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

• Slide 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 Slide 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 Slide 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 Slide 4 4 1.Early days (1991-2005,..,..) Slide 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 Slide 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 Slide 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 Slide 8 8 2.Developing a methodology: WCA 2000 (1996-2005) Slide 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 Slide 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 Lab 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 Slide 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 Slide 12 12 labour constraints in headed HH DATA Active male members / sex of HoHH, Tanzania Slide 13 13 Gender variation at sub-national level DATA Area under maize, NIGER Slide 14 14 Gender variation at sub-national level area under vouandzou, NIGER DATA Slide 15 15 Under - presentation of women farmers work Area cultivated / crop by sex of agricultural holder BURKINA FASO DATA Slide 16 16 Enhanced presentation of women farmers work Area cultivated / crop by sex of agricultural holder & sub-holder NEW CONCEPT > PLOT-MANAGERS DATA Slide 17 17 2.Developing a methodology: WCA 2000 (1996-2005) Lessons learned document OUTCOME Slide 18 18 2. Developing a methodology: WCA 2000 (1996-2005) Thematic census reports: Tanzania, Niger OUTCOME Slide 19 19 3.Consolidation WCA 2010 (2006 - 2015) Slide 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 Slide 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 Slide 22 22 ii - Access to productive resources, LAND Slide 23 23 LAND Collective management / Head of HH DATA Slide 24 24 LAND Individual management / active HH members DATA Slide 25 25 ii - Access to productive resources: ANIMALS Slide 26 26 Agricultural HH / principal activity / sex HoHH, Niger Source: RGAC 2004-2007, Niger DATA Slide 27 27 Household level question ii - Access to productive resources: ANIMALS Slide 28 28 Source: RGAC 2004-2007, Niger Sedentary animals / type of animal / sex of owner, Niger DATA Slide 29 29 Ownership chicken / sex of owner, Niger DATA Source: RGAC 2004-2007, Niger Slide 30 30 DATA Ownership pigeons / sex & age of owner, Niger Source: RGAC 2004-2007, Niger Slide 31 31 iii destination of agricultural produce Part 2 Crop usage proportions (percentages) ETHIOPIA Slide 32 32 Destination of birds / sex of HoHH, Niger DATA Source: RGAC 2004-2007, Niger Slide 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) Slide 34 34 Use of CREDIT / sex of HH member, Tanzania Slide 35 35 Female HoHH use credit to hire labour - DATA to purchase seeds TANZANIA Slide 36 36 Reasons for not receiving a loan or credit - UGANDA Source: Uganda Pilot Census of Agriculture 2003 PCA Form 2: Section 2.2 Slide 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 Slide 38 38 iv - Division of Labour, Tanzania DATA Slide 39 39 V Poverty indicators, Tanzania Source: United Republic of Tanzania Agricultural Sample Census 2002/2003- Small holder/Small Scale Farmer Questionnaire: Section 34 Slide 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 Slide 41 41 3.Consolidation phase WCA 2010 (2006 2015) Integration into: FAO STATISTICAL DEVELOPMENT SERIES ACTIONS Slide 42 42 3.Consolidation WCA 2010 (2006 2015) ACTIONS Forthcoming Slide 43 43 3.Consolidation WCA 2010 (2006 2015) ACTIONS Reinforcing sex-disaggregated data in COUNTRY STAT Slide 44 44 4.Remaining challenges Slide 45 45 analysis of available sex-disaggregated data use sex-disaggregated data policy-making, implementation & impact assessment Remaining challenges Discussion points Slide 46 46 integration national statistical systems Progress & impact indicators Discussion points Remaining challenges Slide 47 47 IMPROVED DATA COLLECTION Labour Decision-making Responsibilities Discussion points Remaining challenges Slide 48 48