Gender Policy for Development: Realizing Opportunities

1. Arianna Legovini Manager, Development Impact Evaluation Initiative The World Bank Gender Policy for Development: Realizing Opportunities

2. 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

3. Two questions

4. First question

5. 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)

6. 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

7. Two questions

8. Second question

9. 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

10. 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)

11. 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

12. 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

13. 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%

14. 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

15. 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

16. 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

17. 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

18. 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)

19. Are effects always different? No difference No difference No difference No difference

20. 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

21. 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)

22. 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

23. 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)

24. 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

25. Gender differentiated results chains: e.g. Ghana

26. 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

27. Indirect beneficiaries

28. 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

29. Qual, quant and feedback

30. 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

31. 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

32. Conclusions • 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

33. Thank you