Women’s Work and Economic development

Women’s Work and Women’s Work and Economic developmentEconomic development

Author(s): Kristin Mammen and Christina Paxson

Source: The Journal of Economic Perspectives, Vol. 14, No. 4, (Autumn, 2000), pp. 141-164

Published by: American Economic Association

Stable URL: http://www.jstor.org/stable/2647079

Presented by Moshe Shaul (S.ID 029429438) 16/07/20008

Essay ObjectiveEssay Objective

How the role of women in the labor force varies with the level of economic development.

Note: Although there is a diversity across countries at similar income levels in how much women work and the types of jobs they perform, several clear patterns emerge from the data.

2Moshe Shaul Student ID-029429438

ContentContentFirst part: presents the theoretical Model.Second part: Presents evidence from cross

country data. Third part: verifies the consistency

between the cross-country data and patterns within India and Thailand

Forth part: discusses the recent literature on resource allocation to women within households in poor counties.


Women’s Work and Economic Women’s Work and Economic Development in TheoryDevelopment in Theory

Moshe Shaul Student ID-029429438 4

Women’s labor supply decision

Earned Unearned

Cost of her work = Education level, Experience and Skill level

Earning of her husband and transfer income of her family

Positive affect Negative affect

How should Economic Development How should Economic Development Affect the Labor Force of Women?Affect the Labor Force of Women?


Man’s opportunities improve relative to women’s, It plays an important role how women’s labor force participation changes with development.

Competitive Labor MarketCompetitive Labor Market


Labor markets do not function competitively in developing counties, especially for women. Following are some of the factors restricting women from working outside her home:

LawsCustom or social norms (manual jobs)Not compatible with child rearing

creating fixed cost of working off-farm.

Agriculture to Urbanization Agriculture to Urbanization (industrialization) Process(industrialization) Process


The process of urbanization and new blue-collar jobs decrease the number of farms and thus decrease the opportunities for women in absolute terms (Goldin 1995).

Until women can acquire the required schooling and transferable skills to find a suitable employment in firms of modern economy the opertunities relative to men may decline (Schlutz 1988)

Women’s Labor Force in Women’s Labor Force in Developed CountriesDeveloped Countries


What explain the increase of women’s labor force in developed countries?

a) Growth of white-collar jobsb) Gains of women education

U-Shaped RelationshipU-Shaped Relationship


Economic Development

Women's labor force participation

Poor CountiesWomen works in farm

Urbanization and social barriers

against women

Women education level raise and start to work in white-collar jobs

Social Norms and White/Blue Social Norms and White/Blue Collar JobsCollar Jobs


Why should social norms dictate that white-collar jobs are “acceptable” for married women whereas blue-collar jobs are not?

a) Women dislike factory work and marriage can be used as escape opportunity.

b) In some countries it is typical for manufacturing firms to terminate women’s jobs upon marriage.

c) Societies stigmatize the husbands of women who do blue-collar work (e.g. lazy, avoid his obligation to the family etc), Note: this reason is not relevant to white-collar jobs (since such women typically have more educated husbands which have relative high income)

d) Factory does not pay wives enough to compensate for the fixed costs of working away from home.

Database Description and Database Description and Objectives Objectives


Geographic location: 90 countiesDates: from the 1970s and 1980sObjectives: trace out the relationships between:

Economic development And Several indicators of women’s status:

Investment in education Labor force participation (self employment, employer or

employee)

Participation in wage work (employee)

Fertility

Research's Evidence-Research's Evidence-Education Analysis Education Analysis


Top curve description: 1) Women's education levels and economic development

• Women's education levels increase with economic development both in absolute and relative terms to those of men.

• Note: Education is a normal consumer good, (more of which is demanded at higher income levels).

2) Women's education levels have risen over time especially for lower and middle income countries.

Research's Evidence-Research's Evidence-Education Analysis, cont Education Analysis, cont


Bottom curve description:• Show the results for female - male education gap. (Average years

of adult female minus Average years of adult male schooling at age of 25). • The largest gap (about 2 years) at a per capita GDP of about 1000$, than shrinks as income

rises.

• Since education level for both men and women rise with income, the gap of education narrows throughout the income range.

Research's Evidence- Women’s labor Research's Evidence- Women’s labor force participation vs. Income level force participation vs. Income level relation Analysis relation Analysis


African South Asian

Country

South America Central America South European East Asian North European North American

Research's Evidence- Women’s Research's Evidence- Women’s labor force participation vs. labor force participation vs. Income level relation Analysis Income level relation Analysis


Women’s labor force participation vs. Income level relation has “U-shape” (Goldin 1995)

High participation in very low and very high incomes. Labor force participation is measured for women

aged 45-59, who are past the child rearing stage. (however, similar results would be obtained if younger women were included.)

Research's Evidence- Women’s wages VS. Research's Evidence- Women’s wages VS. Fertility Rate relation Analysis Fertility Rate relation Analysis


Income ,Family enterprise Paid jobs, Fertility

Research's Evidence- Women’s wages VS. Research's Evidence- Women’s wages VS. Fertility Rate relation Analysis. Cont’ Fertility Rate relation Analysis. Cont’


If we assume that children are normal goods thenwage may have the following affect:

Wage Fertility

But if we consider the opportunity cost of women’s time raises and it has largest effect then wage may have the following affect:

Wage Fertility

Research's Evidence- Women’s wages VS. Research's Evidence- Women’s wages VS. Fertility Rate relation Analysis. Cont’ Fertility Rate relation Analysis. Cont’


Other factor may drive fertility decline :a) Reduction in child mortality that come with

development may allow for lower fertility level if the “demand” for complete family size which increases or remains the same.

b) Development of public or private pension systems decries the expectation from children to provide income for their parents especially in their old age.



between the cross-country data and patterns within India and Thailand.



Two examples: Thailand and IndiaTwo examples: Thailand and India

These countries were not chosen to be representative of the entire developing world, indeed, no two counties can be.


Characteristic Thailand IndiaRecent growth (1980,1995 GDP per capita)

+125% +69%

Women’s Labor force Relative high Relative low

Women’s ownership and control of lands

Acceptable Against social norms

Distribution of rural household lands

Fairly evenly distributed 72% own the land11% rent the land

16% farm laborer

Less equal distribution36% farm laborer

Thailand Across Cohort PatternsThailand Across Cohort Patterns


Thai Socioeconomic surveys allow us to track birth cohorts over time, we can examine how women's labor force participation and work activity have changed during a period of rapid economic growth. Notes:a)Below data are not applicable to India because of lack of available data but we expect to have the same behavior.b)The relatively flat cohort lines indicate that this fraction varies little over time within cohorts.

Male-Female Gap in Education VS. Male-Female Gap in Education VS. Expenditure Expenditure


a) Educational achievement is lower for women then man at both graphs.

b) In both countries, the male-female gap in education rises with expenditure (e.g. spending) in rural areas, but remain steady with expenditure in urban areas.

Women Labor force VS. Women Labor force VS. Expenditure Expenditure


a) Labor force definition: applicable to women as employee, employer or self employment (e.g. free family labor)

b) Women labor force is lower in both countries for urban areas (due to

fewer work opportunities).c) In urban areas women labor force follows the “U shape”

Women Working for Wages VS. Women Working for Wages VS. Expenditure Expenditure


a) The probability of working as an employee increases steadily with living standard.

b) In India there is relatively large number of landless or near landless poor household, the member of which often work as casual on lager farms. Thus work as “free family labor” is not an option for many women in the poorest families.

Thai Free family labor

India’s women must work due to lack of lands

Education affect Education affect (regression results)(regression results)


a) Secondary school-I. In India women with secondary school has minor affect on the

probability to be part of labor force.II. In Thai secondary school has no affect on the probability to be part of

labor force.b) Post-secondary school-

In both countries Post-secondary school has large affect on the probability to be part of labor force.

c) Rural women-In both countries are more likely to be part of labor force

d) Spousal education- Has negative affect on participation in labor force in India but not in Thai.

e) Special tribe- In India being a member of a specific tribe may increase the affect on

participation in labor force.f) Following are more affects of education:

I. More likely to work in non-manual jobs (e.g. white-collar)II. More likely to work as employee rather than self-employed

Gender Gaps in developed Gender Gaps in developed Countries Countries


a) Girls in poor countries receive less education on average than boys, that gaps decline as living standards raise.

b) Women’s life expectancy rise with income and have improved over time given per capita GDP (i.e. development).

c) Women’s life expectancy improves relatively to male as income raise.

Gender Gaps in developed Gender Gaps in developed Countries. cont’ Countries. cont’


d) Women and girls in developed countries receive fewer resources within the household.

e) More labor market opportunities, higher wages may increase women’s well being both through direct affect and also by strengthening their bargaining position within households.

f) Difference in men’s and women’s well being and achievement as adult may be rooted in difference in investment they received as boys and girls.

g) One possible reason why parents invest less in girl is the higher future returns to parents.

Conclusion Conclusion


Mortality rate and education levels indicates that women’s well being improves on average with development, both in absolute term and relative to men.

Women’s Work and Economic development

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