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n. 504 September 2013
ISSN: 0870-8541
The Impact of an Ageing Population on EconomicGrowth: An Exploratory Review of the Main
Mechanisms
Renuga Nagarajan 1,2
Aurora A.C. Teixeira 1,2,3
Sandra Silva 1,2
1 FEP-UP, School of Economics and Management, University of Porto2 CEF.UP, Research Center in Economics and Finance, University of Porto
3 INESC TEC and OBEGEF
1
The impact of an ageing population on economic growth: an exploratory review of the
main mechanisms
Renuga Nagarajan
CEF.UP, Faculdade de Economia, Universidade do Porto
Aurora A.C. Teixeira
CEF.UP, Faculdade de Economia, Universidade do Porto; INESC
Porto, OBEGEF
Sandra Silva
CEF.UP, Faculdade de Economia, Universidade do Porto
Abstract
Although a myriad of important theoretical and empirical contributions on ageing populations
exist, these contributions are diffuse and lack an integrated vision of the distinct mechanisms
through which ageing populations impact on economic growth. As such, in this paper we
survey the literature that provides insights on the ageing population and its effect on economic
growth. In particular, we sought to uncover the main mechanisms through which ageing
impacts on economic growth.
The literature review shows that the impact of ageing on the performance of countries is
intimately related to the mechanism elected. About 70% of the empirical studies that focused
on the ‘public social expenditure’ mechanism convey a negative impact of ageing on
economic performance, whereas the majority (60%) of empirical studies that focus on ‘human
capital’ fail to uncover any significant statistical relation between ageing and the economic
growth proxy and the positive impact is more closely related to the ‘consumption and saving
patterns’ mechanism. Estimation methodologies also seem to be associated with distinct
impacts of ageing on economic growth, with less sophisticated econometric methods (i.e.
OLS and panel) being most often associated with negative (cor)relations. The bulk of the
empirical evidence concerns developed countries (and the ‘public social expenditure’
mechanism), with most of the analysis indicating a negative and significant relation between
ageing and growth. Given that developed, developing and even the least developed countries
are/will be affected by the phenomenon of an ageing population, knowing the degree to which
the influence of ageing varies among countries (including developing and the least
developed), and through which mechanisms, is essential to specifying sound public policies.
Keywords: Ageing; economic growth; consumption and saving patterns; public expenditure;
human capital
2
1. Introduction
Even though longevity and lower mortality rates are considered major successes for medical
science (Dalgaard, 2012), the demographic change they convey is commonly taken as having
a negative influence on national economies (Mason and Lee, 2011).
Many developed countries are approaching an era of ageing populations due to an increase in
longevity, a decrease in mortality rates and a decrease in fertility rates (Harper and Leeson,
2009). The decline in population growth has been visible since the mid-1970s when the adult
working-age population in several countries outpaced child population (Mason and Lee,
2011).
According to the World Health Organization (WHO, 2012), the proportion of people aged 65
and above in Europe is predicted to increase from 14% in 2010 to 25% in 2050. Hence, it is
expected that, in the near future, the prime working age group will be smaller than the older
age group.
The involvement of women in the labour force is also considered to be negatively related to
the fertility rate (Becker et al., 1990). In developed countries more women have entered the
labour market. For instance, the growth rate of female employment in the Euro area (17
countries) increased from 1.3% in 1996 to 2.3% in 2007 (Eurostat 2012) and here having a
child became a choice for female employees (Alders and Broer, 2004). Since human capital
and the fertility rate are negatively correlated (Alders and Broer, 2004), the increasing trend
of women to be better educated generally leads to a decrease in the fertility rate. Productivity
shocks and the retirement of the baby boom generation reinforces the increase in the ageing
population (Alders and Broer, 2004). Underlying the issue of fertility, Alders and Broer
(2004) further argue that the current demographic transfer faced by developed countries is no
longer an exogenous shock since it is due to the increase of women capital in the labour
market, which has led to a decrease in the fertility rate. Given this critical situation, Alders
and Broer (2004) further state that the altruistic behaviour of married couples will be a key
factor in building the future human capital. Nonetheless, it is argued that the current financial
crisis is not helping to promote the necessary altruistic behaviour of couples.
Declining fertility leads to populations with many working age individuals and fewer children
to succeed them (Weil, 2006; Lee et al., 2011). For a highly developed country the ‘ideal’
fertility rate is considered to be associated with a 2.1 replacement level (Nimwegen and Erf,
2010). In 2011, for almost all European countries, the fertility rate was below this replacement
3
level (cf. Figure 1). In particular, the figures for Portugal, Spain, Italy, Austria and Greece are
far below that replacement rate. The average fertility rate for these five countries is below 1.5.
Figure 1: Fertility rates in European countries, 2000 – 2011
Source: Eurostat (2012).
It is important to note that a decrease in the fertility rate alone will not turn a country into an
ageing country; along with this, a lower mortality rate and increasing life expectancy have
played an important joint role as well (Dalgaard, 2005).
This structural ageing of the population has profound consequences on the economic growth
of countries. Most economists argue that a country with a higher proportion of the older age
group tends to be associated with lower productivity levels and savings and higher
government spending (Bloom et al., 2010; Mèrette and Georges 2009; Sharpe, 2011; Walder
and Döring, 2012). This demographic tendency also makes room for an increase in the age
dependency ratio, meaning that the smaller working age group will be obliged to care for the
older age group (Lindh, 2004).
Although there is a myriad of important theoretical and empirical contributions on the ageing
population, these contributions are diffuse and lack an integrated vision of the various
mechanisms through which an ageing population impacts on economic growth. Thus, the
main goal of this paper is to provide an in-depth survey of the literature on the interaction
mechanisms between population ageing and economic growth.
Our paper is structured as follows. In Section 2, we provide a general overview of the
literature on population ageing and economic growth, giving an account of the main
mechanisms through which this influence occurs. Section 3 details the empirical studies in the
area and Section 4 offers some concluding remarks.
1,00
1,20
1,40
1,60
1,80
2,00
2,20
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
Denmark Finland Austria Ireland Germany France
1,00
1,10
1,20
1,30
1,40
1,50
1,60
1,70
1,80
1,90
2,00
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
Greece Spain Portugal Italy
4
2. The impact of an ageing population on economic growth: main mechanisms
2.1. An overview of the interaction between ageing and growth
The inequality in age structure leads to demographic transition and can have a positive effect
on growth if the proportion of the active working age group is higher than the non-working
group (Lee et al., 2011). However, as the European Commission (EC) (2006) highlights, a
contrary situation is being delineated, featuring a relatively higher proportion of the non-
working group, especially retirees, in many developed countries. This phenomenon means
that most industrial countries are classified as ageing population countries (Weil, 2006).
According to Bloom et al. (2010), the current global life expectancy is 65 years and this is
projected to increase to 75 years by 2050. For example, the life expectancy of Japan has been
the highest in the world since 2000 (Weil, 2006; Lee et al., 2011). Moreover, since the growth
of current working group is higher than the future population growth, the future working
population group will be smaller than the retirees, and this is one of the causes of the ageing
population in Japan.
Most of the literature argues that there is a negative relationship between population ageing
and economic growth (Narciso, 2010; Bloom et al., 2010; Lisenkova et al., 2012; Walder and
Döring, 2012). Even so, some authors, such as Prettner (2012) and Lee et al. (2011), claim the
existence of a positive effect. According to Prettner (2012), older individuals tend to save
more and so there tend to be more resources available for investment, impacting positively on
growth. A longer life span will further enable investment in Research and Development
(R&D). Therefore, the rise in longevity will increase savings and the savings time span,
which will positively influence investment, particularly in R&D, which is consensually
recognized as the engine of economic growth (Aghion and Howitt, 1992).
As Figure 2 highlights, the increase in the ageing population via medical advances and the
less altruistic behaviour of couples affects economic growth mainly through three
mechanisms: consumption and saving patterns, public social expenditure, and human capital
(Bakshi and Chen, 1994; Tosun, 2003; Alders and Broer, 2004; Elmeskov, 2004; Lee et al.,
2007).
5
The next section looks at these mechanisms in more detail. It is important though to
acknowledge the existence of a reverse causality between these two phenomena - in other
words economic growth may also influence the determinants of an ageing population.1
Figure 2: Main mechanisms through which an ageing population impacts on economic growth
Source: Authors’ design
2.2. Consumption and saving patterns
Some authors (e.g., Hock and Weil 2012; Walder and Döring, 2012) content that the increase
in the ageing population will lead to a fall in consumption, which ultimately deprives growth.
The argument runs as follows: an increase in the elderly population tends to reduce the per
capita income of the three generations, child, working group and retiree, and this will mean a
net decrease in the total consumption of the family (Lee et al., 2007).
To Hock and Weil (2012) consumption patterns are affected by ageing through disposable
income. Indeed, the increase in the old age dependency ratio will reduce the disposable
1 Given that this paper focuses on the impact of ageing on growth, the important issue of reverse causality will not be developed. A few studies on the causes of an ageing population (e.g. Bloom and Williamson, 1998; Hodgson, 1988; Alders and Broer, 2004; Elgin and Tumen, 2010; Dalgaard et al., 2012). Alders and Broer (2004) and Elgin and Tumen (2010) argue that a country’s economic growth negatively affects its population growth and its fertility rate. Specifically, Alders and Broer (2004) show that the fertility rate tends to decline when there is a positive productivity shock - this shock increases the cost of having children and creates a substitution effect between children and the consumption of goods. Moreover, increasing returns on human capital will increase investment and raise labour force participation, inducing a decline in fertility rates since couples now choose to allocate their time resource between child bearing, investment in human capital and work; this means fewer children. The international financial and economic crisis also has an important impact on demographic variables. The significant increase in unemployment rates and the income reduction observed during the crisis is contributing to a reduction in the fertility rate, especially for developed countries, since families have a greater role in supporting children than the elderly (Weil, 2006; Sobotka et al., 2010).
6
income of the working population, resulting in a decrease in the fertility rate and further
reinforcing population ageing.
Private consumption has a considerable influence on demand (Walder and Döring, 2012).
Therefore, the demand for goods and services is crucial for defining both the production
structure and the labour market, which are directly influenced by the age composition of a
country’s population.
The saving rate decreases for retirees as saving becomes the source of their spending (Davies
and Robert III, 2006). Hence, the ageing population will increase the dependency ratio in a
family. An increase in the child dependency in a family will lead to a significant decline in the
per capita income of the child generation alone (Lee et al., 2007). Moreover, an increase in
the old age dependency will lead to a significant decline in both child and worker generations
(Lee et al., 2007). This means that, as already noted, the increase in the ageing population will
decrease the overall consumption of the family.
Focusing on changes of the composition of aggregate basket of consumption derived from
ageing, Mèrette and Georges (2009) claim that ageing population will prompt changes in
consumption patterns such as a higher demand for health services and a lower demand for
housing. Such changes in the demand for goods and services will definitely influence the
economic growth of a country.
2.3. Public social expenditure
Taxation is relied on as the major source of income for a government agency. Rise in the
ageing population will affect government revenue from taxes and increase government
spending, especially on health care, the pension system and other old age related benefits
(Tosun, 2003; Elmeskov, 2004).
On the one hand, taxes directly provoke an increasing deficit in the government budget. In
fact, strategies whereby government agencies raise taxes to accommodate pension and
medical expenses affect the disposable income of the working group, which tends to result in
a decline in the fertility rate (Hock and Weil, 2012). Consequently, this type of response will
further enhance the ageing problem. For instance, the ageing population in New Zealand
means that social expenditure as a percentage of gross domestic product (GDP) is predicted to
increase from 22.7% in 2001 to 31.0% in 2051 (Creedy and Scobie, 2002). As such,
population ageing tends to cause significant changes in government budget allocation.
According to Eiras and Niepelt (2012) and Lisenkova et al. (2012), population ageing will
7
increase government spending on social security against the allocation for education and
infrastructure investment, which ultimately impact (negatively) on economic growth.
2.4. Human capital
According to some authors, such as Bloom et al. (2010), the increase in the retirement age and
immigration will in fact help to overcome the decrease in the labour force. Other authors
claim that countries can sustain economic growth despite the ageing population problem. For
instance, Elgin and Tumen (2010) states that faced with a decline in human capital, the
economy will switch from traditional production (that uses young workers) to new human
capital oriented production (that uses old age workers). Therefore, in this line of
argumentation, an ageing population will affect neither the production nor the growth
dynamics. Furthermore, Elgin and Tumen (2012) also argue that modern economies rely more
on machines than labour force. Therefore, a fall in the labour force will have no effect on
productivity. According to the authors, labour can be replaced by machines. They believe that
this means that a decrease in the young working group has no effect on economic growth.
Lisenkova et al. (2012) have a contrasting view of this phenomenon, though. They find that
even though increasing the retirement age will help to overcome a decreasing labour market,
workers of different ages are not perfect substitutes and so there will definitely be a decline in
productivity per worker. Other authors also stress the negative impact of population ageing
and the associated decrease in a country’s stock of human capital (Narciso, 2010), with a
subsequent negative influence on economic growth. Accordingly, an ageing population will
decrease the labour force, which will then affect economic growth due to lower productivity
levels. Even though the higher participation of women in the labour force increases labour
productivity, this participation will further lower the fertility rates, which will eventually lead
back to the initial problem (Alders and Broer, 2004).
There is also the argument that, apart from the increase in the retirement age, higher
immigration is unable to help much with overcoming public spending due to this ageing
problem, as immigrants will also have rights under the pension and health care system
(Elmeskov, 2004). Despite the negative effect on human capital accumulation identified by
Lindh (2004), Ludwig et al. (2011) and other authors argue that, for the US economy,
increasing human capital investment will reduce the impact of an ageing population. The
endogenous human capital through formal schooling and on-the-job training programmes will
positively influence human capital technology (Ludwig et al. 2011). Hence in the case of the
US, Ludwig et al. (2011) report that when we allow for endogenous human capital
8
accumulation the welfare losses in terms of lifetime consumption increase only about 8.7%,
whereas when human capital is assumed as exogenous, these losses rise to 12.5% (assuming
that replacement rates to the pension system are constant).
3. Surveying the empirical studies assessing the impact of ageing on economic growth
Although high quality empirical research on the impact of an ageing population on countries’
economic growth does exist, (this latter often proxied by GDP growth rates) this literature is
still relatively scarce. Table 1 summarizes some of the most relevant studies in this area,
highlighting the main mechanisms through which ageing impacts on growth: consumption
and saving patterns, public social expenditure and human capital. Attention is paid to
assessing the possible distinct impact of ageing on economic growth depending on the
mechanism focused on, econometric estimation techniques used and countries analysed.
3.1. The effect of an ageing population through consumption and saving patterns
Few empirical studies have addressed the impact of ageing on growth through consumption
and saving patterns. The two studies summarised in Table 1 focused on the influence of an
ageing population on the economic performance of China and Taiwan. Even though Taiwan
and China had a common history in the past, the empirical analysis undertaken on these two
countries shows contrasting results. Li et al. (2012) showed that there is an increase in savings
and investment in China by an ageing population and this is expected to boost the economic
growth of the country. Whereas, in the case of Taiwan, Lee et al. (2007) found that the
increase in the ageing population will negatively affect the income per capita of families.
Analysing the impact of the old age dependency ratio on Chinese savings and investment
(controlled for other variables such as the working age population and population growth
rate), for the period 1985 to 2005, Li et al. (2012) demonstrate that ageing has a positive
effect on both savings and investment. The authors note that China’s imperfect social security
system (policies including family planning, child bearing, pension and marriage) is the reason
for the increase in savings among older people. The government’s one-child policy system
and Pay-As-You-Go (PAYG) pension plan make the current working group start saving for
their future expenses.
The statement that economic growth increases with the old age dependency ratio is further
borne out by estimation results. However, the authors failed to show a significant relationship
between the working age population and savings or investment rates. Finally, their results
show a negative impact of the population growth rate on either the savings rate or investment
9
rate. The authors stress that the increase in the number of children in China will result in
additional consumption needs and this will reduce people’s savings and investment capacity.
On the other hand, Lee et al. (2007) state that when a country faces demographic burdens due
to having a smaller working group and larger non-working group, the dependency ratio will
increase and this will reduce families’ per capita income. They analysed the impact of old age
dependency ratio on the per capita income of family members (child generations, worker
generations and old-age generations). In fact, when using the population dependency method
to compute the dependency ratio for Taiwan, Lee et al. (2007) introduced a new method
called ‘the family dependency ratio’. Using this, the authors computed the dependency ratio
as the number of pensioners per family to the number of workers per family. The main
reasons for using the family dependency ratio instead of the population dependency ratio
were: i) the population dependency ratio is less accurate in capturing the impact of the relative
number of working family members over the lifecycles of families; ii) the family dependency
structure is different among cohorts, whereas the population dependency structure has the
same cohorts. The model assumes that no saving or per capita consumption of each generation
is determined by an altruistic family utility function (Lee et al., 2007). Thus, the consumption
of each dependent generation is equal to that generation's labour income plus net family
transfers. The estimated results for the period 1951 – 2101 show that an increase in the old-
age dependency ratio will significantly reduce the per capita income of all three generations
(children, workers and elderly). The possible reason for the contrasting results is that the two
authors (Lee et al., 2007; Li et al., 2012) analysed the influence of ageing based on different
mechanisms: savings and income per capita and the variables were measured by Li et al.
(2012) through the total amount of savings and investment, whereas Lee et al. (2007)
measured the variables in per capita terms. If the authors had used the same method to
measure the variables they would have obtained similar results.
3.2. The effect of ageing on economic growth through public social expenditure
Ageing populations do affect public social expenditure in many ways. Empirical analysis has
been carried out to identify the influence of ageing populations through foreign direct
investment (FDI) (Davies and Robert III, 2006; Narciso, 2010), foreign portfolio investment
(FPI) (Narciso, 2010) and GDP per worker growth rate (Lindh et al. 2009).
Davies and Robert III (2006) and Narciso (2010) analysed the influence of an ageing
population on a country’s FDI and FPI (Davies and Robert III, 2006; Narciso, 2010). Overall,
10
Davies and Robert III, (2006) and Narciso (2010) show a significant negative correlation
between the old dependency ratio and FDI for the countries studied.
Davies and Robert III (2006) use the OLS method to test the determinants of US inbound and
outbound FDI for 55 countries for the period 1983-1998, whereas Narciso (2010) tested the
relation between both old-age dependency ratio and youth-age dependency ratio and FDI and
FPI in 8 home OECD countries, for the period 2001-2007. As is usual in the literature, Davies
and Robert III (2006) compute the dependency of the home country and host country by
dividing the old-age individuals and the population of young individuals. According to Davies
and Robert III (2006), FDI is negatively correlated with both the home-country dependency
ratio and the host-country dependency ratio. This means that an increase in the old-age
dependency ratio of either the home or host country will significantly reduce US FDI in
general. However, when the authors test this relationship separately for poor countries and
rich countries, different results emerge. Even though changes in the dependency ratio of rich
host countries still have a negative correlation with US FDI (outbound), the related changes of
rich home countries have no significant impact on inbound flows (Davies and Robert III
2006). For the estimation of poor countries alone, changes in the home countries’ dependency
ratio have a negative correlation with US FDI (inbound) and no significant estimated impact
on US FDI (outbound) exists relative to the changes in host countries. Narciso (2010) tests
two relationships: between old age dependency ratio and FDI, and between old age
dependency ratio and FPI, with a negative correlation emerging for both. Moreover, for the
youth dependency ratio, there is a positive correlation with FDI and FPI. Hence, both Davies
and Robert III (2006) and Narciso (2010) provide generally similar results. The impacts of
FDI and FPI due to an ageing population will consecutively affect the GDP growth of the
countries.
11
Table 1: S
tudies on the impact of an ageing populat
ion on economic perform
ance (…
)
Mechanism
S
ample
Tim
e Period
Methodology
Dependent (in case of econom
etric m
odel) / Endogenous (in case of
simulation) variable
Independent (in case of econom
etric model) /
Exogenous (in case of
simulation) variable
Effect
Author
Co
nsu
mp
tion
and
savings
Pattern
s
Ch
ina
19
85 –
2005
-Pan
el data.
-Gen
eralized M
ethod
o
f Mo
men
ts(GM
M)
Savin
gs
(total am
ou
nt)
Old
age dep
end
ency ratio
(o
ld age 65
and ab
ove)(1)
Po
sitive Li et al. (2
012
) In
vestmen
ts (to
tal amo
un
t) O
ld age d
epen
den
cy (age 6
5
and
above)( 2)
Po
sitive
Taiw
an
Po
pulation
Fo
recasting:
19
51 –
2101
. In
1998
: interview
ed
14
,031
hou
sehold
s and
52
,610
ind
ividuals.
-Overlap
pin
g fam
ilies (O
LF) m
od
el (usin
g in
tergeneratio
nal
fam
ilial effect).
- Ord
inary Le
ast S
qu
ares (OLS
) estim
ation
.
Per cap
ita inco
me o
f child
generatio
ns O
ld-age d
epen
den
cy ratio(3)
Negative
Lee et al. (2
007
) P
er capita in
com
e of w
orker
generatio
ns
Negative
Per cap
ita inco
me o
f old
-age gen
eration
s N
egative
Pu
blic so
cial exp
end
iture
US
inbou
nd an
d outbo
und
Fo
reign direct in
vestmen
t (F
DI) fo
r 55
coun
tries (e.g. G
erman
y, Brazil,
Au
stria, Ch
ina an
d etc.)
19
83 –
1998
OLS
meth
od
US
Fo
reign direct in
vestmen
t (FD
I) (In
boun
d) fo
r all coun
tries H
om
e cou
ntry d
epen
den
cy ratio
(4) N
egative
Davies an
d
Ro
bert III
(200
6)
US
FD
I (O
utbo
und
) for all co
untries
Ho
st coun
try dep
end
ency
ratio(5)
Negative
OLS
meth
od
FD
I (Inbo
und
) for th
e group
of rich
co
un
tries H
om
e cou
ntry d
epen
den
cy ratio
(6) N
o sign
ificant
relation
FD
I (Ou
tboun
d) fo
r the grou
p o
f rich
cou
ntries
Ho
st coun
try dep
end
ency
ratio(7)
Negative
OLS
meth
od
FD
I (Inbo
und
) for th
e group
of po
or
cou
ntries
Ho
me co
un
try dep
end
ency
ratio(8)
Negative
FD
I (Ou
tboun
d) fo
r the grou
p o
f po
or co
un
tries H
ost co
untry d
epen
den
cy ratio
(9) N
o sign
ificant
effect
8 sou
rce cou
ntry (OE
CD
). 3
8 h
ost co
untry (O
EC
D
and
non O
EC
D).
20
01 –
2007
Balan
ced p
anel d
ata (fixed
effects)
FD
I (Investm
ent o
f origin
country in
a d
estination
coun
try j) O
ld d
epen
den
cy ratio (age
65
and abo
ve) (10) N
egative N
arciso
(201
0)
Fo
reign po
rtfolio in
vestmen
t (FP
I) (In
vestmen
t of o
rigin cou
ntry in
a d
estination
coun
try j) O
ld d
epen
den
cy ratio (11) N
egative
OE
CD
cou
ntries
19
50 –
2004
Po
oled
Ord
inary L
east S
qu
ares (PO
LS)
meth
od
Gro
wth
rate of real G
DP
per w
orker
Age 5
0 –
64
(12) P
ositive
Lind
h et al.
(200
9)
EU
15 excep
t Luxe
mb
urg
G
row
th rate o
f real GD
P p
er wo
rker A
ge 50
– 6
4(13)
Po
sitive
OE
CD
cou
ntries
19
50 –
2004
Po
oled
Ord
inary L
east S
qu
ares (PO
LS)
meth
od
Gro
wth
rate of real G
DP
per w
orker
Age 6
5 an
d ab
ove
(12) N
egative
EU
14 (excep
t Luxe
mb
urg
in th
e EU
15)
Gro
wth
rate of real G
DP
per w
orker
Age 6
5 an
d ab
ove
(13) N
egative
12
(1
) W
orking a
ge pop
ula
tion grow
th ra
te (0); p
opu
lation
growth
rate (-); Lo
g jun
ior high
school en
rolmen
t (0
); log sen
ior high
school en
rolmen
t rate (0
); 5 yea
r lagg
ed log G
DP
(0); Log
FD
I sha
re (0); du
mm
y var
iab
les for time p
eriods
1990
– 1
995 (0
) ,1995
– 2
000 (0
), Period
2000
– 2
005
(0).
(2)
Log old a
ge d
epen
den
cy ratio (+
); workin
g age p
opu
lation gro
wth
rate (0
); popu
lation
growth
rate (-);
Log ju
nior h
igh sch
ool enrolm
ent (0
); log senior high
school en
rolmen
t rate (+
); 5 yea
r lag
ged log G
DP
(-); Log FD
I sha
re (0);
du
mm
y varia
bles for tim
e period
s 1990 –
1995
(0) ,1
995 –
2000
(0), P
eriod 2
000 –
2005
(0).
(3)
Ea
rnings of w
orkers (+); ea
rnin
gs of child
ren (+
); ea
rnin
gs of pen
sioners rela
tive to workers (+
); chi
ld dep
endency ra
tio (-); old a
ge dep
enden
cy ratio (
-); pop
ulation d
epen
dency ra
tio (-). (4
) H
ome d
epen
den
cy (-); Hom
e social secu
rity (-); Hom
e n
ationa
l savin
gs (-); Hom
e Investm
ent (0
); Hom
e GD
P (+
); Hom
e Skill (w
orkers skill level) (+
); Hom
e Trade C
ost (-); FX
(Excha
nge ra
te) (-); Distan
ce (-); T
rend
(0); R
ich
(deve
loped
countries).
(5)
Host d
epend
ency (+
); Host socia
l security (-); H
ost n
ational sa
vings (-); H
ost Investm
ent (-); H
ost GD
P (+
); Host S
kill (workers skill level) (+
); Host Trad
e Cost (0
); Host In
vestmen
t cost (-); FX
(Exch
ange ra
te) (+); D
istance (-);
Tren
d (0
); Rich (d
eveloped
countries) (-).
(6)
Hom
e dep
end
ency (0
); Hom
e social secu
rity (+); H
ome
nation
al sa
vings (+
); Hom
e Investm
ent (-); H
ome G
DP
(+); H
ome S
kill (workers skill leve
l) (+); H
ome Trad
e Cost (-); F
X (E
xchange ra
te) (-); Distan
ce (-); T
rend
(0).
(7)
Host d
epend
ency (-); H
ost social secu
rity (0); H
ost n
ational sa
vings (0
); Host In
vestmen
t (+); H
ost GD
P (+
); Host S
kill (wo
rkers skill. level) (0
); Host
Tra
de C
ost (-); Host In
vestmen
t cost (-); FX
(Exch
an
ge rate) (+
); Distance (-);
Tren
d (0
). (8
) H
ome d
epen
den
cy (-); Hom
e social secu
rity (-); Hom
e n
ationa
l savin
gs (-); Hom
e Investm
ent (-); H
ome G
DP
(+); H
ome S
kill (workers skill level) (+
); Hom
e Trade C
ost (-); FX
(Exch
ange ra
te) (0); D
istance (-)
; Tren
d (0
). (9
) H
ost dep
end
ency (+); H
ost social secu
rity (-); Host
na
tiona
l savin
gs (-); Host In
vestmen
t (0); H
ost GD
P (+
); Host S
kill (workers skill level) (+
); Ho
st Trade C
ost (0); H
ost Investm
ent cost (-); F
X (E
xcha
nge ra
te) (+); D
istance (-); T
rend
(0).
(10
) G
DP
in a
capita
l origin coun
try (+); G
DP
in a
capit
al d
estination
country (+
); Ma
rket capita
lization
leve
l of the ca
pita
l destina
tion coun
try (0); G
ross
capita
l forma
tion on
destin
ation cou
ntry (-); Na
tion
al p
olitical stab
ility on the
destin
ation country (0
); Econ
omic freed
om a
nd
prosperity in
the d
estination
country (0
); Old
age d
epen
den
cy ratio of th
e destin
ation cou
ntry (-); You
th age d
epend
ency ra
tio of the d
estination
country (+
); O
ld d
epend
ency ratio
forecast in 20
years’ tim
e of the origin
country (+
); You
th d
epend
ency ra
tio forecast in 20
years’ tim
e for the d
estination country(+
). (1
1)
GD
P in
a ca
pital origin
country (+
); GD
P in
a ca
pita
l destin
ation cou
ntry (+); M
arket cap
italiza
tion l
evel of th
e ca
pital d
estination
country (0
); Gross ca
pital form
ation
on d
estination
country (-); N
ati
ona
l politica
l stability on
the d
estination coun
try (0); E
conom
ic freedom
an
d p
rosperity in
the d
estination
country (0
); Old
age d
epen
den
cy ratio of th
e destin
ation cou
ntry (-); You
th age d
epend
ency ra
tio of the d
estination
country (+
); O
ld d
epend
ency ratio
forecast in 20
years’ tim
e of the origin
country (+
); You
th d
epend
ency ra
tio forecast in 20
years’ tim
e for the d
estination country(0
). (1
2)
Th
e inverse of th
e converg
ence term
(+); P
opu
lation sha
re of ag
e group
(15-29
) (0); P
opu
lation sh
are o
f age grou
p (30
– 4
9) (0
); Pop
ulation
share of a
ge g
roup
(50
– 64
) (+); P
opula
tion sha
re of ag
e group
(65
and
above) (-); a
verag
e
investm
ent sha
re (+); a
verage gro
wth
rate of th
e wo
rk force (-); initial leve
l of GD
P p
er worker (-).
(13
) T
he in
verse of th
e conve
rgence te
rm (0
); Popu
lation
share of a
ge grou
p (1
5-2
9) (0
); Pop
ulation
sha
re of a
ge group
(30
– 4
9) (0
); Pop
ulation
sha
re of age
grou
p (5
0 –
64) (+
); Pop
ulation
sha
re of ag
e group
(65
and
above) (-); a
verage
investm
ent sha
re(+); a
verage gro
wth
rate of th
e wor
k force (-); initial leve
l of GD
P p
er worker(0
). (1
4)
log cap
ital (+
);dum
my va
riab
les for age [20,2
5) (-), [25
,30) (0
), [30,35
) (+), [4
0 45) (0
), [45,50
) (0),[50
,55
) (-),[55,6
0)(-);w
omen
(-); Ge
rma
ns (0
); Ap
pren
ticeship
s (+); un
skilled (0
); high
skilled (0
); w
hite-colla
r (+); pa
rt time (+
); good
equ
ipm
ent (+); A
ge-d
ispersion (0
); Exp
ort (+);
nu
mb
er of workers (+
); East G
erma
ny (-);d
um
my va
riab
les for cohort [190
0,1930
) (0), [1
930,1
940) (0),
[1940
,195
0) (+
), [1960
,1970
) (0), [1970
,1980
) (-), [1
980,1
900) (-);
du
mm
y varia
bles for ten
ure [10
,20
) (0), [20,3
0) (+
), [30
,40)(0
), [40, 50
) (+).
(15
) log ca
pita
l (+);du
mm
y varia
bles for age [20
,25
) (0)
, [25,30
) (0), [3
0,35) (0
), [40 4
5) (0
), [45,5
0) (0), [5
0,55) (0
), [55,60
)(0); w
omen
(0); G
erma
ns (0
); A
pp
renticesh
ips (+
); un
skilled (-); h
igh skilled
(0
); wh
ite-collar (+
); part tim
e (0);
good eq
uip
ment (+
); Age
-disp
ersion (-); Exp
ort (+);
num
ber of w
orkers (0); E
ast Germ
an
y (-); constant (+
);dum
my va
riab
les for cohort [19
00,19
30) (0
), [1930
,1940
) (0), [19
40,19
50) (0
), [1960
,1970
) (0), [197
0,1980
) (-), [198
0,1900
) (-); dum
my va
riables for ten
ure [10
,20)
(0), [20
,30) (0
), [30,40)(0
), [40, 5
0) (0
). (1
6)
Log cap
ital (+
);dum
my va
riab
les for age [20
,25
) (0)
, [25,30
) (0), [3
0,35) (0
), [40 4
5) (0
), [45,5
0) (-), [50
,55
) (-), [55,60
)(-); wom
en (-); G
erm
an
s (0);
Ap
prenticesh
ips (+
); un
skilled (-); h
igh skilled
(0
); wh
ite-collar (+
); part tim
e (0);
good eq
uip
ment (+
); Age
-disp
ersion (-); Exp
ort (+);
num
ber of w
orkers (0); E
ast G
erma
ny (-); con
stant
(+);d
um
my va
riab
les for [1900
,1930
) (-),[1930,1
940)
(0), [19
40,19
50) (+
), [1960,19
70) (0
), [197
0,1980
) (0
), [1980
,1900) (-);
du
mm
y varia
bles for ten
ure [10
,20
) (0), [20,3
0) (0
), [3
0,40)(0
), [40, 50
) (0).
Mechanism
S
ample
Tim
e Period
Methodology
Dependent (in case of econom
etric m
odel) / Endogenous (in case of
simulation) variable
Independent (in case of econom
etric model) /
Exogenous (in case of
simulation) variable
Effect
Author
Hu
ma
n cap
ital
Germ
an
y 1
997 –
2005
-Dyna
mic G
eneralized
Methods of M
om
ents
(GM
M)
Ma
nufacturing (P
roductivity) A
ge [50 –
55) a
nd Age [55
-6
0) (labour productivity) (14)
No effect
Gö
bel an
d
Zw
ick (2
012
) S
ervices (Productivity)
Age [50
– 5
5) and A
ge [55-
60) (lab
our productivity) (15) N
o effect
Meta
l Working sectors (P
roductivity) A
ge [50 –
55) a
nd Age [55
-6
0) (labour productivity) (16)
No effect
Scotla
nd 2
006 –
2106
(Foreca
sting) O
LG m
odel.
Sim
ulation
Outp
ut per- p
erson W
ith age sp
ecific features. C
hanges in the
output is higher
Lisenkova
et a
l. (2012)
Outp
ut per- p
erson W
ithout age sp
ecific features. C
hanges in the
output low
er
13
Lindh et al. (2009) studied the trend between OECD and EU countries. The authors analyse
the influence of an ageing population on real GDP per worker growth rate in the OECD and
EU 15 countries (except Luxembourg). In order to minimize the endogeneity issues, instead
of GDP per capita, the authors considered GDP per worker has a dependent variable. They
conclude that for these countries changes in the population for the age 65 and above have a
significant negative impact on real GDP per worker growth rate. According to the authors,
when there is an escalation in the old age group (age 65 and above), the growth rate of GDP
per worker will decline. Therefore, the result confirmed that the demographic transition does
affect GDP growth.
3.3. The effect of an ageing population on human capital
If workers of different ages are not perfect substitutes, the productivity level of the particular
worker will be lower with an ageing population, considering their physical ability to actively
participate in the labour market (Lisenkova et al. 2012). Even though both Göbel and Zwick
(2012) and Lisenkova et al. (2012) agree that, in general, the impact of an ageing population
on labour productivity is negative, Göbel and Zwick (2012), based on an empirical study,
state that the level of this effect will differ according to the sectors analysed.
Göbel and Zwick (2012) looked at the differences in the age productivity profiles between the
metal manufacturing sector and the service sector in Germany, for the period 1997–2005.
Using the generalised method of moments (GMM) as an estimation tool, the authors obtained
results showing that for the labour age group at the age 55–60 there is no significant effect on
productivity in the metal manufacturing and service sectors. Hence, the study concludes that
an increase in the old-age group in Germany has no effect on the productivity in the two
analysed sectors. However, Lisenkova et al. (2012) explain that, in general, regardless of the
sector in focus, the age-specific effect will influence productivity in Scotland.
Lisenkova et al. (2012), setting out to see if the age specific features significantly influence
output productivity in Scotland, predict its output level for the period 2006 – 2106, based on a
simulation exercise. The results show that when age-specific features are not taken into
account changes in the output level are lower, whereas when age-specific effects are
considered, these changes will be higher. According to the authors, since the physical
strength of human beings declines as they get older so increasing the retirement age and
having more old-age labour will definitely negatively affect output productivity.
14
4. Some final remarks on the relation between ageing and economic growth
The demographic dividend through industrialization has improved the economic growth of
developed countries (Bloom and Williamson, 1998). Although government policy on fertility
control has benefited developed countries, the demographic dividend achievement did not last
forever. The unbalanced population structure has led to many developed countries being
christened ‘ageing countries’ (Bloom and Williamson, 1998). An ageing population and
economic growth are related, as extensively discussed above. The current ageing problem
faced by many developed countries is occurring, however, without any past history. Hence,
these ageing impacts might be considered a new experience for the world.
Our review of the literature has led us to conclude that an ageing population has affected
economic growth through three main mechanisms: consumption and saving patterns, public
expenditure, and human capital. This literature review shows that the impact of ageing on
countries’ performance is intimately related to the mechanism chosen. Indeed, about 70% of
the empirical studies that focused on ‘public social expenditure’ convey a negative impact of
ageing on economic performance, whereas the majority (60%) of empirical studies that focus
on human capital do not find any significant statistical relation between ageing and the
economic growth proxy, and the positive impact is much more related to the ‘consumption
and saving patterns’ mechanism (cf. Figure 2). In short, the mechanism seems to have a non-
trivial impact on the estimated relation between ageing and economic growth.
Figure 3: Estimated impact of ageing on economic growth by main mechanism
Note: The analysis was based on 26 econometric estimations reported in the studies surveyed and listed in Table 1. Source: Authors’ computations.
60.0
20.0
68.8
57.7
0.0
60.0
12.5
19.2
40.0
20.0 18.823.1
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Consumption and savings
patterns
Human capital Public social expenditures All
Positive
No effect
Negative
#26#16#5
#5
15
Estimation methodologies also seem to be associated with distinct impacts of ageing on
economic growth. Indeed, as Figure 4 shows, less sophisticated econometric methods (i.e.,
OLS and panel) are most often associated with negative (cor)relations, whereas overlapping
generation methods and the generalized method of moments (GMM) are more likely to
generate positive or no significant effects.
Figure 4: Estimated impact of ageing on economic growth by main methodologies of analysis
Note: The analysis was based on 26 econometric estimations reported in the studies surveyed and listed in Table 1. Source: Authors’ computations.
The evidence gathered helps little in assessing to what extent the impact of ageing on growth
varies according to the mechanisms and countries analysed. The bulk of the empirical
evidence concerns developed countries and the ‘public social expenditure’ mechanism, with
most of the analysis indicating a negative and significant relation between ageing and growth.
It is important, however, to acknowledge that developed, developing and even the least
developed countries are affected by the ageing population phenomenon. As Börsch et al.
(2002) state, ageing population patterns are similar in most countries; the only observable
difference concerns the timing of the situation. Furthermore, an ageing population’s influence
on economic growth has been labelled as ‘remarkable’, especially during the current financial
and economic crisis (Lee et al., 2011). Several economic studies (e.g. Creedy and Scobie,
2002; Alders and Broer, 2004; Weil, 2006; Sobotka et al., 2010) not only confirm the
existence of ageing populations all over the world, but also document and analyse the
mechanisms that influence economic growth, as well as proposing possible remedies to solve
the problem.
80.0
40.0
75.0
0.0 0.0
50.0
100.0
57.7
20.0
0.0
0.0
0.0
100.0 0.0
0.0
19.2
0.0
60.0
25.0
100.0
0.0
50.0
0.0
23.1
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
OLS method Pooled OLS Panel data Generalized
Method of
Moments(GMM)
Dynamic
Generalized
Methods of
Moments (GMM)
Overlaping
generation model
Simulation All
Positive
No effect
Negative
#26#10 #5 #4
#1
#3
#2
#1
16
Figure 5: Estimated impact of ageing on economic growth by main countries blocks analysed
Note: The analysis was based on 26 econometric estimations reported in the studies surveyed and listed in Table 1. Source: Authors’ computations.
The movement both developed and developing countries are going through, featuring a
convergence to the era of ageing populations, has its own consequences for economic growth
dynamics through the distinct mechanisms detailed above: consumption and saving patterns
(Fougère et al., 2009; Li et al., 2012; Walder and Döring, 2012), human capital (Elgin and
Tumen, 2010; Sharpe, 2011; Göbel and Zwick., 2012), and public social spending (Creedy
and Scobie, 2002; Tosun, 2003; Elmeskov, 2004; Hock and Weil, 2012).
Realizing the seriousness of the issues raised by ageing populations, policy makers are
desperate to find ways to tackle the issues. Policy implications such as the ‘Blue card’ system
introduced by European countries to encourage foreign immigration to overcome labour
shortages, increasing the retirement age to lower government expenditure, increasing the
working group’s income tax and social planning whereby couples are encouraged to have
more children are considered the major ones. However, for some reason, general policy plans
are not yet regarded as an effective way to solve the problem. Knowing the degree to which
the influence of ageing varies from country to country, and through which mechanisms, is
essential to specifying adequate policies.
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Editorial Board ([email protected])Download available at: http://wps.fep.up.pt/wplist.php
also in http://ideas.repec.org/PaperSeries.html
22