Transcript What We Hope To Accomplish

Summer 2011
Macroeconomics – Lecture 1
Extra Slides
1
Understanding Housing Prices
2
Average Annual Real Housing Price Growth By US State
State
AK
AL
AR
AZ
CA
CO
CT
DC
DE
FL
GA
HI
IA
ID
IL
IN
1980-2000
-0.001
0.000
-0.009
-0.002
0.012
0.012
0.012
0.010
0.011
-0.002
0.008
0.004
-0.001
-0.001
0.010
0.002
2000-2007
0.041
0.024
0.023
0.061
0.066
0.012
0.044
0.081
0.053
0.068
0.019
0.074
0.012
0.047
0.030
0.020
State
MT
NC
ND
NE
NH
NJ
NM
NV
NY
OH
OK
OR
PA
RI
SC
SD
1980-2000
0.003
0.008
-0.010
-0.002
0.014
0.015
-0.002
-0.005
0.020
0.003
-0.019
0.009
0.008
0.017
0.007
0.002
2000-2007
0.049
0.022
0.033
0.007
0.041
0.058
0.043
0.060
0.051
-0.001
0.019
0.051
0.042
0.059
0.025
0.025
3
Average
0.011
0.036
Typical “Local” Cycle
New York State: Real Housing Price Growth
0.200
0.150
0.100
0.050
0.000
-0.050
-0.100
-0.150
HPI-Growth-Real
4
Typical “Local” Cycle
0.250
California: Real Housing Price Growth
0.200
0.150
0.100
0.050
0.000
-0.050
-0.100
-0.150
HPI-Growth-Real
5
Housing Cycles: Part 1
U.S. Metro Area Data, (1980 - 1990 vs. 1990 - 2000)
Real House Price Changes
0.60
0.50
0.40
y = -0.3798x + 0.0027
R² = 0.3804
0.30
0.20
0.10
0.00
-0.10
-0.20
-0.30
-0.40
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
6
1
Housing Prices and Housing Cycles (Hurst and Guerrieri (2009))
• Persistent housing price increases are ALWAYS followed by persistent
housing price declines
Some statistics about U.S. metropolitan areas 1980 – 2000
• 44 MSAs had price appreciations of at least 15% over 3 years during this
period.
• Average price increase over boom (consecutive periods of price increases):
55%
• Average price decline during bust (the following period of price declines):
30%
• Average length of bust: 26 quarters (i.e., 7 years)
• 40% of the price decline occurred in first 2 years of bust
7
Real House Price Changes By State: 1997-2005 (x-axis) vs. 2005 – 2009 (y-axis)
-.2
0
ND
MT
OKTX LA
NC
UT SD
NM
AL
ID AK
WVKS
TN SC
KY
IA
MS
PA
NEAR
CO OR
MO
WI
IN
IL
GA
OH
VT
WA
DE NY
ME
VA
CT
MN
DC
NJ
HI
MD
MA
NH
RI
-.4
MI
AZ
-.6
FL
CA
-.8
NV
0
.5
g_97_05
g_05_09
1
Fitted values
8
1976
1977
1978
1979
1981
1982
1983
1984
1986
1987
1988
1989
1991
1992
1993
1994
1996
1997
1998
1999
2001
2002
2003
2004
2006
2007
2008
OFHEO House Price Index
Typical “Country” Cycle (US – OFHEO Data)
0.20
U.S. Nominal House Price Appreciation: 1976 - 2008
0.15
0.10
0.05
0.00
-0.05
-0.10
9
Typical “Country” Cycle (US – OFHEO Data)
0.12
U.S. Real House Price Appreciation: 1976 - 2008
0.09
0.06
0.03
0.00
-0.03
-0.06
-0.09
-0.12
10
Average Annual Real Price Growth By OECD Country
Country
1970-1999
2000-2006
Country
1970-1999
2000-2006
U.S.
Japan
Germany
France
Great Britain
Italy
Canada
Spain
Australia
0.012
0.010
0.001
0.010
0.022
0.012
0.013
0.019
0.015
0.055
-0.045
-0.029
0.075
0.068
0.051
0.060
0.081
0.065
Netherlands
Belgium
Sweden
Switzerland
Denmark
Norway
Finland
New Zealand
Ireland
0.023
0.019
-0.002
0.000
0.011
0.012
0.009
0.014
0.022
0.027
0.064
0.059
0.019
0.065
0.047
0.040
0.080
0.059
1970-1999
2000-2006
0.012
0.046
Average
11
Country Cycles – The U.S. is Not Alone
Real House Price Growth
UK: 1978 - 2006
0.250
0.200
0.150
0.100
0.050
0.000
-0.050
-0.100
-0.150
12
Country Cycles – The U.S. is Not Alone
Real House Price Growth
Italy: 1978 - 2006
0.250
0.200
0.150
0.100
0.050
0.000
-0.050
-0.100
-0.150
13
Country Cycles – The U.S. is Not Alone
Real House Price Growth
Japan: 1978 - 2006
0.120
0.100
0.080
0.060
0.040
0.020
0.000
-0.020
-0.040
-0.060
-0.080
14
Housing Cycles: Part 2
OECD Country Level Data (1970 - 2000)
Price Changes in Booms vs. Subsequent Busts
0
-0.1
y = -0.6185x + 0.0584
R² = 0.483
Size of Subsequent Bust
-0.2
-0.3
-0.4
-0.5
-0.6
-0.7
0
0.2
0.4
0.6
Size of Boom
0.8
15
1
Regression Analysis
• Use Historical Analysis (Country, State, Metropolitan Area)
• Regress Size of Subsequent Bust on Size of Consecutive
Boom
• Depending on the sample, coefficient on mean revision
ranged from: -0.5 to -0.6.
• Implication: 100% increase in house prices are usually
followed by periods of 50% - 60% declines.
16
Equilibrium in Housing Markets
Fixed Supply (Short Run)
PH
Demand
QH
17
Equilibrium in Housing Markets
Fixed Supply (Short Run)
PH’
PH
Demand
QH
18
Equilibrium in Housing Markets
Fixed Supply (Short Run)
PH’
PH
Demand
QH
Demand shocks cause large price increases when supply is fixed
19
Equilibrium in Housing Markets
Fixed Supply
Supply Eventually Adjusts
PH’
PH”
PH
Demand
QH
20
How Does Supply Adjust?
•
Build on Vacant Land
•
Convert Rental or Commercial Property
•
Build Up
•
Build Out (Suburbs)
•
Build Way Out (Create New Cities)
•
Some of these adjustments can take consider amounts of time.
21
Do Supply Factors Explain 2000-2008 Cycle
.04
Change in Total Housing Units Against Change in Housing Price
Adjusted for Population Changes (2000-2005, State Level)
ND MN
IN
NC
WI
GA
LA
SCIA
MS SD
MI
AL
KS
OH
NE
ID
KY
TN
WV
IL
ARMO
UT
OK
NM
TX
-.02
0
.02
CO
NV
VA
FL
WY
WA
DE VT
PA
ME
NH MA
OR
NY
AZ
MT
CT
NJ MD
CA
RI
DC
-.04
AK
HI
-.2
0
Residuals
.2
Residuals
.4
.6
Fitted values
22
Do Supply Factors Explain 2000-2008 Cycle
Change in Total Housing Units Against Change in Housing Price
Adjusted for Population Changes (2005-2009, State Level)
.02
NV
FL
.01
HI
0
MI
RI
-.01
CA
AZ
ND
ME
AL
SC
NJ
ID
MD
VA
NH
VT
DE
MS
GA WICO
AR TN
MNOH IL
WA
WV SD
NC
NE IA
NM
CT
TX
IN
KY
MO
PA
OR
KS
MA
DC
OK
NY
UT
WY
AK
-.02
MT
-.03
LA
-.6
-.4
-.2
Residuals
Residuals
0
.2
Fitted values
23
Average Annual Real Price Growth By OECD Country
Country
1970-1999
2000-2006
Country
1970-1999
2000-2006
U.S.
Japan
Germany
France
Great Britain
Italy
Canada
Spain
Australia
0.012
0.010
0.001
0.010
0.022
0.012
0.013
0.019
0.015
0.055
-0.045
-0.029
0.075
0.068
0.051
0.060
0.081
0.065
Netherlands
Belgium
Sweden
Switzerland
Denmark
Norway
Finland
New Zealand
Ireland
0.023
0.019
-0.002
0.000
0.011
0.012
0.009
0.014
0.022
0.027
0.064
0.059
0.019
0.065
0.047
0.040
0.080
0.059
1970-1999
2000-2006
0.012
0.046
Average
24
What Does This All Mean
•
Decline in Residential Housing Prices in the U.S. was very
predictable (although the timing was not).
•
Using OFHEO price index, real housing prices rose by 46% between
1997 and 2006 (for the entire U.S.).
•
My model predicts that housing prices will fall by roughly 25-30% (in
real terms) over the next 5-7 years.
•
So far, the real OFHEO price index has fallen by roughly 15-20%
(from peak to current levels).
•
More “real” residential price declines to come! (Nominal prices
should stabilize late this year/early next year).
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1991
1991
1992
1993
1994
1994
1995
1996
1997
1997
1998
1999
2000
2000
2001
2002
2003
2003
2004
2005
2006
2006
2007
2008
2009
OFHEO House Price Index
U.S. OFHEO Housing Cycle - Levels
120
110
100
90
80
70
60
26
Bonus Material: The Yield Curve
27
What is a Yield Curve
•
•
A yield curve graphs the interest rate for a given security of differing maturities.
For example, it represents the yield on 1, 3, 5, 7, and 10 year treasuries.
Historically, yield curves tend to be upward sloping
Data on U.S. treasury yields from late 2004
Maturity (in years)
28
Yield Curve Mechanics
• Consider a two period model
• Define the interest rate on a one year treasury starting today as i0,1
• Define the interest rate on a two year treasury starting today as i0,2
• What is the relationship between one year treasuries and two year treasuries?
• Appeal to theory of arbitrage. If arbitrage holds, then by definition:
(1 + i0,2)2 = (1 + i0,1) * (1 + i1,2)
where i1,2 is the interest rate on a one year treasury starting one period from now.
29
Shape of the Yield Curve: Macro Explanations
• Solve for long interest rates (i0,2) as a function of short rates:
i0,2 = [(1+i0,1) * (1+i1,2)]1/2 – 1
• Question:
When does the yield curve slope up (i.e., i0,2 > i0,1)?
• Answer:
When i1,2 > i0,1
30
Shape of the Yield Curve: Macro Explanations
• When does i1,2 > i0,1 ?
• Remember: i = r + πe + ρ (or, with time subscripts, i0,1 = r0,1 + πe0,1 + ρ0,1)
where ρ is a risk premium
• To start, assume risk free assets (ρ = 0)
• So, if r is held fixed over time (i.e., r0,1 = r1,2) then the yield curve will slope up
if πe1,2 > πe0,1. Increasing inflation will cause the yield curve to slope up (all
else equal)!
• Also, if πe is fixed over time (i.e., πe1,2 = πe0,1) then the yield curve will slope up
if r1,2 > r0,1. Higher future real rates will cause the yield curve to slope up (all
else equal).
31
Shape of the Yield Curve: Micro Explanations
• Suppose ρ is not equal to zero such that:
i=r+π+ρ
• Alluding back to our previous discussion, i1,2 > i0,1 if ρ1,2 > ρ0,1
• Components of ρ include default premiums and term premiums
• Changes in ρ for long term assets relative to short term assets (i.e., a decline in
the term premium) will affect shape of the yield curve.
• See an interesting discussion by Ben Bernanke on the shape of yield curves:
http://www.federalreserve.gov/boarddocs/Speeches/2006/20060320/default.htm
32
Flat or Inverted Yield Curves
• There is no reason that yield curves need to slope upwards. Expected future
short term rates could be the same or lower than current short term rates. This
would imply that current long rates will be the same or lower than current short
rates.
• This will lead to flat yield curves (current short rates = current long rates) or
inverted yield curves (current short rates > current long rates).
• This possibility could exist in equilibrium! This will occur if inflation is
expected to decline over time (or if deflation is predicted), if future
expectations of real interest rates are lower than current real interest rates,
and if risk premiums in the future are thought to decline.
• Key: Some people assume that a flat or inverted yield curve means that the
economy will be entering a recession! This is not always true. But, demand
side recessions cause both r and expected inflation to fall.
33
Current Yield Curve for U.S. Treasuries (12/1/09)
3.5
3
2.5
2
1.5
1
0.5
0
34
Other Flattening of the Yield Curve: Micro Explanations
• One component of the term premium: Uncertainty in the future
– If investors are risk averse and the government is risk neutral, an
equilibrium could exist where the government will compensate borrowers
for holding longer term assets.
– A decline in uncertainty (perhaps due to the “Great Moderation”) could
flatten yield curves relative to historical standards.
• A second component of the term premium: Liquidity premium
– If short term assets are more liquid than long term assets (or demand for
short term assets is relatively higher than long term assets), a risk premium
will exist.
– An increase in the demand for long term U.S. assets (perhaps by foreign
35
investors) could cause the yield curve to flatten.
Current “10”- “2” Year Treasury (Through 2/09)
36