Population aging, intergenerational transfers, and economic growth: Asia in a global context
Ronald Lee, University of California, Berkeley
Andrew Mason, University of Hawaii and East‐West Center
Policy Research and Data Needs to Meet the Challenges and Opportunities of Population Aging in Asia
New Delhi, March 14‐15, 2011
Acknowledgements
• National Transfer Accounts (NTA) research network
– 35 high‐ and low‐income economies
– 8 Asian members: China, India, Indonesia, S Korea, Japan, Philippines, Taiwan, and Thailand
• Leaders of NTA – India research team
– Professor Ladusingh, International Institute of Population Sciences, Mumbai
– Professor Narayana, Institute for Social and Economic Change, Bangalore
• Funding – National Institutes of Health (NIA R37 AG025247 and R01 AG025488)
– International Development Research Centre (IDRC)
– United Nations Population Fund (UNFPA)
Ronald Lee and Andrew Mason, March 14, 2011
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Overview
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NTA lifecycle estimates: Consumption and labor income
• Uses cross‐sectional data from existing surveys for a recent year.
• Averages across all population at a given age, combining males and females. • Consumption includes
– Private expenditures, imputed to individuals within each household
– Public in‐kind transfers (e.g. education, health care)
• Labor income includes
– Wages, salaries, fringe benefits before tax
– 2/3 of self employment income
– Average includes 0’s.
• For comparisons age profiles are standardized by dividing by average labor income for ages 30‐49. Ronald Lee and Andrew Mason, March 14, 2011
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Economic Lifecycle of India, 2004
Per capita consumption and labor income
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Economic Lifecycles Compared
3 Asian Countries
Later peak in labor
income in India and
especially Japan.
Higher labor income at
younger ages in China
and India.
Steeper decline in labor
income in Japan; lower at
old ages.
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Economic Lifecycles Compared
3 Asian Countries Elderly consumption is
as high as consumption
by other adults; higher
in case of Japan.
High human capital
investment in Japan
Low consumption (high
saving) at all ages in
China.
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Profile Value, Relative to Average Labor Income
Countries of South and Southeast Asia
1.2
1
Consumption
0.8
TH
ID
0.6
PH
0.4
IN
0.2
Labor Income
0
0
20
40
60
80
Age
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Profile Value, Relative to Average Labor Income
East Asian Economies
1.2
Consumption
1
JP
TW
0.8
KR
0.6
CN
0.4
0.2
Labor Income
0
0
20
40
60
80
Age
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The Support Ratio
• Measures the number of workers relative to the number of consumers.
• Given worker productivity, a 1% increase in the support ratio leads to a 1% increase in per capita income.
• Use NTA profiles as base years estimates of:
– Age‐specific variation in labor productivity
– Age‐specific variation in consumption
• Multiply profile values by past or projected population by age to find how the number of effective workers varies with respect to the number of effective consumers. Ronald Lee and Andrew Mason, March 14, 2011
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Support Ratio, China
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Support Ratio, China
Net swing of 1.2% per year in per capita growth due to population age structure.
Plus 0.8% per year
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Support Ratios: Divergent Paths for China, India, and Japan
India
China
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Support Ratios: Divergent Paths for China, India, and Japan
India
China
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Support Ratio, Annual Growth
NTA Economies, 2010‐2050
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Responding to population aging: Investment in human capital
• NTA synthetic cohort measure of HK • Sum of spending on health and education per child – at ages 0 to 17 for health
– ages 0 to 26 for education
• Separately for public and private spending
• Express in years of labor income (30‐49)
• First look at PUBLIC spending in relation to fertility.
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Public Human Capital Investment vs Fertility in 23 NTA Countries
log (Public Human Capital Spending per child, Relative to Labor Income)
2.0
y = ‐1.29x + 1.60
R² = 0.59
t = ‐5.46
SE
SI
HU JP
AT
ES
DE
1.5
1.0
TW
FI
TH
KR
0.5
US
CR
MX
CL BR
UY
ID
IN
0.0
‐0.5
0
0.5
PH
1
KE
1.5
2
CN
‐1.0
‐1.5
NG
‐2.0
log (Total Fertility Rate)
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Public Human Capital Investment vs Fertility in 23 NTA Countries
log (Public Human Capital Spending per child, Relative to Labor Income)
2.0
y = ‐1.29x + 1.60
R² = 0.59
t = ‐5.46
SE
SI
HU JP
AT
ES
DE
1.5
1.0
TW
FI
TH
KR
0.5
US
CR
MX
CL BR
UY
ID
IN
0.0
‐0.5
‐1.0
‐1.5
0
0.5
PH
1
KE
1.5
2
CN
Public spending low in China and “normal” in India
NG
‐2.0
log (Total Fertility Rate)
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Total Human Capital Investment vs Fertility in 23 NTA Countries
2.0
Asian countries
log (Human Capital Spending,
Relative to Labor Income)
SE
TW
SI
JP
1.5
KR
HU
ES
AT
US
FI
TH
DE
CR
MX
CL
BR
UY
1.0
PH
CN
ID
y = ‐0.67x + 1.66
R² = 0.64
NG
t = ‐6.12
IN
0.5
Adding in private spending raises
China’s position a little, but
greatly reduces India’s.
0.0
0
0.5
1
KE
1.5
2
log (Total Fertility Rate)
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Responding to population aging: Funding consumption by the elderly
• Three approaches to funding old‐age consumption
– Elderly continue to work
– Elderly rely on assets
– Elderly rely on transfers
• from family
• from public sector
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Funding consumption of the elderly in 17 economies around 2000: Labor income, Transfers (public and private combined), and Assets
1) Main tradeoff is between
relying on transfers and on
assets.
Assets
2) In economies relying more
on assets, people also
have more labor income in
old age. But this effect is
not as large.
1/3
Id
Mx
2/3
US
Ph
Es
Uy
1/3
Jp
De
2/3
KR
CR
Sl
At
Hu
Transfers
Br
Tw
Cl
Se
2/3
1/3
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Labor
income
22
RDL4
Funding consumption of the elderly in 17 economies: Labor income, Transfers (public and private combined), and Assets
Asian economies:
Assets
1/3
Id
Mx
2/3
US
Ph
Es
Uy
1/3
Jp
De
2/3
KR
CR
Sl
At
Hu
Transfers
Br
Tw
Cl
Se
2/3
1/3
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Labor
income
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Slide 23
RDL4
Where is Thailand/s point? We only have five Asian in the diagram instead of six (after deleting China and India).
Too bad we can't do the other triangle too, with India and China included. Next year!
Ronald D. Lee, 3/10/2011
Conclusion
• Changes in the relative size of the working age population will greatly advantage India over China and especially Japan. • Eventually, the support ratio in India will begin to decline too.
• The effect of a declining support ratio can be offset by – Investing in human capital as fertility declines.
– Avoiding excess reliance on transfers to support old‐age consumption. • The experience in Asia is quite varied
– Low levels of human capital spending in China and India
– Support systems estimates for China and India not yet complete
– Higher income economies in East Asia are relying fairly heavily on a combination of public and private transfers. Ronald Lee and Andrew Mason, March 14, 2011
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The importance of HRS type surveys
The new HRS‐type surveys will make it possible to explore these and other aspects of population aging in Asia more deeply than possible with available data.
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THE END
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