Inequality of Opportunity and Outcomes in Asia: A Gendered Perspective

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Inequality of Opportunity and Outcomes in Asia:A Gendered Perspective

Yana van der Meulen Rodgers, Rutgers University

Joseph E. Zveglich Jr., Asian Development Bank

January 17, 2012

Asian Development Bank

ERD Seminar

The views expressed in this paper are the views of the author and do not necessarily reflect the views or policies of the

Asian Development Bank (ADB), or its Board of Governors, or the governments they represent. ADB does not guarantee

the accuracy of the data included in this paper and accepts no responsibility for any consequence of their use. The

countries listed in this paper do not imply any view on ADB's part as to sovereignty or independent status or necessarily

conform to ADB's terminology.



Intro: Gender Perspectives on Inclusive Growth

• Equality of opportunity and outcomes are related andself-reinforcing

• Equality of opportunity

– Associated with formal, legal equality in access toeducation, health services, and employment

– But also equality in decision-making and voicewithin the household

• Equality of outcomes

– Includes equality in income, wealth, and assets



Intro: Gender Perspectives on Inclusive Growth

• Labor force participation is viewed as both an opportunityand outcome

• As an opportunity, labor force participation enables womento

– Ability to enhance individual and household income andwealth

– Greater say over household decisions (such aschildren’s education)

• As an outcome, labor force status has an intrinsic value

– Income-earning production viewed differently fromuncompensated household production

– Enhanced status itself has value



Links between Growth and Gender Inequality

• Growth affects gender inequality– Complex dynamic (Figure 1)

– Growth has led to reductions in disadvantages faced bywomen, especially in educational attainment, lifeexpectancy, and labor force participation.

– Yet growth does not necessarily mean inequality willdecline, especially if women continue to face constraintsin obtaining new, well-paid employment opportunities

• Gender inequality affects growth

– Can enhance short-run growth (such as by providinglow-wage labor to export sectors)

– But inequality in education and employment can act asa drag on long-term growth



FormalInstitutions

Markets

InformalInstitutions

Households

Labor MarketOpportunities

G D P G r o w t h

Source: World Bank (2011)

Drivers of Labor MarketOpportunities



In Asia, women’s labor force participationvaries widely

Sub-region 1990 2010

Central & West Asia 55% 55%

East Asia 53% 54%

South Asia 39% 45%

Southeast Asia 62% 62%

The Pacific 49% 52%

Developed Members 52% 57%



Labor force participation drops and then rises—acrossAsian countries in 2010

Note: All data are for 2010 or the closest year available. GDP per capita is adjusted by PPP indices, in constant2005 international $.



Labor force participation drops and then rises—over time

• U-shape also seen in long historical US time series



Factors driving the U-shape

• Industrial transformation– Shift away from agriculture production to

manufacturing/industry and later to services

– Stigma against women’s manual work, but no such

stigma for white collar work• Income effects

– Rising male wages allows for labor specializationwithin the household

– But also leads to smaller families

• Changing social attitudes

– Evolution in “women’s work”

– Rising education levels



Case Studies Using Micro-Level Data

• Manpower Utilization Survey (MUS)

– Annual data for Taipei, China spanning 1978–2010

• Demographic and Health Surveys (DHS)

– South Asia: Bangladesh, India, Maldives, Nepal, and

Pakistan

– Southeast Asia: Cambodia, Indonesia, and Philippines

– The Pacific: Timor-Leste

– Data from 2005–2009



Manpower Utilization Survey

• Take advantage of the long time series to explore:

– Effect of demographic change on women’s laborforce participation

– Driving factors behind changing labor force

participation for different age groups– How drivers of employment decisions over time

compare with drivers across countries

• Under preparation



The DHS: Sample Information

• Large nationally-representative samples of women betweenthe ages of 15 and 49

• Part of collection of DHS datasets on population, health, HIV,and nutrition for 85+ countries (http://www.measuredhs.com/)

• Used the individual recode and merged in variables onhousehold composition from household member recode

• Sample sizes ranged from 7,131 women in Maldives to124,385 in India

• Disadvantages: Employment may be measured with error ascompared to using labor force surveys; women officially

unemployed grouped together with women out of labor force• Advantages: Allows for comparable regressions across

countries; provides extensive information on women’sproductivity characteristics, household composition, andhousehold wealth not contained in most labor force surveys

http://www.measuredhs.com/

http://www.measuredhs.com/



Methodology• Empirical strategy: measure the effects of women’s

individual characteristics, household wealth, andhousehold composition on women’s employmentdecisions

• Estimation equation:

•Dependent variable: binary variable for whether or notthe woman is currently employed

• Regressions performed with cross-section data at theindividual level, separately for each country

• Use probits (and report marginal effects)

• Tolerance statistics estimated to test for the presence of multicollinearity among full set of independent variables

• Standard errors corrected for clustering at the level of the household



Findings using the DHS• Wealth effects

– In six countries, women from higher wealth quintilehouseholds less likely to be employed as compared to thosefrom the lowest wealth households

• Bangladesh, India, Indonesia, Nepal, Pakistan, and Timor-Leste:economic necessity pushes women from low-wealth households

to engage in market-based work

– In remaining three countries, women from wealthierhouseholds are more likely to be employed as compared towomen from the poorest households

• Maldives and Philippines: relatively more developed economies;

low socioeconomic status among households does not play asstrong a role in pushing women to be employed

• Cambodia: other variables related to income are capturing theincome effect (woman’s education, having access to safe water,and living in urban area)

– Similar findings for education effects



Women’s Employment Determinants: MarginalProbabilities, 2005-09

Bangladesh Cambodia India Indonesia Maldives Nepal Pakistan Philippine s Timor- Leste

Household wealth index (reference: 1st quintile)

2nd

quintile-0.021 0.001 -0.042*** -0.017 -0.009 -0.130*** -0.073*** 0.015 -0.050***

(0.017) (0.015) (0.007) (0.015) (0.019) (0.024) (0.016) (0.019) (0.016)

3rd

quintile-0.102*** 0.029* -0.104*** -0.028* -0.031 -0.209*** -0.113*** -0.007 -0.042**

(0.017) (0.015) (0.007) (0.016) (0.019) (0.026) (0.015) (0.021) (0.017)

4th

quintile -0.120***

0.034**

-0.206***

-0.063***

0.032 -0.275***

-0.186***

0.038*

-0.082***

(0.020) (0.017) (0.007) (0.018) (0.026) (0.029) (0.014) (0.022) (0.018)

5th

(richest)

quintile

-0.216*** -0.006 -0.294*** -0.027 0.100** -0.439*** -0.248*** 0.115*** -0.050**

(0.020) (0.025) (0.007) (0.019) (0.042) (0.030) (0.014) (0.023) (0.025)



DHS findings

• Effect of marriage and children– Marriage is associated with lower employment, with

large and statistically significant coefficients in everycountry except Nepal and the Philippines

– Across all countries, having young children reduceswomen’s employment:

• A child under the age of five reduces probability that a womanis employed by 1% (Pakistan) to 10% (Indonesia), with anaverage of about 4% across the region

– But that effect tends to fade as children get older• A child above the age of five can raise or lower probability a

woman is employed or have no effect depending on thecountry and age of the child



Women’s Employment Determinants: MarginalProbabilities, 2005-09

Bangladesh Cambodia India Indonesia Maldives Nepal Pakistan PhilippinesTimor-

Leste

Number of children (linear)

<5 yrs

old-0.047*** -0.034*** -0.037*** -0.095*** -0.029*** -0.027*** -0.014*** -0.046*** -0.018***

(0.007) (0.007) (0.003) (0.007) (0.009) (0.007) (0.005) (0.006) (0.006)

5-12 yrs

old0.010* 0.003 0.009*** -0.006 0.002 0.008** -0.002 0.005 -0.019***

(0.005) (0.004) (0.002) (0.005) (0.007) (0.004) (0.004) (0.005) (0.004)

13-17 yrs

old-0.029*** -0.038*** -0.022*** -0.003 0.003 -0.016** -0.002 -0.031*** -0.019***

(0.007) (0.006) (0.003) (0.007) (0.008) (0.007) (0.005) (0.006) (0.006)



Issues to highlight for ADO

• Importance of women’s participation in formal labor marketsto make growth inclusive

• Policy reforms play a role

– Improve women’s wages and working conditions

– Improve compatibility of women’s market work withhousehold responsibilities

• Maternity and parental leave benefits

• Support for child care schemes

– Promote enabling policies so women in informal sector andagriculture become less marginalized

• Microfinance, rural banking reforms, training programs,provision of business-development services, strongerproperty rights, gender-responsive social protectionmeasures

Documents

Inequality of Opportunity and Outcomes in Asia: A Gendered Perspective