4 th Inter-Agency and Expert Group Meeting (IAEGM) Dead Sea, Jordan 9-10 May 2016 The Gender Disaggregated Data in Agriculture and Rural Development Mohamed Barre, Regional Statistician, FAO

Importance of GDD m Human input/energy crucial to agricultural production & rural development m Data on rural producers (esp. women) still marginally relevant in policy-making m More effective planning through better statistical representation

Importance of GDD In its 2010–2011 report The State of Food and Agriculture: Women in Agriculture, the Food and Agricultural Organization (FAO) emphasizes that achieving gender equality and empowering women in agriculture is crucial for agricultural development and food security. FAO called for improved collection and analysis of baseline data with monitoring and evaluation (M&E) of gender impacts.

Supporting Facts of the Importance of GDD Women represent more than 75% of the rural poor. Economic productivity of the rural poor is more to do empowering women to recognize their capacity. Women are effective in projects aimed to reduce poverty.

Collecting GDD m Different situations of men & women along socioeconomic lines m Specific contributions to economy m Consequence of roles

Need for: m More accurate statistics m Data more relevant to needs & concerns of data users and producers

Censuses & Surveys Must adequately address gender differentiation in: Must adequately address gender differentiation in: m Land ownership and use m Access to credit m Labour & time use m Training & extension services m Technology access m Income

Agriculture Census Round 2020 Methodology/Guidelines The WCA 2010 introduced the theme “Management of the holding” that included the concepts of “sub-holding” and “sub- holder” in order to assess the role of women in agriculture. The WCA 2010 introduced the theme “Management of the holding” that included the concepts of “sub-holding” and “sub- holder” in order to assess the role of women in agriculture. The past experience showed that those items were not suitable for such objective. Therefore in the WCA 2020 Programme that theme has been changed to Theme 10: “Intra-household distribution of managerial decisions and ownership” looking for an improved approach to a gender oriented census.The past experience showed that those items were not suitable for such objective. Therefore in the WCA 2020 Programme that theme has been changed to Theme 10: “Intra-household distribution of managerial decisions and ownership” looking for an improved approach to a gender oriented census. In consequence the items referred to sub-holding and sub-holder and those related to them were changed as: sex of household members making managerial decisions; area of crops by sex of the person managing them; number of livestock by sex of the person managing them; area of land owned by sex of the owner; number of livestock owned by sex of the owner.In consequence the items referred to sub-holding and sub-holder and those related to them were changed as: sex of household members making managerial decisions; area of crops by sex of the person managing them; number of livestock by sex of the person managing them; area of land owned by sex of the owner; number of livestock owned by sex of the owner.

General characteristics of the theme The theme improves the approach for assessing the distribution of managerial decisions and introduces the identification of ownership within the household. The theme improves the approach for assessing the distribution of managerial decisions and introduces the identification of ownership within the household. The main purpose of this theme is to assess the role of gender in decision- making on the holding.The main purpose of this theme is to assess the role of gender in decision- making on the holding. Some countries may wish to reflect more precisely the intra-household distribution of decision- making and ownership within the holding, particularly to investigate the gender-based differences in decision-making.Some countries may wish to reflect more precisely the intra-household distribution of decision- making and ownership within the holding, particularly to investigate the gender-based differences in decision-making. It is recommended that countries collect data on these items for each individual household member. This needs effort. And possibility of analysing managerial decisions not only by sex but also by other characteristics such as age and education.It is recommended that countries collect data on these items for each individual household member. This needs effort. And possibility of analysing managerial decisions not only by sex but also by other characteristics such as age and education.

Managerial Decisions In general, two different levels of decisions can be distinguished on the holding: In general, two different levels of decisions can be distinguished on the holding: 1) Planned decision for the year – for example “this year we plant maize” or “this year we market all our bean production” 1) Planned decision for the year – for example “this year we plant maize” or “this year we market all our bean production” 2) day-to-day operational decisions, such as when to weed or spray the crops or graze the livestock.

Items Theme 10 comprises 5 items. The first three refer to management while the last two refer to ownership: Management 1001 Sex of household members making managerial decisions; 1002 Area of crops by sex of the person managing them; 1003 Number of livestock by sex of the person managing them. Ownership 1004 Area of land owned by sex of the owner; 1005 Number of livestock by sex of the owner.

Statistics Users: m Planners & decision-makers m Development experts m NGOs m General public m Gender equity advocates m Others

Statistics Users: m Planners & decision-makers m Development experts m NGOs m General public m Gender equity advocates m Others

Statistics Users: m Planners & decision-makers m Development experts m NGOs m General public m Gender equity advocates m Others

Producing GDD: m Identify gender issues for special treatment m Identify gender-relevant data m Review existing data sources m Improve existing sources/develop new programmes m Compile, analyse, present, disseminate data

Main Information Sources m Censuses (agricultural, population, housing) m Surveys (farm, rural, employment, food consumption, household income/expenditure) m Time-use studies

GDD Constraints m Lack of reliable sources m Lack of precision m Inadequate concepts/definitions m Weak analysis m Weak dissemination system m Lack of audience analysis m Competition with other priorities

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