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IFPRI Policy Seminar "Beyond Gender Myths Closing the Knowledge Gap in Agriculture and Food Security" Presentation by Ruth Meinzen-Dick, Senior Research Fellow, IFPRI and Agnes Quisumbing, Senior Research Fellow, IFPRI at IFPRI on 22 November 2013.

TRANSCRIPT

The Gender Asset Gap: Pieces of the puzzle

Agnes Quisumbing

Poverty, Health and Nutrition DivisionInternational Food Policy Research Institute

IFPRI Policy Seminar, November 22, 2013Washington DC

What we know• What we learned from SOFA 2010-2011:

– Gender gaps in land, assets, nonland inputs, and technologies have a high opportunity cost in terms of gains in yields, production, and potentially, reduction in hunger

• We know gender gaps exist, and there are gains to closing those gaps

• But we do not know:– The extent of the gender gap across resources (myths

prevail)– The extent of the gains in closing the gap– Most effective ways to close the gap (although there is

evidence from some impact evaluations)

Nonland inputs:

Assets and technology

Photo credit: Maria Theresa Castro, IRRIPhoto credit: Ruth Meinzen-Dick, IFPRI

Gender gaps in nonland assets and technology

Source: Peterman, Behrman and Quisumbing, 2010. IFPRI Discussion Paper 975. (SOFA background paper)

Num

ber

of s

tudi

es r

evie

wed

Land

Photo credit: Supriya Chatterjee, Landesa

Sound bites

-- Oxfam, Action Aid, etc.

-- Infographic from the Bill and Melinda Gates Foundation

-- Variations found in UN Women, Bread for the world and others citing FAO gender land rights database

Does the single statistic contain some element of truth?• Problematic because:

1. Masks regional and within country variations2. No clear attention to how ‘women’s land ownership’ is

defined – and how this relates to bundles of rights3. Treatment of joint ownership?4. No clear comparison group (assumed to be men in the

same context?)5. Based on limited data

All these factors handicap policy recommendations, ultimately hurting efforts towards understanding gender-inequalities in land rights.

Gender Inequalities in Ownership and Control of Land in Africa: Myth and Reality (Doss, Kovarik, Peterman, Quisumbing, van den Bold 2013)

1. Explores conceptual and methodological issues in estimating “women’s land ownership.”

2. Reviews existing evidence from large-scale studies in Africa (data collected post 2002).

3. Provides new data-based estimates on women’s land ownership in Africa:

Food and Agriculture Organization (FAO) gender and land rights database

Demographic and Health Surveys (DHS) Living Standard Measurement Study-Integrated Surveys on

Agriculture (LSMS-ISA).

4. Discusses policy, advocacy and research implications of findings.

FAO Gender and land database

• Primarily from agricultural censuses• Landholder is defined as a “…person who makes major

decisions regarding resource use and exercises management control over the agricultural holding operation. The holder has technical and economic responsibility for the holding and may undertake all responsibilities directly, or delegate responsibilities related to day-to-day work management to a hired manager.” (FAO, 2007)

• Therefore, a landholder is not necessarily a land owner• 9 countries, N = 44,450 in Cape Verde - 15,732,850 in Nigeria

FAO Gender and land database (2002 – 2013)

Cape Verde (2004)

Botswana (2004)

Comoros (2004)

Tanzania (2007–2008)

Ethiopia (2001–2002)

Madagascar (2004–2005)

Nigeria (2007)

Gambia (2001–2002)

Mali (2004–2005)

0

10

20

30

40

50

60

Percentage of landholders who are women

Perc

enta

ge

Country (year)

Demographic and Health Surveys

• Starting in 2009, select DHS started collecting information on individual land ownership:

Household level: “Does any member of this household own agricultural land?”

Individual level: “Do you own any land either alone or jointly with someone else?” Response options: no ownership, sole ownership, joint ownership, or both sole and joint ownership.

• 10 countries

DHS – sole + joint ownership (2009 – 2013)

Burundi (2010)

Rwanda (2010)

Malawi (2010) Burkina Faso (2010)

Tanzania (2010)

Ethiopia (2011)

Uganda (2011) Zimbabwe (2010-11)

Lesotho (2009)

Senegal (2010-11)

0

10

20

30

40

50

60

70

80

90

100

8681 80 79 77

73 72

63

53

47

54 54

48

32 30

50

3936 38

11

64

55 54 54

60

36 34

28

Percentage of households owning any agricultural land

Women owning any land (sole or joint)

Men owning any land (sole or joint)

Country (year)

Per

cent

age

owni

ng la

nd

* *

* means that data is not available

DHS – sole ownership (2009 – 2013)

Burundi (

2010)

Rwanda (

2010)

Mala

wi (2010)

Burkin

a Fas

o (2010)

Tanza

nia (2

010)

Ethio

pia (2

011)

Uganda (

2011)

Zimbab

we (2010-1

1)

Lesoth

o (2009)

Seneg

al (2

010-11)

0

10

20

30

40

50

60

70

80

90

100

8681 80 79 77

73 72

63

53

47

11 13

23

128

12 1411

7 5

50

25

43

28

46

22

9

22

Percentage of households owning any agricultural landWomen owning any land (sole only)Men owning any land (sole only)

* *

Per

cent

age

owni

ng la

nd

LSMS-Integrated Surveys on Agriculture

• Joint effort led by the World Bank in 7 African countries starting in 2008 (Mali still in progress).

• Detailed plot level characteristics including, ownership, documentation, area (GPS) measures and value (self reported) measures.

• Among total land area owned or accessed by households, women own a high of 31% in Malawi, followed by Uganda (16 %), Tanzania (15 %), Nigeria (9%) and Niger (8 %).

• Comparatively, men solely own on average 21.8 times as much absolute land area in comparison with women in Nigeria, and between 1.1 to 6.9 times as much land as women solely own in the other countries.

LSMS-ISA Uganda: Distribution of Land Area

Women's ownership, undocumented; 13%

Women's ownership, documented; 3%

Men's ownership, un-documented; 24%

Men's ownership, doc-umented; 6%

Joint ownership, undoc-umented; 32%

Joint ownership, doc-umented; 10%

Accessed; 11%

LSMS-ISA (area measures)

Ethiopia

16%6%

19%

17%41%

31%

0.2%32%

0.4%

13%

0.6% 22%

Malawi

7% 0.4%

49%

5%

22%

2.9% 15%

Niger

14% 1%

36%

5%

31%

5% 8%

Tanzania

13%3%

24%

6%

32%

10%

11%

Uganda

Women's ownership, undocumented

Women's ownership, documented

Men's ownership, undocumented

Men's ownership, documented

Joint ownership, undocumented

Joint ownership, documented

Accessed

Owned, undocumented (men and women)

Legend

3%

68%

7%

22%

Nigeria*

*In Nigeria “ownership is defined as the right to sell or use as collateral”

Which countries have data?

Conclusions and discussion points

• Isolated statistics cannot be generalized and do not present an accurate picture of women’s landownership worldwide

• But most consistent message is: women are disadvantaged and often the gender gap is large.

• In future analysis it is crucial to: Define definitions and indicators used Improve methodology, data collection and analysis efforts Recognize that country-specific statistics are the most relevant to

drive policy and advocacy efforts in a given context and focus should be on developing strong in country systems for data collection and dissemination.

Acknowledgements

Funding for this work was provided by the Consultative Group on International Agriculture Research (CGIAR), Program on Policies, Institutions, and Markets and by an anonymous donor.

We are grateful to IFPRI colleagues Maha Ashour, Zhe Guo, Caitlin Kieran, Hazel Malapit, Ruth Meinzen-Dick, and Wahid Quabili for helpful comments and assistance.

Hosaena Ghebru Hagos of IFPRI for allowed access to unpublished Trabalho de Inquerito Agricola (TIA) survey collected by Ministry of Agriculture data from Mozambique; Perrine Burnod of Centre de coopération internationale en recherche agronomique pour le développement (CIRAD) for allowing access to unpublished data from Madagascar.

This paper benefited from helpful comments from the participants at the Gender and Agricultural Productivity in Sub-Saharan Africa workshop at the International Fund for Agricultural and Development in Rome, and the International Conference on Agricultural Statistics 2013 in Rio de Janeiro, and to the Living Standards Measurement Study—Integrated Surveys on Agriculture (LSMS-ISA) team at the World Bank for helpful comments.

Gender and Social Capital

Ruth Meinzen-Dick

Environment and Production Technology DivisionInternational Food Policy Research Institute

IFPRI Policy Seminar, November 22, 2013Washington DC

• Group membership– Producer groups– Microfinance– Funeral societies– Civic, religious groups– Advocacy

• Social networks– Kinship– Friendship– Contacts

Types of Social Capital

Photo credits: Regina Birner

Importance of Social Capital

• Access to services (extension, credit, seed, etc.)• Control of resources • Resilience to shocks• Status• Empowerment

Is there a gender gap in social capital?

Women’s Empowerment in Agriculture Index data on group membership

NEPAL* TAJIKISTAN* KENYA* RWANDA UGANDA MALAWI* ZAMBIA*0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

22.9

64.763.0

82.2 82.779.5

36.4

16.7

37.0

70.6

79.281.3

73.7 74.5

Group Membership: Percentage of women and men in dual households with adequate achievement regardless of overall

empowerment status

Men Women

Perc

enta

ge w

ith a

dequ

ate

achi

vem

ent

* Indicates statistically significant difference at 0.05 level

Asia East Africa Southern Africa

Is there a gender gap in social capital?

• Formal organizations– Men in farmer groups, market oriented– Women in civic and religious groups– Men more likely to be in leadership

• Social networks– Quantity vs quality of ties

BondingBridging

Linking

Gendered barriers to participation

• Structural (e.g. membership requirements)

• Time• Mobility • Material constraints (money)

• Confidence• Gender norms

– Public space as male– Female seclusion– Speaking in public

Implications• Social capital: potential, not panacea

– Substitute or complement to other assets?– Exclusion of the very poor, marginalized

• Service delivery– Building on what (whose) groups or networks?– Group composition: men’s, women’s, or mixed?

• Organizational efforts– Potential, but not costless– Do organizations meet men’s or women’s needs?– Address gendered barriers to participation

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