National Transfer Accounts: Selected Variables
National Transfer Accounts:
Per Capita Consumption by Children and the Elderly a
Private
DATA SHEET
Thousand CFA Francs
800
Labor income
400
Consumption
200
Senegal
0
0
10
20
30
40
50
60
70
80
90+
Age
Thousand Kronas
Labor income
Consumption
150
Sweden
0
0
10
20
30
40
50
Age
60
70
80
90+
I
n countries all over the world, per capita consumption exceeds labor income
during childhood and old age. These periods of economic dependency bracket
a stage of life during which more is being produced than consumed. Labor income
exceeds consumption for 42 years, on average, in Senegal and 38 years in Sweden.
In many other countries, this stage of life is much shorter. NTA helps explain how
children and the elderly, who consume more than they produce, are supported.
On average, individuals start earning labor income at younger ages in Senegal than
in Sweden and continue earning at least some labor income throughout old age. This
reflects the fact that many Senegalese work in agriculture or other forms of selfemployment, while many Swedes work in the formal sector with relatively late entrance
into the job market and a relatively early retirement age. Per capita consumption, including
spending on education and healthcare, is higher for children in Sweden than in Senegal.
Per capita consumption is extremely high for Sweden’s elderly population, reflecting a
particularly high level of spending on healthcare and long-term care in old age.
The National Transfer Accounts (NTA) project focuses on the economic impact of changes in
population age structure. By providing estimates of income, consumption, saving, and both public
and private transfers for specific age groups, NTA adds an important dimension to measures of
Gross Domestic Product (GDP) and other widely used economic indicators. Project coordinators
are Ronald D. Lee at the Center for the Economics and Demography of Aging, University of California
at Berkeley, and Andrew Mason at the East-West Center and the Department of Economics, University
of Hawai‘i at Mānoa.
One of the unique features of the NTA project is the development of a unified framework for
studying generational economic issues in widely varying cultural, social, political, economic, and
demographic contexts. NTA teams all over the world are compiling data and developing new
approaches to help answer important policy questions. Current work focuses on improving and
expanding NTA analysis to new countries and additional time periods.
NTA members are also engaged in four major new initiatives: (1) the Counting Women’s Work
project is constructing accounts separately for males and females and measuring the production
and consumption of unpaid care and housework services; (2) The AGENTA project looks at taxes
and public transfers in Europe in light of demographic change and the potential for public policy
reform; (3) a regional project on the demographic dividend in West and Central Africa is helping 13
countries construct accounts using the NTA model; and (4) work in Asia helps draw out the policy
implications of population dynamics in the region by improving the availability and quality of NTA
data and strengthening the links between data analysis and policy response.
Support for NTA has been provided by the United States National Institute on Aging; the
International Development Research Centre (IDRC) of Canada; the William and Flora Hewlett
Foundation; the Bill & Melinda Gates Foundation through the Gates Institute for Population and
Reproductive Health at the Bloomberg School of Public Health; the United Nations Population
Fund (UNFPA); the United Nations Population Division; the Asian Development Bank; the World
Bank; the John D. and Catherine T. MacArthur Foundation; the European Union's Seventh Framework
Programme for Research, Technological Development, and Demonstration; and the Japanese
government’s Academic Frontier Project for Private Universities.
Revised August 2016
(% of per capita
combined consumption
age 25–64)
Support Ratios
Fiscal Support
Ratio Index
Human-Capital Spending
(effective number
(projected tax revenues (% of average annual labor
of producers per 100 relative to public transfers
income of a prime-age
effective consumers) a as % of values in 2015) b
(30–49) adult) c
Average Annual Labor
Income Age 20–29
(% of average annual
labor income of a
prime-age (30–49) adult)
Annual Economic Resources
for Children, Age 0–24
Annual Economic Resources
for the Elderly, Age 65+
(as % of annual consumption) d
(as % of annual consumption) e
Age
0–24
Age
65+
Age
0–24
Age
65+
Age
0–24
Age
65+
2015
2035
2055
2035
2055
Africa
61
88
131
93
70
89
43
48
52
110
117
89
110
200
46
17
u
22
u
45
u
6
u
Benin (BEN) 20 07
Burkina Faso (BFA) 20 1 4
Chad (TCD) 2 0 1 1
Côte d’Ivoire (CIV) 2 0 1 5
Ethiopia (ETH) 2005
Ghana (GHA) 2005
Guinea (GIN) 2 0 1 2
Kenya (KEN) 2005
Mali (MLI) 2 0 1 5
Mauritania (MRT) 20 1 4
Mozambique (MOZ) 20 0 8
Niger (NER) 20 1 4
Nigeria (NGA) 20 09
Sao Tome &
Principe (STP) 2 0 1 1
Senegal (SEN) 2 0 1 1
South Africa (ZAF) 2005
55
59
64
66
56
65
59
58
60
65
61
63
82
95
79
84
81
94
96
88
85
91
94
65
95
96
168
117
103
123
144
130
163
142
119
119
143
119
137
10 0
97
84
80
10 1
94
95
10 0
94
95
84
99
93
66
70
67
67
65
71
81
69
68
78
69
71
85
96
83
84
82
94
95
90
87
92
94
67
96
96
41
45
39
45
49
41
38
43
40
45
48
32
41
46
50
44
54
54
46
42
46
43
50
52
31
44
51
55
51
58
59
52
46
48
49
54
57
36
49
u
u
u
u
u
u
u
109
u
u
108
u
u
u
u
u
u
u
u
u
116
u
u
117
u
u
47
52
38
107
97
58
88
34
41
122
20
89
4 87
108
79
47
32
139
74
2 92
97
62
15 6
137
38
40
154
131
86
139
236
132
3 80
131
103
278
157
127
5 27
41
54
43
60
42
37
42
51
47
40
72
30
51
15
25
13
25
8
10
11
22
16
15
32
11
19
u
u
u
u
u
u
u
u
u
u
u
u
u
u
u
u
u
u
u
u
19
u
u
13
u
u
u
u
u
u
u
u
u
u
u
u
u
u
u
45
76
47
50
45
39
57
15
28
66
33
20
62
u
u
u
u
u
u
u
u
u
u
u
u
u
u
u
u
u
u
u
u
10
u
u
8
u
u
u
u
u
u
u
u
u
u
u
u
u
u
u
58
58
42
97
93
83
127
103
140
84
82
114
65
68
59
96
90
88
50
43
55
56
47
60
60
52
60
u
u
113
u
u
119
13
49
88
95
175
194
107
224
282
60
39
36
24
17
10
u
u
53
u
u
35
u
u
3
71
53
11
u
u
– 23
u
u
0
u
u
112
East Asia & the Pacific
76
89
162
168
94
10 6
52
46
41
87
77
20 5
279
4 84
60
21
52
29
–6
15
10
43
34
63
91
67
71
86
82
90
91
10 8
84
75
89
159
155
194
127
176
160
215
141
228
111
1 55
161
81
111
90
78
10 4
99
114
107
130
87
91
10 4
56
53
45
56
52
52
51
44
40
52
44
44
49
39
36
51
38
34
90
85
87
u
u
87
85
76
77
u
u
71
113
180
14 0
237
323
238
296
198
389
112
307
372
408
378
529
349
630
610
70
85
48
58
49
50
28
48
14
14
12
9
36
66
50
u
u
55
33
20
33
u
u
32
4
–3 4
3
u
u
3
13
20
12
23
14
8
1
16
0
u
u
23
41
45
51
u
u
35
44
19
37
u
u
35
South & Southeast Asia
65
98
146
112
77
100
55
57
55
109
114
97
149
24 6
65
25
58
16
0
27
1
–3
74
Bangladesh (BGD)
Cambodia (KHM)
India (IND)
Indonesia (IDN)
Iran (IRN)
Lao PDR (LAO)
Malaysia (MYS)
Maldives (MDV)
Nepal (NPL)
Philippines (PHL)
Thailand (THA)
Timor-Leste (TLS)
Vietnam (VNM)
73
66
59
68
64
61
59
66
67
62
64
68
76
95
98
107
90
111
72
87
131
92
116
86
109
83
117
112
124
24 3
157
14 9
181
125
105
152
197
109
132
10 1
117
137
1 20
107
116
113
118
98
102
126
102
102
75
69
67
82
77
72
78
76
83
69
89
91
80
96
99
111
92
111
78
91
1 29
94
115
94
10 5
84
58
69
56
57
54
53
55
55
45
55
61
34
64
62
69
60
58
57
61
57
57
54
57
56
38
57
60
64
58
59
51
63
54
49
52
57
50
45
52
u
10 5
102
u
u
129
u
u
u
u
10 1
u
u
u
102
101
u
u
157
u
u
u
u
95
u
u
127
151
68
178
67
46
63
91
76
100
85
25
187
18
44
107
2 53
25 4
10 8
253
92
71
67
41 8
207
42
14 5
19 4
175
431
32 1
154
316
183
146
167
503
231
22 9
65
101
54
61
41
60
56
66
68
77
55
56
91
43
48
22
18
13
29
18
29
13
33
15
7
40
u
49
66
u
u
u
u
u
u
u
59
u
u
u
5
7
u
u
22
u
u
u
u
31
u
u
u
–2
5
u
u
u
u
u
u
u
–4
u
u
46
17
27
33
32
61
33
20
13
24
19
16
12
u
18
1
u
u
u
u
u
u
u
–1 7
u
u
u
5
2
u
u
–27
u
u
u
u
7
u
u
u
61
70
u
u
u
u
u
u
u
92
u
u
61
10 0
157
132
75
104
56
57
54
94
83
1 56
24 5
401
61
21
61
18
1
25
8
52
25
58
54
67
60
57
59
57
62
73
61
61
97
103
107
106
97
88
102
93
86
111
108
143
126
182
156
141
161
120
170
181
181
166
121
112
164
143
151
1 20
141
139
114
10 0
14 3
87
70
82
82
69
71
62
74
84
74
75
10 5
10 5
114
114
10 5
92
10 5
98
89
109
112
51
59
54
63
57
57
58
59
53
55
53
52
58
51
62
56
60
62
58
57
56
53
51
52
46
58
50
60
58
54
56
54
51
100
88
84
91
87
94
102
10 5
u
92
97
93
75
69
81
71
85
92
102
u
74
88
86
82
2 22
160
72
80
186
180
350
139
162
475
218
258
2 85
252
194
1 20
169
232
19 5
299
561
300
4 80
445
324
2 74
306
349
581
334
461
61
56
47
68
61
58
66
73
57
61
58
17
20
12
47
21
20
18
27
14
23
18
u
u
u
u
62
59
71
54
u
61
u
38
17
19
16
16
13
7
17
u
26
12
u
u
u
u
1
8
3
3
u
–1 1
u
19
22
20
46
25
44
19
21
26
23
12
u
u
u
u
–2
0
10
53
u
–1 9
u
88
68
54
67
50
64
15
8
u
65
44
u
u
u
u
27
–8
56
17
u
32
u
61
99
176
220
83
1 23
55
49
48
u
u
87
378
465
50
15
u
u
u
22
u
u
u
67
86
192
203
92
109
55
49
47
u
u
54
4 16
470
53
16
u
u
u
21
u
u
u
54
113
159
237
74
137
54
50
48
90
88
1 20
3 40
4 60
48
13
43
38
6
24
–4
28
52
59
93
173
169
85
111
51
45
43
85
78
40
371
411
54
19
44
32
3
10
–2
74
23
2010
200 6
20 1 1
200 8
200 5
200 8
2010
200 8
20 03
200 6
58
54
58
58
60
58
68
65
57
57
94
90
99
10 5
95
96
95
83
89
93
188
178
14 8
152
151
201
20 8
203
213
115
1 59
196
169
168
136
181
141
165
231
102
86
84
82
78
87
88
101
93
102
61
10 9
116
117
119
107
113
106
99
1 29
93
53
46
46
49
50
52
47
54
47
68
45
42
41
41
47
43
38
45
42
70
41
41
40
39
42
40
35
40
41
67
82
88
89
84
89
80
81
83
91
80
73
84
87
77
76
72
76
73
88
68
24
10
38
37
34
48
49
71
18
48
43 1
347
33 3
2 92
376
472
4 81
4 42
586
31
4 54
3 57
37 1
3 29
4 10
520
5 30
5 13
604
79
58
54
53
51
55
50
44
49
56
60
26
19
17
18
15
14
14
13
18
29
42
29
46
41
32
51
53
52
42
u
28
46
44
40
44
32
30
34
38
–1
4
6
–7
2
9
4
3
2
3
u
6
5
3
3
7
8
6
9
6
54
–1
2
–7
–10
5
–5
2
1
–12
u
84
79
71
56
93
74
74
64
99
77
11
14
32
51
–4
23
19
26
6
u
20 07
62
86
141
215
78
112
52
47
45
91
86
64
2 95
3 59
69
28
50
20
2
6
0
43
52
Australia (AUS)
China (CHN)
Japan (JPN)
Mongolia (MNG)
Rep. Korea (KOR)
Taiwan (TWN)
450
300
Combined
(% of per capita
(% of per capita
private consumption public consumption
age 25–64)
age 25–64)
Per capita labor income and consumption by age in
Senegal (2005) and Sweden (2003)
600
Public
2010
20 07
200 4
20 1 4
2010
2010
2010
200 9
2004
2012
20 1 1
2012
2009
2010
20 1 1
20 1 1
20 1 1
20 1 1
2012
Latin America
& the Caribbean
Argentina (ARG)
Brazil (BRA)
Chile (CHL)
Colombia (COL)
Costa Rica (CRI)
Ecuador (ECU)
El Salvador (SLV)
Jamaica (JAM)
Mexico (MEX)
Peru (PER)
Uruguay (URY)
2010
20 02
2012
20 0 8
20 04
20 1 1
2010
20 02
2010
20 07
2013
North America
Canada (CAN) 2006
United States
(USA) 2 0 1 1
Europe
Austria (AUT)
Finland (FIN)
France (FRA)
Germany (DEU)
Hungary (HUN)
Italy (ITA)
Slovenia (SVN)
Spain (ESP)
Sweden (SWE)
Turkey (TUR)
United Kingdom
(GBR)
This data sheet was published in 2016 by the
National Transfer Accounts Project
East-West Center
1601 East-West Road, Honolulu, HI 96848-1601, USA
Telephone: +1.808.944.7566 | Fax: +1.808.944.7490
Email: [email protected] | Website: www.ntaccounts.org
Private Public
Labor Private
Public
Asset-Based
Income Transfers Transfers Reallocations
Total
Source: Calculated from National Transfer Accounts data, 2016.
u Unavailable.
a The effective number of producers sums the population in each one-year age group, weighted to
incorporate age differences in employment and productivity estimated for the base year. The effective
number of consumers sums the population in each one-year age group, weighted to incorporate age
differences in consumption estimated for the base year.
b Revenues and expenditures are projected assuming that per capita taxes and public expenditures by
single year of age remain constant at base-year values.
Labor Private
Public
Asset-Based
Income Transfers Transfers Reallocations
c Human-capital spending is total spending per child given per capita health spending for children age
0–17 and per capita education spending for children age 3–26 in the base year.
d In some cases, annual economic resources for children do not sum to 100% of their consumption due
to rounding. Regional averages do not necessarily sum to 100% because the information available for
some countries is incomplete.
e In some cases, annual economic resources for the elderly do not sum to 100% of their consumption
due to rounding. Regional averages do not necessarily sum to 100% because the information available
for some countries is incomplete. Negative values for transfers indicate that the elderly are providing
more resources to other age groups than they are receiving.