gender inequality, economic development and the ...1 gender inequality, economic development and the...
TRANSCRIPT
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Gender Inequality, Economic Development
and the Knowledge Economy
Second MENA Knowledge for Development Forum
Marseilles, FranceMarch 15-16, 2004
The World Bank
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This presentation was prepared byDerek H. C. Chen and Aimilios Chatzinikolaou
The Knowledge for Development (K4D) ProgramThe World Bank Institute
The World Bank
The views, interpretations, findings and conclusions contained in this presentation do not necessarily represent the views of the World Bank, its Executive Directors or the countries they represent.
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This presentation draws upon material from various key references that include
• Klasen, Stephan (1999). “Does Gender Inequality Reduce Growth and Development? Evidence from Cross-Country Regressions.”Policy Research Report on Gender and Development Working Paper Series, No. 7, the World Bank, November.
• World Bank (2001). Engendering Development. Washington, D.C.
• World Bank (2003). Gender and Development in the Middle East and North Africa Region. World Bank MENA Development Report.
• World Bank (2003). Gender Equality and the Millennium Development Goals. Washington, D.C., April.
• World Bank (2003). ICT and MDGs: A World Bank Group Perspective. Washington, D.C., December.
Acknowledgements
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• Gender Inequality and Economic Development
• Gender Inequality and Human Development
• Gender Inequality around the World
• Gender Inequality and the Knowledge Economy
• ICTs and Gender Inequality
Overview
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Gender Inequality and Economic Development
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Gender Inequality andEconomic Development
0
5000
10000
15000
20000
25000
30 50 70 90 110 130Ratio of Female to Male Literacy Rates in year 2000 (%)
GD
P pe
r cap
ita in
yea
r 200
0
GDP per capita = -7335.84 + 159.10 Literacy Ratio (-3.03) (5.72)
Positive Correlation between Literacy Ratio and GDP per capita
7
Gender Inequality andEconomic Development
0
10000
20000
30000
40000
50000
60000
55 65 75 85 95 105 115
Ratio of girls to boys in primary and secondary education in year 2000 (%)
GD
P pe
r cap
ita in
yea
r 200
0
GDP per capita = -30744.4 + 419.73 Student Ratio (-3.46) (4.59)
Positive Correlation between Student Ratio and GDP per capita
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• Main channels through which gender inequality affects economic development
Selection-Distortion Effect
Environment Effects
Demographic Transition Effects
Better Governance and Institutions
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Selection-Distortion and Environment EffectsGender Inequality in Education
Boys with lower innate abilities get
educated
Less Educated Mothers -Less intellectually
stimulating environment
Less life-long learning at the
household level
Lower quality of students
Gender Inequality in Employment
Lower Quality Labor Force
Lower TFP Growth
Marginal Product of Capital Decreases
Less Investment
Lower Economic GrowthKnowledge for Development Program 2004
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Selection-Distortion Effects• Assume similar distribution of innate abilities for male
and females• Gender inequality in education leads to less able boys
getting educated• Average quality of students is lower• Together with gender inequality in employment, lower
quality of labor force results• Labor force is less productive and innovative, which
results in lower total factor productivity• At the same time, the marginal product of capital falls,
which results in a decline in the investment rate.• Lower rate of economic growth resultsKnowledge for Development Program 2004
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Environment Effects• Gender inequality in education – less female
education at each level of male education– Less-educated mothers provide environments that
are less intellectually stimulating– Resulting in a lower quality of students
• Equally educated siblings and couples tend to strengthen each other’s educational success and life-long learning– Gender inequality in education tends to result in
less life-long learningKnowledge for Development Program 2004
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Demographic Transition EffectsGender Equality in Education
Education attainment of women increases
Lower fertility – less children
Aggregate Savings Increases
More InvestmentHigher per-capita Income
Relative size of the working–age population increases
Marginal Product of Capital Increases
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• Fertility tends to decline with female education
• With gender equality, fertility tends to decline
• With less children and a smaller youth and total dependency burden, aggregate savings.
• Slowdown in fertility will eventually result in a relatively large working-age population
• Marginal product of capital increases
• Investment rate increases
• More labor and capital results in a higher level of income per capita.
Demographic Transition Effects
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• Women’s participation in public office tend to be associated with
– Cleaner businesses and government
– Less corruption
• Better governance and institutions tend to be associated with higher rates of economic growth
Better Governance and Institutions
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Governance and Institutions
Index of women’s economic and social rights
Cor
rupt
ion
Inde
x
Source: World Bank, 2001
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Gender Inequality and Human Development
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Gender Inequality and Human Development
Higher Maternal
Education
Greater Control over Financial Resources
by Women
Lower Infant Malnutrition and Mortality
Lower Child Malnutrition and Mortality
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Evidence• Thomas (1990)
– Impact of unearned income on child survival was 20 times greater if the income was brought in by the mother than if it was brought in by the father.
• Demographic and Health Surveys– Data from than 40 developing countries– Mortality rate of children under 5 is lower in
households where mothers have some primary schooling than in households where they have no schooling
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• Kirk and Pillet (1998)– Study over 25 developing countries– One to three years of maternal schooling would
reduce child mortality by about 15 percent, whereas similar increases in paternal schooling would only achieve only a 6 percent reduction
• Smith and Haddad (2000)– Data from 63 countries– Gains in women’s education made the single
largest contribution to declines in malnutrition in 1970-1995, accounting for 43 percent of the total decline
Gender Inequality and Human Development
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Gender Inequality and Human Development
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Gender Inequality and Human Development
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Gender Inequality and Human Development
Gap between male and female literacy rates (% points)
% (l
og s
cale
)
Urban Adult HIV Prevalence Rate
Source: World Bank, 2001 Knowledge for Development Program 2004
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• Greater control of income by women also tends to lower child mortality
• Increases in household income tends to reduce child mortality risks, but the marginal impact is greater if the income is allocated by the mother
• The marginal effect of female income– 20 times larger for child survival – 8 times as large for weight-for-height measures– 4 times as large for height-for-age measures
Gender Inequality and Human Development
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Gender Inequality in the World
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Gender Inequality in the World
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Gender Inequality in the WorldRatio of Female to Male Literacy Rates
81 81
97 96
57
67
60
83 85
97 97
62
72
66
8588
97 98
66
78
72
0
20
40
60
80
100
World East Asia & Pacific Europe & CentralAsia
Latin America &Caribbean
South Asia Sub-SaharanAfrica
Middle East &North Africa
%
199019962002
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Gender Inequality in the WorldRatio of Female to Male Youth Literacy Rates
90
96 98 100
71
8075
91
98 99 100
75
8582
92
99 99 101
79
8987
0
20
40
60
80
100
World East Asia &Pacific
Europe &Central Asia
Latin America& Caribbean
South Asia Sub-SaharanAfrica
Middle East &North Africa
%
1990 1996 2002
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Gender Inequality in the WorldRatio of Girls to Boys in
Primary and Secondary education (%)
84
96 96
85
68
79 81
92
101 10197
102
7982
92
0
20
40
60
80
100
World High income High income:OECD
East Asia &Pacific
LatinAmerica &Caribbean
South Asia Sub-SaharanAfrica
Middle East& NorthAfrica
1991 / 92
1998 / 99
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Gender Inequality in the WorldRatio of Female to Male Gross Primary Enrollment Rates
90
100
94
99 98
75
8284
92
99 98 98 99
7983
86
94
99 10197
8286
92
0
20
40
60
80
100
World High income East Asia &Pacific
Europe &Central Asia
Latin America &Caribbean
South Asia Sub-SaharanAfrica
Middle East &North Africa
%
1990 1995 1999
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Gender Inequality in the WorldRatio of Female to Male Gross Secondary Enrollment Rates
87
102
79
101
112
60
7774
91
102
90
101
114
64
83 83
94
102
91
109
73
82
92
0
20
40
60
80
100
120
World High income East Asia &Pacific
Europe &Central Asia
LatinAmerica &Caribbean
South Asia Sub-SaharanAfrica
Middle East& NorthAfrica
%
1990 1995 1998 / 99
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Gender Inequality in the WorldRatio of Female to Male Gross Tertiary Enrollment Rates
97104
70
115
95
5147
58
101
112
72
119
106
5763
69
115
125 123
65
0
20
40
60
80
100
120
World High income East Asia &Pacific
Europe &Central Asia
LatinAmerica &Caribbean
South Asia Sub-SaharanAfrica
Middle East& NorthAfrica
%
1990 1997 1999
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Gender Inequality in the WorldFemale Labor Force
4041
4446
33 32
42
24
4042
4446
3433
42
26
41
4546
3534
42
29
43
0
10
20
30
40
50
World High income East Asia &Pacific
Europe &Central Asia
LatinAmerica &Caribbean
South Asia Sub-SaharanAfrica
Middle East& NorthAfrica
(% of total labor force)
1990 1996 2002
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Gender Inequality in the World
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Gender Inequality in MENA
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Gender Inequality in G7 & Western Europe
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Gender Inequality in EA and ECA
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Gender Inequality in LAC & South Asia
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Gender Inequality and the Knowledge Economy
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Knowledge EconomyEconomy in which knowledge is the engine of growth
Four Pillars of the Knowledge EconomyEconomic incentive and institutional regime that provides incentives for the efficient use of existing and new knowledge and the flourishing of entrepreneurshipEducated, creative and skilled peopleDynamic information infrastructure Effective national innovation system
Knowledge Economy Framework
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• Knowledge Assessment Methodology (KAM): 76 structural/qualitative variables to benchmark performance on 4 pillars
• Variables normalized from 0 (worst) to 10 (best) for 121 countries
• www.worldbank.org/kam• Multiple modes offering wide range of graphic
representations and functionalities (1995 - Most Recent, comparison options)
• Aggregate Knowledge Economy Index (KEI) –average of performance in 4 pillars – KI
• Weighted and unweighted version – Innovation Variables
K4D Program’s KAM Methodology 2004
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KE Index
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KE Index with Gender Variables
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ICT and Gender Inequality
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World Bank Group defines ICT asconsisting of hardware, software, networks, mediafor collection, storage, processing transmission, presentation
of information (voice, data, text, images)
OECD defines ICT sectors as a combination of manufacturing and service industries that
capture, transmit and display data and information electronically.
ICT can play an important role in economic development By providing new and more efficient methods of productionBy improving the delivery of government servicesBy facilitating management and transfer of knowledge
ICT
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ICTThe ICT-producing sector includes the following industries according to the International Standard Industry Classification (ISIC) Revision 3
Manufacturing
3000 Manufacture of office, accounting and computing machinery
3130 Manufacture of insulated wire and cable
3210 Manufacture of electronic valves and tubes and other electronic components
3220 Manufacture of television and radio transmitters and apparatus for line telephony and line telegraphy
3230 Manufacture of television and radio receivers, sound or video recording or reproducing apparatus, and associated goods
3312 Manufacture of instruments and appliances for measuring, checking, testing, navigating and other purposes, except industiral process control equipment
3313 Manufacture of industrial process control equipment
Services - goods related
5150 Wholesale of machinery, equipment and supplies
7123 Renting of office machinery and equipment (including computers)
Services - intangible
6420 Telecommunications
7200 Computer and related activities
OECD Definition of ICT-producing Industries
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Channels via which ICT can improve gender in equality– Influencing public opinion on gender equality
– Increasing women’s education
– Allowing more economic opportunities for women
ICT and Gender Inequality
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Influencing Public Opinion on Gender Equality– ICT increases flow of knowledge and information
– Increases exposures of customs, norms and practices from other cultures and societies
– Raises the awareness and informs the constituency of gender inequality issues
– Increases pressure on policymakers to include gender as an important component of their social and economic policies
ICT and Gender Inequality
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Increasing Women’s Education– Lack of schooling coupled with gender biases that dictate domestic roles for women tend to perpetuate gender disparities– ICT allow women to obtain and update their skills for equal participation in the knowledge economy
• Increasing access through distance learning• Broadening the availability of quality educational
materials• Efficiency and Effectiveness of Educational
Administration
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Increasing Economic Opportunities for Women– ICTs allow women to telecommute and hence they are able to work and interact with men without face-to-face contact and even without being in the same place
– ICTs allow micro and small enterprises (MSE), which are dominated by women to compete in the marketplace
ICT and Gender Inequality
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Econometric Estimation– empirically determine the effects of ICTs on gender inequality in education and employment
– estimated panel regressions with country fixed-effects
– dependent variables: measures of gender inequality
– independent variables: measures of ICT and control variables
– broadest coverage include 94 countries for the years 1985 to 2000
ICT and Gender Inequality
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ICT and Gender Inequality in EducationDependent Variable: Ratio of Female to Male Students
Independent Variables R eg 1.1 R eg 1.2 R eg 1.3 R eg 1.4 R eg 1.5
Lagged Log 4.9185 10.5198 3.6664 7.0667 7.3444(T rend R G DP per capita)
Y outh Sex R atio 1.9005*** 1.7384*** 1.3304*** 1.7965*** 1.7976**
Education Variables
Lagged Av erage 6.6108*** 4.5668* 1.7151 6.4211*** 7.0171***Y ears of School
Lag Public Education -0.0010 0.0011 0.0002 0.0032*** 0.0032***Expenditure per capita
IC T Variables
Lagged C om puters 0.0094***(per 1,000 persons)
Lagged Log 0.4165***(Internet Users)(per 1,000 persons)
Lagged Log (Phones) 3.6693***(per 1,000 persons)
Lagged Log 3.6432***(IC T Expenditure) (% of G DP)
Lagged Log (IC T 1.6479**Expenditure per capita)
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Main Empirical Findings– ICT availability /density when measured by number of
• personal computers per 1,000 persons• Internet users per 1,000 persons • telephones per 1,000 persons• ICT expenditure / GDP• ICT expenditure per capita
– All have statistically significant positive effects on gender equality in education–General Education when measured by the average years of schooling also has significant positive effects
ICT and Gender Inequality in Education
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ICT and Gender Inequality in Employment Dependent Variable: Ratio of Female to Male Labor Activity Rates
In d e p e n d e n t V a r ia b le s R e g 2 .1 R e g 2 .2 R e g 2 .3 R e g 2 .4 R e g 2 .5
L a g g e d 2 .0 9 6 2 5 .0 6 3 8 *** 1 .6 8 1 2 5 .1 6 4 5 ** * 3 .3 4 0 7 **L o g (R G D P p e r c a p ita )
L a g g e d U rb a n iz a tio n -0 .0 5 7 8 0 .0 8 9 3 -0 .0 2 3 1 0 .0 1 3 3 0 .0 5 6 3R a tio
U n e m p lo y m e n t R a te -0 .0 4 9 8 * -0 .0 1 1 6 0 .0 0 0 4 0 .0 0 8 7 0 .0 3 7 5
E d u c a tio n V a r ia b le s
L a g g e d A v e ra g e 2 .3 1 7 9 *** 2 .1 6 0 7 *** 3 .4 0 5 4 *** 3 .3 4 3 8 ** * 3 .0 4 2 3 ***Y e a rs o f S c h o o l
L a g g e d R a tio o f A v e ra g e 0 .0 2 7 1 0 .0 7 6 2 ** 0 .1 2 8 2 *** 0 .0 8 5 4 * 0 .0 7 9 8 *Y e a rs o f S c h o o l
IC T V a r ia b le s
L a g g e d L o g (C o m p u te rs ) 1 .4 5 4 8 ***(p e r 1 ,0 0 0 p e rs o n s )
L a g g e d 0 .1 8 1 7 ***L o g (In te rn e t U s e rs )(p e r 1 ,0 0 0 p e rs o n s )
L a g g e d P h o n e s 0 .0 0 4 8 ***(p e r 1 ,0 0 0 p e rs o n s )
L a g g e d IC T 0 .1 2 8 6 *E x p e n d itu re (% o f G D P )
L a g g e d (IC T 0 .0 0 1 5 ***E x p e n d itu re p e r c a p ita )
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ICT and Gender Inequality in EmploymentMain Empirical Findings
– ICT availability /density and General Education have statistically significant positive effects on gender equality in employment
In addition – Gender inequality in education when measured by the ratio female to male average years of schooling– tends to have positive effects on gender inequality in employment
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ICT, Gender Inequality and Economic Development
Increasing ICT Infrastructure
More Gender Equality in Education More Gender
Equality in Employment
Higher Level of Economic Development
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References:Dollar, David. and Roberta Gatti (1999). “Gender Inequality, income, and
Growth: Are Good Times Good for Women? Policy Research Report on Gender and Development, Working Paper Series, No. 1, The World Bank, May.
Humana, Charles (1992). World Human Rights Guide. 2nd ed. London: Hodder and Stoughton.
Klasen, Stephan (1999). “Does Gender Inequality Reduce Growth and Development? Evidence from Cross-Country Regressions.” Policy Research Report on Gender and Development Working Paper Series, No. 7, the World Bank, November.
Kirk, Dudley and Bernard Pillet (1998). “Fertility Levels, Trends, and Differentials in Sub-Saharan Africa in the 1980s and 1990s.” Studies in Family Planning. Vol. 29, No. 1.
Smith, Lisa C. and Lawrence Haddad (2000). “Explaining Child Nutrition in Developing Countries: A Cross-Country Analysis.” Research Report 111, International Food Policy Research Institute. Washington D.C.
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References:Thomas, D. (1990). “Intrahousehold Resource Allocation: An Inferential
Approach.” Journal of Human Resources. Vol. 25, pp. 634-664.
United Nations (2002). Arab Human Development Report 2002: Creating Opportunities for Future Generations. United Nations DevelopmentProgramme, Arab Fund for Economic and Social Development.
World Bank (2001). Engendering Development. Washington, D.C.World Bank (2003a). Gender Equality and the Millennium Development Goals.
Washington, D.C., April.
World Bank (2003b). Engendering ICT: Ensuring Gender Equality in ICT for Development. Washington, D.C., September.
World Bank (2003c). ICT and MDGs: A World Bank Group Perspective. Washington, D.C., December.
World Bank (2003d). Gender and Development in the Middle East and North Africa Region. World Bank MENA Development Report.
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