Transcript An Overview of National Transfer Accounts

Gender and the
Demographic Dividend
Karen Oppenheim Mason
East-West Center
Outline
1.
What is the demographic dividend?
2.
What role might gender play in the
demographic dividend?
3.
What is the evidence about gender and
the demographic dividend?
4.
Report on ICRW Study
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National Transfer Accounts
1. What is the
demographic dividend?
The demographic dividend
►
Refers to the economic growth that
results when fertility declines
►
Fertility decline temporarily reduces the
dependency ratio
►
If the “extra” income is invested wisely,
per capita income will grow
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National Transfer Accounts
India 2005
85-89
80-84
75-79
Male
Female
70-74
65-69
60-64
55-59
50-54
45-49
40-44
35-39
30-34
25-29
20-24
15-19
10-14
5-9
0-4
70,000 60,000 50,000 40,000 30,000 20,000 10,000
10,000 20,000 30,000 40,000 50,000 60,000 70,000
5
NationalUnited
Transfer
Accounts
Source:
Nations
Population Division 2006.
S. Korea 2005
85-89
80-84
Male
Female
75-79
70-74
65-69
60-64
55-59
50-54
45-49
40-44
35-39
30-34
25-29
20-24
15-19
10-14
5-9
0-4
2,500
2,000
1,500
1,000
500
500
Thousands
NationalUnited
Transfer
Accounts
Source:
Nations
Population Division 2006.
1,000
1,500
2,000
2,500
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The Most Important Graph in the World:
An Asian Economic Lifecycle
Per Capita Consumption and Labor
Income
600
Labor Income
500
400
Consumption
300
200
100
0
0
20
40
60
80
Age
7
National Transfer Accounts
What are wise investments?
► Physical
capital: savings accounts, equity
markets, etc.
► “Human capital:” education, health care,
nutrition
► Both government & household invest-ments
will work
► But whether investment occurs depends on
policies
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National Transfer Accounts
Policies that encourage investment
► Economic
and political stability
► Reliable banking and investment systems
► Openness to trade
► Incentives to invest in human capital
(health, education)
► Type of pension system (asset-based
versus pay-as-you-go)
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National Transfer Accounts
2. What role might gender
play in the demographic
dividend?
Gender systems
►
►
►
Refers to the socially prescribed roles &
rights of women and men
Culturally agreed on and enforced, so it’s
a feature of groups
Important for the DD are restrictions on
women’s freedom of movement, ability
to operate in public venues (e.g.,
schools, factories), and ability to make
decisions within the household & family
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National Transfer Accounts
Five possible effects of nonrestrictive gender systems
1.
Increased investment in female education
2.
Rising female labor force participation rates
3.
Increased investments in children’s human
capital
4.
Increased household savings or investment
5.
Declining familial support of the aged (an
incentive to save for old age)
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National Transfer Accounts
1. Investment in female education
►
►
►
►
►
►
Fertility decline reduces the value of girls’ domestic
labor (fewer siblings to care for)
Rising income & smaller family size also reduce
parents’ need to ration their investments in children (a
well-established finding)
So parents are more willing to invest in girls’ schooling
(unless gender norms seclude girls)
Rising educational levels of both sexes encourage later
ages at marriage
Later age at marriage allows parents to reap the
monetary rewards of investing in girls’ schooling
So where girls’ freedom of movement is not severely
restricted, “extra” income may be used to invest in
female education
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National Transfer Accounts
2. Rising female labor force
participation rates
Low fertility & increased life expectancy reduce the
length of the child-rearing years
►

►
►
►
so the number of years women are available for labor force
participation increases
Better educated workers can command higher wages,
so rise in female schooling makes their employment
more attractive
Once low fertility cohorts reach working age, the
growth of the labor force slows, wages rise, and more
women are attracted into the work force
All these effects, however, depend on a gender system
that does not severely restrict women’s freedom of
movement
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National Transfer Accounts
3. Investment in children’s human
capital
Studies from a variety of settings show that women
are more likely than men to invest in children’s health,
nutrition and schooling
►

Studies include Bangladesh, Brazil, Canada, Cote d’Ivoire,
Ethiopia, Indonesia, South Africa, Taiwan, and the U.S.
►
So rise in women’s employment may encourage
greater investments in children’s human capital
(daughters’ and sons)
►
But this effect depends on whether women are able to
determine how money is spent, i.e., on a gender
system that gives wives some degree of economic
autonomy or power
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National Transfer Accounts
4. Increased household savings?
Women face greater economic insecurity in old
age than men do
► Gender bias in the ownership of land and other
real estate undermines women’s ability to fund
old age support from accumulated wealth
► So with rise in women’s employment, women
may save for their old age more than men do
► Households may also see women’s earnings as
“extra” income and may be more inclined to
save or invest such income than an equal
amount earned by the husband
►
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National Transfer Accounts
5. Declining familial support of the
aged
Upward intergenerational transfers from family
members or the state are thought to reduce
the propensity to save for old age
► Studies find less intergenerational co-residence
with rising female education and employment
► Daughters-in-law are less available to care for
elderly parents when they are working
► So rising female employment may undermine
upward transfers from family members
(although increased income may help to fund
such transfers)
►
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National Transfer Accounts
3. What is the evidence
about gender and the
demographic dividend?
General picture
Much evidence that gender equality
contributes to economic growth (see World
Bank, Engendering Development)
► But little evidence on the extent to which
gender is important in creating a demographic
dividend
► Will review some of the general evidence
►
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National Transfer Accounts
4
3
(percent)
Average annual growth in per capita GNP, 1960-1992
Closing the gender gap in schooling promotes
economic growth
2
Predicted
1
Actual
0
Sub-Saharan
Africa
National Transfer Accounts
South Asia
Middle East/
North Africa
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East Asia vs. the Middle East
► East
Asia has enjoyed a very large
demographic dividend
► The Middle East/North Africa region has not
thus far, despite declining fertility
► Why?
► One reason may be the restrictive gender
systems found in MENA vs. the less
restrictive ones found in East Asia
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National Transfer Accounts
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National Transfer Accounts
Female Labor Force Participation Rate (ages 15 and over)
90
80
70
60
FLFP RATE
Japan
Korea
50
Taiwan
Singapore
40
Thailand
Indonesia
30
20
10
0
1950
1960
1970
1980
1990
YEAR
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National Transfer Accounts
Percentage of Working Women Employed in Manufacturing
60
50
PERCENTAGE
40
Japan
Korea
Taiwan
30
Singapore
Thailand
Indonesia
20
10
0
1950
1960
1970
1980
1990
YEAR
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National Transfer Accounts
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National Transfer Accounts
“It is difficult to imagine East Asia’s laborintensive, export-led industrialization
occurring without the efforts of female
workers, whose labor fueled the growth in
manufacturing and helped to moderate
wage growth.”
John Bauer 2001, pp. 366-7
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National Transfer Accounts
Needed research
► How
do changes in age structure affect
female education and employment?
► How does female employment affect
household saving rates?
► How do changes in female education and
employment affect familial support for the
elderly?
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National Transfer Accounts
4. Report on an ICRW Study
Reference
Based on a paper by Jeffrey Edmeades,
Janna McDougall, Anju Malhotra & Margaret
Greene, “Gender Equality and the
Demographic Dividend,” presented at the
PAA Meeting, New Orleans, April 17-19,
2008
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National Transfer Accounts
Research Design
► Country-level
growth regressions that build on the
Bloom-Canning-Malaney (2000) model
► Hypothesis is that gender inequality in education
(a) slows economic growth, and (b) reduces the
positive effects of a favorable age structure on
growth
► Reasoning is that inequality represents lost human
capital and productivity
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National Transfer Accounts
Data
► Data
for 82 countries covering six five-year
periods,1965-1999 (N = 470) – Ghana & S.
Africa removed as “outliers”
► All data time-varying with independent
variables measured in the base year for each
period
► Dependent variable is the logged annual
average percentage growth of real GDP per
capita measured in PPPs
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National Transfer Accounts
Data, continued
►
►
Gender inequality is measured as the ratio of female to
male years of completed secondary schooling in the
population 15+ years of age (model also includes “total
schooling” as stock measure)
Inequality is treated as a dummy variable classification:
1.
2.
3.
►
Female/male > 1.0
.75 = or < Female/male = or <1.0
Female/male < .75
Reason for this choice is not discussed in the paper
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National Transfer Accounts
Models
►
►
►
►
►
Basic model predicts growth from age structure (log [15-64/N]),
base-year GDP, tropics dummy, landlocked dummy, quality of
institutions, openness of economy, total schooling, growth in
total population, % of GDP from agriculture, and period
dummies
Second model adds the educational inequality dummies
Third model adds the interaction between base-year GDP and
age structure (I’ll ignore this model)
Final model adds interaction terms for (a) gender inequality &
age structure, (b) gender inequality & base-year GDP, and (c)
gender inequality & pop growth
They also run separate models within each of the three gender
inequality groups
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National Transfer Accounts
Selected Results 1
Model 1
Model 2
Model 4
Age structure
6.8**
6.7**
2.3
F ed > m ed
--
0.5
0.7
F ed = m ed
--
0.6*
0.9***
F>m * age str
--
--
26.5***
F=m * age str
--
--
10.6***
Variable
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National Transfer Accounts
Selected Results 2
Variable
Age structure
F<M
F=M
F>M
1.9
13.2***
14.1***
Initial GDP
-2.4***
-2.9***
-3.6***
Age * Int GDP
-7.7***
-2.9
-3.0
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National Transfer Accounts
Questions
► What
would results look like if there were
fewer interactions in the models?
► How did the “outliers” affect the results –
and why did removing only 12 observations
out of 482 change the results substantially?
► Is gender inequality in education what is
driving these results or is it some other
correlated variable?
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National Transfer Accounts
Acknowledgement
Support for this project has been provided by the following
institutions:
► the John D. and Catherine T. MacArthur Foundation;
► the National Institute on Aging: NIA, R37-AG025488 and
NIA, R01-AG025247;
► the International Development Research Centre (IDRC);
► the United Nations Population Fund (UNFPA);
► the Academic Frontier Project for Private Universities:
matching fund subsidy from MEXT (Ministry of Education,
Culture, Sports, Science and Technology), 2006-10,
granted to the Nihon University Population Research
Institute.
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National Transfer Accounts
The End