gender inequality, economic development and the ...1 gender inequality, economic development and the...

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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.

Knowledge for Development Program 2004

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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


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

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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


Gender Inequality and Human Development


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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



20



21


22


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 in the World


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26

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



%

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


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


Latin America &Caribbean



%

1990 1995 1999


30

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






%

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






%

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






(% of total labor force)

1990 1996 2002


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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


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


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



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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



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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



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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



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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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