arianna legovini manager development impact evaluation initiative the world bank n.
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Arianna Legovini Manager, Development Impact Evaluation Initiative The World Bank. Gender Policy for Development: Realizing Opportunities. Motivation. Gender matters for development E vidence from research Policy can address gender gaps

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arianna legovini manager development impact evaluation initiative the world bank
Arianna Legovini

Manager, Development Impact Evaluation Initiative

The World Bank

Gender Policy for Development: Realizing Opportunities

  • 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
development improves gender balance
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
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
venues for gender to affect 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
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
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
Create wealth by gender equality: Burkina Faso (Udry1996)
  • 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
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
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
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
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
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
Measuring differential impacts: Ethiopia (Deiningeret 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
Are effects always different?

No difference

No difference

No difference

No difference

unpacking no gender difference results
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
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 e xternalities or unintended effects peru field 2005
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
How to engender your impact evaluation in practice?

4 Steps:

  • IE concept stage

 whatto look for

  • Data collection: Design

 howto measure it

  • Analysis

 doing it (cf. Operational Issues , Saturday)

  • Results feed back into policy making

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

1 ie concept stage
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
consider both direct and indirect beneficiaries
Consider bothDirect and Indirect Beneficiaries
  • Gender differences on direct beneficiaries
    • Ex.: the effects of providing irrigation on female vs. male farmers’ yields
  • Gender differences on indirect beneficiaries
    • Ex.: non-head male and female agro-processing incomes in households where the head receives the intervention
data collection
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
3 impact evaluation analysis
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
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
  • Gender policy is development policy
  • To better influence policy in this direction, need
    • To experiment with gender differentiated interventions
    • Measure gender differentiated effects
  • Developimpact 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