AADAPT Workshop South AsiaGoa, December 17-21, 2009

Gender Policy for Development: Realizing Opportunities

Arianna LegoviniManager, Development Impact Evaluation InitiativeThe World Bank

Motivation

Gender matters for development Evidence from research

Policy can address gender gaps Incorporate gender dimensions in policy

interventions and learn from impact evaluation how to make gender policy work for development

Two questions

Does development matter for gender?

Does gender matter for development?

First questionDoes development matter for gender?

Does gender matter for development?

Development improves gender balance Gender gaps narrow with growth

Girls/boys ratio in secondary schools rose from 40/100 to 79/100 in 1970-2005

Female labor force participation rose Female life expectancy increased more than male

Poverty and crises negatively affect girls In poor neighborhoods in Delhi, girls are twice as

likely to die of diarrhea (Khanna et al.) During draughts in India girls die

disproportionately (Rose)

But bias persists Parental expectations (PROBE, India) (-)

57% of parents wanted their sons to study as far as possible

Only 28% of parents wanted their daughters to study as far as possible

Education in English (+) More lower caste girls in Mumbai study in

English and have better opportunities More low caste boys study in Marathi because of

old boy networks and have lower opportunities

Two questionsDoes development matter for gender?

Does gender matter for development?

Second question

Does development matter for gender?

Does gender matter for development?

Venues for gender to affect development Women have different preferences

and take different decisions than men at home and for policy

Position of weakness in the household may reduce household overall productivity through unequal sharing of resources

Rules, constraints and disadvantages may reduce productivity in the economy

Change perceptions through quotas? India (Beaman et al.)

Random assignment of gender quotas across Indian village councils

Technical audits show female presidents provide more public goods and at better quality than male presidents

Villagers are 1.5% less likely to pay bribes in female headed villages

However, villagers are 2% less satisfied with female presidents. Rate them less effective the first time they are exposed to them

The bias disappears for villagers that have already experienced female leaders in the past

Quotas for female presidents of councils may be justified to change gender perceptions (and developmental outcomes)

Money in the hands of women have different effects

In South Africa, Girls bridge half the growth gap between South African and US

children when living with female pension recipient There is no effect when they live with a male pension recipient

(Duflo) Children 13-17 are more likely to be in school when they live

with a male pension recipient (Edmonds) In Cote d’Ivoire, households spend more

on food in years when female crops do better on alcohol and tobacco when male crops do better (Duflo and

Udry) Many transfer and microcredit programs target

women hoping to achieve more results

Create wealth by gender equality: Burkina Faso (Udry 1996)

In households with female and male controlled plots:

Many more inputs are used on male than female plots male plots are 30% more productive than female plots

But fertilizers have diminishing returns if more equally shared household product would increase

Households could increase output by 6% if they shared resources

Allocation within the household is not efficient and gender inequality is a cause of poverty

Strengthening female property rights good for growth? Ghana (Goldstein & Udry 2008)

Women have weaker property rights on their land than men

Women fallow their land less than men do because they can suffer expropriation during fallowing

As a result women’s maize & cassava yields are much lower than men’s within the same household

Inefficient fallowing is costly More secure property rights for women

could increase Ghana’s GDP by 1%

Gender policy is development policy These examples show that

women’s preferences can help growth, and

gender disparities can cause inefficiencies in household production and country growth

Worth investing in gender policies to support development policy

Gender factors that can be addressed through policy

Perceptions Differential access to land, inputs, capital,

output markets Traditional rules on duties, movement,

household decisions Different formal or informal rights on

property

How impact evaluation can help Hypothesize factors that may induce inefficiencies

in the context of your program Think about what policy interventions may

address them Test policy alternatives rigorously

Impact evaluation will separately isolate the effect of a particular intervention from that of other interventions of factors

There is currently little impact evaluation evidence on gender differentiated program effects AADAPT, in collaboration with the GAP, will support

governments build the evidence

How to measure gender differentiated effects

Measure differential effects on men and women for the same interventions

Larger samples Different data collection strategy Additional indicators For each type of intervention, measure spillover effects

on the targeted individual as well as other members of the households who may be affected (wife of the head, daughters)

or, Target men and women with different interventions and measure effects on men and women

Measuring differential impacts: Ethiopia (Deininger et al’s 2008)

Securing land property rights had significant impacts on women heads of household

Women heads of household who received land certificates were 20% more likely to make soil & water

conservation investments in land (extensive margin)

Spend 72% more time on these investments (intensive margin)

Are effects always different?Intervention Outcome(s) Impacts by gender

Ethiopia land certification

Tenure security, land investment & rental market participation

-Female-headed HHs 20% more likely to invest in land & spend 72% more time on land investments & repairs-No difference in tenure security or land rental

Kenya export crop adoption & marketing

Export crop cultivation, HH income, marketing costs

Malawi rainfall insurance

Adoption of hybrid seed credit

Ethiopia roads & agricultural extension

Poverty & consumption growth

Kenya fertilizer Adoption of fertilizer

No difference

No difference

No difference

No difference

Unpacking “no gender difference” results When we find no differences, it could

mean one of two things: We can’t tell – the estimates are so noisy

as to be indistinguishable (sample size too small) NO information for policy

The difference is actually zero (well estimated) Policy relevant result

We need more and better evidence A well estimated zero result is informative

If the policy is aimed at a documented gender gap, it did not work

If the policy is not aimed at a gender gap, men and women are affected equally

Why not report more “zero” results? Gender analysis isn’t always done: requires

specific sampling strategy Editors’ bias for non-zero results (publication

bias)

Also important is measuring externalities or unintended effects: Peru (Field 2005)

The impact evaluation of a national land titling program in urban Peru found: No change in women’s labor supply but A 21% reduction in birthrates in program

areas

How to engender your impact evaluation in practice?

4 Steps:1. IE concept stage

what to look for2. Data collection: Design

how to measure it3. Analysis

doing it (cf. Operational Issues , Saturday)4. Results feed back into policy making

what to do with it (cf. Operational Issues , Saturday)

1. IE concept stage

Understand what the gender issues are in your target population How are the program objectives relate to

them Think about causal chain of the

project How might it be different for men and

women? Consider gender differentiated

interventions Design an evaluation that captures

above

Gender differentiated results chains: e.g. Ghana

Teach men to fallow land

Men fallow land

Increased productivi

ty

Teach women to fallow land

Women cannot

fallow land for risk of

expropriation

Provide them with

legal tenure

Women fallow land

Women increase

productivity

Consider bothDirect and Indirect Beneficiaries

1. Gender differences on direct beneficiaries Ex.: the effects of providing irrigation on

female vs. male farmers’ yields2. Gender differences on indirect

beneficiaries Ex.: non-head male and female agro-

processing incomes in households where the head receives the intervention

Indirect beneficiaries

Provide fertilizers to head farmer

Men use fertilizer

Men’s productivi

ty increase

Provide fertilizer to

head farmer

Men uses fertilizer and shares some

with wife

Men’s productivity

increase

Women‘s productivity

increase

2.Data Collection Most rural surveys collect information at the

household level For gender, look into the structure of production

within the household Collect data on land and asset ownership, control

over resources, use of resources, use of labor and results by class of land, type of household member

Gender disaggregation generally requires More indicators More data

▪ For each indicator, what is the relevant level of data collection? (individual, household, plot, community…)

Bigger sample

Qual, quant and feedback

Qualitative work Understand existing constraints and inform questionnaire design

Quantitative baselineMeasure existing conditions before intervention, study determinants of,

quantify problems

Qualitative work Investigate causal chains at work and possible externalities

Quantitative endline Measure overall and gender specific impacts both direct and indirect

Qualitative work Interpret results

Feedback loop Formulate credible policy implications

3. Impact evaluation analysis Analyze direct and indirect impact by gender Draw conclusions on whether policy is

effective as per direct impact Understand whether policy has adverse

effects and what could be done to amend to them

Estimate whether there are significant positive externalities and spill over effects that make the policy even more effective

4. Feedback

Reduce the analysis to simple explanations to support Scale up or down of interventions that

work or do not work well Modifications to interventions that have

adverse effects Discuss with operations and take

advantage of policy cycles to introduce changes

Conclusions

Gender policy is development policy To better influence policy in this direction,

need To experiment with gender differentiated

interventions Measure gender differentiated effects

Develop impact evaluations that are well designed to capture gender differences Target women Measure spillovers Key is to understand how gender plays out in the

causal chain

AADAPT Workshop South AsiaGoa, December 17-21, 2009

Thank you