ppt icasv.133 tempelman data quality africa...support of n = 10,000+++ men and women farmers...

ICAS - V SESSION 3.1

Agricultural statistics country assessment

Agricultural sector

“GENDER STATISTICS”

Improving data quality using a gender sensitive perspective of agricultural statistics

"HOW TO" lessons learned from Africa"HOW TO" lessons learned from Africa

REGIONAL OFFICE FOR AFRICA

Diana TempelmanSenior Officer, Gender and Development

3

AGRI - GENDER DATABASEa statistical toolkit for the production of

sex-disaggregated agricultural data

RESULT OF:

Nearly 2 decades collaboration FAO & NBS-s

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� Nearly 2 decades collaboration FAO & NBS-s in Africa

� “joint-venture” with N = 100+ statisticians

� Support of N = 10,000+++ men and women farmers responding to census / survey Q.

AGRI-GENDER DATABASE / TOOLKIT

INTRODUCTION

Data Items SECTION 1 SECTION 2

1 Agricultural population and households Questionnaire Table

2 Access to productive resources Questionnaire Table

5

2 Access to productive resources Questionnaire Table

3 Production and productivity Questionnaire Table

4 Destination of agricultural produce Questionnaire Table

5 Labour and time-use Questionnaire Table

6 Income and expenditures Questionnaire Table

7 Membership of agricultural/farmer organisationsQuestionnaire

Table

8 Food security Questionnaire Table

9 Poverty indicators Questionnaire Table

EXAMPLES of news “gender-relevant” results from WCA 2000 and 2010

Presentation outline

� Analysis of demographic data

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� Analysis of demographic data

� Access to productive resources

���� relevance of sub-holder concept

� Credit, labour and time-use

� Poverty indicators

� Lessons learned

Guinea

85+

80 - 84

75 - 79

70 -74

Guinea – Labé Region

85+

80 - 84

75 - 79

70 -74

Demographic data (1) Guinea

FEMINISATION AGRICULTURAL SECTOR

DATA

7

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

Male FemaleScale maximum = 800000

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

Male FemaleScale maximum = 90000

‘Standard’ format demographic data questions

1 2 3 4 5 6 7 8

If column 3, code 1

8

S/N

Full name

(Starting

wi th the

head of

household)

Is the member of

the household a

holder

1 = Yes

2 = No

Holder

ID

Type of holding

1 = Crop

2 = Livestock

3 = Both

Sex

1 = Male

2 = Female

Relation to the

head of household

1 = Head

Etc

Age in

completed

years

Code Code Code Code

01

02

03

04

05

Etc.

Demographic data (2) - NIGER

Average FFH: smaller but more dependentsAverage FFH: smaller but more dependents

Average size and dependency ratio of agricultural households by sex of Head of Household at regional and national level

Male HoHH Female HoHH

DATA

9 Source: RGAC 2004-2007, Niger

Male HoHH Female HoHH

Region

Average size Dependency

ratio Average size

Dependency ratio

AGADEZ 5,5 0,87 4,0 0,90

DIFFA 5,8 0,84 3,6 0,92

DOSSO 7,6 0,82 4,4 0,89

MARADI 7,7 0,95 3,9 0,96

TAHOUA 6,6 0,86 4,3 1,16

TILLABERY 8,3 0,83 4,5 0,99

ZINDER 5,9 0,85 3,7 1,07

NIAMEY 6,1 0,69 4,8 0,65

Total 6,9 0,86 4,0 1,03

Demographic data (3) Tanzania

labour constraints in headed HHlabour constraints in headed HH

Male active / sex of HoHH Selected

Active male members / sex of HoHH, Tanzania

DATA

10

Male active / sex of HoHH Selected

regions Male HoHH Female HoHH

Dodoma 1.1 0.3

Mtwara 1.0 0.5

Iringa 1.1 0.2

Mbeya 1.1 0.3

Mara 1.0 0.5

Tanzania 1.1 0.4

Section 2 : Inventory of plots of agricultural holdings (NIGER)

Identification

Plots, farms

Family name & first name of

Plotmanager

Sex of Plot manager

Type de plot

management

Plot culture history

Type of culture

Type of land tenure

Type of Relief

1 2 3 4 5 6 7 8 9

Access to productive resources (1) LAND

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1 2 3 4 5 6 7 8 9

Male 1 Individual 1 cultivated 1 Cul, pur 1 1 Inheritance 1 Plane

Female 2 Collective 2 fallow 2 Cult, mixed 2 2 Purchase 2 valley bottom

3 renting or crop sharing

2 slope

4 Loan

5 Gift

Field

Plot Write first and family name of Plotmanager, starting with the

HoHH

6 Other

|____|____|

|____|____| |____| |____| |____| |____| |____| |____|

|____|____|

|____|____| |____| |____| |____| |____| |____| |____|

Data / sex of Head of household ����

Under - presentation of women farmers’ involvement

Area cultivated / crop by sex of agricultural holder

DATA

12

Enhanced presentation of women farmers’ work

Holder

(Collective fields) Sub-Holder

(Individual fields) Both

Crops

Area cultivated / crop by sex of agricultural holder and sub-holder

DATA

13

(All fields) Crops

M F M F M F

Millet 97 3 45 55 87 13

Maize 99 1 90 10 89 11

Rice 98 2 65 35 85 15

Groundnuts 97 3 32 68 54 46

Vouandzou 96 4 20 80 50 50

White sorghum 98 2 58 42 90 10

Red sorghum 97 3 55 45 91 9

(sub) Total 98 2 48 52 86 14

RELEVANCE OF SUBRELEVANCE OF SUB--HOLDER HOLDER

Male holder: Area under collective management per

type of acquisition - NIGER3%

1%

7%

1%

5%

83%

Inherited

Purchased

Share-cropping

Loan

Gift

Other

DATA

14

LAND Collective management / Head of HH

Female holder: Area under collective management

per type of acquisition - NIGER

5%9%

11%

0%

6% 69%

Inherited

Purchased

Share-cropping

Loan

Gift

Other

Male sub-holder: Area under individual management

per type of acquisition at national level - NIGER

10%2% 1%

2%

9%

76%

Inherited

Purchased

Share-cropping

Loan

Gift

Other

DATA

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LAND Individual management

/ active HH members

Female sub-holder: Area under individual

management per type of acquisition at national level,

NIGER

12%1%

35%

48%

3%

1%

Inherited

Purchased

Share-cropping

Loan

Gift

Other

Section 2 : Number of sedentary animals par kind and sex of owner

Household level question

Access to productive resources (2) ANIMALS

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Code Kind of animal, sex and age Total number Number owned by women

1 2 3 4

10 Cattle

11 Female |____|____|____| |____|____|____|

12 Male |____|____|____| |____|____|____|

13 Castrated male |____|____|____| |____|____|____|

30 Sheep |____|____|____| |____|____|____|

40 Goat |____|____|____| |____|____|____|

Sedentary animals / type of animal / sex of owner, Niger

DATA

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Source: RGAC 2004-2007, Niger

cattle sheep goats

Men Women Men Women Men Women

77.7 % 22.3 % 60.3 % 39.7 % 45.5 % 54.5 %

Ownership chicken / sex of owner, Niger

Chicken

Repartition des poulets par proprietaire au niveau

du Niger

DATA

18

du Niger

32%

46%

22%

Femmes

Hommes

Enfants

Source: RGAC 2004-2007, Niger

Access to productive resources (3.1) CREDIT

Q 13.1: During the year 2002/2003 did any of the

household members borrow money for

agriculture?

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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)

Credit details Source “a”

Use codes to indicate source |__|

Provide to Male=1, Female=2 |__|

S/N

Use of credit

Tick boxes below to indicate the

Access to productive resources (3.2) CREDIT

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S/N Use of credit to indicate the use of the credit

13.2.1 Labour

13.2.2 Seeds

13.2.3 Fertilisers

13.2.4 Agrochemicals

13.2.5 Tools/equipment

13.2.6 Irrigation structures

13.2.7 Livestock

13.2.8 Other ………………………………

Source of credit 1 = Family, friend or relative 2 = Commercial bank

3 = Cooperative 4 = Savings and credit soc. 5 = Trader/trade store

6 = Private individual 7 = Religious organisation/NGO/Project 8 = Other (specify) ………………………

Female HoHH use credit to hire labour -

Chart 7.5 Percent of Households that have access to Credit by sex of

Household Head30

Per

cen

tDATA

to purchase seeds

TANZANIA

21

0

10

20

30

Labour Seeds Fertili -

zers

Agro-che

micals

Tools /

Equip

ment

Irrigation

Structures

Livestock Other

Use of Credit

Per

cen

t

Male Headed Female Headed

Time-use, EthiopiaSource: Ethiopian Agricultural Sample Enumeration Miscellaneous Questions – 2001/02 (1994 E.C.)

Adults Children S/N

Activity Male Female Boys Girls

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

22

S/N Activity Male (code)

Female (code)

Boys (code)

Girls (code)

21.1 Tilling |__| |__| |__| |__|

21.2 Sowing |__| |__| |__| |__|

21.3 Weeding |__| |__| |__| |__|

21.4 Harvesting |__| |__| |__| |__|

21.5 Feeding/Treating |__| |__| |__| |__|

21.6 Milking |__| |__| |__| |__|

21.7 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

Chart 5.17 Percent of Households by Type of Labour - MALE Headed

Households

Making BeerBeekeeping

FishingFish Farming

Off - farm Income Generation

Chart 5.18 Percent of Households by Type of Labour

- Female Headed Households

Making BeerBeekeeping

FishingFish Farming

Off - farm Income Generation

Division of Labour, Tanzania

DATA

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0% 20% 40% 60% 80% 100%

Land Clearing

Soil Preparation by HandSoil Preparation by Oxen / Tractor

PlantingWeeding

Crop ProtectionHarvest ing

Crop ProcessingCrop Marketing

Cattle RearingCattle Herding

Cattle MarketingGoat & Sheep Rearing

Goat & Sheep HerdingGoat & Sheep Marketing

MilkingPig Rearing

Poultry KeepingCollecting Water

Collecting FirewoodPole Cutting

Timber Wood CuttingBuilding / Maintaining Houses

Making Beer

Ty

pe o

f L

ab

ou

r

Percent

Head of Household Alone Adults Males Adult Female

Adults Boys Girls

Boys & Girls All Household Members Hired Labour

0% 20% 40% 60% 80% 100%

Land Clearing

Soil Preparation by HandSoil Preparat ion by Oxen / T ractor

PlantingWeeding

Crop ProtectionHarvest ing

Crop Processing

Crop MarketingCattle Rearing

Cattle HerdingCatt le Marketing

Goat & Sheep RearingGoat & Sheep Herding

Goat & Sheep MarketingMilking

Pig RearingPoultry Keeping

Collecting WaterCollect ing Firewood

Pole Cutt ingTimber Wood Cutt ing

Building / Maintaining Houses

Making Beer

Ty

pe o

f L

ab

ou

r

Percent

Head of Household Alone Adults Males Adult Female

Adults Boys Girls

Boys & Girls All Household Members Hired Labour

Food security / Poverty indicators Tanzania

34.6.1

Number of meals the household normally has per day

|__|

24 Source: United Republic of Tanzania – Agricultural Sample Census 2002/2003- Small holder/Small Scale Farmer

Questionnaire: Section 34

Code 34.6.3 1 = Never 3 = Sometimes 6 = Always 2 = Seldom 4 = Other

34.6.2

Number of days the household consumed meat last week

|__|

34.6.3

How often did the household have problems in satisfying the food needs of the household last year (code)

|__|

Food security

Frequency of food shortages, Tanzania

Chart 9.4 Percent of Male and Female Headed

Households by Frequency of Facing Food Shortages

50

A higher percent male-headed HHs never has food shortage.

A higher percent of female-

DATA

25

0

10

20

30

40

50

Never Seldom Sometimes Often Always

Frequency of Food Shortage

Per

cen

t of

Hou

seh

old

s

Male Female

A higher percent of female-headed HHs has often or always food shortages.

The same pattern appears in the regions.

Gender perspective in agricultural census/surveys

� No technical problems / additional human/financial costs (Senegal 1998/99 Ag census)

Lessons learned

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� Enriches info obtained from data

� ENHANCES QUALITY OF DATA

� Allows for gender specific planning and M & E agricultural development

LESSONS LEARNED http://www.fao.org/sd/dim_pe1/pe1_051003_en.htm

OUTCOME

27 2005

THEMATIC CENSUS REPORTS

Tanzania Niger

OUTCOME

28

OUTCOME

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Links agri-gender toolkit

BROCHURE:

http://www.fao.org/docrep/012/k8472e/k8472e00.pdf

OUTCOME

30

http://www.fao.org/docrep/012/k8472e/k8472e00.pdf

TOOLKIT ITSELF:

http://www.fao.org/gender/agrigender/en

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Links agri-gender toolkit

BROCHURE:

http://www.fao.org/docrep/012/k8472e/k8472e00.pdf,

OUTCOME

32

http://www.fao.org/docrep/012/k8472e/k8472e00.pdf,

TOOLKIT ITSELF:

http://www.fao.org/gender/agrigender/en