RAF/AFCAS/07 – 2 c
December 2007
Agenda Item 4
AFRICAN COMMISSION ON AGRICULTURAL STATISTICS
Twentieth Session
Algiers, Algeria, 10 - 13 December 2007
AGRI-GENDER DATABASE
TOOL KIT FOR COLLECTION AND USE OF SEX DISAGGREGATED DATA
1. WORLD PROGRAMME FOR THE CENSUS OF AGRICULTURAL (WCA) 1930–’90
The first six rounds of the World programme for the Census of Agricultural
(WCA 1930 - 1980) focussed mainly on data collection concerning the quantities produced of
selected principal agricultural products (crops and livestock). Data collection related to the human
factor in agricultural production, if at all collected, pertained to the head of the household or
agricultural holder, initially without distinction of his/her sex. Women’s involvement in
agricultural production was usually perceived as domestic or reproductive work rather than
economic or productive work and was therefore seldom recorded (FAO, 2005b).
Male and female farmers are affected differently by agricultural policies and programmes because
of their diverse yet often complementary roles and responsibilities in agricultural production,
disparities in their access to and control over productive resources and the existence of social
norms and legal legislations that often favour men over women. Sex-disaggregated agricultural
data can be used to illustrate economic, social and political differences that may exist between
male and female farmers, to assess the possible impacts of these differences on their production
and productivity, and to better understand and recognize men and women’s (changing) roles and
responsibilities related to the agricultural sector, rural development and food security.
With the 7th round of the programme (1990), more attention was being paid to the collection of
socio-economic and sex-disaggregated agricultural data. New data requirements had come up
because of the expanding role of the private sector and civil society, increased decentralization in
decision-making, a rising demand for greater transparency in decision-making, the emergence of
poverty reduction and food security programmes and by the end of that decade, the establishment
of the Millennium Development Goals. Data producers responded by expanding the number of
topics covered in line with the change in focus from agricultural to rural development, presenting
E
data at sub-national levels and accepting the need to reflect gender concerns through the
collection of sex-disaggregated data at household and sub-household levels. Agricultural censuses
carried out during this round of the WCA provided more data on human resources required for
agricultural production, including data on women’s contributions to agricultural production and
their access to productive resources (FAO, 1995).
2.
GENDER RELATED DATA IN THE 2000 WCA
The 2000 round of the programme expanded data collection to also cover small-scale and periurban agricultural activities and started to address gender biases in statistical tools used.
During this round of WCA, several countries in Africa1 experimented with analysing and
presenting data at sub-holding2 level, introducing the sub-holder3 concept to try and reduce the
under-representation of women farmers’ efforts in agricultural production in statistical data
collection. These concepts allow for a better assessment of the role of all household members,
particularly women, in the management of an agricultural holding, as their productive activities
are statistically no longer attributed to the male head of households, as was previously the case.
Data presentation at sub-holding level and per sex of sub-holder allows for extensive crosstabulation of production factors such as plot/field sizes, cultures and inputs used with sociodemographic factors. The data thus obtained provides the necessary basis for in-depth analysis of
intra-household sex and age-based differences in agricultural production.
Furthermore, many countries started collecting data in such a way that presentation of the results
became possible at sub-national level, be it provincial, regional and at times at district level. This
further contributed to greater visibility of female farmers work as most gender-based differences, like
any other variation, show more clearly at sub-national levels.
The resulting data provides useful insights in and confirms trends earlier identified by incidental case
study material in relation to, among others:

The feminisation of the agricultural sector;

The male-dominated rural out-migration;

Differences between male and female farmers’ access to productive resources like land, water
and animals, but also differences in access to extension services, credit and marketing
facilities;

Differences in availability of family –unpaid- labour and its impact on female farmers’
production costs;

Differences in preferences in crops cultivated and animals reared.
Burkina Faso, Côte d’Ivoire, Guinea, Mozambique, Niger and Sénégal.
A sub-holding is defined as a single agricultural activity or group of activities managed by a particular
person or group of persons in the holder’s household on behalf of the agricultural holder. There may be one or
more than one sub-holding in a holding. A sub-holding could comprise a single plot, a whole field, a whole
parcel, or even the whole holding. A sub-holding could also be a livestock operation associated with a plot,
field or parcel, or a livestock operation without any land (FAO, 2005a).
3
A sub-holder is a person responsible for managing a sub-holding on the holder’s behalf. There is only one
sub-holder in a sub-holding, but there may be more than one sub-holder in a holding. The holder may or may
not be a sub-holder. The sub-holder concept is broadly similar to the concepts of “plot manager” (or
“responsable de parcelle” in French) and “farm operator” used in some countries (FAO, 2005a).
2
1
2
Obviously such differences vary between countries and between different regions within the
countries. Most important however is that data are now becoming available, allowing for targeted
planning of agricultural and rural development programmes and gender-specific evaluation and
monitoring of the impact of such programmes.
Noteworthy here is the publication of thematic census reports providing insight into gender relations
in the agricultural sector. In September 2007, Tanzania launched Volume IX of its 2002/2003
agricultural sample census, entitled “Gender profile of smallholder rural agricultural population in
Tanzania Mainland” and Niger and Cape Verde are expected to follow shortly with similar thematic
census reports.
The PowerPoint presentation with give further details of data collected by selected countries
3.
GENDER RELATED DATA IN THE 2010 WCA
For the current round of the World Programme for the Census of Agriculture (WCA 2010), FAO
recommends the use of a modular approach, consisting of: -i- a core census module covering a
limited number of variables on which data is to be collected in an exhaustive manner and –iitwelve supplementary modules4, collecting data in greater detail through sample surveys, covering
sub-sectors selected on the basis of the country-specific circumstances. This way the organisation
hopes to support countries in reducing costs and the time required for data processing and analysis
thereby facilitating early dissemination of the results.
The approach proposed by FAO for the 2010 round of the programme is expected to further
enhance the production and use of sex-disaggregated agricultural data for a number of reasons:

First of all, this round takes into account the need to use agricultural census data for
monitoring countries’ achievements towards attaining the Millennium Development Goals,
including MDG 3 Promote gender equality and empower women.

Secondly, the agricultural holder5 concept has been modified to better reflect the realities of
farm management practices such as differences in men’s and women’s managerial and
financial control over the production, storage, processing and marketing of agricultural
products. It is now recognized that more than one person, for example a husband and a wife,
could manage a holding as joint holders.6
4
Theme 01: Land / Theme 02: Irrigation and water management / Theme 03: Crops / Theme 04: Livestock
/ Theme 05: Agricultural practices / Theme 06: Agricultural services / Theme 07: Demographic and social
characteristics / Theme 08: Farm labour / Theme 09: Household food security / Theme 10: Aquaculture /
Theme 11: Forestry / Theme 12: Management of the holding
5
The agricultural holder is defined as the person who makes the major decisions regarding resource use and
exercises management control over the agricultural holding. The agricultural holder has technical and
economic responsibility for the holding and may take all responsibilities directly, or delegate responsibilities
related to day-to-day wok management to a hired manager (FAO, 2005a).
6
A joint holder is a person making the major decisions regarding resource use and exercising management
control over the agricultural holding operations, in conjunction with another person. A joint holder can be
from within the same household of from a different household (FAO, 2005a).
3

Thirdly, the programme encourages countries to include items in the supplementary
modules of their census that provide greater insight into the roles and responsibilities of men
and women in agricultural production. Theme 12 of the supplementary modules covers data
collection about the Management of the holding, including reference to any sub-holders
mentioned before, that may be operating on a farm. Information obtained under Theme 12
becomes particular relevant if the data collection is linked to other modules, especially those
pertaining to access to productive resources (themes 01, 02, 04, 10 and 11), agricultural
practices and inputs (themes 05 and 06) and farm labour (theme 08).

Finally, employment concepts have been amended in line with standards of the International
Labour Organization to better reflect the structure of employment in rural areas (FAO,
2005a).
4.
AGRI-GENDER DATABASE – STATISTICAL TOOL FOR COLLECTION OF
SEX-DISAGGREGATED DATA
This database is being prepared in support of increased production and analysis of sexdisaggregated agricultural data. It presents gender-sensitive questions/questionnaire components
and tables obtained from agricultural censuses that have been implemented in Africa during the
2000 round of the WCA programme.
The database covers the following nine data items:
Data items essential for gender specific analysis of the agricultural sector
1
Agricultural population and households
2
Access to productive resources
3
Production and productivity
4
Destination of agricultural produce
5
Labour and time-use
6
Income and expenditures
7
Membership of agricultural/farmer organisations
8
Food security
9
Poverty indicators
The list of items is not exhaustive but highlights subjects which are considered essential for
gender specific analysis of the agricultural sector. Data items 1, 2, 3 and 5 represent minimum
data requirements to adequately reflect the roles and responsibilities of men and women farmers
in the agricultural sector. Collection of sex-disaggregated data on data items 4, 6, 7 and 8 are
considered vital for planning food security and poverty reduction programmes and advancing
gender equality and the empowerment of women. They are crucial for measuring achievements
made towards the Millennium Development Goals and other internationally set development
targets.
The Agri-gender database comprises two sections. Section 1 presents examples of gendersensitive questions and questionnaire components obtained from recent agricultural censuses,
while Section 2 presents examples of tables that can facilitate analysis and presentation of the data
collected. Each table provides sex-specific information and as such builds on the more classical
presentation of agricultural census data.
This presentation will look into data items 1, 2, 3, and 5 for reasons of time.
4.1
Data item 1 - Agricultural population and households
4
The demographic data collected on agricultural population and households provide important
information on the gender-based structure of an agricultural population, the composition of
agricultural households and socio-economic characteristics of the household members.
Analysis of the agricultural population by sex and age groups at national and sub-national levels
offers insight into the effects of rural out-migration, civil conflicts and the HIV/AIDS pandemic
on the agricultural labour force and availability of farm labour.
Agricultural census data from Guinea, clearly reflect a phenomenon commonly called
“feminisation of the agricultural sector”
Figure 1: Agricultural population at the national
level per sex and age group in Guinea
Figure 2: Agricultural population per sex and age
group in the Labé Region of Guinea
85+
85+
80 - 84
80 - 84
75 - 79
75 - 79
70 -74
70 -74
65 - 69
65 - 69
60 - 64
60 - 64
55 - 59
55 - 59
50 - 54
50 - 54
45 - 49
45 - 49
40 - 44
40 - 44
35 - 39
35 - 39
30 - 34
30 - 34
25 - 29
25 - 29
20 - 24
20 - 24
15 -19
15 -19
.10 - 14
.10 - 14
.5 - 9
.5 - 9
>5
>5
Scale maximum = 800000
Male
Female
Scale maximum = 90000
Male

The
degre
Source: National Agricultural Census (RNA), Guinea, 2000
e
of
analys
Agricultural census data from Tanzania illustrates the impact male rural out-migration
is, can have
which
on the availability of male active members in female-headed households.
can
be
Table 1 Active agriculture Population by Sex in Male and Female Headed Agricultural Households
applie
Male- headed households
Female- headed households d
to
this
male:
Male:
questi
Selected
female
Total
males
females
female
Total
males
females
Regions
ratio
per hh
per hh
per hh
ratio
per hh
per hh
on,
per hh
is
Arusha
rather
110:100
2.8
1.5
1.3
65:100
2.3
0.9
1.4
limited
Mtwara
97:100
2.4
1.2
1.2
38:100
1.7
0.5
1.2
due to
Ruvuma
102:100
2.6
1.3
1.3
38:100
1.8
0.5
1.3
the
Iringa
107:100
2.6
1.3
1.2
38:100
1.8
0.5
small1.3
Mbeya
105:100
2.5
1.3
1.2
43:100
1.7
0.5
1.2
numb
Mwanza
107:100
3.3
1.7
1.6
56:100
2.5
0.9
er 1.6
of
Mara
activiti
105:100
3.1
1.6
1.5
60:100
2.3
0.9
1.4
Manyara
es 1.5
115:100
3.0
1.6
1.4
64:100
2.4
0.9
includ
Tanzania
Mainland
ed, 1.3
106:100
2.8
1.4
1.4
49:100
2.0
0.7
the
Source: National sample census of agriculture, Tanzania, 2002/03
groupi
ng of
The following chart then illustrates how the lack of male adult family labour effectshouse
the use of
credit in female headed households.
hold
memb
5
ers
(male
and
femal
Percent
Chart 7.5 Percent of Households that have access to Credit by sex of
Household Head
30
20
10
0
Labour
Use of Credit
Seeds
Fertili zers
Agro-che
micals
Tools / Irrigation Livestock
Other
Equip
Structures
ment
Male Headed
Female Headed
Source: National
sample census of
agriculture,
Tanzania, 2002/03
These examples clearly show how cross-tabulating demographic data with other agricultural
related data contributes to greater insights in gender-related issues prevailing in the agricultural
sector.
4.2
Data item 2 - Access to productive resources
Sex-disaggregated data on men and women’s access to and control over productive resources7
provide vital information for planners and policy makers. They illustrate gender differences in
agricultural production and productivity and provide insight into support measures needed.
Land is one if not the most important productive resource for farmers. The Agri-gender database
presents an example from Niger on how to collect data about male and female sub-holders’
access to land within the family agricultural holding. Column 1 and 2 record the number of the
plots and fields, column 3 and 4 record the name and sex of the sub-holder or plot manager with
column 5 collecting data on whether the land is cultivated jointly, as “family land” or
individually, (col. 5) and how it was obtained (col. 8).
Example: Question regarding landownership by sub-holder
Identification
champs, parcelles
1
2
Inscrire le
Inscrire le
numéro
numéro
d'ordre
d'ordre de
du champ la parcelle
|__|__|
|__|__|
|__|__|
|__|__|
|__|__|
|__|__|
Etc.
INVENTAIRE DES PARCELLES DU MËNAGE AGRICOLE
Nom et prénoms du responsable Sexe du responsable Type de gestion de la
de la parcelle
de la parcelle
parcelle
3
4
5
Inscrire d'abord le nom, puis les
prénoms du responsable
1 = Masculin
1 = Individuel
de la parcelle en commençant
2 = Féminin
2 = Collectif
par le Chef de Ménage
|__|
|__|
|__|
|__|
|__|
|__|
Continue
INVENTAIRE DES PARCELLES DU MËNAGE AGRICOLE
Passé cultural
Système de
Mode
7
Type de relief
land, animals, agricultural inputs, labour, equipment, credit, information, extension services
6
de la parcelle
6
1 = Cultivé
2 = Jachère
|__|
|__|
|__|
culture
7
1 = Culture pure
2 = Cult. associé
|__|
|__|
|__|
d'acquisition
8
1 = Héritage
2 = Achat
3 = Fermage ou métayage
4 = Prêt
5 = Don
6 = Autre
|__|
|__|
|__|
9
1 = Plaine ou plateau
2 = Bas-fonds
3 = Versant colline montagne
|__|
|__|
|__|
Etc.
Source: Recensement général de l’agriculture et du cheptel, Niger, 2005/06
Access to land is particular important give that landownership may have an impact on access to:
credit, membership in cooperatives and the services these may provide. Moreover, insecure landrights reduces farmers’ incentives to invest in higher yielding agricultural practices or to preserve
and regenerate the land.
The Niger census also provided interesting results about the ownership of livestock and poultry,
which was recorded by sex of the owner (individual household member). Based on the countryspecific circumstances, the results given in Table 2 indicate a relatively high percentage of
sedentary cows belonging to a woman, whereas the percentage of female owned chicken was
much lower than expected.
Table 2 – Ownership of selected animals by sex of owner – Niger
Region
Cows
men
women
%
%
74.2
25.8
83.6
16.4
84.1
15.9
76.7
23.3
65.1
34.9
80.5
19.5
76.9
23.1
69.9
30.1
Sheep
men
women
%
%
73.1
26.9
76.0
24.0
60.9
39.1
48.3
51.7
62.4
37.6
61.7
38.3
57.5
42.5
64.1
35.9
Goats
men
women
%
%
44.8
55.2
72.1
27.9
35.2
64.8
25.2
74.8
51.1
48.9
58.0
42.0
42.9
57.1
58.4
41.6
Agadez
Diffa
Dosso
Maradi
Tahoua
Tillabery
Zinder
Niamey
Ensemble
77.6
22.4
59.9
40.1
45.2
54.8
Niger
Source: Recensement général de l’agriculture et du cheptel, Niger, 2005/06
Birds
men
women
%
%
46.0
54.0
68.3
31.7
66.1
33.9
72.4
27.6
74.7
25.3
61.3
38.7
74.4
25.6
74.3
25.7
70.3
29.7
Senegal’s last agricultural census recorded data on men and women’s access to agricultural
extension, which showed that at national level, male sub-holders receive three times more
extension services that female sub-holders.
Table 3: Access to agricultural extension services by plot manager – Senegal
Region
Male Plot Managers
Female Plot Managers
7
Total
%
N
Region of Diourbel
Region of Thiès
Region of Koalack
Region of Kolda
National
16 197
7 826
39 889
18 364
155 072
%
4.62
1.37
6.55
4.05
4.08
N
4 722
5 895
9 075
4 612
53 253
%
1.35
1.03
1.47
1.02
1.40
20 919
13 721
48 964
22 976
208 325
3.9
1.2
5.6
3.4
3.4
Source: Recensement National de l'Agriculture, Sénégal, 1998-99
4.3
Data item 3 - Production and productivity
Sex-disaggregated data on agricultural production and productivity, especially at sub-holding
level, can give insight into who produces what, the amount produced and -when linked with other
production factors- the constraints encountered by men and women farmers in this regard.
The following section from the 1999/2000 Mali agricultural census gives a good example of how
data on planted area and kind of culture can be recapitulated and then be used for calculations
about the production level of sub-holders. The Agri-gender database recommends that column
156 is added to ensure that the information on the sex of the sub-holder remains linked to the subholding as this link could easily get lost when demographic data is collected on a separate
questionnaire sheet.
RECAPITULATIF DES BLOCS ET PARCELLES DE L’EXPLOITATION TRADITIONELLE
N° Bloc
N° parcelle
Saison :
1=
Hivern.
2= Hors
hivern.
Culture principale
Nom
Code
Superficie en ares
N° d’ordre
Nom du
Sexe du
du
responsable responsable
responsabl
de la
de la parcelle
e de mise
parcelle
1=M
en val. de
2=F
la parcelle
154
155
156
I___I___I _________
|__|
148
I__I__I
149
I__I__I
150
I___I
151
_____
152
I__|__|__I
153
I__I__I__I__I,I__I__I
I__I__I
I__I__I
I___I
_____
I__|__|__I
I__I__I__I__I,I__I__I
I___I___I
_________
|__|
I__I__I
I__I__I
I___I
_____
I__|__|__I
I__I__I__I__I,I__I__I
I___I___I
_________
|__|
Etc.
Total (1)
I___I___I___I___I___I, I___I___I
Source : République du Mali – Recensement Général de l’Agriculture 1999 / 2000
Data on productivity levels per sex of (sub-) holder is more difficult to establish, as most census
programmes apply one common multiplier factor determined as an average for a particular agroecological zone. In this regard it will be interesting to see the results of the Niger census, which
tried to collect information about quantities produced at plot level. When compared with plot
sizes and the sex of the plot manager this could give valuable information regarding differences,
if any, in productivity levels of male and female sub-holders.
8
Code
Champ Parcelle
1
|__|__|
|__|__|
|__|__|
|__|__|
Etc.
2
|__|__|
|__|__|
|__|__|
|__|__|
Système
Sexe du
de
responsable Nom de la
culture
de parcelle
culture
(code) (1 = M ; 2 = F)
3
3’
4
………….
|__|
|__|
|__|
………….
|__|
|__|
………….
|__|
|__|
………….
|__|
Code
de la
culture
5
|__|__|
|__|__|
|__|__|
|__|__|
Poids brut en
kilogramme
(kg)
Poids net en
kilogramme
(kg)
6
|__|__|,|__|__|__|
|__|__|,|__|__|__|
|__|__|,|__|__|__|
|__|__|,|__|__|__|
7
|__|__|,|__|__|__|
|__|__|,|__|__|__|
|__|__|,|__|__|__|
|__|__|,|__|__|__|
Source République du Niger – Recensement Général de l’Agriculture et du Cheptel 2004-2006
The Agri-gender database also comprises an example from the 2001 agricultural census of the
Gambia on how to collect data about ownership of animals by male and female members of an
agricultural household.
9
11.
Enter in the tables below the number of livestock and/or poultry that the holder has on this
day of filing the questionnaire
Number of Cattle
Males
Females
A. CATTLE AND CALVES
(a)
Total number of cattle of all ages
(If “None” enter X and move to B)
Total number under 2 years of age
Total number 2 years of age and over
(c)
Number of Goats
Males
Females
B. GOATS
(a)
Total number of goats of all ages
(If “None” enter X and move to C)
Total number under 1 years of age
Total number1 year of age and over
(b)
(a)
Total number of sheep of all ages
(If “None” enter X and move to D)
Total number under 1 years of age
Total number 1 year of age and over
D. PIGS
(a)
Total number of pigs of all ages
(If “None” enter X and move to E)
Total number under 6 months of age
Total number 6 months of age and over
Hens, Cocks,
Pullets and
Chicks
(b)
(e)
Total
Sheep
(d)
Other Poultry such
as Turkeys, Guinea
Fowls, etc.
(f)
Number of Sheep managed or
owned by sex of members
Male
Female
(e)
Total Pigs
(d)
(f)
Number of Goats managed or
owned by sex of members
Male
Female
(d)
(a)
(b)
(c)
Total number
Total under 6 months
XXXX
XXXXXXXXXXX
6 months and over
XXXX
XXXXXXXXXXX
Source: The Republic of the Gambia – Agricultural Census 2001
10
(e)
Total
Goats
(c)
Number of Pigs
Males
Females
(b)
(c)
Ducks and
Ducklings
(d)
(c)
Number of Sheep
Males
Females
C. SHEEP AND LAMBS
E. POULTRY AND RABBITS
(b)
Number of Cattle managed or
owned by sex of members
Male
Female
Total
Cattle
(f)
Number of Pigs managed or
owned by sex of members
Male
Female
(e)
(f)
Other Farm
Animals such
as beehives,
etc. (Specify)
(d)
XXXXXXXX
XXXXXXXX
Rabbits
(e)
XXXXXXXX
XXXXXXXX
4.4
Data item 5 - Labour and time-use

Labour
Smallholder agricultural activities depend largely on the holders’ access to labour. Data
presented earlier from Tanzania indicate that female headed households tend to have less adult
family labour at their disposal compared to male headed households As shown, this has an impact
on their production costs and the way they use credit.
Assessing the amount of work carried out by female farmers has proven to be more difficult than
for male farmers due to a number of reasons. Firstly, women’s work often contributes to outputs
of others through, for example, the provision of unpaid family labour. Secondly, rural women’s
work is frequently destined for household consumption and, as such, is/was not always
recognised as productive work. Thirdly, women are often engaged in a range of activities spread
out over the day such as clean/washing, working on the family plot as well as their own, taking
care of animals, gathering fuel wood and water, transporting agricultural produce to the home or
market and preparing meals for the family. IFAD estimates that household work (including the
fetching of water and fuel wood) may take up between one third and half of a woman’s working
day and therefore limits their abilities to be fully engaged in productive activities, though it
indirectly contributes to the productive activities of other household members (IFAD, 2001).
But the collection of sex-disaggregated data on agricultural labour has improved in the past
decade, as most countries now collect sex and age-disaggregated data on different kinds of
agricultural labourers employed (family labourers, hired workers and mutual support groups),
their employment status (seasonal, occasional or permanent) and payment status (unpaid versus
paid labour).
The following example from Ethiopia gives a basic and clear overview of the holders’ use of
various types of farm labourers, indicating the sex and the number of permanent and temporary
workers, family workers or partners, whether they were paid or not and whether they were
employed on a full-time or seasonal basis.
5.
S/N
5.1
5.2
5.3
5.4
5.5
How many persons were engaged on the holding other than the holder? (Last 12 months)
Labour status
Permanent paid workers (full-time)
Temporary (seasonal paid workers)
Unpaid family workers
Partners (share holders paid/unpaid)
Total persons engaged at any time of the year
Male
Number
Female
Total
Source: Ethiopian Agricultural Sample Enumeration Miscellaneous Questions – 2001/02
This example does however not provide any insight in the type of agricultural activities
performed by the labourers, their ages (adults or children) and payments received.
The Uganda 2003 Pilot Census of Agriculture presents an example of how more detailed
information could be collected about farm labour by sex, age, labour status and activity. This
format gives greater insight into the division of agricultural tasks between men, women and
children, while cross-tabulations with the sex of the holder will show any differences between
male and female holders in terms of their access to farm labour.
11
5.3.1 Number of household members working on the holding
26
How many household members worked permanently or temporarily on the holding this agricultural
season? (Give the number worked for all categories).
Number of household members who worked
Number of household members who worked
permanently
temporarily
Males
Females
Children
Males
Females
Children
Boys
Girls
Boys
Girls
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
5.3.2 Household members work on the holding by specific operations
27
How many household members worked permanently or temporarily on the holding this agricultural
season on the specified operations? (Give the number worked for all categories).
Number who participated
Operation
Code
Children
Males
Females
Boys
Girls
(1)
(2)
(3)
(4)
(5)
(6)
Ploughing
1
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
Planting
2
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
Weeding
3
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
Pruning
4
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
Harvesting
5
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
Bush clearing
6
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
Herding
7
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
Feeding
8
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
Milking
9
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
Fish farming
10
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
Construction/maintenance
11
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
Other, specify
12
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
5.3.3 Hired labour
28
Were any persons hired permanently or temporarily for pay in cash or kind on the holding
this agricultural season?
|__| 1 = yes, 2 = No.
If yes, go to 29
If no, go to 32
5.3.4 Hired labour total
29
How many persons were hired as permanent or temporary labourers during this agricultural
season? (Give the number worked for all categories).
30
For how long period did you usually hire each type of labour (no. of expected days if piece meal)?
Number of permanent labourers
Males
Females
Children
Boys
Girls
(1)
(2)
(3)
(4)
Number of temporary labourers
Males
Females
Children
Boys
Girls
(5)
(6)
(7)
(8)
1. Number
2. Payment
period in no. of
days
5.3.5 Hired labour by specification
27
How many persons were hired as permanent or temporary labourers during this agricultural
season on the specified operations? (Give the number hired for all categories).
[Hired] Labourers
12
Operation
(1)
Ploughing
Planting
Weeding
Pruning
Harvesting
Bush clearing
Herding
Feeding
Milking
Fish farming
Construction/maintenance
Other, specify
Code
(2)
1
2
3
4
5
6
7
8
9
10
11
12
Males
(3)
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
Females
(4)
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
Children
Boys
Girls
(5)
(6)
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
|__|__|__|
Source: Uganda – Pilot Census of Agriculture 2003
The list of agricultural operations/activities could be modified and/or extended depending on the
country specific circumstances (activities relating to irrigation, manure application, crop spraying,
crop storage, the transportation of agricultural products and agro-processing)

Time use
Time-use surveys are one of the best tools for evaluating gender specific contributions to
economic and non-economic activities of a household. They give insight into differences in timeuse and time constraints between male and female farmers. These surveys are however timeconsuming and complex, which is why time-use related questions form seldom part of
agricultural censuses.
Moreover, the concept of “time worked” in the agricultural sector is much more difficult to
capture than in other economic sectors because “There is no fixed place of work, as farm work
includes working in the fields, preparing agricultural products for marketing, taking farm produce
to the market, bringing farm requisites from town, keeping farm records, etc. Part of the work is
done on the holding, another part in the holder’s dwelling, still another in markets or in towns,
etc. Travel between these different sites of work may be long and time-consuming. It is therefore
advisable that all relevant periods of work and travel time are taken into account when recording
the time worked by the holder, family workers and paid workers” (FAO, 1999b).
The Agri-gender database includes examples from two countries that did include a time-use
questions in their agricultural census: Ethiopia and Tunisia.
The example from Ethiopia is basic but allows for a comparison of time-use of male and female
household members with regard to the farming activities listed. Cross-tabulations of the results
with the sex of the head of household will show any differences between male and femaleheaded households in terms of the time spent by their male and female household members on
selected agricultural activities. The Agri-gender database suggests the addition of two columns,
permitting data collection on children’s contributions to farm labour.
21
S/N
21.1
21.2
21.3
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
Make
(code)
|__|
|__|
|__|
Activity
Tilling
Sowing
Weeding
13
Female
(code)
|__|
|__|
|__|
Children(code)
Boys
Girls
|__|
|__|
|__|
|__|
|__|
|__|
21.4
21.5
21.6
21.7
Harvesting
Feeding/Treating
Milking
Marketing of agricultural products
|__|
|__|
|__|
|__|
|__|
|__|
|__|
|__|
|__|
|__|
|__|
|__|
|__|
|__|
|__|
|__|
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
Source: Ethiopian Agricultural Sample Enumeration Miscellaneous Questions
This following example from Tunisia provides more detailed information on time spent by the
respondent during the past day, week, month and year on agricultural and non-agricultural activities.
When cross- tabulated with the number of the household member responding it would illustrate any
differences in time-use of male and female household members.
Nom …..
GRILLE BUDGET-TEMPS
Temps
Heure réveil!_!_!_!_! HIER.......
(heures)
Semaine dernière (heures)
Activités
P.
Matin Midi A. midi Soir Total 2è
mat
j.
3è j. 4è
j.
5è
j.
6è
j.
A. AGRICOLE
1. Préparation du
sol (labour,
binage, sarclage,
désherbage,
fertilisation,
semis, taille,
piquage,
irrigation)
2. Récolte,
cueillette,
moisson
3. Act. paraagricoles
(transport, récolte,
marché, entretien,
stock, etc.)
14
Mois dernier (jours)
7è
j.
Année dernière (jours)
Total 2ème 3ème 4ème Total Eté Print. Autom Hiver Total
CONTINUE
B. ELEVAGE
1. Elevage
ruminants (ovins,
bovins, caprins,
soins,
alimentation,
tonte, etc.)
2. Petit élevage
(poulailler,
apiculture,
cuniculture, etc.)
C. PECHE
1. Pêche côtière
2. Pêche palourde
D. ACTIVITES DOMESTIQUES NON REMUNEREES
1. Production
domestique
(transf. produits
agricoles,
séchage, etc.)
2. Artisanat
3. Préparation du
repas et du pain
4. Autres travaux
ménagers et soins
membres de la
famille
5. Transport eau
6. Transport bois
7.
Commercialisatio
n
E. ACTIVITES. NON AGRICOLE. REMUNEREES (commerce. services. administration., industrie)
1. Secteur
structuré
2. Secteur
informel
F. AUTRES
1. Ecole
2. Déplacement
lieu de travail
NB: Faire suivre le chiffre par l’indice “a” si l’activité est exercée sur une autre exploitation.
Source: Statistiques et Genre Recensements Agricole – Orientations pour une révision des concepts et de la
méthodologie (FAO, 1999)
15
5.
CONCLUSION
This paper gave a brief overview of how agricultural statistical data evolved during the
subsequent cycles of the World Programme for the Census of Agricultural (WCA), gradually
expanding to, among others, data collection covering the human factor in agricultural production.
The 2000 round of the WCA made good progress in reducing the statistical invisibility of female
farmers’ work and resources: agricultural statisticians analysed statistical methodologies and
concepts used on explicit and implicit gender biases, introduced gender concerns into interviewer
and supervisor training, and increased the dialogue with users of sex-disaggregated data.
Selected countries in Africa produced useful sex-disaggregated data during the immediate past
WCA round that by and large substantiated gender differences previously documented by
incidental case studies. The results show, however, great variation at national and sub-national
levels, which underscores the importance of collecting such data.
More sex-disaggregated agricultural statistical data is needed in support of effective evidencebased planning of sector development programmes. Monitoring of the gender-specific impact of
agricultural development plans is needed to determine how these contribute to poverty reduction
and food security enhancing programmes. Besides, only sex-disaggregated data will allow for an
effective assessment of countries achievements towards attaining their MDGs.
Based on the 2000 WCA experiences, FAO developed a statistical toolkit entitled Agri-gender
database. The current paper presented some of the examples included in the electronic toolkit of
questions and tables that facilitate the collection, analysis and dissemination of sex-disaggregated
agricultural data, as they were used in agricultural census programmes implemented on the
continent. It is expected that the Agri-gender database will assist statisticians in further sexdisaggregated data collection. It is furthermore hoped that the toolkit will assist potential users of
sex-disaggregated data in better understanding what kind of gender related data can be collected
through agricultural census programmes and what not.
FAO expects that the Agri-gender database will contribute to increased user-producer dialogue
on sex-disaggregated agricultural data and hopes that –in the medium term- it will have supported
greater use of such data in the planning, monitoring and evaluation of agricultural development
programmes and policies.
16
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17