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Determinants and Measurements of Food Insecurity in Nigeria: Some Empirical Policy Guide

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This study aims at identifying and analyzing food security measures in Borno State, Nigeria. A multi-stage sampling technique was applied on 1,200 households. Cost-of-Calories (COC) method and Logit model are used as analytical techniques for the study. Based on the recommended daily energy levels of 2,250 kcal, food insecurity line (s) for the households is N23, 700.12 or US $176.87 per adult equivalent per year. Over 58% of the sample households are therefore food insecure. Major determinants of this food insecurity factors are, household size, gender, educational level, farm size and type of household farm enterprise. Policy measures directed towards the provision of better family planning should be given adequate attention and priority by the Government in addition to improved access to education, credit facility and agricultural extension services by rural households. The poster plan begins with the introduction in section 1, followed by study objectives in section 2. The description of the study area and sampling procedure are presented in section 3, followed the analytical technique section 4. The results are presented and discussed in section 5 and policy recommendations in section 6.
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DETERMINANTS AND MEASUREMENT OF FOOD INSECURITY IN
NIGERIA: SOME EMPIRICAL POLICY GUIDE
P. S. Amaza*1; J.C. Umeh2; J.Helsen1 and A. O. Adejobi3
1International Institute of Tropical Agriculture, Oyo road, PMB 5320, Ibadan, Nigeria
Email: p.amaza@cgiar.org;
2Department of Agricultural Economics, University of Agriculture, Makurdi, Nigeria,
Email: jceu1@yahoo.com
3Department of Agricultural Economics, Obafemi Awolowo University, Ife, Ile-Ife;
Nigeria. Email: adeprince1@yahoo.co.uk
Contributed Poster prepared for presentation at the International Association of
Agricultural Economists Conference, Gold Coast, Australia
August 12-18, 2006
Copyright 2006 by P. S. Amaza; J.C. Umeh; J.Helsen and A. O. Adejobi. All rights
reserved. Readers may make verbatim copies of this document for non-commercial
purposes by any means, provided that this copyright notice appears on all such
copies.
Abstract
This study aims at identifying and analyzing food security measures in Borno
State, Nigeria. A multi-stage sampling technique was applied on 1,200 households.
Cost-of-Calories (COC) method and Logit model are used as analytical techniques for
the study. Based on the recommended daily energy levels of 2,250 kcal, food
insecurity line (s) for the households is N23, 700.12 or US $176.87 per adult
equivalent per year. Over 58% of the sample households are therefore food insecure.
Major determinants of this food insecurity factors are, household size, gender,
educational level, farm size and type of household farm enterprise. Policy measures
directed towards the provision of better family planning should be given adequate
attention and priority by the Government in addition to improved access to education,
credit facility and agricultural extension services by rural households.
Keywords: Determinants, Food Security and Policy Guide.
I Introduction
The Federal Government of Nigeria prepared and adopted in 2001 a new
national Rural Development Strategy (RDS). Its aim is to improve livelihoods and
food security through a process of community-based agriculture and rural
development. The strategy advocates a community-driven development (CDD)
approach, which ensures the active participation of the beneficiaries and Local
Governments at all levels of decision-making. It is within this development
framework that the Canadian
International Development Agency (CIDA) approved in September 2003 funding to
the agricultural and rural development sector by supporting in Borno State, Nigeria,
2
the proposal for Promoting Sustainable Agriculture in Borno State, Nigeria
(PROSAB).
The Project is being implemented in the agro ecological zones of the Southern
Guinea, Northern Guinea and Sudan Savannas of Borno State, Nigeria. The goal of
the project is to improve food security and reduce environmental degradation. The
purpose is to improve sustainable agricultural production through the transfer of
improved agricultural technologies and management practices, improved market
access, and enhance a more enabling policy environment.
2. Study objectives
The objectives of this study are to:
i) identify and analyse the food security measures of project
beneficiaries; and
ii) prepare check list of rural security measures for assessing food
security status in the LIFDC.
3. Study area and sampling technique
The study is carried out in Borno State, located in northeast Nigeria covering
an area of 69,435 km2. It has 3.64 million people 20041 distributed into four agro-
ecological zones – southern and northern Guinea Savanna, Sudan Savanna, and the
sahel
The data were obtained through a household survey conducted between June
and August 2004. The main instruments for data collection were well-structured
questionnaires administered on households.
One thousand two hundred households were selected for the study through a
multi-stage sampling approach. First, four Local Government Areas (LGAs) were
selected and from the four LGAs, thirty communities were purposively selected.
3
Finally, 1,200 households were selected the thirty communities by randomized
sampling design.
4. Analytical technique
Cost-of-calories (COC) and logit model are the analytical techniques used for
the study. This method has been applied to several studies, whose main focus was on
food security (Greer and Thorbecke, 1984; Hassan and Babu, 1991; Makinde, 2000).
Therefore, following their approach, the food insecurity line is given as:
LnX=a+bC (1)
Where X is the adult equivalent food expenditure (in Naira) and C is the actual
calorie consumption per adult equivalent of a household (in kilocal). The calorie
content of the recommended minimum daily nutrients level (L) (FAO, 1982; Food
Basket, 1995) was used to determine the food insecurity line Z using the equation:
S=e (a+bL) (2)
Where:
S= the cost of buying the minimum calorie intake (food insecurity line); a and
b= parameter estimates from equation 1; L= recommended minimum daily energy
(calorie) level1
Based on the S calculated, households were classified as food secured or food
insecure, depending on which side of the line they fell. Due to differences in
household compositions in terms of age and sex, there was a need to calculate the
levels of expenditure required by households with different compositions. One of the
easiest ways to achieve this was to divide the household expenditure by household
1 The FAO recommended minimum daily energy requirement per adult equivalent is 2250kcal
4
size to get the per capita expenditure as used by the World Bank (1996) and several
other studies. The household expenditure was decomposed on per adult equivalent.
Empirical model for the determinants of food insecurity
A Logit model was used to examine the determinants of household food insecurity,
which is specified as:
Y1 = g (I1) ……. (3)
n
Ii = b0 = bjXji …….. (4)
j=1
Where,
Yi is the observed response for the ith observation (i.e. the binary variable, Yi=0 for
food secure household and Yi =1 for a food insecure household). Ii is an underlying
and unobserved stimulus index for the ith observation (conceptually, there is a critical
threshold (Ii*) for each household; if Ii< Ii* the household is observed to be food
secure, if Ii I
i* the household is observed to be food insecure). g is the functional
relationship between the field observations (Yi) and the stimulus index (Ii) which
determines the probability of being food secure.
The logit model assumes that the underlying stimulus index (Ii*) is a random
variable, which predicts the probability of being food insecure. Therefore, for the ith
observation (a household):
P
n
Ii = In = b0 + bj Xji ……….. (5)
1-Pi j=1
The relative effect of each explanatory variable (Xji) on the probability of being food
5
insecure is measured by differentiating with respect to Xji, using the quotient rule
(Green and Ng’ong’ola 1993):
dPi = eIi Ii …….. (6)
dXji (1+eIi)2 Xji
here,
Pi = the probability of an ith household being food insecure
Xi=Vector of explanatory variables which are defined below:
AGE= Age of head of household (Years); FARMINC= Farm income of a household
per annum (N
W
); FARMSZ= Farm size of a household (ha); HHSZ= Household size
of a farmer; FAMEX= Farming experience (years); COOP =Co-operative
membership; (D=1, if yes; D=0, otherwise); EDUC= Level of education of a farmer
(years);DIST = Distance to input source (km); GEND=Gender of head of household
(D = 1 for; male, D = 0 for female) ; DIVER=Diversification index (Using
Herfindhal index); ASSETS=Total value of household disposable assets (N
3
4
);
FARMEN=Household production enterprise (D = 1 if farm enterprises alone,
otherwise D = 0); COOP= Membership of cooperative societies D = 1 if yes,
otherwise D = 0); CREDIT=Household head’s access to credit facilities (D = 1 if
yes, otherwise D = 0)
CDR= Child dependency ratio; EXTAG=Household head’s access to extension
agents (D = 1 if yes, otherwise D = 0); EXCOM=Extent of produce
commercialization (proportion of farm produce sold); REMIT=Total value of
2 One dollar is equivalent to N134.00
3 D in the description of variables stands for dummy
6
remittances received per adult equivalent per annum by household (N); HLAB=Hired
labour (mandays); FLAB= Family labour (mandays)
The diversification extent (DIVER) was measured using Herfindal index defined as:
n
DIVER = Ri 2 ……………. (7)
i=1
Where,
Ri = Ai
n
Ai …….. (8)
i=1
Ai = share of farm revenue from enterprise i cultivated by the household.
n = number of enterprises owned by household.
5. Results and Discussions
The summary statistics of Food insecurity measures among the households are
presented in Table 1. Based on the recommended daily energy levels (L) of 2250
Kcal, the food insecurity line (S) for the households is found to be N 63.71 per day
per adult equivalent (N1975.01 per month per adult equivalent). On an annual basis,
this is equivalent to N 23700.12 per adult equivalent. From the food insecurity line, it
was shown that 58% of the sampled households are food insecure by headcount (H).
Furthermore, the aggregate income gap (G) of –375.74 indicates the amount
(N375.74) by which the food insecure households are away from meeting their
monthly basic food requirements.
7
Table 1: Summary statistics and food insecurity measures among sampled households
Variable Value
Cost-of-calories equation Constant= 4.154 (0.534)
Slope coefficient=0.0019 (0.0004)
FAO recommended daily energy levels (L) 2250 Kcal
N 63.71 per day Food insecurity line Z: cost of the minimum
energy requirements per adult equivalent N1975.01 per month
N 23700.12 per year
Head count (H) 0.58
Aggregate income gap (G) -375.74
Figures in parenthesis are t-values
Source: Calculations from OLS estimates and cost-of-calories equation.
Determinants of Household Food Insecurity
The results of the Logit regression are presented in Table 2.
8
Table 2: Result of the Logit function for Household Food Insecurity Status
Variable Parameter Estimate t-value
Constant 2.388 1.373
HHSZ -0.014** -2.031
GEND 0.946* 2.097
EDUC -0.8957** -3.226
CDR -0.003 -0.054
RFETE 1.317 1.367
FARMSZ -0.1184* -1.899
CREDIT -0.009 -0.403
FARMEN 1.025* 1.743
FLAB -0.471 -0.345
HLAB 0.018 0.088
PERCUL 0.651 1.56
RQPQC -0.220** -3.766
DIVER -0.234 -1.396
EXCOM 0.261** 2.946
EDUCEX 0.034** 3.860
EXTAG -0.1308** -2.623
COOP -0.034** -3.928
ASSETS -0.0E-04** -4.396
REMIT -0.5E-04 ** -0.086
9
Household size (HHSZ): The coefficient of the variable is significant at 1%
and carries a negative sign. This shows that household with large sizes had higher
possibility of being food insecure than those with smaller size and vice versa in the
project area. The larger the number of less active adults (e.g. old or unemployed) and
children is, the higher the burden of the active members in meeting the cost of
minimum household nutrition would be and, hence, the higher the level of food
insecurity, and vice versa.
Gender of the head of household (GEND): The coefficient is significant at 5%
and shows a positive relationship with household’s food insecurity status. Households
headed by female have higher probability of being food insecure in the project area.
Educational level of head of household (EDUC): The coefficient of this
variable is significant at 1% and carries a negative sign suggesting that the higher the
educational level of a head of household is, the more food secure the household and
vice versa. This is expected because such households are assumed to have better food
management techniques that will ensure equitable and all round supply of food.
Farm size (FARMSZ): The coefficient of the variable is significant and
exhibits a negative relationship with the food insecurity status of the household,
showing that households with larger farm sizes are more food secure than those with
smaller sizes and vice versa.
Type of household enterprises (FARMEN): Households who are into farming
alone had higher probability of food insecurity than those that have diversified from
farming into some other non-farm enterprises and vice versa. This is plausible
because households that have other sources of income in addition to farming are more
resilient in times of food crisis that those that are into farming alone.
10
Ratio of quantity produced to the ratio of quantity consumed (RQPQC): The
coefficient is significant at 1% and shows a negative correlation with food insecurity.
This shows that the higher the ratio is, the lower the probability of food insecurity and
vice versa.
Extent of agricultural output commercialization (EXCOM): The coefficient of
the variable is significant at 1% and exhibits a positive correlation to food insecurity
suggesting that the higher the extent of commercialization the higher the probability
of food insecurity and vice versa. This is contrary to a priori expectation because
most of the household produce at a scale meant for home consumption and are forced
to sell when a need arises, thus depleting the stock for home consumption and thereby
exposing the household to food insecurity.
Expenditure on education (EDUCEX): The coefficient of the variable is
significant and carries a positive sign, suggesting that the higher a household’s
expenditure is on education, the higher the probability of food insecurity and vice
versa. This is plausible as education of children is a priority area, which the
households could deny itself some comfort in the short-run. Households sometimes
sell out of their food reserve to provide for this need and as such expose themselves to
food shortages.
Household’s access to extension agent (EXTAG): The coefficient of the
variable is significant at 1% and has a negative relationship with the food insecurity
status of households. This implies that households that had access to extension agents
have higher probability of being food secure than those that did not have access to
extension agent and vice versa. This is because access to extension agents enhances
the chances of households having access to better crop production techniques,
11
improved input as well as other production incentives and these go to affect their
output vis-à-vis their food security status.
Household heads’ membership of cooperative societies (COOP): The
coefficient of the variable is significant at 1% and carries a negative sign, implying
that households whose heads were members of cooperative or other farmers
organizations had higher probability of being food secure than those whose heads
were. This can be closely linked to the beneficial effects of their memberships in
terms of production and other welfare enhancing services that these cooperative or
other farmers’ associations offer.
Value of household assets (ASSETS): Household assets holding is considered
as one of the measures of household resilience, which cushion the effects of adverse
circumstances such as crop failure, drought, etc on household food security. It is
believed that some of the assets could be disposed of in terms of pressure. The
coefficient of the variable was significant and carries a negative sign, suggesting that
the higher the value of household assets is, the lower the probability of food
insecurity.
6 Policy Recommendations
The following policy implications and recommendations are suggested for
reduction in food insecurity.
Policy measures directed towards the provision of better family planning to
reduce household size should be given adequate attention and priority by the
government. Education that encompasses all aspects of training and which brings
about attitudinal changes is important for households in the project area. Also,
strategies for an effective community participation in the design of concepts and
12
messages aimed at imparting knowledge about family planning to the households are
recommended.
Second, there is the need for policy, which shall promote formal education as
a means of enhancing efficiency in food crop production over the long-term period. In
the short-term, informal education could be effective, especially when targeted at
farmers who have had limited formal educational opportunities.
A policy which provides adequately trained and equipped extension workers
for disseminating improved agricultural technologies has the potential of raising
efficiency in food crop production, which enhances food security.
References
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East, Food and Nutrition Paper 20, FAO, Rome.
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food Security Programme: Overall approaches and Issues”, FAO, Rome.
Food Basket Foundation International (1995). Nutrient Composition of Commonly
Eaten foods in Nigeria-Raw, Processed, and Prepared. 131pp.
.Greer, J. and E. Thorbecke. 1986. A methodology for measuring poverty applied
to Kenya. Journal of Development Economics, 24 (1) pp59-74.
Hassan, R.M. and Babu, S.C. 1991). Measurement and determinants of rural poverty:
household consumption patterns and food poverty in Rural Sudan. Food
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Makinde, K.O (2000). Determinant of Food Security in Bauchi Area of Northern
Guinea Savanna of Nigeria. Unpublished Ph.D. Thesis; Department of
Agricultural Economics, University of Ibadan
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Umeh, J.C., C.C. Agunwamba and O.A.D. Agada (1996). “Grain Stocking and
storing in Benue State: An Appraisal of silo Federal Government of Nigeria’s
Food Grain Storage Policy.” International Journal of Production Economics,
45, 261 – 270.
World Bank, (1996). Nigeria Poverty in the Midst of Plenty. The Challenge of
Growth with Inclusion. A World Bank Poverty Assessment. Population and
Human Resources Division, West Africa Department, Africa Region. Report
No. 14733 UNI.
14
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Nigeria Poverty in the Midst of Plenty. The Challenge of Growth with Inclusion. A World Bank Poverty Assessment. Population and Human Resources Division
  • World Bank
World Bank, (1996). Nigeria Poverty in the Midst of Plenty. The Challenge of Growth with Inclusion. A World Bank Poverty Assessment. Population and Human Resources Division, West Africa Department, Africa Region. Report No. 14733 UNI.
Food Consumption Tables for the Near East
  • Food
  • Organization
Food and Agricultural Organization (1982). Food Consumption Tables for the Near East, Food and Nutrition Paper 20, FAO, Rome