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An Evaluation of Effect of Climate Change on Food Security of Rural Households in Cross River State, Nigeria

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Asian Journal of Agricultural Sciences 5(4): 56-61, 2013
ISSN: 2041-3882; e-ISSN: 2041-3890
© Maxwell Scientific Organization, 2013
Submitted: June 23, 2012 Accepted: July 31, 2012 Published: July 25, 2013
Corresponding Author: P.O. Emaziye, Department of Agricultural Economics and Extension, Delta State University, Asaba
Campus, Asaba, Nigeria
56
An Evaluation of Effect of Climate Change on Food Security of Rural Households in
Cross River State, Nigeria
P.O. Emaziye, R.N. Okoh and P.C. Ike
Department of Agricultural Economics and Extension, Delta State University, Asaba
Campus, Asaba, Nigeria
Abstract: The study focused on the linkage between climate change and food security of rural households in Cross
River state. The specific objectives are to ascertain the level of food security of rural households and impacts of
climate change factors on the food security of rural households. Cross River State is located within Latitude 05°13’
26’’ North and longitude 08° 17’ 44’’ East with an estimated population of 2.888,966 persons. The state is a coastal
area usually affected by climate events (flooding) coupled with existing oil spillage hazard. Multistage sampling
procedure was used to select local government areas, communities and rural households for the study. Data were
obtained from both primary and secondary sources and analyzed using descriptive statistic, food security index and
correlation matrix. The mean annual income of the rural farming households in Cross River state was N71, 895
($412) revealing a low annual income with a large household size of 9 persons. The food security index in the State
was found to be moderately food insecure with food security having statistically significant relationship with the
climate change factors. The impact perceived by the rural households on climate events was severe. The percentage
of losses of annual income was 67.07%. It is therefore recommended that Government and donor agencies should
provide a short-term relief measures to alleviate the food insecurity situations in the state and entrench a policy of
long term development of agriculture. The rural farming households should be encouraged to carry out climate
change adaptation and mitigation measures in alleviating the food insecurity situation in the state.
Keywords: Climate change, cross river state, food security, Nigeria rural household
INTRODUCTION
FAO’s vision of a world without hunger is one
which most people are able by themselves, to obtain the
food they need for an active and healthy life and where
social safety nets ensure that those who lack resources
will get enough to eat” (FAO, 2007f). The achievement
of the vision is a big question in Cross River state due
to climate change impacts.
Climate change is a major threat to food security in
many regions of the developing world, which are
largely dependent on rainfed and labor-intensive
agricultural production (Parry et al., 1999, 2004; IPCC,
2001a). Although the issue of food security is directly
linked to climate variability and change (Winters, 1999;
Reilly, 1995), it must be noted that climate is not the
single determinant of yield, nor is the physical
environment the only decisive factor in shaping food
security (Parry et al., 2004). But climate change would
severely compromise agricultural production and access
to food (IPCC, 2001a). This applicable to the
developing countries, so climate change study as it
relate to food security must be taken seriously due to its
negative impacts. This is in line with the finding of the
United Nation (2005) which observed that growing
populations and poor agricultural productivity have
been the main reasons for food shortages in the regions
of Sub-Saharan Africa and Southern Asia.
Food security is an essential element of overall
well-being. Increasingly, in the last decade attention has
been focused on means of eliminating food insecurity
and hunger world-wide. The 1992, international
conference on nutrition and the 1996 World Food
Summit both emphasized the critical need to decrease
food insecurity and hunger globally. Detailed
understanding of food security globally is of greater
significance in this study.
Food security exists, according to the world food
summit draft plan of action, when all people at all times
have physical and economic access to sufficient, safe
and nutritious (and some would add culturally
acceptable and adequate), food to meet their dietary
needs for an active and healthy life (World Food
Summit, 1996a). In other words, food security depends
on the availability, accessibility, adequacy and
acceptability of food.
The number of people without enough food to eat
on a regular basis remains stubbornly high, at over 800
Asian J. Agric. Sci., 5(4): 56-61, 2013
57
million and is not falling significantly. Over 60% of the
world’s undernourished people live in Asia and a
quarter in Africa (FAO, 2002). Food insecurity remains
a global threat and human tragedy. Food insecurity
results in considerable health, social, psychological and
behavioural consequences and is undeniably linked to
poverty. Climate change refers to the variation in the
earth’s global climate or in regional climates over time.
It describes changes in variability or average state of
the atmosphere overtime scales ranging from a decade
to millions of years (Ikeme, 2001).
Food security is an environmental issue, because
hunger as a result of food insecurity drives people to
exploit marginal lands, misuse water supplies, exhaust
soils and deforest the land. The forest also provide
habitat for myriads of wildlife that are hunted for games
to meet the protein needs of the rural household.
According to FEPA (1992), the World Bank reports
estimate that the animal term losses from deforestation
to Nigeria will be around US$750 million except
mitigative measures are taken. The world’s vegetation
can be described as the renewable green gold
(Odeyemi, 1998) on which the long term sustainability
of life on earth rests. It is the single source of primary
biological production that sustains the human
population and animal species.
Climate change impacts are already visible and the
most recent scientific evidence shows the problem is
worsening fast, with current trajectories of Greenhouse
Gas (GHG) emissions and sea-level rise outpacing
previous projections (IARU, 2009). Changing
temperature and precipitation averages and a more
variable, unpredictable, or extreme climate can alter
today’s yields, earnings, health and physical safety and
ultimately the paths and levels of future development.
These are already manifesting in Nigeria including
Cross River state in terms of low agricultural yield and
ill health such as malaria and borne diseases.
Climate change phenomenon affects agriculture in
a number of ways. For example, uncertainties in the
onset of the farming season, due to changes in rainfall
characteristics (early rain may not be sustained and
crops, planted at their instance may become smothered
by heat waves). This can lead to an unusual sequence of
crop planting and replanting which may result in food
shortages due to harvest failure as was reported by
Okoh et al. (2011). Extreme weather events such as
thunderstorms, heavy winds and floods, devastate
farmlands and can lead to crop failure. Pests and crop
diseases migrate in response to climate changes and
variations (e.g., the tsetse fly has extended its range
northward) and will potentially pose a threat to
livestock in the drier northern areas (FAO, 2002).
The consequences of hunger and malnutrition are
adversely affecting the livelihood and well-being of a
massive number of people and inhibiting the
development of many poor countries (Gebremedhin,
2000). These led to the following research questions:
What is the relationship between climate change
and the food security of the poor rural households’
in the state
What is the food security status of the rural
household in the state
What are the impacts of climate change events on
food security of the rural households in the state
MATERIALS AND METHODS
The study area: Cross River State is located within
Latitude 05° 13’ 26’’ North and longitude 08° 17’ 44’’
East. The State is covered by a body of waters from the
tributaries of the Cross River and the Atlantic Ocean.
This renders the land very fertile and provides abundant
aquatic resources for exploitation. Two-thirds of Cross
River State is covered by tropical rain forests, making it
one of the world's biodiversity hotspots. The state is
also blessed with mineral resources like: oil and gas;
clay; salt; lime stone; kaolin, barite and quartzite
(www.//en.wikipedia.org).
Cross River State has a land mass of 21,930 km2
with a population estimated at 2.89 million persons
(National Population Census (NPC), 2006). Forty
percent of the estimated population constitutes the
active population that is engaged in various economic
activities; ranging from subsistence agriculture to urban
commerce and transport business.
Agriculture has, since 1970, been acknowledged as
the leading economic sector of the state. Agriculture
currently employs about 80% of the State's labour force
and contributes about 40% to the Gross Domestic
Products (GDP) of the State (Crossriverstate.gov.ng).
The Cross River State capital is Calabar and the
State has 18 local government areas namely; Abi,
Akamkpa, Akpabuyo, Bakassi, Bekwara, Biase, Boki,
Calabar Municipal, Calabar South, Etung, Ikom,
Obanliku, Obubra, Odukpani, Obudu, Ogoja, Yakuur
and Yala. Cross River state climate and weather is
tropical but temperate in the north eastern fringes, with
dry and wet seasons, with major Languages as Efik,
Ejagham, Bekwarra and English.
Multistage sampling procedure was used in random
selection of local government areas, communities and
households for the research study. Firstly, six local
government areas were selected from the 18 local
government areas. Secondly, 2 communities from each
of the local government areas were selected, making it
up to 12 communities. Finally, twenty five rural
Asian J. Agric. Sci., 5(4): 56-61, 2013
58
households were randomly selected from each of the
sampled communities making it up to 300 households.
Data for this study were obtained using structured
questionnaire survey. Properly filled questionnaires
utilized for this research study were 284.
Data collection: The mean of annual time series data
from Nigerian Meteorological Agency (NIMET) that
include the following; temperature and rainfall from
January, 1971 to December, 2009 were collected for the
study. The primary data (field survey data) were
obtained using structured questionnaire survey.
Method of data analysis:
Descriptive statistics: Descriptive statistics were used
to summarize the socio-economic characteristics and to
examine the severity of food insecurity as well as the
food security status among rural farming households.
Food security index: Food security index was used to
determine the level of food insecurity among the rural
households that have been affected by flood and or
other climate hazard over the past 38 years. Food
security equation used by Feleke et al. (2003) and ways
of measuring household food security status by
Hoddinott (2001) were adopted for this study. The
equation is stated as:
C* = Cj – Yj (1)
Food security indicator for this study is defined by
frequency and the number of different food consumed
over a period of time.
where,
C* = Food security index of rural farming
household
Cj = Quantity of food consumed (N = 1 to 5)
Yj = Expected required food to be consumed
(N = 5)
If C* = 0 = The household will be said to be a food
secured household
If C*<0 = Then the household will be said to be
food insecure
The required food = carbohydrate, fat/oil, vitamin,
mineral and protein given food. Hoddinott (2001)
outlined four ways of measuring household food
security status; among them is dietary diversity which
involves determining the frequency and the number of
different foods consumed by an individual over a period
of time. Dietary diversity method of measurement was
preferred to other methods as it is very difficult to
calculate exactly the quantity of rural household food
consumption in kilogram’s or calories as most daily
food consumed by the rural farming households are not
measured (Emaziye and Okoh, 2012).
Therefore, food security index of the rural farming
household were obtained based on the frequency and
the number of different foods consumed by household
daily over a period of time (Carbohydrate, Vitamins,
Water, Proteins, Minerals and Fat/oils). Water was
excluded as all the rural households consume water
daily; hence a food secured household is expected to
consume all the 5 categories (Carbohydrate, Vitamins,
Proteins, Minerals and Fat/oils).
Expected required food to be consumed (Yj) = 5
Quantity of food actually consumed daily (Cj)
ranges from 1 to 5
Food security index of rural household (C* = Cj
Yj) = 5-5 = 0 (food secured household)
While C*<0 is food insecure household, but for the
purpose of this study the food insecure household
category was further categorized into mild food
insecure, moderately food insecure and severe food
insecure household.
Food security index of rural household (C* = Cj
Yj) = 4-5 = -1 (Mild food insecure)
Food security index of rural household (C* = Cj – Yj) =
3-5 = -2 (Moderately food insecure)
Food security index of rural household (C* = Cj – Yj) =
2-5 = -3 (Severe food insecure)
Correlation matrix: Correlation matrix was used to
determine the relationship between calculated climate
Change variables coefficient of variation and food
security of rural household in Cross River state.
Fs = Atcv Tcv + ArcvRcv +Aycv Ycv + e (2)
where,
Fs = Food Security
TCV = Temperature coefficient of
variation (%)
Rcv = Rainfall coefficient of variation (%)
Ycv = Food production (yield) coefficient
of variation (%)
e = Error term
Atcv, Arcv, Aycv = Model parameters
RESULTS AND DISCUSSION
Socio-economic characteristics of respondents: The
mean annual income of the rural farming households in
Cross River state was N71, 895 ($ 412) revealing a low
annual income level which shows a poverty situation of
the rural household of less than $1 a day. The mean age
Asian J. Agric. Sci., 5(4): 56-61, 2013
59
Table 1: Socio-economic characteristics of respondents in cross river
state, Author computed result, 2011
Variables
Respondents
Percentages
Age (Years)
(n = 284)
(%)
30 39
34
11.9
40 49
118
41.6
50 59
103
36.3
60 69
29
10.2
70 79
0
Mean
49 years
Gender
Female
126
44.4
Male
158
55.6
Marital Status
Single
19
6.7
Married
178
62.7
Widow
51
18.0
Widower
6
2.1
Divorced
30
10.5
Educational Status
Informal
84
29.6
Primary
117
41.2
Secondary
57
20.1
Tertiary
26
9.1
Mode
Primary school
Household Size
2 4
9
3.2
5 7
40
14.1
8 10
108
38.0
11 13
82
28.9
14 16
45
15.8
Mean (persons)
9
Annual Income (N)
21,000-60,000
134
47.2
61,000-100,000
144
50.7
101,000-140,000
5
1.8
141,000-180,000
1
0.3
181,000-220,000
0
0.0
221,000-260,000
0
0.0
Mean (N)
71, 895 ($412)
Author computed result, 2011
Table 2: Distribution of respondents according to food security index,
Source: Field surveys data, 2011
Food security index
Cross river (n = 284)
Percentages
Food secured (0)
12
4.1
Mild food insecure
(-1)
119
41.9
Moderately food
insecure (-2) 122 43.0
Severe food insecure (-
3)
31
11.0
Mean
Moderately food insecure
Field surveys data, 2011
of respondents is 49 years. Most of them engage in
farming activities and males dominate as the household
heads (Table 1). The household size has a mean of 9
persons showing a large household size while primary
school level of education was dominant in the state.
Most rural households were married confirming that
they were conscious on the level of climate change
variables that affect food security in the state.
Rural household food security index: Table 2 shows
the food security index in Cross River State to be
moderately food insecure on the average. This is
Table 3: The relationship between climate change variables
(temperature and rainfall) and food security in cross river
state, Author computed result, 2011
Correlation
Food
security (FS)
Temperature
(Tcv)
Rainfall
(Rcv)
Pearson
Correlation
1.000
.
.
.
1.000
.
1.000
Sig.
(1-tailed)
.
.000
.000
.000
.
.
.000
.
.
N
5
5
5
5
5
5
5
5
5
Author computed result, 2011
Table 4: Distribution of respondents according to the level of impact
of losses, Field survey data, 2011
Impact of losses
Cross River (n = 284)
Percentages
No effect (0)
31
10.9
Low (1)
21
7.4
Moderate (2)
38
13.4
Severe (3)
117
41.2
Very severe (4)
77
27.1
Mode
Severe
Field surveys data, 2011
Table 5: Distribution of respondents according to estimated annual
income losses (N), Field survey data, 2011
Estimated losses (N)
Cross river (n = 284)
Percentages
20,000 39,000
60z
20.1
40,000 59,000
184
64.8
60,000 79,000
40
14.1
80,000 99,000
0
0.0
Mean (N)
48,221
Field surveys data, 2011
confirmed by Olayemi (1996) that the issue of food
insecurity is of high importance in Nigeria because
average calorie and protein intake is grossly inadequate
and that estimates showed that at least 41% of the
population is food insecure: with 16% being severely
undernourished. This situation if not properly checked
will lead to non achievement of one of the millennium
Development Goals (MDGs) initiative aimed at
achieving food security globally (in particular the
MDG1 to eradicate extreme poverty and hunger).
The relationship between climate change variables
(temperature and rainfall) and food security in cross
river state: The correlation matrix results in Table 3
reveals that rural household food security has a
statistical significant relationship with the climate
change variables (temperature and rainfall) in Cross
River State. The results revealed that temperature and
rainfall were contributors toward rural household food
security in the state since they were statistically
significant.
Level of impact of losses: Table 4 reveals that rural
households in Cross River state perceived a severe
impact of losses. This impact was as a result of climate
Asian J. Agric. Sci., 5(4): 56-61, 2013
60
change events such as flooding that destroyed most of
their agricultural production (yield). This brought a
colossal loss in income arising from the loss in
agricultural output.
The average estimated annual income losses per
households of N48, 221 ($ 321.47) recorded in the
state. The percentage of annual losses to annual income
was 67.07% losses (Table 5).
CONCLUSION AND RECOMMENDATIONS
The mean annual income of the rural farming
households in Cross River state was N71, 895 ($ 412)
revealing a low annual income level. This shows a
poverty situation of the rural household of less than $1
a day. The mean age of respondents is 49 years
dominated by male headed households with a mean
household size of 9 persons. The percentage of annual
losses to annual income was 67.07% with a severe
impact of losses witnessed in the state. Food security
index in Cross River State reveals moderate food
insecurity situation. The study revealed that
temperature and rainfall were contributors toward rural
households’ food security in the state since they were
statistically significant. The determination of the effects
of climate change variables and events on rural
households’ food security will assist in the evaluation
of rural households’ economic and physical access to
their daily food needs for a healthy life. Government
and donor agencies should provide a short-term relief
measures to alleviate the food insecurity situations in
the state, as rural households are moderately food
insecure. The rural farming households should be
encouraged to carry out climate change adaptation and
mitigation measures in alleviating the food insecurity
situation in the state.
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... Food security index: food security index was used to determine the level of food insecurity among rural farmers that have been affected by drought, flood, and other climate hazards over the past 40 years. The food security equation used by Felake, et al., (2003) and ways of measuring farmers' food security status by Hoddinott (2001) in Emaziye et al., (2013) were adopted for this study. The equation is stated as: C x = Cj-Yi---------------------i C x = food security index of rural farmers ...
... Hoddinott (2001) in Emaziye (2013) outline four ways of measuring household food security status; such as dietary diversity which involves determining the frequency and the number of different foods consumed by an individual over a period of time. Therefore food security index of rural farmers in this study was adopted from Emaziye (2013), based on the total household daily consumption (carbohydrate, vitamins, water, proteins, minerals, and fat/oil). ...
... Fs = Atcv Tcv + Arcv Rcv + Aycv Ycv +e where, Fs = food security Tcv = Temperature coefficient of variation (%) Rcv= Rainfall coefficient of variation (%) Ycv = food production (yield) coefficient of variation (%) E = Error term Atcv, Arcv, Aycv= Model parameter. Adopted from: Emaziye et al., (2013). ...
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Anthropogenic climate change is adversely impacting people and contributing to suffering and increased costs from climate-related diseases and injuries. In responding to this urgent and growing public health crisis, mitigation strategies are in place to reduce future greenhouse gas emissions (GHGE) while adaptation strategies exist to reduce and/or alleviate the adverse effects of climate change by increasing systems’ resilience to future impacts. While these strategies have numerous positive benefits on climate change itself, they also often have other positive externalities or health co-benefits. This knowledge can be harnessed to promote and improve global public health, particularly for the most vulnerable populations. Previous conceptual models in mitigation and adaptation studies such as the shared socioeconomic pathways (SSPs) considered health in the thinking, but health outcomes were not their primary intention. Additionally, existing guidance documents such as the World Health Organization (WHO) Guidance for Climate Resilient and Environmentally Sustainable Health Care Facilities is designed primarily for public health professionals or healthcare managers in hospital settings with a primary focus on resilience. However, a detailed cross sectoral and multidisciplinary conceptual framework, which links mitigation and adaptation strategies with health outcomes as a primary end point, has not yet been developed to guide research in this area. In this paper, we briefly summarize the burden of climate change on global public health, describe important mitigation and adaptation strategies, and present key health benefits by giving context specific examples from high, middle, and low-income settings. We then provide a conceptual framework to inform future global public health research and preparedness across sectors and disciplines and outline key stakeholders recommendations in promoting climate resilient systems and advancing health equity
... Apata ( Similarly, Emaziye, Okoh, and Ike (2013) studied the effect of climate change on food security of rural households in Cross River State using Food Security Index. The result revealed a moderate food insecurity situation, and that temperature and rainfall 46 were found to be statistically significant as contributors toward rural households' food security in the state. ...
Thesis
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This study assessed rural peoples’ perception, vulnerability, and adaptation capacity to climate change in Kaduna State in order to develop an adaptation framework that could enhance the resilience of the vulnerable people. Data on rural peoples’ perception, impact, vulnerability, and adaptation capacity to climate change in the six selected Local Government Areas (LGAs) were collected by using household questionnaire survey, focus group discussions, key informant survey, and field observations. Forty years (1975-2014) monthly temperature and rainfall data for three meteorological stations in the state were used for this study. A major information solicited from the respondents was the observed variations in temperature and rainfall, and the occurrence of extreme events over the past 30 years. Trends in temperature and rainfall variations were analyzed using linear trend lines, standard deviation, and Cramer’s test. Impacts of climate change were determined using a five point Likert scale. A total of 20 indicators were used in assessing the vulnerability of the rural communities’ people to the changing climate. The fact that these indicators were in different units and scale, they were normalized using two types of functional relationship: 1) when the observed values are positively related to the vulnerability; and 2) when the values are negatively related to the vulnerability. A five point Likert scale was also used to assess the adaptation capacity of the rural communities to the changing climate based on five livelihood assets: wealth, farm inputs, availability of infrastructures and institutions, irrigation potentials, and literacy level. The results of trend analysis of both the observed temperature and rainfall from the linear trend lines, the plotted standard deviation, and the Cramer’s test in all the zones showed an increasing trend from the beginning of the data (1975) to the recent years. Findings showed that the study area has recorded a mean increase in average temperature and annual rainfall of 0.793oC and 258.29mm respectively for the forty years (1975-2014) period studied. The respondents’ perception that temperature is increasing is in line with the observed temperature data of the study area. On the other hand, the perception that rainfall is decreasing in the study area is as a result of the shrinking in length of the rainy season. Findings also showed that majority of the respondents, including the focus group discussions and key informant survey, have a good knowledge of the fact that industrial pollution, combustion of fossil fuel and destruction of nature through deforestation, bush burning, urbanization and industrialization are some of the major human causes of climate change. The mean adaptive capacity index among the rural communities revealed that Kajuru LGA has high adaptive capacity (3.87) to climate change. Moderate adaptive capacity is recorded in Kagarko (3.27), Soba (3.12) and Sanga (3.07) LGAs, while Ikara (2.42) and Kauru (2.35) LGAs have low adaptive capacity and are likely to be the most threatened LGAs in the state in terms of adaptation capacity. The result of the analyzed 20 vulnerability indicators revealed that vulnerability varies considerably among the various communities and social groups. Ikara was found to be the most vulnerable LGA and is ranked 1st. It is therefore classified as highly vulnerable in the state. Sanga, Kauru, and Soba LGAs were ranked 2nd, 3rd, and 4th respectively, and are classified as moderately vulnerable. On the other hand, the less vulnerable LGAs are Kagarko (ranked 5th) and Kajuru (ranked 6th). Findings showed that households that do not own livestock, farmlands and/or irrigated lands in addition to their low literacy level are highly vulnerable as were households that have no access to fertilizer and are located far away from farm inputs, health care and veterinary services. Findings further showed that the most vulnerable social group are the poor. On the basis of findings, the study recommends awareness programs on climate change challenges; the development of climate change policies that would enhance the adaptive capacities of the rural communities that are specifically geared toward more vulnerable areas of the state; livelihoods diversification and moving away from over reliance on natural resources that are climate-sensitive; and lastly, the developed rural communities’ adaptation framework model if implemented will go a long way in enhancing the resilience of the vulnerable rural communities of Kaduna State.
... Several studies have shown that social, economic and environmental factors affect food security. Socio-economic factors such as income, household size, credit access, livestock ownership, level of education, farm size, sex, age of head of household, marital status (Ahmed and Dotti, 2014;Djangmah, 2016;Goshu, 2016;Ajaero, 2017;Dawit and Zeray, 2017) and environmental factors such as climate change, soil fertility, drought and flooding (Nzeadibe et al., 2011;Emaziye et al., 2013;Yaro, 2013) all define level of food security. Flooding as an environmental factor affecting food security has not been extensively studied in South-eastern Nigeria, even though Ramakrishna et al. (2014) and Zakari et al. (2014) found flooding to have negative impacts on food security in India and Niger Republic, respectively. ...
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... Indeed, a number of scholarly attention and reports have been generated on the incidence of climate change in the Niger Delta such as Emaziye, et al (2013); Ibaba (2012);Efe, (2011);Nzeadibe, et al (2011);and Akinro, et al (2008). However, these works focused mainly on such isolated issue like climate change and conflict; agricultural production; fish farming; flood hazard, sea level rise, et cetera. ...
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In the early 1980s, a paradigm shift occurred in the field of food security, following Amartya Sens (1981) claims that food insecurity is more of a demand concern, affecting the poor's access to food, than a supply concern, affecting availability of food at the national level. Despite the wide acceptance of Sen's thinking, many controversies including the relative importance of supply-side versus demand-side variables in causing and solving food insecurity have remained in academic and policy circles. This study develops a recursive household food security model within the framework of consumer demand and production theories following Singh et al. (1986), and parses out the relative importance of supply-side versus demand-side variables in determining household food security in southern Ethiopia. Based on results of a test of full/reduced model and the magnitude of changes in conditional probabilities of food security, we conclude that the supply-side variables are more powerful determinants of food security than the demand-side variables. Copyright 2005 International Association of Agricultural Economics.
The socioeconomics effects of climate variability on rural farming households and their food security status in Niger Delta region
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Emaziye, P.O. and R.N. Okoh, 2012. The socioeconomics effects of climate variability on rural farming households and their food security status in Niger Delta region, Nigeria. Int. J. Agric. Dev. Econ., 2(1): 111-119.
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