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Housing and the Economy
Johannes Stroebel, NYU Stern
June 2015
Introduction
• The goal of this class is to get us to think seriously about the
economics of real estate...
• ... and its interaction with the broader macroeconomy.
Housing
Markets
Real
Economy
1
Motivation
• Why should we study real estate?
2
Motivation
• Why should we study real estate?
−
Important Asset
2
Motivation
Gross Domestic Product Components
2005
2008
Total
12,623
14,291
15,075
Consumption
Housing Consumption Expenditure
- Rental of tenant-occupied housing
- Imputed rental of owner-occupied housing
8,804
1,329
265
1,045
9,301
1,530
330
1,179
10,729
1,623
378
1,223
Investment
2,172
2,088
1,855
775
472
339
16.7
14.0
13.0
Market Value in USD Billion
Residential Investment
Total contribution of Housing to GDP (%)
2011
Source. Flow of Funds Data, Table F.5; NIPA Table 2.4.5
3
Motivation
U.S. Household (and nonprofit) Balance Sheets
Market Value in USD Billion
Total Assets
Real Estate
Deposits
Corporate equities
Mutual Fund Shares
Credit Market Instruments
Total Liabilities
Mortgages
2005
2008
2011
73,281
67,613
73,737
24,141
6,232
8,092
3,673
4,223
19,952
8,107
5,765
3,343
4,900
18,297
8,621
8,721
4,645
4,905
12,145
8,895
14,106
10,509
13,477
9,713
Source: Flow of Funds Data, Table B.100
4
Motivation
U.S. NonFinancial Corporate Balance Sheets
Market Value in USD Billion
Total Assets
Real Estate
Equipment and Software
Inventories
Financial Assets
- Trade receivables
Total Liabilities
Mortgages
2005
2008
2011
25,269
28,861
29,948
8,171
3,602
1,588
11,907
2,108
9,946
4,191
1,787
12,937
2,085
8,807
4,314
1,967
14,806
2,332
11,182
786
13,225
880
13,593
663
Source: Flow of Funds Data, Table B.102
5
Motivation
• Why should we study real estate?
−
Important Asset
−
Linked to a key credit market
6
Secondary Mortgage Markets
7
Motivation
• Why should we study real estate?
−
Important Asset
−
Linked to a key credit market
−
Significant aggregate implications
8
Motivation
• The “Great Depression” related to problems in the housing
market.
9
Motivation
• Why should we study real estate?
−
Important Asset
−
Linked to a key credit market
−
Significant aggregate implications
−
Many idiosyncratic features
→ Real Estate is different from stocks and bonds!
10
Motivation
• Real Estate is different from stocks and bonds!
−
Investment and consumption good.
−
Each asset unique - location. Different locations are imperfect
substitutes.
−
Significant information asymmetries.
−
High transaction costs - illiquid.
−
Usually mortgage financed; High leverage.
−
Public Policy Role - risks and opportunities.
11
This Course
• Class 1: Introduction to the ”Macro Dimensions” of Housing
Markets
• Class 2 + 3: Recent research on and using housing markets.
−
Class 3: Prof Theresa Kuchler presentation
12
House Prices - The Macro
Dimension
13
Understanding House Price Movements
• How does one measure house prices?
14
Understanding House Price Movements
• How does one measure house prices?
• House Price Facts: What needs to be understood?
14
Understanding House Price Movements
• How does one measure house prices?
• House Price Facts: What needs to be understood?
• Static equilibrium framework to understand long-run movements
in prices.
−
Evaluate theories of the boom-bust.
−
Analyze role of interest rates (“too low for too long”)
−
Analyze role of supply constraints.
14
Understanding House Price Movements
• How does one measure house prices?
• House Price Facts: What needs to be understood?
• Static equilibrium framework to understand long-run movements
in prices.
−
Evaluate theories of the boom-bust.
−
Analyze role of interest rates (“too low for too long”)
−
Analyze role of supply constraints.
• Extension to take account of role of expectations.
−
Analyze response to government policy (remove MID).
14
House Prices - The Macro Dimension
Measuring House Prices
15
Measuring Changes in House Prices
• Challenge: Houses transact very rarely, and are unique.
16
Measuring Changes in House Prices
• Challenge: Houses transact very rarely, and are unique.
• Heterogeneity of housing stock: Houses differ (and are
unique) in many different dimensions of quality, such as location,
size, condition.
• Come up with concept of “house prices” when average quality of
(all or transacted) homes changes over time.
16
Measuring Changes in House Prices
• Challenge: Houses transact very rarely, and are unique.
• Heterogeneity of housing stock: Houses differ (and are
unique) in many different dimensions of quality, such as location,
size, condition.
• Come up with concept of “house prices” when average quality of
(all or transacted) homes changes over time.
• Illiquidity of housing asset: How much will a house sell for
today? Since each house is unique, sometimes hard to tell.
16
Measuring Changes in House Prices
• Look at prices indices (similar to Dow Jones Index).
17
Measuring Changes in House Prices
• Look at prices indices (similar to Dow Jones Index).
• There are a few common indices used to measure house prices:
−
S&P Case-Shiller Index
−
OFHEO HPI
−
Zillow Home Value Index
• None are perfect; need to understand what they are!
17
Measuring Changes in House Prices
Case Shiller
OFHEO
Zillow
Methodology
Repeat Sale
Repeat Sale
Median Zestimate
Coverage Type
All Transactions observed
(Excludes non-disclosure states)
Purchases and Refinancing
with conforming mortgage
purchased by Fannie or Freddie.
All Properties
Transactions
Home Appraisals
Zestimate
Coverage Geographic
20 Metros + U.S.
384 MSA Indices
All
Range
Since early 1990s
Since 1974
Recently
Data
• Dealing with Heterogeneity: Repeat Sale versus Median
Zestimate.
18
Measuring Changes in House Prices
Case Shiller
OFHEO
Zillow
Methodology
Repeat Sale
Repeat Sale
Median Zestimate
Coverage Type
All Transactions observed
(Excludes non-disclosure states)
Purchases and Refinancing
with conforming mortgage
purchased by Fannie or Freddie.
All Properties
Transactions
Home Appraisals
Zestimate
Coverage Geographic
20 Metros + U.S.
384 MSA Indices
All
Range
Since early 1990s
Since 1974
Recently
Data
• Key Differences: UNDERSTAND WHAT YOU MEASURE
19
House Prices - The Macro Dimension
Key Housing Facts
20
US House Price Data
OFHEO Price Index normalized by PCE-Inflation
1.6
1.4
1.2
1
0.8
0.6
1975
1978
• Real House
− 0% per
− 3% per
− 0% per
− 0% per
1981
1984
1987
1990
1993
1996
1999
2002
2005
2008
2011
Prices appreciated by:
year
year
year
year
in the 1960s
in the 1970s
in the 1980s
1990 - 1998
21
US House Price Data
Month-on-Month Growth Real OFHEO Price Index
0.04
0.03
0.02
0.01
0
-0.01
-0.02
-0.03
-0.04
-0.05
1975
1979
1983
1987
1991
1995
1999
2003
2007
2011
• Yet, cycles of various sizes have been common.
• The bigger the boom, the bigger the subsequent bust.
• Similar trends across other countries.
22
US House Price Data
250
225
200
175
150
125
100
75
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
Case-Shiller - 20 Composite
• Since 1998 house prices have been very volatile (Case-Shiller 20
cities more than double, then collapse by > 30%; OFHEO
national similar, lower amplitude)
23
US House Price Data
250
225
200
175
150
125
100
75
2000
2001
2002
2003
Phoenix - AZ
2004
2005
Chicago - IL
2006
2007
Dallas - TX
2008
2009
2010
2011
2012
Case-Shiller - 20 Composite
• House price movements are very heterogeneous across regions;
Different peak amplitudes and times; Sand States.
24
US House Price Data
• Bigger Boom → Bigger Bust also true in cross-section.
25
US House Price Data
Housing Starts (Thousand per Year)
3000
2500
2000
1500
1000
500
0
1959
1964
1969
1974
1979
1984
1989
1994
1999
2004
2009
• Construction somewhat more volatile.
• At all-time low, creeping back up (residential investment 6% to
3% of GDP).
26
US House Price Data
Homeownership Rate
70.0
69.0
68.0
67.0
66.0
65.0
64.0
63.0
62.0
61.0
60.0
1960
1965
1970
1975
1980
1985
1990
1995
2000
2005
2010
• Homeownership Rate declining from peak values.
27
US House Price Data
• Long run real house price appreciation runs from 0-2% per year.
• Fact is consistent across time, countries, states, metro areas, etc.
• Housing cycles are very common; recent cycle (2000-now) most
extreme.
• Large housing booms that occur over a relatively short period of
time at country, state, and metro area levels almost always lead
to substantial reversals.
• Will build a simple theoretical framework that helps us
think through these facts.
28
House Prices - The Macro Dimension
Equilibrium Model of Housing Market
29
Equilibrium model of the housing market
• Need a framework to:
1. Understand past aggregate price movements
2. Forecast future price movements
30
Equilibrium model of the housing market
• Need a framework to:
1. Understand past aggregate price movements
2. Forecast future price movements
• Housing plays a dual role:
−
Consumption - Provides consumption services
−
Asset - Generates “dividends”
• The markets for housing as an asset and provider of consumption
services interact to determine house prices.
30
Equilibrium model of the housing market
• Need a framework to:
1. Understand past aggregate price movements
2. Forecast future price movements
• Housing plays a dual role:
−
Consumption - Provides consumption services
−
Asset - Generates “dividends”
• The markets for housing as an asset and provider of consumption
services interact to determine house prices.
• Introduce an equilibrium model of the housing markets that
allows us to understand long-run movements in house prices.
30
Equilibrium model of the housing market
Rent ($ per sqft)
Demand for Housing
D(Rent, Economy)
Housing Stock (sqft)
• Demand for living space depends on rents and economic
conditions, demographics, ease of financing, amenities.
31
Equilibrium model of the housing market
Rent ($ per sqft)
Demand for Housing
D(Rent, Economy)
Housing Stock (sqft)
• Demand for living space depends on rents and economic
conditions, demographics, ease of financing, amenities.
• Rents: Price for living space, clears market in equilibrium.
31
Drivers of Demand for Living Space
• Rents: When living space becomes cheaper, people want to
consume more of it.
32
Drivers of Demand for Living Space
• Rents: When living space becomes cheaper, people want to
consume more of it.
• Income: More income → More Housing Demand
−
From consumer theory, since housing is a “normal good.”
−
Bay Area: Prices move very closely with Tech Stocks.
32
The Role of Income
Source: Glaeser (2007)
33
The Role of Income
34
Drivers of Demand for Living Space
• Rents: When living space becomes cheaper, people want to
consumer more of it.
• Income: More income → More Housing Demand
−
From consumer theory, since housing is a “normal good.”
−
Bay Area: Prices move very closely with Tech Stocks.
• Formal Time-Series Test: Correlation between 1-year GDP vs.
1-year HP changes:
−
Michigan: 0.685
−
New York: 0.653
−
California: 0.512
• These correlations are huge!
35
Drivers of Demand for Living Space
• Demographics:
−
Ageing of the baby-boomers.
36
Drivers of Demand for Living Space
• Demographics:
−
Ageing of the baby-boomers.
−
Increases in life expectancy.
36
Drivers of Demand for Living Space
• Demographics:
−
Ageing of the baby-boomers.
−
Increases in life expectancy.
−
Retirees moving south (Phoenix, Inland Empire).
36
Drivers of Demand for Living Space
• Demographics:
−
Ageing of the baby-boomers.
−
Increases in life expectancy.
−
Retirees moving south (Phoenix, Inland Empire).
−
Trends in household formation rates (e.g. divorce laws).
“From 1997 to 2007, about 1.5 million households were formed on
average each year in the United States. Then the Great Recession hit,
and in the ensuing three years, the rate fell to 500,000 per year. This
decline in household formation occurred even as the U.S. population
was expanding at a rate of 2.7 million per year, only slightly below the
rate of 2.9 million a year observed between 1997 and 2007. A modest
rebound has since followed during the economic recovery, with 1.1
million new households being created in 2011 (Cleveland Fed, 2012).”
37
Drivers of Demand for Living Space
• Demographics: Evidence
• Formal Test: Correlation between 1-year population change vs.
1-year HP changes:
−
Michigan: 0.356
−
New York: 0.321
−
California: 0.337
38
Drivers of Demand for Living Space
• Government Policy: (studied in much more detail later)
−
First-Time Homebuyer Tax Credit.
−
“Ownership Society” and the “American Dream.”
39
Drivers of Demand for Living Space
• Government Policy: (studied in much more detail later)
−
First-Time Homebuyer Tax Credit.
−
“Ownership Society” and the “American Dream.”
• “We’re creating... an ownership society in this country, where more
Americans than ever will be able to open up their door where they live and
say, welcome to my house, welcome to my piece of property.” - President
George W. Bush, October 2004.
39
Drivers of Demand for Living Space
• Government Policy: (studied in much more detail later)
−
First-Time Homebuyer Tax Credit.
−
“Ownership Society” and the “American Dream.”
• “We’re creating... an ownership society in this country, where more
Americans than ever will be able to open up their door where they live and
say, welcome to my house, welcome to my piece of property.” - President
George W. Bush, October 2004.
• “For millions of America’s working families throughout our history, owning a
home has come to symbolize the realization of the American Dream. Yet
sadly, in the 1980s, it became much harder for many young families to buy
their first home, and our national homeownership rate declined for the first
time in forty-six years. Our Administration is determined to reverse this
trend, and we are committed to ensuring that working families can once
again discover the joys of owning a home.” - President Bill Clinton, 1995
39
Drivers of Demand for Living Space
• Belief in the home-ownership == American Dream Story is
declining?
• Age or Cohort Effect? Hard to tell, but important for investors.
40
Drivers of Demand for Living Space
• Belief in the home-ownership == American Dream Story is
declining?
• Age or Cohort Effect? Hard to tell, but important for investors.
• Ideal home size declining - the end of the McMansion?
40
Drivers of Demand for Living Space
41
Drivers of Demand for Living Space
42
Drivers of Demand for Living Space
• Belief in the home-ownership == American Dream Story is
declining?
• Age or Cohort Effect? Hard to tell, but important for investors.
• Ideal home size declining - the end of the McMansion?
43
Drivers of Demand for Living Space
• Amenities - Trendy:
−
Location becomes “trendy”
−
Opening of restaurants/bars.
−
School quality.
−
Location is desirable because of neighbors.
• Hard to measure, but key for developers (think of South Loop!)
44
Equilibrium model of the housing market
Rent ($ per sqft)
Demand for Housing
D(Rent, Economy)
Housing Stock (sqft)
• Demand for living space depends on rents and economic
conditions, demographics, ease of financing, amenities.
45
Equilibrium model of the housing market
Rent ($ per sqft)
Demand for Housing
D(Rent, Economy)
S*
Housing Stock (sqft)
• Demand for living space depends on rents and economic
conditions, demographics, ease of financing, amenities.
• Rents: Price for living space, clears market in equilibrium.
46
Equilibrium model of the housing market
Rent ($ per sqft)
Asset Market Valuation:
P=
House Prices
($ per sqft )
ோ௘௡௧
௜
Demand for Housing
D(Rent, Economy)
Housing Stock (sqft)
• Demand for living space depends on rents and economic
conditions, demographics, ease of financing, amenities.
• Rents: Price for living space, clears market in equilibrium.
• Valuation of housing as an asset depends on capitalization of
rents.
47
Equilibrium model of the housing market
Valuation using capitalization rate:
Value =
Net operating Income (Rent)
Capitalization Rate (i)
• The minimum, unlevered return requirement.
• Similar to valuation using the WACC.
• Affected by:
−
Risk free cost of capital
−
Inflation
−
Market risk (risk associated with rental stream)
−
Tax treatment.
48
Equilibrium model of the housing market
What determines the capitalization rate i?
• No-arbitrage condition for consumers for housing services.
• People have to be indifferent between buying and renting.
R = (m + t + δ) ×P
|
{z
}
i
−
m = Mortgage interest rate (Real rate + inflation)
−
t = Property tax rate
−
δ = Depreciation + Maintenance
49
Equilibrium model of the housing market
What determines the capitalization rate i?
• No-arbitrage condition for consumers for housing services.
• People have to be indifferent between buying and renting.
R = (m + t + δ) ×P
|
{z
}
i
−
m = Mortgage interest rate (Real rate + inflation)
−
t = Property tax rate
−
δ = Depreciation + Maintenance
• What about downpayments? Doesn’t this reduce costs?
49
Equilibrium model of the housing market
What determines the capitalization rate i?
• No-arbitrage condition for consumers for housing services.
• People have to be indifferent between buying and renting.
R = (m + t + δ) ×P
|
{z
}
i
−
m = Mortgage interest rate (Real rate + inflation)
−
t = Property tax rate
−
δ = Depreciation + Maintenance
• What about downpayments? Doesn’t this reduce costs?
• Has opportunity cost! Assumes that this is opportunity cost is
roughly nominal mortgage interest rate.
49
Equilibrium model of the housing market
What determines the capitalization rate i?
• No-arbitrage condition for consumers for housing services.
• People have to be indifferent between buying and renting.
R = [(m + t)(1 − T ) + δ] ×P
|
{z
}
i
−
m = Interest rate (Risk free + inflation)
−
t = Property tax rate
−
δ = Depreciation + Maintenance
−
T = Marginal Tax Rate for Deductions
• Property Taxes and Mortgage Interest Rates Tax Deductible.
50
Equilibrium model of the housing market
What determines the capitalization rate i?
• No-arbitrage condition for consumers for housing services.
• People have to be indifferent between buying and renting.
R = [(m + t)(1 − T ) + δ] ×P
|
{z
}
i=User
Cost
−
m = Interest rate (Risk free + inflation)
−
t = Property tax rate
−
δ = Depreciation + Maintenance
−
T = Marginal Tax Rate for Deductions
• Property Taxes and Mortgage Interest Rates Tax Deductible.
51
Equilibrium model of the housing market
Rent ($ per sqft)
Asset Market Valuation:
P=
House Prices
($ per sqft )
ோ௘௡௧
௜
Demand for Housing
D(Rent, Economy)
Housing Stock (sqft)
• Demand for living space depends on rents and economic
conditions, demographics, ease of financing, amenities.
• Rents: Price for living space, clears market in equilibrium.
• Valuation of housing as an asset depends on capitalization of
rents.
52
Equilibrium model of the housing market
Rent ($ per sqft)
Asset Market Valuation:
P=
House Prices
($ per sqft )
Demand for Housing
D(Rent, Economy)
ோ௘௡௧
௜
S*
Housing Stock (sqft)
• Consider short-run effect of a positive demand shock.
• Possible Sources: Release of good school test scores.
• In short-run, housing stock is fixed at S∗
53
Equilibrium model of the housing market
Rent ($ per sqft)
Asset Market Valuation:
P=
Demand for Housing
D(Rent, Economy)
ோ௘௡௧
௜
House Prices
($ per sqft )
S*
Housing Stock (sqft)
• Consider short-run effect of a positive demand shock.
• Possible Sources: Release of good school test scores.
• In short-run, housing stock is fixed at S∗ .
• Prices and Rents increase significantly.
54
Equilibrium model of the housing market
Rent ($ per sqft)
Asset Market Valuation:
P=
Demand for Housing
D(Rent, Economy)
ோ௘௡௧
௜
House Prices
($ per sqft )
S*
Housing Stock (sqft)
• But by how much?
55
Equilibrium model of the housing market
Rent ($ per sqft)
Asset Market Valuation:
P=
Demand for Housing
D(Rent, Economy)
ோ௘௡௧
௜
House Prices
($ per sqft )
S*
Housing Stock (sqft)
• But by how much?
• Depends on the user cost of housing!
56
Equilibrium model of the housing market
Rent ($ per sqft)
Asset Market Valuation:
P=
Demand for Housing
D(Rent, Economy)
ோ௘௡௧
௜
House Prices
($ per sqft )
S*
Housing Stock (sqft)
• But by how much?
• Depends on the user cost of housing!
• Higher user cost of housing: Same demand shock leads to lower
price increase.
57
Equilibrium model of the housing market
Rent ($ per sqft)
Asset Market Valuation:
P=
Demand for Housing
D(Rent, Economy)
ோ௘௡௧
௜
House Prices
($ per sqft )
S*
Housing Stock (sqft)
• What is missing from this model?
58
Equilibrium model of the housing market
Rent ($ per sqft)
Asset Market Valuation:
P=
Demand for Housing
D(Rent, Economy)
ோ௘௡௧
௜
House Prices
($ per sqft )
S*
Housing Stock (sqft)
• What is missing from this model?
• A lot of things...
58
Equilibrium model of the housing market
Rent ($ per sqft)
Asset Market Valuation:
P=
House Prices
($ per sqft )
Demand for Housing
D(Rent, Economy)
ோ௘௡௧
௜
S*
Housing Stock (sqft)
• In the long-run, the housing stock will adjust!
59
Equilibrium model of the housing market
Rent ($ per sqft)
Asset Market Valuation:
P=
Demand for Housing
D(Rent, Economy)
ோ௘௡௧
௜
House Prices
($ per sqft )
S*
Housing Stock (sqft)
• In the long-run, the housing stock will adjust!
• Need to consider construction sector.
• Supply elasticity: Manhatten vs. Phoenix.
59
US House Price Data
Housing Starts (Thousand per Year)
3000
2500
2000
1500
1000
500
0
1959
1964
1969
1974
1979
1984
1989
1994
1999
2004
2009
• Construction key part of long-run equilibrium adjustment
mechanism.
60
Equilibrium model of the housing market
The construction market is equilibrium is characterized by:
1. Zero-profit condition for constructing new units.
−
Build new houses (C) until the construction cost for a new house
b(C) equals the market-price P.
P = b(C)
61
Equilibrium model of the housing market
The construction market is equilibrium is characterized by:
1. Zero-profit condition for constructing new units.
−
Build new houses (C) until the construction cost for a new house
b(C) equals the market-price P.
P = b(C)
−
b(C) can be increasing in C due to:
F
Construction bottlenecks.
F
During Arizona housing boom, construction quality declined in
part due to lack of skilled workers (Stroebel, 2015).
F
“Laborers became plumbers, and plumbers became electricians.
(Bloomberg, 2011)”
61
Equilibrium model of the housing market
The construction market is equilibrium is characterized by:
1. Zero-profit condition for constructing new units.
−
Build new houses (C) until the construction cost for a new house
b(C) equals the market-price P.
P = b(C)
−
b(C) can be increasing in C due to:
F
Construction bottlenecks
F
Land use regulation
F
Topology
62
Equilibrium model of the housing market
The construction market is equilibrium is characterized by:
1. Zero-profit condition for constructing new units.
−
Build new houses (C) until the construction cost for a new house
b(C) equals the market-price P.
P = b(C)
−
b(C) can be increasing in C due to:
F
Construction bottlenecks
F
Land use regulation
F
Topology
2. Steady-state equation for housing stock
−
New Construction = Depreciation of Existing Stock
C = δS
63
Equilibrium model of the housing market
Rent ($ per sqft)
Asset Market Valuation:
P=
House Prices
($ per sqft )
ோ௘௡௧
௜
Demand for Housing
D(Rent, Economy)
Housing Stock (sqft)
64
Equilibrium model of the housing market
Rent ($ per sqft)
Asset Market Valuation:
P=
Demand for Housing
D(Rent, Economy)
ோ௘௡௧
௜
House Prices
($ per sqft )
Housing Stock (sqft)
Stock adjustment:
C = δS
Construction (sqft)
65
Equilibrium model of the housing market
Rent ($ per sqft)
Asset Market Valuation:
P=
Demand for Housing
D(Rent, Economy)
ோ௘௡௧
௜
House Prices
($ per sqft )
Housing Stock (sqft)
Construction:
P = b(C)
Stock adjustment:
C = δS
Construction (sqft)
66
Equilibrium model of the housing market
Rent ($ per sqft)
Asset Market Valuation:
P=
Demand for Housing
D(Rent, Economy)
ோ௘௡௧
௜
House Prices
($ per sqft )
Housing Stock (sqft)
Construction:
P = b(C)
Stock adjustment:
C = δS
Construction (sqft)
67
Equilibrium model of the housing market
Rent ($ per sqft)
Asset Market Valuation:
P=
Demand for Housing
D(Rent, Economy)
ோ௘௡௧
௜
House Prices
($ per sqft )
Housing Stock (sqft)
Construction:
P = b(C)
Stock adjustment:
C = δS
Construction (sqft)
68
Equilibrium model of the housing market
Rent ($ per sqft)
Asset Market Valuation:
P=
House Prices
($ per sqft )
Demand for Housing
D(Rent, Economy)
ோ௘௡௧
௜
S*
Housing Stock (sqft)
69
Equilibrium model of the housing market
First take-aways:
• Many factors affect the demand for housing services (Income,
Demographics, Policy, Mortgage Market, Amenities).
• Need to think of these when considering real estate investments.
• Relative importance depends on time horizon considered.
• A positive demand shock increases house prices.
• Prices rise by more in the short-run relative to the long-run.
• By how much prices rise depends on capitalization rate (user
cost) and supply elasticity (see below).
70
Equilibrium model of the housing market
Now have a tool to analyze a few theories of house prices.
• Numerical Example (allows us to talk about magnitudes)
• Theories of the Housing Boom / Bust
−
Role of interest rates.
−
Role of mortgage innovation.
• Role of supply elasticity.
• Role of government interventions.
71
House Prices - The Macro Dimension
Theories of the Boom / Bust
72
US House Price Data
250
225
200
175
150
125
100
75
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
Case-Shiller - 20 Composite
• What drove the 2000 - 2006 house price boom?
73
Equilibrium model of the housing market
• Lots of disagreement in academic literature!
• One explanation: house price increases driven by interest rates
too low:
74
Equilibrium model of the housing market
• Lots of disagreement in academic literature!
• One explanation: house price increases driven by interest rates
too low:
• Taylor Rule: How central bank should set the interest rate.
r∗ = 2% + 0.5 × (π − 2%) + 0.5 × (GDP − GDP∗ )
74
Equilibrium model of the housing market
• Lots of disagreement in academic literature!
• One explanation: house price increases driven by interest rates
too low:
• Taylor Rule: How central bank should set the interest rate.
r∗ = 2% + 0.5 × (π − 2%) + 0.5 × (GDP − GDP∗ )
My critique is based on the simple observation that the
Fed’s target for the federal-funds interest rate was well
below what the Taylor rule would call for in 2002-2005. By
this measure the interest rate was too low for too long,
reducing borrowing costs and accelerating the housing boom
(John Taylor, WSJ 2010).
74
Equilibrium model of the housing market
• The Economist (2007): “Fast and loose - How the Fed made the
subprime bust worse.”
75
Equilibrium model of the housing market
• Can use our equilibrium model to consider how realistic that
explanation is.
• Q: How can interest rates affect house prices?
−
Required to differentiate between different theories of the boom.
−
Required to understand sensitivity of real estate investments to
monetary policy.
76
Equilibrium model of the housing market
• Can use our equilibrium model to consider how realistic that
explanation is.
• Q: How can interest rates affect house prices?
−
Required to differentiate between different theories of the boom.
−
Required to understand sensitivity of real estate investments to
monetary policy.
• A: Lower interest rates reduce capitalization rate i.
• A: Lower interest rates might also reduce construction costs
(ignored here).
76
Equilibrium model of the housing market
Rent ($ per sqft)
Asset Market Valuation:
P=
Demand for Housing
D(Rent, Economy)
ோ௘௡௧
௜
House Prices
($ per sqft )
Housing Stock (sqft)
Construction:
P = b(C)
Stock adjustment:
C = δS
Construction (sqft)
77
Equilibrium model of the housing market
Rent ($ per sqft)
Asset Market Valuation:
P=
Demand for Housing
D(Rent, Economy)
ோ௘௡௧
௜
House Prices
($ per sqft )
Housing Stock (sqft)
Construction:
P = b(C)
Stock adjustment:
C = δS
Construction (sqft)
78
Equilibrium model of the housing market
Rent ($ per sqft)
Asset Market Valuation:
P=
Demand for Housing
D(Rent, Economy)
ோ௘௡௧
௜
House Prices
($ per sqft )
Housing Stock (sqft)
Construction:
P = b(C)
Stock adjustment:
C = δS
Construction (sqft)
79
Equilibrium model of the housing market
Rent ($ per sqft)
Asset Market Valuation:
P=
Demand for Housing
D(Rent, Economy)
ோ௘௡௧
௜
House Prices
($ per sqft )
Housing Stock (sqft)
Construction:
P = b(C)
Stock adjustment:
C = δS
Construction (sqft)
80
Equilibrium model of the housing market
• Decrease in Interest Rates leads to a large increase in prices in
the short-run, an increase in construction, and then a partial
reversal of the initial boom.
• Theoretical predictions of John Taylor consistent with our model.
• Does that mean he is correct?
• Q: What does the empirical evidence look like?
81
Equilibrium model of the housing market
• What does the empirical evidence look like?
• Time-Series Evidence (within US)
220
7.00
6.00
200
5.00
180
4.00
160
3.00
140
2.00
120
1.00
0.00
100
2000
2001
2002
2003
2004
2005
Case-Shiller 20
2006
2007
2008
2009
2010
2011
2012
Fed Funds Rate
82
Equilibrium model of the housing market
• What does the empirical evidence look like?
• Cross-Country Evidence - IMF World Development Report (2009)
83
Equilibrium model of the housing market
• Decrease in Interest Rates leads to a large increase in prices in
the short-run, an increase in construction, and then a partial
reversal of the initial boom.
• Theoretical predictions of John Taylor consistent with our model.
• Does that mean he is correct?
• Q: What does the empirical evidence look like?
84
Equilibrium model of the housing market
• Decrease in Interest Rates leads to a large increase in prices in
the short-run, an increase in construction, and then a partial
reversal of the initial boom.
• Theoretical predictions of John Taylor consistent with our model.
• Does that mean he is correct?
• Q: What does the empirical evidence look like?
• A: Empirical evidence consistent with story, but hard to rule out
other stories (e.g. mortgage lending, Fannie/Freddie).
84
Equilibrium model of the housing market
• Decrease in Interest Rates leads to a large increase in prices in
the short-run, an increase in construction, and then a partial
reversal of the initial boom.
• Theoretical predictions of John Taylor consistent with our model.
• Does that mean he is correct?
• Q: What does the empirical evidence look like?
• A: Empirical evidence consistent with story, but hard to rule out
other stories (e.g. mortgage lending, Fannie/Freddie).
• Probably a combination of many different factors.
84
Equilibrium model of the housing market
• Decrease in Interest Rates leads to a large increase in prices in
the short-run, an increase in construction, and then a partial
reversal of the initial boom.
• Theoretical predictions of John Taylor consistent with our model.
• Does that mean he is correct?
• Q: What does the empirical evidence look like?
• A: Empirical evidence consistent with story, but hard to rule out
other stories (e.g. mortgage lending, Fannie/Freddie).
• Probably a combination of many different factors.
• BUT: You now know one channel through which monetary
policy affects house prices.
84
House Prices - The Macro Dimension
The Role of Supply Elasticity
85
The Role of Supply Elasticity
Why are some cities more expensive than others?
• Again, many factors: Demand for housing could be different
(e.g. different economic situation, different amenities - San
Diego vs. Minnesota), etc.
• The role of housing supply elasticity?
• Higher supply elasticity ⇒ Easier to build additional housing
units.
86
The Role of Supply Elasticity
Rent ($ per sqft)
Asset Market Valuation:
P=
Demand for Housing
D(Rent, Economy)
ோ௘௡௧
௜
House Prices
($ per sqft )
Housing Stock (sqft)
Construction:
P = b(C)
Stock adjustment:
C = δS
Construction (sqft)
87
The Role of Supply Elasticity
Rent ($ per sqft)
Asset Market Valuation:
P=
Demand for Housing
D(Rent, Economy)
ோ௘௡௧
௜
House Prices
($ per sqft )
Housing Stock (sqft)
Construction:
P = b(C)
Stock adjustment:
C = δS
Construction (sqft)
88
The Role of Supply Elasticity
Rent ($ per sqft)
Asset Market Valuation:
P=
Demand for Housing
D(Rent, Economy)
ோ௘௡௧
௜
House Prices
($ per sqft )
Housing Stock (sqft)
Construction:
P = b(C)
Stock adjustment:
C = δS
Construction (sqft)
89
The Role of Supply Elasticity
Rent ($ per sqft)
Asset Market Valuation:
P=
Demand for Housing
D(Rent, Economy)
ோ௘௡௧
௜
House Prices
($ per sqft )
Housing Stock (sqft)
Construction:
P = b(C)
Stock adjustment:
C = δS
Construction (sqft)
90
The Role of Supply Elasticity
The role of housing supply elasticity (theory)?
• Higher supply elasticity ⇒ Easier to build additional housing
units.
• With higher supply elasticity: Same shock to housing demand
leads to bigger increases in production / housing and a lower
impact on prices.
• Cities with higher supply elasticity should have lower house prices
on average.
91
The Role of Supply Elasticity
The role of housing supply elasticity (evidence):
• How to measure it? Geographic and Regluation....
• Regulation: Wharton Regulation Index (freely available on Joe
Gyourko’s website)
−
Good cross-country coverage.
−
Interesting first-step to understanding local regulation.
• Geographic: Saiz (2010) analyzes satellite images for
developable land.
92
The Role of Supply Elasticity - Saiz (2010)
• More elastic cities have lower prices.
• Not just driven by outliers Manhattan and SF.
93
The Role of Supply Elasticity - Saiz (2010)
• More elastic cities have lower housing growth.
• Both levels and growth affected.
94
House Prices - The Macro Dimension
Conclusions on Equilibrium Model
95
Conclusion on Equilibrium Model
• Introduced a framework to thinking about long-run house price
movements.
• Analyzed impact of changes in demand shocks, interest rates,
changes in supply elasticity.
• BUT: Very long-run analysis. Housing stock takes long time to
adjust, so do prices.
• For almost any policy, transition path is very important (see
later).
• Simple extension to equilibrium approach required.
96
House Prices - The Macro Dimension
The Role of Public Policy
97
Analyzing Policy
• The US tax code subsidizes home ownership in a number of
ways:
98
Analyzing Policy
• The US tax code subsidizes home ownership in a number of
ways:
−
Non-taxation of imputed rents from owner-occupied housing.
98
Analyzing Policy
• The US tax code subsidizes home ownership in a number of
ways:
−
Non-taxation of imputed rents from owner-occupied housing.
−
Deduction of mortgage interest rates.
98
Analyzing Policy
• The US tax code subsidizes home ownership in a number of
ways:
−
Non-taxation of imputed rents from owner-occupied housing.
−
Deduction of mortgage interest rates.
−
Deduction of property taxes.
98
Using our equilibrium model
• Where does mortgage interest deductibility show up?
99
Using our equilibrium model
• Where does mortgage interest deductibility show up?
• User cost equation:
R = [(m + t)(1 − T ) + δ] ×P
|
{z
}
i
99
Using our equilibrium model
• Where does mortgage interest deductibility show up?
• User cost equation:
R = [(m + t)(1 − T ) + δ] ×P
|
{z
}
i
• Removing MID will increase i.
99
Using our equilibrium model
• Where does mortgage interest deductibility show up?
• User cost equation:
R = [(m + t)(1 − T ) + δ] ×P
|
{z
}
i
• Removing MID will increase i.
• What effect will that have on prices in the short-run and the
long-run?
99
Mortgage Interest Deductibility
Rent ($ per sqft)
Asset Market Valuation:
P=
Demand for Housing
D(Rent, Economy)
ோ௘௡௧
௜
House Prices
($ per sqft )
Housing Stock (sqft)
Construction:
P = b(C)
Stock adjustment:
C = δS
Construction (sqft)
100
Mortgage Interest Deductibility
Rent ($ per sqft)
Asset Market Valuation:
P=
Demand for Housing
D(Rent, Economy)
ோ௘௡௧
௜
House Prices
($ per sqft )
Housing Stock (sqft)
Construction:
P = b(C)
Stock adjustment:
C = δS
Construction (sqft)
101
Mortgage Interest Deductibility
Rent ($ per sqft)
Asset Market Valuation:
P=
Demand for Housing
D(Rent, Economy)
ோ௘௡௧
௜
House Prices
($ per sqft )
Housing Stock (sqft)
Construction:
P = b(C)
Stock adjustment:
C = δS
Construction (sqft)
102
Mortgage Interest Deductibility
• Removal of mortgage interest deductibility will reduce home
prices.
• Prices will overshoot in the short-run.
• As the housing stock moves towards its new equilibrium, prices
recover.
103
Mortgage Interest Deductibility
• Removal of mortgage interest deductibility will reduce home
prices.
• Prices will overshoot in the short-run.
• As the housing stock moves towards its new equilibrium, prices
recover.
• All intuition in this model, but:
−
Magnitude?
−
Timeframe?
−
Very relevant for policy makers and investors!!!
103
Mortgage Interest Deductibility
• Removal of mortgage interest deductibility will reduce home
prices.
• Prices will overshoot in the short-run.
• As the housing stock moves towards its new equilibrium, prices
recover.
• All intuition in this model, but:
−
Magnitude?
−
Timeframe?
−
Very relevant for policy makers and investors!!!
• Enter Floetotto, Kirker and Stroebel (2014)
103
Floetotto, Kirker and Stroebel (2014)
• Complex general equilibrium model of the economy.
• Consider life-cycle aspects, transaction costs, moving shocks,
rental market frictions, etc. etc. etc.
• Considers policy experiment: What if we removed mortgage
interest deductibility tomorrow?
104
Floetotto, Kirker and Stroebel (2014)
• Complex general equilibrium model of the economy.
• Consider life-cycle aspects, transaction costs, moving shocks,
rental market frictions, etc. etc. etc.
• Considers policy experiment: What if we removed mortgage
interest deductibility tomorrow?
• What will happen in the long-run if we removed mortgage
interest deductibility?
104
Floetotto, Kirker and Stroebel (2014)
Transfer Development
2
0
1.5
-1
In Percent
In Percent
House Price Development
1
-2
-3
-4
-5
1
0.5
0
-0.5
0
20
40
60
-1
80
0
Rent Development
60
80
1
0
0
In Percent
-2
In Percent
40
Housing Quantity Development
2
-4
-6
-8
-1
-2
-3
-4
-10
-12
20
0
20
40
Years
60
80
-5
0
20
40
Years
60
80
105
Floetotto, Kirker and Stroebel (2014)
• Prices decline by about 2% in new steady state.
• Immediate price drop is about 4%, afterwards predictable
appreciation.
• New equilibrium housing stock about 4% lower than before.
• Transition to new equilibrium takes many decades.
106
Conclusion
• Housing service demand driven by many factors, including
economy, amenities, demographics, etc...
107
Conclusion
• Housing service demand driven by many factors, including
economy, amenities, demographics, etc...
• Translation into house prices affected by many factors, including
government intervention, interest rates, etc...
107
Conclusion
• Housing service demand driven by many factors, including
economy, amenities, demographics, etc...
• Translation into house prices affected by many factors, including
government intervention, interest rates, etc...
• In long-run, housing supply will adjust to any shocks - effects
depends on supply elasticity.
107
Conclusion
• Housing service demand driven by many factors, including
economy, amenities, demographics, etc...
• Translation into house prices affected by many factors, including
government intervention, interest rates, etc...
• In long-run, housing supply will adjust to any shocks - effects
depends on supply elasticity.
• You now have:
−
A sense of a large number factors affecting house prices.
−
An intuitive tool to analyze the impact of shocks on house prices.
107