Comments on
Intergenerational Transfers, Age Structure,
and Macroeconomics
Sang-Hyop Lee
University of Hawaii at Manoa
WEAI 83rd Annual Conference, Honolulu, USA
July 2, 2008
National Transfer Accounts
Do they look alike?
• Some age profiles show similar pattern
• Economic lifecycle is influenced by biology. Individual
choices and economics constraints are similar.
• Some age profiles are quite different.
• Source of supports are quite different (triangle graphs)
• However, even for similar age profiles, there are
IMPORTANT differences and similarities across countries
and over time.
National Transfer Accounts
Important differences
1.2
1
0.8
Average of 25
0.6
0.4
0.2
Age
National Transfer Accounts
85
90
+
80
75
70
65
60
55
50
45
40
35
30
25
20
15
10
5
0
0
Normalized labor income (30-49)
Age Profile of Labor Income (M exico, 2005)
Source of differences
•
•
Population structure matters
Level of development matters
• Consumption on elderly is high in rich countries, and is
mostly due to medical expenditures
• Richer countries have larger public consumption
expenditures, on both health and education.
• Consumption on children is low in low-income countries.
• Richer countries have low LFPRs for children and elderly
• Richer countries have low share of self-employment income
National Transfer Accounts
Asset
Capital-based
transformation
Social welfare
transformation
Traditional
society?
Familial
Transfers
Old-Age Reallocation Systems
Source: Andrew Mason.
National Transfer Accounts
Public
Transfers
Policy matters.
Public Education Consumption of China
China 1995 & 2002, per capita
0.06
0.05
0.04
0.03
Ratio
0.02
0.01
Public Public Education 1995y
National Transfer Accounts
Age
88
84
80
76
72
68
64
60
56
52
48
44
40
36
32
28
24
20
16
12
8
4
0
0.00
Public Public Education 2002y
Policy may have other consequences.
Private education consumption of China
China 1995 & 2002, per capita
0.12
0.10
0.08
0.06
Ratio
0.04
0.02
Private Education 1995y
National Transfer Accounts
Age
Private Education 2002y
88
84
80
76
72
68
64
60
56
52
48
44
40
36
32
28
24
20
16
12
8
4
0
0.00
Institution matters.
Kenya and Nigeria Public consumption of Education
Composition of Public Consumption in Health and Education
0.070
Normalised to average labour
income ages 30-49 years
0.060
0.050
0.040
0.030
0.020
0.010
0.000
0
10
20
30
Kenya Education (Public)
Nigeria, Education (Public)
National Transfer Accounts
40
50
Age in years
60
70
Kenya Health (Public)
Nigeria, Health (Public)
80
90+
Disaster/Crisis matters.
Labor Income,China,Aggregate,2002
3500
10^8 Yuan
3000
2500
2000
1500
1000
500
0
0
6
12 18
24 30 36 42 48 54 60 66
72 78 84 90+
Age
Compensation to employees
National Transfer Accounts
Self-employed Income
Data matters.
• Constructing NTA requires lots of data sets.
• A good data set has the properties of
• Extent (richness): it has the variables of interest at a certain level
of details.
• Reliability: the variables are measured without error.
• Validity: the data set is representative.
• E.g.) Asset based reallocations
• A lot of countries use information on inflow, but the profiles of
outflow might be different
• Find a proxy (until you find a better proxy)
• One type of asset income
• Use ratio of survey
• Use other country data! (Kenya vs. Uganda)
National Transfer Accounts
In a comparative analysis,
• Computing confidence intervals helps.
• Comparing countries with similar culture, policy,
economic development helps (regional analysis)
• Each country has its own issues; how does it make
the country different from others?
• China: urban vs. rural issues, negative LCD
• India: public sector age reallocations.
• Kenya & Nigeria: composition of consumption
(education). Tax for education is earmarked.
• Mexico: Revenue from oil, remittances.
National Transfer Accounts
Comparative Analysis (Cont’d)
•
•
•
•
In particular, replication of some interesting
results in another country setting greatly
increases the confidence of the results.
Comparing components is useful.
(education/health/pension benefit/..)
Comparing within a country across years
has an advantage.
Do more analysis.
National Transfer Accounts
E.g. of “Do more analysis”.
India and Mexico has different labor
income profile
1.4
1.2
1
0.8
0.6
0.4
0.2
0
India
National Transfer Accounts
88
80
72
64
56
48
40
32
24
16
8
0
Mexico
Not mainly due to active population
(L/N) by age,
0.9
0.8
0.7
0.6
0.5
Mexico
0.4
0.3
0.2
India
National Transfer Accounts
84
77
70
63
56
49
42
35
28
21
14
7
0
0.1
0
but due to different productivity per
worker.
1.800
1.600
1.400
1.200
1.000
Mexico
India
0.800
0.600
0.400
0.200
National Transfer Accounts
84
77
70
63
56
49
42
35
28
21
14
7
0
0.000
Conclusion; Let me repeat
“The goals of the NTA project”
• Develop a system of economic accounts that can
be used to study the macroeconomic implications
of aging.
• Estimate the accounts with historical depth for
economies with different cultures, levels of
development, economic systems and policies.
• Analyze and explain
• variation in the economic lifecycle and the reallocation
systems,
• macroeconomic effects of population aging, (simulation)
• economic implications of education, pension, health
care, child subsidies, and other policy.
National Transfer Accounts
Thank you.
National Transfer Accounts