Gender and Agriculture: what do we know about what interventions work for technology adoption? Markus Goldstein The World Bank

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1 Gender and Agriculture: what do we know about what interventions work for technology adoption? Markus Goldstein The World Bank

2 What do we know #1 True or False or Unknowable: Women perform 60 to 80 percent of the agricultural labor in the developing world UN Women, citing World Economic Forum, among many others False: Labor force data (with its own problems) shows women at just over 40% of the economically active economic pop in DCs, with a lot of regional variation

3 What do we know #2 True, False or Unknowable: Women produce 60 to 80 percent of the food in developing countries and half of the world s food production. FAO, others Unknowable. What s food? What s production? And don t they both work on the farm??? (credit for this answer also goes to the FAO)

4 What do we know #3 True, false or unknowable: Women produce less than men (when they farm separately), per acre/hectare? True, in about half of the 20+ studies out there. No difference the other half

5 So are women worse farmers? No evidence for this Bottom line: when you control for access to inputs, land, land tenure security, education, access to extension, there is no difference in yields per hectare between male and female farmers.

6 The female disadvantage Less access to land, less secure land when they have it Less access to fertilizer Lower access to labor Worse human capital Less access to credit Worse access to extension All of these matter for tech adoption à What do we know (rigorously) about what to do about this?

7 What do we know: land Ethiopia, land certification (Deininger, Ali and Alemu): National land title registration program. Low cost, participatory adjudication. Significant reductions in tenure insecurity: HH s with certificates 9% less likely to expect decrease in land holdings and 14% less likely to expect increase Strong effects on land investment: boosted soil & water conservation investments by 30% (equal to costs, easily in the first year) Female-headed HHs 20% more likely to invest in land & spend 72% more time on land investments & repairs

8 What do we know: export crop adoption & marketing Kenya (Ashraf, Gine & Karlan) Provided credit, agricultural extension and export facilitation services to farmers in Central Kenya to adopt and market export crops (French beans and baby corn) For-profit NGO facilitated farmer linkages with banks, farm input retailers, transporters, and exporters Farmers in program (with or without credit) were 19.2% more likely to grow export crops and had 4.3% more land devoted to cash crops & epilogue.. And no significant difference by gender

9 What do we know: insurance Malawi (Gine and Yang) Half the farmers were offered credit to purchase high-yield maize and groundnut seeds Other half were offered credit for high-yield seeds with a required rainfall insurance policy Evidence suggests that farmers were less likely to accept a high-yield seed loan when attached to a rainfall insurance policy 33% of farmers accepted standard loan without insurance. No significant difference by gender

10 What do we know: fertilizer Kenya (Duflo, Kremer, Robinson) Experiment with fertilizer subsidy (as usual) versus commitment or reminders to buy it at end of previous season Small, well-timed discounts can induce some farmers to purchase productive inputs Time dimensions and farmer impatience may be important for technology adoption No significant difference by gender

11 So that s a lot of not significant differences Are women and men benefitting equally? No we can t tell Two ways to get no significant difference Precisely estimated zero Noisy estimates Most studies do not have enough statistical power to tell

12 So we don t know much, what should we do? 1. Need more data (i.e. more individuals) in evaluations now so zero means zero. 2. Studies now are opportunistic we need a framework to ask the right questions in an organized fashion (a common agenda for policy research)

13 Thank you