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The Luxembourg Wealth Study : enhancing
comparative research on household finance
Rome, 6th July 2007
Do the elderly reduce housing equity?
An international comparison
Maria Concetta Chiuri* and Tullio Jappelli**
* Università di Bari, CSEF and CHILD
** Università di Napoli Federico II, CSEF and CEPR
1
Outline
 Motivations
Main contribution of our paper
The evidence to date
The international dataset
Estimating ownership trajectories
Explaining international differences
in ownership trajectories
2
Motivation 1 - Policy




o
Population aging makes of clear policy interest
understanding the determinants of decisions
over:
how much to save
how to save
should wealth be annuitized, … etc.
as people get older.
Real estate is the largest component of total
wealth (more than 70% of tot. wealth)
3
Motivation 2 - Theory



Life Cycle Hypothesis (LCH) predicts
that with perfect markets selfish
individuals run down their wealth in
order to smooth consumption over
their life-cycle
from owning to renting or downsizing.
Bequest motives
Housing as a source of consumption
itself
4
Main contribution of our paper

A systematic international comparison of
age-trajectories of home-ownership
17 OECD countries, 59 national surveys,
years 1974-2000, 300.000 obs.

Empirical test on whether they are
explained by differences in financial
markets, institutions and public policy.
5
The evidence to date -1






US
Feinstein and McFadden (1989) use PSID and find
transition from owning to renting of <0.3% per year.
Venti and Wise (2002; 2004) HRRS, SIPP, AHDAOO find
1.76%; but about 8% for those with precipitating shocks;
they do not depend on h/h composition. Cohort effects are
relevant.
Fisher, Johnson, Marchand, Smeeding and Torrey
(2007) evidence from CEX that the elderly prefer to
stay in their home.
Canada
Crossley and Ostrovsky (2003) use three Canadian
surveys and find an annual decline of 0.6% from age 55
to 80.
6
The evidence to date - 2




UK
Ermisch and Jenkins(1999) use five waves
of BHPS and find only rare residential
mobility.
Germany
Börsch-Supan (1994) compare data from
Germany and the US and find that the
decline is similar in the two countries.
7
Summing up – previous evidence

Decumulation, but slow

Importance of cohort effects
8
Table 1- The international dataset: the LIS
project
Country
Survey and years available
Australia
Australian Inc. and Hous. Costs Survey: 1981
Austria
Micro-census: 1987, 1995; ECHP : 1997
Belgium
Panel S. of CSP: 1985, 1988, 1992, 1997; Panel S. of
Belgium H/h: 2000
Canada
S. Consumer Fin.: 1975, 1981, 1987, 1991, 1994,
1997; S. of Lab. and Income Dyn. 2000
Denmark
Income Tax S.:1987, 1992
Finland
Income Distribution S.: 1995, 2000
France
Household Budget S.: 1984, 1989, 1994
Germany
GSoEP : 1984, 1989, 1994, 2000
Ireland
ESRI Survey: 1987; ECHP: 1994, 1996, 2000
Italy
SHIW: 1986, 1991, 1993, 1995, 1998, 2000
Luxembourg
Lux. Socio Econ. Panel S.: 1985, 1997, 2000
9
-continued
Netherlands
Add. Enq. on Use of Pub. Serv.: 1983, 1987. SoEP:
Norway
Income and Prop. Distrib. S.: 1986
Spain
Exp. and Inc. S.: 1990
Sweden
Inc. Distrib. S.: 1992, 1995
UK
FamEx S.:1991, 1995; Fam. Res. S.: 1999
US
Census: 1974, 1979, 1986, 1991, 1994, 1997,
All countries
59 surveys; 300,967 women aged 50-80.
1991, 1994, 1999
2000
10
Sample selection

Definition of h/h heads is biased:
Individuals rather than h/hs
e.g. if they move in their children’s place,
treated as renters.

Mortality rate and potential entrance in a
nursing home:
women aged 50-80.
11
Table 2- Sample composition by age-groups
Country
Age 51-60
Age 61-70
Age 71-80
H/hs
Indiv.s
H/hs
Indiv.s
H/hs
Indiv.s
Australia
41.45
39.13
33.91
33.84
24.65
27.04
Austria
42.27
38.74
34.45
34.41
23.28
26.85
Belgium
45.54
44.87
34.76
34.49
19.70
20.64
Canada
43.59
41.95
30.20
29.67
26.21
28.38
Denmark
41.62
40.07
33.76
33.16
24.62
26.77
Finland
52.84
50.99
32.23
31.90
14.93
17.11
France
45.32
43.48
34.00
34.14
20.68
22.38
Germany
48.55
45.54
33.26
33.74
18.20
20.72
Ireland
45.59
44.72
32.87
32.09
21.53
23.19
Italy
46.52
44.89
33.80
33.85
19.67
21.26
Luxemb.
47.63
45.66
31.56
30.91
20.81
23.43
Netherl.
44.44
42.56
34.59
35.22
20.97
22.22
Norway
44.75
44.20
35.47
34.65
19.78
21.15
Spain
46.67
42.79
33.89
35.45
19.44
21.76
Sweden
47.29
45.94
28.61
27.96
24.10
26.10
UK
41.81
40.47
33.92
33.56
24.27
25.97
US
46.52
44.90
31.37
31.33
22.12
23.77
12
Further data treatment


Comparability in educational
attainment: ISCED classification
Survey design can vary over time
13
Table 3- Ownership by age-group (individuals)
Country
Age 51-60
Age 61-70
Age 71-80
Australia
82.16
81.02
71.76
Austria
67.04
60.69
47.16
Belgium
77.60
74.89
65.33
Canada
78.62
73.73
58.98
Denmark
65.40
54.02
43.65
Finland
83.54
75.10
61.62
France
69.27
67.56
55.11
Germany
49.62
50.62
41.44
Ireland
89.93
87.82
78.24
Italy
69.74
64.36
50.02
Luxemburg
79.23
71.89
57.90
Netherlands
44.92
33.41
22.67
Norway
67.21
55.93
39.11
Spain
80.02
74.32
57.30
Sweden
75.39
69.12
53.32
United Kingdom
75.93
67.08
55.58
United States
76.52
76.92
72.03
14
Cross-sectional vs. cohort adj. profiles


In a cross-section individuals belong
to different generations.
Repetead cross-sections allow to
track cohorts over time.
Avg. home-ownership rates for 30
age groups (from age 51-80).
15
Estimating ownership trajectories -1

The restricted model:
H a,b,c    f (a)  X a,b,c   b   c   a,b,c
where:
f(a) is a common third order polynomial of age
X= educ, marital and work status
b=common cohort effect
γ=country fixed eff.

[1]
Model [1] is estimated with WLS using a robust
Var matrix to control for neighborhood effects.
16
Table 4- Regressions for homeownership (N=1595)
Age
Age2
Age3
No cohort
effects
With cohort effects
0.038
0.078
0.104
(0.025)
(0.024)**
(0.025)**
-0.047
-0.046
-0.037
(0.018)*
(0.018)**
(0.018)*
0.003
0.003
-0.000
(0.004)
(0.004)
(0.004)
0.004
0.005
Year of birth
(0.000)**
Married
With cohort effects
and demographics
(0.000)**
0.041
(0.017)*
High school and college
-0.032
degrees
(0.022)
Employed
0.071
(0.017)**
Country dummies
yes
yes
yes
R-squared
0.78
0.80
0.81
17
Figure 1. The cross-sectional and cohort-adjusted profile of
.4
.5
.6
.7
.8
homeownership (all countries)
50
60
Cross-sectional profile
70
80
Cohort-adjusted profile
18
Estimating ownership trajectories -2


The assumption that age and cohort effects are the
same in all countries is rather restrictive (an F-test
rejected the null at 1 percent level).
A more general model for each single country:
H a,b    f (age)   b   a,b
where:
f(age) is a third-order polynomial in age.
b=cohort effect

[2]
We plot the difference in cohort-adjusted ownership
trajectories between 4 age groups (age 61-65, age
66-70, age 71-75 and age 76-80).
19
Figure 2. The cross-sectional and cohort-adjusted profiles of
homeownership
Belgium
Canada
Denmark
Finland
France
Germany
Ireland
Italy
Luxembourg
Netherlands
Sweden
.2 .4 .6 .8
1
.2 .4 .6 .8
1
.2 .4 .6 .8
1
Austria
50
70
80
50
60
70
80
US
.2 .4 .6 .8
1
UK
60
50
60
70
80
50
60
70
Cross-sectional profile
80
Cohort-adjusted profile
20
Figure 3. Change in ownership: from age-group 61-65 to 66-70
Austria
Belgium
Canada
Denmark
Finland
France
Germany
Ireland
Italy
Luxembourg
Netherlands
Sweden
UK
US
-.08
-.06
-.04
-.02
Change in cohort adjusted profile
0
.02
21
Figure 4. Change in ownership: from age-group 66-70 to 71-75
Austria
Belgium
Canada
Denmark
Finland
France
Germany
Ireland
Italy
Luxembourg
Netherlands
Sweden
UK
US
-.08
-.06
-.04
-.02
Change in cohort adjusted profile
0
22
Figure 5. Change in ownership: from age-group 71-75 to 76-80
Austria
Belgium
Canada
Denmark
Finland
France
Germany
Ireland
Italy
Luxembourg
Netherlands
Sweden
UK
US
-.08
-.06
-.04
-.02
Change in cohort adjusted profile
0
23
Compare with previous findings



Negative values in all contries
(after age 70)
Large differences across countries
Can we trace such differences to
country characteristics?
24
Explaining international differences
in ownership trajectories
o

Characteristics of rental market, moving costs.
Wealth taxes, property taxes and transaction
costs

The generosity of Social Security systems
o
The local availability of long term care services
o
Financial markets development
25
Explaining international differences
in ownership trajectories



o
The availability of financial instruments
which help house-rich but cash poor old
people to release housing equity:
Reverse mortgages
Mortgage equity withdrawal (trading-down,
over-mortgaging, re-mortgaging or secondmortgage)
Regulation in financial mkt difficult to
distinguish from other economy-wide
regulation
26
Table 5 - Index of mortgage market and economy-wide regulation, property
taxes and no. of beds in nursing homes: international comparisons
Index of
mortgage market
regulation
Index of economy
wide regulation
Property taxes to
GDP ratio
Number of beds in
nursing homes
Australia
.1
.30
.027
4.8
Austria
.9
.37
.006
1.7
Belgium
.9
.50
.013
2.9
Canada
.5
.41
.037
12.2
Denmark
.3
.19
.017
5.1
Finland
.5
.08
.011
4.3
France
.7
.60
.024
1.3
Germany
.7
.39
.01
8.6
Ireland
.1
.06
.016
6.9
Italy
.9
.75
.023
2.7
Luxembourg
.3
.036
5.9
Netherlands
.5
.08
.019
3.8
Norway
.3
.34
.011
9.1
Spain
.5
.42
.02
0.3
Sweden
.3
.43
.02
5.4
UK
.1
.0
.038
3.1
US
.3
.09
.032
5.4 27


The index of mortgage market regulation is taken
from Tsatsaronis and Zhu (2004). The score adds one
point for fulfilling each of the following five criteria: (i)
Mortgage rate arrangement are primarily extended on
the basis of fixed rate contracts; (ii) Mortgage equity
withdrawals is absent or limited; (iii) The loan-to-value
ratio does not exceed 75 percent, (iv) Valuation
methods of property is based on historical values,
rather than based on market values (v) Mortgage
backed securitization is absent or limited. The index is
then normalized to one.
The index of economy wide regulation is taken from
Kaufman, Kraay and Zoldo Lobaton (1999). The index
is a very wide indicator of the degree of economic
regulation covering many different regulatory areas
(state control, barriers to entrepreneurship,
administrative regulations, tariff and non-tariff barriers,
etc.) aggregated through factor analysis.
28
0
Figure 6. Change in ownership and mortgage market regulation
Netherlands
-.02
UK
Luxembourg
Ireland
-.04
Denmark
US
Sweden
Austria
Germany
-.08
-.06
France
Italy
Belgium
Canada
-.1
Finland
0
.1
.2
.3
.4
.5
.6
.7
.8
.9
1
Index of mortgage market regulation
Note. Cohort-adjusted change in ownership between age 71-75
and age 76-80.
29
0
Figure 7. Change in ownership and economy-wide regulation
Netherlands
-.02
UK
Ireland
Denmark
US
-.04
Sweden
Austria
Germany
-.06
Italy
France
-.08
Belgium
Canada
-.1
Finland
0
.1
.2
.3
.4
.5
.6
.7
.8
Index of economy-wide regulation
Note. Cohort-adjusted change in ownership between age 71-75
and age 76-80.
30
Table 6 Regressions for change in ownership
(1)
Index of mortgage
market regulation
(2)
(3)
(4)
(5)
-0.045
-0.048
(0.018)**
(0.024)*
Index of economywide regulation
(6)
-0.063
-0.060
(0.016)***
(0.016)***
Property tax to GDP
ratio
1.006
0.096
0.187
(0.730)
(0.641)
(0.416)
0.003
-0.001
-0.001
(0.003)
(0.003)
(0.002)
Number of beds in
nursing homes
Ownership in age
-0.020
-0.011
-0.036
-0.007
-0.029
-0.019
group 71-75
(0.036)
(0.028)
(0.054)
(0.050)
(0.035)
(0.026)
0.003
-0.008
-0.032
-0.042
0.016
-0.003
(0.030)
(0.020)
(0.039)
(0.042)
(0.041)
(0.024)
14
13
14
13
13
12
0.36
0.61
0.15
0.06
0.49
0.72
Constant
Observations
R-squared
31
Sensitivity analysis

Lagged ownership

Overall ownership rate (proxy for thin
rental mkt)

Property vs. transaction taxes

Social security income replacement rate

Price to income ratio
32
Conclusion





We estimated the home-ownership rate for the
elderly using data from 17 OECD countries.
The analysis at the individual level
Controlling for cohort effects, the ownership rate
falls after age 70; after age 75 falls at 1% per year.
Differences across countries are highly explained by
the degree of morgage mkt regulation and by the
economy-wide regulation.
Credit market imperfections are an explanatory
factor for international differences in the aggregate
saving rate.
33