Housing, Credit and Consumer
Spending
John Muellbauer, Nuffield College, Oxford
Conference
‘The Macroeconomics of Housing Markets’
Banque de France, Paris, Dec 3-4 2009
1. Introduction: Implications of some
evidence-based macro research
1. Introduction: institutional diversity.
2. Aggregate UK consumption evidence for role of
expectations vs. collateral, wealth,
unemployment etc.
3. Aggregate evidence (UK, US, Japan) for failure
of Euler equation.
4. Japan is very different.
5. US evidence for solved out consumption.
6. Systems method for AUS with common latent
variable.
Co-authors





Janine Aron, CSAE, University of
Oxford
John Duca, Federal Reserve Bank
of Dallas and Southern Methodist
University
Keiko Murata, Tokyo Metropolitan
University
Anthony Murphy, Hertford
College, Oxford
David Williams, New College,
Oxford
Motivation
The global economic crisis of 2008-9
originated in a credit crisis.
Core to a credit crisis is asymmetric
information between lenders and
borrowers.
The household credit channel played an
important part in the preceding boom, as
well as in the crisis which began in the
sub-prime mortgage market.
4
Figure 1: The Channels of Transmission
of the Mortgage and Housing Crisis
Mortgage and
Housing Crisis
Lower Demand
for Housing
Less Home
Construction
Lower Capital of
Financial Firms
↓Home Prices &
Wealth, Slower
Consumption
↑ Counter-Party
Risk, Money &
Bond Mkts Hit
Slower
GDP Growth
Credit Standards
Tightened
on All Loans
12
5
Financial accelerator neglected



by DSGE models popular with central
banks and with main-stream macro
economists.
-even with ‘New Keynesian’ frictions,
mainly price stickiness and adjustment
costs.
Micro assumptions usually ignored
asymmetric information revolution of
1970s and 1980s for which George
Akerlof, Michael Spence and Joe Stiglitz
shared the 2001 Nobel Prize in economics.
6
Don Kohn, Vice Chair FRB, Speech
Nov 12, 2008

“The recent experience indicates that we did
not fully appreciate how financial innovation
interacted with the channels of credit to
affect real economic activity-both as credit
and activity expanded and as they have
contracted. In this regard, the macroeconomic
models that have been used by central banks to
inform their monetary policy decisions are clearly
inadequate. These models incorporate few, if
any, complex relationships among financial
institutions or the financial-accelerator
effects and other credit interactions that are
now causing stresses in financial markets to spill
over to the real economy”.
7
No model currently fully captures
linkages and feedbacks of financial acc



Hence work is needed on the individual
elements of such a model without, initially
at least, a general equilibrium solution.
This paper presents estimates of
consumption functions for four major
economies in the tradition of Modigliani
and Brumberg (1954, 1980) and Ando
and Modigliani (1963) but more explicitly
incorporating income expectations,
uncertainty and credit channel influences,
the latter differing across countries and
over time.
In Cameron et al (2006), Duca et al
(2009) we explore credit, expectations
etc. in house price determination.
8
SOLVED OUT CONSUMPTION FUNCTION




The Friedman-Ando-Modigliani consumption
function requires an income forecasting model
to generate permanent non-property income.
Unlike Euler equation, it does not throw away
long-run information on income and assets.
Evidence by Campbell-Mankiw 1989, 1991 and
us is of huge rejection of martingale implication
of Euler eq – ‘excess sensitivity’ rules.
Confirmed by our evidence on UK, US, AUS,
Japan.
9
Log-linearizing the consumption
function

The basic aggregate life-cycle/permanent
income consumption function has the form:
ct   * At 1  ytP

Dividing by yt and a little manipulation
shows that this implies:
ct / yt  [( * /  ) At 1 / yt  1  ( ytP  yt ) / yt ]
Log-linearization cont’d

RHS of this eq. has the form 1+ x, where x is usually a
fairly small number. Then take logs, using the fact that
log (1+x) ≈x, (2nd order approx. would use x-0.5x2) and
P
log( ytP / yt ) approx  ( yt  yt ) / yt .We then see that
log ct   0  log yt  At 1 / yt  log( ytP / yt )
where

   * /
and
 0  log 
The last term captures income growth expectations. The
log formulation is good for exponentially trending macro
data, since residuals are likely to be homoscedastic.
Habits or adj costs implies partial
adjustment
 log ct   (0   At 1 / yt  log( ytP / yt )  log yt  log ct 1 )
Solved out approach, relaxing
parameter restrictions


Robust to limited rationality – just need
household common sense about the budget
constraint and a concern about sustaining
consumption.
Does not require strong assumptions of
typical DSGE models: rational expectations
common to all agents, representative agent,
efficient (financial and credit!) markets, no
asymmetric information, no agency problems.
13
But Friedman-Ando-Modigliani model
needs modification for housing and credit


Classical life-cycle theory suggests the
‘housing wealth effect’ on aggregate
consumption (including imputed housing)
is small or negative.
The credit channel is crucial to explain a
positive impact of house prices on
consumption via 2 mechanisms:


Down-payment constraint affecting mainly
consumption/income.
Ability to borrow against home equity,
affecting mpc out of housing collateral.
14
Implications….


Poorly developed credit markets (e.g.
Italy’s) imply aggregate consumption falls
when house prices rise. Future first time
buyers (and renters) save more for a
deposit (or higher future rents), and
home-owners have limited access to
home equity loans.
Deep mortgage markets imply the
opposite. A lower ratio of down-payments
to value applies, so future first time
buyers will save little and not respond
much to higher house prices. Higher
collateral values boost spending.
15
Encompassing Friedman-Ando-Modigliani
Consumption Function and Credit Channel:

Many studies of housing wealth effects suffer
from poor controls, but not this one:
 log ct   ( 0t  1t rt   2tt   3t Et log( yperm / y )
 1 NLAt 1 / Yt   2 IFAt 1 / Yt
 3t HAt 1 / Yt  log yt  log ct 1 )
 1t  log yt   2t nrt ( DBt 1 / Yt )   t
16
Encompassing the Friedman-Ando-Modigliani
Consumption Function:

c is real per capita consumption, r is the real
interest rate, θ is an uncertainty indicator, and y
is real per capita non-property income;
k s 1
k s 1
log(
yperm
/
y
)

E
(


log
y
/

)  log yt

t
t
t
1
t s
1 
measures income growth expectations;

NLA/y is the ratio of liquid assets minus debt to
non-property income, IFA/y is the ratio of illiquid
financial assets to non-property income, HA/y is
the ratio of housing wealth to non-property
17
income;
Encompassing the Friedman-Ando-Modigliani
Consumption Function:


∆nrt.(DBt-1/Yt), where nr is the
nominal interest rate on debt and DB
is debt, measures the cash flow
impact on borrowers of changes in
nominal rates (Jackman and Sutton,
1982);
the speed of adjustment is β and the
γ parameters measure the mpcs for
each of the three types of assets.
18
The credit channel features through:




the different mpcs for net liquid assets,
illiquid financial assets (larger for net
liquid, Otsuka, 2006) and for housing;
through the cash flow effect for
borrowers;
by the possibility of parameter shifts with
credit market liberalisation, index CCI.
CCI is modelled as latent variable in
model of 10 credit indicators with rich
controls, Fernandez-Corugedo and
Muellbauer (BOE, wp 2006)
19
Credit market liberalisation should raise:





the intercept α0, implying a higher level of
log(c/y)
the real interest rate coefficient, α1
the impact of expected income growth, α3
the mpc for housing collateral, γ3 .
But lower the cash flow impact of the change
in the nominal rate, β2.
20
2. UK application: first, income
forecasting equation
We use average of naïve and
sophisticated: naïve has trend reversion,
change in short term interest rate, and
log real house price x post Thatcher
dummy.
(incl. real hp avoids charge that housing
collateral effect on consumption is
omitted income expectations).
Sophisticated model also includes tax rate,
government deficit/GDPxPostThatcher
dummy, stock market, union density,
credit growth, real oil prices.

UK Empirical Evidence on Consumption
1967-2005



The CCI (credit conditions) level effect is
important: in partial equilibrium, it lowers
the current household saving rate by 6.5
percentage points, compared to 1980.
The housing collateral effect on
consumption rises with CCI, and appears
to be close to zero before 1980, Figure 2.
The cash flow impact of nominal rate rises
weakens with easier access to credit.
22
UK Empirical Evidence 1967-2005

The marginal propensities to consume:
 for liquid assets is 0.11 (close to micro
evidence by Gross & Souleles, 2002);
 for illiquid financial wealth is around
0.02, Figure 3;
 for housing wealth is 0.032 from 2001
(at the CCI maximum).
Liquidity effect helps clarify role of money
– great confusion reigns currently!

The t-ratios for the mpcs are at least 5.
23
UK Empirical Evidence 1967-2005



Co-integration analysis suggests that,
given CCI, there is a single vector linking
log(c/y) and the three ratios of assets to
income.
Parameter stability is excellent – recursive
betas.
Simpler models, e.g. with single net
worth, omitting CCI, omitting change in
unemployment rate and in nominal r, are
far worse.
24
Estimated UK consumption function
1967Q1-2005Q4
Dependent variable =  ln c
ln y  ln c1
Credit conditions index CCI
Net liquid assets/income
(1)
(2)
(3)
(4)
0.16
(4.9)
0.23
(6.3)
0.31
(8.5)
0.33
(8.9)
0.020
(3.5)
0.038
(5.6)
0.0061
(4.7)
0.0036
(4.8)
0.026
(4,3)
0.0076
(5.9)
0.033
(5.6)
0.0071
(5.1)
0.0111
(5.7)
Illiquid financial assets/income
Ditto
Housing assets/income
Ditto
Ditto
-
-
0.21
(4.9)
0.18
(4.4)
0.22
(5.5)
Expected income growth and CCI
interaction
-
-
-
Real mortgage interest rate
-
-
Change in unemployment rate  4ur
-
-
Debt/income and Δ4 nominal interest
rate interaction
-
Debt/income, Δ4 nom. interest rate and
CCI interaction
-
Housing assets/income and CCI
interaction
Expected income growth
-
-0.03
(1.4)
-0.56
(7.8)
0.0106
(6.3)
0.10
(2.4)
0.15
(1.6)
-0.04
(1.5)
-0.64
(8.6)
-
-0.0029
(3.8)
-0.0072
(3.1)
-
-
0.0057
(1.9)
-
Figure 2: Long-run contributions to log consumption/income of the credit conditions
index and its interaction with housing wealth/income.
log ratio
0.150
log (consumption/non-property income)
Credit conditions index (CCI)
Housing wealth/income x CCI
0.125
0.100
0.075
0.050
0.025
0.000
1970
1975
1980
1985
1990
1995
2000
2005
26
Figure 3: Long-run contributions to log consumption/income of net liquid assets/income
and illiquid financial assets/income.
log ratio
0.150
log (consumption/non-property income)
Illiquid assets (mov.av.)/income
Net liquid assets/income
0.125
0.100
0.075
0.050
0.025
0.000
1970
1975
1980
1985
1990
1995
2000
2005
27
Some policy implications






Model gives 3.5 times larger weight to debt
than to housing wealth so net housing wealth is
wrong concept for consumption fn. (see Fig 3).
In short run, hard to reduce debt while asset
prices and income are collapsing.
Credit crunch has direct and interaction effects.
Model made coming UK recession in 2008H2
obvious in summer 2008.
But mortgage rate reductions help
consumption.
Some evidence for partial ‘Ricardian’ effects in
UK means fiscal policy effects are limited.
Income growth expectations as the
driver of consumption vs. credit, asset
prices, uncertainty etc.





King, Pagano 1990 vs Muellbauer-Murphy
1990
What caused the fall in the UK personal
saving ratio in the 1980s?
Take perfect foresight view. Define
permanent non-prop income over 10 year
horizon. (assume historical growth rate
continues beyond 2007).
Plot log c/y against log yperm/y….
Cannot account for 1984/5 to 1988/9 rise
in c/y
Log (c/y) vs. log (yperm/y) with
discount rate 1.25% per quart.
Log (yperm/y) is close to fitted trend –
log y, hence easy to predict
Log (c/y) vs. log (yperm/y) with
discount rate 10% per quart.
Income growth expectations (perfect f.,
rational or ‘ols learning’) cannot alone
explain log consumption/income



Regression of log change in consumption
on lagged log c/y and income growth
expectations finds latter effect is not
significant, 1967-2005
Including lagged A/y, as in AndoModigliani (1963), gives sensible long run
solution (col 1). Our extended model is
even better (col 4).
Strong evidence against DSGE view that
asset prices are JUST proxy for expected
future growth. Frictions, inefficiencies,
non-RE matter.
Section 3: failure of Euler equation





Centrepiece of all DSGE models is consumption
Euler equation.
Hall (1978) established that consumption
growth should be unforecastable.
Most DSGE literature ignores inconvenient
truth: Campbell & Mankiw (1989, 1991) multicountry evidence on ‘excess sensitivity’ i.e.
forecastability, of consumption growth.
New evidence for UK, US and Japan of dramatic
rejection of Hall hypothesis, consistent with
failure of simple RE.
Supports less restrictive consumption model of
Sections 1 and 2.
Section 4. Japan is different: no credit
shifts, stable parameters for 1961-2006,
and...





Positive real interest rate effect on
consumption
Negative real land price (or physical
wealth/income) effects.
Net financial wealth: mpc≈0.06
Deposits + shares + pension wealth
- debts can be aggregated -- unlike
UK or US, where illiquid financial
assets have lower mpc.
Unlike UK and US, (liquid assets –
35
debt)/income failed to decline.
Ratios to income of household deposits, total debt and liquid assets
(Japan)
4.5
4
3.5
N et financialassets/incom e
D ebt(excl.uninc.bus)/incom e
D eposit/incom e
3
2.5
2
1.5
1
0.5
19
60
19
62
19
64
19
66
19
68
19
70
19
72
19
74
19
76
19
78
19
80
19
82
19
84
19
86
19
88
19
90
19
92
19
94
19
96
19
98
20
00
20
02
20
04
20
06
0
N ote:Incom e m eans non-property disposable incom e.
Theory suggests +’ve direct real r effect
on consumption…



If households have large share of
liquid assets in life-cycle wealth
And intertemporal elasticity of
substitution is low, i.e. consumers
are averse to consumption
fluctuations.
Likely to hold in Japan.
Model for Japan (with different income
uncertainty measure and annual data)

Income growth expectations
 BG 
 log yt 1    a1 log yt  a2Trend  a3Trend 73  a4  

0  GDP t 1
 a5  it  it 3   a6 logUSGDPt 1   t
2

Consumption
 log ct    b1  log yt  log ct 1   b2  log yt  b3 Et  log yt 1
 b4 ( Et  log yt 1 )( yt )  b5 rt  b6
NFAt 1
yt
 b7 log( pland / pc)t 1  et
38
Stability and other tests




The Japanese consumption equation
passes recursive stability tests.
The LR parameters obtained in the
consumption equations are not
statistically different from those obtained
in system cointegration analyses.
Weak exogeneity tests were accepted for
Δlog y and income volatility.
Results also supported by IV estimates.
39
Figure 11: Recursive stability tests for the equation, Table 2a, col. 4.
0.00
-0.05
-0.10
1990
0.6
0.4
0.4
0.2
2000
1990
2000
0.0
-2.5
-5.0
-7.5
0.6
0.4
0.2
1990
2000
1990
-0.01
0.025
-0.02
2000
2000
1990
2000
1990
2000
1990
2000
0.00150
0.00125
0.00100
-0.03
1990
2000
0.6
0.5
0.4
0.3
0.00
0.050
1990
1990
2000
0.01
0.00
-0.01
Note: order of variables is constant, logy-logc-1, log change in y, forecast income
growth, interaction between forecast income growth and income volatility, real
interest rate ,net financial assets-1/income, log real land price-1. The cumulative
sum of squared residuals and a recursive Chow-test for structural breaks are
shown last.
40
Long-run contribution to log consumption/income of real interest rate,
net financial assets/income and log real land price
Log (cons/non-prop income)
Log relative price of land
0.25
real interest rate
net financial assets (-1)/income
0.20
0.15
0.10
0.05
0.00
-0.05
-0.10
1960
1965
1970
1975
1980
1985
1990
1995
2000
2005
41
Policy implications
Japan’s ‘lost decade’ was partly due
to weak overall consumption
response to lower interest rate.
 US scare in 2002-4 about ‘US lost
decade’ could have been avoided if
special nature of Japan’s monetary
policy response had been
understood.
Could have avoided one of the causes
– too low US rates- of the recent
global crisis.

‘Ricardian’ effect is strong in Japan

Rise in govt debt/income lowered
growth rate of disposable income
and raised saving rate, contributing
to policy ineffectiveness.
5: US Results



We construct CCI back to 1966 from
Senior Loan Officer Survey response
on willingness to extend credit on
consumer installment loans.
Not ideal, since likely to miss some,
more specifically mortgage market
related financial innovations.
Important to ‘exogenize’ index to
remove some of the cyclical
economic conditions.
44
Figure 7: Credit Conditions Index for the US based on SLO
1.0
CCI from SLO Survey
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0.0
1970
1975
1980
1985
1990
1995
2000
2005
45
US income forecasting models, naïve and
sophisticated have big role for Michigan expected
fin. conditions

For
log( yperm / y )  E (  log y /   )  log y
k
t


t
t
1
s 1
k
t s
1
s 1
t
Naïve model with no trend reversion also driven
by recent av. growth rate, change in nominal Tbill rate, change in log real raw mat. price
index.
Sophisticated model has reversion to 1968 split
trend and labor productivity; change in T-bill
rate (as in UK and Japan); change in log real
raw mat. price index; change in unemployment
rate; govt. surplus/GDP (as in UK and Japan);
and per capita housing starts.
46
US Consumption Function 1966 Q3 2008 Q3




Traditional net worth version has very poor
fit, residual autocorrelation and a low
adjustment speed of 0.05.
Adding change in unemployment rate and
in nominal auto finance rate improves fit
and adj. speed 0.07.
Adding CCI (t=4.7) and splitting assets into
three categories greatly improves fit and
adj. speed to 0.26.
But mpc for housing collateral or wealth at
0.05 (t=3.5) exceeds mpc for net liquid
assets.
47
US Consumption Function (Cont’d)





Adding housing wealth dynamics doesn’t
change this.
(Liquid assets - debt)/income trends down
almost monotonically since 1980.
So correlation with ‘true’ CCI induces
downward bias.
Need to introduce specific mortgage credit
conditions indicator
Progress on systems approach where MCCI is
latent variable in consumption, mortgage,
equity withdrawal, refi equations, also lowers
est. housing collateral effect.
48
Implications for recent fiscal policy
discussion




Marty Feldstein and John Taylor wrongly
concluded that 2008 temp tax cut had no
effect on consumer spending.
With Blinder-Deaton temp tax adj. our
model has largest outlier in 13 years in
2008Q2, approx ¾% of consumption.
Back on track for 2008Q3.
2008Q2 would have been a lot worse w/o
the tax cut!
‘Ricardian’ effects weaker in US than
Japan or UK.
6. Further progress on systems…


In current work on Australia 1978-2008
with David Williams we model
consumption, mortgage stock, mortgage
equity withdrawal and hp jointly using
common spline function to pick up credit
liberalisation specific to the mortgage
market.
The first paper to obtain sensible long-run
solutions for hp and consumption in
Australia, and first to model AUS equity
withdrawal.
Mortgage credit conditions index as
common latent variable
0.6
Mortgage credit conditions index for Australia
0.5
0.4
0.3
0.2
0.1
1980
1985
1990
1995
2000
2005
Long-run solutions for AUS






Long–run coeff. on MCCI:
for log real hp is 1,
for log real mortgage stock is 2.3
(t=4.9)
for equity withdrawal/income 0.62
(t=5.0)
for cons/income 0.16 (t=2.6)
Speed of adj for cons function 0.31
(t=9.5)
Long-run solutions cont’d




Mpc for net liquid assets 0.17
(t=5.8)
illiquid financial assets 0.033
(t=2.5)
housing collateral 0 before 1978,
0.04 at max MCCI (t=2.8)
Coeff on log yperm 0.29 in 1978, 1
at MCCI max. (less with naïve
forecasting model)
Conclusions




The ‘housing wealth effect’ on consumer
expenditure works via the credit channel.
Evidence on Japan suggests no collateral
or H-wealth effect & little consumer credit
market liberalisation.
For US, collateral effect is larger than for
UK or AUS (tax subsidy, low interest rate
risk, walk-away default option)
There have been major shifts in behaviour
with credit market development: a fall in
the saving rate (given income, wealth
etc) and an increase in the housing
collateral effect on expenditure.
54
Conclusions (Cont’d)




Only part of a larger system, but highly
relevant for policy and short term
forecasting, given consumption is about
70% of GDP.
US and UK equations imply large rise in
household saving rates for 2008 Q32009Q2: fall in HW/Y, reduced credit
supply, fall in stock market, rise in
unemployment rate.
Other system feedbacks need modelling,
but mainly amplify direction of these
effects – though policy offset.
BOE is currently “up the creek without a
model” since BEQM misses most of this.
55