Adeolu B. Ayanwale; Adewale A. Adekunle; Oluwole Fatunbi and Luke O Olarinde

Outline of Presentation

Introduction

Research questions

Methodology

Data

Results

Conclusions

Introduction Agricultural sector’s performance in Africa is fundamental

for poverty reduction and food security.

Substantial investments have been made in agricultural research and innovations

However impacts of these investments have not been felt beyond the immediate localities of the research environment

This is the motivation for the “systems based and innovation focused” approach tagged “IAR4D” concept by FARA

Introduction The IAR4D operates via a network configuration

comprising all actors in the agricultural value chain – “systems approach”

Incidentally, the systems approach of the IAR4D also tackles another major acknowledged obstacle to agricultural development which is “gender relations”

Men and women are acknowledged to have different roles and resources especially as regards household food security

Introduction FAO 2011 noted that “gender inequalities and a lack of

attention to gender in agricultural development have contributed to lower productivity, higher levels of poverty and under nutrition”

Any efforts at addressing the gender gap is therefore a major leap in the global effort at meeting the Millennium Development Goal 3 (Grown et.al 2005)

Introduction The SSA CP had at the core of its mandate the

empowerment of vulnerable rural farmers (especially women and youths) in the sub-region.

Studies have been conducted on both the homogenous and heterogeneous impact of the progamme on the participants.

However, very little attention seem to have been placed on the gender dimension of the household’s food security. This is the focus of this paper.

Research Questions The key research questions addressed in this paper are?

What determines food security status of male headed households as opposed to female headed households in the KKM PLS of the SSA CP?

Does the membership of IPs ensure household food security?

Among female headed households what determines their food security status?

Kano-Katsina-Maradi PLS

Data The data used for this study was derived from two strands

of surveys conducted at the KKM PLS level

These are the baseline and the midline surveys

The data provided a panel of dataset that were used to compare vital variables of interest in the paper

The data set also provided an opportunity to disaggregate by gender

Data IP Taskforce PLS

No of IPs 1 4 12

No of IR4D villages

5 20 60

NO of conventional villages

5 20 6-

No of non IAR4D, non conventional villages

5 20 60

Total no of Households

150 600 1800

Methodology

We used the subjective measure of food security as dependent variable. Following after Kassie et.al. (2013) we used the households’ own perception of food security

Three categories: 1= Chronic food insecurity; 2= Transitional Food Insecurity; and 3 = Break even/food secure.

We used an ordered probit regression model which allowed us to identify the effects on food security of different inequalities and different forms of discrimination within the household.

Results The results presented in the table reveals that women had more years of farming experience than men, had larger size of family (– more dependants) and almost equal years of formal education as men.

0

2

4

6

8

10

12

14

Education Famly Size Farm Exp

Descriptive of Male and Female Headed households

Male Headed Female Headed

Results Results from the analysis

shows that although the IPs

are composed of more female

than male

more male headed

households are food secure

(break-even) .

experience transitory food

insecurity, and

experience (chronic food

insecurity)

than female headed.

0

0.1

0.2

0.3

0.4

0.5

0.6Households food security

status

MaleHeaded

FemaleHeaded

Picture 3: Knowledge management and information sharing in a rice field

Results

Further results reveals some interesting gender dimensions in food security.

More de facto FHH are food secure than de jure FHH, interestingly they also suffer more chronic food insecurity.

However, de jure FHH experience more transitional food insecurity than de facto.

This is plausible because although the husband might not be around, the wife can still use the assets of the family, unlike de jure households who might have been disenfranchised by the husbands’ family members.

0

0.1

0.2

0.3

0.4

0.5

0.6Food security status of Female

Headed Households

De jure FHH

De facto FHH

Results

The results of analysis by membership of the IP shows that more members are food secure than non members.

Almost half of the respondents in transitional are members of an IP.

This suggest the ability of social capital to encourage and empower their members.

0.28 0.32

0.29

0.12

0.26

0.36

Fd secure Transitional Chronic

Food security by Membership of IP

Members Non members

Determinants of Food Security

Specifically, from the results we can assert that

Women are more food secure than men.

Members of IPs are more food secure than non members.

Elderly and more educated households are more food secure

Furthermore, households with more productive assets are food secure

Finally farming households in Sudan savanna taskforce also perceive themselves more food secure.

Determinants of Food security

Pooled regression Marginal Effects

Coeff Std Error Coeff Std error

Age -0.228** 0.138 0.078** 0.29

Marital Status

0.016 0.048 -0.004 2.22

Educ 0.085** 0.041 -0.024** 0.50

Household size

-0.059 0.057 0.018 0.02

Farming Exp 0.011 0.048 0.003 1.59

Asset -0.003*** 0.001 -0.001** 1.17

Membership 0.357*** 0.097 -0.089*** 0.021

NGS 0.069 0.097 -0.089 0.023

Sudan 10.305** 0.081 -0.019** 0.021

gender -0.174** 0.081 -0.046** 0.0.021

No 1404

LR chi2 77.40***

Log likelihood

-1396.849

Determinants of Food Security From the results it is obvious that that factors that determine of food security are different for MHH and FHH thus suggesting different intra-household decisions modules

Whereas MHH who are members of IP, elderly with productive assets and are in both NGS ad Sudan savanna TFs are food secure,

Elderly educated FHH who are members of IP also having productive assets and residing in Sudan savanna are food secure

Determinants of Food security

MHH FHH

Coeff Std Error Coeff Std error

Age 0.131*** 0.086 0.072* 0.029

Marital Status

-0.006 0.027 0.004 0.015

Educ 0.002 0.022 -0.024** 0.011

Household size

-0.019 0.033 0.012 0.016

Farming Exp 0.004 0.028 0.009 0.013

Asset -0.002*** 0.000 -0.001*** 0.000

NGS 0.381** 0.170 -0.031 0.023

Sudan 0.351*** 0.145 -0.078*** 0.021

Membership 0.274*** 0.071 -0.086*** 0.022

No 267 350

LR chi2 22.80*** 66.85***

Log likelihood

-248.405 -1343.761

Conclusions Food security status of smallholders in the PLS is generally

low – less than 30 percent.

In the KKM PLS, as the SSA CP was implemented, there was an increase in percentage of households who are food secure

The evidence suggests that although women are members of IPs, FHHs experience more food insecurity than MHHs

Generally, members of IPs are food secure than non members

De facto FHH whose husbands are not around are more food secure than de jure where the husband/family had assets, but will be chronically food insecure where the husbands do not leave productive assets

Conclusions Factors that determine food security among MHHs and

FHHs are different suggesting differences in intra-household decision making and outcomes

Marital status, ownership of productive assets, location and membership of IPs are some of the factors that determine household food security in the study area.

To enable FHHs become food secure and thereby increase their productivity, it is necessary to encourage active participation in the IPs.

Acknowledgements

FARA

IITA