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Engendering agricultural censuses, Experience from Africa Diana Tempelman Senior Officer, Gender and Development FAO Regional Office for Africa, Accra.

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Presentation on theme: "Engendering agricultural censuses, Experience from Africa Diana Tempelman Senior Officer, Gender and Development FAO Regional Office for Africa, Accra."— Presentation transcript:

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, 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 ( ) 3. Consolidation - WCA 2010 (2006 – 2015) 4. Remaining challenges * WCA = World Census of agriculture

4 4 1.Early days ( ,..,..)

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 ( )

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 ( ) ACTIONS

10 10 Guinea > 5 MaleFemale Scale maximum = Guinea – Labé Region > 5 MaleFemale Scale maximum = 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, , ,828.2 South84, , ,228.8 Coast79, , ,236.8 West75, , National ,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 ( ) Lessons learned document OUTCOME

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

19 19 3.Consolidation WCA 2010 ( )

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 , 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 , Niger DATA

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

28 28 Source: RGAC , Niger Sedentary animals / type of animal / sex of owner, Niger DATA

29 29 Ownership chicken / sex of owner, Niger DATA Source: RGAC , Niger

30 30 DATA Ownership pigeons / sex & age of owner, Niger Source: RGAC , 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 , 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


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