The aim of this paper is to understand and identify factors affecting the choice of drought coping mechanisms in smallholder farm households living in dry lands of northern Eritrea. Data on socioeconomic characteristics and drought coping mechanisms were collected using a structured questionnaire and focus group discussions from a sample of 200 households drawn from dry lands of northern Eritrea using stratified random sampling. Multinomial logistic regression and descriptive statistics were used for data analysis. The findings of this research indicate that the choice of household’s drought coping mechanism is influenced by livestock ownership, current asset holding, its level of food insecurity, access to credit and age of household head. A household with a high amount of livestock is more likely to depend on selling livestock as a drought coping mechanism. However, if a household is food insecure, it is more likely to choose migration, remittance, restriction of consumption, and borrowing as a means for coping with drought episodes. Moreover, younger household heads tend to look for off-farm work than the selling of livestock. Policies and relief programs aimed at enhancing rural household’s resilience to drought episodes need to consider a multi-dimensional approach.

1. Understanding Drought Coping Mechanisms in Smallholder Farm Households: Evidence from Dry Lands of Eritrea
Understanding Drought Coping Mechanisms in Smallholder
Farm Households: Evidence from Dry Lands of Eritrea
Menghistab Ghebreselassie Debesai1*, Tesfai Tsegai Kidane2,7, Woldeselassie Ogbazghi3,
Woldeamlak Araia4, Simon Measho5, Semere Amlesom6
1,2Department of Agricultural Economics, Hamelmalo Agricultural College, Eritrea, P.O. Box 39
3,5Department of Land Resource and Environment, Hamelmalo Agricultural College, Eritrea, P.O. Box 397
4Department of Agronomy, Hamelmalo Agricultural College, Eritrea, P.O. Box 397
6Department of Agricultural Engineering Hamelmalo Agricultural College, Eritrea, P.O. Box 397
7China Agricultural University, Haidian district, Beijing, China, P. O. Box, 100083
The aim of this paper is to understand and identify factors affecting the choice of drought coping
mechanisms in smallholder farm households living in dry lands of northern Eritrea. Data on
socioeconomic characteristics and drought coping mechanisms were collected using a
structured questionnaire and focus group discussions from a sample of 200 households drawn
from dry lands of northern Eritrea using stratified random sampling. Multinomial logistic
regression and descriptive statistics were used for data analysis. The findings of this research
indicate that the choice of household’s drought coping mechanism is influenced by livestock
ownership, current asset holding, its level of food insecurity, access to credit and age of
household head. A household with a high amount of livestock is more likely to depend on selling
livestock as a drought coping mechanism. However, if a household is food insecure, it is more
likely to choose migration, remittance, restriction of consumption, and borrowing as a means for
coping with drought episodes. Moreover, younger household heads tend to look for off-farm work
than the selling of livestock. Policies and relief programs aimed at enhancing rural household’s
resilience to drought episodes need to consider a multi-dimensional approach.
Keywords: Drought, Coping mechanism, Dry lands, Smallholder farmers, Eritrea
INTRODUCTION
The prevalence and frequency of drought in Sub Saharan
Africa, India, North America, China, Russia, Australia, and
western Europe have witnessed that it is a topic of global
concern (Wilhite, 1985). The prolonged social and
environmental impact has resulted in continuous land
degradation and desertification as it happened in the Sahel
regions in the late 1960’s and 1970’s (Zing, 2003). Severity
and duration, and narrowing of the gap between water
supply and demand have remarkably increased in both the
developing and developed world (Wilhite, 2000). The
Intergovernmental Panel on Climate Change (IPCC)
disclosed that the impact of drought is higher in developing
countries and particularly in Sub-Saharan Africa (SSA)
due to their vulnerability and low adaptive capacities,
though it is felt across all affected regions (IPCC, 2007).
During the last four decades, the SSA has witnessed
increased frequency of drought at times with devastating
consequences on humans and natural resources base.
Such disasters threaten food security through the
disruption of normal cropping, pastoral and marketing
activities with negative impacts on economic growth
(Ndikumana et al., 2002). Communities coping response
to drought episodes are highly diverse and complex as
they vary by region, community, social group. household,
gender, age, season and time in history (Chambers,
1989). A number of studies identified specific variables
which may positively or negatively affect the choice of
particular coping mechanisms. While previous studies
focus on long-term climate change adaptation of farmers
*Corresponding Author: Menghistab Ghebreselassie
Debesai, Department of Agricultural Economics,
Hamelmalo Agricultural College, Eritrea, P.O. Box 397.
E-mail: robeljan20134@gmail.com
Case Study
Vol. 5(1), pp. 548-554, March, 2019. © www.premierpublishers.org, ISSN: 2167-0477
Journal of Agricultural Economics and Rural Development

2. Understanding Drought Coping Mechanisms in Smallholder Farm Households: Evidence from Dry Lands of Eritrea
Debesai et al. 549
in general (Deressa, et al., 2010; Berman, 2014; Burney et
al., 2014), this paper focuses on short term coping
responses of smallholder subsistence farmers. While
adaptation strategies are of long-term duration, coping
mechanisms refer to adjustments or immediate
interventions, which take place in order to manage the
losses or take advantage of the opportunities presented by
a changing climate (Coulibaly et al., 2015).
Owing to its geographical location, Eritrea is naturally
prone to greater climatic variations in general and drought
in particular. Eritrea’s current climatic condition is quite
variable and is influenced by the Sahel Saharan desert,
the Red Sea and its various physical characteristics.
According to the report of the Ministry of Land, Water and
Environment (MLWE), around 70% of the country is
characterized as hot and arid, receiving an annual rainfall
of less than 350 mm (MLWE, 2007). Environmental
degradation has been prevalent, water bodies have dried
up, forests disappeared, fertile soils eroded and the
expansion of desertification has been observed during the
past several decades and has been observed in the
country every 5-7 years in the past. Moreover, global
projections of climate change indicate that the East African
region including Eritrea is among the most vulnerable to
the adverse effects of climate change, mainly because of
its least adaptive capacities. Eritrea is expected to
experience temperature increases with the rise of 1.1o to
3.8o C by 2060s. While uncertainty about changes in
precipitation exists, the report of the Ministry of Agriculture
(MOA) discloses that there is an agreement that the
country will experience more frequent droughts (MOA,
2010). Furthermore, about 80% of the population depends
on traditional subsistence agriculture, including crop
production and livestock husbandry. This production
system is affected by a host of factors including high
rainfall variability with recurrent and long drought periods,
continuous degradation of the soil, and loss of agricultural
biodiversity, frequent pest outbreaks and lack of research
and extension services. As a result, people who live
especially in the dry land are much more vulnerable to
drought, as they have limited adaptive capacities mainly
due to the shortage of agricultural inputs and lack of
knowledge concerning environmental management
(MLWE, 2007). This research aims to understand the
different drought coping mechanisms in the drylands and
identify the socio-economic factors affecting the choice of
their coping mechanisms.
THEORETICAL FRAMEWORK
Drought may be defined as conceptually or operationally
with reference to the definitions formulated to identify the
boundaries of the concept. The conceptual definitions
provide little guidance to those who wish to apply them to
current drought assessments. For example, the Oxford
dictionary (Stevenson, 2010) defines drought conceptually
as “a prolonged period of abnormally low rainfall, leading
to a shortage of water”. The operational definitions attempt
to identify the onset, severity, and termination of drought
and sometimes the potential impacts. Operational
definitions can also be applied in analysing frequency,
severity, and duration drought for a given historical period
(Wilhite, 1985).
Moreover, drought can be divided into different categories
from disciplinary perspectives. Wilhite (1993) has
identified six types of drought as meteorological,
climatological, atmospheric, agricultural, hydrologic, and
water-management and discussed them in the following
four groups. 1-The meteorological drought has been
defined as a “period of more than some particular number
of days with precipitation less than some specified small
amount.” 2- Agricultural definition of drought relates the
meteorological definition that relates the current
meteorological conditions with a specific plant’s biological
characteristics, stages of development and the physical
and biological properties of soil. 3 -The hydrologic
definitions of drought emphasize on the effects of dry
spells on surface or subsurface hydrology, instead of the
meteorological explanation of the event. 4 - A relatively
more comprehensive definition of drought is the economic
view of drought. It can be viewed as inputs to the physical
and social environment in which the characteristics of the
event and socio-physical environment interact to produce
a certain impact and the social system responds to
mitigate or alleviate the impact (Wilhite, 1985). Thus, as
drought has both natural and social dimensions the risk
associated with a drought episode in any region is the
product of the probability of occurrence of the event and
vulnerability of the society in the region to the event
(Wilhite, 2005). Vulnerability, as defined by Chambers
(1989), is the degree of defenselessness, insecurity,
exposure to risk, shocks, stress, and difficulty in coping
with them. The Palmer Drought Severity Index (PDSI) that
relates drought severity to the accumulated weighted
differences between actual precipitation and the
precipitation requirement of evapotranspiration is probably
the best internationally known meteorological definition of
drought (Palmer, 1965).
The issue of this paper is more on socio-economic drought
emphasising on coping mechanisms. Though complex,
understanding peoples vulnerability is vital in designing
drought preparedness, mitigation, and relief policies and
programs. The macro level determinants of vulnerability
may include, the strength of security, the structure of local
governance and its ability to provide relief resources. At
the micro leve of a households physical assets, human and
social capital determines the degree of vulnerability.
Therefore, households with more diverse asset base are
expected to be more resilient and the most impoverished
communities exhibit more vulnerability (Wilhite, 2005).
Given the differences in biophysical and socio-economic
conditions understanding the vulnerability, responses of
the social system to drought episodes and the factors that
affect the choice of these coping responses is important
for designing policies and programs that promote
resilience of vulnerable communities.

3. Understanding Drought Coping Mechanisms in Smallholder Farm Households: Evidence from Dry Lands of Eritrea
J. Agric. Econ. Rural Devel. 550
METHODOLOGY
The study was conducted in dry lands of Eritrea in
Hamelmalo and Habero subzones of Anseba region,
Eritrera. The study area is located at 150 47’ 34’’ and 160
29’ 52’’ latitude, 380 15’ 32’’ and 380 36’ 45’’ longitude;
covering an area of 17, 8197 hectares of land, and is
sparsely populated with 74, 463 individuals (Araia, et.al.,
2014).
Sampling and Data collection Method
Considering a fairly acceptable degree of the error term
and 95% confidence interval, the sample size was
calculated using the following formula: n = (z2
α/2pq)/e2
(Israel, 2016). Using stratified random sampling, a sample
size of 196 plus 4 contingencies a total of 200 households
was drawn. Two sets of data: structured questionnaire
survey and focus group discussions were used to collect
socio-economic characteristics of households including
age, sex, level of education, household income, access to
credit, food security and livestock ownership. In order to
capture relevant information four Group discussions, two
in each subzone, were conducted with elders and
knowledgeable community members. A check list was
prepared to guide the discussion. Information on different
drought coping mechanisms used by individual
households such as selling of livestock, migration,
remittance, restriction of consumption, borrowing or credit,
using of reserve food or selling the assets and off-farm
work were also collected in order to have an in-depth
understanding of the coping mechanisms.
Model Specification and Data Analysis
This study employed a multinomial logit (MNL) model to
analyse factors influencing the choice of drought coping
mechanisms. The techniques of multinomial logit models
can be employed to study nominal categories where there
is a single decision among two or more alternatives
(Greene, 2002;Gujarati, 2004). The theoretical framework
adopted for this study is based on the random utility model
as specified by Green (2003). A common formulation is the
linear random utility model:
𝑈 = 𝑋𝛽 + 𝜀 Equation (1)
The probability that a given household chooses certain
coping strategy among many alternatives is assumed to
be a function of a number of attributes; namely socio-
economic, institutional and environmental characteristics,
X. This can be technically represented as follows:
Pr(Yi = j) =
𝑒 𝛽𝑗𝑋𝑖
∑ 𝑒 𝛽𝑋𝑛
𝑘=0
; 𝑗 = 1. . 𝑛 𝐸𝑞𝑢𝑎𝑡𝑖𝑜𝑛 (2)
Where βj is a vector of coefficients on each of the
exogenous variable X, and Yij denotes a random variable
taking on the values {1, 2 … j} for choices j, and Xi denotes
a set of conditioning variables (Greene, 2002; Wooldridge,
2002).
In this particular case, Yij represents the drought coping
strategy represented by j including selling of livestock,
migration, remittance, restriction of consumption,
borrowing or credit, that a particular household chooses for
the number of i observations; whereas Xi represents a
number of socioeconomic characteristics of households
and other factors for the number of i observations.
From this regression equation, we can understand that the
relationship between the response variable Yij and
explanatory variable Xi is nonlinear. Equation (2) can,
therefore, be normalized to remove indeterminacy by
assuming that β0 = 0 and the probability is estimated as;
Pr (Yi =
1
Xi
) =
𝑒 𝛽𝑗𝑋𝑖
1 + ∑ 𝑒 𝛽𝑋𝑛
𝑘=0
; 𝑗 = 1. . 𝑛 Equation (3)
In satisfying the requirements of keeping the values of the
response variable between 0–1, the model is designed in
a nonlinear form which is not compatible with the familiar
OLS procedure of estimation procedures. However, this
problem can be linearized, using the Maximum likelihood
estimation of Equation (3) that yields the log-odds ratio
presented in Equation (4):
𝐿𝑛 (
Pij
Pik
) = 𝑋𝑖(𝛽𝑗 − 𝛽𝑘) = 𝑋𝛽 Equation (4)
That is, Ln, in (4) the log of the odds ratio, is now linear not
only in X but also (from the estimation viewpoint) linear in
the parameter.
The advantage of the MNL is that it permits the analysis of
decisions across more than two categories, allowing the
determination of choice probabilities for different
categories (Maddala, 1992);(Wooldridge, 2002) and it is
also computationally simple (Hossain, 2009). In this study,
the coping strategy or response variables are: remittance,
restriction of consumption, borrowing, use reserve food or
sell assets, migrate, sell livestock, and off-farm work;
whereas the explanatory variable include age, sex,
education, credit, food security, household income,
household size, and livestock index. Descriptive statistics
like frequencies, percentages, and measures of central
tendencies were also used to explicit the household
characteristics and coping strategies on top of the
multinomial logit model analysis.
RESULTS AND DISCUSSION
Descriptive Statistics
The socioeconomic profile shows that the households are
characterised by a large number of aged household heads
and a low level of education. Most of the household heads
(about 69%) were male and about 18.2% were illiterate
and 74.5% at the primary level of education. The majority
(57%) do not have access to either formal or informal credit
(Table 1).

4. Understanding Drought Coping Mechanisms in Smallholder Farm Households: Evidence from Dry Lands of Eritrea
Debesai et al. 551
Table 1. Descriptive Information on Household Heads
Age (Years) Percentage
Under 18 0.7
18-24 2.2
25-34 10.3
35-44 25
45-55 29.4
Over 55 32.4
Sex
Male 69.3
Female 30.7
Education
No Education 18.2
Primary education 74.5
Secondary education 6.6
Post-secondary education 0.7
Access to Credit
Yes 43
No 57
HH size Livestock ownership
Mean (7.28) 16.57
Median (7.00) 10.00
Source: Researchers’ own calculation from survey data.
The average and median household size were
respectively 7.28 and 7 well above the average national
level. Looking at the livestock ownership the average
number of livestock ownership (equivalent to the number
of goats or sheep) is 16.6 with a median of 10, which
indicates that half of the respondents own less than 10 and
still others without any animal. The sources of income are
from agricultural and non-agricultural products. When
agriculture cannot support the livelihood of farmers due to
drought or climate change, the farmers seek for other
alternative sources of income like off-farm work, wage
labour, and remittance.
Households in the study area employ a range of drought
coping mechanisms. The most used drought coping
mechanism was the selling of livestock (26.7%); and the
least used was selling of other assets or using of reserve
food (8.1%) followed by off-farm work (8.9%), restrict
consumption (12.6%), borrowing (12.6%), remittance
(13.3%) and migration (17.8%), implying that a number of
the household don’t keep reserve food as a safety net
(Figure 1). This is partly in agreement with the finding of
(Helgeson and Dietz, 2013) in rural Uganda, where they
found the most frequently reported choice was selling of
livestock. The striking point here is that selling livestock as
a drought coping mechanism rather than more reliance on
mechanisms like eating less and spending less today,
would exacerbate the loss of productive assets.
Figure 1. Percentages of Drought Coping Mechanisms
Employed by HHs
Multinomial Regression Results
Model fitting information as given by the Chi-Square was
found to be significant at 95% level of significance,
indicating that, at least, one of the predictors’ regression
coefficients is not equal to zero in the model. The results
of the association between the household’s socio-
economic profiles and drought-coping mechanism are
presented in Table 2. Most of the socioeconomic
characteristics of the households (age, gender, level of
education and household size had no influence (P>0.05)
on the household’s choice for drought coping strategies.
There is mixed information in literature as to the influence
of socioeconomic characteristics of households on their
drought-coping mechanism. The study by (Rakgase and
Norris, 2014) showed that farm experience, farm income,
and farm size had an impact on drought coping strategies
while age, education level, and extension had no effect. In
a study on climate change adaptation strategies, (Tazeze,
Haji, & Ketema, 2012) observed that sex, age, and
education of the household head, family size, livestock
ownership, household farm income, non-farm income,
access to credit had a significant effect on the choice of
climate change adaptation strategies.
The study by (Melka et al., 2015) revealed that perceiving
climate variability and climate change does not always
guarantee coping and adaptation responses, particularly
among the rural people who face more binding constraints
that deter adaptation decisions. Legesse, et al. (2012)
investigated the small-holder farmers’ perception and
adaptation to climate variability and climate change in
Ethiopia and the results of the study showed that agro-
ecological location, sex of household head, family size, off-
26.7
17.8
13.3 12.6 12.6
8.9 8.1
0
5
10
15
20
25
30

5. Understanding Drought Coping Mechanisms in Smallholder Farm Households: Evidence from Dry Lands of Eritrea
J. Agric. Econ. Rural Devel. 552
farm income, herd size, frequency of extension contact
and training, were determinant factors influencing
adaptation strategies (Legesse, Ayele and Bewket, 2012).
Moreover (Deressa, Ringler and Hassan, 2010) observed
that wealth (on-farm income, off-farm income, and
livestock ownership) and household characteristics, such
as level of education, age of household head and
household size, increased the probability of adaptation to
drought. Farm location also influenced farmers’ adaptation
to climate change.
In their studies of Smallholder Farmers’ Perception of the
Impacts of Climate Change and Variability on Rain-fed
Agricultural Practices in Semi-arid and Sub-humid
Regions of Kenya (Kalungu, Filho and Harris, 2013)
reported that there was a significant association between
the observed changes in agricultural practices and
household gender. According to (Gebreyohannes, 2014)
access to climate information, access to extension
services and sex of household head were important
factors that affect farmers’ perception of climate change.
On the other hand, farmers use change in crop type and/or
variety, soil, and water conservation practices, crop
diversification, change in planting date and irrigation
practices as climate change adaptation options in Tigray
Region, Northern Ethiopia. Peter and James, (2015)
reported that age, gender, marital status and availability of
climate information were found to be basic determinants of
farmer’s perception on cassava as climate change crop in
Tanzania.
The present study showed that livestock ownership, food
security, household income and access to credit had
significant influences (differing in degrees) on households’
choice of drought coping mechanisms. With an increase of
livestock ownership, a particular household chooses
‘selling of livestock than ‘depending on remittance’ as a
means of coping with drought, ceteris paribus. Technically
this can be interpreted as “keeping all other factors in the
model constant, if a household were to increase livestock
index (equivalent to one goat) by one unit, the multinomial
log-odds of depending on remittance, relative to selling of
livestock as a mechanism to coping with drought
decreases by 0.073” (Table 2). More specifically, if a
household were to increase its livestock index by one unit,
it would be expected to depend on selling livestock (0.93
times) than to choose remittance as a drought coping
strategy.
On the other hand, if a household feels food insecure, it is
more likely to depend on remittance as a drought coping
mechanism than the selling of livestock. That is, keeping
all other factors in the model constant, if a household were
to feel food insecure than otherwise, the multinomial log-
odds of depending on remittance, relative to the selling of
livestock as a mechanism to coping with drought increases
by 1.75. Therefore, if a given household is food insecure,
the relative risk of depending on remittance than selling
livestock, as a drought coping mechanism, would be 5.74
times more likely when the other variables in the model are
held constant.
Further, the regression analysis indicated that a food
insecure household is more likely to depend on the
restriction of consumption than selling livestock as a
drought coping strategy. Keeping all other factors
constant, as the household feels food insecure; it is more
likely to depend on the restriction of consumption (33.81
times) as a drought coping mechanism than the selling of
livestock. Likewise, if a given household is food insecure,
the relative risk of depending on borrowing than selling
livestock, as a drought coping mechanism, would be 11.42
times more likely when the other variables in the model are
held constant. More generally, we can say that if a
household were to feel food insecure, we would expect it
to be more likely to depend on borrowing than selling
livestock to cope with drought. Whereas, if a household
has a reserve food and owns other assets in addition to
livestock, the subject prefers using the reserve or selling
other assets (37.10 times) to selling livestock when it feels
food insecure.
Similarly, a household with a higher livestock index
chooses to sell off livestock as a drought coping
mechanism than borrowing for consumption. As the
number of livestock ownership increases, a household is
more likely (0.89 times) to sell livestock as a drought
coping mechanism than to depend on borrowing, ceteris
paribus.
Another important drought coping mechanism is migration.
Food insecure households prefer to migrate as drought
coping strategy to selling their livestock i.e. one would
expect households to migrate (5.52 times) rather than
selling livestock to cope with drought. Historically,
migration in the face of drought and floods has been
identified as one of the adaptation options in Africa.
Migration has also been found to present a source of
income for those migrants, who are employed as seasonal
labor (IPCC, 2007). Moreover, households were found to
use off-farm work as a drought coping mechanism than the
selling of livestock when they feel food insecure.
Consequently, given that a household is food insecure, the
relative risk of looking for off-farm work than selling
livestock, as a drought coping mechanism, would be 32.15
times more likely when the other variables in the model are
held constant. Young working age groups (25-35) were
found to look for off-farm work than to sell livestock as a
drought coping strategy. There was no statistically
significant difference on whether to look for off-farm work
or sell livestock with other age groups. It was also found
that when households had access to credit, they were less
likely to restrict consumption as a drought coping
mechanism relative to the selling of livestock. Moreover, it
was indicated that as income of household increases, the
probabilities of choosing remittance, borrowing, using of
reserve food or migrating as a drought coping mechanism
increases relative to the selling of livestock.

6. Understanding Drought Coping Mechanisms in Smallholder Farm Households: Evidence from Dry Lands of Eritrea
Debesai et al. 553
Table 2. Coefficients and Odds Ratio of the Association between Socioeconomic Characteristics and Drought
Coping Mechanisms (Only Significant Factors Are Presented)
Comparison group Remittance Restrict Consumption
Explanatory variables β Std. Error Sig. Exp (β) β Std. Error Sig. Exp (β)
[Livestock Index] -0.073** .033 0.027 0.929** -0.031 .032 0.337 .970
[Access to Credit] -0.301 0.726 0.678 0.740 -1.345* .744 0.071 0.261*
[Food Insecure] 1.748** 0.861 0.042 5.741** 3.521** 1.241 0.005 33.81**
Comparison group Borrowing Reserve food or Sell other Assets
Explanatory variables β Std. Error Sig. Exp (β) β Std. Error Sig. Exp (β)
[Income] 0.0001* 0.00005 0.061 1.000* 0.005** 0.000 0.025 1.000*
[Livestock Index] -0.112** 0.047 0.017 0.894** -- -- -- --
[Food Insecure] 2.435** 1.034 0.018 11.42** 3.612** 1.430 0.012 37.06**
Comparison group Migrate Off-farm Work
Explanatory variables β Std. Error Sig. Exp(β) β Std. Error Sig. Exp(β)
[Income] 0.00003* .00002 0.089 1.000 0.000 0.000 0.158 1.000
[Age] [25-35] 1.333 1.318 0.312 3.793 3.857** 1.816 0.034 47.335
[Food Insecure] 1.708** 0.724 0.018 5.518 3.470** 1.296 0.007 32.145
Reference Category = Sell Livestock, ** Significant at α 0.05,* Significant at α 0.10,
Source: Researchers’ own calculation from data collected
CONCLUSION AND POLICY IMPLICATIONS
The findings of this research indicate that the choice of
households coping mechanisms is influenced by the
livestock ownership, the current asset holding, its level of
food insecurity, access to credit and age of household
head. A household with a high amount of livestock is more
likely to depend on selling livestock as a drought coping
mechanism. However, if a household is food insecure, it is
more likely to choose remittance, restriction of
consumption, borrowing and migration as a means for
coping with drought episodes.
This implies that policies and relief programs aimed at
enhancing rural household’s resilience to drought
episodes need to consider a multi-dimensional approach.
Developing and promoting drought-resistant livestock,
creating opportunities for income diversification, and
establishing effective rural finance institutions along with
extension service are intervention options that require
consideration of specific locality’s social and economic
system. Identifying the needs of different groups within a
social system could also increase the effectiveness of
such programs through tailor-made specialized support
services.
ACKNOWLEDGMENTS
The Authors acknowledge the financial support from the
Bureau of Standards and Evaluation of the National
Commission for Higher Education of the state of Eritrea;
and the Department of Environment of the Ministry of Land
Water and Environment.
REFERENCES
Berman, R. (2014) ‘Developing climate change coping
capacity into adaptive capacity in Uganda’, p. 253 pp.
Burney, J. et al. (2014) ‘Climate change adaptation
strategies for smallholder farmers in the Brazilian
Sertão’, Climatic Change, 126(1–2), pp. 45–59. doi:
10.1007/s10584-014-1186-0.
Chambers, R. (1989) ‘Editorial Introduction : Vulnerability ,
Coping and Policy’.
Coulibaly, J. Y. et al. (2015) ‘Responding to crop failure:
Understanding farmers’ coping strategies in Southern
Malawi’, Sustainability (Switzerland), 7(2), pp. 1620–
1636. doi: 10.3390/su7021620.
Deressa, T. T., Ringler, C. and Hassan, R. M. (2010)
‘Factors affecting the choices of coping strategies for
climate extremes: The case of farmers in the Nile Basin
of Ethiopia’, IFPRI Discussion Paper, 1032(November),
p. 25. Available at: http://www.ifpri.org/publication/
factors-affecting-choices-coping-strategies-climate-
extremes%5Cnhttp://www.ifpri.org/sites/default/files/pu
blications/ifpridp01032.pdf.
Gebreyohannes, G. H. (2014) ‘Impact of Climate Change
on Crop Production and Productivity in Tigray, Northern
Ethiopia: Analysis of Observed Changes and Future
Adaptation Options’, (May).
Greene, W. H. (2002) Econometric Analysis. 5th ed. New
Jersey: Prentice Hall.
Gujarati, D. (2004) Basic Econometrics. 4th ed. McGraw-
Hill Companies.
Helgeson, J. and Dietz, S. (2013) ‘Vulnerability to weather
disasters : the choice of coping strategies in rural
Uganda October 2012 Centre for Climate Change
Economics and Policy’, Ecology and Society, 18(12),
pp. 1–13.

7. Understanding Drought Coping Mechanisms in Smallholder Farm Households: Evidence from Dry Lands of Eritrea
J. Agric. Econ. Rural Devel. 554
Hossain, Z. (2009) ‘A Review On Some Alternative
Specifications Of The Logit Model’, Journal of Business
& Economics Research, 7(12), pp. 15–23.
IPCC (2007) Climate Change 2007: impacts, adaptation
and vulnerability: contribution of Working Group II to the
fourth assessment report of the Intergovernmental
Panel, Genebra, Suíça. doi:
10.1256/004316502320517344.
Israel, D. G. (2016) ‘Using Published Tables Using
Formulas To Calculate A Sample Size Using A Census
For Small Populations’.
Kalungu, J. W., Filho, W. L. and Harris, D. (2013)
‘Smallholder Farmers’ Perception of the Impacts of
Climate Change and Variability on Rain-fed Agricultural
Practices in Semi-arid and Sub-humid Regions of
Kenya’, Journal of Environment and Earth Science,
3(7), pp. 129–140. Available at: http://www.iiste.org/
Journals/index.php/JEES/article/view/6379.
Legesse, B., Ayele, Y. and Bewket, W. (2012) ‘Smallholder
Farmers’ Perceptions and Adaptation to Climate
Variability and Climate Change in Doba District, West
Hararghe, Ethiopia’, Asian Journal of Empirical
Research, 3(3), pp. 251–265.
Maddala, G. S. (1992) Introduction to Econometrics. 2nd
ed. New York, Oxford, Singapore, Sydney: Macmilan
Publishing Company.
Melka, Y. et al. (2015) ‘The effect of drought risk
perception on local people coping decisions in the
Central Rift Valley of Ethiopia’, Journal of Development
and Agricultural Economics, 7(9), pp. 292–302. doi:
10.5897/JDAE2015.0674.
MLWE (2007) National Adaptation Programme of Action-
Eritrea.
MOA (2010) Eritrea Post-Crisis Rural Recovery and
Development Programme.
Ndikumana, J. et al. (2002) ‘Copying mechanisms and
their efficacy in disaster-prone pastoral systems of
greater horn of Africa.’, Sustainable livelihoods of
farmers and pastoralists in Eritrea.
Palmer, W. C. (1965) ‘Meteorological Drought’, U.S.
Weather Bureau, Res. Pap. No. 45, p. 58. Available at:
https://www.ncdc.noaa.gov/temp-and-
precip/drought/docs/palmer.pdf.
Peter, J. and James (2015) ‘Perception of farmers on
cassava as a potential crop for climate change
adaptation in Kigoma region, Tanzania’, p. 75.
Rakgase, M. and Norris, D. (2014) ‘Factors that Influence
Choice of Drought Coping Strategies in Limpopo
Province , South Africa’, 47(2), pp. 111–116.
Stevenson, A. (2010) ‘Oxford dictionary of english’, Oxford
University Press, (ISBN-13: 9780199571123), p. 1777.
doi: 10.1093/acref/9780199571123.001.0001.
Tazeze, A., Haji, J. and Ketema, M. (2012) ‘Climate
Change Adaptation Strategies of Smallholder Farmers:
The Case of Babilie District, East Harerghe Zone of
Oromia Regional State of Ethiopia’, Issn, 3(14), pp.
2222–1700. Available at: www.iiste.org.
W. Araia, W. Ogbazghi, M. Ghebreselassie, S. M. and S.
A. (2014) Post Crisis Recovery and
DevelopmentProgram-Anseba, Eritrea.
Wilhite, D. (1985) ‘Understanding the Drought
Phenomenon: The Role of Definitions’, (August 2013),
pp. 37–41.
Wilhite, D. A. (1993) ‘Chapter 1 The Enigma of Drought’.
Wilhite, D. A (2000) ‘Drought Preparedness and Response
in the Context of Sub-Saharan Africa’, Journal of
Contingencies and Crisis Management, 8(2), pp. 81–
92. doi: 10.1111/1468-5973.00127.
Wilhite, D. A (2005) Drought and Edited by, Management.
Wooldridge, J. (2002) Econometric Analysis of Cross
Section and Panel Data. Cambridge, Massachusetts
London, England: The MIT Press.
Zing, N. (2003) ‘Drought in the Sahel’, 302(5647), pp. 999–
1000.
Accepted 14 February 2019
Citation: Debesai MG, Kidane TT, Ogbazghi W, Araia W,
Measho S, Amlesom S (2019). Understanding Drought
Coping Mechanisms in Smallholder Farm Households:
Evidence from Dry Lands of Eritrea. Journal of Agricultural
Economics and Rural Development, 5(1): 548-554.
Copyright: © 2019: Debesai et al. This is an open-access
article distributed under the terms of the Creative
Commons Attribution License, which permits unrestricted
use, distribution, and reproduction in any medium,
provided the original author and source are cited.