Using the WEAI for analysis in

different socio-cultural contexts: Ghana, Bangladesh and Nepal

Hazel Malapit and Agnes Quisumbing

Poverty, Health and Nutrition DivisionInternational Food Policy Research Institute

Supported by the US Agency for International Development through the Bangladesh Policy Research and Strategy Support Program and the WEAI

Introduction

• Global report has provided suggestive evidence that women’s empowerment is strongly correlated with several outcomes (hunger, diet diversity), but not with others (nutritional status)

• How can we use the WEAI – To diagnose patterns of disempowerment and identify

areas for policy intervention? – To understand the relationship between empowerment

and desired outcomes in different socio-cultural contexts?

• Two neat features of the WEAI:– Decomposable into its component domains and

indicators– Based on extremely detailed individual- and

household-level data

What this presentation tries to do:

1. Use the WEAI to diagnose areas where gaps in empowerment exist for women in Bangladesh, Nepal, and Ghana, three very different socio-cultural contexts

2. See how outcomes related to food security and nutrition are correlated with indicators that contribute most to disempowerment using regression analysis

3. Learn from similarities and differences in the results to hypothesize how empowerment “works” in different social and cultural contexts

Main messages (spoiler alert!)

• Patterns of (dis)empowerment vary across country and context

• Indicators and policy instruments will therefore vary

• Domains of empowerment are not equally important in determining different outcomes at the household, mother, and child level

Data

• Bangladesh: Bangladesh Integrated Household Survey (BIHS) 2011-2012; nationally representative of rural Bangladesh (http://www.ifpri.org/dataset/bangladesh-

integrated-household-survey-bihs-2011-2012)

• Nepal: Nepal Suaahara Baseline Survey, 2012; survey included 8 intervention districts where Suaaharaplanned to implement programs, and 8 matched comparison districts

• Ghana: Feed the Future’s Population-Based Survey, Baseline 2012; statistically representative of FTF’s zone of influence (http://agrilinks.org/library/feed-future-ghana-

baseline-survey-dataset)

Bangladesh

% Contribution of domains & indicators to women’s disempowerment

Nepal

% Contribution of domains & indicators to women’s disempowerment

Ghana

% Contribution of domains & indicators to women’s disempowerment

Regression analysis

We estimate the following:f = β0 + β1 empowerment + β2 h + β 3 c + ε

where: f = vector of outcomesempowerment = measures of empowermentβ0 , β1, β2 , β3 = coefficients to be estimatedh = vector of individual & HH characteristicsc = vector of community characteristicsε = error term

Where possible, we use instrumental variables methods to deal with endogeneity of empowerment

Empowerment measures

Bangladesh Nepal Ghana

WEAI Women’s 5DE score Women’s 5DE score Women’s 5DE score

Production Relative Autonomy Index (RAI) score

# of production decisions

Resources # of credit decisions# assets with sole/jointownership#decisions over purchase/sale of assets

# of credit decisions

Income # ag and nonagactivities in which she has input in income decisions or feels she can make decisions

Leadership # of groups in which she is an active member

# of groups in which she is an active member

Time # hours worked # hours worked

Does the aggregate women’s 5DE

score tell us anything meaningful?

Bangladesh Nepal Ghana

Household leveloutcomes

HH per capitacalorie adequacy (+)HH per adult equivalent adequacy (+)Dietary diversity (+)

Maternal outcomes Maternal dietary diversity (+)

Child outcomes Girls: dietary diversity (-), min. acceptable diet (-), min. diet diversity (-), wasted (+), underweight (+)

Bangladesh results: summary from IV regressions

Household-level outcomes Child outcomes

Calorie availability

Dietdiversity

Anthropometrics

Education(6-10)

Education(11-15)

Group membership

+ + n.s. n.s. n.s.

Credit decisions

+ + n.s. n.s. n.s.

Asset ownership

+ + n.s. n.s. n.s.

Rights over assets

+ + n.s. n.s. n.s.

Gender parity gap

- - n.s. n.s.

Father’s education

+ (WAZ, HAZ)

+ +

Mother’s education

n.s. n.s. +

BANGLADESH

Summary of Results• Empowerment gaps are greatest in terms of leadership in the

community and control and access to resources

• Women’s 5DE score, the number of groups in which women actively participate, women’s control of assets are positively associated with calorie availability and dietary diversity.

• Reducing the empowerment gap between men and women in the same household also contributes to increasing calorie availability and dietary diversity

• Results concerning credit decision-making need to be interpreted with caution (weak instruments, seeking credit is not necessarily a sign of empowerment in this context)

• Increasing production diversity also contributes to household calorie availability and dietary diversity

• Other non-ag dimensions of empowerment (parental education) may be more important for child nutrition and education outcomes

Nepal results: summary from OLS and IV regressions

Maternal outcomes Child outcomes

Diet diversity

BMI Dietdiversity

WAZ WHZ HAZ

Woman’s 5DE n.s. + - + for < 2 n.s. -

Autonomy + n.s. + + n.s. +

Control over income

+ (OLS), n.s. (IV)

+ n.s. +, + for <2

n.s. n.s.

Group member n.s. + n.s., positivefor <2

+ for <2 n.s. -, + for <2

Workload (hours) + - (OLS), n.s. (IV)

- (OLS) +, - for < 2

+, - for < 2

+

NEPAL

Summary of Results

• Empowerment gaps are greatest in terms of group membership, control over income, autonomy in production and workload

• Empowerment measures are significantly associated with maternal outcomes, and variable relationships with child outcomes

• Autonomy in production is significantly associated with improvements in maternal dietary diversity and child nutrition

• Higher workload is significantly associated with dietary diversity for mothers and children, and children’s height-for-age z-scores

• Time poverty is associated with disempowerment but actually does improve outcomes, though sensitive to age of child—WEAI is decomposable but not necessarily monotonic in indicators because of context-specific gender norms

Ghana results: Maternal outcomes, summary from OLS

regressions

Maternal outcomes

Diet diversity Underweight

5DE n.s. n.s.

Agricultural decisions

n.s. n.s.

Credit decisions + n.s.

Ghana results: ICYF behavior and child outcomes,

summary from OLS regressions

Exclusivelybreastfed

Dietdiversity

Min dietary diversity

Stunted Wasted Underweight

5DE n.s. - for girl n.s. n.s. n.s. + for girl

Agriculturaldecisions

n.s. - for girl - for girl + for girl n.s. + for girl

Credit decisions

n.s. n.s. n.s. n.s. n.s. n.s.

• Women’s empowerment associated with ICYF behaviors for girls, not boys (but the sign is contrary to expectations)

• Less diverse and lower quality diets in empowered hhs?• Possibility that diet diversity scores are capturing poor appetite and illness among

infants, because different foods are typically offered only when children are ill or refuse food (Davis 2000)

GHANA

Summary of Results

• Empowerment gaps are greatest in terms of production decisions and control and access to resources

• Women’s empowerment strongly associated with good IYCF behaviors, and likelihood of wasting and underweight for girls but not boys – however, relationship indicates women’s empowerment does not favor girls!

• Women’s participation in credit decisions significantly correlated with dietary diversity, consistent with bargaining models

Summary of 3-Country Results

• Different indicators of empowerment matter for different outcomes

• Other non-agricultural dimensions of empowerment may be more important for some outcomes (especially for children’s nutrition and education)

• We sometimes get unexpected results:– Empowerment not significant for boys’ nutrition, but girls

in empowered households are worse off (Ghana)

– Time poor women have better dietary diversity and taller children, but lower BMI (Nepal)

The WEAI as an analytical tool

Conclusions on the use of WEAI

• WEAI is a blunt instrument, but it is like a Swiss Army knife—individual indicators are very revealing, so use them!

• While indicators “add up” in the computation of the WEAI, they don’t always add up in the same direction because gender norms are context specific. This could lead to ambiguity of interpretation

• Use knowledge of gender norms and context to guide analysis and interpretation of results