1. How Much Do Women in Africa Contribute to Agriculture? Luc Christiaensen, Talip Kilic, Amparo Palacios-López, AGRICULTURE IN AFRICA TELLING FACTS FROM MYTHS

2. Page 2 RHETORIC “….women are responsible for 60-80 [percent] of the agricultural labour supplied on the continent of Africa.” (UNECA, 1972; FAO, 1995) Women produce 60 to 80 percent of the food in developing countries and 50 percent of the world’s food supply (Momsen, 1991)

3. Page 3 Female Share in Agriculture Labor Uganda 56 Tanzania 53 Malawi 52 Nigeria 37 Ethiopia 29 Niger 24 Total Average 40 REALITY

4. Page 4 MOTIVATION Enduring claims based on inadequately documented statistical analyses. Weaknesses in survey methods; gaps & inconsistencies in gender- disaggregated agricultural statistics; lack of nationally- representative survey data on agriculture Claims often coupled with other (non-compatible) evidence on the gender gap in land productivity to project gains in total agricultural output, living standards & child development outcomes from gender gap alleviations. LSMS-ISA provides unique opportunity to revisit these claims.

5. Page 5 DATA MANIPULATION Our focus: Family crop labor input – Transform household member-disaggregated plot-level labor data into an individual-level database with links to plot, individual & household data. o Treatment of outliers in labor variable, single imputation o Multiple imputation of land variables (GPS using self reported) o Winsorising extreme observations – Compute female agricultural labor share on the whole & across different categorical variables. – Multivariate analysis of the female share of agricultural household labor.

6. Page 6 BENCHMARKING Key findings: Large variation in the female share of agricultural labor, very little variation in the female share of the total population Female Share of Agricultural Labor and Female Share of Total Population

7. Page 7 1. MALE LABOR IS MOSTLY ALLOCATED TO CASH CROPS Key finding: no systematic difference, except for non-edible crops where female labor share allocated tends to be smaller. * The non-edible category includes: -Malawi: tobacco, cotton, sunflower, sugar cane; -Niger: cotton; -Nigeria: cotton, gum arabic, rizga, tobacco, jute, oil palm, palm oil, oil bean; -Tanzania: cotton and tobacco; -Uganda: sugarcane, cotton, tobacco, coffee, cocoa, tea, ginger, curry, oil palm, vanilla Female Share of Agricultural Labor by Crop

8. Page 8 2. LAND PREPARATION IS MAINLY A “MALE ACTIVITY” Key findings: Women are relatively more involved in harvesting and less in land preparation in the countries in which men have the higher share of agricultural labor Notes: *Uganda – Data not available by activity. Female Share of Agricultural Labor by Activity

9. Page 9 3. LABOR ALLOCATION VARIES BY AGE, YOUNG MEN ARE ONLY SLIGHT LESS ENGAGED IN AGRICULTURE Key findings: There is very slight indication of young men less engaged in agriculture, the exception being Nigeria Female Share of Agricultural Labor by Age

10. Page 10 MULTIVARIATE ANALYSIS: Malawi, Niger and Nigeria These three countries offer different contexts with regards to women’s contribution to agriculture: Comparison

11. Page 11 PROCESSES UNDERLYING FEMALE LABOR INPUT INTO AGRICULTURE Factors that may explain women’s contribution to agriculture: (i)Household labor availability and substitutes (ii)Culture-specific gender roles (iii)Economic reasons (iv)Methodological approach to data collection

12. Page 12 PROCESSES UNDERLYING FEMALE LABOR INPUT INTO AGRICULTURE Factors that may explain women’s contribution to agriculture (i)Household labor availability and substitutes o Presence and quantity of both male and female labor in the household. o Access to non-household labor, either hired or exchange o Use of labor saving technologies (ii)Culture-specific gender roles (iii)Economic reasons (iv)Methodological approach to data collection

13. Page 13 PROCESSES UNDERLYING FEMALE LABOR INPUT INTO AGRICULTURE Factors that may explain women’s contribution to agriculture: (i)Household labor availability and substitutes (ii)Culture-specific gender roles o Multiple household activities that women are expected to perform – Headship, presence of children, sick adults o Choice between on-farm and off-farm activities o Crop choice o Ethnicity (iii)Economic reasons (iv)Methodological approach to data collection

14. Page 14 MULTIVARIATE ANALYSIS: Malawi and Niger (cont’d) Outcome variable: Household Female Share or Agricultural Labor Explanatory variables -Demographic factors -Gender and age composition of the HH labor pool -Household labor substitutes: Hired and exchange labor, agricultural implements -Cultural Roles Gender of head of household, presence of infants and young children, adult members suffering sickness -Farm Organization Total Land cultivated by the household, share of cultivated land under different crop categories -Economic Reasons Education of men and women in the hh, wealth, livestock ownership, non-farm income, share of land owned by female, travel time to nearest 20k city, urban gravity, strata fixed effects -Survey Methodology Female manager, female respondent, recall months Specification

15. Page 15 MULTIVARIATE ANALYSIS: Malawi and Niger (cont’d) Result

16. Page 16 PROCESSES UNDERLYING FEMALE LABOR INPUT INTO AGRICULTURE Factors that may explain women’s contribution to agriculture: (i)Household labor availability and substitutes (ii)Culture-specific gender roles (iii)Economic reasons o Farm Organization o Education o Discrimination in the non-farm labor market o Economic status of the household: wealth, livestock o New economic opportunities far from the household compound o Opportunity costs (iv)Methodological approach to data collection

17. Page 17 PROCESSES UNDERLYING FEMALE LABOR INPUT INTO AGRICULTURE Factors that may explain women’s contribution to agriculture: (i)Household labor availability and substitutes (ii)Culture-specific gender roles (iii)Economic reasons (iv)Methodological approach to data collection o Who reports labor data o Most knowledgeable person o Gender bias

18. Page 18 MULTIVARIATE ANALYSIS: Malawi and Niger (cont’d) Result

19. Page 19 MULTIVARIATE ANALYSIS: R square Decomposition Malawi and Nigeria Result

20. Page 20 PREDICTIONS OF POTENTIAL BIAS: Malawi and Nigeria Result

21. Page 21 CONCLUSIONS No evidence supporting the view of women perform the bulk of labor in agriculture (range from 56 to 24%) Number and gender distribution of children, adults, and elderly are the primary factors consistently correlated with the household-level female share of labor in crop production. The multivariate analysis of Malawi and Niger illustrates the differences in characteristics of both countries and how they affect differently the gender allocation decisions, as well as the shortcomings of generalizations based on non-representative samples.