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American Journal of  Applied 
Statistics and Economics (AJASE)

Factors Affecting Adaptation Strategies of  Small Holder Farmer’s to Climate 
Changes: Evidence from Dale Woreda in Sidama Regional State, Ethiopia

Gezahegn Belguda Baramo1*

Volume 2 Issue 1, Year 2023
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Article Information ABSTRACT

Received: September 25, 2022

Accepted: May 15, 2023

Published: May 23, 2023

The objective of  this study was to analyzing factors that affect smallholder farmers’ choice 
of  adaptation strategy and identifies adaptation measures to climate change in Ethiopia using 
Dale Woreda as a case study. The data was collected from 359 sample households using a 
survey questionnaire and was analyzed using both descriptive statistics and econometric 
methods. Multinomial logit model (MNL) was used to identify factors influencing smallholder 
farmers’ choice of  adaptation strategies to climate change and variability.  The adaptation 
strategies considered in the MNL model were crop diversification, growing drought tolerant 
crop, soil and water management, early and late planting and small scale irrigation practice. 
The result from the multinomial logit analysis showed that sex, education, farm experience, 
family size, farm income, farm size, distance to the market, soil fertility, access to credit, access 
to climate information, and extension access were significant factors influencing smallholder 
farmers’ adaptation strategies. a unit increases in number of  years of  education could increase 
8.1% of  the likelihood of  adopting crop diversification ,1.8% of  the likelihood of  adopting 
growing drought tolerant crop and 1.2% of  the likelihood of  early and late planting as 
adaptation measures. The basic barriers to climate change adaptation on the farmers’ side are 
lack of  credit access, lack of  knowledge, lack of  support from government, shortage of  farm 
land, lack of  climate information and lack of  climate related problem. Therefore, expanding 
extension service, improving the availability of  credit and enhancing research on use of  new 
crop diversification and distributing drought tolerant crop varieties and encouraging continuous 
climate training center, disseminating climate information by local language through social 
media and providing modern tool for soil and water management and small scale irrigation by 
government are more suited in three agro-ecological zones. 

Keywords

Climate Change, Adaptation, 
Adaptation Strategy, 
Multinomial Logit Model, 
Dale Woreda 

1 Furra College, Yirgalem Campus, Sidama, Ethiopia
* Corresponding author’s e-mail: gezahegnbelg@gmail.com 

INTRODUCTION
The impacts of  climate change are experienced to 
changing degrees across and within countries due to 
contrast in exposure, susceptibility and coping capacities. 
Small holder farmers in sub -Sahara region in general 
and eastern Africa countries in particular are facing 
considerable multifaceted challenges (Yaro, 2013; IPCC, 
2007). Developing countries, particularly Small Island 
developing States, face disproportionate risks from an 
altered climate, while high-income countries are generally 
less vulnerable and more resilient. Within countries, 
people living in poverty and other vulnerable groups 
including smallholder farmers, indigenous peoples and 
rural coastal populations are more vulnerable to climate 
alter and incur greater looseness from it, while having 
fewer resources with which to cope and recover. Climate 
change can generate a vicious cycle of  increasing poverty 
and vulnerability, worsening inequality and the already 
precarious condition of  many disadvantaged groups 
(Yenesew et al. 2015; IPCC, 2014). Moreover, adaptation 
is critical and necessary in developing countries, 
especially in Ethiopia where the fact that vulnerability 
is high. Most people of  livelihoods and living standard 
are affected by the impact of  climate change. Farmers 
with better knowledge and information on climate 
change and agronomic practices enable to use adaptation 
methods to cope up with change in climate and other 

socioeconomic conditions. A better understanding of  
the local dimensions of  climatic change is also essential 
to develop appropriate adaptation measures that can 
mitigate the adverse impact of  climate change. Therefore, 
awareness of  the potential benefits from any adaptation is 
very important issue (Belay, 2017).   
This prediction and expectation coupled with the current 
situation worries all citizens especially in developing 
countries. For example, if  we take Ethiopia, the 
agricultural sector which is the backbone of  the country’s 
economy is entirely dominated by smallholder farmers 
who are very vulnerable and sensitive to climate change 
related problems. Thus, owing to this fact, the effort 
should focus on finding mechanisms in which smallholder 
farmers can reduce these problems and save their lives. 

LITERATURE REVIEW
Climate change is caused by the emission of  greenhouse 
gases into the earths atmosphere through both natural 
processes and human activities; though growing evidence 
demonstrates the largest contribution is from the 
latter. The burning of  fossil fuels, largely as a result of  
transportation, is the primary contributor to the emission 
of  carbon dioxide while processes such as deforestation 
and industrial agriculture are the main contributors to 
the emission of  methane and nitrous oxide compounds 
into the atmosphere. Despite constituting less than 

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15% to total GHG emissions, methane is a very strong 
greenhouse gas which is 23 times stronger than CO2 (FAO. 
2010; IPCC. 2007).
Agriculture is ranked as the most susceptible sector to climate 
change impacts and so do the livelihoods of  subsistence 
farmers and pastoralists. Climate change exerts multiple 
stresses on the biological, physical, social and institutional 
environments that affect agricultural production. Its impacts 
disproportionately affected Sub-Saharan African countries 
including Ethiopia because of  the higher dependency of  
their economies on climate-sensitive activities such as rain-
fed agriculture. Some of  the induced changes are expected 
to be immediate, while others involve gradual shifts in 
temperature, vegetation cover and species distributions. 
Climate change is expected to and in parts of  Africa has 
already begun to alter the dynamics of  drought, rainfall 
and heat waves, and trigger secondary stresses such as the 
spread of  pests, increased competition for resources, and 
biodiversity losses  (FAO. 2010).
To decrease vulnerability and build the resilience of  
ecological and social systems and economic sectors to 
react current and future adverse effects of  climate change 
in order to minimize the problem agricultural production, 
human health, livelihoods, food security, assets, amenities, 
ecosystems and sustainable development. There are many 
different strategies that farmers can implement to reduce 
the risk of  climate change impacts. Farmers use different 
adaptation strategies that match with the types of  the 
climate related problems they faced (Di Falco et al 2011). 
This is due to the fact that impact of  the climate change is 
not evenly distributed over different geographic areas and 
hence the adaptation mechanisms also vary with types 
and amount of  the impact of  climate change. Therefore, 
we can find a number of  adaptation strategies that the 
farmers used to reduce the impact of  climate change in 
different literature. This includes: crop diversification, 
small scale irrigation ,changing crop variety, changing 
planting dates, mix crop and livestock production, 
decrease livestock, moving animals/temporary migration, 
change livestock feeds, soil and water management, 
planting trees, planting drought tolerant crop, change 
from livestock to crop production, change animal breeds, 
seek off-farm employment, planting short season crop, 
and irrigation/water harvesting are among some of  the 
several strategies available to enhance social resilience in 
the face of  climate change (Deressa, T. 2009; Temesgen 
et al. 2014)

Problem of  the Statement
Agriculture is the most important sector in sub-Saharan 
Africa, including Ethiopia, but it is predicted to be 
negatively impacted by climate change. It is clear that 
climate change was brought about substantial welfare 
losses especially for smallholders whose main source of  
livelihood derives from agriculture. As site specific issues 
require site specific knowledge, it is very important, 
therefore, to clearly understand what is happening at 
community level, because farmers are the most climate 

vulnerable group. In the absence of  such location specific 
studies, it is difficult to fine tune interventions geared 
towards achieving effective and efficient adaptation 
options to cope with the adverse impact of  climate 
change at the local (Lemessa, 2019; MoA 2016).
Farmers of  dale woreda are, like farmers in any other part 
of  Ethiopia, is suffering from Climate upheavals which 
have become common natural disasters in the country. 
First, there has been more erratic and unreliable rainfall 
in the rainy seasons, bringing drought and reduction in 
crop yields and plant varieties; the rainfall especially in the 
later  rains towards the end of  the year has been reported 
as coming in more intense and destructive downpours, 
bringing floods, landslides and soil erosion. Second, there 
has been a fluctuation in temperature which disturbs 
the physiology of  crops, the micro-climate, and the soil 
system on which they grow. Third, the crop production 
has been recurrently hit by erosion, and floods. Fourth, 
annual river runoff  and water availability has been 
reported to decrease dramatically. Food insecurity in the 
area is a major challenge and all these climate shocks have 
exacerbated the negative impacts on the livelihood of  
poorer farm households as they have the lowest capacity 
to adapt to changes in climatic conditions (MoA. 2016).
However, farmers in the study area were responded to 
climate change through various adaptation strategies. But, 
there was no empirical data that substantiates or supports 
the existing adaptation strategies practiced by the farmers 
in the area. The information obtained in various literatures 
was insufficient and general, but adaptation strategies 
vary contextually and spatially (within communities and 
even within individuals).In this regard, no empirical 
study has been conducted to identify adaptation choices, 
examine the perception of  farmers to climate change and 
their determinants in the study area to date to the best of  
the researchers‟ knowledge. Consequently, the primary 
motive to embark on this research was to investigate and 
fill the existing gap of  knowledge on farmers‟ perception 
and adaptation strategies to changing climate and their 
determinants in the study area.

Research Gap
The determination and understanding of  cumulative 
and combined impacts of  factors affecting smallholder 
farmer’s adaptation strategies to climate change. The most 
of  empirical literature carried out on demographic, socio-
economic and institutional factors affecting adaptation 
strategies to climate change is debatable because they come 
up with different conclusion on the same independent 
variable about climate adaption strategies to climate alter. 
For example, regarding to age of  household according 
to elderly farmers were more active and experienced in 
farming activities than youths. On the contrarily way, the 
investigation conducted by shows that even though there 
is high variability in the ages of  the sampled households, 
generally the household within the productive age that 
can fully and efficiently engaged in agricultural activities 
than elderly people.

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Research question 
This study was attempted to answer the following questions: 

1. What are the determinant components that influence 
farmers’ choice of  adaptation strategies to the climate 
change in dale woreda? 

2. What are the adaptation measures that were 
employed by farmers in study site? 

3. Did farmers perceive the existing climate change?

Specific Objective of  the Study
1. To analyze the factors that impact farmers’ choice of  

adaptation strategies to climate change in Dale woreda.
2. To identify adaptation strategies used by farmers in 

response to adverse effects of  climate change in the study 
area. 

3. To analyze farmers‟ perception to climate change

METHODOLOGY
Determining sample is very important issue because 
samples that are too large may waste time, resources and 
money while samples too small may lead inaccurate results.
As discussed in the above section, kebeles being differ in 
both in terms of  size and variability of  agro-ecological 
zone; they was different level of  adaptation strategies 
to climate change. Using data on climate change and 
small holder farmers’ characteristics the number of  

survey producers per division was computed according 
to the formula developed by Yamane (1967) because 
it is simplest formula to calculate sample sizes and its 
importance in small sample size to solve resource and 
time constraint. 
Where n is the sample size, N is the population size (total 
number of  household heads in selected kebeles), and e 
is the level of  precision. n =367 is the total sample size 
planned to be covered. The Sample Size (n) for Precision 
(e) of  5% where confidence level is 95% will be 

It is assumed that the sample will have 95% reliability 
about population and sampling error will be 5%. The 
selected sample size will be identified from six kebeles by 
proportionate random sampling. 
At this stage, to give equal chance and free from selection 
bias, a total of  367 households of  respondents was 
selected from the respective list of  farmers which is 
complete list of  households in each kebele obtained from 
the woreda administration and kebele offices in 6 kebeles 
by using systematic sampling technique. The list kebeles 
covered by size of  ultimate sampling unit was determined 
by using proportionate sampling technique giving a size of  
640,762,852,806,788 and 670 from wenenata ,hidaqalite, 
soyama, kalitesimita,shiifa and Beera respectively. 

Table 1: Sample Kebeles and Sample Size Determination
Kebeles No of  hh Proportion of  each 

kebele
Sampling for each 
kebele

Sample size

Wenenata 640 0.14 367*0.14 51
Hidaqalite 762 0. 17 367*0.17 62
Soyama 852 0.19 367*0.19 70
Kalitesimita 806 0.18 367*0.18 66
Shiifa 788 0.17 367*0.17 63
Beera 670 0.15 367*0.15 55
Total 4518 1 367

Source: Dale Woreda Rural Development and Agricultural Office

Theoretical Model
In this study it is interesting and necessary to develop 
theoretical framework on farm household. This theoretical 
framework draws on adopting a version of  model based 
on the random utility model as specified by (Greene, 
H.W. 2003). This random utility model is commonly used 
as a framework in determining of  farmers’ choice for 
different adaptation options. We can specify a common 
formulation of  linear random utility model as; 
          Uij =βj Xij + εij     for j ∈…… (1) 
Following Greene (2003), we can modify it to adapt 
the objective of  the study. Where, i = 1,…., N are the 
individual farmer and j = 1,…..J are the alternative 
adaptation methods, Xij  vector are the factors that 
influence farmers’ choice an adaptation method to climate 
change and εij  is the random error term /disturbance 
term. To elaborate the model, we assume that farmers’ 
are rational decision makers who maximize the utility 

from adaptation strategies in their farming activities. And 
also assuming that farmers face climatic change in their 
farming activities was looked for adaptation strategies. 
If  farmer i make choice j adaptation in particular, then 
we assume that Uij is the maximum utility among the J 
adaptation methods.  
               Prob (Uij  > Uik)      for all other k ≠ j. 
The probability of  that a particular farmer will choose a 
particular alternative j is given by the probability that the 
utility of  that alternative to the farmer is greater than the 
utility to that farmer of  all other alternative J. 

Multinomial Logit Model
Multinomial logistic regression is a simple extension of  
binary logistic regression (takes only two categories of  
the dependent) that allows for more than two categories 
or levels of  the dependent or outcome variable and is 
easy, simple in calculating the choice probability and 

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expressible in analytical form. MNL model is appropriate 
for this study because MNL model is   the simplest and 
often preferable compared to more complex multinomial 
probit to identify factors affecting adaptation strategy 
of  smallholder farmers to climate change. MNP is 
susceptible to a number of  estimation problems, the 
most serious of  which is that the MNP is often weakly 
identified in application to analyze factors affecting the 
choice of  adaptation strategy of  smallholder farmer to 
climate change. Weak identification is difficult to diagnose 
and may lead to plausible, yet arbitrary or misleading 
inferences. The main limitation of  the model is the 
independent of  irrelevant alternative (IIA) property, 
which states that the ratio of  the probability of  choosing 
any two alternatives is independence of  the attributes of  
any other alternative in the choice set. The multinomial 
probit (MNP) model specification for discrete choice 
model does not require the assumption of  the IIA. 
The MNL model was used by many researchers to the 
model climate change adaptation practices of  smallholder 
farmers. Therefore, the multinomial logit model is 
appropriate to the model of  climate change adaptation 
practice of  smallholder farmers in this study area
The Multinomial logit model for the adaptation choice can 
be specified as in the following relationship between the 
probability of  choosing option and a set of  explanatory 
variables X [11] Prob(Yi = j) =    
                                                          
                                                        
Equation (1) is normalized to remove indeterminacy in 
the model by assuming β0=0 and the probabilities can be 
estimated as:- 
Prob(Yi = j/xi) =   
  
β_(0=0)  …..(2)
Maximum likelihood estimation of  equation (2) yields the 
log-odds ratio

The dependent variable of  any adaptation option is 
therefore the log of  odd in relation to the basealternative.
According to Greene (2003), the MNL coefficients are 
difficult to interpret and associating theβ_j with the jth 
outcome is tempting and misleading. Marginal effect is 
useful to interpret the effect of  independent variable on 
the dependent variable in terms of  probabilities. 

The marginal effects, measure the expected change in 
probability of  a particular choice being made with respect 
to a unite change in explanatory variable.

Independence of  Irrelevant Alternative (IIA) Test 
for MNL Model
As it is discussed earlier, the multinomial logit model 
requires the fulfillment of  the assumption of  the 
Independence of  Irrelevant Alternatives (IIA), otherwise 
the model is not appropriate. Different literatures suggest 

different ways to handling the problem of  IIA and to test 
the fulfillment of  the assumption. For instance, McFadden 
(1973) forwarded that models with independence of  
irrelevant alternative assumption should be used in cases 
where the alternatives can plausibly be assumed to be 
distinct and weighted independently in the eyes of  each 
decision option. Moreover, Multinomial logit models are 
work well when the alternative is dissimilar. Beside, two 
most commonways that are used to test Independence of  
irrelevant alternative (IIA) are (Bazeley, P. 2009).
In this model six categorical outcome tests of  IIA are 
reported here. Then the study computed the model using 
no adaptation strategy as a base category. The study was 
used (Tse, Y.K. 1987) test of  independence of  irrelevant 
alternatives. 

Statistical and Specification Tests
Before carry out the final model regressions, all the 
hypothesized explanatory variables were checked 
for some statistical problems such as the issue of  
multicollinearity. Basically, multicollinearity problem 
may arise due to a linear relationship among explanatory 
variables and the problem is that, it might cause the 
estimated regression coefficients to have wrong signs of  
coefficients, smaller t-ratios for many of  the variables in 
the regression and high R-square value. Besides, it causes 
large variance and standard errors with a wide confidence 
interval. Hence, it is quite difficult to estimate accurately 
the effect of  each variable on the dependent. There are 
different methods suggested to detect the existence of  
multicollinearity problem between the model explanatory 
variables. Correlation Matrix method will be used to 
detect the degree of  association explanatory variables. 
These variables are said to be collinear if  the value of  the 
coefficient correlation Matrix is greater than 0.75. 

Definitions Research Variables Used in the Model
Independent variable is climate change adaptation 
strategies.

Dependent Variables 
The dependent variable for multinomial logit model 
of  this study was adaptation strategies that the sample 
households employed in response to climate change. The 
choice of  adaptation strategies was based on the actions 
the sample households take to counteract the negative 
impact of  climate change/variability. From previous 
researches, different climate change adaptation methods 
have been identified. 
The researcher was asked numerous alternative adaptation 
strategies to the sample respondents and finally identified 
five major adaptation methods most commonly used in 
the area as dependent variable for the multinomial logit 
model. These included crop diversification, changing 
planting dates, use of  water and soil management 
practices, use of  drought tolerant varieties and use of  
irrigation.

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Table 2: Summary of  Definition, Measurement and Hypothesis of  Explanatory Variables
Independent
Variable

Crop
Diversification
Expected Sign

Growing 
Drought 
Tolerant Crop
Expected Sign

Soil and Water 
Management
Expected Sign

Changing 
Planting Date 
Expected Sign

Small Scale    
 Irrigation
Expected Sign

Age + + + + +
Sex + + + + +
Education + + + + +
Farm experience + + + + +
Off-farm income + + + + +
Farm income + + + + +
Credit access + + + + +
Market distance - - - - -
Farm size + + + + +
Family size + + + + +
Soil fertility + + + + +
Extension access + + + + +
Access to climate 
information

+ + + + +

Yi=β0+β1age +β2sex+β3edu+β4fex+β5ofi+
β6cra+β7c+β8mkd+β9fas+β10fms+β11sof+
β12aci+β13exa  +ei………..... 4  
Where: Yi are the climate change adaptation strategies that 
are currently being used to deal with climate change and 
others are demographic, institutional and socio economics 
factors. Where
β0 is constant, βk are regression and coefficients ei error term

Data Analysis 
Descriptive Analysis Method
Under this section the responses of  the farm households 
of  Dale Woreda was analyzed by using descriptive 
statistical method. The results found in this part could 

help for the later econometric methods in section 4.3. 
Additionally, it is also important for analyzing some of  
the necessary information which is not easily captured by 
the econometrics methods. 

RESULTS AND DISCUSSION
Background Characteristics of  Respondents
This section summarizes the demographic characteristics 
of  respondents, which includes gender, and age. The 
purpose of  the demographic analysis in this research is 
to describe the characteristics of  the sample respondents 
accordingly, and the following tables provide the 
demographic profile of  the respondents. 
From the data presented in the above table 3, the majority 

Table 3: Demographic Characteristics of  Respondents
Variables Categories Frequency Percentage
Sex Male house hold head 195 54.3

Female 164 45.7
Total 359 100

Age 15-30 47 13.2
31-40 134 37.3
41-50 125 34.8
51-64 53 14.7
Total 359 100

Source:- Own Survey Data, 2022

(54.3%) of  the respondents were male and the remaining 
(45.7%) of  the respondents were female. This indicates 
that out of  359 household respondent, around 195 
household head were male and the remaining 164 were 
female. This shows that most of  the household head of  
the farmers are male. As indicated in table 3 among the 

total gathered questionnaire, 13.2% of  the respondents 
were found to be in the age category of  15-30 years. 
The respondents who compose of  37.3% are in the age 
category of  31-40 years, 34.8% in the age categories of  
41-50, and 51-64 are 14.7 This data indicated that most of  
the respondents categorized between age group of  31-40.

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Table 4: Social Characteristics of  Respondents
Variables Categories Frequency Percentage
Education Status Illiterate 178 49.5%

1-6 87 24%
7-12 64 17.8%
Certificate/Diplom 22 6.2%
Degree 8 2.5%
Total 359 100

Respondent Farm 
Experience 

1-10 97 27%
11-20 111 30.9%
21-30 110 30.6%
>30 41 11.5%

Source: Own Survey Data, 2022

Educational Status
As shown in the above table 4, the majority of  the 
respondents were grouped under the educational level 
of  respondent are illiterate covering 49.5% of  the total 
respondents, followed by 1-6 composes 24%. The 
respondents were categorized under the educational 
level of  7-12 who covers 17.8%, and 6.2% and 2.5% are 
certificate/diploma and degree holder respectively. This 

shows that most of  the smallholder farmers are illiterate.
From the above table 4, indicated that 30.9% smallholder 
farmer have experience of  between 11-20 years; 30.6% 
had an experience of  21-30 years; 27% had between  1-10 
years and the remaining 11.5% of  the respondents had 
experience of  greater than 30 years with in farm. This 
indicated that majority of  respondents had found under 
11-20 years’ of  farm experience.

Table 5: Economic Characteristics of  Respondents
Variables Categories Frequency Percentage
Off  Farm Income No off  farm income 218 60.7

500-1000 63 17.5
1001-1500 32 8.9
1501-2000 20 5.6
>2000 26 7.3
Total 359 100

Farm Income No income 44 12.3
500-1000 Birr 186 51.8
1001-1500 Birr 96 26.7
1501-2000 Birr 17 4.7
>2000 16 4.5

Total 359 100
Source: Own Survey Data, 2022

Considering the off  farm income characteristics of  the 
respondents, majority of  the smallholder farmer have 
no off  farm income; who fall to 60.7%, followed by 
respondents 17.5%, 8.9%, 5.6% and 7.3% who off  farm 
income 500-100,1001-1500,1501-200 and greater than 
2000 respectively. The income category clearly shows the 
majority(51.8%) of  the smallholder farmer have farm 
income between 500-1000and 12.3% of  the respondent 
have no farm income and the remaining 26.7%, 4, 7% 
and 4.5% have income  between 1001-1500, 1501-2001 
and greater than 2000 respectively. 

The above table shows that, about 39.3% of  the respondents 
from Weyna-dega agro ecological zone had used crop 
diversification as primary choice of  adaptation strategy to 
climate change followed by soil and water management 
(15.3%), 15.3%, 7.4% and 4.9% had practiced soil and water 
management, changing planting date and growing drought 
tolerant crop respectively and on other side; only 4.3% had 
used small scale irrigation as least used adaptation strategy. 
The result indicated that most of  smallholder farmers used 
crop to reduce consequences of  climate change in the 
Weyna-dega agro-ecological zone of  study site. 

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Table 6: Cross Tabulation of  Agro-Ecological Zone and Adaptation Decision
Agro-ecological zone Types of  adaptation 

strategy practiced
Number of  respondents 
who took strategy

Type of  adaptation 
practice in percent (%)

Woyna-Dega Crop diversification 64 39.3%
Growing drought tolerant crop 8 4.9%
Soil and water management 25 15.3%
Changing planting date 12 7.4%
Small scale irrigation 7 4.3%

Dega Crop diversification 11 17.2%
Growing drought tolerant crop 2 1.2%
Soil and water management 21 33.3%
Changing planting date 4 6.9%
Small scale irrigation 3 4.8%

Kola Crop diversification 4 3%
Growing drought tolerant crop 56 42%
Soil and water management 18 13.1%
Changing planting date 7 5.3%
Small scale irrigation 16 12%

Source: Own Survey Data, 2022

Summary statistics for explanatory variables
The above table shows that about 33.3% of  the 
respondents from dega agro-ecological zone had used 
soil and water management as their major choice of  
adaptation strategy to cope with the impact of  climate 

change followed by crop diversification (17.2%) and 
Growing drought tolerant crop is least choice of  
adaptation strategy to moderate climate change in dega 
agro-ecology of  the Woreda.

Table 7: Sum Agehh Sex Fex Edu Ofi Fai Cra Mkd Fms Fas Sof  Aci Exa
Independent Variables Description Summary Statistics 

Mean                  Std.Dev.         Min Max
Age of  household continuous variable 2.5125 .8995554 1  4
Sex Dummy 1 if  male, otherwise .84958220 .357979 0 1
Farm experience Continuous in year 2.264624 .9828995 1 4
Education Continuous .8718663 1.051875 0 4
Off  farm income In ETB (continuous variable) 1.785515 1.26677 0 5
Farm income 2.37325 .9184382 1 5
Credit access Dummy 1 if  yes, 0 otherwise .6991643 .4592615 0 1
Distance from farm to 
market farm             

Continuous in km  2.509749 .9271146 1 5

Farm size Continuous in hectare   2.34818 .9680314 1 4

Family size Continuous 2.07799 .942207 1 4
Soil fertility Categorical 1 very fertile,2 for 

moderate fertile and 3 infertile
1.793872 1.793872 1 3

Access to climate 
information

Dummy 1 if  yes, 0 otherwise .5933148 .4919008 0 1

Extension access Dummy 1 if  yes, 0 otherwise .6406685 .4804742 0
Source: Own Survey Data, 2022

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Factors that Affecting Smallholder Farmers’ Choice 
of  Adaptation Strategies in the Study Area
Estimated results of  the multinomial logit regression 
modelshowed how factors that affecting farmers’ choice 
of  adaptation strategies  in the study area. The MNL 
adaptation model was run and showed that significant 
levels of  the parameters estimates. Table 8 represents that 
the results of  MNL regression model. 

The likelihood ratio statistics as indicated by ch2 statistics 
(LR chi-square (65) = 649.46 and Pseudo R2 = 0.5421 
are highly significant P < 0.0000), explaining the model 
has a strong explanatory power. In all cases, the estimated 
coefficients should be compared with the base category 
of  no adaptation. Therefore, Table 8 presents the MNL 
results along with the levels of  statistical significance. 
Coefficient from the multinomial logit model can tell 

Table 8: Parameter estimates of  the multinomial logit climate change adaptation model
Explanatory 
variable

Crop
Diversification

Growing Drought 
tolerant crop

Soil and water
Management

Changing
Planting date 

Small scale 
irrigation

Coef  Coef   Coef Coef Coef
 p-value p-value p-value p-value p-  value

Age 0.154 0.063 0.358 0.275 0.032
0.639 0.867 0.33 0.715 0.931

Sex -1.371 6.03 6.836 12.163 -14.983
0.434 0.001** 0.00** 0.000** 0.990

Education 1.285 2.067 1.149 1.34 0.879
0.000** 0.000** 0.003** 0.037** 0.029**

Farm experience 2.314 1.316 2.162 2.296 1.852
0.000** 0.001** 0.000** 0.009** 0.001**

Off  farm income   0.876 0.039 1.149 0.637 0.185
0.017** 0.924 0.003** . 0.227 0.682

Farm income     3.222 3.245 2.505 1.216 0.575 5.533
0.000** 0.007** 0.018** 0.574 0.000**

Credit access 2.558 3.407 4.125 -0.444 2.379
0.005** 0.001** 0.000** 0.811 0.032**

Market distance             -2.804 -2.965 -3.166 -3.12 -3.987
0.000** 0.008** 0.001** 0.139** 0.000**

Farm size         4.016 4.276 4.786 6.447 4.076
0.000** 0.000** 0.000** 0.000** 0.000**

Family size    0.701 0.985 1.25 1.519 1.419
0.072** 0.030** 0.004** 0.207** 0.002**

Soil fertility 1.53 4.101 3.773 1.734 1.589
0.020** 0.000** 0.000** 0.173** 0.032**

Access to climate 
information

1.381 1.791 2.349 -1.683 0.96
0.063** 0.027** 0.004** 0.316 0.24

Extension access 3.222 2.393 3.328 2.903 18.686
0.000** 0.008** 0.000** 0.085*** 0.979

Base  category       No adaptation
Number of  observation  359
LRchi2(65) 649.46
Prob > chi2  0
Loglikelihood -274.30607
Pseudo R2   0.5421
NB *, **, *** = significant at 1%, 5%, and 10% probability level, respectively     
Source; own survey data 2022

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about the direction effect not the magnitude effect. How 
to compute the magnitude of  effect by using stata-15 
command mfx after multinomial logit regression and 
it results marginal effect.  Marginal effect of  marginal 

probabilities is the function of  probabilities and measures 
the expected change in probabilities where particular 
adaptation choice is being made by a unit change of  the 
independent variable from the mean.

Table 9: Marginal Effects of  Explanatory Variables From Multinomial Logit Model
Independent 
Variable

Crop 
Diversification

Growing 
Drought 
Tolerant Crop

Soil and Water 
Management

Changing 
Planting Date

Small Scale 
Irrigation

Marginal effect Marginal effect Marginal effect Marginal effect Marginal effect
Age -.0143 -.022 .041 .000 -.000
Sex .688 -.070 -.334 -.330 .001
Education .081 .018 -.000 .012 -.000
Farm experience .034 .017 .016 .011 -.000
Off  farm income .193 .091 -.087 .000 -.000
Farm income .141 .053 -.107 -.003 .000
Credit access .133 .093 .232 -.015 -.000
Market distance .018 -.023 -.076 -.005 -.000
Farm size .064 .027 .152 -.004 .002
Family size -.089 .022 .090 -.001 .014
Soil fertility .528 .304 .297 .000 .012
Access to climate 
information

.122 .033 .160 0.013 .001

Extension access .154 -.098 087 .000 .019
(*) dy/dx is for discrete change of  dummy variable from 0 to 1. Source: own survey data 2022

Interpretation of  Regression Result 
Sex of  Household Head
From the result of  multinomial logistic regression the 
coefficients of  sex of  household head are negative and 
statistically not significant for crop diversification and 
small scale irrigation, keeping other variables constant. 
Being female household head is better in practice of  crop 
diversification and small scale irrigation as adaptation 
measure with (p< 0.434) and (p<0.099) respectively at 
5% level of  significance in the study area. Being male 
household head has positive and highly significant effect 
on adapting strategy like growing drought tolerant crop, 
for soil and water management and changing planting date 
to climate change impact with probability of  p<0.001, 
p<0.000 and p<0.000 at 5% level of  significance in the 
study site. Based on the result of  marginal effect, even 
if  the effects of  sex on the probabilities of  three of  the 
strategies are negative and do not suggest important 
information, this could be an indication of  the different 
implications of  sex on adaptation measure. Given these 
situations, the result is justified with the possibility 
that being male and female farmer usually practice of  
adaptation measures which can be practiced to increase 
farm labour.

Education Level of  Smallholder Farmer
The result of  multinomial logistic regression shows that 
education had a positive effect on farmers’ adaptation 
strategies and statistically significant in increasing 

adaptation strategies of  crop diversification, growing 
drought tolerant crop, soil and water management, 
changing planting date and small scale irrigation with 
respective p-value p<0.00, p<0.00, p<0.03, p<0.037 and 
p<0.029. Education is highly significant in determining 
crop diversification and growing drought tolerant crop at 
5% level of  significance keeping other variables constant.
Farmers who have more education level were more likely 
to adapt to climate change using crop diversification 
and growing drought tolerant crop practices than those 
who do have lower education level. This result might 
source of  the fact that education improves farmers‟ 
capacity of  obtaining and analyzing new information 
about climate change and best adaptation practices that 
increases the probability of  adapting to climate change. 
More specifically, it equipped farmers with knowledge 
of  selecting appropriate crop diversification and drought 
tolerant variety. The result of  from marginal effect shows 
that a unit increases in number of  years of  education 
could increase by 8.1% of  the likelihood of  adopting 
crop diversification and 1.8% practice of  growing 
drought tolerant crop as adaptation measures at 5% level 
of  significance.

Farm Experience of  Household
In this study the coefficient of  household farm experience 
is positive and statistically significant in determining 
adaptation measure such as crop diversification, growing 
drought tolerant crop, soil and water management, 

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changing planting date and small scale irrigation with 
p<0.00, p<0.001, p<0.00, p<0.009 and p<0.001 
respectively in the study site. The result of  marginal 
effect shows a unit increases in number of  years of  farm 
experience could increase by 1.4% of  the likelihood of  
adopting crop diversification, 5.7% of  growing drought 
tolerant crop and 1.6% of  soil and water management 
as adaptation measure at 5% level of  significance. The 
number of  years a farmer has spent cultivating crops on 
a farm is considered as his/her agricultural experience. 
Possessing many years of  farming experience implies 
that one is better informed about climate variability and 
change in relation to crop produce, in the study areas; 
hence, experienced farmers are likely to use adaptation 
strategies which had reduced the effects of  change and 
improved crop production.
 
Off-Farm Income
Off-farm income is significantly and positively affected 
crop diversification and the practice of  soil and water 
management with p<0.01 and P<0.03 at 5% level of  
significance. The result of  marginal effect shows a unit 
increases in number of  years of  farm experience could 
increase by 1.9% of  the likelihood of  adopting crop 
diversification. The higher farmers have off-farm income, 
the more likely they were to adapt climate change using 
crop diversification and soil and water management.  
Perhaps the reason is farmers have had an optional 
income source that help them withstand the impact 
of  climate change and they are also capable of  buying 
instruments for soil and water management.

Farm Income
Coefficients of  farm income from result of  multinomial 
logistic regression is positive and statistically significant in 
determining the practice of  adaptation measure such as 
crop diversification, growing drought tolerant crop, soil 
and water management and the use small scale irrigation 
at 5% level of  significance with p-value 0.000, 0.007 
,0.001 and 0.000 respectively. The result of  marginal 
effect shows a unit increases in number of  years of  farm 
experience could increase by 1.4% of  the likelihood of  
adopting crop diversification, 5% of  growing drought 
tolerant crop at 5% level of  significance. This implied 
that smallholder farmers who have higher farm income 
are more likely to adapt to the change in climate using 
these strategies. When the main source of  income in 
farming increase, farmers tend to invest on productivity 
smoothing options such as using crop diversification and 
growing drought tolerant crop. Farm income enables 
the farmer to perceive and adapt to climate change by 
devoting higher cash for the purchase of  seed and 
seedlings whenever the rain comes, buying a drought 
tolerant variety and apparatus for the use of  soil and 
water management practice and irrigation at higher price.
 
Credit Access
The multinomial regression model revealed that farmers 

access to credit has a statistically significant positive effect 
on using of  crop diversification, growing drought tolerant 
crop, soil and water management and using small scale 
irrigation at 5% level of  significance, keeping another 
variable constant. Farmers who have access to credit are 
more likely to adapt climate change by practicing these 
adaptation strategies. a unit increase of  access to credit 
could increase likelihood of  crop diversification by 13.3%, 
growing drought tolerant crop by 9.3%, soil and water 
management by 23.2%. The result showed that having 
access to credit increases the propensity of  farmers to 
apply the four adaptation strategies in response to climate 
change. This is due to the fact that access to affordable 
credit mitigates the financial limitation of  the farmer and 
increases their ability to meet transaction costs associated 
with the various adaptation options they might want to 
take. It enables farmers to change their management 
practices in response to changing climatic factors and to 
buy varieties for crop diversification and drought tolerant 
varieties, tool/ instrument for soil and water management 
and small scale irrigation irrigation technologies like water 
pumps and other inputs to smoothening production and 
reduce the negative impact of  climate change.
 
Market Distance
This variable is a continuous variable measured in 
kilometers from farmers home/farm to their market and 
coefficients of  market distance is negative and statistically 
significant in determining crop diversification, growing 
drought tolerant crop, soil and water management and 
using small scale irrigation at 5% level of  significance 
with p-value 0.000, 0.008, 0.001 and 0.000 respectively, 
keeping other variables constant. Market is an important 
determinant to buy input for crop diversification, growing 
drought tolerant crop, soil and water management 
practices and small scale irrigation tool to take adaptation 
measure to climate change, most probably reason the 
market serves as a means of  exchanging information 
with other farmers. Moreover, access to inputs and 
transportation cost will be high for households far from 
a given market.

Farm Size
Landholding size highly significant and positively affected 
use of  crop diversification, growing drought tolerant crop, 
soil and water management, changing planting date and 
small scale irrigation in response to climate change at 5% 
level of  significance with all p-value 0.00, keeping other 
variables constant. The bigger the landholding, the more 
likely the farmer is to adopt crop diversification, growing 
drought tolerant crop, soil and water management, 
changing planting date and small scale irrigation. The 
possible reason is that farmers who have bigger farm 
size have an option to divide their farm into different 
enterprises. From results of  marginal effect shows a 
unit increase in farm land by hectare could increase the 
likelihood of  adopting  crop diversification by 6.4%, 
growing drought tolerant crop by 2.7%, soil and water 

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Am. J. Appl. Stat. Econ. 2(1) 15-27, 2023

management by 1.5% and small scale irrigation by 0.02%.
 
Family Size
Family size also has statistically significant and positive 
effect on adaptation strategies to climate alter. A unit 
increase of  number of  family size, could increase 
likelihood of  using crop diversification by 7.2%, growing 
drought tolerant by 0.3%, soil and water management by 
0.04% and small scale  irrigation by 0.02% as adaptation 
measure respectively, keeping other variables constant. 
Because household size can influence adaptation, due to 
the fact that its association with labor endowment. 

Soil Fertility
Soil fertility has statistically significant and positive effect 
on adaptation strategies to climate alter. From marginal 
effect result, a unit increase of  number of  soil fertility 
, could increase likelihood of  using crop diversification 
by 5.2%, growing drought tolerant by 3%, soil and water 
management by 2.9% and small scale irrigation by 0.02% 
as adaptation measure respectively, than infertile soil 
keeping other variables constant. Fertile soil make easy 
farmers production during climate change adaptation 
measure such as crop diversification, growing drought 
tolerant crop and soil and water management. 

Access to Climate Information
Access to climate information significantly and positively 
affected using of  drought tolerant varieties and using 
soil and water management at 5% level of  significance. 
Farmers who have access to climate related information 
from different media like radio and television have 
a higher probability of  awareness creation in using 
drought tolerant varieties and using soil and water 
management as an adaptation strategy to reverse climate 
change.  Most likely, the reason is that access to climate 
information admits to perceive the change and choose 
appropriate strategies in response to climate change. 
Climate information notifies the condition of  the existing 
climatic situations to enable the farmers to use alternative 
adaptation strategies like drought tolerant variety and soil 
and water management. From result of  marginal effect 
unit increase climate information, could increase likelihood 
of  using crop diversification by 12.2%, drought tolerant 
crop by 3.3%, and soil and water management by 16.1%. 

Extension Visit
Is also among the positive and  significant explanatory 
variable in this model. A result from marginal effect, those 
who have access to farm extension service expected to 
have had unit increase of  farm extension service could 
increase likelihood of  using crop diversification adaption 
methods by 15.4%, growing drought tolerant crop by 8.7% 
and using small scale irrigation by 1.9% as compared to the 
farmers who have no access to farm extension service to 
handle climate change at 5% level of  significance. 

CONCLUSION 
Multinomial logistic regression analysis was employed to 
analyze the factors influencing smallholder farmers’ choice 
of  adaptation strategies to climate change. The result 
from the multinomial logit regression analysis shows that 
sex, education, farm experience, off-farm income, credit 
access, market distance, farm size, family size, soil fertility, 
access to climate information and extension access have 
a significant influence on smallholder farmers’ choice 
of  adaptation strategies to climate change and age is not 
significant to climate change.
The strategy of  crop diversification was positively affected 
by education, farm experience, off-farm income, credit 
access, farm size, family size, soil fertility, soil fertility, 
climate information and extension access, while sex and 
market distance negatively affect crop diversification. 
The unit increase in education, farm experience, off-farm 
income, credit access, farm size, family size, soil fertility, 
climate information and extension access will increase the 
practice of  crop diversification likelihood of  6.8%, 8.1%, 
3.4%, 1.7%, 14.1%, 6.4%, 5.3%, 1.2% and 1.5%. The unit 
increase in kilometer of  market distance from farm to 
market could decrease likelihood of  1.8% use of  crop 
diversification.
Growing drought tolerant crop was positively affected 
by education, farm experience, off-farm income, farm 
income, credit access, farm size, family size, soil fertility, 
access to climate information and extension access, while 
growing drought tolerant crop negatively affected by 
market distance. The unit increase in education, farm 
experience, farm income, credit access, farm size, family 
size, soil fertility and access to climate information could 
increase adoption of  growing drought tolerant crop by 
1.8%, 1.7%, 5.3%, 9.3%, 2.7%,2.2%, 3.04% and 3.3%.
Soil and water management as climate change adaptation 
strategy was positively affected by farm experience, farm 
income, credit access, farm size, family size, soil fertility, 
access to climate information and extension access, while 
sex and market distance negatively affect soil and water 
management.The unit increase of  farm experience, farm 
income, credit access, farm size, family size, soil fertility, 
access to climate information and extension access could 
increase likelihood of  1.6%, 23.2%, 15.2%,9%,29.7%, 
16% and 8.7% practicing soil and water management.
The strategy of  changing planting date positively affected 
by education, farm experience and farm size while sex 
negatively affect the strategy changing planting date.The 
unit increase of  education, farm experience and climate 
access information could likelihood of  adopting strategy 
of  changing planting date 1.2%, 1.1% and 1.3%.
Small scale irrigation as climate change measure was 
positively affected by credit access, farm size and family 
size while small scale irrigation negatively affected by 
market distance. The unit increase of  farm size and family 
size 0.02%, 1.4% and 1.2% could increase likelihood 
adopting small scale irrigation.

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RECOMMENDATION 
Based on the findings of  this study, the following 
recommendations were forwarded for decreasing the 
impacts of  climate change on smallholder farmer 
agricultural production. Encouraging efforts on enhancing 
the farmers’ adaptive capacity to climate change and 
variability is an important policy measurement. 
The government and any concern body should give 
emphasis to address this issue of  climatic change 
through paying greater focus. In the study area problem 
of  food shortage is a common by the farmers of  this 
Woreda especially when there is crop failure due to 
increased frequency of  farm destruction, increased 
frequency of  drought, off-seasonal rainfall and little 
rainfalls. Therefore, effort and strengthen the farmers’ 
adaptive capacity to climate change through by providing 
different varieties for crop diversification and drought 
tolerant crop,introducing climate change problem and 
use of  adaptation strategy into educational curriculum, 
organizing continuous climate related training center, 
providing modern tool for soil and water management 
and small scale irrigation  and disseminating climate 
related information by local language through social 
media for farmers to enhance awareness has an important 
mechanism.
Due to the availability of  different micro climate in the 
area and to improve the coverage and quality of  climatic 
data local meteorology station should be established at 
least at woreda level. And it is important for monitoring 
climate data, developing climate forecasts and early 
warning for climatic hazards as early as possible.
The level of  perception farmers to climate change has 
a very important role on the level of  using adaptation 
strategies to lessen the effect of  climate alter. But there 
are still a considerable number of  smallholder farmers 
who did not perceive the changing climate. Therefore, 
emphasizing on awareness creation work about the 
changing climate is crucial.
Improving farmer’s farm and off/non-farm income-
earning opportunities is of  great need for smallholder 
farmers. Thus, sufficient input supply which increases 
farm income and creation of  off/non-farm employment 
opportunities in the rural areas can be underlined as a 
policy option in the reduction of  the negative impacts of  
climate change. 
Improve farmers access to affordable credit and support 
the growth and development of  credit institutions and it is 
important to consider its accessibility to farmers nearby their 
locality and of  other income generating activities to increase 
their ability and flexibility in response to climate change.
Policy interventions aimed at mitigating the adverse 
effect of  climate alter and variability need to focus on 
supporting farmers to intensively use and expand the 
existing adaptation strategies in the way match with agro-
ecology: by using crop diversification, growing drought 
tolerant crop, soil and water management, changing 
planting date and small scale irrigation practices. 
Electing model farmers of  adopter and making them to 

share their experiences to the non-adopter of  farmers is 
very important to promote adaptation in the community. 
This encourages Promotion of  a given adaptation 
strategies should consider the agro-ecological setting 
of  the area special consideration for successful use of  
adaptation measures by smallholder farmers.  
Policies aimed at promoting farm-level adaptation need 
to emphasize on the crucial role of  providing information 
on better production techniques and enhancing farmers’ 
awareness on climate change (through extension) and 
creating the financial means through affordable credit 
schemes to enable farmers to use different adaptation 
measures to climate change. 
Including climate change related agenda in education 
curriculum will increase the continuous  knowledge about 
the use of  adaptation strategy as a culture because it is 
necessary to design and implement policies that aim to 
expand adult education so that improve education level 
of  farmers. Literate farmers could be able to easily collect, 
analyze and interpret relevant information about climate 
change and adaptation strategies. It will enable them to 
select appropriate adaptation strategies and farming 
practices to manage climate change impacts. Hence, it is 
essential to improve education level of  farmers through 
expansion of  adult schools and crafting systems that 
allow farmers to get education.
Generally, future policy should focus on awareness 
creation on climate change through different sources 
such as media and extension, facilitating the availability 
of  credit especially to adaptation technologies, enhancing 
research on use of  new crop varieties that are more 
suited to drier conditions, improving farmers farm and 
off-farm income earning opportunities, improving their 
literacy status, and improving their access to credit. 
Moreover, encouraging informal social net-works and 
environmental settings enhance the adaptive capacity of  
smallholder farmers.
Information on appropriate adaptive measures should be 
made available to the entire community. As part of  this 
effort, communication between policymakers, research 
institution,Universities, and the media, among other 
actors, should be strengthened in order to ensure accurate 
information is available and widely disseminated.

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