1. Engendering agricultural censuses, Experience from Africa Diana Tempelman Senior Officer, Gender and Development FAO Regional Office for Africa, Accra Global Forum on Gender Statistics Accra, 26 - 29 January 2009

2. 2 GENDER CONCERNS IN AGRICULTURAL SECTOR Male dominated rural out-migration Access to productive resources: land & animals Access to agricultural inputs: seeds, fertilizer / agro-chemicals, extension / training, finances, farmers organisations (market-)information Access to / provision of family labour Responsibilities

3. 3 Engendering agricultural statistics Outline of presentation 1. Early days – first half 1990-ies 2. Developing methodology - WCA 2000 (1996-2005) 3. Consolidation - WCA 2010 (2006 – 2015) 4. Remaining challenges * WCA = World Census of agriculture

4. 4 1.Early days (1991-2005,..,..)

5. 5 1.Early days – first half 1990-ies Though t? Those feminists from Beijing! Yes, womens agricultural work doesnt show in statistics Early REACTIONS

6. 6 1.Early days – first half 1990-ies ACTIONS re-analysing existing raw data data by sex of Head of Holding technical support to user-producers workshops availability / demand / users of sex-disaggregated agricultural data revision of concepts & definitions

7. 7 1.Early days – first half 1990-ies Awareness on need for sex-disaggregated data Knowledge among statisticians Openness to test collection sex-disaggregated data through existing agricultural surveys / censuses OUTCOME

8. 8 2.Developing a methodology: WCA 2000 (1996-2005)

9. 9 Gender analysis training Data analysis & presentation at sub-national level Data presentation at sub-household level ALL MEMBERS WORK 2.Developing a methodology: WCA 2000 (1996-2005) ACTIONS

10. 10 Guinea 85+ 80 - 84 75 - 79 70 -74 65 - 69 60 - 64 55 - 59 50 - 54 45 - 49 40 - 44 35 - 39 30 - 34 25 - 29 20 - 24 15 -19.10 - 14.5 - 9 > 5 MaleFemale Scale maximum = 800000 Guinea – Labé Region 85+ 80 - 84 75 - 79 70 -74 65 - 69 60 - 64 55 - 59 50 - 54 45 - 49 40 - 44 35 - 39 30 - 34 25 - 29 20 - 24 15 -19.10 - 14.5 - 9 > 5 MaleFemale Scale maximum = 90000 FEMINISATION AGRICULTURAL SECTOR DATA

11. 11 feminisation of agriculture feminisation of agriculture ProvinceAgric. census 1984Agric. survey85– 86Agric. surveys 89 – 90 MaleFemaleMaleFemaleMaleFemale Extreme North91,88.291,88.292,67.4 East91,68.490,89.285,614.4 Central77,822.278,521.571,828.2 South84,915.181,118.971,228.8 Coast79,120.979,920.163,236.8 West75,824.273,626.466.034.0 National85.414.685.214.879,420.6 Heads of agricultural holdings / sex in selected provinces - CAMEROON DATA

12. 12 labour constraints in headed HH DATA Active male members / sex of HoHH, Tanzania

13. 13 Gender variation at sub-national level DATA Area under maize, NIGER

14. 14 Gender variation at sub-national level area under vouandzou, NIGER DATA

15. 15 Under - presentation of women farmers work Area cultivated / crop by sex of agricultural holder – BURKINA FASO DATA

16. 16 Enhanced presentation of women farmers work Area cultivated / crop by sex of agricultural holder & sub-holder NEW CONCEPT > PLOT-MANAGERS DATA

17. 17 2.Developing a methodology: WCA 2000 (1996-2005) Lessons learned document OUTCOME

18. 18 2. Developing a methodology: WCA 2000 (1996-2005) Thematic census reports: Tanzania, Niger OUTCOME

19. 19 3.Consolidation WCA 2010 (2006 - 2015)

20. 20 3.EXAMPLES of Best practises from WCA 2010 i. Analysis of demographic data ii. Access to productive resources (/ sex of HoHH & individual) iii. Destination of agricultural produce / sex of HoHH (min.) iv. Credit, labour and time-use v. Poverty indicators

21. 21 i - Demographic data - NIGER Average size and dependency ratio of agricultural households by sex of Head of Household at regional and national level Source: RGAC 2004-2007, Niger DATA

22. 22 ii - Access to productive resources, LAND

23. 23 LAND Collective management / Head of HH DATA

24. 24 LAND Individual management / active HH members DATA

25. 25 ii - Access to productive resources: ANIMALS

26. 26 Agricultural HH / principal activity / sex HoHH, Niger Source: RGAC 2004-2007, Niger DATA

27. 27 Household level question ii - Access to productive resources: ANIMALS

28. 28 Source: RGAC 2004-2007, Niger Sedentary animals / type of animal / sex of owner, Niger DATA

29. 29 Ownership chicken / sex of owner, Niger DATA Source: RGAC 2004-2007, Niger

30. 30 DATA Ownership pigeons / sex & age of owner, Niger Source: RGAC 2004-2007, Niger

31. 31 iii – destination of agricultural produce Part 2 – Crop usage proportions (percentages) ETHIOPIA

32. 32 Destination of birds / sex of HoHH, Niger DATA Source: RGAC 2004-2007, Niger

33. 33 iv – Credit, labour, time-use. Tanzania Q 13.1: During the year 2002/2003 did any of the household members borrow money for agriculture? Yes or no Q 13.2 If yes, then give details of the credit obtained during the agricultural year 2002/2003 (if the credit was provided in kind, for example by the provision of inputs, then estimate the value)

34. 34 Use of CREDIT / sex of HH member, Tanzania

35. 35 Female HoHH use credit to hire labour - DATA to purchase seeds TANZANIA

36. 36 Reasons for not receiving a loan or credit - UGANDA Source: Uganda – Pilot Census of Agriculture 2003 – PCA Form 2: Section 2.2

37. 37 iv Time-use, Ethiopia Source: Ethiopian Agricultural Sample Enumeration Miscellaneous Questions – 2001/02 (1994 E.C.) 21 How much time do men and women spend in the household on each of the following agricultural activities? Use the codes given below the table Codes: 1 = Not participated 2 = One fourth of the time (1/4) 3 = One half of the time (1/2) 4 = Three fourth of the time (3/4) 5 = Full time 6 = Not applicable

38. 38 iv - Division of Labour, Tanzania DATA

39. 39 V – Poverty indicators, Tanzania Source: United Republic of Tanzania – Agricultural Sample Census 2002/2003- Small holder/Small Scale Farmer Questionnaire: Section 34

40. 40 Frequency of food shortages, Tanzania A higher percent male-headed HHs never has food shortage. A higher percent of female- headed HHs has often or always food shortages. The same pattern appears in the regions. DATA

41. 41 3.Consolidation phase WCA 2010 (2006 – 2015) Integration into: FAO STATISTICAL DEVELOPMENT SERIES ACTIONS

42. 42 3.Consolidation – WCA 2010 (2006 – 2015) ACTIONS Forthcoming

43. 43 3.Consolidation – WCA 2010 (2006 – 2015) ACTIONS Reinforcing sex-disaggregated data in COUNTRY STAT

44. 44 4.Remaining challenges

45. 45 analysis of available sex-disaggregated data use sex-disaggregated data – policy-making, implementation & impact assessment Remaining challenges Discussion points

46. 46 integration national statistical systems Progress & impact indicators Discussion points Remaining challenges

47. 47 IMPROVED DATA COLLECTION Labour Decision-making Responsibilities Discussion points Remaining challenges

48. 48