Download Ageing paranoia, its fictional basis and all too real costs

Ageing paranoia:
its fictional basis and
all too real costs
Jane O’Sullivan
Fenner Conference 2013 – Population, Resources and Climate Change.
AAS 10-11 October 2013
Ageing is the main excuse for
maintaining population growth
• Population growth is a policy variable (a choice).
• A significant shift in policy in the past 20 years:
• High fertility nations have reduced family planning.
• Low fertility nations have resisted stabilisation.
• A consequent resurgence in global population
growth.
Global population won’t peak unless nations
embrace stabilisation or descent.
Population Projections 2012 Revision
2012UNUN
Population Projections
18
World Population (billions)
16
14
12
10
8
6
4
2
0
1960
1980
2000
2020
Year
2040
2060
2080
2100
Population Projections 2010 and 2012
2012 UN
UN
Population Projections
18
High
15.8 16.6 billion
World Population (billions)
16
14
12
Medium
10.1 10.9 billion
10
8
Low
6.1 6.8 billion
6
4
2
0
1960
1980
2000
2020
Year
2040
2060
2080
2100
Population Projections 2010 and 2012
2012UNUN
Population Projections
Constant Fertility 28.6 billion
18
High
15.8 16.6 billion
World Population (billions)
16
14
12
Medium
10.1 10.9 billion
10
8
Low
6.1 6.8 billion
6
4
2
0
1960
1980
2000
2020
Year
2040
2060
2080
2100
UN Population Projections 2010 and 2012
Projections
are blind to carrying capacity
18
World Population (billions)
High
15.8 16.6 billion
Resource Constraints?
16
14
12
Medium
10.1 10.9 billion
10
8
Low
6.1 6.8 billion
6
4
2
0
1960
1980
2000
2020
2040
2060
2080
2100
YearEarth Support”: 7-12 billion is “the zone”
Joel Cohen “How Many People can the
“If most people would
2012prefer
Estimatea decline in birth rates to a rise in death rates, then they
Estimate a decline in fertility while time remains to realize that choice.”
should take actions2010
to support
Annual UNIncrement
of2010
Population
Population Projections
and 2012
Annual Increment of Population (millions)
120
Constant
Fertility
Projection
100
80
60
Recent estimates from
Population Reference Bureau
Medium
Projection
40
20
0
1990
2000
2010
Year
2020
2030
Press briefing upon publication of
UN’s “World Population Prospects:
The 2012 Revision”
“…Most of this increase is due to changes in our
estimates of current fertility for several high-fertility
countries …
“Our medium-variant projection continues to assume a
rapid fall in future levels of fertility for these countries.
We continue to calibrate the pace of future fertility
decline using the historical experience of countries that
underwent a major reduction of fertility levels after
1950, in an era of modern contraception.
The medium‐variant projection is thus an expression of
what should be possible …
“… [it] could require additional substantial efforts to
make it possible.”
John Wilmoth, Head of Population Division, UNDESA
Fertility reduction in response to
population-focused
family planning programs
8
TFR (births per woman)
7
6
5
Least developed countries
Less developed excl. China
Maldives
Iran
Viet Nam
Thailand
Mauritius
South Korea
4
3
2
1
0
1950
1960
1970
1980
1990
2000
2010
Year
Typical fertility reduction of 2-3 units per decade in the first two decades.
(UN projection assumes 1 unit per decade.)
UN Survey of Population Policy 2011
Population growth and Government opinion of it
Old age dependency and Govt concern
40
Japan
South Sudan
Jordan
4
Liberia
Niger
Germany
Italy
30
Angola
Burundi
Uganda
Eritrea
Greece
Sweden
Latvia
Portugal
Bulgaria
Austria
Croatia
Estonia
Belgium
France
Finland
Denmark
United
Kingdom
Spain
Switzerland
Hungary
Slovenia
Somalia
Singapore
Gabon
Israel
Sierra Leone
Solomon
Islands
Tajikistan
Guinea-Bissau
Oman
Luxembourg
2
Saudi Arabia
Bahamas
Maldives
Panama
Australia
Monaco
Lebanon
Ecuador
Mongolia
Cyprus
Spain
Canada
Cook Islands
CzechItaly
Republic
Palau
Slovenia
0
Benin
Malawi
Congo
Burkina Faso
Madagascar
Zambia
Rwanda
Senegal
Mauritania
Nigeria
Ethiopia
Kenya
Afghanistan
Mozambique
Togo
Cameroon
Comoros
Guinea
Belize
Ghana
Guatemala
Iraq
Yemen
Sudan
Vanuatu
Austria
Uruguay
Thailand
Slovakia
Portugal
Greece
TFYR Macedonia
Japan
Poland
Cuba
Hungary
Germany
Romania
Croatia
Armenia
Belarus
Georgia
Estonia
Ukraine
Costa
Rica
Swaziland
Libya
Colombia
Namibia
Ireland
Saint
Lucia
Iceland
South
Africa
Uzbekistan
Turkey
Mexico
Azerbaijan
Turkmenistan
Kyrgyzstan
Tunisia
Norway
Switzerland
Kazakhstan
New
Zealand
Peru
Suriname
Morocco
Botswana
Chile
Brazil
Seychelles
Fiji
Argentina
Lesotho
Belgium
Sri
Lanka
Liechtenstein
Sweden
San
Marino
Myanmar
Samoa
Guyana
China
Tonga
France
Denmark
Malta
ElBarbados
Salvador
Finland
Jamaica
Netherlands
Cape
Verde
Grenada
Mauritius
Dominica
Montenegro
Honduras
Bhutan
Pakistan
Paraguay
Malaysia
Algeria
Cote
dIvoire
Philippines
Egypt
Timor-Leste
Kiribati
Cambodia
Djibouti
Indonesia
India
Haiti
Nicaragua
Nepal
Bangladesh
Viet Nam
United
Kingdom
Zimbabwe
Tuvalu
Holy See
Old Age Dependency Ratio (65+ / 15to64years)
Population Growth Rate (% p.a.) 2005-2010
Mali
Chad
Gambia
20
Argentina
Netherlands
Norway
Ukraine
Lithuania
Czech
Republic
Uruguay
Romania
Georgia
Malta
Luxembourg
Canada
Australia
Serbia
Belarus
Poland
Montenegro
Cuba
Slovakia
Ireland
Israel
TFYRCyprus
Macedonia
Albania
Armenia
Barbados
New Zealand
Iceland
Seychelles
Turkey
Tonga
Tunisia
Suriname
Ecuador
10
South
Sudan
Kiribati
Cameroon
Djibouti
Liberia
Sudan
Somalia
Niger
Comoros
Yemen
Sierra
Leone
Nauru
Albania
Samoa
Egypt
Nepal
Guatemala
Cambodia
Maldives
Indonesia
Nicaragua
Haiti
Morocco
Myanmar
Lesotho
Honduras
Pakistan
Malaysia
Algeria
Libya
Bhutan
Vanuatu
Kyrgyzstan
Uzbekistan
Ethiopia
Congo
Timor-Leste
Turkmenistan
Philippines
Iraq
Malawi
Solomon
Guinea
Namibia
Senegal
Swaziland
MaliIslands
Botswana
Mauritania
Jordan
Mongolia
Tajikistan
Guinea-Bissau
Zambia
Chad
Nigeria
TogoFaso
Gambia
Angola
Burkina
Kenya
Burundi
Saudi
Arabia
Afghanistan
Eritrea
Oman
Kuwait
Bahrain
Chile
Saint Lucia
Lebanon
Jamaica
Thailand
Singapore
SriChina
Lanka
ElGrenada
Salvador
Mauritius
Panama
Brazil
Bahamas
Kazakhstan
Gabon
Costa
Rica
Peru
Mexico
Viet
Nam
Cape
Verde
Colombia
Paraguay
Azerbaijan
South
Africa
India
Fiji
Zimbabwe
Bangladesh
Belize
Mozambique
Ghana
Cote
dIvoire
Guyana
Benin
Madagascar
Uganda
Rwanda
Qatar
Serbia
Bulgaria
0
Andorra
Latvia
Lithuania
-2
Low
Satisfactory
High
Government's opinion of population growth
No Issue
Minor Concern
Major Concern
Government's level of concern about ageing
International support for family
planning has fallen
Basic Research
HIV/AIDS
Basic Reproductive
Health Services
Family Planning
Services
Allocation of international funding for “Population Assistance”
from S.W. Sinding 2009. Population Poverty and Economic Development.
Phil. Trans. R. Soc. B 2009 364, 3023-3030.
Fertility rebound in developed countries
from: Myrskyla et al. 2009 “Advances in development reverse fertility declines”
Ageing is an inevitability of the
demographic transition
from: Productivity Commission 2005: “Economic Implications of an Ageing Australia”
Population growth only partly
delays ageing
30
30
TFR=2, NOM=0
20
10
10
1970
1980
1990
2000
2010
2020
2030
2040
100
80
20
0
2050
100
80
“Real” dependency ratio?: (<20 & >70) / 20-70
60
60
40
Dependency Ratio: (<15 & >65) / 15-65
40
20
Aged dependency: >65 / 15-65
20
0
1960
% over 65
1970
1980
1990
2000
2010
Year
2020
2030
2040
Population (millions)
TFR=2, NOM=220,000
0
1960
Proportion of dependents (%)
40
0
2050
Proportion of dependents (%)
Population (millions)
40
The “3 Ps”:
GDP = Population x Participation x Productivity
Assumptions:
• Natural resources don’t count.
• Diluting, degrading and depleting them will not affect per capita
wealth, because they are not in the model.
• Job seekers create jobs.
• The size of the economy will be proportional to the number of
working age people.
• The 3 factors are independent.
• Population growth will not reduce participation (competition for
jobs) or productivity (competition for resources and markets).
• Growth rate costs nothing.
• The infrastructure, equipment and professional personnel that
added people need will be created without penalty.
Self-affirming factorisation:
• The “Kaya formula” for global emissions is another
example:
Emissions = Population x GDP/person
x Energy Intensity of $ x Carbon intensity of energy
Greenhouse Gas Emissions
(Gt CO2e p.a.)
7
50
6
40
5
4
30
3
20
Emissions (IPCC)
Population (UN)
10
2
1
0
0
1970
1980
1990
Year
2000
2010
Global Population (Billions)
8
60
The first “P”: Population
- but wealth is a per capita thing!
GDP versus Per Capita GDP
• Did population growth help Australia avoid the GFC?
2.0
Population growth rate
% annualised
per cent change
1.5
% change in GDP
per Quarter
1.0
0.5
0.0
% change in GDP per capita
per Quarter
-0.5
2004
2006
2008
Date
2010
2012
• Negative per capita growth for >4 quarters – made deeper by population
% change in GDP in each Quarter
growth.
% change in GDP per capita in Quarter
Population growth rate (annualised percentage)
• Population growth delinks
GDP from wealth.
So, does population growth increase
participation or productivity?
• The ageing argument: keep the proportion of working age
people high.
• Productivity Commission 2011
• “Plausible increases in fertility and net migration would have little impact on
ageing trends.”
• “any effect would be short lived. This is because immigrants themselves age”
• “to maintain the age structure of 2003-04 in 2044-45, annual migration
during that period would need to be above 3 per cent of Australia’s
population, leading to a population of over 100 million by the middle of this
century”
• Sustainable Australia Report 2013:
• “every 50,000 new migrants have roughly half the impact on ageing trends
than the previous 50,000.”
Models show ageing will reduce
participation
Productivity Commission (2005)
“Economic Implications of an ageing Australia”
The unemployed are unlikely to
take up the slack because:
“Unemployed people and
people outside the labour force
are generally different from the
employed in skill, motivation
and aptitude.”
The real world experiment
• Is the proportion of people employed
by the supply of people of
2D governed
Graph 2
working age, or by the supply of work?
% employed of total population
56
54
52
NORWAY
CANADA
AUSTRALIA
JAPAN
DENMARK
SWEDEN
GERMANY
UK
50
48
USA
FINLAND
46
44
FRANCE
42
40
18
20
22
24
26
28
30
32
34
36
38
Old age dependency ratio (%65+/15to64yrs)
• There is no correlation between ageing and proportion of people employed.
The real world experiment
• Is the proportion of people employed
governed
by the supply of people
2D Graph
2
of working age, or by the supply of work?
% employed FTE of total population
56
54
52
50
48
NORWAY
CANADA
46 AUSTRALIA
SWEDEN
DENMARK
USA
44
FINLAND
JAPAN
GERMANY
UK
42
FRANCE
40
18
20
22
24
26
28
30
32
34
36
38
Old age dependency ratio (%65+/15to64yrs)
• The differences are even smaller when part-time work is considered.
The real world experiment
GNI per capita growth, % p.a. 2000-2010
Graph 2
• Does population growth increase 2D
productivity?
2.0
SWEDEN
1.8
1.6
1.4
FINLAND
GERMANY
AUSTRALIA
UK
1.2
DENMARK
1.0
CANADA
NORWAY
0.8
JAPAN
0.6
USA
FRANCE
0.4
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
Population growth rate, % p.a. 2000-2010
• There is no trend among nations, nor among municipalities (USA).
Are we measuring productivity
decline as GDP growth?
• Density diseconomies: Infrastructure Australia
(2011)
• “The cost of providing new infrastructure is rising faster
than the rate of inflation — in part, because costlier
construction options, such as tunnelling for new roads,
now need to be adopted in the large cities.”
• Unremunerated costs of labour: Grattan Institute
(2013):
• on the perimeters of Brisbane, Sydney, Melbourne and
Perth, more than 90 per cent of jobs are at least an hour
away on public transport.
• Residential housing debt tripled since 2003.
What about wealth distribution?
2D Graph 2
• Does a growing workforce create more opportunities for the needy?
Lowest quintile % share of income
11
JAPAN
10
FINLAND
NORWAY
SWEDEN
9
GERMANY
DENMARK
8
CANADA
7
FRANCE
UK
6 AUSTRALIA
USA
5
18
20
22
24
26
28
30
32
34
36
38
Old Age Dependency Ratio (%65+/15to64yrs)
• The most youthful nations have the poorest poor.
• “Because immigration makes labour more abundant relative to the existing
stock of capital and land, it tends to increase the returns to the latter at the
expense of labour.” – Productivity Commission 2011
What about wealth distribution?
2D Graph 2
• The GINI coefficient measures inequality of income:
0.42
USA
0.40
GINI coefficient
0.38
0.36
UK
AUSTRALIA
0.34
FRANCE
CANADA
0.32
0.30
GERMANY
0.28
FINLAND
0.26
NORWAY
0.24
DENMARKSWEDEN
JAPAN
0.22
18
20
22
24
26
28
30
32
34
36
38
Old Age Dependency Ratio (%65+/15to64yrs)
• Greater inequality is associated with worse physical health, mental health,
drug abuse, education, imprisonment, obesity, social mobility, trust and
community life, violence, teenage pregnancies, and child well-being
(Wilkinson & Pickett, “The Spirit Level” 2009)
What about Pensions and
Health Care Costs?
• If the labour market is oversupplied, pensions only
replace unemployment and disability benefits.
• Raising the pension age by 3-5 years negates change
in working age proportion.
… but is not needed if labour supply holds up.
• The worst trends for retirement funding are
housing inflation and casualised work.
… a generational time-bomb imposed by population growth.
Can population growth offset
Health Care Costs?
• Most increase in health costs is due to changing
treatment technologies and expectations.
• Cost is related more to proximity to death than to
age.
• Proportion of adults with <15 years life expectancy in
creases at half the rate of old-age dependency.
• Proportion of adults with disabilities increases even less.
• However, death rate will increase with ageing – only
partly offset by population growth.
• Why is expanding construction regarded as
economic boom, but expanding health care
regarded as a burden?
Remeasuring Ageing
Remeasuring Ageing
1.0
0.8
Old Age Dependency: 65+ / 15-to-64
Adults with <15 years Life Expectancy / > 15 years
Adults with disability / able adults
Ratio
0.6
0.4
0.2
0.0
2005-10 2025-30 2045-50
USA
2005-10. 2025-30. 2045-50.
Japan
Data from Sanderson & Sherbov, “Remeasuring Ageing”
Science 329:1287-1288, October 2010.
What about the cost of growth rate?
• A higher population growth rate means a greater
proportion of total economic activity dedicated to
expanding infrastructure, equipment and skills.
• For each 1% p.a. population growth, around 7-10% of GDP is
needed for expansion.
• Govt infrastructure spending has been around 1.85% of GDP
per 1% p.a. growth.
• The increased burden is proportional to the lifespan of
the assets to be multiplied.
• If infrastructure lasts 50 years, maintenance requires creation
of 2% of the stock per year. 2% population growth doubles
this burden.
• This is an “opportunity cost” – income that would
otherwise be available for wellbeing of existing people.
Cost of ageing vs. growth
• Difference in all age-related costs between stabilising
around 25 million (IGR1) and “Big Australia” projection
(IGR3) is 1% of GDP by 2050.
• Public Infrastructure cost of growth has historically been
around 2.6% of GDP (1.85% per 1% population growth) but
is currently over 3.3% an rising. (Not included in the IGRs.)
• Expect energy and materials costs to outpace inflation.
• More than doubles the cost of decarbonising the economy.
• Loss of biodiversity, food and water security, public amenity
and quality of life.
Dependency Ratio
A: Gross National Income (GNI) distributed per capita to age categories
Young
Young
Young
Young
Old
Old
Old
Old
Working age
Working age
Uganda
Australia
Working age
European Union
Working age
Japan
B: Inclusion of capacity expansion (on behalf of the not-yet-added) to distribution of GNI
Not yet
added
Young
Not yet
added
Young
Old
Not yet
added
Young
Young
Old
Old
Old
Working age
Working age
Working age
Working age
Uganda
Australia
European Union
Japan
3.3% p.a.
1.5% p.a.
0.3% p.a.
-0.1% p.a.
Dependency Ratio
A: Gross National Income (GNI) distributed per capita to age categories
Young
Young
Young
Young
Old
Old
Old
Old
Working age
Working age
Uganda
Australia
Working age
European Union
Working age
Japan
B: Inclusion of capacity expansion (on behalf of the not-yet-added) to distribution of GNI
Not yet
added
Young
Not yet
added
Young
Old
Not yet
added
Young
Young
Old
Old
Old
Working age
Working age
Working age
Working age
Uganda
Australia
European Union
Japan
3.3% p.a.
1.5% p.a.
0.3% p.a.
-0.1% p.a.
Depopulation Dividends
German perspectives (Kluge et al. 2013):
• Smarter? - greater proportion with higher ed.
• Cleaner? - fewer greenhouse gases.
• Richer? - concentration of inheritance.
• Healthier? - greater proportion of life in wellness.
• Happier? - more leisure in the life cycle.
In summary:
Population growth
• Delinks GDP from wealth
• Doesn’t strengthen workforce
• Doesn’t increase productivity
• Increases poverty and inequality
• Diverts income from wellbeing to infrastructure
creation
• Reduces per capita resources
• Increases climate change and biosphere impacts
• Creates increasingly interdependent and brittle socioeconomic conditions.
Remember the Millennium Bug?
• Like ageing, the trigger conditions are inevitably reached.
• But the dire consequences are conspicuous only by their absence.
• In the mean time, we are turning our backs on real threats.