 6 8 10 12 14 16 18 J an -06 M a r-0 6 M ay -06 J u l-0 6 S e p-06 N ov -06 J an -07 M a r-0 7 M ay -07 J u l-0 7 S e p-07 N ov -07 J an -08 M a r-0 8 M ay -08 J u l-0 8 S e p-08 N ov -08 J an -09 M a r-0 9 M ay -09 J u l-0 9 S e p-09 N ov -09 J an -10 M a r-1 0 M ay -10 J u l-1 0 S e p-10 N ov -10 J an -11 M a r-1 1 M ay -11 J u l-1 1 S e p-11 N ov -11 J an -12 M a r-1 2 M ay -12 J u l-1 2 S e p-12 N ov -12

Existing Single-Family Existing Condominiums Sale Duration, Months

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MIT Center for Real Estate Base Price Recovery: homeownership stabilizes at 65%

Real Prices - Real Rents

RHPI RRNT 1980 1985 1990 1995 2000 2005 2010 2015 2020 250 275 300 325 350 375 400 425 220 230 240 250 260 270 280

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MIT Center for Real Estate

CANFLAZ homeownership rose/fell 2x US!

60 61 62 63 64 65 66 67 68 69 70 19 91 19 92 19 93 19 94 19 95 19 96 19 97 19 98 19 99 20 00 20 01 20 02 20 03 20 04 20 05 20 06 20 07 20 08 20 09 20 10 20 11

US CANVFLAZ (simple average)

Homeownership rate, %

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MIT Center for Real Estate

CANFLAZ purchase of 2nd or Investment (speculative) homes

2x US average (Condos excluded)

Source: Loan Performance, Torto Wheaton Research

0 10 20 30 40 50 Nation San Diego Sacramento Riverside Miami Tampa Phoenix Orlando Las Vegas Fort Myers Atlantic City 1999 2005

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MIT Center for Real Estate

The result: Housing price “bubble” in CANFLAZ: 2x rest of the US 100 125 150 175 200 225 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

CS20 metros CANVFLAZ 7 metros Others 13 metros

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MIT Center for Real Estate

MSA level Forecasts

• For 68 MSA, take FHA price data, quarterly from 1980:1 – 2012:2, deflate into constant $. • For 68 MSA, sum total units constructed,

quarterly, into housing stock.

• Estimate Error Correction Model predicting price given housing stock for each MSA.

• Estimate Vector Error Correction Model jointly predicting both prices and stock for each MSA • Forecast from 2012:3 to 2022:2

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MIT Center for Real Estate

(continued)

• With ECM forecast assume that MSA stock growth will be 20% lower than historic, due to demographic aging and slow recovery in headship rates from great recession.

• Price and Stock forecasts in left graph

• With VECM (right graph) both variables are forecast. Generally stock and price

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MIT Center for Real Estate

Two fundamental forecast questions

• For each MSA, if you purchased in 2012:3 how much appreciation are you likely to experience over the next decade? What will be the “user

cost” of owning a house: (1-ty) i - ∆p/p

• For each MSA if you purchased a house near the peak (i.e. 2007) when or will you recover your equity. When will nominal prices return to their 2007 value?

• Forecasts done in real prices. 2007-2012 CPI inflation 9%, assume 2012-2022 is 20%

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MIT Center for Real Estate

Chicago

Chicago

ECM stock-price forecast

STKV RHPIV 1990 2000 2010 2020 2500000 2750000 3000000 3250000 3500000 3750000 4000000 100 120 140 160 180 200 220 240 Chic ago

VECM stock-price forecast

STK RHPI 1990 2000 2010 2020 2500000 2750000 3000000 3250000 3500000 3750000 4000000 4250000 100 125 150 175 200 225 250 275 300 325

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MIT Center for Real Estate

New York

NewYork

ECM stock-price forecast

STKV RHPIV 1990 2000 2010 2020 4000000 4100000 4200000 4300000 4400000 4500000 4600000 4700000 4800000 4900000 50 100 150 200 250 300 350 400 NewYork

VECM stock-price forecast

STK RHPI 1990 2000 2010 2020 4000000 4250000 4500000 4750000 5000000 50 100 150 200 250 300 350 400

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MIT Center for Real Estate

San Francisco

SanFrancisco

ECM stock-price forecast

STKV RHPIV 1990 2000 2010 2020 650000 675000 700000 725000 750000 775000 800000 100 150 200 250 300 350 SanFranc is c o

VECM stock-price forecast

STK RHPI 1990 2000 2010 2020 650000 675000 700000 725000 750000 775000 800000 825000 100 150 200 250 300 350 400

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MIT Center for Real Estate

Dallas

Dallas

ECM stock-price forecast

STKV RHPIV 1990 2000 2010 2020 750000 1000000 1250000 1500000 1750000 2000000 140 150 160 170 180 190 200 210 220 230 Dallas

VECM stock-price forecast

STK RHPI 1990 2000 2010 2020 750000 1000000 1250000 1500000 1750000 2000000 140 150 160 170 180 190 200 210 220 230

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MIT Center for Real Estate

Las Vegas

LasVegas

ECM stock-price forecast

STKV RHPIV 1990 2000 2010 2020 200000 300000 400000 500000 600000 700000 800000 900000 1000000 1100000 100 125 150 175 200 225 250 275 300 Las Vegas

VECM stock-price forecast

STK RHPI 1990 2000 2010 2020 200000 400000 600000 800000 1000000 1200000 100 125 150 175 200 225 250 275 300

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MIT Center for Real Estate

Miami

Miami

ECM stock-price forecast

STKV RHPIV 1990 2000 2010 2020 600000 700000 800000 900000 1000000 1100000 100 150 200 250 300 350 400 Miami

VECM stock-price forecast

STK RHPI 1990 2000 2010 2020 600000 700000 800000 900000 1000000 1100000 1200000 100 150 200 250 300 350 400

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MIT Center for Real Estate

Phoenix

Phoenix

ECM stock-price forecast

STKV RHPIV 1990 2000 2010 2020 600000 800000 1000000 1200000 1400000 1600000 1800000 2000000 2200000 125 150 175 200 225 250 275 300 325 350 Phoenix

VECM stock-price forecast

STK RHPI 1990 2000 2010 2020 600000 800000 1000000 1200000 1400000 1600000 1800000 2000000 2200000 125 150 175 200 225 250 275 300 325 350

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MIT Center for Real Estate

Full Paper:

Error Correction Models of MSA Housing “Supply” Elasticities:

Implications for Price Recovery

Available at:

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MIT Center for Real Estate

Price Appreciation versus Recovery

1). Price appreciation 2012-2022 will be greatest where prices have fallen the most (Atlanta,

Detroit, Vegas, Miami Phoenix) and/or where there are strong upward trends (NY, Boston, Seattle, Chicago).

2). User Cost in such areas: .7x.05-.06 = -.025 ! 3). In current dollars prices recover in all areas by

2022 but: West Palm, Phoenix, Orlando, Fort Lauderdale, Charlotte, Vegas, Riverside.

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MIT Center for Real Estate

Conclusions

• Housing construction is already beginning to recover but has a lot of ground to make up.

• Going from 800,000 to 1.4m units yearly adds .7% to GDP growth over the next 2-3 years.

• There has not been any permanent “return to renting” and in fact buying a home today looks like a lifetime opportunity. Similar to 1980s. Many areas will

experience cumulative real appreciation of 30% over the next decade, 50% in current dollars.

• Serious Underwater homes (those purchased or

refinanced near the peak) will refloat in most areas by 2022. The exceptions are the severely cyclic “sand

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